• East Asian Economic Review
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• 제26권3호
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• pp.227-253
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• 2022

Despite the proliferation of free trade agreements (FTAs), many exporting firms are still confronted with several challenges in utilizing the FTA preferential tariffs. Based on the Technology-Organization-Environment (TOE) framework, this study empirically examines the factors affecting the utilization of FTA schemes by exporting firms. To clarify the key factors influencing FTA utilization, this study develops a conceptual model from the perspective of the adoption of information technology innovations. Eight factors derived from the TOE framework are proposed to explore the determinants of FTA utilization in export. Partial least squares structural equation modeling is employed to analyze the data collected from 162 exporting small- and medium-sized enterprises in the South Korean textile industry. The findings reveal that compatibility and trading partner influence are positively associated with FTA utilization, while complexity is negatively related. Factors of organizational context do not show any relationship with FTA utilization. This study is the first to theoretically analyze and empirically test the determinants of FTA utilization from the perspective of technological innovation adoptions. By examining the relative importance of TOE factors in the utilization of FTA schemes, this study expects to advance a holistic understanding on the perceived factors that could potentially affect the utilization of FTA schemes.

• 컴퓨터교육학회논문지
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• 제8권5호
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• pp.63-72
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• 2005

본 연구는 초중고학생들의 웹 교육정보 시스템인 에듀넷의 활용 결정에 영향을 미치는 변수들을 찾아냄으로써 에듀넷 활용 확산을 위한 방안을 모색하고자 하였다. 이를 위해 혁신의 확산 이론과 웹 활용 교육에 대한 관련 선행연구들의 조사를 통해 에듀넷 활용에 영향을 미칠 것으로 예상되는 변수로써 혁신의 속성(상대적 유용성, 적합성, 복잡성), 혁신성, 자기효능감, 주관적 판단, 지원을 추출하였다. 설문 조사는 서울.경기 지역의 초등학교 5, 6학년 315명을 대상으로 실시하였으며, 응답결과는 로지스틱 회귀분석 방법을 이용하여 분석하였다. 분석 결과, 혁신의 속성, 혁신성, 자기효능감, 주관적 판단, 지원을 포함한 회귀 모형의 적합성이 검정되었으며, 주관적판단, 지원이 에듀넷활용 여부를 결정짓는데 유의미한 영향을 미치는 변수로 확인되었다.

• 한국정보시스템학회지:정보시스템연구
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• 제25권4호
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• pp.163-179
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• 2016

Purpose This study investigates the associations between SNS fatigue and stress of smartphone SNS, with SNS characteristics. The study focuses on two types of SNS characteristics: information and systems characteristics. We examine SNS stress factors that includes the communication and system overload. Design/methodology/approach To test the proposed hypotheses, the study conducted structural equation modeling with Smart PLS 3.0. The study conducted A sample of 286 participants was collected from SNS users. Findings The results indicated that the information relevance in the information characteristics had an effect on the communication overload, but it had not an effect on the system overload. The information accuracy had an effect on the communication and system overload. The app pace of change influenced the communication and system overload, but the app complexity influenced the system overload. Finally, the SNS stress showed significant relationship with SNS fatigue. The academic and managerial implications were discussed based on the this results.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.1082-1087
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• 2006

Human factors still plays a significant role in railway accidents. The accidents often resulted from multiple causes of hardware failures and human errors. So to ensure the safety of railway operations, human error should be effectively prevented and managed. Among several factors influencing human performance, task load (or task complexity) is well known as a major contributor to human error. In order to reduce the potential of human error, a systematic analysis should be undertaken to evaluate task load and to reduce it by modifying task process and/or education&training. In this paper, we proposed a systematic framework for railway industry to perform task analysis and to evaluate task load, and applied it to KTX operational tasks. According to the application study, we identified 14 generic task types of KTX operation. And also this paper shows the quantitative task load of those generic tasks which were analyzed by NASA-TLX method.

• 한국주거학회논문집
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• 제19권5호
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• pp.37-46
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• 2008

The purpose of this study is to derive and adapt the Valuation Factor of urban regeneration scientifically and synthetically, which is the basis of developing a rational plan for urban revitalization. For this, we have selected 37 factors relating to urban regeneration as outlined in preceding studies and inquiry about importance of factors. we analysed he Valuation factors influencing he importance of urban revitalization through a questionnaire which was completed by inhabitants and expert groups in Gwangju Metropolitan City. From he results of he Factor analysis using SPSSWIN(VER.14.0), it was found that the factors which influence the importance of urban regeneration are Environment, Function, Resources and Policy Factors. Environment Factor comprises amenity, culture, beauty and convenience, The while the Function Factor comprises interchange, information, complexity and security. This classification has credibility because of the high factor loading through the Varimax Factor Analysis and is due to a high Cronbach's coefficient. There is a strong correlation between the classified factors through correlation analysis. Finally, through AMOS (Analysis of Moment Structure) 16.0 it was found that the upper classification is credible because main suitability index confirms recommending an admission standard.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 봄 학술논문 발표대회
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• pp.151-152
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• 2021

The sale price of apartment buildings is a key factor in the success or failure of apartment projects, and the factors that affect the sale price of apartments vary widely, including location, environmental factors, and economic conditions. Existing methods of predicting the sale price do not reflect the nonlinear characteristics of apartment prices, which are determined by the complex impact factors of reality, because statistical analysis is conducted under the assumption of a linear model. To improve these problems, a new analysis technique is needed to predict apartment sales prices by complex nonlinear influencing factors. Using machine learning techniques that have recently attracted attention in the field of engineering, it is possible to predict the sale price reflecting the complexity of various factors. Therefore, this study aims to conduct a basic study for the development of a machine learning-based prediction model for apartment sale prices.

• 아태비즈니스연구
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• 제12권3호
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• pp.1-36
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• 2021

Purpose - This empirical study, aims to identify the determinants of adoption and acceptance of mobile payment as to understand why it is successful in some countries in Sub-Saharan Africa but failing in others. A comparative study of a successful mobile payment service and a purported failed one was done as to have some insights to the factors affecting acceptance of the technology. Design/methodology/approach - The strength of three notable theories: theory of diffusion of innovation (DOI), the extended unified theory of user acceptance of information technology (UTAUT2) and self-efficacy theory were use. The self-efficacy of government support inclusion as, a moderating variable in the form of infrastructure, securing transaction and price value revealed the relevance of government in the success of mobile payment service. By means of a field survey of 705 subjects in two separate regions of Africa (East and West), the data was collected and use to test the research model. Findings - The study result shows the importance of the moderating factor of government support to the success of mobile payment of any nation. The result also shows the importance of the perception of relative advantage, compatibility, complexity, social influence as already revealed by other studies. Research implications or Originality - Mobile payment success in some part of Sub-Saharan Africa is well known but also suggested to fail in some Sub-Saharan African countries. Buttressing the need for understanding of the factors affecting mobile payment acceptance. This article empirically examined the factors influencing the success of mobile payment, and we implicated that if the implementation of mobile payment is to be successful for mobile commerce in any nation, adoption, acceptance and use by its citizen is imperative.

• 유통과학연구
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• 제14권11호
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• pp.37-47
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• 2016

Purpose - Many countries nowadays look at cloud computing as an opportunity because it holds great advantages for governments. Public sector in Yemen still uses traditional computing. This study tends to explore the factors that would affect cloud computing adoption in government organizations in Yemen. Research design, data and methodology - We used a combination of DOI theory and TOE framework with some changes to suit the context of government organizations. Eight hypotheses were proposed with a questionnaire developed and sent to people in Yemen. 118 responses were collected to assess the hypotheses. Results - Results indicate that Yemen lacks some prerequisites of cloud technology in terms of technological readiness and regulations. The factors: relative advantage, compatibility, security concern, perception of benefits and government support were accepted. Perception of benefits, in particular, is found to affect the decision of adoption. Security concern also showed a direct and indirect influence on cloud adoption in the government. Respondents consider security a key issues of the technology. The factors: complexity, technology readiness and regulatory support were rejected. Conclusions - Based on all analysis results, this study proposed some steps toward adopting cloud computing in Yemen.

• 지식경영연구
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• 제9권3호
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• pp.77-105
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• 2008

This study primarily aims at identifying what factors significantly affect the diffusion of knowledge management systems(KMS) and finding out how these identified factors can be effectively managed, especially for Korean companies. The research model is derived based on previous researches on innovation diffusion, information systems implementation, and KMS. The model is used to examine the role of determinants in influencing the extent to which KMS is diffused within organizations. Independent variables of this research are composed of technical characteristics, organizational characteristics and environmental characteristics. 'Breadth of diffusion' and 'depth of diffusion' concept are used to measure the extent of KMS diffusion which is the dependent variable of this model. The 101 companies of total 1,000 samples responded to the survey. To analyze tile results of this empirical study, we performed the multiple regression analysis. As a result, it was shown that the relative advantage, complexity, information system maturity, size, top management support, champion, competitive pressure have influences on both the breadth and the depth diffusions. On the other hand, the organizational culture, valuation and compensation, and uncertainty of environmental factors were not verified to be significant. This empirical study will provide Korean companies with insights into effective ways to diffuse the KMS and succeed in business competition.

• 대한안전경영과학회지
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• 제26권3호
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• pp.101-106
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• 2024

The health and working conditions of employees have become increasingly important issues in modern society. In recent years, there has been a continuous rise in problems related to the deterioration of workers' alth, which seriously affects their safety and overall quality of life. Although existing research has investigated various factors affecting workers' health and working conditions, there is still a lack of studies that scientifically analyze and identify key variables from the vast number of factors. This study employs the Lasso (Least Absolute Shrinkage and Selection Operator) technique to mathematically analyze the key variables influencing workers' health status and satisfaction with their working environment. Lasso is a technique used in machine learning to identify a small number of variables that impact the dependent variable among a large set of variables, thereby reducing model complexity and improving predictive accuracy. The results of the study can be utilized in efficiently improving workers' health and working environments by focusing on a smaller set of impactful variables.