Determinants of Firm
Competitiveness in Latin
American Emerging Economies:
Evidence from Brazil’s
Auto-parts Industry
Luiz F. Mesquita
Sergio G. Lazzarini
Patrick Cronin
Insper Working Paper
WPE: 089/2007
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Determinants of Firm Competitiveness in Latin American Emerging
Economies: Evidence from Brazil’s Auto-parts Industry
Luiz F. Mesquita*
Assistant Professor of Strategic Management
School of Global Management and Leadership, Arizona State University
4701 West Thunderbird Rd. FAB N130. 85306-4908. Phoenix, AZ.
Phone: 602 543 6126; Fax 602 543 6221
E-mail – [email protected]
Sergio G. Lazzarini
Assistant Professor of Organization and Strategy
Ibmec São Paulo
R. Maestro Cardim 1170. 01323-001 São Paulo, SP Brazil
Phone: 55-11-4504-2300; Fax: 55-11-4504-2315
E-mail – [email protected].
Patrick Cronin
Assistant Professor of International Management
Thunderbird Garvin Graduate School of International Management
15249 N. 59th Avenue. 85306-6000. Glendale, AZ.
Phone / Fax 602-978-7000
E-mail – [email protected]
November 2005
* Corresponding author
Authors thankfully acknowledge Patricia Friedrich and seminar participants at Arizona State
University for suggestions on earlier version. We are also thankful to Fabio Wrobel Zausner,
Fernanda Taís Nagamatsu, Guilherme de Moraes Attuy, Luciana Shawyuin Liu, Marcelo de
Biazi Goldberg, Michel Tridico Tortelli, Pedro Alberto Puhler and Vanessa Lima Gonsalez
for their research assistance on data collection and analysis, as well as William Mufarej,
Flávio Del Soldato and Vanderlei Bueno from Sindipeças for helping us contacting members.
This research received funds from the CIBER at the Thunderbird-Garvin International School
of Management and institutional support from Sindipeças, Brazil’s auto-parts firms
association, and the Center for Research in Business Strategy at Ibmec São Paulo.
1
Determinants of Firm Competitiveness in Latin American Emerging
Economies: Evidence from Brazil’s Auto-parts Industry
ABSTRACT
We study how intra-firm practices, inter-firm relationships, and institutions influence
the competitiveness of individual companies. We propose that participation in industry
associations allows firms to enhance intra- and inter-firm practices that lead to increased
production efficiencies. Based on survey data and interviews with suppliers in the Brazilian
auto-parts industry, we find that participation in associations encourages companies to work
together and provides them with information and other resources that foster the development
of superior intra-firm practices and inter-firm relationships. For their part, and as expected,
the adoption of firm-level practices and a willingness to develop closer ties with customers
were directly associated with stronger performance at the company level. Our study
highlights the importance of studying the joint impact of intra-firm firm practices and interfirm relationships (both vertical and horizontal) on the competitiveness of firms.
2
Over the last couple of decades, scholars interested in Latin America and emerging
economies in general have devoted increased attention to the study of firm competitiveness
(e.g. Austin, 2002; Carrera, Mesquita, Perkins, & Vassolo, 2003; Fishlow, 2000). In this
literature, and in particular the section concerned with Latin America, firm competitiveness
(which we define as the ability of these entities to successfully compete in a given business
environment - Porter, 1980; 1990) has often been portrayed as a result of factors of the
‘macro-sphere’ environment; such factors include active and flexible government policy
regulation and enforcement, operative institutional structures such as judicial systems,
appropriate country infra-structures such as roads and telecommunication systems (Ferraz,
Kupfer, & Haguenauer, 1995; Porter, 1990; 1998) as well as solid macro economic
foundations and strong bouts of development (e.g. Austin, 2002; Coutinho, 1997; Fishlow,
2000). This focus on macro-sphere factors seems to have resulted from a long history of
macro economic and political instability in Latin America across several decades, and the
clear pattern of effects that such variations have had on the emergence of competitive
national firms (e.g. Carrera et al., 2003; Mesquita, 2003; Porter, 1990).
This emphasis on macro sphere factors, however, tends to obscure and even downplay
variations in the creation of firm competitiveness as a result of micro (i.e. firm) level factors.
As a result, information at the firm level, particularly as it relates to company strategy and
organizational practices, has been in short supply. This uneven view of firm competitiveness
gains particular relevance as many large economies in the region – e.g. Brazil, Chile,
Colombia, and Mexico, to name a few – have entered new periods of economic and political
stability, thus leading firms to enact several new intra-firm and inter-firm managerial
practices with important consequences for their competitiveness (e.g. Coutinho, 1997; Wood
& Caldas, 2002). As such, this study seeks micro-level explanations for the variation in firm
performance in Latin America. The question we seek to answer is: how do intra- and inter-
3
firm practices as well as support from micro-level institutions such as associative
organizations affect firm competitiveness in Latin American emerging economies?
We investigate this question by modeling the interrelationships among intra-firm, interfirm and institutional practices as drivers of firm performance in a given industrial sector.
Looking at firm performance across many companies, within the same sector allows us to
control for a variety of potentially confounding macroeconomic and sector-specific factors.
We specifically integrate three sets of explanatory factors that are likely to explain firm
competitiveness: firm-level resources and capabilities (e.g. hard to imitate capabilities Barney, 1991; Dierickx & Cool, 1989; Peteraf, 1993), inter-firm coordination (e.g. the
coordination of joint action and interdependencies - Gulati & Singh, 1998; Mesquita &
Brush, 2005; Thompson, 1967), and the support of micro-level institutional organizations
(Harrison, 1992; Kogut, 2000; Piore & Sabel, 1984; Porter, 1998; Pyke, 1994; Schmitz,
1995). Specifically, we propose that the strength of the institutional support from associative
organizations (e.g. business associations) positively affects the degree to which firms invest
and possess superior resources and capabilities as well as the degree to which firms
coordinate actions and tasks amongst themselves. These resulting factors, in turn, affect firm
competitiveness in the form of production efficiencies. We test our model through a structural
equation model, based on exclusive survey data from 182 Brazilian auto-parts makers, as
well as interview data from 15 industry executives. Our findings show strong support for our
model of the interrelationships among the three sets of influences on firm performance.
We believe our model and findings bring significant implications for the theoretical
literature and managerial practice for the region and other similar emerging economies. First
we demonstrate that firm-level factors do matter have a strong explanatory power on firm
performance, after controlling for macro sphere explanations to competitiveness; thus, we
call for a balance in studies to focus on firm level factors. Moreover, albeit many Latin
4
American firms seem to have mimicked the adoption (as opposed to sincerely and
wholeheartedly adopting) imported managerial practices such as modern manufacturing
techniques developed in the U.S. and Japan so as to satisfy public opinion expectations
(Wood & Caldas, 2002), we confirm that those firms who seriously implemented such
techniques outperform those who did not. Lastly, interesting from a managerial and public
policy perspective, our qualitative data suggested that large multinational companies are
engaged in more—and more intense—interactions with such institutions compared to their
local counterparts. Lastly, to the extent that many other emerging economies around the
globe have followed similar patterns of economic development, the lessons implied from our
study can be considered of relative significance for their firms as well.
The following section describes our model and hypotheses, derived from the literature.
Subsequent sections describe our methodology, analyses and findings. We conclude with a
detailed account of the implications for theory and practice.
THEORY AND HYPOTHESES
As shown in Figure 1, our model begins by highlighting the effect of institutional support
from associative organizations on three sources of firm competitiveness. Particularly, we
posit that the degree to which firms rely on the institutional support of such associative
organizations (e.g. business associations and trade organizations) positively affects the degree
to which these same firms invest in the acquisition of competitive resources and capabilities,
as well as the degree to which firms within the sector coordinate (vertically and horizontally)
joint activities amongst themselves. Each of these effects is explained in turn.
<< Insert Figure 1 about here >>
Associative organizations and firm investments in competitive resources & capabilities
Associative organizations are those that work to support the collective of firms in a given
industry (e.g. business associations, governmental agencies); their institutional role is said to
5
be that of providing specific services and resources that individual firms often find too costly
to acquire alone. For example, such associative organizations can help firms lower costs and
improve their competitiveness by gathering information on markets and suppliers,
establishing common standards and quality control, and also sponsoring design, marketing
and technology transfer programs for the collective of firms in a given industry (Altenburg &
Meyer-Stamer, 1999; Lane & Bachmann, 1996). Moreover, their institutional value also
spans across social activities, whereby these associations promote formal and informal
gatherings that strengthen the fabric of inter-firm relationships, as well as lobbying activities,
whereby they represent the collective interest in negotiations with larger entities, such as
government agencies or even foreign groups of firms (Harrison, 1992). These functions are
particularly important since many firms are subject to scale limitations to scan their markets,
update their managerial expertise, organize coordinated joint actions with competitors and
even negotiate sector sponsorships from several levels of government (Casaburi, 1999;
Ramos, 2000).
As these associative organizations provide firms in a given industry with such crucial, yet
universal resources and capabilities, individual firms are unfettered to invest their flexible
and generic resources (i.e. capital and managerial time) into highly specialized and
idiosyncratic competitive resources and capabilities (e.g. customer-focused physical assets
and manufacturing-management processes). Looking from an inverse perspective, firms
which are unable to tap into the common-to-all institutional resources and capabilities
provided by associative organizations often find their capital and managerial time are either
spread too thin, across all their needs for resources and capabilities or at best are kept in their
flexible and generic form (i.e. capital reserves) to provide liquidity for times of emergencies
(Altenburg & Meyer-Stamer, 1999; Canina, Enz, & Harrison, 2005). In sum, we expect that
the more firms rely on the institutional support of associative entities for the provision of
6
collective services and resources, the more these firms invest in the acquisition of competitive
resources and capabilities.
As we deal with manufacturing firms, we define the ‘development of specialized sources
of competitive advantage’, mentioned above, as the acquisition of manufacturing-related
competitive capabilities. Such specialized resources and capabilities are exemplified by
investments in total quality management, lean manufacturing and the Toyota Production
System (Hopp & Spearman, 2000; Ohno, 1988; Womack, Jones, & Roos, 1990) as well as
other practices such as work-teams (Nishiguchi, 1994; Ohno, 1988), and the incorporation of
new related technologies.1 Our hypothesis is:
H1a: The institutional support from associative organizations positively relates to
firms’ investments in new competitive resources & capabilities
In addition to the acquisition of competitive resources and capabilities, we also highlight
that the institutional support of associative organizations affects the ability of firms to
establish coordinated efforts with other firms within the industry. In this regard, a growing
body of research on inter-firm networking and industrial districts/clusters detail the
interrelationship between our constructs. For their part, network researchers such as Lane and
Bachmann (1996) focus on the institutional framework in which a firm’s operations take
place. They highlight that networked firms are able to cooperate when they develop not only
‘process-based trust’ (that is, trust earned from repeated interactions) but also ‘institutionalbased’ trust (i.e. the trust among firms that is enabled by commonly accepted institutions).
Institutional trust, as Lane and Bachman highlight, enables firms networked within a
particular region to reduce the risk of opportunism in coordinated joint activities as it creates
commonly understood standards for firm behavior. They emphasize that business
1
For more details on these practices, see the extensive reviews presented in the special issues at the Academy of
Management Journal in 1996 (Vol. 39, No. 4) and Industrial Relations in 1996 (Vol. 35, No. 3).
7
associations are particularly important for their role in promoting and enforcing such
behavioral standards.2
In a similar venue, using Granovetter’s (1985) concept of ‘social embeddedness,’ scholars
researching the phenomenon of industrial networks stress the importance of the institutional
environment in which coordinated activities take place (Coutinho & Ferraz, 1994; Harrison,
1992; Piore & Sabel, 1984; Porter, 1990; Pyke, 1994; Schmitz, 1995). The ability of firm
owners to trust (or mistrust) each other is the result of experiences built up over time and
close interactions. To the extent that the socio-cultural and political landscapes provided by
an associative organization bring firms together, for example through shared memberships
and meetings, then these associative organizations become institutionalized, and as a result
promote cooperation among firms, based on earned personal friendships and trust (Harrison,
1992). Thus, for example, by belonging to a common business association, and recurrently
gathering informally for common purposes, firms are more likely to create opportunities for
shared activities with peer firms (i.e. those which produce similar products) and also with
buyers and suppliers (i.e. those which are linked to the firm in a sequential form, that is, in a
supply chain). Thus, we hypothesize that associative organizations have an indirect influence
on firm performance as they provide the institutional framework within which firms
coordinate joint action, not only horizontally but also vertically in the supply chain.
Specifically, we expect that:
H1b: Institutional support from associative organizations positively relates to vertical
inter-firm coordination.
H1c: Institutional support from associative organizations positively relates to
horizontal inter-firm coordination.
Sources of firm advantage and competitiveness
2
For Lane and Bachmann (1996), the central elements of a country’s institutional structure include the law,
business associations, the financial system, the role of the state in the industry, and the system of general and
8
As firms make investments in competitive resources and capabilities and coordinate joint
actions with their vertical and horizontal partners, we posit that they achieve performance
gains. We explain each of these effects in turn. The effect of competitive resources and
capabilities on performance can be explained through the theoretical lens of the Resource
Based View, or RBV (Barney, 1991; Dierickx & Cool, 1989; Peteraf, 1993), and the dynamic
capabilities approach (Teece, Pisano, & Shuen, 1997). According to RBV scholars, firms
earn an advantage when they acquire and possess capabilities which their competitors are
unable or find it too costly to imitate. Peteraf (1993), for example, explains that a
performance edge over competitors results from resources and capabilities that are rare (i.e.
resources possessed by the firm are not possessed by another), non-imitable (i.e. resources are
not easily replicated), durable (i.e. competition does not erode the value of the capability) and
non-substitutable (i.e. competitors are unable to find alternative resources to obtain the same
results). Teece, Pisano, & Schuen (1997) supplemented this concept by offering the dynamic
capabilities approach; according to them, the characteristics outlined above are found mainly
in those resources and capabilities that are subject to path dependency, that is, those that are
built over time, and thus present time-compression challenges to potential imitators.
Based on the above, and to the extent that the development of the manufacturing
competitive resources and capabilities defined above are subject to extensive path
dependencies and as a result are costly to acquire (Dyer & Nobeoka, 2000; Dyer & Singh,
1998; Ohno, 1988), we submit that those firms making the most investments in the
acquisition of such competitive resources and capabilities will have a competitive advantage
in regards to manufacturing productivity gains:
H2a: Investments in new competitive resources and capabilities positively associates
with firm production efficiency gains.
vocational education.
9
In the past fifteen years, a consensus has emerged that one of the more effective
strategies to boost firm competitiveness lies in collaborative efforts that promote productivity
gains. Companies can increase their individual and collective competitiveness levels by
engaging in both vertical and horizontal collaboration efforts with other firms. These
interactions, normally longer-term and with deeper degrees of closeness, go beyond simple
arms-length interactions between independent companies. Thus, suppliers and customers may
cooperate closely in subcontracting arrangements that allow them to share risks and costs, to
bring together different but complementary core competencies, and to promote mutual
learning (see for example Dyer & Nobeoka, 2000; Kale, Singh, & Perlmutter, 2000; Porter,
1998). At the same time, firms may find it advantageous to cooperate, at least in certain areas,
with firms they normally compete with. As Ahuja (2000) notes, a firm may decide to work
with a competitor to obtain needed assets, to manage its dependence on its partner, or to
maintain its position vis-à-vis the competition.
In a complementary manner, scholars studying networks indicate that performance
benefits accrue to firms pursuing both vertical and horizontal forms of inter-firm cooperation
(Lazzarini, Chaddad, & Cook, 2001). Drawing from Marshall's (1920) idea of
‘agglomeration economies,’ a large literature developed around the concept of ‘industrial
districts’--large numbers of firms linked horizontally or vertically and engaged in cooperative
efforts to boost the competitiveness of individual firms and the entire cluster. Marshall
identified ‘external economies of scale’ which appeared in geographic areas populated by a
critical mass of companies in the same sector. He noted that such companies attracted
suppliers, skilled labor, service providers, capital, infrastructure and other needed factors of
production. As the production and support base deepened--and through the specialization
that this allowed--production costs and prices to the consumer were lowered. Seizing upon
Marshall’s idea of external economies, but adding a crucial distinguishing characteristic,
10
several scholars have emphasized that competitiveness gains of firms arises mostly through
the presence of purposeful cooperative relationships between firms (Harrison, 1992). Typical
forms of cooperation in firms networked in particular regions of the world (e.g. Third Italy,
Silicon Valley) include information exchanges, particularly about markets and technologies,
and the collective provision of various services (Brusco, 1990; Harrison, 1992; Pyke &
Sengenberger, 1990; 1992; Saxenian, 1994b; Saxenian, 1994a; Schmitz, 1995; Schmitz,
1999) and mutual assistant that enable collaborating firms to reduce uncertainty in the supply
of mutual goods as well as keep partners current in regards to new production technologies
(Pyke, 1994). Thus, we expect that:
H2b: Coordination between firms and their partners in a supply chain is positively
associated with firm production efficiency gains.
H2c: Coordination between firms and their peers is positively associated with
production efficiency gains.
METHODOLOGY
We tested these hypotheses by surveying a large sample of parts manufacturers supplying
the auto industry in Brazil. Our approach avoids a recurring weakness of many extant studies
that exclusively rely on qualitative methods that limit the ability to generalize (see for
instance Boyer, Lasserre, & Moreaux, 1998; Doner, McKendrick, & Haggard, 2000). As
described in the methodology section below, our large N study relies heavily on quantitative
methods--complemented with selected interviewing--that allows for more robust conclusions
regarding the processes under study.
We believe this population under study is highly appropriate since these industries have
been the target of several governmental development programs (i.e. Brazil’s industrial
development policies) which include support from government agencies, targeted financing
and government export support (Addis, 1999; Shapiro, 1991). Moreover, the population also
11
has a history of active involvement with strong business associations (such as the
ANFAVEA, Associação Nacional dos Fabricantes de Veículos Automotores, which
represents the sixteen auto manufacturers producing in Brazil, and the Sindipeças, the
Sindicato Nacional da Indústria de Componentes para Veículos Automotores, whose
members contribute with over 90% of revenues of the parts sector in Brazil), a fact which
enables us to study the impact of these agencies on the competitiveness of firms (Addis,
1999). The approach used in selecting this industry is similar to that employed in other sector
and cluster-related research (e.g. Casaburi, 1999; McEvily, 1997; Mesquita & Lazzarini,
2005; Saxenian, 1994a; Schmitz, 1999).
In this research we avoid a singular focus on small regional firms, a method often
employed by early scholars studying patterns of inter-firm collaboration in industrial sectors.
Instead, we included both large and small firms, as well as domestic and multinational ones.
The more recent literature notes that both foreign and large firms (as opposed to national and
small ones) have a role to play in the environmental conditions that affect firm performance,
and therefore, should be included in studies focusing on the determinants of firm
competitiveness (Schmitz & Nadvi, 1999: 1504). As a result, nearly half (45%) of the firms
surveyed were subsidiaries of foreign multinationals. Moreover, firms had a diverse scope as
far as size is concerned. Measured by sales volume in millions of dollars, 7% of them had
sales that were less than US$2.5 million, 25% had sales between $2.5 million and $10
million, 36% had sales between $10 million and $40 million, 22% had sales between $40
million and $200 million, 6% had sales between $200 million and $400 million, while 8%
had sales of more than $400 million.
Research design and data collection
Our survey data collection processes mostly followed prescriptions by Dillman (2000).
We initially developed a questionnaire by identifying construct items used in previous
12
studies. We also obtained the help of other academics and managers to develop items where
the literature was silent, to refine survey wording, and to check the overall validity of
questions vis-à-vis the industry environment. We compiled a mailing list of approximately
500 firms, using a list of Sindipeças members. As noted above, the Sindipeças’ member
directory is representative of the population as a whole as it covers over 95% of the parts
made in Brazil (Sindipeças, 2005). Through Sindipeças, we identified the manager (general
or division manager) who would be most knowledgeable about his firm’s relationships with
customers in this industry group, as well as with production related information. The
response rate was just above 33% (182 responses).
In the questionnaire, we asked respondents about the prior three years of their firm’s
activities to avoid biased responses due to specific aberrant experiences. We also assessed
whether non-respondents could have produced any significant biases, by comparing early
with late respondents using a t-test (see Armstrong & Overton, 1977 for similar treatment).
We found no significant differences. In the survey we asked respondents to assess vertical
and horizontal relationships and performance characteristics. In the former case, we asked
about “this” customer, which we defined as “a customer the respondent was most
knowledgeable about.”3 To measure the nature of the company’s horizontal relations, we also
asked the respondent to identify a “peer”, which we defined as “a firm which currently
supplies “this” customer with a product similar or complementary to your product, and with
whom you interact frequently (e.g. to exchange ideas or business opportunities)”. We also
asked questions related to each firm’s relationships with Sindipeças. Respondents were
asked to list other important institutions for their firm and the role of these was explored more
fully in semi-structured interviews with a subset of respondents.
3
In case the supplier serviced multiple facilities of “THIS” customer and/or serviced “THIS” customer with
multiple products, the respondent was to answer the questions relative to the facility and product-family that was
most representative for his business. If the respondent’s company had multiple divisions, we asked him to
respond to the questionnaire with respect to the division in which he was a manager.
13
Variables for the survey questionnaire:
Our theoretical model establishes the performance outcomes from three sets of
explanatory variables on performance levels: intra-firm practices and investments, inter-firm
coordination and institutional support from collective associations. Each set was
operationalized as follows:
[Insert Table 1 about here]
Institutional support from associative organizations: We gauge the respondents’
assessments of the effectiveness of their business association (i.e. Sindipeças) in helping
firms organize collective actions. In the survey we specifically asked for each respondent’s
assessment of Sindipeças. Sindipeças was singled out for special focus because both the
literature and preliminary work on the survey confirmed that this organization is the
dominant institution for parts firms (Addis, 1999; Marx, 1993).4 We measured the
effectiveness of Sindipeças by establishing a multi-dimensional construct, where the
respondent indicated in a 5-point Likert scale the degree to which she agreed with the
following statements. “Sindipeças is effective for…”: a) organize and supply technical
training to its associates; b) develop economic/technical studies and disseminate the results of
such studies to its members; c) hold social events to gather members; d) hold ‘collective
representation’ responsibilities in negotiations with the government.
Space restrictions in the survey limited our ability to more fully explore the role of other
institutions and how they might be contributing to firm performance. With this in mind, we
conducted a series of fifteen interviews, eleven with randomly chosen firms and four with
officials from four institutions that survey participants identified more often as ones with
which their companies had prior contact (See Table 2).5 While many of the interview
4
The survey did ask respondents to list other institutions that their firms had contact with. These then helped
guide our selection of institutional interview targets.
5
The eleven companies were chosen in a manner to ensure a sample of views across a number of dimensions
that we thought might influence the amount and nature of firm contacts with sectoral institutions: multinational
14
questions focused on firm level interactions with institutions, some time was also devoted to
exploring inter-firm relationships. Because of the small interview sample size, the results of
these consultations can only be thought of as suggestive. Nevertheless, they offer a much
richer understanding of the ways in which parts firms have chosen--or not--to interact with
institutions and with each other. As such, the interview data serve as an important
complement to the statistical results presented below.
Investments in Competitive Resources & Capabilities. We adopted a multi-item scale
approach to measure the degree to which firms had “invested” or “participated” in any of a
series of knowledge acquisition programs listed. Based on literature searches (e.g. Liker,
1996; Ohno, 1988) and interviews with managers, we inventoried several programs
emphasizing the training of people- and team- oriented capabilities, such as kaizen (i.e.
constant improvement techniques), lot-size optimization, machinery and plant set-up
techniques as well as total quality management. We used a 5-point Likert scale (1 = “not at
all”; 5 = “to a large degree). Alpha resulted in 0.82.
Vertical Coordination and Horizontal Coordination: as defined previously, coordination
relates to the actions (as opposed to the commitments) of parties in fostering joint activities.
We measured coordination as a multidimensional construct, where each item was measured
using a 5-point Likert scale. Specifically, we gauge the extent to which parties engage in
activities such as information exchange, mutual assistance or any other form of coordinated
action, in areas such as: a) marketing and exports related activities; b) new product and
process development; c) sharing of equipment and other resources; d) joint purchase of
inputs; e) joint representation at governmental agencies. Cronbach’s alpha for coordination
with “THIS” customer was 0.721, whereas coordination with “peer” was 0.711.
firms (5 companies) v. national firms (6); large firms (6) v. small firms (5); first tier suppliers (8) v. second tier
suppliers (3).
15
Production efficiency gains. To model production efficiency gains, we turned to research
done by scholars working closely with the implementation of such production systems for
measures (Boyer, Leong, Ward, & Krajewski, 1997; De Meyer & Ferdows, 1985; Ferdows,
Miller, Nakane, & Vollmann, 1986; Miller & Vollmann, 1884; Ward, Duray, Leong, & Sum,
1995). Indicators such as manufacturing lead time and delivering goods in a timely manner
are measures which capture such performance dimensions. Because we are interested in the
impact of the inter-firm networks (i.e. inter-firm collaboration and the support from
institutions) on the enhancement of performance of the firms, we measured a specific
dimension of ‘performance enhancement’ in these two aspects of production efficiency. More
specifically, we asked respondents to indicate their performance today relative to what it was
three years ago, using a Likert scale of one to five: one = substantially worse; two =
somewhat worse; 3 = the same; 4 = somewhat better; 5 = substantially better. We measured
manufacturing lead time (the time it takes from the point an order arrives at the shop floor to
the moment the product is shipped out of the factory), inventory turns (inventory turns
necessary to support 12 month sales) and timely delivery (percentage of goods delivered
within the time promised). These operational measures have not only been useful in
operations management research, but also in strategy research as well (e.g. Dyer & Nobeoka,
2000; Kotabe, Martin, & Domoto, 2003). We standardized the measures.
Control variables: Although we are interested in developing a parsimonious model, other
alternative factors may also influence firms’ entry into global markets. Thus, we include
control variables to ensure results are not unjustifiably influenced by these factors. First, we
control for the possible effect of ‘formal contracts’. Formal contracting has often been
referred to as a traditional way of governing inter-firm relationships (Williamson, 1985).
Thus, we aimed at identifying the extent to which firms perform better not because they
coordinate actions with peers and customers, but because they are required by contracting
16
clauses. We asked respondents to indicate whether each clause ‘exists’ in their current
contract, and if so, the probability the manager perceives such a clause would be enforced in
case of contractual breach. Based on interviews with managers, we identified whether the
contracts between the respondent’s firm and its customers involved any of the following
specifications: a) contract duration in months; b) fee the firm would have to pay in case of
contract breach; c) exclusivity clauses (i.e. the firm is the exclusive supplier); d) minimum
purchase clauses; e) fees in case firm underperforms in dimensions such as product quality
and or delays in delivery.
Second, we control for firm size. Larger firms may possess a superior pool of resources
and the capacity as well as the scale necessary to invest in competitive resources and
capabilities regardless of the institutional support they receive from associative bodies; as a
consequence, they may have the ability to develop productivity gains on their own, regardless
of whether they promote cooperative efforts with peers and customer firms. We measure firm
size as the log of 3-year average yearly revenues. A last possible confounding effect relates
the competitive pressure of the market place. If a firm faces stiff competition in its domestic
market segment, is more likely to invest in competitive resources and capabilities regardless
of institutional support from associative organizations as well as the extent to which they
promote cooperative arrangements with peers and customers.
ANALYSES AND RESULTS
Building the structural equation modeling
We performed a two-step structural equation model analysis; in the first step we specified
the relationship between latent and observed variables through a measurement model and in
the second step we specified the paths among constructs of interests through a structural
model. The measurement model allows for a confirmatory factor analysis and demonstration
of an acceptable fit to the data (Anderson & Gerbing, 1988; Bentler, 1989b; Joreskog &
17
Sorbom, 1989). Here, we assessed multi-item reliability – or whether responses of related
items are stable across the sample – by computing Cronbach’s alpha. As demonstrated in
Table 1, all values were above the 0.70 point, which as a rule of thumb indicates these
estimations are reliable (Nunnally, 1978). We also assessed convergent validity – or whether
indicator variables measure the same underlying construct (i.e. items correlate rather highly
with one another) – by computing t-tests for factor loadings (Anderson & Gerbing, 1988). We
kept indicators for which factor loadings were greater than twice their standard errors (all
items presented in Table 1 surpass the recommended level). Lastly, we assessed discriminant
validity, or whether closely related constructs are distinct (i.e. indicator variables across
constructs clearly measure different constructs). We used chi-square difference tests for
constrained and unconstrained models; the constrained model sets the correlation between
two constructs equal to one, and a significantly lower chi-square value for the unconstrained
model supports the discriminant validity criterion. As values in Table 2 indicate, all
constructs exhibit satisfactory discriminant validity. Table 3 performs an exploratory analysis
of the relationships among variables through correlation coefficients. These values are highly
consistent with the results obtained in our structural equation model.
In the path analysis sequence of our structural equation model (see Figure 1), we specified
given causal relationships as demonstrated in our theoretical model, and assessed the overall
goodness of fit. To test the hypotheses developed earlier, we used the maximum likelihood
estimation procedure, often preferred in management and social sciences studies (Ping,
1996)6. The results shown in Table 4 include the path coefficients and t-values shown in
parentheses corresponding to each hypothesized relationship, and five standard fit indices
reflecting the degree of overall fit between the actual and predicted covariances among
variables of a model. The first index, chi-square statistic (χ2), tests the correspondence
6
We used the CALIS software (SAS); CALIS explicitly models the measurement error of the indicators, a
necessary feature for our computations, as we rely a great deal on psychometric measurement instruments.
18
between the model and the underlying data. A non significant χ2 value is desirable and
indicates that the model is not significantly different from the underlying data. Because the
chi-square test is frequently not valid in applied settings, it has been recommended that it be
treated as a general goodness of fit index, but not as a statistical test in the strictest sense
(Joreskog & Sorbom, 1989).
Given the above, we supplement the chi-square test with four other goodness of fit indices,
which are known to reveal a relatively good fit even when the chi-square test suggests
rejection of the model (Hatcher, 1998: 191): the goodness of fit index (GFI), the adjusted
goodness of fit index (AGFI), the Non-normed fit index (NNFI), and the comparative fit
index (CFI). With the exception of the NNFI index, all indices range from zero to 1.00 (being
that the NNFI index may assume values below zero and above 1). A commonly accepted rule
of thumb is that fit indices should be greater than 0.90 (Hatcher, 1998)7. Our first trial at
fitting the model resulted in a highly significant chi-square. We conducted a search to
identify poor fitting constructs within the model (Joreskog & Sorbom, 1989). We found none.
Table 5 presents the correlation matrix, whereas Table 4 presents results for the path
analysis with latent variables.
[Insert tables 2, 3, 4 and 5 about here]
Fit indices are presented in Table 4, column C. Although the chi-square statistic was
significant, χ2 (80, N=182) = 103.85, based on recommendations by James, Mulaik & Brett
(1992) we take this statistic with other fit indices to make an inference about model
7
The GFI indicates the relative amount of variance and covariance jointly explained by the model, whereas the
AGFI is similar to the GFI measure but adjusts for the number of degrees of freedom in the model. The NNFI
(Bentler & Bonnett, 1980) is defined as “the percentage of observed-measure covariation explained by a given
measurement or structural model … that solely accounts for the observed measure variances” (Anderson &
Gerbing, 1988: 421). The NNFI is often viewed as a superior variation of the Bentler & Bonnett’s (1980)
normed fit index (NFI) since it has been shown to be more robust in reflecting model fit regardless of sample
size (Anderson & Gerbing, 1988; Bentler, 1989a). The last index, Bentler’s (1989b) CFI, is similar to the NNFI
in that it provides an accurate assessment of fit regardless of sample size. The CFI tends to be more precise than
the NNIF however in describing comparative model fit as it corrects for small sample size by subtracting the
degrees of freedom from their corresponding χ2 values (Bentler, 1989b).
19
acceptance. Our analysis of all other fit indices (i.e. GFI, AGFI, CFI and NNFI) indicate that
there is in fact a good fit for the model, as they are above the 0.9 benchmark (see Table 4).
We thus accept the model.
Our findings are as follows. Hypothesis 1a – which establishes that the institutional
support from associative organizations positively associate with investments in competitive
resources and capabilities – is supported. The path coefficient is positive (PF1F2 = 0.190) and
statistically significant (t-value = 2.67; p < 0.05). Hypotheses 1b and 1c, which respectively
establish that vertical inter-firm coordination (i.e. between two firms sequentially linked in a
value chain) and horizontal inter-firm coordination (i.e. between two peer firms) result from
the institutional support of associative organizations are supported. The path coefficients are
positive and statistically significant (i.e. respectively PF1F3 = 0.3622; t-value = 4.930; pvalue < 0.001, whereas for horizontal coordination PF1F4 = 0.210; t-value = 3.091; p-value <
0.01). Hypothesis 2a is also supported. This hypothesis establishes that the more firms invest
in competitive resources and capabilities, the more they will accrue gains in production
efficiencies. The path coefficient is positive and statistically significant (i.e. PF2F5 = 0.176;
t-value = 2.61; p-value < 0.01). Hypothesis 2b is supported, thus suggesting that vertical
cooperation positively affects production performance. The path coefficient is positive and
statistically significant (PF2F6 = 0.215; t-value = 3.15; p-value < 0.001). Hypothesis 2c,
however, is not supported. The path coefficient is positive but statistically insignificant, thus
failing to provide support to our claim that horizontal collaboration with a peer firm yields
production efficiency gains. A Wald test (Bentler, 1989a) suggested that it was possible to
delete this path coefficient, and thus we dropped it from the model.
Qualitative analysis
In addition to the statistical analyses above, we also performed a qualitative analysis of the
relationships established between the firms and several institutions in the market place. Our
20
interviews helped to confirm and elaborate on the relationship between institutions and firm
performance. Almost uniformly, firm managers believed that the institutions they interacted
with have had a positive impact on both firm and sector competitiveness. Generalizing across
the interview data, the two most prominent links between institutional support and increased
firm competitiveness were the provision of specific services and institutions serving as a
mechanism for collective action vis-à-vis the government. Among services, virtually all firms
singled out the role of Sindipeças as a provider of high quality market trend information.
Those firms which took advantage of this data—and not all do who are Sindipeças
members—found it an invaluable tool for forecasting production.
Equally important for most firms, particularly the smaller and national ones, was
Sindipeças as the sector’s instrument for collective action. This has been important for two
reasons. First, with its long history of state-directed development, the Brazilian government
continues to play a major determining role in the automotive sector. Secondly, the parts
sector finds itself in a structurally weak position vis-à-vis major input suppliers and its
customers. In both cases (steel mills and original equipment manufacturers, respectively),
these sectors are oligopolies that periodically squeeze parts companies from both directions.
State intervention, for instance through price controls on steel or taxation levels, can play a
crucial role in determining the health of the parts sector. Given a traditionally interventionist
state and a structurally weak position, parts firms have long cultivated relationships with
government at all levels in Brazil’s federalist system (Addis, 1999). Interviewees cited
Sindipeças’ important contribution to firm and sector competitiveness through its collective
action function. Individually, firms felt that they were outgunned compared to the much
larger steel mills and OEMs. But collectively they feel that they have been able to exercise an
important amount of influence in government in a way that protects, and at times, promotes
their position. Among the most recent examples of Sindipeças’ success was a federal
21
government decision to reinterpret and reshape a value-added tax with the result of lowering
tax obligations for all parts firms. A majority of interviewees singled this result out for
lowering firm costs and enhancing competitiveness, particularly in foreign markets.8
In a less uniform manner, firm managers singled out a variety of other institutions and
other services that they felt had improved their firm’s competitiveness. These include
Sindicpecas’ services relating to training, trade fairs, and legal/tax advice as well as more
specialized services (needed on an ad hoc basis) from other service providers related to
norms/standards, testing, and ISO certification. In our limited interview sample, there was
considerable variation in the amount and nature of contacts between firms and sector
institutions. Large multinational firms (three were interviewed) stood out in having
substantially more—and more intense—relationships with institutions compared to both
national and smaller firms. These large multinationals were also unique for their intensive
interactions with SENAI, a technical training institute, which operated partnerships with
these companies to develop skilled workers. All three of these firms sought out SENAI’s
services and their managers believed that it provides an important boost to competitiveness.
Strikingly, no other firm manager who was interviewed singled out SENAI as an institution
that they interacted with in any important way, even though some remarked that shortages of
skilled labor were problematic at times.9
Although our interviews focused primarily on the influence of institutions on firm and
sector performance, interviewees were also asked about their horizontal and vertical
relationships with other firms. Consistent with the literature discussed earlier, vertical
cooperation was much more likely—though not prevalent—compared to horizontal
8
The statistical analysis above is obviously not structured to capture this type of sectoral influence on firm
performance since it seeks variation across firms. Nevertheless, the interviews add to our larger understanding
of the ways in which instutitions can enhance firm competitiveness.
9
Large multinational firms were also much more likely to interact with public and private institutions that
discussed and made recommendations related to government safety standards that affected the transportation
industry.
22
interactions. In the former case, the large multinationals again stood out for their interactions
with suppliers, OEMs or parts companies that supplied complementary parts. Other firms
reported little or nothing in the way of either vertical or horizontal cooperation. Horizontal
interactions were severely undermined by high degrees of competition among parts
companies as well as a sense that such interactions might violate government rules against
cartels. Domestic competition levels were enhanced in part by the aggressiveness of some
parts companies (particularly the arrival of multinationals in the mid-1990s) as well as more
recent plans by some OEMs to reduce their number of suppliers. When horizontal
interactions took place, they were typically limited to the exchange of market and, in some
cases, process information. In only one instance (the filters segment) did we hear of an
institutionalized forum (via Sindipeças) for a regular exchange of market and process
information, discussions of segment problems, and an active attempt to achieve economies of
scope (a willingness to sell products to one another). Despite what the literature might
suggest in terms of the benefits of horizontal cooperation, Brazilian parts companies act no
differently than firms in many other countries.
CONCLUSION AND FUTURE RESEARCH
Extrapolating from the existing literature, this paper created a model detailing how
intra-firm practices, inter-firm relationships, and institutions influence the competitiveness of
individual companies. We tested our model using survey research and interviews involving
Brazilian auto part producers. We found that all three sets of explanatory factors had a
positive impact on firm performance as measured by increased production efficiencies. As
expected, institutions exercised an indirect influence, by encouraging companies to work
together and by supplying information and other resources that enhanced operations within
particular companies. For their part, and as expected, the adoption of firm-level practices and
a willingness to develop closer ties with customers were directly associated with stronger
23
performance at the company level. We failed to find, however, a positive effect of horizontal
cooperation with peers on the performance of suppliers. Apparently, in the Brazilian autoparts sector, horizontal relationships do matter, but only when built up through inter-firm
associations (Sindipeças) instead of direct ties among suppliers.
From a theoretical point of view, our results are important. Our model and empirical
findings offer a significant contribution to the literature by detailing a model of firm
performance that integrates three sets of explanatory factors. In doing so, we show that these
are not competing but complementary; and we detail the pathways through which they
interact and combine with one another to enhance firm competitiveness. Explanations of
firm performance that rely on only one of these three explanations miss the contribution,
sometime indirect, of the others.
At the same time, our findings are important in a more practical sense. Recent reviews
of the strategy/operations literature note that despite massive investments by multinational
firms in the region, throughout the 1990s, it is still unknown by the English-speaking
academic community whether such investments in modern manufacturing and management
techniques have yielded performance differences (Correa, 2005). Our findings suggest that at
least for this sector in Brazil, prior investments in these “firm-level practices” are having a
positive impact. At the same time, however, we find that other actions to increase firm
performance can complement this investment. Our observation that major multinationals
appear more likely to take advantage of institutional services and resources suggests that at
least some firms understand that a strategy to maximizing performance requires a
multifaceted approach.
From a public policy stand point, there are additional implications from this research.
It is clear that institutions—business associations, technical institutes, and the like—can help
drive increases in firm competitiveness. Both the quantitative and qualitative data support
24
this conclusion. But at the same time, institutions play a supporting role in this process;
managers must often consciously seek them out or decide to avail themselves of the resources
that institutions have to offer. By virtue of this fact, institutions typically receive less
managerial attention than intra-firm operations and practices when it comes to devising
strategies to increase competitiveness. However, managers must come to understand the
positive benefits that can accrue from working with institutions while institutional leaders
must develop and then actively reach out and market services which promote what we call
firm-level practices as well as those that encourage inter-firm relationships. Helping to break
down the barriers to trust and cooperation is an important function that institutions can
furnish, provided that they act as an impartial intermediary. For their part, governments
should be supportive of public and private institutions that provide important resources—
albeit indirectly—that enhance their companies’ performance levels. Instead of seeing
institutions as interest groups that may be competing for scarce public resources, the public
and private sectors must become partners in the globally competitive business environment.
In the Brazilian context, government officials would do well to not treat horizontal
cooperative actions as anti-competitive practices, hopefully in a way that does not discourage
forms of inter-firm networking. They should also work with institutions like Sindipeças to
promote more institutional interaction with Brazilian companies.
Admittedly our research raises several other questions. First, our claim that engagement
in association enhances the effectiveness of intra- and inter-firm practices needs to be further
studied in order to assess whether it can be generalized to other industries and countries.
Second, we need to understand more about the interplay between horizontal and vertical
relationships and their impact on performance. Our finding suggests that horizontal
involvement in associations is positively associated with vertical patterns of collaboration,
which in turn leads to superior operational performance. However, we fail to find a direct
25
effect of horizontal ties among peers on their performance. Further research examining the
differential effect of horizontal and vertical relationships on firm performance is needed.
Finally, the literature would benefit from longitudinal research settings examining how
participation in associations evolves and influence the formation of inter-firm ties. Such an
analysis would be particularly helpful for firms located in countries with weak institutional
support, where complex patterns of inter-firm networking are critical to provide resources
that are critical for the competitiveness of firms.
26
Figure 1: Model and Hypotheses
F2 - Investments in
Competitive Resources
& Capabilities
H2a
CONTROL VARIABLES
H1a
F1 - Institutional
Support from
Associative
Organizations
H1b
F3 - Inter-firm
Cooperation (vertical)
H2b
F4 - Inter-Firm
Cooperation
(horizontal)
H2c
F7 - size; F8 - market
pressure; F9 - formal
contracts
F5 - Production
Efficiency Gains
H1c
Figure 2: Results (‘dotted’ paths not supported in Structural Equation Analysis)
F2 - Investments in
Competitive Resources
& Capabilities
H2a
F3 - Inter-firm
Cooperation (vertical)
H2b
CONTROL VARIABLES
F8 - market pressure
H1a
F1 - Institutional
Support from
Associative
Organizations
H1b
F5 - Production
Efficiency Gains
F7 - Size; F9 - formal
contracts
H1c
F4 - Inter-Firm
Cooperation
(horizontal)
H2c
27
Table 1: Constructs items, factor loadings, measurement scale and Cronbach’s alpha.
Construct items (factor loadings)
Scale (standardized values)
Cronbach's
alpha
Likert Scale 1-5
0.804
Likert Scale 1-5
0.820
Percentage
0.721
Percentage
0.711
F1 - Institutional Support from Associative Organizations - degree to which your firm uses specialized
support from your business association, SINDIPECAS…
Organize and supply technical training to its associates (0.643)
Develop economic / technical studies and disseminate the results of such studies to its members (0.576)
Hold ‘collective representation’ responsibilities in negotiations with the government
Hold social events to gather members (0.501)
F2 - Acquisition of Competitive Resources & Capabilities: to what extent has your firm invested in or
participated in programs related to knowledge acquisition in the following areas
kaizen (constant improvement)
lot size optimization
total quality management
machinery and plant set up techniques
F3 - Vertical Coordination - Customer: extent to which your firm and this customer engage in coordinated
efforts (e.g. intensively exchange information, or mutually assist each other, or any other form of
coordination) in the following areas…
Marketing and exports related activities
New product and process development
Sharing of equipment and other resources
Joint purchase of inputs
Joint representation in negotiations with government and government agencies
F4 - Horizontal Coordination - Peer: extent to which your firm and this peer-firm engage in coordinated
efforts (e.g. intensively exchange information, or mutually assist each other, or any other form of
coordination) in the following areas…
Marketing and exports related activities
New product and process development
Sharing of equipment and other resources
Joint purchase of inputs
Joint representation in negotiations with government and government agencies
F5 - Production Efficiencies
Timely delivery: percentage of goods delivered on time
Manufacturing lead time: number of day it takes from day order arrives at shop floor till day product leaves
factory
Rate of inventory turn over: firm level number of inventory turns necessary to support 12 month sales
N.A.
F7 - Size
Log of sales volume (R$)
NA
F8 - Market pressure
Log number of firms competing
in your business segment
NA
F9 - Formal contracting: degree to which you and your partners rely on the following formal contractual
clauses…
contract duration in months
fee for contract breach
exclusivity of supply
minimum purchase clauses
fees for underperformance in quality and delivery
0.700
28
Table 2 – Chi square difference test
Covariance
CF1F2
CF1F3
CF1F4
CF2F3
CF2F4
CF3F4
Latent Variables
F1 - Institutional Support
from Associative
Organizations
F1 - Institutional Support
from Associative
Organizations
F1 - Institutional Support
from Associative
Organizations
F2 - Investments in
Competitive Resources &
Capabilities
F2 - Investments in
Competitive Resources &
Capabilities
F3 - Inter-Firm Coordination
(vertical)
χ2 statistics
Constrained Model Unconstrained
(d.f. = 81)
Model (d.f. = 80)
Difference (d.f. = 1) significant if chi-square
> 3.85
F2 - Investments in
Competitive Resources &
Capabilities
116.5
105.33
11.17
F3 - Inter-Firm Coordination
(vertical)
131.41
105.33
26.08
F4 - Inter-Firm Coordination
(horizontal)
249.87
106.32
143.55
F3 - Inter-Firm Coordination
(vertical)
116.92
105.33
11.59
F4 - Inter-Firm Coordination
(horizontal)
112.34
105.33
7.01
F4 - Inter-Firm relational
content (horizontal)
137.59
105.33
32.26
29
Table 3 – Correlation matrix
F1
F2
F3
F4
F1
Institutional Support from
Associative Organizations
1.00
F2
Investments in Competitive
Resources & Capabilities
0.18**
1.00
0.34****
0.6****
1.00
0.17**
0.12*
0.13*
1.00
F3
F4
Inter-firm cooperation
(vertical)
Inter-firm cooperation
(horizontal)
F5
F5
Production Efficiency Gains
0.07
0.15**
0.16**
0.03
1.00
F6
F7
F8
Firm size
Market pressure
Formal ontracts
0.07
0.08
0.09
0.00
0.16**
0.07
0.01
0.13**
0.05
0.00
0.10
0.02
0.02
0.25***
0.04
F6
F7
F8
1.00
0.04
0.01
1.00
0.00
1.00
* Significant at the .1 level
** Significant at the .05 level
*** Significant at the .01 level
**** Significant at the .001 level
30
Table 4 – Parameter estimates for the structural equation model
Column A
Column B
HYPOTHESIS
PARAMETER
H1a
H1b
H1c
H2a
H2b
H2c
Control - size
Control - market forces
Control - formal contract
PF1F2
PF1F3
PF1F4
PF2F5
PF2F6
PF2F7
PF6F5
PF7F5
PF8F5
Column C
STANDARDIZED
SOLUTION (t-value)
0.190 (2.67)
0.3622 (4.930)
0.210 (3.091)
0.176 (2.61)
0.215 (3.15)
not supported
0.354 (4.857)
0.198 (2.84)
not supported
FIT INDEX - - - - - - - SOLUTION
2
χ (-p-value)
103.85 (p = 0.05)
degrees of freedom
N
GFI
AGFI
CFI
NNFI
80
182
0.9034
0.8999
0.9156
0.9049
31
Table 5: List of Interviewed Firms/Institutions
National
Multinational
10
Large10
• Usiparts (1st tier)
• Ichoe-Maxxion (1st tier)
• Bosch (1st tier)
• Haldex (1st tier)
• Tyssenkrupp (2nd tier)
•
•
•
•
•
•
Small
Montepino (1st tier)
Olimpus (1st tier)
Cartec (2nd tier)
SBU (2nd tier)
Parker (1st tier)
Voith (1st tier)
Institutions
• Sindipeças
• ANFAVEA
• IPT-USP
• CIESP
“Large” is defined as sales greater than $500 million reais (about US$200 million).
32
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