Production
https://prod.org.br/article/doi/10.1590/0103-6513.20230092
Production
Research Article

Simulating continuance and resilience: an agent-based model for nanostores operations

Agatha Clarice da Silva-Ovando; Gonzalo Mejía; Christopher Mejía-Argueta; Daniela Granados Rivera; Dayana Nicol Yugar Quiroz; Mario Chong

http://dx.doi.org/10.1590/0103-6513.20230092 Production, vol.34, e20230092, 2024
PDF
Downloads: 0
Views: 210

Abstract

Paper aims: This study investigates the nanostores' endurance in serving underserved regions in developing countries. The research explores how various competing retail formats influence market choice and demand. We used data from a survey conducted in Sabana Centro, Colombia, in this study.

Originality: We believe this is the first study examining the nanostores' resilience in serving emerging markets under this novel hybrid technique.

Research method: We propose a multi-agent-based model mimicking nanostore survival and resilience in a competitive market. Household agents use a discrete choice model to select their preferred retail format for household purchases based on location, price, and service levels. Considering supply breakdowns, we tested the outcoming model under different disruption scenarios.

Main findings: Results indicated nanostores' great resiliency in competitive markets, specifically in peripheral areas, which are usually neglected by other retail formats. This suggests that this retail format can strategically complement household supply in underserved areas, displaying the importance of supporting these channels and generating tools that improve their performance in the market.

Implications for theory and practice: Theoretically, we aim to improve the understanding of households' decision-making process when buying food. Practically, a multi-agent-based model simulating end customers and sellers offers insights into future interventions and their impacts on the retail landscape and various supply chain stakeholders.

Keywords

Supply chain management, Facility location, Nested logit model, Multi-agent simulation, Urban logistics

References

Awasthi, A., Chauhan, S. S., & Goyal, S. K. (2011). A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty. Mathematical and Computer Modelling, 53(1-2), 98-109. http://doi.org/10.1016/j.mcm.2010.07.023.

Bartik, A. W., Bertrand, M., Cullen, Z. B., Glaeser, E. L., Luca, M., & Stanton, C. T. (2020). How are small business adjusting to COVID-19? Early evidence from a survey. Cambridge: National Bureau of Economic Research. http://doi.org/10.3386/w26989.

Bierlaire, M. (2023). A short introduction to Biogeme (Technical Report, No. TRANSP-OR 230620). Lausanne: EPFL.

Boulaksil, Y., & Belkora, M. J. (2017). Distribution strategies toward nanostores in emerging markets: the Valencia case. Interfaces, 47(6), 505-517. http://doi.org/10.1287/inte.2017.0914.

Boulaksil, Y., Fransoo, J. C., Blanco, E. E., & Koubida, S. (2019). Understanding the fragmented demand for transportation: small traditional retailers in emerging markets. Transportation Research Part A, Policy and Practice, 130, 65-81. http://doi.org/10.1016/j.tra.2019.09.003.

Brown, J. R., & Guiffrida, A. L. (2017). Stochastic modeling of the last mile problem for delivery fleet planning last mile algorithm comparison view project stochastic modeling of the last mile problem view project. Journal of the Transportation Research Forum, 56(2), 93-108.

Brown, J. R., Bushuev, M. A., & Guiffrida, A. L. (2021). “Distance metrics matter: analysing optimisation algorithms for the last mile problem. Inderscience Publishers, 38(2), 151-174. http://doi.org/10.1504/IJLSM.2021.113233.

Cajamarca, I. (2022, Junio 11). ‘Tiendas para la Gente’ fortalecerá a 5.700 tiendas de barrio afectadas por el COVID-19. La República.

Calisti, R., Proietti, P., & Marchini, A. (2019). Promoting sustainable food consumption: an agent-based model about outcomes of small shop openings. Journal of Artificial Societies and Social Simulation, 22(1), 2. http://doi.org/10.18564/jasss.3901.

Colombia, Departamento Administrativo Nacional de Estadística – DANE. (2022). Geoportal DANE. Bogotá D.C. Retrieved in 2023, July 5, from https://geoportal.dane.gov.co/servicios/descarga-y-metadatos/datos-geoestadisticos/?cod=111

Constanza Gómez, G. (2005, Noviembre 25). Los fruver, un modelo de los comerciantes que crece para atender a clientes exigentes. El Tiempo.

Cummins, S., Smith, D. M., Aitken, Z., Dawson, J., Marshall, D., Sparks, L., & Anderson, A. S. (2010). Neighbourhood deprivation and the price and availability of fruit and vegetables in Scotland. Journal of Human Nutrition and Dietetics, 23(5), 494-501. http://doi.org/10.1111/j.1365-277X.2010.01071.x. PMid:20831708.

Escamilla, R., Fransoo, J. C., & Tang, C. S. (2021). improving agility, adaptability, alignment, accessibility, and affordability in nanostore supply chains. Production and Operations Management, 30(3), 676-688. http://doi.org/10.1111/poms.13309.

Fenalco. (2022). La tienda de barrio sigue siendo la joya de la corona para los productos de consumo masivo. Retrieved in 2024, May 28, from https://www.fenalco.com.co/blog/gremial-4/la-tienda-de-barrio-sigue-siendo-la-joya-de-la-corona-para-los-productos-de-consumo-masivo-456

Food and Agriculture Organization – FAO, International Fund for Agricultural Development – IFAD, United Nations Children’s Fund – UNICEF, World Food Programme – WFP, World Health Organization – WHO. (2022). The state of food security and nutrition in the world 2022 - repurposing food and agricultural policies to make healthy diets more affordable. Rome: FAO.

Fransoo, J. C. (2021). Nanostore supply chains leverage the Triple A: agility, adaptability and alignment. LinkedIn. Retrieved in 2023, August 1, from https://www.linkedin.com/pulse/nanostore-supply-chains-leverage-triple-agility-jan-fransoo/

Fransoo, J. C., Blanco, E., & Mejía-Argueta, C. (2017). Reaching 50 million nanostores: retail distribution in emerging megacities. Scotts Valley: CreateSpace.

Freitas, E., & Domingues, N. (2013). The economy of distribution centers: the case of large retail networks in Brazil. African Journal of Business Management, 7(16), 1541-1552. http://doi.org/10.5897/AJBM2013.1579.

Ge, J., Honhon, D., Fransoo, J. C., & Zhao, L. (2021). Supplying to mom and pop: traditional retail channel selection in megacities. Manufacturing & Service Operations Management, 23(1), 19-35. http://doi.org/10.1287/msom.2019.0806.

Ghosh-Dastidar, B., Cohen, D., Hunter, G., Zenk, S. N., Huang, C., Beckman, R., & Dubowitz, T. (2014). Distance to store, food prices, and obesity in urban food deserts. American Journal of Preventive Medicine, 47(5), 587-595. http://doi.org/10.1016/j.amepre.2014.07.005. PMid:25217097.

Gutiérrez-Rubiano, D. F., Hincapié-Montes, J. A., & León-Villalba, A. F. (2019). Collaborative distribution: strategies to generate efficiencies in urban distribution: results of two pilot tests in the city of Bogotá. Dyna, 86(210), 42-51. http://doi.org/10.15446/dyna.v86n210.78931.

Kin, B. (2020). Less fragmentation and more sustainability: how to supply nanostores in urban areas more efficiently? Transportation Research Procedia, 46, 117-124. http://doi.org/10.1016/j.trpro.2020.03.171.

Kin, B., Ambra, T., Verlinde, S., & Macharis, C. (2018). Tackling fragmented last mile deliveries to nanostores by utilizing spare transportation capacity: a simulation study. Sustainability, 10(3), 653. http://doi.org/10.3390/su10030653.

Larrea-Gallegos, G., Benetto, E., Marvuglia, A., & Navarrete Gutiérrez, T. (2022). Sustainability, resilience and complexity in supply networks: a literature review and a proposal for an integrated agent-based approach. Sustainable Production and Consumption, 30, 946-961. http://doi.org/10.1016/j.spc.2022.01.009.

Levi, R., Paulson, E., & Perakis, G. (2020). Fresh fruit and vegetable consumption: the impact of access and value (MIT Sloan Research Paper, No. 5389-18). Rochester: SSRN. http://doi.org/10.2139/ssrn.3691925.

Macal, C. M., & North, M. J. (2007). Agent-based modeling and simulation: desktop ABMS. In Proceedings - Winter Simulation Conference (pp. 95-106). New York: IEEE. http://doi.org/10.1109/WSC.2007.4419592.

Mejía, G., & García-Díaz, C. (2018). Market-level effects of firm-level adaptation and intermediation in networked markets of fresh foods: a case study in Colombia. Agricultural Systems, 160, 132-142. http://doi.org/10.1016/j.agsy.2017.06.003.

Mejia Argueta, C., Udenio, M., Mutlu, N. R., & Fransoo, J. C. (2019a). Are nanostores there to stay in emerging markets? (Working Paper). Cambridge: MIT Center for Transportation and Logistics.

Mejía-Argueta, C., Benitez-Perez, V., Salinas-Benitez, S., Brives, O., Fransoo, J. C., Salinas-Navarro, D., & Rangel, G. (2019b, August 15). Nanostores, a force to reckon with to fight malnutrition. LinkedIn. Retrieved in 2022, September 17, from https://www.linkedin.com/pulse/nanostores-force-reckon-fight-malnutrition-escf-professors/

Mora-Quiñones, C. A., Cárdenas-Barrón, L. E., Velázquez-Martínez, J. C., & Gámez-Pérez, K. M. (2021). The coexistence of nanostores within the retail landscape: a spatial statistical study for Mexico City. Sustainability, 13(19), 10615. http://doi.org/10.3390/su131910615.

Moyano, M., Castillo, J., Chong, M., & Mejía, C. (2022). Comparison of nanostore supply chain strategies in urban areas: the case of Ica, Peru. Springer Proceedings in Mathematics and Statistics, 391, 513-531. http://doi.org/10.1007/978-3-031-06862-1_39.

Nogueira, L. R., Fontanelli, M., Aguiar, B. S., Failla, M. A., Florindo, A. A., Barrozo, L. V., Goldbaum, M., Cesar, C., Alves, M., & Fisberg, R. (2018). Access to street markets and consumption of fruits and vegetables by adolescents living in São Paulo, Brazil. International Journal of Environmental Research and Public Health, 15(3), 517. http://doi.org/10.3390/ijerph15030517. PMid:29538324.

Paswan, A., Santarriaga Pineda, M. D., & Soto Ramirez, F. C. (2010). Small versus large retail stores in an emerging market—Mexico. Journal of Business Research, 63(7), 667-672. http://doi.org/10.1016/j.jbusres.2009.02.020.

Rios Monroy, J. (2020). Cultivos en Colombia durante la pandemia por coronavirus. El Tiempo.

Ritter, F. E., Schoelles, M. J., Quigley, K. S., & Klein, L. C. (2011). Determining the Number of Simulation Runs: Treating Simulations as Theories by Not Sampling Their Behavior. In L. Rothrock, S. Narayanan (Eds.), Human-in-the-Loop Simulations (pp. 97-116). London: Springer. http://doi.org/10.1007/978-0-85729-883-6_5.

Sabana Centro Cómovamos. (2017). Municipios. Chía, Colombia. Retrieved in 2023, April 5, from https://sabanacentrocomovamos.org/municipios/

Sabana Centro Cómovamos. (2021). Informe de calidad de vida 2020 (Vol. 6). Chía, Colombia.

Salinas-Navarro, D. E., Pacheco-Velazquez, E., Silva-Ovando, A. C., Mejia-Argueta, C., & Chong, M. (2024). Educational innovation in supply chain management and logistics for active learning in Latin America. Journal of International Education in Business, 17(1), 148-169. http://doi.org/10.1108/JIEB-07-2023-0050.

Shaaban, M., Voglhuber-Slavinsky, A., Dönitz, E., Macpherson, J., Paul, C., Mouratiadou, I., Helming, K., & Piorr, A. (2023). Understanding the future and evolution of agri-food systems: a combination of qualitative scenarios with agent-based modelling. Futures, 149, 103141. http://doi.org/10.1016/j.futures.2023.103141.

Shoukat, A., & Moghadas, S. (2020). Agent-based modelling: an overview with application to disease dynamics. ArXiv, arXiv:2007.04192.

Silva-Ovando, A. C., Granados-Rivera, D., Mejía, G., Mejía-Argueta, C., & Jarrín, J. (2021). Spatial analysis of fresh food retailers in Sabana Centro, Colombia. In L. Rabelo, E. Gutierrez-Franco, A. Sarmiento & C. Mejía-Argueta (Eds.), Engineering analytics (pp. 235-253). Boca Raton: CRC Press. http://doi.org/10.1201/9781003137993-15.

Sopha, B. M., Sri Asih, A. M., Pradana, F. D., Gunawan, H. E., & Karuniawati, Y. (2016). Urban distribution center location: combination of spatial analysis and multi-objective mixed-integer linear programming. International Journal of Engineering Business Management, 8, 1-10. http://doi.org/10.1177/1847979016678371.

Sturley, C., Newing, A., & Heppenstall, A. (2018). Evaluating the potential of agent-based modelling to capture consumer grocery retail store choice behaviours. International Review of Retail, Distribution and Consumer Research, 28(1), 27-46. http://doi.org/10.1080/09593969.2017.1397046.

Swinburn, B., Sacks, G., Vandevijvere, S., Kumanyika, S., Lobstein, T., Neal, B., Barquera, S., Friel, S., Kelly, B., Kumanyika, S., L’Abbé, M., Lee, A., Lobstein, T., Ma, J., MacMullan, J., Mohan, S., Monteiro, C., Neal, B., Rayner, M., Sanders, D., & Walker, C. (2013). What are ‘food environments’? EPHA, 14(Suppl 1), 24-37. PMid:24074208.

Torrens, P. M. (2023). Agent models of customer journeys on retail high streets. Journal of Economic Interaction and Coordination, 18(1), 87-128. http://doi.org/10.1007/s11403-022-00350-z.

Train, K. E. (2009). Discrete choice methods with simulation (2nd ed.). Berkeley: Cambridge University Press.

United Nations. (2020). Cómo evitar que la crisis del COVID-19 se transforme en una crisis alimentaria: acciones urgentes contra el hambre en América Latina y el Caribe. Santiago de Chile: CEPAL.

van Voorn, G., Hengeveld, G., & Verhagen, J. (2020). An agent based model representation to assess resilience and efficiency of food supply chains. PLoS One, 15(11), e0242323. http://doi.org/10.1371/journal.pone.0242323. PMid:33211734.

Widener, M. J., Metcalf, S. S., & Bar-Yam, Y. (2012). Developing a mobile produce distribution system for low-income urban residents in food deserts. Journal of Urban Health, 89(5), 733-745. http://doi.org/10.1007/s11524-012-9677-7. PMid:22648452.

Zhang, J., & Robinson, D. T. (2022). Investigating path dependence and spatial characteristics for retail success using location allocation and agent-based approaches. Computers, Environment and Urban Systems, 94, 101798. http://doi.org/10.1016/j.compenvurbsys.2022.101798.

Zissis, D., Aktas, E., & Bourlakis, M. (2018). Collaboration in urban distribution of online grocery orders. International Journal of Logistics Management, 29(4), 1196-1214. http://doi.org/10.1108/IJLM-11-2017-0303.
 

Submitted date:
11/25/2023

Accepted date:
08/29/2024

670feae2a9539546cd5a4603 production Articles
Links & Downloads
1980-5411 (Electronic) 0103-6513 (Printed)
Production ©2024 All rights reserved.

Production

Share this page
Page Sections