Abstract

Impulse buying is an unintended and persuasive purchasing behavior. It is estimated that 40% of online buying is due to impulse behavior (Chan, Cheung, and Lee 2017). Despite the increasing importance of online buying for businesses, our understanding of the topic is limited in two ways. First, online buying and impulsiveness are understudied. Although impulse buying has been studied extensively, it has received limited attention in online settings (Akram et al. 2018). The majority of the published papers in an online context are focused on rational and planned buying behavior rather than impulse behavior (Liao et al. 2016). Second, a limited number of factors and their effect on customer behavior have been studied in online shops (Ladhari 2010). Extant literature examined the impact of the design of online shops, types of products, and the presentation of products on customers’ impulse buying behavior. The emphasis of past research is on the technical aspects of a website rather than overall electronic service quality (ESQ). There are different ESQ factors, including operational related factors (e.g., shipping, return policies, etc.), seller related factors (ratings), and pricing related factors (billing accuracy) that are neglected in the past studies. To address the two mentioned gaps, we study customers’ impulse online buying behavior through the identification of critical ESQ parameters that affect customer decisions. We focus on the impulse online buying behavior of customers and use cognitive emotion theory to analyze the behavior of customers in response to the ESQ stimulus provided by online shops. To develop the research, we conduct a comprehensive literature analysis to identify ESQ factors and to develop a research model underlying customers’ impulse online buying behavior. We will conduct a field experiment and an online survey to explore the effect of different factors on impulse buying behavior of online buyers. We will collect data from customers of two online shops on eBay. Each of these stores has multiple products from different product categories. The data will be analyzed based on the design of experiment (DOE) and appropriate structured equation modeling methods. The findings of this research can have important implications for practitioners. The identified ESQ factors assist online shops in enhancing their performance efficiently by focusing on and investing in areas with practical importance.

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