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1、1Progress in Web-based decision support technologiesDecision Support Systems 43 (2007) 1083 1095Hemant K. Bhargava , Daniel J. Power , Daewon Sun Available online 8 August 2005授課老師：林娟娟 教授報告學生：簡子晴、李建翰2022/2/212Content Introduction Historical perspective The typologies of DSS Web-based decision suppor

2、t Web-enabled decision support Recent research in Web-based decision support Conclusions2IntroductionDSS(Decision Support System)l These systems support complex non-routine decisions.l Primary purpose to process data into informationl DSS systems are typically employed by tactical level management w

3、hose decisions and what-if analysis are less structured. l This information system not only presents the results but also expands the information with alternatives.l Some DSS methodologies Mathematical Modeling Simulation Queries What-If (OLAP-Cubes) Datamining3Introductionl Current DSS facilitate a

4、 wide variety of decision tasks: information gathering and analysis model building sensitivity analysis collaboration alternative evaluation decision implementation.l The growing Web, the on-going Web-based DSS such as health care, private companies, government, and education4Introductionl A Web-bas

5、ed DSS delivers decision support to a manager or business analyst using a “thin-client” Web browser interface (Java applets or JavaScript) since 1995 ( the discussion of the idea at the 3rd ISDSS in HK. )l This article expands and updates Bhargava and Powers 5 status report on DSS and Web technologi

6、es in 2001. Section2- a brief historical overview Section3- the extent to which Web technologies impact Section4- State of Practice Section5- State of Research52022/2/216Historical perspective62022/2/217Historical perspective72022/2/218The typologies of DSSl Implemented approaches data-driven DSShel

7、p managers organize, retrieve, and analyze large volumes of relevant data using database queries and OLAP techniques model-driven DSSuse formal representations of decision models and provide analytical support using the tools of decision analysis, optimization, stochastic modeling, simulation, stati

8、stics, and logic modelingl Web technologies Communication-driven DSS Knowledge-driven DSS document-driven DSS8Web-based decision supportl Decision technologies as services Web services Messaging protocols such as SOAP several XML-related languages applications for data interchange The prior articles

9、l Web-enablement of model-driven DSS (Bhargava and Krishnan 4)l Web-enabling DSS (cf., 15,16,3 8,43) l Web-enabled data-intensive applications (Fraternali 22)l geographic information systems tools (Coddington et al. 14)l optimization and alternative ways (Fourer and Goux 21)l using a company intrane

10、t (Sridhar 51)92022/2/2110Web-based decision supportl Relevant technologies (Bhargava and Krishnan 4) server-side implementationlCGI, Java applications, server-side scripting languages, Active Server pages, PHP, and Java server pagesclient-side implementationlscripting languages, Java applets, Activ

11、eX controls, and browser pluginsdistributed implementationlCORBA, COM+, Java RMI, and Enterprise Java Beans2022/2/2111Web-based decision supportl Web technologies and decision support tasks Application-specific DSS vs. DSS generators2022/2/2112Web-enabled decision supportl Web as media DSS Resources

12、、The OLAP Report、Data Warehousing Online (Decision support portals) Teradata University Network (teaching and learning resource related to data warehousing) IBM OSS COIN (similar portals)l Web as computer Digital product demonstrations (QuickTime movies or Shockwave animation) Previewing a decision

13、support product using online interactive (Lumina、TreeAge、HDS) On-line, Web-based Decision Support Systems (OptA、Grazing Systems)2022/2/2113Web-enabled decision support2022/2/2114Recent research in Web-based decision supportl Architectures and technologies Gregg et al. developed a DSS metadata model

14、for distributing decision support systems on the Web Bharati and Chaudhury conducted an empirical study to investigate customers satisfaction with a Web-based decision support system (system quality, information quality, and information presentation) Iyer et al. studied model management for decision

15、 support in a computing environment where enterprise data and models are distributed(VBE) Gu ntzer et al. proposed Structured Service Models that use a variant of structured modeling Zhang and Goddard applied Software Architectures to the design of Web-based DSS (3CoFramework-NADSS) Mitra and Valent

16、e provided an overview of Web-based optimization for model-driven decision support (ASP and e-Services)2022/2/2115Recent research in Web-based decision supportl Architectures and technologies Research indicatesl Web users need detailed information about DSS to organize and understand the available c

17、ontentl Systems should be designed to include constructs and artifacts that support delivery of high-quality informationl New approaches for model management are needed that facilitate storage, search, retrieval, matching, and composition from a library of decision models2022/2/2116Recent research i

18、n Web-based decision supportl Applications and implementations Kohli et al. reported a case study of a Web-based DSS for hospital management called Physician Profiling System (PPS) Ngai and Wat developed and implemented a Web-based DSS that used a model based on fuzzy set theory to perform risk anal

19、ysis for e-commerce development Dong et al. developed a Web-based DSS framework for portfolio selection (OLAP&PVM-WPSS) Sundarraj identified key issues in managing service contracts and developed a prototype that can support a managers planning process Ray reported a case study that demonstrates

20、 the implementation of Web-based decision support technologies (DelDOT) Liou et al. discussed the development and implementation of a Web-based Group DSS, Team-Spirit(GDSSs) Delen et al. developed a Web-based DSS, called Movie Forecast Guru, to help decision makers in the movie industry Others, Bart

21、on(SDM)、Walton(9/11)2022/2/2117Conclusionsl Web technologies provide Platform-independent Remote and distributed computation The exchange of complex multimedia informationl System maintenance is simplified and centralized letting end users focus on problem analysis and decision makingl Challenges Te

22、chnological challenges Economic challenges Social and behavioral challenges17ConclusionslWeb Technological challengesarchitectural modell random jumps in hyperspacel limitations cookies, embedding models or data within a Web page, using Java applet limitations of the Web browser HTTP, round-trip network delays, “pull” nature Further researchldetermi