Strategic Entrepreneurship Journal
Strat. Entrepreneurship J., 1: 27–47 (2007)
Published online 16 November 2007 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/sej.1
WHAT MAKES A PROCESS A CAPABILITY?
HEURISTICS, STRATEGY, AND EFFECTIVE CAPTURE
OF OPPORTUNITIES
CHRISTOPHER B. BINGHAM,1* KATHLEEN M. EISENHARDT,2
and NATHAN R. FURR2
1
Robert H. Smith School of Business, University of Maryland, College Park,
Maryland, U.S.A.
2
Department of Management Science and Engineering, Stanford University,
Stanford, California, U.S.A.
While organizational processes, such as internationalization, acquisition, and alliance, are
a fundamental concept within many literatures and central to firm capabilities, controversy
exists regarding how they become high performing. One view emphasizes the role of experience while a second view emphasizes cognition and, in particular, the role of articulated
heuristics. Using qualitative and quantitative field data on the internationalization process
of entrepreneurial firms from three culturally distinct regions (Finland, U.S., Singapore), we
juxtapose these two competing theoretical views to better gain insight into organizational
processes and capabilities. The core contribution of our paper is insight into the structure
of firm capabilities. Results show that organizational heuristics more closely relate to the
development of a high performing process and hence a firm capability. At a broader level, we
contribute to strategy by empirically validating the strategic logic of opportunity, a logic that
is particularly relevant in dynamic markets and growth oriented firms. We also contribute to
entrepreneurship by adding to the opportunity discovery vs. opportunity creation debate, and
by shedding light on the relationship between structure and performance in new ventures.
Overall, we contribute to the emerging but growing body of research emphasizing a more
cognitive view of firms. Copyright © 2007 Strategic Management Society.
Organizational processes are a central concept within
the strategy, organizations, and entrepreneurship literatures (Eisenhardt and Martin, 2000; Helfat and
Peteraf, 2003; Pentland, 1995; Zollo and Winter,
2002). By organizational processes, we mean the
sets of actions that repeat over time and allow managers to accomplish some business task (Pentland
and Rueter, 1994; Ray, Barney, and Muhanna, 2004;
Keywords: organizational process; capabilities; experience;
heuristics; opportunity capture; cognition
* Correspondence to: Christopher B. Bingham, Department of
Management and Organization, Robert H. Smith School of
Business, University of Maryland, 4519 Van Munching Hall,
College Park, MD 20742, U.S.A.
E-mail: [email protected]
Copyright © 2007 Strategic Management Society
Teece, Pisano, and Shuen, 1997). Common processes include acquisitions (Zollo and Singh, 2004),
alliances (Kale, Dyer, and Singh, 2002), product
development (Brown and Eisenhardt, 1997; Miner,
Bassoff, and Moorman, 2001), and internationalization (Sapienza et al., 2006; Zahra, Ireland, and Hitt,
2000). Organizational processes have long been
seen as central to how the work of organizations
gets done (Miles and Snow, 1978; Weber, 1947).
Recent theoretical arguments go a step further
to designate organizational processes as a central
feature of capabilities. Amit and Schoemaker (1993:
35), for example, describe how ‘capabilities refer to
a firm’s capacity to deploy resources . . . using organizational process, to effect a desired end.’ Others
28
C. B. Bingham, K. M. Eisenhardt, and N. R. Furr
argue that organizational processes form dynamic
capabilities that are crucial to strategy (Eisenhardt
and Martin, 2000; Teece et al., 1997). Teece and colleagues (1997: 524) state, ‘The essence of a firm’s
competence and dynamic capabilities is presented
here as being resident in the firm’s organizational
processes.’ In addition, there is growing consensus
that capabilities imply a threshold of performance
(Grant, 1996; Helfat et al., 2007; Maritan, 2001),
suggesting the particular relevance of high performing processes to capabilities.
Some scholars have even suggested that organizational processes are not just crucial to strategy, but
rather are the strategy of firms, especially in entrepreneurial firms and dynamic markets (Bingham and
Eisenhardt, 2007). In contrast to positioning (Porter,
1996) and leverage (Collis and Montgomery, 1995)
strategic logics, the logic here is that organizational
processes put firms in the midst of opportunity flows
(e.g., flows of new product opportunities, alliance
opportunities, and country opportunities). By selecting processes with the most attractive flows of opportunities and effectively executing those processes,
firms can gain a series of temporary performance
advantages (Wiggins and Ruefli, 2005). Supporting
this strategic logic of opportunity, Roberts (1999)
found that pharmaceutical firms adopting a strategy
of product development, where leaders continually
repeated the process to create a series of new products, were able to stay ahead of the competition,
capture emergent product opportunities and generate a string of short-term competitive advantages
over time. Other popular examples of ‘organizational process as strategy’ include Cisco’s acquisition process, Hewlett-Packard’s alliance process and
Starbuck’s internationalization process.
Despite their fundamental importance for firm
action, capabilities and even strategy, it is unclear
how organizational processes become high-performing. Two streams of research are particularly relevant. One stream is organizational learning from
experience. Numerous studies in this area emphasize
the role of more experience in developing a highperforming organizational process. Research shows
that as firms engage in more acquisitions (Haleblian
and Finkelstein, 1999), country entries (Barkema,
Bell, and Pennings, 1996) or alliances (Kale et al.,
2002) process performance improves. Other organizational learning studies emphasize that particular
types of experience (e.g., similar and paced) lead to
a high performing process. For example, research on
internationalization finds that this process is higher
Copyright © 2007 Strategic Management Society
performing when country entry experience is paced
(Vermeulen and Barkema, 2002) and accumulates
in culturally similar regions (Davidson, 1980; Hofstede, 2001; Kogut and Singh, 1988). But, while
studies in this stream are useful, it is unclear what
is actually learned from experience and how that
learned content leads to high process performance.
The second stream relates to organizational cognition. It emphasizes that firms must translate their
experience into articulated heuristics in order to
develop an organizational process. Simply gaining
experience is not enough. By opening up the ‘black
box’ of what is learned from experience, empirical research finds that these heuristics are simple
rules that focus on capturing opportunities within
a given process (Bingham, Eisenhardt, and Davis,
2007). These heuristics delineate the selection, priority, pacing and execution of specific opportunities
from the larger set of possibilities that is especially
common in dynamic markets where opportunities
are often ‘super-abundant’ (Davis, Eisenhardt, and
Bingham, 2007). The semi-structure of heuristics
enables flexibility to adjust to the unique demands of
any particular opportunity while still retaining some
coherence and efficiency (Brown and Eisenhardt,
1997; Burgelman, 1996; Rindova and Kotha, 2001).
But while work in this second stream finds that
some firms develop heuristics as they gain process
experience (Bingham et al., 2007), the link between
these heuristics and high process performance lacks
empirical validation.
The purpose of this paper is to compare experience and heuristics as theoretical explanations of
organizational process performance. Specifically,
we ask whether firms learn high performing processes by simply gaining more or particular types of
experience, or whether they have to translate experience into articulated heuristics. We begin by developing predictions for each theoretical explanation.
We then examine these alternative explanations by
focusing on the internationalization process of technology-based entrepreneurial firms from three culturally distinct regions (Finland, U.S., Singapore). A
unique feature of our study is combining both qualitative and quantitative data. This research approach
is particularly appropriate when the research aim is
to reinvestigate measures from prior theory, and yet
simultaneously test promising new measures from
provisional theory (Edmondson and McManus,
2007). Such an approach provides not only granularity and depth of understanding, but also statistical
precision and generalization.
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
What Makes a Process a Capability?
Our core contribution is the insight that heuristics
are at the heart of firm capabilities. That is, firm
members must actively translate their process experience into shared heuristics for opportunity capture
in order to develop a high performing process, and
hence a firm capability. In contrast, experience
per se is insufficient for creating high performing
organizational processes. Thus, capabilities rest
on an explicit structure of heuristics, and not just
tacit knowledge built from accumulated experience.
Broadly, we contribute to strategy by confirming the
strategic logic of opportunity, a logic that is particularly relevant in dynamic markets and growth-oriented firms. We also contribute to entrepreneurship
by adding insights into the creation vs. discovery
of opportunities debate, and the crucial importance
of increased structure in new ventures. Overall, by
combining rich field insights with theory and evidence from psychology and cognitive science, we
promote a fresh and empirically valid view where
simple cognitive structures are central to firm capabilities and the effective capture of entrepreneurial
opportunities.
THEORETICAL BACKGROUND
Organizational learning: experience
Extensive literature on organizational learning
links experience with an organizational process to
improvements in the performance of that process
(for a review see Argote, 1999). Typically, these
studies tie experience to performance while positing
an underlying learning mechanism. Much of this
research has theoretical roots in early psychological studies (e.g., Thorndike, 1898). Psychologists
discovered that the amount of time individuals used
when performing a task, as well as the extent of mistakes when accomplishing the task, decreased with
increased experience (Thurstone, 1919). Organizational researchers later identified learning curves at
the firm level, and emphasized repeated experience
as a primary mechanism for the creation of high performing processes. Through ongoing trial-and-error
and repeat practice, firm members better comprehend
the specific causal links between prior firm decisions
and firm outcomes. They also gain insights about the
production and management of processes such that
these processes become more efficient and reliable,
and thus higher performing (Argote, 1999).
Much empirical evidence supports the tie between
experience and process performance. For example,
Copyright © 2007 Strategic Management Society
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one of the earliest pieces of research on organizational learning curves is a study by Wright (1936) on
the labor required to build airplanes. Wright found
that, as more airplanes were produced, the amount
of labor hours needed to produce a single plane
decreased at a decreasing rate. Later research on
the manufacturing process of automobiles (Levin,
2000), trucks (Epple, Argote, and Devadas, 1991),
and ships (Rapping, 1965) also showed that, as firms
produced more of a discrete product, the unit cost
of production typically decreased at a decreasing
rate. Beyond its historical roots in manufacturing settings, organizational learning research in a
wide variety of settings, such as pizza assembly
(Darr, Argote, and Epple, 1995), alliance formation (Anand and Khanna, 2000), surgical procedures
(Pisano, Bohmer, and Edmondson, 2001), semiconductor production (Chung, 2001; Gruber, 1994) and
internationalization (Martin and Salomon, 2003)
lends support for experience effects. To illustrate,
Kale and colleagues (2002) analyzed approximately
1572 alliances from 78 firms. The authors found that
cumulative alliance experience was significantly
related to abnormal stock gains following alliance
announcements. As a whole, theoretical argument
and empirical evidence suggest that more experience
should lead to a higher performing organizational
process.
Hypothesis 1: Organizational experience is positively associated with process performance.
The timing of experience is also likely to influence the learning of a high performing organizational process. On the one hand, insufficient time
between discrete experiences (e.g., specific alliances,
acquisitions or country entries) may lower process
performance since it limits a firm’s ability to absorb
new knowledge (Gersick, 1994). When experiences
occur in quick succession, firm members do not have
time to draw inferences or assimilate learning from
the past (Hayward, 2002; Levitt and March, 1988).
A rapid internationalization process consisting of
multiple country entries within the same quarter,
for example, can lead to poor internationalization
performance by exceeding the cognitive limits of
managers to internalize the learning from each new
country. Consistent with this logic, Vermeulen
and Barkema (2002) found that the development
of a high performing internationalization process
depends on the firm’s rhythm of expansion. Using
a panel of 572 observations covering the country
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
30
C. B. Bingham, K. M. Eisenhardt, and N. R. Furr
entries of 22 Dutch firms over 26 years, the authors
discovered that irregularity in movement abroad
negatively moderated internationalization performance. Similarly, research on the acquisition process
(Haunschild, Davis-Blake, and Fichman, 1994) also
suggests that firms cannot learn effectively when
acquisitions follow each other too rapidly.
On the other hand, too much time between
experiences may lower process performance since
firms may forget lessons from the past (Argote,
1999). Such organizational forgetting may occur
for two reasons. First, when the time interval
between experiences is long, individuals believe
that the experiences are one-time events that are
unlikely to repeat. In this situation, firm members
are less prone to encode action steps in memory
since they foresee little future performance payoff
(Winter and Szulanski, 2001). Organizational forgetting can also occur when individuals learn some
action steps from their experience, but then leave
the firm or move on to other activities within the
firm. Thus, unless knowledge is currently relevant
for those individuals involved with the focal process,
knowledge from prior experience with that process
is likely to be seen as less salient, inappropriate,
or even obsolete, and to be forgotten (Hayward,
2002).
Hypothesis 2: The period of time between experiences has an inverted U-shaped relationship with
process performance.
Similarity of experience also influences the development of a high performing process. Unlike relatively homogeneous experiences (e.g., production
of automobiles, ships, or planes) where experiences
are highly similar to one another, experiences with
organizational processes such as product development, alliance formation, acquisitions, and country
entries are often heterogeneous. For example, the
acquisitions of a given firm may be undertaken
for many reasons, involve different negotiation
challenges, and present distinct integration issues
(Graebner, 2004). Therefore, the learning benefits
of prior acquisitions exist only to the extent that
these past experiences are sufficiently similar
to provide insight to the focal one. In particular,
research suggests that, when the focal experience
is similar to those of the past, processes improve
through specialization (Haleblian and Finkelstein,
1999; Zollo, Reuer, and Singh, 2002). Small deviaCopyright © 2007 Strategic Management Society
tions in context permit firm members to focus their
time and effort, elaborate on existing knowledge,
and develop deeper causal understandings for how
to accomplish tasks. The result is often steeper
organizational learning curves and greater gains in
efficiency (Von Hippel, 1998). This relationship is
consistent with psychological research which shows
that becoming expert in a given field (e.g., chess)
often requires at least ten years of dedicated study
(Hayes, 1989). Overall, these arguments imply that
similarity of experiences is helpful for developing
a high performing organizational process. Studies
on internationalization, for example, show that
firms entering culturally similar countries develop a
better internationalization process than firms entering countries at random (Johanson and Vahlne,
1977).
But, if experiences are too similar, firms are unable
to form the generalist skills needed to cope with heterogeneity (Hayward, 2002). Ongoing experience
with the same alliance partners or entering culturally
similar countries may lead to a lower performing
process by stifling creativity and making it difficult
to capture a broad range of future opportunities. This
occurs because the ability to understand, integrate,
and effectively leverage new knowledge is largely
dependent on the state of prior related knowledge
(Cohen and Levinthal, 1990). Thus, the more similar
a firm’s process experiences are to each other, the
more likely that the firm is to develop core rigidities
(Leonard-Barton, 1992), under invest in exploration
(March, 1991), and fail to recognize fresh opportunities for growth and profit (Schilling et al., 2003).
Research on individual learning supports these arguments by showing that reinforcing a specialized
knowledge base dampens problem solving skills by
strengthening connections among existing cognitive
nodes without fostering connections with new nodes
that are essential for bridging knowledge gaps and
assimilating new information (Martindale, 1995).
Research on personal insight likewise shows that
new understandings of problems are less likely to
arise when domains are too closely related (Simonton, 1999). Taken together, these arguments suggest
that moderately similar experience is likely to lead to
a high performing organizational process (Schilling
et al., 2003).
Hypothesis 3: The similarity of experiences has
an inverted U-shaped relationship with process
performance.
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
What Makes a Process a Capability?
Organizational cognition: heuristics
In contrast to the first stream, a second and
more recent research stream deals directly with
the content of learning from experience. This
research emphasizes cognition, and the related articulation of what is learned as experience is gained
(Bingham et al., 2007; Zollo and Singh, 2004).
Although studies identify elaborated and codified tools such as check-lists, integration manuals,
and training books (Kale et al., 2002; Szulanski
and Jensen, 2006; Zollo and Singh, 2004) as the
articulated learning in stable environments and
large firms, we focus on dynamic markets and
entrepreneurial firms where studies highlight
that articulated learning takes the form of simple
heuristics. By heuristics, we mean articulated and
often informal rules-of-thumb shared by multiple participants within the firm. In the context of
organizational processes, these heuristics center
on capturing discrete opportunities (e.g., entering
specific countries, developing specific products,
acquiring particular firms) (Bingham et al., 2007;
Burgelman, 1996; Rindova and Kotha, 2001), and
become increasingly ‘expert’ as experience with
opportunities accumulates (Bingham et al., 2007).
Our theoretical argument is that, while experience
may improve process performance, active learning
by which firm members translate their accumulating experience into increasingly honed heuristics
that are expected to apply across multiple country
entries is more likely to be associated with a higher
performing process.
There are several reasons why heuristics
create a high performing organizational process.
First, heuristics focus attention and save time. The
reason is that heuristics are cognitive structures
that categorize stimuli (e.g., types of countries,
customers, mode of entry). Such categorization
frees up time to improvise unexpected aspects
of opportunities (Daft and Weick, 1984;
Friedman, 1979), and so enables rapid and
accurate troubleshooting when surprises and
problems (e.g., ‘this is an acquisition integration
error’ or ‘this mode of country entry is incorrect’)
arise.
Second, heuristics allow for improvisation (Brown
and Eisenhardt, 1997; Miner et al., 2001). Their
semi-structure enables the flexibility and responsiveness necessary for the effective capture of attractive
but novel opportunities that are common in dynamic
Copyright © 2007 Strategic Management Society
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markets.1 But they also allow for at least some efficiency since that limited structure provides guidance that keeps behavior partially constrained. This
creates the coherence necessary during adaptation
to achieve congruence with new opportunities (e.g.,
new countries, new products) (Teece et al., 1997).
Third, heuristics limit errors. They provide guidelines and rough preliminary plans for how individuals
should respond to future events, thereby reducing the
amount of learning that needs to take place through
pure trial-and-error (Eysenck and Keane, 1995). In
their studies of expertise, for example, Chi and colleagues (1981) found that physicists who spent more
time creating cognitive representations of the problem
situation before beginning were more successful
solving problems than those who began without such
representations. Similarly, Gitomer (1988) described
how electronics technicians who engaged in troubleshooting after creating a conceptual model of the
task were more successful than those technicians
who began immediately using trial-and-error. As a
whole, these arguments suggest that, while experience is probably needed to learn a high performing
process, it is the articulation of that experience into
heuristics by firm members that leads to a high performing process. The use of heuristics focuses attention, reduces errors, and provides structure, and leads
to ‘expertness’ that improves process performance.
This leads to the following hypothesis:
Hypothesis 4: A greater number of heuristics is
positively associated with process performance.2
1
The differences between extensive codified knowledge and
simple articulated heuristics may relate to differences in environments. In stable environments, codified knowledge is beneficial since there is greater predictability in situations and thus
greater efficiencies to be had from using many standardized
steps. In dynamic environments however, codification may
be less useful as situations are less predictable (more heterogeneous). Here maintaining plasticity, not just efficiency, is
important. Therefore, we argue that effective knowledge is
probably simpler in dynamic environments, and probably more
complicated and elaborated in stable ones.
2
The more general prediction is that the total number of heuristics has an inverted U relationship with performance because
many heuristics may become too constraining and so lower
performance (Davis et al., 2007). But since we study firms
that are just beginning, we do not observe a sufficient range
to test this prediction. That is, in the setting investigated for
the study, entrepreneurial organizations suffered from having
too few heuristics: managers generally struggled to learn new
processes, making the development of sufficient heuristics the
primary challenge. Accordingly, we did not observe organizations with enough heuristics to test a curvilinear (inverted-U)
shaped relationship to performance.
Strat. Entrepreneurship J., 1: 27–47 (2007)
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C. B. Bingham, K. M. Eisenhardt, and N. R. Furr
Prior research shows that firms learn several types
of process heuristics. Some of these are lower order
heuristics – i.e., selection and procedural heuristics
that relate to the capture of one particular opportunity
such as a single country or acquisition (Bingham et
al., 2007). Selection heuristics are defined as rules
for choosing an opportunity, such as which types
of countries to enter, which types of customers to
target, and which product to develop. They narrow
the range of opportunity choices by specifying
which to pursue and which to ignore. Thus, they
provide focus, and lead to higher process performance because they channel the efforts of dispersed
firm members into similar kinds of opportunities.
For example, firms may rely on selection heuristics to restrict their product development activities
to retail software products and not financial ones,
or low-cost mobile semiconductor products, not all
semiconductor products. Or, firms may use selection
heuristics to focus on specific customer types (e.g.,
large financial institutions or telecom operators),
or on targeted geographic locations (e.g., Asia, big
cities, or Scandinavia).
Without selection heuristics, firm members may
chase too many, widely varying opportunities, and
so lose efficiency and lower process performance.
Or, individuals may become confused about which
opportunities to pursue, and so may be reluctant to
do anything at all. Indeed, the inability to structure
uncertainty can significantly reduce decision making
speed and process effectiveness in dynamic markets
(Eisenhardt, 1989). Hence, the absence of selection
heuristics reduces efficiency, engenders confusion, and leads to lowered process performance. In
contrast, selection heuristics enhance process performance by helping firm members allocate scare
resources to a more focused opportunity set and
eliminate poor opportunities that do not fit the firm
well.
Procedural heuristics are defined as rules that
specify the actions a firm should take to execute a
chosen opportunity (Bingham et al., 2007). Procedural heuristics focus attention on how to capture
selected opportunities, and reflect learning on the
part of firm members about past actions and their
efficacy for process execution. Their use leads
to improved process performance by specifying
behaviors likely to prove helpful during execution.
Examples include ‘hold weekly meetings between
engineers and marketers’ in a product development
process (Brown and Eisenhardt, 1997) and ‘do no
exclusive deals’ in an alliance process (Rindova and
Copyright © 2007 Strategic Management Society
Kotha, 2001). More generally, procedural heuristics lead to improved process performance because
they structure action, improve sensemaking, and aid
problem solving. Psychological research shows that
making sense out of life requires that individuals
learn not only what to do, but also how to do it
(Siegler, Deloache, and Eisenberg, 2003). It also
suggests that effective problem solving involves
problem structures that are defined by a goal and
knowledge necessary to achieve the goal (Newell
and Simon, 1972). Poor performance arises when
one of these elements is missing (Simon, 1973).
Thus, procedural heuristics improve process performance by elucidating understanding about how
to capture opportunities within the firm’s purview.
Like selection heuristics, procedural heuristics focus
attention, structure action, and eliminate errors.
In sum, these arguments imply that firms with
selection and procedural heuristics will have a
higher performing organizational process due to
more focused choice of particular opportunities
from the larger set of possibilities, and more efficient guidance for actions regarding what to do (and
not to do) while attempting to capture the selected
opportunities.
Hypothesis 5: A greater number of lower order
heuristics (i.e., selection and procedural) is positively associated with process performance.
While lower order heuristics focus on the capture
of a single opportunity, higher order heuristics such
as those dealing with time and priorities link multiple opportunities together. As such, they require
greater cognitive sophistication, and are associated
with higher expertise (Bingham et al., 2007). Temporal heuristics are defined as rules for opportunity
capture that relate to sequence, pace, or synchronization (Brown and Eisenhardt, 1997; Gersick, 1994).
Examples of sequence rules include ‘Use the U.K.
as a launching pad into France and Germany,’ or
‘Move from tier-three to tier-two to tier-one countries,’ while examples of pace and synchronization
rules include ‘Enter one country every two months’
and ‘Build up enough strength in current markets
before making a high-cost commitment to a new
market,’ respectively.
Temporal heuristics improve process performance
for several reasons. First, they synchronize various
work groups (e.g., sales, engineering, marketing)
with each other and the market. Such timing allows
firm members to regulate the tempo of their actions,
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
What Makes a Process a Capability?
and so lower the likelihood of confusion, fatigue
and wasted effort. Second, temporal heuristics
provide natural break points that are tied with market
rhythms such as the product development cycle of
customers. This allows firm members to entrain with
the environment, and thus reassess their efforts and
the competitive landscape at regular time intervals
(Ancona and Caldwell, 1992). Temporal heuristics
are especially valuable in dynamic markets where
ongoing organizational change is critical to capture
fleeting opportunities, but where it is easy to either
change too often (Sastry, 1997) or too little
(Gersick, 1994). Finally, temporal heuristics are
effective because they help managers maintain
momentum. Momentum provides focus and direction
about when and where to move forward from current
opportunities. Overall, specifying the sequence,
synchronization and pace by which a process takes
place is likely to improve performance (Barkema
et al., 1996; Chang, 1995; Vermeulen and
Barkema, 2002).
In contrast, processes may be lower performing
when firms lack temporal heuristics. Firm members
may try to capture too many opportunities at once,
or execute the appropriate actions but in the wrong
order. Chang (1995), as one illustration, found that
when Japanese electronic firms entering the U.S. followed a sequence of starting with small investments
and then increasing the scale of those investments
over time, they performed better than other firms
that did not follow any sequence. Finally, without
heuristics for sequence, pace, and synchronization,
firm members may not be able to effectively choreograph the switch from one opportunity to another
and properly coordinate different parts of the firm
to manage the transitions (Brown and Eisenhardt,
1998).
Priority heuristics are defined as rules that specify
the ranking of opportunities (Bingham et al., 2007).
Specifically, they involve the identification of a
firm’s most important opportunities within the
limits proscribed by its selection heuristics. Priority
heuristics increase the probability of high process
performance because they target effort on the most
attractive opportunities. Since their creation and use
require thoughtful evaluation and comparison of
multiple opportunities, firm members come to better
understand which are more important to the performance of an organizational process when they rank
opportunities in relation to others. Thus, they are
likely to create heuristics that focus their efforts on
the best opportunities. Intel, for example, relied on
Copyright © 2007 Strategic Management Society
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a priority heuristic of ‘maximize-margin-per-wafer’
to allocate capacity in its manufacturing process
(Burgelman, 1996). When memory margins fell
dramatically, Intel followed their heuristic and reallocated capacity to microprocessors where margins
were higher. Priority heuristics may also improve
process performance by stipulating where within
its proscribed scope of operations the firm should
begin its opportunity search such as ‘Enter regions
with the highest mobile penetration first,’ ‘Start with
the automotive sector,’ or ‘Enter English speaking
markets first.’ Alternatively, priority heuristics can
specify where to end such as ‘Work towards entering China.’ Firms lacking priority heuristics may
not have high process performance because they
pursue low-value opportunities when better opportunities are available or because they pursue too many
opportunities in parallel, thereby failing to capture
the value of any single opportunity. Collectively,
these arguments suggest that higher order heuristics
are likely to lead to a higher performing organizational process because they help firm members to
synchronize and order their efforts more effectively
across multiple opportunities.
Hypothesis 6: A greater number of higher order
heuristics is positively associated with process
performance.
METHODS
Sample
Our setting is entrepreneurial firms – i.e., small and
young organizations. We chose these firms because
they offer methods advantages. Their young age
avoids left censoring by allowing observation of
process development and learning from firm inception. Their small size enhances transparency (Argote,
1999), and so ensures better identification of shared
process heuristics if they exist.
We focus on the internationalization process in
which each discrete experience is a unique country
entry. Our sample consists of 67 country entries
performed by 12 entrepreneurial firms between 1997
and 2003. Consistent with the internationalization
literature (e.g., Root, 1994), we define a country
entry as a firm’s physical entry into a foreign country
through institutional arrangements (e.g., joint ventures, acquisitions, Greenfield investments) for the
primary purpose of enabling sales. Although often
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
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C. B. Bingham, K. M. Eisenhardt, and N. R. Furr
overlooked as a setting in which to study organizational processes, internationalization is a good
choice for several reasons. First, since each country
entry is a discrete event, it can be analyzed in isolation as a single opportunity and/or as part of a larger
set of experiences. Second, since performance data
exist for each country entry, process performance
can be measured. Finally, a discrete experience
such as a country entry, acquisition or alliance is an
appropriate, commonly used unit of analysis for the
study of organizational processes (Hayward, 2002;
Vermeulen and Barkema, 2001).
Country entries were compiled from a random
sample of entrepreneurial firms operating in four
global technology industries (IT hardware, software,
medical equipment, and computer security) from three
key entrepreneurial metropolitan areas (Singapore,
Helsinki, San Jose). We sample firms operating across
industries and locales to improve the generalizability
of the results. We also sample firms that had experienced a minimum of three entries during the sample
period, and that started internationalization within five
years prior to data collection. This helps to ensure that
we study firms where learning an internationalization
process is important, and where company informants
would be likely to recall the events surrounding the
process in each country entry.
A unique feature of our research design is the
collection of multiple types of data (Edmondson
and McManus, 2007). This helps to ensure greater
measurement accuracy, and instill confidence in the
findings. There are currently no databases tracking
international country entries in sufficient detail to
measure learned content. Therefore, we collected
data from multiple primary and secondary sources:
quantitative and qualitative data from semi-structured
interviews with firm management; archival data from
public and private documents such as annual reports,
business press, Federal Reserve Economic Data and
the Hofstede index (2001) on cultural differences;
and emails, phone calls, and follow-up interviews
to track the real-time internationalization process.
The primary source of data is over 70 interviews
during a 15-month period with corporate executives
of our focal firms on three different continents. We
conducted all interviews according to well-established research procedures including ‘courtroom’
questioning, event tracking, and non-directive questioning from multiple informants at different levels
of hierarchy in order to ensure robustness, reliability, and internal consistency (Golden, 1992; Huber,
1985; Huber and Power, 1985; Miller, Cardinal,
Copyright © 2007 Strategic Management Society
and Glick, 1997; Schwenk, 1985). Our interviews
yielded about 900 pages of single-spaced pages of
transcript data.
All research designs make tradeoffs due to the
practical limits of data collection. Although archival
sources often yield extensive data, they do not allow
direct, rich observation of organizational processes
in the field, and therefore, provide distant measures
of the presence, content, and effects of constructs
such as learned heuristics. Since a primary goal
was to examine the relationship between learned
heuristics and process performance, archival data
that would afford a large sample size is inadequate.
Therefore in order to ensure depth of understanding
and accurate measures, we elected to gather fieldbased measures across a varied sample of industries
and geographies for our empirical test of the influence of heuristics on process performance. Hence,
although our sample is small, this was a necessary
tradeoff to get accurate measures of constructs like
heuristics. Our qualitative data, in particular, play a
critical role in uncovering unique insights that are
unavailable from archival data and quantitative measures alone (Jick, 1979). Thus, we sacrifice some
statistical power in exchange for more measurement
accuracy. This choice increases the likelihood that
our results will be not only generalizeable and thus
externally valid, but also fresh and insightful.
Dependent variable
Performance
Consistent with prior studies of the internationalization process, we rely on multiple measures of
performance (Brush and Vanderwerf, 1992; Delios
and Beamish, 2001; Dunning, 1980; Geringer and
Herbert, 1990; Zahra and Dess, 2001). First, we
measured country entry performance as the log of
average revenue generated by the international entry
into the specific country, adjusted for inflation. We
chose the log of average annual revenue because
it provides a reliable, objective measure of performance available across the sample. Although we
considered other financial measures such as CAGR,
we found them unreliable or unavailable. Second,
we measured country entry performance using
a Likert scale. We asked top management team
members responsible for the entry to rate the ‘overall
success of the entry’ on a 10-point Likert scale (0 =
very poor, 5 = moderate, 10 = excellent), and then
computed the mean response. Third, we measured
country entry performance with a qualitative assessStrat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
What Makes a Process a Capability?
ment of entry performance. For this measure, we
asked the informants to describe the performance of
each country entry that they knew (mean informants
per entry = 5). One author then coded all responses
as positive, negative, or neutral. Examples of positive responses include ‘We have done very well in
Malaysia,’ or ‘I think Taiwan has been very successful.’ Examples of negative responses include ‘In
China, we were not very successful,’ or ‘We got
nothing working in the Czech Republic.’ Examples
of neutral responses include ‘Difficult to estimate at
this point,’ or ‘Not making losses, but not making
too much profit.’ A second author confirmed this
categorization. We then calculated two qualitative
performance measures: proportion of all comments
that were positive and proportion that were negative.
These measures are likely to be accurate because
they span informants and hierarchical levels, thereby
providing a robust and rich assessment of process
performance from multiple vantage points.
We combined the performance measures (log of
average revenue, Likert scale rating, and qualitative performance assessments) using factor analysis.
This produced a single factor with an eigenvalue >1
(i.e., 2.2). Loadings occurred as expected with very
high positive loadings (0.8) for both the Likert scale
rating and the proportion of positive comments, a
very negative loading (−0.8) for the proportion of
negative comments, and a positive loading for log
of average revenue growth (0.6). The performance
factor score has a mean of 0 and a standard deviation
of 0.9. Using multiple, independent assessments of
performance that are congruent provides convergent
validation and a more reliable performance measure
than is possible from objective or subjective measures alone.
Independent variables
Cumulative experience
We measured cumulative experience as a count of
the total country entries performed by a firm prior
to the focal entry. Our measure is consistent with
existing literature which also measures cumulative
experience as the sum total of events undertaken by
a firm (Haleblian and Finkelstein, 1999; Hayward,
2002).
Time between experiences
Consistent with prior research (Vermeulen and
Barkema, 2002), we measured time between experiences as the number of quarters between the focal
country entry and the prior entry. If the entry were
Copyright © 2007 Strategic Management Society
35
a firm’s first venture into another country, this lag
was coded as the time between founding and the first
entry (the lag between founding and first entry was,
on average, not significantly different than the lag
between other entries).
Similarity of experiences
Similar to others (Brockner et al., 2000; Gibson
and Zellmer-Bruhn, 2001), we measured similarity of experiences as the cultural similarity between
the focal country entry and the firm’s headquarter
country. To measure cultural similarity, we first used
Hofestede’s (2001) index of cultural distance and
calculated index rankings for each country relative
to other countries. We then collapsed Hofstede’s
four dimensions into a single measure of cultural
distance for each country entry using a methodology developed by Kogut and Singh (1988). This
measure calculates the sum of the squared differences for each of Hofstede’s (1980) four primary
cultural dimensions.3
Heuristics
We assessed the existence of heuristics in two different ways: behavioral and cognitive (Cyert and
March, 1963; Miner et al., 2001). First, we captured the behavioral action patterns used to enter
new countries. Specifically, we analyzed the actions
of individuals before and during each country entry.
We then coded actions as heuristics only if they
consisted of a recognized guide for internationalization that was articulated by more than one informant
in each firm.4 Second, we assessed the existence of
3
Studies on the influence of cultural distance often use the four
dimensions of Hofstede (1980): power distance (the degree to
which people accept the unequal distribution of power inside
organizations), uncertainty avoidance (the degree to which
people tolerate uncertainty and ambiguity in situations), individualism (the preference of people to belong to a loosely
versus tightly knit social framework), and masculinity (the
degree to which people prefer values of success and competition over modesty and concern for others). Although Hofstede
(2001) includes a recently developed fifth dimension, we calculated the index using only Hofstede’s original four dimensions
to facilitate comparability to previous empirical studies.
4
To illustrate, to enter new countries one Singapore-based
security software firm followed a heuristic of targeting ‘government and financial institutions.’ As a senior executive stated
about the firm’s entry into Malaysia, ‘Banks have the money to
spend, so you got to focus on them.’ He also added, ‘Government is again by design . . . If so much is going through the IT
infrastructure, then protection is needed.’ The CEO noted the
same target group when he said, ‘What we want is, whether
you are a government agent or bank, when you think about
info-security call (firm name).’
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
36
C. B. Bingham, K. M. Eisenhardt, and N. R. Furr
heuristics from a cognitive perspective. We analyzed
each informant’s articulated descriptions of what the
firm had learned in each country entry that could
be used in other country entries. These descriptions
occurred in response to our open-ended questions
about the chronology of each country entry (e.g.,
Tell me the story of how you received your first
sale?). They also occurred in response to our wrapup questions where we focused on lessons learned
in the country (e.g., What, if any, were the lessons/
insights your firm gained from its experience in this
country?). As with behavioral patterns, we considered these to be articulated heuristics when two or
more informants independently described the same
lessons regarding how to enter new countries.5 Each
author independently examined the data with the
aid of charts, tables, and cell designs to accurately
identify heuristics from both behavioral and cognitive perspectives. Two authors then iterated the differences in assessments using the definition criteria.
The third verified this iteration independently. If
there were still disagreements, the authors iterated
until they agreed (less than 1% of heuristics required
iteration). Finally, we identified and categorized
heuristics independent of the performance data. In
general, the combination of behavioral and cognitive
approaches for assessing heuristics is consistent with
research describing how organizational processes
improve through the development of behavior consistencies, in the form of repeated action patterns,
and through the improvement of cognitive frames,
in the form of enhanced mental models and causal
theories (Miner et al., 2001). This dual approach
5
For example, during the aforementioned firm’s preinternationalization experience in Singapore, management had been
successful by targeting their sales approach to IT groups within
customer organizations. Looking forward, managers believed
IT managers in other countries would also most appreciate their
technology and would have the greatest incentive to purchase
the company’s software solutions since they were responsible
for information security. However, after entering Hong Kong,
the TMT realized that the sales approach of targeting IT groups
was ineffective. Because new technology guidelines required
senior executives to understand the risks associated with their
technology, many Hong Kong corporations had shifted responsibility for information security from IT and into audit. Thus,
the new belief was that managers should target audit groups,
not IT groups (heuristic). The CEO stated, ‘We learned from
experience who makes the decision – the auditors of governments and banks instead of IT. In more and more organizations, IT security is out of IT . . . The audience is the CFO, the
group-auditor, and the CEO.’ Another leader recounted the
same lesson when he said, ‘Instead of talking to the technical
people, we learned that we need talk to the CEO and business
people . . .’
Copyright © 2007 Strategic Management Society
provides ‘thick description’ of heuristics with proximity to the data, and illumination of the learned
content in context.
Total heuristics is the count of heuristics a firm
employed in a focal country entry. It was calculated
as the sum of both lower (selection and procedural)
and higher (temporal and priority) order heuristics
used in a focal entry.
Lower order heuristics is the count of selection
and procedural heuristics employed in a country
entry. We categorized heuristics as ‘selection heuristics’ if the articulated knowledge specified which
countries to enter, which customers to pursue, or
which products to promote in each new country.
Examples include ‘Enter English speaking markets,’
‘Focus on large original device manufacturers,’ and
‘Promote electronic diary solutions.’ We categorized
heuristics as ‘procedural heuristics’ if consistencies
existed regarding how to enter new countries such
as, ‘Use acquisitions,’ ‘Use joint venture partnerships,’ or ‘Hire experienced locals using the advisory board.’
Higher order heuristics is the count of temporal
and priority heuristics used in each country entry. We
categorized heuristics as ‘temporal heuristics’ if consistencies emerged about (1) pacing (i.e., executing
processes in cadence with some internal timing); (2)
synchronization, (i.e., executing a process in cadence
with some external timing); and (3) sequence, (i.e.,
the order of experiences that the firm needs to follow).
Examples include, ‘Enter one country at a time,’
‘Regulate entry according to the market readiness of
the country,’ and ‘Build up Europe, move to U.S.,
then China.’ We categorized heuristics as ‘priority
heuristics’ if consistencies emerged about opportunity rankings such as ‘Tier-three countries’ or ‘Large
European retail markets.’
Control variables
We controlled for the country entry team because
internationalization research indicates that these
management teams may affect process performance
(e.g., Carpenter, Sanders, and Gregersen, 2001;
Daily, Certo, and Dalton, 2000). Consistent with
this work, we define a country entry team as those
individuals directly involved with deciding and
executing the country approach, and who had direct
responsibility for the performance of the country
entry. We control for three effects suggested by the
literature: team size, team functional diversity and
team international experience.
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
What Makes a Process a Capability?
Team size is the count of country entry team
members. Controlling for team size is important since
research demonstrates that a larger team increases
the quantity of skills and attention available to the
firm (Eisenhardt and Schoonhoven, 1990).
Team functional diversity is an index measuring
the diversity of functional roles in the country entry
team. A diverse team is better able to manage the
multi-faceted nature of international entry as well
as lead to more effective problem solving by adding
more divergent views (Bantel and Jackson, 1989;
Carpenter and Fredrickson, 2001). Consistent with
previous research, we operationalize functional
diversity by first classifying individuals using functional classifications established in the literature such
as backgrounds in sales, engineering, and marketing
(Bantel and Jackson, 1989; Michel and Hambrick,
1992; Wiersema and Bantel, 1992). We then calculated a team heterogeneity measure using Blau’s
(1977) method (heterogeneity is measured as 1 − Σ
(Pi)2 where Pi represents the percentage of individuals with a background in category i).
Team international experience is the number of
country entry team members who had lived and
worked outside their home country for over one year
(Carpenter, Pollock, and Leary, 2003; Sambharya,
1996). Controlling for team international experience is important since prior research suggests that
such experience leads to a greater understanding
of foreign customers, employees, and competitors
and so can improve process performance (Carpenter
et al., 2001; Daily et al., 2000).
In results available from the authors, we also
examined additional controls beyond those reported.
These include year indicators for temporal effects;
firm indicators for firm-specific effects and for firm
size, age, and headquarters location; and country
entry indicators such as entry mode. None of these
controls was significant or influenced the hypothesized results, and so they were eliminated from
the models in order to focus on the estimation of
theoretically relevant variables.
Estimation technique
Given that we treat our data as cross-sectional
rather than panel data, we use ordinary least squares
regression (OLS) which, similar to random effects,
combines an un-weighted average of between and
fixed effects (Kennedy 2003). In early estimations,
we included indicator variables to control for firm
effects but these variables dropped out of signifiCopyright © 2007 Strategic Management Society
37
cance. Therefore, we concluded that we had enough
variables controlling for firm effects, and that OLS
was the most appropriate technique in this situation. OLS results were tested for violations of the
standard assumptions including autocorrelation and
heteroskedasticity. We found no violations. We
further tested for the correct specification using the
Ramsey (1969) omitted variable test and found no
support for omitted variables. In results available
from the authors, we confirmed our results using
cluster analysis and ordered probit for three and six
clusters of performance. Overall, our use of OLS is
consistent with prior studies exploring sequential,
discrete activities (e.g., country entries, acquisitions)
performed by single firms (Hayward, 2002; Vermeulen and Barkema, 2001).6
RESULTS
Table 1 reports descriptive statistics and correlations. Table 2 presents the OLS regression results.
Model 1 includes the team control variables. Of the
three team control variables (i.e., size, functional
diversity, and international experience) only team
functional diversity is significant (p < 0.01). The
overall model is significant (p < 0.10).
Model 2 adds the results for the experience
hypotheses (H1–H3). Hypothesis 1 predicted that
cumulative experience is positively associated with
country performance. This hypothesis is not supported. Hypothesis 2 predicted that the time between
experiences has an inverted U-shaped relationship
with country performance. Results show that the
linear term is not supported and the quadratic term is
6
We considered several alternative statistical techniques. A
fixed effects model, which is used primarily with panel data,
was viewed as less appropriate for several reasons. First, fixedeffects models eliminate across-firm variation, a key source of
interest to the study. Second, although we tested fixed effects,
resulting models were generally poor and failed to reject the null
hypothesis that the mean of firm indicator variables was equal
to zero, suggesting that our current variables may sufficiently
control for firm effects. Third, we tested a between fixed-effects
model, which models between firm variation without accounting for within firm variation, and found that, although in line
with our hypotheses, the overall model was only weakly significant due to the heavy loss of degrees of freedom. Besides
fixed effects, we tested a random effects model which combines
a matrix-weighted average of the between and fixed effects
estimators. The results supported our hypotheses but we did use
random effects models because they are generally appropriate
for panel data, not cross sectional data.
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
Copyright © 2007 Strategic Management Society
6.37
3.75
3.07
24.63
4 Team Intern. Exp
5 Cumulative Experience
6 Time Btwn Experience
7 Time Btwn Experience2
7.71
5.88
1.69
11 Lower Order Heuristics
12 Higher Order Heuristics
4.54
10 Total Heuristics
9 Similar Experience
1.69
0.18
3 Team Funct. Diversity
2
2.31
2 Team Size
8 Similar Experience
0.89
−0.02
1 Performance
2.06
2.39
4.10
6.31
1.30
54.02
3.93
2.24
7.07
0.25
1.44
S.D.
Mean
Variable
0.41
0.47
0.09
0.21
0.18
0.08
−0.03
0.49
0.05
0.01
0.26
−0.04
−0.45
−0.16
0.19
−0.35
−0.07
0.01
0.53
2
0.29
0.17
1
Table 1. Descriptive statistics and bivariate correlations
0.02
0.13
0.10
0.04
0.03
0.22
0.28
−0.37
−0.09
3
−0.05
−0.23
−0.27
−0.13
−0.28
−0.31
−0.20
0.01
−0.28
−0.28
5
0.06
0.10
−0.19
−0.16
0.49
4
−0.17
−0.11
−0.16
0.02
0.04
0.94
6
−0.20
−0.17
−0.21
0.07
0.10
7
0.07
−0.16
−0.07
0.94
8
0.12
−0.13
−0.01
9
0.87
0.88
10
0.54
11
12
38
C. B. Bingham, K. M. Eisenhardt, and N. R. Furr
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
What Makes a Process a Capability?
39
Table 2. OLS regression results
Variable
Model 1
(Controls)
Model F Value
Adjusted R-square
N
Team Size
Team Functional Diversity
Team International Experience
Model 2
(Exp &
Controls)
Model 3
(Controls &
Heuristics)
Model 4
(Controls &
Heuristic
Types)
Model 5
(Full Model)
Model 6
(Parsimonious
Model)
2.54*
0.06
67
1.53
0.06
67
6.07****
0.23
67
4.96****
0.23
67
3.6****
0.28
67
7.47****
0.33
67
−0.02
(0.09)
1.19***
(0.50)
−0.00
(0.01)
0.05
(0.10)
0.74*
(0.56)
−0.00
(0.01)
−0.05
(0.06)
0.09
(0.09)
−0.00*
(0.00)
0.51**
(0.26)
−0.10**
(0.05)
−0.05
(0.08)
1.21***
(0.45)
0.00
(0.01)
−0.05
(0.08)
1.22****
(0.45)
0.00
(0.01)
0.00
(0.09)
0.76*
(0.49)
0.01
(0.01)
−0.02
(0.05)
0.04
(0.08)
−0.00
(0.00)
0.55***
(0.23)
−0.11***
(0.04)
0.54***
(0.21)
−0.11***
(0.04)
0.11**
(0.05)
0.12***
(0.05)
0.11***
(0.04)
0.12***
(0.05)
Cumulative Experience
Time Between Experience
Time Between Experience2
Similarity of Experience
Similarity of Experience2
Total Heuristics
Lower Order Heuristics
Higher Order Heuristics
0.87***
(0.36)
0.09****
(0.02)
0.09**
(0.04)
0.11**
(0.05)
Coefficients with standard errors listed under coefficients
****p < 0.001; ***p < 0.01; **p < 0.05; *p < 0.10
only weakly supported (p < 0.10).7 Hypothesis 3 predicted that similarity in experience has an inverted
U-shaped relationship with country performance,
and is supported (p < 0.05). As a robustness check,
we also measured similarity in experience as the
cultural distance between a focal entry and the entry
immediately preceding it (Kogut and Singh, 1988).
Because this measure provided roughly equivalent
results, we do not report them in our tables. The
overall model is not significant.
7
We further tested linear models for experience inverted Us
that were not significant (i.e., time between experience) and
found that they were still not significant.
Copyright © 2007 Strategic Management Society
Model 3 presents the results of total heuristics
(H4), including the team control variables. Hypothesis 4 predicted that an increase in the total number
of heuristics would positively impact process performance. The overall model is highly significant
(p < 0.001) and provides strong support for Hypothesis 4 (p < 0.001) indicating that the greater the
number of heuristics a firm employs when entering a new country, the greater its performance in
that country. Model 3 also shows that the relationship between heuristics and process performance is
much more significant than the effects of experience alone (adjusted R-square value of 0.23 versus
0.06).
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
40
C. B. Bingham, K. M. Eisenhardt, and N. R. Furr
Model 4 presents the results of the lower and
higher order heuristics (H5–H6), including the
control variables from Model 1 regressed on process
performance. We entered these variables as a separate theoretical block from total heuristics due to
high correlation between total heuristics and heuristic types (see Table 1). Hypotheses 5 and 6 predicted that lower and higher order heuristics would
each have a positive effect on performance. Results
show that the model is highly significant (p < 0.001)
with an adjusted R-square of 0.23. There is strong
and significant support for Hypothesis 5 (p < 0.05).
The greater the number of lower order heuristics,
the higher the country performance. Model 4 also
strongly and significantly supports Hypothesis 6
(p < 0.05) indicating that the greater the number
of higher order heuristics, the higher the
performance.
Model 5 presents a full model with all control
and hypothesized variables. This model is highly
significant (p < 0.001) with continued statistical significance for similarity of experience (inverted U)
(H3), lower order heuristics (H5) and higher order
heuristics (H6). However, time between experiences
(H2) is no longer significant. Model 6 is a parsimonious version of Model 5, and includes only those
variables with statistical significance in previous
models. This model is also highly significant (p <
0.001) with an adjusted R-square of 0.33. Together,
Models 5 and 6 suggest that heuristics and experience similarity have significant and positive relationships with country performance, with heuristics
having much stronger effects.
DISCUSSION
Organizational processes such as internationalization, acquisition, alliance, and product development are central within the strategy, organizations,
and entrepreneurship literatures. They enable
firm members to perform tasks more effectively
(Pentland, 1995; Ray et al., 2004; Teece et al., 1997),
capture fresh opportunities for growth (Gilbert,
2006), adapt to changes in the market (Brown and
Eisenhardt, 1997) and, when high-performing, constitute a primary feature of capabilities (Amit and
Schoemaker, 1993; Eisenhardt and Martin, 2000;
Maritan, 2001). Yet, the source of high performing
organizational processes is unclear. One research
stream emphasizes organizational learning from
experience. In contrast, an emerging research
Copyright © 2007 Strategic Management Society
stream emphasizes organizational cognition and, in
particular, heuristics. Our purpose is to juxtapose these competing theoretical explanations
to gain insight into organizational processes and
capabilities.
Principal results: heuristics-basis of capabilities
Our core contribution is the insight that heuristics
are at the heart of high performing organizational
processes, and so are central to firm capabilities.
Specifically, we find that high performing organizational processes consist of heuristics – i.e., informal
rules-of-thumb that center on the capture of opportunities within flows of process-specific opportunities
(e.g., new countries, acquisition targets, or product
development projects). We also find that more heuristics relate to higher process performance. Moreover,
high performing organizational processes consist of
particular types of heuristics. These are lower order
heuristics for choosing (selection) and executing
(procedural) opportunities. For example, in one very
high performing country entry, firm members used
several selection heuristics such as ‘Focus on low
cost chips for mobile devices,’ and ‘Target countries
that have ODMs or OEMs for mobile devices,’ and
several procedural heuristics such as ‘Use a consultant to provide introductions and insight about the
local market,’ and ‘Segment customers into tiers.’
We also find that higher order heuristics for pacing,
sequencing, synchronizing (temporal) and ranking
(priority) multiple opportunities are especially
related to higher process performance. To illustrate, in one very high performing entry described
as ‘perfect,’ firm members used several temporal
and priority heuristics such as ‘Take one continent
at a time (i.e., build up Europe, move to U.S., then
China),’ ‘Synchronize entry pace with country’s
retail lifecycle,’ and ‘Begin with direct sales (then
move to indirect sales).’ In contrast, in low performing country entries, firm members have very few
heuristics that apply across country entries. Rather,
they mostly engage in country-specific learning and
related behaviors without developing or adapting
more generalized heuristics. Firm members are particularly unlikely to have higher-order heuristics that
signal cognitive sophistication and expertness. For
example, in one very low performing country entry
(e.g., ‘not really any sales’), heuristics were notably
absent. As the CEO noted, ‘We’re taking it opportunistically.’ Thus, we find that simply accumulatStrat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
What Makes a Process a Capability?
ing experience (even when paced and appropriately
similar) is weakly or not at all associated with a high
performing process.
A related contribution is the insight that ‘opportunity-capture’ heuristics are also central to capabilities. Although there is much debate on capabilities
in the literature, there is convergence on several
themes. First, capabilities rely extensively on organizational processes (Amit and Schoemaker, 1993;
Eisenhardt and Martin, 2000; Helfat et al., 2007;
Teece et al., 1997). For example, Stalk and colleagues (1992: 62) stated that ‘a capability is a set
of business processes strategically understood,’
while Eisenhardt and Martin (2000: 1106) noted that
‘dynamic capabilities consist of specific strategic
and organizational processes . . .’ Second, capabilities are learned from experience. Therefore, while
preexisting endowments (e.g., human capital of
founding team) may set the stage for capability creation (Gavetti, 2005; Helfat and Lieberman, 2002),
capabilities are primarily learned through ‘doing’
as firm members enhance their understanding of
causal relationships with accumulated experience
(Chang, 1995; Helfat and Peteraf, 2003; Martin and
Salomon, 2003). Finally, there is consensus on the
need for high performance if a capability is to exist.
Thus, several studies show how the presence of a
capability results in increased effectiveness (Zollo
and Winter, 2002), productivity (Galunic and Eisenhardt, 2001; Makadok, 2001) or efficiency (Collis,
1994). In short, a central purpose of capabilities
is ‘to improve performance’ (Maritan, 2001: 514).
Yet while there is convergence on these aspects of
capabilities, their actual content is unclear. Some
empirical research equates the content of capabilities with outcomes such as measures of firm performance (e.g., abnormal stock market returns) or
non-financial measures of process performance
(e.g., subjective measures of project development
performance) (for a review see Ethiraj, Kale, and
Krishnan, 2005). But this approach focuses on the
results of capabilities, not their actual content. Some
theoretical research argues that capabilities consist
of resources, but lacks specifics about content (e.g.,
types of resources, organization of tacit knowledge)
(Barney, 1991; Helfat and Peteraf, 2003). Still
other research points to the content of capabilities
as being best practice (Szulanski, 1996) or codified
knowledge (Kale and Singh, 2007; Zollo and Singh,
2004; Zollo and Winter, 2002), but also generally
neglects details about content (e.g., structure and
types of codified knowledge). In contrast, by using
Copyright © 2007 Strategic Management Society
41
a methodology that opens the ‘black box’ of what is
learned from organizational process experience, we
can be more specific about the actual content of firm
capabilities. Thus, a core contribution of our study
is that ‘opportunity-capture’ heuristics are central to
the structure of capabilities, especially in dynamic
markets and among entrepreneurial firms.
Another contribution is expanding the role of cognition in the creation of capabilities. While prior
work highlights how cognitive phenomena such
as threat vs. opportunity framing (Gilbert, 2006),
analogy (Gavetti, Levinthal, and Rivkin, 2005), and
identity (Tripsas and Gavetti, 2000) can influence
capability development, we contribute heuristics to
this emergent cognitive emphasis. In particular, we
show how the creation of heuristics involves active
cognitive engagement and results in the formation
of a robust organizational memory needed for effectively coping in dynamic markets. Memory is associated with the brain’s efforts to impose structure
on experience (Edelman, 1992). Numerous studies
in the cognitive sciences show that memory performance is highly influenced by the encoding of experience (Broadbent, 1958; Miller, 1956). Without
some form of encoding, individuals often reflect less
on their experiences and thus retain only incomplete and impoverished recollections of what they
have done and how they did it (Schachter, 1996).
This in turn increases the likelihood that short-term
experiential lessons will not make it to longer-term
memory and be inaccurately recalled (if at all) in
the future (Braddeley and Hitch, 1974; Broadbent,
1958). Intriguingly however, research also suggests
that only a certain type of encoding generates high
long-term memory performance – a cognitively
sophisticated encoding consisting of simple (not
elaborate) lessons that allow individuals to combine
new information with existing knowledge (Braddeley and Hitch, 1974; Broadbent, 1958). Heuristics
provide such an encoding because their semi-structure gives shape to organizational processes, but
also leaves room for heedful cognitive engagement
such as improvisation. Encoding of experience into
generalizeable heuristics may, therefore, not only
improve the quantity of organizational memory, but
also its quality such that firms are better able to adapt
to uncertain situations. Overall, while prior work
on heuristics in the entrepreneurship domain often
points to their maladaptive nature (Busenitz and
Barney, 1997), we spotlight their adaptive nature as
simple, deep, and flexible knowledge structures that
underpin capabilities.
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
42
C. B. Bingham, K. M. Eisenhardt, and N. R. Furr
Implications for strategy: extending the
strategic logic of opportunity
Our work also contributes to strategy. Recent theory
has sketched a typology of theoretical logics leading
to competitive advantage: position, leverage and
opportunity (Bingham and Eisenhardt, 2007). Yet
while strategic logics of position (Porter, 1996;
Rivkin, 2000) and leverage (Barney, 1991; Peteraf
1993) are well-known, the strategic logic of opportunity is less well-developed. Although this logic
is implicit in empirical research (Burgelman, 1996;
Rindova and Kotha, 2001) and explored by simulation (Davis et al., 2007), this study is the first
to validate the logic empirically. Specifically, we
confirm the theory underpinning the strategic logic of
opportunity – i.e., superior performance in dynamic
markets and among entrepreneurial firms comes
from choosing one or a few key organizational processes that put the firm in abundant and attractive
opportunity flows, and developing simple heuristics
to guide the effective capture of those opportunities.
While past empirical research reveals that firms learn
‘opportunity capture’ heuristics from accumulating
experience (Bingham et al., 2007), this study ties
those heuristics to performance. That is, we support
the strategic logic of opportunity that links heuristics
(i.e., their number and types) to effective opportunity capture (and thus, high performance) through
an improvisational mix of efficient rule adherence
and flexible action.
At a broader level, this study may begin to reveal
the essence of strategy in dynamic markets. As
Porter (1996) notes, strategy is about ‘being different.’ But while he focuses on ‘different’ positions
in stable markets, we focus on ‘different’ heuristics in dynamic markets – i.e., the distinctive set of
heuristics developed by firms as their idiosyncratic
decisions for how to compete. Although some heuristics may relate to best practices (e.g., conduct
due diligence when entering a country through an
acquisition mode), most are unique choices about
how to be different in a competitively advantageous way. Hence, while all of our firms identified
the internationalization process as being vital and
possessed the same types of heuristics (i.e., selection, procedural, temporal, and priority), the specific
detail of their heuristics varied by firm and formed
the basis of their strategy for ‘being different.’ For
example, three Singapore-based firms had different
procedural heuristics for entering countries, even
when they entered the same country (Japan). One
Copyright © 2007 Strategic Management Society
firm’s heuristics focused on using U.S. venture capitalists for insight (e.g., as the Japan country manager
stated, ‘We have American investors, like DFJ and
Walden International. They gave us some great
advice about who to work with, what to do, and
what to start with.’) In contrast, a second firm relied
on the local subsidiaries of multi-national corporations (e.g., their Japan country manager noted, ‘We
talk to quite a few people such as IBM Japan . . . It
gave us a very good sense of the Japanese market.’)
The third company watched the moves of prominent competitors. Overall, the uniqueness (and likely
inimitability) of heuristics reinforces the key point
that organizational processes such as internationalization and their related heuristics are not just
relevant for strategy, but perhaps are the strategy,
especially in dynamic markets and among entrepreneurial firms.
Implications for entrepreneurship: opportunity
capture and the role of structure
Our work contributes to entrepreneurship in several
ways. One contribution is sharpening understanding of opportunity capture in dynamic markets.
Prior research debates whether opportunities
are discovered or created (Kirzner, 1997; Shane,
2000). In contrast, we note that our entrepreneurs
had a super-abundance of opportunities (e.g., many
potential countries). For example, one leader said
his firm could potentially ‘sell in 139 countries.’
Since abundant opportunities imply that opportunities are readily discovered, entrepreneurs can be discriminating and pick the most promising. Moreover,
although we saw many easily discovered opportunities, these opportunities were also ill-formed, and so
were more effectively captured when firm members
relied on heuristics. Heuristics appeared to guide
the extensive improvisational behavior needed to
adjust to the unique aspects of each opportunity.
As a whole, these arguments suggest that opportunity capture for firms in dynamic markets may be
more about appropriate selection and execution of
opportunities, and less about discovery or creation.
Since these environments are opportunity-rich, discovery is not difficult, and creation can be inefficient
when it leads to the under-exploitation of present
possibilities. Rather, the imperative for managers in
these unpredictable settings is using organizational
heuristics as improvisational referents to provide a
flexible constraint within which opportunity capture
may unfold.
Strat. Entrepreneurship J., 1: 27–47 (2007)
DOI: 10.1002/sej
What Makes a Process a Capability?
Another contribution is insight into the fundamental value of more structure for entrepreneurial firms.
While cutting structure is often vital for established
firms entering dynamic markets (Gilbert, 2005),
our findings suggest that the reverse is actually true
for new firms in these settings. They need to add
structure, especially since new firms lack the coherence, direction and control that structure brings. For
example, a leader in a Finnish security software firm
lacking heuristics remarked that there was ‘No clear
picture of the major countries that we should target.’
In several country entries, leaders in this firm relied
on only a few procedural heuristics, and suffered
uniformly poor performance across countries. By
contrast, in a Singapore security firm, leaders quickly
developed many and different types of heuristics
including selection and procedural heuristics such as
‘Restrict internationalization to Asia,’ ‘Target government and financial institutions,’ ‘Target the IT
group within customer organizations to get sales,’
and ‘Always use a partnership entry mode when
entering new countries.’ Over time, they added more
selection and procedural heuristics such as ‘Hire
an experienced country manager,’ and ‘Employ a
consultative sales approach that highlights value
over technology.’ They also developed temporal
and priority heuristics such as ‘Use Hong Kong as
a springboard to enter larger markets,’ ‘Synchronize
entry with the pace of the local macro economy,’
‘Push 24 × 7 security monitoring, then security
systems integration,’ and ‘Enter one country at a
time.’ Not surprisingly, country entry performance
for this Singaporean security firm was positively
related to their use of heuristics, and was consistently higher (e.g., ‘we own the market’) than that
of its industry counterpart in Finland. Overall, an
important insight of this study is that entrepreneurial firms need to quickly develop structure such as
opportunity capture heuristics. Without structure,
new ventures flounder since they experience neither
order nor traction.
CONCLUSION
While organizational processes are important to
firm action, firm capabilities and even strategy,
controversy exists about how they become high
performing. One view emphasizes organizational
learning from experience, while a more recent view
emphasizes organizational cognition and the use
of heuristics. Our core contribution is the insight
Copyright © 2007 Strategic Management Society
43
that heuristics are at the heart of high-performing
processes, and thus firm capabilities. Experience
per se is not enough. Rather experience must be
articulated into ‘opportunity capture’ heuristics to
achieve high-performance. At a broader level, we
offer support for the view that strategy in dynamic
markets and among entrepreneurial firms rests on
a strategic logic of opportunity, and may well be
distinctive heuristics and organizational processes.
Most important, we add heuristics to the increasingly influential cognitive paradigm in organization
theory, strategy, and entrepreneurship.
ACKNOWLEDGEMENT
Support for this research was generously provided by the
National Science Foundation (IOC Award #0323176),
the Robert H. Smith School’s Business and International
Education grant, and the Stanford Technology Ventures
Program.
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