http://hdl.handle.net/10453/148704 2026-10-15T05:28:42Z http://hdl.handle.net/10453/197207 Title: Cultural Influences on AI-Driven Decision-Making in Digital Commerce Systems Authors: Shao, C; Kang, K Abstract: This chapter explores how cultural diversity shapes consumer interactions with AI-driven digital commerce systems. While AI technologies revolutionize online shopping through personalized recommendations and intelligent assistants, their effectiveness varies significantly across different cultural backgrounds. This chapter proposes a theoretical framework examining how cultural values influence trust, acceptance, and usage patterns of AI commerce systems. This research introduces the Cultural-Adaptive Decision-Making (CADM) framework to guide the development of culturally-sensitive AI commerce systems. This framework provides theoretical design principles for creating adaptive interfaces that respond to cultural preferences while maintaining system efficiency. The study offers conceptual insights for global commerce companies seeking to optimize AI implementations across multicultural markets, ultimately enhancing user experience and business performance through AI design. This work provides a new perspective and possibilities for AI-driven commerce innovation. 2026-11-20T00:00:00Z http://hdl.handle.net/10453/197205 Title: Mapping Educational Data Literacy: A Bibliometric Analysis of Interdisciplinary Perspectives, Theoretical Frameworks, and Assessment Measures Authors: Atif, A; Merigó, JM Abstract: This chapter uses bibliometric analysis and a systematic literature review to map the evolution of educational data literacy research, highlighting key theoretical trends, empirical contributions, and interdisciplinary developments across social sciences, engineering, and computer science. Educational data literacy refers to the ability of educators, instructional designers, and learners to interpret, evaluate, and apply educational data in teaching, learning, and decision-making. Recognized as essential in data-driven education, this study situates it within broader concepts like data and assessment literacy, examining its development and impact. A dual methodological approach combines a systematic literature review with bibliometric analysis using VOSviewer to explore citation patterns, thematic trends, and interdisciplinary collaborations. Techniques such as co-citation analysis, bibliographic coupling, and keyword co-occurrence mapping reveal the intellectual structure and evolution of the field. Findings identify four critical themes: (1) teacher data literacy, focusing on educators’ competencies in data-informed decision-making; (2) critical data literacy, addressing ethical and social justice concerns; (3) data literacy and artificial intelligence (AI), exploring AI’s role in education; and (4) data literacy in higher education, analyzing institutional efforts to integrate data literacy. The results highlight increasing interdisciplinarity, emerging theoretical frameworks, and global variations in research focus. Influential works and key contributors are identified, emphasizing educational data literacy’s growing significance. The chapter concludes with implications for curriculum design, teacher training, and integrating data literacy into AI and digital education, advocating for interdisciplinary and culturally responsive approaches in education. 2026-01-31T00:00:00Z http://hdl.handle.net/10453/197204 Title: RETHINKING BUSINESS DECISIONS: THE SYNERGY OF DECISION SUPPORT SYSTEM, ANALYTICS, BUSINESS INTELLIGENCE, ARTIFICIAL INTELLIGENCE, AND DATA SCIENCE Authors: Atif, A; Qureshi, MA 2026-01-01T00:00:00Z http://hdl.handle.net/10453/197203 Title: Information Dashboards Authors: Atif, A 2026-01-01T00:00:00Z