Son Adım Teslimat Yöntemi Olan Otonom Teslimat Araçlarının Tüketiciler Tarafından Kabulü: Teknolojiye Hazırlığın Düzenleyici Rolü

Year 2023, Volume: 6 Issue: 1, 166 - 183, 27.03.2023

Mehmet Zahid Ecevit

https://doi.org/10.51513/jitsa.1256291

Cited By: 1

Abstract

Özet: Dünyada ve Türkiye’de elektronik ticaretin artmasıyla müşterilerin teslimat konusundaki hız ve esneklik beklentisini artırmıştır ve son adım teslimatı daha da önemli hale getirmiştir. Nihai tüketiciye dokunması nedeniyle memnuniyet üzerinde doğrudan etkiye sahip olan bu aşama, lojistik açısından en problemli ve maliyetli bir evredir. Bu problemlerden bazıları gürültü kirliliği, CO2 salınımı ve trafik yoğunluğu olup bunlarla da sınırlı değildir. Son adım teslimat uygulamalarında yeniliklere ihtiyaç duyulmaktadır. Özellikle kaldırımlarda ve sokaklarda giden elektrikli ve sürücüsüz kara araçları olarak tanımlanan otonom teslimat araçlarının (ADV) değişim ihtiyacını karşılayabileceğine ve son adım teslimat pazarında devrim yaratma potansiyeline sahip olduğuna inanılmakta, bu nedenle daha sürdürülebilir, verimli ve müşteri odaklı bir ulaşım alternatifi olarak karşımıza çıkmaktadır. Otonom araçların kabulü birçok araştırmaya konu olmasına rağmen, çok az araştırma Otonom Teslimat Araçlarının kabulünü konu edinmiştir. Bu nedenle ADV'lerin kullanıcı kabulünü belirleyen yapılara ilişkin daha kapsamlı bir genel bakış elde etmek önem arz etmektedir. Bu çalışmada uyarlanmış bir UTAUT2 modeli ve TRI modeli kullanılarak üniversite öğrencilerinin ADV kabulü ile ilgili algı ve niyetleri araştırılmıştır. Hipotezlerin test edilmesinde Smart PLS4 yazılımı kullanılmış ve çoklu grup analizi ile TRI yüksek ve düşük gruplar kıyaslanmıştır. Araştırma sonucunda göre iki grup arasında özellikle fiyat hassasiyetinin ADV kabulü üzerindeki etkisinde anlamlı farklılık tespit edilmiştir.

Keywords

Son Adım Teslimat, Otonom Teslimat Araçları, Teknoloji Hazırlık Endeksi

References

• Althuizen, N. (2018). Using structural technology acceptance models to segment intended users of a new technology: Propositions and an empirical illustration. Information Systems Journal, 28(5), 879-904.
• Anderson, J. C. ve Gerbing, D. W. (1988), “Structural equation modelling in practice: A review and recommended two-step approach”, Psychological Bulletin, 103, 411-423.
• Bagozzi, R.P. ve Yi, Y. (1988), “On the evaluation of structural equation models”, Journal of the Academy of Marketing Science, 16 1, 74-94.
• Bates, O., Friday, A., Allen, J., Cherrett, T., McLeod, F., Bektas, T., ve Davies, N. (2018, April). Transforming last-mile logistics: Opportunities for more sustainable deliveries. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (pp. 1-14).
• Boysen, N., Fedtke, S., ve Schwerdfeger, S. (2021). Last-mile delivery concepts: a survey from an operational research perspective. Or Spectrum, 43, 1-58.
• Brown, S. A., ve Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS quarterly, 399-426.
• Carmines, E. G., ve Zeller, R. A. (1979). Reliability and validity assessment. Sage publications.
• Chaveesuk, S., Chaiyasoonthorn, W., Kamales, N., Dacko-Pikiewicz, Z., Liszewski, W., ve Khalid, B. (2023). Evaluating the Determinants of Consumer Adoption of Autonomous Vehicles in Thailand—An Extended UTAUT Model. Energies, 16(2), 855.
• Choi, J. K., ve Ji, Y. G. (2015). Investigating the importance of trust on adopting an autonomous vehicle. International Journal of Human-Computer Interaction, 31(10), 692-702.
• Çakılcı, C., ve Öztürkoğlu, Y. (2021). Sürdürülebilir ‘Son Kilometre’teslimat Süreci İçin Kavramsal Bir Çerçeve Modelinin Geliştirilmesi. Lojistik Dergisi, (54), 61-81.
• Davis, F. D., Bagozzi, R. P., ve Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
• Dündar, A. O. (2021). Kitle Kaynak Lojistiğin Son Adım Teslimatlarda Uygulanması Üzerine Bir Araştırma. Selçuk Üniversitesi Sosyal Bilimler Meslek Yüksekokulu Dergisi, 24(2), 511-527.
• Faul, F., Erdfelder, E., Buchner, A., ve Lang, A. G. (2009). Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior research methods, 41(4), 1149-1160.
• Faul, F., Erdfelder, E., Lang, A. G., ve Buchner, A. (2007). G* Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior research methods, 39(2), 175-191.
• Fornell, C. ve Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, 18, 1, 39-50.
• George D ve Mallery P. (2003). SPSS for Windows Step by Step: A Simple Guide and Reference 11.0 update (4th ed.), Allyn & Bacon: Boston.
• Ghalandari, K. (2012). The effect of performance expectancy, effort expectancy, social influence and facilitating conditions on acceptance of e-banking services in Iran: The moderating role of age and gender. Middle-East Journal of Scientific Research, 12(6), 801-807.
• Goldsmith, R. E., Kim, D., Flynn, L. R., ve Kim, W. M. (2005). Price sensitivity and innovativeness for fashion among Korean consumers. The Journal of social psychology, 145(5), 501-508.
• Gondoli, D. M. ve Jacob, T. (1993), “Factor structure within and across three family-assessment procedures”, Journal of Family Psychology, 6, 3, 278.
• Gürsoy, D., Chi, O. H., Lu, L., ve Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169.
• Güzel, D., Tüzemen, A., ve Yaprak, B. (2017). Firmaların 3PL (üçüncü parti lojistik) hizmet sağlayıcılarını seçerken kullandıkları kriteler üzerine bir çalışma: Erzurum ihracatçıları örneği. Ataturk University Journal of Economics & Administrative Sciences, 31(3).
• Hair, J. F., Risher, J. J., Sarstedt, M., ve Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24.
• Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. ve Tatham, R.L. (2009), Multivariate Data Analysis, Pearson.
• Hair, J.F., Ringle, C.M. ve Sarstedt, M. (2011), “PLS- SEM: indeed, a silver bullet”, Journal of Marketing Theory and Practice,19, 2, 139-152.
• Hegner, S. M., Beldad, A. D., ve Brunswick, G. J. (2019). In automatic we trust: investigating the impact of trust, control, personality characteristics, and extrinsic and intrinsic motivations on the acceptance of autonomous vehicles. International Journal of Human–Computer Interaction, 35(19), 1769-1780.
• Hohenberger, C., Spörrle, M., ve Welpe, I. M. (2016). How and why do men and women differ in their willingness to use automated cars? The influence of emotions across different age groups. Transportation Research Part A: Policy and Practice, 94, 374-385.
• Hu, L. T., ve Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55. Joerss, M., Schröder, J., Neuhaus, F., Klink, C., ve Mann, F. (2016). Parcel delivery: The future of last mile. McKinsey & Company, 1-32.
• Kapser, S. (2019). User acceptance of autonomous delivery vehicles–an empirical study in Germany. University of Northumbria at Newcastle (United Kingdom).
• Kapser, S., Abdelrahman, M., ve Bernecker, T. (2021). Autonomous delivery vehicles to fight the spread of Covid-19–How do men and women differ in their acceptance?. Transportation Research Part A: Policy and Practice, 148, 183-198.
• Kapser, S., ve Abdelrahman, M. (2019). Extending UTAUT2 to Explore User Acceptance of Autonomous Delivery Vehicles.
• Kapser, S., ve Abdelrahman, M. (2020). Acceptance of autonomous delivery vehicles for last-mile delivery in Germany–Extending UTAUT2 with risk perceptions. Transportation Research Part C: Emerging Technologies, 111, 210-225
• Lakhal, S., Khechine, H., ve Pascot, D. (2013). Student behavioural intentions to use desktop video conferencing in a distance course: integration of autonomy to the UTAUT model. Journal of Computing in Higher Education, 25, 93-121.
• Latané, B., ve Wolf, S. (1981). The social impact of majorities and minorities. Psychological Review, 88(5), 438. Law, R., Chan, I. C. C., ve Wang, L. (2018). A comprehensive review of mobile technology use in hospitality and tourism. Journal of Hospitality Marketing & Management, 27(6), 626-648.
• Li, B., Liu, S., Tang, J., Gaudiot, J. L., Zhang, L., ve Kong, Q. (2020). Autonomous last-mile delivery vehicles in complex traffic environments. Computer, 53(11), 26-35.
• Liu, C., Wang, Q., ve Susilo, Y. O. (2019). Assessing the impacts of collection-delivery points to individual’s activity-travel patterns: A greener last mile alternative?. Transportation Research Part E: Logistics and Transportation Review, 121, 84-99.
• Madigan, R., Louw, T., Wilbrink, M., Schieben, A., ve Merat, N. (2017). What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems. Transportation research part F: traffic psychology and behaviour, 50, 55-64.
• Marsden, N., Bernecker, T., Zöllner, R., Sußmann, N., ve Kapser, S. (2018, June). BUGA: log–A real-world laboratory approach to designing an automated transport system for goods in Urban Areas. In 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1-9). IEEE.
• Mateos-Aparicio, G. (2011). Partial least squares (PLS) methods: Origins, evolution, and application to social sciences. Communications in Statistics-Theory and Methods, 40(13), 2305-2317.
• Nakıboğlu, G. (2020), Drone Taşımacılığı ve Son-Adım Teslimatta Kullanımı. Çukurova Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 24(2), 285-298.
• Panagiotopoulos, I., ve Dimitrakopoulos, G. (2018). An empirical investigation on consumers’ intentions towards autonomous driving. Transportation research part C: emerging technologies, 95, 773-784.
• Pangaribuan, C. H., ve Wulandar, Y. S. (2019). A crowdfunding platform user acceptance: An empirical examination of performance expectancy, effort expectancy, social factors, facilitating condition, attitude, and behavioral intention. In SU-AFBE 2018: Proceedings of the 1st Sampoerna University-AFBE International Conference, SU-AFBE 2018, 6-7 December 2018, Jakarta Indonesia (p. 346). European Alliance for Innovation.
• Pani, A., Mishra, S., Golias, M., ve Figliozzi, M. (2020). Evaluating public acceptance of autonomous delivery robots during COVID-19 pandemic. Transportation research part D: transport and environment, 89, 102600. Parasuraman, A., ve Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of service research, 18(1), 59-74.
• Rahman, M. M., Lesch, M. F., Horrey, W. J., ve Strawderman, L. (2017). Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. Accident Analysis & Prevention, 108, 361-373.
• Rather, R. A. (2018). Investigating the impact of customer brand identification on hospitality brand loyalty: A social identity perspective. Journal of Hospitality Marketing & Management, 27(5), 487-513.
• Salari, M., Kattan, L., and Gentili, M. (2022). Optimal roadside units location for path flow reconstruction in a connected vehicle environment. Transportation Research Part C: Emerging Technologies, 138, 103625.
• Sarstedt, M., Henseler, J., ve Ringle, C. M. (2011). Multigroup analysis in partial least squares (PLS) path modeling: Alternative methods and empirical results. In Measurement and research methods in international marketing. Emerald Group Publishing Limited.
• Shmueli, G., ve Koppius, O. R. (2011). Predictive analytics in information systems research. MIS quarterly, 553-572.
• Statista (2021a). E-commerce worldwide - Statistics & Facts, erişim tarihi: 15.08.2021, https://www.statista.com/topics/871/online-shopping/#dossier-chapter1
• Statista (2021b). Digital Market Outlook: retail e-commerce sales CAGR in selected markets 2021-2025, erişim tarihi: 15.08.2021, https://www.statista.com/forecasts/220177/b2c-e-commerce-sales-cagr-forecast-for-selected- countries
• Tsai, H. Y. S., ve LaRose, R. (2015). Broadband Internet adoption and utilization in the inner city: A comparison of competing theories. Computers in human behavior, 51, 344-355.
• Venkatesh, V., Morris, M. G., Davis, G. B., ve Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
• Venkatesh, V., Thong, J. Y., ve Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.
• Wang, Y., Zhang, D., Liu, Q., Shen, F., ve Lee, L. H. (2016). Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions. Transportation Research Part E: Logistics and Transportation Review, 93, 279-293.
• Yuen, K. F., Wong, Y. D., Ma, F., ve Wang, X. (2020). The determinants of public acceptance of autonomous vehicles: An innovation diffusion perspective. Journal of Cleaner Production, 270, 121904.