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An Empirical Analysis of User Content Generation and Usage Behavior on the Mobile Internet
Open accessAbstract
We quantify how user mobile Internet usage relates to unique characteristics of the mobile Internet. In particular, we focus on examining how the mobile-phone-based content generation behavior of users relates to content usage behavior. The key objective is to analyze whether there is a positive or negative interdependence between the two activities. We use a unique panel data set that consists of individual-level mobile Internet usage data that encompass individual multimedia content generation and usage behavior. We combine this knowledge with data on user calling patterns, such as duration, frequency, and locations from where calls are placed, to construct their social network and to compute their geographical mobility. We build an individual-level simultaneous equation panel data model that controls for the different sources of endogeneity of the social network. We find that there is a negative and statistically significant temporal interdependence between content generation and usage. This finding implies that an increase in content usage in the previous period has a negative impact on content generation in the current period and vice versa. The marginal effect of this interdependence is stronger on content usage (up to 8.7%) than on content generation (up to 4.3%). The extent of geographical mobility of users has a positive effect on their mobile Internet activities. Users more frequently engage in content usage compared to content generation when they are traveling. In addition, the variance of user mobility has a stronger impact on their mobile Internet activities than does the mean. We also find that the social network has a strong positive effect on user behavior in the mobile Internet. These analyses unpack the mechanisms that stimulate user behavior on the mobile Internet. Implications for shaping user mobile Internet usage behavior are discussed. This paper was accepted by Pradeep Chintagunta and Preyas Desai, special issue editors. This paper was accepted by Pradeep Chintagunta and Preyas Desai, special issue editors.
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“In fact, the integrated measure of media use is seldom found in past research [74] with exceptions of some studies (e.g.: [7] [75] [34]).”
From Watch, Share or Create: The Influence of Personality Traits and User Motivation on TikTok Mobile Video Usage (2020) · cites this paper as [74]
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Metadata
- Authors
- Ghose, A., & Han, S. P.
- Affiliations
- New York University (US)
- Venue
- Management Science
- Published
- 2011-09
- Volume
- 57
- Issue
- 9
- Pages
- 1671-1691
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2168997347
- Cited by
- 282
- References
- 64
- Citations by year
- 2026: 3 · 2025: 12 · 2024: 14 · 2023: 15 · 2022: 20 · 2021: 11 · 2020: 19 · 2019: 20 · 2018: 18 · 2017: 22 · 2016: 31 · 2015: 27 · 2014: 25 · 2013: 25 · 2012: 13
- FWCI
- 28.50
- Type
- journal article
- Language
- en
- Open access
- green
- repository.upenn.edu
- Locations
- Management Science (publishedVersion)
- ScholarlyCommons (University of Pennsylvania) (submittedVersion)
- Funders
- National Science Foundation (0643847)
- Topics
- Social Sciences › Communication › Media and Digital Communication
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Keywords
- mobile internet use, user-generated content, content creation, spatial mobility, social networks, calling patterns, mobile phone users, user behavior, systems of equations, endogeneity
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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