A decision-making framework based on prospect theory with probabilistic linguistic term sets

Gu, Jing; Zheng, Ying; Tian, Xiaoli; Zhang, Xu

doi:10.1080/01605682.2019.1701957

Cited by 30 publications

(10 citation statements)

References 22 publications

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“…Probability weighting is the decision maker's perception of the probability of an event, which is traditionally considered as a linear function. However, an abundance of evidence shows that the individuals do not use objective probabilities to evaluate the possibility of an event but rather the transformed probabilities obtained from objective probabilities via mental processing [39][40][41]. A recent empirical study by Stearns shows that innovation will may fail fast as a result of overconfidence by a firm's managers, which indicates that the cognitive biases may affect investment decisions [42].…”

Section: Literature Reviewmentioning

confidence: 99%

Evolutionary Game Analysis of Firms’ Technological Strategic Choices: A Perspective of the Behavioral Biases

et al. 2021

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To reveal the mechanisms of firms’ technological strategic choices between innovation and imitation, an evolutionary game model is proposed from the perspective of the behavioral biases. First, behavioral biases such as reference point dependence, loss aversion, and probability weighting can be defined and modeled based on the prospect theory. Second, according to the firm theory, a Cournot or Stackelberg game modeled with a technology spillover effect and intellectual property protection is applied to portray the interaction between firms. Third, an improved evolutionary game model is provided by incorporating behavioral biases into the framework of the decision-making process. Finally, the simulation analysis of some important factors, such as intellectual property protection, patent fees, innovation risks, decision-making attitudes, and consumers’ price preference on firms’ technological strategic choices, is presented. The corresponding results show that (1) innovation risk is an important factor affecting the technological strategic choices of firms, (2) increasing the intellectual property protection and the patent fee for technology transfer can effectively control the spillover effect of technology, (3) there is a partial U-shaped relationship between the consumers’ price preference and innovation, and (4) the behavioral biases such as reference point dependence, loss aversion, and probability weighting will change the perception of payoff and risk and will eventually induce firms to adopt the innovation strategy.

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Section: Literature Reviewmentioning

confidence: 99%

Evolutionary Game Analysis of Firms’ Technological Strategic Choices: A Perspective of the Behavioral Biases

et al. 2021

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“…We have #L(p) k�1 p (k) � 1 under complete information, #L(p) k�1 p (k) � 0 under complete ignorance, and 0 < #L(p) k�1 p (k) < 1 under partial ignorance, where the ignorance represented by 1 − #L(p) k�1 p (k) should be averagely assigned to all of the linguistic terms in L(p). e PLTSs in equation ( 6) are called standard PLTSs [56] with a certain point value of probability. e interval value of probability is more suitable for solving practical decisionmaking problems because of its consideration of DMs' vagueness.…”

Section: Preliminariesmentioning

confidence: 99%

“…However, it is also less computable. erefore, Gu et al [56] provided a method for converting intervalvalued PLTSs into standard PLTSs as follows.…”

Section: Preliminariesmentioning

confidence: 99%

“…In order to solve this problem, several researchers have made strong attempts [65][66][67] by introducing new aggregation operators and comparison laws for interval values, which provide new calculation methods to accommodate the vagueness of linguistic terms and complicated calculations. We believe that the method as in equation ( 7) proposed by Gu et al [56] is simple and applicable to deal with interval-valued probability. Additionally, it should be noticed that the situation of Bel n (θ j ) � Pl n (θ j ) actually exists in practice when DMs only definitely assign the probabilities with no ignorance on single elements of the frame of discernment rather than any subset including more than one element.…”

Section: Fusion Of Information At the Criterion Levelmentioning

confidence: 99%

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Multiple Criteria Group Decision-Making Method with Dempster–Shafer Theory and Probabilistic Linguistic Term Sets

Wang

2020

Mathematical Problems in Engineering

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The motivation of this study is to propose a novel multiple criteria group decision-making (MCDGM) method based on Dempster–Shafer theory (DST) and probabilistic linguistic term sets (PLTSs) to handle the distinctions between compensatory information at the criterion level and noncompensatory information at the individual level in the process of information fusion. Initially, the information at the individual level is extracted by BPA functions. Then, they are fused with DST considering ignorance and DMs’ reliabilities. Next, the obtained BPA functions are transformed into interval-valued PLTSs with the assistance of intermediate belief and plausibility. Subsequently, the interval-valued PLTSs are converted into standard PLTSs. After normalization, the holistic PLTS is obtained with weighted addition operation and the round function is applied to determine the ultimate evaluation result. Finally, a case simulation study of evaluating the marine ranching ecological security is presented to verify and improve the validity and feasibility of the proposed method and algorithm in practical application. The proposed method and its relevant algorithm are both innovative combination of DST and PLTSs from the perspective of compensatory and noncompensatory features of information, which provides a new angle of view for the development of probabilistic preference theory and is beneficial to apply probabilistic preference theory in practice.

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“…Liu and Li [12] applied prospect theory to the decision environment of probabilistic linguistic and proposed a multiobjective optimization method of MUL-TIMOORA based on prospect theory. Gu et al [13] proposed a multiattribute decision-making framework based on prospect theory in probabilistic linguistic environment. Wang et al [14] constructed a novel risk priority model for failure mode and effects analysis (FMEA).…”

Section: Introductionmentioning

confidence: 99%

A Novel IVPLTS Decision Method Based on Regret Theory and Cobweb Area Model

Peng

2020

Mathematical Problems in Engineering

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For the multiple criteria decision-making (MCDM) problem with interval-valued probabilistic linguistic information, we propose a novel method considering the regret theory and cobweb area model. We first propose a new score function, which can be used to compare different interval-valued probabilistic linguistic term sets (IVPLTSs) and transform the IVPLTSs into crisp numbers. Some properties of the score function are verified. Then, we utilize the regret theory to obtain the perceived utilities of decision makers (DMs), which can reflect the DMs’ bounded rationality. Furthermore, we use the cobweb area model to aggregate decision information. Finally, a real case of evaluating nursing homes is used to illustrate the effectiveness and features of our method.

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A decision-making framework based on prospect theory with probabilistic linguistic term sets

Cited by 30 publications

References 22 publications

Evolutionary Game Analysis of Firms’ Technological Strategic Choices: A Perspective of the Behavioral Biases

Evolutionary Game Analysis of Firms’ Technological Strategic Choices: A Perspective of the Behavioral Biases

Multiple Criteria Group Decision-Making Method with Dempster–Shafer Theory and Probabilistic Linguistic Term Sets

A Novel IVPLTS Decision Method Based on Regret Theory and Cobweb Area Model

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