Based on technological acceptance models and perceived risks, this study examines and assesses the variables affecting customer intentions to make online transactions in Indian state Haryana. Three hundred-eight valid responses were obtained from the poll, which was performed online. The Smart PLS 3.0 application and structural equation modeling methods were used to examine the data. The results showed that perceived utility, danger, and simplicity of use all positively affected online purchase intentions. In contrast, perceived risk apprehensions have a detrimental impact on plans to make purchases online. The study focused on how online purchase intentions are impacted by perceived usability, perceived risk, along with perceived ease of use. Future research has to take other factors into account.
TopIntroduction
More than 4 billion people will utilize the internet by the year 2020, according to Internet World Stats (2015). The majority (50.3%) of internet users are from the Asian area. Second on the list, among the nations behind China, is India. With a presentation of achieved 692 million subscribers, India placed second in Asia's greatest considerable internet use presentation, according to Annur (2019). It is impossible to distinguish the growing number of internet users in India from those who conduct online transactions. An estimated 1.8 billion people made online purchases in 2018 around the globe. Internet sales have reached $2.8 billion due to the average number of users globally, and they are expected to reach $4.8 billion by 2021. (Statista, 2019).
According to Statista (2019), online business transactions are available everywhere there is an internet connection, including at home, at the workplace, in a public space, and on devices like PCs, cellphones, and tablets (Ariffin et al., 2018). Nowadays, it is a commonplace to utilize an online shopping system to buy things like airline tickets, hotel bookings, movie tickets, clothes, and cosmetics. Travel-related items, which had an overall score of 82.2 percent among the things customers bought online, were followed by general goods (59%) and books (69%) (Ariffin et al., 2018). E-commerce has changed how consumers think about getting products and services. Scholars and marketers have focused their attempts on better comprehending online purchase behavior as online transactions and clients have grown in popularity (Lim, 2015). Businesses engaged in e-commerce need to monitor the expansion of online spending and understand the elements influencing buyers' choice to make a purchase online (Marron & Steel, 2000; Lohse & Spiller, 1998). One of the 2 major features that influence the behavior of a customer while shopping is their desire to buy (Mayer et al., 1995; Muncy & Wilkie, 1987).
In studies on the elements that affect consumers' online shopping decisions, several models are used. The adoption of new technologies has often been assessed utilizing the TAM (“Technology Acceptance Model”). To comprehend the elements of acceptance of IT or driving user adoption, Davis (1985) created the TAM. These elements are utility and usability. The literature studies have effectively used the technology acceptance model to look at people's intentions and behavior when they purchase online (Pavlou, 2003; Gefen et al., 2003a; b). A technological acceptance model was proposed in the earlier investigation to assess the elements affecting the adoption of e-shopping technologies (Mpinganjira, 2016). Investigators have deemed e-shopping to accept the usage of IT systems since it revolves around utilizing mobile apps and web apps to buy goods as well as services. The technological acceptance model may help in understanding e-commerce adoption since it has been applied to online transactions.
Among the most important elements that influence customer inclination to purchase online is perceived risk. Given that buyers do not personally contact sellers or the products in question while making an online purchase, the risk for customers is increased (Jarvenpaa et al., 2000; Pavlou, 2003). Product risk and financial risk are 2 potential dangers that internet shoppers may encounter (Bhatnagar et al., 2000). Perceived risk’s impact on online purchase intentions has been studied extensively. Nevertheless, the outcomes of certain investigations varied. Perceived risk is a characteristic that influences online purchasing intentions adversely, according to earlier research (Chiu, 2014; Almousa, 2011; Ha et al., 2020; Ariffin, 2018; Clement, 2019; Pires et al., 2006; Singh & Srivastava, 2018; Prayag et al., 2009). Gefen et al. (2003) discovered that there is no correlation between the desire to purchase online and perceived risk. As per Ventre & Kolbe (2020), intentions for online purchases were unaffected by perceived risk. Therefore, to analyse customer intentions in Indian online buying, this research integrates perceived risk with the technological acceptance model.