A model for public postal network reorganization based on DEA and fuzzy approach

    Jelena Milutinović Affiliation
    ; Dejan Marković Affiliation
    ; Bojan Stanivuković Affiliation
    ; Libor Švadlenka Affiliation
    ; Momčilo Dobrodolac Affiliation


One of the most important segments in management of Universal Service Providers (USPs) is reaching the decisions concerning changes in the postal network infrastructure. USPs decide on such matters based on an analysis of financial indicators and defined qualitative parameters in accordance with the international regulations and obligations imposed by a competent regulatory agency. In this paper, the previously known method to analyse the existing postal network and define the minimal number of Postal Network Units (PNU) is implemented and upgraded by a new approach based on Data Envelopment Analysis (DEA) and fuzzy logic. The final aim of the proposed new approach is to determine which of the considered PNU should be closed or reorganized having in mind the minimization of negative effects, both financial and social. The proposed model gives the indices for all considered postal branches, which allows the decision-maker to rank the importance of each unit. The proposed model is a business intelligence tool, which replaces a multidisciplinary team composed from managers of the company and policymakers from both the postal sector as well as a sustainable rural development sector in reaching an important decision on changing the postal network. This decision may be considered as extremely complex since it should sublimate the opposed criteria that relate to the business success of the company, state regulations and sustainability of the local community. The indices obtained in the proposed method exactly include the mentioned three categories. The authors demonstrate the applicability of the suggested methodology based on the real data acquired in a district of the Serbia, i.e. in a regional organizational entity of the USP and provide the analysis of the results reached for the rural delivery post offices.

Keyword : postal services, postal network units, social criteria, fuzzy logic, DEA, rural area

How to Cite
Milutinović, J., Marković, D., Stanivuković, B., Švadlenka, L., & Dobrodolac, M. (2020). A model for public postal network reorganization based on DEA and fuzzy approach. Transport, 35(4), 401-418.
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Oct 28, 2020
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Aigner, D. J.; Chu, S. F. 1968. On estimating the industry production function, The American Economic Review 58(4): 826–839.

Ali, O. A. M.; Ali, A. Y.; Sumait, B. S. 2015. Comparison between the effects of different types of membership functions on fuzzy logic controller performance, International Journal of Emerging Engineering Research and Technology 3(3): 76–83.

Barham, L.; Maunder, S.; Dodgson, J. 2007. Access to Postal Services: a Final Report for Postcomm. NERA Economic Consulting (National Economic Research Associates).

Blagojević, M.; Šelmić, M.; Macura, D.; Šarac, D. 2013. Determining the number of postal units in the network – fuzzy approach, Serbia case study, Expert Systems with Applications 40(10): 4090–4095.

Borenstein, D.; Becker, J. L.; Do Prado, V. J. 2004. Measuring the efficiency of Brazilian post office stores using data envelopment analysis, International Journal of Operations & Production Management 24(10): 1055–1078.

Cabras, I.; Lau, C. K. M. 2019. The availability of local services and its impact on community cohesion in rural areas: evidence from the English countryside, Local Economy: the Journal of the Local Economy Policy Unit 34(3): 248–270.

Cazals, C.; Dudley, P.; Florens, J.-P.; Patel, S.; Rodriguez, F. 2008. Delivery offices cost frontier: a robust non parametric approach with exogenous variables, Review of Network Economics 7(2): 294–308.

Charnes, A.; Cooper, W. W.; Rhodes, E. 1978. Measuring the efficiency of decision making units, European Journal of Operational Research 2(6): 429–444.

Christiaanse, S.; Haartsen, T. 2017. The influence of symbolic and emotional meanings of rural facilities on reactions to closure: the case of the village supermarket, Journal of Rural Studies 54: 326–336.

Comber, A.; Brunsdon, C.; Hardy, J.; Radburn, R. 2009. Using a GIS-based network analysis and optimisation routines to evaluate service provision: a case study of the UK Post Office, Applied Spatial Analysis and Policy 2(1): 47–64.

Çakır, S.; Perçin, S.; Min, H. 2015. Evaluating the comparative efficiency of the postal services in OECD countries using context-dependent and measure-specific data envelopment analysis, Benchmarking: an International Journal 22(5): 839–856.

Deprins, D.; Simar, L.; Tulkens, H. 2006. Measuring labor-efficiency in post offices, in P. Chander, J. Drèze, C. K. Lovell, J. Mintz (Eds.). Public Goods, Environmental Externalities and Fiscal Competition, 285–309.

Doble, M. 1995. Measuring and improving technical efficiency in UK post office counters using data envelopment analysis, Annals of Public and Cooperative Economics 66(1): 31–64.

ERGP. 2014. ERGP Report 2014 on the Quality of Service and End-User Satisfaction. European Regulators Group for Postal Services (ERGP). 86 p. Available from Internet:

EU. 1997. Directive 97/67/EC of the European Parliament and of the Council of 15 December 1997 on Common Rules for the Development of the Internal Market of Community Postal Services and the Improvement of Quality of Service. European Union (EU). Available from Internet:

EU. 2002. Directive 2002/39/EC of the European Parliament and of the Council of 10 June 2002 Amending Directive 97/67/EC with Regard to the Further Opening to Competition of Community Postal Services. European Union (EU). Available from Internet:

EU. 2008. Directive 2008/6/EC of the European Parliament and of the Council of 20 February 2008 Amending Directive 97/67/EC with Regard to the Full Accomplishment of the Internal Market of Community Postal Services. European Union (EU). Available from Internet:

Filippini, M.; Zola, M. 2005. Economies of scale and cost efficiency in the postal services: empirical evidence from Switzerland, Applied Economics Letters 12(7): 437–441.

Hamilton, C. 2016. Changing service provision in rural areas and the possible impact on older people: a case example of compulsory post office closures and outreach services in England, Social Policy and Society 15(3): 387–401.

Higgs, G.; Langford, M. 2013. Investigating the validity of rural–urban distinctions in the impacts of changing service provision: the example of postal service reconfiguration in Wales, Geoforum 47: 53–64.

Higgs, G.; White, S. D. 1997. Changes in service provision in rural areas. Part 1: the use of GIS in analysing accessibility to services in rural deprivation research, Journal of Rural Studies 13(4): 441–450.

Ibrahim, S.; Lawal, D. M. 2015. Assessment of the proposed impact of post-office closure in Leicestershire (UK) using GIS-based network analysis, International Journal of Geomatics and Geosciences 6(1): 1–10.

Ipsos MORI. 2009. Impact of Post Office Closures: Area 1. Ipsos MORI, London, UK. 7 p. Available from Internet:

Iturralde, M. J.; Quirós, C. 2008. Analysis of efficiency of the European postal sector, International Journal of Production Economics 114(1): 84–90.

Klingenberg, J. P.; Bzhilyanskaya, L. Y.; Ravnitzky, M. J. 2013. Optimization of the United States postal retail network by applying GIS and econometric tools, in M. A. Crew, P. R. Kleindorfer (Eds.). Reforming the Postal Sector in the Face of Electronic Competition, 118–131.

Knežević, N.; Trubint, N.; Macura, D.; Bojović, N. 2011. A two-level approach for human resource planning towards organizational efficiency of a postal distribution system, Economic Computation and Economic Cybernetics Studies and Research (4): 155–168.

Kujačić, M.; Šarac, D.; Jovanović, B. 2012. Access to the postal network of the public operator, in Proceedings of International Conference “The Role of Strategic Partnership and Re Engineering or the Public Postal Network in the Sustainable Provision of Universal Service”, 26 October 2012, Budva, Montenegro, 15–25.

Mamdani, E. H.; Assilian, S. 1975. An experiment in linguistic synthesis with a fuzzy logic controller, International Journal of Man–Machine Studies 7(1): 1–13.

Maruyama, S.; Nakajima, T. 2002. Efficiency Measurement and Productivity Analysis for Japanese Postal Service. Tokyo, Japan. 26 p. Available from internet:

Mizutani, F.; Uranishi, S. 2003. The post office vs. parcel delivery companies: competition effects on costs and productivity, Journal of Regulatory Economics 23(3): 299–319.

Mostarac, K.; Kavran, Z.; Rakić, E. 2019. Accessibility of universal postal service according to access points density criteria: case study of Bjelovar–Bilogora County, Croatia, Promet – Traffic & Transportation 31(2): 173–183.

Nedeljković, R. R.; Drenovac, D. 2012. Efficiency measurement of delivery post offices using fuzzy data envelopment analysis (possibility approach), International Journal for Traffic and Transport Engineering 2(1): 22–29.

Neutens, T.; Delafontaine, M.; Schwanen, T.; Van de Weghe, N. 2012. The relationship between opening hours and accessibility of public service delivery, Journal of Transport Geography 25: 128–140.

Okholm, H. B.; Cerpickis, M.; Möller Boivie, A.; Facino, M.; Gårdebrink, J.; Almqvist, M.; Basalisco, B.; Geus, M.; Apon, J. 2018. Main Developments in the Postal Sector (2013–2016). European Commission, 102 p.

Okholm, H. B.; Möller, A. 2013. Vulnerable users in times of declining demand: the case of basic bank services in Norway and Sweden, in M. A. Crew, P. R. Kleindorfer (Eds.). Reforming the Postal Sector in the Face of Electronic Competition, 148–162.

Pošta Srbije. 2009. Opšti plan poštanske mreže. Beograd, Republika Srbija. (in Serbian).

Ralević, P.; Dobrodolac, M.; Marković, D. 2016. Using a non-parametric technique to measure the cost efficiency of postal delivery branches, Central European Journal of Operations Research 24(3): 637–657.

Ralevic, P.; Dobrodolac, M.; Markovic, D.; Mladenovic, S. 2015. The measurement of public postal operators’ profit efficiency by using data envelopment analysis (DEA): a case study of European Union member states and Serbia, Inžinerinė Ekonomika – Engineering Economics 26(2): 159–168.

Ranković Plazinić, B.; Jović, J. 2014. Women and transportation demands in rural Serbia, Journal of Rural Studies 36: 207–218.

Schuster, P. B. 2013. One for all and all for one: privatization and universal service provision in the postal sector, Applied Economics 45(26): 3667–3682.

SORS. 2011. Census 2011: The Census of Population, Households and Dwellings in the Republic of Serbia. Statistical Office of the Republic of Serbia (SORS). Available from Internet:

Sueyoshi, T.; Aoki, S. 2001. A use of a nonparametric statistic for DEA frontier shift: the Kruskal and Wallis rank test, Omega 29(1): 1–18.

Taylor, J.; Rubin, G.; Raymond, P. 2006. The Last Post: the Social and Economic Impact of Changes to Postal Services in Manchester. New Economics Foundation. 60 p.

Teodorović, D.; Šelmić, M. 2012. Računarska inteligencija u saobraćaju. Saobraćajni fakultet, Univerzitet u Beogradu, Republika Srbija, 210 s. (in Serbian).

Unterberger, M.; Vešović, P.; Mostarac, K.; Šarac, D.; Ožegović, S. 2018. Three-dimensional corporate social responsibility model of a postal service provider, Promet – Traffic & Transportation 30(3): 349–359.

UPU. 2014. Development Strategies for the Postal Sector: an Economic Perspective. Universal Postal Union (UPU), Bern, Switzerland. 237 p. Available from Internet:

US PSOIG. 2014. Providing Non-Bank Financial Services for the Underserved. Report No RARC-WP-14-007. US Postal Service Office of Inspector General (US PSOIG), Arlington, VA, US. 33 p. Available from Internet:

Wang, L.-X.; Mendel, J. M. 1992. Generating fuzzy rules by learning from examples, IEEE Transactions on Systems, Man, and Cybernetics 22(6): 1414–1427.

White, S. D.; Guy, C. M.; Higgs, G. 1997. Changes in service provision in rural areas. Part 2: changes in post office provision in Mid Wales: a GIS-based evaluation, Journal of Rural Studies 13(4): 451–465.