Optimal Decision Making and the Value of Information in a Time-Dependent Version of the Cost-Loss Ratio Situation

Murphy, Allan H.; Ye, Qian

doi:10.1175/1520-0493(1990)118<0939:odmatv>2.0.co;2

Cited by 13 publications

(9 citation statements)

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“…Wilks (1995, chapter 8) describes Markov chains and Markov processes that have continuous state variables, and Katz (Murphy and Katz 1985, chapter 7) summarizes some applications of Markov chains in a meteorological context. Readers interested in a deeper treatment of decision making on the basis of Markov models are directed to Puterman (1994).…”

Section: A Stochastic Modelingmentioning

confidence: 99%

“…The alternatives may vary by context; for example, there may be preparations that cannot be initiated at night, as a given preparation might have different cost curves depending on the time of day. To conceptually illustrate the value of dynamic optimization, we examine the performance of dynamic and static policies using both a linear function and an exponential function, with each increasing from C( ϭ crit ) ϭ C crit to C( ϭ 0) ϭ L. Murphy and Ye (1990) use a similar, exponential cost function. We further assume that the cost:loss ratio at the critical lead time (C crit ϭ C crit /L) is 0.1 (i.e., that the cost of preparing is 10% of the mitigative portion of the loss).…”

Section: B Preparation Cost Profilementioning

confidence: 99%

“…Though the persistence model would allow for the use of earlier forecasts in decision making, only one forecast for each event is used because the cost of protection is modeled as constant, and therefore there is no value to making the decision before the best-that is, last-forecast becomes available. Murphy and Ye (1990) also model successive forecasts with increasing accuracy for a single event and investigate the trade-off between increasing cost and increasing accuracy as lead time decreases. However, they assume that the decision maker must decide ex ante the lead time at which he or she will acquire the forecast and make a decision.…”

Section: Introductionmentioning

confidence: 99%

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A Dynamic Decision Model Applied to Hurricane Landfall

Regnier

Harr

2006

Weather and Forecasting

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The decision to prepare for an oncoming hurricane is typically framed as a static cost:loss problem, based on a strike-probability forecast. The value of waiting for updated forecasts is therefore neglected. In this paper, the problem is reframed as a sequence of interrelated decisions that more accurately represents the situation faced by a decision maker monitoring an evolving tropical cyclone. A key feature of the decision model is that the decision maker explicitly anticipates and plans for future forecasts whose accuracy improves as lead time declines. A discrete Markov model of hurricane travel is derived from historical tropical cyclone tracks and combined with the dynamic decision model to estimate the additional value that can be extracted from existing forecasts by anticipating updated forecasts, rather than incurring an irreversible preparation cost based on the instantaneous strike probability. The value of anticipating forecasts depends on the specific alternatives and cost profile of each decision maker, but conceptual examples for targets at Norfolk, Virginia, and Galveston, Texas, yield expected savings ranging up to 8% relative to repeated static decisions. In real-time decision making, forecasts of improving information quality could be used in combination with strike-probability forecasts to evaluate the trade-off between lead time and forecast accuracy, estimate the value of waiting for improving forecasts, and thereby reduce the frequency of false alarms.

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Section: A Stochastic Modelingmentioning

confidence: 99%

Section: B Preparation Cost Profilementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Dynamic Decision Model Applied to Hurricane Landfall

Regnier

Harr

2006

Weather and Forecasting

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“…Moreover, considerable approaches were discussed to investigate the relationship between forecast quality and forecast value for the situation of both static and dynamic versions Katz and Murphy, 1990;Thornes, 2001;Wilks, 2001;Mylne, 2002;Zhu et al, 2002). In addition, Murphy and Ye (1990) suggested a time-dependent version of the cost/loss ratio model to describe a situation in which the decision maker may delay the decision until forecasts of greater accuracy become available despite the increased cost of protection caused by the delayed action.…”

Section: Introductionmentioning

confidence: 99%

The economic value of weather forecasts for decision‐making problems in the profit/loss situation

Lee

2007

Meteorological Applications

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This article presents a method to estimate the economic value of forecasts for profit-oriented enterprise decision-making problems related to the levels of preparations for goods or services. The sales of goods or services in the study are supposed to be influenced and predicted by meteorological variables. Value is calculated in terms of monetary profit (or benefit) returned from the user's decision under the specific payoff structure, which is represented by a profit/loss ratio model. The decision is determined as a function of the user's subjective reliability of forecasts and forecast probability. The resulting value score (VS) curve shows the scaled economic values relative to the value of a perfect forecast, specified by a function of the profit/loss ratios for different decision makers. The proposed evaluation method, based on the profit/loss ratio model and the VS, is illustrated using hypothetical sets of forecasts, and later verified by applying site-specific probability and deterministic forecasts, each of which is generated from the Korea and China Meteorological Administrations (KMA and CMA). The application results show that decision makers with high subjective reliability of forecasts can receive great benefits from a given forecast, and there are ranges of profit/loss ratios in which each of the forecast sources used for the evaluation is preferred.

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“…Moreover, considerable approaches were discussed to investigate the relationship between forecast quality and forecast value for the situation of both static and dynamic versions [2,[11][12][13][14][15]. In addition, the study of [16] suggested a time-dependent version of the cost/loss ratio model to describe a situation in which the decision maker may delay the decision until forecasts of greater accuracy become available despite the increased cost of protection caused by the delayed action.…”

Section: Introductionmentioning

confidence: 99%

Optimal Decision-Making and the Value of Weather Forecasts Information: A Case of CRM in a Korean Resort

Kee¹,

Han

2007

2007 International Conference on Convergence Information Technology (ICCIT 2007)

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This paper presents a method to estimate and analyze the economic value of weather forecasts for CRM decision-making problems in a leisure industry. Value is calculated in terms of customer's satisfaction returned from the user's decision under the specific payoff structure, which is represented by a customer's utility ratio model. The decision is determined as a function of the customer's utility patterns and the characteristics of forecast information. The resulting value score (VS) curve shows the scaled economic values relative to the value of a perfect forecast, specified by a function of the profit-loss ratios for different decision makers. The proposed evaluation method based on the profit/loss ratio model and the VS is verified by applying site-specific probability and deterministic forecasts, each of which is generated from the Korea and China Meteorological Administrations (KMA and CMA). The application results show that the proposed VS method can help decision makers choose the optimal decision strategy for specific customers with various utility patterns.

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Optimal Decision Making and the Value of Information in a Time-Dependent Version of the Cost-Loss Ratio Situation

Cited by 13 publications

References 0 publications

A Dynamic Decision Model Applied to Hurricane Landfall

A Dynamic Decision Model Applied to Hurricane Landfall

The economic value of weather forecasts for decision‐making problems in the profit/loss situation

Optimal Decision-Making and the Value of Weather Forecasts Information: A Case of CRM in a Korean Resort

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