The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Adoption of AI Chatbots: Revolutionizing E-Grocery Shopping in Delhi-NCR
Abstract
With the advancement of Artificial Intelligence (AI), there has been a rise in AI-driven tools like chatbots that have human-like characteristics and provide resolutions to almost all the queries of the customers. However, no study has been conducted on the experience of Delhi NCR customers regarding the effectiveness of chatbots in e-grocery shopping. The hypotheses were tested by means of the Technology Acceptance Model (TAM) technique using Structural Equation Modeling (SEM). The results illustrated that chatbots enhance the general experience of users by providing a way that is fast, accurate, and comfortable. Tech-savvy customers highly value chatbots due to their ability to provide them with attractive offers, a variety of secure payment options, and real-time tracking capabilities. The study provides valuable insights to retailers, enabling them to further modify their chatbots and create a more personalized, user-friendly experience through the deployment of anthropomorphic AI in marketing practices.
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In the citing paper
“Systems designed to minimize friction (e.g., expedited information access, simplified input, structured guidance, enhanced navigation) augment perceived utility and user satisfaction, thereby reinforcing trust and subsequent intention outcomes (e.g., retention, purchase intention, reliance-oriented metrics) [6,44,45,48,50,52,67,69].”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [45]
In the citing paper
“As systems move toward truly agentic, transaction-executing commerce [24,40,44,45,50,52,67], the main limitation is measurement: a significant portion of the evidence deduces delegation from adoption or continuation intentions, rather than from direct observation of explicit delegation choices or verified execution.”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [45]
In the citing paper
“In many studies,”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [45]
In the citing paper
“Positive when fric-tion drops or rec-ommendations fit, but not universal”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [45]
In the citing paper
“Behavioral lift appears when systems reduce fric-havioral intention rather than verified execution. tion (latency/steps) or improve option fit (recom-mendation relevance).”
From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [45]
Citations
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
Cascella, M., Semeraro, F., Montomoli, J., Bellini, V., Piazza, O., & Bignami, E. (2024) · Journal of Medical Systems · doi:10.1007/s10916-024-02045-3 · Cited by 219
Sharma, S., Singh, G., Sharma, C. S., & Kapoor, S. (2024) · International Journal of System Assurance Engineering and Management · doi:10.1007/s13198-023-02193-8 · Cited by 80
Self-citation
Flagged first, then by citations
Research works printed but not linked: 28
- Matosas-López, 2024, The impact of digitalization on current marketing strategies, 10.1108/9781837536863 · DOI
- 10.1007/s13198-023-02163-0 · DOI
- 10.4018/979-8-3693-1155-4.ch012 · DOI
- Yu, 2024, Consumers’ Tolerance When Confronted with Different Service Types in Service Retailing, Journal of Distribution Science, 22, 103
- 10.1007/s10796-021-10168-y · DOI
- 10.1109/icnwc60771.2024.10537491 · DOI
- Kuhn, 2023, Sustainability in Food: AI-based interactions, based on data fusion for consumer protection by the government
- 10.69554/apsb6546 · DOI
- Shendge, 2022, CHATBOTS AND CUSTOMER SERVICE SATISFACTION, The journal of contemporary issues in business and government, 28, 2295
- 10.1007/s10660-022-09562-8 · DOI · Paper page
- 10.1108/978-1-80071-348-220211007 · DOI
- 10.1108/INTR-11-2019-0447 · DOI
- 10.1108/EJM-12-2019-0942 · DOI
- 10.47974/JSMS-1143 · DOI
- 10.1108/JCM-03-2022-5234 · DOI
- Indarsin, 2017, Saudi Journal of Business and Management Studies Attitude toward Using m-Commerce: The Analysis of Perceived Usefulness, Perceived Ease of Use, and Perceived Trust: Case Study in Ikens Wholesale Trade, Jakarta-Indonesia, Saudi Journal of Business and Management Studies, 2, 995
- 10.1016/j.elerap.2023.101304 · DOI
- 10.1057/s41599-024-03212-0 · DOI · Paper page
- 10.4018/979-8-3693-1842-3.ch001 · DOI
- 10.1109/ICCR61006.2024.10533049 · DOI
- Schiffman, 2010, Consumer behavior
- M, 2021, An Introduction to Structural Equation Modeling, 1
- 10.1037/1082-989X.7.1.64 · DOI · Paper page
- 10.1108/MIP-03-2023-0103 · DOI
- 10.1016/j.jretconser.2024.103779 · DOI
- Khennouche, 2024, Revolutionizing generative pre-traineds: Insights and challenges in deploying ChatGPT and generative chatbots for FAQs, Expert Syst Appl, 246, 123224, 10.1016/j.eswa.2024.123224 · DOI
- 10.1108/AJIM-12-2023-0551 · DOI · Paper page
- 10.1109/UPCON59197.2023.10434375 · DOI
Cited by
Sorted by citations
Balaskas, S. (2026) · Information · doi:10.3390/info17030222 · Cited by 8
Metadata
- Authors
- Ranjan, N., Gupta, A., Sharma, L. K., & Kapoor, S.
- Affiliations
- Amity University (IN)
- Galgotias University (IN)
- Venue
- 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit)
- Publisher
- IEEE
- Published
- 2024-09-04
- Pages
- 1292-1297
- OpenAlex
- W4409310816
- Cited by
- 1
- References
- 3
- Citations by year
- 2026: 1
- FWCI
- 0.30
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Global AI Summit - International Conference on Artificial Intelligence and Emerging Technology (AI Summit) (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Marketing › Customer Service Quality and Loyalty
- Keywords
- AI chatbots, technology acceptance, customer experience, online retail, personalized marketing, payment security, order tracking
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