Adoption of crowdsourced delivery: An online focus group interview

Öz

This research aims to investigate university students' perceptions of crowdsourced delivery and identify factors that influence crowdsourced delivery platform acceptance as a consumer and as a driver. Research design is a qualitative exploratory case study that was performed on university students' perceptions of crowdsourced delivery in Turkey. Online focus group discussions were used to collect data with 35 university students. Data included six online focus groups and were analyzed using thematic analysis. To increase credibility and trustworthiness, the researcher triangulation was applied. The findings show that as a consumer; performance expectancy, price sensitivity, social influence, and perceived risk and as a driver; compensation, working environment, and perceived risk affect acceptance of crowdsourced delivery. The findings are helpful for crowdsourced delivery platforms to increase the acceptance rate in the beginning stage of crowdsourced delivery and provide suggestive knowledge for other emerging countries. This paper highlights what factors influence students' acceptance of crowdsourced delivery in the introduction phase from the perspective of a group of university students in an emerging country.

Anahtar Kelimeler

• Crowdsourced delivery
• emerging market
• technology acceptance
• last mile delivery solutions
• B2C delivery

Kitle Kaynaklı Teslimatın Benimsenmesi: Bir Çevrimiçi Odak Grup Görüşmesi

Öz

Bu araştırma, üniversite öğrencilerinin kitle kaynaklı teslimat algılarını araştırmayı ve bir tüketici ve bir sürücü olarak kitle kaynaklı teslimat platformunun kabulünü etkileyen faktörleri belirlemeyi amaçlamaktadır. Araştırma tasarımı, Türkiye’de üniversite öğrencilerinin kitle kaynaklı teslimata ilişkin algıları üzerine gerçekleştirilen nitel bir keşifsel durum çalışmasıdır. Veri toplamak için 35 üniversite öğrencisinin dahil olduğu odak grup görüşmeleri gerçekleştirilmiştir. Veriler altı çevrimiçi odak grup görüşmesini içermiş ve tematik analiz yöntemi kullanılarak analizleri gerçekleştirilmiştir. Verilerin inandırıcılık ve güvenirliğini arttırmak için araştırmacı çeşitlemesi kullanılmıştır. Bulgulara göre, tüketici olarak; performans beklentisi, fiyat duyarlılığı, sosyal etki ve algılanan risk ve bir sürücü olarak; gelir, çalışma ortamı ve algılanan risk, kitle kaynaklı teslimatın kabulünü etkilemektedir. Bulgular, kitle kaynaklı teslimat platformlarının, kitle kaynaklı teslimatın başlangıç aşamasında kabul oranını artırması ve diğer gelişmekte olan ülkeler için anlamlı bilgiler sağlaması açısından yararlıdır. Bu makale, gelişmekte olan bir ülkedeki bir grup üniversite öğrencisinin bakış açısıyla, giriş aşamasında öğrencilerin kitle kaynaklı teslimatı kabul etmesini etkileyen faktörlerin önemini ortaya koymaktadır.

Anahtar Kelimeler

• Kitle kaynaklı teslimat
• gelişmekte olan ülke
• teknoloji kabulü
• son adım teslimat çözümleri
• B2C teslimat
• Kitle kaynaklı teslimat, gelişmekte olan ülke, teknoloji kabulü, son adım teslimat çözümleri, B2C teslimat

Kaynakça

1. Aitken, R., Watkins, L., & Kemp, S. (2019), "Envisioning a sustainable consumption future," Young Consumers, Vol. 20 No. 4, pp. 299-313. https://doi.org/10.1108/YC-12-2018-0905
2. Allen J., Browne M., & Holguín-veras J. (2015) Sustainability strategies for city logistics. In: Mckinnon a, Browne M, Whiteing a, Piecyk M (eds) green logistics (3rd edition). Kogan page, pp. 293-319
3. Archetti, C., Savelsbergh, M., & Speranza, M.G., (2015). "The vehicle routing problem with occasional drivers", European Journal of Operational Research, 254, pp. 472–480. http://dx.doi.org/10.1016/j. ejor.2016.03.049.
4. Berg, N., & Knights, M. (2021), Amazon: How the world's most relentless retailer will continue to revolutionize commerce, Kogan Page Publishers, London, England.
5. Buldeo Rai, H., Verlinde, S., & Macharis, C. (2018). Shipping outside the box. Environmental impact and stakeholder analysis of a crowd logistics platform in Belgium. Journal of Cleaner Production, 202, pp. 806-816. https://doi.org/10.1016/j.jclepro.2018.08.210
6. Buldeo Rai, H., Verlinde, S., & Macharis, C. (2021a). Who is interested in a crowdsourced last mile? A segmentation of attitudinal profiles. Travel Behaviour and Society, 22, pp. 22-31 https://doi.org/10.1016/j.tbs.2020.08.004
7. Buldeo Rai, H., Verlinde, S., & Macharis, C. (2021b). Unlocking the failed delivery problem? Opportunities and challenges for smart locks from a consumer perspective. Research in Transportation Economics, 87, 100753. https://doi.org/10.1016/j.retrec.2019.100753
8. Carbone, V., Rouquet A., & Roussat C. (2017), "The rise of crowd-logistics: a new way to co-create logistics value?", Journal of Business Logistics, 38(4), pp. 238-252 https://doi.org/10.1111/jbl.12164

9. Chawla, D., & Sondhi, N. (2016), Research methodology: Concepts and cases (2nd ed.), Vikas Publishing House, New Delhi, India.
10. Chen, P., & Chankov, S. M. (2017), "Crowdsourced delivery for last-mile distribution: An agent-based modelling and simulation approach", paper presented at the IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 10-13 December, 2017, Singapore, pp. 1271-1275. DOI: 10.1109/IEEM.2017.8290097
11. Chen, Y., Yu, J., Yang, S. & Wei, J. (2018), "Consumer's intention to use self-service parcel delivery service in online retailing: An empirical study", Internet Research, Vol. 28 No. 2, pp. 500-519. https://doi.org/10.1108/IntR-11-2016-0334
12. Cramer-Flood, E., (2020), "Global e-commerce 2020", available at https://www.emarketer.com/content/global-ecommerce-2020 (Accessed 2 November 2020)
13. Devari, A., Nikolaev, A. G., & He, Q. (2017), "Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers", Transportation Research Part E: Logistics and Transportation Review, 105, pp. 105-122. https://doi.org/10.1016/j.tre.2017.06.011.
14. Ghajargar, M., Zenezini, G., & Montanaro, T. (2016), "Home delivery services: innovations and emerging needs", IFAC-PapersOnLine, 49(12), pp. 1371-1376. https://doi.org/10.1016/j.ifacol.2016.07.755
15. Goetting, E., & Handover, W. N. (2016), Crowd-shipping: Is crowd-sourced the secret recipe for delivery in the future?, German Industry and Commerce LTD/GCC, available at http://docplayer.net/38621729-Crowd-shipping-is-crowd-sourced-the-secret-recipe-for-delivery-in-the-future.html (Accessed 7 January, 2022)
16. Gundumogula, M. (2020), "Importance of Focus Groups in Qualitative Research", International Journal of Humanities and Social Science (IJHSS), 8(11), pp. 299-302. 10.24940/theijhss/2020/v8/i11/HS2011-082
17. Hancock, M. E. (2017), "The use of WordPress in online focus group studies", The Qualitative Report, 22(8), pp. 2273-2280, available at http://nsuworks.nova.edu/tqr/vol22/iss8/12 (Accessed 17 August, 2021)
18. Hayashi, K., Nemoto, T., & Visser, J.J., (2014), E-commerce and city logistics solution, Taniguchi and Thompson (Ed.s.) City Logistics: Mapping the Future vol. CRC Press, Boca Raton, FL, pp. 55-78.
19. Huang, L., Xie, G., Blenkinsopp, J., Huang, R., & Bin, H. (2020), "Crowdsourcing for sustainable urban logistics: Exploring the factors influencing crowd Workers' participative behavior", Sustainability, 12(8), 3091, https://doi.org/10.3390/su12083091
20. 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, pp. 210–225, https://doi:10.1016/j.trc.2019.12.016
21. Krueger, R. A., & Casey, M. A. (2002). 'Designing and conducting focus group interviews', Social Development Papers, No:36 pp. 4-23, , available at https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.607.4701&rep=rep1&type=pdf#page=10
22. Le, T. V., & Ukkusuri, S. V. (2018), "Crowd-shipping services for last mile delivery: Analysis from survey data in two countries. 97th Annual Meeting Transportation Research Board (No. 18-03779). January 7-11, 2018 in Washington, D.C. https://doi.org/10.1016/j.trip.2019.100008
23. Le, T. V., & Ukkusuri, S. V. (2019a). Modeling the willingness to work as crowd-shippers and travel time tolerance in emerging logistics services. Travel Behaviour and Society, 15, pp. 123–132. https://doi:10.1016/j.tbs.2019.02.001
24. Le, T. V., & Ukkusuri, S. V. (2019b), "Crowd-shipping services for last mile delivery: Analysis from American survey data", Transportation Research Interdisciplinary Perspectives, 1, 100008, https://doi.org/10.1016/j.trip.2019.100008.
25. Le, T. V., Stathopoulos, A., Van Woensel, T., & Ukkusuri, S. V. (2019), "Supply, demand, operations, and management of crowd-shipping services: A review and empirical evidence", Transportation Research Part C: Emerging Technologies, 103, pp. 83-103, https://doi.org/10.1016/j.trc.2019.03.023
26. McKinnon, A. (2016). Crowdshipping: A communal approach to reducing urban traffic levels, 41 Logistics White Paper 1/2016. Alan McKinnon, 42.
27. Miller, J., Nie, Y., & Stathopoulos, A., 2017. Crowdsourced Urban Package Delivery: Modeling Traveler Willingness to Work as Crowdshippers. Trans. Res. Rec. 2610. http://dx.doi.org/10.3141/2610-08.
28. Moroz, M., & Polkowski, Z., (2016), "The last mile issue and urban logistics: choosing parcel machines in the context of the ecological attitudes of the Y generation consumers purchasing online", Transp. Res. Procedia 16, pp. 378–393. https://doi.org/10.1016/j.trpro.2016.11.036
29. Morrison, D., Lichtenwald, K., & Tang, R. (2020), "Extending the online focus group method using web-based conferencing to explore older adults online learning", International Journal of Research & Method in Education, 43(1), pp. 78-92. https://doi.org/10.1080/1743727X.2019.1594183
30. Paloheimo, H., Lettenmeier, M., & Waris, H. (2016), "Transport reduction by crowdsourced deliveries–a library case in Finland", Journal of Cleaner Production, 132, pp. 240-251. https://doi.org/10.1016/j.jclepro.2015.04.103
31. Prince, M., & Davies, M. (2001), "Moderator teams: an extension to focus group methodology", Qualitative Market Research: An International Journal, 4 (4), pp. 207-216. https://doi.org/10.1108/EUM0000000005902
32. Punel, A., & Stathopoulos, A. (2017), "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects", Transportation Research Part E: Logistics and Transportation Review, 105, pp. 18-38, https://doi.org/10.1016/j.tre.2017.06.007
33. Punel, A., Ermagun, A., & Stathopoulos, A. (2018), "Studying determinants of crowd-shipping use", Travel Behaviour and Society, 12, pp. 30-40, https://doi.org/10.1016/j.tbs.2018.03.005
34. Rougès, J. F., & Montreuil, B. (2014). Crowdsourcing delivery: New interconnected business models to reinvent delivery. In 1st international physical internet conference (Vol. 1, pp. 1-19). https://doi.org/10.1016/j.jclepro.2018.08.210
35. Wicaksono, S., Lin, X., & Tavasszy, L. A. (2021). Market potential of bicycle crowdshipping: A two-sided acceptance analysis. Research in Transportation Business & Management, 100660. https://doi:10.1016/j.rtbm.2021.100660
36. Willis, K., Green, J., Daly, J., Williamson, L., & Bandyopadhyay, M., (2009). "Perils and possibilities: achieving best evidence from focus groups in public health research". Aust. N. Z. J. Public Health 33 (2), pp. 131-136. http://dx.doi.org/10.1111/ j.1753-6405.2009.00358.x.
37. YÖK (2021), "Turkish higher education statistics", available at https://istatistik.yok.gov.tr// (Accessed, 17 September 2021).