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Understanding the impacts of user- and marketer- generated content on free digital content consumption

Authors:

Hsun-Ming LeeAuthors Info & Claims

Volume 154, Issue C

https://doi.org/10.1016/j.dss.2021.113684

Published: 01 March 2022 Publication History

Abstract

The literature has shown that user-generated content (UGC) and marketer-generated content (MGC) simultaneously influence consumers' decision-making process. Yet it is unclear how UGC and MGC jointly affect the overall market reaction, when digital content is freely available to all consumers. To fill the gap, we integrate the UGC and MGC literature and research of determinants of physical exercise to develop a comprehensive conceptual model. Using a dataset collected from a leading online fitness brand, we find that both UGC and MGC affect a free fitness video's incremental view count. We further categorize UGC into three dimensions, where favorability represents the normative dimension, various textual features represent the informational dimension, and reply-density of the self-organized reviewer community represents the social dimension. While both normative and social UGC are positively associated with online fitness videos' view count increase, the impact of informational UGC is insignificant. More importantly, product features, such as exercise intensity, moderate the impacts of UGC and MGC on free digital content consumption. When facing strenuous exercises, the consumer group relies more on peer users and less on marketers to make their content consumption decisions. The findings provide insightful implications to understand how consumers decide their engagement with free digital content delivered via social media channels.

Highlights

•

The incremental view count of a free fitness video is affected by both user-generated content (UGC) and marketer-generated content (MGC).

•

While both normative and social UGC are positively associated with online fitness videos' view count increase, the impact of informational UGC is insignificant.

•

Exercise intensity strengthens the impacts of UGC on free digital content consumption.

•

Exercise intensity weakens the impacts of MGC on free digital content consumption.

References

[1]

S. Aral, D. Walker, Creating social contagion through viral product design: a randomized trial of peer influence in networks, Manag. Sci. 57 (9) (2011) 1623–1639.

[2]

R. Bachman, A fitness empire quietly rises on YouTube, Wall Street J. (April 19th, 2017) URL: https://www.wsj.com/articles/a-fitness-empire-quietly-rises-on-youtube-1492616455.

[3]

V. Baka, The becoming of user-generated reviews: looking at the past to understand the future of managing reputation in the travel sector, Tour. Manag. 53 (April 2016) 148–162.

[4]

R. Bapna, A. Umyarov, Do your online friends make you pay? A randomized field experiment on peer influence in online social networks, Manag. Sci. 61 (8) (2015) 1902–1920.

Digital Library

[5]

B. Biron, Fitness Has Exploded into a Nearly $100 Billion Global Industry as More People Become Obsessed with Their Health. Business Insider, September 3rd, 2019.

[6]

C. Bouchard, S.N. Blair, W.L. Haskell, Physical Activity and Health, Human Kinetics, Inc, 2012.

[7]

F. Bronner, R. Hoog, Consumer-generated versus marketer-generated websites in consumer decision making, Int. J. Mark. Res. 52 (2) (2010) 231–248.

[8]

G. Burtch, A. Ghose, S. Wattal, An empirical examination of the antecedents and consequences of contribution patterns in crowd-funded markets, Inf. Syst. Res. 24 (3) (2013) 499–519.

[9]

A.V. Carron, H.A. Hausenblas, D. Mack, Social influence and exercise: a meta-analysis, J. Sport Exerc. Psychol. 18 (1996) 1–16.

[10]

R.L. Celsi, J.C. Olson, The role of involvement in attention and comprehension processes, J. Consum. Res. 15 (2) (1988) 210–224.

[11]

C.M. Cheung, D.R. Thadani, The impact of electronic word-of-mouth communication: a literature analysis and integrative model, Decis. Support. Syst. 54 (1) (2012) 461–470.

Digital Library

[12]

B. Choi, I. Lee, Trust in open versus closed social media: the relative influence of user- and marketer-generated content in social network services on consumer trust, Telematics Inform. 34 (2017) 550–559.

[13]

K. Clarke, R.W. Belk, The effects of product involvement and task definition on anticipated consumer effort, in: H.K. Hunt (Ed.), Advances in Consumer Research, 5, Association for Consumer Research, Ann Arbor, MI, 1978, pp. 313–318.

[14]

D.A. Colton, Antecedents of consumer attitudes’ toward corporate blogs, J. Res. Interact. Mark. 12 (1) (2018) 94–107.

[15]

A.R. Dennis, R.K. Minas, N.S. Lockwood, Mapping the corporate blogosphere: linking audience, content, and management to blog visibility, J. Assoc. Inf. Syst. 17 (3) (2016) 2.

[16]

S. Dewan, Y.J. Ho, J. Ramaprasad, Popularity or proximity: characterizing the nature of social influence in an online music community, Inf. Syst. Res. 28 (1) (2017) 117–136.

[17]

S. Dewan, J. Ramaprasad, Research note—Music blogging, online sampling, and the long tail, Inf. Syst. Res. 23 (3-part-2) (2012) 1056–1067.

[18]

R.K. Dishman, J.F. Sallis, D.R. Orenstein, The determinants of physical activity and exercise, Public Health Rep. 100 (2) (1985) 158–171.

[19]

L.R. Duncan, C.R. Hall, P.M. Wilson, O. Jenny, Exercise motivation: a cross-sectional analysis examining its relationships with frequency, intensity, and duration of exercise, J. Behav. Nutrit. Phys. Activ. 7 (1) (January 2010) 7.

[20]

L. Eadicicco, Streaming is causing a fitness revolution-and it could redefine gyms as we know them, Bus. Insid. (September 5th, 2019) URL: https://www.businessinsider.com/streaming-workouts-peloton-mirror-soulcycle-redefining-gym-2019-9.

[21]

K. Floyd, R. Freling, S. Alhoqail, H.Y. Cho, T. Freling, How online product reviews affect retail sales: a meta-analysis, J. Retail. 90 (2) (2014) 217–232.

[22]

A. Ghose, P.G. Ipeirotis, Estimating the helpfulness and economic impact of product reviews: mining text and reviewer characteristics, IEEE Trans. Knowl. Data Eng. 23 (10) (2010) 1498–1512.

Digital Library

[23]

K. Goh, C. Heng, Z. Lin, Social medic brand community and consumer behavior: quantifying the relative impact of user- and marketer-generated content, Inf. Syst. Res. 24 (1) (2013) 88–107.

[24]

R.E. Goldsmith, D. Horowitz, Measuring motivations for online opinion seeking, J. Interact. Advert. 6 (2) (2006) 2–14.

[25]

B. Gu, J. Park, P. Konana, Research note—the impact of external word-of-mouth sources on retailer sales of high-involvement products, Inf. Syst. Res. 23 (1) (2012) 182–196.

[26]

D.N. Gujarati, Basic Econometrics, 4th ed., McGraw-Hill, New York (NY), 2003.

[27]

T. Hennig-Thurau, C. Wiertz, F. Feldhaus, Does twitter matter? The impact of microblogging word of mouth on consumers’ adoption of new movies, J. Acad. Mark. Sci. 43 (3) (2015) 375–394.

[28]

J.P. Higgins, Smartphone applications for patients’ health and fitness, Am. J. Med. 129 (2016) 11–19.

[29]

A.P. Hoang, R.J. Kauffman, Content sampling, household informedness, and the consumption of digital information goods, J. Manag. Inf. Syst. 35 (2) (2018) 575–609.

[30]

Z. Katona, P.P. Zubcsek, M. Sarvary, Network effects and personal influences: the diffusion of an online social network, J. Mark. Res. 48 (3) (2011) 425–443.

[31]

J. Koetsier, Global online content consumption doubled in 2020, Forbes Sep 26 (2020).

[32]

C. Kohli, R. Suri, A. Kapoor, Will social media kill branding?, Business Horizons 58 (1) (2015) 35–44.

[33]

K.K. Kuan, K.L. Hui, P. Prasarnphanich, H.Y. Lai, What makes a review voted? An empirical investigation of review voting in online review systems, J. Assoc. Inf. Syst. 16 (1) (2015) 48–71.

[34]

S. Liang, M. Schuckert, R. Law, C. Chen, The importance of marketer-generated content to peer-to-peer property rental platforms: evidence from Airbnb, Int. J. Hosp. Manag. 84 (2020) 1–11.

[35]

Y. Lim, Y. Chung, P.A. Weaver, The impact of social media on destination branding: consumer-generated videos versus destination marketer-generated videos, J. Vacat. Mark. 18 (3) (2012) 197–206.

[36]

J. Liu, C. Li, Y.G. Ji, M. North, F. Yang, Like it or not: the fortune 500’s Facebook strategies to generate users’ electronic word-of-mouth, Comput. Hum. Behav. 73 (2017) 605–613.

[37]

C. Luo, Y. Xu, X. Luo, M. Warkentin, C.L. Sia, Examining the moderating role of sense of membership in online review evaluation, Inf. Manag. 52 (3) (2015) 305–316.

[38]

E.C. Malthouse, M. Haenlein, B. Skiera, E. Wege, M. Zhang, Managing customer relationships in the social media era: introducing the social CRM house, J. Interact. Mark. 27 (4) (2013) 270–280.

[39]

M.S. McCarthy, D.L. Mothersbaugh, Effects of typographic factors in advertising-based persuasion: a general model and initial empirical tests, Psychol. Mark. 19 (7–8) (2002) 663–691.

[40]

M. Meire, K. Hewett, M. Ballings, V. Kumar, D. Van den Poel, The role of marketer-generated content in customer engagement marketing, J. Mark. 83 (6) (2019) 21–42.

[41]

P. Mikalef, K. Sharma, I. Pappas, M. Giannakos, Seeking information on social commerce: an examination of the impact of user- and marketer-generated content through an eye-tracking study, Inf. Syst. Front. (2020),. forthcoming.

Digital Library

[42]

H. Na, J. Hwang, J. Hong, D. Lee, Efficiency comparison of digital content providers with different pricing strategies, Telematics Inform. 34 (2017) 657–663.

[43]

Y. Pan, J.Q. Zhang, Born unequal: a study of the helpfulness of user-generated product reviews, J. Retail. 87 (4) (2011) 598–612.

[44]

G. Parfitt, S. Hughes, The exercise intensity-affect relationship: evidence and implications for exercise behavior, J. Exerc. Sci. Fit. 7 (2) (2009) S34–S41.

[45]

G. Parfitt, D. Markland, C. Holmes, Responses to physical exertion in active and inactive males and females, J. Sport Exerc. Psychol. 16 (2) (1994) 178–186.

[46]

P. Parganas, C. Anagnostopoulos, S. Chadwick, “You’ll never tweet alone”: managing sports brands through social media, J. Brand Manag. 22 (7) (2015) 551–568.

[47]

D.H. Park, J. Lee, I. Han, The effect of on-line consumer reviews on consumer purchasing intention: the moderating role of involvement, Int. J. Electron. Commer. 11 (4) (2007) 125–148.

[48]

D.H. Park, J. Lee, eWOM overload and its effect on consumer behavioral intention depending on consumer involvement, Electron. Commer. Res. Appl. 7 (4) (2008) 386–398.

Digital Library

[49]

L.G. Pee, Negative online consumer reviews: can the impact be mitigated?, Int. J. Mark. Res. 58 (4) (2016) 545–567.

[50]

W. Read, N. Robertson, L. McQuilken, A.S. Ferdous, Consumer engagement on Twitter: perceptions of the brand matter, Eur. J. Mark. 53 (9) (2019) 1905–1933.

[51]

A.B. Rosario, K. de Valck, F. Sotgiu, Conceptualizing the electronic word-of-mouth process: what we know and need to know about eWOM creation, exposure, and evaluation, J. Acad. Mark. Sci. 48 (2020) 422–448.

[52]

S. Ross, A conceptual framework for understanding spectator-based brand equity, J. Sport Manag. 20 (2006) 22–38.

[53]

S. Samendinger, C.R. Hill, N.L. Kerr, B. Winn, A. Ede, J.M. Pivarnik, L. Ploutz-Snyder, D.L. Feltz, Group dynamics motivation to increase exercise intensity with a virtual partner, J. Sport Health Sci. 8 (3) (2019) 289–297.

[54]

M. Scholz, J. Schnurbus, H. Haupt, V. Dorner, A. Landherr, F. Probst, Dynamic effects of user- and marketer-generated content on consumer purchase behavior: modeling the hierarchical structure of social media websites, Decis. Support. Syst. 113 (2018) 43–55.

[55]

T. Song, J. Huang, Y. Tan, Y. Yu, Using user- and marketer-generated content for box office revenue prediction: differences between microblogging and third-party platforms, Inf. Syst. Res. 30 (1) (2019) 191–203.

[56]

A.T. Stephen, J. Galak, The effects of traditional and social earned media on sales: a study of a microlending marketplace, J. Mark. Res. 49 (5) (2012) 624–639.

[57]

J.L. Stevens, B.I. Spaid, M. Breazeale, C.L.E. Jones, Timeliness, transparency, and trust: a framework for managing online customer complaints, Business Horizons 61 (3) (2018) 375–384.

[58]

M.M. Susan, S. David, What makes a helpful online review? A study of customer reviews on amazon.com, MIS Q. 34 (1) (2010) 185–200.

[59]

V. Swaminathan, A. Sorescu, J. Steenkamp, T. O’Guinn, B. Schmitt, Branding in a hyperconnected world: refocusing theories and rethinking boundaries, J. Mark. 84 (2) (2020) 24–46.

[60]

M. Trusov, R.E. Bucklin, K. Pauwels, Effects of word-of-mouth versus traditional marketing: findings from an internet social networking site, J. Mark. 73 (5) (2009) 90–102.

[61]

S. Ullrich, C.B. Brunner, Negative online consumer reviews: effects of different responses, J. Prod. Brand. Manag. 24 (1) (2015) 66–77.

[62]

R.D. Waters, P. Ghosh, T.D. Griggs, E.M. Searson, The corporate side of the blogosphere: examining the variations of design and engagement among fortune 500 blogs, J. Promot. Manag. 20 (5) (2014) 537–552.

[63]

J.M. Wilson, M. Boyer O’Leary, A. Metiu, Q.R. Jett, Perceived proximity in virtual work: explaining the paradox of far-but-close, Organ. Stud. 29 (7) (2008) 979–1002.

[64]

J. Wooldridge, Econometric Analysis of Cross Section and Panel Data, 2nd ed., MIT Press, 2010.

[65]

M. Zhang, B.J. Jansen, A. Chowdhury, Business engagement on twitter: a path analysis, Electron. Mark. 21 (3) (2011) 161.

[66]

K.Z. Zhang, S.J. Barnes, S.J. Zhao, H. Zhang, Can consumers be persuaded on brand microblogs? An empirical study, Inf. Manag. 55 (1) (2018) 1–15.

[67]

P. Zhang, H.M. Lee, K. Zhao, V. Shah, An empirical investigation of eWOM and used video game trading: the moderation effects of product features, Decis. Support. Syst. 123 (2019) 113076.

[68]

K. Zhao, B. Zhang, X. Bai, Estimating contextual motivating factors in virtual interorganizational communities of practice: peer effects and organizational influences, Inf. Syst. Res. 29 (4) (2018) 910–927.

[69]

M.J. Zhou, B. Lu, W.P. Fan, G.A. Wang, Project description and crowdfunding success: an exploratory study, Inf. Syst. Front. 20 (2) (2018) 259–274.

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Understanding the impacts of user- and marketer- generated content on free digital content consumption

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Published In

cover image Decision Support Systems

Decision Support Systems Volume 154, Issue C

Mar 2022

129 pages

ISSN:0167-9236

Issue’s Table of Contents

Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 March 2022

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Cited By

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Jha AVerma N(2024)Social Media Platforms and User Engagement: A Multi-Platform Study on One-way Firm Sustainability CommunicationInformation Systems Frontiers10.1007/s10796-023-10376-826:1(177-194)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s10796-023-10376-8
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https://dl.acm.org/doi/10.1016/j.ipm.2023.103496
Alqadhi MMohaisen D(2023)The Infrastructure Utilization of Free Contents Websites Reveal Their Security CharacteristicsComputational Data and Social Networks10.1007/978-981-97-0669-3_24(255-267)Online publication date: 11-Dec-2023
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Leszczuk MJanowski LNawała JGrega M(2022)User-Generated Content (UGC)/In-The-Wild Video Content RecognitionIntelligent Information and Database Systems10.1007/978-3-031-21967-2_29(356-368)Online publication date: 28-Nov-2022
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