Ali, Khan Sarfaraz
Unknown Affiliation

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

The Impact of Green Innovation on Business Sustainability A Case Study of SMEs Hindarsah, Ida; Fauzi, Teddy Hikmat; Fachrudin, Adi; Ali, Khan Sarfaraz
International Journal of Science and Society Vol 7 No 3 (2025): International Journal of Science and Society (IJSOC)
Publisher : GoAcademica Research & Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54783/ijsoc.v7i3.1515

Abstract

Micro, Small, and Medium Enterprises (MSMEs) can be an alternative for the government to increase the country's economic productivity. This enormous economic potential cannot be separated from existing challenges, such as adapting sustainable business practices. This study aims to analyze the relationship between green innovation and business sustainability. Using a quantitative approach, data was collected through questionnaires distributed to 64 knitting and weaving MSMEs in Bandung Regency. The data was analyzed using the Structural Equation Modelling - Partial Least Squares (SEM-PLS) method. The results of the analysis show that Green Innovation has a significant positive effect on Business Sustainability, where 58.5% of the variance in Business Sustainability can be explained by Green Innovation. Based on these findings, it can be concluded that Green Innovation has a significant positive effect on Business Sustainability.
Integrating generative AI in higher education for lifelong learning Chowdhury, Mozaffar Alam; Sam, Toong Hai; Rana, Md. Sohel; Ali, Khan Sarfaraz; Wong, Whee Yen; Tushar, Hasanuzzaman
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i2.36796

Abstract

This study investigates the impact of generative artificial intelligence (GenAI) on learning outcomes (LO) and lifelong skills (LLS) within higher education, emphasizing ethical considerations. Employing a quantitative approach, data was collected from 180 students via a questionnaire, examining their AI usage in education. Structural equation modeling (SEM) using SmartPLS 4.1.0.9 was used to analyze the relationship between GenAI use, LO, and LLS. Findings reveal that GenAI can enhance LO, personalize learning experiences, and contribute to developing crucial LLS. However, the study highlights the importance of ethical guidelines to prevent academic dishonesty. This research contributes to the existing literature by exploring the link between GenAI use, LO, and the development of LLS. Practically, it demonstrates that ethical GenAI use promotes both LO and LLS among higher education students, aligning with the sustainable development goals (SDGs) of inclusive and equitable quality education and lifelong learning opportunities.