报告题目：The Effects of Digital Resources on Firms’ Export-Financial Performance under Immigrant Ownership
报告人：Sui Sui 教授
邀请人：张尧 教授
报告时间及地点：2026年6月3日 9：00-10：30 经济管理学院B309
报告人简介：：
Dr. Sui Sui’s research focuses on international entrepreneurship and sustainability, with particular emphasis on small business exporters and immigrant-, Indigenous-, and women-owned enterprises. Her work examines how firms internationalize, innovate, and build resilience in the context of global uncertainty, inclusive trade, and sustainability transitions. In parallel, she studies governance and sustainability, including how board gender diversity influences environmental performance, green innovation, ESG engagement, and organizational resilience during crises, as well as how firms respond to institutional and policy pressures related to sustainability transitions. She has published in leading Financial Times Top 50 academic journals, including the Journal of International Business Studies, Journal of Business Venturing, and Entrepreneurship Theory and Practice.
报告摘要：：
This study explains why digital resources generate higher export returns for some small and medium-sized enterprises (SMEs) but not others. Drawing on the liability-of-outsidership framework, we argue that digital resources create virtual embeddedness, while immigrant ownership enhances their effectiveness by enabling real network embeddedness. Using a representative sample of 7,723 Canadian SMEs from Statistics Canada, we employ instrumental-variable models to analyze their export intensity and financial performance. Digital resources increase export intensity, but this effect is substantially stronger for immigrant-owned firms. Export intensity improves financial performance only when digital resources and immigrant ownership are combined. For non-immigrant-owned firms, exporting yields weaker or even negative financial returns. These findings demonstrate that digital resources alone provide only a partial solution to the liability of outsidership and that owner-level social networks critically condition their performance effects.
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