• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3992-4005
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• 2018

In our current information-based society in which knowledge is a fundamental asset to production, the capability to utilize information and produce knowledge with the use of information technology (IT) has become essential to learning. Massive Open Online Courses (MOOCs) have recently been introduced in light of such changes and are recognized as an alternative to open education. MOOCs' capabilities are being acknowledged in lifelong education in terms of reeducation and knowledge sharing, and also in terms of improving teaching quality, and improving university students' levels of creativity and integrated thinking by supporting high-level content and teaching. Therefore, this study presents an extended research model that combines information system (IS) continuance and task-technology fit models. Our study researches previous literature, revealing factors of continuous use after accepting MOOCs from the learner's perspective, and analyzes the model empirically. The ideal environment for MOOCs learners is evaluated, and a strategic approach to the successful settlement and diffusion of MOOCs is presented based on this study's findings.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.133-153
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• 2021

Recently, organizations are making significant technology investments to build a centralized content management system. However, high-quality technology adoption can conversely create techno-stress in the user and cause negative behavior. The purpose of this study is to suggest the negative effects and mitigation directions of enterprise content management system(ECMS) related techno-stress. In order to verify the hypothesis, this study conducted a questionnaire survey on employees of organizations that adopted content management technology and conducted structural equation modeling. As a result of the analysis, ECMS related techno overload and complexity decreased the intention of continuous use of ECMS. But, internal communication activities reduced ECMS related techno stress and task-technology fit moderated the relationship between techno-stress and intention of continuous use of ECMS. The study has implications in terms of suggesting a strategic direction to minimize the negative causes of the use of content management systems.

• 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.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.189-214
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• 2012

In recent years, the innovative management tool of Business Process Management (BPM), has begun to reorganize business processes to enhance firms' operational performance. As practitioners have identified a number of failed BPM projects, research has begun to consider the Critical Success Factors (CSFs) for successful BPM implementation. However, these research works have not yet been properly theoretically grounded in being able rigorously to classify and then compare different BPM implementation practices. The main objective of this paper is thus to identify a theoretical basis for BPM implementation. The paper proposes a combined theoretical framework of dynamic capability and task-technology fit to identify CSFs for BPM. This basis is then used to interpret three different case studies of BPM implementation in Korea.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.1025-1032
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• 2021

The study investigates factors affecting the loyalty of Food Delivery Application (FDA) service in Thailand. This study employs quantitative research methodology with a non-probability sampling method to draw 510 FDA samples from the FDA users in Thailand. The online questionnaires with a Cronbach's alpha coefficient of 0.886 were used as a research tool to collect data from samples. By using the Structural Equation Modeling (SEM) to analyze data, the results show that trustworthiness, social influence, system design, and task-technology fit affect the user's technology acceptance, which also show the significant relationship with the loyalty of FDA users in Thailand. The study checks the harmony with the statistics; χ2 = 258.686, df. =160, χ2/df. = 1.616, p-value = 0.050, CMIN/DF = 1.616, GFI = 0.960, AGFI = 0.969, TLI = 0.953, CFI = 0.965, RMSEA = 0.047, significant level at 0.05, along with testing the weight factor. In conclusion, the research model was harmonious with the empirical data at the significant level 0.05. The finding of this study suggested that the FDA service provider might apply this research finding to develop a greater understanding of the FDA's customer loyalty, as well as determine marketing strategies, identify opportunities, and create a competitive advantage in the future.

• Journal of Information Technology Applications and Management
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• v.22 no.1
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• pp.37-60
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• 2015

As the dependence on information systems in enterprises has grown dramatically, the importance of implementing information systems in audit has been increased as well. However, there is a lact of about utilization of information system for audit process. Thus, this study is to investigate the factors that effect auditor's adopting Data Analytics to audit work. Through literature research and focus group interview, we added two factors that affect the behavioral intention to UTAUT model. We have selected performance expectancy, effort expectancy, social influence, facilitating conditions, anxiety, task fit, behavioral intention as variables and verified hypotheses based on survey questionnaires from auditors. As a result, it was found that performance expectations, social influence, task fit influenced the behavior intention. In Addition, we analyzed adding two variables, IT-related work experience and type of auditor as moderate variable. This study has an implication for companies to motivate implementation as well as activation of Data Analytics technique.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.37-64
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• 2022

As the social acceptance of artificial intelligence increases, the number of cases of applying machine learning methods to companies is also increasing. Technical factors such as accuracy and interpretability have been the main criteria for selecting machine learning methods. However, the success of implementing machine learning also affects management factors such as IT departments, operation departments, leadership, and organizational culture. Unfortunately, there are few integrated studies that understand the success factors of machine learning selection in which technical and management factors are considered together. Therefore, the purpose of this paper is to propose and empirically analyze a technology-management integrated model that combines task-tech fit, IS Success Model theory, and John Rice's algorithm selection process model to understand machine learning selection within the company. As a result of a survey of 240 companies that implemented machine learning, it was found that the higher the algorithm quality and data quality, the higher the algorithm-problem fit was perceived. It was also verified that algorithm-problem fit had a significant impact on the organization's innovation and productivity. In addition, it was confirmed that outsourcing and management support had a positive impact on the quality of the machine learning system and organizational cultural factors such as data-driven management and motivation. Data-driven management and motivation were highly perceived in companies' performance.

• Journal of Information Technology Services
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• v.12 no.1
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• pp.15-32
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• 2013

The concrete information technology (IT) has affected ways for supporting agricultural products. However, studies relating IT to agriculture in a broader sense have not been prevalent. The objective of this study is to improve agencies' effectiveness and performance in the use and application of IT through understanding the organizational fit and misfit. This research applied a multi-contingency view to Korean IT supporting agricultural promotion agencies and it evaluated the competitiveness of these agencies with reference to the correspondence of factors (Goal, Strategy, Environment, Knowledge Exchange, Task Design, and Information System) affecting their performance with organizational goals. The results reveal that organizations with good performance show better organizational fit with their organizational goal. This study contributes to the ways of efficient IT management in agricultural organizations in Korea.

• Journal of Information Technology Applications and Management
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• v.24 no.3
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• pp.1-21
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• 2017

Business Intelligence (BI) system is a strategic tool that presents an analytical perspective about business and external environments. Even though its strategic value was well known, users often avoid using it or adopt it ceremonially. In fact, over 50 per cent of BI projects worldwide are reported to end in failure. Such an unexpectedly lower success rate has been a key issue in BI studies. In order to enhance a proper use of information systems, MIS field provided a number of theoretical constructs. One example is Goodhue & Thompson's Task-Technology Fit (TTF). In addition, internalization, the degree to which people make their own effort to modify behavior, was recently suggested as another important determinant of use. Though in MIS community both TTF and internalization proved to be a key determinant of system use, there has been not much study aiming to discover antecedents influencing these constructs. In this study we assert that user participation should be highlighted in BI projects. Especially, we emphasize user participation at the phase of feasibility study that is mainly conducted to determine whether a BI system is essentially necessary and practicable. Our research model employs participative feasibility study as a major antecedent for TTF and internalization that consequently will lead to user satisfaction and actual use. This model was empirically tested on 121 BI system users. The result shows that user participation in feasibility study is positively associated with TTF and internalization, each being related to user satisfaction and system use. It implies that, if an organization has BI users get involved in strategic feasibility study phase, the BI system would turn out to fit users' tasks and, furthermore, users would put more efforts spontaneously in order to use it properly.