• Korean Management Science Review
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• v.12 no.2
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• pp.147-164
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• 1995

There have been two dominant paradigms in understanding and modeling an expert's decision-making behavior: output analysis and process-tracing. While the two paradigms are complementary, they have not been used yet in a combined manner. This study extends the previous research work in the two paradigms to inductive modeling research by 1) analyzing individual experts' decision strategies, 2) comparing performance of four popular inductive modeling methods, and 3) matching their performance against the type of decision strategy employed by experts.

• The Journal of Information Systems
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• v.18 no.3
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• pp.89-110
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• 2009

In today's e-business environment, it is important to make decisions cooperatively between companies on a supply chain for their business success. This research analyzes empirically the influences of organizational factors on joint decision making and the ones of the joint decision making on business performance. We collected 188 corporate-level data through a Web survey and tested them statistically through PLS method based on a structured equation modeling. The results showed that (i) partner's knowledge creation capabilities, inter-organizational process modularity, and inter-organizational trust had direct effects on joint decision making, (ii) joint decision making and electronic business interfaces bad direct impacts on business performance. Contrary to our expectation, however, the moderating effects of electronic business interfaces between corporations on the relationship between joint decision making and business performance was not significant. On the basis of these results, we discussed theoretical and managerial implications of the findings. The results are expected to provide useful perspectives when companies establish strategies to improve capabilities of cooperative decision making and business performance.

• IE interfaces
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• v.13 no.1
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• pp.17-28
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• 2000

As knowledge has been recognized as a new resource in gaining organizational competitiveness, Knowledge Management (KM) is suggested as a method to manage and apply knowledge for business management. KM research, however, has focused on identifying, storing, and distributing the transaction-related knowledge in an organization. There has been little research on applying the knowledge to decision-making or strategy development that is the main task of business management. The application of knowledge to decision making has higher impact on organizational performance rather than just the knowledge management for process transaction. In this research, we suggest System Dynamics (SD) for the knowledge-based decision-making. Based on the modeling method of SD, we can translate partial and implicit knowledge resident in individual's mental model into organized explicit knowledge. The simulation test of the organized knowledge model enables decision-makers to understand the structure of the target problem and its behavior mechanism, which facilitates effective decision-making. We will compare the proposed method and other KM methods and discuss this research based on the application case to a real telecommunication company.

• Journal of Korean Academy of Nursing
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• v.49 no.5
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• pp.601-612
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• 2019

Purpose: The purpose of this study was to construct and test a hypothetical model of clinical decision-making ability of nurses based on the Decision Making Process model and the Cognitive Continuum theory. Methods: The data were collected from nurses working at 11 hospitals in Busan, Daejeon, and South Gyeongsang Province from June 30 to August 1, 2017. Finally, the data from 323 nurses were analyzed. Results: The goodness-of-fit of the final model was at a good level ($x^2/df=2.46$, GFI=.87, AGFI=.84, IFI=.90, CFI=.90, SRMR=.07, RMSEA=.07) and 6 out of 10 paths of the model were supported. The clinical decision-making ability was both directly and indirectly affected by task complexity and indirectly affected by experiences, autonomy, and work environment. Specifically, it was strongly directly affected by analytical competency but was insignificantly affected by intuitive competency. These variables accounted for 66.0% of clinical decision-making ability. Conclusion: The nurses' clinical decision-making ability can be improved by improving their analytical competency. Therefore, it is necessary to organize nursing work, create a supportive work environment, and develop and implement various education programs.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.12
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• pp.49-63
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• 1985

This paper is focused on the introduction of the types of models and explanation of the fundamental concepts and theory for development and use of the corporate planning and modeling system. Nowadays, a great deal of companies have been or experimenting with some form of a corporate planning and modeling system to support managerial and strategic decision making. From previous studies it was noted that most applications have tended to be financially based. This trend will probably continue. However, with the software and hardware currently available it is likely that companies will move more toward integrated models that link marketing, production, as will as financial areas. More emphasis will undoubtedly be placed on the use of econometric modeling, since this subelement of the overall planning and modeling process is closely tied to the market place and the economy. At any rate, wherever the development of corporate planning and modeling system is directed, clear understanding for the fundamental concepts and elements of the system is settled in advance in order to develope and use it.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.833-837
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• 1998

This paper presents preliminary findings regarding a modeling framework under development for use in a multi-attribute decision model for advanced emergency operating procedures(EOPs). This model provides a means for optimal decision making strategy for advanced emergency operating procedures conceptualizing the dynamic coordination of responsibilities and information in the human system interactions with advanced reactor systems. For the purpose of evaluation of the applicability of this modeling framework, an empirical case study for a post-cooldown strategy during an steam generator tube rupture (SGTR) accident was carried out. As a result, it was found empirically that the multi-attribute decision model is a useful tool for establishing advanced EOPs that reduce the operator's cognitive and decision making burden during the accident mitigation process.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.71-78
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• 2022

Recently, the number of people wishing to return to farming is increasing, However, the lack of farming experience and management information of returnees is one of the main reasons for increasing the probability of agricultural failure. This study proposes an interface to support early facility cultivation management decision-making for returnees who want facility cultivation. The proposed interface is designed with UML(Unified Modeling Language) and provides key decision-making information such as land/crop suitability, land/facility costs, and management costs according to input data such as cultivation areas, selected crops, and cultivation types selected by the user. Through the proposed interface, facility cultivators can effectively and quickly acquire initial decision-making information for facility cultivation in the desired target area.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.189-195
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• 2014

In this paper, we conducted a study on place-free and time-free cloud computing (CC) adoption decision-making model. Panel survey data which is collected from 65 people and CART (classification and regression tree) which is one of data mining approaches are used to construct decision-making model. In this modeling, there are 2 steps: In the first step, significant questions (variables) are selected. After that, the CART decision-making model is constructed using the selected variables. In the variable selection stage, the 25 questions are reduced to 5 ones. The benefits of question reduction are quick response from respondent and reducing model-construction time.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.1-16
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• 1995

The field of human judgment and decision making provides useful methodologies for examining the human decision making process and substantive results. One of the methodologies is a lens model analysis which can examine valid nonlinearity in the human decision making process. Using the method, valid nonlinearity in human decision behavior can be successfully detected. Two linear(statistical) models of human experts and two nonlinear models of human experts are compared in terms of predictive accuracy (predictive validity). The results indicate that nonlinear models can capture factors(valid nonlinearity) that contribute to the expert's predictive accuracy, but not factors (inconsistency) that detract from their predictive accuracy. Then, it is argued that nonlinear models cab be more accurate than linear models, or as accurate as human experts, especially when human experts employ valid nonlinear strategies in decision making.

• Journal of KIBIM
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• v.6 no.3
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• pp.24-33
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• 2016

Planning occurs from day-to-day, small-scale decisions to large-scale infrastructure investment decisions. For that reason, various attempts have been made to appropriately assist decision-making process and its optimization. Lately, initiation of a large amount of data, also known as big data has received great attention from diverse disciplines because of versatility and adoptability in its use and possibility to generate new information. Accordingly, implementation of big data and other information management systems, such as geographic information systems (GIS) and building information modeling (BIM) have received enough attention to establish each of its own profession and other associated activities. In this extent, this study illustrates a series of big data implementation cases that can provide a lesson to urban planning domain. In specific, case studies analyze how data was used to extract the most optimized solution and what aspects could be helpful in relation to planning decisions. Also, important notions about GIS and its application in various urban cases are examined.