The Diffusion and Adoption of Electronic Payment Systems in Bangkok

The Diffusion and Adoption of Electronic Payment Systems in Bangkok

Wornchanok Chaiyasoonthorn (Faculty of Administration and Management, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand) and Watanyoo Suksa-ngiam (The Center for Information Systems and Technology (CISAT), Claremont Graduate University, USA)
Copyright: © 2019 |Pages: 14
DOI: 10.4018/IJEBR.2019040106

Abstract

This article aims to study the diffusion and adoption of electronic payment systems in Bangkok, Thailand. This study is a cross-sectional survey of 394 respondents who lived in Bangkok. This research employs Pearson's correlation and structural equation modeling (SEM) to answer two research questions: 1) How do the socio-economic classes of people show differences in the use of e-payment systems? and 2) What are significant factors driving customers to use e-payment systems? The findings show that user behavior has a positive correlation with personal income. Higher-income people tend to use electronic payment systems more than lower-income people. There is no relationship between areas and use behavior. Moreover, the research shows that adoption readiness, income, and internet banking positively influence use behavior significantly, while electronic money shows a significant negative relationship with use behavior. Education and age indirectly influence use behavior via personal income. The authors also addressed both theoretical and practical implications.
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Introduction

Electronic payment (e-payment) systems are necessary for digital economy. The widespread adoption and diffusion of e-payment systems in various forms lead to the drive of the digital economy. Many electronic commerce (e-commerce) platforms are increasingly using e-payment systems as tools to facilitate customers' transactions. Although e-commerce does not necessarily require e-payment because payment can be made physically (OECD, 2014), e-payment systems are the major part of the financial circulation system of e-commerce (Özkan, Bindusara, & Hackney, 2010). Additionally, in 2012, the adoption of e-payment systems worldwide generated 360 billion US dollars in transactions (Laudon & Traver, 2012).

The adoption and diffusion of e-payment can promote the effectiveness and efficiency of the economic system. Governments attempt to encourage their citizens to use e-payment systems because governments can save costs from producing paper money. Also, governments can force businesses to pay tax by using e-payment systems as monitoring tools. Additionally, people can benefit from the use of e-payment systems when purchase products or services on the Internet or other electronic systems without having to send money physically. Moreover, e-payment offers businesses the opportunity to connect with customers worldwide since e-commerce is a part of the global digital economy.

Recently, the Thai government has initiated digital economy strategies. These strategies are difficult to execute without knowing how and why e-payment systems are adopted and diffused. Knowing so could lead to the right policy implementations. These policy implementations have to comply with types of e-payment systems, such as business-to-business (B2B) or business-to-customer (B2C) transactions. Although the significant business transactions are B2B transactions, the growth of B2C transactions is rising rapidly. The value of transactions grew from 99,706 million Baht ($ 3,115.8 million: 32 Bath per USD) to 121,392 million Baht ($ 3,793.5 million) in 2012 (National Statistical Office, 2013), ultimately leading to the broad adoption of e-payment. Statista.com estimated that the transactions of e-payment in Thailand is expected to grow 281.24% from $ 8,757 million in 2016 to $ 24,628 million in 2022 (Digital payment-Thailand, 2017).

Although there were studies on e-payment systems (Chellappa & Pavlou, 2002; K. K. Kim & Prabhakar, 2004; Özkan et al., 2010; Pavlou, 2003; Pikkarainen, Pikkarainen, Karjaluoto, & Pahnila, 2004; Plouffe, Vandenbosch, & Hulland, 2001; Rakhi & Mala, 2014; Roca, García, & de la Vega, 2009; K. C. C. Yang, 2005; Y. Yang, Liu, Li, & Yu, 2015), there has been no research conducted in Thailand. Moreover, the theoretical frames that these articles employed are based on TAM (Pikkarainen et al., 2004; Plouffe et al., 2001; K. C. C. Yang, 2005) and UTAUT (Rakhi & Mala, 2014). However, none of these papers applied UTAUT2, which is a recent theory in Information Systems (IS). A new theory has to generalize across space and time. Besides, this study uses UTAUT2 as AR (a single latent variable) to account for possible attitudinal constructs. AR together with socio-economic and technology variables can control the effects of each other. Controlling the effects of possible variables helps us prevent the confounding effects on statistical results. Most research in technology adoption has used the behavioral lens in the conceptual framework, while the socio-economic lens is often ignored.

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