Sustainable knowledge-based decision support systems (DSS): perspectives, new challenges and recent advance
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2017-07-03Author
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Evolution of decision making and DSS. Evidence has clearly shown that excellent business performance can only be achieved based on the right decisions (Liu et al, 2013). The ability to make good decisions is the mark of successful and promotable business leaders and managers (Martinsons and Davison, 2007). Research on decision making can be traced back to preceding work in two main research streams: theoretical study of organisational decision making undertaken by Simon et al. at the Carnegie Institute of Technology during late 1950s and early 1960s (Simon, 1960), and technical work on interactive computer systems carried out by Gerrity et al. at the MIT in 1960s (Gerrity, 1971). Simon's three-stage human decision making process (i.e. intelligence, design and choice) is still one of the most widely cited decision models. However, Gerrity’s work has identified a key issue with human decision making, that is, the fact that there are many constraints on effective decision making, for example, with limited information and limited decision analysis ability. Along with the fast IT advancement over 1970s and 1980s, it has been widely recognised that computers could be used to overcome many human limitations. Subsequently, decision support systems (DSS), defined as an interactive computer-based system to support solving decision problems, have been developed and widely applied in real world decisions (Shim et al, 2002). DSS was considered to be one of the most popular research areas in information systems during 1980s. Most notably, DSS have evolved from supporting individual decisions to supporting groups and then to supporting organisation-wide decisions (Liu et al, 2009). In addition, the types of decisions that DSS are able to support extend from operational to strategic decision making (Martinsons and Davison, 2007). A number of review papers can be found which have embraced the DSS success over the time (Keen, 1987; Eom, 1999; Carlsson and Turban, 2002; Shim et al, 2002; Liu et al, 2010).
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