2013 Cambridge Business & Economics Conference ISBN : 9780974211428
RELATIONSHIP MARKETING FACTORS AS KEY PREDICTORS OF INTERFIRM COOPERATION AND SUCCESS
Veronica Rosendo-Ríos, Colegio Universitario de Estudios Financieros (CUNEF). +34645638886. email@example.com
Relationship Marketing Factors as Key Predictors of Interfirm Cooperation and Success
Verónica Rosendo-Ríos, firstname.lastname@example.org, Colegio Universitario de Estudios Financieros (CUNEF)
This study aims to provide a picture of how trust, integration and commitment can have a positive influence on inter-firm cooperation and success. The research was conducted in a business-to-business setting between private and public sector institutions, namely university-industry relationships. The survey was targeted to private Spanish enterprises that were engaged in research and development projects of collaboration with a major Spanish Public University in Madrid. Online survey was chosen for data collection. The total number of usable questionnaires was 183. Factor analysis using principal components was performed in order to validate the different constructs used in this study. Hypotheses were tested by means of correlations and linear regressions. The results show that the key predictors for inter-organizational cooperation and success are mainly integration, commitment, and, to a lesser extent, trust. Satisfaction also appears as a crucial factor for customer retention, therefore enhancing university-industry relationship success.
Relationship Marketing, University-Industry Links, Satisfaction, Intention to Renew.
Factors such as globalization (Gummesson, 2002), or the rapid technological change (Palmer, 2002) have forced organizations to establish long-term relationships with other actors in the marketplace in order to get sustainable competitive advantages, and thereby to survive in today´s marketplace. University-Industry linkages constitute a good example of these relationships. However, while the business-to-business stream of Relationship Marketing literature tends to focus primarily on the private sector, little attention has been paid so far to inter-organizational collaborations between private and public institutions from this research field (Plewa & Quester, 2007). Hence, a closer look at these collaborations is taken in this study, more specifically at University and Industry relationships.
Firms are now pressurized to speed the process of innovation through the creation and development of new products and technologies (Santoro & Chakrabarti, 2002). For its attainment, they are currently looking for new ways of outsourcing R&D activities. On the other hand, universities are also on the lookout for additional financial resources, due to factors such as the decrease in government funds, the fact that the potential funding from students fee is limited, and the increase of competition regarding research support (Rosendo, 2010). In view of these challenges, the commercialization of knowledge has grown rapidly over the last few years. According to RedOtri (2008) - a public Spanish national report on R&D- the investment gained in Spain by R&D activities with organizations and other institutions amounted to 617 million Euros in 2007. The larger increase was reported to be achieved on research activities with third parties that involved financial support for the Spanish university. Notwithstanding the relevance of these collaborations, there has been a large number of failures in technology transfer attempts between these two institutions (Lee, 2000; Cyert & Goodman, 1997), and researches carried out in this context from a relational approach have been very limited. Few notable exceptions include the studies reported by Plewa & Quester (2007, 2008) and Plewa (2009).
Therefore, the purpose of this paper is to contribute to the understanding of University-Industry success by examining the effect that certain relational variables, namely trust, integration and commitment can have on some outcome measures, more specifically, satisfaction and customer retention - measured in terms of the firm´s intention to renew the relationship of collaboration with the university. Hence, information generated from this research should provide managers with a greater insight into the successful process of University-Industry relationship creation and development, as well as a guideline on more effective governance.
The remainder of the article is structured as follows. First, some hypotheses are stated. After a description of the methodology followed in this research, the procedures used to test the hypotheses are explained. Namely, factor analysis is carried out in order to validate the different constructs under study. Following the resultant factor scores, the hypotheses are empirically tested using correlations and linear regressions. The findings of the study are then presented. The paper concludes with a summary of the study´s research contributions and directions for further research in this context.
CONCEPTUAL BACKGROUND AND HYPOTHESES DEVELOPMENT
Trust has been traditionally considered in the literature of Relationship Marketing as a cornerstone to facilitate and maintain long-term relationships (Doney & Cannon, 1997; Berry, 1995; Morgan & Hunt, 1994; Moorman et al., 1993; Dwyer et al., 1987). This relevance is reflected in the increasing number of empirical studies that have corroborated the positive influence that trust has on a large number of variables, such as future intentions or satisfaction (Garbarino & Johnson, 1999), thus becoming a key strategic factor for business management (Spekman, 1988). Regarding its conceptual definition, there have commonly been two general approaches to trust in the literature (Moorman et al., 1993). Trust as a cognitive belief or expectation based on the counterparty´s reliability or expertise (Doney & Canon, 1997; Dwyer & Oh, 1987), and trust as a behavioral intention that involves vulnerability and uncertainty on the part of the trustor (Morgan & Hunt, 1994). Following Moorman et al., (1992), for the purpose of this research, business firm´s trust in the university is defined as “a willingness to rely on an exchange partner in whom one has confidence”. In relation to its dimensionality, the dimensions to be used in this research to assess the level of a firm´s trust in the university partner follow Ganesan´s (1994) approach and include two facets, namely credibility and benevolence, since this multidimensionality allows a more comprehensive understanding of the differential effects of trust in a relationship (Singh & Sirdeshmuk, 2000). Turning to the specific context of University-Industry collaborations, trust among partners is important for many reasons (Barnes et al., 2002). Due to their research nature, these organizational linkages have often been characterized by structural market failures, such as excessive secrecy, high uncertainty, or the use of an opportunistic behavior of the research outcomes by one of the counterparties. Moreover, firms are faced with the resultant knowledge derived from the collaborative research projects that they have carried out together with the university. However, as posited by Moorman et al., (1993), it is possible that the ultimate firm users are unable to assess the quality of the research services, or even to interpret the research findings. Additionally, the information and knowledge that both parties have to share is confidential, since this information is crucial for the strategic decisions that firms may face in the near future. Therefore, firms become vulnerable and have to rely on the university researchers´ good will. Notwithstanding the relevance of this variable, the number of empirical studies that have applied this relational factor in this specific context is surprisingly very limited. Hence, the following hypothesis is proposed:
Hypothesis 1: Trust is positively related to satisfaction in University-Industry Links.
As well as trust, commitment has been proposed in Relationship Marketing literature as one of the main factors in order to foster long-term relationships (Morgan & Hunt, 1994). This is reflected in the fact that committed partners are more likely to share resources, and invest time, and effort to reinforce their relationship (Anderson & Weitz, 1992). In this respect, trust without commitment to share the appropriate resources would turn into a poor relationship that could not eventually be maintained in the long-term (Gounaris, 2005). Hence, although there is no agreed consensus on which one of the two factors is the antecedent of the other (Morgan & Hunt, 1994), it is practically unquestionable that both factors have a high impact on the effective development of a relationship. Setting the limits of these general approaches, and despite the many conceptualizations of commitment available in the literature, this study follows the definition of commitment proposed by Anderson & Weitz (1992), as ´a desire to maintain a stable relationship, a willingness to make short-term sacrifices to maintain the relationship, and a confidence in the stability of the relationship´, since this conceptualization does not only include the behavioral and attitudinal components of commitment, but also its long-term orientation and stability, and hence, is deemed more appropriate for the study of University-Industry relationships. Therefore, based on the previous discussion of trust and commitment as basic components of long-term relationships, the following hypotheses are established:
Hypothesis 2: Commitment is positively related to satisfaction in University-Industry Links.
Hypothesis 3: Trust is positively related to Commitment in University-Industry Links.
From a general approach, strategic collaboration and integration between organizations starts when the relationship exchange acquires relevance, that is, when for both relational parties the establishment of a relationship is a fundamental characteristic rather than a secondary one (Anderson et al., 1994). According to Kahn (1996), integration is composed of two main facets, namely collaboration and communication. Following Kahn and Mentzer (1996), communication by itself does not guarantee the success of a business relationship, since this factor is supposed to be linked with a specific transaction of information. This view is also shared by Bernasco et al. (1999), who stated that communication processes such as meetings, committees or telephone calls do certainly improve the level of interaction, but not necessarily the level of collaboration. On the contrary, relationships based on collaboration emphasize the relational continuity and the integration between the exchange members. According to Nevin (1995) relationship formation is based on the level of reciprocity between the parties involved. The reasons behind that reciprocity are mainly cooperation, collaboration and coordination between the exchange partners, as opposed to domination, power or control. This is in line with the postulates of Relationship Marketing. In fact, Parvatiyar and Sheth (1994), for example, view Relationship Marketing as an orientation "that seeks to develop close interactions with selected customers, suppliers and competitors for value creation through cooperative and collaborative efforts". Therefore, collaboration is suggested to be a key element in order to maintain long-term relationships. Cooperation has been defined by Anderson & Narus (1990) as, ´similar or complementary coordinated actions taken by firms in interdependent relationships to achieve mutual outcomes or singular outcomes with expected reciprocation over time´. Anderson & Narus (1990) argued that meaningful communication and cooperation between firms in a relationship is a necessary antecedent of trust. In this respect, integration or collaboration enables the proper flow of information between partners, which may reduce certain types of risks perceived by either party of the relationship. As stated before, University-Industry links have long been characterized by the sharing of confidential information, and therefore the presence of risk by an opportunistic behavior on the part of an exchange partner. Morgan and Hunt (1994) continued to develop the above definition by accentuating the proactive aspect of cooperation in opposition to being pressurized to take interdependent actions. According to them, the interaction of cooperation and commitment results in cooperative behavior that enables the partnership to work and ensures that both parties receive the benefits of the relationship, and therefore, achieve mutual satisfaction. Although research on the influence of integration in trust and commitment is scant, there is evidence that both communication (Sharma & Patterson, 1999) and collaboration or cooperation (Plewa, 2009) improves the level of trust in inter-organizational relationships. The following two hypotheses are thus stated:
Hypothesis 4: Trust is positively related to integration in University-Industry Links.
Hypothesis 5: Commitment is positively related to integration in University-Industry Links.
Integration has acquired during the last few decades an outstanding relevance in the strategic alliances literature (Rothaermel et al., 2006) and in the merger and acquisition literature (Chaterje et al., 1992). Due to the high relevance of the technological transfer of knowledge in the process of the University-Industry research collaborations, integration has been highlighted as one of key factors in order to achieve this transfer, and hence one of the main predictors of satisfaction (Mora-Valentin et al., 2004; Plewa, 2009). Therefore, the following hypothesis is posited:
Hypothesis 6: Integration is positively related to satisfaction in University-Industry Links.
Customer´s satisfaction with a service provider, in this case the university, can be defined as a consumer´s related fulfillment response regarding his consumption experience with a product or service (Oliver, 1980). According to many Marketing postulates, the relevance of this concept is mainly based on the fact that business profitability is a direct consequence of the achievement of customer´s satisfaction (Churchill & Suprenant, 1982). Notwithstanding its significance, there is a lack of general consensus regarding its conceptualization, delimitation and measurement (Giese & Cote, 2000). In this respect, customer satisfaction has been generally conceptualized as either an emotional or a cognitive response, although most recent researches have conceded an emotional response to it (Giese & Cote, 2000). This response has been traditionally based on the disconfirmation paradigm (Oliver, 1980), as a feeling coming from a comparison of customer´s expectations with a product or service and the perceived performance of that product or service (Yi, 1990). In this respect, whenever performance exceeds expectations, satisfaction would be increased. At this point, it is also important to clearly distinguish between transaction specific satisfaction and overall satisfaction, as well as between economic and non-economic satisfaction. Prior to Geykens et al.´s (1999) proposals, and mainly for relationships between channel members, it was generally understood that satisfaction was a positive affective state resulting from the appraisal of all aspects of a firm´s working relationship with another firm (Gaski & Nevin, 1985; Frazier et al., 1989). In line with this approach, satisfaction was composed of both economic and non-economic components. Economic satisfaction referred to the economic reward (e.g. price discounts) that was obtained from the relationship with the exchange partner. Non-economic satisfaction referred to the positive affective response to non-economic psychological aspects of any relationship, such as respectfulness, or good-willingness (Geykens et al., 1999). Geykens & Steenkamp (1999) proposed that these two facets of satisfaction should be separated, since the proportion of economic and non-economic items that had been included in the rating scales proposed to measure satisfaction varied considerably in the different researches available, and therefore, it was not possible to make an effective comparison across previous studies. In this regard, and in line with Marketing Relationship postulates, for the purpose of this research satisfaction will be considered as a non-economic factor. Regarding the aforementioned distinction between transaction specific and relational - or overall - satisfaction, researchers have traditionally opted for either one of these concepts of satisfaction, although it is worth mentioning that some researchers (e.g. Tse & Wilton, 1988; Szymanksy & Henard, 2001) have stated that only overall satisfaction can properly measure this construct. Overall satisfaction has been understood as a global assessment based on the buying experience of multiple encounters, whereas transaction specific satisfaction is more related with a feeling of satisfaction or dissatisfaction regarding a specific transaction or service (Anderson et al., 1994). Following the objectives presented here, and having into account that University-Industry collaborations or links form normally a part of long-term projects, for the purpose of this research satisfaction has been conceptualized as an overall uni-dimensional construct based on non-economic components. Concerning satisfaction as a predictor of customer´s intention to renew the relationship with the service provider, there is no consensus on the direct effects between these variables. Whereas many researchers have emphasized the relevance of customer satisfaction to attain short-term profitability (Mittal y Kamakura, 2001), others have taken a different view, showing not only that there is no linear effect between these variables (Simó, 2002), but also the possible lack of a direct effect (Garbarino y Johnson, 1999). Following this line, many mediating and moderating factors that could influence this direct effect have been proposed in the literature, depending on the context under study and on the research field. In this respect, Homburg and Biering (2001) examined personal characteristics such as variety seeking, age or the customer´s level of income, while other authors posited that customer´s intention to renew the relationship was moderated by the level of attachment or the customer´s loyalty (Garbarino & Johnson, 1999. Therefore, given that the direct effect between satisfaction and intention to renew has not been applied in university-industry linkages (Rosendo & Laguna, 2010), but that this causal effect seems to be evident in many other research fields and sectors, and based on the previous discussion of satisfaction and its predictors, the proposition that satisfaction positively impacts the customer´s intention to renew the relationship with the service provider is formalized as follows:
Hypothesis 7: Satisfaction is positively related to intention to renew the relationship in University-Industry Links.
3.1 Data Collection and Sampling
The target population for this study consisted of national firms operating all over Spain that had recently been, or were at the moment of the study, engaged in research and development projects of collaboration with a major public Spanish University in the Autonomous Community of Madrid. The unit of analysis was the project collaborative relationship as a whole. An initial list of companies was provided by the major public university and served as a sampling frame. There was no alternative sampling frame available because there is no public registration database of firms that collaborate with universities in Spain. The complete list was assessed and shortened following certain criteria, namely, a) the time-span period was limited to collaborations that were current or that had not finished prior to the last two years, b) the purpose of the collaboration was of a research nature, and c) the firms could not be public institutions. To examine whether the final sample was representative of the population under study, the selected firm profiles were compared to descriptions of industries that collaborate with universities in research projects provided by previous studies (Barge-Gil et al., 2007). Overall, the profile of the selected companies matched well with the overall University-Industry relationships in terms of project duration, firm characteristics and firm size. Subsequently, the study followed a two-step approach based on an exploratory qualitative investigation and an explanatory quantitative survey. The exploratory investigation was deemed important in order to ensure the appropriate adaptation and measurement of the different constructs used in this study. Therefore, a critical validation by a group of experts was conducted in order to review and edit the items, leading to the final questionnaire developed for the self-administered electronic survey. Following a pre-test conducted with managers similar in profile to the target respondents, in April 2010 the final questionnaire was e-mailed to 370 ID managers of national firms on the sampling frame operating all over Spain. To account for the impact of the low response rate normally associated with electronic surveys, respondents were offered a summary of the results to encourage their participation. A letter from the R&D Vice-Chancellor of the university was also included, encouraging cooperation and reiterating that individual responses would be strictly confidential. Surveys were returned directly to the researcher to emphasize the academic control of the information. The response rate for this initial phase was 18%. Follow-up surveys were sent to those respondents who had not returned their surveys within a three-week period, thereby increasing the response rate to 25%. Two weeks after the second mailing, a reminder was sent to respondents asking them to complete the questionnaire. After extensive mail and telephone follow-up, an effective response rate of 49% was accomplished with a total of 183 completed questionnaires valid for use in this study. It was considered a very satisfactory rate for this type of survey of business people, where response rate below 15% become questionable (Malhotra, 1993). All 183 questionnaires were analyzed. In order to avoid the so called non-response bias, possible differences in the means obtained for each one of the factors proposed in this study were analyzed between early and late respondents, as well as non-respondents and late respondents. To this end, the Levene´s-Test and the independent samples t-test were conducted. Results showed no statistical significant differences in the mean scores (Rosendo et al., 2011). Having considered non-response bias in sample quality, and assuming non-response is not the only source of possible sample bias (Blair and Zinkhan, 2006), coverage bias and selection bias were also checked (Rosendo, 2010). All these previous steps suggested that the final sample was adequate for further analysis.
3.2 Operationalisation of Constructs
The measurements used in this study were derived from existing scales in Relationship Marketing literature. These measures were slightly modified to be adapted to the specific context of University-Industry Links. The final scales were all seven-point Likert-type ones, anchored by completely disagree (1) to completely agree (7).
Trust was measured based on the scale reported by Ganesan (1994). It consisted of 10 items that included the two dimensions most often referred to in the literature, that is, credibility and benevolence (Anderson & Weitz, 1989; Kumar et al., 1995). The main reason for its use was that this rating scale has been consistently reported in the literature as having very sound psychometric properties in the context of inter-organizational relationships (c.f. Joshi & Stump, 1999; Gao et al., 2005).
Commitment was measured following Anderson & Wetiz (1992). The twelve items included in the scale tap the multiple facets of commitment most often highlighted in the literature, namely credible commitment, idiosyncratic investment, and the dedicated allocation of resources (Anderson & Weitz, 1992). Therefore, the set of items included in this scale reflect a close, long-term and stable relationship. These are relational characteristics that should apply to University-Industry Links.
Regarding satisfaction, a wide number of measures have been used in the available literature, ranging from direct to indirect measurements (Yi, 1990). The scale adapted for this study reflects the level of firm satisfaction with the overall relationship, and is based on the measure reported by Oliver (1980,1981) and Westbrook and Oliver (1981). One of the main reason behind this choice is that this scale has been highly recommended in Marketing as a reference scale to measure this construct (c.f. Hausknecht, 1990), besides it has been reported in previous studies as a very consistent and reliable one (c.f. Bearden & Teal, 1983). Likewise, intention to renew the relationship was based on a single item scale reported by Oliver (1980, 1981), Westbrook (1980, 1981), and Westbrook & Oliver (1981).
Integration has been scarcely applied in the field of Relationship Marketing. Therefore, there is a considerable lack of scales available in this specific literature. On the other hand, this variable has been largely applied in the area of strategic alliances, as well as in the context of research and its commercialization, and in the field of technological transfer. This study is based in the scale proposed by Dwyer & Oh (1987, 1988). This 4-item seven-point Likert scale measures the level of respondents´ integration with the university research group.
All the items were randomized in the final questionnaire to minimize the impact of order bias.
4.1 Validation of Measurements
First, all reverse-scored items were re-codified, and factor analysis using principal component was performed in order to validate the different constructs used in this study (Churchill, 1979). Those items with factor loadings below 0.5 and low item-to-total correlation were excluded (Hair et al., 1999). Secondly, in order to assess the underlying reliability of each scale and get further clarification of the items contributing to each factor, the Cronbanch´s Alpha scores were calculated (Nunnally, 1978), alongside with the improvements these scores would have if certain items were removed. The results obtained from the four factor analyses, together with the reliability scores for scales, are reported in table 2 (Appendix I). Although most of the scales have an alpha coefficient higher than the recommended value of 0.7 (Bagozzi & Yi, 1988), the analyses identified problems in several factors. Regarding the first construct (i.e. trust) even though most of the factor loadings exceeded 0.5, some of the items were below this limit, suggesting a better uni-dimensionial fit if these items were excluded. It was therefore decided to eliminate these indicators in further analysis. As for the construct of integration, the Cronbanch´s alpha coefficient improved notably with the elimination of item I4. As regards the third factor (i.e. commitment), results were not quite as expected. Most factor loadings were below the cut-off limit of 0.5, and therefore were excluded. Notwithstanding this fact, the remaining items kept the three facets established as significantly important in the literature, namely behavioral, attitudinal and temporal components. Principal component analysis of the fourth factor confirmed the uni-dimensionality of the construct, with a single factor explaining practically 85% of the variance.
On the basis of these modifications -and once the aforementioned items were excluded due to their low factor loading with the correspondent variables- a second exploratory factor analysis was carried out. The results, which are to be found in table 3 (Appendix I), show that the factor loadings for all the corresponding factors exceeded the recommended cut-off point of 0.5, hence corroborating the dimensionality of each of the constructs under study and confirming that the composition of each of the four factors was adequate. Likewise, the variance explained by three of the factors was higher than 80%, being nearly 70% for the remaining one. The Cronbach´s alpha scores for the different scales were all above 0.7, which indicates a very satisfactory internal consistency and reliability, and shows to be in line with the scores reported in previous studies (cf. Ganesan, 1994; Dwyer & Oh, 1987, 1988; Anderson & Weitz, 1992; Oliver, 1980). Hence, the trust scale was finally comprised of six items, the integration and commitment scales were comprised of three items respectively, and satisfaction was based on the original four-item scale. As previously stated, the factor intention to renew was based on a single item, so no further psychometric analyses were carried out.
4.2 Correlations and Regressions Results
The established hypotheses were tested by means of correlations and linear regressions. To this end, in order to obtain composite scores on each uni-dimensional construct in table 1, summative scales were developed by creating four variables, one for each of the constructs, measured through the arithmetic mean of the individual scores of their component items. A correlation analysis was conducted on all variables in this study for two main reasons. The first one was to check the existence of multi-collinearity between the factors, which is revealed when the inter-correlation between the explanatory variables exceeds 0.8 (Berry & Feldmann, 1985). The Pearson correlations matrix showed that this was not the case in the present study. The second reason was to explore the relationships between independent and dependent variables. The bi-variate correlation procedure was subject to a two tailed tests of statistical significance at two different levels –highly significant (p<0.01) and significant (p<0.05). Correlations analyses supported all the positive relationships among the independent variables and the dependent variables posited in this study at a highly significant level, except for the correlation between trust and satisfaction (p>0.05).
The results of the regression analyses presented in table 1 support the notion of most of the hypothesized relationships among the independent and the dependent variables with very high statistical significance (p<0.001), showing strong associations among most variables, and proving six of the hypotheses to be supported. Commitment was found to be significantly correlated with satisfaction (H2, p<0.001). In line with hypothesis H3, trust was also positively related to integration (p<0.001), as well as integration to satisfaction (p<0.001). Commitment emerged as well positively correlated with integration (p<0.001), supporting H4. Analyzing the effect of trust on commitment, results were very much as expected, showing a significant relationship between both constructs, hence supporting H5. H7 was also supported, with a strong link between satisfaction and intention to renew the relationship. However, contrary to the expectations in hypothesis H1, trust was not found to be positively related to satisfaction, therefore this hypothesis had to be rejected (H1, p>0.05).
Table 1: Results of the regression analyses
DISCUSSIONS AND IMPLICATIONS
The results obtained in this study supported most of the hypothesized paths in this paper, confirming -either directly or indirectly- the relevance of commitment, integration and trust for customer´s retention in this specific context. Following this empirical research, trust emerged as a fundamental construct for University-Industry collaboration success due to its significant and positive influence both on commitment (β=0.614***), and on integration (β=0.491***). These findings are aligned with the relevance that trust has acquired in RM literature (Morgan & Hunt, 1994), as well as with the empirical evidence presented in the context of strategic alliances between private research centers and private sector organizations (Davenport et al., 1999; Montoro-Sanchez et al., 2000). The role of trust as a predictor of commitment and integration can be explained by the intrinsic research nature that characterizes University-Industry relationships. The unfeasibility by both parties to predict the ultimate outcomes of any research process carried out by the university gives rise to a high level of firm uncertainty (Harman & Sharwell, 2002). Moreover, the information that both parties share is generally distinguished for being highly confidential, mainly due to the fact that some of the strategic decisions that firms may take in the near future depend, to some extent or another, on that same information. This can lead to an opportunistic behavior by one of the exchange counterparts, thus, making trust a fundamental pillar for University-Industry relationship success. Although it could be argued that contractual agreements may also reduce this potential risk, the exclusive use of these contractual safeguards could also have a discouraging effect, by reducing the development of new knowledge not specifically agreed on the contractual clauses. Therefore, the usage of trust as an alternative -or complementary- relationship tool can, firstly, help to mitigate these adversities (Bendapudi & Berry, 1997), and secondly, help to increase the level of integration and commitment among both relationship parties. Additionally, trust can have a persuasive effect in the resolution of disagreements or conflicts between the exchange partners, easing the mutual understanding and the friendly acceptance of discrepancies between both parties, and enhancing their joint cooperation (Dwyer et al., 1987). Furthermore, a trusting research relationship may offer flexibility in operations and information exchange, settling down the basis for discovery and successful research, and for more satisfying collaborative research outcomes (Plewa, 2009). Surprisingly, the results obtained in relation to the direct impact of trust on satisfaction (β=0.051; t=0.079) were quite unexpected, although as previously discussed, it is worth mentioning the fact that trust does have an indirect impact on satisfaction due to its high correlation with integration and commitment. Trust was operationalised in this research as an affective construct based on two dimensions, namely credibility and benevolence. Therefore, it could be suggested that, although trust is a relevant factor for University-Industry links, firm satisfaction and retention will not be directly determined by affective factors such as trust, but by behavioral factors, such as integration or commitment. That is, trust evolves in line with relationships evolvement. In this respect, there is theoretical support that trust may be the consequence, rather than the determinant of a long-term relationship (Ganesan, 1994). Hence, firm trust would be achieved once the university research team has proved to be cooperative and committed in the University-Industry relationship. On that account, if university managers aim at encouraging industry linkages, incentives should be given to the academic staff that form part of a research group in order to motivate their collaboration with their exchange partners, and their commitment to the relationship. This will lead to the achievement of a higher involvement of academic staff in University-Industry links, and thus to better research output and customer retention through higher levels of firm satisfaction.
The results obtained in this study also showed a positive effect between all dimensions of commitment and both satisfaction (β=0.651***) and integration (β=0.511***). These results are lined up with previous researches in Relationship Marketing (Jap & Ganesan, 2000; Morgan & Hunt, 1994; Mohr & Spekman, 1994). They do also confirm prior studies carried out in the context of research cooperation among private institutions, as well as previous literature on technology transfer and its commercialization (Barnes et al., 2002; Irwin et al., 1998).
Relationship commitment, together with relationship trust, has been proposed as a relevant factor in order to reduce the level of opportunistic behavior by one of the exchange parties (Williamson, 1981). Additionally, according to the results of this study, the correlation between commitment and satisfaction may be influenced by the level of integration between the parties. In this sense, a high collaboration and integration among the exchange partners may induce a higher level of commitment in the research group, thus increasing the overall level of firm satisfaction with the relationship and therefore the likelihood of customer retention.
Lastly, commitment was operationalised in this study following Anderson & Weitz´s (1992) conceptualization as a multi-dimensional construct based on behavioral, attitudinal and temporal facets. It reflects, therefore, elements regarding a feeling of loyalty towards the counterpart, a long-term effort in order to maintain the relationship, and the willingness to invest the necessary resources in the relationship. Hence, the encouragement of all these dimensions between the members that form part of a university research group will constitute a valuable resource for university managers that wish to retain firms as their customers. Likewise, this will contribute to a higher collaboration and cooperation between the parties involved in the relationship, leading to a better cooperation, an increase in the quality and the quantity of the research outcomes, and an increase on customer retention.
CONCLUSIONS AND FURTHER RESEARCH
This research contributes to the Relationship Marketing literature by demonstrating the importance of developing relationship marketing strategies in order to achieve higher levels of success in University-Industry collaborations. The present study is noteworthy for several reasons. As to the knowledge of the researcher, no prior study has been done previously in Spain on any public university to examine the effects that trust, commitment and integration can have on short-term and long-term outcome measures, namely on firm´s satisfaction and on firm´s intention to renew the relationship. Therefore, this study will definitely benefit university managers to understand the extent to which the effective application of these relational factors can affect the level of customer retention in this type of collaborative projects.
Our results revealed a weighty effect between integration and satisfaction, suggesting that integration is significantly important for University-Industry linkages, as industries will only be satisfied with a public university research project when they feel the levels of collaboration and integration between the parties are appropriate. Finally, our study empirically validated the link between commitment and satisfaction, and between satisfaction and intention to renew. It was observed that commitment and satisfaction were significantly and positively related. Moreover, our research empirically validated the effect of trust on commitment in a business-to-business context between private and public institutions. Previous empirical research on trust and commitment was primarily conducted only in industrial and channel literature (Doney & Cannon, 1997; Baker et al., 1999; Kumar et al., 1995).
Finally, the findings of this study have to be interpreted considering the limitations of the research. Some limitations might be related to collecting the data and interpreting the results. First, data collection was limited to a major public university, so the results might be challenged whether it is truly representative of the entire country. Second, a probability sampling would have been a better on to draw realistic inferences regarding the studied variables. Another potential shortcoming in the study is common method bias. One sample questionnaire was used to measure all constructs included in this study, so maybe the strength of the relationships between these constructs may be somewhat inflated. Moreover, confirmatory factor analysis could have been employed to make the model more robust. Lastly, the results of a study conducted in a single context can not necessarily be generalized to other contexts.
More research is necessary on collaborations between universities and private organizations. In this respect, the general conclusions argued in this study do not preclude the possibility of introducing new factors in the context of University-Industry links. For instance, supplementary factors in University Industry linkages may be included as antecedents, mediators or moderators. In this sense, the level of organizational similarity between the partners, or the level of employee experience similar research groups of collaborations could be incorporated as additional antecedents of trust, integration or commitment. Potential moderating or mediating factors could include the level bureaucracy implied in these collaborations, or the life cycle stage of the research project. Future research is guaranteed to allow for additional variables. It should also be noted that the lack of support for the influence of trust on satisfaction deserves further analyses. These recognized shortcomings will definitely inspire further studies in future research agendas.
Anderson, E.W., Fornell, C., & Lehmann, D.R. (1994). Customer Satisfaction, Market Share, and Profitability: Findings from Sweden. Journal of Marketing, 58 (July), 53-66.
Anderson, E. & Weitz, B. (1992). The Use of Pledges to Build and Sustain Commitment in Distribution Channels. Journal of Marketing Research, 29 (February), 18-34.
Anderson, E. & Weitz, B. (1989). Determinants of Continuity in Conventional Industrial Channel Dyads. Marketing Science, 8 (4), 310-323.
Bagozzi, R., & Yi, Y. (1988). On the Evaluation of Structural Equation Models. Journal of the Academy of Marketing Science, 16 (1), 74-94.
Baker, T., Simpson, P., & Siguaw, J.A. (1999). The Impact of Suppliers´ Perceptions of Reseller Market Orientation on Key Relationship Constructs. Journal of the Academy of Marketing Science, 27 (1), 50-57.
Barge-Gil, A., Modrego, A., & Santamaria, L. (2007). Complementarities Between External Sources of Knowledge: The Case of Universities and Technology Industries in Spain. Proceedings of XII of Seminario Latino-Iberoamericano de Gestión Tecnológica. Buenos Aires. ALTEC.
Barnes, T., Pashby, I., & Gibbons, A. (2002). Effective Universitiy-Industry Interaction: A Multi-Case Evaluation of Collaborative R&D Projects. European Management Journal, 20 (3), 272-285.
Bearden, W.O., & Teel, J.E. (1983). Selected Determinants of Consumer Satisfaction and Complaint Reports. Journal of Marketing Research, 20 (February), 21-28.
Bendapudy, N. & Berry, L.L. (1997). Customers´Motivations for Maintaining Relationships with Service Providers. Journal of Retailing, 73 (1), 15-37.
Bernasco, W., Weerd-Nederhof, P.C., Tillema, H., & Boer, H. (1999). Balanced Matrix Structure and New Product Development Process at Texas Instruments Materials and Control Division. R&D Management, 29 (2), 121-131.
Berry, L.L. (1995). Relationship Marketing and Services- Growing Interest, Emerging Perspectives. Journal of the Academy of Marketing Science, 23 (4), 236-245.
Berry, W., & Feldmann, S. (1985). Multiple Regression in Practice. California. Sage Publications.
Blair, E., & Zinkhan, G.M. (2006). Nonresponse and Generalizability in Academic Research. Journal of the Academy of Marketing Science, 34 (1), 4-7.
Bucklin, L.P., & Sengupta, S. (1993). Organizing Successful Co-Marketing Alliances. Journal of Marketing, 57(2), 32-46.
Chatterje, S., Lubatkin, M., Schuweiger, D.M., & Weber, Y. (1992). Cultural Differences and Shareholder Value in Related Mergers: Linking Equity and Human Capital. Strategic Management Journal, 13(5), 319-334.
Churchill, G.A.J. (1979). A Paradigm for Developing Better Measures of Marketing Constructs. Journal of Marketing Research, 16 (February), 64-73.
Churchill, G.A.J., & Suprenant, C. (1982). An Investigation into the Determinants of Customer Satisfaction. Journal of Marketing Research, 19 (4), 491-504.
Cyert, R.M. & Goodman, P.S. (1997). Creating Effective University-Industry Alliances: An Organizational Learning Perspective. Organizational Dynamics, 25 (4), 45-57.
Davenport, S.J., Davies, J., & Grimes, C. (1999). Collaborative Research Programmes: Building Trust from Difference. Technovation, 1, 31-40.
Doney, P.M. & Cannon, J.P. (1997). An Examination of the Nature of Trust in Buyer-Seller Relationships. Journal of Marketing, 61 (2), 35-51.
Dwyer, R.F., & Oh, S. (1987). Output Sector Munificence Effects on the Internal Political Economy of Marketing Channels. Journal of Marketing Research, 24 (4), 347-358.
Dwyer, R.F., Schurr, P., & Oh, S. (1987). Developing Buyer-Seller Relationships. Journal of Marketing, 52 (2), 21-34.
Frazier, G.L., Gill, D., & Kale, S.H. (1989). Dealer Dependence Levels and Reciprocal Actions in a Channel of Distribution in a Developing Country. Journal of Marketing, 53 (January), 50-69.
Gao, T., Sirgy, M.J., & Bird, M.M. (2005). Reducing Buyer Decision-Making Uncertainty in Organizational Purchasing: Can Supplier Trust, Commitment, and Dependence Help?. Journal of Business Research, 58, 397-405.
Ganesan, S. (1994). Determinants of Long-Term Orientation in Buyer-Seller Relationships. Journal of Marketing, 58 (2), 1-19.
Garbarino, E., & Johnson, M.S. (1999). The Different Roles of Satisfaction, Trust, and Commitment in Customer Relationships. Journal of Marketing, 63 (2), 70-87.
Gaski, J.F., & Nevin, J.R. (1985). The Differential Effects of Exercised and Unexercised Power Sources in a Marketing Channel. Journal of Marketing Research, 22 (May), 130-142.
Geykens, I., Steenkamp, J.B., & Kumar, N. (1999). A Meta-Analysis of Satisfaction in Marketing Channel Relationships. Journal of Marketing Research, 36 (May), 223-238.
Geykens, I., Steenkamp, J.B., & Kumar, N. (1998). Generalizations about Trust in Marketing Channel Relationships Using Meta-Analysis. International Journal of Research in Marketing, 15, 223-248.
Geykens, I., Steenkamp, J.B., Scheer, L., & Kumar, N. (1996). The Effects of Trust and Interdependence on Relationship Commitment: A Transatlantic Study. International Journal of Research in Marketing, 13 (4), 303-317.
Giese, J.L., & Cote, J.A. (2000). Defining Consumer Satisfaction. Academy of Marketing Science Review, accessed April 16, 2010 (Available at http://www.amsreview.org/articles/giese01-2000.pdf)
Gounaris, S.P. (2005). Trust and Commitment Influences on Customer Retention: Insights from Business-to-Business Services. Journal of Business Research, 58, 126-140.
Gundlach, G.T., Achrol, R.S., & Mentzer, J.T. (1995): “The Structure of Commitment in Exchange. Journal of Marketing, 59 (January), 78-92.
Gummesson, E. (2002). Relationship Marketing in the New Economy. Journal of Relationship Marketing, 1 (1), 37-58.
Hair, J.F.J., Anderson, R.E., Tatham, R.L. & Black, W.C. (1999): Análisis multivariante. España. 5th Edition. Prentice Hall Internacional.
Harman, G., & Sharwell, V. (2002). Risks in University-Industry Research Links and the Implications for University Management. Journal of Higher Education Policy and Management, 24 (1), 37-51.
Hausknecht, D.R. (1990). Measurement Scales in Consumer Satisfaction/Dissatisfaction. Journal of Consumer Satisfaction, Dissatisfaction, and Consumer Behavior, 3(1), 1-11.
Homburg, C. & Giering, A. (2001). Personal Characteristics as Moderators of the Relationship between Customer Satisfaction and Loyalty- An Empirical Analysis. Psychology and Marketing, 18, 43-66.
Irwin, H., More, E., & Mcgrath, M. (1998). Relationship Management for Innovation: The Central Role for Communication in Australia´s Participation in two High-Tech Industries. Technology Analysis and Strategic Management, 10 (4), 467-481.
Jap, S.D., & Ganesan, S. (2000). Control Mechanisms and the Relationship Life Cycle: Implications for Safeguarding Specific Investments and Developing Commitment. Journal of Marketing Research, 37 (May), 227-245.
Joshi, A.W., & Stump, R.L. (1999). The Contingent Effect of Specific Asset Investments on Joint Action in Manufacturer-Supplier Relationships: An Empirical Test lf the Moderating Role of Reciprocal Asset Investments, Uncertainty, and Trust. Journal of the Academy of Marketing Science, 27 (3), 291-305.
Kahn, K.B. (1996). Interdepartmental Integration: A Definition with Implication for Product Development Performance. Journal of Product Innovation Management, 13 (2), 137-151.
Kahn, K.B., & Mentzer, J.T. (1996). Logistics and Interdepartmental Integration. International Journal of Physical Distribution and Logistics, 26 (8), 6-14.
Kumar, N., Scheer, L., & Steenkamp, J.B. (1995). The Effect of Supplier Fairness on Vulnerable Resellers. Journal of Marketing Research, 32 (1), 42-53.
Lee, Y.S. (2000). The Sustainability of University-Industry Research Collaboration: An Empirical Assessment. The Journal of Technology Transfer, 25 (2), 111-133.
Malhotra, N.K. (1993). Marketing Research: An Applied Orientation. Englewood Cliffs, N.J. Prentice-Hall.
Mohr, J., & Spekman, R. (1994). Characteristics of Partnership Success: Partnership Attributes, Communication Behavior, and Conflict Resolution Techniques. Strategic Management Journal, 15 (2), 135-152.
Montoro-Sanchez, A., Mora-Valentin, E.M., Guerras-Martin, L.A. (2000). La naturaleza del socio como factor moderador en la relación entre confianza y éxito en los acuerdos de cooperación. Revista de Economía y Empresa, 14 (40), 31-57.
Mora-Valentin, E.M., Montoro-Sánchez, A., & Guerras-Martin, L.A. (2004). Determining Factors in the Success of R&D Cooperative Agreements between Firms and Research Organizations. Research Policy, 33 (1), 17-40.
Morgan, R.M. & Hunt, S.D. (1994). The Commitment-Trust Theory of Relationship Marketing. Journal of Marketing, 58 (3), 20-38.
Moorman, C., Deshpandé, R., & Zaltman, G. (1993). Factors Affecting Trust in Market Research Relationships. Journal of Marketing, 57 (January), 81-101.
Moorman, C., Zaltman, G. & Deshpandé, R. (1992). Relationships between Providers and Users of Market Research: The Dynamics of Trust within and between Organizations. Journal of Marketing Research, 24 (3), 314-328.
Nevin, J.R. (1995). Relationship Marketing and Distribution Channels: Exploring Fundamental Issues. Journal of the Academy of Marketing Science, 23 (4), 327-334.
Nunnally, J.C. (1978): Psychometric Theory. New York. Second Edition. McGraw-Hill. Oliver, R.L. (1981). Measurement and Evaluation of Satisfaction Processes in Retail Setting. Journal of Retailing, 57 (Fall), 25-48.
Oliver, R.L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17 (November), 460-469.
Palmer, A. (2002). The Evolution of an Idea: An Environmental Explanation of Relationship Marketing. Journal of Relationship Marketing, 1 (1), 79-94.
Parvatiyar, A., & Sheth, J. (1994). Paradigm Shift in Marketing Theory and Approach: The Emergence of Relationship Marketing. In Relationship Marketing: Theory, Methods and Applications Section I, Session 2.1. Eds. Jagdish Sheth and Atul Parvatiyar. Center for Relationship Marketing. Atlanta. Emory University.
Plewa, C. (2009). Exploring Organizational Culture Difference in Relationship Dyads. Australasian Marketing Journal, 17, 46-57.
Plewa, C. & Quester, P. (2008). A Dyadic Study of “Champions” in University-Industry Relationships. Asia Pacific Journal of Marketing and Logistics, 20 (2), 211-226.
Plewa, C. & Quester, P. (2007). Key Drivers of University-Industry Relationships: The Role of Organizational Compatibility and Personal Experience. The Journal of Services Marketing, 21 (5), 370-382.
Plewa, C. & Quester, P. (2006). The Effects of a University´s Market Orientation on the Industry Partner´s Relationship Perception and Satisfaction. International Journal of Technology Intelligence and Planning, 2 (2), 160-170.
Rothaermel, F.T., Hitt. M. A., & Jobe, L. A. (2006). Balancing Vertical Integration and Strategic Outsourcing: Effects on Product Portfolio, Product Success, and Firm Performance. Strategic Management Journal, 27, 1033–1056.
Rosendo, V. (2010). Modelización de los factores determinantes del éxito en la colaboración Universidad-Empresa: Un enfoque basado en el Marketing Relacional. Doctoral dissertation. Rey Juan Carlos University, Madrid, Spain.
Rosendo, V.; Laguna, P. (2010). La satisfacción del consumidor y la intención de renovación en el contexto de vínculos interorganizacionales: Una aproximación desde el Marketing Relacional. Proceedings of the 11º Forum Internacional sobre las Ciencias, las Técnicas y el Arte aplicadas al Marketing. Academia y Profesión. Madrid.
Rosendo, V.; Laguna, P.; Mercado, C. (2011). An Empirical Examination of University-Industry Links based on a Relationship Marketing Approach. Proceedings of XXI Jornadas Hispano-Lusas de Gestión Científica. Córdoba.
Santoro, M. & Chakrabarti, A.K. (2002). Firm Size and Technology Centrality in Industry-University Interactions. Research Policy, 31, 1163-1180.
Shane, S., & Stuart, T. (2002). Organizational Endowments and the Performance of University Start-ups. Management Science, 48 (1), 154–171.
Sharma, N., & Patterson, P.G. (1999). The Impact of Communication Effectiveness and Service Quality on Relationship Commitment in Consumer Professional Services. Journal of Services Marketing, 13 (2), 151-170.
Siegel, D.S., Waldmann, D., & Link, A. (2003). Assessing the Impact of Organizational Practices on the Relative Productivity of University Technology Transfer Offices: An Exploratory Study. Research Policy, 32, 27-48.
Singh, S.N., & Sirdeshmukh, D. (2000). Agency and Trust Mechanisms in Consumer Satisfaction and Loyalty Judgements. Journal of the Academy of Marketing Science, 66 (January), 15-37.
Simó, A.L. (2002). Análisis de la satisfacción en la experiencia del consumidor: una aplicación en empresas de servicios de ocio y turismo. Investigaciones Europeas de Dirección y Economía de la Empresa, 8 (3), 199-214.
Slaughter, S. & Leslie, L.L. (1997). Academic Capitalism: Politics, Policies, and the Entrepreneurial University. Baltimore, M.D. The John Hopkins University Press.
Slaughter, S., & Rhoades, G. (2004). Academic Capitalism and the New Economy: Markets, State, and Higher Education. Baltimore, M.D The Johns Hopkins University Press.
Spekman, R. (1988). Strategic Supplier Selection: Understanding Long-Term Buyer Relationships. Business Horizons, 31, 75-81.
Szymansky, D.M., & Henard, D.H. (2001). Customer Satisfaction: A Meta-Analysis of Empirical Evidence. Journal of the Academy of Marketing Science, 29 (1), 16-35.
Tse, D.K., & Wilton, P.C. (1988). Models of Consumer Satisfaction Formation: An Extension. Journal of Marketing Research, 25 (May), 104-112.
Westbrook, R.A., & Oliver, R.L. (1981). Developing Better Measures of Consumer Satisfaction: Some Preliminary Results. In Advances in Consumer Research, Kent B. Monroe, ed. Ann Arbor, MI: Association for Consumer Research, pp. 94-99.
Williamson, O.E. (1981). The Economics of Organizations: The Transaction Cost Approach. American Journal of Sociology, 87 (3), 548-577.
Yi, Y. (1990). A Critical Review of Customer Satisfaction. Review of Marketing. Eds. Valerie A., Zeithmal, American Marketing Association, 68-123.
TABLES AND FIGURES
Table 2. Principal Components. First Analysis
Table 3. Principal Components. Second Analysis
July 2-3, 2013