Design for Social Sharing: The Case of Mobile Apps

• 成果类型: Article
• 署名作者: Karanam, Subrahmanyam Aditya; Agarwal, Ashish; Barua, Anitesh
• 署名单位: National University of Singapore; University of Texas System; University of Texas Austin
• 刊物名称: INFORMATION SYSTEMS RESEARCH
• ISSN/ISSBN: 1047-7047
• DOI: 10.1287/isre.2022.1151
• 发表日期: 2023
• 页码: 721-743
• 关键词: product variety; long tail; ECONOMICS; strength; features; purchase; demand; media; trust

摘要

With a large number of mobile apps on platforms such as iOS and Android, app developers face a significant challenge in generating market demand. Apps can incorporate social features to share information and create awareness. Wefocus on the impact of these features and their interplay with intrinsic features in the head, body, and tail of the demand distribution. Using a panel of version release notes from the iOS platform, we develop a novel hierarchical deep learning model to extract intrinsic and social features. Our results suggest that social features help increase the demand for tail apps and are also useful for head apps in informing users about new intrinsic features. To explore possible mechanisms, we analyze howdifferent types of social features (personal and platform), intrinsic features (common versus differentiating), and app quality influence demand. We find that social features that allow sharing on platformswith large audiences aremore effective at increasing demand than those on personalmessaging systems. Furthermore, within platforms, social features performbetter on those with stronger ties, such as Facebook as opposed to Twitter. Our analysis of different types of intrinsic features reveals that social features can help increase the demand for all apps when introduced with differentiating or less common intrinsic features. Furthermore, we find that there is a negative effect on the demand of tail appswhen differentiating intrinsic features are combined with platform-based social features that have weaker ties. However, this negative effect is limited to low-quality tail apps only. Our results underscore the differences in the effect of different types of social and intrinsic features in various parts of the demand distribution. Our study providesmanagerial guidance to app developers in enabling social sharing through design choices and generating higher demand.