Evaluation of After Service Location with Hesitant Fuzzy Vikor: A Case of Drone Company in Türkiye

Yıl 2025, Cilt: 8 Sayı: 4, 937 - 944, 15.07.2025

Dilan Sarpkaya , Gül Tekin Temur

https://doi.org/10.34248/bsengineering.1657267

Öz

This study is conducted to evaluate the suitability of after sales services in drone technology with the use of Hesitant Fuzzy VIKOR method. The main aim of the study is to compare cities’ performances with considering critically important factors such as customer accessibility, operational costs, infrastructure availability, logistics access and regional needs. In this context, eight different after sales service locations of a drone company are evaluated. The research aimed to guide strategic planning processes of decision makers and to determine which cities are more suitable for the adoption of drone technology in commercial and logistics applications. At the same time, infrastructural availability considering regional needs and improvements of operational strategies are points that aimed to draw attention. The findings provide light on the order of importance of the criteria, as well as the strengths and weaknesses of the cities in terms of their ability to effectively use drone technology with ease.

Anahtar Kelimeler

Drone technology, After sales service location, Hesitant fuzzy, Decision making

Kaynakça

• Akram J, Anaissi A. 2024. Ddrm: Distributed drone reputation management for trust and reliability in crowdsourced drone services. In: 2024 IEEE International Conference on Web Services (ICWS), IEEE, pp: 921-931.
• Bruni ME, Khodaparasti S, Perboli G. 2024. Economic sustainability in last-mile drone delivery problem with fulfillment centers: A mathematical formulation. In: ICORES, pp: 382-389.
• de Miguel Molina B, Segarra Oña M. 2018. The drone sector in Europe. Ethics and Civil Drones: European Policies and Proposals for the Industry, pp: 7-33.
• Delgado M, Herrera F, Herrera-Viedma E, Martinez L. 1998. Combining numerical and linguistic information in group decision making. Inf Sci, 107(1-4): pp: 177-194.
• Gou X, Xu Z, Liao H, Herrera F. 2021. Probabilistic double hierarchy linguistic term set and its use in designing an improved VIKOR method: The application in smart healthcare. J Oper Res Soc, 72(12): pp: 2611-2630.
• Jaber A, Ashqar H, Csonka B. 2024. Determining the location of shared electric micro-mobility stations in urban environment. Urban Sci, 8(2): pp: 64.
• Karaaslan F, Karamaz F. 2022. Hesitant fuzzy parameterized hesitant fuzzy soft sets and their applications in decision-making. Int J Comput Math, 99(9): pp: 1868-1889.
• Leech SA, Clark N, Collier PA. 1999. A generalized model of decision-making processes for companies in financial distress. Account Forum, 23(2): pp: 155-174.
• Li D, Ignatius J, Wang D, Yin Y, Cheng TCE. 2024. A branch-and-price-and-cut algorithm for the truck-drone routing problem with simultaneously delivery and pickup. Nav Res Logist, 71(2): pp: 241-285.
• Li F, Kunze O. 2023. A comparative review of air drones (UAVs) and delivery bots (SUGVs) for automated last mile home delivery. Logistics, 7(2): pp: 21.
• Liao H, Xu Z. 2013. A VIKOR-based method for hesitant fuzzy multi-criteria decision making. Fuzzy Optim Decis Mak, 12(4): pp: 373-392.
• Liao H, Si G, Xu Z, Fujita H. 2018. Hesitant fuzzy linguistic preference utility set and its application in selection of fire rescue plans. Int J Environ Res Public Health, 15(4): pp: 664.
• Liao H, Xu Z, Zeng XJ. 2014. Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Trans Fuzzy Syst, 23(5): pp: 1343-1355.
• Mandal P, Ranadive AS. 2019. Hesitant bipolar-valued fuzzy sets and bipolar-valued hesitant fuzzy sets and their applications in multi-attribute group decision making. Granul Comput, 4(3): pp: 559-583.
• Min H. 2023. Leveraging drone technology for last-mile deliveries in the e-tailing ecosystem. Sustainability, 15(15): pp: 11588.
• Navarro Lafuente A. 2024. Business modelling of 5G-based Drone-as-a-Service solution. Universitat Politècnica de Catalunya, Master's thesis, Barcelona, Spain, pp: 86.
• Neziraj EQ, Shaqiri AB. 2018. The impact of information technology in decision making process of companies in Kosovo. Informatologia, 51(1-2): pp: 13-23.
• Nonami K. 2016. Drone technology, cutting-edge drone business, and future prospects. J Robot Mechatron, 28(3): pp: 262-272.
• Pöysäri A. 2023. Customer value of drones. Aalto University, Master of Science in Economics and Business Administration, Helsinki, Finland, pp: 78.
• Qian J, Jin W, Wang X, Yu Y, Zheng M, Miao D. 2023. VIKOR decision making method based on multi-granularity hesitant fuzzy linguistic term sets. In: 2023 International Conference on Cyber-Physical Social Intelligence (ICCSI), pp: 297-302.
• Qian J, Wang T, Lu Y, Yu Y. 2024. A multi-granularity hesitant fuzzy linguistic decision making VIKOR method based on entropy weight and information transformation. J Intell Fuzzy Syst, 46(3): pp: 6505-6516.
• Ravich TM. 2018. Grounding innovation: How ex-ante prohibitions and ex-post allowances impede commercial drone use. Colum Bus L Rev, pp: 495.
• Ray A, De A, Dan PK. 2015. Facility location selection using complete and partial ranking MCDM methods. Int J Ind Syst Eng, 19(2): pp: 262-276.
• Shaikh SA, Memon M, Kim KS. 2021. A multi-criteria decision-making approach for ideal business location identification. Appl Sci, 11(11): pp: 4983.
• Shiau TA, Lin LM, Ding JF, Chou CC. 2011. Hub location selection of third-party logistics service on multiple countries consolidations for ocean freight forwarders by using fuzzy multiple criteria decision-making (MCDM) approach. Int J Phys Sci, 6(19): pp: 4548-4557.
• Shu-we C. 2013. Interval-valued hesitant fuzzy sets. Fuzzy Syst Math, pp: 75-83.
• Singh G, Sharma S, Tandon A, Kaur P. 2022. Drone food delivery: A solution to crowding during the global COVID-19 pandemic. IEEE Trans Eng Manage, 71: pp: 3993-4005.
• Soares LDP, De Oliveira FM, Kamienski CA, Bittencourt LF. 2023. Drone edge management system (drems): Sequencing drone takeoff and landing. In: 2023 10th International Conference on Future Internet Things Cloud (FiCloud), pp: 114-121.
• Sousa M, Almeida MF, Calili R. 2021. Multiple criteria decision making for the achievement of the UN sustainable development goals: A systematic literature review and a research agenda. Sustainability, 13(8): pp: 4129.
• Torres ER, Cano CAG, Castillo VS. 2022. Management information systems and their impact on business decision making. Data Metadata, 1: pp: 21.
• Ullah A, Khan SD. 2024. Impact of sound decision-making on small and medium businesses in Pakistan. Int J Asian Bus Manage, 3(2): pp: 177-192.
• Wei G, Zhang N. 2014. A multiple criteria hesitant fuzzy decision making with Shapley value-based VIKOR method. J Intell Fuzzy Syst, 26(2): pp: 1065-1075.
• Widada AAH, Rahadi RA. 2024. Corporate valuation of Indonesian drone service company: Case study of PT Kelana Geospasial. Int J Econ Bus Manage Res, https://doi.org/10.51505/ijebmr.2024.8818 (accessed date: July 11, 2025).
• Yigit F, Basilio MP, Pereira V. 2024. A hybrid approach for the multi-criteria-based optimization of sequence-dependent setup-based flow shop scheduling. Mathematics, 12(13): pp: 2007.
• Yin Y, Li D, Wang D, Yu Y, Cheng TCE. 2024. Truck-drone pickup and delivery service optimization with availability profiles. Nav Res Logist, Hoboken, USA, pp: 15.
• Yu H, Sun X, Solvang WD, Laporte G. 2021. Solving a real-world urban postal service network redesign problem. Transp Res Part A Policy Pract, 147: pp: 1-18.
• Zarrinpoor N, Fallahnezhad MS, Pishvaee MS. 2017. Design of a reliable facility location model for health service networks. Int J Eng Trans A Basics, 30(1): pp: 75-84.
• Zhu B, Xu Z. 2016. Extended hesitant fuzzy sets. Technol Econ Dev Econ, 22(1): pp: 100-121.