Group Decision and Negotiation最新文献

We consider a situation in which two parties have concluded an efficient contract corresponding to one major bargaining solution. After the parties have agreed on one particular contract, an unanticipated shock may change the contract outcomes in a way that benefits one party but harms the other party. If this happens, they have the option to either stay with the original exchange contract or adjust some contract parameters such as the price. We propose a model to perform such adjustments automatically, to obtain the same bargaining solution as in the initial contract under the restriction that the new contract dominates the outcomes of the original contract. We study several bargaining solutions within this general framework. These bargaining solutions offer various sharing rules to distribute the benefit between the parties. To reflect practical considerations, we only consider adjustments made via one contract parameter (the price), while all other parameters result from the original contract and the random shock. To evaluate the efficiency of the proposed approach, we also compare it to a full re-negotiation scenario, in which all parameters can be modified within the boundaries resulting after the random shock. However, waiting and re-negotiation might be costly compared to the situation when the smart contract executes the adjustment automatically. Therefore, the automatic adjustment might be more efficient compared to the other types of contracts. We present several numerical examples and run large random simulations, which we also check statistically.

Digital platforms facilitate the coordination, match making, and value creation for large groups of individuals. In consumer-to-consumer (C2C) online sharing platforms specifically, trust between these individuals is a central concept in determining which individuals will eventually engage in a transaction. The majority of today’s online platforms draw on various types of cues for group coordination and trust building among users. Current research widely accepts the capacity of such cues but largely ignores their changing effectiveness over the course of a user’s lifetime on the platform. To address this gap, we conduct a laboratory experiment, studying the interplay of cognitive and affective trust cues over the course a multi-period trust experiment for the coordination of groups. We find that the trust-building capacity of affective trust cues is time-dependent and follows an inverted u-shape form, suggesting a dynamic complementarity of cognitive and affective trust cues.

The most difficult decision problems arise when several parties with several criteria must reach a consensus. This problem can be modelled as a game with vector-valued payoffs. If the players are allowed to use mixed strategies, there can be many Nash equilibria, and therefore many outcomes. The role of negotiation is to choose a specific outcome, or to restrict the set of outcomes to a small subset. One promising approach to negotiation support is scalarization of the vector payoff function. Here we apply Germeier scalarizing function, also known as the Rawlsian function, to mixed-strategy multicriteria games. After developing the mathematical background, we extend to these games the principle of Best Guaranteed Value, the value that a player may count on regardless of the other players’ actions. We suggest that a good outcome for negotiation in a multicriteria game is a Nash equilibrium outcome that provides each player with the payoffs that are better than its Best Guaranteed Value. We describe all such outcomes, thereby defining a new negotiation support mechanism.

Under competitive business scenarios, project selection is a crucial process for ensuring that projects appropriately align with an organization’s goals, available resources, and relationships. This study proposes a novel hybrid decision support model that integrates the best–worst method (BWM) with the elimination and choice expressing reality (ELECTRE) method to solve project selection problems. The approach can be used to determine the weights of criteria by comparing two vectors and to provide the best result based on concordance and discordance analysis. An empirical study regarding the selection of strategic marketing information system projects is conducted to demonstrate the proposed methodology’s benefits and rationality. The findings show that using the BWM–ELECTRE approach systematically leads to solid decision-making results involving compromise rankings based on quantitative and qualitative data, including decision-makers’ preferences. This study contributes to the literature with a new methodology that consumes less time, provides high consistency, and enables subjectivity reduction in human-based judgments while providing helpful information to decision-makers in choosing the best project and/or outranking results among different relationships, resource constraints, or dynamic environments.