JOURNAL ARTICLE

The interplay of app characteristics and smartphone addiction in mobile shopping behaviour.

  • Published In: International Journal of Consumer Studies, 2024, v. 48, n. 1. P. 1 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Prodanova, Jana; Chopdar, Prasanta Kr. 3 of 3

Abstract

In recent years, we have witnessed accelerated digital interactions among new technology users as a means of communication, leading to addictive behaviours owing to the overuse of smartphones and other new technological interfaces that have reshaped our daily routines. Thus, we adopted the social cognitive theory and the attachment theory to explore and understand the users' app adaptations and how mobile app characteristics, through their influence on smartphone addiction, impact mobile shopping behaviour. We designed an online survey to gather responses from 302 mobile app shoppers in India. We analysed the data using the partial least squares structural equation modelling technique. The results indicate that perceived privacy and security, personalization, contextual offers, and retailers' reputations trigger smartphone addiction. Moreover, the interaction between smartphone addiction and app incentives encourages mobile shopping intentions and frequent purchases. These findings would presumably enhance mobile app characteristics as the stimulus of a closer relationship between consumers and retailers. We present valuable avenues for practitioners to strategically manage their businesses' mobile app environment. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Consumer Studies. 2024/01, Vol. 48, Issue 1, p1
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2024
  • ISSN:1470-6423
  • DOI:10.1111/ijcs.12992
  • Accession Number:175055737
  • Copyright Statement:Copyright of International Journal of Consumer Studies is the property of Wiley-Blackwell 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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