Resource Allocation in Strategic Factor Markets: A Realistic Real Options Approach to Generating Competitive Advantage

2016 ◽  
Author(s):  
Michael J. Leiblein ◽  
John S. Chen ◽  
Hart E. Posen
2017 ◽  
Vol 43 (8) ◽  
pp. 2588-2608 ◽  
Author(s):  
Michael J. Leiblein ◽  
John S. Chen ◽  
Hart E. Posen

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.


2016 ◽  
Vol 22 (2) ◽  
pp. 133-155 ◽  
Author(s):  
Utkur Djanibekov ◽  
Grace B. Villamor

AbstractThis paper investigates the effectiveness of different market-based instruments (MBIs), such as eco-certification premiums, carbon payments, Pigovian taxes and their combination, to address the conversion of agroforests to monoculture systems and subsequent effects on incomes of risk-averse farmers under income uncertainty in Indonesia. For these, the authors develop a farm-level dynamic mean-variance model combined with a real options approach. Findings show that the conservation of agroforest is responsive to the risk-aversion level of farmers: the greater the level of risk aversion, the greater is the conserved area of agroforest. However, for all risk-averse farmers, additional incentives in the form of MBIs are still needed to prevent conversion of agroforest over the years, and only the combination of MBIs can achieve this target. Implementing fixed MBIs also contributes to stabilizing farmers’ incomes and reducing income risks. Consequently, the combined MBIs increase incomes and reduce income inequality between hardly and extremely risk-averse farmers.


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