Modeling for the Growth of Unorganized Retailing in the Presence of Organized and E-Retailing in Indian Pharmaceutical Industry

ArXiv ID: 2507.17023 “View on arXiv”

Authors: Koushik Mondal, Balagopal G Menon, Sunil Sahadev

Abstract

The present study considers the rural pharmaceutical retail sector in India, where the arrival of organized retailers and e-retailers is testing the survival strategies of unorganized retailers. Grounded in a field investigation of the Indian pharmaceutical retail sector, this study integrates primary data collection, consumer conjoint analysis and design of experiments to develop an empirically grounded agent-based simulation of multi-channel competition among unorganized, organized and e-pharmaceutical retailers. The results of the conjoint analysis reveal that store attributes of price discount, quality of products offered, variety of assortment, and degree of personalized service, and customer attributes of distance, degree of mobility, and degree of emergency are key determinants of optimal store choice strategies. The primary insight obtained from the agent-based modeling is that the attribute levels of each individual retailer have some effect on other retailers performance. The field-calibrated simulation also evidenced counterintuitive behavior that an increase in unorganized price discounts initially leads to an increase in average footprint at unorganized retailers, but eventually leads to these retailers moving out of the market. Hence, the unorganized retailers should not increase the price discount offered beyond a tipping point or it will be detrimental to them. Another counterintuitive behavior found was that high emergency customers give less importance to variety of assortment than low emergency customers. This study aids in understanding the levers for policy design towards improving the competition dynamics among retail channels in the pharmaceutical retail sector in India.

Keywords: Pharmaceutical Retail, Agent-Based Modeling, Multi-Channel Competition, Conjoint Analysis, Retail Strategy

Complexity vs Empirical Score

• Math Complexity: 5.0/10
• Empirical Rigor: 7.0/10
• Quadrant: Street Traders
• Why: The paper employs agent-based modeling with a structured, multi-attribute utility framework (conjoint analysis) for store choice, requiring parameter estimation and iterative simulation rules, representing moderate mathematical complexity. It is heavily grounded in primary field data from the Indian pharmaceutical sector, involves experimental design for attribute calibration, and produces actionable, counterintuitive insights for market strategy, indicating high empirical rigor.

  flowchart TD
    Start["Research Goal:<br>Modeling competition in Indian pharma retail<br>(Unorganized vs Organized vs E-retailers)"] --> Methodology

    subgraph Methodology ["Key Methodology Steps"]
        A1["Field Investigation<br>Primary Data Collection"]
        A2["Conjoint Analysis<br>Consumer Preference Modeling"]
        A3["Design of Experiments<br>Multi-Channel Variables"]
    end

    Methodology --> Computation
    subgraph Computation ["Computational Process"]
        C1["Agent-Based Simulation<br>Field-Calibrated Model"]
    end

    Computation --> Outcomes
    subgraph Outcomes ["Key Findings/Outcomes"]
        O1["Tipping Point:<br>High price discounts lead to market exit"]
        O2["Emergency Behavior:<br>Low variety preference during crises"]
        O3["Policy Insight:<br>Optimal levers for retail competition"]
    end

    style Start fill:#f9f,stroke:#333,stroke-width:2px
    style Outcomes fill:#ccf,stroke:#333,stroke-width:2px