• The Journal of Asian Finance, Economics and Business
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• 제9권5호
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• pp.225-237
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• 2022

The term "artificial intelligence" is considered a component of sophisticated technological developments, and several intelligent tools have been developed to assist organizations and entrepreneurs in making business decisions. Artificial intelligence (AI) is defined as the concept of transforming inanimate objects into intelligent beings that can reason in the same way that humans do. Computer systems can imitate a variety of human intelligence activities, including learning, reasoning, problem-solving, speech recognition, and planning. This study's objective is to provide responses to the questions: Which factors should be taken into account while deciding whether or not to use AI applications? What role do these elements have in AI application adoption? However, this study proposes a framework to explore the significance and relation of success factors to AI adoption based on the technology-organization-environment model. Ten critical factors related to AI adoption are identified. The framework is empirically tested with data collected by mail surveying organizations in Vietnam. Structural Equation Modeling is applied to analyze the data. The results indicate that Technical compatibility, Relative advantage, Technical complexity, Technical capability, Managerial capability, Organizational readiness, Government involvement, Market uncertainty, and Vendor partnership are significantly related to AI applications adoption.

• 유통과학연구
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• 제21권1호
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• pp.53-63
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• 2023

Purpose: Big Data analytics (BDA) has been recognized to improve firm performance because it can efficiently manage and process large-scale, wide variety, and complex data structures. This study examines the determinants of Big Data analytics adoption toward marketing and financial performance of global logistic companies in Thailand. The research framework is adopted from the technology-organization-environment (TOE) model, including technological factors (relative advantages), organizational factors (technological infrastructure and absorptive capability), environmental factors (industry competition and government support), Big Data analytics adoption, marketing performance, and financial performance. Research design, data, and methodology: A quantitative method is applied by distributing the survey to 450 employees at the manager's level and above. The sampling methods include judgmental, stratified random, and convenience sampling. The data were analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The results showed that all factors significantly influence Big Data analytics adoption, except technological infrastructure. In addition, Big Data analytics adoption significantly influences marketing and financial performance. Conversely, marketing performance has no significant influence on financial performance. Conclusions: The findings of this study can contribute to the strategic improvement of firm performance through Big Data analytics adoption in the logistics, distribution, and supply chain industries.

• Asia pacific journal of information systems
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• 제19권1호
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• pp.33-62
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• 2009

Internet computing is a disruptive IT innovation. Semantic Web can be considered as an IT innovation because the Semantic Web technology possesses the potential to reduce information overload and enable semantic integration, using capabilities such as semantics and machine-processability. How should organizations adopt the Semantic Web? What factors affect the adoption and diffusion of Semantic Web innovation? Most studies on adoption and diffusion of innovation use empirical analysis as a quantitative research methodology in the post-implementation stage. There is criticism that the positivist requiring theoretical rigor can sacrifice relevance to practice. Rapid advances in technology require studies relevant to practice. In particular, it is realistically impossible to conduct quantitative approach for factors affecting adoption of the Semantic Web because the Semantic Web is in its infancy. However, in an early stage of introduction of the Semantic Web, it is necessary to give a model and some guidelines and for adoption and diffusion of the technology innovation to practitioners and researchers. Thus, the purpose of this study is to present a model of adoption and diffusion of the Semantic Web and to offer propositions as guidelines for successful adoption through a qualitative research method including multiple case studies and in-depth interviews. The researcher conducted interviews with 15 people based on face-to face and 2 interviews by telephone and e-mail to collect data to saturate the categories. Nine interviews including 2 telephone interviews were from nine user organizations adopting the technology innovation and the others were from three supply organizations. Semi-structured interviews were used to collect data. The interviews were recorded on digital voice recorder memory and subsequently transcribed verbatim. 196 pages of transcripts were obtained from about 12 hours interviews. Triangulation of evidence was achieved by examining each organization website and various documents, such as brochures and white papers. The researcher read the transcripts several times and underlined core words, phrases, or sentences. Then, data analysis used the procedure of open coding, in which the researcher forms initial categories of information about the phenomenon being studied by segmenting information. QSR NVivo version 8.0 was used to categorize sentences including similar concepts. 47 categories derived from interview data were grouped into 21 categories from which six factors were named. Five factors affecting adoption of the Semantic Web were identified. The first factor is demand pull including requirements for improving search and integration services of the existing systems and for creating new services. Second, environmental conduciveness, reference models, uncertainty, technology maturity, potential business value, government sponsorship programs, promising prospects for technology demand, complexity and trialability affect the adoption of the Semantic Web from the perspective of technology push. Third, absorptive capacity is an important role of the adoption. Fourth, suppler's competence includes communication with and training for users, and absorptive capacity of supply organization. Fifth, over-expectance which results in the gap between user's expectation level and perceived benefits has a negative impact on the adoption of the Semantic Web. Finally, the factor including critical mass of ontology, budget. visible effects is identified as a determinant affecting routinization and infusion. The researcher suggested a model of adoption and diffusion of the Semantic Web, representing relationships between six factors and adoption/diffusion as dependent variables. Six propositions are derived from the adoption/diffusion model to offer some guidelines to practitioners and a research model to further studies. Proposition 1 : Demand pull has an influence on the adoption of the Semantic Web. Proposition 1-1 : The stronger the degree of requirements for improving existing services, the more successfully the Semantic Web is adopted. Proposition 1-2 : The stronger the degree of requirements for new services, the more successfully the Semantic Web is adopted. Proposition 2 : Technology push has an influence on the adoption of the Semantic Web. Proposition 2-1 : From the perceptive of user organizations, the technology push forces such as environmental conduciveness, reference models, potential business value, and government sponsorship programs have a positive impact on the adoption of the Semantic Web while uncertainty and lower technology maturity have a negative impact on its adoption. Proposition 2-2 : From the perceptive of suppliers, the technology push forces such as environmental conduciveness, reference models, potential business value, government sponsorship programs, and promising prospects for technology demand have a positive impact on the adoption of the Semantic Web while uncertainty, lower technology maturity, complexity and lower trialability have a negative impact on its adoption. Proposition 3 : The absorptive capacities such as organizational formal support systems, officer's or manager's competency analyzing technology characteristics, their passion or willingness, and top management support are positively associated with successful adoption of the Semantic Web innovation from the perceptive of user organizations. Proposition 4 : Supplier's competence has a positive impact on the absorptive capacities of user organizations and technology push forces. Proposition 5 : The greater the gap of expectation between users and suppliers, the later the Semantic Web is adopted. Proposition 6 : The post-adoption activities such as budget allocation, reaching critical mass, and sharing ontology to offer sustainable services are positively associated with successful routinization and infusion of the Semantic Web innovation from the perceptive of user organizations.

• 지식경영연구
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• 제16권1호
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• pp.117-142
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• 2015

Recently, the personal cloud computing service has been being spotlighted as an individual tool of productivity enhancement. However, compared to the rosy forecast, its diffusion rate in the domestic (Korean) market is much slower than expected. In order to find the reason for the slow growth of personal cloud computing service, we attempt to identify influencing factors on user's adoption resistance, while most prior research has focused on the factors affecting its adoption. Based on both the person-technology fit model and the privacy calculus model, we propose technostress and perceived value as key antecedents of adoption resistance. In addition, we identify (1) technical (pace of change and complexity) and personal (self-efficacy) influencing factors on technostress, and (2) beneficial (perceived mobility and perceived availability) and harmful (perceived vulnerability) influencing factors on perceived value. To validate our research model, 133 individual samples were gathered from undergraduate and graduate students who had actual experience of using at least one of personal cloud computing services. The results of the structural equation modeling confirm that both technostress and perceived value have significant effects on adoption resistance, but they have different influencing mechanisms to different types of adoption resistance (indifference, postponement, and rejection). Theoretical and practical contributions are discussed in the conclusion.

• The Journal of Asian Finance, Economics and Business
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• 제8권2호
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• pp.833-849
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• 2021

Cloud accounting represents a new area of accounting information systems. Past research has often focused on accounting information systems and its antecedents, rather than factors that adopt cloud accounting system. The purpose of this paper is to explain the factors that influence the adoption of cloud accounting in the financial sectors. This paper applied the technology acceptance model (TAM), technology-organization-environment, and the De Lone and Mc Lean model, coupled with proposed factors relevant to cloud accounting. The proposed model was empirically evaluated using survey data from 187 managers (financial managers, IT department managers, audit managers, heads of accounting departments, and head of internal control departments) in Jordanian bank branches. Based on the SEM results, top management support, organizational competency, service quality, system quality, perceived usefulness, and perceived ease of use had a positive relationship with the intention of using cloud accounting. Cloud accounting adoption positively affected cloud accounting usage. This paper contributes to a theoretical understanding of factors that activate the adoption of cloud accounting. For financial firms in general the results enable them to better develop cloud accounting framework. The paper verifies the factors that affect the adoption of cloud accounting and the proposed cloud accounting model.

• Journal of Information Technology Applications and Management
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• 제10권1호
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• pp.47-59
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• 2003

This study analyses the level of resistance which workers have against the adoption of ERP systems and the factors affecting the resistance to the adoption of the new systems. The major results of the study include 1) about 40% of workers showed resistance to the adoption of ERP systems, and 2) all six factors (technical characteristics of ERP system, functional characteristics of ERP system, implementation approach, task changes caused by the adoption of ERP system, attitude toward change, and altitude toward organization) were proved to affect the resistance to the adoption of the ERP systems. In practice, adoption of ERP system brings significant changes to workers. In order for an organization to succeed, it is necessary to reduce the resistance of workers. Since this study is performed based on a case study, the results of the study may not be generalized. However, the results of the study may provide guidance which organizations can refer in the course of effective personnel management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.18-37
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• 2016

Cloud computing is an upcoming technology and emerging concept in the field of information technologies. Companies have begun to invest in cloud computing with the expectation that it will improve their business performances, operations, and processes. However, many companies are not so much aware of the cloud computing, so they can hesitate to adopt this new technology. The aims of the study are analyzing factors affecting the adoption of cloud computing and applying structural equation modeling technique to analyze the important dimensions of the adoption. Concordantly, previous studies are examined and expert interviews are arranged. Based on both our literature review and expert interviews, a model is proposed to measure the adoption of cloud computing. It is obvious that there are scarce researches about cloud computing adoption in the literature. Thus, the originality of the paper lies on that it proposes a research model for cloud computing adoption and it investigates various dimensions of cloud computing adoption in detail.

• The Journal of Asian Finance, Economics and Business
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• 제9권9호
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• pp.75-91
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• 2022

This study assesses the Internet banking adoption tendency by existing bank customers of Bangladesh. Currently, almost all the leading banks in the country have implemented Internet banking platforms. However, the active user count remains relatively low and there hasn't been any conclusive research on the drivers and inhibitors of Internet banking. This study evaluates the reasons and quantitatively establishes the factors leading to the adoption and usage continuance of internet banking by existing bank customers. Responses from 460 bank account holders were collected via online questionnaires using a purposive sampling approach, and a core conceptual framework based on Technology Acceptance Model (TAM) and Technology Readiness Index (TRI) was used. The study concluded that internet banking adoption is significantly impacted by the ease of use, customer service, and technology familiarity. Similarly, customer satisfaction is affected by the perceived value and the perceived risk. Through regression analysis, it was found that usage continuance is 89% explained by adoption and customer satisfaction. Multi-group moderation showed significant impact by groups divided based on usage frequency, income level, and age. Perceived risk weakened the impact of perceived value and technology familiarity on usage adoption. Additionally, perceived risk reduced the impact of consumer satisfaction and usage continuance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권3호
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• pp.610-632
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• 2024

Mobile Learning (M-learning) adoption and success in supporting students' learning engagement mainly depend on many factors. Therefore, this study systematically reviews the literature, synthesizes and analyzes the predictors of M-learning adoption, and uses success for students' learning engagement. Literature from 2016 to 2023 in various databases is covered in this study. Based on the review's findings, the factors that influence students' learning engagement when it comes to M-learning usage and adoption, can be divided into technical, pedagogical, and social factors. More specifically, technical factors include mobile devices availability and quality, connectivity to the internet, and user-friendly interfaces, pedagogical factors include effective instructional design, teaching methods, and assessment strategies, and social factors include motivation of students, social interaction and perceived enjoyment - all these factors have a significant impact on the M-learning adoption and use success. The findings of the review also indicated that M-learning has a key role in enhancing the learning engagement of students through different ways, like increasing their motivation, attention, and participation in their process of learning, paving the way for interaction and building relationships opportunities with peers and instructors, which in turn, can lead to strengthening the learning environment. The implications of these findings extend beyond immediate educational contexts, offering vital insights for future educational technology strategies and policy decisions, particularly in addressing global educational challenges and embracing technological advancements in learning.

• Asia pacific journal of information systems
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• 제33권3호
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• pp.652-676
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• 2023

The objective of this study is to provide a deeper understanding of the factors that lead to the development and adoption of AI-based chatbots. We analyze the structural relationship between the organizational (externalities), systematic (fit), and the consumer-related (psychological) factors and their role in the adoption of AI-based chatbots. Founded on the theories of task-technology fit and network externalities, we present a conceptual model overlooking common perception-based theories (e.g., Technology Acceptance Model). We collected 380 responses from Indian banking consumers to test the model using the PLS-SEM method. Interestingly, the findings present a positive impact of all factors on consumers' intention to adopt AI-based chatbots. However, the interplays between these factors provide a mixed perspective for literature. Apart from employing a combination of factors that have been used to study technology adoption, our study explores the importance of externalities and their relationship with fit factors, a unique outlook often overlooked by prior research. Moreover, we offer a clear understanding of latent variables such as trust, and the intricacies of their interplays in a novel context. Thereby, the study offers implications for literature and practice, followed by future research directions.