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All Journal Involvement International Journal of Business
Singh, Chandra Bhooshan
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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How Digital Addiction Fuels Youth Consumerism in India? Singh, Chandra Bhooshan; Sharma, Dr. Nistha; Pandey, Dr. Shinki K
Involvement International Journal of Business Vol. 2 No. 2 (2025): April 2025
Publisher : PT Agung Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62569/iijb.v2i2.72

Abstract

The rise of digital technology has significantly transformed consumer behavior, particularly among young individuals in India. Increased screen time, social media influence, and digital payment methods have contributed to impulsive spending habits. This study examines the impact of digital addiction on youth consumerism, emphasizing psychological, behavioral, and socio-economic factors. This study adopts a qualitative research design with a phenomenological approach with young consumers aged 18–30 in urban India. The data collection focused on digital consumption patterns, purchasing behavior, and financial awareness. Statistical analysis was employed to assess correlations between digital addiction levels and spending habits. Findings indicate that digital addiction significantly influences youth consumerism through instant gratification, Fear of Missing Out (FOMO), and algorithm-driven advertising. Social media platforms and influencer marketing intensify impulsive buying behaviors. The increasing adoption of Buy Now, Pay Later (BNPL) schemes fosters financial instability, pushing many young consumers into debt cycles. Additionally, excessive digital engagement has socio-economic implications, affecting traditional retail businesses and financial well-being. The study highlights the need for regulatory measures, including financial literacy programs and ethical digital marketing practices, to mitigate the negative impacts of digital-driven consumerism. A multi-stakeholder approach involving policymakers, educators, and businesses is essential for promoting responsible digital consumption among Indian youth.
Predicting Consumer Purchase Decisions through Packaging Color Strategies in FMCG Markets Bharti, Rakshak; Khatri, Urvija; Singh, Chandra Bhooshan; Barik, Tushar Ranjan; Thakur, Kanchan; Lepcha, Dawakit
Involvement International Journal of Business Vol. 3 No. 1 (2026): January 2026
Publisher : PT Agung Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62569/iijb.v3i1.197

Abstract

Examining highly competitive Fast-Moving Consumer Goods (FMCG) markets reveals that consumers often make purchase decisions within seconds, rendering packaging design particularly color a critical strategic cue. Although prior research has established the psychological influence of color, few studies have integrated neuromarketing measures with predictive analytics to forecast consumer purchase behavior. This study employs a mixed-methods design combining eye-tracking, physiological emotional measurement (FEMG and GSR), consumer surveys, and machine learning analysis. A total of 1,500 participants evaluated FMCG products across food, beverage, and personal care categories using standardized color treatments. Data were analyzed using ANCOVA and an XGBoost machine learning model to predict purchase decisions. The results show that warm colors significantly reduced time-to-first-fixation (mean = 420 ms) and increased visual engagement, while high-contrast packaging improved fixation duration by up to 32%. Emotional analysis revealed that warm, high-saturation colors generated higher arousal (GSR +18.6%), whereas cooler colors produced stronger positive valence linked to trust. The XGBoost model achieved a prediction accuracy of 89.2%, substantially outperforming traditional regression models. The findings demonstrate that packaging color operates as a neuromarketing stimulus that shapes attention and emotion prior to conscious deliberation. Integrating behavioral science with machine learning advances both theory and practice by enabling accurate prediction of consumer decisions. The study highlights the strategic value of data-driven color design for FMCG marketers seeking competitive advantage in complex retail environments.
Co-Authors Barik, Tushar Ranjan Bharti, Rakshak Khatri, Urvija Lepcha, Dawakit Pandey, Dr. Shinki K Sharma, Dr. Nistha Thakur, Kanchan