Bacon causes cancer: Do consumers care?

In October 2015, the International Agency for Research on Cancer (IARC) released a report classifying processed meat as a type 1 carcinogen. The report prompted headlines and attracted immediate public attention, but the economic impacts remain unknown. In this paper, we investigate the impacts of the IARC report on selected processed meat prices and purchases using retail scanner data from US grocery stores. We compare changes in prices and sales of selected processed meat products to a constructed synthetic control group (using a convex combination of nonmeat food products). We find a significant decrease in bacon prices in the wake of the IARC report release, but we find no evidence of a sales reduction. We find no significant changes in price and sales for ham and sausage. The pattern of price and quantity changes are consistent with downward shifts in demand and outward shifts in supply for bacon and sausage following the release of the IARC report.

The Effects of the COVID-19 Pandemic on the Mass Market Retailing of Wine in Italy

The purpose of this study was to provide a detailed framework of wine purchases in supermarkets during the COVID-19 pandemic. The unexpected diffusion of the virus and the restrictions imposed in Italy to prevent its spread have significantly affected the food purchasing habits of consumers. By analyzing the scanner data of the wine sales in the Italian mass market retail channel, this study was intended to show whether and how the dynamics triggered by the pandemic have modified the overall value and type of wine purchases, focusing on prices, formats, and promotional sales. In particular, this study explores sales in two separate periods, namely March–April (the “lockdown”, with general compulsory closing and severe restrictions) and June–July 2020 (the “post-lockdown”, in which some limitations were no longer effective). The analysis of wine sales during lockdown and post-lockdown and the study of the variations compared to the sales of the previous years showed some significant changes in purchase behavior. The results could provide managers, researchers, and policy makers with extensive insights into the purchasing patterns of consumers during this unprecedented time and reveal trends that may characterize the structure of the future wine demand.

The Effect of Ballot Characteristics on the Likelihood of Voting Errors

In the United States, people are asked to vote on a myriad of candidates, offices, and ballot questions. The result is lengthy ballots that are time intensive and complicated to fill out. In this paper, we utilize a new analytical technique harnessing ballot scanner data from a statewide midterm election to estimate the effects of ballot complexity on voting errors. We find that increases in ballot length, increases in the number of local ballot questions, and increases in the number of candidates listed for single offices significantly increase the odds of encountering ballot marking and scanning errors. Our findings indicate that ballots’ characteristics can help election administrators make Election Day planning and resource allocation decisions that decrease ballot errors and associated wait times to vote while increasing the reliability of election results and voter confidence in the electoral process.

The effect of competition on product removal

The relationship between innovation and competition has been vastly studied over the past fifty years. However, one piece of the puzzle that has not been studied in detail is how in certain industries competition has an effect in the number of products that are removed from the market. That is why in this paper, I use scanner data to analyze the effect of competition on product removal. In particular, I track sales in the beer industry across a set of 1107 over a period of four years. Following previous studies, I use the merger between SABMiller and Molson Coors as an unexpected change in the industry to estimate future market concentration. I find that there is a negative relationship between removal and concentration. Therefore, retailers decide to remove products from their shelves in a faster way when the market is more competitive to open the gates for a more dynamic assortment.

Going healthy: how product characteristics influence the sales impact of front-of-pack health symbols

Manufacturers increasingly adopt health symbols, which translate overall product healthiness into a single symbol, to communicate about the overall healthiness of their grocery products. This study examines how the performance implications of adding a front-of-pack health symbol to a product vary across products. We study the sales impact of a government-supported health symbol program in 29 packaged categories, using over four years of scanner data. The results indicate that health symbols are most impactful when they positively disconfirm pre-existing beliefs that a product is not among the healthiest products within the category. More specifically, we find that health symbols are more effective for (i) products with a front-of-pack taste claim, (ii) lower priced products, and (iii) private label products. Furthermore, these results are more pronounced in healthier categories than in unhealthier categories. Our findings imply that health symbols can help overcome lay beliefs among consumers regarding a product’s overall healthiness. As such, adding a health symbol provides easy-to-process information about product healthiness for the consumer and can increase product sales for the manufacturer.

Investigating Undercurrents of Stationarity and Growth With Long-Term Panel Data

There have been frequent calls in the literature for a more comprehensive understanding of marketing impact on long-term firm performance. Retail scanner data has been the principal source of empirical evidence in this strategic domain, but it cannot explain the behavioural shifts that underpin the sales dynamics it reports. With the availability of far larger and extended household panels, it is now possible to observe the effects of accumulating penetration on brand and category buying over many years. This type of data nevertheless presents theoretical and methodological challenges to researchers. In this article, we discuss an approach to extending established marketing theory to long-run repeat buying and then outline the inherent constraints of long-term panels. We illustrate these challenges using one-, five- and 10-year panel datasets and present a research agenda to progress explanatory theories of long-run brand building and category growth in this new but so far mostly untapped resource.