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

Abstract

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.

The Research of Key Indicators of Performance to Predict to Advance the Knock Out Stage in the International Football Tournament

“…In order to analyse the data, we conducted a GRA to determine each team's performance with respect to their UEFA Euro 2021 or Copa America 2021 rivals. GRA is a multistep procedure that provides a comprehensive ranking system for sets of data [4,17,19]. According to Chuang et al [19], GRA is one of very popular methods to analyse various relationships among the discrete data sets and make decisions in multiple criteria situations.…”

“…GRA is a multistep procedure that provides a comprehensive ranking system for sets of data [4,17,19]. According to Chuang et al [19], GRA is one of very popular methods to analyse various relationships among the discrete data sets and make decisions in multiple criteria situations. us, this study uses GRA to calculate the weight of goals impact criteria (total attempts, on target, possession, passes attempted, passing accuracy, fouls committed, off sides, and corners taken) and team of performance in the knock out stage.…”

“…ξ is the distinguishing coefficient whose purpose is to expand or compress the range of the grey relational coefficient. Generally, 0.5 is taken as a benchmark [19].…”

Identifying and Prioritizing Service Compensation Factors Influencing Nurses’ Motivation: Application of Hybrid Fuzzy DEMATEL-BWM Method

“…Chuang et al ( 2018 ) specified criteria that influence players’ salaries. Then, they adopted a gray relational analysis (GRA) and gray prediction model to calculate the weight of effective salary criteria, players’ annual performance index, and next year’s salary forecast.…”

“…The results revealed that service compensation has a positive and significant effect on work motivation, and one can argue that it is approximately 6.5% effective in increasing work motivation. Chuang et al (2018) specified criteria that influence players' salaries. Then, they adopted a gray relational analysis (GRA) and gray prediction model to calculate the weight of effective salary criteria, players' annual performance index, and next year's salary forecast.…”