Social Commerce: The Good, the Bad, and the Ugly

Permanent URI for this collection

https://hdl.handle.net/10125/109963

Browse

Recent Submissions

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Dual-Technique Privacy & Security Analysis for E-Commerce Websites Through Automated and Manual Implementation
    (2025-01-07) Kishnani, Urvashi; Das, Sanchari
    As e-commerce continues to expand, the urgency for stronger privacy and security measures becomes increasingly critical, particularly on platforms frequented by younger users who are often less aware of potential risks. In our analysis of 90 US-based e-commerce websites, we employed a dual-technique approach, combining automated tools with manual evaluations. Tools like CookieServe and PrivacyCheck revealed that 38.5% of the websites deployed over 50 cookies per session, many of which were categorized as unnecessary or unclear in function, posing significant risks to users’ Personally Identifiable Information (PII). Our manual assessment further uncovered critical gaps in standard security practices, including the absence of mandatory multi-factor authentication (MFA) and breach notification protocols. Additionally, we observed inadequate input validation, which compromises the integrity of user data and transactions. Based on these findings, we recommend targeted improvements to privacy policies, enhanced transparency in cookie usage, and the implementation of stronger authentication protocols. These measures are essential for ensuring compliance with CCPA and COPPA, thereby fostering more secure online environments, particularly for younger users.
  • Thumbnail Image
    Item
    Introduction to the Minitrack on Social Commerce: The Good, the Bad, and the Ugly
    (2025-01-07) Sundaram, David; Hassna, Ghazwan; Peko, Gabrielle; Sadovykh , Valeria
  • Thumbnail Image
    Item
    Does AI-Generated Review Summarization Affect Consumer Purchasing Behavior?— An Empirical Study Based on the Amazon Platform
    (2025-01-07) Wang, Huike; Wang, Tianmei
    The product reviews on e-commerce platforms have become an important reference for consumers' purchase decisions. However, the sheer volume of reviews can lead to information overload, which may negatively affect consumer purchasing behavior. The AI-generated review summarization brings an opportunity to solve this dilemma. We collected 48,019 panel data of 3,781 products from the Amazon platform between February 2023 and February 2024, and employed a difference-in-differences model to investigate the impact mechanism of AI-generated review summarization on consumer purchasing behavior. The research found that AI-generated review summarization promotes consumer purchasing behavior. The number of product reviews has a U-shaped moderating effect, and the average product rating and rating dispersion both have positive moderating effects. Additionally, compared to experience products, search products amplify the impact of AI-generated review summarization on consumer purchasing behavior. The findings offer theoretical support for enhancing the design of AI-human interactions on e-commerce platforms.