The chapter aims at understanding the predictors of customer satisfaction with online shopping in India by using self-determination theory. This research validates perceived enjoyment, social influence, social media interactions, reverse logistics, and pay-on-delivery (POD) mode of payment as new predictors of customer satisfaction in online shopping. Data was collected through a self-administered and structured questionnaire targeting online shoppers in North Indian states. A sample of 424 online shoppers was considered in this research. Structural equation modelling (SEM) was used to evaluate the constructs. CFA was applied to calculate validity and composite reliability. To examine the hypothesized relationships, path analysis was carried out. The findings of the chapter revealed that social influence, reverse logistics, and POD mode of payment had a significant positive impact on customer satisfaction. Perceived enjoyment emerged as the strongest predictor of online shopping satisfaction. In contrast, social media interactions emerged as non-significant.
TopIntroduction
Online shopping has expanded its horizons over the last few decades due to higher Internet penetration rates, time convenience, swift availability of product-related statistics, reviews about the experience with the product, and social media interactions. As a result, the Indian e-commerce market is projected to cross a figure of US$ 200 billion by 2026 (IBEF, 2020). A significant part of this penetration and development could be attributed to technological advances such as 4G networks and the adoption of smartphones. Furthermore, in an endeavor to encourage online retail, the present government has permitted 100 percent foreign direct investment (FDI) since 2016 (IBEF, 2016). Consequently, until August 2020, a significant upsurge in the number of internet connections was observed.
Additionally, driven by the “Digital India” initiative, the number of internet connections significantly reached 760 million in 2020, where 61% of connections were in urban areas, of which 97% of connections were wireless (IBEF, 2020). This has resulted in profound fluctuations in consumer behavior. At present, India's e-commerce sector includes only 3.4 percent of the overall retail market, with 100-110 million users and an online gross merchandise value (GMV) of about $30 billion (Salman, 2020). In addition to financial technology (fintech) constraints, e-retailers also counter poor infrastructural problems and connectivity with scattered areas comprising 6000 small cities and 0.6 million villages (Nielsen, 2017). In sum, although there has been a sharp upsurge in Internet penetration, this growth has not rendered into more e-shopping numbers.
India also lags behind its neighboring country China in e-Commerce adoption and penetration, which had a 14% online retail penetration at the end of 2019. In contrast, in a developed economy such as the USA, there are slightly more than 284 million internet users in 2020, around 87 percent of the total population (Statista, 2020). But alone in 2020, there were 227.5 million online shoppers, which is approximately 88 percent of the adult population (Salman, 2020). With the upsurge in online shopping due to the COVID-19 outbreak, this number is anticipated to reach 230.5 million in 2021 (Statista, 2020).
Additionally, US e-commerce sales reported 11 percent of all retail sales in the United States, and the figure is anticipated to increase to more than 15 percent in 2021. While there are apparent population and size differences between the USA and India, developing and developed nations also differ very much in their e-commerce development. Developing nations are symbolized by low e-commerce penetration. It is thus of utmost importance to understand the variables that improve the online customer base and retain the existing online customers (Vijay, 2020). Therefore, there is an indispensable requirement to investigate the variables that facilitate e-retailers acquiring additional consumers in an emerging economy context like the Indian one. The Indian setting is similar to a variety of other emerging economies.
Several studies have investigated the online shopping phenomenon in the emerging Indian economy context, yet several issues may arise in extant research. First, most past studies have analyzed e-commerce adoption with limited sample sizes (Sharma and Rehman, 2012; Kumar and Kashyap, 2018). This is problematic from a statistical perspective but also an ecological validity viewpoint. Samples should represent the population under study. Such small samples cannot appropriately reflect either the volume or the diversity of such a large nation as the Indian one. In fact, and related to the previous point, most studies have been restricted to specific geographical areas (e.g., Kandulapati and Bellamkonda, 2014; Kumar and Kashyap, 2018; Merugu and Mohan 2020; Kripesh et al., 2020).
Second, most studies focused on purchase or repurchase intentions (e.g., Kwahk and Kim, 2017; Safia et al., 2019; Oumayma, 2019). Intentions are important, but they may not necessarily translate into behaviour due to the intention-behavior gap. Studying behaviour frequency, on the other hand, informs about behavioural loyalty (repeated visits, repurchases) but not about emotional loyalty (positive attitudes, favourable recommendations) that are more important to spur stable and sustainable e-commerce growth (Chaffey and Ellis-Chadwick, 2019; Kingsnorth, 2019). Greater emphasis should thus be put on exploring satisfaction as an essential component of emotional loyalty.