Research Methodology in Strategy and Management: Volume 4

Table of contents

(15 chapters)
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Introduction

Pages xi-xiii

Welcome to the fourth volume of Research Methodology in Strategy and Management (RMSM). The publication of our fourth volume provides a source of satisfaction because our original contract with Elsevier only guaranteed a three volume run for the series. The popularity of RMSM led our contacts at the publisher to be eager to continue beyond their original commitment. We are excited about the future of the series, and have begun assembling Volume 5.

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While research related to the resource-based view (RBV) has expanded markedly in the last decade, debates continue over the theory, the extent to which our understanding of the theory has been advanced in a meaningful way, and the most appropriate approaches for empirical RBV research. We present some additional perspectives on current debates, summarize key challenges that empirical studies face, and offer some suggestions and directions for future RBV research.

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We argue that resource-based view (RBV) researchers must take into account three interdependencies, (i) intrafirm resource complementarity, (ii) interfirm resource complementarity or rivalry, and (iii) compatibility or incompatibility of firm resources to broader socio-economic institutions, when attempting to empirically verify the RBV. However, these interdependencies lead to three potential causes of statistical bias, which can reduce the interpretability of such empirical examinations. First, omitted variable bias results from a researcher's inability to find and include in empirical analyses appropriate operationalizations of constructs. Second, selection bias can arise when a researcher samples only from one subset of the population, and not others. Bias in estimates can occur if a correlation between unobserved determinants of the outcome and factors affecting the selection process exist. Finally, joint dependence, where two explanatory variables are themselves mutual determinants, can lead to biased estimation.

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This chapter focuses on the empirical research on the resource-based view of the firm (RBV), and its main purpose is to analyse the use of mixed methods in this perspective. The recent advance of the RBV has posed new challenges, and the issue need not be quantitative versus qualitative methods, but rather how to combine the strengths of each in a mixed methods approach. This study carries out a literature review about the use of mixed methods in the RBV and provides an examination of opportunities and challenges associated with the application of mixed methods in order to improve RBV research. Moreover, the chapter seeks to introduce mixed methods research in order to familiarize to strategic management and the RBV scholars about this type of research and its terminology, procedures, designs and purposes.

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The resource-based view (RBV) of the firm focuses on how firm-level assets and capabilities influence firm performance. Scholars have noted the need for studies grounded in the RBV to account for the role of the strategic group level, but uncertainty remains about how to do so. Random coefficients modeling (RCM) provide an appropriate technique to integrate these two levels of analysis, but its use has been limited in strategic management research to date. I review research integrating firm and strategic group levels and provide a roadmap for future research seeking to integrate these two levels’ influences on firm performance, and use RCM to illustrate the effects of firm resources on performance under three depictions of the strategic group level culled from strategic management research. Findings suggest that interpretations about the efficacy of resources’ influence on performance vary considerably across methodological specification. Next, I use RCM to illustrate how strategic management researchers can further integrate the firm and group levels by demonstrating how variables at the group level of analysis may interact with firm-level characteristics. I conclude with suggestions for future research using RCM to integrate the strategic group into multilevel studies predicting firm performance.

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Strategy deals with decisions about the scope of the firm and related choices about how to compete in various businesses. As such, research in strategy entails the analysis of discrete choices that may not be independent of each other. In this paper, we review the methodological implications of modeling such choices and propose conditional, nested, mixed logit, and hazard rate models as solutions to the issues that arise from non-independence among strategic choices. We describe applications with an emphasis on international strategy, an area where firms face a multiplicity of choices with respect to both location and mode of entry.

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Emerging thoughts and models in strategic management increasingly involve complex hypotheses at different levels of analysis and multiple sides of relationships. Such complexities often result in less than ideal empirical testing, with the ensuing implications being limited or sometimes even wrong. One such case is global relationship management (GRM). The effective implementation of GRM has been argued to be a principal source of a firm's value creation but the testing of GRM scenarios have been very limited. Using GRM as a case example, we introduce a new methodology to the strategic management literature that alleviates many of the limitations of existing techniques – static triangulation simulation (STS). A series of GRM hypotheses are briefly introduced and then tested via the STS technique. Starting values for the simulation, based on input from companies, are included from two sides of each GRM relationship (customer and supplier) and two levels (company and account) from each side. Such elaborate testing is typically not feasible via “normal” methodology – the STS technique, however, allows for a robust assessment of the different drivers that affect GRM outcomes.

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International business research has long acknowledged the importance of regional factors for foreign direct investment (FDI) by multinational corporations (MNCs). However, significant differences when defining these regions obscure the analysis about how and why regions matter. In response, we develop and empirically document support for a framework to evaluate alternative regional grouping schemes. We demonstrate application of this evaluative framework using data on the global location decisions by US-based MNCs from 1980 to 2000 and two alternative regional grouping schemes. We conclude with discussion of implications for future academic research related to understanding the impact of country groupings on MNC FDI decisions.

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This chapter describes how to use popular software programs (Hierarchical Linear Modeling, LISREL) to analyze multiwave panel data. We review prevailing methods for panel data analyzes in strategic management research and identify their limitations. Then, we explain how multilevel and latent growth modeling provide more rigorous methodologies for studying dynamic phenomena. We present an example illustrating how firm performance can initiate temporal change in the human and social capital of members of Board of Directors, using hierarchical linear modeling. With the same data set, we replicate this test with first-order factor latent growth modeling (LGM). Next, we explain how to use second-order factor LGM with panel data on employee cognitions. Finally, we review the relative advantages and disadvantages of these new data-analytical approaches.

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As a field, we should put more emphasis on interpreting the magnitude of coefficient estimates rather than only assessing statistical significance. To support this claim, I demonstrate how focusing only on statistical significance can lead to incorrect and incomplete conclusions in many common applications of the linear regression model. Moreover, I demonstrate why interpreting coefficient estimates in common non-linear estimators (e.g., probit, logit, Poisson, and negative binomial estimators) requires additional care compared to the linear regression model.

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Mediating effects allow strategic management researchers to understand “black box” processes underlying complex relationships whereby the effect of an independent variable is transmitted to a dependent variable through a third variable. Since the seminal work of Baron and Kenny (1986), advancements have been made in mediation analysis. Thus, literature on the latest techniques for analyzing mediating and intervening varibales is presented. In addition, strategy literature published in the Academy of Management Journal and the Strategic Management Journal between 1986 and 2005 employing tests of mediation is reviewed to better understand how mediation techniques are used by strategy scholars. Finally, implications and limitations of current mediation analysis in strategy research are discussed, and recommendations are provided to strategy scholars examining mediation.

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This chapter outlines purpose, procedure, benefits and limitations of the policy capturing methodology. It further presents an example of use of the methodology.

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This article classifies empirical research on vertical integration under four approaches – value-added-to-sales, qualitative–quantitative, input–output, and microanalytic. The emphasis here is on the microanalytic approach which has accumulated the most systematic evidence to support its theoretical propositions. In particular, this article emphasizes theoretical and empirical contributions from organizational economics (especially transaction costs and agency theories) for both vertical integration and (vertical) contracting. Limitations and methodological challenges concerning the empirical testing of theories of vertical integration are addressed and suggestions for further research are provided.

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The double challenge of strategic management research is to come up on the one hand with a truthful account of issues relating to the organization itself and on the other hand doing so in a way that is relevant for meeting the challenges of strategic management. To achieve this need for increased rigour and relevance we follow Heidegger's thinking and develop an ontological ascertainment of the organization as being a work. A work in this sense is the kind of entity that is fundamentally characterized by setting up a world for people. We then argue that because an organization is a work, an appropriate way of giving an account of an organization is in the form of strategic narratives: narratives that give a truthful account of the world of an organization as it is and as it could be. Since narratives play a fundamental role in human existence and are a powerful means to shaping peoples thinking and actions, we argue that strategic narrative research and development meet the double challenge of strategic management research and illustrate the application with an account of strategic narrative research and development in an organization.

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DOI
10.1016/S1479-8387(2007)4
Publication date
Book series
Research Methodology in Strategy and Management
Editors
Series copyright holder
Emerald Publishing Limited
ISBN
978-0-7623-1404-1
Book series ISSN
1479-8387