Group Decision and Negotiation最新文献

As user-generated online content has been flourishing with both useful information and misinformation. One of the complexities surrounding such phenomena is its huge amounts of data and its associated difficulties to effectively moderate content, particularly as most initiatives are centralised and fraught with its intrinsic trust issues. One of the few examples using mainly a decentralised (i.e., community-driven) mechanism is Twitter’s Community Notes (once named as Birdwatch) experimental project. This paper thus is about testing the efficiency of such community-based content moderation mechanism and scenarios of interest aiming to better understanding how the users themselves better moderate online content. This is done through an agent-based approach and three conclusions are discussed in detail: (1) to some extent the community is able to fight against misinformation, (2) a Birdwatch-like mechanism can indeed boost the community’s content moderation ability, but there is a nontrivial trade-off between social influence and content timeliness and (3) a simple proposition, in the form of a reminder mechanism to users, cannot fulfil the task of improving the content moderation efficiency, which means a different approach to design is needed.

The increasing frequency of extreme weather (EW) events has created significant vulnerabilities in the normal operations of the prefabricated construction supply chain (PCSC). This study aims to enhance the resilience of the PCSC against EW by utilizing smart contracts. The study proposes a prototype smart contract application to mitigate the risks posed by EW to the PCSC. Additionally, it identifies 28 potential barriers affecting smart contract adoption in the PCSC using the Technology-Organization-Environment framework. Furthermore, the paper presents a multi-objective optimization-based group decision-making method to assess the feasibility of smart contract adoption in the PCSC. An online survey was then conducted among 50 stakeholders from various links of the PCSC to gather insights into smart contract adoption. The results indicate that stakeholder awareness of smart contracts and the current corporate level are the most influential factors in decision-making. This research extends the application of smart contracts to risk management within the PCSC, offering valuable insights for stakeholders to enhance resilience and address the adverse effects of EW proactively.

There are numerous proposals for Group Decision-Making (GDM) inspired by the ELECTRE multiple criteria decision approach. These proposals capitalize on ELECTRE's resemblance to certain voting systems and its ability to navigate veto situations. However, while ELECTRE-based methods have commendable features for establishing the credibility degree of the predicate “x is collectively considered at least as good as y”, they do not address three relevant issues: (1) the reinforced preference in favor of x exhibited by certain members of the group; (2) the strength of the coalition of Decision-Makers (DMs) who favor y over x; and (3) the effects of preference dependence (complementarity, redundancy, antagonism) among different DMs. This paper addresses group ranking problems within scenarios where a group is under the control of a special powerful actor, called a “Supra-Decision Maker”, or when a group adheres to a predetermined system of rules agreed upon by its members. Unlike other ELECTRE-based methods for GDM, this proposal comprehensively addresses the issues (1), (2) and (3) to determine the credibility degree of the collective outranking predicate. This determination can be utilized to derive a collective ranking or another form of recommendation in GDM. This proposal is expected to excel in a collaborative organizational environment where group members express genuine judgments, devoid of malicious intentions to manipulate collective decisions. Moreover, it has relevance in socially oriented decision-making contexts, especially when government agencies seek to reconcile opinions of diverse stakeholder groups with highly contradictory points of view. In such scenarios, where phenomena such as preference dependence, reinforced preference, and intense disagreement manifest, this proposal could offer valuable insights.

Group consensus (GC) is important for generating a group solution satisfactory or acceptable to most decision-makers in a group. Its convergency usually depends on several rounds of iterations and becomes more difficult with unknown parameters because GC is usually associated with parameters. To address the GC with unknown parameters, this paper proposes a Markov chain-based GC method, in which criterion weights and expert weights are considered as parameters. Given the interval-valued assessments of decision-makers, the GC at the alternative and global levels is defined. Based on the Markov chain, a two-hierarchical randomization algorithm is designed with unknown criterion weights to determine the transition probability matrix used to generate the stable GC. To accelerate the stable GC’s convergency, criteria significantly contributing negatives to the stable GC are identified and suggestions on helping renew decision-makers’ assessments on the identified criteria are provided. On the condition that the stable GC is definitely satisfied, a GC-based two-hierarchical randomization algorithm is designed based on the Markov chain to determine the transition probability matrix for generating the stable ranking value distribution of each alternative. The proposed method is employed to analyze a development mode selection problem. It is compared with the stochastic multicriteria acceptability analysis and simple additive weighting methods based on the problem by calculation and principle.

Bargaining with suppliers is a key Purchasing and Supply Management (PSM) activity but there is considerable ambiguity over what bargaining entails and the concept currently lacks a systematic treatment, despite its significant interest to PSM professionals. The literature shows that bargaining can be seen as an adversarial approach to negotiation (in contrast to more integrative/collaborative ones) and also the back-and-forth discussion over price and other variables between buying and supplying organisations to reach an agreement. In addition, many will move between fundamentally distributive and integrative approaches as the discussions play out. A systematic literature review of the Scopus, ProQuest, ScienceDirect, JSTOR and Web of Science databases was undertaken to address this gap, identifying 427 relevant journal papers that were systematically analysed. First, descriptive techniques identified the trajectory of published papers, methods, theories and their industrial context. Second, content analysis identified the key constructs and associated operational measures/variables of bargaining. Third, the constructs have then been ordered temporally and by areas of location (organisational/departmental and individual levels) to generate a model and inform a series of practice-based recommendations at different stages of the bargaining process. The findings will allow future researchers to use the constructs either directly in developing focused hypotheses to test relationships or as a basis for refinement and extension in cumulative theory building and testing. In addition, a series of focused research gaps have been identified, such as addressing the current contradictory findings of the effect of purchasing volume or organisational size on bargaining power.

Scoring rules are a popular method for aggregating rankings; they are frequently used in many settings, including social choice, information retrieval and sports. Scoring rules are parametrized by a vector of weights (the scoring vectors), one for each position, and declare as winner the candidate that maximizes the score obtained when summing up the weights corresponding to the position of each voter. It is well known that properly setting the weights is a crucial task, as different candidates can win with different scoring vectors. In this paper, we provide several methods to identify the winner considering all possible weights. We first propose VolumetricTop, a rule that ranks alternatives based on the hyper-polytope representing the set of weights that give the alternative the highest score, and provide a detailed analysis of the rule from the point-of-view of social choice theory. In order to overcome some of its limitations, we then propose two other methods: Volumetric-runoff, a rule that iteratively eliminates the alternative associated with the smallest region until a winner is found, and Volumetric-tournament, where alternatives are matched in pairwise comparisons; we provide several insights about these rules. Finally we provide some test cases of rank aggregation using the proposed methods.

The product–service system (PSS) is a strategic design approach proposed to address sustainability in socio-economic systems amidst rapid industrialization and transition. Evaluating the concept design of a PSS is a crucial and initial step prior to implementation. This study presents an innovative framework for evaluating concept designs of sustainable PSS based on a well-defined evaluation index system via integrating quality function deployment (QFD) and the technique for order preference by similarity to ideal solution (TOPSIS) while accommodating extended basic uncertain linguistic information (EBULI). Specifically, a QFD-based framework is first developed to identify the requirements of various stakeholders and then to establish the multi-dimensional criteria for evaluating sustainable PSS. Then, a House of Quality-based relationship matrix is introduced to determine the weights of criteria more accurately. Further, an adaptive consensus-reaching process method based on an expert weighting optimization model is proposed to ensure a collective outputs recognized by multiple involved stakeholders. Finally, an improved EBULI-based TOPSIS method is presented to determine the priority ranking of alternative sustainable PSS concepts. A case study on a car-sharing PSS project demonstrates the viability and effectiveness of the proposed QFD–TOPSIS integrated approach under EBULI settings. The alternative PSS concept design, which demonstrates relatively good performance in criteria of high importance, is selected as the most suitable option. Moreover, relevant comparative and sensitivity analyses reveal that the proposed approach exhibits superiorities in appropriate criteria elicitation, accurate weights determination, and high consensus ranking outputs.

In the consensus reaching process of group decision making (GDM), consensus measures do not require the consensus opinions of all decision makers. Meanwhile, unit adjustment cost is one of the important and often uncertain factors that affect consensus in GDM. Due to the uncertainty of unit adjustment costs, the moderator may not be able to provide each decision maker with an accurate unit adjustment cost. To overcome these problems, a novel class of group consensus decision models is proposed in this paper. First, fuzzy consensus measures are defined to make the consensus flexible using the specificity and coverage of the consensus granule. Secondly, to describe the uncertainty of the cost of unit adjustment, three uncertainty scenarios are created by the robust optimization approach is introduced. In the end, the feasibility and applicability of the method are verified by taking the classical GDM problem as an example, and sensitivity and comparative analyses are also performed.