Abstract
Benchmarking has been adopted by private organisations in search of commercial efficiency gains and public sector organisations in terms of efficiency, effectiveness and accountability. One such sector that has considerable potential to benefit from benchmarking is the transport sector. Focusing on the pavement management of road networks, this paper reviews a number of popular benchmarking techniques cited in the literature and undertakes a comparative analysis of their suitability with respect to a number of selection criteria. The audience for the paper is researchers and practitioners in pavement management and, consequently, the benchmarking techniques presented range from simple ratios or regression analyses to more complex frontier-based methods incorporating optimisation of weightings. Two of these frontier-based methods, Data Envelopment Analysis, a non-parametric data-orientated approach, and Stochastic Frontier Analysis, a parametric stochastic approach, are shown to be the most suitable for use in the pavement management sector. As the true level of efficiency is unknown in benchmarking, it is not possible to determine which technique is the best. Both have their advantages and disadvantages, however, we have stated a preference for Data Envelopment Analysis recognising that its non-parametric form offers a possible advantage in pavement management given the complexity and number of influencing variables.
Similar content being viewed by others
References
Neely, A., & Bourne, M. (2000). Why measurement initiatives fail. Measuring Business Excellence, 4(4), 3–7
Henning, T. F. P., Muruvan, S., Feng, W. A., & Dunn, R. C. (2011). The development of a benchmarking tool for monitoring progress towards sustainable transportation in New Zealand. Transport Policy, 18(2), 480–488
Codling, S. (1995). Best practice benchmarking: A management guide. Hampshire: Gower Publishing Ltd.
Bhutta, K. S., & Huq, F. (1999). Benchmarking–best practices: An integrated approach. Benchmarking: An International Journal, 6(3), 254–268.
Voss, C. A., Åhlström, P., & Blackmon, K. (1997). Benchmarking and operational performance: Some empirical results. Benchmarking for Quality Management & Technology, 4(4), 273–285
Armstrong, M., Brown, S., & Smith, H. (2014). Benchmarking and threshold standards in higher education. New York: Routledge.
Goncharuk, A. G., & Monat, J. P. (2009). A synergistic performance management model conjoining benchmarking and motivation. Benchmarking, 16(6), 767–784. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770911000105
Gurumurthy, A., & Kodali, R. (2009). Application of benchmarking for assessing the lean manufacturing implementation. Benchmarking, 16(2), 274–308. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770910948268
Wei-Wen, W., Lan, L. W., & Yu-Ting, L. (2013). Benchmarking hotel industry in a multi-period context with DEA approaches: A case study. Benchmarking, 20(2), 152–168. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635771311307650
Sufian. F. (2011). Benchmarking the efficiency of the Korean banking sector: A DEA approach. Benchmarking, 18(1), 107–127. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635771111109841
Raymond, J. (2008). Benchmarking in public procurement. Benchmarking, 15(6), 782–793. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770810915940
Welborn, C., & Bullington, K. (2013). Benchmarking Award Winning Health Care Organizations in the USA. Benchmarking, 20(6), 765–776. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/BIJ-02-2012-0012
Yasin, M., Alavi, J., Sallem Koubida, & Small, M. H. (2011). An assessment of the competitiveness of the Moroccan tourism industry. Benchmarking, 18(1), 6–22. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635771111109797
Galoro C.A.O., Mendes, M. E., & Nascimento Burattini, M. (2009). Applicability and potential benefits of benchmarking in Brazilian clinical laboratory services. Benchmarking, 16(6), 817–830. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770911000132
Srivastava, S. K., & Ray, A. (2013). Benchmarking Indian general insurance firms. Benchmarking, 20(1), 4–24. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635771311299461
Seong-Jong Joo, & Fowler, K. L. (2014). Exploring comparative efficiency and determinants of efficiency for major world airlines. Benchmarking, 21(4), 675–687. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/BIJ-09-2012-0054
Tutie, A., Zailani, S., & Fernando, Y. (2010). Best practices for the effectiveness of benchmarking in the Indonesian manufacturing companies. Benchmarking, 17(1), 115–143. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635771011022343
Goncharuk, A. G. (2014). Competitive benchmarking technique for "the followers": A case of Ukrainian dairies. Benchmarking, 21(2), 218–225. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/BIJ-04-2012-0027
Magd, H., & Curry, A. (2003). Benchmarking: Achieving best value in public-sector organisations. Benchmarking, 10(3), 261
Goncharuk, A. G. (2008). Performance benchmarking in gas distribution industry. Benchmarking, 15(5), 548–559. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770810903141
Braadbaart, O. (2007). Collaborative benchmarking, transparency and performance. Benchmarking, 14(6), 677–692. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770710834482
Kovacic, A. (2007). Benchmarking the Slovenian competitiveness by system of indicators. Benchmarking, 14(5), 553–574. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770710819254
Hjalmarsson, L., Kumbhakar, S. C., & Heshmati, A. (1996). DEA, DFA and SFA: A comparison. Journal of Productivity Analysis, 7(2–3), 303–327
Costello, S. B., Smith, N. E., Henning, T. F. P., & Hendry, M. (2014). Towards measuring road maintenance efficiency and effectiveness in local authorities. ARRB Road & Transport Research Journal, vol. 23.
Putterill, M. S., Maani, K. E., & Sluti, D. G. (1990). Performance ranking methodology for roading operations management. Transport Reviews, 10(4), 339–352
Thanassoulis, E., Boussofiane, A., & Dyson, R. G. (1996). A comparison of data envelopment analysis and ratio analysis as tools for performance assessment. Omega, International Journal of Management Science, 24(3), 229–244
Abbott, M., & Wu, S. (2002). Total factor productivity and efficiency of Australian airports. Australian Economic Review, 35(3), 244–260
ASTM. (2018). “Standard practice for roads and parking lots pavement condition index surveys.” D6433, West Conshohocken, PA.
Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard – measures that drive performance, Harvard Business Review, 71–79.
Punniyamoorthy, M., & Murali, R. (2008). Balanced score for the balanced scorecard: A benchmarking tool. Benchmarking, 15(4), 420–443. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770810887230
Kaplan, R. S., & Norton, D. P. (2001). Transforming the balanced scorecard from performance measurement to strategic management: Part I. Accounting Horizons, 15(1), 87–104
Chia, A., Goh, M., & Sin-Hoon Hum. (2009). Performance measurement in supply chain entities: Balanced scorecard perspective. Benchmarking, 16(5), 605–620. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770910987832
Gurd, B., & Ifandoudas, P. (2014). Moving towards agility: The contribution of a modified balanced scorecard system. Measuring Business Excellence, 18(2), 1–13
Hoque, Z., & James, W. (2000). Linking balanced scorecard measures to size and market factors: Impact on organizational performance. Journal of Management Accounting Research, 12(1), 1–17
Turnbull, K. F. (2005). Performance Measures to Improve Transportation Systems: Summary of the Second National Conference. (Vol. 36)Washington, DC: Transportation Research Board.
Costello, S. B., Nuttall, S. R., Powell, J. E., & Arrowsmith, R. (2012). Performance Management Framework for Managing Agent Contractors. Proceedings of the Institution of Civil Engineers, Transport, 165(TR4), 2012
Adler, N., Friedman, L., & Sinuany-Stern, Z. (2002). Review of ranking methods in the data envelopment analysis context. European Journal of Operational Research, 140(2), 249–265
Battese, G. E., & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20(2), 325–332
Anderson, R. I., Fish, M., Xia, Y., & Michello, F. (1999). Measuring efficiency in the hotel industry: A stochastic frontier approach. International Journal of Hospitality Management, 18(1), 45–57
Rosko, M. D. (2001). Cost efficiency of US hospitals: A stochastic frontier approach. Health Economics, 10(6), 539–551
Liu, Y., & Myers, R. (2009). Model selection in stochastic frontier analysis with an application to maize production in Kenya. Journal of Productivity Analysis, 31(1), 33–46
Rouse, P., & Swales, R. (2006). Pricing public health care services using DEA: Methodology versus politics. Annals of Operations Research, 145(1), 265–280
Ruggiero, J. (2007). A comparison of DEA and the stochastic frontier model using panel data. International Transactions in Operational Research, 14(3), 259–266
Aigner, D., Lovell, C. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37
Sickles, R and Zeleniuk, 2019. Measurement of productivity and efficiency : theory and practice. Cambridge University Press. Chapter 6 page 185
Dharmapala. S., & Saber, H. M. (2007). Resource allocation within academic units. Benchmarking, 14(2), 202–210. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1108/14635770710740396
Rickards, R. C. (2003). Setting benchmarks and evaluating balanced scorecards with data envelopment analysis. Benchmarking, 10(3), 226
Ramanathan, R. (2003). An introduction to data envelopment analysis: A tool for performance measurement. New Delhi: Sage Publishers.
Ozbek, M. E., de la Garza, J. M., & Triantis, K. (2009). Data envelopment analysis as a decision-making tool for transportation professionals. Journal of Transportation Engineering, 135(11), 822–831
Rouse, P., & Chiu, T. (2009). Towards optimal life cycle management in a road maintenance setting using DEA. European Journal of Operational Research, 196(2), 672–681. http://dx.doi.org.ezproxy.auckland.ac.nz/https://doi.org/10.1016/j.ejor.2008.02.041
Rouse, P., Putterill, M., & Ryan, D. (1997). Towards a general managerial framework for performance measurement: A comprehensive highway maintenance application. Journal of Productivity Analysis, 8(2), 127–149
Garza, J. M., Triantis, K., & Fallah-Fini, S. (2009, June). Efficiency measurement of highway maintenance strategies using data envelopment analysis, Proceedings of NSF Engineering Research and Innovation Conference. Honolulu, Hawaii.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092
Cooper W.W., Seiford L.M., Zhu J. (2011) Data Envelopment Analysis: History, Models, and Interpretations. In: Cooper W., Seiford L., Zhu J. (eds) Handbook on Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 164. Springer, Boston, MA
Cooper, W. W. (2013). Data envelopment analysis. Encyclopaedia of Operations Research and Management Science, 349–358.
Cooper, W. W., Seiford, L. M., & Zhu, J. (2004). Data envelopment analysis. Handbook on data envelopment analysis (pp. 1–39) Springer.
Thanassoulis, E. (2001). Introduction to the theory and application of data envelopment analysis. Dordrecht: Kluwer Academic Publishers.
Gong, B., & Sickles, R. C. (1992). Finite sample evidence on the performance of stochastic frontiers and data envelopment analysis using panel data. Journal of Econometrics, 51(1–2), 259–284
Simar, L. and P. Wilson. 2008. Statistical Inference in Nonparametric Frontier Models: Recent Developments and Perspectives. Chapter 4 in Fried H.O., Lovell, C.A.K. and S.S. Schmidt (eds). The Measurement of Productive Efficiency and Productivity Growth. Oxford University Press
Battese, G. E., Heshmati, A., & Hjalmarsson, L. (2000). Efficiency of labour use in the Swedish banking industry: A stochastic frontier approach. Empirical Economics, 25(4), 623–640
Golany, B., & Roll, Y. (1989). An application procedure for DEA. Omega, 17(3), 237–250
Rouse, A. P. B. (1997). A methodological framework of performance measurement with applications using data envelopment analysis (Doctoral dissertation). Available from e-Theses University of Auckland. (MMS ID: 9967651614002091)
Cook, W. D., Kazakov, A., & Roll, Y. (1994). On the measurement of relative efficiency of highway maintenance patrols. (pp. 195–210). Boston: Kluwer Academic.
Cook, W. D., Roll, Y., & Kazakov, A. (1990). A DEA Model for Measuring the Relative Efficiency of Highway Maintenance Patrols. Infor, 28(2), 113–124
Ganley, J. A., & Cubbin, J. S. (1992). Public sector efficiency measurement: Applications of data envelopment analysis. New York: Elsevier Science Inc.
Mia, M. N. U., Henning, T. F. P., Costello, S. B., & Foster, G. (2015). Application of fuzzy logic based risk analysis to identify the moisture damage potential in flexible road pavements. International Journal of Pavement Research and Technology, 8(5), 325–336. https://doi.org/10.6135/ijprt.org.tw/2015.8(5).325
Acknowledgements
The authors wish to acknowledge the partial funding provided by the New Zealand Transport Agency in making this research possible.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Shivaramu, H., Costello, S.B., Henning, T.F.P. et al. Analysis of Benchmarking Techniques for Application in Pavement Management. Int. J. Pavement Res. Technol. 15, 196–212 (2022). https://doi.org/10.1007/s42947-021-00018-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s42947-021-00018-0