Previous efforts to improve stakeholders’ involvement in planning and decision-making processes mostly put planners and decision makers as the ones who decide which solution is the best for the decision problems. In bottom-up planning and decision-making processes that supposedly involve stakeholders as much as possible, the most common practice is that when stakeholders have different preferences about the decision issues, supra decision makers such as planners and experts gather stakeholders’ preferences, and then, using their expertise and experience, decide what is the best choice for stakeholders. We approach the involvement of stakeholders in planning and decision-making not by relying on planners’ expertise but from a negotiation perspective. Previous works related to stakeholders’ negotiation mostly require stakeholders to engage in a face-to-face negotiation that seldom involves a computer system to improve the process. In this paper, we develop a negotiation system to support multi-issue and multi-stakeholder decision-making problems. In our approach, stakeholders do not directly interact with each other. Their proposals are submitted to a system that produces counter-proposals to reduce the differences among stakeholders’ proposals. Therefore, stakeholders do not exchange their preferences directly, but rather preference elicitations are mediated by the system. This approach is called computer-mediated negotiation. The system itself is based on the principle of an orthogonal strategy. Our computer-mediated negotiation protocol consists of two main phases. The first phase is the preference elicitation phase, which measures stakeholders’ utility functions. The second phase is the e-negotiation phase, in which stakeholders make their proposals and the computer system provides suggestions to improve them. To simulate real-world negotiations where stakeholders make proposals and counter-proposals in a series of negotiation rounds, we implemented the indifference curve approach to enable stakeholders to make incremental changes of their proposals during negotiation. The results from our experiment suggest that our method can produce an optimum solution for a multi-issue and multi-stakeholder decision problem by moving stakeholders’ proposals closer to one another.
|Number of pages||25|
|Journal||Environment and Planning B: Urban Analytics and City Science|
|Publication status||Published - 1 Jul 2019|