Neha Sharma

Assistant Professor of Operations, Information and Decisions

Contact Information

Primary Email:
nehash@wharton.upenn.edu

office Address:
3730 Walnut Street
550 Jon M. Huntsman Hall
Philadelphia, PA 19104

Research Interests: Online Marketplaces, Question & Answer Communities, Service Operations, Urban Mobility

Links: CV

Research

Neha Sharma, Sumanta Singha, Milind Sohoni, Achal Bassamboo, List now or Later? An equilibrium analysis of advance-booking platforms.
Neha Sharma, Gad Allon, Achal Bassamboo, Structuring Online Communities. Abstract
Online Question and Answer communities were started to supplement customer support services. In contrast to conventional customer support, users in online communities can post questions, and other users with more experience or knowledge can answer these questions. Generally, questions answered get rewards and visibility in the community, while the askers gain knowledge if their questions get answered. We study how users decide to join, leave, and participate in these communities. We link the user participation decisions to the underlying network structure of the community. Finally, we explore the levers a community designer can use to balance user participation level and the community’s efficiency in providing answers to users’ questions. We model the community as a multistage stochastic game where all the users have different skill levels. We find the stationary equilibrium of this game and theoretically show that only a core-periphery network structure can emerge in such communities. This network structure has been empirically observed in most online communities. Furthermore, we find that increasing the cost of asking questions in the community improves the proportion of askers that get answers to their questions. This results in higher user satisfaction. However, a higher asking cost lowers the participation level in the community. This trade-off between participation and community efficiency results in non-monotonicity in the number of users in the community with the participation cost. The paper explores the cost of asking a question as a lever that can be used by communities to control the number and knowledge type of users in the community. The communities typically operationalize higher asking costs by either directly penalizing question asking activity or setting up stricter guidelines for questions to be answered. We find that increasing the cost of asking is not always bad for the community. In fact, a higher asking cost improves user satisfaction which can lead to an increase in the number of users in the community despite higher asking cost. We also discuss how the existence of low knowledge users in the community (and not necessarily the high knowledge users) is essential to the survival of such communities.
Neha Sharma, Sripad Devalkar, Milind Sohoni (2020), Payment for Results: Funding Non-Profit Operations, . Abstract
Payment for results (PfR) funding approach, where donors reimburse the non-profit organization (NPO) based on outcomes, is being increasingly adopted in the non-profit sector. However, there is also concern expressed by many voluntary organizations that such a funding approach puts an undue financial burden on small NPOs and could actually be detrimental to social welfare. In this study, we build a theoretical framework to analyze PfR funding mechanisms. We use a sequential game to model the interaction between the donor and the NPO, with the donor as the first mover. This model captures how PfR funding is typically implemented in practice using social impact bonds (SIB), wherein social investors provide the upfront funding needed by the NPO to implement the project. The donor provides funding, based on the actual benefit delivered, at the end of the project and the investors are paid back using these funds. We find that higher targets set by the donor do not necessarily translate to higher expected utility or expected benefit delivered under PfR. When comparing the performance of PfR and traditional funding (TF) mechanisms, we find that the donor typically has a higher expected utility under the PfR mechanism when the probability of a negative outcome shock is either high or low, and is better off using the TF approach otherwise. When the donor’s opportunity cost of funding the project is high, the donor is better off using a PfR mechanism when her belief about the NPO having low efficiency is sufficiently high. Interestingly, we find that for a large range of parameter values there is a mismatch between the approach that gives a higher expected utility to the donor and the approach that maximizes the expected social benefit delivered. Our model and analysis suggest that the optimal funding approach, and the optimal target set under PfR, depend on the NPO’s financing cost from social investors and project outcome uncertainty.

Teaching

Past Courses

OIDD2200 - Operations Management Analytic
This course introduces basic concepts of operations management and application of the same in business practice today. We will examine the theoretical foundations of operations management and how these principles or models can be employed in both tactical and strategic decision making. Topics covered in detail are forecasting techniques, planning under deterministic and uncertain demand, operations planning and scheduling, queuing theory, service operations management, newsvendor models, risk pooling strategies in firms, capacity and revenue management, and supply chain coordination. We will conclude by discussing how supply chains evolve under technological change.