Performance Measurement in Cargo Distribution Center A Case Study

Year 2022, Volume: 6 Issue: 1, 1056 - 1064, 30.06.2022

Pervin Ersoy , Burak Çetiner

Abstract

Cargo transportation is a key element for an effective and properly functioning logistics chain. Due to the role it plays in overall logistics chain performance, it is important for cargo firms to be at their peak level in terms of provided service quality and implementation. Continuous performance evaluation is critical for diagnosing and preventing any problems that might disrupt the firms’ ability to keep providing their services and further prevent customer dissatisfaction. Therefore, the aim of this paper is identifying the problems that cause the performance of Company X’s distribution center located in City A to stay below desired levels, which consequently lead to customer dissatisfaction, and to offer a feasible solution for the identified problems. In order to identify underlying problems, performances of two distribution centers located in different cities are compared and improvements for worker performance, workload distribution, and processes are suggested.

Keywords

Cargo Transportation, Service Quality, Distribution Center, Performance Measurement

References

• Akyuz, G. A., & Erkan, T. E. (2010). Supply chain performance measurement: a literature review. International journal of production research, 48(17), 5137-5155.
• Bititci, U. S., Carrie, A. S., & McDevitt, L. (1997). Integrated performance measurement systems: a development guide. International journal of operations & production management, 17(5), 522-534.
• Boussofiane, A., Dyson, R.G. and Thanassoulis, E. (1991), “Applied data envelopment analysis”,European Journal of Operational Research, Vol. 52 No. 1, pp. 1-15.
• Chan, F. T. (2003). Performance measurement in a supply chain. The international journal of advanced manufacturing technology, 21(7), 534-548.
• Folan, P., & Browne, J. (2005). A review of performance measurement: Towards performance management. Computers in industry, 56(7), 663-680.
• Jordan, K. (2009). Performans Değerlendirme Harvard Business School Press Pocket Mentor. Çev: Melis İnan, City Y: Optimist Yayınları.
• Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., & Bansal, R. C. (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596-609.
• Min, H. and Joo, S.J. (2006), “Benchmarking the operational efficiency of major third-party logistics providers using data envelopment analysis”, Supply Chain Management: An International Journal, Vol. 11 No. 3, pp. 259-65
• Murphy, D.J., Pearson, J.N. and Siferd, S.P. (1996), “Evaluating performance of the purchasing department using data envelopment analysis”, Journal of Business Logistics, Vol. 17 No. 2, pp. 77-91.
• Nozick, L. K., Borderas, H., & Meyburg, A. H. (1998). Evaluation of travel demand measures and programs: a data envelopment analysis approach. Transportation Research Part A: Policy and Practice, 32(5), 331-343.
• Parker, C. (2000). Performance measurement. Work study, 49(2), 63-66.
• Poli, P.M. and Scheraga, C.A. (2000), “The relationship between the functional orientation of senior managers and service quality in LTL motor carriers”, Journal of Transportation Management, Vol. 12 No. 2, pp. 17-31
• Shafer, S.M. and Byrd, T.A. (2000), “A framework for measuring the efficiency of organizational investments in information technology using data envelopment analysis”, Omega, Vol. 28, pp. 125-41
• Talluri, S., Hug, F. and Pinney, W.E. (1997), “Application of data envelopment analysis for cell performance evaluation and process improvement in cellular manufacturing”, International Journal of Production Research, Vol. 35 No. 8, pp. 2157-70.
• Valdmanis, V. (1992), “Sensitivity analysis for DEA models: an empirical example using public vs NFP hospitals”, Journal of Public Economics, Vol. 48 No. 2, pp. 185-205.
• White, G. P. (1996). “A survey and taxonomy of strategy‐related performance measures for manufacturing”, International Journal of Operations & Production Management, 16(3), 42-61
• Zacharia, Z. G., Sanders, N. R., & Nix, N. W. (2011). The emerging role of the third‐party logistics provider (3PL) as an orchestrator. Journal of Business Logistics, 32(1), 40-54.