Author(s):  
Songnian Li

The rapidly expanding range of Web technology has made it possible to collaboratively make decisions over the Web. This chapter examines some of these Web technologies important to the development of collaborative spatial decision support systems, and identifies their technology impediments and strengths. The outcomes provide a basis for discussing how the existing collaborative spatial decision support systems may be redesigned to take advantage of new Web technologies, and how new collaborative spatial decision support systems may be designed and developed in this Web-based paradigm. Some discussions on selected design and development issues that are important to the development of collaborative spatial decision support systems including system design, user’s impact, and performance are presented.


1998 ◽  
Vol 41 (3) ◽  
pp. 71-78 ◽  
Author(s):  
Robert M. O'Keefe ◽  
Tim McEachern

2007 ◽  
Vol 43 (4) ◽  
pp. 1081-1082
Author(s):  
Hemant K. Bhargava ◽  
Daniel J. Power ◽  
Daewon Sun

2004 ◽  
Vol 37 (3) ◽  
pp. 367-376 ◽  
Author(s):  
Jichang Dong ◽  
Helen S. Du ◽  
Shouyang Wang ◽  
Kang Chen ◽  
Xiaotie Deng

2014 ◽  
Vol 8 (3) ◽  
pp. 1364-1371
Author(s):  
Mohammed A. I. Ayoub

Web-based decision support systems are increasingly used over the past years. However, few studies have been conducted on evaluation of web-based decision support systems especially in the field of online shopping. This paper attempts to explore the critical success factors that influence decision making satisfaction in online shopping context by providing a conceptual model for this purpose. Although there are various factors which contribute in making online shopping decisions but this study focuses on five factors i.e. web site quality, data quality, knowledge management, decision making satisfaction, and perceived net benefit. Also, this research will use existing models that explain and predict information systems success. However, these success models need to be updated to recurrent industry developments since the updating existing IS success models, a better understanding of web-based DSS practitioner success can be achieved.


Author(s):  
Ramanathan Sugumaran ◽  
Shriram Ilavajhala ◽  
Vijayan Sugumaran

A SDSS combines database storage technologies, geographic information systems (GIS) and decision modeling into tools which can be used to address a wide variety of decision support areas (Eklund, Kirkby, and Pollitt, 1996). Recently, various emerging technologies in computer hardware and software such as speedy microprocessors, gigabit network connections, fast internet mapping servers along with Web-based technologies like extensible markup language (XML), Web services, etc provide promising opportunities to take the traditional spatial decision support systems one step further to provide easy-to-use, round-the-clock access to spatial data and decision support over the Web. Traditional DSS and Web-based spatial DSS can be further improved by integrating expert knowledge and utilizing intelligent software components (such as expert systems and intelligent agents) to emulate the human intelligence and decision making. These kinds of decision support systems are classified as intelligent decision support systems. The objective of this chapter is to discuss the development of an intelligent web-based spatial decision support system and demonstrate it with a case study for planning snow removal operations.


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