Letter From the Chair
Welcome to the Management Division of Columbia Business School! Our website offers a window into the teaching and research activities of the division.
We explore the forces that affect the performance of organizations by studying individual and interpersonal behavior, group interactions, organizational structure and strategic interactions. The insights are relevant for established and large firms to small and growing entrepreneurial ventures. The members of our division are scholars and practitioners that shed light on management questions from different disciplines that include psychology, strategy, sociology, political science, and economics.
The Management Division prepares leaders for the future of business based on our theoretical and empirical research at the scientific frontier. We publish cutting edge research and translate it into insights that are practical and tangible for business leaders of today and tomorrow.
Stephan Meier
James P. Gorman Professor of Business; Chair of Management Division
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Research
Privacy and the Value of Data
How does protecting the privacy of consumers affect the value of their personal data? We model an intermediary that uses consumers' data to influence the price set by a seller. When privacy is protected, consumers choose whether to disclose their data to the intermediary. When privacy is not protected, the intermediary can access consumers' data without their consent. We illustrate that protecting consumers' privacy has complex effects. It can increase the value of some consumers' data while decreasing that of others.
Proximity Bias: Motivated Effects of Spatial Distance on Probability Judgments
Welfare Consequences of Sustainable Finance
We model the welfare consequences of portfolio mandates that restrict investors to hold firms with net-zero carbon emissions. To qualify for these mandates, value-maximizing firms have to accumulate decarbonization capital. Qualification lowers a firm’s required rate of return by its decarbonization investments divided by Tobin’s q, i.e., the dividend yield shareholders forgo to address the global-warming externality.
The Value of Data Records
Many e-commerce platforms use buyers' personal data to intermediate their transactions with sellers. How much value do such intermediaries derive from the data record of each single individual? We characterize this value and find that one of its key components is a novel externality between records, which arises when the intermediary pools some records to withhold the information they contain. Ignoring this can significantly bias the evaluations of data records.
Thompson Sampling with Information Relaxation Penalties
We consider a finite-horizon multi-armed bandit (MAB) problem in a Bayesian setting, for which we propose an information relaxation sampling framework. With this framework, we define an intuitive family of control policies that include Thompson sampling (TS) and the Bayesian optimal policy as endpoints. Analogous to TS, which, at each decision epoch pulls an arm that is best with respect to the randomly sampled parameters, our algorithms sample entire future reward realizations and take the corresponding best action.
