Database Management Systems, Management Information Systems, Decision Support Systems

Author(s):  
HARVEY M. DEITEL ◽  
BARBARA DEITEL
2016 ◽  
Vol 12 (1) ◽  
pp. 201
Author(s):  
Bilal Mohammed Salem Al-Momani

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.


Author(s):  
Kijpokin Kasemsap

This chapter explains the overview of Intelligent Decision Support Systems (IDSSs); the overview of Enterprise Information Management (EIM); the IDSS techniques for EIM in terms of Expert System (ES), Multi-Agent System (MAS), Fuzzy Logic (FL), Artificial Neural Network (ANN), Evolutionary Computation (EC), and Hybrid System (HS); and the multifaceted applications of IDSSs in EIM. IDSS techniques are rapidly emerging as the modern tools in information management systems and include various techniques, such as ES, MAS, FL, ANN, EC, and HS. IDSS techniques can increase the sensitiveness, flexibility, and accuracy of information management systems. IDSS techniques should be implemented in modern enterprise in order to gain the benefits of using the decision-making process concerning EIM. The chapter argues that utilizing IDSS techniques for EIM has the potential to increase organizational performance and reach strategic goals in global operations.


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