Time for a change! Uprooting users embedded in the status quo from habitual decision-making

IF 6.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xue Sun , Bo Guo , Yufeng Yang , Yu Pan
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引用次数: 0

Abstract

Introducing the feature of “Buy Again” or “Order Again” is a common practice for online platforms to facilitate consumer repurchases. Although the adoption of these features can cultivate consumers' dependence on focal products and promote habitual purchases, it potentially hinders the promotion of new products and reduces consumer choice diversity. This raises a broader issue of how to inhibit habitual decision-making, rendering exploring the underlying mechanisms for inhibiting habitual decision-making essential, a topic largely overlooked by previous literature. To address this gap, this research explores how decision-related new information, namely Bayesian updating information, influences consumers' repeated decision-making. Utilizing the paradigm of Monty Hall dilemma, the findings show that Bayesian updating information curtails habitual decisions by encouraging consumers to choose alternative options in both scenarios in which the initial choices are self-decided or given by default. Applying the HDDM (hierarchical drift-diffusion model), the results indicate that, in both scenarios, Bayesian updating information reduces consumers' status quo bias, i.e., mitigates their initial preferences for initial choices, and facilitates the accumulation of evidence for changing initial choices. Notably, when the initial choices are self-decided, consumers with Bayesian updating information tend to seek more evidence to make decisions than those without it, while this trend is not observed when the initial choices are given by default. These findings deepen our understanding of online repeated decision-making and provide valuable insights into the design of decision support systems to discourage consumers' habitual decisions and enhance their choice diversity in online shopping.
是时候改变了!将扎根于现状的用户从习惯性决策中剔除
引入“再次购买”或“再次订购”功能是在线平台方便消费者再次购买的常见做法。虽然采用这些功能可以培养消费者对焦点产品的依赖,促进习惯性购买,但也可能阻碍新产品的推广,降低消费者选择的多样性。这提出了一个更广泛的问题,即如何抑制习惯性决策,使得探索抑制习惯性决策的潜在机制至关重要,这一主题在很大程度上被以前的文献所忽视。为了解决这一差距,本研究探讨了与决策相关的新信息,即贝叶斯更新信息,如何影响消费者的重复决策。利用Monty Hall困境的范例,研究结果表明贝叶斯更新信息通过鼓励消费者在初始选择是自我决定的或默认给出的两种情况下选择替代选项来限制习惯性决策。应用HDDM(分层漂移-扩散模型),结果表明,在两种情况下,贝叶斯更新信息都降低了消费者的现状偏见,即减轻了消费者对初始选择的初始偏好,并有利于改变初始选择的证据积累。值得注意的是,当初始选择是自我决定的时候,拥有贝叶斯更新信息的消费者比没有信息的消费者更倾向于寻找更多的证据来做出决定,而当初始选择是默认的时候,这种趋势就没有被观察到。这些发现加深了我们对网络重复决策的理解,并为决策支持系统的设计提供了有价值的见解,以阻止消费者的习惯性决策,增强他们在网络购物中的选择多样性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Decision Support Systems
Decision Support Systems 工程技术-计算机:人工智能
CiteScore
14.70
自引率
6.70%
发文量
119
审稿时长
13 months
期刊介绍: The common thread of articles published in Decision Support Systems is their relevance to theoretical and technical issues in the support of enhanced decision making. The areas addressed may include foundations, functionality, interfaces, implementation, impacts, and evaluation of decision support systems (DSSs).
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