mathematics - Publications - Faculty & Research

Contagion models are ubiquitous in epidemiology, social sciences, engineering, and management. This paper formulates a prescriptive contagion analytics model where a decision maker allocates shared resources across multiple segments of a population, each governed by... View Details

Keywords: COVID-19; Mathematical Methods

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Competitive Strategy

By: Michael E. Porter

Porter is engaged in a major new body of work on the theoretical foundations of competitive positioning and the underpinnings of sustainable competitive advantage. This research highlights the distinction between positioning and operational effectiveness; the... View Details

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By: Ethan C. Rouen

Relying on empirical archival methodologies—as well as techniques in data science—to develop and structure new sources of data by which to approach questions of looming disclosure changes, Professor Rouen has focused on one of the Securities and Exchange Commission’s... View Details

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By: Kris Johnson Ferreira

Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details

Keywords: E-commerce; Analytics; Revenue Management; Pricing; Assortment Planning; Field Experiments; Operations; Supply Chain; Supply Chain Management; Retail Industry

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Reputation Burning: Analyzing the Impact of Brand Sponsorship on Social Influencers

By: Mengjie Cheng and Shunyuan Zhang

The growth of the influencer marketing industry warrants an empirical examination of the effect of posting sponsored videos on influencers' reputations. We collected a novel dataset of user-generated YouTube videos created by prominent English-speaking influencers in... View Details

Keywords: Reputation; Mathematical Methods; Marketing Reference Programs; Social Media; Brands and Branding

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Slowly Varying Regression Under Sparsity

By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami

We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem... View Details

Keywords: Mathematical Methods; Analytics and Data Science