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Journal of business and psychology, 2017-10, Vol.32 (5), p.595-610
2017

Details

Autor(en) / Beteiligte
Titel
First and Second Strings: Using Entity Analytics to Contrast Core and Supporting Teams
Ist Teil von
  • Journal of business and psychology, 2017-10, Vol.32 (5), p.595-610
Ort / Verlag
New York: Springer Science + Business Media
Erscheinungsjahr
2017
Link zum Volltext
Quelle
EBSCOhost Business Source Ultimate
Beschreibungen/Notizen
  • Purpose This research demonstrates the importance of the concept of the core team (Humphrey et al. in Journal of Applied Psychology 94:48–61, 2009 ) in contrast to supporting or peripheral members within the context of larger nominal teams. It asks the question, “In a team-oriented organization, should we assume that all nominal team members are, in fact, relatively equal contributors?” Design Utilizing individual batter, fielder, and pitcher data from the National League from 2005 to 2014, we operationalize the concept of the core group, which is a subset of high-performing members. Findings After testing for aggregation, we found that for core team members, their collective versions of batting average, runs batted in (RBI), and pitching earned run average (ERA) significantly predicted team win-loss percentages with an R 2 of .62, p < .0001. The prediction of team attendance based on the performances of the core team was also significant with an R 2 of .40, p < .0001. The same three independent variables based solely on supporting players were neither aggregable nor significant. Similarly, results for the nominal teams composed of all players on the roster were also not aggregable. Implications These findings highlight the importance of identifying and managing core members (Fonti et al. Strategic Management Journal 37:1765–1786, 2016 ). Implications for team settings in management and business settings are discussed. Originality WABA provides a unique multi-level, visual analytical tool for testing the existence of entities for these baseball data. Its application shows very different data configurations for nominal, core, and support subteams and dissimilar patterns of relationships among the key performance variables for each type of team.

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