Attractiveness in Business-to-Business MarketsConceptual Development and Empirical Investigation

  • Zsofia Toth

Student thesis: Phd


Attractiveness matters in business markets, because firms do not dedicate resources equally to all partners. Instead they invest more resources in partners with higher relational attractiveness. Firms need to become attractive in order to gain access to more resources or to be able to work with more skilled or reputable partners. This dissertation studies the construct of relational attractiveness of the customer (RAC), defined as the attractiveness of a business relationship with a particular customer in the eyes of the supplier. The research also investigates corporate online references (COR), because gaining powerful referrals is one of the driving forces behind creating attractiveness in business markets. The study is a three-stage research project drawing on an empirical investigation comprising two focus groups, 79 interviews, a survey of 107 suppliers and online referral data from 1002 companies. These studies investigate the conditions and configurations leading to high or low relational attractiveness, and the motivational conditions and structure of a specific corporate online referral network. Bearing in mind that attractiveness exists in the eyes of the beholder, Study I resolves the previously unclarified problem of how attractiveness can be achieved in different ways. Social Exchange Theory helps to identify conditions of RAC: Trust, Dependency, Financial, Non-Financial Rewards and Costs. In Study II conditions of Trust and Dependency are further developed into Relational Fit and the Comparison Level of Alternatives that address the mutuality and network perspectives of relationship development. The time perspective is introduced to the configurational analysis of RAC through the Maturity condition. As it is revealed in Study I and II, Nonfinancial Rewards are important in creating attractiveness and one of their essential forms is referrals that are addressed in more detail in Study III. This PhD research takes a configurational approach to attractiveness and explores different causal recipes in order to reach the same outcome. In order to investigate the relational complexity of attractiveness, fuzzy set Qualitative Comparative Analysis (fsQCA) is applied throughout the three studies combined with some other methods, such as content analysis and Social Network Analysis (SNA). QCA is a data analytic strategy that combines within-case analysis and formalised cross-case studies in order to identify multiple configurations leading to the same outcome. Hence, QCA deals more efficiently with the equifinality of complex business problems compared with traditional data analysis methods. Equifinality means that there are various ways in the causal system of achieving the desired outcome. QCA is sufficient in handling methodological challenges such as multi-causality (an outcome of interest rarely has a single cause), interrelatedness (causes are usually not independent of one another) and asymmetry (a specific cause may have different effects on the outcome depending on the context). By challenging existing knowledge, the results show that there is no one best way to achieve relational attractiveness. It is achievable even if Trust and Financial Rewards are not present. Very high RAC was typically achieved in less mature relationships. During the initiation of referral relationships in the case of COR, the expected increase in the initiators` attractiveness in the eyes of potential future partners also plays a vital role. The generalizability of the findings has some limitations, especially regarding the qualitative study where the results are appropriate to falsify some theories (for example, the primary importance of Financial Rewards) but their impact is more related to theoretical development than to statistical generalizability.
Date of Award1 Aug 2015
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorPeter Naude (Supervisor) & Stephan Henneberg (Supervisor)


  • online networks
  • Social Network Analysis
  • fuzzy set Qualitative Comparative Analysis
  • Word-of-Mouth
  • customer attractiveness
  • relational attractiveness
  • referral networks

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