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Although location-based augmented reality (AR) games are popular in recent years, the motivation of in-app purchases still needs further investigation. The purpose of this paper is to investigate the antecedents of the intention to make a purchase in location-based AR games.

This research develops a conceptual model and hypotheses based on the theory of perceived values and satisfaction to investigate the antecedents. An online questionnaire was developed and distributed on popular websites to collect data, and 662 usable responses were collected from the players of Pokémon Go in Taiwan.

In total, 22 hypotheses were validated by using partial least squares techniques. Among the antecedents of in-app purchases intention in the model, the perceived value and satisfaction were found to have strong direct effects. The antecedents of the perceived value (flow, design aesthetic, social self-expression and good price) have direct influences on the perceived value of all players. Design aesthetic, reward and the perceived value were found to have a direct impact on all players’ satisfaction. Moreover, the differences between paying users and non-paying users were discussed and verified.

The model demonstrated relatively good explanatory power for purchase intention in the context of location-based AR game. The proposed model can provide insights to location-based AR game developers to design their games and marketing strategies.

The purpose of this study is twofold. First, an integrated model will be developed based on task-technology fit, innovation diffusion theory and the new product adoption model in order to explore the factors that affect smartwatch adoption. Second, the differences in the factors that affect users’ intention to adopt the Apple Watch and other smartwatches will be examined.

The data for this study were collected via an online survey questionnaire. The responses of 341 potential adopters of smartwatches were used to test the hypotheses in the research model. The casual model was assessed using partial least squares techniques.

The model can account for more than 50 percent of the variance in adoption intention. The research results affirm prior findings that perceived product attributes have relatively strong influence on adoption intention. Among these attributes, relative advantage has the strongest effect. Moreover, this study revealed differences between the antecedents of Apple watches and those of non-Apple watches.

The insights provided by this study can help smartwatch providers formulate better growth strategies. The findings also provide some directions for further development.

This study provides a better understanding of how the factors in the theories influence the adoption intentions of Apple watches and non-Apple watches.

Artificial intelligence (AI) customer service chatbots are a new application service, and little is known about this type of service. This study applies service quality, trust and satisfaction to predict users' continuance intention to use a food-ordering chatbot.

The proposed model and hypotheses are tested using online questionnaire responses to collect users' perceptions of such services. One hundred and eleven responses of actual users were received.

Empirical results show that anthropomorphism and service quality, such as problem-solving, are the antecedents of trust and satisfaction, while satisfaction has the most significant direct effect on the users' intention.

The results provide further useful insights for service providers and chatbot developers to improve services.

In recent years, the ongoing development and rapid popularization of mobile devices, not only has brought new forms of lifestyle but also has boomed a wide array of service contents, allowing users to engage in entertainment, study and other daily activities, in addition to business transactions. To explore the factors that affect users' continued use of mobile app software, this paper aims to take into account the utilitarian value and privacy, as well as security factors and intends to propose an integrated research model based on the information systems success (ISS) model.

The data for this study were collected via an online survey questionnaire. A total of 190 valid responses were used to examine the hypotheses in the research model. The casual model was assessed using partial least squares techniques.

The results indicated that the three quality factors (information quality, system quality and service quality) in the ISS model significantly affected satisfaction and utilitarian value. Private and security have significant negative association with utilitarian value. The results also showed that private and security did not significantly affect satisfaction. The findings also provide some directions for further research.

The results show that user's continued use of mobile app software depends upon the perceived utilitarian value and satisfaction. The quality characteristics are the three critical factors that would affect the perceived utilitarian value and satisfaction. Compared to information quality and service quality, system quality has a higher degree of positive impact, which indicates that users are more concerned about the immediate download ability and ease-of-use provided by the system. Furthermore, the research also finds that privacy and security concerns have a negative influence on the utilitarian value, showing that in the context of task-oriented IS, the perceived risk of privacy and security during the process of using mobile app software services, will negatively affect users’ perception of utilitarian value. The insights provided by this study can help mobile app developers optimize design and marketing strategies.

This study provides a better understanding of how the factors in the theories influence the continuance usage intention of life style mobile applications.

Compulsive usage of mobile applications may have a negative effect on people’s health and social interaction. Past studies have indicated that personality traits were related to compulsive usage of technologies, but most of them have explored the factors from the system and interface design perspectives, specifically. The purpose of this paper is to explore how the Big Five personality traits, materialism, and external locus of control affect compulsive mobile application usage, and examines how compulsive usage impacts technostress.

The present study proposes a framework based on Big Five personality traits and related literature. The author collected a total of 546 valid responses to the online survey, and the author examined the 18 proposed hypotheses using SmartPLS software.

The results show that neuroticism, extraversion, materialism, and external locus of control have significant effects on compulsive usage of mobile social applications. In addition, agreeableness, materialism, and external locus of control significantly influence compulsive usage of mobile game applications. Compulsive usage (of both mobile social apps and mobile games), materialism, and external locus of control all have a positive, direct impact on technostress.

This study offers mobile app design companies and educational institutions a understanding of the social problems caused by the misuse of mobile devices, helping them to prevent the increase of the negative influences of such misuse.

The primary value of this paper lies in providing a better understanding of the influence of personality traits on the compulsive use of mobile apps and technostress.

Massive open online courses (MOOCs) differ from non-MOOC e-learning platforms mainly in terms of degree of openness, with MOOCs designed to maximize learner access and interaction. The purpose of this paper is to propose a new research model to explore intention to continue to use MOOCs from the perspectives of openness and interactivity, based on related theories and dimensions from previous research.

In order to evaluate the effectiveness of the MOOC platform, two online survey questionnaires were developed and e-mailed to the all of the university students in Taichung, Taiwan. The first one and second one are the same except the construct openness. The first one was delivered in late 2015 while the second one was delivered in the middle 2016. After the authors eliminated incomplete responses and duplicates, 995 and 854 usable responses from platform users remained, respectively, and were used to test the relationships in the model.

The model can account for more than 75 percent of the variance in continuance intention. The research results affirm prior findings that satisfaction has a strong direct influence on intention. Among the three interaction factors, human-message interaction on the platform has the strongest effect on satisfaction. This study found that the effects of interactions and motivation on MOOC and non-MOOC platforms were consistent and similar. Moreover, perceived openness was found to influence usage intention but its effects were relative low.

The model demonstrated good explanatory power for continued intention in the context of MOOCs. This study provides a better understanding of the relationships among interactions, motivations, perceived openness, and continuance intention.

With the advent of the digital era, the internet has gradually become an essential factor in people’s lives. Its increasing popularity has also caused e-commerce to thrive, and has increased the power of online marketing. In recent years, social commerce has emerged as a new mode of operation which can be distinguished from traditional e-commerce. The paper aims to discuss these issues.

The main purpose of this study is to determine which factors influence a consumer’s behavioral intention in the context of social commerce websites, and to explore overall purchase intentions based on the consumer’s cognitive evaluation. The examination reveals that consumers’ multidimensional perceptions influence both their perceptions of value and their purchase intentions. Other related social awareness factors explored by this study are also shown to influence customers’ purchase intentions.

In summary, the results show that perceived value and social awareness factors influence customers’ purchasing decisions and behavioral intentions for different gender. These findings have significant theoretical and managerial implications.

Social commerce is a subset of e-commerce brought about by the development of social networking. Activities conducted on social networking websites can be considered as a form of social commerce. In Taiwan, social commerce is still in the early stages of development.

Although many universities have begun to provide artificial intelligence (AI)-related courses for students, the influence of the course on students' intention to participate in the development of AI-related products/services needs to be verified. In order to explore the factors that influence students' participation in AI services and system development, this study uses self-efficacy, AI literacy, and the theory of planned behaviour (TPB) to investigate students' intention to engage in AI software development.

The questionnaire was distributed online to collect university students' responses in central Taiwan. The research model and eleven hypotheses are tested using 151 responses. The testing process adopted SmartPLS 3.3 and SPSS 26 software.

AI programming self-efficacy, AI literacy, and course satisfaction directly affected the intention to participate in AI software development. Moreover, course playfulness significantly affected course satisfaction and AI literacy. However, course usefulness positively affected course satisfaction but did not significantly affect AI literacy and AI programming self-efficacy.

The model improves our comprehension of the influence of AI literacy and AI programming self-efficacy on the intention. Moreover, the effects of AI course usefulness and playfulness on literacy and self-efficacy were verified. The findings and insights can help design the AI-related course and encourage university students to participate in AI software development. The study concludes with suggestions for course design for AI course instructors or related educators.

This paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.

Publications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.

The annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.

This paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.