Research Methodology in Strategy and Management: Volume 2

Welcome to the second volume of Research Methodology in Strategy and Management. This book series’ mission is to provide a forum for critique, commentary, and discussion about key research methodology issues in the strategic management field. Strategic management relies on an array of complex methods drawn from various allied disciplines to examine how managers attempt to lead their firms toward success. The field is undergoing a rapid transformation in methodological rigor, and researchers face many new challenges about how to conduct their research and in understanding the implications that are associated with their research choices. For example, as the field progresses, what new methodologies might be best suited for testing the developments in thinking and theorizing? Many long-standing issues remain unresolved as well. What methodological challenges persist as we consider those matters? This book series seeks to bridge the gap between what researchers know and what they need to know about methodology. We seek to provide wisdom, insight, and guidance from some of the best methodologists inside and outside the strategic management field.

While strategy scholars once thought that the resource-based view could not be tested directly by observing resources, recent work has dispelled this notion. While resources are difficult to measure, many clever scholars have been able to measure resource heterogeneity and performance.

Good research goes beyond testing the aggregate predictions of a theory to test the theory's underlying mechanism. A mechanism is a plausible account of the process that causes a systematic relationship between variables. Strategy researchers particularly need to understand the mechanisms that drive firm behavior and outcomes because we seek both to explain and offer prescriptions. We recommend that theories clearly specify their mechanisms and that empirical research test such mechanisms. Such tests will help differentiate among theories with similar aggregate predictions.

Meta-analysis has been relied on relatively infrequently in strategic management studies, certainly as compared to other fields such as the medical sciences, psychology, and education. This may be unfortunate, as there are several aspects of the manner in which strategic management studies are typically conducted that make them especially appropriate for this approach. To this end, we provide a brief foundation for meta-analysis, an example of meta-analysis, and a discussion of those elements that strongly recommend the efficacy of meta-analysis for the synthesis of strategic management studies.

Research on strategic industry groups provides numerous examples of the tensions between theory and methodology in strategic management research. After an initial explosion of largely non-theoretical, methods-driven studies led to mounting criticisms, researchers recognized the need for more theoretical guidance concerning the nature of groups and their potential influences on firm performance. This refocusing on theory has produced different research streams, each with its own methodological concerns. This chapter reviews these developments with the objective of understanding how researchers balance theory and methods in current research.

I am interested in clarifying the discussion of how researchers might try to isolate real option effects to identify whether managerial decisions are guided by a real option heuristic. If we are to claim that the theory of real options illuminates managerial behavior, then as a field, we must converge on an understanding as to what constitutes a real option effect, and what does not. The discussion centers on hypothesis development, measurement issues, and research methodology.

Entrepreneurship remains a young scholarly discipline characterized by low paradigmatic development. Herein, we discuss theoretical and methodological issues associated with this rapidly emerging yet still developing research area. We argue that theory and methodology are symbiotic components of research and should develop concurrently in order to support the evolution of a paradigm for entrepreneurship research. Further, we posit that effective growth of entrepreneurship research will occur as a result of appropriately extending theory and methods from other scholarly disciplines as well as from theoretical and methodological innovations that are unique to entrepreneurship. Based on the positions taken in this chapter, we also advance recommendations for scholars to consider as work is completed to develop a systematic body of knowledge about entrepreneurship.

This chapter highlights the personal side of research methods. We begin with an overview of Hans-Georg Gadamer's insights into the general problem of method in the social sciences and hermeneutics. This is followed by an overview of Michael Polanyi's explanation of the practice of scientific investigation. The second half of the chapter considers implications of the personal side of methods for how we conduct management research. This section discusses critical realism as a philosophy of science consistent with the assumptions of our field, the reasons for methodological pluralism and possible responses, and management research as a social practice.

Given the ubiquity of Internet access in the business world, the question for strategy researchers is no longer over whether or not Internet surveys are viable, but rather over the comparative advantages and disadvantages of this modality. To address this question, we provide guidelines for researchers to help minimize the challenges while still reaping the benefits. We begin by first defining Internet survey modalities and some of their benefits, and then we focus on the associated sampling challenges and often ways that strategy researchers can address them. To further assist researchers in using this survey modality, we present a comparison of some software packages that might be useful, followed by a discussion of the lessons that we have learned from our own use of Internet surveys.

The purpose of this chapter is to offer a discussion of the key issues in mixed-level, multi-theoretical research in strategic management. Mixed-level issues are grouped into two categories: (1) measurement of constructs, with discussion of situations in which the level of theory, level of measurement, and level of analysis differ; and (2) relationships among constructs, including cross-level and multilevel models. Key theories and views found in the strategic management literature are discussed briefly to illustrate the basic arguments of each, its focal unit of analysis, and the implicit or explicit incorporation of mixed-level perspectives.

Our primary objective is to provide method-related broad guidelines to researchers on the entire spectrum of issues involved in cause mapping and to encourage researchers to use causal mapping techniques in strategy research. We challenge strategists to open the black box and investigate the mental models that depict the cause and effect beliefs of managers, “walk” readers through the causal mapping process by discussing the “nuts and bolts” of cause mapping, provide an illustration, and outline “key issues to consider.” We conclude with a discussion of some promising research directions.

Organizational performance is widely recognized as an important – if not the most important – construct in strategic management research. Researchers also agree that organizational performance is a multidimensional construct. However, the research implications of the construct's multidimensionality are less understood. In this chapter, we use a synthesis of previous attempts to describe the dimensions of performance and our own analysis of performance measurement in the Strategic Management Journal to build a conceptual model of organizational performance and its dimensions. Our model suggests that operational performance and organizational performance are distinct, and that organizational performance can be further dimensionalized into accounting returns, stock market, and growth measures. The model has implications for how future research might advance understanding about performance and how empirical studies should conceptualize and measure performance.