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Investigation Of The Mediating Roles Of Perceived Risk And Word Of Mouth İn The Effect Of Perceived Trust İn With Drone Delivery On İntention To Use

Yıl 2023, Cilt 10, Sayı 1, 49 - 67, 21.03.2023
https://doi.org/10.48064/equinox.1254198

Öz

Delivery by drone will create important opportunities for companies, depending on the idea that people will prefer contactless transactions after the pandemic. In this study, the mediating roles of perceived risk and word of mouth in the effect of perceived trust in drone delivery on intention to use were investigated. It is expected that the variables to be included in the study will provide important insights for companies in the context of contactless delivery. The population of the study consisted of people living in Turkey. The sample of the study consisted of 260 people. Data were collected with a questionnaire given on the Internet and snowball sampling method. Before filling out the questionnaire, the participants were shown a video about the delivery by drone. Statistical analyzes were made with structural equation modeling. According to the findings, it was seen that perceived trust had a positive effect on word of mouth and intention to use but had a negative effect on perceived risk. It was concluded that the perceived risk did not have any effect on the intention to use. Word of mouth communication was found to have a positive effect on the intention to use. Word of mouth communication mediates the impact of perceived trust on the intention to use. But perceived risk not mediated the impact of perceived trust on the intention to use. Within the framework of the results obtained, it can be stated that it is very important to increase the perceived trust of consumers for drone delivery. In order to increase perceived trust, it is thought that it is very important to minimize the technical risks of this delivery method and to explain to people that this delivery method is reliable through marketing communication activities.

Kaynakça

  • Aydın, İ. (2022). Hedonik motivasyonun drone ile teslimata yönelik tutum üzerindeki etkisi: ağızdan ağıza iletişimin aracılık rolü. İşletme Akademisi Dergisi, 3 (1), 34-45.
  • Benarbia, T., & Kyamakya, K. (2022). A literature review of drone-based package delivery logistics systems and their implementation feasibility. Sustainability, 14(1), 1-15.
  • Büyüköztürk, Ş. (2011). Sosyal Bilimler İçin Veri Analizi El Kitabı İstatistik, Araştırma Deseni SPSS Uygulamaları ve Yorum. Ankara: Pegem Akademi.
  • Campbell, M. C., & Goodstein, R. C. (2001). The moderating effect of perceived risk on consumers' evaluations of product incongruity: Preference for the norm. Journal of consumer Research, 28(3), 439-449.
  • 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.
  • Chen, C., Leon, S., & Ractham, P. (2022). Will customers adopt last-mile drone delivery services? An analysis of drone delivery in the emerging market economy. Cogent Business & Management, 9(1), 1-18.
  • Chiang, W. C., Li, Y., Shang, J., & Urban, T. L. (2019). Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization. Applied energy, 242, 1164-1175.
  • 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.
  • 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.
  • Cobb, M. D., & Macoubrie, J. (2004). Public perceptions about nanotechnology: Risks, benefits and trust. Journal of Nanoparticle Research, 6, 395-405.
  • Çelik, Z., & Aydın, İ. (2021). Perakendecilikte drone ile ürün teslimatının tüketicilerin davranışsal niyetlerine etkisi. Business & Management Studies: An International Journal, 9(4), 1422-1436.
  • Demirören Haber Ajansı. (2022). Yurtiçi Kargo, otonom drone ile kargo teslimatına başladı. https://www.dha.com.tr/kurumsal/yurtici-kargo-otonom-drone-ile-kargo-teslimatina-basladi-2182343 Erişim Tarihi: 13.01.2023
  • Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of consumer research, 21(1), 119-134.
  • Dowling, G. R. (1986). Perceived risk: the concept and its measurement. Psychology & Marketing. 3(3), 193-210.
  • Dülek, B., & Aydın, İ. (2020). Effect of social media marketing on e-wom, brand loyalty, and purchase intent. Bingöl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (20), 271-288.
  • Dülek, B., & Çelik, Z. (2022). Factors affecting positive word-of-mouth communication intention for drone-based delivery service in retailing. Akademik Yaklaşımlar Dergisi, 13(1), 40-55.
  • Fill, C. ve Turnbull, S. (2016). Marketing Communications. Edinburgh: Pearson Education Limited.
  • Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006). eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty. Journal of Business research, 59(4), 449-456.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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, 1-12.
  • 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.
  • Jasim, N. I., Kasim, H., & Mahmoud, M. A. (2022). Towards the development of smart and sustainable transportation system for foodservice industry: modelling factors influencing customer’s intention to adopt drone food delivery (DFD) services. Sustainability, 14(5), 2852, 1-21.
  • 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.
  • Kaur, D., & Kaur, R. (2023). Does electronic word-of-mouth influence e-recruitment adoption? A mediation analysis using the PLS-SEM approach. Management Research Review, 46(2), 223-244.
  • Kawakami, T., Kishiya, K., & Parry, M.E. (2014) Personal word of mouth, virtual word of mouth and innovation use. Journal of Product Innovation Management, 30(1), 17–30.
  • 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.
  • 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.
  • 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, 1-11.
  • Kotler, P. ve Armstrong, G. (2012). Principles of Marketing. Pearson Education, Inc.
  • Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human factors, 46(1), 50-80.
  • Leon, S., Chen, C., & Ratcliffe, A. (2021). Consumers’ perceptions of last mile drone delivery. International Journal of Logistics Research and Applications, 1-20.
  • Lin, L. Y., & Lu, C. Y. (2010). The influence of corporate image, relationship marketing, and trust on purchase intention: the moderating effects of word‐of‐mouth. Tourism review. 65(3), 16-34.
  • Mainardes, E. W., Portelada, P. H. M., & Damasceno, F. S. (2023). The influence on cosmetics purchase intention of electronic word of mouth on Instagram. Journal of Promotion Management, 1-31.
  • 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.
  • Mayer, R.C., Davis, J.H., & Schoorman F.D. (1995). An integrative model of organizational trust.” Academy of Management Review, 20(3), 709–734.
  • McAuliffe, Z. (2023). Walmart Delivery Drones Now Operate in 7 States, https://www.cnet.com/tech/computing/walmart-delivery-drones-now-operate-in-seven-states/ Erişim: 13.01.2023
  • Merkert, R., Bliemer, M. C., & Fayyaz, M. (2022). Consumer preferences for innovative and traditional last-mile parcel delivery. International Journal of Physical Distribution & Logistics Management, 52(3), 261-284.
  • Mittendorf, C., Franzmann, D., & Ostermann, U. (2017). Why would customers engage in drone deliveries?. In AMCIS 2017 Proceedings, 1–10.
  • Nelson, J., & Gorichanaz, T. (2019). Trust as an ethical value in emerging technology governance: The case of drone regulation. Technology in Society, 59, 1-8.
  • Osakwe, C. N., Hudik, M., Říha, D., Stros, M., & Ramayah, T. (2022). Critical factors characterizing consumers’ intentions to use drones for last-mile delivery: Does delivery risk matter?. Journal of Retailing and Consumer Services, 65, 1-11.
  • Rahman, T., Noh, M., Kim, Y. S., & Lee, C. K. (2022). Effect of word of mouth on m-payment service adoption: A developing country case study. Information Development, 38(2), 268-285.
  • Ramadan, Z. B., Farah, M. F. ve Mrad, M. (2017). An adapted TPB approach to consumers’ acceptance of service-delivery drones. Technology. Analysis & Strategic Management, 29 (7), 817-828.
  • Sahal, R., Alsamhi, Saeed.H. ve Brown, K.N. (2022). Conceptual framework of contact-less consumer products industry during and postpandemic era. 5th The Global IoT Summit, GIoTS 2022, Dublin, Ireland, 20-23 June, in A. González-Vidal, A. Mohamed Abdelgawad, E. Sabir, S. Ziegler, and L. Ladid (Ed.). Internet of Things, Lecture Notes in Computer Science, vol 13533 Cham: Springer International Publishing, pp. 161–174.
  • Schellekens, G. A., Verlegh, P. W., & Smidts, A. (2010). Language abstraction in word of mouth. Journal of Consumer Research, 37(2), 207-223.
  • Seçer, İ. (2015). SPPS ve LISREL ile Pratik Veri Analizi. Ankara: Anı Yayıncılık.
  • Singh, G., Sharma, S., Tandon, A., & Kaur, P. (2022). Drone food delivery: A solution to crowding during the global COVID-19 pandemic. IEEE Transactions on Engineering Management,1-13.
  • Stevens, J. (1996). Applied Multivariate Statistics for the Social Sciences. Mahwah, NJ: Lawrence Erlbaum.
  • Tabachnick, B. G. ve Fidell, L. S. (2007). Using Multivariate Statistics. Boston: Pearson Education.
  • Tamke, F., & Buscher, U. (2023). The vehicle routing problem with drones and drone speed selection. Computers & Operations Research, 152, 1-20.
  • Valencia-Arias, A., Rodríguez-Correa, P. A., Patiño-Vanegas, J. C., Benjumea-Arias, M., De La Cruz-Vargas, J., & Moreno-López, G. (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.
  • Wedari, C. I. A., & Yasa, N. N. K. (2022). The role of brand image to mediate the effect of word of mouth on the intention of using wicitra wedding salon services in the City of Denpasar. European Journal of Business and Management Research, 7(2), 1-6.
  • Weng, Y. Y., Wu, R. Y., & Zheng, Y. J. (2023). Cooperative truck–drone delivery path optimization under urban traffic restriction. Drones, 7, 59, 1-20.
  • Yaşlıoğlu, M. M. (2017). Sosyal bilimlerde faktör analizi ve geçerlilik: keşfedici ve doğrulayıcı faktör analizlerinin kullanılması. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 74-85.
  • 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.
  • Zhang, T., Tao, D., Qu, X., Zhang, X., Lin, R., & Zhang, W. (2019). The roles of initial trust and perceived risk in public’s acceptance of automated vehicles. Transportation research part C: emerging technologies, 98, 207-220.
  • Zhu, X., Pasch, T. J., & Bergstrom, A. (2020). Understanding the structure of risk belief systems concerning drone delivery: A network analysis. Technology in Society, 62, 101262, 1-12.

Drone İle Teslimata Yönelik Algılanan Güvenin Kullanım Niyeti Üzerindeki Etkisinde Algılanan Risk Ve Ağızdan Ağıza İletişimin Aracılık Rollerinin Araştırılması

Yıl 2023, Cilt 10, Sayı 1, 49 - 67, 21.03.2023
https://doi.org/10.48064/equinox.1254198

Öz

Drone ile teslimat insanların pandemi sonrasında da temassız işlemleri tercih edeceği düşüncesine bağlı olarak şirketler açısından önemli fırsatlara neden olacaktır. Bu çalışmada, dronla teslimata dair algılanan güvenin kullanım niyeti üzerindeki etkisinde ağızdan ağıza iletişim ve algılanan riskin aracılık rolleri incelenmiştir. Çalışmada yer alan değişkenlerin temassız teslimat bağlamında şirketler için önemli öngörüler sunacağı beklenmektedir. Çalışmanın evrenini Türkiye’de yaşayan insanlar oluşturmuştur. Çalışmanın örneklemi 260 kişiden oluşmuştur. İnternette verilen bir anket ile ve kartopu örnekleme yöntemiyle veriler toplanmıştır. Katılımcılara anket formunu doldurmadan önce drone ile teslimatla ilgili bir video izletilmiştir. Yapısal eşitlik modellemesi kullanılarak istatistiki analizler yapılmıştır. Bulgulara göre algılanan güvenin, ağızdan ağıza iletişim ve kullanım niyeti üzerine olumlu fakat algılanan risk üzerine olumsuz etkisi olduğu görülmüştür. Algılanan riskin kullanım niyeti üzerinde herhangi bir etkisinin olmadığı sonucuna ulaşılmıştır. Ağızdan ağıza iletişimin ise kullanım niyeti üzerinde olumlu etkisinin olduğu görülmüştür. Algılanan güvenin ağızdan ağıza iletişim aracılığıyla kullanım niyeti üzerinde etkisinin olduğu ancak algılanan risk aracılığıyla herhangi bir etkisinin olmadığı sonuçlarına ulaşılmıştır. Elde edilen sonuçlar çerçevesinde drone ile teslimata yönelik tüketicilerde algılanan güvenin arttırılmasının oldukça önemli olduğu ifade edilebilir. Algılanan güvenin arttırılması için bu teslimat yönteminin risklerinin teknik olarak en aza indirilmesi ve bu teslimat yönteminin güvenilir olduğunun pazarlama iletişimi faaliyetleriyle insanlara anlatılmasının oldukça önemli olduğu düşünülmektedir.

Kaynakça

  • Aydın, İ. (2022). Hedonik motivasyonun drone ile teslimata yönelik tutum üzerindeki etkisi: ağızdan ağıza iletişimin aracılık rolü. İşletme Akademisi Dergisi, 3 (1), 34-45.
  • Benarbia, T., & Kyamakya, K. (2022). A literature review of drone-based package delivery logistics systems and their implementation feasibility. Sustainability, 14(1), 1-15.
  • Büyüköztürk, Ş. (2011). Sosyal Bilimler İçin Veri Analizi El Kitabı İstatistik, Araştırma Deseni SPSS Uygulamaları ve Yorum. Ankara: Pegem Akademi.
  • Campbell, M. C., & Goodstein, R. C. (2001). The moderating effect of perceived risk on consumers' evaluations of product incongruity: Preference for the norm. Journal of consumer Research, 28(3), 439-449.
  • 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.
  • Chen, C., Leon, S., & Ractham, P. (2022). Will customers adopt last-mile drone delivery services? An analysis of drone delivery in the emerging market economy. Cogent Business & Management, 9(1), 1-18.
  • Chiang, W. C., Li, Y., Shang, J., & Urban, T. L. (2019). Impact of drone delivery on sustainability and cost: Realizing the UAV potential through vehicle routing optimization. Applied energy, 242, 1164-1175.
  • 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.
  • 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.
  • Cobb, M. D., & Macoubrie, J. (2004). Public perceptions about nanotechnology: Risks, benefits and trust. Journal of Nanoparticle Research, 6, 395-405.
  • Çelik, Z., & Aydın, İ. (2021). Perakendecilikte drone ile ürün teslimatının tüketicilerin davranışsal niyetlerine etkisi. Business & Management Studies: An International Journal, 9(4), 1422-1436.
  • Demirören Haber Ajansı. (2022). Yurtiçi Kargo, otonom drone ile kargo teslimatına başladı. https://www.dha.com.tr/kurumsal/yurtici-kargo-otonom-drone-ile-kargo-teslimatina-basladi-2182343 Erişim Tarihi: 13.01.2023
  • Dowling, G. R., & Staelin, R. (1994). A model of perceived risk and intended risk-handling activity. Journal of consumer research, 21(1), 119-134.
  • Dowling, G. R. (1986). Perceived risk: the concept and its measurement. Psychology & Marketing. 3(3), 193-210.
  • Dülek, B., & Aydın, İ. (2020). Effect of social media marketing on e-wom, brand loyalty, and purchase intent. Bingöl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (20), 271-288.
  • Dülek, B., & Çelik, Z. (2022). Factors affecting positive word-of-mouth communication intention for drone-based delivery service in retailing. Akademik Yaklaşımlar Dergisi, 13(1), 40-55.
  • Fill, C. ve Turnbull, S. (2016). Marketing Communications. Edinburgh: Pearson Education Limited.
  • Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006). eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty. Journal of Business research, 59(4), 449-456.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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, 1-12.
  • 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.
  • Jasim, N. I., Kasim, H., & Mahmoud, M. A. (2022). Towards the development of smart and sustainable transportation system for foodservice industry: modelling factors influencing customer’s intention to adopt drone food delivery (DFD) services. Sustainability, 14(5), 2852, 1-21.
  • 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.
  • Kaur, D., & Kaur, R. (2023). Does electronic word-of-mouth influence e-recruitment adoption? A mediation analysis using the PLS-SEM approach. Management Research Review, 46(2), 223-244.
  • Kawakami, T., Kishiya, K., & Parry, M.E. (2014) Personal word of mouth, virtual word of mouth and innovation use. Journal of Product Innovation Management, 30(1), 17–30.
  • 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.
  • 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.
  • 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, 1-11.
  • Kotler, P. ve Armstrong, G. (2012). Principles of Marketing. Pearson Education, Inc.
  • Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human factors, 46(1), 50-80.
  • Leon, S., Chen, C., & Ratcliffe, A. (2021). Consumers’ perceptions of last mile drone delivery. International Journal of Logistics Research and Applications, 1-20.
  • Lin, L. Y., & Lu, C. Y. (2010). The influence of corporate image, relationship marketing, and trust on purchase intention: the moderating effects of word‐of‐mouth. Tourism review. 65(3), 16-34.
  • Mainardes, E. W., Portelada, P. H. M., & Damasceno, F. S. (2023). The influence on cosmetics purchase intention of electronic word of mouth on Instagram. Journal of Promotion Management, 1-31.
  • 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.
  • Mayer, R.C., Davis, J.H., & Schoorman F.D. (1995). An integrative model of organizational trust.” Academy of Management Review, 20(3), 709–734.
  • McAuliffe, Z. (2023). Walmart Delivery Drones Now Operate in 7 States, https://www.cnet.com/tech/computing/walmart-delivery-drones-now-operate-in-seven-states/ Erişim: 13.01.2023
  • Merkert, R., Bliemer, M. C., & Fayyaz, M. (2022). Consumer preferences for innovative and traditional last-mile parcel delivery. International Journal of Physical Distribution & Logistics Management, 52(3), 261-284.
  • Mittendorf, C., Franzmann, D., & Ostermann, U. (2017). Why would customers engage in drone deliveries?. In AMCIS 2017 Proceedings, 1–10.
  • Nelson, J., & Gorichanaz, T. (2019). Trust as an ethical value in emerging technology governance: The case of drone regulation. Technology in Society, 59, 1-8.
  • Osakwe, C. N., Hudik, M., Říha, D., Stros, M., & Ramayah, T. (2022). Critical factors characterizing consumers’ intentions to use drones for last-mile delivery: Does delivery risk matter?. Journal of Retailing and Consumer Services, 65, 1-11.
  • Rahman, T., Noh, M., Kim, Y. S., & Lee, C. K. (2022). Effect of word of mouth on m-payment service adoption: A developing country case study. Information Development, 38(2), 268-285.
  • Ramadan, Z. B., Farah, M. F. ve Mrad, M. (2017). An adapted TPB approach to consumers’ acceptance of service-delivery drones. Technology. Analysis & Strategic Management, 29 (7), 817-828.
  • Sahal, R., Alsamhi, Saeed.H. ve Brown, K.N. (2022). Conceptual framework of contact-less consumer products industry during and postpandemic era. 5th The Global IoT Summit, GIoTS 2022, Dublin, Ireland, 20-23 June, in A. González-Vidal, A. Mohamed Abdelgawad, E. Sabir, S. Ziegler, and L. Ladid (Ed.). Internet of Things, Lecture Notes in Computer Science, vol 13533 Cham: Springer International Publishing, pp. 161–174.
  • Schellekens, G. A., Verlegh, P. W., & Smidts, A. (2010). Language abstraction in word of mouth. Journal of Consumer Research, 37(2), 207-223.
  • Seçer, İ. (2015). SPPS ve LISREL ile Pratik Veri Analizi. Ankara: Anı Yayıncılık.
  • Singh, G., Sharma, S., Tandon, A., & Kaur, P. (2022). Drone food delivery: A solution to crowding during the global COVID-19 pandemic. IEEE Transactions on Engineering Management,1-13.
  • Stevens, J. (1996). Applied Multivariate Statistics for the Social Sciences. Mahwah, NJ: Lawrence Erlbaum.
  • Tabachnick, B. G. ve Fidell, L. S. (2007). Using Multivariate Statistics. Boston: Pearson Education.
  • Tamke, F., & Buscher, U. (2023). The vehicle routing problem with drones and drone speed selection. Computers & Operations Research, 152, 1-20.
  • Valencia-Arias, A., Rodríguez-Correa, P. A., Patiño-Vanegas, J. C., Benjumea-Arias, M., De La Cruz-Vargas, J., & Moreno-López, G. (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.
  • Wedari, C. I. A., & Yasa, N. N. K. (2022). The role of brand image to mediate the effect of word of mouth on the intention of using wicitra wedding salon services in the City of Denpasar. European Journal of Business and Management Research, 7(2), 1-6.
  • Weng, Y. Y., Wu, R. Y., & Zheng, Y. J. (2023). Cooperative truck–drone delivery path optimization under urban traffic restriction. Drones, 7, 59, 1-20.
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Ayrıntılar

Birincil Dil Türkçe
Konular İşletme
Bölüm Research Article
Yazarlar

İbrahim AYDIN> (Sorumlu Yazar)
VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ
0000-0002-0720-364X
Türkiye


Zübeyir ÇELİK>
VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ
0000-0003-1692-9378
Türkiye

Yayımlanma Tarihi 21 Mart 2023
Yayınlandığı Sayı Yıl 2023, Cilt 10, Sayı 1

Kaynak Göster

APA Aydın, İ. & Çelik, Z. (2023). Drone İle Teslimata Yönelik Algılanan Güvenin Kullanım Niyeti Üzerindeki Etkisinde Algılanan Risk Ve Ağızdan Ağıza İletişimin Aracılık Rollerinin Araştırılması . Equinox Journal of Economics Business and Political Studies , 10 (1) , 49-67 . DOI: 10.48064/equinox.1254198
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Equinox Journal of Economics Business and Political Studies