Cilt 9 Sayı 4 (2021): Business & Management Studies: An International Journal
Makaleler

Perakendecilikte drone ile ürün teslimatının tüketicilerin davranışsal niyetlerine etkisi

PDF
  • Zübeyir Çelik,
  • İbrahim Aydın
Zübeyir Çelik
Arş. Gör. Dr., Van Yüzüncü Yıl Üniversitesi, Erciş İşletme Fakültesi, İşletme Bölümü, Van, Türkiye
İbrahim Aydın
Dr. Öğr. Üyesi, Van Yüzüncü Yıl Üniversitesi, Erciş İşletme Fakültesi, İşletme Bölümü, Van, Türkiye

Yayınlanmış 25.12.2021

Nasıl Atıf Yapılır

Perakendecilikte drone ile ürün teslimatının tüketicilerin davranışsal niyetlerine etkisi. (2021). Business & Management Studies: An International Journal, 9(4), 1422-1436. https://doi.org/10.15295/bmij.v9i4.1919

Telif Hakkı (c) 2021 Zübeyir Çelik- İbrahim Aydın

Creative Commons License

Bu çalışma Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License ile lisanslanmıştır.

Nasıl Atıf Yapılır

Perakendecilikte drone ile ürün teslimatının tüketicilerin davranışsal niyetlerine etkisi. (2021). Business & Management Studies: An International Journal, 9(4), 1422-1436. https://doi.org/10.15295/bmij.v9i4.1919

Öz

Bu çalışmanın amacı, perakendecilikte drone ile ürün teslimatının tüketicilerin davranışsal niyetleri üzerindeki etkisini incelemektir. Online anket ve deney yöntemi kullanılarak katılımcılardan toplanan 404 veri için istatistiksel analizler yapılmıştır. Tek örneklem t-testi sonuçlarına göre; drone ile ürün teslimatı, tüketicilerin drone'ları alışveriş için kullanma davranışsal niyetleri üzerinde olumlu ve anlamlı bir etkiye sahiptir. Bağımsız örneklemler t-testi sonuçlarına göre; erkek ve kadınlar arasında ve tek yönlü varyans analizi sonuçlarına göre; X, Y ve Z jenerasyonları arasında tüketicilerin drone'ları alışveriş için kullanma davranışsal niyetlerinde anlamlı bir farklılık yoktur. Basit doğrusal regresyon analizi sonuçlarına göre; algılanan yenilikçilik, hızın göreceli avantajı, fonksiyonel motivasyon, hedonik motivasyon, algılanan güven ve problem farkındalığı drone kullanmaya yönelik tutum üzerinde olumlu ve anlamlı bir etkiye sahiptir. Ancak algılanan riskin drone kullanmaya yönelik tutum üzerindeki olumsuz etkisi anlamlı değildir. Öte yandan drone kullanmaya yönelik tutumun drone kullanma niyeti üzerinde olumlu ve anlamlı bir etkisi bulunmaktadır. Bu çalışma, tüketicilerin perakendecilikte drone ile ürün teslimat hizmetlerini kullanma konusundaki davranışsal niyetlerini başarılı bir şekilde açıklamaktadır.

PDF

Referanslar

  1. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11-39). Springer, Berlin, Heidelberg.
  2. Ajzen, I., & Fishbein, M. (1969). The prediction of behavioral intentions in a choice situation. Journal of experimental social psychology, 5(4), 400-416.
  3. Cha, S. S. (2020). Customers’ intention to use robot-serviced restaurants in Korea: relationship of coolness and MCI factors. International Journal of Contemporary Hospitality Management, 32(9), 2947-2968.
  4. Choe, J. Y. J., Kim, J. J., & Hwang, J. (2021a). Perceived risks from drone food delivery services before and after COVID-19. International Journal of Contemporary Hospitality Management, 33(4), 1276-1296.
  5. Choe, J. Y., Kim, J. J., & Hwang, J. (2021b). 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.
  6. Coombs, W. N., & Schroeder, H. E. (1988). Generalized locus of control: An analysis of factor analytic data. Personality and Individual Differences, 9(1), 79-85.
  7. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
  8. Dunteman, G. H. (1989). Principal Components Analysis. Sage Publications.
  9. Field, A. (2000). Discovering Statistics Using SPSS for Windows. London: Sage Publications.
  10. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading, MA.
  11. Gorsuch, R. L. (1983). Factor Analysis (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
  12. Gramatikov, S., Kitanovski, I., Mishkovski, I., & Jovanovik, M. (2019). Last mile delivery with autonomous vehicles: Fiction or reality.
  13. Hair, J. F., Jr., Black, William C., Babin, B. J., & Anderson, R. E. (2009). Multivariate Data Analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.
  14. Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational and Psychological measurement, 66(3), 393-416.
  15. Hernández, E. J. U., Martínez, J. A. S., & Saucedo, J. A. M. (2020). Optimization of the distribution network using an emerging technology. Applied sciences, 10(3), 857.
  16. Hwang, J., & Choe, J. Y. J. (2019). Exploring perceived risk in building successful drone food delivery services. International Journal of Contemporary Hospitality Management, 1(8), 3249-3269.
  17. Hwang, J., & Kim, H. (2019). Consequences of a green image of drone food delivery services: The moderating role of gender and age. Business Strategy and the Environment, 28(5), 872-884.
  18. Hwang, J., Kim, H., & Kim, W. (2019a). Investigating motivated consumer innovativeness in the context of drone food delivery services. Journal of Hospitality and Tourism Management, 38, 102-110.
  19. Hwang, J., Kim, W., & Kim, J. J. (2020). Application of the value-belief-norm model to environmentally friendly drone food delivery services. International Journal of Contemporary Hospitality Management, 32(5), 1775-1794.
  20. Hwang, J., Lee, J. S., & Kim, H. (2019b). Perceived innovativeness of drone food delivery services and its impacts on attitude and behavioral intentions: The moderating role of gender and age. International Journal of Hospitality Management, 81, 94-103.
  21. Hwang, J., Kim, J. J., & Lee, K. W. (2021). Investigating consumer innovativeness in the context of drone food delivery services: Its impact on attitude and behavioral intentions. Technological Forecasting and Social Change, 163, 120433.
  22. Hwang, J., & Kim, H. (2021). The effects of expected benefits on image, desire, and behavioral intentions in the field of drone food delivery services after the outbreak of COVID-19. Sustainability, 13(1), 117.
  23. Jaramillo, F. P., Shih, K. H., & Cheng, C. C. (2019). Can Drones Deliver Food? What the Food Delivery Industry Needs to Know. International Journal of Performance Measurement, 9(2), 41-62.
  24. Kaoy, N. A., Lesmini, L., & Budiman, T. (2020). Customers’acceptance in using unmanned aerial vehicles (UAV) delivery service. Advances in Transportation and Logistics Research, 3, 629-634.
  25. Kapser, S., & 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.
  26. Kayış, A. (2005). Parametrik Hipotez Testler, SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri. Editör: Kalaycı, Ş., Ankara: Asil Yayın Dağıtım Ltd.Şti., ss.403-419.
  27. Khan, R., Tausif, S., & Javed Malik, A. (2019). Consumer acceptance of delivery drones in urban areas. International Journal of Consumer Studies, 43(1), 87-101.
  28. Kim, J., & Forsythe, S. (2008). Adoption of virtual try-on technology for online apparel shopping. Journal of Interactive Marketing, 22(2), 45-59.
  29. Kim, J. J., & Hwang, J. (2020). Merging the norm activation model and the theory of planned behavior in the context of drone food delivery services: Does the level of product knowledge really matter?. Journal of Hospitality and Tourism Management, 42, 1-11.
  30. Kim, J. J., Kim, I., & Hwang, J. (2021). A change of perceived innovativeness for contactless food delivery services using drones after the outbreak of COVID-19. International Journal of Hospitality Management, 93, 102758.
  31. Köse, N., & Yengin, D. (2018). Dijital pazarlamadan fijital pazarlamaya geçişe örnek olarak artırılmış gerçeklik ve sanal gerçeklik uygulamalarının pazarlama üzerindeki katkılarının incelenmesi. İstanbul Aydın Üniversitesi Dergisi, 10(1), 77-111.
  32. Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30, 607-610.
  33. Macrina, G., Pugliese, L. D. P., Guerriero, F., & Laporte, G. (2020). Drone-aided routing: A literature review. Transportation Research Part C: Emerging Technologies, 120, 102762.
  34. Mathew, A. O., Jha, A. N., Lingappa, A. K., & Sinha, P. (2021). Attitude towards Drone Food Delivery Services—Role of Innovativeness, Perceived Risk, and Green Image. Journal of Open Innovation: Technology, Market, and Complexity, 7(2), 144.
  35. Mittendorf, C., Franzmann, D., & Ostermann, U. (2017). Why Would Customers Engage in Drone Deliveries?. In AMCIS 2017 Proceedings, 1–10.
  36. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222.
  37. Nunnally, J. C. (1978). Psychometric Theory. New York: McGraw-Hill. PewInternet.
  38. Park, J., Kim, S., & Suh, K. (2018). A comparative analysis of the environmental benefits of drone-based delivery services in urban and rural areas. Sustainability, 10(3), 888.
  39. Ramadan, Z. B., Farah, M. F., & Mrad, M. (2017). An adapted TPB approach to consumers’ acceptance of service-delivery drones. Technology Analysis & Strategic Management, 29(7), 817-828.
  40. Rogers, E. M. (1983). Diffusion of Innovations, Third Edition. The Free Press, New York.
  41. Shahzaad, B., Bouguettaya, A., Mistry, S., & Neiat, A. G. (2021). Resilient composition of drone services for delivery. Future Generation Computer Systems, 115, 335-350.
  42. Sipahi, B., Yurtkoru, E.S. ve Çinko, M. (2008). Sosyal Bilimlerde SPSS’le Veri Analizi: İstanbul: Beta Yayınları.
  43. Stevens, J. (1996). Applied Multivariate Statistics for the Social Sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum.
  44. Stevens, J. P. (2002). Applied Multivariate Statistics for the Social Sciences (4th ed.). New Jersey: Lawrance Erlbaum Association.
  45. Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics, (5th ed.). Pearson Education: Boston.
  46. Tabachnick, B. G. & Fidell, L. S. (2013). Using Multivariate Statistics (6th ed.). USA: Pearson Education Limited.
  47. Tom, N. M. F. (2020). Crashed! Why drone delivery is another tech idea not ready to take off. International Business Research, 13(7), 251-251.
  48. Warshaw, P. R., & Davis, F. D. (1985). Disentangling behavioral intention and behavioral expectation. Journal of Experimental Social Psychology, 21(3), 213-228.
  49. Wu, W. Y., & Ke, C. C. (2015). An online shopping behavior model integrating personality traits, perceived risk, and technology acceptance. Social Behavior and Personality: an international journal, 43(1), 85-97.
  50. Vandecasteele, B., & Geuens, M. (2010). Motivated consumer innovativeness: Concept, measurement, and validation. International Journal of Research in Marketing, 27(4), 308-318.
  51. Yoo, W., Yu, E., & Jung, J. (2018). Drone delivery: Factors affecting the public’s attitude and intention to adopt. Telematics and Informatics, 35(6), 1687-1700.