JOURNAL ARTICLE
The Impact of Mobile Data Cost on Consumer Price Sensitivity: A Study of a Hotel Booking App.
Published In: Information Systems Research (INFORMS), 2025, v. 36, n. 3. P. 1912 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Luo, Xiaopeng; He, Cheng; Hu, Yu Jeffrey; Li, Xitong; Cheng, Yuan 3 of 3
Abstract
This article investigates how the perceived cost of using mobile data versus Wi-Fi affects consumer price sensitivity in the context of a hotel booking app. Analyzing individual-level data from a major Chinese online travel agency, the study finds that consumers using mobile data exhibit approximately twice the price sensitivity compared to those on Wi-Fi, resulting in an average revenue loss of US$17 per booking. This heightened price sensitivity is attributed to a mental cost associated with mobile data usage—stemming from fixed data quotas and potential overage charges—that drives consumers into a satisficing search mode characterized by reduced search effort and less acquisition of product information. The study further demonstrates that this effect is more pronounced at the end of the monthly billing cycle when consumers are closer to exceeding their data limits. Implications include recommendations for firms to tailor marketing strategies and app designs based on connectivity type, consider mobile data subsidies, and for policymakers to monitor potential price discrimination in mobile shopping environments.
Additional Information
- Source:Information Systems Research (INFORMS). 2025/09, Vol. 36, Issue 3, p1912
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2025
- ISSN:1047-7047
- DOI:10.1287/isre.2023.0450
- Accession Number:188497599
- 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.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.