Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective

Tam, Kar Yan; Ho, Siu Lau

doi:10.1287/isre.1050.0058

Cited by 472 publications

(330 citation statements)

References 38 publications

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“…Researchers in marketing and decision-making also analyze behavioral data, but focus more on decision time, switching behavior after the choice, or total consumption volume (Häubl et al 2004;Pedersen 2000;Vijayasarathy and Jones 2001;Stolze and Nart 2004;Hostler et al 2005;Ho and Tam 2005;Tam and Ho 2005;Pathak et al 2010). A common problem with behavioral data, however, is that they are not always good indicators of users' subjective experience.…”

Section: Triangulation Of (Logged) Behavioral Datamentioning

confidence: 99%

Explaining the user experience of recommender systems

Knijnenburg

Willemsen

Gantner

et al. 2012

User Model User-Adap Inter

616

340

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Research on recommender systems typically focuses on the accuracy of prediction algorithms. Because accuracy only partially constitutes the user experience of a recommender system, this paper proposes a framework that takes a user-centric approach to recommender system evaluation. The framework links objective system aspects to objective user behavior through a series of perceptual and evaluative constructs (called subjective system aspects and experience, respectively). Furthermore, it incorporates the influence of personal and situational characteristics on the user experience. This paper reviews how current literature maps to the framework and identifies several gaps in existing work. Consequently, the framework is validated with four field trials and two controlled experiments and analyzed using Structural Equation Modeling. The results of these studies show that subjective system aspects and experience variables are invaluable in explaining why and how the user experience of recommender systems comes about. In all studies we observe that perceptions of recommendation quality and/or variety are important mediators in predicting the effects of objective system aspects on the three components of user experience: process (e.g. perceived effort, difficulty), system (e.g. perceived system effectiveness) and outcome (e.g. choice satisfaction). Furthermore, we find that these subjective aspects have strong and sometimes interesting behavioral correlates (e.g. reduced browsing indicates higher system effectiveness). They also show several tradeoffs between system aspects and personal and situational characteristics (e.g. the amount of preference feedback users provide is a tradeoff between perceived system usefulness and privacy concerns). These results, as well as the validated framework itself, provide a platform for future research on the user-centric evaluation of recommender systems.

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Section: Triangulation Of (Logged) Behavioral Datamentioning

confidence: 99%

Explaining the user experience of recommender systems

Knijnenburg

Willemsen

Gantner

et al. 2012

User Model User-Adap Inter

616

340

View full text Add to dashboard Cite

show abstract

“…Tang, Jang and Morrison (2012) studied information processing by dual routes in the context of travel sites and confirmed that people are more likely to consider persuasive messages through the central route when they're relatively involved. For example, users are more likely to carefully evaluate information on the web if the content is more detailed and has more reviews by other users (Tam & Ho, 2005). However, people are more likely to go through the peripheral route if they can exert less cognitive effort by following heuristics rules (Tang et al, 2012).…”

Section: Persuasive Messagesmentioning

confidence: 99%

The effects of social media opinion leaders’ recommendations on followers’ intention to buy

Nunes

Ferreira

Freitas

et al. 2018

RBGN

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Purpose -The objective of this study is to investigate how consumers are influenced in their intention to buy after having access -within social media -to persuasive messages sent out by digital opinion leaders.Design/methodology/approach -Data collection carried out via survey and data analysis carried out with the use of structural equation modeling.Findings -Digital opinion leaders capable of generating persuasive messages can change the attitudes of followers and make them accept the information provided, influencing their intention to buy evaluated products.Originality/value -The results show that it was possible to verify the direct and positive relationship between the persuasiveness of a message and the acceptance of the information contained in this message, while also indicating a significant relationship between the persuasiveness of the message and attitude change in relation to the purchase of goods evaluated by it. This highlights the relevance of these digital opinion leaders to the definition of marketing strategies by companies.

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“…Personalized information [62] (relating content to the user and his activities) is included and prioritized in all relevant pages to increase persuasion [63] and facilitate participation for both novice and expert users [64]. For example, when browsing application or component models, system recommendations for models that might be of interest to the user are displayed topmost.…”

Section: Prioritization Of Personalized Informationmentioning

confidence: 99%

Design and implementation of a social networking platform for cloud deployment specialists

Magoutis

Papoulas

Papaioannou

et al. 2015

J Internet Serv Appl

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A new discipline at the intersection of the development and operation of software systems known as DevOps has seen significant growth recently. Among the wide range of tasks of DevOps professionals, we focus on that of selecting appropriate cloud deployments for distributed applications. Despite the advent of automated software deployment and management frameworks, reasoning about good deployments still requires interaction with experts, often through discussions on online technical forums and social networks. Current social networking technologies offer basic ways to communicate. Within the DevOps community, communication on application structure and cloud deployment tradeoffs could become more effective by using knowledge present in global community-sourced information repositories. In this paper we argue for the benefits of tapping into such knowledge and for seamlessly feeding it back into the social networking platform. The social networking platform presented in this paper integrates social networking with automated deployment of applications on multi-clouds and with knowledge drawn from community-sourced information repositories. The implementation leverages two such repositories, the PaaSage repository and Chef Supermarket. Our user evaluation experiments demonstrate the value created for DevOps professionals.

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Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective

Cited by 472 publications

References 38 publications

Explaining the user experience of recommender systems

Explaining the user experience of recommender systems

The effects of social media opinion leaders’ recommendations on followers’ intention to buy

Design and implementation of a social networking platform for cloud deployment specialists

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