The investment decision under uncertainty

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Statistical Techniques for Risk Analysis

Innovations involving information technology IT provide potentially valuable investment opportunities for industry and government organizations. Significant uncertainties are associated with decision-making for IT investment though, a problem that senior executives have been concerned about for a long time. The uncertainties include consumer, market and regulatory responses, IT-driven changes in operational and transactional performance, technology standards and competition, and future market conditions. As a result, traditional capital budgeting, investment experience, and intuition have not been very effective in IT investment decision-making. We propose a new option-based stochastic valuation modeling approach for IT investment under uncertainty that incorporates a mean reversion process to capture cost and benefit flow variations over time. We apply the proposed approach in two industry settings: to a large-scale IT investment in the consolidation of data marts at a major airline, and to a mobile payment system infrastructure investment on the part of a start-up.

Investment decision making under uncertainty: the impact of risk aversion, operational flexibility, and competition

Innovations involving information technology IT provide potentially valuable investment opportunities for industry and government organizations. Significant uncertainties are associated with decision-making for The investment decision under uncertainty investment though, a problem that senior executives have been concerned about for a long time.

The uncertainties include consumer, market undet regulatory responses, IT-driven changes in operational and transactional performance, technology standards and competition, and future market conditions. As a result, traditional capital budgeting, investment experience, and intuition have not been very effective in IT investment decision-making.

We propose a new option-based stochastic valuation modeling approach for IT investment under uncertainty that incorporates a mean reversion process to capture cost and benefit flow variations over time. We apply the proposed approach in two industry settings: to a large-scale IT investment in the consolidation of data marts at a major airline, and to a mobile payment system infrastructure investment on the part decisino a start-up.

The applications supported the evaluation of the proposed methods, and offered some illustrations about the kinds of managerial insights that can be obtained.

We also report on several extensions that demonstrate how the creation of useful management findings from the modeling approach can be supplemented with project value sensitivity analysis and the use of simulation-based least-squares Monte Carlo valuation. The findings are useful to assess the power and value of the approach.

This is a preview of subscription content, log in to check access. We thank an anonymous reviewer for suggesting the ivestment reversion process, instead of the geometric Brownian motion process due to its lognormal distribution, with a time-dependent mean and variance, and for pointing out the relevance of the technology product lifecycle. Benaroch et al. In contrast, a data warehouse combines enterprise databases.

Three-point estimation is used in management and systems for constructing an approximate probability distribution based on limited information. For information on the triangular distribution, see Johnson [ 39 ], Kotz and Dorp [ 45 ] ddcision Yang [ deciison ]. We apply a different model specification for benefit growth of Square m-payment system excluding the process of benefit decay, since m-payment technology is still in the technology trigger phase of hype cycle, yet reaches the trough of disillusionment stage [ 27 ].

Also, m-payment technologies are associated with a uncertanty network effects. Square currently prices at a flat rate of 2. We adopted a fixed unccertainty of 0. This perspective has been best articulated by Robert Merton [ 55p.

Uncerttainty is, if one could trade continuously thhe cost, then following their dynamic trading strategy using the underlying traded asset and the riskless asset would exactly replicate the payoffs on the option.

Thus, in a continuous-trading financial environment, the option price must satisfy the Black—Scholes formula or else there would be an opportunity for arbitrage profits. Int J Ind Org 25 1 — Amram M, Kulatilaka N Strategy and shareholder value: the real options frontier.

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Decision Analysis 1: Maximax, Maximin, Minimax Regret

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They have to estimate whether the NV would be negative or the IRR would be less than the cost of capital. Downloads by country — last 12 months. Thus normal probability distribution is an important statistical technique for evaluating the risk in investmen business. Abstract Introduction, University of California. Article Contents. Investment Under Uncertainty Advertisements. Google Scholar.