Mohammed Alyakoob

Mohammed Alyakoob serves as an Assistant Professor of Data Sciences and Operations within the Marshall School of Business at the University of Southern California. His academic work centers on the economic and societal implications of digital marketplaces, with particular attention to how market structure, demographic factors, and expertise create barriers that result in unequal distribution of platform benefits. He is an active educator, teaching core business analytics courses in both the MBA and Master of Science in Business Analytics (MSBA) programs, and has been featured in prominent media outlets including the Washington Post, Chicago Tribune, and LA Times for his research contributions.

Research Focus

Dr. Alyakoob's research program critically examines the Sharing Economy and Information Systems through the lens of equity and access. He investigates how traditional barriers—such as geographic location, local market competition, and expertise—shape participant experiences and outcomes in digital platforms. His work bridges economic theory with empirical analysis of real-world marketplace data to uncover systemic inequities and propose pathways toward more inclusive platform design. This research intersects multiple disciplines including Economics, Information Systems, and Social Sciences, with specific applications in platform governance and policy.

Publication Trends

His recent scholarly output demonstrates a consistent focus on disparity and access in digital economies. Key publications analyze the sharing economy's promise of shared prosperity against observed realities of inequality, and investigate how local banking structures influence borrower outcomes in online lending platforms. These works collectively contribute to the fields of Platform Economics, Digital Finance, and Socio-Technical Systems, highlighting the complex interplay between technology infrastructure and socioeconomic factors in shaping marketplace equity.

Educational Contributions

In the classroom, Alyakoob delivers foundational instruction in business analytics (DSO-510) and advanced topics in data sciences (DSO-699). He also mentors graduate students through DSO-596 Research Practicum courses, providing hands-on research experience within the Data Sciences and Operations Department. His teaching philosophy emphasizes practical application of analytical methods for data-driven decision making and innovation in business contexts.