Analysis of the Impact of Stakeholders on Companies with Home Delivery Platforms Using Hybrid Optimization and Simulation Approaches

Análisis del impacto de los Stakeholders en empresas con plataformas de entrega a domicilio mediante enfoques híbridos de optimización y simulación.

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Daniel Giraldo-Herrera
David Álvarez Martínez

Resumen

Logistics companies have developed virtual platforms where users get food and medicine via the different businesses associated with these applications. The efficient delivery of these products through these platforms is defined as the Meal Delivery Routing Problem (MDRP). These platforms are the subject of legal and regulatory research due to their collaborative economy model. These platforms function only as service promoters, whereby there should be no labor relations involving businesses or domiciliary workers. These characteristics dilute and alter the employment relationships between worker and employer, decreasing a worker’s labor rights, well-being or health, and compensation. This research proposes a simulation model with interchangeable policies and uses behavioral data on domiciliary workers to analyze their multidimensional impact on stakeholders (ordering platforms, businesses, users, and domiciliary workers). The proposed methodology has been applied in a real company, demonstrating its efficiency, improving domiciliary workers’ conditions, and decreasing potential losses.


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Referencias (VER)

Arriagada, A., Bonhomme, M., Ibáñez, F. & Leyton, J. (2023). The gig economy in Chile: Examining labor conditions and the nature of gig work in a Global South country. Digital Geography and Society, 5, 100063. https://doi.org/10.1016/j.diggeo.2023.100063

Bensusán, G. & Santos, H. (2021). Digital platform work in Latin America: Challenges and perspectives for its regulation. In U. Huws, R. Forde, D. Spencer & K. Stuart (Eds.), Work and Labour Relations in Global Platform Capitalism (pp. 236-260). Edward Elgar Publishing. https://doi.org/10.4337/9781802205138.00020

Berg, J., Furrer, M., Harmon, E., Rani, U. & Silberman, M. S. (2018). Digital labour platforms and the future of work: Towards decent work in the online world. ILO.

Boysen, N., Emde, S. & Schwerdfeger, S. (2022). Crowdshipping by employees of distribution centers: Optimization approaches for matching supply and demand. European Journal of Operational Research, 296(2), 539-556. https://doi.org/10.1016/j.ejor.2021.04.002

De Stefano, V. (2016). The rise of the “just-in-time workforce”: On-demand work, crowdwork, and labour protection in the “gig-economy”. ILO.

Freeman, R. E., Harrison, J. S., Wicks, A. C., Parmar, B. L. & de Colle, S. (2010). Stakeholder Theory: The State of the Art. Cambridge University Press. https://doi.org/10.1017/CBO9780511815768

Galière, S. (2020). When food‐delivery platform workers consent to algorithmic management: A Foucauldian perspective. New Technology, Work and Employment, 35(3), 357-370. https://doi.org/10.1111/ntwe.12177

González, D. F. (2021). Solucionando el problema de enrutamiento de pedidos de comida, teniendo en cuenta el bienestar de los domiciliarios. [Tesis de Maestría, Universidad de los Andes]. https://hdl.handle.net/1992/52944

Huang, H. (2022). Algorithmic management in food‐delivery platform economy in China. New Technology, Work and Employment, 38(2), 185-205. https://doi.org/10.1111/ntwe.12228

Jarrahi, M. H., Sutherland, W., Nelson, S. B. & Sawyer, S. (2020). Platformic management, boundary resources for gig work, and worker autonomy. Computer Supported Cooperative Work (CSCW), 29, 153-189. https://doi.org/10.1007/s10606-019-09368-7

Kadolkar, I., Kepes, S. & Subramony, M. (2024). Algorithmic management in the gig economy: A systematic review and research integration. Journal of Organizational Behavior, 46(7), 1057-1080. https://doi.org/10.1002/job.2831

Kenney, M. & Zysman, J. (2016). The rise of the platform economy. Issues in Science and Technology, 32(3). https://issues.org/rise-platform-economy-big-data-work/

Liu, R. & Yin, H. (2024). How Algorithmic Management Influences Gig Workers' Job Crafting. Behavioral Sciences (Basel, Switzerland), 14(10), 952. https://doi.org/10.3390/bs14100952

Martínez-Sykora, A., McLeod, F., Cherrett, T. & Friday, A. (2024). Exploring fairness in food delivery routing and scheduling problems. Expert Systems with Applications, 240, 122488. https://doi.org/10.1016/j.eswa.2023.122488

Muldoon, J. & Raekstad, P. (2022). Algorithmic domination in the gig economy. European Journal of Political Theory, 22(4), 587-607. https://doi.org/10.1177/14748851221082078

Öborn, D. R., MacKenzie, R., Örnebring, H. & Van Couvering, E. (2024). Bypassing the Limitations of Algorithmic Management via Out‐of‐App Activities and the Emergence of Opportunistic Agency in the Swedish Gig economy. New Technology, Work and Employment, 40(3), 368-379. https://doi.org/10.1111/ntwe.12323

Parker, G. G., Van Alstyne, M. W. & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy and how to make them work for you. WW Norton & Company.

Pilatti, G. R., Pinheiro, F. L. & Montini, A. A. (2024). Systematic Literature Review on Gig Economy: Power Dynamics, Worker Autonomy, and the Role of Social Networks. Administrative Sciences, 14(10), 267. https://doi.org/10.3390/admsci14100267

Quintero Rojas, S. (2020). Computational framework for solving the meal delivery routing problem. [Tesis de Maestría, Universidad de los Andes]. https://hdl.handle.net/1992/50995

Reyes, D., Erera, A., Savelsbergh, M., Sahasrabudhe, S. & O’Neil, R. (2018). The meal delivery routing problem. Optimization Online. https://optimization-online.org/?p=15139

Ulmer, M. W. & Savelsbergh, M. (2020). Workforce scheduling in the era of crowdsourced delivery. Transportation Science, 54(4), 1113-1133. https://doi.org/10.1287/trsc.2020.0977

Ulmer, M. W., Thomas, B. W., Campbell, A. M. & Woyak, N. (2020). The restaurant meal delivery problem: Dynamic pickup and delivery with deadlines and random ready times. Transportation Science, 55(1), 75-100. https://doi.org/10.1287/trsc.2020.1000

Valencia Jiménez, G. D. Universidad de los Andes. (2021). El trabajo líquido: la subordinación laboral en las plataformas digitales: el caso de Rappi. [Tesis de Maestría, Universidad de los Andes]. https://hdl.handle.net/1992/53466

Vallas, S. & Schor, J. B. (2020). What do platforms do? Understanding the gig economy. Annual Review of Sociology, 46, 273-294. https://doi.org/10.1146/annurev-soc-121919-054857

Van Doorn, N. (2024). The contingencies of platform power and risk management in the gig economy. Internet Policy Review, 13(2). https://doi.org/10.14763/2024.2.1778

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