UA Study: Strict Return Policies Can Cost Retailers
Attempting to reduce product-return costs, retail companies have clamped down on return policies.
But, paradoxically, shrinking the window of time in which returns can be made results in more returns, according to a new paper co-authored by University of Arizona assistant professor of marketing Narayan Janakiraman and professor of management Lisa OrdÃ³Ã±ez published in the Journal of Consumer Psychology.
Existing research focuses on developing models to determine when policies should be lenient and when they should be restrictive.
In their paper, Janakiraman and OrdÃ³Ã±ez take a behavioral approach to determine how return deadlines and required effort influence a consumer's decision to return or keep items. They designed a series of live experiments involving student returns to the UA BookStores to test these interactions.
"We show that individuals are more likely to return products when deadlines are shorter and effort requirements are lower," Janakiraman said. "There are fewer returns when deadlines are longer or when effort requirements are increased."
The researchers believe this is explained by the consumers' reluctance to apply effort, both physical and mental, to the process of returning products.
"We also show a reversal of this effect, where individuals are more sensitive to return effort under longer rather than under shorter deadlines when the deadlines are framed as time between planned stores visits," Janakiraman said.
The paper builds on Janakiraman's research focus on individual decision making and time. "Life is a series of waits," he said. "I'm very interested in how people respond to waiting and the perception of time."
Another recent paper reported on using call center data to examine how people react to telephone wait queues.
"Many things influence our perception of wait time, from cultural norms to a sense of fair play," he said. Customers in line for service at the airport tolerate seeing first-class customers or frequent flyers access priority boarding or check-in, for example.
"But an invisible queue is very different," said Janakiraman. "It can seem crazy, the way we react to wait times."
He examined 911 call data in one project and found that when the wait went on too long, people would give up and call back.
"But then they have to start over at the end of the queue," he said.
"We are always looking for short cuts," he said. "If you get to a stoplight, and you're the only person there, and two minutes go by and the light hasn't changed ... you start to think that the light must be broken."
"Real-life phenomenon is the basis of all my studies," he added. "We create experiments to replicate these phenomena and then feed back into the loop so firms can understand the dynamics at play."
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