Al Niswah: Secure Online Trading for Women with Expert Support and Complaint Resolution

Abstract

Women’s participation in online commerce is increasing; however, many women entrepreneurs in developing contexts continue to face substantial barriers to selling online. These barriers include limited access to customers, as well as serious concerns related to reliability, security, and fairness in online trading. This paper presents Al Niswah, a women-focused web marketplace designed to support home-based and small-scale women sellers through features that directly address these challenges. The platform enables direct communication between buyers and sellers, reducing dependence on intermediaries and potentially improving seller profitability. It also incorporates administrative supervision and a structured complaint-handling mechanism to enhance transparency, reduce misuse, and support accountability. In addition, Al Niswah provides guidance through expert support and includes a keyword-based help module that responds to user queries when expert assistance is unavailable. The system is designed to reflect common constraints faced by women sellers and to offer a practical solution for secure online trading and product promotion. To validate the platform at the functional level, black-box testing was conducted using representative test cases. The results confirm the correct operation of key workflows, including account registration and login, seller approval, product listing and browsing, complaint submission and handling, and advisory interactions through the support module. The paper also summarizes major implementation decisions and highlights system requirements related to safe and secure use. Finally, planned enhancements are outlined, including mobile text-message notifications for expert availability, an Android application, a more advanced advisory system, online payment support, and a user-rating feature. Future work will involve user-based evaluation to assess outcomes such as trust, usability, and adoption in real-world settings.