eesti teaduste
akadeemia kirjastus
SINCE 1952
Proceeding cover
of the estonian academy of sciences
ISSN 1736-7530 (Electronic)
ISSN 1736-6046 (Print)
Impact Factor (2020): 1.045

A concept for performance measurement and evaluation in network industries; pp. 536–542

Full article in PDF format | doi: 10.3176/proc.2015.4S.01

Kristjan Kuhi, Kati Kõrbe Kaare, Ott Koppel


The structure and functioning of network industries have a great effect on the well-being of society, being also prerequisites for economic growth and productivity. Social goals, industry trends, ownership structures, and the economic environment play an important role in the development of such networks. Most network industries enjoy a dominant position on the market. Their performance is steered by national regulatory authorities via price control and quality requirements. For this the regulatory authorities need besides financial indicators feedback on the technical performance of the provided services. The vast development in sensing, data transmission, and collection technologies, as well as in analytical methods, has made it possible and feasible to acquire the needed feedback. Such comprehensive data enable to construct a performance measurement system to regulate, develop, and administer the networks. This paper explores the possibility of developing an overall technical performance index and presents a relevant concept. The suggested overall index would be an additional regulatory tool to evaluate the performance of network industries and their compliance with consumers’ requirements. The aim of the proposed concept is to establish empirically verifiable feedback between a given state of technology, state of institutional governance, and the performance of network industries.



  1. Oswald, M., Li, Q., McNeil, S., and Trimbath, S. Measur­ing infrastructure performance: development of a national infrastructure index. Public Works Manage­ment & Policy, 2011, 16(4), 373–394.

  2. Göttinger, H. Economies of Network Industries. Routledge, London, 2003.

  3. A Methodological Note for the Horizontal Evaluation of Services of General Economic Interest. European Commission, Brussels, 2002.

  4. Uukkivi, R., Ots, M., and Koppel, O. Systematic approach to economic regulation of network industries in Estonia. Trames: J. Humanit. Soc. Sci., 2014, 18(3), 221–241.

  5. Brignall, S. and Modell, S. An institutional perspective on performance measurement and management in the ‘new public sector’. Manage. Account. Res., 2000, 11, 281–306.

  6. Kõrbe Kaare, K. Performance Measurement of a Road Network: A Conceptual and Technological Approach for Estonia. TUT Press, Tallinn, 2013.

  7. Hagerty, J. and Hofman, D. Defining a Measurement Strategy, Part III. BI Review, 2006, 8.

  8. Performance Measurement Fundamentals. U.S. Federal Highway Administration, Washington, 1998.

  9. De Toni, A. and Tonchia, S. Performance measurement systems. Models, characteristics and measures. Int. J. Oper. Prod. Man., 2001, 21(1/2), 46–71.

10. Ghalayini, A. M. and Noble, J. S. The changing basis of performance measurement. Int. J. Oper. Prod. Man., 1996, 16(8), 63–80.

11. How to Measure Performance. A Handbook of Techniques and Tools. U.S. Department of Energy, Washington, 1995.

12. Sinclair, D. and Zairi, M. An empirical study of key elements of total quality-based performance measure­ment systems: a case study approach in the service industry sector. Total Qual. Manage., 2001, 12(4), 535–550.

13. Zheng, J., Garrick, N. W., Atkinson-Palombo, C., McCahill, C., and Marshall, W. Guidelines on develop­ing performance metrics for evaluating transportation sustainability. Research in Transportation Business & Management, 2013, 7, 4–13.

14. Kaare, K. K. and Koppel, O. Performance measurement data as an input in national transportation policy. In Proc. XXVIII Int. Baltic Road Conf. Baltic Road Association, Vilnius, 2013, 1–9 [CD-ROM].

15. Ismail, M. A., Sadiq, R., Soleymani, H. R., and Tesfamariam, S. Developing a road performance index using a Bayesian belief network model. J. Franklin Inst., 2011, 348, 2539–2555.

16. Litzka, J., Leben, B., La Torre, F. et al. The Way Forward for Pavement Performance Indicators Across Europe. COST Action 354 Final Report. Austrian Transporta­tion Research Association, Vienna, 2008.

17. Lurdes Antunes, M. de. Framework for Implementation of Environment Key Performance Indicators. EVITA (Environmental Indicators for the Total Road Infra­structure Assets), Deliverable D4.1. Institut Français des Sciences et des Technologies des Transports, de l’Aménagement et des Réseaux, and PMS-Consult, 2011.

18. Kuhi, K., Kõrbe Kaare, K., and Koppel, O. Performance measurement in network industries: example of power distribution and road networks. In Proc. 9th Int. Conf. DAAAM Baltic Industrial Engineering (Otto, T., ed.). TUT Press, Tallinn, 2014, 115–120.

19. Davey, E. Rail Traffic Management Systems (TNS). In IET Professional Development Course on Railway Signalling and Control Systems (RSCS). IET, London, 2012, 126–143.

20. Corriere, F. and Di Vincenzo, D. The rail quality index as an indicator of the “global comfort” in optimizing safety, quality and efficiency in railway rails. Procedia – Social and Behavioral Sciences, 2012, 53, 1090–1099.

21. Tsang, A. H. C. A strategic approach to managing main­tenance performance. J. Qual. Mainten. Eng., 1998, 4(2), 87–94.

22. Åhrén, T. and Parida, A. Maintenance performance indicators (MPIs) for benchmarking the railway infrastructure. Benchmarking, 2009, 16(2), 247–258.

23. Parida, A. Development of a Multi-criteria Hierarchical Framework for Maintenance Performance Measure­ment: Concepts, Issues and Challenges. Luleå University of Technology, 2006.

24. Kumar, U., Galar, D., Parida, A., Stenström, C., and Berges, L. Maintenance performance metrics: a state-of-the-art review. J. Qual. Mainten. Eng., 2013, 19(3), 233–277.

25. Queiroz, L. M. O. de. Assessing the Overall Performance of Brazilian Electric Distribution Companies. The George Washington University, Washington, 2012.

26. Electricity Network Performance Report 2011/2012. Ausgrid, 2011.

27. Gosbell, V. J., Perera, B. S. P., and Herath, H. M. S. C. Unified Power Quality Index (UPQI) for continuous disturbances. In 10th Int. Conf. Harmonics and Quality of Power, 2002, 1, 316–321.

28. Meldorf, M., Tammoja, H., Treufeldt, Ü., and Kilter, J. Jaotusvõrgud [Distribution Networks]. TUT Press, Tallinn, 2007 (in Estonian).

29. Markiewicz, H. and Klajn, A. Standard EN 50160 – Voltage Characteristics in Public Distribution Systems. European Copper Institute, Brussels, 2004.

30. IEEE Guide for Electric Power Distribution Reliability Indices. IEEE, New York, 2012.

31. Reliability Benchmarking Application Guide for Utility/Customer PQ Indices. Electric Power Research Institute, Palo Alto, 1999.

32. Billinton, R. and Li, W. Reliability Assessment of Electrical Power Systems Using Monte Carlo Methods. Plenum Press, New York, 1994.

33. Waverman, L. and Koutroumpis, P. Benchmarking tele­coms regulation – the Telecommunications Regulatory Governance Index (TRGI). Telecommun. Policy, 2011, 35, 450–468.

34. Matteson, S. Methods for multi-criteria sustainability and reliability assessments of power systems. Energy, 2014, 71, 130–136.

35. Shukla, V. and Dubey, P. K. Big data: beyond data hand­ling. Int. J. Scientific Research And Education, 2014, 2(9), 1929–1935.

36. Kaisler, S., Armour, F., Espinosa, J. A., and Money, W. Big data: issues and challenges moving forward. In 46th Hawaii Int. Conf. System Sciences (HICSS). IEEE, Wailea, 2013, 995–1004.

37. Big Data Analytics Guidebook. Unleashing Business Value in Big Data. TM Forum, Morristown, 2014.

38. Yang, H., Dasdan, A., Hsiao, R.-L., and Parker, D. S. Map-reduce-merge: simplified relational data pro­cessing on large clusters. In Proc. ACM SIGMOD Int. Conf. Management of Data. ACM, New York, 2007, 1029–1040.

39. Wu, E., Diao, Y., and Rizvi, S. High-performance complex event processing over streams. In Proc. ACM SIGMOD Int. Conf. Management of Data. ACM, New York, 2006, 407–418.


Back to Issue