Modelling Behaviour Change in Online Users: A Study of Influencing Healthier Shopping Habits in E-commerce Shoppers

While a lot of effort and research has gone towards influencing people to be more active with the use of apps, games, and exercise tools not much has been done in influencing people to eat healthy foods, especially by influencing healthy shopping habits. The use of persuasive strategies to change people’s behaviour is an active research area in several domains including e-commerce. Research suggests that persuasive strategies are more effective in bringing about the desired behaviour change when they are tailored to individuals or groups of similar individuals. There is, therefore, a need to identify what factors can be used to tailor persuasive strategies in ecommerce. To fill this gap and to tailor persuasive strategies to consumers, this dissertation proposes two consumer behaviour traits commonly used in consumer studies research: consumers’ need for uniqueness and their need for status (called "status consumption" in the literature), as well as a factor called "shopper type" accounting to the shopper's motivation. Two structural research models were developed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to identify the receptiveness of shoppers to persuasive strategies based on their consumer behaviour trait (consumers’ need for uniqueness and status consumption) and their shopping motivation (shopper types: convenience shoppers, variety seekers, store oriented shoppers, and balanced buyers). These models were tested by conducting a user study of 244 e-commerce shoppers. The results from these models were used to develop ShopRight, a persuasive game to influence behaviour change in e-commerce shoppers and to help them develop healthier shopping habits. To evaluate the game's effectiveness, a study of 305 participants was conducted using a data-driven approach to measure the receptiveness of participants to the persuasive strategies. The findings from this dissertation suggest that consumer behaviour traits and consumer’s online shopping motivation can be used to tailor persuasive strategies in ecommerce and in particular, influence healthy shopping online. This dissertation’s findings also show that tailored persuasive strategies are more likely to bring about a change in attitude or behaviour than non-tailored strategies. Furthermore, a serious game can be used as a learning tool to influence healthy shopping habits, educate shoppers on the nutritional value of foods and show that healthy foods can be purchased on a budget

How buyers perceive the credibility of advisors in online marketplace: review balance, review amount and misattribution

In an online marketplace, buyers rely heavily on reviews posted by previous buyers (referred to as advisors). The advisor’s credibility determines the persuasiveness of reviews. Much work has addressed the evaluation of advisors’ credibility based on their static profile information, but little attention has been paid to the effect of the information about the history of advisors’ reviews. We conducted three sub-studies to evaluate how the advisors’ review balance (proportion of positive reviews) affects the buyer’s judgement of advisor’s credibility (e.g., trustworthiness, expertise). The result of study 1 shows that advisors with mixed positive and negative reviews are perceived to be more trustworthy, and those with extremely positive or negative review balance are perceived to be less trustworthy. Moreover, the perceived expertise of the advisor increases as the review balance turns from positive to negative; yet buyers perceive advisors with extremely negative review balance as low in expertise. Study 2 finds that buyers might be more inclined to misattribute low trustworthiness to low expertise when they are processing high number of reviews. Finally, study 3 explains the misattribution phenomenon and suggests that perceived expertise has close relationship with affective trust. Both theoretical and practical implications are discussed

Complexity or simplicity? Designing product pictures for advertising in online marketplaces

In online marketplaces, many sellers highlight product and service information directly within product pictures for advertising purposes. Such a strategy increases the visual complexity of the picture and provides more information to support buyers’ judgment. However, when other sellers adopt the same method, a given picture will not be conspicuous enough to be noticed. To address this issue, the concept of complexity contrast is introduced. No prior attention has been paid in literature to the interplay between visual complexity and complexity contrast. This research proposes a theoretical model to explain the influences of visual complexity and complexity contrast on buyers’ pleasantness in shopping, while perceptual and conceptual fluency act as mediators. Results from a lab experiment suggest an entangled effect of complexity contrast and visual complexity, indicating that buyers are influenced more by the conspicuousness of a product picture, rather than the information conveyed by a product picture when it is visually overwhelming

Modelling User Collaboration in Social Networks Using Edits and Comments

SIGCHI ACM Special Interest Group on Computer-Human Interaction SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and WebResearch has shown that in Q&A social networks, collaboration between respondents results in quality answers. Since good answers are required to keep any Q&A social network active, it is important to understand the characteristics of these collaborations and the collaborators. In this paper, we investigate how Stack Overflow promotes collaboration by allowing users to edit existing questions and answers in order to improve them. Using over 40,000 answer posts, our study reveals that collaboration in answer posts is not a function of achievement earned in terms of badges, as most edits associated with "best answer" rewards were posted by users who have not earned any answer badge. Our study further shows that posts that earned the "best answer" reward have more comments than those that did not. This study though, work in progress, can aid developers in implementing collaboration strategies in social networks that work

Adaptive and Personalized Persuasive Technologies

The 2021 Adaptive and Personalized Persuasive Technology (ADAPPT 2021) workshop is the second edition of the ADAPPT series, which commenced in 2019. It is organized in conjunction with the 29th Association for Computer Machinery (ACM) Conference on User Modeling, Adaptation and Personalization (UMAP). We summarize the main ideas, topics and results of the 10 papers accepted for publication in the adjunct proceedings of the UMAP conference and for video/oral presentation at the virtual workshop