THE GROWTH CORRIDOR: A MULTI-PERSPECTIVE MODEL
OF OPTIMUM FIRM GROWTH
DISSERTATION
of the University of St. Gallen,
Graduate School of Business Administration,
Economics, Law and Social Sciences (HSG)
to obtain the title of
Doctor Oeconomiae
submitted by
FLORA FERLIC
from
Austria
Approved on the application of
Prof. Dr. Peter Gomez
and
Prof. Dr. Georg von Krogh
Dissertation no. 3500
sihldruck Stulz AG, Zürich 2008
THE GROWTH CORRIDOR: A MULTI-PERSPECTIVE MODEL
OF OPTIMUM FIRM GROWTH
DISSERTATION
of the University of St. Gallen,
Graduate School of Business Administration,
Economics, Law and Social Sciences (HSG)
to obtain the title of
Doctor Oeconomiae
submitted by
FLORA FERLIC
from
Austria
Approved on the application of
Prof. Dr. Peter Gomez
and
Prof. Dr. Georg von Krogh
Dissertation no. 3500
sihldruck Stulz AG, Zürich 2008
II
The University of St. Gallen, Graduate School of Business Administration,
Economics, Law and Social Sciences (HSG) hereby consents to the printing of the
present dissertation, without hereby expressing any opinion on the views herein
expressed.
St. Gallen, June 23, 2008
The President:
Prof. Ernst Mohr, PhD
III
to Clemens with love
IV
V
Acknowledgements
Writing this dissertation has intellectually and personally been one of the most
challenging but also enriching and rewarding experiences of my life. I have spent a
glorious time here at St. Gallen and owe much to the people who have been with me
during the past three years. I would like to express my gratitude to all of them and
thank them for having accompanied and supported me in completing this work.
I am much obliged to my doctoral advisor Professor Peter Gomez whom I appreciate
greatly and who has been a role model to me in many ways. I would like to thank him
for his support and guidance and for the freedom he granted me in pursuing this
project. It is thanks to him that this dissertation has a strong practical orientation, while
maintaining academic standards. His vast experience and astuteness have aided me in
many ways and have greatly enriched my job as research assistant from both a
professional and personal point of view.
Further, I would like to thank Professor Georg von Krogh for his academic support. It
was his doctoral seminar and inspirational personality that truly sparked my
enthusiasm for management research. His intellectual support has been very enriching
and advanced my work in many ways. I feel honored to have had the chance to work
together with him and hope that more opportunities to work on joint projects will arise
in the near future.
My most sincere thanks goes to Sebastian Raisch whose ideas and support lay the
foundations for this dissertation. His unconditional aid and guidance have inspired me
personally as well as my work in profound ways. His vast knowledge, versatile mind,
and academic excellence have been of great assistance. His open-mindedness and
understanding made the time I have spent here both fun and a rewarding experience.
Sebastian has not only been an excellent teacher but, even more importantly, has
become a true friend.
I would also like to thank Florian Hotz for not only putting up with me as his
colleague, but primarily for offering his friendship. He has introduced me to many
great people and I have shared hilarious times with him at St. Gallen. His generosity
and kindness have inspired me and I am convinced that our friendship will endure.
Likewise, I thank Dirk Martignoni for his company and the intellectually stimulating
times we spent together. I hope for many more to come.
VI
Furthermore, I would like to thank everybody at the Institute of Management, the
Center for Organizational Excellence and my fellow doctoral students for their
support. It was a pleasure to work together with them and I am grateful for having had
the opportunity to share my time with so many outstanding personalities. For her
support and amity I would especially like to thank Nicola Gesing. I would also like to
thank Florian Bertram, Markus Kreutzer and Alexander Zimmermann for their
personal support, intellectual inspiration, and the fun times we have spent together.
Finally, and most importantly I would like to thank my family for their support and
understanding. If it hadn't been for them, I would have never have achieved what I
have. They have unconditionally loved, supported, and trusted me. I am deeply
grateful for their understanding, advice and encouragement. In particular I would like
to thank my grandmother for sharing her worldly wisdom with me. She has inspired
and helped me in many ways. Since Clemens Rainer made the biggest sacrifice in
respect of this work by standing by me despite the geographical distance between us, I
would like to dedicate this dissertation to him. I can not imagine ever sharing my life
with anybody else.
St. Gallen, August 20, 2008
Flora Ferlic
VII
Table of Contents
TABLE OF CONTENTS ....................................................................................... VII
LIST OF FIGURES, TABLES, AND ABBREVIATIONS .................................. XI
SUMMARY OF THE DISSERTATION ............................................................. XIII
1. INTRODUCTION .................................................................................................. 1
2. THEORETICAL BACKGROUND ...................................................................... 6
2.1. GROWTH AND FIRM PERFORMANCE ................................................................... 6
2.1.1. The Upsides of Growth ................................................................................. 6
2.1.2. The Downsides of Growth ............................................................................ 7
2.1.3. Empirical Evidence ...................................................................................... 7
2.1.4. Optimum Growth .......................................................................................... 8
2.2. THEORETICAL PERSPECTIVES ON FIRM GROWTH ............................................... 9
2.2.1. The Market-Based Perspective on Growth .................................................. 9
2.2.2. The Resource-Based Perspective on Growth ............................................. 10
2.2.3. The Financial Perspective on Growth ....................................................... 10
3. A MULTI-PERSPECTIVE MODEL OF OPTIMUM FIRM GROWTH ...... 12
4. RECONCILING COMPETITIVE ACTION AND COMPETITIVE
RIVALRY: IMPLICATIONS FOR FIRM PERFORMANCE ............................. 16
4.1. THEORY ............................................................................................................. 18
4.2. COMPETITIVE ACTION: THE LOWER BOUNDARY ............................................. 19
4.3. COMPETITIVE RIVALRY: THE UPPER BOUNDARY............................................. 21
4.4. ORGANIZATIONAL SLACK AND COMPETITIVE ACTION .................................... 23
4.5. RESEARCH DESIGN............................................................................................ 25
4.5.1. Sample and Data ........................................................................................ 25
4.6. MEASUREMENTS ............................................................................................... 26
4.6.1. Competitive Action ..................................................................................... 26
4.6.2. Rivals’ Competitive Action ......................................................................... 27
4.6.3. Firm Competitive Action ............................................................................ 28
4.6.4. Competitive Position .................................................................................. 28
4.6.5. Financial Resource Limits.......................................................................... 28
VIII
4.6.6. Unabsorbed and Absorbed Slack ............................................................... 29
4.6.7. Performance ............................................................................................... 29
4.6.8. Control Variables ....................................................................................... 30
4.7. STATISTICAL METHODS AND DATA ANALYSIS................................................. 30
4.8. RESULTS ............................................................................................................ 32
4.9. DISCUSSION AND CONCLUSION......................................................................... 35
5. EXCESS HUMAN RESOURCES: GROWTH AND PERFORMANCE
IMPLICATIONS OF ABSOLUTE AND RELATIVE LEVELS OF SLACK ..... 43
5.1. INTRODUCTION.................................................................................................. 43
5.2. THEORY ............................................................................................................. 44
5.3. RELATIVE HUMAN RESOURCE SLACK AND MINIMUM FIRM GROWTH............. 46
5.4. RELATIVE HUMAN RESOURCE SLACK AND MAXIMUM FIRM GROWTH ........... 49
5.5. ABSOLUTE HUMAN RESOURCE SLACK AND FIRM GROWTH ............................ 50
5.6. RESEARCH DESIGN............................................................................................ 52
5.6.1. Sample ........................................................................................................ 52
5.6.2. Data ............................................................................................................ 52
5.7. MEASUREMENTS ............................................................................................... 52
5.7.1. Relative Human Resource Slack................................................................. 52
5.7.2. Absolute Human Resource Slack................................................................ 53
5.7.3. Firm Growth ............................................................................................... 53
5.7.4. Performance ............................................................................................... 54
5.7.5. Control Variables ....................................................................................... 54
5.8. STATISTICAL METHODS AND DATA ANALYSIS................................................. 54
5.9. RESULTS ............................................................................................................ 57
5.10. DISCUSSION.................................................................................................... 60
5.10.1. Resource-Based View of Growth................................................................ 60
5.10.2. Slack, Growth, and Performance ............................................................... 61
5.10.3. Conceptualizations of Human Resource Slack........................................... 62
5.10.4. Limitations and Directions for Future Research ....................................... 63
5.10.5. Managerial Implications ............................................................................ 64
6. TO MEET OR TO BEAT: SHAREHOLDERS' EXPECTATIONS AND
FIRM PERFORMANCE ........................................................................................... 67
6.1. INTRODUCTION.................................................................................................. 67
6.2. SHAREHOLDERS' EXPECTATIONS AND FIRM PERFORMANCE ............................ 69
6.2.1. Meeting Shareholders' Expectations .......................................................... 69
6.2.2. Beating Shareholders' Expectations........................................................... 70
6.2.3. Irrational Shareholders' Expectations ....................................................... 72
IX
6.3. RESEARCH DESIGN............................................................................................ 73
6.3.1. Sample and Data ........................................................................................ 74
6.4. MEASUREMENTS ............................................................................................... 74
6.4.1. Firm Growth ............................................................................................... 74
6.4.2. Expected Sales Growth Rate ...................................................................... 75
6.4.3. Financial Resource Limits.......................................................................... 75
6.4.4. Performance ............................................................................................... 76
6.4.5. Control Variables ....................................................................................... 76
6.5. STATISTICAL METHODS AND DATA ANALYSIS................................................. 77
6.6. RESULTS ............................................................................................................ 79
6.7. DISCUSSION ....................................................................................................... 81
6.7.1. Limitations and Managerial Implications .................................................. 83
7. THEORETICAL CONTRIBUTIONS ............................................................... 86
7.1. CORPORATE GROWTH ....................................................................................... 86
7.2. CORPORATE CHANGE ........................................................................................ 87
7.3. CORPORATE LEARNING ..................................................................................... 88
8. PRACTICAL IMPLICATIONS ......................................................................... 90
8.1. THE CORRIDOR OF OPTIMUM FIRM GROWTH ................................................... 90
8.2. SMART GROWTH: NESTLÉ'S PATH TO SUCCESS ................................................ 91
8.2.1. Nestlé's Profitable Growth: The Point of Departure ................................. 92
8.2.2. Earning the Right to Grow ......................................................................... 93
8.2.3. The Nutrition and Wellness Initiative......................................................... 94
8.2.4. Strengthening Innovation ........................................................................... 95
8.2.5. Achieving Smart Growth ............................................................................ 97
9. EXCESSIVE GROWTH, CASH-STARVED, AND GROWTH LAGGARDS:
PERFORMANCE IMPLICATIONS OF GROWTH OUTSIDE THE
CORRIDOR .............................................................................................................. 100
9.1. EXCESSIVE GROWTH ....................................................................................... 100
9.1.1. Vodafone ................................................................................................... 100
9.1.2. Stabilizing Operations .............................................................................. 101
9.1.3. Future Prospects ...................................................................................... 102
9.2. CASH-STARVED .............................................................................................. 103
9.2.1. Allianz ....................................................................................................... 103
9.2.2. From Smart Growth to Cash-Starved ...................................................... 104
9.2.3. Earning the Right to Grow ....................................................................... 104
9.3. GROWTH LAGGARDS....................................................................................... 105
X
9.3.1. Renault...................................................................................................... 105
9.3.2. Reviving Growth ....................................................................................... 106
9.3.3. Future Prospects ...................................................................................... 106
10.
LIMITATIONS AND FUTURE RESEARCH DIRECTIONS ................... 108
10.1.
CONCLUSION ................................................................................................ 109
REFERENCES .......................................................................................................... 110
XI
List of Figures, Tables, and Abbreviations
List of Figures
FIGURE 1.1: STRUCTURE OF THE DISSERTATION ............................................................. 4
FIGURE 8.1: NESTLÉ'S GROWTH CORRIDOR .................................................................. 92
FIGURE 9.1: VODAFONE'S GROWTH CORRIDOR .......................................................... 103
FIGURE 9.2: ALLIANZ'S GROWTH CORRIDOR .............................................................. 105
FIGURE 9.3: RENAULT'S GROWTH CORRIDOR ............................................................. 107
List of Tables
TABLE 4.1: LIST OF VARIABLES .................................................................................... 30
TABLE 4.2: TIME SERIES CROSS-SECTIONAL SUMMARY STATISTICS ........................... 33
TABLE 4.3: HYPOTHESIS 1, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 33
TABLE 4.4: HYPOTHESIS 2, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 34
TABLE 4.5: HYPOTHESIS 3, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 35
TABLE 4.6: HYPOTHESIS 4, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 35
TABLE 5.1: LIST OF VARIABLES .................................................................................... 54
TABLE 5.2: TIME SERIES CROSS-SECTIONAL SUMMARY STATISTICS ........................... 57
TABLE 5.3: HYPOTHESIS 1, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 58
TABLE 5.4: HYPOTHESIS 2, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 58
TABLE 5.5: HYPOTHESIS 3, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 59
TABLE 5.6: HYPOTHESIS 4, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 59
TABLE 6.1: LIST OF VARIABLES .................................................................................... 77
TABLE 6.2: TIME SERIES CROSS-SECTIONAL SUMMARY STATISTICS ........................... 79
TABLE 6.3: HYPOTHESIS 1, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 80
TABLE 6.4: HYPOTHESIS 2, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 81
TABLE 6.5: HYPOTHESIS 3, RESULTS OF FIXED EFFECTS PANEL DATA REGRESSION... 81
List of Abbreviations
€
£
AG
CEE
CEO
CGR
CHF
ed.
eds.
Euro
Pound Sterling
Public Limited Company (German Aktiengesellschaft)
central and eastern Europe
Chief Executive Officer
competitive growth rate
Swiss Franc
editor
editors
XII
e.g.
et al.
GLOBE
i.e.
Inc.
plc
PTC
R&D
SA
s.d.
SGR
SIC
UK
U.S.
USD
vol.
for example; for instance (Latin exempli gratia)
and other people (Latin et alii/alia)
Global Business Excellence
that is to say; in other words (Latin id est)
Incorporated
Public Limited Company
Product Technology Center
research & development
Public Limited Company (French Société Anonyme)
Standard deviation
sustainable growth rate
Standard Industrial Classification
United Kingdom
United States
United States Dollar
volume
XIII
Summary of the Dissertation
The aim of the present study is to develop a multi-perspective model of optimum firm
growth, to bridge a gap in existing research on the nature of the relationship between
firm growth and performance. After outlining the theoretical foundations of this
dissertation, I proceed to develop three self-contained, full papers which constitute the
main part of this study. These papers seek to address the question whether there is an
optimum pace of growth and, if so, how this optimum rate can be determined from
different theoretical perspectives.
In the first paper, I build on research on competitive dynamics to shed light on the
relationship between firm growth and performance. By reconciling findings from the
competitive action and competitive rivalry research stream, I specify firm-specific
boundaries for competitive activity. Drawing on panel data from Fortune 500
companies, I observe a negative performance effect in respect of firms whose
competitive action is insufficient to defend their competitive position, and whose
competitive action exceeds their financial resource limits. In the second paper, I build
on the resource-based view of the firm to shed light on the relationship between firm
growth and performance. The findings of this analysis suggest that relative human
resource slack induces a firm to grow. However, the positive performance effect
experienced by firms whose sales growth rate exceeds relative human resource slack
tapers off as growth increases. Further, I provide evidence on the moderating role of
absolute human resource slack in the firms’ growth process. In the third paper, I build
on financial theory, which indicates that firm performance is positively related to the
act of meeting or beating shareholders’ growth expectations. The results of this
analysis, however, suggest that there is a significant difference regarding the
performance implications of meeting revenue growth expectations, as opposed to
beating them. Further, the results suggest that firm performance deteriorates in the face
of irrational shareholders’ expectations.
To provide an integrative view of firm growth, I then synthesize the results of these
three papers. By combining their individual findings, I deduce the concept of the
growth corridor, which determines a firm’s minimum growth requirement as well as
its maximum growth boundary. After outlining the papers’ combined theoretical
contributions, I proceed to demonstrate the implications of the growth corridor for
managerial practice. More specifically, I review four positions firms may take within
the growth corridor and analyze consequent performance effects. The dissertation
concludes with final remarks on its limitations and implications for future research.
XIV
1
Growth, after all, is the result of success,
of offering what the market wants, buys,
and pays for, of using economic resources
effectively, and of making profits for
expansion and for the risks of the future.
(Drucker, 1994: 135)
1. Introduction
Asked to reveal their prime objective, most managers reply that corporate growth
ranks first on their strategic agenda (Zook & Seidensticker, 2004). Statements related
to challenging growth targets such as "we plan to double sales in the next five years"
are common in annual reports and are frequently cited in the business press (Brush,
Bromiley, & Hendrickx, 2000; Hall, 1967; Whetten, 1987). Growth helps to establish
legitimacy, achieve economies of scale, attract investment capital, and increase firm
profitability (Nicholls-Nixon, 2005). After all, when companies are able to grow, they
generally offer customers what they want (Raisch & von Krogh, 2007: 65).
Increasing growth rates, however, do not always translate into better performance.
Firms that are able to sustain high growth and high performance over long periods of
time are the exception rather than the rule (Nicholls-Nixon, 2005, Probst & Raisch,
2005). A brief analysis of the companies listed in the Fortune 500 ranking, for
example, reveals that, between 1995 and 2004, not even a quarter of those companies
managed to simultaneously increase their sales and profits by over 5% per year
(Raisch, Probst, & Gomez, 2007). Further, empirical evidence suggests that periods
of high growth are very often followed by a sharp decline in the firm's sales (Olson,
van Bever, & Verry, 2008; Probst & Raisch, 2005). Managers and business leaders
are thus faced with two challenges: they fight to sustain high levels of growth over
longer periods, and they struggle to align sales increases with corresponding
improvements in performance.
A large number of practitioners and management theorists have been intrigued to
resolve this corporate challenge. Explaining the relationship between firm growth and
performance is a key element of strategic management research. Indeed, the study of
firm growth is one of the longest established lines of empirical work in this area
(Geroski, 2005). A considerable number of books and journal papers have been
published that examine the benefits and risks of growth, with supportive evidence
having been found for both. On the one hand, researchers regard growth as essential
if companies are to remain vital and competitive (Drucker, 1973; Robins &
Wiersema, 1995). At the same time, however, it has been argued that rapidly growing
2
companies face greater managerial complexity than slower-growing firms (Covin &
Slevin, 1997; Gartner, 1997; Hambrick & Crozier, 1985). Studies have shown that
high levels of growth may destroy shareholder value and adversely affect profitability
(Baumol, 1962; Hedberg, Nystrom, & Starbuck, 1976; Richardson, 1964; Whetten,
1987). While theorists commonly agree that corporate performance rises with sales
growth, there may be an optimal point beyond which further growth adversely affects
performance. However, there is a lack of empirical evidence on the exact link
between a firm’s growth rate and its performance (Markman & Gartner, 2002). While
some studies found support for a curvilinear relationship (e.g., Ramezani, Soenen, &
Jung, 2002), others revealed a positive and linear effect (e.g., Miedich & Melicher,
1985), or no significant linkage at all (e.g., Markman & Gartner 2002).
The inconsistencies and ambiguities in existing research raise the question whether
there is an optimum growth pace and, if so, how this optimum rate can be determined.
Addressing this gap, the aim of the present study is to develop a multi-perspective
model of optimum firm growth. The model's fundamental assumption is that optimum
growth rates are firm-specific and cannot be established across groups of different
firms. I believe that existing countervailing results may be traced back to the common
practice of classifying growth rates across companies and industries into normal,
high, and hyper growth (e.g., Markman & Gartner, 2002). However, it is more likely
that each firm's optimum degree of growth has to be determined on an individual
basis. I argue that identifying a firm's distinct optimum growth rate requires an indepth understanding of the firm-specific characteristics which determine corporate
growth.
Researchers have for years been intrigued by various factors that could enable and
constrain growth. To develop a multi-perspective model of optimum firm growth, I
seek to aggregate previous insights from different areas within the broader scope of
business economics. More specifically, I will build on the contributions of three
cornerstones of management research:
(1) the market-based view of the firm,
(2) the resource-based view of the firm, and
(3) financial theory.
Business economists from the market-based view point to external market factors’
dominant influence on firm growth (Ferrier, Smith, & Grimm, 1999; Kirzner, 1973;
Porter, 1980; Schumpeter, 1934). Theorists from the resource-based perspective
3
argue that growth is primarily determined by a firm’s human resources (Gander,
1991; Mishina et al., 2004; Penrose, 1959; Pettus, 2001), while studies from the
financial perspective emphasize the role of financial resources in enabling and
curtailing growth (Clark, Chiang, & Olson, 1989; Higgins, 1977; Kasznik &
McNichols, 2002). I will draw on these theoretical perspectives to derive minimum
and maximum thresholds that denote a firm's inherent corridor of optimum firm
growth. I argue that firms need to restrain their actual growth to the limits set by these
thresholds in order to realize superior performance.
In order to develop a theoretically as well as empirically well-grounded model of
optimum firm growth, I choose to proceed as follows. This dissertation begins with
an examination of the positive and negative effects of growth and the impact of
growth on firm performance. I will then outline the basic foundations of the marketbased, resource-based, and financial perspective on the antecedents and consequences
of firm growth. This literature review provides the groundwork for three selfcontained, full papers which constitute the main part of this study. The aim of these
three papers is to approach the question whether there is an optimum pace of growth
and, if so, how this optimum rate can be determined from each of the theoretical
perspectives previously outlined. In each paper, I will present a distinct model of
optimum firm growth. Considering previous theoretical insights, I will develop
research hypotheses, present the empirical research design, and the results of the
study, as well as concluding remarks on the contributions to existing research,
limitations, and managerial implications of each paper.
To provide an integrative view of firm growth, I will then synthesize the results of
these three papers. By combining their individual findings, I will deduce the concept
of the growth corridor, which determines a firm's minimum growth requirement as
well as its maximum growth boundary. After outlining the papers’ combined
theoretical contributions, I will proceed to demonstrate the implications of the growth
corridor for managerial practice. More specifically, I will review four positions firms
may take within the growth corridor. By presenting business cases of European
companies, I aim to provide practical guidelines on how to achieve successful growth
and outline the performance implications resulting from unfavorable positions within
the corridor.
This dissertation concludes with final remarks on its limitations as well as
implications for future research. I seek to make a valuable contribution to the current
academic debate as well as to assist practitioners in succeeding in their quest for
4
successful growth. The following figure provides an overview of the basic layout of
this study.
A Multi-Perspective Model of
Optimum Firm Growth
The Market-Based
Perspective
The Resource-Based
Perspective
The Financial
Perspective
The Corridor of Optimum
Firm Growth
Maximum Threshold
Minimum Threshold
Performance
Implications
Low
High
Low
Figure 1.1: Structure of the Dissertation
Theoretical
Background
Growth and Firm Performance:
Theoretical Foundations for a Multi-Perspective
Model of Optimum Firm Growth
5
GROWTH AND FIRM PERFORMANCE:
THEORETICAL FOUNDATIONS FOR A
MULTI-PERSPECTIVE MODEL OF OPTIMUM FIRM
GROWTH
Growthand
and Firm
Firm Performance:
Growth
Performance:
TheoreticalFoundations
Foundations for
Theoretical
for aa Multi-Perspective
Multi-Perspective
Modelof
ofOptimum
Optimum Firm
Model
FirmGrowth
Growth
Theoretical
Theoretical
Background
Background
A Multi-Perspective Model of
Optimum Firm Growth
The Corridor of Optimum
Firm Growth
The Market-Based
Perspective
Performance
Implications
Low
Maximum Threshold
The Resource-Based
Perspective
High
Minimum Threshold
The Financial
Perspective
Low
6
2. Theoretical Background
Growth refers to the increase in a firm size measure from one period to another
(Penrose, 1959: 11). Existing studies have utilized sales, profitability, as well as
workforce measures to determine growth. There is, however, an emerging consensus
in the literature that sales are the most relevant indicator of growth (Delmar,
Davidsson, & Gartner, 2003; Hoy, McDougall, & Dsouza, 1992; Weinzimmer,
Nystrom, & Freeman, 1998). Accordingly, throughout the entire study I will refer unless stated otherwise - to growth as the annual percentage increase in sales, defined
as rt = Salest / Salest-1 - 1.
2.1. Growth and Firm Performance
2.1.1. The Upsides of Growth
Most commonly, researchers have argued that growth may be advantageous for
organizations as larger businesses tend to have higher survival rates than small
companies (Aldrich & Auster, 1986; Baum, 1996; Mitchell, 1994; Schary, 1991). A
vast array of studies has come up with various explanations to elucidate this positive
relationship. First, it has been argued that large companies benefit from favorable
economies of scale and scope (e.g., Chandler, 1990; Porter, 2001). Bercovitz and
Mitchell (2007), for example, argue that firms with greater sales have access to more
extensive financial resources, increase the efficiency and effectiveness of
organizational routines, and create deeper external ties that may protect them in times
of crisis. Second, firm growth is regarded as an important indicator of firms’ health as
growth may help to overcome inertia and contribute to corporate renewal, which is
considered vital for survival in changing environments (Pettus, 2001; Robins &
Wiersema, 1995). Besides these positive effects on the organization, it has been
argued that corporate growth attracts exceptional management talent (Canals, 2001;
Morgan, 1988). First, growth increases opportunities for promotion within a company
(Dent, 1959; Whetten, 1987). Further, growth has been associated with higher levels
of executive compensation (Lambert, Larcker, & Weigelt 1991; Tosi, Werner, Katz,
& Gomez-Mejia, 2000) as well as increased prestige and other managerial benefits
(Morck, Shleifer, & Vishny, 1990; Murphy, 1985; Roberts, 1959). Conducting a meta
analysis, Tosi et al. (2000) found that firm size accounts for more than 40% of the
variance in total CEO pay, while firm performance accounts for less than 5% of the
variance. Lastly, it has been argued that larger firms attract financial resources
(Bercovitz & Mitchell, 2007). Growth is therefore generally considered essential to a
long and healthy corporate life and is an important indicator of corporate success
7
(Donaldson & Lorsch, 1984; McGrath, Kroeger, Traem, & Rockenhaeuser, 2001; von
Krogh & Cusumano, 2001).
2.1.2. The Downsides of Growth
Contrary to the pro-growth paradigm, other authors have related growth to numerous
challenges and long-term problems that could diminish a firm’s ability to generate
profits (Gartner, 1997; Greiner, 1972; Kazanjian, 1988). Hambrick and Crozier
(1985), for example, have identified four fundamental challenges of high growth:
instant size, a sense of infallibility, internal turmoil and frenzy, and extraordinary
resource needs. Inadequate management of these challenges is regarded as leading to
failure. Other authors point to the escalation in complexity that comes with growth
(Clifford, 1975; Covin & Slevin, 1997). An increase in complexity, defined as an
increase in the number and variety of, and interrelationships between tasks required
to effectively and efficiently administer a firm’s operations, demands substantial
changes in systems, structures, and capabilities (Miller, 1993; Nicholls-Nixon, 2005;
Penrose, 1959). The creation and effective administration of these changes is
considered to be very difficult to manage (Mahoney & Pandian, 1992). These
changes may furthermore lead to a momentous upsurge in costs (Covin & Slevin,
1997). Additionally, uncontrolled growth leads to internal friction that could hinder
normal operating procedures and may even lead to failure and bankruptcy (Markman
& Gartner, 2002; Slater, 1980). While a few firms do surmount the problems that
high growth engenders, many others fail (Hambrick & Crozier, 1985).
2.1.3. Empirical Evidence
One of the most controversial issues in the literature on corporate growth is therefore
whether there is an optimum long-term growth rate that maximizes firm performance.
Baumol (1962: 1078) was the first to suggest an "equilibrium rate of growth". He
maintained that beyond a certain point, a further increase in growth leads to a
decrease in organizational efficiency. Many subsequent studies adopted the view of
growth only being beneficial up to a point (e.g., Fethke & Currie, 1978; Hedberg,
Nystrom, & Starbuck, 1976; Richardson, 1964; Williamson, 1966). Whetten (1987:
342), for instance, proposes the "curvilinear benefits of growth" viewpoint,
suggesting that corporate performance generally rises with sales growth, but that
there is an optimal point beyond which further growth destroys shareholder value and
adversely affects profitability. Rather than maximizing growth, firms should thus
strive for optimum growth (Drucker, 1973; Higgins, 1977).
8
2.1.4. Optimum Growth
While the notion of optimum firm growth has gained common acceptance, the
empirical evidence remains ambivalent. Only two studies found support for a
curvilinear relationship. Pfeffer and Salancik (1978) found that up to a point
profitability in growing companies increased and then tapered off. Similarly,
Ramezani and his colleagues (2002) identified an inverted U-shaped relationship
between market performance and sales growth. Others, however, revealed a positive
relationship between sales growth and performance. Nerlove (1968) found a
significant positive link between sales growth and return on investment. Subsequent
studies by Stano (1976) and Miedich & Melicher (1985) confirmed Nerlove’s
findings of a positive relationship. Capon, Farley, and Hoenig (1990) reviewed 88
studies that – while testing other propositions – also analyzed the relationship
between growth and performance. They concluded that growth was consistently
related to higher financial performance. More recent studies have, however, mostly
failed to establish a significant relationship. Chandler and Jansen (1992) found no
statistical relationship between firm growth and financial performance. Likewise, in a
study of law firms, Weisbord (1994) found that sales growth and profitability were
not correlated. Markman & Gartner (2002) used longitudinal data on Inc. 500 firms
and found no significant relationship between sales growth and profitability. In sum,
empirical evidence for the relationship between growth and performance is
inconclusive.
These inconsistent findings can be partially ascribed to methodological weaknesses in
many of the above studies – such as biased samples and issues with common method
variance – that obscure or distort the true relationships. However, the more pertinent
explanation may be traced back to the practice of classifying growth rates across
companies and industries into normal, high, and hyper growth (e.g., Markman &
Gartner, 2002). Various researchers have argued that firms’ growth abilities are
dependent on their unique resource bases and market conditions (e.g., Penrose, 1959;
Porter, 1980; Slater, 1980). It is thus more likely that the relative degree of growth is
contingent upon firm-specific characteristics, rather than being valid and applicable
to firms in general. Increasing the firm's size by 20% may represent high growth for
one firm, while representing moderate or even low growth for another.
I argue that the level of optimum growth varies from firm to firm and cannot be
established across whole populations of firms. Determining a firm’s optimum growth
rate may require a more in-depth understanding of the firm-specific thresholds to
growth. Consequently, I argue that there are firm-specific minimum requirements and
9
maximum boundaries which determine the amount of growth that relates positively to
firm performance. I will build on three distinct research streams within the broader
scope of business economics to determine these boundaries. I argue that growth
outside these thresholds (both too little growth and too much growth) may have a
negative performance effect.
2.2. Theoretical Perspectives on Firm Growth
A firm’s growth rate may be determined and constrained by one or more of four
circumstances: (1) physical inputs, (2) managerial capacity, (3) financial resources,
and (4) investment opportunities (Richardson, 1964; Mahoney & Pandian, 1992).
While scholars generally agree that physical inputs play a minor role in today’s
business environments, the three remaining factors – human resources, financial
resources and market factors – have gained widespread attention in the extant
literature.
2.2.1. The Market-Based Perspective on Growth
Business economists point to external market factors’ dominant influence on firm
growth (Ferrier et al., 1999; Kirzner, 1973; Porter, 1980; Schumpeter, 1934). Both
resource-based and financial theories implicitly assume that the firm is not
constrained by the external environment. However, this is not a reasonable
assumption in respect of most firms operating in imperfectly competitive markets.
The influence of industry-wide factors on a firm’s growth and profitability is a
center-piece of business economics and has become a main tenet of business policy
(Porter, 1980; Smith, Ferrier, & Grimm, 2001a). From this perspective, an
understanding of the competitive structure within which the firm is operating is a
precondition for setting realistic growth targets (Porter, 1979; Prescott, Kohli, &
Venkatraman, 1986).
Within the broader scope of the market-based view of the firm, the competitive
dynamics stream of research analyzes the consequences of firm interactions within an
industry. The aim of this research stream is to uncover why some firm interactions
turn out beneficial while others are detrimental to firm performance (Ketchen, Snow,
& Hoover, 2004). Findings suggest that firms have to engage in competitive activity
in order to be able to expand their position within a market and defend it (e.g., Ferrier
et al., 1999). At the same time, however, it has been found that competitive activity
may provoke industry rivalry, which negatively affects the firm's performance (e.g.,
Chen & Miller, 1994). Considering the combined insights of the competitive
dynamics research stream indicates that firms have to consider the competitive
10
environment within which they act when planning their growth. While they need to
be able to defend their position within a market, they have to balance the amount of
competitive action against the risk of triggering competitor retaliation if market share
gains are achieved at the expense of the firm's rivals.
2.2.2. The Resource-Based Perspective on Growth
Firm growth is one of the core topics of the resource-based view of management
science (Mahoney & Pandian, 1992). Most of all Edith Penrose, pioneer of the
resource-based view of the firm, has extensively studied the antecedents and effects
of firm growth. She suggests that firms can be viewed as collections of productive
resources. A firm may achieve superior returns not simply because of better
resources, but rather because the firm’s distinctive capability involves making better
use of those resources. In her seminal work, "The Theory of the Growth of the Firm",
she states that "the firm's existing human resources provide both an inducement to
expand and a limit to the rate of expansion." (1959: xii).
More specifically, the resource-based view of the firm suggests that excess human
capacity (i.e., human resource slack) takes center stage in explaining corporate
growth (Goerzen & Beamish, 2007; Penrose, 1959; Pettus, 2001). Firms grow to
utilize the excess capacity that human resources provide (e.g., Penrose, 1959). The
existence of excess resources has been explained by the process of learning through
experience (Goerzen & Beamish, 2007). As employees gain experience in their daily
routines and learn how to do operations more efficiently, firm-specific human
services are freed up. Those resources in turn provide an incentive to expand the
existing business and/or diversify into new businesses to achieve economies of scale
and scope (Kor & Mahoney, 2000). On the other hand, it has been argued that the
limited amount of human resource slack determines the maximum amount of firm
growth (Pitelis, 2007).
2.2.3. The Financial Perspective on Growth
Studies from the finance literature emphasize the role played by financial resources in
enabling and curtailing growth (Clark et al., 1989; Higgins, 1977; Kyd, 1981;
Robinson, 1979). From a financial perspective, one of the firm’s main objectives is to
maximize shareholder returns (Rappaport, 1986). Studies dealing with the formation
and consequences of shareholders' expectations have linked high levels of firm
performance to the meeting or beating of these expectations. Growth is thus
considered an important prerequisite for superior shareholder returns.
11
Excessive sales growth, however, can be as destructive to a firm’s survival as no
growth (Clark et al., 1989). Empirical evidence shows that the stock market penalizes
companies that pursue growth without a simultaneous consideration of their cost of
capital (Koller et al., 2005: 72). Van Horne (1997: 744) concludes: "The management
of growth requires careful balancing of the sales objectives of the firm with its
operating efficiency and financial resources". Beating expectations may thus be
constrained by the firm's available financial resources to sustain high levels of sales
growth.
12
3. A Multi-Perspective Model of Optimum Firm Growth
In the following three chapters of my dissertation, I will present three models of
optimum firm growth that consider the market-based, resource-based, and financial
perspectives of business theory, as introduced above. Each of these theories has made
its own contributions to explain the antecedents and/or consequences of firm growth.
However, there is a lack of consensus within and between those research streams on
the factors that influence the rate of firm growth as well as on the way firm
performance may consequently be affected. The aim of the three ensuing papers is to
delve into these discussions and shed light on the contradictions in existing
theoretical and empirical findings.
In the first paper, I build on research on competitive dynamics to specify firmspecific boundaries for profitable firm growth. The aim of the paper is to close a gap
in existing research regarding the performance implications of competitive activity.
While researchers in the competitive action stream suggest that increasing
competitive activity positively affects firm performance, the competitive rivalry
stream argues that there may be a limit to this positive relationship. This research
stream indicates that increasing levels of competitive action provoke industry rivalry,
which negatively affects firm performance. While acknowledging this differential
effect of competitive action, extant research has hitherto not provided an integrative
view upon the relationship between competitive activity and firm performance which
recognizes the findings of both research streams. The results of my study indicate that
firms should engage in a level of competitive activity that allows them to defend their
relative competitive position. At the same time, however, competitive action should
remain within the limits set by the firm's financial resources. I find that firms that
engage in competitive action beyond this limit experience a negative performance
effect. Furthermore, the results of this study indicate that unabsorbed slack positively
moderates the relationship between high levels of competitive activity and firm
performance.
In the second paper, I build on resource-based theory to derive thresholds of optimum
firm growth. The study centers on different types of human resource slack and their
effect on the relationship between firm growth and performance. Previous research is
divided by disagreement on the conceptualization of human resource slack. The
classic resource-based view suggests a positive relationship between relative human
resource slack and firm growth. The modern resource-based view, on the other hand,
studies absolute human resource slack and suggests a negative effect on firm growth.
13
Neither research stream, however, has studied the combined effects of different types
of human resource slack and growth on firm performance. The results of this paper
indicate that firms whose rate of sales growth exceeds relative human resource slack
perform better than firms whose sales growth rate remains below its level of relative
human resource slack. At the same time, however, the positive performance effect
tapers off as the firm's growth increases. Absolute human resource slack curbs the
negative effect of high growth. On the other hand, the findings of this study indicate
that absolute human resource slack aggravates the overall negative performance
effect experienced by firms that don't transform relative slack into growth.
The third paper builds on a research stream within financial theory, which analyzes
the mechanisms behind the formation of earnings expectations. This research stream
suggests that firms which exceed growth expectations outperform firms which don't
meet expectations. Contrary to this finding, I argue that a significant performance
difference results from meeting expectations, as opposed to beating them. The
findings of this paper indicate that there is a limit to the degree of beating revenue
expectations, and that firms which grow beyond this limit experience a negative
performance effect. Additionally, I find that irrational shareholders' expectations may
have serious consequences for firm performance. More specifically, the results of this
study suggest that the total return to shareholders decreases if shareholders expect a
rate of sales growth beyond the firm's financial limits.
Taken together, the following three papers combine to form a multi-perspective
model of optimum firm growth. Each of the studies points to certain firm-specific
minimum requirements and maximum thresholds of profitable growth. While each
paper individually contributes to existing theoretical findings as well as offering
implications for business practice, an added value results from their combined
insights. Subsequent to the following three papers, I will thus reconcile their
individual findings to derive the corridor of optimum firm growth. I will then discuss
the corridor's implications for management practice.
14
PAPER I:
THE MARKET-BASED PERSPECTIVE TO
OPTIMUM FIRM GROWTH
Growth and Firm Performance:
Theoretical Foundations for a Multi-Perspective
Model of Optimum Firm Growth
Multi-Perspective
of The Corridor of Optimum
Theoretical A A
Multi-Perspective Model
Model of
Firm Growth
Background Optimum
OptimumFirm
FirmGrowth
Growth
Performance
Implications
The Market-Based
ThePerspective
Market-Based
Perspective
Low
Maximum Threshold
The Resource-Based
Perspective
High
Minimum Threshold
The Financial
Perspective
Low
15
Reconciling Competitive Action and Competitive Rivalry:
Implications for Firm Performance
Abstract
Research on competitive dynamics proposes that competitive action positively affects
firm performance. Conversely, scholars investigating rivalry argue that high
competitive action levels may negatively affect performance. Reconciling the two
streams, I specify firm-specific boundaries for competitive action. Drawing on panel
data from Fortune 500 companies, I observe a negative performance effect in respect
of firms (1) whose competitive action is insufficient to defend their competitive
position, and (2) whose competitive action exceeds their financial resource limits.
Further, I find that specific types of organizational slack enable firms to curb the
negative performance effects related to high competitive action levels.
Keywords: Competitive Action; Competitive Dynamics; Competitive Rivalry; Firm
Performance; Organizational Slack.
16
4. Reconciling Competitive Action and Competitive Rivalry:
Implications for Firm Performance
A key objective of research in the field of strategic management is to reveal the
dynamics underlying interfirm competition (Hitt, Boyd, & Li, 2004). The purpose of
strategic management’s "action perspective" is to study the antecedents and
consequences of competitive moves. Building on Schumpeter's (1934) theory of
creative destruction, the literature on competitive dynamics attempts to uncover why
some firm interactions turn out beneficial while others are detrimental to firm
performance (Ketchen, Snow, & Hoover, 2004). Research on this topic has found that
the number, type, and timing of competitive moves that a firm undertakes against its
rivals are a determining factor regarding long-term competitive advantages and firm
performance (Smith et al., 2001a). Such insights are of paramount importance to
strategic management as they help scholars and managers alike to understand how
competitive dynamics impact on firm performance (Chen & MacMillan, 1992).
One of the most important research streams on competitive dynamics proposes that a
firm's competitive advantage results from the competitive action undertaken against
rivals (e.g., Ferrier et al., 1999; Grimm, Lee, & Smith, 2005; Ketchen et al., 2004).
Accordingly, firms need to engage in aggressive behavior in order to defend and
expand their position within a market. From this perspective, competitive action
positively affects firm performance. Conversely, an alternative research stream on
competitive rivalry proposes that ameliorating a firm's market position relative to that
of its competitors can negatively impact its performance (e.g., Chen & Miller, 1994;
Rindova, Becerra, & Contardo, 2004; Schomburg, Grimm, & Smith, 1994).
Accordingly, market share gains frequently presuppose excessive marketing
expenditures, below-cost pricing or inappropriate mergers and acquisitions (Smith et
al., 2001a). Further, competitive moves could lead to competitors retaliating or
competitive wars, which tend to impact negatively on the warring firms’
performance.
While the combined insights from the competitive action and the competitive rivalry
research streams indicate that there should be an optimum competitive action level,
no theory has been formulated to date, nor has empirical research been conducted on
this important topic. This lack of studies is the result of the two research streams
emerging in a somewhat isolated and self-contained manner (Ketchen et al., 2004).
This paper’s objective is therefore to reconcile the two research streams by
identifying a firm-specific "corridor" that determines the required upper and lower
17
boundaries of competitive action to sustain competitive advantage. Building upon
existing research (e.g., Chen & Hambrick, 1995; Ferrier, 2001; Ferrier et al., 1999;
Schomburg et al., 1994; Young, Smith, & Grimm, 1996), I propose that competitive
action results in a general positive performance effect, but that this effect decreases
with increasing competitive action levels. More specifically, I argue that firms need
to engage in sufficient competitive action to defend their competitive position,
although this competitive action should remain within the limits set by the firm's
financial resources (e.g., Raisch & von Krogh, 2007; Smith et al., 2001a;
Varadarajan, 1983). I thus propose that firms that engage in competitive action
beyond the limits set by their financial resources experience a negative performance
effect. Since previous authors have suggested that different types of organizational
slack moderate the relationship between competitive action and performance (e.g.,
Ferrier, 2001), I also investigate this relationship in the context of my interest in "the
corridor" of competitive action.
The remainder of this paper is structured as follows: In the next section, I review the
literature on competitive action and competitive rivalry, formulating theory that
reconciles findings from both research streams. Reviewing the literature on
organizational slack, I also hypothesize the way in which different types of slack may
moderate the relationship between competitive action and performance.
Subsequently, I outline the research design. Here, I argue for a new measure for
competitive action. Prior research measured the competitive action level as the
number of competitive moves a firm carries out during a given period (e.g., Ferrier et
al., 1999; Young et al., 1996). This measure is, however, input-oriented and fails to
assess competitive action's actual qualitative output. In contrast, the present study
measures the level of competitive action by computing changes in the firm’s relative
competitive position. A feasible generalized least squares estimation is deployed to
test the hypotheses by means of panel data drawn from the Fortune 500 list of
companies over a ten year period.
Next, I discuss the results of the study. I find a positive relationship between
competitive action and firm performance, but also boundaries that constrain a firm’s
competitive action. I find a negative performance effect when a firm’s competitive
action level is insufficient to defend its relative competitive position and a negative
performance effect for those firms whose competitive action levels exceed their
financial resource limits. Moreover, I find that unabsorbed slack curbs the negative
performance effect related to high competitive action levels. Finally, I discuss the
18
results and conclude the paper by pointing to avenues for future research and drawing
implications for management practice.
4.1. Theory
In the following, I briefly introduce the origins of competitive dynamics research, and
develop theory based on a review of the two research streams within this area:
competitive action and competitive rivalry. Moreover, based on a review of work
from organization theory, I hypothesize relationships between organizational slack
and competitive action.
The origin of competitive dynamics research is Schumpeter's (1934) theory of
"creative destruction" which explains the dynamic market processes by which firms
act and react in the pursuit of market opportunities (e.g., Smith, Grimm, Gannon, &
Chen, 1991). Researchers working on competitive dynamics have recently extended
the Schumpeterian perspective by integrating Austrian economics (Young et al.,
1996; Ferrier et al., 1999). Austrian economics focuses on the processes by which
markets move toward and away from equilibrium (Smith, Ferrier, & Ndofor, 2001b),
allowing researchers to theorize the role played by competitive action and reaction.
Consequently, recent research on competitive dynamics has three characteristics:
First, authors take an external view of firms, studying their behavior and actions in
the marketplace. The timing, type, and number of actions firms undertake have
become pivotal variables with substantial explanatory power (Smith et al., 2001a).
Second, researchers tend to focus on competitive interdependence. Each of a firm's
moves needs to be coordinated and must be evaluated in terms of the response that it
may elicit from rivals (Ketchen et al., 2004). The unit of analysis is therefore not the
single firm, but samples of interacting firms (e.g., Smith et al., 1991; Young et al.,
1996). Finally, competitive dynamics researchers aim to identify the reasons for and
effects of competitive actions.
Within the larger area of competitive dynamics, two distinct, self-contained, and
isolated research streams have emerged (Ketchen et al., 2004). While the competitive
action stream of research focuses mainly on the positive role played by competitive
action, the competitive rivalry stream of research highlights the negative performance
effects that escalating competition might have on firms within an industry.
19
4.2. Competitive Action: The Lower Boundary
The competitive action research stream defines competitive action as any "externally
directed, specific, and observable competitive move initiated by a firm to enhance its
relative competitive position" (Smith et al., 2001b: 321). Researchers in this stream
usually make three important assumptions derived from D’Aveni’s (1994) theory of
hypercompetition: (1) competitive advantage is short-lived because aggressive firm
actions disrupt the causal linkages between competitive conduct and performance; (2)
firms must undertake a series of actions to continuously recreate competitive
advantage; (3) firms with more competitive actions are expected to show superior
performance.
Based on these assumptions, researchers empirically investigated different aspects of
competitive action, including repertoires, timing, and level of competitive action.
First, a group of researchers studied entire repertoires of competitive action carried
out by a firm in a given year. Their findings suggest that broad and complex sets of
actions are more likely to have a positive impact on firm performance than narrow
and simple repertoires of actions. In a study of the U.S.-based airline industry
between 1979 and 1986, Miller and Chen (1994) found that the action level that a
firm exhibits when altering its competitive stance had a positive effect on short-term
performance, while these benefits diminished with increases in market diversity.
Further, Miller and Chen (1996) studied "competitive simplicity" - a tendency by
firms to concentrate intensely on a few central competitive actions. Competitive
simplicity hurts firm performance as the firms do not take full advantage of the
opportunities offered by changing competitive environments. In a cross-industry
study, Ferrier et al. (1999) confirmed the earlier finding that market leaders that carry
out a simpler set of competitive actions than their challengers, are more likely to
experience market share erosion and dethronement.
Second, researchers examined the effects of the timing of competitive actions. For
example, D'Aveni (1994) argued that the faster a firm acts, the more effectively it can
outmaneuver its competitors and delay their response. Furthermore, firms build
internal routines and knowledge on how to compete, which increase their decisionmaking efficiency (Dickson, 1992). Examining first-mover advantages in three
distinct industries, Lee, Smith, Grimm, and Schomburg (2000) found a positive
relationship between the speed of product introduction relative to that of rivals, and
firm performance. Moreover, the study revealed greater shareholder wealth effects for
first and second movers compared to late movers. This research supports earlier work
by Ferrier et al. (1999) who found that firms that were slower than their challengers
20
in introducing new competitive actions were more likely to experience market share
erosion and dethronement. Studying the drivers and consequences of competitive
aggressiveness in a matched-pairs sample in 16 different industries over a seven-year
period, Ferrier (2001) found that firms carrying out competitive actions in rapid
succession experienced a positive impact on firm performance. Further, Smith et al.
(2001a) studying the effects resulting from a delay in competitive reaction, found that
the faster a firm responds to challenger actions, the greater the firm's profits.
Third, researchers aimed to reveal how the level of a firm's competitive action affects
firm performance over a given period. In their study of single-business firms in the
U.S. computer software industry, Young and his colleagues (1996) found that higher
levels of firm-level competitive action (measured as the annual sum of each firm's
moves) relates to higher firm performance. Similarly, Ferrier et al. (1999)
demonstrated that the higher the number of competitive moves carried out by a firm
in a given year, the better the firm performance, since firms may exploit the
opportunities available in the market better. Further, Ferrier (2001) found that firms
that carry out a high number of actions in response to a rival's attack, experience
market share gains. Reversing this proposition, Miller and Chen (1994) established
that unsuccessful firms exhibited a lower competitive action level than their rivals.
Firms that initiated few competitive moves in the past decreased their competitive
action over time even further. Studying 57 bankrupt firms and 57 matched survivors,
D'Aveni and MacMillan (1990) found that managers of failing firms had gradually
reduced their firms' competitive action level. The reduced aggressiveness and lack of
an external focus contributed to negative performance.
In sum, recent research suggests that the more complex and broad the repertoire of
competitive actions, the faster the execution of competitive moves, and the higher the
competitive action levels are, the better the firm performance is (Ketchen et al.,
2004). Ferrier (2001: 859) concludes that "the main lessons drawn from these
research efforts is that aggressive competitive behavior is related to better
organizational performance."
While prior literature suggests that competitive action relates to firm performance, it
does not explicitly address the question if there is a minimum competitive action level
needed to induce this positive performance effect.
Possible answers are found in a research stream within the competitive dynamics
literature that investigates dynamic market processes to explain the persistence of
21
market share leadership and changes in firms’ competitive position (e.g., Ferrier et
al., 1999; Young et al., 1996). Here, researchers argued that competitive action helps
the firm chip away market share from the leader, thus improving its own competitive
position in the market (Huff & Robinson, 1994). Similarly, market share leaders are
expected to lose their position unless they take competitive action to prevent market
share erosion (Ketchen et al., 2004). Studying 41 industry leaders and their respective
challengers over seven-years, Ferrier and his colleagues (1999) found that market
leaders are more likely to lose market share if they initiate fewer moves than their
challengers, if the timing of their actions is slower than that of their challengers, and
if the action repertoires are less complex than those of their challengers. In turn,
engaging in competitive action to prevent market share erosion and dethronement by
more aggressive rivals is positively related to firm performance (Chen & Hambrick,
1995; Young et al., 1996). Defending one’s relative competitive position by actively
engaging in sufficient competitive action levels is thus considered a prerequisite for
firm success. Based on the foregoing discussion, I expect that:
Hypothesis 1. Firms whose competitive action enables them to defend their relative
competitive position have higher performance than firms with lower competitive
action levels.
4.3. Competitive Rivalry: The Upper Boundary
While research on competitive action provides some support for the positive
relationship between competitive action and firm performance, a concomitant
research stream examining competitive rivalry proposes a different relationship (e.g.,
Chen & Miller, 1994; Rindova et al., 2004; Schomburg et al., 1994). This stream is
derived from the industrial organization paradigm. Industrial organization scholars
thus define "rivalry" as a sequence of competitive moves by industry incumbents
(e.g., Bettis & Weeks, 1987; Caves, 1984; Porter, 1980). Firm-level competitive
action may provoke industry-level rivalry that dissipates positive performance
outcomes in a competitive battle. Rindova et al. (2004: 671), for example, coined the
term "competitive war" to describe periods of "intensified competitive action among
rivals."
In turn, strong industry-level rivalry is expected to negatively affect incumbent firms’
performance. For example, Young and his colleagues (1996) argue that the industry
rivalry level affects firm profitability prior to strategy implementation by increasing
the costs of resource acquisition. Furthermore, the industry rivalry level affects firm
profitability after strategy implementation, by increasing the cost of defending the
22
firm against product or market rivals. Consequently, the competitive rivalry stream of
research suggests that overly active firms may damage their financial performance,
since their competitive actions affect competitors, thus inciting competitive retaliation
(Chen & Miller, 1994; Schomburg et al., 1994; Smith, Grimm, & Gannon, 1992).
The negative relationship between high levels of competitive action and firm
performance has been validated in a series of empirical studies. Firms improving their
relative competitive position usually achieve this by price-cuts or excessive
expenditures, depleting their financial resources (e.g., Armstrong & Collopy, 1996;
Buzzell, Gale, & Sultan 1975). Zeithaml and Fry (1984) examined conditions for
simultaneous increases in market share and profitability. Their findings suggest that
firms with a decreasing Return on Investment (ROI) spend more than competitors on
media advertising and other promotion than those with increasing ROI. Additionally,
empirical studies indicate that intense industry rivalry is related to the surging costs
of scarce resource procurement, and could spur suppliers to extend distribution to
rivals (Barney, 1991; Mahoney & Pandian, 1992; Peteraf, 1993).
Researchers have also argued that competitor responses do not only neutralize a
competitive action’s benefits, but that they may also induce a need for further actions.
Consequently, either costs rise and profitability shrinks, or revenues fail to rise fast
enough to compensate for the surging costs (Porter, 1980, 1985; Scherer & Ross,
1990; Shamsie, 1990). Price-cuts and excessive advertising have received the most
attention in prior work as both types of competitive moves could have possible
disastrous consequences for firm performance (see for example, Scherer & Ross,
1990). Netter (1982), who examined the performance implications of excessive
advertising on 116 firms in twelve industries, found that competitive advertising may
be destructive to firm performance. Competitors' advertising reduces the profitability
in firms that advertise intensively.
Several authors consequently suggest that competitive actions have to be evaluated in
respect of their financial feasibility (e.g., Raisch & von Krogh, 2007; Varadarajan,
1983). Armstong and Collopy (1996) argue that firms with a strong "competitor
orientation" - those that increase their relative competitive position at all costs - are
less profitable than firms with stronger profit orientation. Beyond a certain point,
negative effects are expected from competitive action such as excessive expenditures
and aggressive pricing below cost. Researchers argue that this point is reached when
competitive action requires capital commitments that exceed a firm’s capitalgenerating ability (Fruhan, 1972; Smith et al., 2001a). Firms’ competitive action may
23
be constrained by the financial resources that are needed to improve and defend their
competitive position. Thus, based on this research stream, I expect that:
Hypothesis 2. Firms whose competitive action remains within their financial means
have higher performance than firms with higher competitive action levels.
4.4. Organizational Slack and Competitive Action
Organizational slack refers to the possession of more resources than are required for
normal, efficient firm operation (Cyert & March, 1963; Bourgeois, 1981; Singh,
1986). Organizational slack can be defined as ". . . actual or potential resources which
allow an organization to adapt successfully to internal pressures for adjustment or to
external pressures for change in policy as well as to initiate changes in strategy with
respect to the external environment" (Bourgeois, 1981: 30).
A conjecture in organization theory (e.g., Mishina et al., 2004; Pfeffer & Salancik,
1978) is that the mere existence of excess resources has a positive impact on firm
performance. Examining determinants of organizational risk raking, Bromiley (1991),
for example, found that organizational slack was positively related to firm
performance. Similarly, Miller and Leiblein (1996) indicate a positive relationship
between slack and performance in respect of a sample of manufacturing firms.
Organizational slack may act as a buffer that insulates the organization’s technical
core from environmental turbulence (Tan & Peng, 2003). It may moreover provide
the flexibility to determine a course of action when trying to adapt to a changing
environment or having to respond to competitor strategies (George, 2005). In
addition, organizational slack enables the firm to experiment with new strategies,
such as introducing new products or entering new markets (Thompson, 1967).
In contrast to the performance-enhancing view of organizational slack, authors using
agency theory suggest a negative performance effect resulting from unproductive
resources within an organization. Organizational slack is therefore regarded as a
source of principal-agent problems, breeding inefficiency, inhibiting risk-taking, and
thus harming firm performance (Fama, 1980; Jensen & Meckling, 1976).
While previous research in the field of strategic management generally assumes that
organizational slack has a performance-enhancing effect (Chakravarty, 1986; Singh,
1986), I argue for a more refined conceptualization of how slack affects competitive
action and performance. According to Tan and Peng (2003) and Sharfman, Wolf,
Chase, and Tansik (1988), the relation between organizational slack and performance
24
depends on the specific type of slack considered. Previous research therefore broadly
conceptualizes organizational slack according to absorbed and unabsorbed slack
dimensions (e.g., Mishina et al., 2004; Sharma, 2000; Tan & Peng, 2003). Absorbed
slack refers to the resources tied up with a firms’ current operation, while unabsorbed
slack refers to resources not currently tied to any specific applications.
Unabsorbed organizational slack is highly discretionary. Such resources can be
converted into different uses should the need or opportunity arise (Mishina et al.,
2004). Examples include excess cash or unexhausted lines of credit (Sharfman et al.,
1988). Highly discretionary and accessible, unabsorbed organizational slack
facilitates problem-solving behavior (Tan & Peng, 2000). Meyer (1982) found that
organizations with unabsorbed slack respond faster and more effectively to
environmental changes than organizations with limited resources. Authors writing on
competitive dynamics argue that unabsorbed slack allows the firm to execute a higher
number of competitive actions (Sharfman & Dean, 1997; Young et al., 1996).
Ferrier's (2001) study lends support to this conjecture by showing that attack volume
and duration relate positively to unabsorbed slack.
Thus, firms possessing a large amount of unabsorbed slack should be able to sustain a
higher competitive action level (Gary, 2005; O'Brien, 2003). Unabsorbed slack
supports, for example, taking advantage of emergent business opportunities, or
resolving unforeseen product complications (Mishina et al., 2004). Further,
unabsorbed slack enables firms to generate a range of competitive actions to
proactively exploit opportunities that may arise in future, or to pursue unexpected
opportunities ex post (Greenley & Oktemgil, 1998). As firms engage in high
competitive action levels, they gradually reduce the amount of slack resources
available (Love & Nohria, 2005). The more unabsorbed slack available to the firm,
the more likely it is to maintain periods of high competitive action without
experiencing a negative performance impact. Therefore, I expect that:
Hypothesis 3. Unabsorbed slack positively moderates the relationship between
competitive action and performance for those firms whose competitive action level
exceeds the limits set by their financial resources.
Absorbed slack is tied up with current operations and amounts to excess costs in
organizations that are not easily redeployed (Tan & Peng, 2003). Absorbed slack
includes idle machines, excess production capacity, or excess overhead expenditures
(Cheng & Kesner, 1997).
25
In order to launch competitive actions, firms require resources that can be accessed
quickly and applied for multiple ends. However, absorbed slack cannot be effortlessly
converted to match different situations (Sharma, 2000). Once allocated, resources are
less useful if the task at hand changes (Mishina et al., 2004). Absorbed slack is thus
less suitable to seize unpredicted market opportunities or react to unpredicted
competitor threats. Accessing absorbed slack may even require substantial and costly
organizational change including downsizing (Cheng & Kesner, 1997; Daniel, Lohrke,
& Fornaciari, 2004). Researchers concur that freeing up resources through
downsizing has a negative effect on firm performance (Chadwick, Hunter, &
Walston, 2004; De Meuse, Vanderheiden, & Bergmann, 1994; Palmon, Sun, & Tang,
1997). Several empirical studies have also found that downsizing undermines longterm competitive advantage, initiates declining stock price performance, and
negatively affects productivity (Capelli, 2000; Iqbal & Shetty, 1995; Worrell,
Davidson & Sharma, 1991). In order to be effective, downsizing may therefore
require substantial (unabsorbed) resources. Consequently, high levels of absorbed
slack could tie up scarce resources over certain periods and thus constrain the firm's
ability to sustain high competitive action levels (Smith et al., 1991). I therefore expect
that:
Hypothesis 4. Absorbed slack negatively moderates the relationship between
competitive action and performance for those firms whose competitive action level
exceeds the limits set by their financial resources.
4.5. Research Design
In the following, I describe the sampling and data, the study measures, and present
the statistical methods and analysis.
4.5.1. Sample and Data
The sample employed for this study consists of all companies listed in the Fortune
500 index for the year 2005. I chose this sample for the following reasons: First, the
Fortune 500 firms represent a very large share of the total business activity in the
U.S., as well as large and diversified firms. Consequently, interest in the factors that
influence these large firms’ strategic decisions and performance outcomes is
warranted (Stimpert & Duhaime, 1997). Second, the sample avoids distorted findings
resulting from smaller firms’ highly volatile rates of competitive action (see Miller &
Chen, 1994; Young et al., 1996). Third, a multi-industry sample complements earlier
studies on competitive dynamics by expanding this area of research to firms with
26
multiple lines of business and which engage globally in multi-market competition
(Smith et al., 2001b). A multi-industry sample also prevents the findings from being
distorted by industry-specific characteristics affecting firm competitive action (Young
et al., 1996).
The reference time frame covers the period between 1995 and 2004. In setting this
time frame, I follow the recommendations by previous studies to use intervals of
between seven and ten years (e.g., Chen & MacMillan, 1992; Ferrier et al., 1999), as
well as research on corporate finance that demonstrates that firms may enjoy
discretion if they only temporarily exceed their financial limits (Clark et al., 1989;
Richardson, 1964). The latter works also prescribe a ten year time frame for empirical
investigations.
All relevant data for this study were obtained from the COMPUSTAT database that is
considered highly reliable and which has been frequently used in prior research (e.g.,
Glaum, Lichtblau & Lindemann, 2004; Lins & Servaes, 2002; Young et al., 1996). In
order to enhance the reliability of the data and counteract coding errors (miscoding
arising from the transfer of data from a primary data source to the electronic
database), I randomly checked the data accuracy against companies’ financial
statements. Some firms lacked data, limiting the final sample to 425 of the 500 firms
in the initial sample.
4.6. Measurements
4.6.1. Competitive Action
I captured competitive action by computing changes in a firm's relative competitive
position, which I measured by comparing the firm’s annual change in sales with the
average change in sales achieved by the firm’s major rivals (Ferrier, 2001). The
annual change in competitive position captures the actual effect of a firm’s
competitive moves, thus revealing the overall level or output of a firm’s competitive
action within a given period.
Conversely, most previous studies on the competitive dynamics stream of research
measured the competitive action level as a firm’s total number of competitive moves
(Young et al., 1996). This measure is, however, input oriented and fails to assess
competitive action’s actual qualitative output. Moreover, counting firms’ number of
competitive moves complicates the comparison of the competitive action levels
across a population of rival firms. Some firms may take fewer actions, but these
actions may be more substantial or more effective than those pursued by rivals.
27
Competitive action does not occur in a vacuum, but depends on what other firms
within the same competitive context do at the same time. An external benchmark is
therefore required to assess the relative level of a firm’s competitive action.
I used two measures to capture the competitive action level in this study: rivals’
competitive action (as an external benchmark for the firm) and firm competitive
action (which can be related to the rivals’ action).
4.6.2. Rivals’ Competitive Action
Rivals’ competitive action indicates the way in which each firm's major competitors
improved their competitive position within the specified time frame. I calculated the
change in industry competitive action in respect of each industry in which the firm
competed as the percentage change in the industry gross sales (e.g., Ferrier et al.,
1999). In accordance with prior studies, I measured industry gross sales at a two-digit
SIC level (e.g., Brush & Karnani, 1996). I computed industry gross sales in respect of
each industry and industry-year (year t) by aggregating the proportionate sales figures
of those firms that generated their largest, second largest, or third largest number of
sales in the respective two-digit industry. Following Raisch and von Krogh (2007), I
considered only the number of sales generated in the respective industry segment, not
the sample firms’ total sales. Firms with annual sales of less than one million USD
generated in the respective 2-digit SIC segment were excluded to avoid distortion of
the data. I furthermore excluded firms whose SIC classification changed from one
year to another (t to t-1). These measures limited the focus to firms that may be
considered long-term rivals to the sample firms in one or several of their business
activities.
In order to determine the level of rivals’ competitive action (RCA) in respect of each
firm, the following formula was applied:
RCAit = (RCASeg1 x WFSeg1) + (RCASeg2 x WFSeg2) + . . . + (RCASegN x WFSegN),
where RCASegN refers to the average change in competitive action in one of the firm’s
two-digit business segments. WF is a weighting factor that is calculated by the ratio
firm segment sales divided by the firm’s total sales, thus indicating the relative
number of sales that a firm generates in each of its businesses. WF thus measures the
relative importance of each segment in respect of the firm’s overall competitive
action. In sum, the formula yields the change of the weighted average industry
competitive action in respect of all two-digit industries in which the firm competes.
28
4.6.3. Firm Competitive Action
A firm’s competitive action (FCA) is measured by the firm’s annual percentage
increase in sales. I used the following formula for calculation purposes:
FCAit = (Salest / Salest-1) - 1.
The comparison of the firm’s competitive action with its rivals’ competitive action in
a given time period reveals the change in the firm’s relative competitive position.
4.6.4. Competitive Position
To assess a firm's ability to defend its relative competitive position I related the firm's
change in sales in each segment and year to the rivals’ competitive action in the same
segment (Ferrier, 2001). Firms, whose change in their competitive action level was
greater than or equal to the change in rivals' competitive action, were thus able to
defend their relative competitive position. In turn, firms, whose change in rival’s
competitive action exceeded their own change in competitive action level, were
unable to defend their relative competitive position. I created a binary variable (FCAit
< RCAit) to indicate whether (0) or not (1) the firm's level of competitive action was
sufficient to defend its relative competitive position. Additionally, RCAit - FCAit,
captures the distance between the firm's level of competitive action and the level of
industry competitive action.
4.6.5. Financial Resource Limits
I computed the firm's financial resource limit by drawing upon the sustainable growth
rate model initially proposed by Higgins (1977). The sustainable growth rate refers to
the "maximum annual increase in sales that can be achieved based on target
operating, debt, and dividend payout ratios" (Van Horne, 1997: 743). If a firm grows
at a faster rate than its sustainable growth rate, it is forced to increase its debt ratio,
decrease dividends, or issue new equity. The sustainable growth rate can be obtained
by equating annual capital requirements and capital generation potential. I applied the
following standard equation (e.g., Higgins, 1977; Varadarajan, 1983) to calculate the
sustainable growth rate:
SGRit = (Pit (1 - Dit) (1 + Lit)) / Ait - Pit (1 - Dit)(1 + Lit),
where Pit is the net profit margin, Dit the dividend payout ratio, Lit the debt-to-equity
ratio and Ait the total assets to sales ratio. In order to determine whether a firm's
competitive action remained within its financial resource limit, I compared the
29
sustainable growth rate with the firm's annual change in sales, using the above
formula. This measure captures the firm's internal boundary regarding the
competitive action level. Firms that exhibit sales growth below (or equal to) their
sustainable growth restrained their competitive action level to their financial limits.
Firms whose sales growth exceeds their sustainable growth rate are unable to
compete within their resource limits. I created a binary variable (FCAit > SGRit) to
indicate whether (1) or not (0) the firm's competitive action level exceeded its
financial limits.
4.6.6. Unabsorbed and Absorbed Slack
In order to capture unabsorbed and absorbed slack, researchers have relied on a vast
array of different measurements (see Daniel et al., 2004). The most widely accepted
measures were proposed by Bourgeois and Singh (1983), and are much used in the
literature on competitive dynamics (e.g., Ferrier, 2001; Smith et al., 1992). In this
study, I use similar measures for unabsorbed and absorbed slack. I measured
unabsorbed slack by means of the quick ratio, the ratio of current assets minus
inventory to current liabilities. The measure reflects the company's resources that are
not tied to any specific use (Bromiley, 1991; Ferrier, 2001; Smith et al., 1992).
Absorbed slack is measured by means of the ratio of sales, general, and
administration (SGA) expenses to sales. The ratio of SGA expenses to sales captures
the slack absorbed in salaries, overhead expenses, and various other administrative
costs (Bromiley, 1991). Both measures have been thoroughly discussed and
empirically validated in previous research (Daniel et al., 2004).
4.6.7. Performance
To assess firm performance, I used a market-based measure. Traditionally, strategy
research has defined performance according to accounting-based measures, with
return on assets considered a reasonable proxy (Lubatkin & Shrieves, 1986). Owing
to this study’s long-term orientation, market-based measures may, however, be more
appropriate for studying performance effects (Bruner, 2002). Moreover, market-based
performance measures are thought to reflect all of performance’s relevant information
rather than being limited to specific performance dimensions (Lubatkin & Shrieves,
1986). Several authors have designated the return to shareholders as a suitable proxy
with which to measure market-based performance (e.g., Baucus & Baucus, 1997;
Bruner, 2002; Holliday, 2001; Rappaport, 2006). I thus use the total return to
shareholders to measure firm performance (TRSit).
30
4.6.8. Control Variables
Previous research on competitive dynamics has generally controlled for time, size,
and industry effects (e.g., Ferrier et al., 1999; Young et al., 1996). I use a fixed-effect
estimator in the analysis to control for variables that are invariant over time, such as
industry membership. Additionally, I control for size effects. I used firm's total
number of employees as a measure of firm size, a proxy which has previously been
used in competitive dynamics research (e.g., Ferrier et al., 1999; Miller & Chen,
1996). Table 4.1 provides an overview of all the variables used in the study.
Control Variable
Sizeit
Dependent Variable
TRSit
Hypothesis 1
FCAit
RCAit
FCAit < RCAit
RCAit - FCAit
Hypothesis 2
SGRit
FCAit < SGRit
Hypothesis 3
SlackUit
Hypothesis 4
SlackAit
Total number of employees
Annual change of return to shareholders
Annual change of the level of competitive action
Annual change of the level of rivals' competitive action
Binary variable indicating whether (1) or not (0) the firm was able
to sustain its relative competitive position.
Variable indicating the distance between the firm's level of
competitive action and the level of rivals' competitive action.
Sustainable growth rate
Binary variable indicating whether (1) or not (0) the firm's level of
competitive action exceeded its financial limits
Level of unabsorbed slack
Level of absorbed slack
Table 4.1: List of Variables
4.7. Statistical Methods and Data Analysis
I made use of cross-sectional time series to assess the effect of competitive action on
firm performance. As previously explained, I collected the annual data of 425 firms
for the period between 1995 and 2004. When the data were pooled across firms and
across these ten years, the resulting sample had 4250 observations. Given the twodimensional structure of the balanced data set, I used panel data statistical methods
(Baltagi, 1995; Hsiao, 1986). I estimated the following general equation:
Yit = α + Xit'βit + δi + γt + εit,
31
where Yit is the dependent variable, Xit is a k-vector of regressors, and εit are the error
terms for i = 1, 2, …, M cross-sectional units observed for dated periods (t = 1, 2, …,
T). The α parameter represents the overall constant in the model, while the δi and γt
terms represent cross-section or period-specific effects (random or fixed). The β
coefficients may be divided into sets of cross-section-specific, period-specific, and
common (across cross-sections and periods) regression parameters.
A key benefit of utilizing panel data is the ability to test and control for the effects of
unobserved fixed factors, which, if left uncontrolled, can induce bias in the
coefficient estimates of the explanatory factors included in the model (Rajagopalan &
Datta, 1996). I restricted the sample to large firms, which prevents different residual
variances that depend on the absolute level of the variables (e.g., sales) from affecting
the estimation. However, the observations may no longer be independent as firm
characteristics are correlated over time (Finkelstein & Hambrick, 1990; Haleblian &
Finkelstein, 1993). It is unreasonable to assume that with regard to this study, the data
points in the longitudinal dimension are independent of one another. For instance,
unobserved firm-specific factors (e.g., corporate reputation, managerial teams) may
influence observations of the same firm and produce correlation across these
observations over time (Gimeno, 1999). Thus, instead of using the standard pooled
ordinary least squares (POLS) estimation, whose key assumption is independence
across all observations, I used a fixed-effect estimator. Fixed-effect estimators
remove all time-constant effects by subtracting the mean of the ten-year period,
thereby ensuring consistency in estimation. Moreover, fixed-effects models predict
the annual change in a dependent variable, as opposed to random-effects models
which are appropriate if aiming to explain variance among firms (Sanders &
Hambrick, 2007). Further, I used a feasible generalized least squares (FGLS)
estimation by assuming the presence of period-specific structures within the
residuals. The weighting of the observations helps to exploit all structures within the
data panel set, which enables efficient estimation. Lastly, I adjusted the standard
errors by using a White adjustment in the longitudinal period. This adjustment leads
to robust significance values. In order to test hypothesis 1 I estimated the following
equation:
TRSit = α + Sizeit βit + FCAit βit + (FCAit < RCAit) βit + (RCAit - FCAit) (FCAit <
RCAit) βit + γt + εit,.
The first coefficient in this and the following equations corresponds to the control
variable for firm size. The following coefficient assesses the general relationship
32
between competitive action and performance. The third coefficient estimates the
average performance of those firms that were unable to defend their relative
competitive position. With the fourth coefficient, I tested whether there is a
relationship between the degree of inaction and performance.
In order to test hypothesis 2 I estimated the following equation:
TRSit = α + Sizeit βit + FCAit βit + FCAit (FCAit < SGRit) βit + γt + εit,.
Again, I tested the relationship between the competitive action and performance. In
addition, I examined the specific effect of firms whose competitive action level
exceeded their financial limits in respect of firm performance.
In order to test hypothesis 3, I estimated the effect of the unabsorbed slack level on
performance in respect of those firms whose competitive action exceeded their
financial limits.
TRSit = α + Sizeit βit + FCAit βit + FCAit (FCAit < SGRit) βit + FCAit (FCAit < SGRit)
SlackUit βit + γt + εit,
For hypothesis 4, I estimated the effect of the absorbed slack level on performance in
respect of those firms whose competitive action exceeded their financial limits.
TRSit = α + Sizeit βit + FCAit βit + FCAit (FCAit < SGRit) βit + FCAit (FCAit < SGRit)
SlackAit βit + γt + εit,.
4.8. Results
In the following I present the results of the analysis. Table 4.2 provides the crosssectional, time series summary statistics (means, standard deviations, and correlation
coefficients) of all the variables employed. The panel data regression results of the
hypotheses testing are reported in Tables 4.3 to 4.6. I report the parameter estimates,
as well as the standard errors and values of the t-statistic in respect of each regression.
The probability levels are indicated by asterisks. The double asterisks indicate
significance at the 1% level, while the single asterisks indicate significance at the 5%
level. The reported results refer to the total return to shareholders (TRSit) as the
dependent variable.
33
Variable
1. Firm Performance, TRSit
2. Firm Competitive Action, FCAit
3. Rivals' Competitive Action, RCAit
4. Sustainable Growth Rate, SGRit
5. Unabsorbed Slack, SlackUit
6. Absorbed Slack, SlackAit
7. Firm Size, Sizeit
Mean
0.23
0.17
0.08
0.10
1.01
0.20
49344
s.d.
1
2
3
4
5
6
0.72
0.47
0.13
0.10
0.09 0.21
0.66
-0.01 -0.03 0.01
0.67
0.08 0.03 -0.00 0.01
0.13
-0.00 -0.08 -0.11 -0.01 0.12
93676 -0.04 -0.06 -0.03 0.02 -0.14 0.05
Table 4.2: Time Series Cross-Sectional Summary Statistics
Hypothesis 1 predicted that firms that engage in sufficient competitive action to
defend their relative competitive position are more successful than less active firms.
To test this hypothesis, I estimated a model with three explanatory variables: the level
of competitive action, a dummy variable for firms that were unable to defend their
relative competitive position, and a variable indicating the performance effect of the
degree of inaction of those firms that were unable to defend their relative competitive
position. Each variable has the expected sign and is statistically significant, thus
supporting the hypothesized relationship. The results indicate a generally positive
relationship between competitive action and performance (0.12, p < 0.02). As
predicted, the average performance of firms that were unable to defend their relative
competitive position is significantly lower than that of all other firms (-0.03, p <
0.02). In addition, the results suggest that performance decreases with the relative
degree of inaction (-0.29, p < 0.01). Thus, the larger the difference between the firm's
competitive action level and the competitive action level of other firms in the same
industry, the weaker the performance.
Variable
C
Sizeit
FCAit
FCAi < RCAit
RCAit - FCAit * FCAi < RCAit
Coefficient
Std. Error
t-Statistic
0.25
0.00
0.12
-0.03
-0.29
0.02
0.00
0.05
0.02
0.10
15.86**
-2.62**
2.33*
-2.38*
-3.05**
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
Cross-sections included
Total observations
0.18
0.66
61.16
0.31
0.72
387
3609
* p < 0.05
** p < 0.01
Table 4.3: Hypothesis 1, Results of Fixed Effects Panel Data Regression
34
In order to test hypothesis 2, I employed two explanatory variables: the level of
competitive action and a dummy variable indicating those firms that exceeded their
financial limits regarding their competitive action level. Both variables have the
expected sign and are statistically significant, thus supporting the hypothesized
relationships. Again, I found a generally positive relationship between competitive
action and performance (0.62, p < 0.01). The results also suggest that firms whose
competitive action level exceeds their financial limits experience a significant
deterioration in performance (-0.50, p < 0.01).
Variable
C
Sizeit
FCAit
FCAit (FCAit < SGRit)
Coefficient
Std. Error
t-Statistic
0.22
0.00
0.62
-0.50
0.01
0.00
0.09
0.09
23.63**
-2.68**
6.90**
-5.31**
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
0.19
0.65
68.89
0.31
0.72
Cross-sections included
Total observations
387
3635
* p < 0.05
** p < 0.01
Table 4.4: Hypothesis 2, Results of Fixed Effects Panel Data Regression
In order to test hypotheses 3 and 4, I built on the model estimating hypothesis 2, as
well as controlling for the effect of unabsorbed and absorbed slack. Of the three
relationships specified in hypothesis 3, all three are significant and have the expected
sign. The regression results suggest that firms with high unabsorbed slack levels are
able to curb the negative performance effect of competitive action levels that exceed
the firm's financial limits (0.40, p < 0.01).
35
Variable
C
Sizeit
FCAit
FCAit (FCAit < SGRit)
FCAit (FCAit < SGRit) SlackUit
Coefficient
Std. Error
t-Statistic
0.20
0.00
0.62
-0.87
0.40
0.01
0.00
0.10
0.17
0.13
23.83**
-2.84**
6.11**
-5.03**
2.98**
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
0.23
0.67
70.18
0.31
0.76
Cross-sections included
Total observations
332
3090
* p < 0.05
** p < 0.01
Table 4.5: Hypothesis 3, Results of Fixed Effects Panel Data Regression
Of the relationships specified in hypothesis 4, all have the expected sign. However,
the effect of absorbed slack is not significant (-0.18, p < 0.28). The findings do not
support the conjecture that high absorbed slack levels aggravate the negative
performance effect associated with high competitive action.
Variable
C
Sizeit
FCAit
FCAit (FCAit < SGRit)
FCAit (FCAit < SGRit) SlackAit
Coefficient
Std. Error
t-Statistic
0.22
0.00
0.64
-0.46
-0.18
0.01
0.00
0.11
0.13
0.17
20.42**
-2.62**
5.62**
-3.66**
-1.09
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
0.18
0.70
48.49
0.32
0.76
Cross-sections included
Total observations
332
2962
* p < 0.05
** p < 0.01
Table 4.6: Hypothesis 4, Results of Fixed Effects Panel Data Regression
4.9. Discussion and Conclusion
Explaining the antecedents and consequences of competitive action has long been a
key element of strategic management research (Hitt et al., 2004). In this study, I
reconciled two research streams within the area of competitive dynamics, in order to
shed light on how the competitive action level is related to firm performance.
Previous research on competitive action maintains that the more actions a firm carries
36
out, the faster it executes these actions, and the more complex and broad the
repertoire of these actions is, the better the firm's performance (e.g., Ferrier, 2001;
Ferrier et al., 1999; Grimm et al., 2005; Ketchen et al., 2004). This proposition
contradicts the competitive rivalry research stream’s findings. These findings suggest
that high competitive action levels within an industry may be negatively related to
firm performance (e.g., Chen & Miller, 1994; Rindova et al., 2004; Schomburg et al.,
1994; Young et al., 1996).
The results of the current study support the assumptions of both the competitive
action and the competitive rivalry perspectives. More specifically, in line with the
competitive action perspective (e.g., Ferrier et al., 1999), I found that competitive
action has a positive effect on firm performance. I extend the competitive action
perspective by demonstrating that a minimum competitive action level is required to
induce a positive performance effect. The results indicate that firms whose levels of
competitive action were insufficient to defend their relative competitive position
exhibit lower performance than firms that were able to defend their competitive
position. Further, I found that the negative effect increases as the difference between
the firm’s competitive action and that of its rivals widens. In line with prior
conceptualizations (e.g., Chen, Smith, & Grimm, 1992; Smith et al., 1991, 2001b;
Young et al., 1996), competitive action is intended to defend and enhance the firm’s
relative competitive position. Thus, the minimum competitive action level in which a
firm must engage may be determined by that of its major rivals.
In line with the competitive rivalry perspective (e.g., Miller & Chen, 1994, 1996), I
found that the positive performance effect decreases when firms engage in high
competitive action levels. I extend the competitive rivalry perspective by revealing
that there may be a firm-specific boundary to competitive action. The findings
indicate a negative performance effect in respect of those firms whose competitive
action level exceeds their financial resources. In line with prior arguments (e.g.,
Armstrong & Collopy, 1996; Raisch & von Krogh, 2007; Smith et al., 2001a),
competitive action may reach its limits when expenditures on advertising, price cuts,
or acquisitions turn excessive.
Reconciling the two research streams, the findings thus indicate that there is an
optimum range of competitive action. Too low as well as too high levels of
competitive action relate negatively to firm performance. A moderate amount, as
much as required to defend the competitive position, while still remaining within the
firm's financial resource limits, has the strongest positive impact on firm
37
performance. It is hoped that these findings will provide the foundation for further
cross-fertilization between the two streams in future research on competitive
dynamics.
Much of the present literature on competitive dynamics is based on the concept of
action and response, as well as the related idea that the performance effects of a
firm’s competitive action depend on the external competitive context in which the
action is carried out (Scherer & Ross, 1990; Smith et al., 1992, 2001b; Young et al.,
1996). My finding of a linkage between a firm’s minimum requirement in respect of
competitive action and the level of its rivals’ competitive action confirms and extends
this line of thinking.
Contrary to the external perspective, I also found that competitive action may be
enabled and constrained by the firm’s internal resources. While prior research has
considered firm characteristics, including size (e.g., Chen & Hambrick, 1995), age
(e.g., Young et al., 1996), and organizational slack (e.g., Smith et al., 1991), there is
limited research on how internal resources affect competitive action. In this study, I
demonstrate that the competitive action level that is beneficial for a firm depends on
the firm’s available resources. A competitive activity beyond the firm’s financial
resource limits has a negative effect on performance. Furthermore, I found that
unabsorbed slack, defined as the firm’s accessible and discretionary resources, may
curb the negative effect related to high levels of competitive action.
Prior research has already established that high levels of unabsorbed slack result in
firms engaging in higher levels of competitive action (Ferrier, 2001; Young et al.,
1996). I show that firms with such resources are also more successful at sustaining
high competitive action levels. Unabsorbed slack can therefore be regarded as a key
enabler underlying aggressive competitive behavior and firm development (Cyert &
March, 1963). Conversely, I did not find a significant relationship between the level
of absorbed slack and firm performance. This result supports prior work that found
absorbed slack to be unrelated to competitive action (Miller & Chen, 1994, 1996).
Firms may thus need to find effective ways of converting absorbed slack into
unabsorbed slack in order to increase their ability to act competitively.
The results of this study demonstrate the need to consider both external factors (such
as industry rivalry) and internal factors (such as the firm’s resource base) when
analyzing the relationship between competitive action and firm performance.
Researchers may thus need to extend the theoretical framing of their future papers
38
beyond Schumpeter and Austrian economics. Smith and his colleagues (2001b)
argued for alternative theories of competitive action, based on different sets of
assumptions, to be considered in competitive dynamics research. Considering and
developing alternative theories grounded in a wider range of literatures, such as the
resource-based view of the firm, organizational ecology, or evolutionary economic
theory, could provide richer explanations in respect of competitive actions and
reactions. For example, future research may investigate how competitive actions
deplete or enrich the firm’s resource base and how changes in the resource base affect
the firm’s subsequent competitive behavior. It could also be rewarding to distinguish
between different categories of resources when investigating their effect on
competitive action. Prior research on organizational slack, for example, has shown
that financial and human resource slack may have different performance outcomes
(Daniel et al., 2004; George, 2005, Mishina et al., 2004). While I focused on
absorbed and unabsorbed organizational slack, future research may adopt more finegrained categories of slack resources.
Prior research has conceptualized and measured competitive action as the number of
competitive moves a firm carries out during a given period (e.g., Ferrier et al., 1999;
Young et al., 1996). This measure is input-oriented and fails to capture competitive
action’s actual output, which makes it difficult to compare a firm’s competitive action
to that of its rivals. Nevertheless, competitive action does not occur in a vacuum. The
findings of this study demonstrate that the way in which a firm’s competitive action
relates to performance depends on that of its rivals. Furthermore, competitive action
is not an end in and of itself: firms undertake actions and responses to achieve certain
competitive outcomes (Smith et al., 2001b). A firm's level of competitive action
should thus be measured in relation to that of its rivals.
In this study, I conceptualize competitive action by measuring changes in the firm’s
relative competitive position over time. This measure provides a proxy for the actual
qualitative output of the firm’s competitive action when compared to that of its major
rivals. Consequently, the competitive action level can be assessed across a population
of firms within the same or different industries. While prior studies have mostly been
limited to single industries (e.g., Chen & Miller, 1994; Smith et al., 1992), the new
measure allowed me to study competitive action across a wide range of industries. An
additional benefit of my measure is that I was able to aggregate and analyze a firm’s
competitive action at the corporate level as opposed to limiting the observation to
single business segments (see Ferrier, 2001; Young et al., 1996). This work may
39
therefore allow future studies to better investigate multi-market competition between
firms (e.g., Gimeno, 1999; Young, Smith, Grimm, & Simon, 2000).
While output-oriented measures of competitive action have a number of advantages
over input-based measures, they fail to capture the firm’s actual effort (or input).
Some firms may have invested more resources than others for a similar gain in
competitive position. Future research investigating the interrelations between firm
resources and competitive action may thus benefit from considering both inputoriented and output-oriented measures of competitive action. A comparison of both
types of measures may allow strong conclusions to be drawn regarding the
effectiveness of the firm’s competitive actions.
Finally, this study has implications for management practice. Firms are frequently
driven to escalate competitive action, either by investors and analysts who expect
strong growth, or in reaction to competitors making similar moves (DiMaggio &
Powell, 1983; Haveman, 1993). Bandwagon effects may give rise to waves of
mergers and acquisitions, as repeatedly observed by prior research (Shleifer &
Vishny, 1991; Stearns & Allan, 1996). While such behavior may be understandable,
the present study suggests that it may not be optimal for the firm’s long-term success.
Firms require competitive action to remain vital, but managers should strive to find
an optimum level of firm competitive action rather than maximizing it. The findings
show that there is a fine distinction between being aggressive and being out of line.
Examples of former Fortune 500 companies, including Enron and WorldCom,
illustrate the dangers inherent in excessive competitive action if the firm’s financial
resource limits are disregarded. Competitive action should thus remain within the
firm's resource limits.
The model described in this study provides managers with a benchmark of what
could be feasibly accomplished. More exactly, the model may aid managers to
determine their company’s optimum competitive action level. While the counting of
the number of competitive moves that a firm undertakes does not capture the
resulting effects, measuring the changes in the relative competitive position provides
managers with an instrument with which to derive concrete targets for their firm’s
competitive action. As events unfold, companies’ realized action may incline to a
higher or lower level. A continued disparity between competitive action and the
boundaries should, however, prompt managers to take corrective action.
40
To conclude, previous research on competitive action and competitive rivalry evolved
in an isolated and self-contained manner. While the former proposes a positive
relationship between competitive action and performance, the latter proposes that this
relationship turns negative at high competitive action levels. The findings of this
study help to reconcile these two research streams. I demonstrate that firms benefit
most when aligning their competitive activities with the level of external rivalry that
they face and the level of disposable internal resources. The effect of competitive
action on firm performance may thus be firm-specific and contingent upon internal
and external conditions. It is my hope that this study will stimulate further integrative
research within the emerging research on competitive dynamics.
41
PAPER II:
THE RESOURCE-BASED PERSPECTIVE TO
OPTIMUM FIRM GROWTH
Growth and Firm Performance:
Theoretical Foundations for a Multi-Perspective
Model of Optimum Firm Growth
Theoretical A A
Multi-Perspective Model
Model of The Corridor of Optimum
Multi-Perspective
Background Optimum
OptimumFirm
FirmGrowth
Growth
Firm Growth
The Market-Based
Perspective
Performance
Implications
Low
Maximum Threshold
The
The Resource-Based
Resource-Based
Perspective
Perspective
High
Minimum Threshold
The Financial
Perspective
Low
42
Excess Human Resources: Growth and Performance
Implications of Absolute and Relative Levels of Slack
Abstract
Research on the relationship between human resource slack and firm growth provides
inconclusive findings. This ambiguity may be attributable to the fact that classic and
modern resource-based theories have conceptualized human resource slack
differently. The findings of this analysis of the Fortune 500 firms over a period of ten
years suggest that relative human resource slack induces a firm to grow. However,
the positive performance effect experienced by firms whose sales growth rate exceeds
relative human resource slack tapers off as growth increases. Absolute human
resource slack, which indicates that a firm possesses more slack than its rivals, may
suit to curb this negative effect. At the same time it aggravates the negative
performance effect of firms that don't use relative slack to further growth.
Keywords: Growth, Human Resource Slack, Performance, Resource-Based View.
43
5. Excess Human Resources: Growth and Performance
Implications of Absolute and Relative Levels of Slack
5.1. Introduction
The main emphasis of the resource-based view of management science is the study of
the antecedents and drivers of firm growth. According to this perspective, the excess
capacity of human resources provides an incentive to firm expansion and a source of
competitive advantage (Penrose, 1959). The emergence of excess human resources
(i.e., human resource slack) has been explained by the process of learning how to do
current operations more efficiently (Goerzen & Beamish, 2007). Excess human
resources arising from these efficiency gains, in turn, provide a resource cushion that
the firm may use to further expansion and drive growth (Kor & Mahoney, 2000).
However, it has also been argued that human resource slack may impede firm growth.
More specifically, researchers have associated human resource slack with political
and cognitive inertia (e.g., Hannan & Freeman, 1989). Accordingly, human resource
slack may not lead to growth into areas that may require new skills or knowledge.
Recent empirical studies examining the relationship between human resource slack
and growth have found evidence for this proposed negative relationship (Mishina et
al., 2004; Voss, Sirdeshmukh, & Voss, 2008). Existing empirical evidence on the
relationship between human resource slack and firm growth is inconclusive.
I suggest that inconsistencies in previous findings on the relationship between human
resource slack and growth may be attributable to the fact that human resource slack
has been conceptualized theoretically, as well as empirically, in two different ways.
On the one hand, relative human resource slack refers to productivity gains within the
firm over time. This type of human resource slack arises through specialization,
division of labor, resource combination, team work, and learning (Pitelis, 2007).
Absolute human resource slack, on the other hand, indicates that a firm possesses
more human resource slack than its industry rivals (Marino & Lange, 1983). Absolute
slack may result from less productive employees or inefficient organizational
routines. (Love & Nohria, 2005). Relative and absolute human resource slack thus
refer to fundamentally different organizational phenomena with distinct impacts not
only on firm growth, but also on firm performance. Relative slack may be positively
related to performance since this type of slack arises through increases in the firm's
efficiency (March, 1981). Absolute slack, on the other hand, indicates a negative
performance effect since it suggests that a firm's operations are inefficient and that its
outputs may be produced with fewer staff than currently employed (Love & Noria,
2005).
44
The aim of the present study is to substantiate existing findings by establishing a link
between relative and absolute human resource slack, growth, and firm performance.
By studying the interaction effects between these four variables, I am seeking to
generate clearer insights on the fundamentally different roles of relative as opposed to
human resource slack in the process of firm growth. Further, I argue that the
relationship between firm growth and performance may be better understood by
considering the drivers of firm growth. Existing findings on the effect of growth on
performance have been inconclusive (Mishina et al., 2004). There is also a lack of
studies examining the combined effects of slack and growth on firm performance
(Voss et al., 2007).
The results of this study indicate that firms whose sales growth rate exceeds relative
human resource slack perform better than firms with sales growth rates below their
levels of relative human resource slack. At the same time, however, the positive
performance effect tapers off when growth rates are high. I also find that absolute
human resource slack curbs this negative effect, which is experienced by firms which
overstrain their levels of relative human resource slack. On the other hand, the
findings of this study indicate that absolute human resource slack aggravates the
overall negative performance effect experienced by firms which don't transform
relative slack into growth.
The findings of this study help to sort through opposing views in two key areas of
research, namely the effects of human resource slack on growth, and the impact of
growth on firm performance. By differentiating between absolute and relative human
resource slack, I generate clearer insights into the role of excess human resources in
the firm's growth process. Further, I add to existing studies in literature analyzing the
relationship between slack and growth by linking these to the performance
implications of firm growth. The results suggest that relative and absolute levels of
human resource slack correspond to fundamentally different organizational
phenomena and thus lead to different organizational consequences and impacts on
firm performance. I build on these results to offer implications for firms seeking
profitable corporate growth.
5.2. Theory
Theorists of the classic resource-based view, building on Penrose's (1959) theory of
the growth of the firm, argue that the firm's expansion is determined by its unique
portfolio of tangible and intangible resources. More specifically, firms grow to utilize
45
the excess capacity that those resources provide (e.g., Penrose, 1959). The existence
of excess resources has been explained by the process of learning through experience
(Goerzen & Beamish, 2007). As employees gain experience in their daily routines
and learn how to do operations more efficiently, firm-specific human services are
freed up. Those resources in turn provide an incentive to expansion of the existing
business and / or diversification into new businesses to achieve economies of scale
and scope (Kor & Mahoney, 2000). This expansion sets off a virtuous circle. When
the firm grows human resources continue to learn due to exposure to new knowledge
and challenges in the expanding business, yielding further human resource slack and
helping in the creation of strategic options for still further growth (Foss, 1998; Kor &
Mahoney, 2000; Pitelis, 2007). In the realm of the classic resource-based view firm
growth and the development of human resource slack are thus interdependent and
mutually reinforcing processes. Further, this virtuous circle accelerates as new
knowledge, for example through engaging in innovation or expansion in new
markets, enters the organization.
The modern resource-based theory takes a fundamentally different perspective on the
role of human resource slack in the process of growth (e.g., Kogut & Zander, 1992,
1996; Teece, Pisano, & Shuen, 1997; Wernerfelt, 1984). Although rooted in Penrose's
work, the modern view contravenes the classic view in a vital point, arguing that
human resource slack is suited to further firm expansion only in a very limited way.
More specifically, human resource slack encourages growth only when it is consistent
with the direction of the expansion currently being pursued (Mishina et al., 2004). It
can, however, not be allocated to growth which is unrelated to prior organizational
routines, such as product expansion or the entry into new markets. The underlying
premise is that slack human resources are associated with political and cognitive
inertia (e.g., Hannan & Freeman, 1989). Accordingly, human resource slack is not
suited to grow into areas that may require different skills or knowledge.
Consequently, only relative human resource slack may be positively related to firm
growth, while the effect of absolute slack is at best minor.
The fundamentally different assumptions regarding human resource slack's role in the
process of firm growth are also reflected in the way in which human resource slack
has been conceptualized. Classic resource-based theory views human resource slack
as a relative quantity. Accordingly, human resource slack amounts to the change in
the level of excess employees an organization possesses over time (e.g., Bourgeois,
1981). It points to efficiency gains triggered by learning which raise with the level of
new knowledge that enters an organization (Kor & Mahoney, 2000; Wiersma, 2007).
46
Relative human resource slack is thus not enmeshed in existing organizational
routines and may be put to different uses should the need or opportunity arise.
Contrary to this conceptualization, modern resource-based theory conceives human
resource slack as an absolute quantity, supposed to identify firms with low as
opposed to firms with high levels of slack. Absolute slack points to operational
inefficiencies and indicates that necessary outputs may be produced with less staff
than currently employed (Love & Nohria, 2005). As opposed to relative human
resource slack, absolute slack is tied up in the organization's current operations (Voss
et al., 2008). This type of human resource slack is difficult to identify and thus
difficult to reallocate to firm growth. Based on a sample of 112 publicly held
manufacturing firms Mishina, Pollock and Porac (2004), for example, found that
absolute human resource slack is negatively related to product expansion which
requires resources that can be flexibly allocated to a new use.
Based on the foregoing discussion, it becomes clear that absolute and relative human
resource slack refer to fundamentally different concepts and only relative human
resources slack may be positively related to firm growth. Aiming to substantiate
existing findings on this relationship I will derive a set of hypotheses relating relative
slack to growth and throw light upon the moderating effect of absolute human
resource slack. Further, I will assess the performance effect resulting from these
relationships. I thus add to existing modern resource-based studies which have noted
a lack of research dealing with the performance effects resulting from the
interdependencies between human resource slack and firm growth.
5.3. Relative Human Resource Slack and Minimum Firm Growth
Relative human resource slack represents excess personnel within an organization,
arising from human resources that have been acquired in the past (Mishina et al.,
2004). Resource-based theorists explain the generation of relative human resource
slack by intrafirm learning (Pitelis, 2007). Researchers engaging in the study of the
human learning curve describe a virtuous cycle that continuously creates excess
resources. They argue that excess human resources are made available in the process
of learning how to do current operations more efficiently (Kor & Mahoney, 2000).
This improvement happens automatically and is referred to as the 'practice makes
perfect' phenomenon for which various studies have found empirical evidence (e.g.,
Argote & Epple, 1990; Li & Rajagopalan, 1998; Yelle, 1979). Wiersma (2007), for
example, empirically observed factors that explain variation in the learning curve
which may aid managers to maintain a positive learning curve even in more mature
companies. As fewer and fewer workers are needed to produce the same amount of
47
output this natural improvement in a firm’s productivity leaves the company with
excess human resources. There are three possible alternatives to deal with those
resources: (1) downsize; (2) retain the excess resources and leave them unproductive;
or (3) increase production.
Downsizing has been conceptualized as one attempt to improve performance by
reducing human resource slack (Cheng & Kesner, 1997). However, empirical studies
have shown that continued downsizing may have a negative effect on firm
performance, affecting competitive advantage, stock prices, and productivity (e.g.,
Chadwick et al., 2004; De Meuse et al., 1994; Hallock, 1998; Worrell et al., 1991).
Analyzing announcements of 194 layoffs, Worrell and colleagues (1991), for
example, found negative stock market reactions in the days around the announcement
events. Extant research has provided different explanations to elucidate the
relationship between slack, downsizing and firm performance. On a general basis,
researchers have argued that downsizing may leave firms with too little human
resource slack, thus negatively affecting firm performance (e.g., Lawson, 2001;
Cascio & Young, 2003). More specifically, it has been stated that removing excess
employees is likely to be disruptive to existing organizational routines. It may throw
the organization out of its internal alignment by causing a mismatch of the remaining
personnel's skills, knowledge, and networks with the needs of existing structures and
systems (Fisher & White, 2000; Buono, 2003). Further, reducing human resource
slack may lead to survivors only making local adjustments as they attempt to perform
the same routines and processes. This may leave survivors in an unsustainable
position, at risk of overwork or 'burn-out' (Love & Nohria, 2005). In congruence with
this argumentation, researchers have also suggested that employees who remain in the
organization after the downsizing have a low morale, are less productive, distrust
management, and become excessively cautious (Rice & Dreilinger, 1991). In sum,
long-term prospects associated with downsizing have been argued to be decidedly
negative when compared to alternatives such as targeting growth (Cascio, 1993,
2002; Harari, 1992).
Regarding the second alternative to deal with relative human resource slack, namely
retaining unproductive resources within the organization, agency theory points to a
negative performance effect (Fama, 1980; Jensen & Meckling, 1976). This research
stream considers excess resources to be a source of principal-agent problems which
breed inefficiency. For example, it has been argued that slack may slow a firms
reaction to competitor response as in the presence of slack, strategic decision-makers
may be more inclined to satisfice (Simon, 1957). Options which are unacceptable in
48
the absence of slack may actually be satisfactory in the presence of excess resources
(Cheng & Kesner, 1997). Further, slack may affect a firm's structural configuration.
According to Child (1972), managers may adopt suboptimal structural arrangements
in the presence of slack which are aligned more with personal preferences than their
concerns over economic efficiency. Thus, when slack is high, organizations can
afford to adopt structures that do not match their environments. Further it has been
argued that managers accumulate excess resources and use them to further their own
interests, for example by empire-building, engaging in unprofitable diversification or
R&D projects, delaying exit, or padding budgets (Love & Nohria, 2005).
While downsizing or retaining of human resource slack may result in negative
performance effects, the alternative of growing the company in order to use its excess
human capacities may be positively related to firm performance. Entrepreneurial
theories, for example, suggest that highly ambitious managers will be motivated to
invest such resources to expand a firm's market or product position. More specifically
it has been argued that excess resources can be put to profitable use without creating
additional costs (Pitelis, 2007). Entrepreneurial managers are thus incentivized to
extract growth from slack resources (Mishina et al., 2004). Further, organization
theorists have suggested that organizations may deploy human resource slack to
respond to environmental shifts and may thus be able to exploit market opportunities
through the introduction of new products or market expansion (Cheng & Kesner,
1997). Lastly, resource-based theorists have provided evidence suggesting that the
use of human resource slack to drive growth may be positively related to firm
performance. Pettus (2001) argued that optimal growth involves a balance between
the exploitation of existing resources and the development of new resources.
Accordingly, a firm will develop new resources only after its existing resource base
has been fully utilized. Extracting the maximum value from its existing resource base
is thus an important prerequisite for firms to develop new sources of competitive
advantage. Lastly, utilizing human resource slack to grow may provide the
organization with a competitive advantage because it is difficult for competitors to
obtain the same resource configurations and copy the firm's strategies (Mishina et al.,
2004).
Based on the foregoing discussion I argue that firms should grow at least at a rate so
that relative human resource slack is used productively by increasing the firm's
output. More specifically, I believe that relative human resource slack induces a firm
to grow and that the rate at which relative human resource slack evolves, determines
the firm's minimum growth requirement. Growth below this rate will lead to either
49
downsizing or excess capacity, both of which have been linked to poor performance.
Hence,
Hypothesis 1. Firms whose sales growth rate is higher than the level of relative
human resource slack will perform better than firms whose growth rate is lower than
the level of relative human resource slack.
5.4. Relative Human Resource Slack and Maximum Firm Growth
While relative human resource slack motivates firm expansion, I argue that
overstretching a firm's level of relative human resource slack may negatively affect
its performance. As previously suggested, firms need slack resources to be able to
react to unforeseen environmental threats. More specifically, slack resources help
buffer firms from environmental shocks and give them freedom in their responses to
competitor strategies, thereby influencing performance (George, 2005). Researchers
have thus argued that ideally, firms should have surplus resources sufficient to
address unforeseen threats or opportunities (Daniel et al., 2004). Accordingly, slack
acts as a resource cushion that stabilizes the firm's operations.
Further, scholars have argued that relative human resource slack may curb the
managerial problems which come with high growth. The conception of expansion
requires managers whose firm-specific knowledge is a prerequisite for the successful
planning and implementation of expansion, and who therefore are not available in the
open market (Pitelis, 2004). Negative levels of relative human resource slack may
thus make it necessary for firms to alternate periods of resource sprinting and pausing
(Mishina et al., 2004). Such alternating rates of growth have come to be known as the
"Penrose Effect" (Penrose, 1959). Besides affecting subsequent growth,
overstretching of relative human resource slack may also have immediate
performance effects by leading to overworking of a firm's existing human resource
base (Love & Nohria, 2005). Thus, if the total managerial services available for
expansion are reduced a disruptive effect on current operations is expected (Mahoney
& Pandian, 1992). Based on the foregoing discussion I expect that increasing rates of
growth will ultimately result in a negative performance effect due to overstretching of
the firm's level of relative human resource slack. Hence,
Hypothesis 2. The relationship between sales growth and performance exhibits an
inverted U-shaped relationship for sales growth above the level of relative human
resource slack.
50
5.5. Absolute Human Resource Slack and Firm Growth
As opposed to relative human resource slack, absolute human resource slack captures
the level of human resource slack as compared to the industry mean. A high level of
absolute slack indicates that the firm possesses more slack resources than the average
of its industry peers (Marino & Lange, 1983). Firms which dispose of high levels of
absolute human resource slack have been referred to as being "fat" (e.g., Caves &
Krepps, 1993). Fat firms are assumed to be inefficient as their necessary outputs may
be produced with fewer staff than currently employed (Love & Nohria, 2005).
Absolute human resource slack can thus be viewed as costs and a reduction of
absolute human resource slack may be desirable (Voss et al., 2007). Analyzing a
sample of 67 Indian state-owned, 63 private sector and 27 foreign-owned enterprises
Majumdar (1998), for example, found that if all firms were equally efficient, stateowned enterprises could raise the value of their output by over 25%.
Reducing absolute human resource slack by downsizing may, however, be very
costly. Absolute human resource slack is tied up in the organization's current
operations (Voss et al., 2007). Structural constraints limit the possibility to identify
and recover absolute human resource slack. Since identifying absolute slack is
difficult, a reduction is supposed to lead to numerous unanticipated expenses (Love &
Nohria, 2005). In sum, those expenses may outweigh the benefits associated with the
reduction in the firm's labor costs (Shah, 2007). Nonetheless, firms with high levels
of absolute human resource slack may be inclined to engage in downsizing in the
hope to increase their efficiency. Pitelis (2007), for example, argues that high levels
of absolute slack do not motivate firm expansion, however, instead often lead to a
focus on shedding resources through downsizings. More specifically, the structural
constraints accompanying absorbed slack inhibit implementation of expansive,
innovative strategies and thus impose pressures to reduce absolute slack (Voss et al.,
2007).
In sum, the precedent argumentation leads to the following assumptions. Considering
firms whose sales growth rate is lower than the level of relative human resource slack
will be affected by the presence of absolute human resource slack in two ways. First,
those firms already possess over unused productive services since their sales growth
is insufficient to consume relative human resource slack. As absolute slack adds up to
the existing level of unproductive resources, the negative performance effect resulting
from leaving slack unproductive may be aggravated. Second, due to already existing
unused productive resources those firms may be inclined to downsize to reduce high
51
levels of absolute resource slack. Thereby, however, they give rise to a negative
performance effect arising from the costs associated to such downsizings. Hence,
Hypothesis 3. Absolute human resource slack negatively moderates the relationship
between firm growth and performance of firms whose growth rate is lower than the
level of relative human resource slack.
In the face of high growth, however, absolute human resource slack assumes another
character. Firms which dispose of high levels of absolute human resource slack have
a resource cushion which renders two advantages when firms expand their business.
First, available resources within the firm alleviate various managerial problems which
have been related to growth (Covin & Slevin, 1997; Gartner, 1997; Hambrick &
Corzier, 1985). For example, firms with high levels of absolute human resource slack
need to employ fewer new managers as there already exist slack resources with firmspecific knowledge to cope with increases in the administrative complexity that
comes with growth (McKinley, 1987). The presence of absolute slack thus buffers the
problem of deterioration of effective managerial control over expanding
administrative processes. Second, those firms dispose of the capacity needed to select
and integrate new managers. Bourgeois and Singh (1983), for example, argued that
rapid growth is accompanied by the arrival of new resources which are not spoken for
by old technical claims. Existing managers need to train and integrate those new
managers which occupies their time and effort and consequently diverts their
attention from running the firm. The faster a firm grows, the more the existing
managers are required to ensure new appointees’ quality as well as to transfer their
tacit knowledge (Faith, Higgins, & Tollison, 1984; Levinthal, 1988).
Relating this argumentation to the second hypothesis of this study, leads me to the
following assumptions. First, firm growth may be a profitable alternative to reducing
absolute human resource slack. Second, firms are able to digest high levels of growth
better if they dispose over absolute resource slack. Hence,
Hypothesis 4. Absolute human resource slack positively moderates the relationship
between firm growth and performance of firms whose growth rate is higher than the
level of relative human resource slack.
52
5.6. Research Design
5.6.1. Sample
The sample employed for this study consists of all companies listed in the Fortune
500 index for the year 2005. I chose this sample because the Fortune 500 firms
represent a very large share of the total business activity in the U.S., as well as large
and diversified firms. Consequently, interest in the factors that influence these firms’
strategic decisions and performance outcomes is warranted (Stimpert & Duhaime,
1997). Further, by including multiple industries, the sample incorporates high
variation in industry and firm growth rates, which may be material to the
accumulation and deployment of resource slack (George, 2005). The reference time
frame covers the period between 1995 and 2004. This longitudinal design seems
appropriate since I study dynamic rather than static processes of slack deployment
and growth. In addition it has been argued that growth rates are volatile in the short
run and "single-year sales or growth (first difference) figures may capture aberrations
and not represent the true health of the organization" (Chandler & Baucus, 1996).
Baumol (1962), for example, refers to a minimum 5-period time horizon as an
adequate time frame for studying firm growth. Further, Mishina et al. (2004) have
suggested that longitudinal research designs are needed to adequately assess the
relationship between slack and growth.
5.6.2. Data
All relevant data for this study were drawn from the COMPUSTAT database that is
considered highly reliable and which has been frequently used in prior research on
slack and growth (e.g., George, 2005; Glaum et al., 2004). In order to enhance the
reliability of the data and counteract coding errors (miscoding arising from the
transfer of data from a primary data source to the electronic database), I randomly
checked the data accuracy against companies’ financial statements. Some firms
lacked data, limiting the final sample to 425 of the 500 firms in the initial sample.
5.7. Measurements
5.7.1. Relative Human Resource Slack
It is commonly accepted that employee productivity serves as an appropriate proxy to
measure human resource slack (e.g., Greenley & Oktemgil, 1998; Mishina et al.,
2004; Welbourne, Neck & Meyer, 1999). Kroll (2006) cites that revenue per
employee is the best metric to assess worker productivity by telling how effectively
employees generate sales. This measure, calculated by dividing total sales by the
number of employees, has commonly been used in previous studies (e.g., Datta,
Guthrie, & Wright, 2005; Huselid, 1995; Koch & McGrath, 1995). In order to assess
53
relative human resource slack (rHRS), i.e., slack that evolves within the organization
over time, I need to gauge the change in employee productivity over time. To
compute relative human resource slack I thus measure the annual percentage change
in a firm's productivity, using the following formula:
rHRSit = (Sit / Eit) / (Sit-1 / Eit-1) -1
where Sit is the firm i's total sales at time t and Eit the firm's total number of
employees at time t. t-1 refers to the numbers of the previous time period.
5.7.2. Absolute Human Resource Slack
As opposed to relative human resource slack which evolves over time, absolute
human resource slack (aHRS) is a static quantity relative to an industry target level
(e.g., Bourgeois & Singh, 1983). To assess absolute human resource slack I thus
compare employee productivity at the firm level to employee productivity at the
industry level (e.g., Mishina et al., 2004). Following Miller & Leiblein (1996) I
defined each industry at the two-digit SIC level. To measure absolute human resource
slack I use the following formula:
aHRSit = (ISit / IEit ) -( Sit / Eit )
where ISt is the total industry sales, IEit is an industry’s total number of employees, Sit
is the firm's sales and Eit the firm's number of employees at the time t. The difference
between the firm's amount of human resource slack and the respective industry level
provides an indicator of whether a firm possesses above or below average amounts of
slack.
5.7.3. Firm Growth
Existing studies have utilized sales, profitability, as well as workforce measures to
determine growth. There is, however, an emerging consensus in the literature that
sales are the most relevant indicator of growth (Delmar et al., 2003; Hoy et al., 1992;
Weinzimmer et al., 1998). In accordance with this study's purpose, I thus measured
the firm's annual growth as the firm’s annual percentage increase in sales. I used the
following formula for calculation purposes:
Sit = (Sit / Sit-1) - 1.
54
5.7.4. Performance
To assess firm performance, I used a market-based measure. Traditionally, strategy
research has defined performance according to accounting-based measures, with
return on assets considered a reasonable proxy (Lubatkin & Shrieves, 1986). Owing
to this study’s longitudinal dynamic orientation, market-based measures may,
however, be more appropriate for studying performance effects (Bruner, 2002).
Moreover, market-based performance measures are thought to reflect all of
performance’s relevant information rather than being limited to specific performance
dimensions (Lubatkin & Shrieves, 1986). Several authors have designated the return
to shareholders as a suitable proxy with which to measure market-based performance
(e.g., Baucus & Baucus, 1997; Bruner, 2002; Holliday, 2001; Rappaport, 2006). I
thus use the total return to shareholders (TRSit) to measure firm performance.
5.7.5. Control Variables
Previous research in growth and slack literature has generally controlled for time,
size, and industry effects (e.g., Markman & Gartner, 2002; Mishina et al., 2004). I use
a fixed-effect estimator in the analysis to control for variables that are invariant over
time, such as industry membership. Additionally, because larger firms can be
expected to have higher levels of human resources it is important to control for the
size of the company. I thus included the total number of employees as a control
variable. Table 5.1 provides an overview of all the variables used in the study.
Control Variable
Sizeit
Dependent Variable
Total number of employees
TRSit
Independent Variables
Annual change of return to shareholders
Sit
rHRSit
aHRSit
Sit < rHRSit
Sales growth
Relative human resource slack
Absolute human resource slack
Binary variable indicating whether (1) or not (0) the firm's level of
relative human resource slack exceeded the level of sales growth
Table 5.1: List of Variables
5.8. Statistical Methods and Data Analysis
I made use of cross-sectional time series to assess the effect of human resource slack
on firm growth and performance. As previously explained, I collected the annual data
of 425 firms for the period between 1995 and 2004. When the data were pooled
across firms and across these ten years, the resulting sample had 4250 observations.
55
Given the two-dimensional structure of the balanced data set, I used panel data
statistical methods (Hsiao, 1986; Baltagi, 1995) for analysis. I estimated the
following general equation:
Yit = α + Xit'βit + δi + γt + εit,
where Yit is the dependent variable, Xit is a k-vector of regressors, and εit are the error
terms for i = 1, 2, …, M cross-sectional units observed for dated periods (t = 1, 2, …,
T). The α parameter represents the overall constant in the model, while the δi and γt
terms represent cross-section or period-specific effects (random or fixed). The β
coefficients may be divided into sets of cross-section-specific, period-specific, and
common (across cross-sections and periods) regression parameters.
A key benefit of utilizing panel data is the ability to test and control for the effects of
unobserved fixed factors, which, if left uncontrolled, can induce bias in the
coefficient estimates of the explanatory factors included in the model (Rajagopalan &
Datta, 1996). I restricted the sample to large firms, which prevents different residual
variances that depend on the absolute level of the variables (e.g., sales) from affecting
the estimation. However, the observations may no longer be independent as firm
characteristics are correlated over time (Finkelstein & Hambrick, 1990; Haleblian &
Finkelstein, 1993). It is unreasonable to assume that with regard to this study, the data
points in the longitudinal dimension are independent of one another. For instance,
unobserved firm-specific factors (e.g., corporate reputation, managerial teams) may
influence observations of the same firm and produce correlation across these
observations over time (Gimeno, 1999). Thus, instead of using the standard pooled
ordinary least squares (POLS) estimation, whose key assumption is independence
across all observations, I used a fixed-effect estimator. Fixed-effect estimators
remove all time-constant effects by subtracting the mean of the ten-year period,
thereby ensuring consistency in estimation. Moreover, fixed-effects models predict
the annual change in a dependent variable, as opposed to random-effects models
which are appropriate if aiming to explain variance among firms (Sanders &
Hambrick, 2007). Further, I used a feasible generalized least squares (FGLS)
estimation by assuming the presence of period-specific structures within the
residuals. The weighting of the observations helps to exploit all structures within the
data panel set, which enables efficient estimation. Lastly, I adjusted the standard
errors by using a White adjustment in the longitudinal period. This adjustment leads
to robust significance values.
56
In order to test hypothesis 1 I estimated the following equation:
TRSit = α + Sizeit βit + Sit βit + (Sit < rHRSit) βit + γt + εit.
The first two coefficients assesses the effect of firm size and sales growth on
performance. The third coefficient estimates the average performance of those firms
whose sales growth rate was below the level of relative human resource slack.
To test hypothesis 2 I split the sample according to those companies that used relative
human resource slack to fuel growth, and those that didn't. I then estimated the
following equation for the sample of firms that used rHRS to fuel growth:
TRSit = α + Sizeit βit + Sit βit + Sit2 βit + γt + εit.
The first coefficient beyond the control variable assesses a linear relationship
between growth and performance. With the following coefficient I test for a
curvilinear relationship between sales growth and performance.
In order to test hypothesis 3, I estimated the effect of absolute slack on performance
for firms that didn't use relative human resource slack to fuel growth, using the
following formula:
TRSit = α + Sizeit βit + Sit βit + Sit (-aHRSit)βit + γt + εit.
Again, I assess the effect of firm size and firm growth on performance. Further, I
estimate how absolute human resource slack affects the relationship between firm
growth and performance.
Lastly, I tested hypothesis 4 by estimating the following equation:
TRSit = α + Sizeit βit + Sit βit + Sit2 βit + Sit2 aHRSit βit + γt + εit.
Here, the first two coefficients beyond the control variable denote a curvilinear
relationship between firm growth and performance. The third coefficient estimates
the effect of absolute human resource slack on the curvilinear relationship between
firm growth and performance.
57
5.9. Results
In the following I present the results of the analysis. Table 5.2 provides the crosssectional, time series summary statistics (means, standard deviations, and correlation
coefficients) of all the variables employed. The panel data regression results of the
hypotheses testing are reported in Tables 5.3 to 5.6. I report the parameter estimates,
as well as the standard errors and values of the t-statistic in respect of each regression.
The probability levels are indicated by asterisks. The double asterisks indicate
significance at the 1% level, while the single asterisks indicate significance at the 5%
level. The reported results refer to the total return to shareholders (TRSit) as the
dependent variable.
Variable
1. Firm Performance, TRSit
2. Sales Growth, Sit
3. Relative Human Resource Slack, rHRSit
4. Absolute Human Resource Slack, aHRSit
5. Firm Size, Sizeit
Mean
0.20
0.16
0.08
-0.01
46811
s.d.
0.66
0.45
0.42
0.61
86508
1
2
3
4
0.12
0.06
-0.01
-0.05
0.60
-0.01
-0.08
0.04
0.00
0.08
Table 5.2: Time Series Cross-Sectional Summary Statistics
Hypothesis 1 predicted that firms that use relative human resource slack to fuel
growth are more successful than firms that don't use relative human resource slack to
fuel growth. To test this hypothesis I estimated a model with two explanatory
variables: the sales growth rate and a dummy variable indicating firms that didn't use
relative human resource slack to fuel growth. Each variable has the expected sign and
is statistically significant, thus supporting the hypothesized relationship. The results
indicate a generally positive relationship between sales growth and performance
(0.12, p < 0.01). Further, the average performance of firms that didn’t use relative
human resource slack to fuel growth is significantly lower than that of all other firms
(-0.03, p < 0.05). In sum, the findings support the hypothesized relationship.
58
Variable
C
Sizeit
Sit
Sit < rHRSit
Coefficient
Std. Error
t-Statistic
0.21
0.00
0.12
-0.03
0.01
0.00
0.04
0.01
18.08**
-2.61**
3.27**
-1.91*
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
0.16
0.64
58.74
0.28
0.69
Cross-sections included
Total observations
384
3590
* p < 0.05
** p < 0.01
Table 5.3: Hypothesis 1, Results of Fixed Effects Panel Data Regression
In order to test hypothesis 2, I estimated a linear relationship between firm growth
and performance and an additional curvilinear effect. Both variables have the
expected sign and are statistically significant, thus supporting the hypothesized
relationship. I found that increasing levels of sales growth positively affect firm
performance (0.27, p < 0.00), however, that this positive effect tapers off at high
levels of growth and eventually devolves into a negative U-shaped relationship (0.03, p < 0.00). Thus, I found significant support for the second hypothesis.
Variable
C
Sizeit
Sit
Sit2
Coefficient
Std. Error
t-Statistic
0.18
0.00
0.27
0.01
0.00
0.05
14.20**
-2.31**
5.41**
-0.03
0.01
-4.36**
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
Cross-sections included
Total observations
0.18
0.50
39.71
0.26
0.54
379
2256
* p < 0.05
** p < 0.01
Table 5.4: Hypothesis 2, Results of Fixed Effects Panel Data Regression
In order to test hypothesis 3 I analyzed how absolute human resource slack influences
the relationship between growth and firm performance for firms that didn't use
relative human resource slack to grow. Both variables have the expected sign and are
statistically significant. I found a positive relationship between firm growth and
59
performance (0.17, p < 0.05). Further, I found that increasing levels of absolute slack
coupled with decreasing growth negatively impact firm performance (0.12, p < 0.00).
Variable
C
Sizeit
Sit
Sit (- aHRSit)
Coefficient
Std. Error
t-Statistic
0.18
0.00
0.17
0.12
0.01
0.00
0.09
0.03
16.33**
-3.12**
1.95*
3.62**
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
0.17
0.85
21.56
0.29
0.92
Cross-sections included
Total observations
336
1237
* p < 0.05
** p < 0.01
Table 5.5: Hypothesis 3, Results of Fixed Effects Panel Data Regression
Of the relationships specified in hypothesis 4, all have the expected sign and are
statistically significant. The findings support the conjecture that high levels of
absolute human resource slack level off the negative performance effect experienced
by firms that have overstrained the relative amount of human resource slack to fuel
growth. More specifically, I found a positive linear relationship between sales growth
and performance (0.25, p < 0.00) which eventually turns into a negative curvilinear
relationship (-0.02, p < 0.00). Absolute human resource slack , however, turns the
relationship between high levels of growth and performance positive (0.02, p < 0.05).
Variable
Coefficient
Std. Error
t-Statistic
0.18
0.00
0.26
0.01
0.00
0.04
19.98**
-2.58**
6.43**
Sit2
-0.02
0.00
-6.28**
2
it
0.03
0.01
3.74**
C
Sizeit
Sit
S aHRSit
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
Cross-sections included
Total observations
0.17
0.64
57.76
0.29
0.70
384
3590
Table 5.6: Hypothesis 4, Results of Fixed Effects Panel Data Regression
* p < 0.05
** p < 0.01
60
In sum, the findings of this study yield strong support (i.e., on a 1%, respectively 5%
level of significance) for all four hypotheses.
5.10. Discussion
The results of this study provide insights on the antecedents as well as consequences
of firm growth. The conceptual and empirical foci on distinct forms of human
resource slack shed light on contradictions in extant research. The results suggest that
absolute and relative human resource slack impact differentially on firm growth and
performance. More specifically, I found a negative performance impact for firms with
lower sales growth rates than levels of relative human resource slack. On the other
hand, the relationship between firm growth and performance exhibited a negative Ushape for firms with higher sales growth rates than levels of relative human resource
slack. Further, the results suggest that absolute human resource slack moderates this
relationship. First, I found that absolute human resource slack aggravates the negative
performance effect experienced by firms with lower sales growth rates than levels of
relative human resource slack. Second, I found that absolute human resource slack
positively moderated the U-shaped relationship between sales growth and
performance for firms with higher sales growth rates than levels of relative human
resource slack. I will explore these insights and their implications for theories in
business research as well as managerial practice.
5.10.1.
Resource-Based View of Growth
Resource-based theorists claim that relative human resource slack induces a firm to
grow (Pitelis, 2007). However, to date no empirical studies have been conducted to
substantiate this assumption. The findings of this study may help to close this gap. I
found that firms with higher sales growth rates than levels of relative human resource
slack performed significantly better than firms that didn't use relative slack to fuel
growth. This result suggests that firms may be rewarded for using increases in
employee productivity to drive growth. Correspondingly, the findings suggest that
firms experience a negative performance effect if the level of firm growth is
insufficient to consume relative human resource slack. This result contributes to
agency theory which considers unproductive resources within an organization to be a
source of principal-agent problems which breed inefficiency, inhibit risk-taking, and
thus hurt firm performance (Fama, 1980; Jensen & Meckling, 1976).
Further, the findings suggest that the positive performance effect of firms that
transform their total amounts of relative human resource slack into growth tapers off
at high growth levels. Prior studies have found that high growth levels will negatively
61
affect the levels of growth in subsequent periods (e.g., Gander, 1991; Shen, 1970;
Tan, 2003; Thompson, 1994). This limitation of a firm’s rate of growth has become
known as the "Penrose effect" (e.g., Marris, 1964). I expand on the concept of the
Penrose effect by establishing a link to firm performance. The results provide
evidence that high growth levels have a direct negative effect on firm performance
beyond subsequent growth.
In a broader context, the findings of this study contribute to the notion of optimum
growth. This view of growth suggests an inverted U-shaped relationship between firm
growth and performance. Baumol (1962: 1078) was the first to suggest that growth is
only beneficial up to a point. He maintained that beyond a certain level, a further
increase in growth leads to a decrease in organizational efficiency. Consequently,
firms should strive for optimum growth rather than maximizing it (e.g., Drucker,
1973; Higgins, 1977). Although the notion of optimum firm growth has gained
common acceptance in management theory, the empirical evidence has remained
ambivalent. While some studies have found support for a curvilinear relationship
(e.g., Ramezani et al., 2002), others revealed a positive and linear effect (e.g.,
Miedich & Melicher, 1985), or no significant linkage at all (e.g., Markman & Gartner
2002). The results of this study may provide helpful insights, adding to evidence for a
negative curvilinear relationship between firm growth and performance. Accordingly,
the firm's level of relative human resource slack may be viewed as a lower boundary
to the firm's optimum rate of growth. My findings suggest that firms growing above
this limit will outperform firms with smaller growth rates. At the same time, however,
the results indicate that growth above this lower limit eventually devolves into a
negative effect, supporting the assumption that there is a point beyond which further
growth may adversely affect firm performance.
5.10.2.
Slack, Growth, and Performance
I argued that absolute human resource slack indicates that a firm possesses more
human resource slack than its industry rivals. High levels of absolute human resource
slack thus signal that a firm is not producing its outputs as efficiently as it could.
Consequently, firms may profit from reducing absolute human resource slack,
thereby becoming more productive. I found that absolute slack works against the
negative performance effect experienced by firms with high levels of growth. On the
other hand, firms which don't use relative slack to fuel growth experience a
significant negative performance effect if they additionally dispose of high levels of
absolute human resource slack. These results suggest that there may be an optimum
level of resource slack. Previous research on the direct relationship between resource
62
slack and firm performance suggests that firms should have "surplus resources
sufficient to address unforeseen threats or opportunities but limited enough to prevent
managers’ irresponsible behaviour" (Daniel et al., 2004: 566). Accordingly, the mere
existence of excess resources has a positive performance impact (e.g., Bromiley,
1991; Miller & Leiblein, 1996; Pfeffer & Salancik, 1978; Thompson, 1967).
However, underlying this positive view, there is also a belief that there is an optimum
level of slack (Love & Nohria, 2005; Tan & Peng, 2003). Proponents of this view
recognize the costs of excessively high slack and found evidence that the relationship
between levels of slack and performance is an inverted U-shape (Bourgeois, 1981;
Nohria & Gulati, 1996). Similarly, my findings suggest that both too little and too
much slack are negatively related to firm performance. In this study, I observed a
negative performance effect if absolute slack adds to unused levels of relative slack.
Further, I observed a negative effect if firms overstrained the level of relative human
resource slack. However, if those firms possessed high amounts of absolute resource
slack, this negative effect vanished.
5.10.3.
Conceptualizations of Human Resource Slack
Lastly, my findings help to sort through inconsistencies in the conceptualization of
slack resources. While authors dealing with types of financial slack have usually
differentiated between absolute and relative resource slack, studies dealing with
human resource slack have commonly relied on absolute conceptualizations of slack
(e.g., Greenley & Oktemgil, 1998; Mishina et al., 2004; Nohria & Gulati, 1996).
However, the study's results show that absolute and relative slack are not
interchangeable. Comparing different slack measures, Marino and Lange (1983)
argue for the need to distinguish between absolute and relative slack. Depending on
the research question, the one or the other may be more appropriate. My findings
build on this call for distinction. I argue that absolute and relative human resource
slack are different concepts and thus also have to be measured differently. Relative
human resource slack, which refers to productivity gains within an firm over time,
must be evaluated relative to a previous time period. In contrast, absolute human
resource slack, which refers to inefficiencies within a firm, must be evaluated relative
to other firms. Relative measures are appropriate to gauge the change in the level of
slack in a firm over time, while absolute measures are intended to identify firms with
high levels of slack. As these concepts obviously refer to distinct organizational
phenomena, they should consequently be treated differently and should each only be
associated with certain dependent variables or measures of performance (Greenley &
Oktemgil, 1998).
63
5.10.4.
Limitations and Directions for Future Research
The implications of this research are subject to several limitations. One potential
limitation is that I have related human resource slack to only one measure of firm
growth. Thus I was not able to ascertain whether slack has a different impact on
different types of growth. Extant resource-based research has conceptualized growth
along the two dimensions of diversifying into new markets or new products (e.g.,
Penrose, 1959). While market growth draws on the firm's past experience, product
expansion requires the development of new processes and taxes human resources
more heavily (Mishina et al., 2004). Relative human resource slack, which is not tied
to a specific use, may be equally useful for both types of firm growth. Absolute
human resource slack, however, which is enmeshed in existing organizational
processes, may have a stronger impact on related market growth than on unrelated
product expansion. Future research should thus differentiate between different types
of growth, regarding its antecedents as well as consequent performance impacts.
Second, while this study's findings indicate that there may be an upper limit to the
firm's optimum growth rate, I have not engaged in establishing a certain point beyond
which further growth negatively affects firm performance. Existing research has
argued that the firm’s current managerial resources set the limits to the firm’s rate of
expansion (Barringer & Jones 2004; Gander, 1991; Penrose, 1959; Slater, 1980). It
would thus be useful if future research would map out the empirical implementation
to firm-specific limits of firm growth resulting from the configuration of a firm's
human resource base.
Lastly, future research may examine differences in acquisitive as opposed to organic
growth. Although Penrose (1959) has argued that while human resources are taxed as
much by acquisitive growth as by organic growth, there may be differences in the
ways human resource slack is affected. The integration of acquisitions requires
human resource slack with firm-specific knowledge (Cohen & Levinthal, 1990;
Gammelgard, 2005). At the same time, acquisitions may speed up the rate at which
relative human resource slack evolves after new knowledge is brought into the firm
(Levinthal & March, 1993; Ranft & Lord, 2002; Vermeulen & Barkema, 2001).
Acquisitions may thus have a significant impact on the dynamic patterns of the
development and consumption of human resource slack. More research is needed to
untangle the relationship between different modes of growth, human resource slack,
and firm performance.
64
5.10.5.
Managerial Implications
The results of this study suggest that relative human resource slack may delineate the
firm's minimum growth requirements. This provides a helpful tool for management in
determining their optimum rate of growth. At the same time, I found that there may
be a limit to the firm's growth rate beyond which further growth negatively affects the
firm's performance. Thus, while reducing slack may be beneficial for firm
performance, overstraining relative human resource slack may lead to an
overworking of the firm's existing resource base. This finding indicates that managers
should not pursue growth at all costs. I did find, however, that absolute human
resource slack may suit to curb this negative performance effect. This result suggests
that growing to increase firm productivity may be beneficial for firm performance.
Thus, firms with lower productivity levels than their industry rivals should consider
firm growth as a viable alternative to downsizing to improve productivity.
65
PAPER III:
THE FINANCIAL PERSPECTIVE TO
OPTIMUM FIRM GROWTH Growth and Firm Performance:
Theoretical Foundations for a Multi-Perspective
Model of Optimum Firm Growth
Multi-Perspective
of The Corridor of Optimum
Theoretical A A
Multi-Perspective Model
Model of
Background Optimum
OptimumFirm
FirmGrowth
Growth
Firm Growth
The Market-Based
Perspective
Performance
Implications
Low
Maximum Threshold
The Resource-Based
Perspective
High
Minimum Threshold
The
The Financial
Financial
Perspective
Perspective
Low
66
To Meet or to Beat: Shareholders' Expectations and Firm
Performance
Abstract
Research in finance indicates that firm performance is positively related to the act of
meeting or beating shareholders' growth expectations. On the other hand,
performance may be negatively affected if firms fall short of expectations. The results
of this analysis of a panel data set of the Fortune 500 firms over a period of ten years
supports the latter assumption. However, the findings suggest that there is a
significant difference regarding the performance implications of meeting revenue
growth expectations as opposed to beating them. The study's findings suggest that the
act of beating expectations is limited by the firm's financial resources. Firm's that
exceed sales expectations and thereby rise above their financial means experience a
negative performance effect. Further, the results suggest that firm performance
deteriorates in the face of irrational shareholders' expectations, i.e., sales growth
expectations that exceed the firm's financial resource means.
Keywords: Bounded Rationality, Firm Performance; Shareholders' Expectations,
Sustainable Growth Rate.
67
6. To Meet or to Beat: Shareholders' Expectations and Firm
Performance
6.1. Introduction
Studies in accounting and finance indicate that firms pay close attention to their
shareholders' expectations regarding measures of firm performance, such as sales and
earnings growth. The shareholders, in turn, view the act of meeting or beating of
those expectations as signals of the firm's future profitability (e.g., Kasznik &
McNichols 2002; Lopez & Rees 2002). Research and managerial practice indicate
that firms are rewarded for meeting shareholders' expectations, even after controlling
for the magnitude of the forecast error (e.g., Bartov, Givoly, & Hayn, 2002).
Empirical evidence suggests that ending the accounting period with a positive
performance surprise results in a positive stock valuation. Even more, those findings
suggest that there is a reward to meeting or beating analysts' earnings expectations
and a penalty for failing to do so, independent of the firm's absolute performance
(Rees & Sivaramakrishnan, 2007). Meeting or beating shareholders' earnings or sales
expectations is thus considered a desirable corporate objective.
While the meeting and beating of expectations have been used synonymously in prior
research, I argue that meeting or beating may make a substantial difference,
particularly in the case of revenue expectations. Rees and Sivaramakrishnan (2007)
suggest that earnings figures are more susceptible to manipulation than firm revenues.
Firms may thus exceed earnings expectations by both earnings manipulation and
expectations management (e.g., Bartov et al., 2002). Exceeding sales expectations
may, however, require managers to actually take managerial action. While there may
not be a limit to a firm's level of earnings, high sales growth levels have been related
to various negative performance consequences (e.g., Covin & Slevin, 1997; Gartner,
1997; Hambrick & Corzier, 1985). Accordingly, increasing sales growth by all means
may not always be profitable. Research in strategic management assumes that high
sales growth levels lead to internal friction that may hinder normal operating
procedures and may even lead to failure and bankruptcy (Markman & Gartner, 2002;
Slater, 1980). While shareholders' expectations may thus be a suitable proxy to
determine a firm's minimum growth requirements, there may be a limit to the extent
of beating expectations which has not previously been discussed in the expectations
literature.
68
Beyond this gap in extant research there are contradicting explanations on the way
shareholders form their expectations. An increasing body of literature in behavioral
finance indicates that shareholders' expectations are subject to various flaws (e.g.,
Kahneman & Tversky, 1982). Accordingly, expectations may exceed the level of
growth a firm can feasibly accomplish. The concept of sustainable growth, for
example, allows a company to determine the rate of sales expansion consistent with
the firm's financial policies (e.g., Higgins, 1977). Greater sales growth can only be
achieved at the expense of financial soundness. There is, however, a lack of studies of
the performance consequences of irrational shareholders' expectations.
The aims of this study are twofold in this regard. First, I believe that the meeting and
beating of revenue expectations do not have the same performance implications.
While meeting expectations may be beneficial for firm performance, I argue that a
limit must be set in the degree of beating them. Second, I aim to bridge a gap in
research on earnings expectations by analyzing the effect of irrational shareholders'
expectations on firm performance. More specifically, I study the performance effects
of boundedly rational revenue expectations which exceed a firm's growth-generating
ability.
The results of this study support extant research on the positive performance effect in
firms that meet shareholders' revenue expectations, compared to firms that grow at a
lower rate. However, as opposed to previous literature, I find that a limit must be set
in the beating of expectations. The results indicate that firms with higher sales growth
rates than financial limits perform significantly worse than firms that meet
expectations and thereby remain within their financial limits. Lastly, the findings of
this study indicate that where shareholders expect a sales growth rate beyond what is
financially feasible, a firm experiences a significantly negative performance impact.
The remainder of this paper is structured as follows: First, I will review literature on
earnings and revenue expectations in order to reveal a firm's minimum growth
requirements. I will then delve into the literature on sustainable growth to reveal how
a firm's maximum growth boundaries can be determined. The subsequent chapter
deals with irrational shareholders' expectations and the resulting performance effects.
I will then present the research design and show the results of the panel data analysis
employed for this study. I conclude the paper by summarizing contributions and
limitations and pointing to possibilities for future research.
69
6.2. Shareholders' Expectations and Firm Performance
A considerable volume of literature in financial theory has centered its research
interest on the formation of shareholders' earnings expectations (DeFond & Hung,
2003). The aim of those studies is to identify attributes that influence the accuracy of
earnings forecasts. Evidence suggests that besides knowledge about the firm itself, a
thorough understanding of the industry the firm operates in may be required to form
reliable expectations (García-Meca & Sánchez-Ballesta, 2006). Relevant
informations may be acquired by analyzing the firm via financial statements and by
recognizing general economic trends of the industries the firm operates in (Clement,
1999; Lang & Ludholm, 1996). Further, financial analysts may increase their
knowledge and understanding of the firm by establishing working relationships with
the corporate management over time (Jacob, Lys, & Neale, 1999). Industry
specialization, on the other hand, allows the analyst to attain deeper knowledge of the
competitive environment the firm finds itself in. For example, analyzing a sample of
over one million forecasts Clement (1999) finds that the more industries an analysts
follows, the higher are forecast errors.
6.2.1. Meeting Shareholders' Expectations
Degeorge, Patel, and Zeckhauser (1999) ascertain that meeting earnings expectations
is one of the most important thresholds that management tries to reach. Researchers
dealing with the effects of earnings expectations on firm performance suggest that,
independent of the firm’s absolute performance, there is a reward for meeting
expectations and a penalty for failing to do so (Bartov et al., 2002; Kasznik &
McNichols, 2002; Skinner & Sloan, 2002). Analyzing 64'872 firm-quarter
observations, Bartov, Givoly and Hayn (2002), for example, found that firms that
meet analysts' earning expectations enjoy a higher return than firms that fail to meet
these expectations. While the premium is relatively small in the short term, there is a
significantly greater return for firms that consistently meet expectations over several
years (Kasznik & McNichols, 2002).
Besides this positive effect on returns, it is assumed that meeting expectations also
benefits the management itself. Burgsthaler and Dichev (1997), for example, found
that managers who meet expectations enhance their reputation with the stakeholders.
More specifically they argue that customers are willing to pay a higher price for
goods, suppliers and lenders offer better terms and valuable employees are less likely
to leave or to demand higher salaries to stay. Further it has been argued that meeting
shareholders' expectations positively affects the bonuses paid to management (Healy,
1985; Matsunaga & Park, 2001). Based on a sample of 3'651 firm-year observations
70
Matsunaga and Park (2001) found that CEO bonuses are lower when the firm reports
earnings below analysts forecasts. Lastly, meeting expectations is assumed to boost
managers' career expectations. Analyzing a sample of 4'015 firm-year observations,
Farrell and Whidbee (2003) found that the likelihood of CEO turnover increased as
firms fail to meet analysts expectations. Meeting expectations has therefore been
identified as one of the most important prerequisite that management tries to fulfill
(Brown & Caylor, 2005; Degeorge et al., 1999).
The shareholders' expected earnings growth can be achieved through growth in sales
and/or growth in net income (Koller et al., 2005: 69). If earnings growth expectations
exceed the firm's net income growth, additional sales growth is required. Next to
meeting earnings expectations, extant research suggests that revenues forecasts are
the most widely followed performance metric by analysts (Rees & Sivaramakrishnan,
2007). Meeting revenue forecasts has previously been associated with an additional
equity premium, beyond the premium for meeting earnings forecasts. Rees &
Sivaramakrishnan (2007), for example, find that the market attaches an equity
premium to the act of meeting revenue forecasts that is separate and distinct from the
equity premium attached to meeting earnings forecasts. Other studies have confirmed
that investors value more highly a dollar of revenue surprise than a dollar of expense
surprise (Swaminathan & Weintrop, 1991). Further, a positive sales surprise may lead
to a positive market reaction, even if earnings forecasts are barely met. Similarly, a
negative sales surprise in the face of barely met earnings forecasts has been
associated with a negative market reaction (Ertimur, Livnat & Martikainen, 2003). A
firm's actual minimum growth requirement may thus be determined not only by the
investor's earnings growth expectations, however, by the rate of expected sales
growth. Based on the foregoing discussion, I thus expect that:
Hypothesis 1. Firms whose sales growth rate is higher than the rate of sales growth
expected by the firm's shareholders perform better than firms growing below this
rate.
6.2.2. Beating Shareholders' Expectations
Over recent years, a number of studies found that the incidents where firms have met
or beaten shareholders' expectations significantly increased (Brown, 2001;
Matsumoto, 2002). Further, Brown and Caylor (2005) found that avoiding negative
surprises relative to analyst's forecasts has become the predominant goal executives
try to reach. Thereby, as much as meeting shareholders' expectations has been
assumed to be positively related to various firm performance measures, the same
71
positive relationship is assumed for firms that beat shareholders' expectations (Bartov
et al., 2002; Degeorge et al., 1999). Building on research within the market-based and
resource-based view of the firm I believe, however, that there is a limit to the extent
to which a firm may exceed expectations. More specifically, I argue that beyond a
certain level above shareholders' expectations, further corporate growth negatively
affects the firm's performance.
Exceeding shareholders' expectations requires companies to either manage earnings
and revenues in a favorable way, for example by altering inventory methods, or to
take unforeseen competitive actions (Barua, Legoria, & Moffitt, 2006; Degeorge et
al., 1999). Earnings management refers to the strategic exercise of managerial
discretion in influencing the earnings figure reported to external audiences (Schipper,
1989). Within the generally accepted accounting principles (GAAP), executives have
considerable flexibility, for example, in the expensing of research and development,
the recognition of sales not yet shipped, the estimation of pension liabilities, the
capitalization of leases and marketing expenses or the delay in maintenance
expenditures (Degeorge et al., 1999). Managing earnings, however, is difficult
because auditors and boards of directors scrutinize questionable accounting practices.
Moreover, because accruals reverse in subsequent periods, managers are unlikely to
be able to use abnormal accruals to continually increase earnings above expectations
every period (Matsumoto, 2002).
While earnings management is suited to exceed expectations only in the short run,
executives may take actual competitive actions to beat expectations. From a market
perspective, competitive action is defined as any newly developed, hence unforeseen,
move that improves the firm's relative competitive position (Ferrier et al., 1999;
Jacobson, 1992). Similarly, resource-based arguments state that strategic actions
suited to exceed shareholders' expectations include valuable and difficult to imitate
actions such as for example the development of new products (Morrow et al., 2007).
Researchers from both research streams, however, argue that such moves are usually
achieved by actions that deplete the firm's financial resources (e.g., Armstrong &
Collopy, 1996; Buzzell et al., 1975). In the realm of the market-based view, pricecuts and excessive advertising have received the most attention as both types of
competitive action may have disastrous consequences for firm performance (see for
example, Scherer & Ross, 1990). In much the same way researchers from the
resource-based view have argued that making major strategic changes may force
firms to acquire significant levels of new resources which may in turn lead to cost
overruns (Morrow et al., 2007). Recent empirical evidence shows that the stock
72
market penalizes companies that pursue growth without simultaneously considering
the cost of their capital (Koller et al., 2005: 72). Several authors consequently suggest
that competitive actions have to be evaluated in respect of their financial feasibility
(e.g., Raisch & von Krogh, 2007; Varadarajan, 1983).
Over the years, the finance literature has presented numerous models with which to
measure the growth that a firm, given its operating and financial constraints, can
sustain (e.g., Babcock, 1970; Clark et al., 1989; Higgins, 1977, 1981; Kyd, 1981;
Varadarajan, 1983). The model of the sustainable growth rate may be appropriate to
depict a firm's growth limits. Sustainable growth refers to the "maximum annual
increase in sales that can be achieved based on target operating, debt, and dividend
payout ratios" (Van Horne, 1997: 743). If a firm grows at a faster rate than its
sustainable growth rate (SGR), it will be forced to increase its debt ratio, decrease
dividends, or issue new equity. Research has shown that all three options are limited,
usually to the detriment of financial soundness. Increasing financial leverage boosts
interest costs, and increases vulnerability to bankruptcy (e.g., Sharma & Mahajan,
1980). Reductions in the payout ratio contribute only minor funds, but often lead to
sharp declines in stock prices (e.g., Ghosh & Woolridge, 1987). Selling new equity is
time-consuming, costly, and often leads to low returns in subsequent years (e.g.,
Loughran & Ritter, 1995; Spiess & Affleck-Graves, 1995). Excessive growth, defined
as growth above the firm’s financial means, is thus regarded as a main reason for
insolvencies (Probst & Raisch, 2005). While growth above the SGR may be
detrimental, sales growth that remains below the SGR allows the firm to increase its
dividends, reduce its leverage, and build liquid assets (Higgins, 1977; Varadarajan,
1983). The sustainable growth rate is thus considered an excellent proxy for the
firm’s long-term maximum growth rate (Clark et al., 1989; Jegers, 2003; Kyd, 1981).
Hence,
Hypothesis 2. Firms whose sales growth is lower than the rate of sustainable growth
perform better than firms growing above this rate.
6.2.3. Irrational Shareholders' Expectations
While researchers commonly assume that shareholder expectations are formed in a
rational manner, an increasing amount of studies has recently questioned this
assumption (Keane & Runkle, 1998). Behavioral finance theory challenges the
efficient markets theory by assuming investors make specific types of information
processing errors that have been documented in the psychology literature (Barberis,
Shleifer, & Vishny, 1998; Slezak, 2003). For example, when revising their beliefs
73
investors tend to overweight recent information and underweight prior data
(Kahneman & Tversky, 1982). Studying the period between January 1926 and
December 1982, de Bondt and Thaler (1985) for instance found significant empirical
support for the overreaction hypothesis. Hereupon, Abarbanell and Bernard (1992)
found supportive evidence that analysts underreact to the most recent quarterly
earnings observation when producing their forecasts. Further, Friesen and Weller
(2006) found that analysts were overconfident about the precision of their own
information. Other studies have put the efficient markets theory at odds by
documenting incidents where stock returns were positively correlated, and reversals,
whereby stock returns were negatively correlated over time (Slezak, 2003). Keane
and Runkle (1998) found a correlation in a given period of analysts' forecast errors in
predicting earnings for firms in the same industry.
Rational investors would expect a rate of growth within the limits set by the firm’s
sustainable growth rate. Bounded rational investors, however, may form expectations
that exceed the firm's actual financial capacity to sustain this growth. If the
sustainable growth rate (SGR) slips below the expected sales growth rate, firms have
to choose between two suboptimal growth strategies: First, the firm may limit its
actual growth to the SGR, which is likely to disappoint shareholders and to cause
declining stock prices (e.g., Kasznik & McNichols, 2002). Secondly, the firm may
continue to grow above the expected sales growth rate, preserving its short-term
valuation at the cost of increasing its long-term risk. Researchers have consequently
warned about the dangers of conforming to irrational market pressures for growth
(Fama, 1998; Fuller & Jensen, 2002). Clark and his colleagues (1989: 293) argue that
shareholders are very sensitive in respect of the mechanisms used to realize growth.
Growth supported by an increase in the firm’s debt may lead to declining shareholder
returns and, ultimately, cause bankruptcy. Both growth strategies are thus likely to
contribute to declining market performance. Firms are clearly better off when the
sustainable growth rate exceeds the expected sales growth rate, providing the
potential for sustainable growth at or above the shareholders’ sales growth
expectations. Hence,
Hypothesis 3. Firms whose rate of sustainable growth is higher than the rate of
expected sales growth perform better than firms that lack this corridor of growth.
6.3. Research Design
In the following, I describe the sampling and data, the study measures, and present
the statistical methods and analysis.
74
6.3.1. Sample and Data
The sample employed for this study consists of all companies listed in the Fortune
500 index for the year 2005. I chose this sample for the following reasons: First, the
Fortune 500 firms represent a very large share of the total business activity in the
U.S., as well as large and diversified firms. Consequently, interest in the factors that
influence these large firms’ strategic decisions and performance outcomes is
warranted (Stimpert & Duhaime, 1997). Second, the sample avoids distorted findings
resulting from smaller firms’ highly volatile rates of growth. Third, a multi-industry
sample prevents the findings from being distorted by industry-specific characteristics
affecting firm growth.
The reference time frame covers the period between 1995 and 2004. In setting this
time frame, I follow the recommendations by previous studies to use intervals of
between seven and ten years (e.g., Baumol, 1962; Chandler & Baucus, 1996) as well
as research on corporate finance that demonstrates that firms may enjoy discretion if
they only temporarily exceed their financial limits (Clark et al., 1989; Richardson,
1964). The latter works also prescribe a ten year time frame for empirical
investigations.
All relevant data for this study were obtained from the COMPUSTAT database that is
considered highly reliable and which has been frequently used in prior research (e.g.,
Glaum et al., 2004; Lins & Servaes, 2002; Young et al., 1996). In order to enhance
the reliability of the data and counteract coding errors (miscoding arising from the
transfer of data from a primary data source to the electronic database), I randomly
checked the data accuracy against companies’ financial statements. Some firms
lacked data, limiting the final sample to 450 of the 500 firms in the initial sample.
The mean values of the independent and dependent variables for the dropped firms
did not differ from those of the retained firms.
6.4. Measurements
6.4.1. Firm Growth
Existing studies have utilized sales, profitability, as well as workforce measures to
determine growth. There is, however, an emerging consensus in the literature that
sales are the most relevant indicator of growth (Delmar et al., 2003; Hoy et al., 1992;
Weinzimmer et al., 1998). I thus measured the firm's annual growth as the firm’s
annual percentage increase in sales (Sit). I used the following formula for calculation
purposes:
75
Sit = (Sit / Sit-1) - 1.
6.4.2. Expected Sales Growth Rate
A formula for determining the expected sales growth rate (ESGit) can be derived in
three steps. First, I establish a basic discounted cash flow valuation model (e.g.,
Koller et al., 2005). For simplicity’s sake, I use a standard perpetuity formula, in
which a company’s enterprise value (EVit) equals its free cash flow (FCFit)
discounted by the weighted average cost of capital (WACCit) minus the expected
earnings growth rate (Eit):
EVit = FCFit /(WACCit-Eit).
Secondly, I reverse engineer the shareholders’ earnings growth expectations by
combining the discounted cash flow model with the current enterprise value. This
will yield an equation in which the expected earnings growth rate is the only
unknown (e.g., Mass, 2005):
Eit = WACCit - FCFit / EVit.
The expected earnings growth can be realized by growth in sales and/or net income
(Koller et al., 2005: 69). A firm’s expected sales growth rate can thus be calculated
by deducting the growth in the net income margin (IMit) achieved over a given time
period from the expected growth in earnings for the same period
ESGit = (1+Eit)/(1+IMit)-1.
In order to determine whether the firm's actual growth rate met shareholders'
expectations, I compared the expected sales growth rate with the firm's annual change
in sales, using the above formula. I created a binary variable (Sit < ESGit) to indicate
whether (0) or not (1) the firm's sales growth exceeded its expected growth rate.
Additionally, Sit - ESGit, captures the distance between the firm's level of growth and
shareholders' expectations.
6.4.3. Financial Resource Limits
I computed the firm's financial resource limit by drawing upon the sustainable growth
rate model initially proposed by Higgins (1977). The sustainable growth rate (SGRit)
can be obtained by equating annual capital requirements and capital generation
76
potential. I applied the following standard equation (e.g., Higgins, 1977; Varadarajan,
1983) to calculate the sustainable growth rate for each company and year:
SGRit = (Pit (1-Dit) (1+Lit)) / Ait - Pit (1-Dit)(1+Lit),
where Pit is the net profit margin, Dit the dividend payout ratio, Lit the debt-to-equity
ratio and Ait the total assets to sales ratio. In order to determine whether a firm's
growth remained within its financial resource limit, I compared the sustainable
growth rate with the firm's annual change in sales, using the above formula. I created
a binary variable (Sit > SGRit) to indicate whether (1) or not (0) the firm's sales growth
exceeded its financial limits.
To be able to test hypothesis 3, I created an additional binary dummy variable to
determine whether (1) or not (0) shareholders' expectations exceeded the firm's
financial resource limits (ESGit > SGRit).
6.4.4. Performance
To assess firm performance, I used a market-based measure. Traditionally, strategy
research has defined performance according to accounting-based measures, with
return on assets considered a reasonable proxy (Lubatkin & Shrieves, 1986). Owing
to this study’s long-term orientation, market-based measures may, however, be more
appropriate for studying performance effects (Bruner, 2002). Moreover, market-based
performance measures are thought to reflect all of performance’s relevant information
rather than being limited to specific performance dimensions (Lubatkin & Shrieves,
1986). Several authors have designated the return to shareholders as a suitable proxy
with which to measure market-based performance (e.g., Baucus & Baucus, 1997;
Bruner, 2002; Holliday, 2001; Rappaport, 2006). I thus use the annual change of total
return to shareholders (TRSit) to measure firm performance.
6.4.5. Control Variables
Previous research in growth and finance literature has generally controlled for time,
size, and industry effects (e.g., Markman & Gartner, 2002; Mishina et al., 2004). I use
a fixed-effect estimator in the analysis to control for variables that are invariant over
time, such as industry membership. Additionally, because larger firms can be
expected to have higher levels of financial resources and more developed market
positions, it is important to control for the size of the company. I thus included the
total number of employees as a control variable. Table 6.1 provides an overview of
all the variables used in this study.
77
Control Variable
Sizeit
Dependent Variable
Total number of employees
TRSit
Independent Variables
Annual change of return to shareholders
Sit
ESGit
SGRit
Sit < ESGit
Sales growth
Expected sales growth rate
Sustainable sales growth rate
Binary variable indicating whether (1) or not (0) the firm's
expected sales growth rate exceeded its sales growth rate
Binary variable indicating whether (1) or not (0) the firm's sales
growth rate exceeded its sustainable growth rate
Binary variable indicating whether (1) or not (0) the firm's
expected sales growth exceeded its sustainable growth rate
Sit > SGRit
ESGit > SGRit
Table 6.1: List of Variables
6.5. Statistical Methods and Data Analysis
I made use of cross-sectional time series to assess the effect of sales growth on firm
performance. As previously explained, I collected the annual data of 425 firms for the
period between 1995 and 2004. When the data were pooled across firms and across
these ten years, the resulting sample had 4250 observations. Given the twodimensional structure of the balanced data set, I used panel data statistical methods
(Hsiao, 1986; Baltagi, 1995) for analysis. I estimated the following general equation:
Yit = α + Xit'βit + δi + γt + εit,
where Yit is the dependent variable, Xit is a k-vector of regressors, and εit are the error
terms for i = 1, 2, …, M cross-sectional units observed for dated periods (t = 1, 2, …,
T). The α parameter represents the overall constant in the model, while the δi and γt
terms represent cross-section or period-specific effects (random or fixed). The β
coefficients may be divided into sets of cross-section-specific, period-specific, and
common (across cross-sections and periods) regression parameters.
A key benefit of utilizing panel data is the ability to test and control for the effects of
unobserved fixed factors, which, if left uncontrolled, can induce bias in the
coefficient estimates of the explanatory factors included in the model (Rajagopalan &
Datta, 1996). I restricted the sample to large firms, which prevents different residual
variances that depend on the absolute level of the variables (e.g., sales) from affecting
the estimation. However, the observations may no longer be independent as firm
characteristics are correlated over time (Finkelstein & Hambrick, 1990; Haleblian &
78
Finkelstein, 1993). It is unreasonable to assume that with regard to this study, the data
points in the longitudinal dimension are independent of one another. For instance,
unobserved firm-specific factors (e.g., corporate reputation, managerial teams) may
influence observations of the same firm and produce correlation across these
observations over time (Gimeno, 1999). Thus, instead of using the standard pooled
ordinary least squares (POLS) estimation, whose key assumption is independence
across all observations, I used a fixed-effect estimator. Fixed-effect estimators
remove all time-constant effects by subtracting the mean of the ten-year period,
thereby ensuring consistency in estimation. Moreover, fixed-effects models predict
the annual change in a dependent variable, as opposed to random-effects models
which are appropriate if aiming to explain variance among firms (Sanders &
Hambrick, 2007). Further, I used a feasible generalized least squares (FGLS)
estimation by assuming the presence of period-specific structures within the
residuals. The weighting of the observations helps to exploit all structures within the
data panel set, which enables efficient estimation. Lastly, I adjusted the standard
errors by using a White adjustment in the longitudinal period. This adjustment leads
to robust significance values.
In order to test hypothesis 1 I estimated the following equation:
TRSit = α + Sizeit βit + Sit βit + (Sit < ESGit) βit + (Sit - ESGit) (Sit < ESGit) βit + γt + εit.
The first coefficient beyond the size control variable assesses the general relationship
between sales growth and performance for all firms in the sample. The second
coefficient estimates the average performance of those firms that were unable to meet
shareholders' sales growth expectations. With the third coefficient, I tested whether
firm performance is affected by the distance between the firm's actual sales growth
rate and the expected sales growth rate.
In order to test hypothesis 2 I estimated the following equation:
TRSit = α + Sizeit βit + Sit βit + Sit (Sit > SGRit) βit + γt + εit.
Again, I tested the relationship between growth and performance. In addition, I
examined the specific performance effect of firms whose sales growth rate exceeded
their financial limits.
79
In order to test hypothesis 3, I estimated the effect of irrational shareholders'
expectations on firm performance. More specifically, I analyzed how expectations
that exceed the firm's financial capabilities affect its performance using the following
equation:
TRSit = α + Sizeit βit + Sit βit + (ESGit > SGRit) βit + γt + εit,.
Again, the first coefficient assesses the general relationship between sales growth and
performance for all firms in the sample. The second coefficient estimates the average
performance of those firms whose rate of expected sales growth exceeds its
sustainable growth rate.
6.6. Results
In the following I present the results of the analysis. Table 6.2 provides the crosssectional, time series summary statistics (means, standard deviations, and correlation
coefficients) of all the variables employed. The panel data regression results of the
hypotheses testing are reported in Tables 6.3 to 6.5. I report the parameter estimates,
as well as the standard errors and values of the t-statistic in respect of each regression.
The probability levels are indicated by asterisks. The double asterisks indicate
significance at the 1% level, while the single asterisks indicate significance at the 5%
level. The reported results refer to the total return to shareholders (TRSit) as the
dependent variable.
Variable
1. Firm Performance, TRSit
2. Sales Growth, Sit
3. Expected Sales Growth Rate, ESGit
4. Sustainable Growth Rate, SGRit
5. Firm Size, Sizeit
Mean
0.24
0.17
0.10
0.15
47897
s.d.
0.66
0.44
0.53
0.38
89718
1
2
3
4
0.14
-0.01
0.06
-0.05
-0.01
0.05
-0.07
-0.44
0.00
0.02
Table 6.2: Time Series Cross-Sectional Summary Statistics
Hypothesis 1 predicted that firms that meet shareholders' expectations are more
successful than firms that fail to do so. To test this hypothesis, I estimated a model
with two explanatory variables: the sales growth rate and a dummy variable
indicating firms that were unable to meet shareholders' sales growth expectations.
Additionally I included a coefficient which assesses the performance effect resulting
from the absolute difference between the firm's actual growth rate and the expected
sales growth rate, for those firms that didn't meet expectations. Each variable has the
expected sign and is statistically significant, thus supporting the hypothesized
80
relationship. The results indicate a generally positive relationship between sales
growth and performance (0.14, p < 0.01). As predicted, the average performance of
firms that were unable to meet shareholders' expectations is significantly lower than
that of all other firms (-0.04, p < 0.05). The third coefficient provides additional
insights in that, the results suggest that performance decreases as the distance
between actual sales growth and the expected growth rate increases (0.02, p < 0.05).
Thus, the larger the difference between the firm's growth and the shareholders'
expected growth, the weaker the performance.
Variable
C
Sizeit
Sit
Sit < ESGit
(Sit - ESGit) (Sit < ESGit)
Coefficient
Std. Error
t-Statistic
0.25
0.00
0.14
-0.04
0.02
0.02
0.00
0.05
0.02
0.01
15.22**
-2.32*
2.60**
-2.34*
1.99*
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
Cross-sections included
Total observations
0.22
0.64
66.37
0.36
0.71
377
3153
* p < 0.05
** p < 0.01
Table 6.3: Hypothesis 1, Results of Fixed Effects Panel Data Regression
In order to test hypothesis 2, I employed two explanatory variables: the rate of sales
growth and a dummy variable indicating those firms that exceeded their financial
limits regarding their growth level. Both variables have the expected sign and are
statistically significant, thus supporting the hypothesized relationships. Again, I found
a generally positive relationship between sales growth and performance (0.62, p <
0.00). The results also suggest that firms whose sales growth exceeds their financial
limits experience a significant deterioration in performance (-0.50, p < 0.00).
81
Variable
C
Sizeit
Sit
Sit (Sit > SGRit)
Coefficient
Std. Error
t-Statistic
0.22
0.00
0.62
-0.50
0.01
0.00
0.09
0.09
23.50**
-2.66**
6.91**
-5.31**
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
0.19
0.66
68.72
0.31
0.72
Cross-sections included
Total observations
387
3624
* p < 0.05
** p < 0.01
Table 6.4: Hypothesis 2, Results of Fixed Effects Panel Data Regression
In order to test hypotheses 3 I analyzed the average performance of firms who lack a
corridor of growth (i.e., the expected growth rate exceeds the sustainable growth
rate). The results indicate that a significantly negative performance effect results (0.11, p < 0.00).
Variable
C
Sizeit
Sit
ESGit > SGRit
Coefficient
Std. Error
t-Statistic
0.26
0.00
0.15
-0.11
0.01
0.00
0.02
0.02
29.16**
-4.69**
9.46**
-6.57**
Weighted Statistics
R-squared
S.E. of regression
F-statistic
Mean TRS
S.D. TRS
Cross-sections included
Total observations
0.22
0.64
73.62
0.36
0.71
377
3132
* p < 0.05
** p < 0.01
Table 6.5: Hypothesis 3, Results of Fixed Effects Panel Data Regression
In sum, all hypothesized relationships are supported on a 1%, respectively 5% level
of significance.
6.7. Discussion
The aim of this study was twofold. First, it was geared to assess performance
differences between firms that meet and firms that beat expectations. Second, this
study aimed at analyzing the consequences of irrational shareholders' expectations on
firm performance. The findings suggest that shareholders' sales growth expectations
82
have a significant performance impact. More specifically, I found that firms with
lower sales growth levels than shareholders' expectations were less successful than
firms with growth levels that met expectations. At the same time, however, I found a
limit in the degree of beating shareholders' sales growth expectations. While previous
studies did not differentiate between firms that meet and firms that beat expectations
(e.g., Bartov et al., 2002; Degeorge et al., 1999), the findings of the present study
suggest a significant difference in performance. I found that firm growth is limited by
the sustainable growth rate. Firms whose sales growth rates exceed their sustainable
growth rates show significantly lower performance than firms that grow within their
financial limits. Additionally, this study revealed that irrational shareholders'
expectations may have disastrous consequences for firm performance. Firms whose
shareholders expected a sales growth rate beyond the firm's financial limits, perform
significantly worse.
The findings of this study have important implications for financial theory. More
specifically, this study adds to research on the formation of earnings expectations in
two different ways. First, the findings indicate that there is a significant performance
difference between meeting and beating shareholders' expectations. In opposition to
prior studies, I assume that the extent to which a firm may beat expectations is
limited. Existing studies analyzing the effects of earnings expectations on firm
performance suggest that there is a reward to meeting or beating analysts’ earnings
expectation (Rees & Sivaramakrishnan, 2007). More specifically, it has been argued
that ending the period with a positive earnings surprise results in a positive stock
valuation. However, little research has been conducted to analyze the reasons
underlying this association (Bartov et al., 2002). Studies from the resource-based
view and market-based view of the firm argue that competitive moves suited to
exceed expectations are usually achieved by actions that deplete the firm's financial
resources (e.g., Armstrong & Collopy, 1996; Buzzell et al., 1975). Beating market
expectations may thus prove very costly indeed. The findings of the present study
support these arguments, pointing to a significant performance difference between
meeting and exceeding expectations.
Second, the findings indicate that shareholders may have unrealistic expectations
regarding firm growth as they may expect a level of growth above a firm's financial
limits. In the case of the non-existence (i.e., where expectations exceed financial
limits) of an optimum corridor of corporate growth, firms have to choose between
two suboptimal growth strategies. Either the firm limits its growth to the sustainable
growth rate, disappointing shareholders, or it continues to grow above its expected
83
sales growth rate, thereby increasing its long-term risk. The findings of this study
show that firms whose expected sales growth rate exceeds its sustainable growth rate
experience a significantly negative performance effect. Consequently, the results
support behavioral finance theory, which assumes that investors' expectations may be
irrational (Zhang, Zhang & Xiong, 2006). Barberis et al. (1998), for example, argue
that security prices overreact to consistent patterns of news pointing in the same
direction. Firms that have a history of consistent growth increases may thus be prone
to irrational shareholder expectations. Other authors have observed that analysts’
forecasts made at the beginning of the period tend to overestimate earnings (e.g.,
Barefield and Comiskey, 1975; Brown, 1997; Richardson, Teoh, & Wysocki, 1999).
Researchers dealing with earnings and expectations management may provide
insights as to how firms can handle such unfavorable situations (e.g., Burgsthaler &
Eames, 1998; Matsumoto, 2002). While previously, studies have focused on how
executives may attain specific expectation levels, the reverse case - of guiding
analysts to issue meetable earnings targets - deserves more attention (Cotter, Tuna, &
Wysocki, 2006). Initial evidence from research on mechanisms of stock pricing, for
example, suggests that positive earnings surprises have a disproportionately large
positive impact on stocks that are priced low relative to four measures of operating
performance, while negative surprises have a relatively benign effect on such stocks
(Levis & Liodakis, 2001). In some instances, keeping financial figures low to avoid
market overreaction is beneficial to firm performance.
In a broader context, the findings of this study also builds on research on the
performance implications of corporate growth. More specifically, the results suggest
that there may be a corridor of optimum corporate growth: both too little as well as
too much growth are negatively related to performance. A moderate level of growth,
as much as is necessary to meet shareholders' expectations, but still within the firm's
financial limits, has the strongest positive impact on firm performance. The findings
thus imply that the performance effect of corporate growth is firm-specific and
dependent on the sales growth rate relative to the firm's lower and upper growth
boundaries. This study thus adds to previous theoretical contributions which indicate
that firms’ ability to growth are contingent on their unique resource base and market
conditions (e.g., Penrose, 1959; Porter, 1980; Slater, 1980).
6.7.1. Limitations and Managerial Implications
The strengths of this study include the cross-sectional time series sample and the
panel data statistical methods used for analysis. Nevertheless, this research is not
without limitations. While the results suggest that there is a limit to the extent to
84
which firms may beat market expectations, more research on extent, as well as
particular performance implications resulting from exceeding, as opposed to meeting,
expectations, is needed. For example, strategic management theory dealing with
corporate risk-taking has suggested that the relationship between beating expectations
and declining firm performance may be the result of overly risky actions. More
specifically, it has been found that firms in situations of decline may feel pressure to
turn around performance quickly and as a result, take actions without sufficient
analysis or evaluation (Morrow et al., 2007). The negative performance effect of
beating expectations observed in this study may thus also be attributable to the failure
of initiatives, rather than their costs, as argued by resource-based and market-based
theorists.
Several fundamental managerial implications follow from this study. Practice shows
that firms are frequently driven into fast growth strategies because their investors and
analysts expect strong results or because they imitate competitors that make similar
moves (DiMaggio & Powell, 1983; Haveman, 1993). Bandwagon effects may give
rise to waves of mergers and acquisitions, as repeatedly observed by prior research
(Shleifer & Vishny, 1991; Stearns & Allan, 1996). While such behavior may be
understandable, the study suggests that it may not be optimal for a firm’s long-term
success. Firms require growth to remain vital and competitive, but they should strive
for optimum growth rather than maximizing growth. There is a fine line between
being aggressive and being out of line. The business landscape is already littered with
the remains of high-flying companies (e.g., Probst & Raisch, 2005).
The model described in this study provides a benchmark of what can feasibly be
accomplished. It also provides a tool which may aid management in finding its
company’s optimum long-term growth rate. Managers may use the model to
determine their company’s upper and lower boundaries of optimum growth. As
events unfold, companies’ actual growth rates may incline to higher or lower levels.
A continued disparity between actual growth and its boundaries should, however,
prompt decision-makers to take corrective action, if this is required to maintain an
internal balance. A balanced growth behavior, rather than uncontrolled behavior, may
be the source of sustainable success and superior performance.
85
THE CORRIDOR OF OPTIMUM FIRM GROWTH:
THEORETICAL AND PRACTICAL IMPLICATIONS
Growth and Firm Performance:
Theoretical Foundations for a Multi-Perspective
Model of Optimum Firm Growth
Theoretical
Background
A Multi-Perspective Model of
Optimum Firm Growth
The Corridor
CorridorofofOptimum
The
Optimum
Firm Growth
Firm Growth
The Market-Based
Perspective
Performance
Implications
Low
Maximum Threshold
Maximum Threshold
The Resource-Based
Perspective
High
Minimum
Threshold
Minimum
Threshold
The Financial
Perspective
Low
86
7. Theoretical Contributions
The reported study examined firm-specific thresholds of optimum growth.
Specifically, it started with the widely accepted notion that after a certain point
increasing firm growth causes decreasing efficiency and firm performance. Yet, there
is very little research that has systematically examined the factors that impact a firm’s
optimum growth and how this optimum may be determined. I believe this is a
critically important yet underexplored issue in corporate growth research. Drawing on
multiple bodies of related literature, I developed three distinct papers which consider
elements of the market-based, resource-based, and financial theory. The findings
suggest that there are firm-specific lower and upper thresholds of optimum growth
and that these may have a significant effect on firm performance.
While each paper makes its own contributions to different business theories,
important theoretical as well as practical implications follow from their integration. I
believe that an added value of this study arises out of the interconnection of the three
papers which should serve as a basis for a detailed and comprehensive discussion of
the antecedents and consequences of optimum firm growth. Combining these insights
provides an integrated academic view upon optimum firm growth, while on the other
hand, providing a comprehensive tool which may aid management determining their
company’s optimum rate of long-term growth.
After having outlined each study's individual theoretical contributions in the
respective conclusions, I will move on to reviewing the paper's combined
contributions to theories in business research. In the ensuing section I explain in
detail in what ways the integrated findings of these studies contribute to research on
corporate growth, change, and learning. In the subsequent chapter I will then
elucidate the practical implications of this dissertation by relating the integrated
findings to real world business cases. I provide examples of European firms and
retrace their paths within the growth corridor over the last decade.
7.1. Corporate Growth
The growth literature suggests that the link between growth and performance is
contingent on the firm’s specific growth strategy. Prior research has mainly focused
on the directions and modes of corporate growth. Growth directions, particularly the
firm’s diversification (e.g., Palich, Cardinal, & Miller, 2000) and the
internationalization (e.g., Hitt, Hoskisson, & Kim, 1997) are among the predominant
fields of management research. Growth modes, including mergers and acquisitions
87
(e.g., Larsson & Finkelstein, 1999) and alliances (e.g., Doz & Hamel, 1998), have
gained great research interest as well. In this study, I suggest a third dimension of
growth strategies: the pace of growth.
While prior research has largely neglected this aspect of firms’ growth strategies,
some recent studies indicate that the pace of growth may indeed matter. In an
empirical study of international expansion, Vermeulen and Barkema (2002) found
that at an escalating rate, internationalization speed negatively moderates the relation
between a firm’s foreign expansion and profitability. Wagner (2004) likewise
reported evidence of an inverted-U form linkage between the rate of
internationalization and performance. In respect of acquisition programs, Hayward
(2002) argued that there is an optimum pace of acquisitions. While low acquisition
rates may hamper the transfer of expertise from one deal to another, high rates may
cause an "acquisition indigestion problem". Keil and Laamanen (2005) found
empirical evidence of a negative relationship between acquisition rate and
performance. In the diversification literature, Chang (1995) argued that the rate of
new business entry may be limited by the need for sequential entry. Successful firms
learn from a series of small-scale entries and thereby reduce the risk of failure. Pettus
(2001) found empirical evidence of sequential entry’s positive effect on firm
performance.
Both research streams thus found pace to be an important moderator of the
relationship between growth directions or modes and performance. The theory of
optimum growth developed in this article provides a common theoretical foundation
for these studies. Contrary to prior research, I conclude that pace is more than just a
simple moderator of growth directions, or modes’ effect on performance. The pace of
growth may have a direct effect on performance, independent of the specific mode or
direction of growth.
7.2. Corporate Change
In a more general context, the study contributes to recent studies on the pace of
organizational change. Traditionally, studies on organizational change promote fast
change as beneficial in overcoming unproductive inertia in firms’ mental maps and
routines (Barkema & Vermeulen, 1998). Firms that develop too slowly in an ever
accelerating world are expected to fall behind as rivals race ahead. Barnett and
Hansen (1996), for instance, describe the "Red Queen" effect in organizational
evolution: only firms that change fast enough benefit from a self-reinforcing cycle of
increased learning and competitive strength.
88
However, since the capacity of a firm to expand and absorb new experiences is
limited, the pace of change may also become too high (Cohen & Levinthal, 1990).
Dierickx and Cool (1989) introduced the notion of "time compression diseconomies":
the mechanism of diminishing returns when the pace of processes increases. A too
rapid experience may overwhelm the organization, harming the firm’s ability to learn
effectively (Eisenhardt & Martin, 2000). Perlow, Okhuyson, and Repenning (2002)
describe how organizations that focus on speed may be caught up in a vicious cycle –
a "speed trap" – that leads to further increases in speed to the detriment of the quality
of decision-making. Barkema, Baum, and Mannix (2002), reviewing some of the
studies mentioned above, thus suggest that firms have an optimum pace of
development and change.
The study contributes to this research by providing concrete thresholds to firm
expansion’s optimum pace. Gersick (1994) states that different organizational
processes require different paces and that the managerial challenge is to manage the
optimal pace of these processes. I argue that a firm’s optimum growth rate may be the
"master clock" setting the pace for related organizational change processes such as
expanding abroad or acquiring firms. While other factors’ moderating influence has
to be considered, the thresholds described in this study may provide the foundation
for further research into the pacing of these processes.
7.3. Corporate Learning
Finally, the results of this study have implications for theories on organizational
learning. A fundamental idea in the knowledge-based theory of the firm is that
optimal growth involves a balance between the exploitation of existing capabilities
and the exploration of new competencies (Chatterjee & Wernerfelt, 1991; Ghemawat
& Costa, 1993; Hansen & Wernerfelt, 1989, March, 1991; Teece et al., 1997). Two
recent empirical studies found support for the superior performance of "ambidextrous
organizations" that balance exploitation and exploration, rather than emphasizing one
at the expense of the other (Gibson & Birkinshaw, 2004; He & Wong, 2004).
My research suggests that organizational ambidexterity and optimum firm growth
may be closely related. Optimum growth requires, for instance, growth above the rate
at which relative human resource slack emerges within an organization. Growth
above this rate allows for efficient exploitation of existing resources. Utilizing
relative resource slack to grow results in learning and eventually the exploration of
new resources. At the same time, I found that performance declines at high levels of
89
growth. This negative U-shaped relationship may imply that there is a limit to firm
growth which ensures that exploration activities are restrained to a level that does not
harm the existing resources’ efficient exploitation.
Similar arguments can be made, for instance, for the market-based model of optimum
firm growth. Growth above competition requires both the exploitation of existing
resources and the exploration of new resources. Such "premium" growth is
impossible to sustain without considerable exploratory activities such as new product
development or acquisitions. The sustainable growth rate ensures that these
explorative ventures are limited to a level that preserves the firm’s ability to
efficiently exploit existing products.
Combining the lower and upper growth thresholds may thus not only indicate the
range for optimum growth, but also the path towards an optimum balance between
exploitation and exploration. Optimum growth could thus be the pacemaker of the
ambidextrous organization – and the latter an important precondition for achieving
optimum growth. Future research may further investigate the interrelations between
optimum growth and organizational ambidexterity.
90
8. Practical Implications
Several fundamental managerial implications follow from this study. Practice shows
that firms are frequently driven into fast growth strategies because their investors and
analysts expect strong results or because they imitate competitors that make similar
moves (DiMaggio & Powell, 1983; Haveman, 1993). Bandwagon effects may give
rise to waves of mergers and acquisitions, as repeatedly observed by prior research
(Shleifer & Vishny, 1991; Stearns & Allan, 1996). While such behavior may be
understandable, this study suggests that it may not be optimal for a firm’s long-term
success. Firms require growth to remain vital and competitive, but they should strive
for optimum growth rather than maximizing growth. There is a fine line between
being aggressive and being out of line. The business landscape is already littered with
the remains of high-flying companies (e.g., Probst & Raisch, 2005).
The findings of the three studies described in this dissertation provide a benchmark of
what can feasibly be accomplished. Further, they provide a tool which may aid
management in finding its company’s optimum long-term growth rate. Managers can
use the models to determine their company’s upper and lower boundaries of optimum
growth. As events unfold, companies’ actual growth rates may incline to higher or
lower levels. A continued disparity between actual growth and the growth thresholds
should, however, prompt decision-makers to take corrective action, if this is required
to maintain an internal balance. A balanced growth behavior, rather than uncontrolled
behavior, may help them build sustainable success and increase firm performance.
8.1. The Corridor of Optimum Firm Growth
An analysis of the variables derived from the perspectives of market-based, resourcebased, and financial theory indicates that two benchmarks stand out in terms of their
relevance for optimum growth. On the one hand, a firm's minimum growth
requirements may be best depicted by its competitive growth rate (CGR). For most
companies in the sample, the CGR presented the largest hurdle to optimum growth.
Compared to resource-based and financial growth requirements, the CGR was the
lowermost boundary for only 16% of the companies in the sample. The relevance of
the CGR as the lower growth boundary is further reflected by its performance
implications. The average ten-year performance of the companies growing above the
CGR was 14.4% per year, as opposed to 8.0% per year for the companies growing
below this rate (p < 0.01; t = 6.4).
91
On the other hand, this study indicates that financial boundaries ultimately constrain a
firm's growth rate. Consequently, the sustainable growth rate (SGR) is well-suited to
delineate the firm's maximum growth boundary. The average return to shareholders
for firms growing within the limits set by their SGR was 14% per year, as opposed to
10% per year for the firms growing above their SGR (p < 0,01; t = 3.6). A company's
optimum growth path may thus be determined by the CGR and SGR. Jointly
examined, these two benchmarks provide the thresholds for the corridor of optimum
firm growth.
A closer look at the overall performance of the companies in the sample illustrates the
relevance of the growth corridor for firms' success. Companies that grew within the
limits set by their growth corridor clearly outperformed peers that did not. Those
firms, throughout the rest of this study referred to as "smart growers", include
companies such as, for example, the world's largest retailer Wal-Mart Stores Inc., the
leading software giant Microsoft, or the world's major manufacturer of industrial
equipment Caterpillar. These companies' return to shareholders on a ten-year average
basis was 17.5%, as opposed to 10.0% for all other companies in the sample (p <
0.01; t = 6.4).
In the ensuing section, I will provide a case study of Nestlé, to illustrate how the
growth corridor works. I will draw lessons from this smart-grower to develop
guidelines for companies that are in less favorable positions in the growth corridor. In
total, I have identified three suboptimal growth situations: (1) companies
experiencing excessive growth, (2) cash-starved companies, and (3) growth laggards.
I will use European companies as examples of those suboptimal growth paths and
draw conclusions regarding performance effects and ways of escaping these
unprofitable situations.
8.2. Smart Growth: Nestlé's Path to Success
Nestlé SA, the Swiss located food giant, provides a good illustration of how the
growth corridor works. Between 1995 and 2007 Nestlé's sales growth rate has been
within the corridor of optimum firm growth. On an average the competitive growth
rate reached 2.8%, the sustainable growth rate amounted to 11.6%, while Nestlé's
sales growth averaged 5.5% during this period. Although Nestlé's growth varied in
the short run, its average sales growth was within its corridor of optimum growth.
The benefits of smart growth are well reflected in Nestlé's return to shareholders
which amounted to an annual average of 16.9% during this period.
92
To analyze the company's growth path I conducted a series of personal interviews
with members of the top management team and an in-depth study of archival data.
The results of this study enabled me to identify three fundamental strategic
characteristics which serve as a good illustration of how the growth corridor works
and allow to deduce guidelines which can help managers to use the model of the
growth corridor in their strategic planning.
20%
Increasing Risk
17.0%
17.5%
Return to
Shareholders
10.9%
Sustainable
Growth Rate
5.2%
Sales
Growth Rate
2.5%
Competitive
Growth Rate
16.1%
15%
12.9%
11.0%
10%
7.4%
4.0%
5%
3.5%
2.4%
Increasing Risk
‘95
‘97
‘99
‘01
‘03
‘05
‘07
Figure 8.1: Nestlé's Growth Corridor
8.2.1. Nestlé's Profitable Growth: The Point of Departure
In June 1997 Peter Brabeck-Letmathe took over as CEO of Nestlé, inheriting a
company that enjoyed the leading position in the global food industry. His
predecessor Helmut Maucher, the CEO between 1982 and 1997, had divested the
firm's unattractive activities, while establishing its position in higher-margin
segments such as pet food and water. Maucher had transformed Nestlé from a
manufacturer with a strong European base focused on milk and coffee, into a truly
diversified global food company. During his 16-year reign, sales had more than
doubled, profits had tripled, and the total return to shareholders was an excellent 17%
per year (Ashcroft & Goldberg, 1996). Looking at the growth corridor between 1995
and 1997 reflects this strong position very well. Nestlé clearly outperformed its
competitors while at the same time keeping its rate of sales growth within its financial
limits.
To maintain the momentum, Peter Brabeck focused his activities on three major
areas. First, he set the company a challenging long-term growth target of 5% to 6%
93
revenue increase per year, well above average market growth. Second, he consistently
worked on improving the firm's efficiency. Third, he invested the cash generated by
operational improvements to develop new products and strengthen Nestlé's
innovative capacity. In the ensuing section I return to the initial situation in 1997
when Brabeck assumed the position as Nestlé's CEO and retrace the company’s
development over the following decade. The objective is to outline Brabeck’s most
important strategic and organizational initiatives that enabled the company to achieve
growth within the limits set by the growth corridor.
8.2.2. Earning the Right to Grow
Brabeck's first task to achieve profitable growth was to strengthen the company’s
operational efficiency. A series of efficiency programs like MH97, Target 2004+, or
Operation Excellence 2007, were initiated to reduce raw material costs, optimize
production and improve the firm's administrative processes. The most important of
those business transformation initiatives was launched in 2000. While covering a
broad range of strategic objectives GLOBE (Global Business Excellence) was also
designed to improve operational efficiency by integrating the company’s businesses
on a global scale. The project’s major objectives are to establish best practices in
business processes, to align data standards, and to install common information
systems. Due to Nestlé's highly decentralized structure and its large number of
acquisitions, it runs multiple versions of accounting, planning and inventory software.
Sharing information between markets and operating units is thus difficult. The
project's impacts range from the way raw materials are bought, to production,
marketing, and sales. By the end of 2006, GLOBE had enabled total savings of CHF
3 billion.1
Besides programs directed towards increasing Nestlé's operational performance,
Brabeck also worked on reducing marketing expenditures by better exploiting the
synergies between brands. Brand strategies were centralized as far as possible to
drive synergies and increase control. The most important strategic initiative was to
allocate as many of the company’s 127,000 products as possible to six strategic
brands: Nestlé, Buitoni, Maggi, Nescafé, Nestea, and Purina. These strategic brands
deliver higher margins, occupy more shelf space, and help retailers generate top-line
growth2. Nescafé, for example, has a brand value of nearly CHF 15 billion, a name
recognition of almost 100% in the world’s leading markets, and margins of around
18% (Goldberg & Hogan, 2002).
1
2
www.nestle.com, Presentation Chris Johnson at the Nestlé Investor Seminar.
Personal interview with Luis Cantarell (January 16, 2006; Vevey, Switzerland).
94
The efficiency initiatives’ combined outcome has been impressive. Nestlé's net
margin rose from 5.7% in 1997 to 9.9% in 2007. The various cost initiatives incurred
total savings of CHF 12 billion. Net income soared from CHF 4 billion in 1997 to
CHF 10.6 billion in 2007, while the free cash flow nearly doubled.3 The effects of the
amelioration of Nestlé's operational efficiency is also well reflected in the growth
corridor. During the period between 1997 and 2003 when most of the efficiency
programs were underway, Nestlé's sustainable growth rate rose from previously 11%
to 12.9%.
8.2.3. The Nutrition and Wellness Initiative
Nestlé’s efficiency improvements were the basis for strong investments in the firm's
growth. Brabeck’s primary task shifted towards generating new sources of growth for
the company's future expansion. Very early on, Brabeck sensed that the growing
demand for wellness and nutritional products could provide an excellent opportunity
for sustained growth. One of Brabeck's first official acts as CEO was the creation of a
dedicated unit engaged in nutrition related to performance, infants, and diet. The
rationale behind the new unit was to develop an innovative product segment with a
strong potential for future growth and considerably higher margins than traditional
products in the food industry.
Building on this first initiative, Brabeck announced his vision of transforming Nestlé
from a food company into a food, nutrition, health, and wellness company in 2000.
An entire package of measures, which included strategic initiatives and
organizational changes, was implemented to integrate nutritional thinking into the
group as a whole. In pursuit of a strong internal growth potential, Brabeck aimed at
two main strategic goals. The first objective was to develop nutrition and wellness as
a value-added in the mainstream food and beverage business. The second objective
was to reinforce the company's leading position regarding specialized nutritional
products. The creation of two dedicated business units, the Corporate Wellness Unit
and the Nestlé Nutrition Unit, reflected these twin objectives.
The creation of the Corporate Wellness Unit was directed at fulfilling the first
strategic objective, namely spreading Nestlé's nutrition and wellness orientation
throughout the group and across all product categories. Matt Hall, head of the
strategic unit "Generating Demand", describes the strategy: "Nestlé remains within its
traditional products and categories, but starts leveraging these products. We increase
3
I calculated these figures based on data published in Nestlé's annual reports.
95
their value by adding health and nutritional elements."4 Aspects of health, wellness
and nutrition are incorporated into a vast array of product categories, ranging from ice
cream, frozen foods, and confectionaries to pet food. The elements added to the
existing products promote digestive health, improve the immune system and skin's
defenses, positively affect weight management as well as physical and mental
performance, and contribute to healthy ageing. To date, Nestlé has modified more
than 700 products by adding nutritional functionalities (Kowalsky & Nolmans, 2005).
The Nestlé Nutrition unit is focused on the core nutrition business. The Nutrition unit
provides products for those consumers whose primary purchasing motivation is the
products’ nutritional value, while taste is simply a value added. The product portfolio
encompasses infant formulas, hospital nutrition, baby cereals, and sports nutrition.
These products operate in a medical environment and require strong scientific support
and long-term research and development. Nestlé devotes about one fifth of its overall
R&D budget to nutrition research. Three-quarters of the current projects at the central
Nestlé Research Center (NRC) in Lausanne focus on health and well-being (Ball,
2004).
Nestlé's nutrition business contributed significantly to the company’s success. Sales
generated by products with added nutritional benefits grew from CHF 200 million in
1998 to CHF 3 billion in 2005. Furthermore, these products’ profit margins are twice
as high as those of traditional food products, and thus contribute strongly to Nestlé's
margin improvements (Ackerman, Smith, Peterson, & Stent, 2006).
8.2.4. Strengthening Innovation
Nestlé is considered the innovation leader in the global food and nutrition sector. The
driving force behind the innovation is the company’s extensive research and
development (R&D) network. Strengthening the company’s R&D success was a key
objective in Brabeck’s quest for growth. Three strategic measures contributed to this
objective.
First, Brabeck set the company’s R&D activities a challenging target: one fifth of the
entire product portfolio has to be innovated or renovated every year. Innovation
refers to moving the group into promising new product segments, whereas renovation
relates to improvements to existing products, such as changes in the packaging,
shape, taste or quality. Two thirds of the company’s R&D activities are dedicated to
renovating existing products, while the remaining third is reserved for more radical
4
Personal interview with Matt Hall (September 21, 2005; Vevey, Switzerland).
96
product innovations.5 Second, a strong budgetary increase as well as improvement in
its operating efficiency enabled the R&D to achieve these challenging targets.
Nestlé’s R&D expenditures nearly doubled, increasing from CHF 770 million in 1997
to CHF 1.5 billion in 2005.6 At the same time, the R&D efficiency increased through
improvements on the operational level. Third, a number of organizational changes
were made to improve the R&D’s connection with the markets in which Nestlé
operates. The most relevant of these organizational measures were the creation of
Product Technology Centers, Local Application Centers, and Clusters.
The Product Technology Centers’ (PTC) objective is to transform research concepts
provided by Nestlé's fundamental research centers into consumer products. These
centers are closely linked to the company's strategic business units and are located in
key consumer markets. The PTCs allow ground-breaking innovations to be
transformed into marketable products more swiftly. Currently, there are nine PTCs
located in France, Germany, Great Britain, Switzerland, and the United States.7
Local Application Centers work inside the most relevant regional markets and are
concerned with adapting global products to local tastes and requirements. Apart from
adaptations in taste, color, and shape, the form and/or packaging of products are also
frequently changed. There are, for example, over 100 local variations of Nescafé
offered around the world8.
Clusters are cross-divisional project structures designed to improve the
communication and knowledge sharing between the R&D and the rest of the
company. Clusters unite researchers with the heads of business and regional units that
face similar market environments. The objective is to jointly launch R&D initiatives
in respect of new product development. Cooperation in clusters results in synergies,
shared investments, and faster product roll-outs. Products developed within these
clusters are either implemented as global solutions, or as "cluster solutions" in the
participating regions. If necessary, the company’s local application centers adapt the
provided solutions to the specific market requirements.9
5
Personal interview with Matt Hall (September 21, 2005; Vevey, Switzerland).
Data taken from the Thomson One Banker database.
7
Personal interview with Herbert Oberhaensli (September 12, 2006; Vevey, Switzerland).
8
Personal interview with Jean-Daniel Luthi (September 21, 2005; Vevey, Switzerland).
9
Personal interview with Tom Coley (October 17, 2005; Vevey, Switzerland).
6
97
Nestlé’s seven strategic business units are the driving forces behind the clusters and,
more generally, behind product development and consumer-oriented renovation and
innovation. Contrary to geographical zones that are operationally responsible for their
businesses, and have clearly set annual profit targets, strategic business units are free
from such short-term targets and thus free to fully concentrate on sustainable longterm development. They develop global business strategies for their respective
categories in which they describe how the product segments should evolve over the
next three to five years, what innovations are required, and how much of the portfolio
should be renovated. In close cooperation with the markets and R&D, the strategic
business units lead Nestlé's innovation process and ensure cooperation and
communication between the company's disparate units.10
The effects of Nestlé's efforts on the expansion of the existing product portfolio and
increases of the company's innovative capacity are well reflected in the growth
corridor. Compared to the period between 1997 and 2003 Nestlé was able to increase
its sales growth rate and boost the total return to shareholders. From previously 4.0%,
average annual sale growth rose to 5.2% in the period after 2003, while return to
shareholders' increased form 16.1% to 17.5%.
8.2.5. Achieving Smart Growth
In sum, the analysis of Nestlé's growth path points to three characteristics important
to enable growth within the boundaries set by the firm's CGR and SGR. First, smart
growers set long-term targets. As in the example of Nestlé, a long-term orientation
prevents to maximize growth in the short run, at the expense of the firm's long term
profitability.
Second, those companies do not only focus on growth, however, constantly work on
improving the firm's efficiency. As a result, those firms are able to continually
increase their SGR. Brabeck's efforts relating to efficiency increases are well
reflected in the growth corridor. In the period between 1998 and 2003 when most of
the cost-reduction programs targeted at improvements of the firm's operational
efficiency were underway the SGR rose from 11% to an average of 12.9%.
Third, the funds generated by increasing operational efficiency are used to further
innovation and thus ultimately drive growth. By investing into high-growth markets
those firms can continually increase their growth rates and maintain them above the
level of the CGR. Looking at the period after 2003 reflects Nestlé's success in
10
Personal interview with Tom Coley (October 17, 2005; Vevey, Switzerland).
98
continually increasing its sales. Albeit a decrease of the CGR to 2.5%, Nestlé's sales
growth rate averaged 5.2% in the period between 2003 and 2007. While it had
slightly decreased in the period between 1997 and 2003 when Brabeck's main effort
was to increase the company's efficiency, it had recovered quickly thereafter.
The interplay between these three factors enables smart growers to gradually shift
their growth corridors to higher levels. Rather than maximizing growth in the short
run and thereby depleting financial resources, those companies incrementally
improve their capacity to grow (Raisch & von Krogh, 2007).
99
THE GROWTH CORRIDOR:
PERFORMANCE IMPLICATIONS OF GROWTH
OUTSIDE THE CORRIDOR
Growth and Firm Performance:
Theoretical Foundations for a Multi-Perspective
Model of Optimum Firm Growth
Theoretical
Background
A Multi-Perspective Model of
Optimum Firm Growth
The Corridor of Optimum
Firm Growth
The Market-Based
Perspective
Performance
Performance
Implications
Implications
Low
Low
Maximum Threshold
Maximum Threshold
The Resource-Based
Perspective
High
High
Minimum
Threshold
Minimum
Threshold
The Financial
Perspective
Low
Low
100
9. Excessive Growth, Cash-Starved, and Growth Laggards:
Performance Implications of Growth Outside the Corridor
More than 75% of the firms in this study's sample failed to grow within the limits of
the growth corridor. These companies may be stuck in one of three unfavorable
situations. First, their sales growth rate may exceed their financial limits. Second,
they may lack the financial muscle to grow with the market. Third, they may fail to
invest their resources into profitable growth trajectories, which leads to growth below
the competitive growth rate. In order to illustrate each of these situations, I have
chosen three different European companies and will retrace their growth path over the
past decade. I will describe how a firm may get trapped in the different positions
outside the growth corridor and reveal the consequences for firm performance.
9.1. Excessive Growth
Companies experiencing excessive growth successfully outperform their competitors
in terms of sales growth, however, do so at the expense of their financial soundness.
Those companies experience many of the negative performance implications
associated with high growth levels, including a momentous upsurge in costs arising
from increasing managerial complexities, for example (Covin & Slevin, 1997).
Excessive growth often leads to failure or even bankruptcy, as witnessed in the
downfalls of firms such as Swissair, Enron and WorldCom (Markman & Gartner,
2002; Slater, 1980; Probst & Raisch, 2005).
9.1.1. Vodafone
Vodafone Group plc, the world-leading mobile telecom company, provides an
example of a firm that has gone through excessive growth in the past decade. In 1997,
Christopher Gent became Vodafone's CEO. During his leadership, Vodafone's sales
growth rate reached an average of 65.4% per year. This figure exceeded its annual
competitive growth rate of 13.3%, however, was also well above the firm's
sustainable growth rate, which averaged 38.3% per year.
During Gent's leadership, the company had pursued a strategy of largely external
growth. Between 1999 and 2003, Vodafone acquired competitors in its domestic as
well as overseas markets, including companies such as AirTouch Communications in
the U.S., Germany's largest network provider, Mannesmann AG, and J-Phone
Communications, Japan's leading mobile operator. This acquisition spree resulted in
the formation of a global conglomerate with operations spread across 28 countries
around the world (Mohanty, 2004). At the same time, however, it left Vodafone with
101
empty war chests. While revenues soared, the company's net income dropped from
£364 million in 1997 to a net loss of £9.8 billion in 2001.
In 2003, Arun Sarin was appointed as Vodafone's new CEO. By that time, the
company's sustainable growth rate had turned negative (-13.9%), and had sunk well
below the firm's competitive growth rate of 11.1%. Sarin was criticized for
Vodafone's overpayment for many of its past acquisitions. A write-off of £28 billion
in 2006 proved skeptical analysts right as it made it obvious that the company was in
a delicate strategic position, requiring major organizational restructurings. Sarin was
compelled to prove that Vodafone could earn returns on the investments and
acquisitions it had made (Vasanthi, 2006). Improving the firm's efficiency and
reducing costs was thus Sarin's major objective when he assumed his position as
CEO. However, this was not the only challenge he faced. In order to be able to
refinance the past acquisitions as well as keep its sales growth above its competitive
growth rate, he was also forced to find new ways of delivering strong revenue
growth.
9.1.2. Stabilizing Operations
Shortly after his appointment, Sarin announced major restructurings to consolidate
the company's far-flung operations. In 2003, he launched the "One Vodafone"
program, aimed at merging activities in different countries and increasing the firm's
operational efficiency by deriving the benefits of scale. The program included
activities such as the harmonization of branding, the sharing of best practices, and the
development of a platform for common purchasing. Additionally, Sarin focused on
buying stakes in emerging markets to boost Vodafone's growth prospects. Between
2003 and 2005, he increased the company's presence in countries where mobile
phone penetration was low, such as, the Czech Republic, Romania, India and Turkey
(Moganty, 2006).
The restructurings, however, did not lead to a major improvement in Vodafone's
ailing profitability. While the group's sales growth rate was still above that of its
competitors, Sarin had not yet managed to return to smart growth by raising the
company's sustainable growth rate.
In 2006, Sarin announced further plans to restructure Vodafone's operations, reacting
to ever-decreasing share prices. By dividing the company into three parts, he aimed at
a better integration of Vodafone's different businesses, tried to leverage economies of
scale and sought increases in the firm's efficiency. The first of these newly created
102
units included the European markets and primarily focused on cost-cutting. The
second unit consisted of emerging markets and concentrated on increasing the
company's revenue growth. The third unit included new businesses and innovations;
it was aimed at developing the technological foundations for Vodafone's future
operations. Sarin commented on this restructuring as follows: "by creating three new
business units, and with an increased focus on costs, we are reflecting the different
approaches that will be required to continue to succeed, both in terms of our existing
operations and in capturing new revenue streams for the future" (Vasanthi, 2006).
9.1.3. Future Prospects
Relating these recent initiatives to the growth corridor reveals valuable insights on the
company's strategy and future prospects. Compared to the period between 1997 and
2003, Vodafone's sales growth rate has declined to a more sustainable level of 14.9%,
thereby still exceeding the company's competitive growth rate of 11.1%. However,
although the company has increasingly worked on ameliorating its cash position, the
sales growth level has remained far above the sustainable growth rate. Further, the
sustainable growth rate, which had turned negative and amounted to -13.9%, had
sagged below Vodafone's competitive growth rate, bearing an additional challenge to
the group's ability to return to smart growth.
The latest strategic changes initiated by Vodafone may enable the group to improve
its position in the growth corridor. Much of Vodafone's recent, growth-directed
activities have been focused on establishing a basis for organic revenue increases.
This focus on internal as opposed to acquisitive growth may further support
Vodafone's path back to moderate growth within the firm's financial limits. Further,
Vodafone has consistently been working on the expansion of its innovative activities,
creating a basis for future success. In sum, those recent activities may enable
Vodafone to boost its sustainable growth rate, while maintaining revenue growth
above the competitive growth rate. The 2007 figures reflect movement in the right
direction. Vodafone's profits have begun to recover, while its revenue growth has
remained above that of its competitors.
103
60%
2004-2007:
Ailing Profitability
65.4%
43.7%
40%
38.3%
20%
13.3%
Sales Growth Rate
11.1%
CGR
Return to
Shareholders
6.8%
0%
-20%
14.9%
-13.9%
1997-2003:
Excessive External Growth
‘97
‘99
‘01
‘03
‘05
SGR
‘07
Figure 9.1: Vodafone's Growth Corridor
9.2. Cash-Starved
More than 35% of the companies in the sample lacked the financial strength to keep
pace with their competitors. The average return to shareholders of those companies
was as little as 6.5% per year, including well-known firms such as Eastman Kodak
and Walt Disney. Since those companies do not have a corridor of growth, they have
to choose between two suboptimal strategies. Either they grow with the market,
thereby risking their financial soundness, or they decide to keep their growth rate
within their financial means, thereby continuously losing market share to
competition.
9.2.1. Allianz
Allianz AG, the world's largest property and casualty insurer in terms of premium
income, and the third-largest European life insurer, provides an example of a
company which has been in a cash-starved position. Until 2000, Allianz had been
among the most successful insurance companies worldwide. In its home country,
Germany, the group profited from strong distribution power, brand recognition, a rich
client base, and high policy retention (Remmers & Walter, 2004). Further, it had been
continuously increasing its foreign operations, acquiring insurers in the UK, U.S., and
the Asia-Pacific region. Possessing considerable cash reserves, those acquisitions
only marginally strained the firm's financial reserves. Until 2001, Allianz's
competitive growth rate, sustainable growth rate, and actual sales growth rate were on
similar levels, around 12%.
104
9.2.2. From Smart Growth to Cash-Starved
In April 2001, Allianz announced the acquisition of Dresdner Bank AG, Germany's
second-largest bank. The merger created a financial giant with combined revenues of
€92.2 billion and an increase in total employees by over 50%11. Allianz sought to
create considerable synergies between the two companies. However, the competitive
environment within which the newly-created group operated was deteriorating. The
stock market bubble had burst, interest rates declined, and real economic activity
suffered, especially in the banking and securities industry (Remmers & Walter,
2004). Both Allianz's insurance business and Dresdner's banking business suffered
severely. In addition to these market-related problems, internal problems emerged.
The cost reductions from synergies were not as expected and sales growth stagnated,
despite the acquisition of Dresdner. From 2001, Allianz's share price declined and the
group ended the fiscal year 2002 with a net loss of €1.17 billion. Between 2001 and
2003, Allianz's sustainable growth rate had turned negative, while the competitive
growth rate had increased to over 21.2%, well above Allianz's average sales growth
during this period of 5.9%.
9.2.3. Earning the Right to Grow
In 2003, Allianz reacted to its ailing profitability and launched the cost reduction
program "Turnaround 2003". It reduced overhead costs, eliminated jobs and made an
effort to further the integration of Dresdner Bank. The group also eliminated
duplications and centralized its marketing and IT functions (Remmers & Walter,
2004). These measures brought about a considerable effect. By 2004, the SGR had
turned upward and approached 12.3%, slightly above the group's CGR of 10.2%.
Allianz had managed to reclaim its corridor of growth.
Although Allianz had successfully increased its operational efficiency, the firm's
sales growth rate of 3.5% lagged behind its competition. As part of the "3+One"
program, which was initially aimed at strengthening operating profitability, Allianz
began to increase its focus on improving revenue growth. Allianz continued to
increase its presence in growth markets such as China, Russia and India as well as
seeking to systematically explore new areas for future growth. In 2006, Allianz was
the second-largest insurer in CEE, Russia's third-largest insurer, India's secondlargest private insurer, and among the top five international insurers in China12.
Further, Allianz started to tap into its potential for cross-selling in order to generate
11
12
Data taken from the Thomson One Banker Database.
www.allianz.com
105
additional funds. For example, Allianz offers an integrated solution in the home-loan
business that covers the group's product range - from financing to insurance. Lastly,
Allianz consistently works on improving its customer focus. To tap growth
opportunities in the savings market, Allianz has increased its direct customer access
and has become more efficient in its product targeting (Remmers & Walter, 2004).
Cash-Starved
30%
25.9%
15%
0%
21.2%
12.3%
13.0%
10.8%
5.9%
11.2%
10.2%
-0.3%
3.5%
SGR
Return to
Shareholders
CGR
Sales Growth Rate
-15%
-23.9%
-30%
Smart Growth
‘96
‘98
Growth Laggard
‘00
‘02
‘04
‘06 ‘07
Figure 9.2: Allianz's Growth Corridor
9.3. Growth Laggards
In contrast to cash-starved companies, growth laggards possess the financial strength
to grow with the market, reflected by a SGR above the CGR. However, those
companies do not manage to tap their potential, and their sales fall behind the
competition, thereby leading to a continuous erosion of their market positions.
Around 18% of the companies in the sample belonged to this group, among them
Colgate-Palmolive, Ford, and Black & Decker. These companies' inability to grow is
neither due to a lack of market potential, nor to a lack of financial means. Rather,
those companies are deadlocked in old routines and are unable to renew themselves, a
phenomenon business research refers to as "success breeds failure" (Raisch & von
Krogh, 2007). To escape this situation, large-scale innovation initiatives and a
renewal of existing business models are often required.
9.3.1. Renault
Renault SA, a French automobile producer, provides an example of a company that
has successfully returned to smart growth after a period of lagging behind the
106
competition. Between 1996 and 2001, Renault's average revenue growth was
negative, and the company continuously lost market share to its competitors. Despite
its financial strength, reflected in a sustainable growth rate of 5.8%, Renault did not
manage to boost its sales. Averaging -1.6%, Renault’s sales growth rate was well
below the competitive growth rate of 4.7%. Renault's difficulties during this period
have largely been ascribed to the fact that the company had been government-run and
was only privatized at the end of 1996. In the subsequent chapter, I will retrace
Renault's growth path over the last decade, to reveal how the company has managed
to renew itself and turn from a growth laggard to a smart grower.
9.3.2. Reviving Growth
Renault's fortunes began to change in 1999, after its merger with Nissan. At that time,
Renault launched a range of initiatives to generate benefits through cost savings and
growth. For example, it decreased the number of employees, closed assembly plants,
reduced the number of suppliers and shortened time-to-market (Ananthi & John,
2007). Most importantly, however, Renault pursued in-depth changes in its habits,
organization, and management processes to live up to both the company's increased
size and its newly created international scope. For example, English was chosen as
the alliance's new official language. International training programs were conducted
and human resource structures changed so as to facilitate transfers and promote staff
member exchange between Renault and Nissan. Not least, the group made major
changes in its performance appraisal system and compensation schemes. These
changes were designed to incorporate long-term objectives and promote the firm's
young executives with strong potential (Som, 2004). The combined outcome of these
initiatives was impressive. From a net loss of €800 million in 1996, Renault's income
had increased to €1.9 billion in 2002. During the same period, the average annual
sustainable growth rate rose from 5.8% to 14.3%.
9.3.3. Future Prospects
Once the company had successfully renewed itself, transforming from the onceFrench firm into a bilingual, internationally reputed company, it faced the challenge
of promoting sustainable growth. To boost its revenues, the company worked on
increasing its innovative capacity. For example, Renault launched a scheme to
incorporate innovative ideas from its employees in its automobile division. Further,
product innovation was accelerated by reducing the number of main platforms and
promoting their common use for different car models. Renault's strategy of profitable
growth made an impact. By 2007, the group's revenues had reached €59.5 billion,
equalling nearly double its 2001 sales. The average annual growth between 2002 and
107
2007 amounted to 11.3%, exceeding Renault's competitive growth rate of 10.2% over
the same period.
By initiating fundamental changes in Renault's culture and an increased focus on
market-oriented product innovation, the auto maker has successfully returned to
smart growth. Today, Renault deploys a powerful global strategy, with strong sales in
Japan, China, and the U.S., being market leader in Europe and making inroads into
the Indian market.
20%
1996-2001:
Growth Laggard
20.1%
17.4%
Return to
Shareholders
16%
14.3%
12%
11.3%
SGR
Sales Growth Rate
10.2%
CGR
8%
5.8%
4.7%
4%
0%
2002-2007:
Smart Growth
-1.6%
-4%
‘96
‘98
‘00
‘02
Figure 9.3: Renault's Growth Corridor
‘04
‘06 ‘07
108
10. Limitations and Future Research Directions
In terms of future research, there is undoubtedly room to refine and expand the
theoretical and empirical findings I have outlined here. I first of all didn’t consider
potential differences between alternative growth modes and directions. Penrose
(1959: 209), for example, argued that the need for managerial services may be higher
when expanding into new fields than when the growth occurs within the existing
businesses. Mishina et al (2004) stated that the context-dependent nature of human
resources may set lower managerial growth limits for product expansion than for
growth within existing markets. Future research may thus benefit from more finegrained conceptualizations of optimum firm growth.
Second, I didn’t consider the influence that internal and external contingency factors
may exert on firms’ growth thresholds. Prior research found firm growth to be
contingent on factors such as firm age, firm size, environmental conditions, and
industry affiliation (e.g., Delmar, 1997). Industry-specific conditions may, for
example, also affect firms’ growth boundaries. The link between industry conditions
and market growth barriers is therefore quite obvious. Industry characteristics may
also, as shown empirically by Tan and Mahoney (2005), affect the extent to which
firms are constrained by managerial limits to growth. In addition, the industry’s risk
profile affects the cost of capital that, in turn, impacts shareholders' growth
expectations (Mass, 2005). Future research should consider such contingency factors
when further exploring the issue of optimum firm growth.
Third, while I discussed the pace of growth, others suggest that the rhythm of growth
may be important as well. Vermeulen and Barkema (2002) found empirical evidence
that the expansion process’s irregularity (i.e., large expansion peaks and periods of
inactivity as opposed to a rhythmic pace) negatively moderates international
expansion’s effect on profitability. Consequently, firms following an irregular
expansion path may encounter time compression diseconomies sooner than firms
expanding rhythmically. Similarly, Tan (2003) suggests that firms benefit from a
stable growth rate over time. High volatility in yearly growth rates may lead to a
shortage of managerial resources in one period and managerial slack at another – both
affecting firm profitability. Future research should complement the arguments
regarding the long-term optimum pace of growth by investigating short-term
variability’s related effects on firms’ growth rates.
109
Finally, I haven't considered firms’ options to shift their thresholds by taking
appropriate action. Norton (1988), for example, has suggested that firms may be able
to overcome some resource-based limits to firm growth through the use of contractual
organizational forms such as franchising. Shane (1998) proved empirically that
franchising could provide small firms with a way to overcome the agency problems
inherent in selecting and assimilating new managers. Barringer and Jones (2004)
found that rapid-growth firms reduced the managerial capacity problem’s impact
through strategic alliances, the use of cash incentives, and employee empowerment
practices. With regard to the expected growth threshold, Burgsthaler and Eames
(1998), to cite another example, described how firms manage shareholders’ growth
expectations. Future research could investigate how individual firms manage to
actively change the boundaries of their optimum growth.
10.1. Conclusion
Theory and practice suggest that firms need to find a balance between their need for
growth and their limited ability to digest that growth. As this study showed, there are
minimum and maximum boundaries to growth. Building on different theoretical
foundations and the empirical findings of this study, I conceptualized optimum
growth as a dynamic path determined by the firm’s competitive situation and its
human and financial resources.
The growth corridor developed in this study is not a deterministic phenomenon but a
dynamic conceptualization of a firm's growth process whereby the path taken affects
long-term performance. The example of Nestlé reveals organizational and managerial
characteristics important to enable growth within the corridor. Vodafone, Allianz and
Renault, on the other hand, served as examples to provide insights on how firms can
get trapped in unfavorable positions within the corridor. In sum, I hope that the model
of optimum firm growth developed in this study will provide the stimulus for future
theoretical investigations of firms’ growth and prosperity, and that this model will
offer practical implications for managers seeking to chart profitable and sustainable
growth paths.
110
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Curriculum vitae
Flora Ferlic
Personal Data
Date of Birth
Nationality
10th of December 1982
Austrian
Education
04/2005 - 06/2008 University of St. Gallen
Doctoral candidate of business administration with a special
emphasis on “Strategy”.
10/2004 - 03/2005 Karl-Franzens University Graz
Doctoral candidate of business administration with a special
emphasis on "Banking and Finance".
09/2001 - 09/2004 Karl-Franzens University Graz
Candidate for Master in Business Administration.
Special emphasis on "International Management"
"Operations Research".
06/2001
and
Matura with Distinction
09/1993 - 06/2001 Graz International Bilingual School (GIBS)
Senior secondary school.
Practical Experience
since 04/2005
University of St. Gallen
Full time employment
Research assistant at the Institute of Management. Project
collaborator at the "Center for Organizational Excellence".
12/2004 - 04/2005 Karl Franzens University Graz
Half time employment
Research assistant at the Institute of Banking and Finance.
05/2004 - 12/2004 Karl Franzens University Graz
Halftime employment
Project collaborator at the Institute of Banking and Finance.
05/2003 - 09/2004 KPMG Bertl Fattinger & Partner
Part time employment
Accounting, compiling of tax returns and balance sheets.