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This paper reviews the main studies on transit users’ route choice in thecontext of transit assignment. The studies are categorized into three groups: static transit assignment, within-day dynamic transit assignment, and emerging approaches. The motivations and behavioural assumptions of these approaches are re-examined. The first group includes shortest-path heuristics in all-or-nothing assignment, random utility maximization route-choice models in stochastic assignment, and user equilibrium based assignment. The second group covers within-day dynamics in transit users’ route choice, transit network formulations, and dynamic transit assignment. The third group introduces the emerging studies on behavioural complexities, day-to-day dynamics, and real-time dynamics in transit users’ route choice. Future research directions are also discussed.

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User-Web interactions have emerged as an important area of research in the field of information science. In this study, we investigate the effects of users’ cognitive styles on their Web navigational styles and information processing strategies. We report results from the analyses of 594 minutes recorded Web search sessions of 18 participants engaged in 54 scenario-based search tasks. We use questionnaires, cognitive style test, Web session logs and think-aloud as the data collection instruments. We classify users’ cognitive styles as verbalisers and imagers based on Riding’s (1991) Cognitive Style Analysis test. Two classifications of navigational styles and three categories of information processing strategies are identified. Our study findings show that there exist relationships between users’ cognitive style, and their navigational styles and information processing strategies. Verbal users seem to display sporadic navigational styles, and adopt a scanning strategy to understand the content of the search result page, while imagery users follow a structured navigational style and reading approach. We develop a matrix and a model that depicts the relationships between users’ cognitive styles, and their navigational style and information processing strategies. We discuss how the findings from this study could help search engine designers to provide an adaptive navigation support to users.

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User-Web interactions have emerged as an important research in the field of information science. In this study, we examine extensively the Web searching performed by general users. Our goal is to investigate the effects of users’ cognitive styles on their Web search behavior in relation to two broad components: Information Searching and Information Processing Approaches. We use questionnaires, a measure of cognitive style, Web session logs and think-aloud as the data collection instruments. Our study findings show wholistic Web users tend to adopt a top-down approach to Web searching, where the users searched for a generic topic, and then reformulate their queries to search for specific information. They tend to prefer reading to process information. Analytic users tend to prefer a bottom-up approach to information searching and they process information by scanning search result pages.

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Many researchers have investigated and modelled aspects of Web searching. A number of studies have explored the relationships between individual differences and Web searching. However, limited studies have explored the role of users’ cognitive styles in determining Web searching behaviour. Current models of Web searching have limited consideration of users’ cognitive styles. The impact of users’ cognitive style on Web searching and their relationships are little understood or represented. Individuals differ in their information processing approaches and the way they represent information, thus affecting their performance. To create better models of Web searching we need to understand more about user’s cognitive style and their Web search behaviour, and the relationship between them. More rigorous research is needed in using more complex and meaningful measures of relevance; across a range of different types of search tasks and different populations of Internet users. The project further explores the relationships between the users’ cognitive style and their Web searching. The project will develop a model depicting the relationships between a user’s cognitive style and their Web searching. The related literature, aims and objectives and research design are discussed.

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Information behavior studies in the field of Library and Information Science (LIS) generally focus on one of many aspects of information behavior: information finding, information organizing, and information using. Information seeking is further specialized into information searching, information seeking, information foraging or information sense making. Spink and Cole (2006) highlighted the lack of integration across these various approaches and models of information behavior within LIS. Often, each approach provides a different language for similar processes (Spink & Cole, 2004), and it is sometimes hard for practicing information professionals to parse the various theories and models to see how they shape and affect the provision of information resources, services, and products. An integrated model of information behaviors that explains the key dimensions of how peoples’ contextual and situational dimensions affect their information needs and behavior will help information providers and LIS researchers alike with a framework that can help “depict and explain a sequence of behaviors by referring to relevant variables, rather than merely indicating a sequence of events… while indicating something about information needs and sources” (Case, 2002). This presentation presents an integrated model of peoples’ information behaviors based on research that studied participants’ information behaviors through a detailed daily information journal maintained for two weeks.

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Background Outcome expectancies are a key cognitive construct in the etiology, assessment and treatment of Substance Use Disorders. There is a research and clinical need for a cannabis expectancy measure validated in a clinical sample of cannabis users. Method The Cannabis Expectancy Questionnaire (CEQ) was subjected to exploratory (n = 501, mean age 27.45, 78% male) and confirmatory (n = 505, mean age 27.69, 78% male) factor analysis in two separate samples of cannabis users attending an outpatient cannabis treatment program. Weekly cannabis consumption was clinically assessed and patients completed the Severity of Dependence Scale-Cannabis (SDS-C) and the General Health Questionnaire (GHQ-28). Results Two factors representing Negative Cannabis Expectancies and Positive Cannabis Expectancies were identified. These provided a robust statistical and conceptual fit for the data. Internal reliabilities were high. Negative expectancies were associated with greater dependence severity (as measured by the SDS) and positive expectancies with higher consumption. The interaction of positive and negative expectancies was consistently significantly associated with self-reported functioning across all four GHQ-28 scales (Somatic Concerns, Anxiety, Social Dysfunction and Depression). Specifically, within the context of high positive cannabis expectancy, higher negative expectancy was predictive of more impaired functioning. By contrast, within the context of low positive cannabis expectancy, higher negative expectancy was predictive of better functioning. Conclusions The CEQ is the first cannabis expectancy measure to be validated in a sample of cannabis users in treatment. Negative and positive cannabis expectancy domains were uniquely associated with consumption, dependence severity and self-reported mental health functioning.

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This paper investigated the phenomenon of prejudice among ISD project members. We presented a theoretical discussion followed by one qualitative and one quantitative study. In the qualitative study, we interviewed different members of the project teams to understand the different types of prejudice possessed by team members. Results of this interview study led to the development of prejudice scales for IT members and users, which was used in the quantitative study. We surveyed 128 ISD teams and found that prejudice was related task and relationship conflict, satisfaction and willingness to work together in the future. Furthermore, prejudice exerts stronger influences on users than IT members in terms of increasing task and relationship conflicts and decreasing goal commitment.

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Comparison are required to understand transport benefits of Transit Oriented Developments (TODs). Mode shares of TOD users need to be understood. Accurate travel demand models for TODs are needed.

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Transit Oriented Developments (TODs) are often designed to promote the use of sustainable modes of transport and reduce car usage. This paper investigates the effect of personal and transit characteristics on travel choices of TOD users. Binary logistic regression models were developed to determine the probability of choosing sustainable modes of transport including walking, cycling and public transport. Kelvin Grove Urban Village (KGUV) located in Brisbane, Australia was chosen as case study TOD. The modal splits for employees, students, shoppers and residents showed that 47% of employees, 84% of students, 71% of shoppers and 56% of residents used sustainable modes of transport.

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[Selection of papers from the Older Road User Safety Symposium, 26 November 2000, Brisbane, Australia.]----- This publication is a selection of papers on older road user safety which were presented at the Older Road User Safety Symposium on Sunday 26 November 2000 at the Sheraton Brisbane Hotel, Queensland, Australia. The Symposium was held on the day before Australia’s annual Road Safety Research, Policing and Education Conference, which provided an opportunity to garner both presenters and participants from the wider road safety community in Australia. Road safety is a large and diverse area of scholarship and practice, and many disciplines are drawn on in the processes of understanding and addressing road safety problems. The safety of older road users is no different. As this selection shows, work on older road user safety can be informed by demography, research on the mental and physical effects of ageing, social research on older people as road users, evaluation of educational and behavioural interventions, road crash analysis, engineering research and practice, and reviews of policy approaches within Australia and elsewhere. It is possible to summarise these into four constellations, which are reflected in the papers selected for this publication: social impacts and responses; physical and cognitive capability; specific road use performance; and environment/ecology. Though three years have passed since the Symposium, the issues raised in these papers remain current.

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Social tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.

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Item folksonomy or tag information is a kind of typical and prevalent web 2.0 information. Item folksonmy contains rich opinion information of users on item classifications and descriptions. It can be used as another important information source to conduct opinion mining. On the other hand, each item is associated with taxonomy information that reflects the viewpoints of experts. In this paper, we propose to mine for users’ opinions on items based on item taxonomy developed by experts and folksonomy contributed by users. In addition, we explore how to make personalized item recommendations based on users’ opinions. The experiments conducted on real word datasets collected from Amazon.com and CiteULike demonstrated the effectiveness of the proposed approaches.