Criação e apropriação de valor em relacionamentos entre empresas compradoras e fornecedores

• Ano de defesa: 2012
• Autor(a) principal: Miguel, Priscila Laczynski de Souza
• Orientador(a): Brito, Luiz Artur Ledur
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Díades empresas compradora-fornecedor; Criação de valor econômico; Métodos mistos
• Palavras-chave em Inglês: Buyer-supplier relationship; Value creation; Mixed methods
• Link de acesso: https://hdl.handle.net/10438/9506

This research aimed to study how value is created in a buyer-supplier relationship, investigating how governance mechanisms impact value creation, how this phenomenon occurs over time and testing if the model derived from the notion of economic value creation (BRANDENBURGER; STUART, 1996) can be used to measure value creation in dyads. We also tested the impact of the relational sources of competitive advantage (DYER; SINGH, 1998) on the value creation for the organizations involved. By integrating the literature on relationships in the Operations and Supply Chain field with the debate on value creation and competitive advantage in the areas of Strategy and Marketing, an integrative model to assess value creation in relationships and their development over time was proposed, based on three important theories: Transaction Cost Theory, Relational View and Theory of Social Exchange. A deductive qualitative research (BARRAT; CHOI, 2011), with 28 executives responsible for the relationship in both suppliers and buyers’ companies, was performed in two industries: Food & Beverages and Personal Care. The results shown that, in these industries, suppliers are more supportive to collaboration that the buyers, but this commitment does not guarantee exclusivity or increased volumes. Relational governance mechanisms are more common in situations involving risks to companies and when there is size or power asymmetry. The qualitative research provided evidences that the model of economic value creation of Brandenburger and Stuart (1996) can be used to assess the value created in relationships, by considering the difference between willingness to pay of the buyer company and the opportunity cost of the supplier. Additionally, the results suggest that companies should assess the gains of the relationships in the long term, as gains are created in different time for buyers and suppliers. Finally, the qualitative stage identified three distinct types of value creation in dyads: situational or episodic, incremental and relational. At the same time, based on a survey with 76 suppliers, a model to evaluate the effect of the four sources of relational advantage on value creation was tested. The measurement models analysis suggested that the constructs of mechanisms of relational governance and resources complementarity resources should be grouped into a latent variable representing the intraorganizational fit (CHEUG; MYERS, Mentzer, 2010; Saxton, 1997). The measurement model for value creation, represented by five dimensions ( relationship benefits, benefits for the supplier, benefits for buyer, switching costs for the buyer company and opportunity costs for the supplier) had good fit and can be used in future research. Using the validated models and multiple linear regression, the causal relationships between the sources of the relational advantage and value creation were tested. The results provided evidence that different sources of relational advantage have different impact on different aspects of the value created. While inter-organizational fit has positive impact on both supplier and buyer benefits, knowledge sharing has a positive effect on the relationship benefit to the relationship. The asset specificity impact the opportunity cost to the supplier, while the switching cost of for the buyer is not affected by these mechanisms in this situation. A cluster analysis was performed and two distinct groups among the respondents were identified: relational dyads and non relational dyads. There are evidences that the first cluster has better performance than the second group.