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UBC Theses and Dissertations

Recos : a request-commitment support model Lu, Feng

Abstract

Organizational work often requires cooperation among workers to achieve task completion. One type of cooperation can be described by the pair , where a “commitment” is defined as an agreement with the requester to carry out the requested action. When a worker receives a request, he must decide what to do with it. In general, many requests demand the responder’s future action, and require substantial resources to complete. For these types of requests, the worker goes through a reasoning process to decide whether he should commit to doing the requested work. The research question of this thesis is: can we build a computerized system to support an individual’s reasoning process in establishing a commitment? In this thesis, a computer-based Request-Commitment Support (RECOS) model is presented in attempting to answer this question. The RECOS model is primarily based on the commitment theory in sociology, the social rule system theory, the contract theory, and artificial intelligence techniques. It proposes that the most relevant factors determining an agent’s commitment are: 1) resource gains/losses, 2) the agent’s competence for fulfilling the requested action, 3) requester, the relationship between the requester and responder, and the related others’ expectations of the agent’s decision about the request, 4) organizational regulations, and 5) the agent’s previous commitments. A computer-based system built on RECOS would assist a user to select the relevant factors and to evaluate these factors, as well as to integrate the evaluation results, in order to make a better justified and consistent commitment. Specifically, it would be able to provide a user with the following support which, we believe, is not typical of traditional decision support systems: • Alerting the user when he makes a commitment that conflicts with prior commitments • Suggesting those individuals that the user can ask to work jointly on the request • Considering sentimental attributes • Conducting simple, single-issue negotiation with the requester or other collaborators • Automatically processing standard requests • Providing limited learning capability (i.e., through case base) in handling non-standard requests A user evaluation of the model has been conducted and the feedback appears promising. A prototype based on the model has been developed using Turbo-Prolog to demonstrate how a system built on the model operates.

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