Service performance evaluation using data envelopment analysis and balance scorecard approach: an application to automotive industry
- 1.7k Downloads
In today’s competitive business environment, service providers have a strong objective to satisfy the customers with low cost to ensure a patronage/loyalty. Performance measurement defines the information or feedback on actions to meeting strategic objectives and client satisfaction. Generally, performance evaluation of the service provider is a time consuming complicated process, depends customer satisfaction. Over the past two decades several researchers have proposed methods to measure service and quality performance in order to improve the performance efficiency of the organization, since there is a considerable room exists. Hence, in this paper, we analyse efficient and inefficient levels of service performance using data envelopment analysis (DEA) and balance scorecard (BSC) techniques, to bridge the exist gap. The DEA approach has been used to measure the performance of automobile dealers from different areas to know their service levels and also treats the quality of service by making use of different cross-efficiency data envelopment analysis models to discriminate the units. Then, a BSC approach analyzes which aspects of decision making units are inefficient, grounded on four perspectives like as; customers, financial, internal business process and learning and growth, based on the study carried out on ten automobile dealers from various areas. The results identify that dealers are inefficient in learning about customer’s growth, which help the dealers to transform from inefficient into efficient. In addition, this study also focused on various insights related to performance evaluation and provide some useful recommendations which can be practiced in future.
KeywordsPerformance measurement Data envelopment analysis (DEA) Balanced scorecard (BSC) Automotive industry
This research was supported in part by the National Natural Science Foundation of China (Grant Nos. 71302005, 71402084), the major Program of the National Social Science Fund of China (Grant No. 13&ZD147).
- Alves, M. E. D., & Portela, M. C. S. (2015) Performance evaluation of PARFOIS retailing stores. In: Operational research (pp. 1–17). Berlin: Springer.Google Scholar
- Andes, S. (2002). Measuring efficiency of physician practices using data envelopment analysis. Managed Care, 11(11), 48–56.Google Scholar
- Beechey, J., & Garlick, D. (1999). Using the balanced scorecard in banking. Journal of the Australian Institute of Bankers, 113(1), 28–31.Google Scholar
- Brewer, P. C., & Speh, T. W. (2000). Using the balanced scorecard to measure supply chain performance. Journal of Business Logistics, 21(1), 75–94.Google Scholar
- Denton, G. A., & White, B. (2000). Implementing a balanced-scorecard approach to managing hotel operations: The case of white lodging services. The Cornell Hotel and Restaurant Administration Quarterly, 41(1), 94–107.Google Scholar
- Eilat, H., Golany, B., & Shtub, A. (2006). R&D project evaluation: An integrated DEA and balanced scorecard approach. Omega. doi: 10.1016/j.omega.2006.05.002.
- Farrell, M.J., (1957). The measurement of productive efficiency. Journal of the Royal Statistical Association Series A, CXX, 253–281.Google Scholar
- Fitzgerald, L., Johnston, R., Brignall, T. J., Silvestro, R., & Voss, C. (1991). Performance measurement in service businesses. London: CIMA.Google Scholar
- Gaiardelli, P., Saccani, N., & Songini, L. (2006). Performance measurement systems in the after sales service: An integrated framework. International Journal of Business Performance Measurement, 9(2), 147–171.Google Scholar
- Gouveia, M. C., Dias, L. C., Antunes, C. H., Mota, M. A., Duarte, E. M., & Tenreiro, E. M. (2015). An application of value-based DEA to identify the best practices in primary health care. OR Spectrum (pp.1–25).Google Scholar
- Hong, S., Yuedong, Z., & Gang, W. (2015). Efficiency evaluation of low-carbon agriculture development supported by public finance based on DEA—taking Heilongjiang province as an example. Chinese Agricultural Science Bulletin, 23, 046.Google Scholar
- Jalali Naini, S. G., Aliahmadi, A. R., & Jafari-Eskandari, M. (2011). Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: A case study of an auto industry supply chain. Resources, Conservation and Recycling, 55, 593–603.CrossRefGoogle Scholar
- Ji, X., Wu, J., & Zhu, Q. (2015). Eco-design of transportation in sustainable supply chain management: A DEA-like method. Transportation Research Part D: Transport and Environment (in press).Google Scholar
- Kaplan, R. S., & Norton, D. P. (1992a). The balanced scorecard as a strategic management system. Harvard Business Review, 6, 1–66.Google Scholar
- Kaplan, R. S., & Norton, D. P. (1992b). The balanced scorecard: Measures that drive performance. Harvard Business Review (January–February) (pp. 71–79).Google Scholar
- Kaplan, R. S., & Norton, D. P. (1996a). Using the balanced scorecard as a strategic management system. January–February. Harvard Business Review.Google Scholar
- Kaplan, R. S., & Norton, D. P. (1996b). The balanced scorecard—Translating strategy into action. Boston, MA: Harvard Business School Press.Google Scholar
- Kaplan, R. S. (1998). Innovation action research: Creating new management theory and practice. Journal of Management Accounting Research, 10(89–1), 18.Google Scholar
- Kaplan, R. S., & Norton, D. P. (2006). Alignment: Using the balanced scorecard to create corporate synergies. Boston: Harvard Business Press. 302.Google Scholar
- Koning, G. M. J. (2004). Making the balanced scorecard work (part 1). Gallup Management Journal. http://gmj.gallup.com/content/12208/making-balancedscorecard-work-part.aspx.
- Neely, A., Adams, C., & Kennerley, M. (2002). The performance prism: The scorecard for measuring and managing business success. London: FT Prentice-Hall.Google Scholar
- Parasuraman, A., Zeithaml, V., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 13–40.Google Scholar
- Qi, Z. (2015). Empirical research on the efficiency of resource allocation of compulsory education based on DEA—Case study of primary schools in an eastern city. Educational Research, 3, 012.Google Scholar
- Sexton, T. R., Silkman, R. H., & Hogon, A. J. (1986). Data envelopment analysis. Critique and extensions. In R. H. Silkman (Ed.), Measuring efficiency: An assessment of DEA (pp. 73–105). San Francisco, CA: Jossey-Boss.Google Scholar
- Thanassoulis, E., De Witte, K., Johnes, J., Johnes, G., Karagiannis, G., & Portela, M. (2016). Applications of DEA in education.Google Scholar
- Zhang, W. (2015). The analysis of the agriculture input and output efficiency based on DEA model. Agricultural Science & Technology, 16(2), 414.Google Scholar