A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit <a rel="external noopener" href="https://upcommons.upc.edu/bitstream/handle/2117/89442/RE4DSS_revised%20document%202.3_PREPRINT-1.pdf;jsessionid=189B2D9278FFB9DC898545D8513CFB27?sequence=6">the original URL</a>. The file type is <code>application/pdf</code>.
DSS from an RE Perspective: A systematic mapping
<span title="">2016</span>
<i title="Elsevier BV">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kqzhqyka2ffqdlbon77fd6trwm" style="color: black;">Journal of Systems and Software</a>
</i>
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
<span class="external-identifiers">
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jss.2016.03.046">doi:10.1016/j.jss.2016.03.046</a>
<a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pqcpxlceqna5xospezrxq2ttki">fatcat:pqcpxlceqna5xospezrxq2ttki</a>
</span>
more »
... 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.
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190430223121/https://upcommons.upc.edu/bitstream/handle/2117/89442/RE4DSS_revised%20document%202.3_PREPRINT-1.pdf;jsessionid=189B2D9278FFB9DC898545D8513CFB27?sequence=6" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext">
<button class="ui simple right pointing dropdown compact black labeled icon button serp-button">
<i class="icon ia-icon"></i>
Web Archive
[PDF]
<div class="menu fulltext-thumbnail">
<img src="https://blobs.fatcat.wiki/thumbnail/pdf/57/23/572397f292142f3d3e141c9f6c1c86fe1a55de36.180px.jpg" alt="fulltext thumbnail" loading="lazy">
</div>
</button>
</a>
<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jss.2016.03.046">
<button class="ui left aligned compact blue labeled icon button serp-button">
<i class="external alternate icon"></i>
elsevier.com
</button>
</a>