Decision Support System

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A Decision Support System is a computer-based information system that supports a decision support task.



References

2015

  • (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/decision_support_system#Taxonomies Retrieved:2015-7-20.
    • Using the relationship with the user as the criterion, Haettenschwiler[1] differentiates passive, active, and cooperative DSS. A passive DSS is a system that aids the process of decision making, but that cannot bring out explicit decision suggestions or solutions. An active DSS can bring out such decision suggestions or solutions. A cooperative DSS allows the decision maker (or its advisor) to modify, complete, or refine the decision suggestions provided by the system, before sending them back to the system for validation. The system again improves, completes, and refines the suggestions of the decision maker and sends them back to them for validation. The whole process then starts again, until a consolidated solution is generated.

      Another taxonomy for DSS has been created by Daniel Power. Using the mode of assistance as the criterion, Power differentiates communication-driven DSS, data-driven DSS, document-driven DSS, knowledge-driven DSS, and model-driven DSS.[2]

      • A communication-driven DSS supports more than one person working on a shared task; examples include integrated tools like Google Docs or Groove[3]
      • A data-driven DSS or data-oriented DSS emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.
      • A document-driven DSS manages, retrieves, and manipulates unstructured information in a variety of electronic formats.
      • A knowledge-driven DSS provides specialized problem-solving expertise stored as facts, rules, procedures, or in similar structures.[2]
      • A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data-intensive. Dicodess is an example of an open source model-driven DSS generator.[4]
    • Using scope as the criterion, Power[5] differentiates enterprise-wide DSS and desktop DSS. An enterprise-wide DSS is linked to large data warehouses and serves many managers in the company. A desktop, single-user DSS is a small system that runs on an individual manager's PC.

2014

2013

  • http://en.wikipedia.org/wiki/Decision_support_system#Taxonomies
    • As with the definition, there is no universally accepted taxonomy of DSS either. Different authors propose different classifications. Using the relationship with the user as the criterion, Haettenschwiler[1] differentiates passive, active, and cooperative DSS. A passive DSS is a system that aids the process of decision making, but that cannot bring out explicit decision suggestions or solutions. An active DSS can bring out such decision suggestions or solutions. A cooperative DSS allows the decision maker (or its advisor) to modify, complete, or refine the decision suggestions provided by the system, before sending them back to the system for validation. The system again improves, completes, and refines the suggestions of the decision maker and sends them back to him for validation. The whole process then starts again, until a consolidated solution is generated.

      Another taxonomy for DSS has been created by Daniel Power. Using the mode of assistance as the criterion, Power differentiates communication-driven DSS, data-driven DSS, document-driven DSS, knowledge-driven DSS, and model-driven DSS.[2]

      • A communication-driven DSS supports more than one person working on a shared task; examples include integrated tools like Microsoft's NetMeeting or Groove[6]
      • A data-driven DSS or data-oriented DSS emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.
      • A document-driven DSS manages, retrieves, and manipulates unstructured information in a variety of electronic formats.
      • A knowledge-driven DSS provides specialized problem-solving expertise stored as facts, rules, procedures, or in similar structures.[2]
      • A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation; they are not necessarily data-intensive. Dicodess is an example of an open source model-driven DSS generator.[7]
  1. 1.0 1.1 Haettenschwiler, P. (1999). Neues anwenderfreundliches Konzept der Entscheidungsunterstützung. Gutes Entscheiden in Wirtschaft, Politik und Gesellschaft. Zurich, vdf Hochschulverlag AG: 189-208. Cite error: Invalid <ref> tag; name "Haettenschwiler 1999" defined multiple times with different content
  2. 2.0 2.1 2.2 2.3 Power, D. J. (2002). Decision support systems: concepts and resources for managers. Westport, Conn., Quorum Books.
  3. Stanhope, P. (2002). Get in the Groove: building tools and peer-to-peer solutions with the Groove platform. New York, Hungry Minds
  4. Gachet, A. (2004). Building Model-Driven Decision Support Systems with Dicodess. Zurich, VDF.
  5. Power, D. J. (1996). What is a DSS? The On-Line Executive Journal for Data-Intensive Decision Support 1(3).
  6. Stanhope, P. (2002). Get in the Groove: building tools and peer-to-peer solutions with the Groove platform. New York, Hungry Minds
  7. Gachet, A. (2004). Building Model-Driven Decision Support Systems with Dicodess. Zurich, VDF.


  • http://en.wikipedia.org/wiki/Decision_support_system
    • A Decision Support System (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization (usually mid and higher management) and help to make decisions, which may be rapidly changing and not easily specified in advance (Unstructured and Semi-Structured decision problems). Decision support systems can be either fully computerized, human or a combination of both.

      The term DSS is difficult to define. In fact, DSS was defined differently according to the authors.The controversy seems more clear between academics and DSS users. While academics have perceived DSS as a tool to support decision making process, DSS users see DSS as a tool to facilitiate organizational processes.[1] Moreover, some authors have extended the definition of DSS to include any system that might support decision making.[2] In order to overcome this difficulty in the definition of DSS, Sprague (1980) recommends to define DSS by its characteristics, as following:

      1. DSS tends to be aimed at the less well structured, underspecified problem that upper level managers typically face;
      2. DSS attempts to combine the use of models or analytic techniques with traditional data access and retrieval functions;
      3. DSS specifically focuses on features which make them easy to use by noncomputer people in an interactive mode; and
      4. DSS emphasizes flexibility and adaptability to accommodate changes in the environment and the decision making approach of the user.
    • DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, and personal knowledge, or business models to identify and solve problems and make decisions.

      Typical information that a decision support application might gather and present includes: *inventories of information assets (including legacy and relational data sources, cubes, data warehouses, and data marts), *comparative sales figures between one period and the next, *projected revenue figures based on product sales assumptions.

  1. Keen, Peter; (1980),"Decision support systems : a research perspective."Cambridge, Mass. : Center for Information Systems Research, Afred P. Sloan School of Management.http://hdl.handle.net/1721.1/47172
  2. Sprague, R;(1980). “A Framework or the Development of Decision Support Systems.” MIS Quarterly. Vol. 4, No. 4, pp.1-25.

1998

  • Ghodsypour, Seyed Hassan, and Christopher O'Brien. "A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming." International journal of production economics 56 (1998): 199-212.