Determining investment allocation strategies to improve consumer satisfaction based on a preference learning model

IF 11 1区 管理学 Q1 BUSINESS Journal of Retailing and Consumer Services Pub Date : 2024-10-30 DOI:10.1016/j.jretconser.2024.104140
Xingli Wu, Huchang Liao
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Abstract

Mining product attribute performance, importance, and their (a)symmetric impacts on consumer satisfaction from online reviews is crucial for enterprises to formulate real-time investment allocation strategies for product improvement. While existing studies have employed machine learning, regression, and correlation analysis to explore these complex relationships, they face the challenge of balancing prediction accuracy with interpretability. This paper proposes an asymmetric importance-performance analysis model based on preference learning with online reviews. It devises an asymmetric value function incorporating unknown preference parameters to elucidate (a)symmetric impacts of attribute performance on overall consumer satisfaction. The process of learning preference parameters is implemented by mathematical programming with a simulation experiment. Attributes are classified into eight categories according to their performance and importance, each corresponding to an improvement strategy. An optimization model is constructed to develop investment allocation strategies for attribute improvement, aiming at maximizing consumer satisfaction within established financial constraints. A hotel-focused case study showcases the approach, and simulations validate the robustness of the proposed model.
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基于偏好学习模型确定投资分配策略,提高消费者满意度
从在线评论中挖掘产品属性的性能、重要性及其对消费者满意度的(对称)影响,对于企业制定实时投资分配策略以改进产品至关重要。虽然现有研究采用了机器学习、回归和相关分析等方法来探索这些复杂的关系,但它们都面临着如何平衡预测准确性和可解释性的挑战。本文提出了一种基于偏好学习和在线评论的非对称重要性-绩效分析模型。它设计了一个包含未知偏好参数的非对称值函数,以阐明属性表现对消费者总体满意度的(a)对称影响。偏好参数的学习过程是通过数学编程和模拟实验实现的。属性根据其性能和重要性被分为八类,每类对应一种改进策略。构建了一个优化模型来制定属性改进的投资分配策略,目的是在既定的财务约束条件下最大限度地提高消费者满意度。以酒店为重点的案例研究展示了该方法,模拟验证了所提模型的稳健性。
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来源期刊
CiteScore
20.40
自引率
14.40%
发文量
340
审稿时长
20 days
期刊介绍: The Journal of Retailing and Consumer Services is a prominent publication that serves as a platform for international and interdisciplinary research and discussions in the constantly evolving fields of retailing and services studies. With a specific emphasis on consumer behavior and policy and managerial decisions, the journal aims to foster contributions from academics encompassing diverse disciplines. The primary areas covered by the journal are: Retailing and the sale of goods The provision of consumer services, including transportation, tourism, and leisure.
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