Meixian Wang(汪媚仙)

Meixian Wang(汪媚仙)

A Ph.D. candidate in Fox Business School of Temple University

Posts by Collection

portfolio

publications

Paper Title Number 4

Published in GitHub Journal of Bugs, 2024

This paper is about fixing template issue #693.

Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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research

The Impact of Realism and AI Disclosure on Virtual Influencer Effectiveness: A Large Field Experiment

Abstract

Influencer marketing has become essential for brands, and the advent of generative AI drives the adoption of AI-generated virtual influencers. However, this innovative approach raises challenges around virtual influencer’s transparency and ethical usage. By conducting a large field experiment, we examine the impact of different levels of realism of virtual influencers and AI identity disclosure on over 1.8 million consumers. Results show that virtual influencers with higher levels of realism outperform those with less. Additionally, the study indicates that AI identity disclosure reduced consumer link clicks and 3s-video play by more than 20% and 6%, particularly with high-realism virtual influencers. The underlying mechanism reveals that the uncanny valley dehumanization effect is triggered when AI identities are disclosed, violating consumers’ expectations and causing negative feelings. Fortunately, the negative dehumanization effect can be mitigated by consumers’ prior experience with virtual influencers. Our findings provide actionable guidelines for brands and content creators to integrate AI agents into content generation and marketing strategies effectively.

Enhancing Digital Fundraising: The Impact of Charity Streams on Streamer Engagement and Donor Behavior

Abstract

Motivated by incorporating charity streams on live streaming platforms, we investigate how adopting charity streams impacts streamers’ engagement and economic performance. Our setting is on a live streaming platform, Twitch, which launched its charity tool to enable viewers to choose between supporting streamers directly or donating to charities easily. Using a combination of coarsened exact matching and a staggered difference-in-differences estimation model, our initial findings indicate that charity streams enhance streamer viewership and followers and potentially increase donations to streamers and charities. The study fills a gap in understanding the strategic use of influencers for fundraising, offering practical insights for influencers on harmonizing prosocial activities to build their image and engage their audience.

An Empirical Case Study of the Impact of Superstar Streamer Exits on Live Streaming E-Commerce Platforms

Abstract

Although superstar streamers currently dominate the emerging live streaming e-commerce (LSE) platforms, their enduring presence on such platforms is not guaranteed. Superstar streamers are important because they attract consumers, promote new sellers, and increase sales. However, their exit from LSE platforms has been largely neglected in the literature. To address this research gap, this study examines how the exit of superstar streamers impacts peer streamers on the same LSE platform. Using data collected from Taobao Live, we model the superstar exit effect, using the unexpected exit of Viya, a once popular streamer on Taobao Live, as an exogenous shock on the performance of peer streamers. Also, we examine challenges posed by the exit of superstar streamers from a market structure perspective, considering the heterogeneous impact of streamer types and brand halo effects. Our results suggest that in general, streamers on LSE platforms benefit from a superstar streamer’s exit through a redistribution of consumer demand across similar streamers. Furthermore, we found that streamers employed by brands benefit from the brand halo effect and gain more sales and viewership than independent streamers. Our study extends the literature on LSE, the superstar effect, and brand halo effects. Our findings also have practical implications for platform managers, brands, streamers, and consumers.

talks

teaching

Teaching experience

Undergraduate course, Temple University, MIS Department, 2024

Course Description

The course provides a foundation for designing database systems and analyzing business data to enhance firm competitiveness. Concepts introduced in this course aim to develop an understanding of the different types of business data, various analytical approaches, and the application of these approaches to solve business problems. Students will have hands-on experience with current, cutting-edge tools such as MySQL and Python and with practical projects (e.g., database design, data visualization, introductory machine learning).