Putting research in the driver's seat

March 7, 2022

College of Business Assistant Professor Wayne Fu鈥檚 research has looked into car warranties for a decade. His discoveries provide manufacturers with important data for their decision-making processes 鈥 and Fu shares if he, as a consumer, would buy an extended warranty.

COB faculty Wayne Fu researches vehicle warranties and recently published his findings
Graphic by Violet Dashi

Some car warranties are three-year/36,000 miles. Others are five-year/60,000 miles. There are even a few that go as high as 10-year/100,000 miles.

Working in the automotive service industry prior to his academic career, Decision Sciences Assistant Professor Wayne Fu wondered why.

鈥淭he first thing I鈥檇 do is check the warranty to see what was covered 鈥 because of how warranties are structured, every transaction was different. It could get a bit complicated, almost like they were testing our intelligence,鈥 said the College of Business faculty member. 鈥淚 was curious why there wasn鈥檛 a standard coverage across the industry. Did it have to do with quality, psychology or something else? And if companies offered longer warranties, would it translate to more sales?鈥

Assistant Professor Wayne Fu
Assistant Professor Wayne Fu

Today 鈥 after a decade of research 鈥 he has some answers: And those findings were  which is on the Financial Times top 50 journal list.

Fu鈥檚 research shows longer warranties do play a role in purchasing, but only for vehicles that are rated with very good or very bad reliability. Those ranked in middle-of-the-road don鈥檛 benefit from extending their warranty length 鈥 showing a 鈥淯鈥 shape when charting the research. So why is this? Fu said research shows it鈥檚 because of the used/secondary car market.

The industry has taken notice.

 Competitive Quality Benchmarking Vice President Renee Stephens, an expert in the automotive warranty bench-marking practice who previously has worked in automotive quality management for J.D. Power and General Motors, said Fu鈥檚 work adds important data to decision-making processes.

We Predict's Renee Stephens
We Predict's Renee Stephens

鈥淢anufacturers believe that offering a longer warranty period will give consumers more confidence in their products and allow them to sell more. But Dr. Fu鈥檚 research shows that is not always the case,鈥 she said. 鈥淭here have been several hypotheses on the impacts to manufacturers when changing warranty policies, but, until Dr. Fu鈥檚 research, very few empirical studies to support the hypotheses.鈥

When Fu started this research in 2012, he discovered the lack of available information. But instead of curbing his enthusiasm, he decided to pave the road for this new area of research.

Fu worked with collaborative partners Professor Atalay Atasu at INSEAD Europe and Associate Professor Necati Tereyagoglu at the University of South Carolina. Stephens, an executive at J.D. Power during that time, also assisted Fu with data.

Fu gathered information from J.D. Power regarding vehicle make and models on the primary market. He looked at the quality assessment and compared it to the offered warranty. He also sorted through several years of U.S. Labor and Bureau survey data to track vehicles bought and sold on the primary and secondary markets, while also factoring in vehicles that were sold for parts or junked.

Following the data, Fu created a mathematical model that helps evaluate current warranty prediction. The model takes the automotive secondary market into consideration since it seems to be a factor when it comes to the U.S. vehicle market 鈥 the used vehicle industry is about three to five times the size of the primary market.

Fu said this model works because of the used car market鈥檚 interference from consumer incentive programs like trading up or trading in programs. And it reflects the data collected very well.  

Fu said producers with sufficiently low product reliability can use secondary markets to jointly avoid vehicle cannibalization 鈥 that鈥檚 the reduction of sales from its own products 鈥 and high warranty fulfillment costs associated with long warranties for low-reliability products.

鈥淢anufacturers use the past to predict the future. But, at the same time, they should realize that the secondary market changes all the time in ways that are often unexpected, and will affect their decisions鈥 he said, referencing the . 鈥淭he model we created considers what may happen in the secondary market and incorporates that.鈥

He said the unexpected makes the automotive industry a bit exciting because there is always something new to learn and discover. And he鈥檚 seen some interesting changes after he began his research. For example, Kia 鈥 which ranked among the lowest quality in 2012, but had a longer warranty at 10-year/100,000 miles 鈥 is  in the most recent J.D. Power data. 

鈥淭hey pretty much went from worst to first. They had low quality, so they offered a longer warranty for buyer peace of mind,鈥 he said. 鈥淲hen more people bought, Kia invested in improving their quality to mitigate their risk because they have such a long warranty. It was interesting to see a vehicle that was assessed as lower quality a decade ago be among luxury cars today.鈥

Fu鈥檚 work focuses on the manufacturer side of warranties, but with the information gathered, what does the data show when it comes to warranties from the consumers point of view?

鈥淢anufacturers have evaluated the risk. They want to improve their reputation and maintain their costs,鈥 he said. 鈥淚 wouldn鈥檛 buy an extended warranty, but you should always go with the warranty coverage you are most comfortable with.鈥

Fu said the past 10 years have taught him and his collaborators a lot when it comes to warranty lengths and secondary markets. With electronic and better-connected vehicles, there are even more areas to explore. For example, Stephens鈥 company We Predict has been investigating service and warranty cost information into components and their suppliers. 

In the future, as new data become available, Fu would like to look more closely at these areas because research helps put decision makers 鈥 both manufacturers and consumers 鈥 in the driver鈥檚 seat. 

Article by Sarah Tuxbury.