Value creation and appropriation in buyer-suppliers relationships

• Grant number: 11/11223-5
• Support type: Regular Research Grants
• Duration: October 01, 2011 - September 30, 2013
• Field of knowledge: Applied Social Sciences - Administration - Business Administration
• Principal researcher: Luiz Artur Ledur Brito
• Grantee: Luiz Artur Ledur Brito
• Home Institution: Escola de Administração de Empresas (EAESP). Fundação Getúlio Vargas (FGV). São Paulo , SP, Brazil
• Assoc. researchers: Aline Rodrigues Fernandes ; Fábio Viard de Campos da Silva Tescari ; Janaina Siegler Marques Batista ; Priscila Laczynski de Souza Miguel

Abstract

The study of buyer-suppliers relationships is one of the traditional areas of Operations Management. This literature posits that these relationships can generate benefits and even competitive advantage for the firms involved. Despite its traditional characteristic, there are still challenges and gaps related to the nature of these benefits, their measurement and the processes, mechanisms and theories used to explain them. This research proposal intends to contribute to the field by identifying and measuring the value created by cooperative relationships, examining how it is appropriated by the parties and its impact on financial performance. The Relational View of Strategy and Transaction Cost Theory will be the theoretical foundation of the investigation. The proposal intends to integrate these theoretical approaches with the notion of value created (defined as the wedge between the willingness-to-pay of the customers and the opportunity cost of suppliers). This notion of value created been used as the conceptual basis for an emerging definition competitive advantage in Strategic Management and constitutes one of the main contributions of the proposal in the field of Operations Management. Methodological approach will use both qualitative and quantitative methods, through case studies and surveys. The qualitative data will be analyzed through the content analysis technique and quantitative data will be analyzed using structural equation and other multivariate techniques. (AU)