Academic journal article International Journal of Business and Information

Does an Established Offline Store Drive Online Purchase Intention?

Academic journal article International Journal of Business and Information

Does an Established Offline Store Drive Online Purchase Intention?

Article excerpt


The development of network technology has made it more convenient to communicate information and has created a new style of business model. Not only has it led to the vigorous growth of online transactions, but also it has changed consumer shopping habits. Unlike the traditional business model, the network provides a faster shopping environment that is less affected by time/geographical restrictions (Bhatnagar et al., 2000; Wani & Malik, 2013). A purchase, bargaining, payment process can be completed through the Internet, which is a great convenience for people (Bhatnagar & Ghose, 2004). Recently, a multichannel strategy - namely, O2O - has emerged for integrating physical and Internet retailing (Vishwanath & Mulvin, 2001; Haeberle, 2003; Jin et al., 2010).

Online-to-offline is defined as the use of online information by consumers to search for and order goods and then pick up the goods at a physical store (Rampell, 2010). For example, in the case of the business model of MOS Burger, Uber, and Opentable in the USA and EZTable in Taiwan, consumers search for information and make reservations online and then receive the service or product at the physical store. Nowadays, more companies engage in reverse online-to-offline (offline-toonline), which means that consumers refer to goods offline and then place their orders online via mobile phones, as in the case of Tesco in Korean supermarkets (Wiki, 2013). Both online-to-offline and offline-to-online are defined as O2O in general. Because of the increasing bandwidth and perfection of the cash-flow mechanism, mobile shopping is becoming more popular. It is very likely that companies will adopt the O2O approach to meet consumer demands. There is a need, therefore, to explore the potential of this emerging business model.

The O2O multichannel retailers hope that online marketing activities will drive offline sales and that offline experiences will drive online revenues. O2O is suitable for customer-to-store shopping, such as eating, body-building, watching movies/shows, and hairdressing. Although more retailers have developed this emerging channel, research related to the subject is scare.

There are four dimensions with regard to online/offline research:

1. The revenue dimension. Pauwels et al. (2011) conclude that offline revenues increase for those customers with high web-visit frequency and suggest that offline retailers could apply specific online activities aimed at those consumers.

2. The dimension of consumer demographic and attitudinal analysis (Ganesh et al., 2010; Vachhani & Bhayani, 2012; Sunil 2013).

3. The emotion dimension. In their study, Loureiro and Roschk (2014) compare this dimension for both online and offline: "Results for the offline context reveal that graphics design foster positive emotions and loyalty, yet information design predicts loyalty. Results for the online context reveal that information design is salient over graphics design. Information design fosters positive emotions and loyalty, while graphics design does not."

4. The dimension of the influence of online information on offline behavior. This aspect has been studied, for example, by Pauwel et al. ( 2011) and Rippe et al. (2015).

In recent years, a new channel pattern has developed; namely, the multichannel pattern, where offline stores join online retailers to increase online performance. There have been few studies of this new channel pattern, but Jin et al. (2010) examine a synergistic interchange between online and offline operations. They propose a multichannel performance model that integrates the motivationhygiene theory by Herzberg (1966) and the halo effect by Thorndike (1920). The essence of the research is to verify that consumer e-satisfaction is influenced by online attributes and offline factors, which then increase their e-loyalty.

The research of Jin et al. (2010) is a good beginning to discover that the performance of e-retailers is increased by extending offline stores. …

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