Serguei Netessine

Are Consumers Strategic? Structural Estimation from the Air-Travel Industry

Consumers often consider delaying a purchase strategically, anticipating that prices might decrease. Combining two unique data sources from the air-travel industry posted fare data and booking data, we use a structural model to estimate the fraction of strategic consumers in the population, assuming different levels of sophistication in consumers perception of future prices: perfect foresight and weak-and strong-form rational expectations. We find that 5.2% to 19.2% of the population is strategic across markets, measured by the first and third quartiles. Our intermarket analysis indicates that shorter trips with more attractive outside options are populated with more strategic consumers. Using a nonparametric approach, we further find that most strategic consumers arrive either at the beginning of the booking horizon or close to departure. Finally, our counterfactual analysis shows that, contrary to conventional wisdom, the presence of strategic consumers does not necessarily hurt revenues. Rather, the impact varies by market. Commitment to a nondecreasing pricing strategy is more likely to benefit business markets than leisure markets, or it could even hurt leisure markets. Intermarket analysis shows that city pairs with lower Internet penetration, higher average price, and shorter distances tend to benefit more from such commitment as well. n nThis paper was accepted by Yossi Aviv, operations management.

Price to Compete … with Many: How to Identify Price Competition in High-Dimensional Space

The authors study price competition in markets with a large number (in magnitude of hundreds or thousands) of potential competitors, using the hotel industry as a test bed.The authors address two methodological challenges: simultaneity bias and high dimensionality. Simultaneity bias arises from joint determination of prices in competitive markets.The authors propose a new instrumental variable approach to address simultaneity bias in high dimensions. The novelty of the idea is to exploit online search and clickstream data to uncover demand shocks at a granular level, with sufficient variations both over time and across competitors in order to obtain valid instruments at a large scale.The authors then develop a methodology to identify relevant competitors in high dimensions combining the instrumental variable approach with high dimensional l-1 norm regularization.The authors apply this data-driven approach to study the patterns of hotel price competition in the New York City market. The authors find that engagement in competition-based revenue management is prevalent across branded and non-branded hotels and across all quality tiers. When choosing whose prices to follow, branded hotels are more confined by quality boundaries but less by geographical boundaries, as compared to independent hotels. Also, budget and luxury hotels are more confined by quality boundaries but less by geographical boundaries, as compared to economy and up-scale hotels.Lastly, the authors show that the competitive responses identified through our method can help hoteliers proactively manage their prices and promotions. The authors find that accounting for competitive responses will lead to more accurate price/promotions decisions (avoiding up to 11-20% of pricing errors and 11-23% missed growth targets for certain hotels and chains).

Philanthropic Campaigns and Customer Behavior: Field Experiments on an Online Taxi Booking Platform

Companies commonly use philanthropic campaigns to attract and retain customers. Such campaigns often take the form of charity-linked promotions, where a company donates money to a cause when a customer makes a purchase. However, customer-related effects of such promotions remain under-studied, an issue this study investigates using field experiments in an online taxi booking company.Customers were randomly assigned to receive either a charity-linked or discount-based promotion. Take-up rates for charity-linked promotions were smaller than for discount-based promotions, and also less sensitive to the monetary amount. This is consistent with customer decisions being driven by a “warm glow” of giving and not just their extent of social impact.Although promotion take-up did represent new bookings rather than substitution of non-promotional bookings, there is little evidence of an increase in subsequent purchase frequency.This result raises questions regarding the common practice of online platforms devoting significant investor funds for short-term promotions.

Selling Off-Grid Light to Liquidity Constrained Consumers

A large proportion of the worlds population has no access to electricity and so relies on noxious kerosene for their lighting needs. Solar-based solutions require a large upfront investment and are often unaffordable in this market owing to consumers tight liquidity constraints. As an alternative, there are business models relying on rechargeable light bulbs that are sold at a subsidized price (which renders them affordable) and require regular micropayments for recharges (which eases liquidity constraints). These bulbs provide a cheaper and healthier light source than kerosene, yet their adoption is lower than expected and some consumers continue to use kerosene. The authors propose a stylized consumer behavior model to explain these observations. In addition to monetary cost incurred while using a particular light source, our model accounts for the inconvenience cost (due to repeated travel to the purchase center) and blackout cost (due to liquidity constraints) associated with that source.Although kerosene lighting is more expensive than bulbs, consumers who face either high inconvenience costs or high blackout costs prefer kerosene to bulbs because the formers flexibility, with regard to quantity, helps reduce whichever cost is dominating.At the firm level, there is an optimal bulb capacity that trades off demand for rechargeable bulbs against recharge revenue from consumers; furthermore, firm can reverse the preferences of kerosene consumers by increasing its products flexibility (e.g., by allowing partial recharges).Although strategies - such as price discounts and mobile micropayments - based on alleviating liquidity constraints are not in themselves sufficient to ensure higher adoption rates, increased bulb use becomes more likely when they are combined with strategies to reduce consumers inconvenience.Problem Definition: A large proportion of the worlds population has no access to electricity and so relies on noxious kerosene for their lighting needs. Solar-based solutions require a large upfront investment and are often unaffordable in this market owing to consumers tight liquidity constraints. As an alternative, there are business models relying on rechargeable light bulbs that are sold at a subsidized price (which renders them affordable) and require regular micropayments for recharges (which eases liquidity constraints). These bulbs provide a cheaper and healthier light source than kerosene, yet their adoption is lower than expected and some consumers continue to use kerosene. This paper explores the potential drivers of such preferences and proposes strategies to alter them, thereby benefiting firms, consumers, and the environment. Academic Relevance: Unlike most of the existing operations management literature which focuses on the problems in developed economies, our paper studies a problem specific to the poor population. Our novel modeling approach, which incorporates several operational features of the impoverished regions, could also serve as a template for other potential modeling attempts in similar settings. Methodology: We propose a stylized consumer behavior model that accounts for { in addition to the monetary cost incurred while using a particular light source { the inconvenience cost (due to repeated travel to the purchase center) and blackout cost (due to liquidity constraints) associated with that source, to explain the consumer preference for kerosene and to recommend strategies that could mitigate that preference. Results: Although kerosene lighting is more expensive than bulbs, consumers who face either high inconvenience costs or high blackout costs prefer kerosene to bulbs because the formers flexibility, with regard to quantity, helps reduce whichever cost is dominating. At the firm level, there is an optimal bulb capacity and recharge price pair that maximizes the firms revenue; furthermore, firm can reverse the preferences of kerosene consumers by increasing the flexibility of the bulbs (e.g., by allowing partial recharges). Although strategies { such as price discounts and mobile micropayments { based on alleviating liquidity constraints are not in themselves sufficient to ensure higher adoption rates, increased bulb use becomes more likely when they are combined with strategies to reduce consumers inconvenience. Managerial Implications: Our paper sheds light on the structure of the market in which firms operate by identifying the characteristics of the market segments that prefer kerosene. It also helps the firms make better decisions by evaluating the efficacy of several strategies in terms of increasing the adoption of bulbs.

Setting Retail Staffing Levels: A Methodology Validated with Implementation

Problem definition: How should retail staffing levels be set? While cost of labor is well understood, the revenue implications of having the right staffing level are hard to estimate. Moreover, the...

When Is the Root of All Evil Not Money? The Impact of Load on Operational Risk at a Commercial Bank

Operational risk has been among the three most significant types of risks in the financial services industry, and its management is mandated by Basel II regulations. To inform better labor decisions, this paper studies how workload affects banks’ operational risk event occurrence. To achieve this goal, we use a unique data set from a commercial bank in China that contains 1,441 operational risk events over 16 months. We find that workload has a U-shaped impact on operational risk error rate. More specifically, the error rate of operational risk events decreases first, as workload increases, and then increases. Furthermore, when workload is low, employees tend to make performance-seeking risks; however, when workload is high, employees tend to exhibit quality degradation due to cognitive multitasking. Based on the causal relationship between workload and operational risk events from the empirical analysis, we discuss staffing policies among branches aimed at reducing operational risk losses. We find that employing a flexible staffing rule can significantly reduce the number of operational risk events by more than 3% under different scenarios. In addition, this significant performance improvement can be achieved by nadding even a little bit of flexibility to the process by allowing employees to either switch their business lines in the same branch or switch branches within the same business lines on a quarterly basis.

At Your Service on the Table: Impact of Tabletop Technology on Restaurant Performance

Some industries, such as healthcare and financial services, have reported significant productivity gains from introduction of new technologies. However, other more traditional, labor-intensive indu...