Valuing pilot projects in a learning by investing framework: An approximate dynamic programming approach

Errais, Eymen; Sadowsky, Jeffrey

doi:10.1016/j.cor.2006.02.015

Cited by 11 publications

(4 citation statements)

References 18 publications

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“…However, from the expression of the evolvement of cost and related research [18] , it is safe to reach the conclusion that higher expanded learning efficiency engenders more resolution of technical uncertainty with same unit of investment. Anyway, as the central mechanism of reducing internal uncertainty, learning by doing or investing is always accelerating the progress of innovation investment, as well as improving its economic value.…”

Section: Fig5 Impact Of Accumulated Learning On Investment Thresholdmentioning

confidence: 97%

“…[9][10] [11] , reconfiguring the problem using new models (such as internalizing the resolution mechanism of technical uncertainty under discrete conditions) [12] [13] or considering the time lag in a game theoretical framework [14] [15] . The basic logic of these models is that optimal decisions are made through the trade-off between the expected cost and value of the project, which are mainly influenced by different types of uncertainties and their resolution through learning process of new information acquisition [16][17] [18] . However, all these models implicitly take the assumption of equal marginal learning efficiency, which means by investing same amount of money, any firm can resolve or reduce same extent of uncertainty.…”

Section: Introductionmentioning

confidence: 99%

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Investment under uncertainty in new technology with time-to-build in perspective of learning

Xing

2009

2009 International Conference on Management Science and Engineering

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Time to build is a characteristic of most of new technology project mainly caused by physical or financial limitations. So, decision-makers have to take account the internal technical uncertainties of the project into when making investment choices instead of considering only external market conditions. This paper analyzes the implicit mechanism underpinning the new technology sequential investment decision in perspective of the patterns and efficiency of different learning in resolving or reducing different types of uncertainty. Especially, this paper introduces the learning heterogeneity in the resolution efficiency of technical uncertainty, which is compensatively determined by learning capability, accumulated and expanded learning effect. Adopting the real options approach, the mathematical model is constructed and solved by numerical method, with comparative static analysis conducted as well. According to this, I expect to give more insight into the investment mechanism of and provide rational decision-making guideline for new technology projects.

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Section: Fig5 Impact Of Accumulated Learning On Investment Thresholdmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Investment under uncertainty in new technology with time-to-build in perspective of learning

Xing

2009

2009 International Conference on Management Science and Engineering

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“…Schwartz () used a simulation approach to value patents and accounted for uncertainty in completion costs, cash flows and the potential for investment‐ending events. Errais and Sadowsky () introduce a general discrete‐time dynamic framework to value pilot investments that reduce idiosyncratic uncertainty with respect to the final cost of a project. They use a dynamic programming algorithm that relies on the independence of increments in state variables in an incomplete market.…”

Section: Measuring Adaptabilitymentioning

confidence: 99%

Optimising adaptation decisions in macadamia production using contingent claim valuation

West

2018

Aus J Agri & Res Econ

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Altering production systems and land management of tree crops is a costly, disruptive and ultimately irreversible decision. Using traditional valuation methods to appraise long‐term land management outcomes ignores the full impact of irreversible or delayed decisions. We employ a variant of the real options decision process to examine uncertainties around climatic effects on macadamia growers and the explicit decision to adapt via cultivar replacement. We examine the trade‐offs between the timing of the decision to replace macadamia cultivars by considering both the value of flexibility as well as the value of new information that can be used to resolve uncertainty. We compare the relative responses that generate the most value for growers across four geographical locations. We show that simple switching decisions using traditional valuation methods are found to be suboptimal and initiate poor decisions, potentially undermining adaptation efforts. As the rate of orchard degradation increases, the need to transition to higher‐yielding cultivars becomes greater, especially for Hawaii, California and Australia where gross margins are leaner. Investment decisions are thus highly dependent on both local conditions and the economic structure of existing production systems.

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“…Some researchers also present a general discrete time dynamic framework to value pilot project investments that reduce idiosyncratic uncertainty by compound perpetual Bermudan option in different stages (Errais & Sadowsky, 2008;Miller, 2010).…”

Section: The Incentive Contract In Project Managementmentioning

confidence: 99%

Two staged incentive contract focused on efficiency and innovation matching in critical chain project management

Zhang

Jin

2014

JIEM

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This paper analyzes a two staged incentive contract coordinated with efficiency and innovation in Critical Chain Project Management using learning real options, based on principle-agent theory. The situational experiment is used to detect the validity check of this basic model. Finding: The two staged incentive scheme is more suitable for employees to create and implement learning real options, which will throw themselves into innovation process efficiently in the situation of Critical Chain Project Management. We prove that the combination of tolerance for early failure and reward for long-term success is effective in motivating innovation.

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Valuing pilot projects in a learning by investing framework: An approximate dynamic programming approach

Cited by 11 publications

References 18 publications

Investment under uncertainty in new technology with time-to-build in perspective of learning

Investment under uncertainty in new technology with time-to-build in perspective of learning

Optimising adaptation decisions in macadamia production using contingent claim valuation

Two staged incentive contract focused on efficiency and innovation matching in critical chain project management

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