Interactive product catalogue with user preference tracking

In the context of m-commerce, small screen size poses serious difficulty for users to browse effectively through a product catalogue, given the limited number of products that may be presented on-screen. Despite the availability of search engines, filters and recommender systems to aid users, these techniques focus on a narrow segment of product offering. The users are thus denied the opportunity to do a more expansive exploration of the products available. This paper describes a novel approach to overcome the constraints of small screen size. Through integration of a product catalogue with a recommender system, an adaptive system has been created that guides users through the process of product browsing. An original technique has been developed to cluster similar positive examples together to identify areas of interest of a user. The performance of this technique has been evaluated and the results proved to be promising

Cognitive and Computational Neuroscience: Principles, Algorithms, and Applications in Surveillance Context

Today, working with human behavior is vitally important, especially if we consider the impact neuroscience and security systems. The responsibility of monitoring in a conventional way is in charge of a human agent (vigilant). On the other hand, a vigilant cannot be aware at all times. He can only be aware for 20 minutes which is the time he can monitor four cameras simultaneously; after that, the task of surveillance ceases to make sense. This reveals one of the shortcomings of surveillance (SV) systems. Whether a surveillance system provides a warning of an activity or situation makes it as important as the selection of the technological elements that allowed it to be captured. Security systems based on intelligent technologies have had an accelerated development in recent times detection and identification of car registration numbers, detection of static objects in tracks, and detection of pedestrians circulating on not permitted routes. The reuse of methodologies, procedures, and ontologies is described in this chapter of the book

Implications of Rewards and Punishments for Content Generations by Key Opinion Leaders

Nowadays, e-commerce platforms have increasingly relied on contents generated by key opinion leaders to engage customers and drive product sales. To stay on top of the growth, e-commerce content platforms have introduced rewards and punishments policies to ensure content quality. However, effectiveness has remained less clear. Besides, there is a dearth of research that focuses on such performance-based output control in the extant platform governance and user-generated content (UGC) literature. In this study, based on the reinforcement theory and UGC literature, we investigate the effects of monetary rewards and punishments on the quantity and quality of contents generated by KOLs in the e-commerce content platform context. Using data collected from JD WeChat Shopping Circle, we empirically testified our hypotheses. Our results indicate that punishments significantly increase the quantity and quality of content generated by KOLs. Monetary rewards only have significantly positive effects on the quality of KOLs\u27 generated content. Nevertheless, the magnitude of the effects of monetary rewards is larger compared with that of punishments. Theoretical and practical implications are discussed

Trustworthy Virtual Advisors and Enjoyable Interactions: Designing for Expressiveness and Transparency

Online virtual advisors have enjoyed an increased research attention and widespread use in the lastseveral years. In investigating the determinants of their adoption, the majority of extant research hasfocused on a set of utilitarian variables that address some outcomes from their use. In contrast, thisstudy focuses on users’ perceptions of these virtual advisors as interaction partners, and on beliefsusers form during these interactions. Specifically, we propose and test for the effects of perceivedadvisor expressiveness and transparency on perceptions of their trustworthiness and interactionenjoyment. The latter two constructs are further proposed to act as antecedents to users’ reuseintentions. The results of an experimental study lend support to the proposed model, and highlight theimportance of designing social and trustworthy advisors and enjoyable interactions

Designing Multi-sided Community Platforms for Local High Street Retail

The continuing rise of online retail comes at the expense of small and medium-sized stores in local high streets. Many cities now experience substantial vacancies and the decline of independent and family-owned stores, impeding citizens’ perceived quality of living. In this paper, we design the community platform ‘smartmarket²’, with which networks of local retailers interact with networks of customers to co-create a physical and at the same time digital customer experience in a high street. The platform connects with retailers’ information systems, while interfacing with in-store technologies to connect with potential customers’ smartphones. From a theoretical perspective, the platform exemplifies how previous research on value co-creation, multi-sided (engagement) platforms, and retail communities can complement each other to constitute online-offline customer experience. Based on comparing smartmarket² with rival IT artifacts, we abstract nascent design knowledge by conceptualizing a design theory for ‘community platforms for high street retail’ as a new class of IT artifacts. We conclude the paper with identifying how digital services—including cross-promotions, geographical recommender systems, and geospatial analytics—may be offered on the platform to leverage the competitive position of small and medium-sized retailers in local high streets through online-offline customer experience

A Study on Consumers’ trust Formation Model Toward Recommendation Agents: Elaboration Likelihood Model

It is important to make them have trust in Recommendation Agents (RAs), further enhance their intentions to adopt RAs. This study is based on Elaboration Likelihood Model (ELM) to examine how consumers’ (1) (central routes) degree of cognitive effort are affected by providing product-related information, (2) (peripheral routes) degree of social presence are affected by anthropomorphic interface, and (3) product knowledge influence their trust in RAs. We used PLS to analysis the 302 valid samples, and test or verify the hypotheses. The conclusions are as follows: (1) Explanation facility and information search about products significantly increase customers’ trust in RAs. (2) Consumers’ degree of cognitive effort and telepresence would increase their decision satisfaction and social presence respectively, further their cognitive trust and emotional trust. (3) The experts and novices have different ways to establish their trust in RAs