A new timeshare method, developed at Brigham Young University, helps timeshare exchange companies better schedule vacation time at affiliated resorts, leading to happier customers and opportunities for increased revenue.
As the holidays approach, timeshare vacation owners are taking advantage of vacation weeks to plan family gatherings and winter getaways. Research has shown that the majority of timeshare vacation owners desire to exchange their resort-weeks each year. But exchanging timeshares can be discouraging, since it is often difficult to get a desired resort-week.
Scott Sampson, a professor at Brigham Young University Marriott School of Management, created a new mathematical timeshare scheduling method that increased the number of customers who could stay at their most-preferred resorts by 30 to 45 percent, without adding additional timeshare units or properties. His results, which demonstrate how using mathematical programming can help match owner requests to resort availability, can be found in the October issue of the academic journal Operations Research.
"I knew that if we applied mathematics to this vacation timeshare problem, we would get tremendous results," Sampson said. "When you're a math geek like I am, you even look at going on vacation as mathematical."
After testing his equations on company data, Sampson implemented his new method at Owner's Resorts and Exchange, a timeshare management company that was recently acquired by Vacation Resorts International.
"In the first year, we demonstrated the potential for a phenomenal increase in satisfaction of timeshare exchange requests," Sampson said. "If you have a better exchange, there can be more people who are happy because they get to go where they want to go. Timeshare exchange companies can perform more exchanges and get a better reputation. It is a win-win situation."
Sampson's models, in different forms, can be applied to conferences, classes or any problem involving scheduling people and limited resources.
"I look at problems involving customers to see how we can use mathematics to make people happier," Sampson said. "If we can optimize, we can have more satisfaction, less stress and happier people."
The $66.7 billion timeshare industry allows owners yearly access to a specific week at a specific resort. To add more variety to their vacations, owners can exchange their week and resort with other time-share owners.
"Survey data shows that more than 60 percent of the people who own timeshare intervals desire to trade them in a given year," Sampson said. "Even though people buy specific weeks at specific properties, the timeshare industry is fundamentally based on exchange."
Exchanging timeshares can be frustrating for some owners because of complex policies, varying membership priority and limited resort availability.
Many timeshare exchange companies use systems that allow people to select from a wide variety of properties for exchange, but without accommodating the fact that some resorts are so popular that it is very difficult to get them in exchange. The highest-priority customers might get to stay at the resort they choose, but there is much less of a guarantee for customers of lower priority.
"The vacation timeshare industry sometimes gets a bad reputation," Sampson said. "There are great locations you can trade into, but customers can be disappointed when they don't consider the free market economics of availability."
Sampson's system acknowledges limited availability, but takes advantage of the fact that people at all levels have some degree of flexibility. His optimization model uses flexibility in customer preferences to allow for trade-offs and to maximize the number of customers whose requests are granted, especially requests from high-priority customers. For example, a high-priority exchange customer might be indifferent between three different resort choices - Sampson's system uses mathematics to determine which of those three options to give the customer so that other customers, of lower priority, can get the most from their resort choices.
Writer: Camille Metcalf