Achieving Accuracy, Generalization-to-Contexts, and Complexity in Theories of Business-to-Business Decision Processes

Abstract

This article describes field research methods that provide advances in developing accurate theories of business-to-business (B2B) decision processes. The article supports and extends prior work by Woodside (2010) that bridging qualitative and quantitative research method is possible to achieve accuracy, complexity, and generality across cases in B2B decision processes. As an aid in doing so, the article argues for the study of a few (n = 5 to 50) cases via case study research (CSR). The article defines CSR, and describes several CSR theories and methods that are useful for describing, explaining, and forecasting processes occurring in business-to-business (B2B) contexts. The discussion includes summaries of six B2B case studies spanning more than 60 years of research. This article advocates embracing the view that isomorphic theory of realities of B2B processes is possible via advances in CSR methods. The discussion advocates rejecting the dominant logic of attempting to describe and explain B2B processes by arms-length fixed-point surveys that usually involve responses from one executive per firm with no data-matching of firms in specific B2B relationships—such surveys lack details and accuracy necessary for understanding, describing, and forecasting B2B processes.