An Empirical Analysis of User Content Generation and Usage Behavior on the Mobile Internet

Ghose, Anindya; Han, Sang Pil

doi:10.1287/mnsc.1110.1350

Cited by 282Media and Digital CommunicationDigital Marketing and Social MediaImpact of Technology on Adolescents

An Empirical Analysis of User Content Generation and Usage Behavior on the Mobile Internet

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Ghose, Anindya, Han, Sang Pil·2011·Management Science

DOI 10.1287/mnsc.1110.1350

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Abstract

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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An integrated measure of media use is seldom found in past research.
“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]

Sample Selection Bias as a Specification Error
Heckman, J. J. (1979) · Econometrica · doi:10.2307/1912352 · Cited by 28,779 · see citing works
Untitled work
(2001) · RePEc: Research Papers in Economics · Cited by 27,577 · see citing works
A Theory of the Allocation of Time
Becker, G. S. (1965) · The Economic Journal · doi:10.2307/2228949 · Cited by 10,354 · see citing works
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735 · see citing works
Identification of Endogenous Social Effects: The Reflection Problem
Manski, C. F. (1993) · The Review of Economic Studies · doi:10.2307/2298123 · Cited by 6,209 · see citing works
On the Pooling of Time Series and Cross Section Data
Mundlak, Y. (1978) · Econometrica · doi:10.2307/1913646 · Cited by 5,412 · see citing works
Social Behavior as Exchange
Homans, G. C. (1958) · American Journal of Sociology · doi:10.1086/222355 · Cited by 5,350 · see citing works
Using Online Conversations to Study Word-of-Mouth Communication
Godes, D., & Mayzlin, D. (2004) · Marketing Science · doi:10.1287/mksc.1040.0071 · Cited by 2,601 · see citing works
PRACTITIONERS’ CORNER: Computing Robust Standard Errors for Within‐groups Estimators *
Arellano, M. (1987) · Oxford Bulletin of Economics and Statistics · doi:10.1111/j.1468-0084.1987.mp49004006.x · Cited by 1,456 · see citing works
Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks
Aral, S., Muchnik, L., & Sundararajan, A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0908800106 · Cited by 1,207 · see citing works
The incidental parameter problem since 1948
Lancaster, T. (2000) · Journal of Econometrics · doi:10.1016/s0304-4076(99)00044-5 · Cited by 1,129 · see citing works
The Heckman Correction for Sample Selection and Its Critique
Puhani, P. A. (2000) · Journal of Economic Surveys · doi:10.1111/1467-6419.00104 · Cited by 1,105 · see citing works
Variety Seeking Behavior: An Interdisciplinary Review
McAlister, L. M., & Pessemier, E. A. (1982) · Journal of Consumer Research · doi:10.1086/208926 · Cited by 1,025 · see citing works
Opinion Leadership and Social Contagion in New Product Diffusion
Iyengar, R., Van den Bulte, C., & Valente, T. W. (2011) · Marketing Science · doi:10.1287/mksc.1100.0566 · Cited by 996 · see citing works
Determining Influential Users in Internet Social Networks
Trusov, M., Bodapati, A. V., & Bucklin, R. E. (2010) · Journal of Marketing Research · doi:10.1509/jmkr.47.4.643 · Cited by 650 · see citing works
Medical Innovation Revisited: Social Contagion versus Marketing Effort
den Bulte, C. V., & Lilien, G. L. (2001) · American Journal of Sociology · doi:10.1086/320819 · Cited by 645 · see citing works
Social Networks and the Diffusion of User-Generated Content: Evidence from YouTube
Susarla, A., Oh, J., & Tan, Y. (2011) · Information Systems Research · doi:10.1287/isre.1100.0339 · Cited by 610 · see citing works
How Is the Mobile Internet Different? Search Costs and Local Activities
Ghose, A., Avi Goldfarb, B., & Han, S. P. (2012) · Information Systems Research · doi:10.1287/isre.1120.0453 · Cited by 530 · see citing works
Self-citation
The Persistence of Marketing Effects on Sales
Dekimpe, M. G., & Hanssens, D. M. (1995) · Marketing Science · doi:10.1287/mksc.14.1.1 · Cited by 457 · see citing works
Network-Based Marketing: Identifying Likely Adopters Via Consumer Networks
Hill, S., Provost, F. J., & Volinsky, C. (2006) · Faculty Digital Archive (New York University Florence) · Cited by 454 · see citing works
Further Evidence on the Estimation of Dynamic Economic Relations from a Time Series of Cross Sections
Nerlove, M. (1971) · Econometrica · doi:10.2307/1913350 · Cited by 432 · see citing works
A Model of Web Site Browsing Behavior Estimated on Clickstream Data
Bucklin, R. E., & Sismeiro, C. (2003) · Journal of Marketing Research · doi:10.1509/jmkr.40.3.249.19241 · Cited by 431 · see citing works
Network-Based Marketing: Identifying Likely Adopters via Consumer Networks
Hill, S., Provost, F., & Volinsky, C. (2006) · Statistical Science · doi:10.1214/088342306000000222 · Cited by 389 · see citing works
Asymmetric Social Interactions in Physician Prescription Behavior: The Role of Opinion Leaders
Nair, H. S., Manchanda, P., & Bhatia, T. (2010) · Journal of Marketing Research · doi:10.1509/jmkr.47.5.883 · Cited by 351 · see citing works
The interrelated dynamics of unemployment and low‐wage employment
Stewart, M. B. (2007) · Journal of Applied Econometrics · doi:10.1002/jae.922 · Cited by 337 · see citing works
Social ties and their relevance to churn in mobile telecom networks
Dasgupta, K., Singh, R., Viswanathan, B., Chakraborty, D., Mukherjea, S., Nanavati, A. A., & Joshi, A. (2008) · International Conference on Extending Database Technology (EDBT) · doi:10.1145/1353343.1353424 · Cited by 333 · see citing works
A Dynamic Model of Brand Choice When Price and Advertising Signal Product Quality
Erdem, T., Keane, M. P., & Sun, B. (2007) · Marketing Science · doi:10.1287/mksc.1080.0362 · Cited by 317 · see citing works
The Role of Targeted Communication and Contagion in Product Adoption
Manchanda, P., Xie, Y., & Youn, N. (2008) · Marketing Science · doi:10.1287/mksc.1070.0354 · Cited by 300 · see citing works
Time and Consumer Behavior: An Interdisciplinary Overview
Jacoby, J., Szybillo, G. J., & Berning, C. K. (1976) · Journal of Consumer Research · doi:10.1086/208644 · Cited by 299 · see citing works
Empirical Analysis of Indirect Network Effects in the Market for Personal Digital Assistants
Nair, H. S., Chintagunta, P. K., & Dubé, J. (2004) · Quantitative Marketing and Economics · doi:10.1023/b:qmec.0000017034.98302.44 · Cited by 294 · see citing works
Modeling Interdependent Consumer Preferences
Yang, S., & Allenby, G. M. (2003) · Journal of Marketing Research · doi:10.1509/jmkr.40.3.282.19240 · Cited by 273 · see citing works
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Asvanund, A., Clay, K. B., Krishnan, R., & Smith, M. D. (2004) · Information Systems Research · doi:10.1287/isre.1040.0020 · Cited by 267 · see citing works
Identifying Formal and Informal Influence in Technology Adoption with Network Externalities
Tucker, C. E. (2008) · Management Science · doi:10.1287/mnsc.1080.0897 · Cited by 251 · see citing works
Modeling social interactions: Identification, empirical methods and policy implications
Hartmann, W. R., Manchanda, P., Nair, H. S., Bothner, M. S., Dodds, P. S., Godes, D., Hosanagar, K., & Tucker, C. E. (2008) · Marketing Letters · doi:10.1007/s11002-008-9048-z · Cited by 211 · see citing works
Consuming video on mobile devices
O'Hara, K. P., Mitchell, A. S., & Vorbau, A. (2007) · ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) · doi:10.1145/1240624.1240754 · Cited by 195 · see citing works
Lessons About Markets from the Internet
Ellison, G., & Ellison, S. F. (2005) · The Journal of Economic Perspectives · doi:10.1257/0895330054048632 · Cited by 195 · see citing works
Neighborhood effects and trial on the internet: Evidence from online grocery retailing
Bell, D., & Song, S. (2007) · Quantitative Marketing and Economics · doi:10.1007/s11129-007-9025-5 · Cited by 186 · see citing works
The Emergence of Market Structure in New Repeat-Purchase Categories: The Interplay of Market Share and Retailer Distribution
Bronnenberg, B. J., Mahajan, V., & Vanhonacker, W. R. (2000) · Journal of Marketing Research · doi:10.1509/jmkr.37.1.16.18723 · Cited by 179 · see citing works
The Visible Hand? Demand Effects of Recommendation Networks in Electronic Markets
Oestreicher-Singer, G., & Sundararajan, A. (2011) · Management Science · doi:10.1287/mnsc.1120.1536 · Cited by 172 · see citing works
The Econometrics of panel data : a handbook of the theory with applications
Mátyás, L., & Sevestre, P. (1996) · Medical Entomology and Zoology · Cited by 161 · see citing works
Regression systems for unbalanced panel data: a stepwise maximum likelihood procedure
Biørn, E. (2003) · Journal of Econometrics · doi:10.1016/j.jeconom.2003.10.023 · Cited by 144 · see citing works
Mobile Advertising: Does Location Based Advertising Work?Preprint
Banerjee, S., & Dholakia, R. R. (2008) · SSRN Electronic Journal · Cited by 135 · see citing works
On the Estimation of Triangular Structural Systems
Lahiri, K., & Schmidt, P. A. (1978) · Econometrica · doi:10.2307/1911446 · Cited by 133 · see citing works
The Effect of Signal Quality and Contiguous Word of Mouth on Customer Acquisition for a Video-on-Demand Service
Nam, S., Manchanda, P., & Chintagunta, P. K. (2010) · Marketing Science · doi:10.1287/mksc.1090.0550 · Cited by 126 · see citing works
Evaluating Promotional Activities in an Online Two-Sided Market of User-Generated Content
Albuquerque, P., Pavlidis, P., Chatow, U., Chen, K., Jamal, Z., Koh, K.-W., & Fitzhugh, A. (2012) · Marketing Science · doi:10.1287/mksc.1110.0685 · Cited by 123 · see citing works
Incomplete Panels and Selection Bias
Verbeek, M., & Nijman, T. E. (1992) · Advanced studies in theoretical and applied econometrics · doi:10.1007/978-94-009-0375-3_13 · Cited by 115 · see citing works
EXPERIMENTAL EVIDENCE ON THE ESTIMATION OF DYNAMIC ECONOMIC RELATIONS FROM A TIME SERIES OF CROSS-SECTION
Nerlove, M. (1967) · The economic studies quarterly/Economic studies quarterly/Kikan riron keizaigaku · doi:10.11398/economics1950.18.3_42 · Cited by 114 · see citing works
Three-stage least-squares estimation for a system of simultaneous, nonlinear, implicit equations
Gallant, A. R. (1977) · Journal of Econometrics · doi:10.1016/0304-4076(77)90035-5 · Cited by 96 · see citing works
Maximum Simulated Likelihood Estimation of Random-Effects Dynamic Probit Models with Autocorrelated Errors
Stewart, M. B. (2006) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x0600600207 · Cited by 91 · see citing works
Fixed and Random Effects Models for Count DataPreprint
Greene, W. H. (2007) · SSRN Electronic Journal · doi:10.2139/ssrn.990012 · Cited by 91 · see citing works
Estimating fixed and random effects models with selectivity
Zabel, J. (1992) · Economics Letters · doi:10.1016/0165-1765(92)90003-h · Cited by 87 · see citing works
<scp>Clicks, Discontinuities, and Firm Demand Online</scp>
Baye, M. R., Gatti, J. R. J., Kattuman, P., & Morgan, J. (2009) · Journal of Economics & Management Strategy · doi:10.1111/j.1530-9134.2009.00234.x · Cited by 79 · see citing works
Research Note—To Continue Sharing or Not to Continue Sharing? An Empirical Analysis of User Decision in Peer-to-Peer Sharing Networks
Xia, M., Huang, Y. M., Duan, W., & Whinston, A. B. (2011) · Information Systems Research · doi:10.1287/isre.1100.0344 · Cited by 76 · see citing works
Untitled work
(2007) · Cited by 69 · see citing works
Incomplete Panels and Selection Bias
Verbeek, M., & Nijman, T. E. (1996) · Advanced studies in theoretical and applied econometrics · doi:10.1007/978-94-009-0137-7_18 · Cited by 63 · see citing works
On the estimation of a fixed effects model with selectivity bias
Verbeek, M. (1990) · Economics Letters · doi:10.1016/0165-1765(90)90129-o · Cited by 53 · see citing works
Consumer Learning, Switching Costs, and Heterogeneity: A Structural ExaminationPreprint
Osborne, M. (2007) · SSRN Electronic Journal · doi:10.2139/ssrn.1015909 · Cited by 30 · see citing works
Mobile TV phone: current usage, issues, and strategic implications
Shim, J. P., Park, S., & Shim, J. M. (2008) · Industrial Management & Data Systems · doi:10.1108/02635570810914937 · Cited by 17 · see citing works
The Visible Hand? Demand Effects of Recommendation Networks in Electronic Markets (Extended Version)Preprint
Oestreicher-Singer, G., & Sundararajan, A. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1268516 · Cited by 15 · see citing works
A Dynamic Structural Model of User Learning on the Mobile InternetPreprint
Ghose, A., & Han, S. P. (2009) · SSRN Electronic Journal · doi:10.2139/ssrn.1485049 · Cited by 15 · see citing works
Self-citation
To Continue Sharing or Not to Continue Sharing? – An Empirical Analysis of User Decision in Peer-to-Peer Sharing NetworksPreprint
Xia, M., Huang, Y. M., Duan, W., & Whinston, A. B. (2007) · SSRN Electronic Journal · doi:10.2139/ssrn.1028165 · Cited by 8 · see citing works
Virality, Network Effects and Advertising EffectivenessPreprint
Tucker, C. E. (2011) · RePEc: Research Papers in Economics · Cited by 1 · see citing works

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Bradlow, E. T., Gangwar, M., Kopalle, P., & Voleti, S. (2017) · Journal of Retailing · doi:10.1016/j.jretai.2016.12.004 · Cited by 516 · see citing works
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Omar, B., & Dequan, W. (2020) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v14i04.12429 · Cited by 493 · see citing works
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Yu, Y., Duan, W., & Cao, Q. (2012) · Decision Support Systems · doi:10.1016/j.dss.2012.12.028 · Cited by 498 · see citing works
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Zheng, X., Men, J., Yang, F. Y., & Gong, X. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.02.010 · Cited by 542 · see citing works
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Information and Communication Technologies in Tourism 2014
Xiang, Z., & Tussyadiah, I. P. (2013) · Springer eBooks · doi:10.1007/978-3-319-03973-2 · Cited by 337 · see citing works
Mobile Targeting
Luo, X., Andrews, M., Fang, Z., & Phang, C. W. (2013) · Management Science · doi:10.1287/mnsc.2013.1836 · Cited by 301 · see citing works
The dark side of elderly acceptance of preventive mobile health services in China
Guo, X., Sun, Y., Wang, N., Peng, Z. C., & Yan, Z. (2012) · Electronic Markets · doi:10.1007/s12525-012-0112-4 · Cited by 271 · see citing works
Where, When, and how Long: Factors that Influence the Redemption of Mobile Phone Coupons
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A multidisciplinary perspective of big data in management research
Sheng, J., Amankwah-Amoah, J., & Wang, X. (2017) · International Journal of Production Economics · doi:10.1016/j.ijpe.2017.06.006 · Cited by 221 · see citing works
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Zubcsek, P. P., Katona, Z., & Sárváry, M. (2017) · Journal of Marketing · doi:10.1509/jm.15.0215 · Cited by 68 · see citing works
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Wang, Z., Liu, H., Liu, W., & Wang, S. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106354 · Cited by 67 · see citing works
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Wu, J., Sun, H., & Tan, Y. (2013) · Journal of Systems Science and Systems Engineering · doi:10.1007/s11518-013-5225-6 · Cited by 57 · see citing works
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Jin, F., Wu, A., & Hitt, L. M. (2017) · Academy of Management Proceedings · doi:10.5465/ambpp.2017.13329abstract · Cited by 49 · see citing works
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Gerpott, T. J., & Meinert, P. (2017) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2017.03.002 · Cited by 38 · see citing works
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Information in Digital, Economic and Social NetworksPreprint
Sundararajan, A., Provost, F. J., Oestreicher-Singer, G., & Aral, S. (2012) · SSRN Electronic Journal · doi:10.2139/ssrn.2141682 · Cited by 35 · see citing works
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Do submission devices influence online review ratings differently across different types of platforms? A big data analysis
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Chen, Y., & Chang, S.-H. (2015) · Electronic Commerce Research · doi:10.1007/s10660-015-9206-3 · Cited by 25 · see citing works
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Beeck, I., & Toporowski, W. (2017) · International Journal of Retail & Distribution Management · doi:10.1108/ijrdm-09-2016-0171 · Cited by 24 · see citing works
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Fu, Y., Liu, J., Li, X., & Xiong, H. (2018) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3151937 · Cited by 23 · see citing works
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Zheng, J., Ren, F. Y., Tan, Y., & Chen, X. (2016) · Information Systems Research · doi:10.1287/isre.2019.0908 · Cited by 21 · see citing works
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Gerpott, T. J., Thomas, S., & Weichert, M. (2012) · Information Systems Frontiers · doi:10.1007/s10796-012-9356-y · Cited by 21 · see citing works
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Kim, J. M., Lee, E., & Mariani, M. M. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2021.08.048 · Cited by 21 · see citing works
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Hussain, S., Sarwar, N., Ali, A., Khan, H., Din, I., Alqahtani, A. M., Shabir, M., & Ali, A. (2025) · Engineering Technology & Applied Science Research · doi:10.48084/etasr.9148 · Cited by 21 · see citing works
The dynamic evolution of social ties and user-generated content: a case study on a Douban group
Shan, S., Ren, J., & Li, C. (2016) · Enterprise Information Systems · doi:10.1080/17517575.2016.1177204 · Cited by 21 · see citing works
Internet móvel nas organizações: fatores de adoção e impactos sobre o desempenho
Lunardi, G. L., Dolci, D. B., & Wendland, J. (2013) · Revista de Administração Contemporânea · doi:10.1590/s1415-65552013000600004 · Cited by 20 · see citing works
Forward-Looking Behavior in Mobile Data Consumption and Targeted Promotion Design: A Dynamic Structural Model
Xu, L., Duan, J. A., Hu, Y. J., Cheng, Y. M., & Zhu, Y. Q. (2019) · Information Systems Research · doi:10.1287/isre.2018.0820 · Cited by 20 · see citing works
To Be or Not To Be Linked: Job Search Using Online Social Networks by Unemployed WorkforcePreprint
Garg, R., & Telang, R. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1813532 · Cited by 20 · see citing works
Competing for Temporary Advantage in a Hypercompetitive Mobile App Market
James, T. L., Qiao, Z., Shen, W., Wang, G. A., & Fan, W. (2023) · MIS Quarterly · doi:10.25300/misq/2022/15079 · Cited by 19 · see citing works
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Self-citation
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Guo, C., Kim, T. H., Susarla, A., & Sambamurthy, V. (2020) · Information Systems Research · doi:10.1287/isre.2020.0951 · Cited by 18 · see citing works
The impact of customer orientation on the quantity and quality of user-generated content
Yoo, B., Katsumata, S., & Ichikohji, T. (2019) · Asia Pacific Journal of Marketing and Logistics · doi:10.1108/apjml-03-2018-0118 · Cited by 18 · see citing works

Authors: Ghose, A., & Han, S. P.
Affiliations: New York University (US)
ORCID: Ghose, Anindya
Han, Sang Pil
Venue: Management Science
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Published: 2011-09
Volume: 57
Issue: 9
Pages: 1671-1691
ISSN: 0025-1909 (ISSN-L)
1526-5501
DOI: 10.1287/mnsc.1110.1350
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: Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
Social Sciences › Sociology and Political Science › 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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An Empirical Analysis of User Content Generation and Usage Behavior on the Mobile Internet

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