• Knowledge Management Research
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• v.17 no.3
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• pp.117-136
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• 2016

External knowledge search is critical to expand the firm's knowledge base, increasing the innovation performance. However, prior literature has paid less scholarly attention on the boundary condition of the search activity. In particular, the few literatures on the contingency factors are either conceptual or focus on the firm characteristics such as resources and capability. In this regard, this study argues the negative moderating effect of knowledge protection and environmental uncertainty of a firm on the positive relationship between external knowledge search and innovation performance, because these contingency factors hamper the reciprocity and the mutual trust between the firm and its external partner that provides knowledge needed in the innovation process. The empirical analysis is based on the sample drawn from Korean Innovation Survey, provided by STEPI in Korea. The sample consists of 1,637 respondent firms that experienced product innovation during the survey period. We could find statistically supporting results for the negative moderating effect on the positive relationship between external knowledge search and innovation performance. This study extends the academic debate on the boundary conditions of external knowledge search and provides managerial implications for successful product innovation.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.2
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• pp.39-60
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• 1995

In this paper, an integration of stochastic dynamic programming (SDP), integer goal programming (IGP) and analytic hierarchy process (AHP) is proposed to handle multiobjective-multicriteria sequential decision making problems under uncertainty inherent in R & D investment planning. SDP has its capability to handle problems which are sequential and stochastic. In the SDP model, the probabilities of the funding levels in any time period are generated using a subjective model which employs functional relationships among interrelated parameters, scenarios of future budget availability and subjective inputs elicited from a group of decision makers. The SDP model primarily yields an optimal investment planning policy considering the possibility that actual funding received may be less than anticipated one and thus the projects being selected under the anticipated budget would be interrupted. IGP is used to handle the multiobjective issues such as tradoff between economic benefit and technology accumulation level. Other managerial concerns related to the determination of the optimal project portifolio within each stage of the SDP model. including project selection, project scheduling and annual budget allocation are also determined by the IGP. AHP is proposed for generating scenario-based transformation probabilities under budgetary uncertainty and for quantifying the environmental risk to be considered.

• Health Policy and Management
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• v.29 no.1
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• pp.49-57
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• 2019

Background: The purpose of this study was to examine the cultural competence of nurses caring for foreign patients in general hospitals. Methods: The subjects are 308 nurses who work in general hospitals in Seoul and Gyeonggi-do. The data, collected using a structured questionnaire on cultural competence, coping strategy, multicultural experience, intercultural uncertainty, and intercultural anxiety, were analyzed using descriptive statistics, t-test, analysis of variance, Pearson's correlation analysis, and hierarchical multiple regression. Results: Cultural competence was significantly associated with marital status, level of education, type of ward, and number of cared foreign patients. In hierarchical multiple regression analysis, the level of cultural competence was significantly associated with married, master degree qualified, high level of coping strategy and multicultural experience, and low level of cultural uncertainty. Conclusion: The findings revealed the need for educational programs which can contribute to lower the intercultural uncertainty and to enhance coping strategies dealing with foreign patients. In addition, individual and organization efforts to provide opportunities to expand nurses' multicultural experience will affect nurses' cultural competence development.

• Knowledge Management Research
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• v.20 no.1
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• pp.175-194
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• 2019

In order to overcome the limitation of market orientation concept, Narver et al. (2004) have extended the original concept into two dimensions, responsive market orientation (RMO) and proactive market orientation (PMO), respectively. Yet, there has been very limited empirical studies that analyzed the differential effects of each market orientation on firm outcomes, especially in the Korean context. We analyze the impact of RMO and PMO on the new product performance in the perspective of SMEs and examine the moderating effect of external factors such as environmental uncertainty and market similarity. The results of this study show that both RMO and PMO have a significant positive effect on the new product performance of SMEs. Also, environment uncertainty shows a negative moderating effect on the relationship between RMO and new product performance, whereas it has positive moderation with PMO. This suggests that focusing on potential customers' needs rather than current needs helps improve firm performance as the competitive environment surrounding the firm becomes more uncertain. Lastly, market similarity showed a positive moderating effect on the relationship between RMO and new product performance, but not on PMO.

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.87-103
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• 2018

This paper introduces the method to develop two main types of the fuzzy OEE (Overall Equipment Effectiveness) models via triangular membership function for measuring uncertainty. The fuzzy OEE includes model type 1 and model type 2. The model type 1 is used when the theoretical machine speed only reflects the time loss whereas model type 2 is used when the actual machine speed reflects both time and speed loss. Model type 2 has shown to perform a lower availability rate and a higher performance rate compared to model type 1. In addition, the fuzzy UPH (Unit Per Hour) which is derived from using the fuzzy OEE is presented to satisfy demand uncertainty. The fuzzy UPH can easily measure the fuzzy tact time and cycle time by reciprocating itself. Finally, this study demonstrates the fuzzy OEE models using IVIFS (Interval-Valued Intuitionistic Fuzzy Set) based on the characterization via membership function, non-membership function and hesitant function. For the purpose of analyzing the fuzzy system OEE, the OEE for each machine of plant structure is considered triangular interval-valued intuitionistic fuzzy number. Regardless of plant structure, the validity degree of fuzzy membership function of system OEE decreases when the number of machine with worst value of the validity degree increases. Corresponding examples are presented in this paper for practitioner to understand the applicability and practicability of the proposed fuzzy OEE methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.552-555
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• 1998

In dealing with representing knowledge under uncertainty there is a sustain tendency to increase flexibility in order to avoid problems of inconsistency in the knowledge. Many knowledge systems(information retrieval systems, expert system) include hybrid representation models. Funny retrieval systems appear as a complement or as an enrichment of this models. In this paper, we describe dynamic rule modification through situation assessment for uncertainty management.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.81-82
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• 2006

• Asia pacific journal of information systems
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• v.8 no.3
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• pp.135-145
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• 1998

There exists popular approach using certainty factor (CF) for the development of effective reasoning mechanism under uncertainty in Expert System, However, there is a problem with CF. The CF values could be resulted in the opposite of given conditional probabilities. In this paper, a method for, reasoning under uncertainty using reliability theory to overcome the problem is proposed. And the proposed method is used in the development of Expert System for the selection of equipment for automated warehouses.

• Smart Structures and Systems
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• v.33 no.4
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• pp.291-300
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• 2024

Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.

• Information Systems Review
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• v.15 no.1
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• pp.45-68
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• 2013

Despite improved technologies, procedures, and regulations, consumers are still uncertain about purchasing online. The objective of this study is to understand uncertainty factors in online shopping and their relationships with the consumers' intention to purchase. For this objective we derived seller anonymity, lack of product transparency, and lack of process transparency as uncertainty factors from previous researches which may affect consumers' perceived uncertainty on online shopping. Then, a causal model was developed to conceptualize the relationships between these uncertainty factors as antecedent variables and consumer's intention to purchase as consequent variable with perceived uncertainty as an intermediary variable. Purchase involvement was used as a moderating variable on the relationship between perceived uncertainty and the intention to purchase online. The model was tested empirically to find meaningful relationships among these variables. The findings indicate that all antecedent variables affect perceived uncertainty significantly and perceived uncertainty negatively affects consumers' intention to purchase. Moreover, the results of analysis show purchase involvement has a significant moderating effect on the relationship between perceived uncertainty and intention to purchase online.