Technology acceptance model for understanding consumer’s behavioral intention to use artificial intelligence based online shopping platforms in Bangladesh

Md. Emam Hossain () and Subarna Biswas
Additional contact information
Md. Emam Hossain: Noakhali Science and Technology University
Subarna Biswas: Noakhali Science and Technology University

SN Business & Economics, 2024, vol. 4, issue 12, 1-61

Abstract: Abstract Science and technology have significantly transformed the world, and artificial intelligence (AI) is revolutionizing sectors like online commerce. In Bangladesh, where traditional buying practices are prevalent, the integration of AI in online shopping presents both challenges and opportunities. Understanding customers’ behavioral intentions (BI) is crucial for AI-based online shopping platforms, but there is limited research on this topic, necessitating further studies to advance the understanding. The study aims to better understand consumers’ BI and determine whether perceived trust (PT) and service quality (SQ) form any positive attitudes (ATT) towards the BI to use AI-based online shopping platforms in Bangladesh. The study employed a broadly used technology acceptance model (TAM) with two additional variables PT and SQ, a quantitative research approach and a purposive sample strategy. Data was obtained using an online survey method with a seven-point Likert scale and evaluated using Smart-PLS and SPSS software, with partial least square (PLS) Smart being used for data analysis. The study found that perceived usefulness (PU) and SQ are the two most crucial variables that influence consumers’ ATT, while perceived ease of use (PEU) and PT are insignificant. However, ATT was found to be the most important factor in consumer’ BI, which influences consumers to use AI-based online shopping platforms. This study enhances knowledge on customers’ BI and AI technologies in online shopping platforms and provides practical insights for retailers and e-marketers to establish effective marketing strategies.

Keywords: Artificial intelligence; Online shopping; Technology acceptance model; AI-driven online shopping platforms (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s43546-024-00754-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:snbeco:v:4:y:2024:i:12:d:10.1007_s43546-024-00754-y

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/43546

DOI: 10.1007/s43546-024-00754-y

Access Statistics for this article

SN Business & Economics is currently edited by Gino D'Oca

More articles in SN Business & Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().