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The fast and rapid development of technology, especially the Internet, has changed consumers’ behavior as well as the way firms conduct their business. The availability of internet platforms for online shopping help customers in comparing prices and products as well as arranging the delivery of product or service purchased (Alrousan, Al-Adwan, Al-Madadha, & Khasawneh, 2020; Yeo, Goh, & Rezaei, 2017). For restaurant and customers, the online technology helps them to purchase the food through online applications such as Eat24 and GrabFood. The online technology help restaurants to increase the accuracy of clients’ order, improve business productivity, develop customer relationship, and more importantly expand their market share (Ng, Wong, & Chong, 2017; Yeo et al., 2017). Recent developments indicate that among online shopping, food is the most preferred product purchased online (Chang, Chou, & Lo, 2014). Although it is providing vast business opportunity, this online business development creates rapid competition among online food business players. In this environment, developing a favorable behavior intention, especially intention to repurchase and recommend the business is imperative (Pee, Jiang, & Klein, 2018; Zhang, Xiao, & Zhou, 2020).
The significance of behavioral intention and its antecedents are well examined in the literature. Among its determinants, literature notes that the quality of product and service, value, and satisfaction are the main antecedents of behavioral intention (Sajad, Maryam, & Naser, 2019; Yeo et al., 2017). However, although there are vast researches examining behavioral intention model, scholars (Dean & Suhartanto, 2019; Guo, Berkshire, Fulton, & Hermanson, 2019) suggested that the formation of behavioral intention is not well comprehended. Further, the findings of a study on behavioral intention in a certain industry is difficult to be applied in other industry environment due to the differences of the industry characteristics. Therefore, scholars (Dean & Suhartanto, 2019; Yeo et al., 2017) advocated to examine customer behavioral intention in other industries. Despite its promise of being a flourishing business (Kedah, Ismail, Haque, & Ahmed, 2015; Yeo et al., 2017), what drives behavioral intention towards online food business has got little attention.
The extant literature clearly shows that customers have different attitudes and behaviors according to their segment characteristics (Roy, 2018). In the restaurant industry, scholars (Ali, Harris, & Ryu, 2019; Suhartanto, Helmi Ali, Tan, Sjahroeddin, & Kusdibyo, 2019) reported that customer intention to revisit differs across customers’ dining frequency. Pantouvakis and Lymperopoulos (2008) found a difference in satisfaction and behavioral intention between new and repeat customers. However, none of the previous researches has examined behavioral intention formation model at different purchasing levels. Understanding this phenomenon is important from the managerial as well as theoretical perspective. Driven by the identified research gaps, this study tries to explore the behavioral intention model across customers’ purchasing levels. Explicitly, this study is intended to assess customer behavioral intention model including E-service quality, food quality, value, and customer satisfaction as the determinant across three online food purchasing levels: light, medium, and heavy purchaser. Examining such issue will help the business restaurateurs to create strategies to satisfy their customers and extend their strategy to create favorable behavioral intention towards their online food purchasing services.