• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.287-308
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• 2023

After launching its service in November 2022, ChatGPT has rapidly increased the number of users and is having a significant impact on all aspects of society, bringing a major turning point in the history of artificial intelligence. In particular, the inference ability of large language models such as ChatGPT is improving at a rapid pace through prompt engineering techniques. This reasoning ability can be considered as an important factor for companies that want to adopt artificial intelligence into their workflows or for individuals looking to utilize it. In this paper, we begin with an understanding of in-context learning that enables inference in large language models, explain the concept of prompt engineering, inference with in-context learning, and benchmark data. Moreover, we investigate the prompt engineering techniques that have rapidly improved the inference performance of large language models, and the relationship between the techniques.

• The Journal of Information Systems
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• v.26 no.4
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• pp.247-284
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• 2017

Purpose The first purpose of this study is to investigate factors that are likely to influence user's intention to adopt third-party mobile payment platform. A comprehensive study about mobile payment services have used various variables to explain user's use intention based on the theory of reasoned action (TRA) or the theory of planned behavior (TPB). Variables such as simplicity, security, costs, relative advantage, individual mobility, subjective norm, trust, satisfaction, attitude towards use, perceived usefulness, perceived ease of use and so on. Among these factors, we expect to find out the most influential factors effecting user's use intention of the third-party mobile payment services. Second, we also examine whether the most influential factors have the same influence to different third-party mobile payment services by conducting comparative study of Alipay and WeChat Pay. Design/methodology/approach Empirical data for this study were collected from Chinese who has the experience using or have used Alipay or WeChat Pay. Participants needed to be familiar with Alipay or WeChat Pay because such users may be more aware of both the advantages and disadvantages of Alipay and WeChat Pay. We conduct a pilot test using Smart PLS 2.0, which includes 50 Alipay users and 82 WeChat Pay users. The result indicates that all the measurement fit for the context. And then 980 questionnaires were mainly sent out to the college students and the e-mails users randomly. To encourage participation, we give the participants a small gift as a present. Finally, we received a total of 683 replied. Data from respondents who gave incomplete or invalid answers were excluded to assure the validity of the constructs. 79 questionnaires were rejected, finally the valid data are 604 (with 372 Alipay users and 232 WeChat Pay users). Findings The results suggest that users' intention is determined by their trust on third-party mobile payment service and perceived usefulness of use. Comparative study results also indicated that the factors have different influence on Alipay group and WeChat Pay group, which offers a new aspect for academic field, and provides useful information to mobile payment service providers in China.

• Journal of Distribution Science
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• v.14 no.8
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• pp.35-44
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• 2016

Purpose - This study aims to understand the relationship between Chinese local SNS usage and social capital building through Chinese international students in South Korea. A research model that illustrates the relationship between the SNS usage (i.e., intensity, communication and social capital building is proposed. Based on the analysis, this study will provide responses to the question of if SNS really presents the danger of trapping international consumers in their local comfort zone or enhance social capital for the users. Research design, data, and methodology - The survey questionnaire is circulated among the WeChat (a Chinese local SNS) users who are the Chinese international students studying in South Korea. The collected data is analyzed by structural equation method using SPSS and AMOS. Results - Proposed hypotheses of the positive relationships between the attachment of SNS use and both individuals' bridging and bonding social capital are supported. It's also supported that (1) interpersonal communication, (2) interpersonal communication with old friends, and (3) interpersonal communication for making new friends on SNS positively influence individuals' bridging social capital. Conclusions - This paper demonstrates the importance of intensity of WeChat use and interpersonal communication that impact Chinese international students' bridging and bonding social capital on WeChat.

• Knowledge Management Research
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• v.22 no.1
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• pp.287-308
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• 2021

This study aims to explore how the effects of the perceived social presence on trust and live chat adoption intention vary with the types of live chats in e-commerce context. As technology develops, live chat with the seller in e-commerce is rapidly replaced by AI-assisted live chat called chat-bot. However, it is not well known how the buyers perceive the difference between the chat with seller and the chat-bot. This study therefore proposes first, the perceived social presence toward the seller will influence trust and the live chat adoption. Second, the effects of social presence will be stronger when using live chat with seller than using chat-bot. To validate, we collect data from 232 e-commerce users and confirm the first proposition. However, the higher level of the social presence effect of live chat with seller is not clearly revealed. This study is expected to provide researchers and managers who are interested in AI-based chatbots with useful theoretical and practical implications.

• Journal of Information Technology Applications and Management
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• v.31 no.3
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• pp.149-163
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• 2024

As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.347-373
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• 2023

As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.6
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• pp.91-101
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• 2019

Tourism or travel business consists of a set of services for people who visit exotic places. Payment is usually marking the end of the series of activities relating to tourism, and it becomes the linkage for the next activity. With the recent advancement of mobile Fintech technologies, we have learned that more convenient and more secure financial transactions are improving the quality of tourism. It should be noted that tourism counts on information technology heavily in terms of mobile Internet and smart devices use, which yields to a wide business opportunities for Fintech startups. However, payment information has not been highlighted for additional marketing promotion activities. The lack of research into information technology-based business models that extend Fintech services related to payment in venture start-up studies hinders the understanding of the possibility of creating new business through the value creation process after payment. This study attempts to investigate this issue based on the theory of smart tourism and service-dominant logic with developing a new information system. More specifically, marketing promotion activities after payment for Chinese tourists visiting Korea are examined. Specifically, WeChat Pay and instant tax refund service were considered while the system was developed by following desing science research methodology. This study is meaningful in that it finds a new possibility of Fintech business model by applying scientific and academic methods, and it reminds the necessity of service automation system centered on instant tax refund.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.125-144
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• 2023

Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.

• International Journal of Contents
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• v.10 no.3
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• pp.64-72
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• 2014

This study explored the elements that affect team achievements in virtual environments. In this study, consideration was given to the role of group dynamics in facilitating productive interaction. We aspired to reveal the mechanisms of group dynamics and examined how group dynamics affected team achievements in virtual environments. The empirical study was performed with undergraduate students enrolled in an e-learning course. In collaboration with other majors, students executed team projects and managed project issues in forums or chat rooms. The results of the empirical study indicated that leadership, creative friction, and group cohesion (components of group dynamics) had positive relationships with team achievements. The findings confirmed that addressing creative conflict is a method to improve team performance and that leadership is a key factor in project teams.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.151-158
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• 2018

As the competition of 21 cyber universities in Korea has been on a continual increase, they are focusing on improving the quality of the e-learning education in cyber universities. In this study, we intended to derive the failure factors of the previous chatting system in the 2010s and the success factors from previous studies. Next, we identified priorities among five factors(Reliability, UI Convenience, Usability, Network effect, Operational policy) using AHP and the practical ways to implement the chatting service. We applied the chatting system to all the curriculums of S cyber university. Our study finds that the chat service affects the satisfaction of education. Finally, we propose the utilization plan to improve the e-learning education of cyber university through the findings of this research.