A scholarly network of AI research with an information science focus: Global North and Global South perspectives.

This paper primarily aims to provide a citation-based method for exploring the scholarly network of artificial intelligence (AI)-related research in the information science (IS) domain, especially from Global North (GN) and Global South (GS) perspectives. Three research objectives were addressed, namely (1) the publication patterns in the field, (2) the most influential articles and researched keywords in the field, and (3) the visualization of the scholarly network between GN and GS researchers between the years 2010 and 2020. On the basis of the PRISMA statement, longitudinal research data were retrieved from the Web of Science and analyzed. Thirty-two AI-related keywords were used to retrieve relevant quality articles. Finally, 149 articles accompanying the follow-up 8838 citing articles were identified as eligible sources. A co-citation network analysis was adopted to scientifically visualize the intellectual structure of AI research in GN and GS networks. The results revealed that the United States, Australia, and the United Kingdom are the most productive GN countries; by contrast, China and India are the most productive GS countries. Next, the 10 most frequently co-cited AI research articles in the IS domain were identified. Third, the scholarly networks of AI research in the GN and GS areas were visualized. Between 2010 and 2015, GN researchers in the IS domain focused on applied research involving intelligent systems (e.g., decision support systems); between 2016 and 2020, GS researchers focused on big data applications (e.g., geospatial big data research). Both GN and GS researchers focused on technology adoption research (e.g., AI-related products and services) throughout the investigated period. Overall, this paper reveals the intellectual structure of the scholarly network on AI research and several applications in the IS literature. The findings provide research-based evidence for expanding global AI research.

Factors influencing university teachers' use of a mobile technology-enhanced teaching (MTT) platform.

The main purpose of this study was to examine the critical factors influencing university teachers' use of a mobile technology-enhanced teaching (MTT) platform during the new coronavirus (COVID-19) epidemic. An integrated model with multiple factors drawing from the theoretical models and learning theories was proposed in this study to examine university teachers' intentions to use an MTT platform. The multiple factors included the individual factor (e.g., growth mindset, help seeking, and self-efficacy), the social factor (e.g., social norms), and the technological acceptance factor (e.g., perceived usefulness and perceived ease of use). The survey method was used to collect data on university teachers' perceptions of the MTT platform use, and a two-step structural equation modeling approach was used for the data analysis. Based on the path analysis of a total of 214 valid responses, the results identified that growth mindset, help seeking, and self-efficacy from the individual factor, as well as perceived usefulness from the technology acceptance factor were the significant determinants of university teachers' intentions to adopt the MTT. The contributions of this study are twofold. First, the proposed model was derived from multiple literature sources, providing a sound theoretical foundation to understand MTT platform use from an academic angle. Second, university teachers' viewpoints are a unique observation of their actual platform use, providing practical insights into the improvement and maintenance of MTT-related platforms for all educators. The findings are especially valuable during the post-COVID-19 era.

An Empirical Exploration of Sports Sponsorship: Activation of Experiential Marketing, Sponsorship Satisfaction, Brand Equity, and Purchase Intention.

The purpose of this study is to investigate the relationship between the activation of experiential marketing, satisfaction with sponsored sporting events, brand equity, and subsequent product purchase intentions in a small-scale sponsorship campaign. Survey data were collected from 238 actual runners in the terminal rest area after they had completed a race. Structural equation modeling with the bootstrap method was carried out to examine the proposed hypotheses. Results revealed that in terms of product purchase intention, brand equity was the most influential factor, followed by experiential marketing activation and satisfaction with the sponsorship. Specifically, experiential marketing activation significantly influenced the sports sponsorship and the sponsor's brand equity; however, satisfaction showed an insignificant effect on purchase intention. In addition, the mediation test shows that brand equity is an important mediator of experience marketing and satisfaction to product purchase intention. Findings provide some empirical insights into how small-scale sponsorship can benefit sponsoring companies, including intangible brand assets and tangible product consumption. The results could encourage more companies to organize small-scale sponsorship races and to present brand-related experiences (e.g., experiencing product packaging, on-the-spot experience areas). In this way, opportunities may be provided to attract more runners (or potential consumers) to participate in the event and have a deeper brand experience. This study contributes to a better understanding of the effectiveness of small-scale sponsorship in Asia to increase the generalization of the small sponsorship literature. Small-scale sporting events can bring public attention and economic benefits to the host company, and encourage more people to participate, thereby resulting in long-term social and health benefits in the community.