FACTORS INFLUENCING EXPECTATIONS AND ACCEPTANCE OF DRONE DELIVERY SERVICES: A CASE STUDY IN THAILAND
DOI:
https://doi.org/10.60101/gbafr.2026.283220Keywords:
Macro environment factor, Expectation, Acceptance of drone delivery, ThailandAbstract
Purpose – This study aims to examine the effects of macro-environmental factors on consumer expectations and the acceptance of drone delivery services within the context of Thailand’s logistics industry.
Methodology – A quantitative cross-sectional research design was employed. Data were collected from 400 consumers in Bangkok and surrounding metropolitan areas using a structured questionnaire and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess reliability, validity, and the relationships among the proposed constructs.
Results – The findings indicate that macro-environmental factors significantly influence consumer expectations and exert a direct effect on the acceptance of drone delivery. Consumer expectations also have a positive effect on acceptance and serve as a mediating variable between macro-environmental factors and drone delivery acceptance.
Implications – The results highlight the importance of developing technological infrastructure, improving regulatory and public policy frameworks, and communicating service value to consumers in order to strengthen trust and accelerate the sustainable commercial adoption of drone delivery services.
Originality/Value – This study provides new empirical evidence from a developing economy perspective by integrating macro-environmental factors and consumer expectations into a comprehensive technology acceptance framework, thereby extending existing knowledge and supporting innovation strategies in emerging logistics markets.
References
Afridi, S., Hlebowicz, K., Cawthorne, D., & Lundquist, U. P. S. (2024). Unveiling the impact of drone noise on wildlife: 2024 international conference on unmanned aircraft systems, ICUAS 2024. In 2024 International Conference on Unmanned Aircraft Systems (ICUAS) (pp. 1409-1416). Chania – Crete. https://doi.org/10.1109/ICUAS60882.2024.10557094
Ahmed, A. A. (2025). Drone technology in logistics revolutionizing last-mile delivery solutions. Eurasian Journal of Theoretical and Applied Sciences, 1(1), 25–35.
Aster, H., Zeilerbauer, L., & Lindorfer, J. (2025). Environmental impacts of drone delivery: A comparative meta-analysis and standardised LCA metrics. Journal of Sustainability, 1(2). https://doi.org/10.55845/jos-2025-1249
Belhor, M., & Nya, D. N. (2025). Drone-based delivery in logistics: Interdisciplinary challenges. In 2025 11th International Conference on Control, Decision and Information Technologies (CoDIT) (pp. 823-828). https://doi.org/10.1109/CoDIT66093.2025.11321813
Bennington, L., & Cummane, J. (1998). Measuring service quality: A hybrid methodology. Total Quality Management, 9(6), 395-405. https://doi.org/10.1080/0954412988343
Dabić, M., Ferreira, J. J., Lopes, J. M., & Gomes, S. (2024). Consumer preferences and barriers in the adoption of drone delivery services: A comprehensive analysis. IEEE transactions on engineering management, 72, 47-61. https://doi.org/10.1109/TEM.2024.3494051
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Ellenrieder, S., Jourdan, N., & Reuter-Oppermann, M. (2023). Delivery Drones - Just a Hype? Towards Autonomous Air Mobility Services at Scale. In Proceedings of the 56th Hawaii International Conference on System Sciences (pp.1469-1478). https://doi.org/10.24251/HICSS.2023.184
Garg, V., Niranjan, S., Prybutok, V., Pohlen, T., & Gligor, D. (2023). Drones in last-mile delivery: A systematic review on Efficiency, Accessibility, and Sustainability. Transportation Research Part D: Transport and Environment, 123, 103831. https://doi.org/10.1016/j.trd.2023.103831
Goebel, P., Moeller, S., & Pibernik, R. (2012). Paying for convenience: Attractiveness and revenue potential of time‐based delivery services. International Journal of Physical Distribution & Logistics Management, 42(6), 584–606. https://doi.org/10.1108/09600031211250604
Goodchild, A., & Toy, J. (2018). Delivery by drone: An evaluation of unmanned aerial vehicle technology in reducing CO2 emissions in the delivery service industry. Transportation Research Part D: Transport and Environment, 61, 58–67. https://doi.org/10.1016/j.trd.2017.02.017
Grofelnik, I., Godnov, U., & Sternad, M. (2022). Drone last mile delivery: An assessment of the viable market and security potential of drone delivery. Ekonomski Vjesnik, 35(2), 337–352. https://doi.org/10.51680/ev.35.2.8
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433. https://doi.org/10.1007/s11747-011-0261-6
Jahani, H., Khosravi, Y., Kargar, B., Ong, K.-L., & Arisian, S. (2025). Exploring the role of drones and UAVs in logistics and supply chain management: A novel text-based literature review. International Journal of Production Research, 63(5), 1873–1897. https://doi.org/10.1080/00207543.2024.2373425
Kim, D. H. (2019). Regulations and Laws Pertaining to the use of Unmanned Aircraft Systems (UAS) by ICAO, USA, China, Japan, Australia, India, and Korea. In Unmanned Aerial Vehicles in Civilian Logistics and Supply Chain Management (pp. 169–207). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-5225-7900-7.ch007
Kim, W., & Hur, S. H. (2024). Why and why not? Systematic review of the willingness to accept drone and robot deliveries. Transportation Research Record, 2678(12), 945–962. https://doi.org/10.1177/03611981241248439
Koellner, E. (2025). Beyond boundaries: Leveraging autonomous drones for sustainable development in emerging economies (SSRN Scholarly Paper No. 5214885). Social Science Research Network. https://doi.org/10.2139/ssrn.5214885
Kutynska, A., & Dei, M. (2023). Legal regulation of the use of drones: Human rights and privacy challenges. Journal of International Legal Communication, 8(1), 39–55. https://doi.org/10.32612/uw.27201643.2023.8.pp.39-55
Lehmann, A., Kalter, I., Jahn, P., & Fink, F. (2025). A user journey: Development of drone-based medication delivery—meeting developers’ and co-developers’ expectations. Designs, 9(2), 27. https://doi.org/10.3390/designs9020027
Liu, D., Lai, M.-C., & Tsay, W.-D. (2020). Determinants analysis of drone delivery service adoption. In 2020 3rd IEEE International Conference on Knowledge Innovation and Invention (ICKII) (pp. 1–4). Kaohsiung, Taiwan. https://doi.org/10.1109/ICKII50300.2020.9318942
Mazur, M., & Borucka, A. (2025). Commercial drone deliveries: Evolution, applications, and market dynamics. In 2025 13th International Conference on Traffic and Logistic Engineering (ICTLE) (pp. 336–340). Macau, China. https://doi.org/10.1109/ICTLE67020.2025.11203681
Nguyen, D. H., de Leeuw, S., Dullaert, W., & Foubert, B. P. J. (2019). What is the right delivery option for you? Consumer preferences for delivery attributes in online retailing. Journal of Business Logistics, 40(4), 299–321. https://doi.org/10.1111/jbl.12210
Nugraha, R. A., Jeyakodi, D., & Mahem, T. (2016). Urgency for legal framework on drones: Lessons for Indonesia, India, and Thailand. Indonesia Law Review, 6(2), 137.
Parasuraman, A., Zeithaml, V. A., & Berry, L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.
Penagos, P., Encarnación, T., & Gonzalez-Calderon, C. A. (2026). Drivers of consumers’ adoption of parcel lockers as an alternative last-mile delivery solution in emerging economies. Transportation Research Interdisciplinary Perspectives, 36, 101866. https://doi.org/10.1016/j.trip.2026.101866
Roca-Riu, M., & Menendez, M. (2019). Logistic deliveries with drones: State of the art of practice and research. In the 19th Swiss Transport Research Conference (pp. 1-14). Monte Verità, Switzerland. https://doi.org/10.3929/ETHZ-B-000342823
Rovinelli, R. J., & Hambleton, R. K. (1976). On the Use of Content Specialists in the Assessment of Criterion-Referenced Test Item Validity. https://eric.ed.gov/?id=ED121845
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2022). Partial Least Squares Structural Equation Modeling. In Handbook of Market Research (pp. 587–632). Springer, Cham. https://doi.org/10.1007/978-3-319-57413-4_15
Schmidt, S., & Saraceni, A. (2024). Consumer acceptance of drone-based technology for last mile delivery. Research in Transportation Economics, 103, 101404. https://doi.org/10.1016/j.retrec.2023.101404
Sham, R., Abuznemah, F., Thong, Q. Y., & Fakir, F. Z. (2025). Urban air delivery: What Malaysians think about it? Environment-Behaviour Proceedings Journal, 10(33), 347–355. https://doi.org/10.21834/e-bpj.v10i33.7193
Shastri, M., & Shrivastav, U. (2025). Optimizing delivery logistics: Enhancing speed and safety with drone technology (arXiv:2507.17253). arXiv. https://doi.org/10.48550/arXiv.2507.17253
Silva, A. T., Duarte, S. P., Melo, S., Witkowska-Konieczny, A., Giannuzzi, M., & Lobo, A. (2023). Attitudes towards urban air mobility for e-commerce deliveries: An exploratory survey comparing European regions. Aerospace, 10(6), 536. https://doi.org/10.3390/aerospace10060536
Sindiramutty, S. R., Jhanjhi, N. Z., Tan, C. E., Yun, K. J., Manchuri, A. R., Ashraf, H., Murugesan, R. K., Tee, W. J., & Hussain, M. (2024). Data Security and Privacy Concerns in Drone Operations. In Cybersecurity Issues and Challenges in the Drone Industry (pp. 236–290). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-0774-8.ch010
Sithanant, T., Chaiyasoonthorn, W., & Chaveesuk, S. (2025). Exploring factors influencing Thai autonomous vehicle acceptance: A grounded theory approach. Edelweiss Applied Science and Technology, 9(11), 556–570. https://doi.org/10.55214/2576-8484.v9i11.10918
Suvittawat, A. (2024). Investigating farmers’ perceptions of drone technology in Thailand: Exploring expectations, product quality, perceived value, and adoption in agriculture. Agriculture, 14(12), 2183. https://doi.org/10.3390/agriculture14122183
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd
Van Droogenbroeck, E., & Van Hove, L. (2022). Are the time-poor willing to pay more for online grocery services? When ‘no’ means ‘yes.’ Journal of Theoretical and Applied Electronic Commerce Research, 17(1), 253–290. https://doi.org/10.3390/jtaer17010013
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view1. MIS Quarterly, 27(3), 425–478.
Waris, I., Ali, R., Nayyar, A., Baz, M., Liu, R., & Hameed, I. (2022). An empirical evaluation of customers’ adoption of drone food delivery services: An extended technology acceptance model. Sustainability, 14(5), 2922. https://doi.org/10.3390/su14052922
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2–22. https://doi.org/10.1177/002224298805200302
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Faculty of Business Administration, Rajamangala University of Technology Thanyaburi
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
