Kun Zhou, Zaiwu Gong, Xiaoqing Chen, Roman Słowiński
{"title":"通过基于价值函数的达成共识过程确定具有代表性的集体价值函数","authors":"Kun Zhou, Zaiwu Gong, Xiaoqing Chen, Roman Słowiński","doi":"10.1007/s10726-024-09883-z","DOIUrl":null,"url":null,"abstract":"<p>Consensus-reaching among decision-makers (DMs) is an important prerequisite for effective group decision-making. Determining a collective value function that is recognized by major DMs is new in consensus research. We are approaching this problem by adopting the preference disaggregation analysis (PDA) to construct a novel consensus-reaching process (CRP). More precisely, we define the value function that can restore the preference information of all DMs as the consensus value function, and determine all such value functions by the PDA method. A consensus discriminant model is constructed to determine whether DMs can reach a consensus. Considering the adjustment cost of DMs, the minimum cost consensus model, and the minimum cost inconsistency elimination model, are constructed by introducing estimation errors and 0–1 variables, respectively, thus assisting DMs to reach a consensus. Furthermore, in the process of selecting a representative collective value function from the consensus space for subsequent decision analysis, a lexicographic optimization process is applied to convert the multi-objective programming problem of DMs’ individual requirements for the collective value function into a multi-stage single-objective programming problem. This study provides a new concept of consensus and extends the classic minimum cost consensus model to the case of value functions. Finally, an illustrative example showing the proposed CRP in action is presented, while conducting sensitivity analysis to explore the impact of parameter changes on the model.</p>","PeriodicalId":47553,"journal":{"name":"Group Decision and Negotiation","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determination of a Representative Collective Value Function Through a Value Function-Based Consensus-Reaching Process\",\"authors\":\"Kun Zhou, Zaiwu Gong, Xiaoqing Chen, Roman Słowiński\",\"doi\":\"10.1007/s10726-024-09883-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Consensus-reaching among decision-makers (DMs) is an important prerequisite for effective group decision-making. Determining a collective value function that is recognized by major DMs is new in consensus research. We are approaching this problem by adopting the preference disaggregation analysis (PDA) to construct a novel consensus-reaching process (CRP). More precisely, we define the value function that can restore the preference information of all DMs as the consensus value function, and determine all such value functions by the PDA method. A consensus discriminant model is constructed to determine whether DMs can reach a consensus. Considering the adjustment cost of DMs, the minimum cost consensus model, and the minimum cost inconsistency elimination model, are constructed by introducing estimation errors and 0–1 variables, respectively, thus assisting DMs to reach a consensus. Furthermore, in the process of selecting a representative collective value function from the consensus space for subsequent decision analysis, a lexicographic optimization process is applied to convert the multi-objective programming problem of DMs’ individual requirements for the collective value function into a multi-stage single-objective programming problem. This study provides a new concept of consensus and extends the classic minimum cost consensus model to the case of value functions. Finally, an illustrative example showing the proposed CRP in action is presented, while conducting sensitivity analysis to explore the impact of parameter changes on the model.</p>\",\"PeriodicalId\":47553,\"journal\":{\"name\":\"Group Decision and Negotiation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Group Decision and Negotiation\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s10726-024-09883-z\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Group Decision and Negotiation","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s10726-024-09883-z","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
Determination of a Representative Collective Value Function Through a Value Function-Based Consensus-Reaching Process
Consensus-reaching among decision-makers (DMs) is an important prerequisite for effective group decision-making. Determining a collective value function that is recognized by major DMs is new in consensus research. We are approaching this problem by adopting the preference disaggregation analysis (PDA) to construct a novel consensus-reaching process (CRP). More precisely, we define the value function that can restore the preference information of all DMs as the consensus value function, and determine all such value functions by the PDA method. A consensus discriminant model is constructed to determine whether DMs can reach a consensus. Considering the adjustment cost of DMs, the minimum cost consensus model, and the minimum cost inconsistency elimination model, are constructed by introducing estimation errors and 0–1 variables, respectively, thus assisting DMs to reach a consensus. Furthermore, in the process of selecting a representative collective value function from the consensus space for subsequent decision analysis, a lexicographic optimization process is applied to convert the multi-objective programming problem of DMs’ individual requirements for the collective value function into a multi-stage single-objective programming problem. This study provides a new concept of consensus and extends the classic minimum cost consensus model to the case of value functions. Finally, an illustrative example showing the proposed CRP in action is presented, while conducting sensitivity analysis to explore the impact of parameter changes on the model.
期刊介绍:
The idea underlying the journal, Group Decision and Negotiation, emerges from evolving, unifying approaches to group decision and negotiation processes. These processes are complex and self-organizing involving multiplayer, multicriteria, ill-structured, evolving, dynamic problems. Approaches include (1) computer group decision and negotiation support systems (GDNSS), (2) artificial intelligence and management science, (3) applied game theory, experiment and social choice, and (4) cognitive/behavioral sciences in group decision and negotiation. A number of research studies combine two or more of these fields. The journal provides a publication vehicle for theoretical and empirical research, and real-world applications and case studies. In defining the domain of group decision and negotiation, the term `group'' is interpreted to comprise all multiplayer contexts. Thus, organizational decision support systems providing organization-wide support are included. Group decision and negotiation refers to the whole process or flow of activities relevant to group decision and negotiation, not only to the final choice itself, e.g. scanning, communication and information sharing, problem definition (representation) and evolution, alternative generation and social-emotional interaction. Descriptive, normative and design viewpoints are of interest. Thus, Group Decision and Negotiation deals broadly with relation and coordination in group processes. Areas of application include intraorganizational coordination (as in operations management and integrated design, production, finance, marketing and distribution, e.g. as in new products and global coordination), computer supported collaborative work, labor-management negotiations, interorganizational negotiations, (business, government and nonprofits -- e.g. joint ventures), international (intercultural) negotiations, environmental negotiations, etc. The journal also covers developments of software f or group decision and negotiation.