Examining consumers’ webrooming behavior: an integrated approach

Abstract

Purpose The purpose of this paper is to employ an integrated technology acceptance model–theory of planned behavior framework intertwined with online risk, e-distrust and product involvement to augment an understanding on consumers’ webrooming behavior. Design/methodology/approach A mix of convenience and selective sampling was used for data collection. A total of 14 propositions were put forth, which were tested using the structural equation modeling method. Findings The results of the study revealed that apart from perceived ease of searching online and overall usefulness of the webrooming sequence, perceived search benefits online and purchase benefits offline significantly determined consumers’ webrooming behavior. The results of the study also indicate that webrooming helps consumers avoid the feeling of post-purchase regret of making sub-optimal product choices offline. Online risk perceptions and e-distrust also play a notable role in inhibiting consumers’ from making online purchases, and as a consequence encourage webrooming behavior. The moderating influence of product involvement was observed between consumers’ intentions toward webrooming and webrooming behavior. Research limitations/implications The research conducted provides rich insights into understanding the rising webrooming phenomenon. However, more exhaustive studies are needed to arrive at definitive findings concerning the webrooming phenomenon. Practical implications The findings of the study can be utilized by the online retailers for formulating strategies to counter webrooming behavior. Originality/value The paper is amongst the first few studies which contribute toward enhancing the understanding on webrooming behavior, an emerging issue in the current retailing environment.

How Does Online Engagement Drive Consumers' Webrooming Intention?

“…Hence, consumers prefer online platforms to search the information (Arora & Sahney, 2018;Shankar and Jain, 2020). Online platforms enable gathering an enormous amount of product information economically (Arora & Sahney, 2019) as consumers can access a huge amount of information in a few clicks. Lower cost of accessing information online promotes online free-riding behaviour among consumers, and they tend to search online before making a final purchase decision.…”

“…Further, active online users can compare the performance of different brands of a specific product category only in few clicks (Verhoef et al, 2007;Shankar et al, 2020a). Consumers can also compare the price of specific products over different online platforms for making a better purchase decision (Arora & Sahney, 2019). Consumers can also explore substitute and complementary products over online platforms (Heitz-Spahn, 2013).…”

“…There is an absence of face-to-face interaction between sellers and buyers over the online platform, which develops a sense of uncertainty towards online purchase (Ha & Stoel, 2009). Consumers can physically examine products during offline shopping, which reduces the uncertainty associated with the purchase (Arora & Sahney, 2019). Online shopping also involves privacy and security risks.…”

“…Further, consumer webrooming behaviour is one of the crucial changes faced by multi-channel retailer hence, in the literature, attempts were made to explore factors affecting webrooming behaviour (Flavián et al, 2016;Fernández et al, 2018;Arora & Sahney, 2019;Aw, 2019Aw, , 2020. Consumer engagement in specific channels plays a crucial role in enhancing consumer experience and consumer channel selection for purchasing a product or availing of services .…”

Multichannel search patterns and webrooming behaviours in the service industries: the case of motor insurance

“…The aim of this research is to identify the main determinants of the above search patterns and, further, to explain what drives the conversion of a specific search pattern into a specific purchase channel decision. In line with these aims, and based on the broad stream of academic literature on channel choices in a multichannel perspective and on the determinants of shopping behaviours (Arora and Sahney 2019;Flavian et al 2016Flavian et al , 2020Konus 2008;Venkatesan et al 2007;Verhoef et al 2007), a set of seven hypotheses on the determinants of customers' patterns of search has been developed. All the psychographic variables we have selected refer to the general shopping attitudes of customers and not to their specific preferences and choices concerning the channels available, which-within our research design-represent, instead, our dependent variable.…”