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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Sustainability Policy and Technology
Kumar, Pankaj
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Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Law, Crime, Criminology & Criminal Justice

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Exploring How User-Generated Content and Micro-Influencers Shape Buying Behavioral Intention Kumari, Kavita; Kumar, Pankaj
Indonesian Journal of Sustainability Policy and Technology Vol. 3 No. 2 (2025): Indonesian Journal of Sustainability Policy and Technology - November 2025
Publisher : PT Global Digital Sains Tekno

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61656/ijospat.v3i2.351

Abstract

Purpose: This study investigates how the buying behavioral intention of Generation X and Baby Boomers is influenced by the user-generated content (UGC) and micro-influencer endorsements. It addresses a gap in existing literature that usually focuses on younger demographics, aiming to understand how older consumers, especially for aged 35 and above, engage with social media marketing exposure. Method: A quantitative explanatory research design was employed, using a structured online survey distributed among Indian consumers aged 35 and above. The study adapted validated scales to measure UGC, micro-influencer credibility, and purchase intention. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess reliability, validity, and the strength of hypothesized relationships. Findings: The results reveal that both UGC and micro-influencer exposure significantly shape buying behavioral intentions among older consumers. Peer-generated content fosters trust and credibility, while micro-influencers—due to their relatability and authenticity—effectively influence purchase decisions. These findings challenge assumptions about digital disengagement among older age groups. Implication: Marketers should consider integrating UGC and collaborating with micro-influencers whose values align with older consumers. Tailored campaigns that emphasize clarity, credibility, and emotional resonance can enhance engagement and drive purchase behavior in this demographic. The study offers actionable insights for inclusive and age-sensitive digital marketing strategies. Originality: This research extends the applicability of social media marketing constructs to older consumer segments, offering an understanding of their decision-making processes. By focusing on Generation X and Baby Boomers, it contributes to a more comprehensive and representative view of consumer behavior in the digital age.
MVC in machine learning: a decade of algorithmic advances, challenges, and applications–a systematic review Kumar, Pankaj; Agrawal, Rashmi
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.11137

Abstract

This systematic review evaluates the developments in multi-view clustering (MVC), its challenges, and applications from 2009 to 2024 and synthesizes 157 studies selected according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines. MVC overcomes the shortcomings of the traditional single-view approaches by using complementary information provided by heterogeneous data sources. We used a strict search strategy in the ACM Digital Library, IEEE Xplore, and Scopus, and then carefully examined the quality of the found articles. The significant results suggest that the MVC research has grown explosively, with China as the major contributor and IEEE/Elsevier as the leading publishers. Developments in algorithms include deep learning, graph-based models, and factorization. Ongoing issues include managing incomplete views, scalability, successful fusion strategies, and interpretability. The review points out the wide range of applications of MVC in various areas, including bioinformatics, social network analysis, and multimedia. Future research must create adaptive frameworks, improve the interpretability of models, and develop strong evaluation measures, thus unlocking the full potential of MVC in real-life data applications.
Co-Authors Agrawal, Rashmi Kumari, Kavita