集合(抽象数据类型)
控制(管理)
投资(军事)
领域(数学)
心理学
多级模型
用户参与度
早期采用者
营销
知识管理
工具变量
感知控制
变量(数学)
计算机科学
控制变量
业务
实证研究
变量
经验证据
客户参与度
持续时间(音乐)
应用心理学
认知心理学
投资决策
关系(数据库)
回归分析
消费者行为
作者
Jake An,André Bonfrer,Christine Eckert
标识
DOI:10.1177/00222437261433457
摘要
Mobile applications in the personal development sector increasingly integrate goal-enabling technology features (GETFs), which allow users to define a service-related end goal, set implementation strategies through subgoals, and monitor progress. Little is known, however, about how the difficulty of goals chosen during GETF adoption affects subsequent app behaviors. This study examines whether customers who set more versus less difficult end goals and subgoals show greater engagement and retention, and whether firms can nudge customers toward goal-difficulty levels conducive to sustained engagement. Using behavioral data from an investment app that introduced GETFs, the authors employ hierarchical modeling with staggered synthetic control and instrumental variable regression to address self-selection and endogeneity. Results reveal substantial heterogeneity: many adopters show no or negative engagement changes, whereas those selecting moderately challenging goals and subgoals significantly increase in-app investment actions, though not sign-ins. Higher engagement post-adoption predicts improved retention after one year. A field experiment confirms that subgoal difficulty causally drives in-app actions. These findings suggest that personalized guidance during GETF adoption can enhance sustained engagement. Marketing managers are advised to tailor goal-setting features to individual needs, providing expert-like support. This research provides novel empirical evidence on goal-difficulty levels that most effectively promote app engagement.
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