Impact of Quick Commerce Applications on Consumers Buying Behaviour and Brand Perception

International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, SI1 (2026), pp. 137143
Proceedings of Selected Papers from the
National Conference on Emerging Trends in Commerce and Management
NCETCM-2K26
2026-03-30 to 2026-03-31
Vijayawada, Andhra Pradesh, India
Organized by Andhra Loyola College, Vijayawada, India
eISSN: 3107-9075

This work is licensed under a Creative Commons Attribution 4.0 International License .

Impact of Quick Commerce Applications on Consumers Buying Behaviour and Brand Perception

1Ch. Vara Lakshmi, 2A. Madhuri, 3B. R. Kumar, 1D. Bhaskara Rao

1Assistant Professor, Department of MBA, Andhra Loyola College, Vijayawada, Andhra Pradesh, India
2Associate Professor, Department of MBA, Andhra Loyola College, Vijayawada, Andhra Pradesh, India
3Director & Professor, Department of MBA, Andhra Loyola College, Vijayawada, Andhra Pradesh, India

Abstract

Q-commerce, or quick commerce, emphasizes rapid deliveries, usually within an hour. This article attempted to evaluate the impact of quick commerce apps on consumer buying behaviour and brand perception, considering demographic factors such as age, gender, occupation, educational qualification, and area of residence. A non-probability convenience sampling method was used to collect data from 100 users through a structured questionnaire. Statistical tools like ANOVA, regression, and correlation were applied for analysis. Findings indicate that demographic factors have no significant statistical correlation with brand perception towards quick commerce apps, with age, gender, qualification, and occupation negatively associated, while area of residence showed a positive association. Additionally, consumer awareness and acceptance of fintech were found to be statistically insignificant in relation to each other.

Keywords: Quick commerce, Brand Perception, Convenience sampling, Consumer Behaviour, E-commerce Adoption.

📄 Download Full Text PDF

DOI: 10.66710/ijersem.v2si1.18

Open Access • Peer Reviewed Article

References

  1. K. H. Muloor, L. S. Iyer, M. Saseekala, and K. S. Manu, “The Role of IoT in Optimizing Quick Commerce Operations: A Comprehensive Analysis of Micro-Fulfillment Centers and Consumer Satisfaction,” in Elsevier eBooks, 2025, pp. 473–487. https://doi.org/10.1016/B978-0-443-34125-0.00014-3
  2. P. Alipour, E. E. Gallegos, and S. Sridhar, “Analyzing Consumer Behavior During Virtual Reality Product Exploration in E-Commerce,” Journal of Business Research, vol. 211, p. 116196, Apr. 2026. https://doi.org/10.1016/j.jbusres.2026.116196
  3. U. S. Bhosekar and K. Gaurav, “Quick Commerce and Customer Loyalty: A Comprehensive Bibliometric Review and Research Agenda,” Strategic Business Research, vol. 2, no. 1, p. 100124, Mar. 2026. https://doi.org/10.1016/j.sbr.2026.100124
  4. R. Lavuri, S. Kokatnur, and P. Thaichon, “Quick-Commerce: Green Initiatives on Customer Brand Engagement,” Asia Pacific Journal of Marketing and Logistics, vol. 36, no. 11, pp. 1–16, Feb. 2024. https://doi.org/10.1108/APJML-05-2023-0396
  5. X. Zhu and J. Xie, “Q-Commerce Service with Behavior-Based Pricing: Self-Logistics or Platform-Logistics?,” Kybernetes, vol. 55, no. 2, pp. 1197–1225, Dec. 2024. https://doi.org/10.1108/K-05-2024-1392
  6. A. Aggarwal, N. Arora, A. Verma, and K. Singh, “From Clicks to Connection: How AI Marketing Fuels Brand Evangelism Through Passion and Personality in Quick Commerce,” Asia-Pacific Journal of Business Administration, vol. 18, no. 3, pp. 826–849, Sep. 2025. https://doi.org/10.1108/APJBA-01-2025-0090
  7. W. Zhang, M. Kong, W. Tan, Y. Song, and A. M. Fathollahi-Fard, “A Reinforcement Learning-Driven Framework for the Q-Commerce Multi-Product Unit Scheduling Problem,” Electronic Commerce Research and Applications, vol. 75, p. 101571, Dec. 2025. https://doi.org/10.1016/j.elerap.2025.101571
  8. N. K. Singh, V. Lahri, and N. Virmani, “An Integrated Framework for Delivery Partner Selection and Order Optimization in Quick Commerce Under Uncertain Demand,” Expert Systems With Applications, vol. 307, p. 131078, Jan. 2026. https://doi.org/10.1016/j.eswa.2025.131078
  9. M. Schorung, “Quick Commerce and the Evolving Business Models of the Food Retail Industry - Investigating the Quick Commerce Supply Chain and the Urban Impacts of Dark Stores,” Transportation Research Procedia, vol. 79, pp. 305–312, Jan. 2024. https://doi.org/10.1016/j.trpro.2024.03.041
  10. S. R. Senthilkumar Renuka, S. C. A., S. D. R., M. Liviya L., S. S. Jayakumar, and R. Anuradha, “Quick Commerce: Product Price Classification Using Machine Learning Algorithms,” in 2025 International Conference on Computational Robotics, Testing and Engineering Evaluation (ICCRTEE), Virudhunagar, India, 2025, pp. 1–6. https://doi.org/10.1109/ICCRTEE64519.2025.11053083
  11. V. Supriya, M. D. Jasmine, L. Sunny Abilash, and S. Hari Krishna, “Behavioral Finance and Impact on Investor Decision Making,” International Journal of Emerging Research in Science Engineering and Management, vol. 2, no. si1, pp. 132–136, May 2026. https://doi.org/10.66710/ijersem.v2si1.17
  12. G. Kaur et al., “AI-Driven Customer Retention System for Quick-Commerce Platforms: A Comparative Case of Blinkit and BigBasket,” in 2025 IEEE 5th International Conference on ICT in Business Industry & Government (ICTBIG), Indore, Madhya Pradesh, India, 2025, pp. 1–8. https://doi.org/10.1109/ICTBIG68706.2025.11323912
  13. B. R. Kumar, A. Madhuri, M. Shireesha, and S. Melchior Reddy, “Exploring the Impact of Social Media Influencers on Consumer Behavior and Brand Loyalty in the Digital Age,” Community Practitioner, vol. 21, no. 06, pp. 2656–2676, 2024. https://doi.org/10.5281/zenodo.12592520
  14. D. Diab, T. N. Khan, and R. S. Almjnoni, “Brand Equity and Consumer Response in the Food and Beverage Industry (Cafés) in Saudi Arabia,” International Journal of Emerging Research in Engineering, Science, and Management, vol. 4, no. 1, pp. 22–30, 2025. https://doi.org/10.58482/ijeresm.v4i1.3