• Industrial Engineering and Management Systems
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• v.12 no.1
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• pp.2-8
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• 2013

Uncertainty theory is a branch of mathematics based on normolity, duality, subadditivity and product axioms. Uncertain process is a sequence of uncertain variables indexed by time. Canonical Liu process is an uncertain process with stationary and independent increments. And the increments follow normal uncertainty distributions. Uncertain differential equation is a type of differential equation driven by the canonical Liu process. Stability analysis on uncertain differential equation is to investigate the qualitative properties, which is significant both in theory and application for uncertain differential equations. This paper aims to study stability properties of linear uncertain differential equations. First, the stability concepts are introduced. And then, several sufficient and necessary conditions of stability for linear uncertain differential equations are proposed. Besides, some examples are discussed.

• Korean Management Science Review
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• v.17 no.1
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• pp.31-40
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• 2000

With the rapidly changing external environment and the increasing internal process complexity more and more organizations are adopting the Electronic Approval System(EAS) for their competitiveness. This paper defines EAS as a core organizational communication medium investigates factors which influence EAS's use from a media rich-ness theory and shows sutiable EAS functions for equivocality resolution and uncertainty reduction. Results from the five EAS implementation sites show that most organizations use EAS only for tasks with low equivocality and low uncertainty. Additional functionalities such as video conferencing and database access were suggested for fu-ture EAS system to enhance their utilization for more cirtical and unstructed tasks.

• Journal of the Korea Safety Management & Science
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• v.1 no.1
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• pp.7-17
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• 1999

As the loss from break-downs and errors, which became more frequent with the growth of elaborateness, complexity and in scale of the plant and equipments, are enormous, the improvement in the reliability, maintenance, safety, and qualify become to have interest. The fault diagnosis is a systematic and unified method to find errors, which is based on the interpretation that data, subconsciously, have noises. But, as most of the methods are inferences based on binomial logic, the uncertainty is not correctly reflected. In this study, we suggest, to manage the uncertainty in the system efficiently on the point of predictive maintenance, We should use fuzzy expert system, which make the decision considering uncertainty possible by taking linguistical variable and fixed quantity by using the fuzzy theory concepts on the basis of an expert's direct observation and experience.

• Knowledge Management Research
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• v.11 no.5
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• pp.59-78
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• 2010

In this paper, we arrange the concept of 'Green' in SCM after literature study of Green SCM and investigate causal relationships between influencing factors, practice level and environmental performance focused on Korean firms empirically and conduct path analysis for hypothesis test using partial least squares regression with bootstrap. Firstly, we divide influencing factors of Green SCM into environmental and organizational factors through the previous studies of innovation diffusion theory and environmental management theory, and then we selected 'uncertainty', 'competitiveness' as the environmental factors and 'top management support', 'perceived benefit', 'training' as the organizational factors. Secondly, we classify practice level of Green SCM into 'internal environmental management', 'green purchasing', 'eco-design'. Finally, we selected 'financial performance', 'environmental performance' as the organizational performance. We conducted a survey on the middle manager of manufacturing companies implementing SCM and an empirical analysis. The results of analysis show that there exist causal relationships between influencing factors, practice level, and environmental performance of Green SCM. We expect that the result of this study will suggest useful information to managers who are responsible for SCM to design and execute Green SCM in strategic perspectives.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.224-227
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• 2004

As a project progresses, it is well known that construction manager has to define the contingency for the expected project cost, which is used as a buffer for uncertainty. In this study, we mention uncertainty as the amount of likelihood that is difficult or impossible to predict project cost. From the completed work package, we obtain the true cost value, and this information is technically good data for estimating the realistic contingency of work packages to be accomplished. Based upon this historical information, construction manager recomputes the contingency for the remaining works. Conditional probability theory is often useful for re-estimating one of the remaining project progress as the true cost of the completed works can be different from the planned cost. As a project is progressing, true value is really important to predict the realistic project budget and to decrease the uncertainty. In this study, we gave applied conditional probability theory to estimating project contingency supposing a project that consists of fire work packages, provide the fundamental framework for setting and controlling project contingency.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.174-178
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• 2015

This paper presents a new method for forecasting construction project cost and time at completion or at any intermediate time horizon of the project duration. The method is designed to overcome identified limitations of current applications of earned value method in forecasting project cost and time. The proposed method usesfuzzy set theory to model uncertainties associated with project performance and it integrates the earned value technique and the contractors' judgement. The fuzzy set theory is applied as an alternative approach to deterministic and probabilistic methods. Using fuzzy set theory allows contractors to: (1) perform risk analysis for different scenarios of project performance indices, and (2) perform different scenarios expressing vagueness and imprecision of forecasted project cost and time using a set of measures and indices. Unlike the current applications of Earned Value Method(EVM), The proposed method has a numberof interesting features: (1) integrating contractors' judgement in forecasting project performance; (2) enabling contractors to evaluate the risk associated with cost overrun in much simpler method comparing with that of simulation, and (3) accounting for uncertainties involved in the forecasting project cost.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.473-476
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• 2003

This paper presents a systematic risk assessment procedure with uncertainty modeling for general construction projects. Since the approach is able to effectively deal with all the related construction risks in terms of the assumed probability with conditional probability concept that systematically incorporate expert's experiences and subjective judgement, the proposed methods with uncertainty modeling is able to apply to all the construction projects inherent in lots of uncertain risk events. The fuzzy set theory is adopted to enhance risk assessment to effectively handle the vague and dynamic phenomenon of an event Therefore, the fuzzy-based risk assessment is very useful, for those countries, such as Korea, where objective probabilistic data for risk assessment is extremely rare, and thus the utilization of subjective judgmental data based on expert's experiences is inevitable.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1647-1651
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• 2009

The uncertainty or imprecision associated with vague parameters and weighting sets, reduces the ability to decide what alternative is better for a particular location. To efficiently reduce the effect of imprecision frequently arising in available information, fuzzy theory has been used to improve consideration of imprecision in a Multi-Criteria Decision Analysis (MCDA) problem. Fuzzy logic offers a way to represent and handle imprecision present in continuous real world applications. A GIS implementing fuzzy set theory, (referred to in this paper as the "Spatial Fuzzy Approach") enables decision makers to express imprecise concepts associated with geographic data and provides decision makers the ability to have even more definition and discrimination in terms of the best alternatives for a particular spatial location. This study is focused on addressing questions pertaining to the methodology of floodplain analysis using GIS and Spatial Fuzzy MCDA to evaluate flood damage reduction alternatives. The issues will be examined in a case study of the Suyoung River Basin in Pusan, Korea.

• Journal of Information Technology Applications and Management
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• v.16 no.4
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• pp.135-165
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• 2009

The major purpose of this study is to identify the factors influencing the implementation performance of ERP Systems from an integrated viewpoint. For this purpose, a research model is developed based on the literature reviews of ERP systems, contingency theory, and change management theory. The research model proposed fifteen variables as the factors influencing the implementation performance in the ERP systems. The data have been collected from the 164 enterprises which implemented ERP systems at least one year ago. The respondents were person in charge of ERP system of each corporation. The results of hypothesis testing through multiple regression analysis are summarized as follows. Firstly, standardization of work, concentration of decision making, top management concern and support, real user participation, project support goodness, ease of use, and system usefulness have positive influence upon non-financial performance. Secondly, market uncertainty, industrial competition, project support goodness, and customization minimization have positive influence upon financial performance. From the analysis, this research have identified important characteristics for the successful implementation of ERP systems. Consequently, this research ends with managerial and theoretical implications of the study results, as well as limitations and future research directions.

• The Journal of Information Systems
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• v.21 no.1
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• pp.173-203
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• 2012

In this paper, we arrange the concept of 'Green' in SCM after literature study of Green SCM and investigate causal relationships between influencing factors, practice level and environmental performance focused on Korean firms empirically and conduct path analysis for hypothesis test using partial least squares regression with bootstrap. Firstly, we divide influencing factors of Green SCM into environmental and organizational factors through the previous studies of innovation diffusion theory and environmental management theory, and then we selected 'uncertainty', 'competitiveness' as the environmental factors and 'top management support', 'perceived benefit', 'training' as the organizational factors. Secondly, we classify practice level of Green SCM into 'internal environmental management', 'green purchasing', 'eco-design'. Finally, we selected 'financial performance', 'environmental performance' as the organizational performance. We conducted a survey on the middle manager of manufacturing companies implementing SCM and an empirical analysis. The results of analysis show that there exist causal relationships between influencing factors, practice level, and environmental performance of Green SCM. We expect that the result of this study will suggest useful information to managers who are responsible for SCM to design and execute Green SCM in strategic perspectives.