Making universities relevant: market orientation as a dynamic capability within institutions of higher learning.

Ma, Jun ; Todorovic, Zelimir

INTRODUCTION

Today's universities are facing significant budget constraints due to economic downturns as well as political and funding trends. Private universities experience reduced donations and returns on investment, while public universities receive less financial resources from governments and other funding sources. Faced with these challenges, many universities reduced the scholarships for newly enrolled students, postponed university building renovations, minimized hiring, and reduced or eliminated salary increases.

Recognizing that these steps represent only a short term solution, many universities focus on promoting programs or actions that can generate long-term revenue for their institutions. Consequently, some universities entered the global market and recruited higher numbers of international students, especially from China and India (Iling, 1996). Other universities focused on bridging gaps between universities and the industry, toward greater facilitation of the technology transfer process. Finally, other universities created different programs to meet specific community needs, such as entrepreneurship programs, leadership certificate programs, and healthcare management programs. To survive the competitive pressures and economic downturns, universities continue to react to political, economic, technological, and other environmental changes.

To deal with the new environmental uncertainty, a university needs a culture that is relevant and responsive to the external environment. Culture, as defined by Todorovic (2004) is a set of complex routines which configure internal organizational resources into capabilities and competencies. Market orientation represents one set of dynamic complex routines, in itself a dynamic capability, which in the private sector is closely correlated to organizational performance (Day, 1994a; Hurley & Hult, 1998; Jaworski, Stathakopoulos, & Krishnan, 1993; Kohli & Jaworski, 1990; Menguc & Auh, 2006; Narver & Slater, 1990; Slater & Narver, 1994b, 1995, 2000). Kotler and Fox (1985) also documented the importance of strategic marketing (also referred to as an orientation) in higher education more than two decades ago. Therefore, a market-oriented university culture should help enable universities to facilitate and manage the change process. We therefore posit that Market orientation does and will increasingly continue to play a significant role in increasing universities' performance--in an increasingly competitive environment.

Although the effect of market orientation on firms' performance has been widely recognized, few studies explore the relationship between market orientation and university performance. This study attempts to fill the gap by first examining the structure of market orientation within the university context. Next, we examine what constitutes MO within the university environment, and how MO is related to university performance (Homburg, Krohmer, & Workman Jr, 2004). To this end, our paper proceeds as follows. First, we review and discuss relevant literature constructs. Then, we discuss the methodology employed in this study and present our findings. We conclude with a discussion of findings, including the overarching role of market orientation, as well as the unique function played by each dimension, in terms of its impact on university performance.

DYNAMIC CAPABILITIES APPROACH

Dynamic capabilities approach is part of the overarching Resource Based View (RBV) paradigm. While RBV considers the competitive advantage gained based on the heterogeneity of firm resources, dynamic capability approach examines the management of those capabilities (Eisenhardt & Martin, 2000). The dynamic capability approach was originally developed as a response to the recognition that the application of the RBV to firms in an environment of rapid technological change is problematic. According to this approach, changes in the external environment are accompanied by a heightened emphasis on "invisible" assets (Arthurs & Busenitz, 2006; Ho & Tsai, 2006; Itami & Roehl, 1987; Lavie, 2006). As the speed of technological expansion increases, firms start to rely more heavily on their internally developed advantages (Kessler & Chakrabarti, 1996; Teece, Pisano, & Shuen, 1997). Learned et al. (1969), quoted in Teece et al. (1997), proposed that the real key to a company's success lies in its ability to find or create a competence that is truly distinctive. This notion is in contrast to the RBV framework, which focuses on the rents accruing to the owners of scarce firm-specific resources (Teece et al., 1997). According to Teece et al. (1997), "the dynamic capabilities framework analyses the sources and methods of wealth creation and capture by private enterprise firms operating in environments of rapid change" (p. 509).

Also seen as best practices, dynamic capabilities have been defined as a set of "specific strategic and organizational processes," by Eisenhardt and Martin (2000, p. 1106). As the dynamic capability patterns vary with market dynamism, this theory is useful for studying firms that operate within dynamic environments (Eisenhardt & Martin, 2000). Dynamic capabilities are seen as the "antecedent organizational and strategic routines by which managers alter their resource base to generate new value-creating strategies" (Eisenhardt & Martin, 2000, p. 1107). Eisenhardt and Martin (2000) further define these capabilities as "the firm's processes that use resources--specifically the processes to integrate, reconfigure, gain and release resources--to match and even create market change" (p. 1107). Branzei and Vertinsky (2006) linked dynamic capabilities to life-cycle stages, providing greater understanding of the timing and extent of expected returns. Dynamic capabilities thus are the organizational and strategic routines by which firms achieve new resource configurations as markets emerge, collide, split, evolve, and die.

Winter (2003) cautions that dynamic capabilities have costs associated with their implementation and development. Winter (2003) finds it is "not necessarily advantageous for a firm to invest in (first-order) dynamic capabilities" (p. 993). Rather, a long term managerial focus on the development of dynamic capabilities is more likely to yield the desired results (Kor & Mahoney, 2005). For such an investment to be beneficial, the long-term benefits of dynamic capabilities must exceed the cost of implementation (Winter, 2003). Winter (2003) defines "first order dynamic capability" (p. 992) as a capability used to directly modify an operational capability, such as a new product development.

Recognizing that dynamic capabilities are often associated with an organization's management, Adner and Helfat (2003) propose the concept of dynamic managerial capabilities, the capabilities with which managers build, integrate, and reconfigure organizational resources and competencies. Rooted in three underlying factors (managerial human capital, managerial social capital, and managerial cognition), dynamic managerial capability influences the strategic and operational decisions of managers, thus providing a potential competitive advantage for the organization (Adner & Helfat, 2003).

MARKET ORIENTATION AS MANIFESTATION OF DYNAMIC CAPABILITY

The concept of market orientation (MO) was first introduced by Narver and Slater (1990) and Kohli and Jaworski (1990) from two different perspectives: behavioral perspective and cultural perspective. Kohli and Jaworski (1990) described market orientation from behavioral perspective and identified manifestation of market orientation of an organization. They suggested that market orientation is exhibited in the generation and dissemination of market intelligence, and the response to such intelligence. Narver and Slater (1990) viewed market orientation from a cultural perspective as "the organizational culture ... that most effectively and efficiently creates the necessary behaviors for the creation of superior value for buyers and thus, continuous superior performance for the business" (p. 21). Since then, there has been a growing body of research exploring the construct of market orientation and its impact on business performance (Day, 1994b; Hurley & Hult, 1998; Jaworski & Kohli, 1993; Kohli & Jaworski, 1990; Narver & Slater, 1990; Slater & Narver, 1994b, 1995, 2000).

Although the two seminal articles published in 1990 examined market orientation from different perspectives, there are underlining connections between the two perspectives. In other words, the three dimensions of MO identified by Naver and Slater (1990) are connected to the three types of behaviors, described by Kohli and Jaworski (1990). Naver and Slater (1990) argued that MO contains three dimensions: customer orientation, competitor orientation, and inter-funcational coordination. On the other hand, Kohli and Jaworski (1990) argued that market intelligence includes "a broader concept than customers' verbalized needs and preferences in that it includes an analysis of exogenous factors that influence those needs and preferences" (p. 4). These exogenous factors include government regulations, competition, technology, and environmental factors, which influence the needs and preferences of their customers. From the definition of market intelligence, we can see that it is related to customer orientation and competitor orientation defined by Narver and Slater (1990). In addition, the generation, dissemination, and the reaction responding to market intelligence requires inter-functional coordination within the organization.

Essentially, MO describes a culture that helps to nurture dynamic capability which enables the firms to react to the changing external environment. Consequently, MO has a positive relationship with firms' financial performance which is evidenced by later studies (Deshpande & Farley, 1998; Matsuno & Mentzer, 2000; Slater & Narver, 2000). In addition, MO also has an impact on other performance. For example, Hult and Ketchen (2001) found that market orientated companies are more innovative and have a higher ability to create and implement new ideas, products, and processes. Increased innovation, in turn, is related to firms' ability to bring in new products and services (Im & Workman Jr, 2004). Market orientation also enhances customer's perception of quality of products and services provided, thereby creating and maintaining superior customer value (Brady & Cronin, 2001) and increasing customer satisfaction and loyalty (Slater & Narver, 1994b).

The relationship between MO and firms' performance is dynamic one, moderated by factors such as market turbulence, technological turbulence, competitive intensity (Slater & Narver, 1994a), economic ideology, and industry type (Sin, Tse, Yau, Chow, & Lee, 2005), culture and profit/non profit (Rodriguez Cano, Carrillat, & Jaramillo, 2004).

MARKET ORIENTATION IN PUBLIC SECTOR: FOCUSING ON UNIVERSITIES

A plethora of studies show evidence of the positive relationship between MO and firm performance in private sector. However, the role of MO in organizations' performance in the public sector received little attention.

Few studies examine the effect of market orientation on organizational performance in not-for-profit organizations such as hospitals (Bhuian & Abdul-Gader, 1997; Lonial, Tarim, Tatoglu, Zaim, & Zaim, 2008; Raju, Lonial, & Gupta, 1995; Wood, Bhuian, & Kiecker, 2000), local government (Cervera, Molla, & Sanchez, 2001) and universities (Caruana & Ramaseshan, 1999; Caruana, Ramaseshan, & Ewing, 1998b; Hammond, Webster, & Harmon, 2006; Webster, Hammond, & Harmon, 2006).

Since this study focuses on universities, we review past research on this topic below. Caruana et al. (1998a, 1998b) surveyed 184 heads of schools or departments in both business and other disciplines in Australia and New Zealand. Using the MARKOR scale (Kohli and Jawoski, 1993) and overall assessment performance measures they developed, they found a positive relationship between universities' market orientated behavior and performance. Building on Narver and Slater's (1990) work, Hammond, Webster, and Harmon (2006) and Webster, Hammond, and Harmon (2006) examined whether the market orientation scale can be reworded to fit the universities context. They also examined the relationship between market orientation and performance measured by the overall subjective performance and enrollment change. Their studies showed that reworded market orientation scales had adequate reliability and validity. They also found that the relationship between the three dimensions of marketing orientation and overall market orientation were positively correlated with business school performance (measured by student enrollment).

Although the above studies are crucial to promoting greater understanding of the topic, they also present some challenges. First, studies by the two groups of authors did not capture the multifaceted nature of university performance. Because universities carry different roles in our society, present measures of performance are rather subjective. Therefore, there is a need to develop a scale that will specifically measure multifaceted university performance. Second, the previous studies adopted measures from the literature but never examined the underlying dimensions of market orientation. Although MO is well defined in the private sector, we observe that the university structure is different from private sector and other not-for-profit organizations (Todorovic, McNaughton, & Guild, 2005). In other words, the same elements of market-oriented behaviors expressed by three dimensions of MO in the private sector may evidence themselves in behaviors unique to universities, which try to satisfy multi-pronged mission objectives. Consistent with the observations made by Todorovic (2004) who noted that entrepreneurial orientation evidenced itself with different dimensions within universities, it is posited that market orientation of universities is evidenced with different constructs than is the case in the for-profit world. To this end, we propose to answer the following three questions: 1) What is the underlying structure of market orientation of university departments? Is the structure of market orientation of university departments the same as market orientation of companies? 2) How to measure university performance? 3) What is the relationship between market orientation of university departments and university performance?

METHODOLOGY

Sample and Data Collection

We employed online surveys to collect data from university department chairs from computer science, engineering, and health science departments within the United States. These departments were selected because they are more likely to engage in research activities, teaching, and outreach to communities (Todorovic 2004). In addition, these three departments were selected because they are usually the most entrepreneurial and market oriented departments within the university (AUTM, 2003). A total of 3072 department chairs were identified, 1531 of them from health science departments, 1113 of them from engineering departments, and 428 of them from computer science departments. One week after we sent the link to the 3072 department chairs, we followed up with phone call. Two weeks after the initial e-mails, a second wave of e-mails was sent to those who had not yet responded to the survey. The second wave of e-mails was followed up with another set of phone calls approximately a week later.

We received 688 responses, which represents a response rate of 22.4%. The breakdown of responses by discipline shows health science with 355 responses; engineering with 242 responses; and computer science with 91 responses. Each respondent was asked to put a predetermined code before entering the survey for identification purposes.

Measures

Market orientation.

Recognizing that market orientation is a part of the organizational culture within universities, we adapted the market orientation scale by Naver and Slater (1990). After being modified for the university context, the measures were sent to 30 department chairs and administrators in a university in northeast Indiana for pretesting. Using the feedback from the pretest, we further modified some of the items and eliminated two items from the instrument. The item "We give close attention to after-sales services" was determined to be inappropriate, as there is no clear understanding about what constitutes the after-sales services in the university context. In addition, we deleted "sharing customer information" because our pre-test results show that it is very rare for the departments within the university to share student information to different departments. This is also compounded by the fact that students' information is considered confidential. The final set of questions representing the marketing orientation within university culture is listed in Table 1.

Performance of University Departments.

We borrowed the university performance measure from Todorovic's (2004) study. The measures are well established and tested within Canadian universities. Todorovic (2004) developed these items as he observed that patents and licensing are not appropriate performance measures of entrepreneurship within most university environments (Todorovic et al., 2005). Developed items, therefore, represent a more appropriate measurement of the constructs sought in this study, as the same incorporate multifaceted aspects of performance of different activities.

Construct Reliability

Table 1 shows the Cronbach's alpha coefficients of the three components of marketing orientation and performance.

RESULTS

Structure of Market Orientation for Universities

Since this study explores waters not frequently charted by researchers, exploratory factor analysis was undertaken to confirm that MO remains a three dimensional latent construct in this environment (Narver & Slater, 1990). Although the original work by Narver & Slater (1990) presented MO as a three factor latent variable, the exploratory factor solution for MO within university environment strongly supports a two (rather than three) factor solution. Items measuring customer orientation and inter-functional coordination (with the exception of one item) were highly loaded on the first factor. The three items for competitor orientation, however, loaded significantly on the second factor.

The results from the exploratory factor analysis suggest that the construct structure of market orientation within universities is different than in the private sector. Based on these results, we posit that market orientation of university departments contains only two dimensions, and thereby strongly affects university's ability to be aligned to the market conditions of the external environment (discussed in greater depth in the next section).

We also utilized the results of the exploratory factor analysis to examine the relationship between market orientation and performance. Using the naming convention suggested by Hair et al. (1998), we labeled the first factor as internal capacity and the second factor as competitor orientation. Table 2 shows the results of the exploratory factor analysis.

To assess the overall correlation matrix significance, Barlett's Test of Sphericity was employed. Although Barlett's Test of Sphericity tests the presence of non-zero correlations, it does not test the pattern for those correlations. For this purpose the Kaiser-Meyer-Olkin Measure of Sampling Adequacy was used. To ensure that the data is suitable, the measure of sampling adequacy (MSA) should be 0.50 or higher (Hair, Anderson, Tatham, & Black, 1998). The KMO of Sampling Adequacy is .868, which exceeds the threshold of 0.50. Chi-Square of Bartlett's Test of Sphericity is 3293, with 78 degree of freedom (p<.001).

The Relationship between Market Orientation and University Department Performance

Regression analysis was employed to examine the impact of the two derived factors on university department performance. The results from the regression analysis are shown in Table 3. The model fit the data well (p<.01). The coefficients for the two factors are significant ([[beta].sub.capacity]=.103, p=.009; [[beta].sub.competitor]=.243, p<.001) indicating that the two derived factors of market orientation contribute significantly to university department performance.

We also assessed the relationship using structure equation modeling approach. The data was derived through EQS. The model we tested and the results are shown in Figure 1.

The results from the structural equation modeling approach show that the model fit the data well and the two dimensions of market orientation have a significant impact on university department performance.

[FIGURE 1 OMITTED]

DISCUSSION AND CONCLUSIONS

In this study, we focused on understanding the role and the potential of MO within universities. To this end, we explored the relationship between market orientation and performance. We first investigated whether the market orientation of university department has the same structure as is found in private sector. Although MO is very well established in the private sector, our results (using exploratory factor analysis) do not show the three factor solution as was originally expected. More significantly, we observe that, within the university environment, the two core dimensions of market orientation (customer orientation and inter-functional coordination) merged into a single construct. This may be due to the difficulty in determining the university "customer," considering the multi-prong mission of the university. In addition, the dimensional characteristics of MO and, for that reason, of other strategic orientations may be industry specific. One can conclude that, aligned with the arguments presented by Todorovic (2004), strategic orientations may function or manifest themselves with different dimensional characteristics in not-for-profit or government sectors and yet still remain useful organizational constructs, fulfilling their strategic purpose.

Our study results pose a significant surprise, in that customer orientation and inter-functional coordination loaded on the same axis. Upon further reflection, we note that this provides a significant insight for this study. Although most organizations also have internal customers, MO definition of a customer focuses on an external entity. We also observe that MO is a dynamic capability, and as such, is involved in reconfiguration of existing and development of newly acquired capabilities and competencies (Menguc & Auh, 2006). Observing that MO aligns organizational resources with the external market conditions, it follows that in today's highly dynamic environment, universities must make sure they are aligned with the external environment. Further, we note that students were identified as university customers by our subject population. Our study results provide convincing evidence that universities, which see students as customers, are internally orientated, as most students also represent internal stakeholders. This conclusion is derived from the observation that the MO dimensions, customer orientation and inter-functional coordination, loaded on the same factor. This only leaves the competitor orientation as a separate external factor. Although the effectiveness of this factor in terms of keeping the university relevant to external environment is a concern, we also observe that this is a usual practice amongst US universities. Figure 2 is a graphical presentation of the significance of our findings, where customer orientation is positioned internally rather than externally. Since most universities have similar practices, competitor orientation is positioned on both sides of the internal-external threshold.

This observation points to the need for MO to configure university resources in alignment with the external environment, which is not the case in most universities. Reflecting upon past criticisms of universities not being relevant to their communities (Bercovitz & Feldman, 2008; Duderstadt, 2000, 2001), we now conclude that MO is a necessary, but mostly absent, ingredient of that readiness.

There is also a second inference gained from this observation. It appears that students, which are internal stakeholders of university, should not be used as a customer reference. Consequently, using the discussion of marketing intelligence as a base, we conclude that universities need to be aware of government, environmental and technological changes in their surroundings (Jaworski & Kohli, 1993; Kohli & Jaworski, 1990; Slater & Narver, 1994a). This, in turn, supports the notion that every university may be dealing with a slightly different set of external customers or stakeholders.

In conclusion, this study suggests that universities stand to benefit significantly from the acquisition of department level MO. Market orientation is likely to provide a much needed external alignment for university related capabilities and resources. This, in turn, will satisfy the growing number of critics who are concerned about the perceived lack of relevance of universities in dynamic global environment.

This study also has managerial implications, especially for university administrators. The results can help university administrators understand how to build competitive advantage to compete in the extensive competitive environment. First, universities may need to better define their customer, and indeed, examine whether it is only the student body. Likewise, this study does not indicate that there is no significant interdepartmental coordination (IC), but rather suggests that most of the interdepartmental coordination may be related to students. This in fact may be highlighting a potential weakness--universities may need to develop structures that allow more diverse IC within their institutions. Again, we have the promise of greater university performance, evidenced by strong correlation between MO and university.

[FIGURE 2 OMITTED]

Implications of this study may also extend to other situations in the private sector, such as departmental units with no clear indication of who their customer is. In such cases the customer may be another internal entity rather than an external entity. In such situations, the theoretical implications of the two dimensions accumulating in a single factor may be significant.

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Jun Ma, Indiana University-Purdue University Fort Wayne

Zelimir Todorovic, University-Purdue University Fort Wayne

Table 1: Construct Reliability

Construct                                  Item-to-Total   Cronbach's
                                            Correlation      Alpha

Customer Orientation                                          .752
  We closely monitor and assess our            .811
  commitment to serving student's needs.

  Our strategies are driven by the goal        .776
  of enhancing student learning
  experience.

  Our competitive advantage is based on        .770
  our understanding of students needs.

  Our department objectives are driven         .574
  solely by student interest.

  We measure student satisfaction              .686
  systematically and frequently.

Competitor Orientation                                        .652
  Our department stays informed about          .695
  the action of peer departments of
  other universities.

  We respond rapidly to actions of             .785
  competitive universities.

  Our administration regularly discusses       .726
  our strengths and weaknesses compared
  to other universities.

  Students are our primary emphasis when       .600
  we have, or can develop, an
  opportunity for competitive advantage.

Inter-functional Coordination                                 .714
  Meeting with students is the highest         .770
  priority of our faculty.

  All of our departments are highly            .827
  dedicated to serving the needs of
  students.

  Our entire university contributes to         .705
  student learning experience.

  We share resources with other                .635
  departments.

Performance                                                   .791
  We are recognized by industry and/or         .748
  society for our flexibility and
  innovativeness.

  Our department is highly regarded by         .749
  industry.

  Many of our faculty members conduct          .775
  research in partnership with
  non-academic professionals.

  We have spun-off a high number of            .623
  ventures.

  Our graduate students often secure           .714
  high quality industry positions.

  Faculty members in our department            .630
  emphasize applied research.

Table 2: Factor Analysis With Oblique Rotation

Items of Market Orientation                          Factor

                                             F1        F2        F3

Our strategies are driven by the goal of    .797
enhancing student learning experience.

Meeting with students is the highest        .770
priority of our faculty.

All of our departments are highly           .744
dedicated to serving the needs of
students.

We closely monitor and assess our           .731
commitment to serving student's needs.

Students are our primary emphasis when      .728
we have, or can develop, an opportunity
for competitive advantage.

Our entire university contributes to        .681
student learning experience.

Our competitive advantage is based on       .670
our understanding of students needs.

We measure student satisfaction             .606
systematically and frequently.

We share resources with other               .435
departments.

Our administration regularly discusses                .865
our strengths and weaknesses compared to
other universities.

We respond rapidly to actions of                      .792
competitive universities.

Our department stays informed about the               .643
action of peer departments of other
universities.

Our department objectives are driven                            .916
solely by student interest.

Percentage variance explained              37.938    11.326    8.480

Table 3: Regression Analysis

 Independent Variable     Coefficient    p-value

Internal capacity             .123         .009
Competitor Orientation        .257        <.001
F Statistics                 33.038
p-value                      <.001
R-square                     0.088