Online Review Consistency Matters: An Elaboration Likelihood Model Perspective

Aghakhani, Navid; Oh, Onook; Gregg, Dawn G.; Karimi, Jahangir

doi:10.1007/s10796-020-10030-7

Cited by 65 publications

(52 citation statements)

References 61 publications

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“…Both Figs. 1 and 2 exemplify the bank's effort to utilise the central and peripheral routes of persuasive communications, an approach in line with the hypothesis put forth by Aghakhani et al (2020).…”

Section: Case Backgroundmentioning

confidence: 85%

Innovation resistance and mobile banking in rural Colombia

Klyton

Mesías

Castaño-Muñoz

2021

Journal of Rural Studies

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Section: Case Backgroundmentioning

confidence: 85%

Innovation resistance and mobile banking in rural Colombia

Klyton

Mesías

Castaño-Muñoz

2021

Journal of Rural Studies

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“…Our research also suggests that a comprehensive investigation of determinants of users’ article-sharing behavior decisions is necessary and important. After comparing many models, we chose the ELM, which is frequently used in information-related decision-making processes (Sussman and Siegal 2003 ; Ha and Ahn 2011 ; Shi et al 2018 ; Aghakhani et al 2020 ; Thompson, et al 2020 ). The overarching theoretical framework allows us to integrate various factors into the model and classify them into two influence routes (Petty and Cacioppo 1986 ).…”

Section: Discussionmentioning

confidence: 99%

“…Article richness (Tseng et al 2017 ; Park and Kaye 2019 ; Ordenes et al 2019 ) and emotional tone (Eckler and Bolls 2011 ; Stieglitz and Dang-Xuan 2013 ; Zhu et al 2020 ) have also been identified as determinants; thus, they also belong to the central route. Additionally, the usefulness of article information has been considered a significant factor in prior studies (Aghakhani et al 2020 ; Shang et al 2020). Usually, when a user sees something useful, the message will be flagged.…”

Section: Research Model and Hypothesesmentioning

confidence: 99%

“… H2 Article richness has a positive impact on users’ article-sharing on social media. Researchers have found that the quality of message content has a significant impact on message rebroadcasting (Ha and Ahn 2011 ; Zhang et al 2017 ); individual perceived usefulness may increase the likelihood of article sharing (Aghakhani et al 2020 ; Shang et al 2020). Thus, we propose the following hypothesis: H3 Perceived usefulness has a positive impact on users’ article-sharing on social media.…”

Section: Research Model and Hypothesesmentioning

confidence: 99%

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Understanding Users' Group Behavioral Decisions About Sharing Articles in Social Media: An Elaboration Likelihood Model Perspective

et al. 2022

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The decision to share information is a common phenomenon in individuals’ daily social media use (e.g., Twitter, micro-blogs). However, research on the information to be shared mainly focuses on short texts, and the research on long texts/article sharing is relatively limited. Based on the elaboration likelihood model (ELM), this study established a conceptual model to reveal the determinants of users' behavior in sharing articles. Data on 1311 articles were collected on WeChat, China's most popular social media, and were processed using multiple linear regression. We found that both the central path and the peripheral path of the ELM affect users' decision-making about article-sharing behavior, and that amount of reading and perceived usefulness have the greatest impact. The rhetorical title, the number of pictures, and the number of fans have a negative impact on users' decision-making about article-sharing behavior. Further, the factors that affect users' online-community sharing and sharing with friends are also different. This study is one of the first to apply ELM to examine the influencing factors of users’ decisions about sharing general articles on social media, contributing to the research on the decision-making behavior of users sharing long texts on social media.

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“…IS researchers have used the ELM to describe how attitudes about information generated by an IS are processed (e.g., Aghakhani et al, 2020;Cheung et al, 2012), paralleled with a second stream in which the theory was applied to understand the emergence of attitudes toward a system itself,, such as download intention or trust in mobile banking (e.g., Gu et al, 2017;Zhou, 2012). Building on the latter and ELM's suitability to distinguish different forms of cognitive processes, we apply the ELM to understand whether and how the presentation of inoculation messages influences the formation of attitudes and discontinuance behavior about a CA after response failures.…”

Section: Ca Response Failure User Behaviormentioning

confidence: 99%

Immunizing with information – Inoculation messages against conversational agents’ response failures

Weiler¹,

Matt

Heß³

2021

Electron Markets

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Conversational agents (CAs) are often unable to provide meaningful responses to user requests, thereby triggering user resistance and impairing the successful diffusion of CAs. Literature mostly focuses on improving CA responses but fails to address user resistance in the event of further response failures. Drawing on inoculation theory and the elaboration likelihood model, we examine how inoculation messages, as communication that seeks to prepare users for a possible response failure, can be used as an alleviation mechanism. We conducted a randomized experiment with 558 users, investigating how the performance level (high or low) and the linguistic form of the performance information (qualitative or quantitative) affected users’ decision to discontinue CA usage after a response failure. We found that inoculation messages indicating a low performance level alleviate the negative effects of CA response failures on discontinuance. However, quantitative performance level information exhibits this moderating effect on users’ central processing, while qualitative performance level information affected users’ peripheral processing. Extending studies that primarily discuss ex-post strategies, our results provide meaningful insights for practitioners.

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Online Review Consistency Matters: An Elaboration Likelihood Model Perspective

Cited by 65 publications

References 61 publications

Innovation resistance and mobile banking in rural Colombia

Innovation resistance and mobile banking in rural Colombia

Understanding Users' Group Behavioral Decisions About Sharing Articles in Social Media: An Elaboration Likelihood Model Perspective

Immunizing with information – Inoculation messages against conversational agents’ response failures

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