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A model of student learning outcomes of information literacy instruction in a business school
This study presents and tests a research model of the outcomes of information literacy instruction (ILI) given to undergraduate business students. This model is based on expectation disconfirmation theory and insights garnered from a recent qualitative investigation of student learning outcomes from ILI given at three business schools. The model was tested through a web survey administered to 372 students. The model represents psychological, behavioral, and benefit outcomes as second-order molecular constructs. Results from a partial least squares (PLS) analysis reveal that expectation disconfirmation influences perceived quality and student satisfaction. These in turn affect student psychological outcomes. Further, psychological outcomes influence student behaviors, which in turn affect benefit outcomes. Based on the study's findings, several recommendations are made.
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Shaping the landscape of research in information systems from the perspective of editorial boards: A scientometric study of 77 leading journals
Characteristics of the Journal of the American Society for Information Science and Technology and 76 other journals listed in the InformationSystems category of the Journal Citation Reports?Science edition 2009 were analyzed. Besides reporting usual bibliographic indicators, we investigated the human cornerstone of any peer-reviewed journal: its editorial board. Demographic data about the 2,846 gatekeepers serving in information systems (IS) editorial boards were collected. We discuss various scientometric indicators supported by descriptive statistics. Our findings reflect the great variety of IS journals in terms of research output, author communities, editorial boards, and gatekeeper demographics (e.g., diversity in gender and location), seniority, authority, and degree of involvement in editorial boards. We believe that these results may help the general public and scholars (e.g., readers, authors, journal gatekeepers, policy makers) to revise and increase their knowledge of scholarly communication in the IS field. The EB_IS_2009 dataset supporting this scientometric study is released as online supplementary material to this article to foster further research on editorial boards.
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Dispositional resistance to change and hospital physicians' use of electronic medical records: A multidimensional perspective
Although electronic medical records (EMR) adoption by health care organizations has been widely studied, little is known about the determinants of EMR individual use by physicians after institutional adoption has taken place. In this study, the determinants of inpatient physicians' continuous use of EMR were studied. Four dimensions of EMR use were analyzed: use intensity, use extent, use frequency, and use scope. A web-based survey was administered to physicians at a large university hospital; respondents filled out a survey with questions relating to their EMR use, attitude, beliefs, work style, and dispositional resistance to change. Structural equation modeling was carried out to analyze the relationship between these factors. Physicians were found to differ substantially in the scope, extent, and intensity of their EMR use. Their attitude toward EMR use was associated with all use dimensions. Dispositional resistance to change was negatively related to perceived ease of use and with perceived usefulness both directly and through the mediation of compatibility with preferred work style. Time loss was negatively related to both perceived usefulness and attitude toward EMR use. Implications for research and practice are discussed.
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The large-scale structure of journal citation networks
We analyze the large-scale structure of the journal citation network built from information contained in the Thomson-Reuters Journal Citation Reports. To this end, we explore network properties such as density, percolation robustness, average and largest node distances, reciprocity, incoming and outgoing degree distributions, and assortative mixing by node degrees. We discover that the journal citation network is a dense, robust, small, and reciprocal world. Furthermore, in- and outdegree node distributions display long tails, with few vital journals and many trivial ones, and they are strongly positively correlated.
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An evaluation of classification models for question topic categorization
We study the problem of question topic classification using a very large real-world Community Question Answering (CQA) dataset from Yahoo! Answers. The dataset comprises 3.9 million questions and these questions are organized into more than 1,000 categories in a hierarchy. To the best knowledge, this is the first systematic evaluation of the performance of different classification methods on question topic classification as well as short texts. Specifically, we empirically evaluate the following in classifying questions into CQA categories: (a) the usefulness of n-gram features and bag-of-word features; (b) the performance of three standard classification algorithms (naive Bayes, maximum entropy, and support vector machines); (c) the performance of the state-of-the-art hierarchical classification algorithms; (d) the effect of training data size on performance; and (e) the effectiveness of the different components of CQA data, including subject, content, asker, and the best answer. The experimental results show what aspects are important for question topic classification in terms of both effectiveness and efficiency. We believe that the experimental findings from this study will be useful in real-world classification problems.
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