According to the ‘Point’ essay, management research’s reliance on corporate data threatens to replace objective theory with profit-biased ‘corporate empiricism’, undermining the scientific and ethical integrity of the field.

Glaser, V., Sloan, J., and Gehman, J.

Current and future developments in artificial intelligence (AI) systems have the capacity to revolutionize the research process for better or worse. On the one hand, AI systems can serve as collaborators as they help streamline and conduct our research.

Glaser, V., Sloan, J., and Gehman, J.

Interest in the possibilities afforded by algorithms and big data continues to blossom as early adopters gain benefits from AI systems that automate decisions as varied as making customer recommendations, screening job applicants, detecting fraud, and optimizing logistical routes.

Lindebaum, D., Glaser, V., Moser, C., and Ashraf, M.

The intertwining of family relationships with business imperatives provides a fascinating but complex arena for study. This Encyclopedia is a valuable resource because family business studies are necessarily multi-disciplinary and wide-ranging, drawing on entrepreneurship, management, governance, economics, ethics, business history, as well as family studies.

Chrisman, J.J., Fang, H., & Steier, L.P.

Conceptual articles are important for theory building but the special challenges of developing conceptual articles on entrepreneurship has not been fully considered. We begin to fill this gap by discussing the nature of conceptual articles on entrepreneurship, particularly those geared for publication in Entrepreneurship Theory and Practice.

Chrisman, J.J., Fang, H.C., & Steier, L.

Leading academics, practitioners, and enterprising families come together to answer the most pressing thirty-five questions of Next Generation members in a short and concise, yet competent way. To empower Next Generation legacies, the authors share best practices, real-life examples, and critical questions for reflection.

Steier, L.