Abstract
This chapter discusses and proposes an integrated model of actual online shopping use behaviour, with a moderating role of personal traits (openness to experience and agreeableness). Building on the TAM model, the proposed framework harnesses its factors from supported theories, namely social cognitive theory, source credibility theory, risk theory, and OCEAN model. A literature review approach is employed in which the author uses previous relevant studies to establish the relationship among the variables. Apart from direct relationships, the chapter conceptualises mediating role of Intention on the relationship between a set of predictors (internet self-efficacy, perceived channel credibility, financial and security risk) and actual online shopping usage behaviour. At the same time, the chapter explores the moderating role of openness to experience and agreeableness on the relationship between the TAM's belief constructs and intention. Finally, the chapter concludes with highlights on the framework's contributions, limitations, and plan for future empirical investigation.
TopIntroduction
The development of Information technology contributes significantly to electronic commerce (e-commerce), which facilitates everything via the internet, including business-to-consumer (B2C) transactions. Chaffey (2016, p.27) defines B2C e-commerce as commercial transactions between a company (business) and consumers. To make successful online transaction businesses need to understand their customers, attract and convert them into actual buyers, process and make delivery as quick as possible, and provide a secure payment method (Egbele & Kelvin, 2016). Once this situation is adequately achieved, customers will undoubtedly embrace online shopping as an alternative means of shopping activities. With this expectation, many customers today have migrated shopping preference from brick-and-mortar to online buying, which makes retailers strengthen their online presence (Huseynov & Yıldırım, 2016). For instance, online shopping is increasingly adopted in the developed and most developing Asian nations to the extent that consumers across various demographic clusters express continuous willingness to accept it (Singh, & Srivastava, 2019). There are more than 4.5 billion people who access the Internet worldwide; indicating approximately 60% of the global human race is already online (Datareportal, 2020). The report further mentioned the total internet users in Asia-Pacific stood at 2.42 billion, with an almost 56% penetration rate. This means an annual change of almost +9.2% (+204 million users). The global e-commerce spending in 2019 by product category indicates fashion and beauty ($620.1 billion), electronics and physical media ($456.9 billion), foods and personal care ($168.8 billion), furniture and appliances ($316.7 billion), toys and hobbies ($383.2 billion) digital music ($13.59 billion), and video games $83.15 billion), making a global e-commerce value of almost 2.04 trillion dollars. This evidenced that B2C e-commerce has come to stay, thereby disrupting the normal traditional commerce operations. This development necessitates understanding what informed consumer decision toward actual online buying.
Key Terms in this Chapter
E-Commerce: All commercial transactions carried out over the Internet.
Purchase Behaviour: The sum of consumer behaviour aimed at satisfying needs and desires from searching products’ information up to actual purchase.
BUSINESS-TO-CONSUMER (B2C): A form of direct selling of products or services, without an intermediary, from the seller to the buyer over the internet.
Channel-Credibility: The customer perception of an online shopping channel being trustworthy, reliable, and dependable.
Moderating Variable: A variable that can strengthen, reduces, or otherwise change the association between independent and dependent variables.
Mediating Variable: An intervening variable that transmits the effect of the independent variable on the dependent variable.
E-Vendor: A retailer selling products or services via the Internet.