• Journal of Distribution Science
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• v.18 no.1
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• pp.107-121
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• 2020

Purpose: Shared mobility services are the most notable in the shared economy; however, they have yet to be activated in Korea due to various regulations and conflicts amongst stakeholders. Nevertheless, shared mobility has become an irresistible trend of the times, as it can cause a great deal of economic and environmental benefits. In this vein, the purpose of this study is to contribute to the revitalization of shared mobility services in Korea and to provide service providers with implications for developing consumer-oriented marketing strategies. Research design, data and methodology: Based on the reasons that the users do not use shared mobility service, the factors influencing the behaviors of shared mobility users are structured and analyzed in a reliable, technical and procedural manner. To this end, the theory of reasoned action (TRA) of Ajzen and Fisbbein, the initial trust model (ITM), task technology fit (TTF) and switching cost (SC) are adopted. A total of 202 questionnaires were collected from the respondents who were aware of shared mobility. Then statistical processing of the collected data used SmartPLS(v.3.2.8), a PLS-SEM (Partial Least Squares Structural Equation Modeling) analysis program. The steps of the analysis are as follows. First, a PLS-Algorithm analysis was performed to evaluate the measurement model, and a Bootstraping and Blindfolding analysis was performed to evaluate the structural model and verify the hypotheses. Second, a multi-group analysis (PLS-MGA) was conducted to further analyze the differences depending on whether or not users experienced shared mobility service. Results: The results showed that initial trusts model (ITM) and task technology fit (TTF) have positive effects on users' behaviors through the mediation of the intention to use. As opposed to the assumption, switching costs did not have negative moderating effects in relation to the intention to use and users' behaviors. The influence of IT self-efficacy was significant, depending on the prior experience to use shared mobility services. Conclusions: This study will contribute to the revitalization of domestic shared mobility services and the formulation of service providers' marketing strategies. In future studies, there is a need to explore, reconstruct, and validate factors other than the impact factors of the shared mobility services used in this research model.

• International Commerce and Information Review
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• v.12 no.2
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• pp.29-57
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• 2010

Global e-Trade system which electronically processes all trade transactions of trading companies is an essential platform where export and import firms enhance international competitiveness. This study is to develop research models suitable for e-Trade and empirically analyze them in order to examine and verify factors affecting e-Trade system of trading companies on the basis of previously-verified studies on global e-Trade such as TAM, TOE, and Task-Technology Fit Model(TTF). Among many factors, this paper comprehensively analyzes an acceptance factor, which is one of the factors affecting the implementation and performance of e-Trade, from the technological, organizational, and environmental context. The finding from this paper will be applied to e-Trade projects carried out by the government in the future by analyzing the correlation between acceptance and performance.

• 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.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.644-654
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• 2013

It is required for enterprises to construct the proper information management system in order to cope with the volatile business situations. The mobile office system is introduced from the needs to provide organization members smart information and mobility. By setting the model, hence, we intend to scrutinize the impact of the task-technology fit model and organizational characteristics of the mobile office system on the job performance. As a result, system quality, information quality and mobility are revealed to affect positively the task-technology fitness and the fitness also affects the job performance positively. Organization characteristics affects the job performance positively through the task-technology fitness, too. Therefore the organization which plans to introduce the mobile office system should consider the task-technology fitness and exert organizational-level efforts to adopt and use the mobile office system in the workplace.

• Korean Management Science Review
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• v.32 no.4
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• pp.135-153
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• 2015

In this paper, we intend to understand distinguishable SNS technology contributions for B2C commerce. In order to theorize this, we draw upon Technology-to-Performance chain (TPC) theory to develop the model that could explain how the technology value of the SNS could be realizable. For the purpose of capturing SNS technology effect to B2C channel effectiveness, on the basis of TPC theory, personal productivity is selected as a performance variable instead of satisfaction from SNS usage. Accordingly, as the antecedents of personal productivity, two variables of locatability and timeliness are extracted to reflect Task-technology-fit (TTF) dimension of performance precursors. For the utilization dimension of TPC framework, convenience and recreation tendency of the personal traits in shopping are included as the precursors of SNS utilization in the sense of reflecting utilitarian and hedonic value of SNS adoption. Empirical validation is conducted with reference to promotion and sales event on Facebook, which is chosen as the typical SNS based B2C commerce scenario. The data analysis result provide useful insights to further investigate the firm's SNS usage potentials for business applications.

• 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 Fashion Business
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• v.18 no.1
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• pp.1-21
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• 2014

This study exceeds the view on the fragmentary fact-finding surveys related to the application of mobile commerce which further develops the evaluation model of fashion mobile commerce website and considers the validity of comprehensive fashion mobile commerce with quality evaluation factors according to the Task-Technology Fit. To fulfill the study objectives, a total of 433 questionnaires are being conducted to the customers with first-hand experience on fashion merchandises through mobile commerce. The judgement sampling method is employed according to the sample population ages from 20s to 30s during two months period. Based on the results of the above-mentioned path analysis, we have observed the following: First, the path relation analysis results show that the M-marketing (M-marketing) between perceived usabilities had effects to the perceived usability and the M-sales had effects to the perceived usability. Second, as seen from the fashion mobile shopping conformance (TTF), the perceived usability, customer satisfaction, and path pipe analysis result conformances between perceived values and immersions have effects of perceived usability, customer satisfaction and perceived value, and thus, indicate that the perceived usability had effects on the customer satisfaction and immersion. Third, the customer satisfaction, perceived value and immersion all have effects on the purchasing intention.

• Informatization Policy
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• v.24 no.1
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• pp.79-99
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• 2017

Despite the early success story, the pan-industry diffusion of big data has been slow mostly due to lack of confidence of the value creation and privacy-related concerns. The problem leads us to the need to a stakeholder analysis on the adoption process of big data. The present study combines technology acceptance model, task-technology fit theory, and privacy calculus theory to integrate the positive and negative factors on the big data adoption. The empirical analysis was performed based on the survey from the current and potential big data users. Results revealed perceived usefulness, task-technology fit, and privacy concern are significant antecedents to the intention to use big data. Furthermore, there are significant differences in the perceptions of each constructs among groups divided by the types of big data use, with several exceptions. And the control effect was found in the magnitude of the relation between independent variables and dependent variable. The theoretical and politic implications of the analysis are discussed as to the promotion of big data industry.

• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.54-67
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• 2021

This paper presents the ISRI (Information Systems Research Indicators) Web tool, publicly and freely available at isri.sciencesphere.org. Targeting Information Systems (IS) researchers, it compiles and organizes IS adoption and use theories/models, constructs, and indicators (measuring variables) available in the scientific literature. Aiming to support the IS theory development process, the purpose of ISRI is to gather and systematize information on research indicators to help researchers and practitioners' work. The tool currently covers eleven theories/models: DeLone and McLean's IS Success Model (D&M ISS); Diffusion of Innovations Theory (DOI); Motivational Model (MM); Social Cognitive Theory (SCT); Task-Technology Fit (TTF); Technology Acceptance Model (TAM); Technology-Organization-Environment Framework (TOE); Theory of Planned Behavior (TPB); Decomposed Theory of Planned Behavior (DTPB); Theory of Reasoned Action (TRA); and Unified Theory of Acceptance and Use of Technology (UTAUT). It also includes currently over 400 constructs, nearly 2,500 indicators, and about 60 application contexts related to the models. For the creation of the tool's database, nearly 580 references were used.