A Fresh Look on Determinants of Online Repurchase Intention

Introduction

Over the period of last decade, electronic commerce (E-Commerce) has gained irreplaceable place in international retail framework. The advent of Internet transformed retail industry like any other sector in recent past. Nevertheless, ongoing fourth industrial revolution and digitization of the economy, consumers have well adopted online shopping and enjoying various perks of the same (Dastane, 2020). Worldwide, there are 4.66 billion internet users and around 2.14 billion people purchases goods online globally. Out of all the retail purchase occasions, 63% shopping occasions begin online. This sales growth is estimated to continue to rise and take up more of a retail share. According to (Statista, 2020), online sales is estimated to reach 6.40 trillion attributing to 21.8% of total retail sales by 2022.

This growth comes with several challenges and issues. The exponential growth has produced tremendous competition as several stalwarts’ retailers have rallied in this sector with their e-stores and mobile apps. Such a high competition has thinner the boundaries of innovation and resulted in difficulties in offering unique value propositions. High competition also results in high switching rate as well as low engagement with prospects (Hui, Dastane, Johari & Roslee, 2020). This then generates need to think on fostering loyalty among existing customers by encouraging repurchase intentions among them. E-commerce industry is struggling with conversion rate, and it is estimated that 62% of visitors will just search products and do not make the purchases (Statista, 2019). On one hand, it is challenging to get new consumers, at the same time, according to (KPMG, 2019), it can cost 5 times more to acquire new than retaining existing one. The success rate if selling products to existing loyal customers is around 60% compared to 5-20% for that for new customers. It then becomes of paramount interest for E-Commerce players, to understand key determinants of ORI.

A number of studies have investigated the concept of repurchase intention (see. Ali & Bhasin, 2019; Bulut, 2015; Edward & Lawler, 2001; Oliver, 1980) and attributed it as a phenomenon mainly resultant of satisfaction (Cheng & lee, 2011; Ibzan, Balarabe, & Jakada, 2016; Sharma, 2017), brand (Aslam, Ham, & Farhat, 2018) and trust (Barnes, 2007; Benazić, & Tanković, 2015; Tirtayani & Sukaatmadja, 2018). However, several other studies have confirmed that repurchase is not a phenomenon limited to single factor such as satisfaction (see. Bauer, Falk, & Hammerschmidt, 2006; Phuong & Dat, 2017). There can be several influences, mediators and moderators determining repurchase intentions (Tran, Pham, & Le, 2018). For example, adjusted expectations are analyzed in reference to the new paradigm of post-consumption (Ha et al., 2010). This is particularly in the context of online shopping whereby in post-consumption the adjusted expectations of online shoppers will guide purchase behavior in the next period (Yi and La, 2004). It is then imperative to analysis various such determinants in online context. Prior literature has identified range of aspects influencing ORI (see. Bhattacherjee, 2001; Pavlou, 2003). However, several factors need to be analyzed as a result of contemporary impacts, issues and recovery post COVID 19 pandemic which significantly influenced online consumer behavior (Sheth, 2020).