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.


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    Title :

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




    Publication date :

    2020




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





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