부산대학교 도서관

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jss.2016.03.046 Byline: Stephany Garcia, Oscar Romero, Ruth Raventos Abstract: Decision support systems (DSS) provide a unified analytical view of business data to better support decision-making processes. Such systems have shown a high level of user satisfaction and return on investment. However, several surveys stress the high failure rate of DSS projects. This problem results from setting the wrong requirements by approaching DSS in the same way as operational systems, whereas a specific approach is needed. Although this is well-known, there is still a surprising gap on how to address requirements engineering (RE) for DSS. To overcome this problem, we conducted a systematic mapping study to identify and classify the literature on DSS from an RE perspective. Twenty-seven primary studies that addressed the main stages of RE were selected, mapped, and classified into 39 models, 27 techniques, and 54 items of guidance. We have also identified a gap in the literature on how to design the DSS main constructs (typically, the data warehouse and data flows) in a methodological manner from the business needs. We believe this study will help practitioners better address the RE stages of DSS projects. Author Affiliation: Departament d'Enginyeria de Serveis i Sistemes d'Informacio (ESSI), Universitat Politecnica de Catalunya, BarcelonaTECH, Spain Article History: Received 12 May 2015; Revised 11 March 2016; Accepted 17 March 2016