Evaluating Service Productivity via Combining Approach FBWM & DEA-EEP (Case Study: Mazandaran Electricity Distribution Company)

Document Type : Research Paper


1 Ph.D., Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.

2 Prof., Department of Technology and Innovation Management, Faculty of Management, University of Tehran, Tehran, Iran.

3 Prof., Department of Industrial Management and Information Technology, Faculty of Management and Accounting, Shahid Beheshti University, Tehran, Iran.

4 Associate Prof., Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.

5 Prof., Department of Industrial Management, Faculty of Management, University of Tehran, Tehran, Iran.



Objective: Today, productivity is one of the most important factors in economic growth. At the organizational level, a high level of productivity indicates optimal performance to gain a competitive advantage. Despite the important role of productivity of service organizations in economic growth, few studies have been conducted in this context. The purpose of this study is to evaluate service productivity by a combined fuzzy best-worst method and data envelopment analysis.
Methods: In the first stage, carrying out a comprehensive review of the research literature, indicators of service productivity evaluation were identified. Then, the evaluation indicators were weighed using the fuzzy best-worst method. After weighing the indicators and determining the importance of each of them, using the data envelopment analysis approach, the efficiency, effectiveness, and productivity of Mazandaran Electricity Distribution Company were evaluated for five consecutive years from 2016 to 2020.
Results: In this study, efficiency, effectiveness, and productivity were simultaneously evaluated using quantitative and qualitative indicators affecting the evaluation of the productivity of electricity distribution companies.
Conclusion: The obtained results would help to assess service productivity by emphasizing both quantitative and qualitative aspects of services and paying attention to the dimensions of efficiency and effectiveness simultaneously. Productivity improvement strategies were also suggested based on the achieved results of the current study.


Main Subjects

 Balci, B., Hollmann, A., & Rosenkranz, C. (2011). Service productivity: a literature review and research agenda. XXI International RESER Conference, Hamburg.
Becker, J., Bernhold, T., Beverungen, D., Kaling, N., Knackstedt, R., Lellek, V., & Rauer, H. P. (2015). Construction of Productivity Models-A Tool-Supported Approach in the Area of Facility Management. Enterprise Modelling and Information Systems Architectures, 7 (1), 28--43
 Bröchner, J. (2017). Measuring the productivity of facilities management. Journal of Facilities Management,15 (3), 285-301. https://doi.org/10.1108/JFM-04-2016-0013
Bobde, S. M., & Tanaka, M. (2018). Efficiency evaluation of electricity distribution utilities in India: A two-stage DEA with bootstrap estimation. Journal of the Operational Research Society, 69 (9), 1423-1434.
Charnes, A., Cooper, W.W., Huang, Z.M. (1990). Polyhedral cone-ratio DEA models with an illustrative application to large commercial banks. J Econom, 46 (1–2), 73–91.
Çelen, A., & Yalçın, N. (2012). Performance assessment of Turkish electricity distribution utilities: An application of combined FAHP/TOPSIS/DEA methodology to incorporate quality of service. Utilities Policy, 23 (C), 59-71.
Çelen, A. (2013). Efficiency and productivity (TFP) of the Turkish electricity distribution companies: An application of two-stage (DEA&Tobit) analysis. Energy Policy, 63, 300-310.
Cooper, R. G., & Edgett, S. J. (2008). Maximizing productivity in product innovation, Research-Technology Management, 51 (2), 47-58.
Corsten, H. (1994). Produktivitätsmanagement bilateraler personenbezogener Dienstleistungen. In Dienstleistungs produktion. America, Springer.
Dyson, R.G., Thanassoulis, E. (1988). Reducing weight flexibility in data envelopment analysis. The Journal of the Operational Research Society, 39 (6), 563–576.
Durdyev, S., Ihtiyar, A., Ismail, S., Ahmad, F. S., & Bakar, N. A. (2014). Productivity and service quality: Factors affecting in service industry. Procedia-Social and Behavioral Sciences, 109, 487-491.
Ervural, B. C., Zaim, S., Demirel, O. F., Aydin, Z., & Delen, D. (2018). An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable and Sustainable Energy Reviews, 82, 1538-1550.
Ghahremanloo, M., Hasani, A., Amiri, M., Hashemi-Tabatabaei, M., Keshavarz-Ghorabaee, M., & Ustinovičius, L. (2020). A novel DEA model for hospital performance evaluation based on the measurement of efficiency, effectiveness and productivity. Engineering Management in Production and Services, 12 (1), 7-19.
 Goto, M., & Tsutsui, M. (2008). Technical efficiency and impacts of deregulation: An analysis of three functions in US electric power utilities during the period from 1992 through 2000. Energy economics, 30 (1): 15-38.
Goto, M. & Sueyoshi, T. (2009). Productivity growth and deregulation of Japanese electricity distribution. Energy Policy, 37 (8), 3130-3138.
Grönroos, C., & Ojasalo, K. (2004). Service productivity: Towards a conceptualization of the transformation of inputs into economic results in services. Journal of Business research, 57 (4): 414-423.
Guo, S. & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121 (1), 23-31.
Hess, B., & Cullmann, A. (2007). Efficiency analysis of East and West German electricity distribution companies–Do the “Ossis” really beat the “Wessis”? Utilities Policy, 15 (3), 206-214.
Irwansyah, D. (2018). Measurement of Study Productivity and Evaluation Analysis by using the American Productivity Center (APC) Model at a Palm Oil Factory (Pks PT. Syaukath Sejahtera)", Proceedings of MICoMS 2017 (Emerald Reach Proceedings Series, Vol. 1), Bingley, 81-86.
Iskandar, B. S., Nugraha, H., & Widi, D. K. (2019). Organizational Productivity Measurement Method Applied on Electric Utility Company. 2019 Annual Reliability and Maintainability Symposium (RAMS). Orlando, FL, USA.
Jagoda, K., Lonseth, R., & Lonseth, A. (2013). A bottom‐up approach for productivity measurement and improvement. International Journal of Productivity and performance management, 62(4), 387-406. DOI: 10.1108/17410401311329625
Johnston, R., & Jones, P. (2004). Service productivity: Towards understanding the relationship between operational and customer productivity. International Journal of Productivity and performance management, 53 (3), 201-213.
Kao, C. & Hung, H.T. (2005). Data envelopment analysis with common weights: the compromise solution approach. Journal of the Operational Research Society, 56 (10), 1196–1203.
Khodabakhshi, M. (2010). An output oriented super-efficiency measure in stochastic data envelopment analysis: Considering Iranian electricity distribution companies. Computers & Industrial Engineering, 58 (4), 663-671.
Kumar, S., Duhan, M., & Haleem, A. (2016). Evaluation of factors important to enhance productivity. Cogent Engineering, 3 (1), 11-45.
Lasshof, B. (2006). Produktivität von Dienstleistungen: Mitwirkung und Einfluss des Kunden. Springer-Verlag. [Productivity of services: Customer cooperation and influence]. Dissertation, Wiesbaden: Fernuniversität Hagen.
Lee, J. J., Patterson, P. G., & Ngo, L. V. (2017). In pursuit of service productivity and customer satisfaction: the role of resources. European Journal of Marketing. European Journal of Marketing, 51 (11/12), 1836-1855.
Leicht, A., Rashidi, M., Klement, U., & Hryha, E. (2020). Effect of process parameters on the microstructure, tensile strength and productivity of 316L parts produced by laser powder bed fusion. Materials Characterization, 159, 110016.
Lovelock, D. M., Zatcky, J., Goodman, K., & Yamada, Y. (2014). The effectiveness of a pneumatic compression belt in reducing respiratory motion of abdominal tumors in patients undergoing stereotactic body radiotherapy. Technology in cancer research & treatment, 13 (3), 259-267.
Luria, G., Yagil, D., & Gal, I. (2016). Quality and productivity: role conflict in the service context. The Service Industries Journal, 34 (12), 955-973.
Maroto-snchez, A. (2012). Productivity growth and cyclical behaviour in service industries : the Spanish case. 2069 (November). https://doi.org/10.1080/02642060902838311
Moore, K., Coates, H., & Croucher, G. (2018). Investigating applications of university productivity measurement models using Australian data. Studies in Higher Education, 44 (12), 2148-2162.
Motlagh, M. A., Valmohammadi, C., & Modiri, M. (2020). Developing a qualitative model of productivity for service companies using fuzzy analytic hierarchy process: a case study. International Journal of Productivity and Quality Management, 29 (1), 126-147.
Oeij, P., De Looze, M., Ten Have, K., Van Rhijn, J., & Kuijt‐Evers, L. (2012). Developing the organization's productivity strategy in various sectors of industry. International Journal of Productivity and performance management, 61 (1), 93-109.
Ojasalo, J. (1999). Quality dynamics in professional services. Swedish School of Economics and Business Administration, Doctoral Dissertation. Helsinki.
Ojasalo, K. (2003). Customer influence on service productivity. SAM Advanced Management Journal, 68 (3), 9-14.
Omrani, H., Azadeh, A., Ghaderi, S., & Aabdollahzadeh, S. (2010). A consistent approach for performance measurement of electricity distribution companies. International Journal of Energy Sector Management, 4(3), 399-416.
Omrani, H. (2013). Common weights data envelopment analysis with uncertain data: A robust optimization approach. Computers & Industrial Engineering, 66 (4), 1163-1170.‏
Omrani, H., Beiragh, R. G., & Kaleibari, S. S. (2015). Performance assessment of Iranian electricity distribution companies by an integrated cooperative game data envelopment analysis principal component analysis approach. International Journal of Electrical Power & Energy Systems, 64 (1), 617-625.
Omrani, H., Alizadeh, A., & Naghizadeh, F. (2020). Incorporating decision makers’ preferences into DEA and common weight DEA models based on the best–worst method (BWM). Soft Computing, 24 (6), 3989-4002.‏
Ostrom, A. L., Bitner, M. J., Brown, S. W., Burkhard, K. A., Goul, M., Smith-Daniels, V., Demirkan, H., & Rabinovich, E. (2010). Moving forward and making a difference: research priorities for the science of service. Journal of service research, 13 (1), 4-36.
Parasuraman, A. (2002). Service quality and productivity, a synergistic perspective Managing service quality: An international journal, 12 (1), 6-9.
Parasuraman, A. (2010). Service productivity, quality and innovation: Implications for service‐design practice and research. International Journal of Quality and Service Sciences, 2 (3), 277-286.
Paslarzadeh, S., Asgharizadeh, E. & Safari, H. (2012). Evaluation of the strategic performance of Hormozgan Electricity Distribution Company. 28th International Electricity Conference, Tehran, Iran. (in Persian)
Petz, A., Duckwitz, S., Schmalz, C., Meyer, S., Mütze-Niewöhner, S., & Schlick, C. (2012). Development of a Model for the Comprehensive Analysis and Evaluation of Service Productivity. International Journal of Industrial and Manufacturing Engineering, 6 (10), 2019-2024.
Pombo, C., & Taborda, R. (2006). Performance and efficiency in Colombia's power distribution system: effects of the 1994 reform. Energy economics, 28 (3), 339-369.
Poursoltani, H. (2016). Major challenges of the electricity industry with the aim of increasing productivity. The 32nd International Electricity Conference, Tehran, Iran. (in Persian)
Rai, A., & Sambamurthy, V. (2006). Editorial notes the growth of interest in services management: opportunities for information systems scholars. In: INFORMS,17 (4), 327- 444.
Ramos-Real, F. J., Tovar, B., Iootty, M., De Almeida, E. F., & Pinto Jr, H. Q. (2009). The evolution and main determinants of productivity in Brazilian electricity distribution 1998–2005: An empirical analysis. Energy economics, 31 (2), 298-305.
Roche, I. C., Romero, J., & Sellers-Rubio, R. (2019). Retail services efficiency: impact of country-specific factors. International Journal of Retail & Distribution Management, 47 (8), 774-792.
Roll, Y., Cook, W.D., Golany, B. (1991). Controlling factor weights in data envelopment analysis. IIE Trans, 23 (1), 2–9.
Sadjadi, S. J., Omrani, H., Makui, A., & Shahanaghi, K. (2011). An interactive robust data envelopment analysis model for determining alternative targets in Iranian electricity distribution companies. Expert Systems with Applications, 38 (8), 9830-9839.
Sahay, B. (2005). Multi‐factor productivity measurement model for service organisation. International Journal of Productivity and performance manageme, 54 (1),7-22.
Scerri, M., & Agarwal, R. (2018). Service enterprise productivity in action: measuring service productivity. Journal of Service Theory and Practice, 28 (4), 524-551.
Sekhon, H., Yalley, A. A., Roy, S. K., & Shergill, G. S. (2016). A cross-country study of service productivity. The Service Industries Journal, 36 (5-6), 223-238.
Siow, H. & Teng, S. (2014). Qualitative productivity analysis: does a non-financial measurement model exist? International Journal of Productivity and Performance Management, 63 (2), 250-256.
Tangen, S. (2005). Demystifying productivity and performance. International Journal of Productivity and performance management, 54, 34-46.
Tehrani, S. Z. (2016). Optimising the service productivity with operational strategic options Multimedia Doctoral Dissertation. University (Malaysia).
Teng, H. S. S. (2014). Qualitative productivity analysis: does a non-financial measurement model exist? International Journal of Productivity and performance management, 63 (2), 250-256.
Tohidi, H., Jabbari, M. M., & Tohidi, O. (2018). Exploratory Analysis of Factors Influencing Delay in EPC Contracts of Iranian Power Development Company. Proceedings of the International MultiConference of Engineers and Computer Scientists, Hongkong.
Thompson, R.G., Singleton, F.D. Jr, Thrall, R.M., Smith, B.A. (1986). Comparative site evaluations for locating a high-energy physics lab in Texas. Interfaces, 16 (6), 35–49.
Vuorinen, I., Järvinen, R., & Lehtinen, U. (1998). Content and measurement of productivity in the service sector: a conceptual analysis with an illustrative case from the insurance business. International Journal of Service Industry Management, 9 (4), 377-396.
Walter, M., Cullmann, A., von Hirschhausen, C., Wand, R., & Zschille, M. (2009). Quo vadis efficiency analysis of water distribution? A comparative literature review. Utilities Policy, 17 (3-4), 225-232.