Stock market undervaluation of resource redeployability

Sakhartov, Arkadiy V.

doi:10.1002/smj.2775

Cited by 21 publications

(40 citation statements)

References 88 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This result, that additional types of uncertainty reduce option value, is consistent with related research on ambiguity, which is thought of as uncertainty about prospective uncertainty (Cont, ; Nishimura & Ozaki, ; Sakhartov, ). However, the mechanism is quite different.…”

supporting

confidence: 88%

“…S(0,0) = 1, K = 1.5, μ = 0, and time to maturity = 1. σ c = 0 for both curves-that is, the firm behaves as if there is no contemporaneous uncertainty. 8 This result, that additional types of uncertainty reduce option value, is consistent with related research on ambiguity, which is thought of as uncertainty about prospective uncertainty (Cont, 1993;Nishimura & Ozaki, 2007;Sakhartov, 2014). However, the mechanism is quite different.…”

Section: Contemporaneous and Prospective Uncertainty Have Very Diffsupporting

confidence: 76%

“…Bernardo and Chowdhry () and Shibata () model drift in the function that defines the future value of an asset. In the strategy literature, Sakhartov () models the situation in which firms and markets face different levels of prospective uncertainty about the value of an asset. Irrespective of the type of ambiguity examined, the decision‐maker is never uncertain about the contemporaneous asset value at exercise time.…”

Section: Incorporating Contemporaneous Uncertainty Into Real Optionsmentioning

confidence: 99%

See 2 more Smart Citations

Toward a behavioral theory of real options: Noisy signals, bias, and learning

Posen

Leiblein

Chen

2018

Strategic Management Journal

View full text Add to dashboard Cite

Research Summary: We develop a behavioral theory of real options that relaxes the informational and behavioral assumptions underlying applications of financial options theory to real assets. To do so, we augment real option theory's focus on uncertain future asset values (prospective uncertainty) with feedback learning theory that considers uncertain current asset values (contemporaneous uncertainty). This enables us to incorporate behavioral bias in the feedback learning process underlying the option execution/termination decision. The resulting computational model suggests that firms that inappropriately account for contemporaneous uncertainty and are subject to learning biases may experience substantial downside risk in undertaking real options. Moreover, contrary to the standard option result, greater uncertainty may decrease option value, making commitment to an investment path more effective than remaining flexible. Managerial Summary: Executives recognize the need to make uncertain investments to grow their business while mitigating downside risk. The analogy between financial options and real corporate investments provides an appealing method to consider the practical challenge of such investment decisions. Unfortunately, the “real options” analogy seems to break down in practice. We identify how a second form of uncertainty confounds real options intuition, leading managers to overestimate the value of uncertain investments. We present a behavioral real options model that accounts for both forms of uncertainty and suggest how uncertainty interacts with behavioral bias in the option execution/termination decision. Our model facilitates assessment of the conditions under which investments in uncertain opportunities are usefully considered as real options, and provides a means to evaluate their attractiveness.

show abstract

supporting

confidence: 88%

Section: Contemporaneous and Prospective Uncertainty Have Very Diffsupporting

confidence: 76%

Section: Incorporating Contemporaneous Uncertainty Into Real Optionsmentioning

confidence: 99%

See 1 more Smart Citation

Toward a behavioral theory of real options: Noisy signals, bias, and learning

Posen

Leiblein

Chen

2018

Strategic Management Journal

View full text Add to dashboard Cite

show abstract

“…Thus, intra-temporal economies of scope, or synergy, from shared knowledge, sales and distribution activities, or other functions are notoriously hard to estimate (Cullinan et al 2004;Eccles et al 1999). Likewise, inter-temporal economies of scope from resource redeployment are difficult to evaluate (Maritan and Florence 2008;Sakhartov 2018).…”

Section: Incomplete Informationmentioning

confidence: 99%

“…In line with this idea, Litov et al (2012) raised the 'uniqueness paradox' wherein unique economies from sharing resources within a multi-business firm are also hard to evaluate adequately. Likewise, Sakhartov (2018) proposed a 'redeployability paradox' that is specific to inter-temporal economies of scope: resource redeployment between two businesses is a valuable option that may be hard to assess due to its uniqueness. Both Litov et al (2012) and Sakhartov…”

Section: Incomplete Informationmentioning

confidence: 99%

Economies of Scope and Optimal Due Diligence in Corporate Acquisitions

Reuer

Sakhartov

2019

Proceedings

Self Cite

View full text Add to dashboard Cite

How much due diligence should an acquiring organization undertake with respect to economies of scope? Conventional wisdom expressed by consultants, the business press, and educators often implies that acquirers cannot be too diligent, given the risks that acquisitions entail. For instance, Moeller and Brady (2014, p. 142) argue that "the 'knowledge is power' mantra could not be more appropriate than in describing the value of genuine due diligence." Accordingly, consultants have cast the pre-deal evaluation of economies of scope as "the prime hard key to deal success, one which can enhance the chance of success to 28 percent above average" (KPMG 1999). Consultants have also warned that 88 percent of corporate acquirers consider insufficient due diligence the most common reason for deal failure (The Storytellers and Mergermarket 2013). Accordingly, the business press advises that organizations undertaking corporate acquisitions be very skeptical about the target's asking price (Eccles et al. 1999) and prepare to refrain from a deal if that price exceeds the value diagnosed in careful due diligence (Cullinan et al. 2004). Likewise, the virtue of extensive due diligence is emphasized in business cases that introduce MBA students to best practices in M&A deal-making. For example, Cisco Systems Inc. is often held out as an exemplar that conducts far-reaching due diligence involving large cross-functional teams from human resources, manufacturing, engineering, and marketing (Singh et al. 2009). Academic research on corporate acquisitions has also advocated extensive due diligence of economies of scope: "Acquiring firm decision makers must have a clear vision of how synergy will be created in the combined firm… Such a vision is worked out through careful due diligence on the part of acquiring firm executives before a decision is made to proceed with the acquisition. Effective visions do not result from transactions that are completed quickly and without careful analyses" (Hitt et al. 2005, p.

show abstract

Analytic models in strategy, organizations, and management research: A guide for consumers

Hannah

Tidhar

Eisenhardt

2020

Strategic Management Journal

View full text Add to dashboard Cite

Research summary Analytic models are a powerful approach for developing theory, yet are often poorly understood in the strategy and organizations community. Our goal is to enhance the influence of the method by clarifying for consumers of modeling research how to understand and appreciate analytic modeling and use modeling results to enhance their own research. Our primary contribution is a guide for reading analytic models. Using comparisons with other methods and exemplar analytic models, we explore key features as well as counterintuitive aspects and common misconceptions. We also add by illuminating strengths and weaknesses of analytic modeling relative to other theory‐building methods. Finally, we identify under‐exploited opportunities for pairing analytic models with complementary methods. Overall, our aim is enhancing the influence of analytic modeling by better‐informing consumers. Managerial summary In this paper, we explore the use of analytic (mathematical) models for developing strategy and organizations theory. Analytic modeling is common in related fields like economics but is often poorly understood among the broader of strategy and organizations community. Whereas existing resources on analytic modeling are geared towards modelers, our aim is to enhance understanding and appreciation of the method among potential consumers of modeling research. We offer three specific contributions in this regard. The first is a guide for reading analytic models, including key features, counterintuitive aspects, and common misconceptions. Second, we clarify the strengths and weaknesses of analytic modeling relative to other theory‐building methods. Finally, we discuss promising opportunities for pairing methods.

show abstract

Stock market undervaluation of resource redeployability

Cited by 21 publications

References 88 publications

Toward a behavioral theory of real options: Noisy signals, bias, and learning

Toward a behavioral theory of real options: Noisy signals, bias, and learning

Economies of Scope and Optimal Due Diligence in Corporate Acquisitions

Analytic models in strategy, organizations, and management research: A guide for consumers

Contact Info

Product

Resources

About