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The Lodging Shared Economy (e.g. Airbnb) has emerged in the past two decades. It was thought that generations participate differently in the Lodging Shared Economy (LSE) and their requirements for LSEs are different for hotels. The current study compares business travelers from three generations (Baby Boomers, Generation X and Generation Y) and their lodging preferences using seven dimensions: Price/Value; Financial Information Security; Personal Safety; Location, Empathy, Amenities, and Cleanliness.

Using MTurk, 614 surveys were completed by two distinct groups of pre-qualified respondents who recently stayed for business in either a hotel or LSE (e.g. Airbnb). This study compared the perceptions of three generations on their responses to seven key lodging attributes.

This study’s results indicate little difference among business travelers from the three generations. Baby Boomers responded they value cleanliness more than Millennials. Boomers are more likely than Xers to tell others about their stay but overall, generational statistical differences were not revealed.

This study suggests that consumer preferences for lodging on business trips are similar across generations and therefore, hotels should focus on business travelers as a homogeneous group rather than attempting to focus on specific generations and specifically not rule out Boomer customers.

While there is much research on the LSE, this is one of the first studies that focuses on business travelers’ preferences for using accommodations other than hotels, which is a gap in LSE research.

The purpose of this paper is to determine how much the lodging shared economy (LSE) utilizes minimum length of stay (MLOS) controls to maximize revenue and reduce housekeeping expense, since cleaning between guest visits represents a substantial variable cost for each guest’s stay. Hosts in the LSE are becoming increasingly perceptive in maximizing revenues.

Daily data for one year were collected for Vacation Rental by Owner properties in Hilton Head Island, SC and Orlando, FL. The collected data include daily vacancies for two different lengths of stay. Linear regression was used to explore the relationship between relative demand and vacancy length of stay differences.

During high-demand periods, there were few differences between the availability of short-term and longer-term reservation vacancies, which indicated hosts were not encouraging guests to stay longer during each visit. These results reveal differences in vacancies for three-night vs six-night reservations. A host can generate more revenue and decrease expenses by maximizing booked nights per visit.

Due to confidentiality issues, this study does not capture vacation bookings but instead captures vacancies. In addition, Average Daily Rate was not utilized in this study.

LSE hosts can maximize revenues using MLOS controls. Minimizing housekeeping costs boosts a host’s profitability.

Although this research has been conducted for hotel MLOS, there is a gap in the literature regarding LSE hosts’ use of MLOS.