Personal Information Management (PIM) research has primarily focused on how users manage information items that are in their local collection, under their control. This investigation will broadly study PIM, additionally looking at items that users decide not to acquire, and seeks to identify factors that influence the leaving, acquiring, and retaining behavior. A theoretical framework developed for the study introduces the hoarding literature into the Personal Information Management (PIM) domain. The study uses a multiple-embedded case study design to naturalistically study students' PIM within the context of a college course.

This paper provides a critical review to analyze the promises and important challenges of studying flow, a psychological state, in the computer-mediated environments (CME). Despite the strong interest in IS, HCI, Marketing, Education, and other research disciplines over more than a decade, adapting the phenomenon of flow to computer users shows high inconsistencies and discrepancies in the literature. In addition, few studies attempt to provide a coherent picture of the area. Based on a careful examination of the literature, we identify both conceptual and methodological challenges faced when studying flow in CME. Although not all challenges are resolved, we point out directions and possible solutions for some challenges and call for more studies in this promising area. The paper further discusses implications for research in human computing behavior in general and in flow in particular. It cautions researchers to examine hidden assumptions of theories in other disciplines before applying them to address IT related issues and concerns.

Metadata provides a higher-level description of digital library resources and serves as a searchable record for browsing and accessing digital library content. However, manually assigning metadata is a resource-consuming task for which Natural Language Processing (NLP) can provide a solution. This poster coalesces the findings from research and development accomplished across two multi-year digital library metadata generation and evaluation projects and suggests how the lessons learned might benefit digital libraries with the need for high-quality, but efficient metadata assignment for their resources.

Flow theory has been applied to computer-mediated environments to study positive user experiences such as increased exploratory behavior, communication, learning, positive affect, and computer use. However, a review of the existing flow studies in computer-mediated environments in Psychology, Consumer Behavior, Communications, Human-Computer Interaction, and Management Information Systems shows ambiguities in the conceptualization of flow constructs and inconsistency in the flow models. It thus raises the question of whether the direct adoption of traditional flow theory is appropriate without a careful reconceptualization to consider the uniqueness of the computer-mediated environments. This paper focuses on flow antecedents and identifies the importance of separating the task from the artefact within a computer-mediated environment. It proposes a component-based model that consists of person (P), artefact (A), and task (T), as well as the interactions of these components. The model, named the PAT model, is developed by understanding the original flow theory, reviewing existing empirical flow studies within computer-mediated environments, and analyzing the characteristics of computer-mediated environments. A set of propositions is constructed to demonstrate the predictive power of the model.

Flow theory has been borrowed from psychology to address positive user experiences with personal computers, and more recently, the Internet. The flow experience has been correlated to increased exploratory behavior, communication, learning, positive affect, and computer use. This paper reviews the flow studies within computer-mediated environments to gain a more coherent understanding. The authors identify ambiguities in the conceptualization of flow, challenges in the operationalization of flow constructs, and difficulties in data collection.