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
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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

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Submitted date:
11/25/2023

Accepted date:
08/29/2024

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