ASSESSMENT OF FACTORS INFLUENCING VENDORS’ ADOPTION OF UNIFIED PAYMENTS INTERFACE (UPI)

The Unified Payments Interface (UPI) system has become the most technologically advanced payment system for Indian consumers and banking institutions. UPI was created to provide constant accessibility, high performance, intuitive navigation, and openness. Despite these positives and the exponential increase of internet and mobile devices users, UPI adoption has lagged behind projections. Understanding customers’ perceptions of trust and knowledge and motivating them to adopt is essential for searching deeper into prevalent issues. Prior UPI studies mostly dealt with its operational dynamics. The elements that affect the decisions of Indian vendors in adopting UPI based on the Technology Acceptance Model (TAM) theory have been examined to draw conclusions about their adoption and influencing factors. A survey of vendors in Hyderabad, India, revealed that personal factors (“perceived risk”, “perceived ease of use”, “perceived usefulness”) affected vendors’ UPI acceptance. Technical knowledge does not moderate the association between personal variables and vendors' UPI adoption; however, the level of trust moderates this relationship. Consequently, UPI service providers would create UPI platforms that appeal to the widest possible audience. Improvements in user friendliness and safety measures can establish UPI as socially acceptable. This study demonstrates to researchers how TAM constructs may be usefully adapted to vendors' UPI adoption. As UPI is a relatively new technology in many domains, its adoption merits further research of its own. Since there is little academic research on UPI usage among vendors, this study adds a significant new contribution to the field.

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Publication Details

Journal
Lex localis - Journal of Local Self-Government
Published
2025-08-25
DOI
https://doi.org/10.52152/800567
Primary Topic
Big Data and Business Intelligence
Type
article
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article

ASSESSMENT OF FACTORS INFLUENCING VENDORS’ ADOPTION OF UNIFIED PAYMENTS INTERFACE (UPI)

Vedala Naga Sailaja K. Padma Kiran
Lex localis - Journal of Local Self-Government
Big Data and Business Intelligence
article

ASSESSMENT OF FACTORS INFLUENCING VENDORS’ ADOPTION OF UNIFIED PAYMENTS INTERFACE (UPI)

Vedala Naga Sailaja K. Padma Kiran
article en

Abstract

The Unified Payments Interface (UPI) system has become the most technologically advanced payment system for Indian consumers and banking institutions. UPI was created to provide constant accessibility, high performance, intuitive navigation, and openness. Despite these positives and the exponential increase of internet and mobile devices users, UPI adoption has lagged behind projections. Understanding customers’ perceptions of trust and knowledge and motivating them to adopt is essential for searching deeper into prevalent issues. Prior UPI studies mostly dealt with its operational dynamics. The elements that affect the decisions of Indian vendors in adopting UPI based on the Technology Acceptance Model (TAM) theory have been examined to draw conclusions about their adoption and influencing factors. A survey of vendors in Hyderabad, India, revealed that personal factors (“perceived risk”, “perceived ease of use”, “perceived usefulness”) affected vendors’ UPI acceptance. Technical knowledge does not moderate the association between personal variables and vendors' UPI adoption; however, the level of trust moderates this relationship. Consequently, UPI service providers would create UPI platforms that appeal to the widest possible audience. Improvements in user friendliness and safety measures can establish UPI as socially acceptable. This study demonstrates to researchers how TAM constructs may be usefully adapted to vendors' UPI adoption. As UPI is a relatively new technology in many domains, its adoption merits further research of its own. Since there is little academic research on UPI usage among vendors, this study adds a significant new contribution to the field.

Lex localis - Journal of Local Self-GovernmentVol. 23(S4)
Openalex Percentile: Top 58%
Big Data and Business Intelligence
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