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Mathematical Problems in Engineering
Volume 2018 (2018), Article ID 7365615, 9 pages
Research Article

Application of Grey Theory in the Construction of Impact Criteria and Prediction Model of Players’ Salary Structure

1Department of Management Sciences, Tamkang University, New Taipei City, Taiwan
2Department of Sport Management, Aletheia University, New Taipei City, Taiwan

Correspondence should be addressed to Chih-Cheng Chen

Received 22 September 2017; Revised 10 January 2018; Accepted 22 January 2018; Published 25 February 2018

Academic Editor: Emilio Jiménez Macías

Copyright © 2018 Chung-Chu Chuang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Salaries of professional players are usually determined prior to the execution of the responsibilities assigned by the organizations and are often based on the expected future performance of these players as derived from their past achievement. The study first identifies criteria that would affect players’ salaries through literature reviews and then utilizes grey relational analysis (GRA) and grey prediction model to calculate weights of salary impact criteria, players’ annual performance index, and salary prediction for the coming year. The performance data of players from the Chinese Professional Baseball League (CPBL) are used in this study. The results are as follows: (i) CPBL teams do refer to players’ past performance records and future performance prediction when deciding on their salaries and (ii) future performance prediction must be made using at least a 3-year data set. The proposed prediction model is able to effectively provide relevant and useful information to the CPBL teams’ management during players’ salary adjustment.