Lojistikte Yeni Teknoloji Kullanımı: Son Kilometre (Adım) Teslimatta Drone (İHA) Kullanımı

Yıl 2023, , 105 - 124, 26.10.2023

Yavuz Toraman , Tuncel Öz

https://doi.org/10.17233/sosyoekonomi.2023.04.05

Öz

Artan e-ticaret hacmi teslimat operasyonlarını zorlaştırmış olup süreçlerin çeşitlendirilmesini zorunluluk haline getirmiştir. Sektörün önde gelenleri teslimat süreçlerinde drone, otonom araç, elektrikli araç vb. kullanmayı denemiştir. Araştırmada İHA’ların teslimatta kullanımının benimsenmesi tüketiciler özelinde incelenmiştir. Araştırmada Teknoloji Kabul Modeli (TKM) kullanılmıştır. Analiz yönteminde ise birden fazla bağımlı ve aracı değişken bulunmasında dolayı literatürde çoklu ilişkilerde sıklıkla kullanılan Kısmi En Küçük Kareler-Yapısal Eşitlik Modellemesi (EKK-YEM) Smart PLS paket programıyla kullanılmıştır. Araştırmada sadece H5 hipotezi reddedilmiş olup diğer hipotezler kabul edilmiştir. Hipotez sonuçları incelendiğinde insanların teknolojik yeniliklere açık olduğu ve gelecekte ürün teslimat süreçlerinde dron kullanımına olumlu baktığını sonucuna ulaşılmıştır.

Anahtar Kelimeler

Lojistik, Son Kilometre (Adım) Teslimat, E-Ticaret, Teknoloji Kabul Modeli (TKM), Tedarik Zinciri Yönetimi

The Use of New Technologies in Logistics: Drone (UAV) Use in Last Mile Delivery

Öz

The increasing volume of e-commerce has complicated delivery operations, making it imperative to diversify the processes. Industry leaders have attempted to use drones, autonomous vehicles, electric vehicles, etc., in delivery processes. The research examined the adoption of consumer drone usage in delivery. The Technology Acceptance Model (TAM) was used in the study. In the analysis method, Partial Least Squares-Structural Equation Modelling (PLS-SEM), which is commonly used in the literature for multiple relationships due to the presence of multiple dependent and mediating variables, was used with the Smart PLS software package. Only the H5 hypothesis was rejected in the research, and the other hypotheses were accepted. When examining the hypothesis results, it was concluded that people are open to technological innovations and have a positive outlook on using drones in future product delivery processes.

Anahtar Kelimeler

Logistics, Last Mile Delivery, E-Commerce, Technology Acceptance Model (TAM), Supply Chain Management

Kaynakça

• Agustina, D. (2019), “Extension of Technology Acceptance Model (Etam): Adoption of Cryptocurrency Online Trading Technology”, Jurnal Ekonomi, 24(2), 272-287.
• Aurambout, J.-P. et al. (2019), “Last mile delivery by drones: an estimation of viable market potential and access to citizens across European cities”, European Transport Research Review, 11, 10.1186/s12544-019-0368-2.
• Balcik, B. et al. (2008), “Last mile distribution in humanitarian relief”, Journal of Intelligent Transportation Systems, 12(2), 51-63.
• Barrett, A. et al. (2023), “Technology acceptance model and multi-user virtual reality learning environments for Chinese language education”, Interactive Learning Environments, 31(3), 1665-1682.
• Chocarro, R. et al. (2023), “Teachers’ attitudes towards chatbots in education: a technology acceptance model approach considering the effect of social language, bot proactiveness, and users’ characteristics”, Educational Studies, 49(2), 295-313.
• Choe, J.Y. et al. (2021), “Innovative marketing strategies for the successful construction of drone food delivery services: Merging TAM with TPB”, Journal of Travel & Tourism Marketing, 38(1), 16-30.
• Curlander, J.C. et al. (2017), Patent Application Publication, Multi-Level Fulfillment Center for Unmanned Aerial Vehicles Pub. No. US 2017/0175413 A1 Pub. Date: Jun. 22.
• Davis, F.D. & V. Venkatesh (1996), “A critical assessment of potential measurement biases in the technology acceptance model: three experiments”, International Journal of Human-Computer Studies, 45(1), 19-45.
• Davis, F.D. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of information technology”, MIS Quarterly, 13(3), 319-340.
• Davis, F.D. (1993), “User acceptance of information technology: system characteristics, user perceptions and behavioral impacts”, International Journal of Man-Machine Studies, 38(3), 475-487.
• Davis, F.D. et al. (1989), “User acceptance of computer technology: A comparison of two theoretical models”, Management Science, 35(8), 982-1003.
• Edwards, D. et al. (2023), “Use of delivery drones for humanitarian operations: analysis of adoption barriers among logistics service providers from the technology acceptance model perspective”, Annals of Operations Research, 1-23.
• Eskandaripour, H. & E. Boldsaikhan (2023), “Last-mile drone delivery: Past, present, and future”, Drones, 7(2), 77.
• Garcia, M.B. (2023), “Factors Affecting Adoption Intention of Productivity Software Applications Among Teachers: A Structural Equation Modeling Investigation”, International Journal of Human-Computer Interaction, 1-14.
• Garcia, O. & A. Santoso (2019), “Comparative Evaluation of Drone Delivery Systems in Last-Mile Delivery”, Masters Thesis, MIT.
• Goodman, R.W. (2005), “Whatever you call it, just don't think of last-mile logistics, last”, Global Logistics & Supply Chain Strategies, 9(12), 46-51.
• Hair, J.F. et al. (2010), Multivariate Data Analysis, 7th ed., Pearson Education.
• Hair, J.F. et al. (2011), “PLS-SEM: Indeed a silver bullet”, Journal of Marketing Theory and Practice, 19(2), 139-152.
• Hair, J.F. et al. (2016), A primer on partial least squares structural equation modeling (PLS-SEM), Sage Publications.
• Hair, J.F. et al. (2017), A Primer on Partial Least Squares Structural Equation Modelling (PLSSEM), Los Angeles: Sage Publication. Second Edition.
• Hinzmann, J. & K. Bogatzki (2020), “Acceptance of autonomous delivery vehicles for last mile delivery in Germany: extension of the technology acceptance model to an autonomous delivery vehicles acceptance model”, Master Thesis, Jönköping University.
• İslamoğlu, A.H. & Ü. Alnıaçık (2014), Sosyal Bilimlerde Araştırma Yöntemleri, İstanbul: Beta Yayınevi.
• Jacobs, K. et al. (2019), The Last-Mile Delivery Challenge, Capgemini Research Institute.
• Joerss, M. et al. (2016), Parcel Delivery: The Future of Last Mile, McKinsey & Company.
• Kamalanon, P. et al. (2022), “‘Why do we buy green products?’ An extended theory of the planned behavior model for green product purchase behavior”, Sustainability, 14(2), 689.
• Kaminski, J. (2011), “Diffusion of innovation theory”, Canadian Journal of Nursing Informatics, 6(2), 1-6.
• Koh, L.Y. et al. (2023), “Urban drone adoption: Addressing technological, privacy and task-technology fit concerns”, Technology in Society, 72, 102203.
• Kurtuluş, K. (2010), Araştırma Yöntemleri, İstanbul: Türkmen Kitabevi.
• Lee, J. et al. (2019), “The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties”, Telematics and Informatics, 39, 37-48.
• Mangiaracina, R. et al. (2019), “Innovative solutions to increase last-mile delivery efficiency in B2C e-commerce: a literature review”, International Journal of Physical Distribution & Logistics Management, 49(9), 901-920.
• Michel, A.H. (2017), Amazon’s Drone Patents, Center for the Study of Drone, <https://dronecenter.bard.edu/files/2017/09/CSD-Amazons-Drone-Patents-1.pdf>, 26.12.2022.
• Moshref-Javadi, M. et al. (2020), “A truck and drones model for last-mile delivery: A mathematical model and heuristic approach”, Applied Mathematical Modelling, 80, 290-318.
• Nakıboğlu, G. (2020), “Drone Taşımacılığı ve Son-Adım Teslimatta Kullanımı”, Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 24(2), 285-298.
• Özdamar, K. (2004), Paket Programlar ile İstatistiksel Veri Analizi, Eskişehir: Kaan Kitabevi.
• Prakarsa, G. et al. (2020), “Integration of mobile perceived compatibility, mobile perceived financial resources, and mobile perceived system quality with TAM in virtual hotel operator applications in Indonesia”, International Journal of Global Operations Research, 1(2), 62-70.
• Rabta, B. et al. (2018), “A drone fleet model for last-mile distribution in disaster relief operations”, International Journal of Disaster Risk Reduction, 28, 107-112.
• Rogers, E.M. et al. (2014), “Diffusion of Innovations”, in: An integrated approach to communication theory and research (432-448), Routledge.
• Shapira, S. & J.R. Cauchard (2022), “Integrating drones in response to public health emergencies: A combined framework to explore technology acceptance”, Frontiers in Public Health, 10, 1019626.
• Shaw, N. et al. (2022), “Towards a Mobile App Diffusion of Innovations model: A multinational study of mobile wallet adoption”, Journal of Retailing and Consumer Services, 64, 102768.
• Şimşek, Ö.F. (2007), Yapısal Eşitlik Modellemesine Giriş: Temel İlkeler ve LISREL Uygulamaları, Ankara: Ekinoks.
• Singireddy, S.R.R. & T.U. Daim (2018), “Technology Roadmap: Drone Delivery-Amazon Prime Air”, in: Infrastructure and Technology Management (387-412), Springer, Cham.
• Sugandini, D. et al. (2018), “The role of uncertainty, perceived ease of use, and perceived usefulness towards the technology adoption”, International Journal of Civil Engineering and Technology (IJCIET), 9(4), 660-669.
• Temando (2016), State of Shipping in Commerce 2016, <https://temando.com/en/research-2016>, 25.12.2022.
• Tian, Y. et al. (2023), “Moderating role of perceived trust and perceived service quality on consumers’ use behavior of Alipay e-wallet system: the perspectives of technology acceptance model and theory of planned behavior”, Human Behavior and Emerging Technologies, (2023), 5276406.
• Toraman, Y. & B.B. Geçit (2023), “User acceptance of metaverse: an analysis for e-commerce in the framework of technology acceptance model (TAM)”, Sosyoekonomi, 31(55), 85-104.
• Valencia-Arias, A. et al. (2022), “Factors associated with the adoption of drones for product delivery in the context of the COVID-19 pandemic in Medellin, Colombia”, Drones, 6(9), 225.
• Venkatesh, V. & F.D. Davis (1996), “A model of the antecedents of perceived ease of use: Development and test”, Decision Sciences, 27(3), 451-481.
• Venkatesh, V. & H. Bala (2008), “Technology acceptance model 3 and a research agenda on interventions”, Decision Sciences, 39(2), 273-315.
• Venkatesh, V. & M.G. Morris (2000), “Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior”, MIS Quarterly, 24(1), 115-139.
• Venkatesh, V. et al. (2003), “User acceptance of information technology: Toward a unified view”, MIS Quarterly, 27(3), 425-478.
• Venkatesh, V. et al. (2007), “Dead or alive? The development, trajectory and future of technology adoption research”, Journal of the Association for Information Systems, 8(4), 267-286.
• Waris, I. et al. (2022), “An Empirical Evaluation of Customers’ Adoption of Drone Food Delivery Services: An Extended Technology Acceptance Model”, Sustainability, 14(5), 2922.