Imperial College London

Dr Mark Thomas Kennedy

Business School

Associate Professor



+44 (0)20 7594 2879mark.kennedy Website




295Business School BuildingSouth Kensington Campus





Mark Kennedy leads the Data Science Institute (DSI) at Imperial and teaches on Ph.D., Masters, and Executive courses in the Business School and the DSI.

Mark's research explores how diffusing innovations become social facts of life—like it or not.

When people encounter the unfamiliar, they at least implicitly ask, "Is this anything?" When the answer becomes, "Yes, this does seem to be a thing", innovations spread and earn approval, incite backlash, or both. Whatever the reception, diffusing innovations become categories in shared catalogues of things worth knowing about—that is, social ontologies.

Examples from Mark's research include categories in computing (workstations), science (nanotech and generative AI), business (online ad exchanges, golden parachutes, AI-driven reorganisations), and law (the rise of trusts and the development of anti-trust law). Across these projects, Mark has a long-stranding interest in developing and using quantitative methods for text and network analysis to do both qualitative and quantitative studies of nascent social realities and collective reactions to them.

Mark's publications have appeared in Academy of Management Journal, Academy of Management Review, American Sociological Review, Big Data Analytics, Journal of Management Studies, Organization Science, and Research in the Sociology of Organizations.

Mark's current projects include (1) the evolution of AI and its impact on work, organisations, and society, (2) the role of cultural and legal precedent in cases where diffusion attracts opposition, (3) "task mining" methods for extracting tasks and task interdependencies from the text of job descriptions, and (4) understanding how individuals pick the people they rely on for friendship, help, and advice in work and life.  



Lo JY-C, Rhee E, Fiss P, et al., 2020, Category viability: balanced levels of coherence and distinctiveness, Academy of Management Review, Vol:45, ISSN:1930-3807, Pages:85-108

Molina-Solana M, Kennedy M, Amador Diaz Lopez J, 2018, foo.castr: visualising the future AI workforce, Big Data Analytics, Vol:3, ISSN:2058-6345

Glaser VL, Fiss PC, Kennedy MT, 2016, Making snowflakes like stocks: stretching, bending, and positioning to make financial market analogies work in online advertising., Organization Science, Vol:27, ISSN:1047-7039, Pages:1029-1048

Lo JY-C, Kennedy MT, 2015, Approval in nanotechnology patents: micro and macro factors that affect reactions to category blending, Organization Science, Vol:26, ISSN:1047-7039, Pages:119-139

Kennedy MT, Fiss PC, 2013, An Ontological Turn in Categories Research: From Standards of Legitimacy to Evidence of Actuality, Journal of Management Studies, ISSN:1467-6486, Pages:n/a-n/a

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