Decision Support versus Knowledge Creation Support

2005 ◽  
pp. 217-250
Author(s):  
Andrzej P. Wierzbicki ◽  
Yoshiteru Nakamori
Keyword(s):  
Decision Support ◽  
Knowledge Creation

Verification Mechanism for Online Responses in Criteria Prioritization

2013 ◽  
Vol 275-277 ◽  
pp. 2555-2559
Author(s):  
Chia Yean Lim ◽  
Vincent K.T. Khoo ◽  
Bahari Belaton
Keyword(s):  
Decision Support ◽  
Knowledge Creation ◽  
Concept Maps ◽  
Group Decision ◽  
Group Decision Support ◽  
Not Given ◽  
Rule Based ◽  
Organizational Knowledge Creation ◽  
Rule Based Approach ◽  
Logical Rules

In online criteria prioritization questionnaires, the respondents are not given an opportunity to verify and deliberate the reasons for each response. This paper describes a novel way to acquire the reasons and contexts behind the prioritization of criteria or alternatives, through a verification mechanism together with a set of logical rules. Essentially, a respondent is expected to visually verify the online responses against the reasons behind the prioritization of each pair of alternatives or criteria. A rule-based approach is then adopted to validate and display the inconsistent responses. Each respondent is expected to correct all detected inconsistency by recording the appropriate reasons and contexts in some concept maps. The resulting verification mechanism could be further enhanced and used as an intelligent organizational knowledge creation and maintenance framework for personalizing a group decision support setting.

Decision Support as Knowledge Creation

2010 ◽  
Vol 1 (1) ◽  
pp. 29-47 ◽  
Author(s):  
David M. Steiger
Keyword(s):  
Decision Support ◽  
Business Intelligence ◽  
Knowledge Creation ◽  
Mental Model ◽  
Design Theory ◽  
Decision Quality ◽  
Enabling Technology ◽  
New Knowledge ◽  
Knowledge Spiral

The primary purpose of decision support systems (DSS) is to improve the quality of decisions. Since decisions are based on an individual’s mental model, improving decision quality is a function of discovering the decision maker’s mental model, and updating and/or enhancing it with new knowledge; that is, the purpose of decision support is knowledge creation. This article suggests that BI techniques can be applied to knowledge creation as an enabling technology. Specifically, the authors propose a business intelligence design theory for DSS as knowledge creation, a prescriptive theory based on Nonaka’s knowledge spiral that indicates how BI can be focused internally on the decision maker to discover and enhance his/her mental model and improve the quality of decisions.

scholarly journals Knowledge Sharing

2017 ◽  
pp. 1-14 ◽  
Author(s):  
John S. Edwards
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Knowledge Acquisition ◽  
Knowledge Sharing ◽  
Decision Support Systems ◽  
Knowledge Creation ◽  
Business Processes ◽  
Support Systems ◽  
Knowledge Use ◽  
The People

Knowledge sharing is central to knowledge management in organizations. The more tacit the knowledge, the harder it is to share. However, successful knowledge sharing means looking not just at the content of the knowledge, and the people and technology concerned in the sharing, but the context in which that sharing takes place. This chapter discusses relevant theories from knowledge management and other fields. It goes on to present a model covering the time, place and context of the knowledge sharing activity, developed using theories about decision support systems. This forms the final part of a three-stage approach intended to help managers (and others) make decisions about how to support knowledge sharing activities in organizations. Each stage takes the form of a question to be answered, as follows: 1) What are the business processes concerned? 2) What is the knowledge to be shared related to - knowledge creation, knowledge acquisition, knowledge refinement, knowledge storage, or knowledge use? 3) What does this mean for the time, place and context of the knowledge sharing?

Knowledge Sharing

2020 ◽  
pp. 344-357
Author(s):  
John S. Edwards
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Knowledge Acquisition ◽  
Knowledge Sharing ◽  
Decision Support Systems ◽  
Knowledge Creation ◽  
Business Processes ◽  
Support Systems ◽  
Knowledge Use ◽  
The People

Knowledge sharing is central to knowledge management in organizations. The more tacit the knowledge, the harder it is to share. However, successful knowledge sharing means looking not just at the content of the knowledge, and the people and technology concerned in the sharing, but the context in which that sharing takes place. This chapter discusses relevant theories from knowledge management and other fields. It goes on to present a model covering the time, place and context of the knowledge sharing activity, developed using theories about decision support systems. This forms the final part of a three-stage approach intended to help managers (and others) make decisions about how to support knowledge sharing activities in organizations. Each stage takes the form of a question to be answered, as follows: 1) What are the business processes concerned? 2) What is the knowledge to be shared related to - knowledge creation, knowledge acquisition, knowledge refinement, knowledge storage, or knowledge use? 3) What does this mean for the time, place and context of the knowledge sharing?

Clinical decision support

2013 ◽  
Vol 46 (2) ◽  
pp. 52
Author(s):  
CHRISTOPHER NOTTE ◽  
NEIL SKOLNIK
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision
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