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Finance Function Performance Measurement-A Data Envelopment Analysis Approach

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  • Stephen Migiro
  • Patricia Shewell

Abstract

The practice of measuring performance of the finance function as a business support unit is not widespread. This study assessed the importance of measuring finance function performance, by ascertaining whether such measurement facilitates identification of the relative efficiency of business finance functions, and by establishing its impact, if any, on overall company performance. Focussing on a sample of companies in the South African Freight Forwarding industry, a performance metric was developed and implemented to measure finance function performance. Relative finance function efficiency was then evaluated using inputorientated data envelopment analysis (DEA) to identify ‘best in class’ performance and to benchmark participants’ performance. Further, value chain DEA (VC-DEA) was applied to evaluate finance function efficiency simultaneously with overall company efficiency. Results show that implementation of the performance metric together with DEA facilitated the benchmarking of the finance functions of the sample group and the establishment of improvement targets for the finance functions determined as inefficient. In addition, a link between overall company performance and finance function performance in terms of inputs was confirmed; however, this link was not conclusively established as regards finance function performance in terms of outputs. The contribution of the study includes confirmation that implementation of the performance metric together with DEA facilitates the critical evaluation of finance function performance, thus establishing the importance of measuring the performance of the finance functions. In addition, incorporating the use of DEA in a performance framework for the finance function as a business support unit has extended the range of applications of DEA.

Suggested Citation

  • Stephen Migiro & Patricia Shewell, 2018. "Finance Function Performance Measurement-A Data Envelopment Analysis Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 9(6), pages 109-121.
  • Handle: RePEc:rnd:arjebs:v:9:y:2018:i:6:p:109-121
    DOI: 10.22610/jebs.v9i6(J).2009
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    References listed on IDEAS

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    1. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    2. Joe Zhu, 2014. "Quantitative Models for Performance Evaluation and Benchmarking," International Series in Operations Research and Management Science, Springer, edition 3, number 978-3-319-06647-9, March.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    5. Yung-Ho Chiu & Chin-Wei Huang, 2010. "Evaluating the optimal occupancy rate, operational efficiency, and profitability efficiency of Taiwan's international tourist hotels," The Service Industries Journal, Taylor & Francis Journals, vol. 31(13), pages 2145-2162, April.
    6. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    7. Chien Wang & Ram Gopal & Stanley Zionts, 1997. "Use of Data Envelopment Analysis in assessing Information Technology impact on firm performance," Annals of Operations Research, Springer, vol. 73(0), pages 191-213, October.
    8. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    9. Mu-Shun Wang & Shih-Tong Lu, 2015. "Information technology and risk factors for evaluating the banking industry in the Taiwan: an application of a Value Chain DEA," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 16(5), pages 901-915, October.
    10. Saranga, Haritha & Moser, Roger, 2010. "Performance evaluation of purchasing and supply management using value chain DEA approach," European Journal of Operational Research, Elsevier, vol. 207(1), pages 197-205, November.
    11. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    12. Ang, Sheng & Chen, Chien-Ming, 2016. "Pitfalls of decomposition weights in the additive multi-stage DEA model," Omega, Elsevier, vol. 58(C), pages 139-153.
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