Next Generation of Product Search and Discovery

Online shopping has become an important part of people’s daily life with the rapid development of e-commerce. In some domains such as books, electronics, and CD/DVDs, online shopping has surpassed or even replaced the traditional shopping method. Compared with traditional retailing, e-commerce is information intensive. One of the key factors to succeed in e-business is how to facilitate the consumers’ approaches to discover a product. Conventionally a product search engine based on a keyword search or category browser is provided to help users find the product information they need. The general goal of a product search system is to enable users to quickly locate information of interest and to minimize users’ efforts in search and navigation. In this process human factors play a significant role. Finding product information could be a tricky task and may require an intelligent use of search engines, and a non-trivial navigation of multilayer categories. Searching for useful product information can be frustrating for many users, especially those inexperienced users. This dissertation focuses on developing a new visual product search system that effectively extracts the properties of unstructured products, and presents the possible items of attraction to users so that the users can quickly locate the ones they would be most likely interested in. We designed and developed a feature extraction algorithm that retains product color and local pattern features, and the experimental evaluation on the benchmark dataset demonstrated that it is robust against common geometric and photometric visual distortions. Besides, instead of ignoring product text information, we investigated and developed a ranking model learned via a unified probabilistic hypergraph that is capable of capturing correlations among product visual content and textual content. Moreover, we proposed and designed a fuzzy hierarchical co-clustering algorithm for the collaborative filtering product recommendation. Via this method, users can be automatically grouped into different interest communities based on their behaviors. Then, a customized recommendation can be performed according to these implicitly detected relations. In summary, the developed search system performs much better in a visual unstructured product search when compared with state-of-art approaches. With the comprehensive ranking scheme and the collaborative filtering recommendation module, the user’s overhead in locating the information of value is reduced, and the user’s experience of seeking for useful product information is optimized

Lone star or team player?:The interrelationship of different identification foci and the role of self-presentation concerns

Work identity is important in the attraction and retention of staff, yet how the facets of such identity relate remains convoluted and unclear despite this being of interest to both scholars and practitioners. We use structural equation modeling to analyze empirical data from 144 employees in the United Kingdom's oil and gas industry, analyzing the nature and interrelationship of identification as individual-level (career advancement) and social-level (work group and organization) foci, as well as considering the two psychological self-presentation factors (value expression and social adjustment) that direct and drive identification processes. A dichotomy between individual and social components of work identity is found, revealing a strong association between both social-level foci of identification. Moreover, both components of work identity are found to be premised on different psychological factors, furthering our knowledge of the enmeshed nature of identity at work

The role of simulations in consumer experiences and behavior: insights from the grounded cognition theory of desire

What are the mechanisms by which extrinsic and environmental cues affect consumer experiences, desires, and choices? Based on the recent grounded cognition theory of desire, we argue that consumption and reward simulations constitute a central mechanism in these phenomena. Specifically, we argue that appetitive stimuli, such as specific product cues, can activate simulations of consuming and enjoying the respective products, based on previous learning experiences. These consumption and reward simulations can lead to motivated behavior, and can be modulated by state and trait individual differences, situational factors, and product-extrinsic cues. We outline the role of simulations within the grounded theory of desire, offering a theoretical framework for understanding motivational processes in consumer behavior. Then we illustrate the theory with behavioral, physiological, and neuroimaging findings on simulations in appetitive behavior and sensory marketing. Finally, we outline important issues for further research and applications for stimulating healthy, prosocial, and sustainable consumer choices