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Market orientation, learning orientation and organisational performance in international joint ventures. Mark Anthony Farrell,. Edward Oczkowski and Radwan ...
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Market orientation, learning orientation and organisational performance in international joint ventures Mark Anthony Farrell, Edward Oczkowski and Radwan Kharabsheh

International joint ventures

289 Received February 2007 Revised January 2008 Accepted February 2008

School of Commerce, Charles Sturt University, Wagga Wagga, Australia Abstract Purpose – Despite failure rates of around 30 per cent, international joint ventures (IJVs) continue to grow. It is argued that IJVs provide a platform for organisational learning, which facilitates organisational performance. Intuitively, IJVs that are learning oriented should have a positive impact upon organisational performance. However, it is unclear as to whether a firm in an IJV should focus more on being learning oriented, or market oriented. The paper aims to address this question. Design/methodology/approach – A survey of 168 senior managers involved in IJVs in Malaysia. Data were analysed using two-stage least squares estimators for latent variable models. Findings – Results suggest that for IJVs, a market orientation has a more positive impact on organisational performance than a learning orientation. The non-linear relationship between market orientation and performance suggest that larger gains in performance are achieved by firms who have low initial levels of market orientation. Thus, in the absence of one or the other, it is preferable for a firm in an IJV to have a strong market orientation. Practical implications – For managers of IJVs, the study would suggest that firms should concentrate on improving their organisations’ overall level of market orientation if they are to improve the level of business performance. Originality/value – This paper is the first to examine the relative effects of a market orientation and a learning orientation in the context of IJVs. Keywords International joint ventures, Learning, Market orientation, Organizational performance Paper type Research paper

Introduction Increasing competition is resulting in many firms looking to operate in offshore markets in order to remain competitive. As Yeniyurt et al. (2005, p. 2) state, ‘‘having a global orientation is no longer a luxury, but a necessity for economic survival in a large number of industries’’. This has created an environment in which international joint ventures (IJVs) are increasing in popularity (Makino and Beamish, 1998), and as such, are the subject of a considerable body of literature (Tsang, 2002). Within IJVs, the importance of knowledge management has been increasingly recognised for achieving a competitive advantage. A stream of research on market-based learning has emphasized the role of IJVs as an instrument of organisational learning (Kandemir and Hult, 2005). The main thrust of this research, argues Kandemir and Hult (2005), is that IJVs provide access to each other’s resources and capabilities (Anand and Khanna, 2000; Grant, 1996; Hamel, 1991; Kogut, 1988). Indeed, within the management literature, it has been proposed that the ability to learn faster than competitors may be the only source of sustainable competitive advantage (DeGeus, 1988; Dickson, 1992). In contrast to the emphasis on organisational learning, marketing scholars have proposed that a market-oriented organisation will be able to outperform its competitors. The literature on market orientation increased exponentially following the

Asia Pacific Journal of Marketing and Logistics Vol. 20 No. 3, 2008 pp. 289-308 # Emerald Group Publishing Limited 1355-5855 DOI 10.1108/13555850810890066

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pioneering studies of Kohli and Jaworski (1990), Narver and Slater (1990), Jaworski and Kohli (1993), and Kohli et al. (1993). As Kirca et al. (2005, p. 25) argue, ‘‘market orientation should enhance an organisation’s innovativeness and new product performance’’ given its focus on customer needs and information use (Atuahene-Gima, 1996; Han et al. 1998). Based on a comprehensive meta-analysis, Kirca et al. (2005) find that market orientation affects a firm’s innovativeness, and also there is a positive relationship between market orientation and organisational performance which does not vary across cost-based versus revenue-based performance measures. However, there remains a lack of clarity regarding the relative contributions of a market and learning orientation to organisational performance. For example, Baker and Sinkula (1999a, p. 422) state that ‘‘in the absence of one or the other, it would be better for a firm to have a strong market orientation’’. Conversely, Baker and Sinkula (1999b, p. 305) find that a market orientation does not have a direct effect on organisational performance. Farrell (2000) found that a learning orientation positively effects organisational performance, while Farrell and Oczkowski (2002) find overall support that a market orientation has a stronger relationship with organisational performance than does a learning orientation. In a recent study, Vijande et al. (2005), find a positive relationship between a market orientation and organisational performance, but no effect for a learning orientation and organisational performance. In short, ‘‘two complementary literature streams have developed and are now converging: research addressing market orientation and organisational learning’’ (Celuch et al., 2002, p. 545). Within the literature on IJVs, research has examined organisational learning and innovation (Kandemir and Hult, 2005). However, we can find no study in the IJV literature that has examined the effects of a market and learning orientation on organisational performance. Based on the assumption that IJVs are a strategic initiative to achieve a sustainable competitive advantage, then knowledge regarding market and learning orientation on the performance of IJVs should be of interest to those firms engaged in or considering an IJV. Thus, the purpose of this study is to examine the effects of a market and learning orientation on organisational performance in IJVs. The paper is organised as follows. In the next section, we briefly review the literature on IJVs. There then follows the theoretical framework for the study, and an overview of the literature on market and learning orientation. This is followed by the research methodology, data analysis and conclusions. International joint ventures In accordance with Reus and Ritchie III (2004, p. 370), we define IJVs as ventures that ‘‘involve two or more legally distinct organisations (the parents), each of which actively participates in the decision-making activities of the jointly owned entity [. . .] with at least one parent organisation [. . .] headquartered outside the JV’s country of operation’’. Joint ventures are discrete, jointly owned entities created by two or more firms that provide inputs and share outcomes of the created entity (Hatfield et al., 1998). In short, the appeal of joint ventures is a result of the globalisation of industries in which some firms find it advantageous to cooperate with other firms in order to be competitive. Joint venturing is also an important alternative entry mode to internal start-up and acquisition (Kogut, 1988). However, joint ventures lessen individual control, and can be slow in their responsiveness to environmental dynamics due to the complexity of joint management (Kanter, 1989).

Research on IJVs has examined a variety of issues, ranging from partner selection (Geringer and Herbert, 1991) to the performance of IJVs (Cullen et al., 1995; Lee and Beamish, 1995; Julian and O’Cass, 2002; Reus and Ritchie III, 2004). It is worth noting that IJVs are becoming popular as a mode of market entry and expansion, despite their failure rate at above 30 per cent (Makino and Beamish, 1998). Given the high failure rate, researchers have attempted to understand why IJVs continue to be popular. Makino and Delios (1996) and Johnson et al. (2001) suggest that IJVs are attractive because they provide access to channels of distribution, enable organisations to share economic and political risks and facilitate the transfer of technology (Julian and O’Cass, 2002). For example, barriers to entry in some countries prevent non-IJV modes of entry. A joint venture provides the know-how or established local distribution channels through which to market (Beamish, 1993). Similarly, Johnson et al. (2001) argue that an IJV may reduce the significant political and economic risks associated with foreign projects. It is also argued that IJVs provide opportunities for foreign partners to access new markets through ‘‘leveraging the local partners’’ market knowledge and local networks (Simonin, 1999) thus reducing risk and increasing revenue (Julian and O’Cass, 2002). In return, argues Inkpen and Beamish (1997) foreign partners provide technology and capital. With regards to government pressure, this may lead the foreign organisation to form a partnership with a local partner (Yan, 1998; Yan and Gray, 1994). Theoretical framework The resource-based view of the firm (Wernerfelt, 1984) regarding the firm’s ‘‘idiosyncratic abilities in the attainment of a sustained competitive advantage in a global marketplace’’ (Yeniyurt et al., 2005, p. 3) provides a firm theoretical foundation for the exploration of market and learning orientation and the relative effect on organisational performance. In brief, the resource-based view focuses on the analysis of various resources possessed by the firm (Das and Teng, 2000). Firms are viewed as having resources, which are firm-specific, not perfectly mobile or imitable, and continuously heterogenous in their resource base. In line with Das and Teng (2000), we argue that the resource-based view is logical when examining IJVs because essentially, firms use alliances to gain access to each other firm’s valuable resources, such as knowledge. According to Barney (1991, p. 102) ‘‘a firm is said to have a competitive advantage when it is implementing a value creating strategy not simultaneously implemented by any current or potential competitors’’. The reason a competitor may not be implementing such a strategy, argue Das and Teng (2000) is that it may not possess the appropriate resources. In short, the resource-based view considers strategic alliances, such as IJVs, used to access other firms’ resources for the purpose of obtaining otherwise unavailable competitive advantages and value to the firm. In the following section we review briefly the literature regarding the learning orientation of the firm and argue that a learning orientation is a resource-based asset, which can benefit firms in IJVs. Learning orientation Kandemir and Hult (2005, p. 432) argue that an IJV learns if, through its processing of information, it is able to adapt to new organisational norms (Hedberg, 1981; Meyer, 1982) and develops new knowledge or insights that have potential to influence its behaviour (e.g. innovativeness culture, innovation capacity) (Fiol and Lyles, 1985; Huber, 1991; Slater and Narver, 1995). Within the resource-based view, a learning

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orientation is central to obtaining the maximum value from the other firm’s knowledge. That is, an IJV confers an advantage if successful learning takes place. We argue that a learning orientation enables a firm to out-perform competitors because it satisfies the four attributes posited by Barney (1991). First, a learning orientation is valuable because it allows the firm to exploit opportunities and/or neutralise threats in a firm’s environment. For example, a learning orientation enables a firm to more successfully understand the needs of customers better than its competitors (Day, 1994; Dickson, 1992; Sinkula, 1994). This should lead to superior outcomes, such as new product success, superior customer retention and superior growth and/or profitability (Slater and Narver, 1995). Secondly, a learning orientation is rare. While most firms seem capable of what Senge (1990) terms ‘‘adaptive learning’’ (learning within the traditional scope of the organisation’s activities), there are fewer organisations that engage in generative learning (Senge, 1990). This occurs when the organisation is willing to question long held assumptions about its mission, capabilities or strategy (Slater and Narver, 1995). According to Slater and Narver (1995), generative learning is more likely to lead to competitive advantage than adaptive learning. Adaptive learning, argues Baker and Sinkula (1999a, p. 412) ‘‘is capable of facilitating incremental innovation, but it is not intrinsically capable of facilitating discontinuous innovation’’. Conversely, argues Baker and Sinkula (1999, p. 412), a learning orientation ‘‘directly affects a firm’s ability to challenge old assumptions about the market and how a firm should be organised to address it’’. Thirdly, a learning orientation is imperfectly imitable, based on the premise that successful organisational learning is socially complex. As Barney (1991, p. 110) states, ‘‘understanding that say, an organisational culture with certain attributes or quality relations among managers can improve a firm’s efficiency and effectiveness does not necessarily imply that firms without these attributes . . . can engage in systematic efforts to create them’’. Finally, a learning orientation is a source of sustained competitive advantage because it is not substitutable. That is, while competing firms may attempt to emulate the efforts of a learning oriented organisation, the complex nature of organisational learning means it is very difficult to create strategically equivalent valuable resources. However, as Barney (1991) points out, a resource which is rare, socially complex, and perfectly imitable, may still be a source of competitive advantage, even if a substitute exists. In the following section, we review the market orientation construct, and argue that a market orientation is a source of competitive advantage for the firm. Market orientation With regards the conceptualisation and measurement of market orientation, two perspectives have gained wide acceptance. The first, developed by Narver and Slater (1990, p. 21) argues that a market orientation ‘‘is the organisation culture that most effectively and efficiently creates the necessary behaviours for the creation of superior value for buyers, and, this, continuous superior performance for the business’’. For Narver and Slater (1990), a market orientation comprises three elements: customer orientation, competitor orientation and inter-functional coordination. The second perspective was proposed by Kohli and Jaworski (1990, p. 6) who define a market orientation as, ‘‘an organisation-wide generation of market intelligence pertaining to current and future customer needs, dissemination of intelligence across departments, and organisation-wide responsiveness to it’’.

Market-oriented firms are successful because they are able to outperform competitors due to their ability to better understand and respond to customer needs, through the effective management of hard-to-duplicate resources (Day, 1994). As Day (1994, p. 43) argues, market-oriented firms are able to demonstrate high levels of competency in their ability to learn about customers, competition and identify opportunities in present and prospective markets. Similarly, Reed and Fillippi (1990) argue that the source of a competency is always internal to the firm and that the competency is produced by the way a firm utilises its internal skills and resources, relative to its competitors. In line with this perspective is the view that market orientation is an organisation culture and not simply a function or set of processes and activities (Narver et al., 1998, p. 243). According to Narver et al. (1998), the difficulty in replicating the market-oriented culture explains why we do not see a large number of companies creating and maintaining a market orientation. In other words, a market orientation enables a firm to outperform its competitors based upon the concept of causal ambiguity (Lippman and Rumelt, 1982). Causal ambiguity is the term used to describe business actions and outcomes that are difficult for competitors to copy (Reed and Fillippi, 1990). A market orientation also satisfies what Reed and Fillippi (1990) refer to as the three characteristics of competencies. First, a market-oriented firm has tacit knowledge, which means that the relationship between actions and results is unclear. Day (1994, p. 39) illustrates this with the example of Wal-Mart’s processes, which K-Mart is aware of, but finds difficult to copy. Secondly, a market-oriented firm is surprisingly complex. Recent work by Gebhardt et al. (2006, p. 51) suggest that to become market oriented involves several interdependent changes at the individual, group and organisation levels that occur overs several years. Similarly, in a paired-comparison ethnographic study of the dynamics of implementing a customer-orientation in a major US public school district, Kennedy et al. (2003) found that despite both schools having a strong commitment to the transformation to a customer orientation, only one school was able to successfully make the transition. A market-oriented firm also possesses what Williamson (1985) describes as asset specificity. A specificity refers to ‘‘durable investments that are undertaken in support of particular transactions’’, Williamson (1985, p. 55). Day (1994, p. 39) provides an example of asset specificity when he compares Marriott Hotels with its competitors. As Day (1994) points out, what sets Marriott apart and reveals a distinctive service capability, is its ‘‘fanatical eye for detail’’, which is a core competency based on its ability to deploy its resources and skills in a highly specific way which competitors find difficult to match. Within the marketing literature there is a growing body of research, which examines the relationship between a market and learning orientation, and associated variables. For example, Celuch et al. (2002) examine the effect of a market and learning orientation on organisational capabilities. Calantone et al. (2002) examine the effects of a learning orientation on firm innovation capability and firm performance, finding a positive relationship between learning orientation and firm performance (market share, new product success, and overall performance). Calantone et al. (2002, p. 522) state that findings suggest ‘‘that learning orientation facilitates the generation of resources and skills essential for firm performance’’. Vijande et al. (2005) find that a market orientation has a positive effect on organisational performance, whereas a learning orientation has a negative direct relationship with performance. Farrell and

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Oczkowski (2002) find that a market orientation has a stronger relationship with organisational performance than does a learning orientation. The preceding discussion suggests that there is debate regarding the relative merits of a market and learning orientation and organisational performance. Theory and empirical evidence is unclear as to which orientation will outperform the other to produce a sustainable competitive advantage. For organisations involved in IJVs, it is important to determine the relative effects of a market and learning orientation. Given this ambiguity, we pose the following research question: Q: Given two rival models: market orientation – organisational performance (MOOP), and learning orientation – organisational performance (LO-OP), which performs better for IJVs? In the following section, we describe the methodology, and in particular, estimating and testing principles employed to address this question. Methodology Data collection The population of the study comprised all currently active IJVs between Malaysian and non-Malaysian companies in the Klang valley in Malaysia. The sampling frame consisted of 545 IJVs in Malaysia. The IJVs surveyed originated from five developed countries; Australia, Germany, Japan, UK and USA. The study used a selfadministered questionnaire survey. An appointment was made with the respective manager, who was then advised of the objectives of the study. The questionnaire was collected later in the day. In total 168 questionnaires were returned, from senior managers who were responsible for overseeing the IJV, producing an effective response rate of 30.8 percent. This method is consistent with similar studies (Si and Bruton, 1999) and is also supported by Geringer and Herbert (1991) who concluded that a single key informant per joint venture allows researchers to obtain reliable data. Out of the 168 IJVs that responded 45 percent (75 IJVs) were in the services sector and 55 percent (93 IJVs) were in the manufacturing sector. Measures We use the measures and follow the analytical procedures described in Farrell and Oczkowski (2002). We employ the (Narver and Slater, 1990) MKTOR measure of market orientation. This measure focuses upon a firm’s customer orientation, competitor orientation and inter-functional coordination. We do not use the proactive measure of market orientation developed by Narver et al. (2004) for the following reasons: .

recent studies have demonstrated that the original measure of market orientation (MKTOR) has a positive effect upon performance; and

.

the MKTOR measure has been employed in many studies which have demonstrated its sound psychometric properties.

For learning orientation, we employ the Baker and Sinkula (1999b) measure, which focuses upon commitment to learning, open-mindedness, and shared vision. We examine five dimensions of business performance relative to all other competitors in the organisation’s principal served market segment over the past year: customer retention; new product success; sales growth; return on investment; and overall performance. We examine these measures individually and as five indicators in a fiveitem scale named business performance. As with previous studies (Narver and Slater,

1990; Oczkowski and Farrell, 1998; Farrell and Oczkowski, 2002) several control variables for the performance relationship were also included. The specified control variables (with expected signs) are: relative size (+), relative cost ( ), ease of entry ( ), supplier power (+), buyer power ( ), market growth (+), competitive intensity ( ), market turbulence ( ), technological turbulence ( ), (see Oczkowski and Farrell (1998, p. 355) for a detailed explanation). In summary the competing models are: performance is a function of market orientation and a set of control variables; and performance is a function of learning orientation and a set of control variables. For each of the competing models, six equations are estimated, one for each of the five single item measures of performance and one for the five item summated measure termed business performance (Note: this is the sum of the five dimensions of business performance as stated above.) Measurement model data analysis The measurement models for the various constructs were initially analysed and refined (if necessary) before the estimation of the competing structural models. Initially all the items in the proposed scales were analysed by a confirmatory factor analysis (CFA) and assessed for their reliability and explained variance extracted properties. All the original measures exhibited some degree of poor data fit in terms of CFA goodnessof-fit measures and/or low-average variance extracted values. In respecifying the measurement models, in order to improve model fit, we chose only to delete existing items. There are strong theoretical reasons against model modification based on correlated measurement errors and cross-factor loadings (Gerbing and Anderson, 1984). Further, there is no theoretical justification to motivate any adhoc correlated measurement errors for the items with regard to acquiescence of responses (Gerbing and Anderson, 1984). The initially proposed scales were reduced by deleting single items (one-by-one) until acceptable good fitting models were attainted. The refined measures, their descriptive statistics and CFA and reliability properties are outlined in Table I. The employed items are listed in the appendix. All the refined multi-item measures have a comparative fit index (CFI) which exceeds 0.90 and most measures have root mean square error of approximation (RMSEA) values of less than 0.08. All reliabilities exceed 0.75 and all average variance extracted values exceed 0.50, which suggests that the variance captured by the underlying latent construct is greater than the variance due to measurement error (Fornell and Larcker, 1981). Structural model data analysis Using the refined scales, the competing structural models are analysed and estimated via Bollen’s (1996) two-stage least squares (2SLS) estimator for latent variable models. The 2SLS estimator is being increasingly used as an alternative to the standard maximum likelihood estimator (MLE) for latent variable models. Recent examples of the use of 2SLS exist in various disciplines, including: marketing (Im et al., 2003; Chandon et al., 2005); politics (deFigueiredo and Elkins, 2003); sociology (Regoeczi, 2002); economics (Oczkowski, 2001); and human resource management (Smith et al., 2003). In part, the attractiveness of the 2SLS estimator is that it does not assume normality for observed variables and it is more robust to specification errors than MLE. Bollen et al. (2003) provide extensive Monte Carlo evidence demonstrating the significantly better performance of 2SLS in the presence of specification error over MLE for particular model design parameters and sample sizes. To the extent that all

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Table I. Descriptive and goodness-of-fit statistics

Measure Business performance (five items) Customer retention New product success Sales growth Return on investment Overall performance Market orientation (eleven items) Scaling item Learning orientation (twelve items) Scaling item Relative size Relative cost Ease of entry Supplier power Buyer power Market growth Competitive intensity (five items) Scaling item Market turbulence (three items) Scaling item Technological turbulence (three items) Scaling item

Mean

Standard deviation

CFI (RMSEA)

2 (d.f.)

Reliability (ave. var. extracted)

4.50 4.92 4.50 4.30 4.06 4.74

0.97 1.17 1.18 1.22 1.33 1.20

0.987 (0.074)

9.63 (5)

0.854 (0.550)

4.73

1.36

5.41 4.11 3.62 3.70 3.64 3.44 4.35

1.23 1.63 1.28 1.55 1.04 1.20 1.73

0.970 (0.069) 0.927 (0.086)

73.49 (41) 113.4 (51)

0.925 (0.604) 0.876 (0.519)

3.63

1.59

0.993 (0.055)

7.52 (5)

4.13

1.58

4.53

1.59

0.868 (0.574) 0.764 (0.562) 0.880 (0.718)

Notes: All measures are single items unless specified otherwise. All items measured on a 1-7 scale except: relative size, relative cost and ease of entry measured on a 1-8 scale and market growth measured on a 1-9 scale. Cronbach’s, alpha are reported for reliabilities. Items listed in the data appendix

models are approximations of reality and hence contain some specification error, 2SLS may be a viable alternative to MLE for latent variable models. Further, the 2SLS estimator is particularly attractive as it easily permits diagnostic testing for assumptions such as adequacy of scale items (instruments), functional form specification error, heteroscedasticity and non-nested model alternatives (Bollen, 1996; Pesaran and Taylor, 1999; Oczkowski, 2002). These diagnostic testing issues are routinely ignored in standard MLE applications for SEM. To employ the 2SLS estimator, a scaling (or reference) variable for each latentindependent variable is specified, this acts as the regressor for the latent variable and the remaining non-scaling items act as instruments in a 2SLS regression (The employed scaling variables are those items which have the highest factor loadings in the various CFA models. The scaling items are identified in the appendix.) For the dependent variable, a summated (or factor-score) based scale can be employed combining various items, as measurement error in the dependent variable does not affect the consistency of the 2SLS estimator. Initially, various models were subject to heteroscedasticity tests appropriate for 2SLS (Pesaran and Taylor, 1999). In general, these tests indicated the presence of some heteroscedasticity and as a consequence all subsequent diagnostic tests and coefficient t-ratios are based on White’s (1980) heteroscedastic consistent covariance matrix.

The RESET functional form specification error test for 2SLS (Pesaran and Taylor, 1999) was conducted for the competing models and indicated in general that the linear form may be an unsuitable specification. As a consequence, various other linearlogarithmic functional forms were employed and evaluated using the RESET test. (Godfrey et al. (1988) illustrate that the RESET test has useful small sample properties for discriminating between linear and logarithmic forms for the standard regression model). The results from the RESET tests for four functional forms and competing business performance models are presented in Table II. Only the linear-log form for both the MO and LO models indicates the complete absence of any specification error. All other forms contain at least one significant RESET statistic, which indicates significant functional form mis-specification. Consequently, the log-linear model is the preferred functional form and will be used in subsequent analysis.

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Encompassing non-nested testing The hypothesized competing models represent non-nested alternatives (i.e. one model can not be gained via suitable parameter restrictions from the other) and therefore appropriately defined non-nested testing principles must be employed. Consistent with the motivation provided by Oczkowski (2002) and Farrell and Oczkowski (2002) the ‘‘augmented’’ encompassing test will be performed for choosing between the MO and LO models. A comprehensive model encompassing both competing models is developed and tests of the sub-models are performed to assess the relative information content of the competing models. The test will determine whether one model can encompass the other. Effectively, one model is said to encompass another if it can explain the performance of the other. The results for the augmented encompassing tests for all six measures performance are presented in Table III. For all measures of performance the MO model encompasses the LO model, LO cannot reject MO. In contrast, the LO model encompasses the MO model for return on investment only (MO cannot reject LO for ROI only). In other words, for customer retention, sales growth, new product success, overall performance and the average business performance measure, the MO model encompasses the LO model, while the LO model cannot encompass the MO model. For these five measures all the information in the LO model can be explained by the MO model but the MO

Dependent variable Customer retention New product success Sales growth Return on investment Overall performance Business performance (Average: five items)

Market orientation model Linear Log Linear log linear 0.73 0.37 2.82** 0.69 2.45* 2.27*

0.85 0.53 0.63 0.06 1.27 1.29

1.05 1.85 3.50** 1.64 3.73** 3.22**

Log log 1.70 0.90 1.80 1.56 3.09** 3.06**

Learning orientation model Linear Log Log Linear log linear log 0.16 0.54 2.30* 0.13 1.75 1.06

0.38 1.00 0.33 0.40 1.15 0.48

0.67 0.66 2.67** 1.66 2.53* 1.94

1.13 0.59 1.13 1.55 2.22* 1.83

Notes: Reported values are asymptotic t-statistics, distributed as N(0, 1), based on White’s heteroscedastic consistent covariance matrix; *significant at the 5 per cent level; **significant at the 1 per cent level

Table II. Reset specification error 2SLS tests

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Dependent variable Customer retention New product success Sales growth Return on investment Overall performance Business performance (Average: five items)

Market orientation null model 0.515 0.822 0.325 1.361 1.301 0.664

Learning orientation null model 2.421* 2.069* 2.441* 1.939 2.940** 2.988**

Conclusion Accept Accept Accept Accept Accept Accept

MO Reject LO MO Reject LO MO Reject LO MO Accept LO MO Reject LO MO Reject LO

Notes: Linear-log models. Reported values are asymptotic t-statistics, distributed as N(0, 1), results Table III. based on White’s heteroscedastic consistent covariance matrix; *significant at the 5 per cent level; Non-nested augmented encompassing 2SLS tests **significant at the 1 per cent level

model cannot be explained by the LO model, thereby making the LO model redundant. For these measures the MO model is clearly superior and it would be erroneous to employ the LO model. For return on investment, both models encompass each other and therefore either is an acceptable specification. The 2SLS coefficient estimates and associated statistics for the MO and LO models for all measures of performance are presented in Tables IV and V. Consistent with the non-nested tests, the GR2 goodness-of-fit statistics are higher for the MO model than for the LO model, expect for ROI where the values are practically identical. The overidentifying restrictions test statistics (OIR) indicate that the retained instruments are valid for both sets of models; this is consistent with the CFA results. The linear-log specifications suggest that the marginal effects of the regressors (X) on the dependent variable are decreasing in X, being represented by (coefficient/X). In other words, the marginal impact of the independent variable on the dependent variable declines as the independent variable increases. In the context of the MO and LO models this implies that as a firm attains higher levels of MO or LO its additional positive impact on performance falls. The most notable findings in Tables IV and V are that MO significantly influences performance for all performance measures except ROI, while LO significantly influences performance only for new product success. These findings reflect the previously discussed non-nested test results. The control variables have relatively different impacts on the various single measures of performance. Supplier power and market growth generally have the most prominent impact on most measures of performance. Relative size is important for customer retention and ROI, while market turbulence is important only for customer retention. Interestingly buyer power is important for customer retention and new product success but with an impact opposite to expectations. Discussion The purpose of this study was to examine the relative effects of a market and learning orientation on organisational performance in the context of IJVs in Malaysia. Analysis of the data employing 2SLS estimators for latent variables demonstrates that on the performance measures of customer retention, sales growth, new product success, overall performance and the measure of average business performance, market orientation was able to encompass learning orientation, but learning orientation was not able to encompass market orientation. For return on investment, learning

0.351* (2.39) 0.204 (1.25) 0.023 (0.87) 0.611** (2.73) 0.248 (1.50) 0.383* (2.52) 0.113 (0.58) 0.328 ( 1.59) 0.315 (1.60) 0.306 11.10

1.104** (2.21) 0.634** (3.44) 0.372 (1.11) 0.400* (2.12) 0.265 (1.31) 0.007 (0.05) 0.699** (2.73) 0.310 (1.86) 0.426* (2.54) 0.299 (1.85) 0.493* ( 2.12) 0.296 (1.34) 0.267 18.98

1.101 (1.28) 0.530** (2.88) 0.228 ( 1.11) 0.208 ( 1.17) 0.022 ( 0.08) 0.426* (2.05) 0.707** (3.70) 0.293 (1.20) 0.912** ( 3.52) 0.466 (1.88) 0.266 15.12

2.623** (4.18) 0.592* (2.57) 0.390 (0.86) 0.594** (3.02) 0.213 ( 1.12) 0.202 ( 1.25) 0.055 (0.16) 0.454* (2.28) 0.752** (3.43) 0.520* (2.33) 0.965** ( 2.86) 0.283 (1.01) 0.231 15.84

2.627** (2.61)

Customer retention MO model LO model

0.195 (1.05) 0.219 (1.06) 0.131 ( 0.73) 0.821** (2.89) 0.492* (2.35) 0.090 ( 0.47) 0.206 ( 0.84) 0.007 ( 0.03) 0.467 (1.87) 0.244 10.88

1.160 (1.84) 0.736** (3.17)

0.989* (2.06) 0.304 (1.49) 0.237 (1.09) 0.206 ( 1.16) 0.943** (3.15) 0.519* (2.00) 0.073 ( 0.35) 0.001 ( 0.003) 0.147 ( 0.56) 0.414 (1.92) 0.227 15.02

0.362 (0.38)

New product success MO model LO model

Notes: Linear-log models. The t-ratios are given in parentheses, based on White’s heteroscedastic consistent covariance matrix; GR2 is the generalized R2 for IV regressions (Pesaran and Smith, 1994); OIR is the heteroscedastic robust over-identifying restrictions test (Wooldridge, 1995) and is distributed as: 2 for the MO models and 2 for the LO models; *significant at the 5 per cent level; **significant at the 1 per cent level

Constant Market orientation Learning orientation Relative size Relative cost Ease of entry Supplier power Buyer power Market growth Competitive intensity Market turbulence Technological turbulence GR2 OIR

Variables

Business performance (Average: five items) MO model LO model

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The 2SLS regressions for performance

Table IV.

Table V. The 2SLS regressions for performance 0.180 (0.95) 0.338 (1.60) 0.329 (1.80) 0.775** (2.68) 0.059 ( 0.28) 0.474* (2.42) 0.108 (0.43) 0.021 ( 0.08) 0.258 (1.02) 0.239 13.01

0.217 (0.34) 0.685** (2.90) 0.464 (1.06) 0.235 (1.01) 0.400 (1.62) 0.300 (1.76) 0.862** (2.68) 0.007 (0.04) 0.513* (2.51) 0.279 (1.27) 0.182 ( 0.65) 0.260 (1.04) 0.206 20.11

0.132 (0.13) 0.483* (2.25) 0.289 (1.20) 0.101 (0.49) 0.868** (2.64) 0.185 (0.76) 0.185 (0.83) 0.027 (0.10) 0.256 ( 0.84) 0.251 (0.87) 0.168 18.93

0.819 (1.12) 0.358 (1.33) 0.151 ( 0.34) 0.484 (1.77) 0.382 (1.26) 0.137 (0.65) 0.953** (3.06) 0.252 (1.14) 0.240 (0.94) 0.222 (0.91) 0.510 ( 1.75) 0.288 (0.93) 0.170 23.43

1.245 (1.15)

Return on investment MO model LO model

0.366 (1.94) 0.403 (1.92) 0.023 (0.12) 0.614* (2.13) 0.197 (0.93) 0.640** (3.27) 0.344 (1.37) 0.444 ( 1.67) 0.131 (0.52) 0.292 10.72

0.702 (1.09) 0.782** (3.32)

0.167 (0.37) 0.386 (1.42) 0.518 (1.73) 0.008 (0.04) 0.682 (1.85) 0.317 (1.35) 0.698** (3.18) 0.477* (2.13) 0.661 ( 1.91) 0.237 (0.62) 0.254 23.35

1.119 (0.95)

Overall performance MO model LO model

Notes: Linear-log models. The t-ratios are given in parentheses, based on White’s heteroscedastic consistent covariance matrix; GR2 is the generalized R2 for IV regressions (Pesaran and Smith, 1994); OIR is the heteroscedastic robust over-identifying restrictions test (Wooldridge, 1995) and is distributed as: 2 for the MO models and 2 for the LO models; *significant at the 5 per cent level; **significant at the 1 per cent level

Constant Market orientation Learning orientation Relative size Relative cost Ease of entry Supplier power Buyer power Market growth Competitive intensity Market turbulence Technological turbulence GR2 OIR

Sales growth MO model LO model

300

Variables

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orientation was able to encompass market orientation, but market orientation was not able to encompass learning orientation. That is, learning orientation was better able to explain variations in ROI than was market orientation. Thus, on balance, these findings suggest that in IJVs, a market orientation is the pre-eminent strategy, given its overall explanatory power in the aforementioned variables of interest. Thus, based on the above, we agree with Baker and Sinkula (1999a, p. 427) that ‘‘in the absence of one or the other’’, it is preferable for a firm in an IJV to have a strong market orientation. Recent studies in the IJV literature (Kandemir and Hult, 2005; Wu and Cavusgil, 2006), have emphasized the importance of a learning orientation as a platform to facilitate learning and organisational performance. In short, it is argued that a learning orientation facilitates generative learning. Generative learning (Senge, 1990; doubleloop learning in Argyris, 1977) ‘‘occurs when the organisation is willing to question long-held assumptions about its mission, customers, capabilities or strategy’’ (Slater and Narver, 1995, p. 63). As Slater and Narver (1995, p. 63) argue, ‘‘generative learning is frame-breaking and more likely to lead to competitive advantage than adaptive learning’’. From a resource based perspective, superior organisational learning should lead to an advantage for the following reasons: ability to successfully understand customers and competitors; ability to engage in generative learning; It is difficult to copy; and It is difficult for competitors to create equivalent valuable resources. However, our results, support recent work and argument by Vijande et al. (2005, p. 189) that ‘‘market-oriented firms can be seen in themselves, as learning-oriented organisations, which do not need any other type of additional orientations to develop such learning’’. In other words, while a learning orientation is a resource which is capable of generating an advantage, it is but one resource. Our findings support the argument that competencies are an important source of sustainable competitive advantage. Clearly, market-oriented firms have highly developed competencies that enable them to outperform competitors in retaining customers, growing sales and new product success. The key resource they have is their superior customer sensing and responding skills (Day, 1994). Similarly, our findings also support the concept of causal ambiguity (Reed and Fillippi, 1990) in that marketoriented firms are able to undertake competitive actions, which are not easily imitable. For firms involved in IJVs, a market orientation will enable them to achieve a competitive advantage. In general, our results provide further support for the resource-based view of the firm. When firms enter IJVs, in which there is the challenge of competing in a relatively unknown market, firms need to possess a variety of resources in which to compete effectively. A market-oriented firm possesses superior resources and skills in the systematic acquisition, dissemination and use of information to guide strategy development and implementation (Kohli and Jaworski, 1990). Such skills enable a firm to identify opportunities and create customer value more effectively than competitors. However, while our results clearly demonstrate the superiority of a market orientation over a learning orientation, we do not advocate that firms engaged in IJVs completely abandon a learning orientation. As Bell et al. (2002, p. 79), a market and learning orientation ‘‘help to explain the critical organisational capability of market sensing . . . [and] both encompass relationships and interdependencies between individuals and groups’’. In IJVs where the transfer of knowledge is seen as a key component of the venture, a learning orientation may be necessary to facilitate organisational learning. Indeed, Vijande et al. (2005, p. 198) state that ‘‘learning orientation is also capable of promoting another type of valuable organisational resource such as the development of

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long-term relationships with strategic clients’’. This is supported by findings that a ‘‘firm that possesses a culture based on learning will tend to generate more easily feelings of trust and effective commitment to its strategic clients’’. Adopting the view of Baker and Sinkula (1999a, p. 421) it can be argued that a market orientation, without a strong learning orientation, may lead to ‘‘more imitative development that can sustain performance but is less likely to lead to the type of competitive advantage that will build market share’’ (Baker and Sinkula, 1999a, p. 422). An aspect of our findings is the existence of a non-linear relationship between market orientation and performance for IJVs. The preferred linear-log relationship implies that for similar improvements in market orientation, larger gains in performance are achieved by firms who have low initial levels of market orientation (For example, a one unit increase in market orientation increases business performance by 0.11 units for a firm with an initial high level of ‘‘six’’ for market orientation and by 0.32 units for a firm with an initial low level of ‘‘two’’ for market orientation). For firms with low levels of market orientation, the impact on performance is three times greater. If the financial and other resource costs are similar across firms for improving market orientation by unit increments, then greater performance benefits are gained by firms with low levels of market orientation. In other words, strategies geared toward improving market orientation are likely to be more effective for firms currently not pursuing market-oriented practices. Conclusion, limitations and directions for further research This study has demonstrated that for firms’ engaged in IJVs a market orientation has a more positive relationship with organisational performance (customer retention, new product success, average performance and overall performance) than a learning orientation, which was found to only have a stronger relationship with ROI. This finding supports Farrell and Oczkowski (2002) and Vijande et al. (2005). Our finding also raises doubts regarding the finding by Calantone et al. (2002), given the fact that their model failed to include a measure of market orientation. An interesting uncommon finding is the existence of a non-linear relationship between market orientation and performance for IJVs. From a theoretical perspective, our findings may tempt readers to question the argument that a learning orientation is a valuable resource based asset. However, despite the empirical evidence in this study which suggests that a market orientation is superior to a learning orientation in relation to the dependent variables in this study, we urge caution in interpretation. We do not believe that our results undermine the resource-based view of the firm, or suggest that a learning orientation is not a valuable resource based asset. Our study used data collected at one point in time. It would be more revealing to collect the same data over a longer period, to determine whether the learning orientation of the firm requires a longer time in which to have the desired effect, and also to control for systematic unobserved heterogeneity that can confound resource-competitive advantage relationships (Henderson and Cockburn, 1994). With regards limitation, the study relied on data collected from a single-informant. Although this approach is commonly used in such studies, future studies may wish to consider collecting data from multiple informants. The study is also limited in that the data was collected from a key informant internal to the organisation. However, given that the resource-based view is concerned with advantage over competitors, future research could also collect data from competitors, or industry experts, such as business analysts, who can then provide an alternative perspective on the firm’s resources (Armstrong and

Shimizu, 2007). Another possible limitation is that we collected data from only one partner in the IJV – the partner that was entering the market. Future studies may consider gathering data from both the partners, international and host-country partner. This data may be useful for studies that wish to examine whether the cultural context has any effect on perceptions. Hofstede’s (2001) power-distance dimension of national culture would be a useful famework for future studies. Future research could also develop measures of adaptive and generative learning. These important constructs have long been the subject of theoretical debate, and attempts to operationalise these and integrate them into a study investigating the performance of IJVs is to be encouraged. References Anand, B. and Khanna, T. (2000), ‘‘Do firms learn to create value’’, Strategic Management Journal, Vol. 21, pp. 295-315. Argyris, C. (1977), ‘‘Double loop learning in organisations’’, Harvard Business Review, Vol. 55, pp. 115-25. Armstrong, C.E. and Shimizu, K. (2007), ‘‘A review of approaches to empirical research on the resource-based view of the firm’’, Journal of Management, Vol. 33 No. 6, pp. 959-86. Atuahene-Gima, K. (1996), ‘‘Market orientation and innovation’’, Journal of Business Research, Vol. 35, pp. 93-103. Baker, W.E. and Sinkula, J.M. (1999a), ‘‘The synergistic effect of market orientation and learning orientation on organizational performance’’, Journal of the Academy of Marketing Science, Vol. 27 No. 4, pp. 411-27. Baker, W.E. and Sinkula, J.M. (1999b) ‘‘Learning orientation, market orientation and innovation: integrating and extending models of organizational performance’’, Journal of Market Focussed Management, Vol. 4, pp. 295-308. Barney, J.B. (1991), ‘‘Firm resources and sustained competitive advantage’’, Journal of Management, Vol. 17 No. 1, pp. 99-120. Beamish, P.W. (1993), ‘‘The characteristics of joint ventures in the People’s Republic of China’’, Journal of International Marketing, Vol. 1 No. 2, pp. 29-48. Bell, S.J., Whitwell, G.J. and Lukas, B.A. (2002), ‘‘Schools of thought in organizational learning’’, Journal of the Academy of Management Science, Vol. 30 No. 1, pp. 70-86. Bollen, K.A. (1996), ‘‘An alternative two stage least squares (2SLS) estimator for latent variable equations’’, Psychometrika, Vol. 61, pp. 109-21. Bollen, K.A., Kirby, J.B., Curran, P.J., Paxton, P.M. and Chen, F. (2003), ‘‘Latent variable models under misspecification: two stage least squares (2SLS) and full information maximum likelihood (FIML) estimators’’, paper presented at Research Methods 2003 Conference, Free University, Amsterdam. Calantone, R.J., Cavusgil, S.T. and Zhao, Y. (2002), ‘‘Learning orientation, firm innovation capability, and firm performance’’, Industrial Marketing Management, Vol. 31, pp. 515-24. Celuch, K.G., Kasouf, C.J. and Peruvemba, V. (2002), ‘‘The effects of perceived market and learning orientation on assessed organizational capabilities’’, Industrial Marketing Management, Vol. 31, pp. 545-54. Chandon, P., Morwitz, V.G. and Reinartz, W.J. (2005), ‘‘Do intentions really predict behaviour? selfgenerated validity effects in survey research’’, Journal of Marketing, Vol. 69 No. 2, pp. 1-14. Cullen, J.B., Johnson, J.L. and Sakano, T. (1995), ‘‘Japanese and local partner commitment to IJVs: psychological consequences of outcomes and investments in the IJV relationship’’, Journal of International Business Studies, Vol. 26 No. 1, pp. 91-115.

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Appendix. Measures Market orientation: (1) Our business objectives are driven by customer satisfaction. (2) We monitor our level of commitment and orientation to serving customers’ needs[1]. (3) Our strategy for competitive advantage is based on our understanding of customer needs[1]. (4) Our business strategies are driven by our beliefs about how we can create greater value for customers. (5) We measure customer satisfaction systematically and frequently. (6) We give close attention to after-sales service. (7) Our salespeople share information within our business concerning competitors’ strategies. (8) We respond to competitive actions that threaten us[1]. (9) We target customers and customer groups where we have, or can develop, a competitive advantage. (10)

The top management team regularly discusses competitors’ strengths and strategies.

(11)

Our top managers from every function visit our current and prospective customers.

(12)

We communicate information about our successful and unsuccessful customer experiences across all business functions.

(13)

All of our business functions (e.g. marketing and sales, manufacturing, R&D, finance and accounting, etc.) are integrated in serving the needs of our target markets.

(14)

All of our managers understand how everyone in our company can contribute to creating customer value[3].

Learning orientation: (1) Managers basically agree that our organisation’s ability to learn is the key to our competitive advantage[1]. (2) The basic values of this organisation include learning as a key to improvement. (3) The sense around here is that employee learning is an investment, not an expense. (4) Learning in my organisation is seen as a key commodity necessary to guarantee organisational survival[3]. (5) Our culture is one that does not make employee learning a top priority[2][1]. (6) The collective wisdom in this enterprise is that once we quit learning, we endanger our future. (7) There is a well-expressed concept of who we are and where we are going as a business. (8) There is total agreement on our organisations’ vision across all levels, functions and divisions. (9) All employees are committed to the goals of this organisation. (10)

Employees view themselves as partners in charting the direction of the organisation[1].

(11)

Top leadership believes in sharing its vision for the organisation with lower levels.

(12)

We do not have a well-defined vision for the organisation[2].

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(13)

We are not afraid to reflect critically on the shared assumptions we have made about the way we do business[1].

(14) Managers in this organisation do not want their ‘‘view of the world’’ to be questioned[2][1]. (15)

Our organisation places a high value on pen-mindedness.

(16)

Managers encourage employees to ‘‘think outside the box’’.

(17)

An emphasis on constant innovation is not part of our corporate culture[2][1].

(18)

Original ideas are highly valued in this organisation.

Market turbulence: (1) In our kind of business, customers’ product preferences change quite a bit over time. (2) Our customers tend to look for new product all the time[3]. (3) We are witnessing demand for our products and services from customers who never bought them before[1]. (4) New customers tend to have product-related needs that are different from those of our existing customers. (5) We cater to many of the same customers that we used to in the past[2][1]. Competitive intensity: (1) Competition in our industry is cutthroat. (2) There are many ‘‘promotion wars’’ in our industry. (3) Anything that one competitor can offer, others can match readily. (4) Price competition is the hallmark of our industry. (5) One hears of a new competitive move almost every day[3]. (6) Our competitors are relatively weak[2][1]. Technological turbulence: (1) The technology in our industry is changing rapidly. (2) Technological changes provide big opportunities in our industry[3]. (3) A large number of new product ideas have been made possible through technological breakthroughs in our industry. (4) Technological developments in our industry are rather minor[2][1]. Notes 1. Deleted item. 2. Reverse scored. 3. Scaling item.

Corresponding author Mark Anthony Farrell can be contacted at: [email protected]

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