THE RESEARCH TREND OF INFORMATION TECHNOLOGY AND DECISION MAKING IN 2009

Author(s):  
YONG SHI

The research topics of the 39 papers published in the International Journal of Information Technology and Decision Making (IT&DM) in 2009 can be classified into three major directions: decision support, multiple criteria decision making, and data mining and risk analysis. The Editor-in-Chief, on behalf of the editorial board and advisory board, highlights the key ideas of these contributions. The seven papers in first issue of 2010 IT&DM are also introduced.

Author(s):  
YONG SHI

On behalf of the editorial advisory board of the International Journal of Information Technology and Decision Making (IT&DM), the Editor-in-Chief reviews the current research trend of this journal based on all the papers published in 2008. They are web-based decision analysis, credit scoring techniques and new data mining methods which combine both decision-making techniques and information technology tools. In addition, the Editor-in-Chief summarizes the key ideas of contributions in this new issue that may contain new research trend of IT&DM in 2009.


2020 ◽  
Vol 7 (2) ◽  
pp. 290
Author(s):  
Daniel F S P Sitohang ◽  
Berto Nadeak ◽  
Putri Ramadani

One effort in the development of information technology today requires fast and accurate information in its implementation. in the assessment of the work ability of well-performing and poor employees with the support of a decision support system it produces one of the implementations of the development of information technology in improving the quality of the company's work. where the decision making process determines employee demotion is still done manually. still there are often a number of errors such as misdirection. Therefore, to make an assessment in making a decision to choose a decent demotion employee based on the assessment carried out in the field. Then the decision support system that will be built with a computerized system so that decision making is done quickly and accurately. For this decision support system, use the Profile Matching method or matching the demotion of employee demos with the profile of the employee assessed with the specified Criteria. Making an application program must be made carefully, so that it looks easy to understand and proven useful and useful for users. the system built can help PT. Nafasindo in determining the demotion of employees who are decent and can reduce errors in determining the demotion of employees


Author(s):  
Hamid R. Nemati ◽  
Christopher D. Barko

An increasing number of organizations are struggling to overcome “information paralysis” — there is so much data available that it is difficult to understand what is and is not relevant. In addition, managerial intuition and instinct are more prevalent than hard facts in driving organizational decisions. Organizational Data Mining (ODM) is defined as leveraging data mining tools and technologies to enhance the decision-making process by transforming data into valuable and actionable knowledge to gain a competitive advantage (Nemati & Barko, 2001). The fundamentals of ODM can be categorized into three fields: Artificial Intelligence (AI), Information Technology (IT), and Organizational Theory (OT), with OT being the core differentiator between ODM and data mining. We take a brief look at the current status of ODM research and how a sample of organizations is benefiting. Next we examine the evolution of ODM and conclude our chapter by contemplating its challenging yet opportunistic future.


2009 ◽  
pp. 82-89
Author(s):  
John Wang ◽  
James Yao

Group decision support systems (GDSSs) which aim at increasing some of the benefits of collaboration and reducing the inherent losses are interactive information technology-based environments that support concerted and coordinated group efforts toward completion of joint tasks (Dennis, George, Jessup, Nunamaker, & Vogel, 1998). The term group support systems (GSSs) was coined at the start of the 1990’s to replace the term GDSS. The reason for this is that the role of collaborative computing was expanded to more than just supporting decision making (Patrick & Garrick, 2006). For the avoidance of any ambiguities, the latter term shall be used in the discussion throughout this paper


Author(s):  
Ken J. Farion ◽  
Michael J. Hine ◽  
Wojtek Michalowski ◽  
Szymon Wilk

Clinical decision-making is a complex process that is reliant on accurate and timely information. Clinicians are dependent (or should be dependent) on massive amounts of information and knowledge to make decisions that are in the best interest of the patient. Increasingly, information technology (IT) solutions are being used as a knowledge transfer mechanism to ensure that clinicians have access to appropriate knowledge sources to support and facilitate medical decision making. One particular class of IT that the medical community is showing increased interest in is clinical decision support systems (CDSSs).


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