Authors

Saurabh Manish

Department of Computer Engineering, Matoshri College of Engineering and Research Centre, Nashik, India

Shivam Aniket

Department of Computer Engineering, Matoshri College of Engineering and Research Centre, Nashik, India

Harsh Abhishek

Department of Computer Engineering, Matoshri College of Engineering and Research Centre, Nashik, India

Abstract

This study systematically examines the intellectual structure, thematic evolution, and knowledge diffusion patterns within digital consumer behavior research through a comprehensive bibliometric investigation. A structured dataset comprising 1,000 peer-reviewed journal articles published between 2000 and 2024 was extracted from the Crossref database using the Publish or Perish software for citation retrieval and metadata refinement. Subsequently, advanced science-mapping techniques were applied using VOSviewer to conduct term co-occurrence, keyword clustering, citation linkage, and thematic network analyses based on article titles and abstracts. Co-word analysis and cluster visualization enabled the identification of dominant research streams, conceptual interrelationships, and longitudinal thematic shifts across the examined time span. The findings reveal that digital consumer behavior scholarship is structured around several major thematic clusters. These include: (i) the strategic impact of digital marketing, social media engagement, and online advertising effectiveness; (ii) accelerated digital transformation processes, particularly those catalyzed by the COVID-19 pandemic; (iii) psychological, cognitive, and emotional determinants influencing online purchasing decisions, such as perceived risk, trust formation, and impulsive buying behavior; and (iv) socio-ethical and trust-based evaluative frameworks shaping consumer attitudes in digital marketplaces. Emerging research trajectories further indicate a growing scholarly emphasis on digital health awareness, sustainability-oriented consumption, omnichannel retail integration, artificial intelligence–driven personalization, and evolving post-pandemic consumer adaptation patterns. Temporal overlay visualization demonstrates a shift from early e-commerce adoption studies (2000–2010) toward platform ecosystems, data analytics, and behavioral modeling approaches in recent years. By providing a systematic and data-driven synthesis of publication trends, citation structures, and thematic convergence, this study contributes to a deeper understanding of the field’s developmental phases and intellectual milestones. The bibliometric evidence offers strategic insights for researchers, policymakers, and practitioners by identifying research gaps, interdisciplinary linkages, and prospective avenues for future empirical and theoretical advancements in digital consumer behavior scholarship.

Keywords

Digital Consumer Behaviour; Digital Marketing; Online Purchasing; Bibliometric Analysis; VOSviewer; Digital Transformation

Citation of this Article

Saurabh Manish, Shivam Aniket, & Harsh Abhishek. (2025). Analyzing the Influence of Online CSR Engagement on Consumer Brand Evaluation and Purchase Decisions. Current Journal of Engineering and Science Research. 2(6), 13-16. Article DOI: https://doi.org/10.47001/CJESR/2025.206003

Licence Copyright (c) 2026 Current Journal of Engineering and Science Research. This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International Licence.

References

  1. Mitchell, V., & Walsh, G. (2004). Gender differences in German consumer decision‐making styles. Journal of Consumer Behaviour, 3(4), 331–346. https://doi.org/10.1002/cb.146
  2. Newholm, T., & Shaw, D. (2007). Studying the ethical consumer: A review of research. Journal of Consumer Behaviour, 6(5), 253–270. https://doi.org/10.1002/cb.225
  3. Chu, S., & Chen, H. (2019). Impact of consumers’ corporate social responsibility‐related activities in social media on brand attitude, electronic word‐of‐mouth intention, and purchase intention: A study of Chinese consumer behavior. Journal of Consumer Behaviour, 18(6), 453–462. https://doi.org/10.1002/cb.1784
  4. Guthrie, C., Fosso-Wamba, S., & Arnaud, J. B. (2021). Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown. Journal of Retailing and Consumer Services, 61(Query date: 2025-12-10 22:48:34), 102570–102570. https://doi.org/10.1016/j.jretconser.2021.102570
  5. Harris, J. M., Ciorciari, J., & Gountas, J. (2018). Consumer neuroscience for marketing researchers. Journal of Consumer Behaviour, 17(3), 239–252. https://doi.org/10.1002/cb.1710
  6. Hausman, A. (2000). A multi‐method investigation of consumer motivations in impulse buying behavior. Journal of Consumer Marketing, 17(5), 403–426. https://doi.org/10.1108/07363760010341045
  7. Pappas, N. (2016). Marketing strategies, perceived risks, and consumer trust in online buying behaviour. Journal of Retailing and Consumer Services, 29(Query date: 2025-12-10 22:48:34), 92–103. https://doi.org/10.1016/j.jretconser.2015.11.007
  8. Pires, G., Stanton, J., & Eckford, A. (2004). Influences on the perceived risk of purchasing online. Journal of Consumer Behaviour, 4(2), 118–131. https://doi.org/10.1002/cb.163
  9. Purohit, S., Arora, R., & Paul, J. (2022). The bright side of online consumer behavior: Continuance intention for mobile payments. Journal of Consumer Behaviour, 21(3), 523–542. https://doi.org/10.1002/cb.2017
  10. Racherla, P., Mandviwalla, M., & Connolly, D. J. (2012). Factors affecting consumers’ trust in online product reviews. Journal of Consumer Behaviour, 11(2), 94–104. https://doi.org/10.1002/cb.385
  11. Badgaiyan, A. J., & Verma, A. (2014). Intrinsic factors affecting impulsive buying behaviour— Evidence from India. Journal of Retailing and Consumer Services, 21(4), 537–549. https://doi.org/10.1016/j.jretconser.2014.04.003
  12. Büttner, O. B., & Göritz, A. S. (2008). Perceived trustworthiness of online shops. Journal of Consumer Behaviour, 7(1), 35–50. https://doi.org/10.1002/cb.235
  13. Heinonen, K. (2011). Consumer activity in social media: Managerial approaches to consumers’ social media behavior. Journal of Consumer Behaviour, 10(6), 356–364. https://doi.org/10.1002/cb.376
  14. Hubert, M., & Kenning, P. (2008). A current overview of consumer neuroscience. Journal of Consumer Behaviour, 7(4), 272–292. https://doi.org/10.1002/cb.251
  15. Schindler, R. M., & Bickart, B. (2012). Perceived helpfulness of online consumer reviews: The role of message content and style. Journal of Consumer Behaviour, 11(3), 234–243. https://doi.org/10.1002/cb.1372
  16. Tonglet, M. (2002). Consumer misbehaviour: An exploratory study of shopliftin. Journal of Consumer Behaviour, 1(4), 336–354. https://doi.org/10.1002/cb.79
  17. Yang, F., Tang, J., Men, J., & Zheng, X. (2021). Consumer perceived value and impulse buying behavior on mobile commerce: The moderating effect of social influence. Journal of Retailing and Consumer Services, 63(Query date: 2025-12-10 22:48:34), 102683–102683. https://doi.org/10.1016/j.jretconser.2021.102683
  18. Lewis, B. R., & Soureli, M. (2006). The antecedents of consumer loyalty in retail banking. Journal of Consumer Behaviour, 5(1), 15–31. https://doi.org/10.1002/cb.46
  19. Lim, W. M., Kumar, S., Pandey, N., Verma, D., & Kumar, D. (2022). Evolution and trends in consumer behaviour: Insights from Journal of Consumer Behaviour. Journal of Consumer Behaviour, 22(1), 217–232. https://doi.org/10.1002/cb.2118