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Development of Modified SERVQUAL–MCDM Model for Quality Determination in Reverse Logistics

Author

Listed:
  • Željko Stević

    (Faculty of Transport and Traffic Engineering Doboj, University of East Sarajevo, Vojvode Mišića 52, 74000 Doboj, Bosnia and Herzegovina)

  • Ilija Tanackov

    (Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovića 6, 21000 Novi Sad, Serbia)

  • Adis Puška

    (Government of Brčko District B&H, Bulevara mira 1, 76100 Brčko, Bosnia and Herzegovina)

  • Goran Jovanov

    (Department of forensics, University of Criminal Investigation and Police Studies, Cara Dušana 196, 11080 Belgrade, Serbia)

  • Jovica Vasiljević

    (State Secretary for Public Transport, City of Belgrade, 27. Marta 43-45, 11000 Belgrade, Serbia)

  • Darko Lojaničić

    (Faculty of Business and Law, MB University, Knez Mihajlova 33, 11000 Belgrade, Serbia)

Abstract

To run a business successfully, quality determination and customer relations are very important factors. Therefore, it is necessary to measure quality and identify critical points of business. In this paper, an original integrated model for measuring the service quality of reverse logistics (RL) was developed for the company Komunalac Teslić, which was used as an example. The Delphi and Full Consistency Method (FUCOM) was applied to determine the significance of the quality dimensions, while a modified SERVQUAL (SQ) model was used to measure the service quality of the logistics. An original SQ questionnaire was formed with a total of 21 statements that were arranged in five standard dimensions. Examining the reliability of the questionnaire for quality dimensions using the Cronbach Alpha coefficient, it was found that the measurement scales for dimensions are appropriate in terms of user expectations, while in terms of quality perception there is no measurement scale for the empathy dimension. An extensive statistical analysis was then performed to verify the results. A Signum test was applied to identify the relationship between the responses in terms of expectations and perceptions, i.e., to examine their differences. The findings obtained by this research show that the expectations were higher than the perceived quality of the services and that there was a significant statistical difference for 12 of the SQ statements. For two statements, there was a significant statistical difference in favor of perceived quality compared to expectations. Based on the results obtained, the company must improve its services in order for service quality to be at a satisfactory level.

Suggested Citation

  • Željko Stević & Ilija Tanackov & Adis Puška & Goran Jovanov & Jovica Vasiljević & Darko Lojaničić, 2021. "Development of Modified SERVQUAL–MCDM Model for Quality Determination in Reverse Logistics," Sustainability, MDPI, vol. 13(10), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5734-:d:558481
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    References listed on IDEAS

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    1. Ya Lan WANG & Tainyi LUOR & Pin LUARN & Hsi-peng LU, 2015. "Contribution and Trend to Quality Research—a literature review of SERVQUAL model from 1998 to 2013," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 19(1), pages 34-45.
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    5. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
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    Cited by:

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    5. Ahmed Dabees & Mahmoud Barakat & Sahar Sobhy Elbarky & Andrej Lisec, 2023. "A Framework for Adopting a Sustainable Reverse Logistics Service Quality for Reverse Logistics Service Providers: A Systematic Literature Review," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    6. Željko STEVIĆ & Dajana NUNIĆ & Ibrahim BADI & Darjan KARABAŠEVIĆ, 2022. "Evaluation of dimensions of SERVQUAL model for determining quality of processes in reverse logistics using a Delphi – Fuzzy PIPRECIA model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 139-159, April.
    7. Chia-Liang Lin & Jwu-Jenq Chen & Yu-Yu Ma, 2023. "Ranking of Service Quality Solution for Blended Design Teaching Using Fuzzy ANP and TOPSIS in the Post-COVID-19 Era," Mathematics, MDPI, vol. 11(5), pages 1-28, March.
    8. Vitor William Batista Martins & Denilson Ricardo de Lucena Nunes & André Cristiano Silva Melo & Rayra Brandão & Antônio Erlindo Braga Júnior & Verônica de Menezes Nascimento Nagata, 2022. "Analysis of the Activities That Make Up the Reverse Logistics Processes and Their Importance for the Future of Logistics Networks: An Exploratory Study Using the TOPSIS Technique," Logistics, MDPI, vol. 6(3), pages 1-17, August.

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