A Positive Value of Information for a Non-Bayesian Decision-Maker

1999 ◽  
pp. 93-107 ◽  
Author(s):  
Arnold Chassagnon ◽  
Jean-Christophe Vergnaud
Keyword(s):  
Decision Maker ◽  
Value Of Information ◽  
Bayesian Decision

Information in Fleeting Opportunities

2013 ◽  
pp. 110-153
Author(s):  
Ibrahim Almojel ◽  
Jim Matheson ◽  
Pelin Canbolat
Keyword(s):  
Utility Function ◽  
Decision Maker ◽  
Optimal Policy ◽  
Value Of Information ◽  
Risk Preference ◽  
Dynamic Program ◽  
Exponential Utility ◽  
Venture Capitalists ◽  
Exponential Utility Function ◽  
Over Time

This paper focuses on the study of information in fleeting opportunities. An application example is the evaluation of business proposals by venture capitalists. The authors formulate the generic problem as a dynamic program where the decision maker can either accept a given deal directly, reject it directly, or seek further information on its potential and then decide whether to accept it or not. Results show well behaved characteristics of the optimal policy, deal flow value, and the value of information over time and capacity. It is presumed that the risk preference of the decision maker follows a linear or an exponential utility function. This approach is illustrated through several examples.

scholarly journals Pre-Test-Market Models: Validation and Managerial Implications

1983 ◽  
Vol 20 (3) ◽  
pp. 221-234 ◽  
Author(s):  
Glen L. Urban ◽  
Gerald M. Katz
Keyword(s):  
Value Of Information ◽  
Predictive Accuracy ◽  
Market Model ◽  
Decision Analysis Model ◽  
Bayesian Decision ◽  
Analysis Model ◽  
Market Shares ◽  
Managerial Implications ◽  
Test Market ◽  
Models Validation

The predictive accuracy of a widely used pre-test-market model (ASSESSOR) is analyzed. The standard deviation between pre-test-market and test-market shares is 1.99 share points before adjustments for achieved awareness, distribution, and sampling and 1.12 share points after adjustment. Sixty-three percent of those products tested passed the pre-test screen and 66% of these were subsequently successful in test market. A Bayesian decision analysis model is formulated and a “typical” case shows a positive value of information. Although some conditions are identified under which a test market may be bypassed, in the authors’ opinion both pre-test and test-market procedures should be used in all but exceptional situations.

Information in Fleeting Opportunities

2011 ◽  
Vol 2 (1) ◽  
pp. 1-41 ◽  
Author(s):  
Ibrahim Almojel ◽  
Jim Matheson ◽  
Pelin Canbolat
Keyword(s):  
Utility Function ◽  
Decision Maker ◽  
Optimal Policy ◽  
Value Of Information ◽  
Risk Preference ◽  
Dynamic Program ◽  
Venture Capitalists ◽  
Generic Problem ◽  
Exponential Utility Function ◽  
Over Time

This paper focuses on the study of information in fleeting opportunities. An application example is the evaluation of business proposals by venture capitalists. The authors formulate the generic problem as a dynamic program where the decision maker can either accept a given deal directly, reject it directly, or seek further information on its potential and then decide whether to accept it or not. Results show well behaved characteristics of the optimal policy, deal flow value, and the value of information over time and capacity. It is presumed that the risk preference of the decision maker follows a linear or an exponential utility function. This approach is illustrated through several examples.

scholarly journals Value of Information-Based Inspection Planning for Offshore Structures

2017 ◽  
Author(s):  
Arifian Agusta ◽  
Sebastian Thöns ◽  
Bernt J. Leira
Keyword(s):  
Decision Analysis ◽  
Value Of Information ◽  
Oil And Gas Industry ◽  
Offshore Structures ◽  
Bayesian Decision ◽  
Inspection Planning ◽  
Information Analysis ◽  
Offshore Structure ◽  
Value Of Information Analysis ◽  
A Value

Asset integrity and management is an important part of the oil and gas industry especially for existing offshore structures. With declining oil price, the production rate is an important factor to be maintained that makes integrity of the structures one of the main concerns. Reliability based and risk-based inspection (RRBI) constitutes an efficient method to optimize inspection planning. Basing the inspection planning on pre-posterior Bayesian decision analysis and especially a Value of Information analysis allows to explicitly quantify the expected benefits, costs and risks associated with each inspection strategy. A simplified and generic risk-based inspection planning utilizing pre-posterior Bayesian decision analysis had been proposed by Faber et al. [1] and Straub [2]. This paper provides considerations on the theoretical background and a Value of Information analysis-based inspection planning. The paper will start out with a review of the state-of-art RBI planning procedure based on Bayesian decision theory and its application in offshore structure integrity management. An example of the Value of Information approach is illustrated and it is pointed to further research challenges.

Maximizing the Value of Information of a Horizontal Polymer Pilot Under Uncertainty Incorporating the Risk Attitude of the Decision Maker

2019 ◽  
Vol 22 (02) ◽  
pp. 756-774
Author(s):  
Dominik Steineder ◽  
Torsten Clemens ◽  
Keyvan Osivandi ◽  
Marco R. Thiele
Keyword(s):  
Decision Maker ◽  
Value Of Information ◽  
Risk Attitude

scholarly journals Value of information analysis in civil and infrastructure engineering: a review

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Wei-Heng Zhang ◽  
Da-Gang Lu ◽  
Jianjun Qin ◽  
Sebastian Thöns ◽  
Michael Havbro Faber
Keyword(s):  
Value Of Information ◽  
Communication Theory ◽  
Structural Integrity ◽  
Bayesian Decision ◽  
Information Analysis ◽  
Starting Point ◽  
Integrity Management ◽  
Historical Developments ◽  
Current Engineering ◽  
Theoretical Foundations

AbstractThe concept of Value of Information (VoI) has attracted significant attentions within the civil engineering community over especially the last decade. Triggered by the increasing focus on structural health monitoring, availability of data and emerging techniques of Big Data analysis and Artificial Intelligence, important insights on how to take benefit from VoI in structural integrity management have been gained. This literature review starts out with a summary of the historical developments and contains (1) a summary of two different VoI analysis origins, (2) a compilation of existing VoI analyses research and (3) current engineering interpretations and applications of VoI in the field of civil and infrastructure engineering. VoI analysis has roots in communication theory and Bayesian decision analysis in conjunction with utility theory. Starting point is thus taken in brief introduction of these theoretical foundations, followed by a discussion on the relevant modelling aspects such as information, probability and utility modelling. A detailed review of relevant existing research is presented, divided into the following main areas: computational methods, optimal sensor placement and engineering risk management. Finally, by way of conclusion and outlook, challenges and some promising directions for VoI analysis in the field of civil and infrastructure engineering are identified.

scholarly journals Monitoring experts

2021 ◽  
Vol 16 (4) ◽  
pp. 1313-1350
Author(s):  
Yaron Azrieli
Keyword(s):  
Cost Function ◽  
Decision Maker ◽  
Value Of Information ◽  
Previous Literature ◽  
Optimal Contracts ◽  
Ex Post ◽  
The Cost ◽  
Entire Vector

We study the design of contracts that incentivize experts to collect information and truthfully report it to a decision maker. We depart from most of the previous literature by assuming that the transfers cannot depend on the realized state or on the ex post payoff of the decision maker. The contract thus has to induce the experts to “monitor each other” by making the transfers contingent on the entire vector of reports. We characterize the least costly contract that implements any given vector of efforts and derive the cost function for the decision maker. We then study properties of optimal contracts by comparing the value of information and its cost.

scholarly journals The Missing Variable in Big Data for Social Sciences: The Decision-Maker

2018 ◽  
Vol 10 (10) ◽  
pp. 3415 ◽  
Author(s):  
Michela Arnaboldi
Keyword(s):  
Social Sciences ◽  
Decision Making ◽  
Big Data ◽  
Decision Maker ◽  
Value Of Information ◽  
Social Impact ◽  
End Users ◽  
Decision Making Process ◽  
Suggested Approach ◽  
Four Dimensions

The value of big data for social sciences and social impact is professed to be high. This potential value is related, however, to the capacity of using extracted information in decision-making. In all of this, one important point has been overlooked: when “humans” retain a role in the decision-making process, the value of information is no longer an objective feature but depends on the knowledge and mindset of end users. A new big data cycle has been proposed in this paper, where the decision-maker is placed at the centre of the process. The proposed cycle is tested through two cases and, as a result of the suggested approach, two operations—filtering and framing—which are routinely carried out independently by scientists and end users in an unconscious manner, become clear and transparent. The result is a new cycle where four dimensions guide the interactions for creating value.

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