the relationship between organizational learning and firms’ financial performance in strategic...

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(2008) 365–379
Journal of World Business 43
The relationship between organizational learning and firms’

financial performance in strategic alliances: A contingency approach

Xu Jiang, Yuan Li *

School of Management, Xi’an Jiaotong University, 710049 Xi’an, PR China

Abstract

This study examines the relationship between organizational learning and firm-level financial performance in the context of

strategic alliances. The strength of the relationship is also examined in light of possible moderating effects of the form, scope, and

competitive regime of the alliance. On the whole, results from a survey of 127 German partnering firms support a contingency

approach to firm performance using structural equation modeling. Results suggest a significant, positive, and strong relationship

between organizational learning and financial performance. This positive relationship is stronger in joint ventures and weaker in

contractual alliances. Also, the relationship is stronger when the partners are based on the same industry and weaker when they are

across industries. However, while it is proposed that the above relationship will be stronger in alliances with broader scope, the

empirical results only partially support this hypothesis.

# 2007 Elsevier Inc. All rights reserved.

Keywords: Strategic alliances; Organizational learning; Performance; Contingency

1. Introduction

The pursuit of superior performance at the partner-

ing-firm level has aroused great interest among

researchers. In the context of strategic alliances, it is

recognized that firm performance cannot be adequately

evaluated without taking into consideration firms’

motives for forming alliances. Historically, the purpose

of a strategic alliance was to improve performance of

the firm through risk sharing and cost reduction. Today,

firms strive to pursue superior performance through the

development of new products, processes, and services

with the help of the partners. As products and services

have become increasingly knowledge intensive, the

* Corresponding author. Tel.: +86 29 82665093;

fax: +86 29 82668382.

E-mail addresses: [email protected] (X. Jiang),

[email protected] (Y. Li).

1090-9516/$ – see front matter # 2007 Elsevier Inc. All rights reserved.

doi:10.1016/j.jwb.2007.11.003

decision to form alliances has gradually come to depend

more upon the partners’ abilities to effectively and

efficiently learn by acquiring each other’s knowledge,

resources, and capabilities (Ainuddin, Beamish, Hul-

land, & Rouse, 2007; Bedrow & Lane, 2003; Kale,

Singh, & Perlmutter, 2000).

Although organizational learning has often been

viewed as an end in itself, from the perspective of

shareholders the final objective of many partnering

firms should be an improvement in financial results,

such as productivity or profitability. This perspective

requires us to shed light on some important research

questions. For example, while firms are seeking to gain

competitive advantage by engaging in interorganiza-

tional learning, we need to understand whether the

organizational learning has an impact on their financial

performance and whether such impact will be condi-

tioned by other factors. In this paper, we attempt to

answer these two questions by conducting an empirical

study.

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http://dx.doi.org/10.1016/j.jwb.2007.11.003

X. Jiang, Y. Li / Journal of World Business 43 (2008) 365–379366

A great deal of research has emphasized the

importance of organizational learning and the processes

through which learning occurs (Bruton, Lohrke, & Lu,

2004). The critical role of organizational learning, in

terms of learning orientation, learning capability or

learning organization, in overall business or economic

performance has been widely documented in the

literature (e.g., Calantone, Cavusgil, & Zhao, 2002;

Prieto & Revilla, 2006; Tippins & Sohi, 2003). This

research has identified organizational learning as a key

factor for performance outcomes. And the ability to

learn from external sources has become critically

important for deriving competitive advantage. The

research has, however, examined the learning–perfor-

mance link mainly at the single firm level. We have

therefore relatively limited knowledge about whether

organizational learning has a similar impact on firms’

financial results in the context of strategic alliances

(compare Simonin, 1997).

Further, it seems unlikely that organizational learning

will affect firm performance equally under all conditions.

Indeed, we know that not all learning strategies will

always improve performance (e.g., Baker & Sinkula,

1999; Santos-Vijande, Sanzo-Perez, Alvarez-Gonzalez,

& Vazquez-Casielles, 2005). Researchers are beginning

to recognize that the learning–performance relationship

may be contingent on other factors. For example,

Calantone et al. (2002) propose that the effect of a firm’s

learning orientation on its performance depends on the

firm’s characteristics, i.e., the age of the organization.

Mohr and Sengupta (2002) argue also that governance

mechanisms may moderate the relationship between

interfirm learning and the benefits of such learning.

These studies suggest that the effect of learning on

performance may magnify under certain conditions but

diminish under other conditions. Therefore, it is best to

use contingency theory to more accurately examine this

relationship. Contingency theory stresses choosing

appropriate collaborative settings for enhancing the

benefits of learning (e.g., Mohr & Sengupta, 2002;

Simonin, 2004). Hence, the present study postulates that

the performance impact of organizational learning will

be contingent upon three alliance-level contextual

factors: the governance form of the alliance, the scope

of the joint activity, and the fact that partners may or

may not be in competition with each other.

The primary aim of this paper is to present a

theoretical model and empirical analysis of the

relationship between organizational learning and firms’

financial performance in strategic alliances. It also

contributes to knowledge about the moderating role of

three alliance characteristics in such a relationship. In

the next section, the conceptual framework is presented

and hypotheses are proposed. Then, the hypotheses of

both main and moderating effects are tested on a sample

of 127 German partnering firms. Following a discussion

of results, we present implications, limitations, and

directions for future research.

2. Theoretical background and hypotheses

2.1. Interorganizational learning

A diversity of perspectives and approaches has been

used to study organizational learning. Early learning

theory researchers argue that learning takes place at the

individual level, and individuals learn as agents for the

organization (March, 1991; Simon, 1991). Even though

learning must be undertaken by individuals, it also

depends on different circumstances or situational cues

in which the individuals are embedded. Learning occurs

also at the group, organizational, industrial, and even

social levels (Miller, 1996). Thus, we have to under-

stand learning by putting it in a specific strategic context

(Crossan, Lane, & White, 1999).

We would like to stress that whereas most prior

studies view learning as a firm-level construct, we

extend this unit of analysis to an interorganizational

level. The interorganizational learning perspective

views strategic alliances as a means to learn or

internalize critical skills or capabilities from the

partners (e.g., Khanna, Gulati, & Nohria, 1998; Lane

& Lubatkin, 1998). Khanna et al. (1998) call such

alliances ‘‘learning alliances.’’ Learning alliances

constitute an important environment for interpartner

learning and can be used as important vehicles for

accessing and acquiring organizationally embedded

knowledge, which because of its tacit character is

difficult to transfer and imitate (Kogut, 1988).

In the strategic alliance field, research on organiza-

tional learning has been mainly concerned with issues

regarding what organizational learning is and how

partners learn from each other. While there have been

numerous attempts to define and conceptualize orga-

nizational learning, at a basic level it is the dynamic

process of acquiring, generating, and exploiting

valuable knowledge through interaction, communica-

tion, interpretation, and comprehension across partners.

This process may lead to new knowledge about

customers and markets, about technical know-how,

about alliance management skills, and about the

partners themselves (Zollo, Reuer, & Singh, 2002).

Organizational learning is a continuous, dynamic,

and interactive process between individuals, groups,

X. Jiang, Y. Li / Journal of World Business 43 (2008) 365–379 367

and organizations (Lane & Lubatkin, 1998). It has both

an individual and a social component. The individual

component points to what Grant (1996, pp. 115–116)

refers to as ‘‘individual knowledge,’’ which is the

knowledge carried by individuals, whereas the social

component points to ‘‘common knowledge,’’ the

knowledge shared by all organizational members.

Common knowledge is the intersection of individual

knowledge sets (Grant, 1996). It resides in the

organizational context and thus very much represents

a social phenomenon. The learning process is a

mechanism by which firms transform the individual

and common knowledge into systems, structures,

procedures, and strategy that result in competitive

advantage and superior performance for the firm (Slater

& Narver, 1995).

If a firm aims to acquire valuable knowledge from its

partners, it must simultaneously have both learning intent

and learning capability (Simonin, 2004). Learning intent

refers to a firm’s initial propensity to view the cooperation

as an opportunity to internalize the partners’ knowledge

and skills (Hamel, 1991, pp. 89–90). Scholars often view

learning intent as one of the major determinants of

learning success. For instance, Hamel (1991), using case

studies, indicates that firms that possess a strong learning

intent and develop an appropriate learning environment

win the ‘‘race to learn.’’ In an international alliance

context, Simonin (2004) finds a strong and positive

relationship between learning intention and knowledge

transfer, an outcome of organizational learning. In an

empirical study of 62 firms, Wang, Tong, and Koh (2004)

find evidence that the greater the China subsidiary

employees’ intent to learn, the more knowledge the

subsidiary learns from their parents.

A firm’s learning capability depends on its ability to

identify, assimilate, and internalize the partners’

knowledge and finally generate rents from the knowl-

edge (Lane & Lubatkin, 1998). Prior studies have

widely acknowledged the critical role of learning

capability in enabling partner firms to learn from each

other (for more detailed analysis, see Simonin, 2004).

Generally, a firm that possesses a higher level of

learning capability is likely to have a full understanding

of knowledge outside its boundaries, the ability to

exploit the knowledge at a faster speed, and therefore a

higher possibility of succeeding in learning and

knowledge acquisition.

2.2. Firm performance

Performance issues have long been an enduring

research theme in alliance literature. Many of the

previous studies have focused on assessing the

performance of the alliance itself, but such a focus

on alliance performance alone may be problematic. The

real financial results of alliances are often not reported,

primarily due to the hybrid structures and transitory

nature of alliances. Alliances’ success and performance

must ultimately translate into a competitive advantage

and superior performance of their parent firms (for more

detailed analysis, see Das & Teng, 2003). Hence, the

partnering-firm-level performance might be a critical

theme in alliance research.

There is no generally accepted measure of firm

performance in the literature, but since accounting-

based or financial results are the final objectives of

many partnering firms, this study focuses on financial

performance in particular. Prior empirical studies show

that performance is a multidimensional construct that

should be measured with multiple items (Dess &

Robinson, 1984). Accordingly, this study operationa-

lizes firm financial performance in terms of improve-

ments in sales, profitability, ROA, and ROI.

2.3. Relationship between learning and

performance

The importance of organizational learning for

performance improvement has long been recognized

in research (Slater & Narver, 1995). There is also

extensive empirical evidence for the direct impact of

organizational learning or learning orientation on

financial as well as non-financial performance, both

in the marketing field (e.g., Baker & Sinkula, 1999;

Calantone et al., 2002; Panayides, 2007; Santos-Vijande

et al., 2005) and in strategic management literature

(e.g., Ellinger, Ellinger, Yang, & Howton, 2002; Lane,

Salk, & Lyles, 2001; Prieto & Revilla, 2006; Tippins &

Sohi, 2003). However, as indicated earlier, these studies

have mainly been conducted at the single firm level, and

empirical evidence is still lacking in the alliance

context. In one exception, however, Simonin (1997)

tests influences of experiential learning and collabora-

tive know-how on tangible and intangible collaborative

benefits and finds evidence that firms do learn from past

collaborations by developing collaborative know-how,

which enables the firms to benefit more from their

strategic alliances.

We propose that organizational learning facilitates

interfirm knowledge transfer and sharing which in turn

leads to improvements in partner firms’ financial

performance. More specifically, the emerging knowl-

edge-based theory of the firm posits that valuable, rare,

and not easily imitable knowledge is a fundamental


source of sustainable competitive advantage (Grant,

1996; Spender, 1996). The extent of this contribution is

often dependent on the organization’s capability to learn

from external sources (Hitt, Ireland, & Lee, 2000). In an

alliance setting, organizational learning performs a dual

role of both acquiring existing knowledge that other

partners already possess and generating new knowl-

edge. This knowledge can be converted into new

products, processes, and services, which contribute

directly to the firms’ final financial results.

Slater and Narver (1995) argue that a firm which is

continuously engaged in learning tends to stand a better

chance of tracking and responding to customer needs,

sensing and seizing on market opportunities, and

offering appropriate and finely targeted products, results

which lead to superior levels of profitability, sales

growth, and customer retention. Through learning from

each other, partners may accumulate substantial

experience and lessons on how to avoid repetitious

mistakes, how to reduce production costs and transac-

tion costs, and how to enhance the capacity of mutual

understanding, coordination, and problem solving (Lei,

Slocum, & Pitts, 1997; Simonin, 1997). All of these

theoretical traditions and empirical evidences suggest

that the firms’ ability to learn from partners leads to a

sustainable improvement in their performance, as

measured through financial assets. Hence, we propose:

Hypothesis 1. Organizational learning will be posi-

tively related to partner firms’ financial performance.

2.4. Moderating effects

Hypothesis 1 does not mean that organizational

learning improves the performance of all partners

equally. Past studies have paid little attention to the

conditions under which learning strategies may con-

tribute differently to firm performance. Organizational

learning should not be separated from the collaborative

context within which it takes place. Indeed, learning

enables the achievement of performance outcomes only

when a proper context is in place (Mohr & Sengupta,

2002; Simonin, 2004).

Taking an analytical approach similar to that of

Hennart (2006), we propose that a focus on alliance

conditions such as the form, scope, and competitive

regime of the alliance gives us a parsimonious yet

effective understanding of what facilitates or destroys

organizational learning within alliances. Generally,

alliances involve different forms of governance struc-

tures, different numbers of joint activities, and different

levels of interfirm competition. These contextual factors

constitute an environment for interorganizational learn-

ing to occur in. If we want to accurately illustrate the

learning–performance relationship, we must consider the

effects of the contextual realities. Next, we posit that the

learning–performance relationship is likely to be

moderated by three contextual factors: the form, scope,

and competitive regime of the alliance. We will show that

the interaction between these alliance conditions and

organizational learning can better explain the sources of

performance differences among partners.

2.4.1. Alliance form

One important contingency that may affect the

learning–performance relationship is the governance

structure of the alliance. Transaction cost economics

argues that alliances may include a variety of

governance forms that lie between internal hierarchies

at one extreme and market exchanges at the other. These

alternative forms can primarily be categorized into

equity and non-equity arrangements (Chen & Chen,

2003). Zollo et al. (2002) indicate that these two forms

of alliances ‘‘have different underlying governance

properties that affect their functioning’’ (p. 704). Hence,

it is reasonable to expect that the benefits of

organizational learning will differ across alliances.

Some studies have emphasized the critical impor-

tance of governance mechanisms in moderating the

relationship between interfirm learning and learning

benefits. For example, Mohr and Sengupta (2002) argue

that the interaction between appropriate governance

mechanisms and interfirm learning can serve to

maximize the benefits of learning while minimizing

the risks of undesirable outcomes. In the same vein, we

posit that organizational learning potentially has a

larger positive impact on firms’ financial performance

in equity alliances than in non-equity alliances.

As compared to non-equity contractual alliances,

equity alliances such as joint ventures (JVs) have been

argued to be more effective mechanisms in facilitating

organizational learning and knowledge transfer. For

example, Oxley (1997) shows that equity JVs outperform

alternative governance structures in supporting interfirm

learning. Kogut (1988) argues that JVs are more effective

vehicles for the transfer of tacit knowledge, whereas

‘‘other forms of transfer, such as licensing, are ruled out

because the very knowledge being transferred is

organizationally embedded’’ (p. 323). Similarly, Mow-

ery, Oxley, and Silverman (1996) indicate that JVs are

more effective conduits than contract-based alliances for

the transfer of complex capabilities.

Inkpen (1998) argues that two categories of factors

may facilitate organizational learning in strategic


alliances: factors that facilitate interactions among

partners and those that facilitate integration of the

knowledge. Compared to contractual alliances, JVs

involve a higher degree of face-to-face communication,

closer forms of collaboration, and higher levels of trust,

confidence, and interdependence among partners

(Gulati, 1995; Pisano, 1989; Sampson, 2004). These

would enable a better opportunity for interpersonal and

interfirm learning in the JV context (Lane & Lubatkin,

1998). This learning through JVs also inevitably entails

internalization and integration of tacit knowledge and

proprietary know-how. Such organizationally

embedded knowledge is essential to firms’ sustained

competitive advantage and high performance.

In contrast, contractual alliances – those with lower

interconnection, less interdependence, and greater

reversibility – may pose a dilemma to partners who are

desirous of learning from each other: while they need

more interactions to access and acquire knowledge,

the loose interconnection inhibits the open, integrative

communication and discussion needed for learning to

occur. The lower level of communication, trust, and

mutual understanding in contractual alliances con-

strains the efficiency of learning, especially in the

transfer of tacit and complex knowledge. Drawing

upon these arguments, the following hypothesis is

proposed.

Hypothesis 2. The positive relationship between orga-

nizational learning and firm’s financial performance is

stronger in joint venture than in contractual alliances.

2.4.2. Alliance scope

Alliance scope refers to the extent that an alliance

involves multiple and sequential functions or value

chain activities, such as R&D, manufacturing, and

marketing (Oxley & Sampson, 2004). This scope of the

joint activity can vary considerably across different

alliances (Reuer, Zollo, & Singh, 2002). For instance,

some cooperative arrangements are limited to a single

activity (e.g., either R&D or manufacturing or market-

ing) while others involve more areas. Generally, the

scope of alliances with multiple-activity or mixed-

activity is broader than that of those with a single

activity. An alliance will have the broadest scope when

its range of functional areas includes the entire spectrum

of R&D, manufacturing, and marketing activities.

The choice of alliance scope is determined by the

nature of the joint activity, the areas of mutual interest,

and the available resources to achieve value objectives

(Khanna, 1998). The greater the anticipated benefits of

the alliance to the partners (private benefits), the broader

the scope that might be chosen (Khanna et al., 1998).

Therefore, we expect that with the scope of the joint

activity increasing, the benefits of organizational

learning will be magnified.

A broader scope may offer greater opportunity to

communicate, to share ideas, and to develop mutual

understanding and trust. Indeed, alliances with multiple

activities may require greater depth and breadth of

interactions among partners so as to coordinate the joint

activities (Sampson, 2004). These interactions facilitate

the development of organizational learning routines and

the sharing of knowledge and experience that cannot be

obtained in narrower alliances (Oxley, 1997; Pisano,

1989). Moreover, an alliance with more joint activities

may increase the partners’ perspectives, cognitive

resources, and overall problem solving capacity, thus

enhancing their ability to acquire diverse but com-

plementary knowledge (Oxley & Sampson, 2004; Reuer

et al., 2002). As argued earlier, this knowledge can be

applied in commercialization and produce higher level

of profitability and productivity.

All these arguments maintain that the alliance scope

is likely to moderate the learning–performance relation-

ship, with firms in broader alliances more able to accrue

positive benefits from organizational learning. It is

expected that the performance effect of organizational

learning may be the greatest in alliances with the

broadest scope, and lowest when the alliance involves

only one single activity. Hence, the following hypoth-

esis is proposed:


nizational learning and firms’ financial performance is

stronger in alliances where the scope of joint activity is

broader than in alliances where the scope is narrower.

2.4.3. Competitive regime

Competitive regime within alliances refers to the

degree that partner firms seek out the same resources or

target the same markets and customers. In some

alliances, the partners compete directly, whereas in

others there is a relatively low level of competition

among them. Generally, alliances between firms which

operate in the same industry may have a higher level of

interfirm competition as compared to those based on

different industries.

Previous studies have produced contradictory find-

ings on the effectiveness of alliances between firms that

do or could compete. Kogut (1989) and Park and Russo

(1996) find evidence that alliances among direct

competitors are less efficient, less effective, and more

likely to fail. They argue that direct competitors may


lack goal alignment, tend to behave opportunistically,

and face a risk of unintended knowledge leakage, and

that, as a result, these alliances are ineffective in

fostering organizational learning and knowledge shar-

ing. Other scholars (e.g., Dussauge, Garrette, &

Mitchell, 2002; Khanna et al., 1998) propose that

alliances between competing firms may create favor-

able contexts particularly for interorganizational learn-

ing. Consistent with the later view, we postulate that

alliances among firms based on the same industry create

a better strategic window onto each other’s knowledge,

technologies, and competences and thus offer a higher

possibility of producing superior performance.

Although a firm may have multiple potential partners

offering diverse opportunities for organizational learn-

ing, it is easier for it to learn from those firms that have

primary operations in the same industry. Lane and

Lubatkin (1998) argue that if partners are to effectively

learn from each other, they must (a) already share some

basic knowledge relevant to the target knowledge, (b)

have similar compensation practices and organizational

structures, and (c) have similar commercial objectives.

Obviously, firms engaged in the same business are more

likely to meet these requirements and have more

potential to absorb proprietary knowledge from each

other (Park & Russo, 1996).

Conversely, we expect organizational learning to

have a weaker impact on firm performance under the

condition of lower interfirm competition. Firms in a low

competitive environment may find it difficult to

understand or appreciate each other’s areas of compe-

tency and scope of knowledge (Cegarra-Navarro, 2005).

As a result, alliances among firms across industries

would provide fewer opportunities for acquisition of the

specific knowledge and expertise that are important to

their performance improvement. Hence, we propose:


nizational learning and firms’ financial performance is

stronger in alliances where the partners have their

primary operations in the same industry than in alli-

ances where the partners have their primary operations

in different industries.

3. Methodology

3.1. Sample and data collection procedure

3.1.1. Questionnaire design

The hypotheses about the direct and contingent

effects were examined using data collected in a survey

of German firms which were involved in either domestic

or international alliances in the time period of 2000–

2005. The mature market economy of Germany

presented an appropriate context for examining the

learning–performance relationship for three primary

reasons. First, as in other countries, strategic alliances

have become one of the most significant organizational

forms to emerge in the past decades in Germany.

Second, the management and function of these alliances

have become a critical issue for German firms. Third,

our interviews with five top executives suggested that

strategic alliances have become an important platform

for German firms to use when sharing or exchanging

information and knowledge. Many of them now enter

into alliances specifically for the purpose of acquiring

valuable technologies and expertise from their partners.

Therefore, the effectiveness and efficiency of inter-

organizational learning among German firms warrants

detailed study. This type of knowledge gained from

Germany can illuminate the practice in other countries

also, especially in developing ones.

The questionnaire was developed on the basis of a

thorough literature review, first in English. All items in

the questionnaire stemmed from empirical studies cited

earlier. This method not only increased the reliability

and validity of the survey items, but also made the

questions more appealing and easy to answer. The

English questionnaire was then translated into German

for facilitating understanding and answering of the

questions. We pre-tested the German-version survey

instrument with three excellent alliance researchers and

five top executives experienced with strategic alliances

in Germany. The interviews, which were semi-

structured and lasted for about 1.5 hours on average,

allowed us to modify the language suitably, clarify the

survey items, and reject items that were difficult to

understand or that involved unnecessary repetition.

After minor modifications were made, the main survey

was initiated. Finally, the German questionnaire was

again back-translated into English to ensure that the

precise meaning and the cross-cultural equivalence of

the language (Berry, 1980). The exact wording of the

measurement items involved in this study is provided in

Appendix A.

3.1.2. Web-based survey method

Web-based online surveys have been becoming more

and more popular as a data collection method due to the

advantages offered in the research. As compared with

the traditional data collection methods such as postal

survey, facsimile survey, or face-to-face interviews,

Internet surveys may provide such benefits as wider


distribution (even throughout the world), less distribu-

tion bias, better likelihood of thoughtful reply, lower

transmission of non-verbal cues, and more time savings

and cost savings (see Simsek & Veiga, 2001). Following

guidelines suggested by Simsek and Veiga (2001), we

adopted a web-based email survey design by using a

computerized, self-administered online questionnaire to

collect data.

We took a data collection approach similar to that

proposed by Simonin (1997). The informants were

selected by using two key criteria: (1) they should be the

most able to recognize and assess the strategy and

performance-related issues within the organizational

boundaries, and (2) they should also be the most

qualified to report specialized information on specific

alliances and the impacts of these alliances on the firms’

internal activities. Top executives such as presidents,

general managers, or vice general managers would

conform to these requirements. We chose firms’ top

executives as informants in this study.

Participating firms were selected in two general

ways. First, they were randomly identified through

several public sources, such as Internet business guides,

company web pages, directories, and periodical indices

for articles in the journals that reported German

alliances during 2000–2005. We contacted by telephone

the firms identified, and 43 of them promised to

participate in the survey. We then noted the names and

email addresses of the top executives. Second, we

contacted by telephone a set of firms randomly chosen

from the database of IHK, a large German industrial

trade enterprise, to determine whether these firms had

established any form of alliances (either JVs or

contract-based alliances) during the six-year period.

In the case where a firm reported that it had been

involved in one or more alliances and also was willing to

participate in the study, we requested it to provide the

name and email address of a top executive. In this way,

180 firms were selected.

The selection of firms from the two sources left us

with a total of 223 firms targeted for participation. A

cover letter explaining the purpose and requirements of

the survey was then sent by email with a URL-

embedded link to the executives. In the same letter, they

were told that a web-based version of the survey was

available for their convenience. They could easily click

on the hypertext link to directly visit the HTML-version

of the German questionnaire.

The top executives were asked to report information

regarding the most significant alliance case (at least one

year old) with which they were familiar. The most

significant alliance case means that, if a firm has formed

several alliances, the informants should choose what

they consider the most strategically important one for

the purpose of answering our questions. The require-

ment that the alliance must be at least one year old

ensures more reasonable and effective research findings

regarding the relationship between organizational

learning and firm performance. Moreover, the items

were randomly ordered to minimize any bias from the

survey method. All the questions except the country

names of the foreign partners can be chosen from the

alternatives.

3.1.3. Respondents

From the 223 participating firms, a total of 127

completed, usable questionnaires were collected.

Among the 127 cases of strategic alliances, 70 were

domestic alliances and 57 were international. The

foreign partners in international alliances were mainly

based on the U.S. (12), Japan (12), China (9), and

France (6). The sample firms represented a wide range

of industries such as automobile, equipment, pharma-

ceuticals, chemicals, biotechnology, electronics, semi-

conductors, and IT.

Twenty-one (16.5%) respondents were presidents

and CEOs, 65 (51.2%) were general managers, and 24

(18.9%) were vice general managers who were

responsible for the alliance affairs (17 respondents

opted for anonymity). On average, they had been in

their current positions for 3.5 years. Based on the

managers’ positions and their experience it was

assumed that they had an appropriate level of awareness

and expert knowledge with the issues addressed in the

questionnaire.

The potential for non-response bias was assessed by

using Armstrong and Overton’s (1977) procedure. We

performed t-tests comparing responding versus non-

responding firms and early versus late respondents, in

terms of industry, number of employees, sales growth,

and the ages of the alliances. Both tests indicate that

there were no statistically significant differences in

either the level of the variables, or in the relationship

between the variables, at the .05 level. It is thus assumed

that non-response bias was not a problem in this study.

As our measurement items were collected in the

same survey instrument, there is also the potential for

common method variance. In order to test this potential,

we started using procedures recommended by Podsak-

off and Organ (1986). The 10 survey items were

examined using an unrotated, principal components

factor analytic procedure, and no single predominant

factor emerged. Instead, three factors were generated

with Eigen values larger than 1. If common method


variance were present, a single factor would have

emerged in such an analysis. Additionally, we applied

varimax rotation to the factor analysis, limiting the

solution to two factors: organizational learning and

financial performance. In the Rotated Component

Matrix, items loaded .8 or greater on organizational

learning in one column while loading more than .7 on

the performance factor in the other column. This

suggests that the two factors and respective loadings of

the items followed our initial design of the instrument

(Waldman, Javidan, & Varella, 2004).

Although the exploratory factor analysis indicated

that there was not a single overall factor for the

assessments of the variables, such an analysis does not

indicate the statistical significance of possible common

method variance. To obtain a more precise assessment

of such bias in the data, we further used a confirmatory

factor analysis approach to test for common method

variance (Menon, Bharadwaj, & Howell, 1996). A

model positing that a single factor underlies the study

variables was assessed by linking all items to a single

factor. This model did not fit the data well (x2 to degrees

of freedom ratio of 7.886, GFI = .705, NFI = .559, and

CFI = .585), as compared with the fit for the measure-

ment models for both independent and dependent

variables (x2 to degrees of freedom ratio of 1.367,

GFI = .946, NFI = .939, and CFI = .982). Collectively,

these results show that no serious threat of common

method variance exists in this study.

3.2. Measurements

This study measures organizational learning and

financial performance from the standpoint of the

partnering firm. The managers were asked to assess

Table 1

Measurement model: parameter estimates and reliability measures

Construct/indicators Standardized loadings

Organizational learning

1. New product development techniques .777

2. New manufacturing processes .732

3. New marketing expertise .928

Financial performance

1. Sales growth .739

2. Increase in overall profitability .758

3. Increase in ROI .730

4. Increase in ROA .779

a CR is the critical ratio obtained by dividing the estimate by its standard er

be used to assess the statistical significance of the coefficient estimates, nb Coefficient of leading indicator for each construct was set to 1.0 to est

*** Significant at the p < .001 level.

the general extent to which the respondent firm learned

from the partners and to which its financial performance

items (i.e., improvement in sales, profitability, ROI, and

ROA) were improved in the six-year period of 2000–

2005. As to the three contingencies, alliance scope was

separated into three categories indicating different

numbers of joint activities (R&D, manufacturing, and

marketing): a single activity (coded 1), two of the

activities (2), and all the three activities (3). The

governance form of the alliance was created as a

dummy variable, where ‘‘1’’ indicated that the alliance

of concern was an equity JV, and ‘‘0’’ that it was a

contractual arrangement. Competitive regime was also

created as a dummy variable, which is coded ‘‘1’’ for

alliances involving firms which had their primary

operations in the same industry, ‘‘0’’ otherwise. Details

of the analytical steps are shown in Appendix B.

4. Results and discussion

Our results suggest that organizational learning has a

significant, positive, and strong impact on partner firms’

financial performance as shown in Tables 1–3. This

finding in the context of strategic alliance replicates and

extends prior empirical studies at the single firm level

(e.g., Baker & Sinkula, 1999; Prieto & Revilla, 2006).

Our significant contribution is the finding that a firm

engaged in the interorganizational learning has the

potential to access and acquire knowledge or expertise

from its partners. This type of firm itself is a learning

organization, and it can continually convert the

knowledge into new products, processes, and services,

which can then serve new markets or customer needs

and, as a result, contribute directly to the firm’s financial

results.

CRa Cronbach alpha Average (%)

.850 77.1

–b

8.437***

9.081***

.837 67.4

–b

7.647***

7.409***

7.802***

ror (Arbuckle, 2005). This statistic is equivalent to t-statistic and it can

= 127.

ablish scale.


Table 2

Correlations and discriminant validity

Variables 1 2 3 4 5

1. Organizational learning .88

2. Financial performance .43*** .82

3. Alliance form .25* .51*** 1.00

4. Alliance scope .22* .43*** .43*** 1.00

5. Competitive regime .22* .27** .34*** .19* 1.00

Notes: Diagonal elements (in bold) are square roots of the average variance extracted values. Off-diagonal elements are the correlations of

independent, dependent, and moderating variables, n = 127. *p < .05; **p < .01; ***p < .001.

There appears to be general support for the idea that

organizational learning is beneficial to the partnering

firms. Recent studies have suggested, however, that the

impact of learning on performance is contingent on

other factors, such as the organization’s age (Calantone

et al., 2002) and the governance mechanisms (Mohr &

Sengupta, 2002). This contingency perspective implies

that although specific alliances may provide the

potential for interorganizational learning, they do not

insure that learning necessarily contributes to perfor-

mance improvement. In this paper, we theorize that

organizational learning has different effects on firms’

financial performance, depending on the form, scope,

and competitive regime of the alliance.

While it is proposed that organizational learning will

be more important for certain types of alliances than for

others, our findings suggest that the positive impact of

learning on performance is stronger in the presence of

equity as shown in Table 3. The advantages of equity

JVs, including formal controls and communication

mechanisms, joint decision making, and mutual

commitment and trust, facilitate interorganizational

learning and knowledge exchange (Dyer & Singh,

1998). JV partners can therefore expect increased

learning efficiency and effectiveness, and they should

be willing to modify their learning intent and capability

Table 3

Structural parameter estimates and goodness-of-fit indices

Hypotheses Sample size

Main effect

Model 1 Learning! performance n = 127

Moderating effects

Model 2 Form = 0 n = 63

Form = 1 n = 64

Model 3 Scope = 1 n = 50

Scope = 2 n = 46

Scope = 3 n = 31

Model 4 Comparison = 0 n = 42

Comparison = 1 n = 85

+p < .1; *p < .05; **p < .01; ***p < .001.

in order to improve financial results. For comparison

purposes, contractual alliances do not involve the same

degree of face-to-face interaction and incentive align-

ment (Zollo et al., 2002). Therefore, organizational

learning is an inevitable process in JVs, but it need not

be so in contractual alliances.

Our findings in Table 3 indicate that the moderating

effect of alliance scope is even more complex than

originally considered. It was initially proposed that,

with the alliance scope increasing, the positive

learning–performance relationship will be strength-

ened. Although we support our hypothesis when

comparing the narrowest scope with the moderate

scope, the association becomes insignificant when the

scope of the joint activity is broadest. This finding thus

shows an interesting inverted U-shaped moderating

effect. As shown in Table 3, when firms extend the

scope of their alliance from one single activity to

involving two of the activities, organizational learning

contributes increased benefits to the partners. But when

the alliance continues to increase so that it involves all

three activities, the firms benefit less from the learning

compared with the two-activity case.

Several possible reasons may account for the above

results. Generally, if an alliance involves a larger

number of joint activities, more learning opportunities

b Fit indices

.431*** x2 (13 d.f.) = 18.316; CFI = .986; RMSEA = .057

.339* x2 (13 d.f.) = 30.912; CFI = .893; RMSEA = .149

.397** x2 (13 d.f.) = 17.841; CFI = .970; RMSEA = .077

.299+ x2 (13 d.f.) = 20.821; CFI = .937; RMSEA = .111

.437* x2 (13 d.f.) = 7.949; CFI = 1.000; RMSEA = .000

.302 x2 (13 d.f.) = 16.141; CFI = .953; RMSEA = .090

.213 x2 (13 d.f.) = 21.070; CFI = .928; RMSEA = .123

.468*** x2 (13 d.f.) = 14.388; CFI = .995; RMSEA = .036


and knowledge access can be available to the partners

(Oxley, 1997; Pisano, 1989). Once the scope increases

to a certain level, such as involving the widest range of

the joint activities, various managerial problems may

occur. For example, such alliances may face a variety of

conflicts, a high degree of difficulty in interpartner

coordination, and high levels of uncertainty and

complexity (Sampson, 2004), leading to scale and

scope diseconomy. Moreover, while the broadest scope

provides the partners with the most learning opportu-

nities, it simultaneously makes the partners exposed to

the highest level of risks because of unintended

knowledge leakage (Oxley & Sampson, 2004). If a

firm loses the tacit knowledge and property know-how

that are most valuable to it, the benefits of organiza-

tional learning will necessarily decrease. All these are

likely to result in an unproductive relationship when the

alliance scope is broadest.

Turning to the moderating effect of competitive

regime, our findings in Table 3 concur with previous

studies that suggest the positive effects of alliances

among competitors (Lane & Lubatkin, 1998), but differ

from the ones that emphasize the negative effects (Park

& Russo, 1996). Hamel (1991) argues that a firm’s

learning intention will be greater among competitors.

Similarly, Lane and Lubatkin (1998) posit that

developing a strategic alliance with competitors

constitutes an important form of interactive learning.

Alliances with firms engaged in the same business can

be formed to facilitate a firm’s learning and enhance its

ability to realize superior financial results.

5. Conclusions

The literature has long made clear that the relationship

between learning and performance is strong within a

firm, but the question of how strong it is externally, such

as in an alliance context, has remained largely

unanswered. In addition, previous research has not

yielded a general theory regarding the conditions under

which organizational learning contributes most to firm

performance. This research was designed to investigate

the learning–performance relationship in the alliance

context and further to incorporate three alliance-level

variables as moderating factors. We developed an

organizational learning model of firm-level performance,

consisting of two kinds of effect. A simple conceptual

model illustrated the direct relationship between

organizational learning and financial performance. A

second conceptual model used contingency theory to

illustrate how the form, scope, and competitive regime of

the alliance regulate the learning–performance link.

5.1. Theoretical contributions

The aim of this study has been to advance our

understanding of the learning–performance relation-

ship at both theoretical and practical levels. Theore-

tically, the contributions of this paper are twofold.

First, although the learning–performance link has often

been assumed and tested at the single firm level, there

has been little research in the context of strategic

alliances. This paper fills this gap by providing

empirical support for the idea that a higher level of

interorganizational learning is beneficial to alliance

firms from the financial performance point of view. It

also responds to the call for research on the effect of

learning orientation in the area of strategic alliances

(Calantone et al., 2002). Second, this paper adds value

to the organizational learning literature by demonstrat-

ing a contingency approach to firms’ financial

performance. In this initial study we offer support

that the strength of the learning–performance link is

conditioned by the form, scope, and competitive

regime of the alliance. This finding suggests that

organizational learning has a significant impact on

financial performance outcomes only when a proper

context of organizational learning is in place.

5.2. Managerial implications

The analysis presented in this paper also yields some

new conclusions that are potentially important for firms

which are engaged in alliances or which plan to form

alliances. Findings suggest that realizing superior

performance is dependent on the firm’s ability to learn

from external sources, and that those firms which are

devoted to develop learning strategies will enjoy high

performance relative to the partners which are not

engaged in effective organizational learning. Managers

should have learning objectives in mind at the beginning

of alliance formation and should attach importance to

the organizational learning process throughout the

lifetime of the alliance. Furthermore, managers should

recognize that organizational learning varies in its

capacity to effect performance. Firms in some alliances

may be more effective and efficient than in other

alliances in their approach for developing an open

context propitious to organizational learning and for

realizing an obvious improvement in performance

outcomes. Managers must craft appropriate governance

mechanisms, a moderate scope, and a certain level of

interfirm competition which match the learning inten-

tion and capability of the partners, so as to maximize the

benefits of organizational learning.


5.3. Limitations and future research

The results of the study should also be considered in

light of its limitations, which also point to several issues

for future research. First, this paper has implicitly

assumed that the alliance is of relatively large strategic

and financial importance to the firm. We have not

considered those alliances that account for only a very

small percentage of the partners’ sales and have only a

limited range of learning opportunities. Future research

should address this issue by dividing alliances into

different types according to their importance to the

firms. This research would provide a more precise

understanding of organizational learning and its impact

on firm performance.

Second, we have reported that there are some

differences in the results across equity and non-equity

alliances. But non-equity alliances themselves involve a

variety of arrangements, such as licensing agreements,

R&D contracts, and technology swap agreements, and

some of these non-equity alliances can also be very

powerful sources of learning. In future research it may

be useful to examine variance, if any, in importance

across different types of non-equity alliances.

Third, when we concluded that alliances among

competing firms would facilitate interfirm learning and

produce greater financial performance for the partners,

we have totally neglected the possibility that intense

competition also exposes the partners to risks of

unintended knowledge encroachment. If a firm loses the

critical knowledge and property resources that are most

valuable to it, its learning benefits will decrease.

Therefore, if unintended knowledge loss exists, the

research results presented here would be different. In

future, this issue should be incorporated into relevant

research.

Fourth, there are also some methodological limita-

tions. For example, it is necessary to acknowledge the

usual limitation of cross-sectional survey research,

namely that it is not completely appropriate for proving

a positive relationship, since there is a delay in the effect

of organizational learning on firm performance.

Gaining a clearer understanding of this issue will

require longitudinal analysis, so that researchers can

conclusively replicate the findings presented here.

We have adopted a web-based Internet survey

approach to collect data. However, no single survey

approach would be ‘‘optimal.’’ Internet surveys have

also limitations (see Simsek & Veiga, 2001). For

example, Internet surveys suffer from coverage error; it

is usually difficult to obtain an unbiased sampling frame

that allows for the drawing of representative samples

because the Internet does not have universal coverage of

many populations. Due to the same reason, sampling

representativeness would be a problem. Future research

can simultaneously use multiple survey methods to

conquer these limitations.

Another methodological problem comes from using

single informants as the source of information. Although

we have provided a number of tests to rule out the

possible biases, the fact remains that the data collection

from multiple sources (e.g., senior management, firm

employees, and archival or public sources) would

provide a stronger test of the model. Future research

could incorporate other sources of information and

correlate subjective measures with objective measures, in

order to improve the validity of the information obtained.

Finally, we have tested the model in the sole German

context by using a medium-sized sample. Although we

hope the findings will also hold when applied to firms

originating from different countries, the moderate

sample size is still a problem. The next step will be

to introduce cross-cultural dimension in the context and

to cross-validate model in different settings based on a

large-sized sample analysis.

Acknowledgements

This paper was supported by NSFC (70671082,

70372050, and 70571063).

Appendix A. Study measurement items

A.1. Independent variable

Organizational learning (Adapted from Lane et al.,

2001): To what extent would you agree with the

following statements as true of your relationship with

the most important alliance partner? (seven-point scale

from completely disagree to completely agree).

� F
rom the partner, you have learnt knowledge about
new product development techniques that only they

knew.

� F
rom the partner, you have learnt new manufacturing
processes that only they knew.

� F
rom the partner, you have learnt new marketing
expertise that only they knew.

A.2. Dependent variable

Financial performance (Adapted from Tippins &

Sohi, 2003): In the past six years, have you seen the

changes in each of the following items in your firm as


true of your relationship with the partner? (seven-point

scale from strongly decrease to strongly increase).

� Sales
� Profit � Return on
investment

� Return on

assets

A.3. Moderator variables

Alliance form: What is the form of the alliance

structure?

� Equity joint venture
� Contractual alliance
Alliance scope (Source: Oxley & Sampson, 2004):

What is the joint activity within the alliance (many

choices)?

� R&D
� Manufacturing/
production

� Marketing/

selling

Competitive regime: Do you and the most

important partner have primary operations in the same

industry?

� Yes
� No
Appendix B. Details of empirical analyses

B.1. Measurement model

B.1.1. Reliability and convergent validity

To assess the direct and contingent effects posited by

the theoretical model, the SPSS 14.0 software with the

maximum-likelihood AMOS 6.0 program was used

(Arbuckle, 2005). The AMOS maximum-likelihood

estimation is preferable for a variety of reasons. It

allows analyzing data from several populations at once.

It can estimate means for exogenous variables and

intercepts in regression equations. And multiple models

can be fitted in a single analysis. In particular, when

confronted with missing data, AMOS maximum-like-

lihood estimation is superior to those relying on ad hoc

methods like pairwise deletion or mean imputation.

Moreover, AMOS estimation, in comparison to other

estimators, is simple (i.e., a simpler weight matrix),

both conceptually and computationally. Its sample size

requirements are also less severe. These advantages of

AMOS program make it particularly well suited to this

empirical research.

Table 1 presents the CFA results of the two latent

constructs: organizational learning and financial per-

formance. As a whole, the results indicated acceptable

psychometric properties for the constructs, thus

supporting the convergent validity (Bagozzi & Yi,

1988).

B.1.1.1. Organizational learning

This study assesses organizational learning using the

managers’ self-reported, seven-point Likert-type scales,

where the value 1 means ‘‘completely disagree’’ with

the statement and 7 ‘‘completely agree.’’ Specifically,

the informants were asked to assess if they have

acquired the following three types of knowledge from

the partners: (1) new product development techniques,

(2) new manufacturing processes, and (3) new market-

ing expertise. The results in Table 1 displayed

satisfactory levels of reliability and construct validity,

as indicated by the Cronbach alpha value of .850, the

variances extracted of 77.1%, and highly significant

factor loadings of the observed items on the latent

construct (at the .001 level).

B.1.1.2. Financial performance

This study uses the managers’ self-reported, seven-

point Likert-type scales to assess financial performance,

where the value 1 means ‘‘strongly decrease’’ with the

statement and 7 ‘‘strongly increase.’’ Four indicators

were included: increases in sales, profitability, ROI, and

ROA. The results in Table 1 displayed satisfactory levels

of reliability and construct validity, as indicated by the

Cronbach alpha value of .837, the variances extracted of

67.4%, and highly significant factor loadings of the

observed items on the latent construct (at the .001 level).

In an attempt to validate our survey measure of

financial performance, we correlated it with objective

performance indices collected from public sources. In

doing so, we focused on measures of sales and profit. Of

the 127 sample firms, only 21 firms publicly reported

their sales and profit figures during the period of 2000–

2005. The correlation between our survey item and the

objective performance was .33 ( p < .05) for the

measure of sales and .28 ( p < .05) for the measure

of profit. These findings provide support for the validity

of our survey measure of firm financial performance.

B.1.2. Discriminant validity

Discriminant validity was assessed using one of the

most common tests suggested by Fornell and Larcker

(1981), who recommend comparing the variance shared

between the constructs with the average variances

extracted for each individual construct to assess

discriminant validity. Table 2 presents the square roots

of the average variance extracted for each construct

along the diagonal and the correlation coefficients


among all theoretically related constructs in the off-

diagonal elements. The discriminant validity of a

construct is adequate when the diagonal element is

greater than each of the off-diagonal elements in the

corresponding rows and columns. Obviously, the data in

Table 2 conform to this rule, supporting the discriminant

validity of the two constructs.

B.2. Structural model

After establishing the structure of the measurement

model, the structural model was subsequently tested.

Table 3 presents each path, the standardized values of

parameter estimates, and the model statistics for the

structural equations. The ratio of x2 to degrees of

freedom for each structural equation corresponded to a

satisfactory fit (all less than 3), and the other fit indices

including CFI and RMSEA were also within acceptable

ranges (one exception was the moderating effect of

contractual alliances in Model 3). Given the medium

size of the sample, the goodness-of-fit indicators

suggest that the main model and the sub-group models

are reasonable representations of the data.

B.2.1. The main effect

Model 1 examined the direct effect of organizational

learning on the dependent variable, firms’ financial

performance. The coefficient on the path was .431 and

significant at the .001 level. This significant, positive,

and strong relationship suggests that Hypothesis 1 was

supported by data at hand.

B.2.2. Moderating effects

The hypotheses of the moderating effects predict that

the magnitude of the learning–performance relationship

will be affected by the form, scope, and competitive

regime of the alliance. To test these effects, we took the

approach of multi-group comparisons. Specifically, we

divided the sample into different groups along each of

the moderating variables and compared the coefficient

estimates of the sub-group structural equations. The use

of this approach enables us to gain each specific

structural coefficient under different conditions. Table 3

shows that the relationship differs somewhat across

groups characterized by the alliance conditions. Hence,

results provide general support for the moderating

model developed in this study.

It was proposed in Hypothesis 2 that the impact of

learning on performance will be stronger in the context

of JVs than in contractual alliances. In testing this

hypothesis, the sample was split into two groups based

on the classification of equity versus non-equity

alliances. Model 2 examined whether there is any

difference between the structural parameter in JVs and

that in contractual alliances. Table 3 shows that the

coefficient is .397 ( p < .01) for JVs and .339 ( p < .05)

for contractual alliances. That is, JVs showed a stronger

learning–performance relationship than contractual

alliances. Hence, results provided good support for

Hypothesis 2.

We split the scope of joint activities into three

groups. Model 3 tested this hypothesis by comparing

three coefficient estimates: .299 ( p < .1) for the

narrowest scope with a single activity, .437 ( p < .05)

for the moderate scope with two activities and .302

( p > .1) for the broadest scope with all the three

activities. Originally, it was proposed in Hypothesis 3

that the broader the scope, the greater the likelihood that

organizational learning will have a positive influence on

financial performance. However, since the coefficient

estimate for the broadest scope was insignificant and

also weaker than that for moderate scope, results

provided only partial support for Hypothesis 3.

Turning to the moderating effect of competitive

regime as examined in Model 4, the coefficient for firms

based on the same industry is .468 ( p < .001) as

compared to .213 ( p > .1) for firms across industries.

That is, alliances among firms based on the same industry

showed a significant positive learning–performance

relationship, whereas the relationship is insignificant

when partners had their primary operations in different

industries. Hence, Hypothesis 4 was supported.

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