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Putting the I in I-voting: An examination of internet voting adoption factors on the individual level

Internet voting (i-voting) has been researched since countries started trialing it two decades ago. Although several countries have abandoned their trials, some implemented i-voting in national elections. I-voting research discusses successful implementations of i-voting in countries such as Estonia, Switzerland, and Canada, which has generated many different factors for successful adoption. However, no systematic literature review (SLR) on i-voting adoption factors has been identified. The problem that this thesis addresses is the lack of a comprehensive overview on reasons why an individual decides to adopt an i-voting solution. Thus, the purpose of this thesis is “to identify i-voting adoption factors on the individual level”. This study aims to answer the following research question: “How can TAM be adapted to explain an individual’s intention to adopt i-voting?” A semi systematic literature review of 117 articles is used that contains articles spanning two decades of i-voting research. The scope is narrowed down to adoption factors on the individual level and include the non-technical factors: “Voter experiences and perceptions”, “Trust”, and “Education”, and the technical factors: “User experience”, and “Performance”. The technology acceptance model (TAM) is used to explain how the factors relate to Perceived Ease of Use (PEOU) and Perceived Usability (PU) within TAM. A suggestion of an extended model is also made that includes other factors which were identified to explain individual adoption. Thus, the conclusion of this thesis is that TAM can in part explain an individual’s intention to adopt i-voting, but that it should be adapted to include the following additional factors: “Trust”, “Demographics”, “Education”, and “Voter experiences and perceptions”. Recommendations for future research on i-voting, limitations, and ethical and societal consequences are also discussed.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:su-219714
Date January 2023
CreatorsChatten, Daniel, Karlsson, Jesper
PublisherStockholms universitet, Institutionen för data- och systemvetenskap
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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