scholarly journals Experiences in Building and Using Decision Support Systems in Postgraduate University Courses

10.28945/3084 ◽  
2007 ◽  
Author(s):  
Arthur Tatnall ◽  
Stephen Burgess
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Visual Basic ◽  
University Courses ◽  
Visual Basic For Applications ◽  
The Cost ◽  
Simple Systems

In this paper we will relate some of our experiences in building and using simple Decision Support Systems (DSS) for use in two postgraduate subjects at Victoria University in Melbourne. These subjects are not about Decision Support Systems, but are Information Systems (IS) subjects that introduce, amongst other things, concepts of decision support and DSS. It has been our experience that the complexity, an inability to examine the logic behind decisions that have been recommended, the proprietary nature and the cost of commercial DSS make their use in teaching less than ideal. Our solution was to produce our own simple systems using Excel, Visual Basic and Visual Basic for Applications, and this has proved to be quite successful. The paper reports on building and using Decision Support Systems in this way.

scholarly journals The Effect of Perceived Factors of Decision Support Systems on Actual Usage: Behavioral Intention of Using Decision Support Systems as a Mediating Variable: “An Empirical Study of Jordanian Higher Education Institutions”

2016 ◽  
Vol 12 (1) ◽  
pp. 201
Author(s):  
Bilal Mohammed Salem Al-Momani
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Behavioral Intention ◽  
Support Systems ◽  
Higher Education Institutions ◽  
Quality Of Information

Decision support systems (DSS) are interactive computer-based systems that provide information, modeling, and manipulation of data. DSS are clearly knowledge-based information systems to capture, Processing and analysis of information affecting or aims to influence the decision making process, performed by people in scope professional job appointed by a user. Hence, this study describes briefly the key concepts of decision support systems such as perceived factors with a focus on quality  of information systems and quality of information variables, behavioral intention of using DSS, and actual DSS use by adopting and extending the technology acceptance model (TAM) of Davis (1989); and Davis, Bagozzi and Warshaw (1989).There are two main goals, which stimulate the study. The first goal is to combine Perceived DSS factors and behavioral intention to use DSS from both the social perspective and a technology perspective with regard to actual DSS usage, and an experimental test of relations provide strategic locations to organizations and providing indicators that should help them manage their DSS effectiveness. Managers face the dilemma in choosing and focusing on most important factors which contributing to the positive behavioral intention of use DSS by the decision makers, which, in turn, could contribute positively in the actual DSS usage by them and other users to effectively solve organizational problems. Hence, this study presents a model which should provide the useful tool for top management in the higher education institutions- in particular-to understand the factors that determine using behaviors for designing proactive interventions and to motivate the acceptance of TAM in order to use the DSS in a way that contributes to the higher education decision-making plan and IT policy.To accomplish or attain the above mentioned objectives, the researcher developed a research instrument (questionnaire) and distributed it amongst the higher education institutions in Jordan to collect data in order to empirically study hypothesis testing (related to the objectives of study). 341 questionnaires were returned from the study respondents. Data were analyzed by utilizing both SPSS (conducted descriptive analysis) and AMOS (conducting structural equation modelling).Findings of the study indicate that some hypotheses were supported while the others were not. Contributions of the study were presented. In addition, the researcher presented some recommendations. Finally, this study has identified opportunities for further study which has progressed greatly advanced understanding constantly of DSS usage, that can help formulate powerful strategies Involving differentiation between DSS perceived factors.

Overview of Decision Support Systems Applied to Construction

2016 ◽  
pp. 77-94
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Markov Decision Processes ◽  
Support Systems ◽  
Decision Processes ◽  
Rule Based ◽  
Markov Decision ◽  
Knowledge Intensive ◽  
The Cost ◽  
Rule Based Systems

The domain of construction is a very knowledge-intensive domain with so many factors involved. This implies undertaking any action requires an understanding of the different factors and how best to combine them to achieve a favourable and optimal outcome. Thus decision-making has been extensively used in the domain of construction. The aim of this chapter is to undertake a review of various decision support systems and to provide insights into their applications in the domain of construction. Specifically, the principle of cost index, sub-work chaining diagram method, linear regression and cost over-runs in time-overrun context (CCOTOV) model and Markov decision processes (MDP), ontology and rule-based systems have been reviewed. Based on the review the Markov decision processes (MDP), ontology and rule-based systems were chosen as the more suitable for the cost control case considered in this study.

DSS and Multiple Perspectives of Complex Problems

2011 ◽  
pp. 286-295 ◽  
Author(s):  
David Paradice ◽  
Robert A. Davis
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Collaborative Work ◽  
Vantage Point ◽  
Decision Makers ◽  
Complex Problems ◽  
Knowledge Based ◽  
Spreadsheet Models

Decision support systems have always had a goal of supporting decision-makers. Over time, DSS have taken many forms, or many forms of computer-based support have been considered in the context of DSS, depending on one’s particular perspective. Regardless, there have been decision support systems (DSS), expert systems, executive information systems, group DSS (GDSS), group support systems (GSS), collaborative systems (or computer-supported collaborative work (CSCW) environments), knowledge-based systems, and inquiring systems, all of which are described elsewhere in this encyclopedia. The progression of decision support system types that have emerged follows to some degree the increasing complexity of the problems being addressed. Some of the early DSS involved single decision-makers utilizing spreadsheet models to solve problems. Such an approach would be inadequate in addressing complex problems because one aspect of problem complexity is that multiple stakeholders typically exist. Baldwin (1993) examined the need for supporting multiple views and provides the only attempt found in the information systems literature to operationalize the concept of a perspective. In his work, a view is defined as a set of beliefs that partially describe a general subject of discourse. He identified three major components of a view: the belief or notion to convey, a language to represent the notion, and a subject of discourse. He further described notions as comprising aspects and a vantage point. Aspects are the characteristics or attributes of a subject or situation that a particular notion emphasizes. A vantage point is described by the level of detail (i.e., overview or detailed analysis). Assuming the subject of discourse can be identified with the notion, Baldwin described how differences in views may occur via differences in the notion, the language, or both.

scholarly journals Measuring How Decision Support Systems Improve Newsvendors’ Performance: The Subjects’ Version

2021 ◽  
Vol 13 (18) ◽  
pp. 10251
Author(s):  
Diego D’Urso ◽  
Ferdinando Chiacchio ◽  
Evangelia Demerouti
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Weather Conditions ◽  
Ex Post ◽  
Human Experiments ◽  
Business Game ◽  
Order Quantities

Despite the emerging contribution of machine automation, artificial intelligence and information systems, humans remain yet the most fragile ring of any organization. Decision support systems are widespread, supporting us to decide among uncertainties, such as weather conditions, suppliers’ performances and financial opportunities, but how humans take into account this information and, most of all, how they trust their own management knowledge is a controversial issue. This paper assesses, by means of a controlled experiment and ex post interviews, how individuals consider and use decision support systems in the context of the Newsvendor Problem. In accordance with prior research, the results show that individuals’ order quantities are pull-to-center biased. Moreover, ex post direct interviews suggest that (i) the individuals’ trust in decision support systems is not blind; (ii) individuals do not play the business game as a real task, (iii) they are biased by the type of incentive promised and (iv) they seem not skilled or trained enough. Ex post interviews shed a new light on controlled human experiments: they should be better analyzed and re-engineered.

E-Planning

2012 ◽  
Vol 1 (1) ◽  
pp. 1-4 ◽  
Author(s):  
Richard E. Klosterman
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Decision Support Systems ◽  
Information And Communication Technologies ◽  
Support Systems ◽  
Communication Technologies ◽  
Geographic Information ◽  
Research And Practice ◽  
Information And Communication

This paper reflects on where e-planning has been and speculates on its future. It begins by briefly reviewing forty years of efforts to use advanced information and communication technologies in planning research and practice. It then considers current efforts to develop planning and decision support systems (PSS/DSS) that adopt current geographic information systems technology to meet the unique needs of planning. It concludes with the hope that the journal will take the first word of its title seriously and share the wealth of exciting e-planning research that is being conducted in all corners of the increasingly interconnected world.

scholarly journals Decision Rules Acquisition for Inconsistent Disjunctive Set-Valued Ordered Decision Information Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hongkai Wang ◽  
Yanyong Guan ◽  
Jilin Huang ◽  
Jianting Shen
Keyword(s):  
Information System ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Decision Rules ◽  
Optimal Decision ◽  
Formal Framework ◽  
Rules Acquisition

Set-valued information system is an important formal framework for the development of decision support systems. We focus on the decision rules acquisition for the inconsistent disjunctive set-valued ordered decision information system in this paper. In order to derive optimal decision rules for an inconsistent disjunctive set-valued ordered decision information system, we define the concept of reduct of an object. By constructing the dominance discernibility function for an object, we compute reducts of the object via utilizing Boolean reasoning techniques, and then the corresponding optimal decision rules are induced. Finally, we discuss the certain reduct of the inconsistent disjunctive set-valued ordered decision information system, which can be used to simplify all certain decision rules as much as possible.

Sign in / Sign up

Export Citation Format

Share Document