Co-authored with Tobias Lieberum, Sebastian Schiffels and Sebastian Jost.
In this paper we examine how agile development principles (iterative sprints, autonomy) affect innovation performance. We find that frequent iterations help improve performance in complex tasks by increasing exploration behaviors. The main mechanism is slower learning under sequential (non-iterative) workflow. Read more
Co-authored with Maqbool Dada and Brett Hathaway.
Chatbot technology can help service firms reduce staffing needs and achieve cost savings. In this paper we use online experiments to examine how people respond to chatbots. We examine when and why chatbots are underutilized and propose a simple nudge to increase chatbot adoption. Read more
Co-authored with Kyle Hyndman and Anyan Qi.
In this research we study how entrepreneurs and investors divide equity. We use the Nash bargaining framework and test several predictions in the lab. We find that the number of investors can have either a positive or a negative effect on the ability of the entrepreneur to retain equity in their venture. Preferred Stock contracts, which are popular in practice, lead to more aggressive investor bargaining tactics. Read more
Co-authored with Jeffrey Sanchez-Burks, David Brophy, Thomas Jensen and Melanie Milovac.
In this report (commissioned by the Kauffman foundation) we look at how entrepreneurial accelerators and incubators organize their mentoring initiatives. We distill some of the best practices and discuss the differences between university and non-university accelerators, and the lessons learned for setting up such programs. Read more
Co-authored with Stephen Leider and Ozge Sahin.
In this paper we look at how people make dynamic (sequential) decisions. We examine decision-making in a range of dynamic problems and find, unsurprisingly, that most people are not ‘forward-looking optimizers’. Rather, decision rules depend on the type of environment: decision rules are static in stopping problems (Stop in round X), but are quite sophisticated in other dynamic problems. Read more
Co-authored with Kyle Hyndman and Andrew Davis.
Waiting is something we encounter daily, whether standing in line at a coffee shop, awaiting a ride-share pickup at the airport, or sitting in a doctor’s office. In this study, we examine how different aspects of waiting affect our preferences among service providers. Our findings reveal that people respond negatively to waits that are more uncertain, more skewed, or less well understood. Read more
Published in Management Science, 2018
This paper is about allocating development time between (creative) idea generation activities, and more production related execution activities. We find that developers benefit from firm deadlines early on in the creative process. Granting developers more autonomy leads to delays in idea inception and development. Read more
Recommended citation: Kagan Evgeny, Stephen Leider, Bill Lovejoy (2018). "Paper Ideation-Execution in Product Development: An Experimental Analysis." Management Science. 64(5). https://pubsonline.informs.org/doi/abs/10.1287/mnsc.2016.2709
Published in Management Science, 2020
This paper studies incentive design in startups, specifically how to split equity in a startup. We find that founders who choose to split equally invest little effort into the venture after the split. Thus, a preference for a contract type can be seen as a signal of being a good (or bad) collaborator. Delaying the equity split until some work is done helps remove some of the collaboration difficulties. Read more
Recommended citation: Kagan Evgeny, Stephen Leider, Bill Lovejoy (2020). "Equity Contracts and Incentive Design in Start-Up Teams." Management Science. 66(10). https://pubsonline.informs.org/doi/abs/10.1287/mnsc.2019.3439
Published in Operations Research, 2023
This paper studies incentives for service workers handling customer service requests. We find that workers are able to incorporate congestion into their decisions - that is, they spend more time with customers when congestion is low, and less time when congestion is high. However, workers struggle to incorporate different components of compensation scheme, such as rewards for successful resolution, and costs for transfers. Read more
Recommended citation: Brett Hathaway, Evgeny Kagan, Maqbool Dada (2023). "The Gatekeeper’s Dilemma: When Should I Transfer This Customer?"Operations Research. 71(3). https://pubsonline.informs.org/doi/abs/10.1287/opre.2021.2211
Published in Production and Operations Management, 2025
This paper develops a model of customer service request resolution in contact centers. This allows us to examine the broader question of strategic selection of an appropriate mix of service channels: live-agent-only, chatbot-only, or both. We show that the availability of chatbot technology may change request resolution policies with important implications for service quality and cost Read more
Recommended citation: Maqbool Dada, Brett Hathaway, Evgeny Kagan (2025). " Operational Strategies for Customer Service: A Gatekeeper Framework." Production and Operations Management. Forthcoming.
Undergraduate Course, University of Michigan, Ross School of Business, 2015
Operations Management studies the processes by which inputs of materials, labor, capital, and information are transformed into products and services which customers want and are willing to pay for. This course will provide students with the managerial tools needed to understand and articulate the impact of an organization’s business processes, and the ability to analyze and continuously improve these business processes to make things work better, faster and cheaper. Read more
Graduate Course, Johns Hopkins University, Carey Business School, 2018
This is a graduate-level course focusing on learning the basics of analytics (predictive, prescriptive) and applying those methods to real-world problems. The course is taught mainly using R and Excel Read more
Graduate Course, Johns Hopkins University, Carey Business School, 2020
Being a business leader in a data driven world requires the knowledge of both data-related (statistical) methods and of appropriate models to use that data. The Foundations of Business Analytics course focuses on the latter: it introduces students to quantitative (“analytical”) frameworks and techniques for decision making. At a high level, these techniques include optimization, risk modeling, and Monte Carlo simulation. For each methodology students are first exposed to the basic mechanics, and then apply the methodology to real world business problems using software. Read more