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All Journal International Journal of Advances in Applied Sciences Bulletin of Electrical Engineering and Informatics Journal of Environmental Science and Sustainable Development Indonesian Journal of Sustainability Policy and Technology
Kumar, Pankaj
Unknown Affiliation
Humanities Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Physics Social Sciences

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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.
Extension of Hermite-Hadamard type inequalities to Katugampola fractional integrals Das, Dipak Kr; Mishra, Shashi Kant; Kumar, Pankaj; Hamdi, Abdelouahed
International Journal of Advances in Applied Sciences Vol 15, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i1.pp1-18

Abstract

In this study, we introduce several new Hermite-Hadamard type general integral inequalities for exponentially (s,m)-convex functions via Katugampola fractional integral. The Katugampola fractional integral is a broader form of the Riemann–Liouville and Hadamard fractional integrals. We utilized the power mean integral inequality, the H¨older inequality and a few additional generalizations to derive these inequalities. Numerous limiting results are derived from the main results presented in the remarks. Furthermore, we provide an example illustrating our theoretical findings, supported by a graphical representation.
LONG-TERM CHANGES IN RELATIVE HUMIDITY AND SOIL WETNESS: IMPLICATIONS ON AGRICULTURE AND ENVIRONMENTAL SUSTAINABILITY IN WESTERN HIMALAYA Ashwani, Ashwani; Kumar, Pankaj
Journal of Environmental Science and Sustainable Development Vol. 9, No. 1
Publisher : UI Scholars Hub

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Abstract

Long-term climate changes in humidity and soil wetness in the cold deserts of the Western Himalaya are still not well researched. Understanding the long-term trends of relative humidity (RH) and soil moisture is crucial in high-altitude, cold desert regions for effective agricultural management and environmental sustainability. The study was conducted in a part of the western Himalaya, which is an ecologically fragile zone with a highly sensitive agricultural region that is vulnerable to climatic variations. A comprehensive study was conducted to evaluate the spatiotemporal variability of RH and soil wetness by means four techniques: Mann-Kendall, Modified Mann-Kendall, Sen’s slope estimator, and innovative trend analysis. All this was done using NASA POWER climate data from 1981 to 2023. High RW and soil wetness levels were observed in all seasons, with a statistical significance obtained through the Z-values: 12.64 for RH and 9.91 for soil wetness. The monsoon and agricultural seasons were the most intense periods of development. The strongest upward trends were observed in the southern and central subregions. The slopes of Sen showed an annual rise of the RH of 0.31% per year and of the soil moisture of 0.0073 m³/m³/year. The results show significant changes in agriculture and its sustainability. The introduction of new disease-resistant and short-duration crop varieties, the implementation of precision irrigation based on real-time soil moisture data, and adoption of agro-climatic advisories tailored to seasonal fluctuations. However, combining these hydro-climatic patterns with regional climate-smart agriculture strategies, improving monitoring infrastructure, and reinforcing early warning and insurance systems are crucial methods for planning climate-resilient policies in cold desert agro-ecosystems.
Co-Authors Agrawal, Rashmi Ashwani, Ashwani Das, Dipak Kr Hamdi, Abdelouahed Kumari, Kavita Mishra, Shashi Kant