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A performance evaluation of Major League Baseball teams: An integrated social network and data envelopment analysis
Author(s) -
Wang AnPang,
Chang CheWei,
Tsai JuinMing,
Hung ShiuWan
Publication year - 2021
Publication title -
managerial and decision economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.288
H-Index - 51
eISSN - 1099-1468
pISSN - 0143-6570
DOI - 10.1002/mde.3316
Subject(s) - betweenness centrality , data envelopment analysis , league , centrality , social network analysis , position (finance) , empirical research , operations research , business , scale (ratio) , measure (data warehouse) , computer science , marketing , operations management , industrial organization , economics , engineering , statistics , mathematics , data mining , physics , finance , astronomy , world wide web , social media , quantum mechanics
An organisation's position within a network is known to influence its performance. This study proposes a novel evaluation model, incorporating social networking variables, to measure 30 Major League Baseball (MLB) teams' performances. Using the data envelopment analysis (DEA) technique, the empirical results of this study show that inefficiencies are due to purely technical rather than scale effects. The results of a sensitivity analysis indicated that the betweenness centrality had a higher level of influence on each team's performance than on the salaries paid. If the betweenness centrality was not considered, five of the teams considered to be technically efficient would become inefficient.