Supporting user interaction and social relationship formation in a collaborative online shopping context

The combination of online shopping and social media allow people with similar shopping interests and experiences to share, comment, and discuss about shopping from anywhere and at any time, which also leads to the emergence of online shopping communities. Today, more people turn to online platforms to share their opinions about products, solicit various opinions from their friends, family members, and other customers, and have fun through interactions with others with similar interests. This dissertation explores how collaborative online shopping presents itself as a context and platform for users\u27 interpersonal interactions and social relationship formation through a series of studies. First, a qualitative interview study shows that online shoppers believe that shopping-related interactions have a positive impact on their social bonds. However, there is uncertainty around the appropriateness of discussing shopping in online marketplaces, forums, and social networking sites between strangers and friends. These uncertainties act as strong deterrents that limit further interactions between users with shared shopping interests. Next, a mix of lab experiments and focus groups demonstrate how informational support and social support affect user participation and relationships, the impact of social structure on interpersonal relationship formation between community members, and the development of desire to be socially connected with others through real-time text conversations on shopping topics. Moreover, a combination of interviews, focus groups, and online survey identify four types of personas to help illustrate the complex nature of user participation and behaviors in online shopping communities: Opportunists, Contributors, Explorers, and Followers. Finally, an online experiment study with 50 participants implements problem-solving tasks to examine users’ relationship building in computer-mediated online shopping groups and the effects of interpersonal relationships on user behaviors in collaborative online shopping contexts. The results suggest that users may develop desire to be socially connected after working on implemented collaborative problem-solving tasks within the group, and the perceived social connectedness may encourage user engagement and contribution behaviors in online shopping groups and communities. The results also show that such help-giving, collaborative tasks lead to developing social capital and facilitating social support that have more significant impacts on user behaviors over the long term

Using explainable food swaps to nudge users towards more sustainable products in grocery websites

The growing concern for climate issues has prompted both consumers and the grocery retail industry to prioritize environmental sustainability. This thesis aims to examine the effectiveness of nudging users towards more sustainable food options in an online grocery store using food swaps. Further, the study utilizes different motivational explanations accompanying the swaps to investigate their impact on swap acceptance and perceived understand- ing. A mockup supermarket interface was created, and screenshots were uploaded to an online survey tool, where participants (N=202) were assigned to one of four conditions (baseline, health, sustainability, or money). Results indicate that motivational framing did not significantly influence swap acceptance. However, perceived understandability was significant in affecting swap acceptance, with the sustainability framing being better understood. Participants were more likely to swap when the cost of the alternative product increased, suggesting other factors influenced consumer behavior. Finally, perceived similarity between the original and alternative product significantly affected the swap acceptance and perceived similarity, where meat swaps showed a strong positive, statistical significance. This thesis provided novel work within the field of encouraging more sustainable products in online grocery shopping services, which can further be expanded by implementing sustainable food swaps in a recommender system.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

Recommendation System for News Reader

Recommendation Systems help users to find information and make decisions where they lack the required knowledge to judge a particular product. Also, the information dataset available can be huge and recommendation systems help in filtering this data according to users‟ needs. Recommendation systems can be used in various different ways to facilitate its users with effective information sorting. For a person who loves reading, this paper presents the research and implementation of a Recommendation System for a NewsReader Application using Android Platform. The NewsReader Application proactively recommends news articles as per the reading habits of the user, recorded over a period of time and also recommends the currently trending articles. Recommendation systems and their implementations using various algorithms is the primary area of study for this project. This research paper compares and details popular recommendation algorithms viz. Content based recommendation systems, Collaborative recommendation systems etc. Moreover, it also presents a more efficient Hybrid approach that absorbs the best aspects from both the algorithms mentioned above, while trying to eliminate all the potential drawbacks observed

Online Recommendation Systems in a B2C E-Commerce Context: A Review and Future Directions

An online recommendation system (RS) involves using information technology and customer information to tailor electronic commerce interactions between a business and individual customers. Extant information systems (IS) studies on RS have approached the phenomenon from many different perspectives, and our understanding of the nature and impacts of RS is fragmented. The current study reviews and synthesizes extant empirical IS studies to provide a coherent view of research on RS and identify gaps and future directions. Specifically, we review 40 empirical studies of RS published in 31 IS journals and five IS conference proceedings between 1990 and 2013. Using a recommendation process theoretical framework, we categorize these studies in three major areas addressed by RS research: understanding consumers, delivering recommendations, and the impacts of RS. We review and synthesize the extant literature in each area and across areas. Based on the review and synthesis, we surface research gaps and provide suggestions and potential directions for future research on recommendation systems

Different Views and Evaluations of IT Artifacts

The introduction and adoption of a multitude of new and interactive information technology (IT) artifacts has impacted adoption research. Rather than solely functioning as productivity tools, new IT artifacts assume the roles of interaction mediators and social actors. This paper describes these varying roles, and discusses the type of perceptions users form when using them. Further, the paper proposes and distinguishes between four foci of how the different types of artifacts are evaluated across cognitive, relational, social, and emotional beliefs. A theoretical model is developed that maps the different views of IT artifacts to the four distinct types of evaluations, and a number of propositions are presented

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

Digital user's decision journey

The landscape of the Internet is continually evolving. This creates huge opportunities for different industries to optimize vital channels online, resulting in various-forms of new Internet services. As a result, digital users are interacting with many digital systems and they are exhibiting dynamic behaviors. Their shopping behaviors are drastically different today than it used to be, with offline and online shopping interacting with each other. They have many channels to access online media but their consumption patterns on different channels are quite different. They do philanthropy online to help others but their heterogeneous motivations and different fundraising campaigns leads to distinct path-to-contribution. Understanding the digital user’s decision making process behind their dynamic behaviors is critical as they interact with various digital systems for the firms to improve user experience and improve their bottom line. In this thesis, I study digital users’ decision journeys and the corresponding digital technology firms’ strategies using inter-disciplinary approaches that combine econometrics, economic structural modeling and machine learning. The uncovered decision journey not only offer empirical managerial insights but also provide guideline for introducing intervention to better serve digital users