JOURNAL ARTICLE

Self-Regulation and External Influence: The Relative Efficacy of Mobile Apps and Offline Channels for Personal Weight Management.

  • Published In: Information Systems Research (INFORMS), 2023, v. 34, n. 1. P. 50 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Kwon, Hyeokkoo Eric; Dewan, Sanjeev; Oh, Wonseok; Kim, Taekyung 3 of 3

Abstract

This article examines the relative effectiveness of mobile app usage versus offline store visits in a multichannel weight loss program offered by a major Korean healthcare company. Using a novel panel data set of over 600 paid users and additional data on free users, the study finds that both mobile app and offline channel usage contribute to short-term weight loss, with the two channels acting as substitutes. However, only mobile app usage—characterized by frequent and granular self-monitoring enabled by its ubiquity, ease of use, and emotional attachment—significantly supports the sustainability and consistency of long-term weight management. Qualitative interviews with actual customers corroborate that mobile apps primarily facilitate self-regulation, while offline visits provide external motivation and guidance, especially when self-regulation via the app is challenging. The findings highlight the critical role of mobile health apps in enabling effective self-regulation for weight control and suggest practical implications for designing and managing omnichannel weight loss interventions.

Additional Information

  • Source:Information Systems Research (INFORMS). 2023/03, Vol. 34, Issue 1, p50
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:1047-7047
  • DOI:10.1287/isre.2022.1144
  • Accession Number:163088276
  • Copyright Statement:Copyright of Information Systems Research (INFORMS) is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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