• Journal of Korean Academic Society of Home Health Care Nursing
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• v.15 no.1
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• pp.22-28
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• 2008

Purpose: The aim of this study was to analyze the effects of time management on the clinical nurse's organizational commitment and job satisfaction. Methods: Subjects were recruited in two general hospitals in Seoul and Incheon. Data collection was done using a self-report questionnaire. Time management was measured using the questionnaire developed by Han (1992). Organizational commitment and job satisfaction were measured using the questionnaire developed by Yoon (2000), based on Mowday et al. (1979) and Stamps et al. (1978). The data were analyzed using the SAS statistical package program, version 10.0. Specifically, descriptive statistics and stepwise multiple regression were performed. Results: The predictive time management factors for organizational commitment included deadline decision, simplification, and goal-setting. The predictive time management factors for job satisfaction included planning/making the priority order, deadline decision, simplification, asking for help, and responsibility reduction. Conclusion: Time management factors are highly correlated with organizational commitment and job satisfaction in clinical nurses. Deadline decision and simplification are common predictive factors for organizational commitment and job satisfaction. These results can be used to develop more effective time management strategies for increasing organizational effectiveness in clinical nurses.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.55-65
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• 2008

The strategic decision makers of the firm have faced with uncertainty and complexity. Although they must make decision under these environments, they can't have enough time, man power, budget and knowledge that they need to decide. They can't, therefore, help getting supports by experts who have implicit knowledge about the domain. But it is difficult for them to find any other procedures and methods to create, transform, combine, and apply new knowledges, whenever decision makers face the problem This paper provides a new method to support a strategic decision making by using the knowledge transformation process suggested by Nonaka. We illustrate an application case of the strategic decision making in consulting industry. This paper uses cognitive map as a decision support technology based on the suggested method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.698-707
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• 2019

The removal of oil spilled by the sinking of a foreign ship in Korea's Exclusive Economic Zone (EEZ) began in May 2019 four years after the ship sunk near Jeju Island. The cleanup was conducted by a foreign company that was contracted to the ship-owner's protection & indemnity (P&I) insurance company. In contrast to the time taken to begin the cleanup, the operation itself was completed in just 22days. Compared to similar cases, the decision to begin the removal was a delayed one. This study analyzes all 93 documents related to the ship's sinking and the eventual cleanup, confirming delays in administrative decision-making on the removal, and identifies factors that influenced this delay. These factors include a neglect of accident-related data verification, and other, legal, technical, environmental, and human aspects. Finally, this study suggests ways to improve decision-making efficiency. As the first study dealing with the cleanup in the EEZ, this research is expected to facilitate decision-making and influence the formulation of policies in the future.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.251-258
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• 2013

Recently companies are confronted with a much more sophisticated business environment than before and at the same time have to be able to adapt to rapid changes. Accordingly, the need for selecting among alternatives and managing systematic decision-making has been steadily increasing to respond to a more diverse customer needs and keep up with the fierce competition. In this study, we propose a framework that consist of problem solving procedures and techniques and knowledge structure built on processes to support strategic decision making. and discuss how to utilize simulation tools as the knowledge-based problem solving tools. In addition we discuss how to build and advance the knowledge structure to implement the proposed architecture. Management decision support systems architecture consist of three key factors. The first is Problem Solving Approach which is used as reference. The second is knowledge structure on business processes that includes standard and reference business processes. The third is simulators that are able to generate and analyze alternatives using problem solving techniques and knowledge base. In sum, the proposed framework of decision-making support systems facilitates knowledge-intensive consulting processes to promote the development and application of consulting knowledge and techniques and increase the efficiency of consulting firms and industry.

• Journal of the military operations research society of Korea
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• v.28 no.1
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• pp.83-96
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• 2002

The Analytic Hierarchy Process (AHP) is well suited to group decision making and offers numerous benefits as a synthesizing mechanism in group decisions. To date, the majority of AHP applications have been in group settings. One reason for this may be that groups often have an advantage over individual when there exists a significant difference between the importance of quality in the decision and the importance of time in which to obtain the decision. Another reason may be the best alternative is selected by comparing alternative solutions, testing against selected criteria, a task ideally suited for AHP. In general, aggregation methods employed in group AHP can be largely classified into two methods: geometric mean method and (weighted) arithmetic mean method. In a situation where there do not exist clear guidelines for selection between them, two methods do not always guarantee the same group decision result. We propose a simulation approach for building group consensus without efforts to make point estimates from individual diverse preference judgments, displaying possible disagreements as is natural in group members'different viewpoints.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.201-206
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• 1994

The linear search problem is concerned with finding a hiden target on the real line R. The position of the target governed by some probability distribution. It is desired to find the target in the least expected search time. This problem has been formulated as an optimization problem by a number of authors without making use of Markov Decision Process (MDP) theory. It is the aim of the paper to give a (MDP) formulation to the search problem which we feel is both natural and easy to follow.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.121-130
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• 1999

The objective of this paper is to apply Extended AND-OR Graph (EAOG)-related techniques to extract knowledge from a specific problem-domain and perform analysis in complicated decision making area. Expert systems use expertise about a specific domain as their primary source of solving problems belonging to that domain. However, such expertise is complicated as well as uncertain, because most knowledge is expressed in causal relationships between concepts or variables. Therefore, if expert systems can be used effectively to provide more intelligent support for decision making in complicated specific problems, it should be equipped with real-time inference mechanism. We develop two kinds of EAOG-driven inference mechanisms(1) EAOG-based forward chaining and (2) EAOG-based backward chaining. and The EAOG method processes the following three characteristics. 1. Real-time inference : The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation. 2. Matrix operation : All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient. 3. Bi-directional inference : Traditional inference method of expert systems is based on either forward chaining or backward chaining which is mutually exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.1-9
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• 2012

It is well known that internet shoppers are very sensitive to sale prices. They visit the various shopping malls and collect the product information including purchase conditions for goods purchase decision-making. Recently the necessity of information support is increasing because of increase of information amount which is necessary and complexity of goods purchase decision-making process. The comparison shopping agent systems have provided price comparison information which is collected from various shopping malls to satisfy internet shoppers information craving. But the frequent price change caused by keen price competition is becoming the primary reason of information quality decline among price comparison sites. RSS which is a family of web feed formats used to publish frequently updated is applied even in on-line shopping malls. This paper develops a RSS product information collection system to get real-time product information. The proposed product information system consists of (1) web crawler module for searching RSS feed shopping malls automatically, (2) RSS reader module for parsing product information from RSS feed file, (3) product DB and (4) product searching module. Performance of the proposed system is higher than the comparison shopping agent systems when it is defined with the volume of collecting product information per unit time.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1881-1888
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• 2008

As the ticket issuing methods have been diversified for the convenience of the passengers such as ticketless service(SMS ticket, e-ticket, home ticket), automatic ticket issuing machine and consignment ticket sale, maintaining the current number of ticket booth has been becoming a issue. Too many booth can cause the inefficiency of the cost of labor. According to the Charter of Customer Service of Korail, on the other hand, 95% of passengers have to purchase a train ticket within 5 minutes. This study was designed to present a decision making model for the optimum number of ticket booth which can affect an efficient operation of train station and improvement of customer convenience. And, this paper shows the proper manpower of ticket booth and the change of customer waiting time by analyzing the arrival and ticket issuing time of passengers based on 'Queueing Theory'. However, it is insufficient to be generalized due to some limitations of analysis. This study will contribute to improve customer satisfaction by reducing the waiting time at the ticket booth. In addition, presenting the optimum number of booth is expected to have an effect on the increase of productivity and cost savings.

• Korean Journal of Construction Engineering and Management
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• v.9 no.5
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• pp.159-167
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• 2008

This study provides a effective approach to the construction management problem with the limited number or amount of available resources using the analytic hierarchy process. Construction management is a series of decision making processes for planning and controling of cost, time and quality as main objectives in construction works. When several activities need the limited same resource at the same time, it is very hard to decide the priority of the activities in the real situations. For that the scientific decision making method and procedure for resource allocation are required. This study solves the resource allocation problem by dealing with the decision making problem which the activities are distributed to multiple projects and under multiple criteria. The analytic hierarchy process is a method devised to solve complex multi-criteria decision problems. The result shows that this study can be effectively used to make decisions in situations involving multiple objectives by evaluating the prioritized ranking and degree of the activity alternatives based on the overall preferences.