The Rise of Cyber Currency, Artificial Intelligence, and Strategies for Women’s Entrepreneurship
Through books and online media, Babson faculty share their knowledge in cyber currency, women’s entrepreneurship, and artificial intelligence.
Babson Names New Assistant Professor of Finance
Linghang Zeng was welcomed as a new tenure-track assistant professor of finance. He recently earned his PhD in finance from Georgia Tech’s Scheller College of Business, and his research interests include labor and finance and empirical asset pricing. Zeng also is studying the impact of e-commerce on brick-and-mortar employees, and has been honored with best paper awards from Northern Finance Association and Chicago Quantitative Alliance.
The Growth of Cyber Currency
Finance Professor John Edmunds’ book on alternative and cryptocurrencies is scheduled to be released in February. Rogue Money and the Underground Economy studies controversies that have accompanied the growth of cyber currency and its relation to the underground economy and illegal activities.
The book provides a greater understanding of economic history and international trade as they relate to cyber currency, and reviews benefits and drawbacks of the role cyber currency has in today’s underground economy.
Analyzing Women’s Entrepreneurship Strategies
Marketing Professor Victoria Crittenden’s book, Go-to-Market Strategies for Women Entrepreneurs,was published earlier this month. The book considers the role women’s entrepreneurship plays in developing self-efficacy, the power of creating and utilizing social capital, the importance of authenticity, and the value of family, friends, and mentors. Crittenden demonstrates how empowerment can positively impact nations through better education, poverty reduction, and decreased violence.
The Best Practice of Artificial Intelligence
Professor of Information Technology and Management Tom Davenport wrote columns for Forbes and Information Age on automated machine learning and how best to use artificial intelligence. Davenport touted automated machine learning for its ability to analyze data and business problems more efficiently than data scientists, and he also said for entities to receive the best results from AI, they must use it to tackle a higher number of simpler, smaller projects.
Featured photo courtesy of 13_Phunkod/Shutterstock.com.