Improvement of e-government service process via a grey relation agent mechanism
This study employs classification and clustering analyses to promote public officials' service performance and enhance citizens' satisfied process. A descriptive data mining approach is applied to achieve a pattern of citizens' satisfaction, and also establishes a fitting grey relation agent to handle the re-service process when a citizen is unsatisfied for his/her on-line requests. This work collected 2023 cases, which are collected from the satisfaction quantity tables in the On-line Service System of Kaohsiung City Government (OSSKCG) database. These cases are accessed during the period from the first of September 2008 to the thirty-first of August 2009. The results of the study show that our selected seven critical measuring indicators could positively evaluate twenty service items and five citizens' attributes, and could report the service performance or automatically recreate a case after citizen was unsatisfied. (C) 2012 Elsevier Ltd. All rights reserved.
e-government service process grey relation agent on-line service system