Role of perceived countries’ advantages of cashless economy in behavioral intentions of using cashless transactions: an empirical analysis

Abstract

Purpose The ultimate aim of this paper is to contribute an extension of the unified theory of acceptance and use of technology (UTAUT) model. The modified UTAUT provides a better explanation for the adoption of cashless transactions. However, it does not consider individuals’ perceived countries’ advantages when cashless transactions are made in the economy. Hence, this research investigates whether individuals’ perceived countries’ advantages of the cashless economy influence behavioral intentions of using cashless transactions. Design/methodology/approach A structured questionnaire has administered with 375 respondents in selected commercially vibrant places, such as Shopping Malls, big retail shops, hotels, and the like, covering the 15 zones of Greater Chennai city Corporation, India. From the 375 respondents, 325 respondents returned the filled-in questionnaire in time. For analysis, exploratory factor analyses used for underlying new latent factors from the identified variables used for measuring the individuals’ perceived countries’ advantages of a cashless economy. After identifying the latent factors, the extracted factors regressed with the intention level of using cashless transactions to validate the influence of newly identified factors. Findings The results of the regression analysis proved that the identified new factors, such as Perceived Economic Offense Reduction (PEOR), Perceived Economic Benefit (PEB), and Perceived Economy’s Security (PES), are positively and significantly influencing the behavioral intention of using cashless transactions. Research limitations/implications This study’s unique contribution is the validation of a measurement scale based on individuals’ perception of countries’ advantages when cashless transactions are made in the economy. The scale development in the present study is an essential step toward the advancement of the UTAUT research model, and this study also proved that identified new latent factors such as PEOR, PEB and the PES are positively and significantly influencing individuals’ behavioral intention toward the use of the cashless transaction. Hence, this study’s result may help contribute an extension of the UTAUT model in a comprehensive view, and this extension may enrich UTAUT’s ability to explain and predict the acceptance of cashless transactions. Originality/value In recent literature, many conceptual and empirical studies have discussed the countries’ advantages resulting from cashless transactions. This study attempts to integrate those advantages as variables through measurement instruments, whether they influence the behavioral intention to use cashless transactions from the general public perspective.

Factors influencing the adoption of cashless transactions during COVID-19: an extension of enhanced UTAUT with pandemic precautionary measures

“…These models include the “Theory of Reasoned Action (TRA) (Fishbein and Ajzen 1977 )”, “Social Cognitive Theory (SCT) (Bandura 1986 )”, “Technology Acceptance Model (TAM) (Davis 1989 )”, “Theory of Planned Behaviour (TPB) (Ajzen 1991 )”, “Model of PC Utilization (MPCU) (Thompson et al 1991 )”, “Decomposed Theory of Planned Behaviour (DTPB) (Taylor and Todd 1995 )”, “Innovation Diffusion Theory (IDT) (Rogers 1995 )”, and “Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al 2003 )”. Among these, the UTAUT framework offers a comprehensive explanation for consumers' behavioural intention to embrace CLT in a range of circumstances (Al-Saedi et al 2020 ; Alalwan et al 2017 , 2015 ; Raj et al 2021 ; Aslam et al 2022 ).…”

“…1 visually represents the model). At present, the enhanced UTAUT model offers a wide-ranging explanation for why people favour CLT methods (Al-Saedi et al 2020 ; Widyanto et al 2021 ; Namahoot and Jantasri 2022; Raj et al 2021 ; Santosa et al 2021 ; Aslam et al 2022 ). However, this theory does not elucidate the individuals’ intention to adopt CLT during the pandemic when there is a need to avoid physical contact as a precautionary measure.…”

“…The effectiveness of a country's monetary and financial institutions is a crucial determinant of economic development, and it is significantly influenced by the widespread adoption of cashless transaction systems (Essame 2006 ; Hasan et al 2012 ; Zandi et al 2013 ). According to Raj et al ( 2021 ), “cashless transactions (CLT)” refer to the use of non-cash payment methods, such as cheques, demand drafts, “Real Time Gross Settlement (RTGS)”, “National Electronic Fund Transfer (NEFT)”, “Immediate Payment Service (IMPS)”, “Unified Payments Interface (UPI)”, “Near Field Communication (NFC)” technology, “Quick Response (QR)” codes, payment by debit or credit card, mobile wallets, and other non-cash payment methods. Transactions in any of these modes are recorded and traceable (Almajali et al 2022 ); hence, growth in the CLT would result in improved transparency in the economy (Warwick 1993 ; Essame 2006 ).…”

“…An increase in transparency would dramatically decline a wide range of economic offences, including the number of incidents of bribery and corruption, money laundering, tax evasion, and the number of hawala transactions (Goel 2018 ; Zabyelina 2015 ; Goel and Mehrotra 2012 ; Schramm and Taube 2003 ; Levin and Satarov 2000 ; Warwick 1993 ). It would also achieve economic growth by influencing economic security (Raj et al 2021 ). For instance, in a cashless economy, it would be hard to make and circulate counterfeit currency and also challenging to finance terrorists through illegal transactions (Warwick 1993 ; Zabyelina 2015 ; Lipow 2010; Goel 2018 ).…”

“…In India, the government and the nation's central bank, the “Reserve Bank of India (RBI)”, responsible for implementing monetary policy, have launched several programmes to promote CLT among the population (Raj et al 2021 ). Consequently, following the initiation of the Digital India campaign in 2015, there has been a significant rise in CLT adoption, with the number increasing from 7046.6 million in 2015–16 to 71,953.1 million in 2021–22, showing a growth rate of 921.10% and an average annual growth rate of 153.52% (RBI Annual Reports).…”