Generation Z use of artificial intelligence products and its impact on environmental sustainability: A cross-cultural comparison

Al-Sharafi M. A., Al-Emran M., Arpaci İ., Iahad N. A., AlQudah A. A., Iranmanesh M., ...Daha Fazla

COMPUTERS IN HUMAN BEHAVIOR, cilt.143, 2023 (SSCI, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 143
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1016/j.chb.2023.107708
  • Dergi Adı: COMPUTERS IN HUMAN BEHAVIOR
  • Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, IBZ Online, Aerospace Database, Applied Science & Technology Source, CINAHL, Communication Abstracts, Compendex, Computer & Applied Sciences, EBSCO Education Source, Education Abstracts, Educational research abstracts (ERA), INSPEC, Linguistics & Language Behavior Abstracts, Metadex, Psycinfo, Social services abstracts, Sociological abstracts, Civil Engineering Abstracts
  • Bursa Uludağ Üniversitesi Adresli: Hayır

Özet

Artificial intelligence (AI) products play a significant role in achieving environmental sustainability. These products can save various resources (e.g., energy, water), achieve cost savings, and manage waste better. However, understanding the determinants affecting the use of AI products and their impact on environmental sustainability is relatively low, specifically in developing countries. To fill this gap in the literature, this study develops a theoretical model by integrating two well-known theories, UTAUT and PMT, to explain the de- terminants influencing Generation Z use of AI products and their impact on environmental sustainability. The developed model was then evaluated using the PLS-SEM approach based on data collected from 562 respondents in Malaysia and Turkey. Although effort expectancy, performance expectancy, social influence, perceived severity, response efficacy, and response costs are significant drivers of green behavior among Malaysian in- dividuals, effort expectancy, facilitating conditions, perceived severity, response efficacy, and response costs are essential determinants among Turkish individuals. Interestingly, there is no significant difference between the importance of coping appraisals (i.e., self-efficacy, response efficacy, and response costs) among these two populations. The outcomes provide several contributions to the literature on AI and environmental sustainability and offer valuable insights for the practitioners, policymakers, and AI product developers.