• Journal of Korean Society for Quality Management
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• v.39 no.4
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• pp.464-479
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• 2011

The purpose of this study is that analyzing the causal relationship between Infra, Process and Performance of companies which are executing the Supply Chain Quality Management(SCQM) with their subcontractors and partners. Korean Standards Association(KSA) provides the Supply Chain Quality Management Model and Quality Collaboration Index for 4 years, but a few study has investigated the critical variables and their causal relationship to organizational performance. Therefore we examine the SCQM model and related index and choose the quality, human resource and risk management processes for identifying the path to organizational performance. In addition, exploratory factor analysis is conducted for figuring out the major factors among the 3 processes. Structural Equation Model are successively used for determining which characteristics of the infra and processes are the most critical variables to performance. The data was collected from KSA and composed of 52 companies and 346 their partners. The result shows that risk management process has no significant effect on the organizational performance and pre-production process collaboration.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.59-72
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• 2021

Concepts and categories offer the basis for inference pertaining to unobserved features. Prior research on category-based induction that used blank properties has suggested that similarity between categories and features explains feature inference (Rips, 1975; Osherson et al., 1990). However, it was shown by later research that prior knowledge had a large influence on category-based inference and cases were reported where similarity effects completely disappeared. Thus, this study tested category-based feature inference when features are connected in a causal chain and proposed a feature inference model that predicts participants' inference ratings. Each participant learned a category with four features connected in a causal chain and then performed feature inference tasks for an unobserved feature in various exemplars of the category. The results revealed nonindependence, that is, the features not only linked directly to the target feature but also to those screened-off by other feature nodes and affected feature inference (a violation of the causal Markov condition). Feature inference model of causal model theory (Sloman, 2005) explained nonindependence by predicting the effects of directly linked features and indirectly related features. Indirect features equally affected participants' inference regardless of causal distance, and the model predicted smaller effects regarding causally distant features.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.1-10
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• 2006

This study constructs a causal relationship model of balance scorecard(BSC) performance in supply chain management(SCM). According to the results, the sample companies show the causal relationship of learning and growth performance, internal process performance, customer performance, and financial Performance indices in SCM. And this study implies that BSC performance indices gives, through direct causal relations among them, impact on the ultimate financial performance of firms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.87-109
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• 2020

Supply chain management can be defined as an information system that connects the inside and outside of a company. Its purpose is to systematically and strategically manage the flow of information, resources and services to improve the long-term performance of the entire organization, including individual companies connected to the supply chain, and the quality of service provided to customers. The ultimate goal of SCM is to create synergy through organic integration of supply and demand based on cooperation and collaboration with stakeholders in the supply chain. This study is based on the hypothesis that the company's management performance will improve as the level of SCM improves. Most of the previous studies dealt with the relationship between corporate performance and SCM in the IT area. In this study, research was conducted through human capacity with IT system. The causal relationship was demonstrated, and there was a difference in the perception of the results of this study depending on whether or not smart factories were consulted in the era of the 4th Industrial Revolution. There is a need to examine the links between management's value chain and its causal relationship.

• Journal of Distribution Science
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• v.20 no.11
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• pp.79-88
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• 2022

Purpose: The purpose of this study was to determine the effect of agricultural exports and imports on economic growth in Bangladesh and propose an upgraded and customized model of the supply chain for agribusiness growth in Bangladesh to achieve plain sailing and systematic operation and financial gains at home and abroad. Research design, data, and methodology: All data in the research have been collected from secondary sources. Gross domestic product was used as the dependent variable and exports and imports of agricultural products were used as independent variables. Pairwise Granger causality was utilized to see the impact of the variable responsible for the economic growth in Bangladesh and the causal relationship between the variables analyzed was measured using Johansen co-integration test. Results: From the empirical analysis, the researchers observed that agricultural commodity imports and exports have a unidirectional impact on economic growth in Bangladesh and a long-run causal link with economic growth in Bangladesh. The suggested supply chain model of agribusiness aids in achieving smooth operations, systematic management, and monetary gains both domestically and internationally. Conclusions: This paper contributes to the development of a more effective and profitable agribusiness supply chain in Bangladesh systematically through their theoretical and practical implications.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.47-75
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• 2010

Two experiments were conducted to explore whether the Or structure works as a default causal model in inferring the causal structure from the contingency data. The contingencies of three unfamiliar variables were used in Experiment 1. Participants inferred the Or structure quite well from the OR data, but incorrectly inferred the Or structure from the And data for about a little less than half of the time, and almost always inferred the Or structure from the chain data. The results suggested that the Or interpretation can be the default causal model. The prevalence of the Or interpretation from the contingency data was reported even when the three variables were familiar ones in Experiment 2. Multinomial modeling performed on the results of the two experiments strongly suggested that the Or interpretation work as a default causal model.

• Journal of Information Technology Applications and Management
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• v.13 no.2
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• pp.41-54
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• 2006

In this paper, we investigate the inter-organizational information systems effect to supply chain partnerships, and subsequently to the performance. The conceptual model for the causal relationships among interorganizational systems usage, interaction, partnership, and supply chain performances has been developed. Theoretical framework is based on the partnership research in relationship marketing area, and the interaction model from IMP group. The questionnaires are designed to test the hypotheses of the conceptual model. The survey result supports our hypotheses that collaborative IT effects to increase the interaction between the firms, and interaction causes to enhance the partnership quality. Also, the level of partnership shows strong positive correlation with the supply chain performances. Despite the limitations of collected sample data size, our study reveals the fact that inter-organizational information systems contribute to supply chain performance through enhancing the interaction and partnership level between the supply chain partners. Our research result is distinct from the most extant literatures that investigated the firm's collaboration impact on interorganizational systems usage.

• The Journal of Information Systems
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• v.23 no.4
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• pp.75-91
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• 2014

The effective supply chain management(SCM) is a matter of survival in many firms because successful supply chains will effectively coordinate their processes, focus on delivering customer value, eliminate unnecessary costs in key functional areas, and create performance measurement systems. The balanced scorecard(BSC) is widely used to measure the performance of the SCM. The BSC framework suggests that balance is obtained by adopting performance measures from four different areas. In this study, we analyzed the causal relationship of SCM performance based on BSC framework. First, we reviewed the nested causal relationships among four different perspective of the BSC, namely, business process perspective, customer perspective, financial perspective, and innovation and learning perspective. Then, we used the chi-square difference test to identify the best model to fit the causal relationship of SCM performance. Of the 800 questionnaires posted, a total of 265 questionnaires were returned after one follow-up. A total of 66 questionnaires were eliminated due to largely missing values. The major finding says alternative model 3 is dominant to other models to fit causal relationships among four different perspective of the BSC. Innovation and learning perspective positively influence on customer perspective, business process perspective, and financial perspective. Business process perspective also positively influence on customer perspective and financial perspective whereas customer perspective does not influence on financial perspective significantly.

• Journal of KIISE:Software and Applications
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• v.28 no.1
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• pp.46-51
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• 2001

2D로 확장한 HMM은 다수 제안되었지만 엄밀한 의미에 있어서 2D HMM이라고 하기에 부족한 점이 많다. 본 논문에서는 기존의 랜덤 필드 모형이 아닌 새로운 2D HMM을 제안한다. 상하 및 좌우 방향의 causal chain 관계를 가정하고 완전한 격자 형성 조건을 두어 2D HMM의 평가, 매개 변수를 추정하는 알고리즘을 제시하였다. 각각의 알고리즘은 동적 프로그래밍과 최우 추정법에 근거한 것이다. 변수 추정 알고리즘은 반복적으로 이루어지며 국소 최적치에 수렴함을 보였다.

• International Commerce and Information Review
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• v.10 no.1
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• pp.237-256
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• 2008

In recent years, most of Supply Chain Management literature has emphasized the importance of information sharing among supply chain partners, but empirical researches are few until now, especially in Korea. The purpose of this study is to develop an empirical model focusing on information exchange among partners in supply chain, and to analyze the main factors influencing the causal relationship between information exchange and performance. Based on cross-sectional questionnaire survey on Korean manufacturing firms, this study analyzed the factors influencing information exchange such as environmental factors, organizational factors, relationship factors, and information characteristics of the sample firms. Our major findings might provide many useful insights for managers in exploring the most efficient system for information exchange among partners in the context of SCM.