Sales performance measurement in bank branches |
| |
| Institution: | 1. Turku Institute for Advanced Studies / Turku School of Economics, Department of Marketing, FI-20014, University of Turku, Finland;2. University of Paderborn, Department of Marketing, Warburger Strasse 100, 33098 Paderborn, Germany;3. Newcastle University Business School, 5 Barrack Road, Newcastle upon Tyne NE1 4SE, United Kingdom;4. Justus Liebig University, Department of Marketing, Licher Str. 66, 35394 Giessen, Germany;5. IMD — International Institute for Management Development, Chemin de Bellerive, 23, 1001 Lausanne, Switzerland;1. School of Economics, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands;2. Ross School of Business, University of Michigan, 701 Tappan Street, Ann Arbor, MI 48109-1234, USA;3. Amsterdam Business School, University of Amsterdam, Section of HRM-OB, Plantage Muidergracht 12, 1018 TV Amsterdam, The Netherlands;1. Department of Marketing, Drexel University, Philadelphia, PA 19104, United States of America;2. Department of Marketing, University of Georgia, Athens, GA 30602, United States of America;3. Accounts Payable Department, University of Georgia, Athens, GA 30602, United States of America |
| |
| Abstract: | Studies of bank branch performance have, to date, concentrated on obtaining a single perspective of efficiency. As the financial services industry has intensified, banks have increasingly engated in a proactive, differentiated and customer-based strategy in retail banking in which the sales component of the bank branch activity is emphasized. With the emerging sales culture within banks, as discussed earlier, there is a need to evaluate both sales and service performance. Cook et al. 12] have proposed a model to evaluate simultaneously the sales, service, and aggregate efficiencies of a bank branch. This model accounted for the fact that inputs, in particular resources, are often shared among these functions. In this paper, we extend the data envelopment analysis additive model using goal programming concepts. We thereby derive optimal efficiency scores while taking into account non-volume related activities, that is those involving resources that cannot be assigned to a specific input or output. Again, the proposed model derives an optimal split of the shared resources that maximizes the aggregate efficiency. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
