• Information Systems Review
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• v.19 no.1
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• pp.185-202
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• 2017

Most studies based on production function theory have concluded that economic growth is a result of information technology (IT) capital use. However, some studies have indicated that economic growth is a determinant of IT investment. To determine if these results also hold at the industry level, we use the Granger causality test to analyze bidirectional causality with industry-level data for 1977~2007 from the United States. The results generally reveal that IT investment causes economic growth in many industries under the concept of Granger causality, that economic growth causes IT investment in some industries, and that IT investment is not associated with economic growth in some industries. In the country-level time-series data made by summing up the IT capital and gross output for each industry, the results do not show any causality between IT investment and economic growth. However, they show bi-directional causality between IT investment and economic growth in the panel data. These results may be a source of IT productivity paradox.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.205-214
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• 2008

The aim of this study is to examine if there is a difference in the recognition of the tax audit between a tax representative and a taxpayer and in the recognition of the tax audit according to characteristics of a tax representative and a taxpayer, and an analysis has been made to heighten fairness and effectiveness of a system of the tax audit. As a result of the analysis, there is a difference in a analysis of a subject variable in both a tax representative and a taxpayer. An alternative policy is required to promote fairness and effectiveness of the tax audit on the basis of the findings in the future.

• Health Policy and Management
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• v.5 no.1
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• pp.161-191
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• 1995

본 논문은 서구의 이론을 바탕으로 개발된 직무만족도에 관한 인과모형을 한국의 병원근무자들을 대상으로 실증적으로 검증하고 직무만족도를 결정하는 인과적 요인들을 파악하는데 목적이 있다. 본 모형의 종속변수는 직무만족도이고 독립변수로는 3개집단의 변수들로 크게 분류하여 선정되었는데 첫째, 사회적 변수들로써 직무의 자율성, 직무의 모호성, 직무 갈등, 직무의 양, 상사 및 동료와의 관계, 발전가능성, 직무의 단순성, 분배정의, 승진기회, 물리적 근무환경, 임금 등이며, 둘째, 심리적 변수들로써 기대 충족도, 근무의욕, 적극적 심성, 부정적 심성 등이고, 셋째, 환경적 변수들로써 외부 취업기회와 가족에 대한 책임 등이 사용되었다. 또한 독립변수들이 종속변수에 영향을 미치는데 있어 개인의 가치관이 어떻게 작용하는지도 검증하였다. 자료수집을 위해 대구에 위치한 750병상 규모의 한 대학병원에 근무하는 전직원을 대상으로 자기가 입식 설문조사를 실시하였으며 879매가 회수되어 74.7%의 응답율을 기록하였다. 수집된 자료중 사용 가능한 836명의 응답을 바탕으로 선형구조관계분석(LISREL)과 다중회구분석기법을 이용하여 인과 모형을 검증하였다. 분석결과 직무만족도에 유의한 영향력을 가지는 변수들은 직무의 모호성, 직무의 모호성, 동료관계, 직무의 단순성, 분배정의(이상 시회적 변수), 기대의 총족도, 근무의욕, 적극적 심성, 부정적 심성(이상 심리적 변수), 외부 취업기회(환경적 변수) 등인 것으로 나타났으며 개인의 가치관과 인구학적인 변수들은 직무만족도에 큰 영향을 미치지 못하는 것으로 나타났다. 또한 본 연구에서 사용된 인과모형은 직무만족도의 변이를 75.4% 설명함으로서 기존의 다른 모형들 보다 높은 설명력을 나타내었다. 결론적으로 본 연구에서 사용된 직무만족도의 인과모형은 한국의 조직에서도 적용이 가능한 것으로 보이며, 또한 직무만족도의 일반적 모형은 구조적 변수, 심리적 변수, 그리고 환경적 변수들을 모두 포함하는 포괄적인 모형이 타당하다는 결론을 얻을 수 있었다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.169-174
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• 2018

In general, the methods of the analysis of variance(ANOVA) for the continuous data and the chi-square test for the discrete data are used for statistical analysis of the effect and the association. In multidimensional data, analysis of hierarchical structure is required and statistical linear model is adopted. The structure of the linear model requires the normality of the data. A multidimensional categorical data analysis methods are used for causal relations, interactions, and correlation analysis. In this paper, Bayesian network model using probability distribution is proposed to reduce analysis procedure and analyze interactions and causal relationships in categorical data analysis.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.63-83
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• 2023

Many existing studies have found significant correlations between green spaces, including urban parks, and children's happiness. Furthermore, it was implied that the area/proximity of the urban park would be effective in enhancing infancy happiness. However, inferring causal effects from observed data requires appropriate adjustment of confounding variables, and from this perspective, the causal relationship between the area of urban parks and children's happiness has not been well understood. The causal effect of urban parks on children's happiness was estimated in this study using data from the panel study on Korean children. As methods for adjusting confounding variables, regression adjustment using a regression method, weighting method, and matching method were used, and key concepts of each method were described before the analysis results. Confounders were chosen for the analysis using a directed acyclic graph. In contrast to previous research, the analysis found no significant causal relationship between the size of the city park and children's happiness.

• Environmental and Resource Economics Review
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• v.15 no.3
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• pp.479-504
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• 2006

This paper analyzes a price discovery process for international crude oils including the WTI, Brent and Dubai. Error correction model is employed considering non-stationarity property of crude oil price and the contemporaneous causality is constructed by graph theory to analyze the short-term causality. The empirical analysis for January 4., 1999 to July 15., 2005 reveals that the Brent price interconnects between the WTI price and the Dubai price. This result implies the substantial influence of the Brent price as a marker oil.

• 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.

• Korean Journal of Health Psychology
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• v.16 no.3
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• pp.609-622
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• 2011

The purpose of this study is to investigate the causality between life satisfaction and domain satisfactions. For this study, data were collected from 207 respondents. They completed World Health Organization Quality of Life Assessment Instrument - Brief (WHOQOL-BREF) which is self-report questionnaire asking about life satisfaction and domain satisfactions. For data analysis, the verification procedure by autoregressive crosslagged modeling of structural equation was used. The analysis results of measures showed the causal relation between the two variables, that is, domain satisfactions acted as cause of life satisfaction. There were discussions on the issues about the analysis method of the autoregressive crosslagged modeling, the implications of the results, and the limits of the research. This study ascertained the intervention direction between life satisfaction and domain satisfactions to promote life satisfaction.

• International Area Studies Review
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• v.15 no.1
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• pp.107-133
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• 2011

This paper aims to analyze the causal relationships between agricultural exports and economic growth in the U.S. economy by 50 states. Using the annual data from 1973 to 2007, the theoretical methodologies based on the export-led growth (ELG) model under the static model, the impulse response function (IRF) and forecast error variation decomposition (FEVD) under the vector autoregressive (VAR) model, and the Granger causality test. The results show the causal relationship between agricultural exports and economic growth at the states' level. Especially, the ELG hypothesis is strongly supported in the case of 16 states (HI, ID, KS, MD, MI, MN, NJ, NC, ND, OK, OR, RI, SD, TX, WA, and WI) and is also weakly supported in the case of 31 states. Therefore, the agricultural exports are important factor of developing in the U.S. economy, and furthermore some states (located in coastal area and breadbasket) indicate the strong evidence for agricultural exports-led growth.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.143-151
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• 2000

The purpose of this study is to suggest usefulness of causal relation analysis about categorical data to business administration and other social sciences. Some examples of their application are presented.