Distributing decision support systems on the WWW: the verification of a DSS metadata model

Gregg, Dawn G.; Goul, Michael; Philippakis, Andy

doi:10.1016/s0167-9236(01)00095-1

Cited by 18 publications

(2 citation statements)

References 25 publications

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“…Some research surveys the state of the art or the trends and potentials of decision technol-Figure 1. The comprehensive EBBSC framework (adapted from Wang & Forgionne, 2007) ogy mediated E-business (Eom, 1999;Papazoglou, 2001;Carlsson & Turban, 2002;Gregg & Philippakis, 2002;Shim et al, 2002;Ganguly & Gupta, 2004;Hayes & Finnegan, 2005;Bhargava et al, 2007;Valente & Mitra, 2007). Most researches agree that rapid advancements in data warehousing, OLAP, data mining, intelligent agents, and the web technology add new and powerful capabilities to decision making support systems.…”

Section: Background Review: the Evolution Of Intelligent Supportmentioning

confidence: 99%

Ebdmss

Wang

Lupton

Rawlinson

et al. 2010

International Journal of Decision Support System Technology

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This paper describes a Web-based intelligent decision making support system (DMSS) to deliver balanced scorecard (BSC) based modelling and analysis in support of strategic E-business management. This framework supports E-business managers during the strategy making process in a comprehensive, integrated, and continuous manner. The paper demonstrates how practitioners can use this system to deliver a wide range of embodied E-business strategy expertise in support of real-time decision making.

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Section: Background Review: the Evolution Of Intelligent Supportmentioning

confidence: 99%

Ebdmss

Wang

Lupton

Rawlinson

et al. 2010

International Journal of Decision Support System Technology

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show abstract

“…To minimize this cognitive burden, new capabilities are being developed such as intelligent agents that help the user in problem formulation and execution [Bui and Lee 1999;Sengupta and Bennett 2003;. Similarly, the cumbersome and monolithic structures of SDSS are being transformed into user-friendly and less resource-intensive systems [Gregg et al 2002;Gao and Sundaram 2007;Zhang and Goddard 2007]. In order to effectively make this transition, modularized and scalable architectures and a diverse set of technologies are needed.…”

Section: Introductionmentioning

confidence: 99%

Web-based Spatial Decision Support Systems (WebSDSS): Evolution, Architecture, Examples and Challenges

Sugumaran¹,

Sugumaran²

2007

CAIS

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Spatial Decision Support Systems (SDSS), which support spatial analysis and decision making, are currently receiving much attention. Research on SDSS originated from two distinct sources, namely, the GIS community and the DSS community. The synergy between these two research groups has lead to the adoption of state of the art technical solutions and the development of sophisticated SDSS that satisfy the needs of geographers and top-level decision makers. Recently, the Web has added a new dimension to SDSS and Web-based SDSS (WebSDSS) are being developed in a number of application domains. This article provides an overview of the emergence of SDSS, its architecture and applications, and discusses some of the enabling technologies and research challenges for future SDSS development and deployment.

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Synergizing the Artificial Intelligence and Decision Support Research Streams: Over a Decade of Progress with New Challenges on the Horizon

Nichols

Goul

Intelligent Decision-Making Support Systems

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Distributing decision support systems on the WWW: the verification of a DSS metadata model

Cited by 18 publications

References 25 publications

Ebdmss

Ebdmss

Web-based Spatial Decision Support Systems (WebSDSS): Evolution, Architecture, Examples and Challenges

Synergizing the Artificial Intelligence and Decision Support Research Streams: Over a Decade of Progress with New Challenges on the Horizon

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