The performance effect of organizational learning and market orientation

Industrial Marketing Management 36 (2007) 694 – 708

The performance effect of organizational learning and market orientation Daniel Jiménez-Jiménez a,⁎, Juan G. Cegarra-Navarro b,1 a

b

Departamento de Organización de Empresas y Finanzas, Facultad de Economía y Empresa, Universidad de Murcia, Campus de Espinardo, CP: 30.100, Espinardo Murcia, Spain Departamento de Economía de la Empresa, Facultad de Ciencias de la Empresa, Universidad Politécnica de Cartagena, Paseo Alfonso XIII, 50, CP: 30.203 Cartagena Murcia, Spain Received 8 December 2004; received in revised form 9 May 2005; accepted 19 February 2006 Available online 5 July 2006

Abstract In recent decades an important set of articles on management has focused upon the marketing concept and the related construct of market orientation. The next challenge is to understand how this organizational orientation can be achieved and maintained. Using data from 451 companies and through structural equation models, this study considers that organizational learning represents the capacity of a company to move from a given situation to another desired situation of market orientation and performance. The results suggest that the influence of market orientation on performance is only significant when it is mediated by organizational learning. The results also indicate that organizational learning has a positive effect on performance. © 2006 Elsevier Inc. All rights reserved. Keywords: Organizational learning; Learning orientation; Market orientation; Performance; Competitive advantage

1. Introduction Over the last few decades there have been an increasing number of studies focusing upon the fields of organizational learning and market orientation as precursors of organizational performance (Hult & Ketchen, 2001), and both can be viewed as resources that a firm might employ to attain competitive advantage (Baker & Sinkula, 1999b; Celuch, Kasouf, & Peruvembac, 2002; Day, 1994a,b; Dickson, 1996; Hunt & Morgan, 1996) and a key to successful product innovation and performance (Dickson, 1996; Slater & Narver, 1995). The relationships among organizational learning, market orientation and organizational performance can be explored from the resource-based view of the firm (Barney, 1986a,b; Prahalad & Hamel, 1990; Wernerfelt, 1984). The resource-based view perceives the firm as a unique bundle of idiosyncratic resources and capabilities where the primary task of management is to maximize value through the optimal deployment of existing ⁎ Corresponding author. Tel.: +34 968 36 79 00. E-mail addresses: [email protected] (D. Jiménez-Jiménez), [email protected] (J.G. Cegarra-Navarro). 1 Tel.: +34 968 32 57 88. 0019-8501/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.indmarman.2006.02.008

resources and capabilities, while developing the firm's resource base for the future (Grant, 1996). Thus, the resource-based view provides a firm-specific perspective wherein the importance of tangible and intangible resources and capabilities that are valuable, rare and not easily imitated or substituted by a firm (Barney, 1991) are emphasized as the source of competitiveness. In this context, market orientation (Day, 1994b; Hult & Ketchen, 2001) and organizational learning (Grant, 1996; Spender, 1996) are some of the capabilities that allow firms to attain a stronger positional advantage. On one hand, ‘market orientation’ could be understood as a philosophy and behavior directed toward determining and understanding the needs of the target customer and adapting the selling organization's response in order to satisfy those needs better than the competition, thereby creating a competitive advantage (Saxe & Weitz, 1982). On the other hand, ‘organizational learning’ is a mechanism by which the organization transforms the individual knowledge of employees into social knowledge (Grant, 1996; Spender, 1996). Although there are many overlaps between a market orientated company and a learning organization (Baker & Sinkula, 1999b; Slater & Narver, 1995), the two constructs are not identical. The purpose of this paper is to contribute to the understanding of the links between these constructs and their effects in performance.

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Specifically, we show how organizational learning is considered to be a main factor in the achievement competitive advantage. This paper is organized as follows: Firstly, we briefly review organizational learning and market orientation and their relationships with organizational performance. Next, we present the model and the hypotheses that are going to be tested in the last part of this research. Finally, the results, discussion of their implications and future research directions are presented. 2. Organizational learning Few topics in management have received more attention over the last decade than that of The Learning Organization (see Crossan, Lane, White, & Djurfeldt, 1995; Dixon, 1992; Dodgson, 1993; Jones & Hendry, 1994; Slater & Narver, 1995 for reviews of relevant literature). Thus, from the original studies focused on organizational learning (Argyris, 1976; Cangelosi & Dill, 1965; Chapman, Kennedy, Newell, & Biel, 1959; Cyert & March, 1963; Hirschman & Lindblom, 1962; March & Olsen, 1975) there is a very rapidly growing interest from a diverse variety of academic perspectives on this subject (Bontis, Crossan, & Hulland, 2002; Crossan, Kane, & White, 1999; Jones & Hendry, 1994; March, 1991; Romme & Dillen, 1997; Senge, 1990; Stata, 1989). The continuing popularity of this paradigm has resulted in two main perspectives: 1) Learning organizations can be seen as “…organizations where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free, and where people are continually learning to see the whole together” (Senge, 1990). This concept, according to Matlay (1997), gains recognition amongst high profile, innovative organizations that set out to increase their market share through highly successful, learning-based human resource and knowledge management strategies. 2) Organizational learning may be seen as a process whereby empirical measurement is easier than a stock perspective (Sinkula, Baker, & Noordewier, 1997) and besides “an understanding of what is known is of less value to the organization than understanding what it is capable of knowing, because a stock of knowledge that is not continually updated rapidly depreciates in value” (Bell, Whitwell, & Lukas, 2002). The capacity of organizations to learn has long intrigued researchers and has motivated an increasing number of these studies. However, there is no extended agreement about the concept of organizational learning due to the diversity of research domains in which learning phenomena have been explored (Crossan et al., 1999) and the concept of organizational learning is embedded in different schools of thought, including contingency theory, psychology, organizational development, Management Science, social anthropology, information theory and system dynamics, sociology, industrial economy, production and operation management systems theory, organizational theory and strategic management that are founded on very different theoretical assumptions and should be viewed as complementary to

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each other in understanding organizational learning (Dodgson, 1993; Easterby-Smith, 1997; Romme & Dillen, 1997; Shrivastava, 1983). Examining the organizational learning concepts, Huber (1991) noted that “an organization learns if any of its units acquire knowledge that it recognizes as potentially useful to the organization”, understanding organizational learning as the development process of new knowledge or insights that have the potential to influence behavior. In this case, “organizational learning occurs when members of the organization act as a learning agent for the organization, responding to changes in the internal and external environment of the organization by detecting and correcting errors” (Argyris & Schon, 1978). It is necessary for the individual knowledge to be transferred to the organization, so that it can be used by individuals other than the progenitor (Sinkula, 1994). Thus, there is a link between the learning of the employees of a company and the learning of this organization (Sinkula et al., 1997). Also, the literature usually distinguishes between singleloop or adaptive learning and double-loop or generative learning. In former individuals and groups adjust their behavior to fixed goals, norms and assumptions, but in the latter, all these goals, norms and assumptions, as well as their behavior, are open to change (Argyris & Schon, 1978; Senge, 1990), and consequently, employees are always questioning their assigned roles and targets rather than merely realizing them. Although there is some variance in the specifics, organizational learning scholars typically conceptualize organizational learning as including four primary constructs: information acquisition, distribution, interpretation, and memory (Crossan et al., 1999; Day, 1994a; Dean & Snell, 1991; Dixon, 1992; Huber, 1991; Nevis, Dibella, & Gould, 1995; Romme & Dillen, 1997; Sinkula, 1994; Slater & Narver, 1995; Snell, Youndt, & Wright, 1996). Organizational learning needs the creation and control of both external and internal knowledge for both current and future operations (Leonard-Barton, 1992). Thus, knowledge acquisition requires constant effort and continual experimentation from all employees of the organization. Then, when an individual acquires knowledge, the company has to foster the distribution of this knowledge among the rest of members of the organization. This distribution consists in the transmission of the acquired knowledge at an individual level principally through individual conversations and interrelations between employees of the organization (Brown & Duguid, 1991; Koffman & Senge, 1993). Before the organization can use the distributed knowledge, it must first be interpreted. For this to happen, knowledge is translated, developing models of understanding, bringing out meaning, and assembling conceptual schemes among key managers (Daft & Weick, 1984) developing a shared understanding and the taking of coordinated action by members of a workgroup (Crossan et al., 1999). Finally, organizational memory is the collective knowledge of an organization and contains theories in use, shared mental models, information databases, formalized procedures and routines, and formal cultural mores that guide behavior (Slater & Narver, 1995), have effect on performance (Walsh & Ungson, 1991), are based on past knowledge and experience (Stata, 1989) and can be brought to bear on present decisions (Walsh & Ungson, 1991).

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Organizational ability to decode and respond to a challenging environment has motivated considerable theoretical and practical interest (Edmondson & Moingeon, 1998a). Thus, the literature has recognized the strategic importance of organizational learning as a means to attain sustained competitive advantage for the firm (DeGeus, 1988; Garvin, 1993; McGill, Slocum, & Lei, 1992; Stata, 1989). By the late 1980s, influential academics, policy makers and practitioners promoted organizational learning as a strategic element in the quest for sustainable business competitiveness (Edmondson & Moingeon, 1998b; Hunt & Morgan, 1996; Senge, 1990), and which allows companies to achieve better results than the competition (Stata, 1989). In essence, learning orientation is reflected by the presence of values that influence the propensity of a firm to proactively pursue new knowledge and challenge the status quo (Sinkula et al., 1997; Slater & Narver, 1995). Discussions of the effect of organizational learning on performance would benefit from a better understanding of what learning is and its theoretical origins (Bell et al., 2002). So, some authors have looked for those organizational characteristics that foster the organizational learning process, such as shared mental models, shared organizational vision and open-minded approaches to problem solving, organizational culture, strategy, teamwork, human resource management or research and development (see e.g. Fiol & Lyles, 1985; Harvey & Denton, 1999; McGill et al., 1992; Senge, 1990). Among these factors, there is an emergent literature focused on how organizational learning confers competitive advantage through its interplay with marketing capabilities and outcomes (e.g. Baker & Sinkula, 1999b; Slater & Narver, 1995). 3. Market orientation Although other terms have previously been used, such as “marketing orientation” or “market driven” (e.g. Kohli & Jaworski, 1990; Shapiro, 1988; Webster, 1988), a review of the literature reveals diverse definitions of the market orientation concept. Day (1994b), Deshpandé, Farley, and Webster (1993), Narver and Slater (1990), Slater and Narver (1995) define this construct as an aspect of organizational culture. Thus, market orientation is “the culture that places the highest priority on the profitable creation and maintenance of superior customer value while considering the interests of other stakeholders; and provides norms for behavior regarding the organizational development and responsiveness to market information” (Slater & Narver, 1995). This culture comprises three behavioral components: customer orientation, competitor orientation and interfunctional coordination (Narver & Slater, 1990). A second perspective, relevant to this paper, suggests that market orientation is related to the implementation of the marketing concept. Kohli and Jaworski (1990) define market orientation as “the organization-wide generation of market intelligence pertaining to current and future customer needs, dissemination of intelligence across departments, and organizationwide responsiveness to it”. Market orientation is defined in a similar way by Ruekert (1992), but emphasizing an explicit focus of strategic planning by business units, so it can be viewed

as the degree to which a firm's analysis of the external marketing environment influences the strategic planning process (Baker & Sinkula, 2002). Hence, the term market orientation includes the ability of the organization to generate, disseminate and use superior information about customers and competitors. Consequently market orientation is not a discrete phenomenon, and a firm’s market orientation exists along a continuum (Baker & Sinkula, 1999b). According to this point of view, key indicators of market orientation include the organization-wide acquisition of market information, followed by its interdepartmental dissemination, consideration and processing and the organizational use of this information to respond to customers, channels, competitors and strategic partners to adapt to changing market conditions. Studies focused on market orientation have investigated the antecedents (e.g. climate, conflict coordination, structural variables), consequences (e.g. business performance, employee attitudes, product innovation) and relationship moderators (e.g. competition, environment) of market orientation (see e.g. Baker & Sinkula, 1999a,b; Han, Kim, & Shrivastava, 1998; Hurley & Hult, 1998; Jaworski & Kohli, 1993; Kohli & Jaworski, 1990; Sinkula et al., 1997). However, academic and practitioner attention has been mostly directed towards the association between market orientation and organizational performance. The conclusions that have been drawn from studies of the relationship between these concepts are mixed. A growing number of empirical studies have verified that an improvement in the level of market orientation will lead to superior organizational performance (Narver & Slater, 1990; Oczkowski & Farrell, 1998; Ruekert, 1992; Slater & Narver, 1994, 2000b), in accordance with the resource-based theory. Another group of studies report no significant relationship (Hart & Diamantopoulos, 1993), and yet a third group report mixed results (Greenley, 1995; Jaworski & Kohli, 1993), showing that perhaps the relationship is more complex than a linear one (Hult & Ketchen, 2001). However, it is generally accepted in the literature that the linkage between a market orientation and performance appears to be robust (Jaworski & Kohli, 1993), and managers should strive to improve the market orientation of their businesses in their effort to attain higher business performance. Despite these relatively consistent findings, a number of authors question the benefits of being market oriented, and suggest that there may be several limitations to a market orientation (Farrell & Oczkowski, 2002). Some authors note that creating a market orientation is only the beginning (Slater & Narver, 1995) and that opting for organizational learning as a key element to sustain competitive advantage is better in the long run (Farrell & Oczkowski, 2002; Lukas, Hult, & Ferrell, 1996; Slater & Narver, 1995). The relationship between organization learning, market orientation and performance is discussed in the next section of this paper. 4. The relationship between market orientation, organizational learning and performance The study of the relationship between market orientation, organizational learning and performance has increased since the

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works of Sinkula (1994) and Slater and Narver (1995). Following these authors, the literature has noted that market orientation is compatible with gaining external knowledge (Day, 1994a). Furthermore, market organizations provide the cultural framework from which a learning orientation can develop (Slater & Narver, 1995), and can also be seen as learning orientated organizations. Thus, market orientation could be described as a set of processes that enable firms to learn (Dickson, 1996). Although we have noted that there is a causal relationship between market orientation and organizational learning, the fact is that the dependent direction of this relationship is not clear. According to Farrell and Oczkowski (2002) the literature review suggests three alternative models. To date, this issue remaining unresolved (Bell et al., 2002). The first model proposes that organizational learning is the foundation for market orientation which in turn leads to organizational performance (Day, 1994b; Santos-Vijande, Sazo-Pérez, Álvarez-González, & VázquezCasielles, 2005). In the second model, it is market orientation which precedes organizational learning in order to attain better performance (Farrell, 2000; Slater & Narver, 1995). Finally, in a third model, both organizational learning and market orientation are directly related to organizational performance (Baker & Sinkula, 1999b). Perhaps the key to the problem is to assume that these possibilities are not exclusive (Santos-Vijande et al., 2005), because a learning organization can succeed in being adequately market orientated, and the cultural values of market orientation and an adequate pattern of behavior coherent with these, may also give rise to a true learning organization. However, the common objective of market orientation and organizational learning studies has been to examine how the successful acquisition of knowledge can help organizations understand customer needs and, ultimately, improve their performance (e.g. Deshpandé et al., 1993; Kohli & Jaworski, 1990; Slater & Narver, 1995). In spite of these affinities, these concepts are not the same thing. First, learning orientation influences the propensity of the firm to create and use all kinds of knowledge, not just market-based knowledge (Baker & Sinkula, 1999b), and specially promote generative learning as a core competency (Sinkula et al., 1997) rather than only the adaptive learning promoted by a market organization. In effect, market orientation is reflected in a firm’s knowledge-producing behaviors and is thereby implicated in its market information processing activity (Baker & Sinkula, 1999b), which may routinely result in adaptive learning. In contrast, learning orientation is reflected by a firm's knowledge questioning values, promoting generative learning which encompasses more than a purely market place focus (Celuch et al., 2002). Second, organizational learning requires other cultural variables (e.g. entrepreneurship, organic structure, facilitative leadership, decentralized strategic planning and a challenging external environment) in addition to market orientation (Slater & Narver, 1995), although this last item may be the most important factor. Finally, learning organizations are characterized by using internal and external sources of knowledge acquisition, while market orientation is focused primarily on observing customers and competitors outside the boundaries of the firm (Day, 1994a,b), for the profitable creation of superior customer value (Slater, 1996). Consequently, although market

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orientation provides information about the current and latent needs of their customers, and also monitors and anticipates what competitors are doing to provide customer value, organizational learning could generate information from experience, learning by doing or from a consolidated policy of R and D to give a few examples beyond the market sphere. It is not necessary for all knowledge acquired to proceed from market sources. Consequently, we understand that, although all acquired knowledge from market orientation could be organizational knowledge in the end, the converse is not true, and not all knowledge that is generated from an internal focus could present in a marked orientation. Hence, our hypothesis is stated as follows: H1. Market orientation has a positive impact on the process of organizational learning. As the literature has recognized, market orientation is considered to be a source of competitive advantage. Because of its external focus, marketing is well positioned to appreciate information about consumers. This orientation provides a focus for the product development of the business and sales growth efforts by enabling the business to develop strong relationships with key customers and insights into opportunities for market development (Slater & Narver, 2000a). As the literature shows on repeated occasions, there is a positive link between market orientation and organizational performance (Doyle & Wong, 1998; Farrell, 2000; Hooley, Fahy, Cox, Beracs, & Snoj, 1999; Jaworski & Kohli, 1993; Ruekert, 1992; Santos-Vijande et al., 2005). This led the authors of the present paper to conclude that marketing orientation is the cause of superior performance. Thus, it follows that: H2. Market orientation has a positive impact on overall organizational performance. A strong market orientation is required to focus the company on those environmental events that are likely to affect their ability to maximize customer satisfaction relative to competitors, but it is a mechanism that primarily facilitates adaptive learning (Baker & Sinkula, 1999b). Adaptive organizations focus on incremental improvements, often based upon the past track record of success. Essentially, they do not question the fundamental assumptions underlying the existing ways of doing work. On the other hand, learning orientation is a mechanism that directly affects a firm's ability to challenge old assumptions about the market and how a firm should be organized to address it (Baker & Sinkula, 1999b). This kind of learning is generative learning. Senge (1990) notes that increasing adaptiveness is only the first stage, and companies need to focus on generative learning. Generative learning emphasizes continuous experimentation and feedback in an ongoing examination of the very way organizations go about defining and solving problems. Furthermore, it is concerned with building new competences, or identifying and creating opportunities based on leveraging existing competences, to generate new business opportunities. While market orientation may lead to adaptive, single-loop learning, producing incremental innovations, organizational learning allows firms to develop generative, doubleloop learning and radical innovations (Argyris & Schon, 1978; Baker & Sinkula, 2002; Sinkula, 1994; Slater & Narver, 1995).

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Table 1 Constructs measurements summary: confirmatory factor analysis and scale reliability Item description Intelligence generation 1. Company does a lot of in-house market research 2. Periodically are analyzed the effect of the shift in the business environment over the company 3. Company adapts quickly to the shift in the business environment (scale: 1 = strongly disagree; 5 = strongly agree) Intelligence dissemination 1. When something important happens to a major customer of the market, the whole business unit knows about it within a short period 2. Data on customer satisfaction are disseminated at all levels in this business unit on a regular basis 3. When one department finds out something about its competitors, it is quick to inform other departments (scale: 1 = strongly disagree; 5 = strongly agree) Responsiveness 1. Company react quickly to changes in their customer’s product or service needs 2. Periodically review our product development efforts to ensure that they are in line with what the customer wants 3. If a major competitor was to launch an intensive campaign targeted at our customers, we would implement a response immediately (scale: 1 = strongly disagree; 5 = strongly agree) Knowledge acquisition 1. There is a consolidated and resourceful R and D policy 2. New ideas and approaches on work performance are experimented continuously 3. Organizational systems and procedures support innovation. (scale: 1 = strongly disagree; 5 = strongly agree) Information distribution 1. All members are informed about the aims of the company 2. Meetings are periodically held to inform all the employees about the latest innovations in the company 3. Company has formal mechanisms to guarantee the sharing of the best practices among the different fields of the activity (scale: 1 = strongly disagree; 5 = strongly agree) Information interpretation 1. All the members of the organization share the same aim to which they feel committed 2. Employees share knowledge and experience by talking to each order 3. Team work is a very common practice in the company (scale: 1 = strongly disagree; 5 = strongly agree)

Standardized loading

t-value

Reliability (SCR a., AVE b)

0.56 0.81 0.84

12.06 19.46 20.39

SCR = 0.77 AVE = 0.52

0.78

18.03

SCR = 0.80 AVE = 0.58

0.77 0.72

17.50 16.09

0.83 0.84 0.61

19.98 20.28 13.48

SCR = 0.79 AVE = 0.56

0.64 0.90 0.90

14.56 23.26 23.40

SCR = 0.84 AVE = 0.64

0.66 0.78 0.76

14.57 17.86 17.34

SCR = 0.78 AVE = 0.54

0.82 0.75 0.62

19.34 17.14 13.39

SCR = 0.77 AVE = 0.53

SCR = 0.83 AVE = 0.62

Organizational memory 1. The company has directories or e-mails filed according to the field they belong to, so as to find an expert on a concrete issue at any time 2. The company has up-to-date databases of its clients 3. Databases are always kept up-to-date (scale: 1 = strongly disagree; 5 = strongly agree)

0.67

15.30

0.87 0.87

21.07 21.11

Open-internal model results 1. Quality product 2. Internal process coordination 3. Personnel activities coordination (scale: in the tree previously years: 1 = decreasing evolution; 5 = rising evolution)

0.56 0.80 0.79

11.60 17.89 17.52

SCR = 0.77 AVE = 0.53

Rational model results 1. Share market 2. Profitability 3. Productivity (scale: in the tree previously years: 1 = decreasing evolution; 5 = rising evolution)

0.70 0.83 0.85

16.13 20.00 20.76

SCR = 0.84 AVE = 0.64

Human relations model results 1. Voluntary personnel rotation 2. Personnel absenteeism (scale: in the tree previously years: 1 = decreasing evolution; 5 = rising evolution)

0.88 0.79

16.99 15.58

SCR = 0.83 AVE = 0.71

Fit statistics for measurement model of 29 indicators for ten constructs: χ2(332) = 722.98; p < 0.001; GFI = 0.90; RMSEA = 0.051; CFI = 0.94; TLI (NNFI) = 0.92. a Scale composite reliability (ρc = (Σλi)2 var (ξ) / ((Σλi)2 var (ξ) + Σθii) (Bagozzi & Yi, 1998)). b Average variance extracted (ρc = (Σλ2i var (ξ)) / (Σλ2i var (ξ) + Σθii) (Fornell & Larcker, 1981)).

Finally, a strong market orientation can be readily copied, but the learning environment that organizes and translates the output of these behaviors into a comparative advantage cannot (Dickson, 1996).

Therefore, there is a increasing body of literature (Brockmand & Morgan, 2003; Dodgson, 1993; Nevis et al., 1995) that suggests that organizational learning is a complex resource of the firm that can be used to create competitive advantage and,

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on the assumption that aspects relating to organizational learning and market orientation affect the entire organization. The information was collected by personal interview with the top executive of the company, using a structured questionnaire and directed to all companies belonging to the population. We have tested for common methods variance (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003) which is a potential danger arising from the use of a single informant when collecting data in each firm, and suggest that the absence of a unique factor with an eigenvalue greater than one indicates that this source of error is not significant. The presence of an interviewer increased the cooperation rates and facilitated immediate clarification. In order to collect high-quality data, the interviewers were trained in order to familiarize them with the variety of situations likely to be encountered, as well as the concepts, definitions, and procedures involved. Four hundred and fifty-one questionnaires were obtained, yielding a response rate of 25.2%. Approximately 55% of responses came from manufacturing firms and the rest from the service sector. The respondent companies were compared with non-respondents on variables such as size and company performance. No statistically significant differences were found between the means of these variables at the 0.01 level in the two groups, suggesting no response bias. Overall, although these variables are frequently used, we cannot be certain that the respondents are not unrepresentative of the population on some other variables.

ultimately, superior performance (Hunt & Morgan, 1996). Although there are studies that suggest the contrary (Baker & Sinkula, 1999b; Farrell & Oczkowski, 2002) that there is a weak relationship between organizational learning and performance, leading to the conclusion that “in the absence of one or the other it would be better for a firm to have a strong market orientation” (Baker & Sinkula, 1999b), there is enough evidence to support a positive link between organizational learning and performance (Bontis et al., 2002; Farrell, 2000; Tippins & Sohi, 2003). Therefore, H3. Organizational learning has a positive impact on overall organizational performance. Thus, although organizational learning is considered to be a key element for competing in the actual markets (Day, 1994b; Tippins & Sohi, 2003), some authors suggest that it is the combination of learning and market orientation which has a higher likelihood of creating a sustainable competitive advantage (Baker & Sinkula, 1999b; Day, 1994b; Dickson, 1996). 5. Method 5.1. Research setting and data collection Our sample was drawn from the SABI database and used single-informants, among Spanish organizations located in the southeast of Spain with more than fifteen employees. In 1986 Spain become a member of European Union. The Spanish economy has grown at an average annual rate of 3.6% between 1996 and 2003, and even though that rate fell to 2.3% last year, that still far outstripped the European Union’s dismal average of 0.6%, allowing real convergence to occur at a fairly brisk pace (OECD, 2005). Today the economy of Spain is the fifth largest in Europe, accounting for around 9% of EU output. Like other studies in organizational learning and market orientation (Jaworski & Kohli, 1993; Sinkula et al., 1997), the present study was designed to extend across industries (excluding the agricultural sector). The sample was composed of companies of different sizes. Many of these companies engage in international activity. Furthermore, others form part of international companies or groups of companies. A total of 1600 companies made up the population. The unit of analysis for this study was the company,

5.2. Measures and measurement properties Before testing the hypotheses, we discuss the set of questionnaire items for each construct (see Table 1). Table 2 provides an overview of the means of the constructs, together with their standard deviations and correlations. 5.2.1. Market orientation In this study, in order to measure the market orientation, we have used an adaptation of the MARKOR scale (Kohli, Jaworski, & Kumar, 1993). This scale considers the three dimensions of market orientation: intelligence generation, intelligence dissemination and responsiveness, from a market orientation related to the implementation of the marketing concept. The confirmatory factor analysis (Table 1) suggests the use of three items to measure

Table 2 Construct correlation matrix Construct

1. Intelligence generation 2. Intelligence dissemination 3. Responsiveness 4. Knowledge acquisition 5. Information distribution 6. Information interpretation 7. Organizational memory 8. Open/internal results 9. Rational results 10. Human results

Mean

3.341 3.546 3.902 3.163 2.791 3.406 3.813 3.947 3.656 3.537

Standard deviation

Correlation matrix 1

2

3

4

5

6

7

8

9

10

0.832 0.843 0.771 0.929 0.909 0.723 0.944 0.562 0.740 0.879

1 0.484 0.513 0.466 0.434 0.405 0.346 0.304 0.262 0.175

1 0.576 0.284 0.342 0.375 0.312 0.233 0.132 0.115

1 0.339 0.286 0.362 0.369 0.237 0.183 0.136

1 0.481 0.470 0.320 0.332 0.301 0.218

1 0.560 0.329 0.380 0.237 0.266

1 0.387 0.347 0.294 0.200

1 0.248 0.181 0.164

1 0.409 0.294

1 0.352

1

700

D. Jiménez-Jiménez, J.G. Cegarra-Navarro / Industrial Marketing Management 36 (2007) 694–708

Table 3 Second-order confirmatory factor analysis of the organizational learning First-order construct

First-order Indicator

Knowledge acquisition

Information distribution Information interpretation

Organizational memory

KA1 KA2 KA3 ID1 ID2 ID3 II1 II2 II3 OM1 OM2 OM3

Second-order Loading

t-value

0.64 0.90 0.91 0.67 0.79 0.76 0.81 0.76 0.62 0.67 0.86 0.87

– 14.95 14.98 –a 12.99 12.74 –a 15.06 12.53 –a 14.99 15.01

Loading

a

t-value 10.53

0.68

0.81

11.63

0.88

14.84

0.46

7.65

Fit statistics for measurement model of 12 indicators for four constructs: χ2(50) = 149.57; p < 0.001; GFI = 0.95; RMSEA = 0.069; CFI = 0.96; TLI (NNFI) = 0.96. a Fixed parameter.

intelligence generation (ρcSCR = 0.77, ρcAVE = 0.52), three to measure intelligence dissemination (ρcSCR = 0.80, ρcAVE = 0.58) and finally another three to quantify responsiveness (ρcSCR = 0.79, ρcAVE = 0.56). 5.2.2. Organizational learning The organizational learning literature advocates more empirical studies into this subject to compensate for a current scarcity. Furthermore, most of the studies in this field are theoretical or derived from consulting stile case study. What little empirical research there is focuses on learning curves (Epple, Argote, & Devadas, 1991), knowledge codification (Kogut & Zander, 1993), the stocks and flows of knowledge (Bontis et al., 2002) or the organizational learning phases (Yahya & Goh, 2002). After reviewing this literature (Armstrong & Foley, 2003; Day, 1994a; Kululanga, Edum-Fotwe, & McCaffer, 2001; Schneider & Angelmar, 1993; Snell et al., 1996), and accepting the theoretical classification of Huber (1991) for organizational learning phases, we have used the organizational learning scale from the study of Pérez López, Montes Peón, and Vázquez Ordás (2004). The measures of these variables are displayed for every phase of organizational learning (see Table 1): knowledge acquisition (scale composite reliability ρcSCR = 0.84, average variance extracted ρcAVE = 0.64), information distribution (ρcSCR = 0.78, ρcAVE = 0.54), information interpretation (ρcSCR = 0.77, ρcAVE = 0.53) and organizational memory (ρcSCR = 0.83, ρcAVE = 0.62). These phases are considered to be a single construct made up of the four behavioral dimensions. A second-order factor analysis is conducted to demonstrate that the four behavioral dimensions can be modeled by a higher order construct in order to analyze our data (Table 3). We estimated this model using LISREL 8.54. The results suggest a good fit of the second-order specification for our measure of organizational learning (χ 2 = 149.57, df = 50, p < 0.001; goodness of fit index [GFI] = 0.95; root mean square error of approximation [RMSEA] = 0.069; comparative fit index [CFI] = 0.96; Tucker-Lewis index [TLI] = 0.95; incremental fit

index [IFI] = 0.96). The GFI, CFI, TLI and IFI statistics exceed the recommended 0.90 threshold level (Hoyle & Panter, 1995). Furthermore, the RMSEA is below 0.080 and the root mean square residual [RMR] and the standardized RMR are 0.059 and 0.050 respectively, which are considered acceptable. Although a significant chi-square value indicates that the model is an inadequate fit, the sensitivity of this test to sample size confounds this finding and makes rejection of the model on the basis of this evidence alone inappropriate (Bagozzi, 1980). However, a ratio less than three (χ2/df < 3) indicates a good fit for the hypothesized model (Carmines & McIver, 1981; Joreskog, 1978). 5.2.3. Performance Finally, the third group of variables presented is that relating to company effectiveness. In order to measure the impact of organizational learning and market orientation on company performance, self-explanatory measures of performance (Baker & Sinkula, 1999b), such as change in market share, new product success, growth, profitability, etc. (e.g. Han et al., 1998) are usually employed, because, as has been shown in previous tests (Dess & Robinson, 1984), subjective and objective measures of performance are highly correlated. Furthermore, the literature defends the use of non-financial performance measures alone (Quinn & Rohrbaugh, 1983; Venkatraman & Ramanujam, 1986). So, the measures of these variables are taken from Quinn and Rohrbaugh (1983), who suggest that the criteria for organizational effectiveness can be sorted to different value dimensions. These dimensions make the identification of four basic models of organizational effectiveness possible: the human relations model, the internal process model, the open system model and the rational goal model. The preliminary exploratory analysis and the confirmatory factor analysis (Table 1) suggest that only three of these models are useful in the present study: the open/internal system model (ρcSCR = 0.77, ρcAVE = 0.53), the rational goal model (ρcSCR = 0.84, ρcAVE = 0.64) and the human relations model (ρcSCR = 0.83, ρcAVE = 0.71). With the aim of analyzing company results, another second order construct has been constructed (see Table 4). The results suggest a good fit of the second-order specification (χ2 = 26.89, df = 17, p = 0.070; GFI = 0.99; RMSEA = 0.035; CFI = 0.99; TLI = 0.99; IFI = 0.99). All, GFI, CFI, TLI and IFI exceed the recommended 0.90 threshold level (Hoyle & Panter, Table 4 Second-order confirmatory factor analysis of the performance First-order construct

First-order Indicator

Loading

t-value

Open/internal model

OR1 OR2 OR3 RR1 RR2 RR3 HR1 HR2

0.55 0.81 0.78 0.70 0.83 0.86 0.84 0.83

–a 10.52 10.51 –a 15.21 15.37 –a 10.36

Rational model Human relations model

Second-order Loading

t-value

0.63

7.65

0.85

9.90

0.85

8.10

Fit statistics for measurement model of 8 indicators for three constructs: χ2(17) = 26.89; p < 0.001; GFI = 0.99; RMSEA = 0.035; CFI = 0.99; TLI (NNFI) = 0.99. a Fixed parameter.

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Fig. 1. A model of the relationship between market orientation, organizational learning and performance.

1995). The RMSEA is below 0.050 and the root mean square residual [RMR] and the standardized RMR are 0.018 and 0.030 respectively, which are very good levels. Therefore, it is possible to conclude that the three result dimensions can be modeled by a second-order construct. To assess the unidimensionality of each construct, a confirmatory factor analysis of the ten constructs employing 29 items was conducted (Anderson & Gerbing, 1988). The measurement model provides a reasonable fit to the data (χ2 = 722.982, df = 332, p < 0.001; GFI = 0.90; RMSEA = 0.051; CFI = 0.94; TLI = 0.92; IFI = 0.94). The traditionally reported fit indices are within the acceptable range. Reliability of the measures is calculated with Bagozzi and Yi's (1998) composite reliability index and with Fornell and Lacker's (1981) average variance extracted index. For all the measures, both indices are higher than the evaluation criteria of 0.6 for the composite reliability and 0.5 for the average variance extracted (Bagozzi & Yi, 1998). Furthermore, all items load on their hypothesized factors (see Table 1), and the estimates are positive and significant (the lowest t-value is 11.60), which provides evidence of convergent validity (Bagozzi & Yi, 1998).

Discriminant validity was tested using three different procedures recommended by Anderson and Gerbing (1988) and Fornell and Larcker (1981). First, discriminant validity is indicated since the confidence interval (±2 S.E.) around the correlation estimate between any two latent indicators never includes 1.0 (Anderson & Gerbing, 1988). Second, discriminant validity was tested by comparing the square root of the AVEs for a particular construct to its correlations with the other constructs (Fornell & Larcker, 1981). Finally, we compared the chi-square statistic between the constrained model where the correlation of a pair of factors was fixed to unity and the unconstrained model with the correlation freely estimated (Anderson & Gerbing, 1988). The results of these three test provided strong evidence of discriminant validity among the constructs. 6. Results The proposed structural model is presented in Fig. 1. This model incorporates the three hypotheses developed previously relating to the relationship of market orientation, organizational learning and

Table 5 Sequential chi-square tests Model

Chi-square

Degrees of freedom

Chi-square difference

Degrees of freedom difference

Probability

Proposed model (MT) Market orientation as a second-order (MA1) Non-organizational learning second-order (MA2) Non-performance second-order (MA3)

771.06 784.70 868.14 814.77

360 364 352 355

13.64 97,08 43.71

4 8 5

p < 0.001 p < 0.001 p < 0.001

Compared to the proposal model (MT), the alternative models (MA) present a significant worse fit. Therefore, MT is preferred as a better alternative. MA1: Market orientation is studied as a second order construct: χ2(364) = 784.70; p < 0.001; GFI = 0.89; RMSEA = 0.052; CFI = 0.93; TLI = 0.92. MA2: Organizational learning is studied as a non-second order construct: χ2(352) = 868.14; p < 0.001; GFI = 0.88; RMSEA = 0.058; CFI = 0.92; TLI = 0.90. MA3: Performance is studied as a non-second order construct: χ2(355) = 814.77; p < 0.001; GFI = 0.89; RMSEA = 0.054; CFI = 0.93; TLI = 0.91.

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Table 6 Construct structural model Linkages in the model

Hypotheses

Standardized parameter estimates

Number

Sign

Parameter

Estimate

H1 H1 H1 H2 H2 H2 H3

+ + + + − + +

γ11 γ12 γ13 γ61 γ62 γ63 β94

0.48 0.22 0.07 0.07 0.15 0.03 0.70

5.24⁎⁎⁎ 2.77⁎⁎⁎ 0.70 0.68 1.59 0.31 5.98⁎⁎⁎

Second-order construct Organizational learning → acquisition Organizational learning → distribution Organizational learning → interpretation Organizational learning → or. memory Performance → open/internal results Performance → rational results Performance → human relations results

+ + + + + + +

β21 β31 β41 β51 β76 β86 β96

0.71 0.81 0.85 0.48 0.74 0.74 0.54

10.42⁎⁎⁎ 10.88⁎⁎⁎ 13.37⁎⁎⁎ 7.89⁎⁎⁎ 8.03⁎⁎⁎ 9.09⁎⁎⁎ 7.97⁎⁎⁎

Indirect effect a Intelligence generation → acquisition Intelligence generation → distribution Intelligence generation → interpretation Intelligence generation → or. memory Intelligence dissemination → acquisition Intelligence dissemination → distribution Intelligence dissemination → interpretation Intelligence dissemination → or. memory Intelligence generation → performance Intelligence dissemination → performance Intelligence generation → open/internal model Intelligence generation → rational model Intelligence generation → human relations model Organizational learning → open/internal model Organizational learning → rational model Organizational learning → human relations model

+ + + + + + + + + + + + + + + +

κ11 κ21 κ31 κ41 κ12 κ22 κ32 κ42 κ61 κ62 κ71 κ81 κ91 ι71 ι81 ι91

0.34 0.39 0.40 0.23 0.16 0.18 0.19 0.11 0.34 0.15 0.31 0.30 0.22 0.52 0.52 0.38

5.23⁎⁎⁎ 5.29⁎⁎⁎ 5.52⁎⁎⁎ 4.79⁎⁎⁎ 2.76⁎⁎⁎ 2.77⁎⁎⁎ 2.80⁎⁎⁎ 2.69⁎⁎⁎ 4.08⁎⁎⁎ 2.50⁎⁎ 3.78⁎⁎⁎ 3.88⁎⁎⁎ 3.75⁎⁎⁎ 6.30⁎⁎⁎ 6.83⁎⁎⁎ 6.17⁎⁎⁎

Hypothesis Intelligence generation → organizational learning Intelligence dissemination → organizational learning Responsiveness → organizational learning Intelligence generation → performance Intelligence dissemination → performance Responsiveness → performance Organizational learning → performance

t-value

⁎p < 0.1; ⁎⁎p < 0.05; ⁎⁎⁎p < 0.01. Fit statistics for measurement model of 29 indicators for twelve constructs: χ2(360) = 771.06; GFI = 0.89; p < 0.001; RMSEA = 0.051; CFI = 0.93; TLI = 0.93. a Only significant effects have been included.

performance. Conventional maximum likelihood estimation techniques were used to test the model (Joreskog & Sorbom, 1996). The fit of the model is satisfactory (χ2 = 771.06, df = 360, p < 0.001; GFI= 0.89; RMSEA = 0.051; CFI= 0.93; TLI = 0.93; IFI= 0.93), thereby suggesting that the nomological network of relationships fits our data — another indicator of support for the validity of these scales (Churchill, 1979). Although p value is small, it is highly unlikely that non-significant test statistics would be obtained with large sample sizes (Kelloway, 1998). To provide greater confidence in our model specification, we tested our theoretical model (MT) against three alternative model specifications (MA). In the first model market orientation was considered to be a second-order construct. The second and third models did not treat organizational learning or performance respectively as second order constructs. This procedure is recommended by Anderson and Gerbing (1988) and suggests the use of the chi-square difference test (CDT) to test the null hypothesis; MT − MA = 0. Compared with a less parsimonious MA, a non-significant CDT would lead to acceptance of the

more parsimonious MT. Table 5 reports a significant change in chi-square between our model and the other models. In each case, the CDT presents a p < 0.01 which permits the conclusion to be drawn that the fit of the alternative model is significantly worse than that of the original model. In terms of our hypotheses (Table 6), the findings for H1 (market orientation → organizational learning) suggests that intelligence generation (γ11 = 0.48, p < 0.01) and intelligence dissemination (γ42 = 0.22, p < 0.01) have a positive and significant effect on the knowledge creation process in the organization. However, no significant effect has been found for responsiveness (γ13 = 0.07, non-significant). Furthermore, we have found indirect effects of intelligence generation (κ11 = 0.34, κ21 = 0.39, κ31 = 0.40, κ41 = 0.23, p < 0.01) and intelligence dissemination (κ12 = 0.16, κ22 = 0.18, κ32 = 0.19, κ42 = 0.11, p < 0.01) over each organizational learning phase. Globally, these findings support the thesis presented in the literature that the acquisition of information about markets contributes to the generation of new organizational knowledge.

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Secondly, the relationship between organizational learning and performance is supported in H3 (organizational learning → performance; β94 = 0.70, p < 0.01). It can be observed that those companies which foster organizational learning improve their competitive position and efficiency. So organizational learning has a direct impact on performance. Finally, there is not enough evidence to accept H2 (market orientation → performance). In this case, we have not found a significant and direct effect of intelligence generation (γ61 = 0.07, non-significant), intelligence dissemination (γ62 = −0.15, nonsignificant) or responsiveness (γ63 = −0.03, non-significant). However, the test of the link between market orientation and performance is taken in the context of testing the link between organizational learning and performance. It might well be that market orientation has an effect on performance that is masked due to the fact that both links are estimated simultaneously. Although we have not found a direct effect on performance, results show an indirect effect of both intelligence generation (κ61 = 0.34, p < 0.01) and intelligence dissemination (κ62 = 0.15, p < 0.05) on performance. These results show that market orientation has a positive influence on performance through organizational learning. 7. Discussion The essential purpose of this study was to test empirically some of the hypotheses derived from the review of the relationship between market orientation and organizational learning and their effect on organizational performance. In this section, we discuss the study results. The first contribution of this research is to extend the debate about the existing models which relate market orientation, organizational learning and performance. As we have men-

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tioned, there is no agreement about the right model that reflects the interactions between these three constructs. Although many reasons have been proposed in support of each model, the main sources maintain that market orientation comes before organizational learning. In effect, although there are many important differences between them, both concepts cover the development of useful knowledge for organizations. This knowledge is a key element for the sustaining of companies that operate in the current turbulent environments, and consequently is a source of sustaining competitive advantage according to the resourcebased view. Thus, researchers have emphasized the importance of market orientation (Jaworski & Kohli, 1993; Narver & Slater, 1990) and learning orientation (Sinkula, 1994; Slater & Narver, 1995) in developing a competitive advantage (Day, 1994b). These assumptions have been incorporated into the model proposed in Fig. 1. In this case, market orientation is analyzed as a precedent construct over organizational learning, and both organizational learning and market orientation simultaneously affect organizational performance, contributing to the attainment of a competitive advantage for the firm. The second contribution is based on the results of the empirical tests of the model (see Fig. 2). In summary, we have uncovered three properties of the data that are worth highlighting. The first is that market orientation has a positive effect on organizational learning. As predicted, companies which strengthen their ability to acquire the information of customers and other agents and try to satisfy their needs are going to encourage the processes of acquiring external and internal knowledge, distributing and interpreting this knowledge and finally save it in organizational memory. However, not all the components of market orientation have the same effect in organizational learning. In fact, we have only found a direct relationship between intelligence generation and intelligence dissemination with organizational learning and

Fig. 2. The performance effect of organizational learning and market orientation.

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an indirect one with each phase of organizational learning. Conversely, no significant link has been found for responsiveness. This could be interpreted as that both intelligence generation and dissemination contribute to the process of acquiring, distributing and interpreting the new knowledge. Also, knowledge from customers or competitors needs to be saved in the organization for later use. On the other hand, responsiveness does not have a clear effect on organizational learning. Although companies could always learn and respond to the information generated and disseminated, responsiveness to customer needs and changing market conditions become more important for the success of firms and the introduction of new products and services. The findings from this study support the proposition by Slater and Naver (1995) that market orientation is the principal cultural foundation of The Learning Organization. The findings also support the proposition by Baker and Sinkula (1999b) that a market orientation provides a grounding for a learning orientation. Our results also support the findings of Farrell (2000) and contradict those of Santos-Vijande et al. (2005), and demonstrate that market orientation is an important element for the process of learning in organizations. Furthermore, our results support a positive relationship between organizational learning and its impacts (Bontis et al., 2002; Farrell, 2000; Tippins & Sohi, 2003). Specifically, the current results indicate that the ability of companies to create knowledge is founded on a fundamental capacity to achieve sustainable competitive advantages. Therefore, organizational performance must be consolidated through empowerment, learning cultures that allow salespeople the freedom and flexibility required to meet dynamic customer expectations and changing contingencies across selling situations. A learning culture (e.g. language, conversation and dialogue, leadership) that stimulates creativity and encourages cooperation among members of the organization or group in tailoring market offerings to individual customers is required. This accomplishes what authors such as Bell et al. (2002) express, when they refer to organizational learning as a basic tool to update knowledge. Consequently, market orientation could provide strong norms for learning from customers and competitors, but it must be complemented by entrepreneurship and appropriate organizational structures and processes for generate higher-order learning, and consequently generative learning (Slater & Narver, 1995). Thus, while market orientation is reflected in knowledge-producing behaviors, organizational learning is reflected in knowledge-questioning values (Baker & Sinkula, 1999b; Sinkula et al., 1997). The findings do not support the views of Kohli and Jaworski (1990) that there is a positive association between corporate performance and market orientation. However, we have found a significant indirect influence on performance via organizational learning. This effect is especially important for the generation of intelligence. These results support the suggestion of Hart and Diamantopoulos (1993), Greenley (1995), Baker and Sinkula, (1999a,b); Hult and Ketchen (2001), that the “linkage is not linear, but rather is embedded within a more complex web of relationships”. Despite of the benefits of being market-oriented companies, “creating a market orientation is only a start” (Slater & Narver, 1995). Indeed, market orientation may not inspire com-

panies to take enough risks if they only concentrate in their current markets and under-invest in emerging markets and/or competitors, fail to understand the latent needs of current and new customers (Slater & Narver, 1995) or underestimate the potential contributions of other learning sources that possess knowledge useful to the organization (Achrol, 1991; Dickson, 1992; Farrell, 2000). In fact, market-oriented success could breed resistance to learning when successful outcomes associated with past behavior and their interpretation prevail (Celuch et al., 2002). Dickson (1996) suggests that market orientation reflects the quantity of a firms’ market information processing activities and not its quality. Consequently, a “firm's market orientation cannot prevent the institutionalization of flawed information acquisition, interpretation and distribution activities that can stymie learning” (Baker & Sinkula, 2002). In other words, the ‘performance through market orientation’ process depends on the ability to acquire and disseminate knowledge from markets and especially to question all goals, procedures and assumptions in an adaptive and responsive way that is open to change. Only a generative learning can contribute to performance. This clearly demonstrates the preeminence of organizational learning over market orientation and is in agreement with much recent literature (Farrell, 2000; Slater & Narver, 1995). In conclusion, a “learning orientation is a more pervasive resource than market orientation because it has bearing on more than marketing-related activities in the firm” (Baker & Sinkula, 1999a), so the key implication of this research is that a strong learning orientation is more important to the firm than a strong market orientation (Baker & Sinkula, 1999a), because organizational learning has a direct effect on organizational performance, unlike market orientation. However, the results also indicate that a ‘learning culture’ is unlikely in an organizational basis without being fostered by a ‘market orientation’. 8. Managerial implications Managing and controlling market orientation and organizational learning both provide a number of important insights for managers. Both reveal the importance and application of customer knowledge. Knowledge derived from customers, suppliers, competitors or personnel is critical to their targets. Specifically, the development and usage of organizational learning and market orientation motivate personnel to direct their activities and processes in a coordinated manner in order to attain their goals. This is particularly crucial for those companies that try to focus on customers and satisfy their needs. The key managerial implications of this study emphasize three main issues. First, learning organizations are exceptional in their ability to anticipate and act on opportunities in turbulent and fragmenting markets (Slater & Narver, 1995). Consequently, learning is preeminent over other resources because only learning enables firms to maintain long-term competitive advantage by continuously improving market information processing activities at a faster rate than rivals (Dickson, 1996). Moreover, organizational learning, through the establishment of organizational routines that encourage the knowledge creating process, allows a company to offer new products, and to improve their competitive

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position. These conclusions should encourage managers to design their organizations with shared organizational vision and open-minded approaches to problem solving, organizational culture and strategy that foster learning, teamwork and other human resource management practices which encourages the creation of new knowledge (see e.g. Fiol & Lyles, 1985; Harvey & Denton, 1999; McGill et al., 1992; Senge, 1990). This configuration allows the development of new knowledge through acquisition, distribution, interpretation and organizational memory. These four phases constitute a single process (Day, 1994b; Dodgson, 1993; Huber, 1991; McGill et al., 1992). As Huber (1991) asserts, “the division of organizational learning into phases is more pedagogic than structural”. That is to say, the variables are neither independent nor autonomous, but they are continually interacting. Consequently, companies that intend fostering the organizational learning process could inhibit this process if they do not foster all of these phases. Furthermore, not only the acquisition of knowledge is determinant, but the company has to have up-to-date databases and processes for unlearning useless knowledge. Second, with the aim of fostering each organizational learning phase, market-oriented companies could foster both intelligence generation and dissemination. This mean that managers should invest in market research, analyze the effects of shifts in the business environment or be in contact with customers to know what they think about their products. On the other hand, the communication of this information all around the organization will encourage all the employees to be conscious of the requirements of customers and the challenges in the market. In any case, the promotion of these activities will foster organizational learning through each phase. Besides, both intelligence generation and dissemination will have an influence on performance mediated by the process of organizational learning. Consequently, firms must focus their attention upon stimulating those activities that foster the external acquisition of knowledge and also upon the generation of internal knowledge, the distribution and interpretation of this knowledge and, finally, the promotion of the organizational memory. In addition managers must respond to the markets with this knowledge. This is in agreement with the work of authors such as Aggarwal and Singh (2004), who state that all departments, not just marketing, should participate in responding to market trends in a market-oriented company. As a result there is a need to coordinate a company's responsiveness with other departments of the firm. The goal of organizational learning will be that all members of the organization are conscious of the location of useful knowledge. Organizational learning can also provide support for action by retaining a broader range of potential responses, thus providing more options for organizational decision makers when they respond to changes in the organizational environment. As a result, organizational learning develops a set of competences and organizational routines that, while generating a real value for external and internal stakeholders, can lay the foundation for effective improvement in performance. Finally, results also indicate that market orientation is a necessity but not a sufficient condition for the maintenance of competitive advantage. It seems that market orientation is not enough for organizations to learn. The ability of an organization

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to learn faster than competitors may be the only source of sustainable competitive advantage (Day, 1994b). The important managerial implications of this proposition are that market orientation may help companies to direct their efforts to attain a competitive advantage using the available information (Baker & Sinkula, 1999b) and can help companies in a first stage, but the competitive environment obliges companies to attain a more comprehensive vision (e.g. Slater & Narver, 1995) than a simple preoccupation among employees to respond to customers' needs. Thus, rather than focusing only on customers and competitors, companies should foster the knowledge creating process both inside and outside the organization. For example, organizational learning provides salespeople with new knowledge which supplies the freedom and flexibility required to meet dynamic customer expectations and the changing contingencies across selling situations. This new knowledge, externally or internally generated, could be converted into new products or services, or may help to reduce the production costs. In any case, failure in the identification, measurement and evaluation of the worth of organizational learning leads to decisions that may not attain competitive advantage. Also, practitioners emphasize the role of network relations, in particular relationships with suppliers, as an important organizational learning factor. In practice, organizational personnel cannot always have all the relevant knowledge to resolve problems and therefore need to contact someone in the network. In this case, organizational learning can be understood as any organizational system and process supporting a knowledge base that can give managers easy access to information that would otherwise require contact with a seller's staff. Consequently, organizations should aim to become learning oriented if they are to compete successfully in the long-run (Slater & Narver, 1995), because organizational learning may be the only source of sustainable competitive advantage (DeGeus, 1988; Dickson, 1992; Slater & Narver, 1995). 9. Limitations and the direction for future research The study is not without limitations. Firstly, only subjective information from the questionnaire for measuring company results was taken into account, thereby limiting this study. Although this kind of information is commonly used in studies, the introduction of other measures from objective sources in order to replicate these results would be interesting. Moreover, other factors which have not being included in this study are also likely to affect organizational learning and market orientation. Taking into account these limitations, this study points to the need to explore new avenues of research. Firstly, we consider that the use of additional information about performance might help to capture the richness of this construct, and would require the combination of information coming from the interviews and other data bases. Secondly, it would also be interesting to extend the survey to other countries since national culture issues might influence the way organizations learn. Finally, another possible research direction could examine the intermediate role of innovation in the relationships between organizational learning, market orientation and organizational performance (e.g. Hult & Ketchen, 2001; Weerawardenaa & O'Cassb, 2004). In this case,

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Yahya, S., & Goh, W. -K. (2002). Managing human resources toward achieving knowledge management. Journal of Knowledge Management, 6(5), 457−468. Daniel Jiménez-Jiménez is Assistant Professor of Management at the University of Murcia. He received his Ph.D. in Management and M.A. in Human Resource Management from the same institution. His current research focus in the relationships among HRM, Innovation, Organizational Learning and Marketing Orientation. He has had recent publications in the International Journal of Manpower. Juan Gabriel Cegarra-Navarro is Assistant Professor of Business Management in the Polytechnic University of Cartagena. His investigation line is focused in Knowledge Management and Marketing Orientation.