Analyze Cognitive Process of Information Requirement Analysis
Huang, I. -Lin, Journal of Management Information and Decision Sciences
Information requirement analysis is the early phase of information systems development. During information requirement analysis, information analysts capture, understand, and translate users' information requirements into requirement specifications (Gibson & Conheeney, 1995; Huang, 2008). The resulting requirement specifications have at least three purposes: (1) facilitating an understanding of the intended system, (2) guiding the process of information system design, and (3) serving as a basis for all communications concerning the information system being developed (Hsia, Davis, & Kung, 1993; Schemer, 1987).
The correctness of requirement specifications is important for the success of an information system development project. An estimation showed that inaccurate requirement specifications might cost in excess of one hundred times what would have been required if the errors were discovered during information requirement analysis (Roman, April 1985; Shemer, 1987). A similar survey done by the Standish Group (1995) also showed that 31.1% of software projects in the United States were cancelled at some point during the development cycle; and inaccurate or incomplete requirement specifications were identified as the most important contributing cause. Therefore, how to specify correct requirement specifications is a critical issue for information requirement analysis.
Information requirement analysis is an error prone process, especially for novice information analysts. Empirical studies have shown that lack of knowledge is a major cause for novice information analysts making more errors in requirement specifications (Schenk, Vitalari, & Davis, 1998). Empirical studies have also shown that four characteristics of modeling behaviors that set expert and novice information analysts apart: model-based reasoning, mental simulation, critical testing of hypotheses, and analogical domain knowledge reuse (Sutcliffe & Maiden, 1990). However, it is unclear how the knowledge of information analysts may influence their modeling behaviors in information requirement analysis. Therefore, the research question of this research is "What is the cognitive process model of information requirement analysis that can explain how the differences of knowledge of information analysts may lead to different modeling behaviors?"
In this article, a cognitive process model of information requirement analysis is constructed on the basis of the structure-mapping model of analogy. On the basis of the cognitive process model of information requirement analysis, the interactions between the knowledge of information analysts and modeling behaviors are explained from the perspective of the dynamic process of information requirement analysis.
The remainder of this paper is organized as follows. First, this research will review the empirical studies related to the knowledge and modeling behaviors of information analysts. Then this research will discuss Gentner's structure-mapping model of analogy and explain why it is a good choice as a basis for modeling the cognitive process of information requirement analysis. Third, on the basis of the structure-building model of analogy, this research will propose a cognitive process model of information requirement analysis. Fourth, this research will use the proposed cognitive process model to explicate the differences between novice and expert information analysts in information requirement analysis. Fifth, this research will discuss the implications of the cognitive process model for research and practices in information requirement analysis. Finally, a conclusion will be made in the final section.
This section will first review the research studies concerning the influence of the knowledge of information analysts on the performance of information requirement analysis. Then, the review will discuss the literature on the differences of modeling behaviors between expert and novice information analysts. …