A two-sided sales promotions modeling based on agent-based simulation

IF 0.8 4区经济学 Q3 ECONOMICS Journal of Economic Interaction and Coordination Pub Date : 2024-02-21 DOI:10.1007/s11403-024-00404-4

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Abstract

The growing competition in the retail market pushes retailers to optimize their sales and marketing strategies. In particular, in sectors where the profit margins are more restricted and customer loyalty depends heavily on the prices offered, in fact, understanding consumer reactions to sales promotions and providing them with the right deal at the right time is critical for retailers to survive. In this study, we propose an agent-based model that uses the Belief Desire Intention (BDI) concept to model how customers react to the various promotional offers they receive, and our study involves a seller agent that dynamically learns the appropriate promotion to give these customers on a customer-specific basis. Using empirical research findings in the literature, we developed the BDI part of the model based on the “Big Five-Factor Model”. Apart from this, we used the Q-learning algorithm to train the seller agent. Furthermore, one of our goals in this study is to show that learning-based decision-making agents can be more competitive on the market than rule-based decision-making agents. We therefore added a rule-based agent to the model and compared its efficacy to that of the learning-based decision-making agent. The model was tested in an artificial market through a series of experiments. The experiment results show that the proposed model can be used in actual applications to automate sales promotion decisions.

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基于代理模拟的双面促销建模

摘要日益激烈的零售市场竞争迫使零售商优化其销售和营销战略。特别是在利润空间较为有限、顾客忠诚度在很大程度上取决于所提供的价格的行业，事实上，了解消费者对促销活动的反应，并在适当的时候为他们提供适当的优惠，对于零售商的生存至关重要。在本研究中，我们提出了一个基于代理的模型，该模型使用 "信念欲望意图"（BDI）概念来模拟顾客对其收到的各种促销优惠的反应，我们的研究涉及一个卖方代理，该代理可根据顾客的具体情况动态学习给予这些顾客的适当促销。利用文献中的实证研究成果，我们在 "大五因素模型 "的基础上开发了模型的 BDI 部分。除此之外，我们还使用了 Q-learning 算法来训练卖方代理。此外，本研究的目标之一是证明基于学习的决策代理比基于规则的决策代理更具市场竞争力。因此，我们在模型中添加了一个基于规则的代理，并将其功效与基于学习的决策代理进行了比较。我们通过一系列实验在人工市场上对该模型进行了测试。实验结果表明，所提出的模型可用于实际应用中的自动促销决策。

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来源期刊

Journal of Economic Interaction and Coordination ECONOMICS-

CiteScore

2.20

自引率

18.20%

发文量

期刊介绍： Journal of Economic Interaction and Coordination addresses the vibrant and interdisciplinary field of agent-based approaches to economics and social sciences. It focuses on simulating and synthesizing emergent phenomena and collective behavior in order to understand economic and social systems. Relevant topics include, but are not limited to, the following: markets as complex adaptive systems, multi-agents in economics, artificial markets with heterogeneous agents, financial markets with heterogeneous agents, theory and simulation of agent-based models, adaptive agents with artificial intelligence, interacting particle systems in economics, social and complex networks, econophysics, non-linear economic dynamics, evolutionary games, market mechanisms in distributed computing systems, experimental economics, collective decisions. Contributions are mostly from economics, physics, computer science and related fields and are typically based on sound theoretical models and supported by experimental validation. Survey papers are also welcome. Journal of Economic Interaction and Coordination is the official journal of the Association of Economic Science with Heterogeneous Interacting Agents. Officially cited as: J Econ Interact Coord