Progress in Web-based decision support technologies

1. Progress in Web-based decision support technologies Dan J. Kim, Donald L. Ferrin, H. Raghav Rao Source : Decision Support System Presenter: Yu-Ming, Huang Date: 2009/10/01 (四)

2. Abstract WWW technologies have transformed the design, development, implementation and deployment of decision support systems.

3. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

4. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

5. 1. Introduction • Modern DSS provide their users with a broad range of capabilities. • Information gathering and analysis • Model building • Sensitivity analysis • Collaboration • Decision implementation • This surveys the progress in implementing Web-based decision support technologies by examining both academic research and industry practice.

6. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

7. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

8. 2. Historical perspective

9. 2. Historical perspective

10. 2. Historical perspective

11. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

12. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

13. 3. Web-based decision support • The two most widely implemented approach for delivering DSS are • Data-driven DSS • Database queries • OLAP techniques • Data Mining • Model-driven DSS • Decision analysis • Optimization • Simulation • Statistics

14. 3. Web-based decision support • The three other types of DSS have become more widespread and sophisticated because of Web technologies. • Communication-driven DSS • Rely on electronic communication technologies to link multiple decision makers. • Knowledge-driven DSS • Can suggest or recommend actions to managers. • Document-driven DSS • Integrate a variety of storage and processing technologies to provide managers document retrieval and analysis.

15. 3. Web-based decision support • Decision technologies as services • Web technologies can be classified in terms of those technologies that enable • server-side implementation • CGI, Java applications, server-side scripting languages, Active Server pages, PHP, and Java server pages • client-side implementation • scripting languages, Java applets, ActiveX controls, and browser plugins • distributed implementation • CORBA, COM+, Java RMI, and Enterprise Java Beans • Computing technologies create many possibilities for changing the way DSS are developed, deployed, and used.

16. 3. Web-based decision support • Decision technologies as services • Related articles discussed • technologies Web-enablement of model-driven DSS. • technologies for developing Web-enabled data-intensive applications. • Web technologies in the context of DSS based on geographic information systems tools. • the concept of optimization as an Internet service and reviewed various alternative ways of delivering such computation. • emphasized decision support using company intranet.

17. 3. Web-based decision support • Web technologies and decision support tasks • Application-specific DSS vs. DSS generators

18. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

19. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

20. 4. Web-enable decision support • Web as media • DSSResources.com, The OLAP Report , DataWarehousing Online • are decision support portals that offer information about software products, vendors, methodologies in the context of DSS technologies. • Teradata University Network • is a vendor supported teaching and learning resource related to data warehousing, DSS/BI, and database classes.

21. 4. Web-enable decision support • Web as computer • Digital product demonstrations • Previewing a decision support product using online interactive examples • On line, Web-based DSS • OptAmaze.com, Grazing Systems

22. 4. Web-enable decision support • Web as computer

23. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

24. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

25. 5. Recent research in Web-based decision support Architecture and technologies

26. 5. Recent research in Web-based decision support Architecture and technologies

27. 5. Recent research in Web-based decision support Applications and implementations

28. 5. Recent research in Web-based decision support Applications and implementations

29. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

30. Outline • Introduction • Historical perspective • Web-based decision support • Web-enabled decision support • Recent research in Web-based decision support • Conclusion

31. 6. Conclusions • The practice of building DSS can benefit in many ways from the increased availability and growing sophistication of Web technologies. • While there is significant promise in the idea of web-based DSS, there are also some important challenges that must be overcome. • Technological challenges • Economic challenges • Social and behavioral challenges

32. 6. Conclusions • Technological challenges • The basic Web architectural model was designed for random jumps in hyperspace. • Network delays • Further researchis needed to • determine guidelines for the use of alternative technologies for Web-based computation. • Understand what technologies may be most effective for different aspects of Web-based decision support.

33. 6. Conclusions • Economic challenges • Only a few firms offering decision computation applications have well-defined revenue models. • optAmaze.com • Used a subscription-based model for its trim optimization service, charging differential prices based on the number of machines optimized. • salesforce.com • Enables subscribers to enter their sales data using an Internet browser and share the data and analysis with other authorized users.

34. 6. Conclusions • Social and behavioral challenges • Users • professional usersV.Scasual, infrequent users • More studies focus on adoption, utilization and performance. • Researches need to learn more about increasing the satisfaction of non-managerial DSS users. • Stand-alone DSS are becoming much less useful.

35. Review Historical perspective Web-based decision support Web-enabled decision support Recent Researches Three challenges

36. Thanks for your listening