Pricing with Big Data

Project Information

BIG

Grant agreement ID: 892142

DOI

10.3030/892142

Project closed

EC signature date 6 May 2020

Start date 2 November 2020

End date 1 November 2022

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 172 932,48

EU contribution

€ 172 932,48

Coordinated by

UNIVERSIDAD DE NAVARRA
Spain

Periodic Reporting for period 1 - BIG (Pricing with Big Data)

Reporting period: 2020-11-02 to 2022-11-01

Summary of the context and overall objectives of the project

This EU project studied the following five areas: (a) novel pricing strategies in online marketplaces, in particular groceries and retail; (b) barriers, frictions, moderators of price dispersion in the online and the offline channels; (c) consumers’ reactions to price formats, price cues, and dynamic price changes; (d) stores and consumers reactions to external shocks; and (e) methodological tools to analyze empirical big datasets. These areas were addressed through four research papers.

Pricing in Online Groceries: This paper studied price dispersion in online and offline groceries. The study reports substantial price dispersion in three dimensions (across time, across sellers, and across locations), compared to offline supermarkets. An important implication of the study is that the usage of algorithms (automation of pricing decisions) in the online channel amplify price discrimination. Algorithms do so at those three dimensions.

Resilience of Retail Stores to External Shocks: This research project studied how fashion retail stores (supply-side) and shoppers (demand-side) are affected by an external shock. The COVID-19 is used as an external shock. Empirically, high-frequency inventory records were collected online for thousands of stores from twenty countries to construct a measure of offline sales for each store. The study reports heterogeneity across stores and sheds light on the store features that explain heterogeneity. For example, proximity to touristic attractions, large stores, locations inside shopping malls, amplify the adverse effect of the COVID-19. Moreover, informs policymakers about the timing and locations of stores that are most poorly performing and, therefore, might require more immediate reactivation packages.

Price Presentation and Shoppers’ Behavior: This research project studies how consumers react to price formats and the sequential timing of the price presentation. For example, when the price discovery is pushed to later stages of the funnel, that delay modifies’ customers perception of the price distribution and the price salience attribute in the decision-making process, and therefore can increase or decrease the probability of making a transaction. This research is embedded in a recent body of literature studying boundedly rational consumers and their interaction with price “frames”.

Dynamic Prices in Restaurants: This project studies dynamic discounts in restaurants in the context of an online marketplace that brings together restaurants and customers. It shows how consumers can strategically redeem discounts across restaurants, and how restaurants strategically decide those discounts to incorporate competitive and demand effects. This research is important managerially, because it sheds light on the business’ strategy, but also more broadly, because the restaurant is an industry characterized by many frictions (e.g. “menu costs”). Therefore, advances to reduce frictions can significantly enhance the restaurant industry going forward.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

To study the research objectives outlined above, this project had to: (a) collect online data from online retailers, (b) analyze scanner offline datasets, (c) run online surveys, and (d) collaborate with a field company. An appealing aspect of the research project as a whole is its combination of various datasets (online, offline, experimental), to study important research questions in economics and marketing. Several scientific achievements have been made during the fellowship. We separate the results by paper.
Pricing in Online Groceries: One important scientific contribution is to show that price algorithms exacerbate price discrimination. Algorithms amplify price dispersion across locations (same retailer, same product, across different locations). Then, algorithms also amplify price dispersion across time (same chain, same location, same product), and do so through frequent price changes. And finally, the paper reports great price differences across sellers (same product, same location, across sellers).

Resilience of Retail Stores to External Shocks: A scientific accomplishment is to characterize what makes a store resilient to shocks. Among the discoveries, there is the value of rural stores, away from touristic spots, small stores, away from shopping malls. Interestingly, these are not the typical stores that (pre-COVID-19) one might have thought as the best performing. Yet, COVID-19 appears to have changed that. These features moderate the effect of the COVID-19 and experience a faster recovery. This is the first paper to show store heterogeneity to external shocks for thousands of stores in 20 countries (see figure attached).

Price Presentation and Shoppers’ Behavior: The key contribution is to show economically meaningful effects when the price format interacts with the timing of the price discovery. Prior academic research has looked at the role of search costs, obfuscation, barriers to learn competitor prices, frames to confuse customers with boundedly rational consumers. A contribution is to show the role of when the price discovery takes place in the purchase process. Postponing price discovery can affect price uncertainty and price salience, and thereby modify the shopping decision.

Dynamic Prices in Restaurants: The key scientific contribution is to measure the economic value of dynamic discounts in the restaurant industry, in the context of an online marketplace with heterogeneous consumers and many sellers (restaurants) that compete for those customers. The contribution is also to provide evidence of pricing tools that might reduce pricing frictions in the restaurant industry.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The researcher expects to publish four research projects at top-tier scientific magazines. Some are under review and close to completion, while others have not yet been submitted. These papers would not have been possible without the EU fellowship.

All four topics are important for the policy agenda as well as for society at large. Pricing is a key concern in economics because it is consequential for business owners, policymakers, and consumers. As society, we care how consumers respond to price dispersion, what price algorithms are doing with respect to price discrimination, and how price formats that affect search costs might influence decisions to purchase. One the research projects sheds light on the role of price algorithms in exacerbating price discrimination. Similarly, policymakers and households and business owners are interested in knowing what drivers affect the performance of brick-and-mortar stores to external shocks. One research project provides a data-based analysis of store resilience to COVID-19. This evidence is critical because it can inform in real-time and with a great geographical precision which types of stores are likely to be less resilient to shocks, and therefore more likely to need assistance and special programs to prevent the business from closing.

figure-summary-big.jpg