In the modern Web, security headers are of the utmost importance for websites to provide protection against various attacks, such as Cross-Site Scripting, Clickjacking, and Cross-Site Leaks. As each security header uses a different syntax and has unique processing rules, correctly implementing them is a complex task for both browser and website developers. Inconsistency in browser behavior related to security headers harms websites as their security depends on their users' browsers. At the same time, compatibility issues may deter developers from deploying such headers in the first place.

Over 65% of web traffic originates from mobile devices. However, much of this traffic is not from mobile web browsers but rather from mobile apps displaying web content. Android's WebView has been a common way for apps to display web content, but it entails security and privacy concerns, especially for third-party content. Custom Tabs (CTs) are a more recent and recommended alternative.

There is significant interest among marketers and academics to understand how to segment online consumers to better fulfill their needs. Previous literature on brick-and-mortar shopping has advocated demographic variables as simple yet valuable indicators to understand consumers and segment them accordingly. However, research in the online shopping context has produced mixed findings about the effects of demographics, which limit their utility to online merchants. As an attempt to address the ambiguity, the study proposes a more comprehensive approach to investigate the effects of demographic variables in the online shopping context. This is done by considering the demographic variables in combinations and using clickstream data to more accurately derive online shoppers’ surfing behaviour for segmentation purposes. Following this approach, our study investigates the effects of the demographic variables of gender, age, income, and education, based on the theories of media naturalness and consumer trait and involvement. The results reveal various effects of age, income, and education on online consumers’ needs being reflected in their store visit strategies. Implications are suggested for e-commerce research and practice.