Network effects in technology acceptance: Laboratory experimental evidence

Pontiggia, Andrea; Virili, Francesco

doi:10.1016/j.ijinfomgt.2009.07.001

Cited by 51 publications

(38 citation statements)

References 36 publications

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“…Past studies determined PU as a desired value realized by a consumer for the accomplishment of any task by using a new technology and/or information system, effectively and successfully (Kim et al, 2014;Venkatesh et al, 2003). Other researchers (Jan & Contreras, 2011;Kang & Lee, 2010;Lee, 2009;Merhi, 2015;Pontiggia & Virili, 2010;Sledgianowski & Kulviwat, 2009;Wu, Chen, & Lin, 2007;Yen, Wu, Cheng, & Huang, 2010) examined that the usefulness of a system in terms of user's thinking had a positive influence on adoption of social networking sites. In other studies, on Facebook adoption, PU is classified as the degree to which a user accepts (with trust) Facebook for educational purposes (Lin, Li, Califf, & Featherman, 2013;Mazman & Usluel, 2010).…”

Section: Perceived Usefulness (Pu)mentioning

confidence: 99%

A multi-analytical approach to predict the Facebook usage in higher education

Sharma

Joshi

Sharma

2016

Computers in Human Behavior

239

177

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Section: Perceived Usefulness (Pu)mentioning

confidence: 99%

A multi-analytical approach to predict the Facebook usage in higher education

Sharma

Joshi

Sharma

2016

Computers in Human Behavior

239

177

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“…The TAM has been applied and investigated in many studies (Chang, 2010;Lin & Lu, 2000;Liao, Palvia, & Lin, 2006;Park, Roman, Lee, & Chung, 2009;Pontiggia & Virili, 2010;Teo, Lim, & Lai, 1999;Teo, 2001;Youngberg, Olsen, & Hauser, 2009) and continues to be explored by scholars. TAM3 synthesizes many previous studies on the TAM and proposes a theoretical framework to explain user acceptance more deeply.…”

Section: The Theoretical Background Of Tam3mentioning

confidence: 99%

An empirical investigation of factors influencing the adoption of data mining tools

Huang

Liu

Chang

2012

International Journal of Information Management

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“…In the information science field, network externalities is a key factor in measuring a product's value, and word-of-mouth throughout the network represents a product's reputation. Accordingly, many researchers use network externalities and word-of-mouth effects to explain online herding behavior (Kauffman et al, 2000;Lee et al, 2009;Pontiggia and Virili, 2010;Muchnik et al, 2013). Network externalities occur when users are directly or 689 Information cascades in online reading indirectly connected in a network of relationships, experiencing growing benefits as the number of connections in the network increases (Pontiggia and Virili, 2010).…”

mentioning

confidence: 99%

Information cascades in online reading: an empirical investigation of panel data

Liu

Zhang²

2014

Library Hi Tech

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to examine information cascades in the context of users' ebook reading behavior and differentiate it from alternative factors that lead to herd behavior, such as network externalities and word-of-mouth effects. Design/methodology/approach -This paper constructed panel data using information concerning 226 e-books in 30 consecutive days from Sina.com's reading channel (of the same year in China. A multinomial logit market-share model was employed.Findings -E-books' ranking has a significant impact on their market share, as predicted by informational cascades theory. Higher ranking e-books' clicks will see a greater increase as a result of an increase in clicks ranking. Due to the information cascades effect, review volume had no impact on the market share of popular e-books. Total votes had a powerful impact on the market share of e-books, showing that once information cascade occurred, it could be enhanced by the increase in total votes. The total clicks of e-books had a significant impact on their market share, suggesting that online reading behavior would be influenced by network externalities. Practical implications -As important information, the ranking or popularity of e-books should be carefully considered by online reading web sites, publishers, and authors. It is not enough for the authors and publishers of e-books to simply pay attention to the content. They should design their marketing strategies to allow network externalities and informational cascades to work for them, not against them. Online reading web sites should also focus on eliminating certain behavior, such as "brush clicks" and "brush votes," in order to prevent an undesirable information cascade due to false information. Originality/value -To the best of the knowledge, this is the first study to examine information cascades in the context of users' e-book reading behavior. Moreover, this study can help other researchers by utilizing a large sample of daily data from one of the earliest online reading platforms in China.

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Network effects in technology acceptance: Laboratory experimental evidence

Cited by 51 publications

References 36 publications

A multi-analytical approach to predict the Facebook usage in higher education

A multi-analytical approach to predict the Facebook usage in higher education

An empirical investigation of factors influencing the adoption of data mining tools

Information cascades in online reading: an empirical investigation of panel data

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