How Hotels Can Win Against Home-sharing Competitors

June 21, 2021

Disruption doesn’t have to be a death sentence for established firms. With the right changes, they can fight back against new competitors and defend their place in the industry. A new study offers incumbent firms a powerful weapon that is relatively inexpensive, rich in data and easy for managers to get their hands on: the online customer review.

These short – and often sharply worded – reviews are so common that they can be easily overlooked as just another data point to collect and set aside. But the researchers behind the study show how managers can use them to make substantive improvements in service. The study, “How Incumbents Beat Disruption: Evidence from Hotels’ Response to Home Sharing,” looks at the hotel industry in Beijing, a popular tourism market that has been threatened by the exponential growth of home-sharing platforms such as Xiaozhu, known as “the Airbnb of China.” A deep, robust analysis of management responses to thousands of customer reviews reveals how taking action to correct problems not only helps hotels hedge against disruptors, it can also differentiate them from their peers.

“While home sharing’s entry has typically [been] seen as a threat to the profitability of incumbent hotels, we view home sharing’s entry as an opportunity,” the researchers write in the paper. “We envision ubiquitous reviews as the most accessible, cost-effective source of inspirations for hotels to develop defense strategies, right from their backyard.”

The researchers are Karen Xie, associate professor of service analytics and Betty and Fritz Knoebel Fellow at the University of Denver’s Daniels College of Business; Wei Chen, assistant professor of management information systems at the University of Arizona’s Eller College of Management; and Yong Liu, professor and marketing department head at the University of Arizona’s Eller College of Management.

MSI asked Xie some questions about the study. Her responses appear below:

MSI: What are the key takeaways from this study for marketers and managers?

Karen Xie: When facing entries by disruptive innovation, one of the marketing strategies advocated in this study is to deep dive into the ubiquitously available customer reviews and interact with consumers through management responses to obtain inspirations on sustaining competitive advantage. In this study, learning from reviews using management responses to adjust quality provision has been shown to be effective in defending incumbents from home-sharing’s entry. Operationally, marketers and managers can resort to machine learning, with algorithms proven precise and valuable by this study, to automate efficient extrapolation of content features in consumer reviews towards targeted management responses.

MSI: You make it clear that simply responding to online reviews isn’t sufficient; managers need to use the information found in the reviews to make real improvements in service. What is the best way for them to go about that?

Xie: When discussing incumbents’ strategy to react to disruptors, this study focuses on a setting of hotels (incumbents) vs. home-sharing (disruptors). Specific to hotel incumbents, home-sharing disruptors’ challenge arises in areas of cleanliness, check-in/out process, room condition, and excursion opportunity, which are informed by machine learning of the consumer reviews. That is, these four areas are the top four topics that speak to the quality gaps between hotels and home-sharing. By responding to reviews associated in these four areas, hotel incumbents can quickly address the service gap between them and the home-sharing disruptors.

MSI: Your research found a distinction in the response of lower-priced hotels and higher-priced hotels. How did they respond, and what accounts for that difference?

Xie: Although the average responses remain stable, the study shows a sharp divergence between higher-priced hotels and lower-priced hotels in their response activities. Specifically, management responses to reviews surge by 2.7% at higher-priced hotels while plummeting by 3.2% at lower-priced hotels. This heterogeneity appears to show the distinct reactions between hotel price segments. While higher-priced hotels lean in to fight home-sharing disruptors by more actively engaging in responding to consumers reviews, the lower-priced ones tend to retreat by becoming less focused on management responses.

The study explores two possible explanations behind such a discrepancy. First, the lower-priced hotels, when facing home-sharing disruptors, tend to compete on price by offering a lower price than the disruptor, while paying less attention to listening to consumers by responding to their reviews and improving quality. In contrast, higher-priced hotels tend to actively respond to consumer reviews for the opportunities to reposition themselves in the higher-quality end of the lodging market as a response strategy.

Second, the lower-priced hotels, although they may attempt to respond to consumer reviews and play the quality-improvement strategy to cope with the disruptor, they lack the resources because of reduced revenues from the disruption.

MSI: This study focuses on disruption to hotels posed by home-sharing platforms. Can the findings be generalized to other industries?

Xie: While we do not have data evidence from other industries as our context is limited to the service products of hotels and home-sharing properties, we can comfortably anticipate the study’s findings can be generalized to other industries. An often-used — although not recommended — strategy of incumbents in any industry (including retail clothing shops, for example) is to offer a lower price than the disruptors to win back the consumers. When you cut your price, you will immediately decrease your reputation as a business with high-quality products and services.

This means that your customers will think that you have lowered your prices because of the low quality that they will get from you. Another possible thinking of your long-term customers can be that you have charged them too much in the past…. Because of that, there is a significant possibility that when you are lowering prices, you will lose some of your current customers. Finally, your disruptors may also lower their prices. Because of that, you cannot expect many new customers because the price [comparison] will still be the same.

This study suggests otherwise. It is important that incumbents focus on quality competition rather than engaging in a price war with the disruptors. Actively sourcing feedback and recommendations from consumers, making consumer reviews a go-to place for quality improvement inspirations, and actively responding to these reviews and making notes of the quality improvement strategies are the recommended practice from this paper to incumbents in the industry.

MSI: What’s next for this line of research?

Xie: This paper focuses on automating the content feature from consumer reviews for marketers and managers. A next line of research would be to propose similar automation for management responses, using advanced machine-learning algorithms to help markets provide automated responses to valuable suggestions in the consumer reviews and efficiently learn from consumers the strategy to sustain the competition with disruptors. This automation process is nonstop, real-time updated with incoming consumer reviews, and takes the close manual monitoring off the shoulders of marketers and managers. AI and machine learning in general offer a lot of possibilities to the future of marketing and management. We hope our next line of research will achieve this goal of management response automation.

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