Proposal of a social alliance success model from a relationship marketing perspective: A meta-analytical study of the theoretical foundations

Barroso-Méndez, María Jesús; Galera Casquet, Clementina; Valero-Amaro, Victor Article Proposal of a social alliance success model from a relationship marketing perspective: A meta-analytical study of the theoretical foundations BRQ Business Research Quarterly Provided in Cooperation with: Asociación Científica de Economía y Dirección de Empresas (ACEDE), Madrid Suggested Citation: Barroso-Méndez, María Jesús; Galera Casquet, Clementina; Valero-Amaro, Victor (2015) : Proposal of a social alliance success model from a relationship marketing perspective: A meta-analytical study of the theoretical foundations, BRQ Business Research Quarterly, ISSN 2340-9436, Elsevier España, Barcelona, Vol. 18, Iss. 3, pp. 188-203, https://doi.org/10.1016/j.brq.2014.09.002 This Version is available at: https://hdl.handle.net/10419/206326 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ BRQ Business Research Quarterly (2015) 18, 188---203 www.elsevier.es/brq BRQ Business Research Quarterly ARTICLE Proposal of a social alliance success model from a relationship marketing perspective: A meta-analytical study of the theoretical foundations María Jesús Barroso-Méndez∗, Clementina Galera-Casquet, Víctor Valero-Amaro University of Extremadura, Department of Business Management and Sociology, Av. de Elvas s/n. 06006, Badajoz, Spain Received 5 March 2014; accepted 29 September 2014 Available online 11 December 2014 JEL CLASSIFICATION M31 KEYWORDS Success model; Relationship marketing; Meta-analysis; Social alliances Abstract Partnerships between businesses and non-governmental organizations (NGOs) have become widely adopted mechanisms for collaboration in addressing complex social issues, the aim being to take advantage of the two types of organizational rationale to generate mutual value. Many such alliances have proved to be unsuccessful, however. To assist managers improve the likelihood of success of their collaborative relationships, the authors propose a success model of business-NGO partnering processes based on Relationship Marketing Theory. They also analyse the theoretical bases of the model’s hypotheses through a meta-analytical study of the existing literature. © 2014 ACEDE. Published by Elsevier España, S.L.U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Introduction Partnerships between businesses and nonprofit organizations (NPOs) have grown substantially in the last two decades (Bennett et al., 2008; Murphy et al., 2014). One reason is their enormous potential in addressing complex social problems, while, in turn, providing multiple benefits for the partners (Berger et al., 2006; Bennett et al., 2008; Reed ∗Corresponding author. E-mail addresses: [email protected], [email protected] (M.J. Barroso-Méndez), [email protected] (C. Galera-Casquet), [email protected] (V. Valero-Amaro). and Reed, 2009; Austin and Seitanidi, 2012a,b; Stadtler, 2012; Sakarya et al., 2012; Schiller and Almog-Bar, 2013; Al-Tabbaa et al., 2014; Murphy et al., 2014). Indeed, a study by the PrC/Partnerships Resource Centre (2011) finds the world’s largest firms to have, on average, 18 ongoing cross-sector collaborations, most of them with NPOs. Their objectives are to contribute to solving social problems, to strengthen their position as market leaders, or, from sharing knowledge and know-how, to develop better products. However, despite their importance, a large proportion of these partnership processes are unsuccessful (Galaskiewicz and Colman, 2006; Gutiérrez et al., 2012). This is due mainly to the many problems involved in their management http://dx.doi.org/10.1016/j.brq.2014.09.002 2340-9436/© 2014 ACEDE. Published by Elsevier España, S.L.U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Social alliances and relationship marketing 189 (Kolk et al., 2010), such as mistrust, misunderstandings, or power imbalances between the partners (Berger et al., 2004; Selsky and Parker, 2005; Seitanidi and Ryan, 2007). In this sense, various researchers have consequently focused their analyses on the factors favouring the success of these processes during the different stages of their development, especially during their formation and initial implementation (Jamali and Keshishian, 2009; Le Ber and Branzei, 2010; Jamali et al., 2011; Seitanidi et al., 2010; Austin and Seitanidi, 2012b; McDonald and Young, 2012). However, to date, the number of explanatory theoretical frameworks for success in partnerships, constructed from different perspectives, has been very limited (with exceptions such as Seitanidi and Crane, 2009; Clarke and Fuller, 2010; Seitanidi, 2010; Murphy and Arenas, 2010; Le Ber and Branzei, 2010; Venn, 2012; Sanzo et al., 2014; Murphy et al., 2014). This scarcity in the literature is even more evident on those success models developed under one Relationship Marketing approach (Sanzo et al., 2014), theoretical perspective which is considered wellsuited to this purpose since it has been widely used in the design of models of success in strategic contexts (Hunt et al., 2002; Arenas and García, 2006; Wittmann et al., 2009). Since its inception, research in Relationship Marketing has worked on identifying and weighing the key constructs determining success in different partnership processes. However, a narrative review of the links between these constructs has showed a diversity of results (Palmatier et al., 2006), which has markedly limited the generalizability of the obtained conclusions (Camisón et al., 2002). There is thus a need to conduct meta-analyses which, by synthesizing the results of previous studies, can improve the scientific knowledge generated up to that time (Geyskens et al., 2009). There have as yet, however, been very few meta-analytical studies in the field of Relationship Marketing. Among the existing studies, it should be highlighted the work conducted by Palmatier et al. (2006), because of the amplitude of its scope, including a large number of links between different constructs. However, this study focuses on the specific ‘‘customer-seller’’ context, with no reference therefore to the research context of the present work, i.e., ‘‘businessNGO’’ relationships. In this sense, the specific objectives of the present study were twofold: first, to cover the gap we had identified in research by proposing a model of success for partnership processes between firms and NGOs based on Relationship Marketing Theory, and second, given the divergence of results in the literature, to conduct a meta-analytical study of the theoretical support for the model’s hypotheses, which could then serve as a basis for future research. The rest of this paper is structured as follows. Section ‘A relational approach to business-NGO partnerships’ analyses alliances between firms and NGOs from a relational perspective, and, following a review of the literature in the domain of Relationship Marketing, presents a success model for such partnership processes. Section ‘Meta-analytic study of the proposed model’ describes the basic notions of metaanalytical techniques, and presents the main results of their use in this study. Finally, section ‘Conclusions and implications for management’ presents the main conclusions of the study, and discusses their implications for management, the limitations of the study, and indications for future research. A relational approach to business-NGO partnerships Concept and evolution of Relationship Marketing Because of its importance and differentiating features, the Relationship Marketing paradigm has received much attention in recent decades on the part of both academics and professionals. The term ‘‘relationship marketing’’ first appeared in 1983 in a book chapter published by Berry (Berry, 1995). In this chapter, Berry (1983, p. 25) defined it as ‘‘attracting, maintaining, and enhancing customer relationships’’. Since then, numerous authors have proposed many alternative definitions of the term, being most of them collected in different research works. Among the existing studies, it should be highlighted the exhaustive work of Harker (1999), which identified 26 different definitions of the concept published up to that time. The conclusion of his study was that the most widely accepted definition of Relationship Marketing in the literature was that of Grönroos (1994): ‘‘Relationship marketing is to identify and establish, maintain and enhance and when necessary also to terminate relationships with customers and other stakeholders, at a profit, so that the objectives of all parties are met, and that this is done by a mutual exchange and fulfilment of promises’’. Also, in order to update and improve the work of Harker (1999), Agariya and Singh (2011) identified 72 definitions of Relationship Marketing in the literature, covering a 28-year period (1982---2010). According to those authors, although the definitions identified in the literature differ slightly due to different contextual scenarios in which they had been put forward, the core of all of them revolved around the acquisition, the retention, the improvement of profitability, the long-term orientation, and the presence of a win-win situation for all of a firm’s stakeholders. Thus, as can be gleaned from the various definitions of relationship marketing mentioned previously, numerous researchers have observed that the scope of relationship marketing should not be restricted to the maintenance of relationships between the firm and its customers but should also include the firm’s relationships with various other stakeholders. This extension to other actors is consistent with and strongly linked to the strategic approach of Stakeholder Marketing (Bhattacharya and Korschun, 2008; Bhattacharya, 2010; Smith et al., 2010; Mish and Scammon, 2010), which ‘‘looks beyond customers as the target of marketing activities and firms as the primary intended beneficiary’’ (Bhattacharya and Korschun, 2008, p. 113). In consequence, firms needs to design, implement, and evaluate its marketing strategy taking all of its stakeholders into account (Bhattacharya, 2010). Relationship Marketing is no stranger to this idea. In fact, it can be found in the literature on this field several contributions recognizing its various target stakeholder groups (Frow and Payne, 2011; see Table 1), with NGOs being one of them (Morgan and Hunt, 1994). 190 M.J. Barroso-Méndez et al. Table 1 Different approaches to describing stakeholders in Relationship Marketing. Author Categories Christopher et al. (1991) 6 markets: a consumer market and five secondary markets. Kotler (1992) 10 actors: four actors of the immediate environment and six of the macro-environment. Morgan and Hunt (1994) 10 relationships, corresponding to four types of partnership: • Supplier partnerships: Partnerships involving relational exchanges between manufacturers and suppliers of goods or services. • Buyer partnerships: Long-term exchanges between businesses and end customers, or relational exchanges of working partnerships. • Internal partnerships: Exchanges established with functional departments between a firm and its employees, or within the firm itself with its business units. • Lateral partnerships: Strategic alliances between businesses and their competitors, businesses and NGOs, or businesses and national, state, or local governments. Gummesson (1997) 30 relationships: seventeen market relationships (three classic and fourteen special) and thirteen non-market relationships (six mega-relationships and seven nano-relationships). Doyle (1995) 4 types of network: partnerships with suppliers, partnerships with customers, internal partnerships, and external partnerships. Laczniak (2006) 6 different groups of stakeholders, divided into primary and secondary. Source: Compiled from Frow and Payne (2011). A proposal of a model of success for business-NGO partnership processes Relationship Marketing Theory, unlike other approaches, stresses that success in the relational exchanges between different agents results from certain characteristics being present in the relationship. In particular, following the arguments of various authors (Hunt et al., 2002; Wittmann et al., 2009), partnerships between businesses and NGOs which exhibit different key characteristics in such exchanges to a greater intensity will be more successful than those which do not. In order therefore to determine which attributes are fundamental in exchanges between firms and NGOs, this study has carried out a review of the main theoretical models proposed for this particular type of relationship. This analysis of the literature, although exhaustive, has uncovered only three research studies on this type of exchange: MacMillan et al. (2005); Reinhard (2012); and Sanzo et al. (2014). The key variables they have mentioned are listed in Table 2. Given this limited number of works on the specific research context of the present study, it was considered appropriate to also review the literature on relational models between businesses and other nonprofit organizations (NPO). Specifically, of the different types of NPO according to their main economic activity (see the classification of Ruíz Olabuénaga, 2000), it was just possible to include those works that had analysed relationship models between businesses and universities, because of they were the only models which had also been dealt with empirically in the Relationship Marketing literature. The works that have studied this connection are those of Plewa and Quester (2006, 2007, 2008), Navarro et al. (2009), and Frasquet et al. (2012). The key variables they have mentioned in this area are listed in Table 3. At this point, it clearly had to be concluded that the number of papers in the Relationship Marketing literature focusing on exchanges between businesses and NGOs/NPOs is very limited. We therefore considered it necessary to explore the main factors proposed in some other type of ‘‘organization-organization’’ relationships. Specifically, we incorporated ‘‘business-business’’ relationship models given the greater number of studies in that field. In the following paragraph, we shall briefly describe those most frequently cited in the literature. In 1987, Dwyer, Schurr and Oh proposed a framework for the management of relationships between buyers and sellers, employing concepts of Modern Contract Law. They emphasized the importance of three key variables in the development of those relationships: trust, commitment, and disengagement. Subsequently, Anderson and Narus (1990) designed a model which employed a number of key variables to explain satisfaction in the relationships between producers and distributors. These variables were cooperation, dependence, influence, conflict, functional conflict (measuring disagreements that the partners resolved amicably), communication, results of the relationship, and trust. In 1992, Anderson and Weitz proposed a model of relationships between producers and distributors in which commitment was the central concept. Later, in 1994, Morgan and Hunt set out their Commitment-Trust Theory which has served as the basis on which most subsequent work has been developed (Bordonaba and Polo, 2006; Suárez et al., 2006; Wittmann et al., 2009; among others). They proposed and validated empirically that commitment and trust, separate from power and dependence, were key concepts in achieving successful relational exchanges. These two concepts were positioned as key mediating constructs between five antecedents (relationship benefits, shared values, communication, opportunistic behaviour, and relationship termination costs) and five outcomes of the relationship (acquiescence, propensity to leave, cooperation, functional conflict, and uncertainty in decision making). However, despite the spread of this theory, other constructs have also been suggested as explaining successful relationships between businesses. Among them, there stands out the construct of ‘‘relationship quality’’, comprising, in general terms, three dimensions: trust, commitment, Social alliances and relationship marketing 191 Table 2 Key variables mentioned in the Relationship Marketing literature on exchanges between businesses and NGOs. Authors Antecedents Mediation Results MacMillan et al. (2005) Termination costs Communication Material benefits Shared Values Opportunistic behaviour Commitment Trust Reinhard (2012) Termination costs Communication Material benefits Shared values Opportunistic behaviour Commitment Trust Sanzo et al. (2014) Shared values Conflict Reputation damage risk Perceived benefits Communication Trust Commitment Learning Internal marketing Funding Technology Scale of operations Visibility Mission accomplishment Source: The authors. and satisfaction (De Wulf et al., 2001; Woo and Ennew, 2004). In view of the divergence in the literature, in 2006, Palmatier et al. conducted a meta-analysis aimed at testing empirically the relative effects on performance of commitment, trust, satisfaction, and the relationship quality. Their results indicated that the greatest influence corresponded to the constructs ‘‘relationship quality’’ and, to a lesser extent, ‘‘commitment’’. This supported a multidimensional perspective of the relationship in which a single mediator, whether commitment, trust, or satisfaction, could not by itself capture the full essence of a relationship. More than one construct of relational mediation had therefore to be included. In order to gain further insight into the main mediating constructs of successful interfirm exchanges, in 2007, Palmatier, Dant and Grewal compared CommitmentTrust Theory with another three dominant theories at that time --- Dependence Theory, Transaction Cost Theory, and Relational Norms Theory. The results of their empirical study showed that the ‘‘commitment-trust’’ binomial indeed played a key role in explaining successful interfirm exchanges. Given the relative scarcity of studies based on Relationship Marketing Theory in the specific field of the present work, and the importance of Commitment-Trust Theory in all types of exchanges that have been analysed, it was considered appropriate to take the model of Morgan and Hunt (1994) as the basis on which to construct our model of relationship success. Since Morgan amd Hunt’s model was initially proposed for an interfirm context, we adapted it to the present study’s context by taking into account the Relationship Marketing literature and the studies on Cross-Sector Social Alliances (see Fig. 1). As can be seen, success of business-NGO partnership processes could depend, directly or indirectly, on seven key variables. The literature on business-NGO partnership processes has enormously mentioned the importance of these variables in the success of such partnership processes: Table 3 Key variables mentioned in the Relationship Marketing literature on exchanges between businesses and other NPOs. Authors Antecedents Mediation Results Plewa and Quester (2006) Participation Trust Commitment Satisfaction Plewa and Quester (2007) Organizational compatibility Personal experience Trust Commitment Integration Satisfaction Intention to renew Plewa and Quester (2008) Participation Experience Trust Commitment Satisfaction Navarro et al. (2009) Satisfaction of firms Commitment by firms Perceived Commitment by universities Participation Frasquet et al. (2012) Communication Trust Satisfaction Functional conflict Commitment Collaboration Source: The authors. 192 M.J. Barroso-Méndez et al. Shared values Trust Relationship learning Cooperation Functional Conflict Commitment Opportunistic behaviour Relational factors Relational success Figure 1 A success model business-NGO partnership processes. Note: The solid arrows indicate direct positive relationships and the dashed arrow direct negative relationships between the given pair of variables. Source: Adapted from Morgan and Hunt (1994). • Opportunistic Behaviour (Das and Teng, 2000; Rondinelli and London, 2003; Graf and Rothlauf, 2012). According to these authors, successful collaboration processes are characterized by the absence of opportunistic behaviour, i.e., the absence of behaviours by partners seeking to maximize their own interests to the detriment of others. • Shared Values (Bryson et al., 2006; Austin and Seitanidi, 2012b; Gray and Stites, 2013). Following these authors, the identification of values that are shared among the partners, for example, expressed through the initial articulation of the social problem that affects both partners, are a key for the avoidance of the appearance of conflict, and therefore to ensure the success of the partnership processes. • Commitment (Rondinelli and London, 2003; Berger et al., 2004; Seitanidi, 2010; Jamali et al., 2011; Graf and Rothlauf, 2012). The partners’ full and active commitment to the objectives set out in the partnership process is a key factor for success in achieving mutual benefits and added value. • Trust (Berger et al., 2004; Bryson et al., 2006; Yaziji and Doh, 2009; Wilson et al., 2010; Dahan et al., 2010; RiveraSantos and Rufín, 2010; Jamali et al., 2011; McDonald and Young, 2012; Graf and Rothlauf, 2012; Gray and Stites, 2013). Trust between the partners is transcendental throughout the partnership process (Berger et al., 2004). According to Bryson et al. (2006), trust is like the glue holding any collaboration together, facilitating working together and sustaining the alliance over time. • Learning Together (Austin, 2000; Rondinelli and London, 2003; Senge et al., 2006). These authors observe that the partners’ learning together about the partnership process (Austin, 2000), which only takes place in a climate of respect, trust, and openness (Senge et al., 2006), is fuelled by their desire to generate more value in the partnership. • Cooperation (Austin, 2000; Wilson et al., 2010). According to Wilson et al. (2010), cooperation allows resources to be combined efficiently in working towards the partnership’s objectives. Cooperation is thus a key enabler of the success of social alliances (Wilson et al., 2010). • Functional Conflict (Seitanidi, 2010; Gray and Stites, 2013). According to these authors, in spite of the fact that in these types of collaborations, conflicts may arise due to the presence of different values among partners, their amicable management is not only a key to the success of the partnership processes, but may also lead to the partners being able to take advantage of those differences. Therefore, the following were the main changes that were made to the initial model of Morgan and Hunt (1994): • Addition of new constructs. Due to its importance in the context of the present study, it was considered advisable to incorporate the construct ‘‘relationship learning’’ as a result of the Commitment-Trust binomial (Selnes and Sallis, 2003; Ling-Yee, 2006). It comprises three sub-processes: exchange of information, common interpretation of the shared information, and integration of knowledge. • Elimination of constructs. Firstly, due to their lack of relevance to the context of the present study, it was considered appropriate to eliminate the following constructs from consideration: relationship termination costs, acquiescence, propensity to leave, and uncertainty in decision making. And secondly, incompatibilities with the new constructs that we had included led us to consider it necessary to exclude the following two constructs: the benefits of the relationship (already considered, albeit with another nomenclature, in the ‘‘success’’ construct of these processes of partnership) and communication (already considered in the model as an element of ‘‘relationship learning’’, specifically in one of its subprocesses --- exchange of information). Meta-analytic study of the proposed model Methodological development At a time characterized by the expansion of scientific production in all areas of research, ‘‘literature reviews’’ have Social alliances and relationship marketing 193 become the indispensable link connecting the scientific work of the past with that of the future (Sánchez-Meca, 1999). Traditionally, these literature reviews have been characterized by a lack of any systematic approach to the decision-making they involve, by the presence of errors of interpretation, or by subjectivity throughout the process of their development (García and Brás, 2008). In response to this common practice, recent years have seen metaanalyses gaining great prominence as a new methodological approach with which to endow literature reviews with the rigour, objectivity, and systematization necessary to fruitfully gather together the scientific knowledge generated up to that time (Sánchez-Meca, 1999). Therefore, meta-analyses have become established as key methodological tools to quantitatively integrate research findings of a large number of primary studies (Geyskens et al., 2009). By combining the results of these studies into a single estimate, meta-analyses, beyond overcoming difficulties associated with such primary studies, such as sampling error or measurement error, enable an analyst to test hypotheses that were not testable in these studies (Eden, 2002), and thus arrive at more accurate conclusions (Hunter and Schmidt, 2004). Every meta-analysis involves a necessary series of steps (Sánchez-Meca et al., 2013): • Formulation of the problem. First, the object of inquiry must be clearly delimited. This is generally the magnitude of some relationship between two variables or concepts (Sánchez-Meca, 2008). • Literature search. Second, the studies to include in the meta-analysis must be located. To this end, it is necessary to specify a set of search criteria that these studies have to meet, for instance, the time range during which they were carried out. • Coding of studies. Third, for each study, the attributes that could affect the results of the meta-analysis need to be extracted. • Choice of effect size metric. Fourth, it is necessary to define the size of the effect, by means of a quantitative metric reporting the magnitude of the relationship found in each study (Sánchez-Meca, 2008). • Statistical analysis and interpretation. Fifth, techniques of statistical analysis are applied that are specifically designed to process this type of data. • Publication. And sixth, the results need to be disseminated. The set of hypotheses that appear in the proposed success model of the present work were subjected to a metaanalysis following the above series of steps. Search process and coding of studies The key impetus for Relationship Marketing research was Dwyer et al. (1987) seminal article (Palmatier et al., 2006). Therefore, we performed a search for empirical articles on the relationships posited in our success model proposal spanning the time period of 1987---2012. Moreover, the search process involved several choices, which we outline below. The first choice made was to include only published journal articles, thereby excluding book chapters or unpublished work. Journal articles have been through a review process that acts as a screen for quality, allowing us to include works meeting a certain level of conceptual and methodological rigour (David and Han, 2004; Newbert, 2007). The second choice made was to use both the ABI/Inform Complete and Academic Search Complete databases as search tools. The reasons were their extensive full-text coverage of academic journals, and their multidisciplinary nature. This latter aspect allowed searches to be made in multiple fields at the same time, including the field of Marketing, the object of the present study. Our next task was to select a sample of articles from over 1 million articles compiled in these databases. The following search process was followed: the selected articles had to include the names of the variables in question1in the title, abstract, or keywords; and the name of the theory (‘‘relationship marketing’’) in any field. In this regard, it should be highlighted, that if the number of articles retrieved from the database in question was high (>100), two additional filters would be applied: (1) since we were taking ‘‘business-business’’ relationship variables and analysing their links in ‘‘business-NPO’’ relationships, the articles had to be framed in a ‘‘business-business’’ or ‘‘business-NPO’’ context; and (2) the articles had to be empirical, since otherwise we would be unable to perform the necessary calculations for the meta-analysis. For each relationship, the articles which passed this set of filters were then examined. This reading allowed us on the one hand to eliminate those articles which were irrelevant for the objectives of the present study (articles in which the variables in question were encompassed in other more general constructs, or were related by means of indirect links), and, on the other, by following citations-to and citationsfrom, incorporating new articles into the present study’s database. The result was a set of 76 valid articles (Table 4). From these, it was possible to evaluate a total of 121 estimated effect sizes.2The number of estimated effect sizes per relationship was similar to those obtained in other metaanalyses in the field of Relationship Marketing Theory (see Palmatier et al., 2006). The data of the final 76 articles were input into an Excel spreadsheet with the following settings: (1) author; (2) year; (3) publication; (4) type of relationship (‘‘business-business’’ or ‘‘business-NPO’’); and (5) statistical techniques used. Choice of the effect size metric As the principal effect size metric, we shall use the correlation coefficient r. This is because it is the commonest 1In line with other authors who have conducted meta-analyses (Palmatier et al., 2006; Arenas and García, 2006), for some variables we included alternative names mentioned in the literature: • Shared Values/Similarity/Compatibility. • Cooperation/Coordination/Joint Action*. • Success/Performance/Satisfaction/Attainment of goal*/Fulfillment of objective*/Outcomes. 2In line with other meta-analytic studies (Geyskens, Steenkamp and Kumar, 1998; Palmatier et al., 2006), when an article provided more than one estimated effect size for the same link and the same sample, we used their mean value. When the effect sizes were independent, however (i.e., from different samples), they were included as separate data. 194 M.J. Barroso-Méndez et al. Table 4 Articles included in the meta-analysis. Authors Year Journal Relationship Type Afonso et al. 2011 Journal of Business and Industrial Marketing ‘‘Business-business’’ Anderson and Narus 1990 Journal of Marketing ‘‘Business-business’’ Armstrong and Yee 2001 Journal of International Marketing ‘‘Business-business’’ Barnes et al. 2011 Industrial Marketing Management ‘‘Business-business’’ Barnes et al. 2010 Journal of International Marketing ‘‘Business-business’’ Bordonaba and Polo 2008 Journal of Strategic Marketing ‘‘Business-business’’ Bordonaba and Polo 2008 Journal of Marketing Channels ‘‘Business-business’’ Brencic et al. 2008 Nase Gospodarstvo ‘‘Business-business’’ Bühler et al. 2007 International Journal of Sports Marketing and Sponsorship ‘‘Business-business’’ Burkert et al. 2012 Industrial Marketing Management ‘‘Business-business’’ Cater and Cater 2009 The Service Industries Journal ‘‘Business-business’’ Chadwick and Thwaites 2006 International Journal of Sports Marketing and Sponsorship ‘‘Business-business’’ Chang and Gotcher 2008 International Journal Technology Management ‘‘Business-business’’ Chen et al. 2008 Supply Chain Management: An International Journal ‘‘Business-business’’ Chen et al. 2009 Journal of Relationship Marketing ‘‘Business-business’’ Chenet et al. 2010 Journal of Services Marketing ‘‘Business-business’’ Chumpitaz and Paparoidamis 2007 European Journal of Marketing ‘‘Business-business’’ Costa et al. 2012 International Business Review ‘‘Business-business’’ Coulter and Coulter 2002 The Journal of Services Marketing ‘‘Business-business’’ Doney et al. 2007 European Journal of Marketing ‘‘Business-business’’ Duarte and Davies 2004 Journal of Marketing Channels ‘‘Business-business’’ Duhan and Sandvik 2009 International Journal of Advertising ‘‘Business-business’’ Eckerd and Hill 2012 International Journal of Operations and Production Management ‘‘Business-business’’ Eng 2006 Industrial Marketing Management ‘‘Business-business’’ Eser 2012 International Journal of Contemporary Hospitality Management ‘‘Business-business’’ Farrelly and Quester 2003 European Journal of Marketing ‘‘Business-business’’ Frasquet et al. 2012 High Education ‘‘Business-NPO’’ Gil-Saura et al. 2009 Industrial Management and Data Systems ‘‘Business-business’’ Giunipero et al. 2012 Journal of Marketing Theory and Practice ‘‘Business-business’’ Ha 2010 Asian Business and Management ‘‘Business-business’’ Huang and Chang 2008 Journal of Intellectual Capital ‘‘Business-business’’ Jap 1999 Journal of Marketing Research ‘‘Business-business’’ Jap and Ganesan 2000 Journal of Marketing Research ‘‘Business-business’’ Jean and Sinkovics 2010 International Marketing Review ‘‘Business-business’’ Jean et al. 2010 Journal of International Marketing ‘‘Business-business’’ Jena et al. 2011 Journal of Indian Business Research ‘‘Business-business’’ Johnson et al. 1996 Journal of International Business Studies ‘‘Business-business’’ Joshi 2012 Journal of Marketing ‘‘Business-business’’ Joshi and Stump 1999 Academy of Marketing Science ‘‘Business-business’’ Kim et al. 2009 Journal of Business and Industrial Marketing ‘‘Business-business’’ Lancastre and Lages 2006 Industrial Marketing Management ‘‘Business-business’’ Levy et al. 2009 International Advances in Economic Research ‘‘Business-business’’ Ling-Yee 2006 Industrial Marketing Management ‘‘Business-business’’ Ling-Yee 2007 Journal of Marketing Channels ‘‘Business-business’’ MacMillan et al. 2005 Journal of Business Research ‘‘Business-NPO’’ Morgan and Hunt 1994 Journal of Marketing ‘‘Business-business’’ Nicholson et al. 2001 Journal of the Academy of Marketing Science ‘‘Business-business’’ Palmatier et al. 2007 Journal of Marketing ‘‘Business-business’’ Palmatier et al. 2007 Journal of Marketing ‘‘Business-business’’ Payan 2006 The Marketing Management Journal ‘‘Business-business’’ Payan and Svensson 2007 Journal of Marketing Management ‘‘Business-business’’ Pesämaa and Franklin 2007 Management Decision ‘‘Business-business’’ Pimentel et al. 2006 Supply Chain Management: An International Journal ‘‘Business-business’’ Plewa 2009 Australasiam Marketing Journal ‘‘Business-NPO’’ Plewa and Quester 2007 Journal of Services Marketing ‘‘Business-NPO’’ Racela et al. 2007 International Marketing Review ‘‘Business-business’’ Rindfleisch 2000 Marketing Letters ‘‘Business-business’’ Social alliances and relationship marketing 195 Table 4 (Continued) Authors Year Journal Relationship Type Ruiz and Gil 2012 Journal of Business-to-Business Marketing, ‘‘Business-business’’ Ryssel et al. 2004 The Journal of Business and Industrial Marketing ‘‘Business-business’’ Salciuviene et al. 2011 Baltic Journal of Management ‘‘Business-business’’ Sang and Hyung 2008 Industrial Marketing Management ‘‘Business-business’’ Sarkar et al. 2001 Journal of the Academy of Marketing Science ‘‘Business-business’’ Selnes and Sallis 2003 Journal of Marketing ‘‘Business-business’’ Sichtmann and Von Selasinsky 2010 Journal of International Marketing ‘‘Business-business’’ Siguaw et al. 1998 Journal of Marketing ‘‘Business-business’’ Skarmeas et al. 2002 Journal of International Business Studies ‘‘Business-business’’ Smith and Barclay 1999 Journal of Personal Selling and Sales Management ‘‘Business-business’’ Theron et al. 2008 Journal of Marketing Management ‘‘Business-business’’ Ulaga and Eggert 2006 European Journal of Marketing ‘‘Business-business’’ Walter and Ritter 2003 The Journal of Business and Industrial Marketing ‘‘Business-business’’ Wiley et al. 2005 Australasian Marketing Journal ‘‘Business-business’’ Wong et al. 2008 Journal of Services Marketing ‘‘Business-business’’ Yang and Lai 2012 Journal of Business Research ‘‘Business-business’’ Zabkar and Makovec 2004 International Marketing Review ‘‘Business-business’’ Zhao and Wang 2011 Journal of Strategic Marketing ‘‘Business-business’’ Zineldin and Jonsson 2000 The TQM Magazine ‘‘Business-business’’ Source: The authors. metric used both in the articles analysed (>75%)3and in previous meta-analyses in the marketing field (see Palmatier et al., 2006; Augusto and Vargas, 2008). In this sense, for the articles which did not directly provide correlation coefficients, but coefficients from regression or structural equation models, we followed the steps recommended by other authors (Peterson and Brown, 2005; Bowman, 2012). First, Bowman (2012) recommends converting the adjusted standardized beta coefficients (which appear in structural equation models), to unadjusted standardized beta coefficients (which appear in regression models) using the following formula: ˇunadjusted = ˇadjusted(√rXX · rYY ) (1) where ˇunadjusted is the unadjusted standardized beta coefficient, ˇadjusted is the adjusted standardized beta coefficient (which appears in the structural equation model), rXX is the internal reliability of the relevant independent variable, and rYY is the internal reliability of the dependent variable. Second, Peterson and Brown (2005) suggest transforming the standardized regression (beta) coefficients into correlation coefficients using the following equation: r = 0.98ˇ + 0.05 (2) where  is an indicator variable that equals 1 when ˇ is nonnegative and 0 when ˇ is negative. The use of the proposed formula is restricted to values of ˇ between −0.5 and +0.5. To check that the mean levels of correlation were the same for the two groups (the studies that provided correlation directly, and the studies whose correlations were obtained indirectly from their standardized regression 3The authors of articles which did not provide correlation matrices were contacted by e-mail, requesting that information. coefficients), a t-test assuming equal variances was applied. The results confirmed that there were no significant differences between the two groups for the links in question at a significance level of 5%. Statistical analysis The literature on methods of meta-analysis allows the researcher various options. In the present case, we considered it appropriate to follow the procedure of Hunter and Schmidt (1990) as perfectly described by Sánchez-Meca (1999). Firstly, we calculated the weighted mean of the empirical correlations using Eq. (3) below, and then the observed total variance of the empirical correlations using Eq. (4). Since the studies used in the meta-analysis had sampling and measurement errors, we also calculated the sampling error variance using Eq. (5) (Hunter and Schmidt, 1990). ¯ r =Niri Ni (3) S2 r=Ni(ri−¯ r)2 Ni (4) S2 e=(1 −¯ r2)2 ¯ N − 1(5) where Niis the sample size of the ith study, riis the empirical correlation of the ith study, ¯ ris a weighted mean of the empirical correlations, and ¯ N is the mean sample size (¯ N = Ni/k where k is the number of studies). 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