Behavioral intention research suggests that it can effectively predicts intention to adopt information technology and emphasizes the importance of examining antecedents of such use. However, the... Show More

Behavioral intention research suggests that it can effectively predicts intention to adopt information technology and emphasizes the importance of examining antecedents of such use. However, the literature also highlights that individual behavioral intentions can be affected by external factors and social influences. Current study examines the impacts of different factors (quality, social, behavioral, and innovative) on behavioral intention to use e-learning system. We designed special instruments to examine female students' behavioral intention to adopt e-learning system by extending the TPB as foundational framework. An extension of TPB is used with McLean & Delone and Innovative Theory to enhance the overall theoretical framework. Survey data collected from 699 female e-learning participants to test the study hypotheses. Findings suggested that subjective norms, self-efficacy, environment quality, and perceived innovativeness presented significant associations to behavioral intention of e-learning. Research implications and limitations are also examined and discussed.

Artificial intelligence (AI)-powered tools such as recommendation engines are widely used in online marketing and e-commerce; however, online retailers often deploy these tools without understanding... Show More

Artificial intelligence (AI)-powered tools such as recommendation engines are widely used in online marketing and e-commerce; however, online retailers often deploy these tools without understanding which human factors play a role in which products and at which stage of the customer journey. Understanding the interaction between AI-powered tools and humans can help practitioners create more effective online marketing platforms and improve human interaction with e-commerce tools. This paper examines customers' reliance on recommendation engines when purchasing fashion goods, electronics, and media content such as video and music. This paper also discusses the potential for improvement in recommendation engines in online marketing and e-commerce.

Research suggests that ChatGPT offers numerous affordances for students, who use it for various purposes, yet the field lacks quantitative studies that offer insight into a variety of students'... Show More

Research suggests that ChatGPT offers numerous affordances for students, who use it for various purposes, yet the field lacks quantitative studies that offer insight into a variety of students' actual uses of ChatGPT and their impact on academic performance. The main aims of this paper were (a) to introduce and validate a typology of students' ChatGPT uses, (b) to identify clusters of students with similar patterns of ChatGPT uses, and (c) to investigate the impact of ChatGPT uses on academic performance. An online survey research was conducted, which resulted in a typology of 10 distinct uses of ChatGPT and four distinct clusters of students. The strongest predictor of academic performance is information searching and explanation. Problematic use of ChatGPT, while resulting in improved grades, is found to be detrimental to competencies. Although the study might not fully represent the diversity of students' experiences across academic institutions, the typology offers a baseline for nuanced research and interventions pertaining to particular ChatGPT uses among students.