Exploring Challenges of Food Delivery Riders in The Gig Economy – A Conceptual Model
Keywords:
online food delivery, food delivery rider, gig economy, challenges, conceptual modelAbstract
The widespread use of smartphone apps and online ordering has contributed to a significant increase in the meal delivery sector in recent years. These riders have flexible job alternatives because of the gig economy; nevertheless, there are drawbacks as well. Food delivery riders play a crucial role in ensuring the smooth and efficient delivery of food to customers. However, not all food delivery procedures go smoothly because there are a number of obstacles and problems that food delivery riders have to deal with before the food is delivered to the clients. Thus, the purpose of this research is to identify the factors that lead to the issues and challenges that urban area of food delivery drivers encounter. A conceptual model has been laid out based on the findings of the interview conducted with 10 food delivery riders in order to accomplish this research based on data saturated. According to the research, there are four main factors that lead to issues and challenges for food delivery riders: time constraints, fraudulent consumers, dangerous behaviour, and system problems. Future research can be shaped by the suggested conceptual framework.
References
Abbas, H., Fatima, P., Akaak, A. A. M. A. A., Frederico, G. F., & Kumar, V. (2023). Modelling the operational maturity challenges faced by online food ordering and delivery enterprises during Covid-19 lockdown in Oman: a fuzzy interpretive structural modelling approach. Journal of Global Operations and Strategic Sourcing. https://doi.org/10.1108/JGOSS-12-2021-0106
Carmi, G., & Segal, S. Y. (2014). Mobile Security! a Review of New Advanced Technologies to Detect and Prevent E-Payment Mobile Frauds. Int. J. Comput. Syst, 292(4), 2394-1065.
Chai, L. T., & Yat, D. N. C. (2019). Online food delivery services: Making food delivery the new normal. Journal of Marketing advances and Practices, 1(1), 62-77.
Chiu, Y. H., Lin, Y. K., & Nguyen, T. P. (2021). Network reliability of a stochastic online-food delivery system with space and time constraints. International Journal of Performability Engineering, 17(5), 433.
Christie, N., & Ward, H. (2018). The emerging issues for management of occupational road risk in a changing economy: a survey of gig economy drivers, riders and their managers. London: UCL Centre for Transport Studies.
Curry, D. (2023, May 24). Food Delivery App Revenue and Usage Statistics (2023).
Damaini, A. A., Nugroho, G. S., & Suyoto. (2018). Fraud crime mitigation of mobile application users for online transportation. International Journal of Interactive Mobile Technologies, 12(3), 153–167. https://doi.org/10.3991/ijim.v12i3.8070
Dong, H., Zhong, S., Xu, S., Tian, J., & Feng, Z. (2021). The relationships between traffic enforcement, personal norms and aggressive driving behaviors among normal e-bike riders and food delivery e-bike riders. Transport Policy, 114, 138–146. https://doi.org/10.1016/j.tranpol.2021.09.014
Gera, M., Nawander, N., Tharwani, N., & Bhatia, P. (2018). Operations research in food delivery. International Journal for Advance Research and Development, 3(10), 73-78.
Guo, B., Wang, S., Ding, Y., Wang, G., He, S., Zhang, D., & He, T. (2021, December). Concurrent order dispatch for instant delivery with time-constrained actor-critic reinforcement learning. In 2021 IEEE Real-Time Systems Symposium (RTSS) (pp. 176-187). IEEE.
Hang Tuah, T. A., Azreena Kamaluddin, N., & Ishak, S. Z. (2022). Challenges of food delivery riders (p-Hailing): An exploratory study to better understand the nature of work and traffic accidents involvement. IEEE Symposium on Wireless Technology and Applications, ISWTA, 2022-August, 29–34. https://doi.org/10.1109/ISWTA55313.2022.9942750
Helling, B. (2023, October 9). Why the DoorDash App Crashes and How You Can Fix It.
Jackson, E. (2021, November 18). History Of Food Delivery And How It’s Changed.
Malik, M., Rusli, R., Nusa, F. N. M., & Adinegoro, Y. (2023). Risky Behaviours Among Delivery Riders At Signalized Intersections In Malaysia. PLANNING MALAYSIA, 21.
Nguyen-Phuoc, D.Q, Ngoc Thi Nguyen, L., Ngoc Su, D., Nguyen, M. H., & Oviedo-Trespalacios, O. (2023). Deadly meals: The influence of personal and job factors on burnout and risky riding behaviours of food delivery motorcyclists. Safety Science, 159. https://doi.org/10.1016/j.ssci.2022.106007
Orhan, M. A., & Collisson, B. (2022). Who said there’s no such thing as a free lunch? Customers’ dark triad traits predict abuse of food refund policies. Personality and Individual Differences, 190. https://doi.org/10.1016/j.paid.2022.111527
Papakostopoulos, V., & Nathanael, D. (2020). The Complex Interrelationship of Work-Related Factors Underlying Risky Driving Behavior of Food Delivery Riders in Athens, Greece. Safety and Health at Work.
Patel, R. (2022, November 18). 6 Problems Delivery Drivers Face in Their Day-To-Day Life: Challenges & Solutions.
Puram, P., Gurumurthy, A., Narmetta, M., & Mor, R. S. (2022). Last-mile challenges in on-demand food delivery during COVID-19: understanding the riders’ perspective using a grounded theory approach. International Journal of Logistics Management, 33(3). https://doi.org/10.1108/IJLM-01-2021-0024
Rodriguez, K. E., Buncaras, Z., Trucilla, L., Rodriguez, K., Ayapana, M., Interia, J., Gumapas, A., & Martin, J. (2022). Food at Speed of a Click: The Experiences and Challenges Faced by Food Delivery Riders Amidst the COVID-19 Pandemic. International Journal of Psychology and Counseling, 12(1).
Rusli, R., Mohammad, M. Z., Azreena Kamaluddin, N., Bakar, H., & Hafzi Md Isa, M. (2022). A comparison of characteristics between food delivery riders with and without traffic crash experience during delivery in Malaysia. Case Studies on Transport Policy, 10(4), 2244–2250. https://doi.org/10.1016/j.cstp.2022.10.006
SA, B., & MM, Z. (2018). Motorcycle Riders’ Risky Behaviors And Safety Measures: A Hospital-Based Study. Egyptian Journal of Occupational Medicine, 42(3), 453–468. https://doi.org/10.21608/ejom.2018.12210
Zheng, J., Wang, L., Wang, S., Chen, J. fang, Wang, X., Duan, H., Liang, Y., & Ding, X. (2022). Modeling stochastic service time for complex on-demand food delivery. Complex and Intelligent Systems, 8(6). https://doi.org/10.1007/s40747-022-00719-4
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