Data analytic trends and training in strategic management

Data analysis is a key element of the research process. Accordingly, appropriate doctoral training in data analysis is vital to the strategic management field's future. We used a two‐study design to evaluate quantitative data analysis trends and doctoral training. An analysis of Strategic Management Journal articles from 1980 to 2001 reveals that, contrary to some predictions, the use of general linear model techniques such as regression has increased over time. However, the use of more specialized techniques, including those suitable for examining longitudinal data, discrete events, and causal structure, has also grown substantially. A survey of recent doctoral graduates shows that, although skilled with general linear models, many are ill prepared to use specialized techniques. Based on our findings, we offer suggestions aimed at bridging gaps between what doctoral students (and other researchers) know and what they need to know about data analysis. Copyright © 2003 John Wiley & Sons, Ltd.     

An assessment of the use of structural equation modeling in strategic management research

Structural equation modeling (SEM) is a powerful, yet complex, analytical technique. The use of SEM to examine strategic management phenomena has increased dramatically in recent years, suggesting that a critical evaluation of the technique's implementation is needed. We compared the use of SEM in 92 strategic management studies published in nine prominent journals from 1984 to 2002 to guidelines culled from methodological research. We found that the use and reporting of SEM often have been less than ideal, indicating that authors may be drawing erroneous conclusions about relationships among variables. Given these results, we offer suggestions for researchers on how to better deploy SEM within future inquiry. Copyright © 2004 John Wiley & Sons, Ltd.     

Models of causal inference: Imperfect but applicable is better than perfect but inapplicable

We assess a recent paper by Durand and Vaara (2009) that advances causal graph modeling as a tool for inferring causes in strategy research. We focus on the Markov condition, a key assumption on which causal graph modeling is based, and show why this condition is invariably violated in strategic management in general and the resource‐based view of the firm in particular. We then introduce vector space modeling as a quantitative alternative to causal graph modeling, and consider how improved methods of causal inference might enhance our ability to test some of the central propositions of the resource‐based view. Copyright © 2013 John Wiley & Sons, Ltd.     

The use of logit and probit models in strategic management research: Critical issues

The logit and probit models have become critical parts of the management researcher's analytical arsenal, growing rapidly from almost no use in the 1980s to appearing in 15% of all articles published in Strategic Management Journal in 2005. However, a review of three top strategy journals revealed numerous areas in their use and interpretation where current practice fell short of ideal. Failure to understand how these models differ from ordinary least squares can lead researchers to misunderstand their statistical results and draw incorrect conclusions regarding the theory they are testing. Based on a review of the methodological literature and recent empirical papers in three leading strategy journals, this paper identifies four critical issues in their use: interpreting coefficients, modeling interactions between variables, comparing coefficients between groups (e.g., foreign and domestic firms), and measures of model fit. For each issue, the paper provides a background, a review of current practice, and recommendations for best practice. A concluding section presents overall implications for the conduct of research with logit and probit models, which should assist both authors and readers of strategic management research. Copyright © 2007 John Wiley & Sons, Ltd.     

Institutional and Organizational Factors Affecting Effectiveness: Geoeconomic Comparison Between Shanghai and Beijing

This study aims at uncovering the geoeconomics of successful strategic management in subculturally diverse countries. The new theory of geoeconomics is defined as the study of geographic influences on economics and management. Using this theory to integrate the key success factor approach and resource-based view of the firm, the study examines geographical differences between two cities in the North and South of mainland China with respect to key factors leading to organizational effectiveness. It employs structural equation modeling to analyze survey data from 124 enterprises in the two most important cities of China, Beijing and Shanghai. Among the dozen factors integrated from different organizational domains, significant differences were found in the impact of government support (more important in the North) and company size (more important in the South). Other differences related to environmental constraints, ownership, leadership, and decision making corresponded to theoretical predictions but were not significant. As hypothesized, appropriate structure was equally important in both regions. Strategic orientation was not significant anywhere. To achieve high performance in China, practitioners must develop regionally adapted strategies, management techniques and performance control benchmarks, which fully consider and leverage the varying success factors in different subcultures. More generally, the results highlight the importance for researchers of strategy and organization to analyze regional differences that might be hidden at the aggregate data level.     

Does firm performance reveal its own causes? the role of Bayesian inference

A central problem in strategic management is how the inference ‘sustainable competitive advantage generates sustainable superior performance’ can be put into practice. In this article we develop a theoretical framework to understand the causal relationships among (1) sustainable competitive advantage, (2) configuration, (3) dynamic capability, and (4) sustainable superior performance. We propose that a firm's competitive advantage, resource bundle configuration, and dynamic learning capability cannot be comprehended by outsiders. Its operational performance, however, can be captured by financial indicators. We promote an inductive Bayesian interpretation of the sustainable competitive advantage proposition. From this viewpoint, the presence or absence of competitive advantage may be reflected in the causal relationship between resource configuration, dynamic capability, and observable financial performance. We apply this theoretical framework to an example drawn from the global semiconductor industry, an area in which resource configuration and dynamic capability are essential to performance. The paper concludes with a summary of the proposed model and suggestions for future theoretical development of strategic management. Copyright © 2009 John Wiley & Sons, Ltd.     

Retrospective reports of strategic-level managers: Guidelines for increasing their accuracy

Strategic management studies frequently involve obtaining retrospective data from strategic-level managers. The use of this data acquisition methodology has received relatively little codification and little critical review or comment. This seems unfortunate, as discussion and codification of the methodology could be useful for those academic researchers and corporate staff who study strategic decisions and organizational processes and for those managers who may be asked to provide the retrospective data. This paper is an attempt to remedy the current state of affairs. In particular, the paper reviews several sources of the data inaccuracies that commonly affect retrospective data and offers guidelines for reducing the occurrence or magnitude of these inaccuracies.     

Assessment and redirection of longitudinal analysis demonstration with a study of the diversification and divestiture relationship

The authors review the application of longitudinal analysis in strategic management research and show that how such analysis is conducted has implications for empirical results and theory development. A content analysis of 203 longitudinal strategic management studies reveals that most researchers have not (1) tested and controlled for violations in the data assumptions underlying longitudinal analysis or (2) tested the stability and form of the empirical relationships over time. Implications of these findings are demonstrated with analyses of the diversification and divestiture relationships of 180 Fortune 500 companies over the period 1985–88. The results show that empirical results, theoretical development, and practical applications can vary on the basis of how longitudinal analysis is performed. Suggestions for the use of longitudinal analysis in strategic management research are offered. © 1997 by John Wiley & Sons, Ltd.     

The relationship between corporate entrepreneurship and strategic management

This study examines the relationship between corporate entrepreneurship intensity and five specific strategic management practices in a sample of 169 U.S. manufacturing firms. The five strategic management practices include: scanning intensity, planning flexibility, planning horizon, locus of planning, and control attributes. The results of the study indicated a positive relationship between corporate entrepreneurship intensity and scanning intensity, planning flexibility, locus of planning, and strategic controls. The fine‐grained nature of these results may be of practical use to firms that are trying to become more entrepreneurial and may help researchers better understand the subtleties of the interface between strategic management and corporate entrepreneurship. Copyright © 1999 John Wiley & Sons, Ltd.     

Raising quality consciousness among Chinese manufacturing personnel: Testing the effectiveness of performance management tools

This study draws upon the strategic management control literature, goal-setting, and expectancy theory to address the management of quality in Chinese manufacturing operations. Operating in a transition economy, Chinese managers face specific challenges in adapting management strategies and control systems. Using causal modeling, we examine the implementation of quality strategies through management control and reward systems in 38 manufacturing firms operating in the Pearl River Delta, examining the effects of company size. The results indicate that for larger firms, significant linkages were found between reward systems based on quality outcomes and quality feedback, and in turn, quality feedback was significantly linked to both quality goals and a strategic focus on quality. However, for smaller firms, while significant relationships exist between reward systems based on quality outcomes and the provision of quality goals and feedback, no significant linkages were found between the implementation of management control systems and a strategic focus on quality. This study emphasizes the need to develop more robust theories to address the manufacturing environments of transition economies such as China, as well as the need for additional field research on indigenous firms in Asia.     

A guide to using event study methods in multi‐country settings

While the event study method has made significant contributions to strategic management research, most event study research published in management journals has analyzed the financial implications of corporate announcements in a single country. This study discusses solutions to methodological challenges that emerge when applying the event study method to multiple countries. Specifically, this study develops the world market model, illustrating how to simultaneously assess the financial impact of strategic actions in multiple countries. These challenges and solutions are illustrated by an example of a multi‐country event study analyzing 241 international alliance announcements of 23 firms in 16 countries. The findings show that the use of the single country market model in a multi‐country event study is likely to overestimate changes in firm value, demonstrating the need for this world market model. Copyright © 2004 John Wiley & Sons, Ltd.     

Research on corporate diversification: A synthesis

Diversification has emerged as a central topic of research in strategic management. Although this topic has been widely and intensively studied by scholars from other areas such as industrial organization economics, financial economics, organization theory, and marketing, a synthesis of these diverse streams of research is lacking. This paper attempts such a synthesis with a view to fostering further strategic management research in this area by taking a multi-disciplinary perspective on diversification. A wide-ranging search of the literature led to the development of an overarching research framework that facilitates the classification of a vast body of literature. Proceeding from the framework, a critique of the literature is performed with a particular emphasis on studies by strategic management researchers. Five key conceptual and methodological problems are identified and discussed. Suggestions are offered for future research on diversification.     

Configurations of resources and capabilities and their performance implications: an exploratory study on technology ventures

As one of the most widely accepted theoretical perspectives in strategy, the resource‐based view (RBV) suggests that a firm's resources underlie its ability to achieve competitive advantage. However, much of the extant work in this stream has examined the characteristics that resources must have in order to yield rents, while efforts to specify the crucial link between resources and value creation have been sparse. As a consequence, current theory is not sufficiently clear on how different kinds of resources and capabilities contribute to performance, nor does it clarify how firms can combine different resources and capabilities to achieve superior performance outcomes. Analyzing data obtained from 230 technology ventures with partial least squares (PLS) structural equation modeling and cluster analysis, this study seeks to improve understanding of the resource‐performance link in two main ways. Based on a careful measurement of resources and capabilities in a well‐defined functional area (sales and distribution), we first show how these resources and capabilities contribute to performance in that functional area. Second, we identify four clusters of firms that deploy different configurations of resources and capabilities. Among the four configurational solutions, two are associated with superior (equifinal) performance outcomes. Copyright © 2010 John Wiley & Sons, Ltd.     

Matching method to paradigm in strategy research: limitations of cross‐sectional analysis and some methodological alternatives

A central focus of empirical research in strategic management has been to understand the relationships associated with the structure–strategy–performance paradigm. To examine these relationships, investigators have relied extensively on cross‐sectional methods that embody the implicit assumption that model parameters are stable across firms and over time. Yet, many of the theoretical constructs used in strategic management have clear firm‐ and time‐specific components. Hence, it might be expected that the parameters of the relationships investigated empirically will vary across firms and over time. Whereas recent research has raised concerns about the use of cross‐sectional analysis when parameters vary over time, little attention has been given to the issue of parameter variability across firms. Given the focus of strategy researchers on firm‐level effects and the predominant reliance on cross‐sectional analysis, accounting for across‐firm variability is a significant methodological issue. Failure to account for such variability can lead to biased parameter estimates and incorrect inferences. This paper argues for the adoption of alternative methods that can overcome the limitations of a cross‐sectional analysis and it offers guidance on how researchers can proceed to use these alternative methods to explicitly incorporate or test for variation in model parameters across firms or over time. Copyright © 1999 John Wiley & Sons, Ltd.     

Development of the conceptual model of energy and utility management in textile processing: A soft systems approach

This paper aims to use soft systems methodology (SSM) to identify management support system opportunities for managing energy and utility usage in textile manufacturing processes. It presents an approach based on SSM to analyze the complex situation of developing an effective energy and utility management support system (EUMSS). This involves the identification of the scope of the system and user requirements, conceptual modeling of complex problem situations, identification of actors and decision processes, and information-needs modeling. The current study pioneers the examination of the application of SSM to the development of a novel EUMSS and contributes to the body of information systems knowledge in the context of EUMSS design. There appears to be limited academic research in the field of energy and utility system development and, in particular, in the area of EUMSS design, and none in the area of the application of SSM to EUMSS design. In addition, the modeling process could be beneficial if EUMSS design ideas could be widely shared and discussed. The identified scope and system requirements can serve as a guideline for designing and developing an effective EUMSS for textile processing.     

Disruptiveness of innovations: measurement and an assessment of reliability and validity

Strategic management scholars have long explored the broad topic of innovation, a cornerstone in creating competitive advantage. Any attempt at theory construction in this area must encompass reliable and valid measures for key innovation characteristics. Yet, with respect to an important construct, i.e., disruptiveness of innovations, there has been relatively little academic research. Without formalizing the disruptiveness concept with a reliable and valid measure, it is difficult to conduct rigorous research to uncover the causes of the innovator's dilemma and identify mechanisms to help incumbents develop such innovations. In this paper, we develop a scale for the disruptiveness of innovations. We collected data from senior executives (vice president or general manager level) at 199 strategic business units (SBUs) in 38 Fortune 500 corporations and performed a series of analyses to establish the reliability and validity of the disruptiveness scale. The reliability measures, exploratory factor analysis, confirmatory factor analysis, and subsequent statistical tests strongly support our measure. Further, we also present nomological validity of the disruptiveness construct, thus establishing its predictive validity. Thus, this paper distinguishes the disruptiveness concept from other established innovation constructs, such as radicalness and competency destroying. Finally, we discuss the significance of our results and how this study might be useful to other researchers. Copyright © 2006 John Wiley & Sons, Ltd.     

How Canon and Sony Drive Product Innovation Through Networking and Application-Focused R&D

To ensure the ongoing vitality of a company's product offerings, R&D professionals must play a daunting array of roles. The already rapid, yet still accelerating, pace of technological change may lead some companies to devote more resources to intensive internal research efforts. However, the shift toward global competition demands a more market-oriented focus from R&D; clear understanding of current and potential markets must drive R&D efforts. And efficient, cost-effective manufacturing of new products requires an R&D organization that understands and interacts effectively with the production department. How does a company create an environment in which its R&D organization comprises market-savvy, production-friendly experts in diverse technologies? With case studies of R&D efforts at Canon and Sony, Sigvald Harryson identifies and illustrates the key mechanisms that these companies use to foster product innovation. His examples show how Canon and Sony use a combination of external and internal networking mechanisms to identify and acquire key technologies and related skills, gain market knowledge, improve the results of internal R&D efforts, and ensure the successful transfer of these results to efficient production processes. He identifies four key mechanisms underlying successful product innovation at Canon and Sony: strategic training and job rotation for engineers, application-driven R&D, direct transfer of development teams from R&D to production, and extensive networking with external centers of excellence and key suppliers. At Canon, the initial training program for all researchers and engineers begins with three months of work on a production line. Sony's new researchers and development engineers spend one month in production. Both companies also give their new R&D professionals three months of training in sales and marketing. The emphasis on market-driven research at both companies means that researchers have identified some commercial application for almost every initial research proposal that gains approval. Neither company treats research as a long-term assignment; almost all engineers at both companies eventually move from the labs to production. And rather than viewing this job rotation strategy as a drain on the technological expertise in their labs, both companies rely on strong external networks with key suppliers and university-based researchers as important sources for acquiring new technologies and the competencies needed to support them.     

Networks of mind and networks of organizations: The map metaphor in business network research

This paper examines the definitions and uses of the network picture metaphor in industrial marketing research. Conceptually, the paper extends our understanding of networks and of representations of networks among researchers and practitioners as pictures or maps. A threefold interpretation is proposed of network pictures as representationalist, mentalist and situated. The representationalist use has dominated business-to-business network research while the mentalist use is prominent in strategic management and has recently made an entrance into industrial marketing research. The representationalist version of pictures, despite its apparent innocence, can either imply or leave unexamined the mentalist version, but mentalism stands in contradiction to much network thinking. This paper seeks to resolve the emerging contradiction of representationalist and mentalist versions of network pictures by advocating a situated version. Seeing network pictures as situated in use is helpful in grasping cognitions and actions in a manner consistent with networks. The paper concludes by developing the situated version of network pictures as ‘actants’ and sketches the benefits and implications for business researchers and practitioners.