The Institute for Business Innovation supports research activities in innovation, entrepreneurship, business analytics, dynamic capabilities, intellectual capital, competitive strategy, and related fields. The Institute provides this support by disseminating research results, organizing academic conferences and seminars, hosting visiting scholars to pursue joint work with our faculty, administering fellowships to support graduate students, and facilitating the process of grant applications to fund future research. The Institute also publishes the academic journal Industrial and Corporate Change (with Oxford University Press).

Corporate Innovation

The Garwood Center for Corporate Innovation generates and shares cutting-edge research on corporate and open innovation, a term coined by Henry Chesbrough. Open Innovation is the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation.

Business Analytics

The Fisher Center for Business Analytics supports world-class research that applies analytics to business. We address business problems by using empirical methods to analyze data of non-trivial scale, construct novel explanatory variables using analytics (e.g. text mining), and apply analytics to integrate previously disparate data sets in novel ways.

Intellectual Property

The Tusher Initiative for the Management of Intellectual Capital engages in rigorous quantitative and qualitative research on issues surrounding intangible assets and firm competitiveness. The intangible assets under study include intellectual property, know how, relational capital, brands, and corporate culture.

Health Analytics Lab

The Health Analytics Lab (HAL) brings together numerous research activities at Berkeley Haas focused on healthcare-related industries, from drug discovery to service delivery to insurance markets. Health care research at Berkeley Haas is bound by the common theme of applying theoretical understandings from the social sciences and cutting-edge statistical and computational methods to very large-scale micro data.

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