Elaboration Liklihood Model:

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The Elaboration Likelihood Model suggests that attitude change among individuals may be caused by two "routes" of influence, the central route and the peripheral route, which differ in the amount of thoughtful information processing or "elaboration" demanded of individual subjects [1]. The central route requires a person to think critically about issue-related arguments in an informational message and analyze the merits and relevance of those arguments prior to forming an informed judgment about the target behavior. In IT acceptance contexts, such arguments may refer to the potential benefits of system acceptance, comparison of alternative systems, availability and quality of system support, and/or costs of and returns from system acceptance. The peripheral route involves less cognitive effort, where subjects rely on cues regarding the target behavior, such as number of prior users, endorsements from IT experts, ease of use, navigation and visual appeal [2], rather than on the quality of arguments, in attitude formation [3].

Exploring the use of ELM in IT acceptance, one of the key findings of Bhattacharjee and Sanford’s paper [7] is that both the central and peripheral routes are acceptable ways of influencing users to accept anything new in IT. While it suggests that attitude change and usefulness perceptions caused by central route processing are more stable and long-term, it also says that both the routes are not mutually exclusive and can be used in conjunction with each other as it was noted that one's usefulness perceptions can be shaped by both argument quality (a central cue) and source credibility (a peripheral cue). 

Another paper [8] discusses the processing of information security messages from an ELM perspective. It suggests two models to study the effects of security message characteristics (argument quality and argument quantity), general security orientation, need for cognition, personal relevance and prior knowledge on users’ attitudes towards security using ELM. The first model is designed to study how argument quality and quantity affect users’ attitudes depending on the processing route (central or peripheral) they take. The second model then studies how the rest of the factors affect elaboration likelihood. This paper not only justifies the selection of these factors but also provides standardized questionnaire items from previous studies that could measure these variables. 

Moreover, ELM has also previously been explored in the context of mobile banking [3]. This study examines users’ initial trust in mobile banking using a comprehensive questionnaire. The results show that both central and peripheral cues have significant effects on initial trust, where central cues include information quality (relevancy, sufficiency, accuracy and currency) and service quality (service reliability, promptness, assurance and personalization), and peripheral cues include system quality (access speed, ease-of-use, navigation and visual appeal), reputation (source credibility) and structural assurance. Among these, information quality, system quality and structural assurance have relatively larger effects on building user trust. It was found that users expect to get relevant, accurate and timely information. Moreover, system quality including visual appeal and navigation structure influence the user’s first impression toward mobile banking; poor interface design can lead to the user doubting the service provider’s ability to provide quality services. Structural assurance is also an important factor that informs user trust. Compared to online banking, mobile banking built on wireless network is vulnerable to eavesdropping and information interception so the service provider needs to assure the user that their information will remain safe. 

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Alternatives to ELM:

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Harri Oinas-Kukkonen and Marja Harjumaa also present a framework [9] to design and evaluate persuasive systems. Relying mostly on Fogg’s functional triad whereby persuasive technologies can act as a tool, media or social actors or as a combination of the above. As such for a persuasive system to be developed a system may rely on providing primary task, dialogue, system credibility, or social support. The following would be an explanation of what each of these might entail:

• Primary Task Support

  • The design principles in this category support the carrying out of the user’s primary task. The design principles in this category are a reduction, tunneling, tailoring, personalization, self-monitoring, simulation, and rehearsal

  • The authors caution against the use of conditioning and surveillance as a means of persuasion

• Dialogue Support

  • The design principles related for implementing computer-human dialogue support in such a manner that helps users keep moving towards their goal or target behavior include praise, rewards, reminders, suggestion, similarity, liking, and social role.

• System Credibility 

  • The design principles in the system credibility category describe how to design a system so that it is more credible and thus more persuasive. The category of system credibility composes of trustworthiness, expertise, surface credibility, real-world feel, authority, third-party endorsements, and verifiability

• Social Support

  • The design principles in the social support category describe how to design the system so that it motivates users by leveraging social influence. The design principles that belong into this category, are social facilitation, social comparison, normative influence, social learning, cooperation, competition, and recognition

A detailed overview of how these can be implemented can be found in tabulated form in the cited paper.

McCarney et al presented the design implementation and evaluation of a password manager [10]. They relied on the Usability Deployability and security Framework defined by Bonneau et al. where a security solution for the web like a password manager must fulfill standards in each of the above avenues in order to be a robust and useful solution. As such an inbetween study was conducted with the following conditions Firefox with no master password (NMP), Firefox with a user-chosen master password (MP), and Tapas. All solutions were measured on the following variables for the purpose of brevity variables of usability are mentioned:

• Usability

  • Memorywise-Effortless

  •  Scalable-for-Users

  • Nothing-to-Carry

  • Physically-Effortless

  • Easy-to-Learn

  • Efficient-to-Use

  • Infrequent-Errors

  • Easy-Recovery-from-Loss 

Variables for Peripheral and Core routes:

In order for us to effectively develop some theory for our designs, we would first need to identify cues that would allow us to attribute facets of our design to some peripheral cues as mentioned by insert source here are: 

• Source Expertise

• Source Likability 

• Argument Quantity

• Visual salience [3]: The visual design of a website is important because it improves website aesthetics and emotional appeal, which in turn may culminate in positive attitudes or trust. Visual design encompasses elements such as images, photographs, colors, shapes, or font types. A combination of pictures and information on a website improves user recall better than text alone.

• Navigation Design: Navigation design refers to the navigational scheme employed to help users as they access different sections of a website. This could include whether text is horizontal or vertical, and the number of drop-down menus or submenus. Without a clear and facilitated path to information, users become lost within the Web structure. Well-designed navigation schemes save time for online consumers leading to trust and satisfaction. Navigation Design refers to ease of use and navigation of the website.

• Social Presence: Social Presence is defined as “the extent to which a medium allows users to experience others as being psychologically present”. Based on prior research, Social Presence refers to a website for which users perceive it to have a sense of human contact, personalness, sociability, as well as human warmth and sensitivity. In the context of hedonic consumer interactions, perceived social presence has received considerable attention as an antecedent to online consumer enjoyment and trust, website involvement, and utilitarian outcomes such as perceived usefulness or effectiveness.

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1. Petty, Richard E. “The Elaboration Likelihood Model of Persuasion.” (1986).http://cyber.scihub.tw/MTAuMTAxNi9zMDA2NS0yNjAxKDA4KTYwMjE0LTI=/10.1016%40s0065-2601%2808%2960214-2.pdf

2. Anthony Vance, Christophe Elie-Dit-Cosaque & Detmar W. Straub. “Examining Trust in Information Technology Artifacts: The Effects of System Quality and Culture.” Journal of Management Information Systems, 2014.http://cyber.sci-hub.tw/MTAuMjc1My9taXMwNzQyLTEyMjIyNDA0MDM=/10.2753%40mis0742-1222240403.pdf

3. Zhou, Tao. “Understanding Users’ Initial Trust in Mobile Banking: An Elaboration Likelihood Perspective.” Computers in Human Behaviour, 2012.http://cyber.scihub.tw/MTAuMTAxNi9qLmNoYi4yMDEyLjAzLjAyMQ==/10.1016%40j.chb.2012.03.021.pdf

4. Cyr, Dianne & Head, Milena & Lim, Eric & Stibe, Agnis. (2018). Using the Elaboration Likelihood Model to Examine Online Persuasion through Website Design. Information & Management. 10.1016/j.im.2018.03.009.https://www.researchgate.net/publication/323977472_Using_the_Elaboration_Likelihood_Model_to_Examine_Online_Persuasion_through_Website_Design

5. Dey, Sanorita & Duff, Brittany & Karahalios, Karrie & Fu, Wai-Tat. (2017). The Art and Science of Persuasion: Not All Crowdfunding Campaign Videos are The Same. 755-769. 10.1145/2998181.2998229.http://sdey4.web.engr.illinois.edu/CrowdfundingVideoAnalysis.pdf

6. Angst, Corey M., and Ritu Agarwal. “Adoption of Electronic Health Records in the Presence of Privacy Concerns: The Elaboration Likelihood Model and Individual Persuasion.” MIS Quarterly, vol. 33, no. 2, 2009, pp. 339–370. JSTOR, https://www.jstor.org/stable/pdf/20650295.pdf?ab_segments=0%2Fdefault-2%2Fcontrol

7. Bhattacherjee, Anol, and Clive Sanford. “Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model.” MIS Quarterly, vol. 30, no. 4, 2006, pp. 805–825. JSTOR,https://www.jstor.org/stable/pdf/25148755.pdf?refreqid=excelsior%3Afa82616a9c2bc02f2082519837e94f13

8. Ng, Boon-Yuen and Atreyi Kankanhalli. “Processing Information Security Messages: An Elaboration Likelihood Perspective.” ECIS (2008).https://pdfs.semanticscholar.org/88a9/f561af6947a7bfc6558251350d7f9d5b68f0.pdf?_ga=2.181310821.319615309.1563109415-1403746961.1562915708

9. Oinas-Kukkonen, Harri, and Marja Harjumaa. "A systematic framework for designing and evaluating persuasive systems." International conference on persuasive technology. Springer, Berlin, Heidelberg, 2008

10. McCarney, Daniel, et al. "Tapas: design, implementation, and usability evaluation of a password manager." Proceedings of the 28th Annual Computer Security Applications Conference. ACM, 2012.

11. Petty, Richard E., and John T. Cacioppo. "The elaboration likelihood model of persuasion." Communication and persuasion. Springer, New York, NY, 1986. 1-24.