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  • × author_ss:"Chan, H.C."
  • × year_i:[2000 TO 2010}
  1. Chan, H.C.; Kim, H.-W.; Tan, W.C.: Information systems citation patterns from International Conference on Information Systems articles (2006) 0.02 
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    Abstract
    Research patterns could enhance understanding of the Information Systems (IS) field. Citation analysis is the methodology commonly used to determine such research patterns. In this study, the citation methodology is applied to one of the top-ranked Information Systems conferences - International Conference on Information Systems (ICIS). Information is extracted from papers in the proceedings of ICIS 2000 to 2002. A total of 145 base articles and 4,226 citations are used. Research patterns are obtained using total citations, citations per journal or conference, and overlapping citations. We then provide the citation ranking of journals and conferences. We also examine the difference between the citation ranking in this study and the ranking of IS journals and IS conferences in other studies. Based on the comparison, we confirm that IS research is a multidisciplinary research area. We also identify the most cited papers and authors in the IS research area, and the organizations most active in producing papers in the top-rated IS conference. We discuss the findings and implications of the study.
    Date
    3. 1.2007 17:22:03
    Type
    a
  2. Chan, H.C.; Teo, H.H.; Zeng, X.H.: ¬An evaluation of novice end-user computing performance : data modeling, query writing, and comprehension (2005) 0.00 
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    Abstract
    End-user computing has become a weIl-established aspect of enterprise database systems today. End-user computing performance depends an the user-database interface, in which the data model and query language are major components. We examined three prominent data models-the relational model, the Extended-EntityRelationship (EIER) model, and the Object-Oriented (00) model-and their query languages in a rigorous and systematic experiment to evaluate their effects an novice end-user computing performance in the context of database design and data manipulation. In addition, relationships among the performances for different tasks (modeling, query writing, query comprehension) were postulated with the use of a cognitive model for the query process, and are tested in the experiment. Structural Equation Modeling (SEM) techniques were used to examine the multiple causal relationships simultaneously. The findings indicate that the EER and 00 models overwhelmingly outperformed the relational model in terms of accuracy for both database design and data manipulation. The associations between tasks suggest that data modeling techniques would enhance query writing correctness, and query writing ability would contribute to query comprehension. This study provides a better and thorough understanding of the inter-relationships among these data modeling and task factors. Our findings have significant implications for novice end-user training and development.
    Type
    a

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