Ruslan Momot


PhD Candidate at INSEAD, Technology and Operations Management Department

I am on the academic job market of 2017/2018.

  1. CV
  2. Research
  3. Teaching
My primary research interests lie in the area of social operations and information management. I explore firm’s operational decision making and customer individual and collective behavior in the presence of social interactions.

Refereed Publications/Articles under Review

The Use and Value of Social Network Information in Selective Selling of Exclusive Products - - [SSRN Link]

We consider the use and value of social network information in selectively selling goods and services whose value derives from exclusive ownership among network connections or friends. Our stylized model accommodates customers who are heterogeneous in their number of friends (degree) and their proclivity for social comparisons (conspicuity). Firms with information on either (or both) of these characteristics can use it to make a product selectively available and increase their profits by better managing the exclusivity-sales trade-off. We find that the firm’s best targets are high-conspicuity customers within intermediate-degree segments – in contrast with the practice of targeting high degree customers. We also find that information about degree is more valuable than information about conspicuity. Surprisingly, strategies informed only by degree perform no worse than those informed by degree and conspicuity both, yet the opposite is not true. Customer self-selection is a perfect substitute for unavailable information on conspicuity, but there is no such recourse when degree information is unavailable. Examining alternate settings (conformance social comparisons, functional value heterogeneity) suggests that there are two canonical categories of social information– less valuable information on characteristics where the firm’s preferred customers are also the most interested customers and more valuable information on characteristics where they are not.

Strategic Investment in Protection in Networked Systems - - [Network Science Link] - [Presentation at WINE 2015]

  • Joint with Matt Leduc, published at Network Science, 2017
  • What are incentives of the individuals (or firms) in a generic networked environment (e.g. social platform, supply chain) to invest in costly protection against both intrinsic (e.g. direct hacker attack, natural disaster) and networked (e.g. leakage of one’s sensitive information that exposes his/her social connections, cascading disruptions) risk?

We study the incentives that agents have to invest in costly protection against cascading failures in networked systems. Applications include vaccination, computer security and airport security. Agents are connected through a network and can fail either intrinsically or as a result of the failure of a subset of their neighbors. We characterize the equilibrium based on an agent’s failure probability and derive conditions under which equilibrium strategies are monotone in degree (i.e. in how connected an agent is on the network). We show that different kinds of applications (e.g. vaccination, airport security) lead to very different equilibrium patterns of investments in protection, with important welfare and risk implications. Our equilibrium concept is flexible enough to allow for comparative statics in terms of network properties and we show that it is also robust to the introduction of global externalities (e.g. price feedback, congestion).

Work in Progress

Inventory Management for 1% Products -

  • Joint with Elena Belavina, work in progress (preliminary draft is available upon request), 2017
  • What is optimal long-term inventory policy when selling products to customers engaged in social comparisons?

Sociological trends have led to consumer's increasing willingness to purchase goods whose value lies partly in the exclusivity of their ownership. Firms selling these goods face a trade-off--while producing more allows for extracting more revenues, it also may compromise the product's reputation for exclusivity. In this study, we develop a dynamic game-theoretic model of reputations--a repeated game with long-lived, short-lived players, incomplete information, adverse selection, Bayesian updating of reputations and strategic memory. Our findings suggest a radical departure from the recommendations of the existing literature. Unlike the over-production equilibrium that is widely touted in the existing literature, our more realistic dynamic model suggests that in equilibrium the firm follows a non-stationary cyclic strategy that alternates scarcity phases with the overproduction phases. While the former is used as an exclusivity reputation building mechanism, the latter represents a reputation exploitation phase.

Nudging Flexible Workforce: Empirical Evidence From Online Cleaning Services Platform -

  • Joint with Ekaterina Astashkina and Marat Salikhov, work in progress (results are available upon request), 2017
  • What is the right personalized assortment of tasks that hybrid platforms (that allow for partial decentralization) should offer to its contractors?

This study focuses on platforms that facilitate matching of heterogeneous customers (tasks) with heterogeneous contractors. Centralized platforms (e.g., Uber) rigidly assign contractors to customers, while decentralized platforms (e.g., TaskRabbit) let contractors choose tasks they prefer. What is the right personalized assortment of tasks that hybrid platforms should offer to its contractors? We build an econometric model of contractors’ choice, which we estimate on a proprietary dataset of the cleaning platform (similar to HomeJoy, Handy). We then formulate platform’s online optimization problem of assortment personalization, and identify policies that achieve near-optimal performance.

Endogenous Privacy in Social Networks

  • Joint with Elena Belavina and Karan Girotra, work in progress, 2017
  • How do decisions of customers whether to reveal private social information or not, influence operational decisions and performance of the firms?

Locality, Caste and Social Media: Comparing Peer-Effects in Diffusion of Fashion Trends