Managing data quality of cooperative information systems: Model and algorithm

Abstract

The low data quality of a cooperative information system (CIS) causes cooperative organizations to recollect data frequently rather than use the data already in the system. In this paper, a method based on source control is proposed to reduce the data quality problem of CIS. It emphasizes improving the data quality of CIS by controlling the data quality of subsystems rather than by screening data. Further, we develop two optimization models for the scenes of independent and negotiated decisions. Compared with the independent decision model, the negotiation decision model considers the impact of the game behavior between the manager of the CIS and the manager of each subsystem on the data quality optimization. The results of the models provide an optimal strategy for allocating capital to minimize the data quality problem of a CIS. To solve the models, we propose an improved artificial bee colony algorithm that enhances the exploration ability by modifying the behaviors of bees. A CIS of a government is used to illustrate the application process of the models and the superiority of the algorithm. The results show that, in all cases, the optimal strategy provided by the negotiation decision model is not worse than that offered by the independent decision model, and the result obtained by the proposed algorithm is better than other comparative algorithms.