• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.376-390
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• 2013

The purpose of this study are as follows : First, This study conceptually and artificially defines concepts of OCB, absorptive capacity, IT group-efficacy, and TTF. Second, this study confirms the relationship among the KMS performance, the result of using KMS, and the result drawn from OCB, absorptive capacity, group-efficacy, and TTF by the preceding researches, suggesting the research model and verifying through empirical study. Lastly, this study suggests the practical and strategic advices to the groups wanting to get on the edge through KMS. The results of data analysis showed that TTF was found to have a positive influence on KMS performance. IT group-efficacy and absorptive capacity were also found to have a positive effect on TTF. And IT group-efficacy was found to have a positive influence on OCB. The findings are discussed and further research topics are suggested as well.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.6
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• pp.61-69
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• 2016

The purpose of this study is to examine the factors influencing usage intention of social network service (SNS) in social enterprise. This model tests various theoretical research hypotheses relating the social enterprise, task-technology fit (TTF), technology acceptance model (TAM), and usage intention of SNS. The data were gathered from 84 questionnaire respondents. Smart partial least square (PLS) 2.0 have been utilized for deriving the study results. The result of hypothesis testing are as follows. First, TTF positively influence perceived usefulness, perceived ease of use, and usage intention of SNS. Second, perceived usefulness positively influence usage intention of SNS. But perceived ease of use does not influence usage intention of SNS. This study will provide theoretical and practical implications of TTF and usage intention of SNS in social enterprise.

• Information Systems Review
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• v.26 no.1
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• pp.193-218
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• 2024

This study identified factors related to the technological characteristics of conversational generative AI services and the user's task characteristics. Then, it analyzed the effects of task-technology fit on user satisfaction and continued use. The effects of trust, which represents the degree of users' belief in the information provided by generative AI, on task-technology fit, user satisfaction, and user continuance intention were also examined. A survey was conducted among users of various age groups, and 198 questionnaires were collected and analyzed using SmartPLS 4.0 to validate the proposed model. As a result of hypothesis testing, it was confirmed that language fluency and interactivity among technology characteristics and ambiguity among task characteristics significantly affect user satisfaction and intention to continue using via task-technology fit. However, creativity among skill characteristics and time flexibility among task characteristics did not significantly affect task-technology fit, and trust did not directly affect task-technology fit and intention to continue using, but only positively affected user satisfaction. The results of this study can provide meaningful implications for vendors who want to develop and provide conversational generative AI services or companies who want to adopt generative AI technology to improve business productivity.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.4
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• pp.71-90
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• 2014

This study aims at examining the ways which a school librarian uses SNS when performing tasks and the use of SNS with the features of the task and the organizational system run by one person affect task performance. In this study, for objective explanation of the interrelation among a librarian's tasks and the use of SNS and performance, the model of a Librarian's Task-SNS Technology Fit was suggested through the combination of the Technology Acceptance Model and the Task-Technology Fit. Based on the result of the survey analysis, their utilization of SNS is not just limited to personal taste nor interferes with their work. Rather, it enhances task performance owing to the characteristics of the tasks or the organization such as the organizational system run by one person.

• 한국IT서비스학회:학술대회논문집
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• 2008.05a
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• pp.409-415
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• 2008

본 연구는 판매원 개인적 요인 중 서비스 및 과업수행 경험기간을 고려하여 CRM의 기술도구인 영업자동화(Sales Force Automation: SFA이하)시스템을 받아들이는 판매원의 행동특성을 파악하고 그들은 어떤 일관된 신념과 데이터만족에 대한 과업기술적합성 그리고 사용행동을 보이는지 밝히고자 한다. 이는 고객과의 관계에서 실질적인 효과를 높일 수 있는 긍정적이고 적극적인 자세로 주도적인 판매 업무를 강화시키기 위한 것으로 판매원이 SFA 시스템 기술을 단순히 업무상으로 접근하는 것이 아니라 좀 더 효과적으로 기술을 수용하려면 판매원의 심리를 어떻게 파악해야하며 적절한 시스템에 적용 및 데이터 만족에 대한 과업기술적합성과 함께 유도하여 사용행동으로 이끌도록 하는데 의의가 있다.

• Journal of Korea Technology Innovation Society
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• v.10 no.4
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• pp.755-788
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• 2007

This study investigates the effects of individual and group level factors on the use of GSS (Group Support System) and task performance from GSS use. GSS facilitates the group work, so that GSS adoption is not necessarily influenced only by individual perceptions on information systems. Adaptive Structuration Theory (AST) in our study to explain the adoption and success from GSS use. AST contends that the success of IS is not necessarily the technical fit between tasks and technology, instead the political outcome among user socializations. We have the following two research inquires: Are the IS use and performance maximized when information technologies are provided properly?; and, Does TTF always influence positively on IS use (or performance)? To research these issues, we investigate the influence of TTF (Task-Technology Fit) on use and performance of GSS, which is introduced to foster collaboration among organizational members. Drawing insights from the AST, we examine if COA (Consensus on Appropriation) among group members and FOA (Faithfulness of Appropriation) between those who use technology and who design it show any moderating effect. A questionnaire survey was conducted on firms using the GSS for one month from June 2 to June 27 2005 and a sample of 303 responses was used for a statistical analysis. The result demonstrates that TTF exerts a positive influence on use and performance of GSS. We find that the stronger the COA, the greater the effect of W on use of GSS and performance. FOA likewise has a positive effect on both use of GSS and performance. The TTF model has been widely applied to studies on individual performance of information system, whereas the AST theory specifically explains members' adaptation process to information system. By integrating the AST theory with the TTF model, the study contributes to heightening our understanding on if and how individual performance varies with the use of GSS.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.577-586
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• 2014

As SNS has increased its influence on the society as a whole, companies also have started to consider how to take advantage of the new service paying specific attention to its characteristics of immediacy, sharability and interactivity. This study aims to circumstantiate the relationship between a task support tool of SNS and task-media fit, user characteristics and performance by focusing on its usage in work field. To address this issue, a Task-Technology Fit model is used to propose a research model considering the characteristics of SNS as a social element, information technology as well as its user characteristics. The outcome shows that job characteristics, virtual competence and media characteristics have a significant influence on task-media fit, whereas virtual competence and SNS characteristics variables have a significant influence on SNS usage. Besides, task-media fit has a significant influence on SNS usage and work performance while SNS usage has a significant influence on work performance. The study suggests that strategic use of SNS helps improve work performance and these individual characteristics should be considered in planning of SNS utilizing strategy.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.119-130
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• 2015

This study empirically analyzed at domestic manufacturing and service firms to find any moderating effects of enterprise management strategies and information-oriented development strategies between enterprise characteristic factors and IT adoption performance. Task characteristics were analyzed based on information provision extent, system quality and perceived effects while environmental characteristics based on competition extent, external pressure, environmental uncertainty, etc. As a result it was found that strategic suitability factors had a moderating effect between adoption performance and task characteristic variables such as system quality and perceived effect, environmental characteristics such as competition level, external pressure and environmental uncertainty. However, strategy suitability was found not to have any moderating role between task characteristic information provision extent and adoption performance. These findings indicate that enterprises need to plan and implement corporate management strategies and information-oriented development strategies in close coordination for new IT adoption and spread.

• The Journal of Society for e-Business Studies
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• v.16 no.1
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• pp.71-100
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• 2011

There are expectations about future internet technology with IT development by end-users. Cloud computing is attracted to satisfy those demands. However, adoption of cloud computing is not active that much. Therefore, this study verified how cloud computing environment affects performance of team project. We conducted empirical study on performance of team project with cloud computing as technology tool focusing on Task-Technology Fit Model. We collected samples that were undergraduate and graduate school students and had experience on initial cloud computing such as Google-Docs and Webhard when they conducted team project for assignment. We focused on accessibility and reliability as task-technology fit and those variables treated as first order factor. Result showed that cloud computing is suitable technology tool for team project. This study suggests positive effects of cloud computing for collaboration by proving perceived fit and performance in initial cloud computing.