Strategic measure of competitiveness for ranked data

Andrew J. Rohm, Sangit Chatterjee and Mohamed Habibullah
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Andrew J. Rohm: Northeastern University, College of Business Administration, 360 Huntington Avenue, 219 Hayden Hall, Boston, MA 02115, USA, Postal: Northeastern University, College of Business Administration, 360 Huntington Avenue, 219 Hayden Hall, Boston, MA 02115, USA
Sangit Chatterjee: Northeastern University, College of Business Administration, 360 Huntington Avenue, 219 Hayden Hall, Boston, MA 02115, USA, Postal: Northeastern University, College of Business Administration, 360 Huntington Avenue, 219 Hayden Hall, Boston, MA 02115, USA
Mohamed Habibullah: Northeastern University, College of Business Administration, 360 Huntington Avenue, 219 Hayden Hall, Boston, MA 02115, USA, Postal: Northeastern University, College of Business Administration, 360 Huntington Avenue, 219 Hayden Hall, Boston, MA 02115, USA

Managerial and Decision Economics, 2004, vol. 25, issue 2, 103-108

Abstract: This study offers a method of evaluating the stability of ranks of a data vector over time. In particular, we study improvement of a process observed over time where the data is ranked. The degree of competition at a major tennis championship (Wimbledon) as well as how trends in the level of competition have changed over time is studied. A metric for shifts in competitiveness and a new statistical methodology is proposed. The findings suggest that competitiveness at Wimbledon has been extremely high. The study offers implications for the sport of tennis as well as an approach to measuring competitive dynamics that can be applied to other contexts. Copyright © 2004 John Wiley & Sons, Ltd.

Date: 2004
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Persistent link: https://EconPapers.repec.org/RePEc:wly:mgtdec:v:25:y:2004:i:2:p:103-108

DOI: 10.1002/mde.1111

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