Cited by 210Technology Adoption and User BehaviourInnovation Diffusion and ForecastingInnovative Human-Technology Interaction

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

The social influence model of technology adoption

Open access
Vannoy, Sandra A., Palvia, Prashant·2010·Communications of the ACM

Abstract

Introduction Human innovation, in combination with the internet, networking, and communications technologies have produced a new platform for social and business networking, formation of community, and communication. This emerging phenomenon is generally known as social computing. While there is no widely accepted definition of social computing, we define it as: intra-group social and business actions practiced through group consensus, group cooperation, and group authority, where such actions are made possible through the mediation of information technologies, and where group interaction causes members to conform and influences others to join the group . In this article, we examine the adoption of information technologies in the context of social computing. Most current information systems research on individual technology adoption has focused upon the adoption of technology in organizations and has utilized such technology acceptance models as the TRA and TAM. It has been suggested, however, that a new perspective on adoption may be necessary to fully capture the nature of technology acceptance in social computing situations, where the technology is embraced rather than simply accepted by the user, and where the action made possible by technology is seen as a behavior embedded in society. Few studies have investigated technology adoption targeting the individual at the level of society, community, or lifestyle experience. There is little research that approaches adoption in the context of social computing, and to our knowledge, no models have been developed to investigate this phenomenon. This study addresses this gap by developing social constructs and providing a theoretically grounded model for technology adoption in the context of social computing. We develop a cross-disciplinary model of technology adoption to address the multi-faceted context of social computing. Our model suggests that social computing action, social computing consensus, social computing cooperation, and social computing authority are antecedents to social influence, and augment usefulness and ease of use. In social influence, group membership legitimizes actions and the individual is guided by the group's rules of practice. Social influence leads to technology adoption. Technology adoption incorporates two essential elements, the embracement of the technology by individuals and its embedment in society. Each of the model's constructs will be explained in further detail. As Figure 1 demonstrates, while technology may influence society, society often exerts influence on technology. Consider SMS text messaging. A technology that was originally intended to deliver subscriber information was adopted by end users as a vehicle for social behavior. Peer-to-peer (P2P) file swapping offers another example. A technology that was intended to provide an efficient mechanism for remote file access was adopted by end users to create music sharing networks. The strength of social influence is evident, as text messaging has now outpaced voice mobile calling as well as email. Similarly, sales of traditional music media such as CDs are declining as the number of music downloads and uploads via P2P networks continue to increase. As the Internet, networking, and communications technologies become increasingly embraced by individuals and embedded in everyday lives and activities, technologically enabled social structures are emerging that are changing the way individuals interact and communicate, and are facilitating fundamental changes to business practices. People socialize and network via their Web browsers by joining social networking sites such as MySpace.com and LinkedIn.com. Text messaging has created a form of communication that has its own user-defined language and protocols. A recent study by Cision on the influence of Web blogs on mainstream media showed that the mention of blogs in top magazines and newspapers has increased from just over 2,000 in 2005 to over 13,000 in 2008. In a 2006 study, Forrester Research found that although social computing is in infancy, societal changes are being witnessed, as individuals increasingly take cues from one another, in addition to traditional sources of authority, such as corporations, media, political institutions or religions. Social computing mechanisms such as blogs, e-Bay-esque Web sites, Web-based forums such as MySpace.com, text messaging, and instant messaging are often utilized instead of traditional sources of news, purchasing, and social interaction. Unauthorized P2P file sharing provides an example of how technology is used in the formation and organization of groups with shared interests. Through cooperation with a particular action , communities based upon the shared interest of music exchange are created by the consensus of the group that it is acceptable to use the Internet and communication technologies to share music among group members. Though the action is illegal in the traditional

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/1743546.1743585

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Interpersonal interaction generates perceived pressure through messages or signals for individuals to act on certain behaviors.

    “Specifically, interpersonal interaction generates perceived pressure through messages or signals for individuals to act on certain behaviors [67].”

    From Advancing Undergraduate Student Mental Healthcare of Social Anxiety Disorder: Evaluating the Acceptance of AR-Assisted Cognitive Behavioral Therapy Through TAM-Based Constructs. (2026) · cites this paper as [67]

    The Model Explanation defines social influence partly as perceiving that important others think one should join a group, and The Social Influence Model says group influence can cause members to conform. These passages support perceived social pressure, but the paper develops this account for technology adoption in social computing, not for behaviors generally; it does not specifically describe pressure being conveyed through messages or signals. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Axelrod , R. On Six Advances in Cooperation Theory The Evolution of Cooperation . School of Public Policy University of Michigan Ann Arbor , MI , Jan. 2000 . Axelrod, R. On Six Advances in Cooperation Theory The Evolution of Cooperation. School of Public Policy University of Michigan Ann Arbor, MI, Jan. 2000.

Cited by

Sorted by citations

Metadata

Authors
Vannoy, S. A., & Palvia, P.
Affiliations
  • Appalachian State University (US)
  • University of North Carolina at Greensboro (US)
Venue
Communications of the ACM
Published
2010-06
Volume
53
Issue
6
Pages
149-153
ISSN
  • 0001-0782 (ISSN-L)
  • 1557-7317
OpenAlex
W2052341645
Cited by
210
References
11
Citations by year
2026: 12 · 2025: 15 · 2024: 16 · 2023: 10 · 2022: 10 · 2021: 15 · 2020: 9 · 2019: 11 · 2018: 15 · 2017: 17 · 2016: 10 · 2015: 17 · 2014: 9 · 2013: 18 · 2012: 12
FWCI
29.11
Type
journal article
Language
en
Open access
Locations
  • Communications of the ACM (publishedVersion)
  • NC Digital Online Collection of Knowledge and Scholarship (The University of North Carolina at Greensboro) (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Innovation Diffusion and Forecasting
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
technology adoption, social computing, social influence, group membership, technology acceptance, social networking, peer-to-peer file sharing, safety management systems, music download, technology acceptance model

About these checks

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 ›

Are you an author, or do you see a problem with this page? Request a review