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Understanding Location Decisions of Energy Multinational Enterprises within the European Smart Cities’ Context: An Integrated AHP and Extended Fuzzy Linguistic TOPSIS Method

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  • Olga Porro

    (Department of Mathematics, Universitat Politècnica de Catalunya (BarcelonaTech), C. Jordi Girona 1-3, 08034 Barcelona, Spain
    ESADE Business School, Universitat Ramon Llull, Av. Pedralbes 60-62, 08034 Barcelona, Spain)

  • Francesc Pardo-Bosch

    (ESADE Business School, Universitat Ramon Llull, Av. Pedralbes 60-62, 08034 Barcelona, Spain
    Departament of Project and Construction Engineering, Universitat Politècnica de Catalunya (BarcelonaTech), C. Jordi Girona 1-3, 08034 Barcelona, Spain)

  • Núria Agell

    (ESADE Business School, Universitat Ramon Llull, Av. Pedralbes 60-62, 08034 Barcelona, Spain)

  • Mónica Sánchez

    (Department of Mathematics, Universitat Politècnica de Catalunya (BarcelonaTech), C. Jordi Girona 1-3, 08034 Barcelona, Spain)

Abstract

Becoming a smart city is one of the top priorities in the urban agenda of many European cities. Among the various strategies in the transition path, local governments seek to bring innovation to their cities by encouraging multinational enterprises to deploy their green energy services and products in their municipalities. Knowing how to attract these enterprises implies that political leaders understand the multi-criteria decision problem that the energy sector enterprises face when deciding whether to expand to one city or another. To this end, the purpose of this study is to design a new manageable and controllable framework oriented to European cities’ public managers, based on the assessment of criteria and sub-criteria governing the strategic location decision made by these enterprises. A decision support framework is developed based on the AHP technique combined with an extended version of the hesitant fuzzy linguistic TOPSIS method. The main results indicate the higher relative importance of government policies, such as degree of transparency or bureaucracy level, as compared to market conditions or economic aspects of the city’s host country. These results can be great assets to current European leaders, they show the feasibility of the method and open up the possibility to replicate the proposed framework to other sectors or geographical areas.

Suggested Citation

  • Olga Porro & Francesc Pardo-Bosch & Núria Agell & Mónica Sánchez, 2020. "Understanding Location Decisions of Energy Multinational Enterprises within the European Smart Cities’ Context: An Integrated AHP and Extended Fuzzy Linguistic TOPSIS Method," Energies, MDPI, vol. 13(10), pages 1-29, May.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2415-:d:357139
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    Cited by:

    1. Sławomira Hajduk, 2021. "Multi-Criteria Analysis of Smart Cities on the Example of the Polish Cities," Resources, MDPI, vol. 10(5), pages 1-23, May.
    2. Sławomira Hajduk & Dorota Jelonek, 2021. "A Decision-Making Approach Based on TOPSIS Method for Ranking Smart Cities in the Context of Urban Energy," Energies, MDPI, vol. 14(9), pages 1-23, May.

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