Asset Optimization According to Customer Preference: The Necessary Evolution of Revenue

From the initial applications of revenue management in the airline industry approximately 60 years ago, the hospitality segment has since clamored to adapt the concept of forecasted demand to pricing strategies in hotels, restaurants, golf courses, casinos, sporting events, and theme parks. Through a review of 25 years of published research on revenue management, Anderson and Xie [1], identified that the evolution of revenue management has moved beyond the focus of revenue measurement at the unit level, i.e., average daily rates in hotels, to a more comprehensive view of total revenues or profits generated by the inventory at the enterprise level, i.e., RevPAR (revenue per available room), GOPPAR (gross operating profit per available room); each of which has its comparable measure in the various industry segments, i.e., RevPASH (revenue per available seat hour in restaurants). However, because traditional revenue management practices of dynamic pricing are rooted in an environment of excess demand, and because current data suggests that increased rates and occupancies may be inversely related to customer satisfaction, a revenue management approach that goes beyond the unit level, to one that considers the value that the greater enterprise can offer may be more appropriate. In other words, once the tipping point for pricing at the unit level is identified, rather than retreating to discount strategies or suffering decreased market share, the new revenue management should move beyond the traditionally focused unit level of rooms, seats, rounds, and ticket holders to an asset optimization view. Identifying existing assets (services, facilities, amenities, etc.) that are not proactively incorporated into the product offering may assist in identifying areas of opportunity for increased customer value and corporate revenue. In this way, the enterprise may find that a less aggressive strategy of unit pricing focused on filling capacity may very well improve revenues, profits, and operating efficiencies through a focus on attracting customers who value what the firm has to offer in totality, beyond the unit level. Trade off analyses are an effective way to identify consumer willingness to pay for products based on attributes including varying levels [2,3]. With the basis of consumer willingness to pay being