The Experts below are selected from a list of 195390 Experts worldwide ranked by ideXlab platform
J. Adetunji Adegbesan - One of the best experts on this subject based on the ideXlab platform.
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On the Origins of Competitive Advantage: Strategic Factor Markets and Heterogeneous Resource Complementarity
Academy of Management Review, 2009Co-Authors: J. Adetunji AdegbesanAbstract:Strategic Factor Market theory suggests that in the absence of luck, asymmetric expectations are a necessary condition for firms to appropriate gains from valuable resources. I argue that this is only true in the absence of heterogeneous resource complementarity. Extending Factor Market theory, I show that firms can profit when they exhibit superior complementarity to target resources, even in the absence of asymmetric expectations, and I determine the components of appropriated value in such Markets. I thus demonstrate the power and simplicity of coalitional analysis, while shedding light on central concepts in strategic management discourse.
Jay B. Barney - One of the best experts on this subject based on the ideXlab platform.
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New Directions in Strategic Factor Market Research: Processes and Mechanisms
Academy of Management Proceedings, 2013Co-Authors: Catherine A Maritan, Thomas P. Moliterno, Jay B. BarneyAbstract:The concept of strategic Factor Markets is a fundamental element of resource-based theories of competitive advantage. Barney’s (1986) article, which introduced the strategic Factor Market (SFM) con...
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strategic Factor Market intelligence an application of information economics to strategy formulation and competitor intelligence
Management Science, 2001Co-Authors: Richard Makadok, Jay B. BarneyAbstract:This paper develops a model of information-acquisition decisions by firms that are competing in a "strategic Factor Market" (Barney 1986) to purchase a scarce resource whose value is unknown and differs across firms. The model builds on the argument that more accurate expectations about the firm-specific value of resources is, other than luck, the only way for firms to obtain the specific resources required for competitive advantage. We address the more specific question of what types of information firms should gather to accomplish this goal. The model generates a series of testable hypotheses about how a firm's optimal mix of different types of information is affected by a number of Factors, including the level of uncertainty about the value of the resource being acquired; the rarity, imitability, and nonsubstitutability of that resource; the level of inscrutability of firms' pre-existing stocks of resources; and firms' information-gathering and information-processing capacities.
Thomas S. Jayne - One of the best experts on this subject based on the ideXlab platform.
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Factor Market activity and the inverse farm size productivity relationship in tanzania
Journal of Development Studies, 2020Co-Authors: Ayala Wineman, Thomas S. JayneAbstract:Although the inverse farm size-productivity relationship (IR) is sometimes used to motivate arguments in favour of smallholder-led agricultural development, it remains unclear what drives this rela...
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Factor Market activity and the inverse farm size productivity relationship in tanzania
2018 Conference July 28-August 2 2018 Vancouver British Columbia, 2018Co-Authors: Ayala Wineman, Thomas S. JayneAbstract:Although the inverse farm size-productivity relationship (IR) is sometimes used to motivate arguments in favor of smallholder-led agricultural development, it remains unclear what drives this relationship. It may be attributed to Market imperfections that compel small farms to use land more intensively than large farms. Using a three-wave longitudinal household survey from Tanzania, we examine whether the intensity of the IR is related to local Factor Market activity for land, labor, credit, and animal and machine traction. The IR is evident in Tanzania, although it disappears when family labor is valued at the prevailing local agricultural wage rate. This suggests that labor Market imperfections (possibly linked to other Market failures) drive the IR. Furthermore, the IR is significantly weakened in the presence of relatively active Markets for most Factors of production. This suggests that the IR is at least partly driven by imperfections in rural Factor Markets, underscoring the importance of strategies to improve the functioning of these Markets. Acknowledgement : The authors are grateful for the encouragement and support of the Food Security Group in the Department of Agricultural, Food, and Resource Economics of Michigan State University. This work was supported by the USAID/Bureau for Food Security through the Feed the Future Innovation Lab for Food Security Policy Cooperative Agreement with Michigan State University, and by the Bill and Melinda Gates Foundation through the Guiding Investments in Sustainable Agricultural Intensification in Africa grant to Michigan State University.
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Factor Market Activity And The Inverse Farm Sizeproductivity Relationship In Tanzania
2017Co-Authors: Ayala Wineman, Thomas S. JayneAbstract:Although the inverse farm size-productivity relationship (IR) is sometimes used to motivate arguments in favor of smallholder-led agricultural development, it remains unclear what drives this relationship. It may be attributed to Market imperfections that compel small farms to use land more intensively than large farms. Using a three-wave longitudinal household survey from Tanzania, we examine whether the intensity of the IR is related to local Factor Market activity for land, labor, credit, and animal and machine traction. The IR is evident in Tanzania, although it disappears when family labor is valued at the prevailing local agricultural wage rate. This suggests that labor Market imperfections (possibly linked to other Market failures) drive the IR. Furthermore, the IR is significantly weakened in the presence of relatively active Markets for most Factors of production. This suggests that the IR is at least partly driven by imperfections in rural Factor Markets, underscoring the importance of strategies to improve the functioning of these Markets.
Ann K. Buchholtz - One of the best experts on this subject based on the ideXlab platform.
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Factor-Market Rivalry
Academy of Management Review, 2009Co-Authors: Gideon D. Markman, Peter T. Gianiodis, Ann K. BuchholtzAbstract:With its focus on product-Market rivalry, competitive dynamics research fails to tell the whole story. We develop a theory of Factor-Market rivalry to shed light on atypical rivals and competitive blind spots. Focusing on resource versatility and mobility, the theory introduces dynamic constructs—resource discontinuities, leapfrogging, and captivity—and explains their role in triggering cascading effects. To illustrate the theory's conceptual utility, we apply the concepts of Factor-Market rivalry to mutual forbearance in multiMarket competition.
Hart E. Posen - One of the best experts on this subject based on the ideXlab platform.
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Resource Allocation in Strategic Factor Markets: A Realistic Real Options Approach to Generating Competitive Advantage:
Journal of Management, 2017Co-Authors: Michael J. Leiblein, John S. Chen, Hart E. PosenAbstract:This paper develops a realistic real option theory of resource allocation decisions in strategic Factor Markets. Competitive advantage in Factor Markets is underpinned by Market failures that allow firms to acquire assets at less than their value in use. We recognize that Market failure may result from uncertainty regarding the current and/or future value of an asset, which map, respectively, to uncertainty as modeled in the feedback learning and real options literatures. The realistic real option framework we develop grafts insights from the strategic Factor Market, feedback learning, and real option valuation literatures. We argue that competitive advantage may emerge not only from luck, or ex ante differences in information or complementary assets, but also because firms differ in a specific type of learning ability — the ability to integrate new information to exercise a contingent claim on an asset in a Factor Market. We dimensionalize these differences in terms of information processing and belief updating, argue that these differences lead to different resource allocation decisions, and suggest how these decisions may generate competitive advantage.
