Newswise — To determine the popularity, quality, and durability of a consumer product, economists and marketing experts have relied primarily on market-share data – the number of units sold during a certain period. Whoever sells the most is crowned the champ.
Professor Andrew Ching of the Johns Hopkins Carey Business School, an economist who studies the behavior of consumers and firms, wanted to dig deeper than the usual market numbers. He came up with the idea of examining the “inter-purchase” periods for products – that is, the amount of time between one purchase of a product and then the next purchase of the same item to replenish the supply.
By applying this metric to purchases of a frequently replaced item familiar to parents everywhere (children’s diapers), lead author Ching and two colleagues wrote in a paper for The Japanese Economic Review that they have developed a new, better way to reveal the most durable product in a particular sector of the consumer market.
Ching, who conducted the study with Professor Tulin Erdem of New York University and Professor Michael Keane of the University of New South Wales, discusses the paper in the following Q&A:
QUESTION: What is the key premise of the study?
ANDREW CHING: Most of the economics and marketing research that looks at consumer preferences takes those consumer choices and reverse-engineers them to uncover what product characteristics buyers prefer and to what extent they prefer them. This includes inferring product quality based on things like market share. But such inferences by researchers can be misleading, given that consumers do not always have complete information about products when they choose them. For instance, many consumers prefer national brands to a store brand because they think their quality is better. But some store brands’ quality could be just as good.
In this study, we propose using observed inter-purchase time (instead of market share) as another way to measure product quality. We argue that this method is more objective than using market share or consumer buying choice because the inter-purchase time primarily depends on product durability, and it is free from the caveat about consumers’ biased perceptions of quality due to their incomplete information.
You state that your paper is, to the best of your knowledge, the first to examine inter-purchase periods as a way of determining a product’s durability and popularity. How did you arrive at that method?
I arrived at it when I read some blogs by new parents. They talked about how some diapers did not hold very well, and that they needed to be changed more often, etc. So I thought: Wait a second, the length of replacement cycle – in other words, the inter-purchase time – can be used to infer product quality, and we can get the data from consumer purchase scanner data. (Many economists and marketing researchers are using this type of data.)
Why did you choose diapers for a study of product durability, when diapers are generally used once and then thrown away?
As you may imagine, this idea can be applied to many different products, like cars. Japanese car brands are well-known to have higher durability; they can keep running for 20 years or so. But other brands need to be replaced much more often. So why not study cars or other durable goods, like TVs? The problem is that the replacement cycle of products like these is still long (at least a few years). For any given individual using that kind of product, we wouldn’t be able to record too many observations.
On the other hand, diapers need to be replaced much more often. So even with just two years of data, we can observe a lot of repeated purchases per individual. Such a rich data set on inter-purchase time allows us to control for individual differences, which can be another threat in empirical research when we try to infer product quality more precisely.
In the study, how did you account for consumption rates, which probably vary among households using a product such as diapers?
Yes, varying consumption rates must be considered, as these can offer other explanations about why people use diapers differently. Roughly speaking, our model uses data based on durability and quantity purchased per household over a wide data window (say, two years), and assumes that the household uses up all the quantity purchased in this two-year window. That’s how we get a proxy for a household- specific consumption rate.
Were you surprised by any of your findings – for instance, the finding that store-brand diapers appeared more durable than Pampers, Huggies, and Luvs, the three leading national brands?
I did not have any expectation about what we would find. We actually found that Huggies is slightly more durable than Pampers, Luvs, and store brands. But the estimated durability for Pampers, Luvs, and store brands is very similar. I am not surprised to see store brands performed similar to some national brands.
I have done a lot of work on consumer choice between brand-name drugs and generic drugs, and the FDA has set very high standards for generic drugs. Some generic-drug makers are large and can handle the production technology very well. So objectively speaking, at least in the United States, we know that generic drug quality is at the same level of brand-name drugs. Yet, many people would still choose brand-name drugs, particularly when insurance covers it.
How might the study’s key takeaways be useful to consumers?
Recent reports in the news have said that diaper prices are going to go up, and the trend will likely continue. Based on our findings, I would suggest consumers (especially new parents) keep an open mind and give store brands a try. They may find that a store brand is as good as the national brands. The store brand could save them quite a bit of money.
Do you plan on building on this study in future research?
We are hoping to extend our work to other product categories and see how consumers’ perceptions of product qualities differ from the objective measures of durability obtained from the inter-purchase time. More importantly, we hope other researchers can use our method in their studies to gather evidence of whether there is incomplete information on the consumer side, and that could help them build a better consumer model.