Category: Hotels

Green Hotels: An Overview

March 20th, 2019 in Business Practices, Design, Hotels, Real Estate, Sustainability, Winter 2019 0 comments

By Minu Agarwal and Prashant Das

In this article, we adopt a real estate perspective and explore the sustainability implications of hotels. First, we provide a background on sustainability, describe how it relates to the hotel sector and synthesize literature on the economic implications of sustainability. Further, we provide and explain trends on sustainability certifications, LEED in particular, in the US context.

 

What is Sustainability, Why is it Important?

The latest report by the inter-governmental panel on climate change (IPCC) has estimated that human activity has resulted in 1°C of global warming above pre-industrial levels[1]. The report calls for reaching and sustaining net zero CO2 emissions to prevent further rise in global temperatures beyond current projections. Buildings contribute nearly a third of the greenhouse gas emissions and US buildings, in particular, contribute 38% of the total national greenhouse emissions[2]. Governments, organizations and individuals are thus increasingly aware that buildings are critical part of addressing an increasingly urgent challenge -climate change. Growing knowledge of the impact of buildings on the environment and their occupants has led to wide scale reconsideration of how buildings are built and operated.

At the same time humans spend increasingly more time inside buildings[3] and thus buildings have a large impact on our health, productivity, and wellness. Several sustainability metrics have thus been developed to address these and other issues.

 

How is Sustainability Incorporated in Real Estate?

A real estate asset could be perceived in terms of its building mass as well as the behavior of the people occupying it. Sustainability could be achieved from both standpoints. For example, using environment friendly materials and design will enhance the sustainability from the building standpoint. Similarly, improving business processes (such as sourcing local material and employees for hotel operations) may enhance sustainability from the human behavior perspective. While the definition of sustainability interventions may differ from one context to another, organizations such as the United States Green Building Council (USGBC) have devised building project certifications for various types of buildings, climates and geographical locations. USGBC was constituted in 1993 as a membership based non-profit organization. The Leadership in Energy and Environmental Design (LEED) certification, administered by the USGBC is continually re-examined by a large body of volunteer committees comprising of building professionals, developers and building systems manufactures. A wide range of parties are involved with the intent of keeping the rating system current and market relevant. Earlier in 1990, the Building Research establishment (BRE) developed the Building Research Establishment Environmental Assessment Method (BREEAM) rating system in the UK.

Since their inception, sustainability labels such as LEED and BREEAM -among several others- have grown in their acceptance rates and are increasingly popular design and performance assessment tools for building projects. While BREEAM is the oldest whole building sustainability rating system, LEED can be regarded as the most widely adopted system on several counts[4]. It has been used in over 165 countries and in many parts of the world it is being adopted at a wider scale[5]. For example, the City of Vancouver and City of New York have recently passed laws[6] that require LEED certification at a pre-specified level to be achieved by all new-construction projects that meet specific byelaw criteria.

LEED regulates and certifies a building’s design or operations validating the buildings as less harmful to the environment compared to a standard building. LEED rates a project’s performance based on a pre-defined multi-criteria-credit system. The most important credit category relates to energy use and atmospheric emissions, the Energy and Atmosphere category (EA). The next big category of credits is related to human health which ensure minimum thresholds of daylight, thermal comfort, air quality and visual connection to the outdoors, the Indoor Environmental category (IEQ). Water-use is the third big category promoting efficiency in use and recycling, the Water Efficiency category (WE). LEED also examines the environmental impact of building projects within and beyond the site boundary and includes the environmental cost of daily transportation and site development, the Sustainable Sites category (SS). Projects with access to public transportation and pre-existing infrastructure receive additional credit.

These rating systems have a profound impact on the design and construction of a building and the ratings achieved are not simply a by-product of the design process. One study[7], for example, examined two residential projects in Italy and found them to score much higher on ITACA, a local rating system, but much less on the LEED system. Thus, designers must be much more efficient to earn the LEED label. LEED rating system has also duly recognized this and USGBC has released several different tracks that have been tailored to different building types and geographical locations.

How do Sustainability Labels Enhance Real Estate Performance?

Initial motivations for incorporating sustainability in real estate were primarily driven by the notion of corporate social responsibility (CSR). As such, sustainable real estate was considered an investment in the society and thus, a cost center. However, over the years, academic studies reported several economic benefits of sustainability in real estate.

Studies have shown significant association between green labels and commercial real estate performance metrics. Green-labeled properties show superior performance in terms of topline[8] (revenue, rental rate), bottom line[9] (net operating income), occupancy rate[10], operating expenses[11], and asset valuation (transaction price[12], capitalization rate[13]).  Some studies also report indirect financial benefits of green-labeled properties such as reduced absenteeism[14] among the occupants, superior marketability[15], better perceived indoor air quality[16], and higher occupant productivity[17]. Besides, green-labeled buildings are less volatile in terms of pricing and rental rates, providing a potential hedge against the property market cycles[18].  Although opting for green labels may add up the investment costs by up to three percent[19], the multiple benefits from the topline, bottom line and valuation may facilitate a payback within a few years.

Sustainability Trend in Hotels: What to Expect and Why

Although tourism and hospitality industries were among the earliest to recognize the importance of sustainability in business, much less is documented about the financial benefit of green labels in hotels. A Beijing (China)-based study reported nearly 7% increased room rate and 20% less complaints about indoor air quality in green hotels[20]. A US based study[21] reported that although green labeled hotels enjoy significantly higher rental rates (ADR: average daily rate) the corresponding occupancy rate are significantly lower such that the revenues are not different from non-green-labeled hotels. The study argues that the revenue managers potentially become too optimistic with room pricing but should be able to benefit from increased revenue by keeping the same (or only marginally higher) room rate in green-labeled hotels. The bottom-line benefits (through reduced operating expenses) and pricing benefits (through reduced capitalization rates) may lead to further financial benefits. However, these benefits have not been scientifically documented yet. A recent study[22] reports a somewhat positive (yet statistically insignificant) pricing effect of LEED label in US hotels, but argues that with a larger number of green hotels being transacted, the price premium in LEED-labeled hotels may become significant.

While other commercial real estate assets have longer-term occupants (owner-occupiers or tenants), hotels are occupied for very short tenancies (usually a day or a few more). Therefore, the motivation for green hotels needs to be analyzed differently. Due to their short tenancy, the enthusiasm for green hotels among hotel customers may be dominated by an expectation of superior comfort or experiential benefits. However, green hotels may not necessarily provide these amenities. In specific types of hotel (airport, conference, etc.) dominated by large, similarly-minded corporate clients, the CSR motivation may still exist, but will be relatively muted due to the presence of retail customers. On the owners’ side, the attractiveness of green labels will be correlated to tangible financial benefits, such as higher revenue, lower expenses and higher valuation. However, beside higher ADR, there is scant scientific evidence on other financial benefits of green hotels. Therefore, we should expect relatively modest popularity of green label in hotels which will gradually grow as more scientific evidence emerges supporting the financial benefits of going green.

What are the Trends for LEED labels in US hotels?

In December 2018, the USGBC database recorded over 112 thousand US-based projects of which nearly 1,600 included hotels. Anecdotal evidence (from reviewing the Real Capital Analytics reports) suggest that nearly 10% of commercial transactions are related to hotels, but less than two percent representation of hotels in the USGBC database is remarkable.

First, the projects are “registered” with the USGBC for a LEED label consideration. Exhibit 1 summarizes the US-based properties on which the certification decision has been taken by USGBC. We also extract statics on hotel-specific projects. Nearly 30% (34,743) of the 112,000 projects have been certified with less than 0.04% (39) projects which were “rejected” certification for some reason.

Exhibit 1: Summary of LEED Certification Decision on US-based properties

LEED Level All Properties % Hotels %
Denied 39 11
Certified 7,929 23% 134 29%
Bronze 3 0.01% 0.00%
Silver 11,694 35% 178 39%
Gold 12,182 36% 126 28%
Platinum 1,894 6% 9 2%
Grand Total 33743 100% 458 100%

Data source: USGBC, based on data up to 1 December 2018.

The review process may take anywhere from a few months to over twelve years to complete after which a “certification” decision is taken. The average time for all properties is 2 years. Hotels, on average, need 3 years for certification processing. However, the processing time for hotel projects varies in a narrower range (up to 8 years). Exhibit 2 presents the trend of property registration and certification. The trends were reinforcing until the financial crisis. Academic research reports this as the “market acceptance” of LEED certification[23].

Exhibit 2: Number of Projects Registered and Certified for LEED in the US over time

Data source: USGBC, based on data up to 1 December 2018.

The number of projects registered waned in the aftermath of the crisis, but has witnessed increased enthusiasm in later years. 2017 and 2018 witnessed relatively smaller number of projects being registered of certified. The two peaks in number of registered projects seen in years 2009 and 2016 coincide with the years of change in versions of the LEED rating system. Registrations under version 3 (also known as LEED 2009) closed[24] on Oct 2016. Version 3 was launched[25] in 2009 marking the close of version 2. Release of new versions thus appears to be a driver for the timing of the registration depending on choice of the version of the rating system. Risk-averse parties may rush to register in the old version to avoid any unforeseeable changes in the new upcoming versions of the rating system. Some parties may wait to be registered in the new version to maintain the market-edge. Exhibit 3 presents the same analysis focusing on hotel projects.

Exhibit 3: Number of Hotel Projects Registered and Certified for LEED in the US over time

Data source: USGBC, based on data up to 1 December 2018.

USGBC awards different “levels” of LEED certification to projects based on the “points” achieved by them. It thus recognizes various degrees up to which a project may demonstrate achievement of the various sustainability goals. Currently there are four available levels of certification namely: Certified, Silver, Gold and Platinum requiring a minimum of 40, 50, 60, 80 points respectively. While the lower three levels of achievement appear equidistant in terms of additional points needed, the incremental design effort and cost may not be so. The energy related credits (EA category) are the strongest indicators of certification level achieved[26]. Additionally, projects needed a mean increase of 3.51, 5.46, and 11.59 in EA credits in order to graduate from certified to silver, silver to gold and gold to platinum. Similar trends were found on the site related (SS) category as well, the next strongest category of credits after EA to indicate level of certification.

A large number of LEED credits deal with indoor environmental quality. While in the current version of LEED, 35% points are directed towards climate change related concerns, 20% deal directly with health and comfort of the occupants. LEED and other similar rating systems thus have a strong synergy with hotel buildings. Hotels can potentially derive direct financial benefits by ensuring comfortable and positive experience of the hotel guests.

Exhibit 1 provides the detailed breakup across the levels of certifications. Hotel project certification rates are lower at Gold and Platinum levels compared to their peers. In terms of mean credits achieved per category, hotels are among top performers[27] only in the SS category credits which tend to be location driven. Energy-related expenses usually constitute a small part of hotel cash flows. The impact of location on hotel valuation is substantially higher. Thus, the importance of SS credits reflect an environment-friendly trend. On EA category, considered important for achieving higher certification levels, hotels were found to be the lowest achievers along with residential property types. This could explain the drop in Gold and Platinum level certification for hotels.

Conclusions

Although academics in tourism economics were among the earliest to study the importance of sustainability, scientific evidence on the economic benefits of sustainability in this sector is still emerging. Some recent studies within the hospitality sector hint towards positive effects of sustainability on business.

Survey-based studies are unequivocal about the positive impacts of going green in hotels: the customer satisfaction as well as the customers’ willingness-to-pay increases. Besides, less customers complain about the indoor air quality when the subject hotel is green[28]. However, positive customer opinions about green hotels may not necessarily translate into their buying behavior. Unlike other commercial assets (e.g. offices), hotel occupants have much shorter tenancy and may assign relatively lower premium to pricing unless the advantages of green-ness to them are concrete.  If going green compromises on the occupant comfort, the green attributes may have an adverse effect on revenues. Some studies[29] have shown positive impact of green attributes on hotel room rates. However, the room rate must interact with the corresponding occupancy rate to generate revenues. It appears that hotel operators overreact to the green labels in terms of increased room rates. Such a behavior results in lower occupancy rates and an insignificant impact on the revenues. Further, concerns have been raised about higher expenses associated with green hotels, in LEED buildings in particular, which lead to lower bottom line.

We find that the enthusiasm for sustainability label in hotels has been relatively low, but the trends have been upwards in recent years. The need for hotels going green cannot be emphasized enough. However, the green strategic plan must include considerations about occupant comfort and requires a more tactical revenue management so as to maintain higher level of occupancy.


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END NOTES
[1] “Global Warming of 1.5 ºC” Accessed December 6, 2018. https://www.ipcc.ch/sr15/
[2] Bond & Worzala (2014)
[3] Klepeis et al. (2001)
[4] Wilkinson (2011)
[5] “LEED | USGBC.” Accessed December 6, 2018. https://new.usgbc.org/leed.
[6] Vancouver, City of. “Passive Design Toolkit,” Accessed December 6, 2018. https://vancouver.ca Low energy intensity building requirements for certain capital projects LEED law, Pub. L. No. LL31/2016 (2016).
[7] Asdrubali et al. (2015)
[8] Miller, Spivey & Florence (2008) ; Eichholtz, Kok & Quigley (2010) ; Wiley, Benefield & Johnson (2010); Das, Tidwell & Ziobrowski (2011); Reichardt, Frantz, Rottke & Zietz (2012); Zhang, Liu, Wu, Zhang (2017)
[9] Pivo & Fisher (2010)
[10] Fuerst & McAllister (2009) ; Eichholtz, Kok & Quigley (2010) ; Reichardt, Frantz, Rottke & Zietz (2012)
[11] Chapell & Corps (2009); Dorsey & Reid (2012)
[12] Miller, Spivey & Florence (2008)  ; Eichholtz, Kok & Quigley (2010); Das & Wiley (2014)
[13] Pivo & Fisher (2010) ;
[14] Miller, Spivey & Florence (2008)
[15] Chapell & Corps (2009)
[16] Zhang, Liu, Wu, Zhang (2017)
[17] Dorsey & Reid (2012)
[18] Das & Wiley (2014); Das, Tidwell & Zioborwski (2011)
[19] Dorsey & Reid (2010)
[20] Zhang, Liu, Wu, Zhang (2017)
[21] Robinson, Singh, Das (2016)
[22] Das, Smith & Gallimore (2017)
[23] Das & Wiley (2014).
[24] “Is LEED 2009 the Most Current Version of LEED? What Is LEED V 3? | U.S. Green Building Council.” Accessed February 4, 2019. http://www.usgbc.org/help/leed-2009-most-current-version-leed-what-leed-v-3.
[25] “LEED Registration Close and Sunset Dates | U.S. Green Building Council.” Accessed February 4, 2019. https://www.usgbc.org/articles/registration-close-and-sunset-dates.
[26] Wu et al (2017)
[27] Wu et al (2017)
[28] Zhang et al (2017)
[29] Zhang et al (2017), Robinson et al (2016)

REFERENCES
Asdrubali, F., G. Baldinelli, F. Bianchi, and S. Sambuco. “A Comparison between Environmental Sustainability Rating Systems LEED and ITACA for Residential Buildings.” Building and Environment 86, no. Supplement C (April 1, 2015): 98–108. Bond, S., & Worzala, E. (2014). Green Buildings. Private Real Estate Markets and Investments, 234.
Chappell, T. W., & Corps, C. (2009). High performance green building: what’s it worth. Investigating the Market Value of High Performance Green Buildings: Cascadia Foundation.
Das, P., & Wiley, J. A. (2014). Determinants of premia for energy-efficient design in the office market. Journal of Property Research, 31(1), 64-86.
Das, P., Tidwell, A., & Ziobrowski, A. (2011). Dynamics of Green Rentals over Market Cycles: Evidence from Commercial Office Properties in San Francisco and Washington DC. Journal of Sustainable Real Estate, 1-22.
Das, P., Smith, P., & Gallimore, P. (2017). Pricing Extreme Attributes in Commercial Real Estate: the Case of Hotel Transactions. The Journal of Real Estate Finance and Economics, 1-33.
Dorsey, T. A., & Read, D. C. (2012). Best practices in high-performance office development: the Duke Energy Center in Charlotte, North Carolina. Real Estate Issues, 37(2-3), 26-31.
Eichholtz, P., Kok, N., & Quigley, J. M. (2010). Doing Well by Doing Good? Green Office Buildings. American Economic Review, 2492-2509.
Fuerst, F., & McAllister, P. (2011). Green Noise or Green Value? Measuring the Effects of Environmental Certification on Office Values. Real Estate Economics, 45-69.
Klepeis, N. E., Nelson, W. C., Ott, W. R., Robinson, J. P., Tsang, A. M., Switzer, P., … & Engelmann, W. H. (2001). The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants. Journal of Exposure Science and Environmental Epidemiology, 11(3), 231.
McGrath, K. M. (2013). The effects of eco-certification on office properties: a cap rates-based analysis. Journal of Property Research, 30(4), 345-365.
Miller, N., Spivey, J., & Florance, A. be formed about the costs and benefits of green in-vestment, yet a single case is seldom the prototyp-ical mean and there exists rauch local variation that adds to or reduces the marginal costs of going green. The current study goes well beyond case.
Reichardt, A., Fuerst, F., Rottke, N., & Zietz, J. (2012). Sustainable building certification and the rent premium: a panel data approach. Journal of Real Estate Research, 34(1), 99-126.
Robinson, S., Singh, A. J., & Das, P. (2016). Financial impact of LEED and energy star certifications on hotel revenues. The Journal of Hospitality Financial Management, 24(2), 110-126.
Robinson, S., Simons, R., & Lee, E. (2017). Which Green Office Building Features Do Tenants Pay For? A Study of Observed Rental Effects. Journal of Real Estate Research, 39(4), 467-492.
Wiley, J., Benefield, J., & Johnson, K. H. (2010). Green Design and the Market for Commercial Office Space. Journal of Real Estate Finance and Economics, 228-243.
Wilkinson, Sara, and Anita Bilos. “A Comparison of International Sustainable Building Tools – An Update,” Vol. 17. Gold Coast, 2011.
Wu, Peng, Yongze Song, Wenchi Shou, Hunglin Chi, Heap-Yih Chong, and Monty Sutrisna. 2017. “A Comprehensive Analysis of the Credits Obtained by LEED 2009 Certified Green Buildings.” Renewable and Sustainable Energy Reviews 68 (February): 370–79. https://doi.org/10.1016/j.rser.2016.10.007
Zhang, L., Wu, J., Liu, H., & Zhang, X. (2017). The value of going green in the hotel industry: evidence from Beijing. Real Estate Economics.

Minu Agarwal is a PhD candidate and researcher at LIPID Lab for interdisciplinary research in building performance and architectural design process at EPFL (École polytechnique fédérale de Lausanne), Switzerland. She acquired her MS in Sustainable Design from Carnegie Mellon University (USA) and a Bachelor in Architecture from Indian Institute of Technology, Roorkee (India). Earlier, Minu worked as a sustainability Consultant with IES Ltd. (Atlanta) and Buro Happold (New York) among other companies. She has been an entrepreneur and served as an external reviewer for the Green Building Certification, Inc. (GBCI).

 

Prashant Das, PhD is an Associate Professor of Real Estate Finance at Ecole hoteliere de Lausanne (Switzerland) where he also serves as a member of the Academic Board and the Acting Director of Hospitality Finance, Real Estate and Economics (H-FREE) Institute.

The Necessity of Error Management Training in the Hospitality Industry

March 20th, 2019 in Business Practices, Hotels, Restaurants, Trends, Winter 2019 0 comments

By Priyanko Guchait

Mistakes and errors come in all shapes and sizes. In 2015, a number of major hotel corporations fell victim to cyber breaches. Hyatt Hotels Corporation’s payment processing system was breached and affected 250 hotels in about 50 countries. In that same year, data security incidents also occurred in Hilton Worldwide Holdings Incorporated and Starwood Hotels & Resorts Worldwide Incorporated. Similarly, 2015 was also not kind to the restaurant segment of the hospitality industry (Chipotle Mexican Grill) where a series of outbreaks, including Norovirus, E. coli, and Salmonella Newport, sickened more than 490 people. While these negative incidents sound extreme, they often occur as a result of ignoring minor mistakes and errors that occurred earlier.

What is more damaging is that such errors and mistakes are not always reported and documented, and thus no measures are taken to prevent them. As a result, over time, these problems become bigger and bigger, leading to critical incidents with extreme negative consequences. While these more critical incidents make it to the news and tarnish the reputation and business of the companies, there are many other seemingly smaller mistakes and errors that occur in the hospitality industry very frequently such as overbooking, dirty rooms, incorrect reservations, incorrect billing, serving the wrong food, food safety errors, recipe errors etc.  If these problems are not managed, these small mistakes and errors will become more critical and damage the good name or ruin the business of companies as well.

The Need for Error Management Practices:

Hospitality organizations are faced with the possibility of errors, mistakes, and failures every day. The negative consequences these can produce include stress, accidents, loss of time, faulty products, quality and performance problems, negative word-of-mouth, customer dissatisfaction, increased costs, and loss of revenue. Since it is the duty of managers and owners to protect the profit margin, taking a proactive approach to mitigate these mistakes and errors is often attempted in organizations by the use of sophisticated technologies, rigid systems, and strict policies focused on controlling employee behavior.

However, the truth is that total elimination of errors is impossible, and it is very difficult to predict what and when specific errors will occur. Error results from physiological and psychological limitations of humans. In hospitality organizations, often times errors occur because of the very nature of the work (high work load, time pressure, fatigue, poor interpersonal communications, imperfect information processing, and flawed decision-making). Errors may also occur due to equipment malfunction and through no fault of an individual, but still the individual may be responsible to resolve the error. Errors can also happen anywhere in a hospitality organization, with external errors involving customers – both front of house (e.g. checking guests into rooms that are not cleaned), back of house (housekeepers forget to report items that need repairs) – and internal errors involving employees, managers, and department (incorrect accounts billings and payments, or scheduling errors resulting in inferior customer service). Therefore, it is important that hospitality organizations not only focus on error avoidance, but also on error management.  In other words, management and owners need to start asking the question of “what needs to be done after an error has occurred.” Error management is an approach that attempts to deal with errors and their consequences after an error has occurred. It is essential that organizations, managers, and employees develop this mindset that even after meticulous planning and training, things can still go wrong, and people need to be prepared to contain and resolve the problem, continue to provide the best service to guests, and learn how unexpected events can cause errors.

Minimizing Negative Consequences; Increasing the Positive:

Error management is both error prevention and error containment as it focuses on minimizing the negative consequences of errors by early detection, quick error correction, and on preventing similar errors in the future by analyzing the causes and learning from errors. Open communication about errors is a critical error management practice, as it allows for the development of shared understanding about errors, potential error situations, and effective error handling strategies. Many quality-award winners such as Ritz-Carlton use error management strategies – first, they make efforts to identify the errors (service failures) and then resolve the customer problems (service recovery), next they use error data to make decisions on process improvements to increase customer satisfaction in the future.

Therefore, for a successful operation, error management is crucial as it focuses on decreasing negative consequences (e.g. time loss; customer dissatisfaction) and increasing positive consequences (e.g. learning and innovation). The goal of error management is for employees to exhibit positive behaviors to handle the situation rather than panic, get stressed, blame others, or freeze, so that they can correct errors quickly and effectively, learn from the situation, seek feedback, share information so others can learn, and anticipate errors to handle it proactively in the future. However, while error management has proven to be prevalent and useful in aviation, manufacturing, and medicine, it has a notable potential positive impact in the hospitality industry. Research has demonstrated that error management practices influence organizational performance positively, irrespective of industry, and it also affects employee outcomes such as reducing job stress, increasing service recovery performance, exhibiting more helping behaviors, increasing engagement and creativity, and lessening turnover intentions in the lodging and food-services contexts/industry.

Advocating for Error Management Training:

Conventional training usually focuses on teaching the correct way to perform skills during training. Traditionally scholars and practitioners have focused on two types of training which are based on a negative perception toward errors, which considered as consequences of poor analysis, design, and lack of prerequisite behavior. The first type is errorless training. Errors are not mentioned in the errorless training process, because it is believed that error is not necessary for learning to occur. Instead, the focus of the training is to train employees to strictly follow the rules. Information regarding how to handle the potential error situation is not mentioned in the training process. In other words, the trainees are not exposed to any error-related elements as if errors didn’t exist in the workplace.

The second type of training is error avoidance training which is designed to prevent errors from occurring, and participants are not informed about the positive functions of errors. Trainees are encouraged to avoid making errors during the training process. Step-by-step instructions are provided to guide trainees to learn in an error-avoidant way. In both these training types, errors are framed as indicators of failure and lack of competence. Since errors are interpreted as having a negative effect on learning, it leads to self-doubt, dissatisfaction, stress and frustration among employees.

Researchers have recently become interested in investigating the effectiveness of error management training (EMT). This training type considers errors as a natural by-product of active learning and recognizes the potentially positive functions of errors. EMT acknowledges that workers will invariably commit errors for a variety of reasons. Errors are inevitable in the hospitality industry and often service providers do not know how to manage the error once it occurs. Error management training prepares employees to anticipate error occurrence and take preventive measures proactively to stop errors from happening and also prepares employees on how to manage and resolve errors effectively and efficiently once it occurs. According to EMT principles, training programs should not be designed to restrict error occurrence but rather should incorporate errors and train for them. EMT is predicated on the assumption that trainees should learn how to deal with errors rather than to avoid them.

The goal of EMT is to help trainees redefine errors as learning opportunities for which emotional and cognitive coping strategies are available. Errors are reframed as beneficial occurrences rather than stressful calamities. Errors are especially important in the training and learning process in that error can have an informative function for the learner, as they pinpoint where knowledge and skills need further improvement. The central premise of EMT is that the learning of complex cognitive skills is best accomplished in environments where trainees can actively engage in exploration, problem solving, hypothesis testing, making mistakes, and learning to recover from mistakes. EMT is likely to increase employee knowledge and by attending to errors and learning error management techniques, trainees are likely to have a deeper understanding of the job, process, and task knowledge than would otherwise be possible. Increased knowledge and understanding may reduce the risk of committing similar errors in the future.

Error management training leads to transfer performances. Transfer implies that knowledge, skills and attitudes are transferred from one task or job to another. Two types of transfer can be distinguished: (a) Analogical transfer refers to problem solutions that are familiar or analogous, and (b) adaptive transfer entails using one’s existing knowledge base to change a learned procedure, or to generate a solution to a completely new problem. From a practical perspective, adaptive transfer is more relevant in the hospitality industry because of the characteristics of the service products (e.g. simultaneity of service product production and consumption, coproduction of service product between customers and employees) and because errors are inevitable. For example, in a hotel, not all complaints of guests could be foreseeable during orientation. Back on the job, however, employees (trainees) may encounter unexpected problems while dealing with guests’ complaints and, in contrast to the protected training situation, might not have any Passistance at all. Therefore, employees are more likely to come up with unique solutions to unique problems and be more prepared and competent to handle difficult situations.

Scholars have noted three processes through which EMT can impact performance: emotional, cognitive, and motivational. Researchers found empirical support for the notion that EMT increases employees’ tendency to use two self-regulatory skills: Employees learn to exert “emotion control” aimed at reducing negative emotional reactions (e.g., stress, frustration) to errors and setbacks, and they engage in activities that involve planning, monitoring, and evaluating one’s progress during task completion and revision of strategies. Such activities are instigated because errors prompt learners to stop and think about the causes of the error and to experiment with different solutions. Finally, EMT creates a mind-set of acceptance of errors (high error tolerance) which can help to increase employee motivation.

EMT will be more effective in improving task and recovery performances (error identification, resolution, containment) compared to error avoidance or errorless training. Compared to employees who receive errorless or error avoidance training, employees who receive EMT will demonstrate high task and recovery performances because these employees are more likely to: (a) control negative emotions after failures/errors/mistakes and stay focused on the task (emotional process); (b) understand sources and causes of failures and come up with new solutions and improved procedures (cognitive process); and (c) be intrinsically motivated to deliver superior task and recovery performances (motivational process). Therefore, employees who undergo EMT are more likely to demonstrate increased knowledge, better task and recovery performances, and enhanced motivation and moods compared to traditional training methods.

Lessons for Hospitality Leaders:

Managers/trainers need to note some characteristics of EMT. Error management training aims to improve transfer performance, not training performance. In fact, training performance may be worse in error management training in terms of error rate, efficiency, or training time because participants are not directly guided to correct solutions. Instead, employees experiment, explore, make errors, and sometimes arrive at wrong solutions. Thus, managers need to hold a more positive view towards errors during the training process. Finally, when assessing the training effectiveness, the managers should not only focus on the evaluation at the end of the training process, but also how the training results have been applied to the work setting in the future. Compared to errorless and error avoidance training methods which concentrate on the problem solutions that are analogous to training process, the error management training focuses on the generation of new solution to new/unexpected problems.


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Key References
Frese, M., & Altmann, A. (1989). The treatment of errors in learning and training. In L. Bainbridge & S.A. Ruiz Quintanill (Ed.), Developing Skills in Information Technology. (pp. 65-87). New York: Wiley.
Frese, M., Brodbeck, F., Heinbokel, T., Mooser, C., Scheiffenbaxim, E., & Thiemann, P. (1991). Errors in training computer skills: On the positive function of errors. Human Computer Interaction, 6, 77-93.
Frese, M., & Keith, N. (2015). Action errors, error management, and learning in organizations. Annual review of psychology, 66, 661-687.
Guchait, P., Neal, J., & Simons, T. (2016). Reducing food safety errors in the United States: Leader behavioral integrity for food safety, error reporting, and error management. International Journal of Hospitality Management, 59, 11-18.
Keith, N., & Frese, M. (2005). Self-regulation in error management training: Emotion control and metacognition as mediators of performance effects. Journal of Applied Psychology, 90, 677–691.
Nordstrom, C. R., Wendland, D., & Williams, K. B. (1998). “Tor err is human”: An examination of the effectiveness of error management training. Journal of Business and Psychology, 12, 269-282.
Guchait, P., Simons, T., & Pasamehmetoglu, A. (2016). Error Recovery Performance: The Impact of Leader Behavioral Integrity and Job Satisfaction. Cornell Hospitality Quarterly, 57, 150-161.
Van Dyck, C., M. Frese, M. Baer, & S Sonnentag. (2005). Organizational error management culture and its impact on performance: A two-study replication. Journal of Applied Psychology, 90, 1228-1240.

Priyanko Guchait, PhD. is a tenured Associate Professor in the Conrad N. Hilton College of Hotel and Restaurant Management at University of Houston. He is an innovative researcher and hospitality educator. Dr Guchait is the author of more than 40 peer-reviewed journal articles, book chapters, conference proceedings and magazines. Dr. Guchait currently teaches Human Resource Management, Leadership, and Organizational Behavior at the undergraduate level, and Multivariate Data Analysis at the Ph.D. level. He taught at the University of Mississippi and The Pennsylvania State University before joining Hilton College in July 2012. Dr Guchait currently serves as the dissertation/thesis chair and in committees for Master’s and PhD students. He serves as the faculty advisor of Eta Sigma Delta—the International Hospitality Honor Society. Dr Guchait also serves as the Chair of Innovation lab in the Hilton College. He serves on the editorial boards of journals including IJCHM and reviews for several journals. Additionally, he is currently serving as Director of Marketing for WFCHRIE. Dr Guchait brings three years of work experience in hospitality management to his classroom.
Highlights
  • University of Houston’s 2012-13 New Faculty Research Award
  • Best Paper Award at the Southern Management Association conference in 2013
  • Provost’s Excellence Award in 2015
  • Stephen Rushmore/HVS Faculty Research Award in 2016
  • Best Paper Award at the ICHRIE conference in 2016
  • Best Paper Award at the WFCHRIE conference in 2018
  • Eta Sigma Delta Chapter Distinction Award

Panacea or peril? The implications of Neolocalism as a more intrusive form of tourism

March 20th, 2019 in Hotels, Trends, Winter 2019 0 comments

By Makarand Mody and Kyle Koslowsky

The tourism industry is like a mirror: what it offers often reflects the trends that we see in society more broadly. The tourism industry from 30 years ago is very different than the one we see today. In particular, there has been a renaissance of sorts in the accommodations industry with the emergence of a plethora of alternative lodging experiences. Companies like Airbnb and HomeAway have changed the way tourists immerse themselves in destinations and the kinds of experiences they have while there. It is important to reflect on how these new forms of travel impact the destinations they facilitate and the local populace who reside there. These new tourism experiences increasingly leverage a societal trend towards neolocalism, defined as “a deliberate seeking out of regional lore and local attachment by residents (new and old) as a delayed reaction to the destruction in modern America of traditional bonds to community and family” (Shortridge, 1996, p. 10). Flack (1997) identifies neolocalism as an attempt to reassert the “distinctively local” in response to a landscape increasingly devoid of the unique. When applied to the tourism industry, neolocalism appears in the form of tourists seeking out more “authentic” experiences that enable a deeper engagement with a destination and its locals, spurred by tourism providers that create specific products to cater to these new kinds of needs. In principle, much neolocal tourism rejects the kinds of tourism pursued by the mass tourist, perhaps best evidenced in Airbnb’s “Don’t Go There, Live There” campaign, which borders on disdain towards the habits of the mass tourist—the boat tours on the river Seine, “doing” Paris on a Segway, or taking selfies in front of the Eiffel Tower.

With neolocal travel practices becoming increasingly prevalent, consumer behavior in the United States is in a period of transition. Consumers are moving away from traveling like tourists—in a sanitized predictable environment often controlled by travel intermediaries—to wanting to live and experience destinations like locals do. No longer is traveling to Paris to see the Eiffel Tower enough, the consumer now wants to experience the cafés in Paris that only locals know about or learn about the secret spots of the Montmartre area of the city, spots that are “hidden from the usual tourist paths and crowded places. So, you will see the real Montmartre and you will get the feeling of a real Parisian” (Airbnb Experience – “Discover secret spots of Montmartre”). We argue that neolocalism in tourism, while noble in its ambitions and multifaceted in its benefits, potentially proliferates an unhealthy level of separation between the seer (the tourist) and the seen (the destination and all it has to offer), resulting in a level of intrusiveness that the traditional barriers of mass tourism do well to moderate.

The staged experiences of mass tourism

A tourist traveling to a new destination often has a checklist to cover—that famous landmark that defines the city, that vista that one has to photograph, that local delicacy one has never tried before. These experiences, although extraordinarily standard to the local, are invaluable to the incoming tourist, who will often pay good money for a peek into what locals take for granted. “Tourists can see the world with fresh eyes, unencumbered with the daily accumulations of local life” (Nagy, 2018). The tourist thus enters a destination with a perspective that is often very different than that of the local. John Urry (1992) describes this lens as The Tourist Gaze. This gaze is made up of “unique and distinctive signs that the tourist may collect” on their travels. By its very nature, the tourist experience is one that is intended to be visually spectacular, differentiated from the mundane activities of everyday life. In this gaze, even the most normal act on a new, exciting backdrop creates a memorable experience. Urry describes this ocular phenomenon by saying “many of these gazes are self-consciously organized by professionals,” i.e. the hospitality and tourism industry has acknowledged that the tourist is looking for these specific aspects, and they create experiences to cater to these touristic needs. Enter mass tourism. The professional intermediaries of tourism—moderators of the tourist’s gaze—allow the tourist to experience all that they seek out from the bubble of the tourist resort or the comforts of the tour bus. Such craftsmanship of specific experiences catering to the gaze of the tourist has been alternatively described as “staged authenticity” (MacCannell, 1973).

To cater to the tourist gaze, many tourism destinations established separate all-inclusive locations, creating a staged experience of tourism authenticity while maintaining a barrier between tourists and locals. These areas are often referred to as tourism enclaves, defined as “tourism that promotes all-inclusive facilities and services centred on controlling the cultural and physical environment that tourists experience as part of their stay” (Freitag, 1994). Enclave tourism, a phenomenon dating back to the 1980s, is most prevalent in island destinations. Because of the small geographic size of many of these islands, the need to isolate tourists into a specific locale is essential to the social and economic well-being of the destination’s inhabitants. Tourism enclaves essentially serve as a breakwater to the deleterious effects of rapid tourism growth. This logic applies equally to a small Caribbean island as it does to New Orleans’ French Quarter. While keeping the annoyances of tourism away from the daily lives of locals, an enclave approach to mass tourism development also presents its own share of problems—lack of local entrepreneurship in tourism, repatriation of tourism dollars to non-local owners and intermediaries, an excessive reliance on tourism in certain destinations, inauthentic intercultural contact, inequitable distribution of resources for tourism over local consumption (for example, locals not being able to access a beach due to a large number of tourists, as in Mallorca), environmental damage due to concentrated tourism activity, among others.

While the staged authenticity of mass and enclave tourism still remains a significant component of the industry, there has been a rapid growth in what Stanley Plog (1974) labeled the allocentric traveler—risk-taking, adventure seeking individuals who like to travel outside the confines of the tourist bubble and experience a destination like someone living there would. The search for the authentic in a world of the staged has made “tourist” a bad word. Instead, one seeks to be a “traveler”, a sexier antithesis to the one who seeks the standardized, cookie-cutter offerings of mass tourism and the tourism enclave. The traveler seeks out the neolocal in tourism.

Neolocalism—an emerging movement

So, what is neolocalism and why is it important? Neolocalism is perhaps the most recent corollary to a much longer trend of tourists not wanting to be seen as tourists. Instead, individuals want to travel in a manner that allows them to have more immersive, meaningful experiences, to the extent that they blend into the landscape of the destinations they visit. The roots of the neolocal movement in tourism can be traced to the call for more sustainable forms of tourism development in the 1980s, and its more recent manifestation of responsible tourism. In addition, a greater mainstreaming of counterculture trends—anti-hyper-consumerism, sharing over ownership, the search for well-being and self-actualization, the need for authentic connection in a hyper-connected world—have embedded the socio-cultural foundations for the neolocalism in tourism. Consequently, the clear and growing self-guilt of being seen as a tourist, an outsider, is best highlighted by MacCannell (1973):

“Touristic shame is not based on being a tourist but on not being tourist enough, on a failure to see things the way that they “ought” to be seen”.

As a response to this rejection of the role of the tourist, travelers are no longer following the path set out for them by travel intermediaries but are instead searching for authentic, locally embedded travel experiences. Enter companies like Airbnb, which have expertly leveraged technology and the power of crowdsourcing to enable access to the neolocal in tourism. Take Airbnb Guidebooks for example. Guidebooks are a collection of all the best places in every city, as told by Airbnb hosts—a way for travelers to “discover a city according to locals”. withlocals is another example of a platform that connects travelers with locals through food and experiences, allowing travelers to get “off-the-beaten track”. In addition, neolocal intermediaries such as KimKim, a company that connects travelers with local travel companies at destinations, are enabling access to a world of experiences that were previously outside the purview of the tourism enclave and typical mass tourism itineraries. In this regard, Tussyadiah and Pesonen (2016) found that the unique local experiences in atypical tourist neighborhoods drive tourists who stay at peer-to-peer (P2P) accommodations to explore the destinations more by staying longer. Similarly, Mody et al. (2017) found that in addition to the traditional dimensions of Pine and Gilmore’s concept of the experience economy, Airbnb enabled travelers to experience a greater sense of localness, communitas, serendipity, and personalization than in the case of hotel accommodations.

In theory, neolocalism has many benefits, many of which directly counter the perils of mass and enclave tourism, such as: enabling closer cultural interaction and thus a more educational experience for the tourist—mediating globalization through tourism (Brain, 2011), spreading tourism dollars to beyond the tourist zone—providing jobs, increasing community involvement in tourism and local pride (Gotham, 2005; Murray and Kline, 2015), encouraging local consumption patterns and support for local causes and charities (Graefe et al., 2018), redefining understanding of sense of place and identity construction (Cavaliere & Albano, 2018), and generating support for conservation and environmental stewardship, among others. However, the fact remains: despite its potentialities, research on the effects of neolocalism in tourism is scarce, other than that in the context of craft beer tourism. Instead, anecdotal evidence emphasizes the negative and unintended consequences of neolocalism in tourism, particularly in the context of tourism enabled by P2P intermediaries like Airbnb.

Neolocalism—(NOT) a solution to perils of mass tourism!

As several destinations are already struggling to cope with the challenges of overtourism, the introduction of neolocal forms of tourism, disseminating crowds of “travelers” away from the safety and security of already established tourist enclaves, often creates challenges that locals, businesses, destinations management organizations (DMOs), governments and policymakers are unable or unprepared to handle. The repercussions of this unpreparedness are multifold.

For destinations, there have been instances of local identity being distorted or lost altogether. For example, a mushrooming of short-term rentals through websites like Airbnb has resulted in tourists in New Orleans staying in neighborhoods across the city—instead of being fenced in to enclaves like the French Quarter, sparking a debate over the nuisance caused to neighbors and resulting threats to the city’s soul (Burdeau, 2016). In Ethiopia and Uganda, the wealthy adventurer’s quest for contact with authentic tribes is causing its own challenges in relation to these tribes’ character. Due to their exposure with Western travelers, some of the tribes look and act much different than a few years ago—dressing differently, asking for money, having drinking problems (“The Rise of Experiential Travel”, 2014). The level of intimate contact enabled by neolocal experiential travel is not always a boon to destinations.

With Airbnb’s rapid growth throughout major cities in Europe and the world, Barcelona is one of many destinations feeling the impacts of a travel industry growing faster than the city’s ability to sustain it. From contributing to overtourism to driving rents up and residents out [see, for example, Wachsmuth and Weisler’s (2018) examination of Airbnb-induced gentrification in culturally desirable and internationally recognizable neighborhoods of New York], Airbnb is cited by Barcelona as responsible for a variety of its tourism problems. Regulators have reactively put in place measures in place to slow the growth of homesharing listings (no new licenses for Airbnb rentals are currently being given out in Barcelona), as well as furthering their ability to monitor and punish those who do not follow regulation (with beefed up enforcement squads). However, enforcement of regulation remains a challenge across cities, with some local councils turning to private companies for enforcement (Leshinsky & Schatz, 2018). Meanwhile, local residents bear the brunt of neolocalism’s impacts, wading through crowds not only at tourism honeypots such as Las Ramblas and La Sagrada Familia, but also through traditionally quiet neighborhoods. Finding one’s once humble café being gentrified to serve tourist-oriented fare, to the meme-ification of physical spaces on Instagram, causing sharp increases of phone-wielding tourists hoping to “live local”, neolocalism has long-term consequences for actual locals’ lives (Spinks, 2018). In fact, neolocalism-oriented companies like Airbnb have acknowledged that the pursuit for neolocalism is transforming many neighborhoods around the world, and many before they are fully ready for mass tourism (Peltier, 2018).

Beyond destinations, travelers have often found themselves in challenging situations in their pursuit of the neolocal. For example, several Airbnb guests have received instructions from hosts telling them to conceal their identity as tourists so as to not expose the illegal listing to vigilant neighbors. This creates an uncomfortable environment for guests as it places them in not only an awkward but possibly illegal situation that they were not prepared for. Moreover, it’s simply unpleasant to book an Airbnb only to find that residents don’t want you there. Travelers have also been at the receiving end of horror stories involving physical harm, hidden cameras in bedrooms, discrimination, scams, and units that just didn’t match up to what they promised online. Traveling outside the predictable environmental bubble of mass tourism opens up a whole host of challenges that stakeholders are still grappling with.

If living like a local isn’t the answer, then what is?

While we are only beginning to wrap our heads around what the neolocal means for tourism, we stand to argue that everything is not all rosy, as the lofty rhetoric of neolocalism often suggests. Neolocalism is not and cannot be a panacea to the world’s tourism-related problems and challenges. At the same time, it is unseemly to make companies like Airbnb a scapegoat for often-inherent systemic problems that destinations like Barcelona and Rome face when it comes to their tourism industries. Instead, one must acknowledge that Airbnb is simply an exemplar, a reflection of society’s (apparent) need for connection with something deeper than the superficiality of mass tourism’s fleetingness. Our hope is simply to stir a debate around the “relatively new lack of separation between touristic and local life” (Spinks, 2018) enabled by neolocal forms of tourism. With international tourist arrivals expected to reach 1.8 billion by 2030, it is imperative that the confluence of mass tourism and neolocal tourism be managed effectively. This requires actors on both the supply and the demand side of neolocal tourism to act responsibly.

On the demand side, it requires sensitivity and thoughtfulness on behalf of the tourist to recognize the potential intrusiveness of their quest for the neolocal. For example, understanding the deleterious effects of using a not-typical tourist destination like Nashville as a “bachelor party” destination can go a long way in mitigating the nuisance that neighbors have to put up with. Moreover, recognizing that most tourism takes place over too short a duration—4 or 5 days, for example—for one to “live like a local” might make tourists more willingly accept their place as an outsider and the associated and often much-needed separation between touristic and local life. As Nagy (2018) stresses: “Pretending to be a local when you are not is inherently inauthentic”. Instead, he states: “to live like a tourist is to travel more deeply, without being concerned with pure harmony and fitting in. Tourists, especially the new wave of thoughtful, educated and self-aware kind, can double down on the moniker to unlock better and more meaningful days on the road and in the world”.

For the tourism industry, understanding the implications of the products they create and how they communicate with travelers is essential. While placing tourists in the heart of the local makes for a great marketing message, companies like Airbnb need to appreciate and take steps towards reconciling the tension between “traveler locals” and actual locals (Spinks, 2018). For example, while Airbnb has a Responsible Hosting policy that encourage hosts to think carefully about their responsibilities towards tourists, neighbors and the law, there are no guidelines for tourists on how they should behave when accessing some of most private spaces of a destination’s residents—be it their homes or their local religious affiliate. Moreover, for the industry to recognize its responsibility towards other stakeholders at destinations, and working with these stakeholders to manage the negative and unintended consequences of neolocalism, is essential. For example, Airbnb recently created an office of “healthy tourism”, which aims to promote proper tourism growth management across the world (Peltier, 2018).

Tourism suppliers can also look to leverage the power of the neolocal for more sustainable forms of tourism development. For example, Airbnb’s new innovation lab Samara’s first endeavor is a communal housing project designed to revitalize a small town in Japan. The project is deeply entrenched into the local economy—from using local building materials and craftsmen to training locals to serve as hosts to incoming tourists—and looks to leverage the power of the neolocal to bring a miniature tourism economy to a once moribund place (Kuang, 2016). Finally, it is important for suppliers to modulate their “anti-tourist” rhetoric, which is exclusionary and avoids the reality that most visitors spend their hard-earned money to live like a tourist and that’s not a bad thing (Stiker, 2016). For example, Tourists is a 55 acre property in North Adams, Massachusetts that aims to “reclaim and celebrate the beauty of the tourist as someone who removes oneself from the routines of their regular life through travel” (Nagy, 2018). A simple message of welcome to the humble tourist.

In sum, we contend that neolocalism cannot be viewed in isolation of other issues and developments in the tourism industry, such as overtourism. Instead, we argue that, as for the perils of mass tourism, neolocalism’s potential intrusiveness into the lives of locals needs to be carefully managed. As travelers, we must not be ignorant of the results of our choices and our actions. This mentality of conscious travel has been apparent in sustainable and ecotourism for many years, but our considerations today go beyond the natural environment and pertain to the destination’s cultural and social landscape as well. So, as you embark on your next vacation, remember that it’s not a bad thing to be a tourist and not seek out the hyperlocal. After all, as George Bernard Shaw famously said: “I dislike feeling at home when I am abroad”.


PDF Version Available Here.


References
Brain, T.J. (2011), Examining the Portland Music Scene through Neo-Localism, Portland State University, available at: https://pdxscholar.library.pdx.edu/open_access_etds/314/.
Burdeau, C. (2016), “New Orleans’ Growing Airbnb Inventory Sparks Debate Over City’s Soul”, Skift.
Cavaliere, C.T. and Albano, D. (2018), “New Jersey Craft Distilleries: Sense of Place and Sustainability”, in Slocum, S.L., Kline, C. and Cavaliere, C.T. (Eds.), Craft Beverages and Tourism, Volume 2: Environmental, Societal, and Marketing Implications, Springer International Publishing, Cham, pp. 101–117.
Flack, W. (1997), “American Microbreweries and Neolocalism: ‘Ale-ing’ for a Sense of Place”, Journal of Cultural Geography, Routledge, Vol. 16 No. 2, pp. 37–53.
Freitag, T.G. (1994), “Enclave tourism development for whom the benefits roll?”, Annals of Tourism Research, Vol. 21 No. 3, pp. 538–554.
Gotham, K. (2005), “Tourism from Above and Below: Globalization, Localization and New Orleans’s Mardi Gras”, International Journal of Urban and Regional Research, John Wiley & Sons, Ltd (10.1111), Vol. 29 No. 2, pp. 309–326.
Graefe, D., Mowen, A. and Graefe, A. (2018), “Craft Beer Enthusiasts’ Support for Neolocalism and Environmental Causes BT  – Craft Beverages and Tourism, Volume 2: Environmental, Societal, and Marketing Implications”, in Slocum, S.L., Kline, C. and Cavaliere, C.T. (Eds.), , Springer International Publishing, Cham, pp. 27–47.
Kuang, C. (2016), “An Exclusive Look At Airbnb’s First Foray Into Urban Planning”, Fast Company.
Leshinsky, R. and Schatz, L. (2018), ““I Don’t Think My Landlord Will Find Out:” Airbnb and the Challenges of Enforcement AU – Leshinsky, Rebecca”, Urban Policy and Research, Routledge, Vol. 36 No. 4, pp. 417–428.
MacCannell, D. (1973), “Staged Authenticity: Arrangements of Social Space in Tourist Settings”, American Journal of Sociology, The University of Chicago Press, Vol. 79 No. 3, pp. 589–603.
Murray, A. and Kline, C. (2015), “Rural tourism and the craft beer experience: factors influencing brand loyalty in rural North Carolina, USA”, Journal of Sustainable Tourism, Routledge, Vol. 23 No. 8–9, pp. 1198–1216.
Mody, M.A., Suess, C. and Lehto, X. (2017), “The accommodation experiencescape: a comparative assessment of hotels and Airbnb”, International Journal of Contemporary Hospitality Management, Vol. 29 No. 9, pp. 2377–2404.
Nagy, C. (2018), “No Need to Live Like a Local: All Tourists Welcome”, Skift.
Peltier, D. (2018), “Airbnb Launching an Effort to Address Overtourism It Helped Create”, Skift, available at: https://skift.com/2018/04/17/airbnb-launching-an-effort-to-address-overtourism-it-helped-create/.
Plog, S. (1974), “Why Destination Areas Rise and Fall in Popularity”, Cornell Hotel and Restaurant Administration Quarterly, Vol. 14 No. 4, pp. 55–58.
Shortridge, J.R. (1996), “Keeping Tabs on Kansas: Reflections on Regionally Based Field Study”, Journal of Cultural Geography, Routledge, Vol. 16 No. 1, pp. 5–16.
Spinks, R. (2018), “The ‘live like a local’ travel ethos has failed-the question is what will replace it”, Quartzy.
Stiker, M. (2016), “Why ‘Live Like a Local’ Marketing Is a Slap in the Face of Most Travelers”, Skift.
The Rise of Experiential Travel. (2014). Available at: https://skift.com/wp-content/uploads/2014/06/skift-peak-experiential-traveler-report1.pdf.
Tussyadiah, I.P. and Pesonen, J. (2016), “Impacts of Peer-to-Peer Accommodation Use on Travel Patterns”, Journal of Travel Research, Vol. 55 No. 8, pp. 1022– 1040.
Urry, J. (1992), “The Tourist Gaze ‘Revisited’”, American Behavioral Scientist, SAGE Publications Inc, Vol. 36 No. 2, pp. 172–186.
Wachsmuth, D. and Weisler, A. (2018), “Airbnb and the rent gap: Gentrification through the sharing economy”, Environment and Planning A: Economy and Space, SAGE Publications Ltd, Vol. 50 No. 6, pp. 1147–1170.

Makarand Mody, Ph.D. has a varied industry background. He has worked with Hyatt Hotels Corporation in Mumbai as a Trainer and as a Quality Analyst with India’s erstwhile premier airline, Kingfisher Airlines. His most recent experience has been in the market research industry, where he worked as a qualitative research specialist with India’s leading provider of market research and insights, IMRB International. Makarand’s research is based on different aspects of marketing and consumer behavior within the hospitality and tourism industries. He is published in leading journals in the field, including the International Journal of Contemporary Hospitality Management, Tourism Management Perspectives, Tourism Analysis and the International Journal of Tourism Anthropology. His work involves the extensive use of inter and cross-disciplinary perspectives to understand hospitality and tourism phenomena. Makarand also serves as reviewer for several leading journals in the field. In fall 2015, he joined the faculty at the Boston University School of Hospitality Administration (SHA). He received his Ph.D. in Hospitality Management from Purdue University, and also holds a Master’s degree from the University of Strathclyde in Scotland.

 

Kyle Koslowsky is a sophomore studying Hospitality Administration with a concentration in real estate from Scarsdale, New York. He has held previous internships in hotel operations and food and beverage operations. Kyle is a teaching fellow for Fundamentals of Food Service Management as well as a BU Hillel engagement intern. He is also the current president of AEPi, a social fraternity at Boston University.

Failure is Not Fatal: Actionable Insights on Service Failure and Recovery for the Hospitality Industry

March 20th, 2019 in Business Practices, Hotels, Restaurants, Winter 2019 0 comments

By Lisa C. Wan and Elisa Chan

The service industry accounts for more than 70% of global GDP and continues to grow. This growth of the service sector in the foreseeable future is partly fueled by the rapid development of service technology (e.g., artificial technology (AI), chatbots, and automated self-service technology) in the digital age. Service performance is pivotal to consumer satisfaction, however, it is characterized by heterogeneity and intensive human involvement, and therefore service failure is almost inevitable (Chan and Wan 2008; Zeithaml, Parasuraman, and Berry 1990). Consequently, service companies must derive service recovery strategies that would help them mend the broken service promise in case of a service failure. For example, how can customer dissatisfaction be reduced in the event of a service failure? When a service was not performed well for a guest at a hotel, should the General Manager apologize in person? Or send a hand-written apology or an email to the customer? Is a private or public service recovery more effective? Does a service failure matter for an observing (potential) customer? How would a customer witnessing a service failure react to the situation and the service recovery effort by the hotel? Does service technology curb service failure due to its ability to offer standardization? Or does it create new challenges for service failure circumstances and service recovery strategy?

In this article, we seek to address each of these questions by discussing the most notable research findings concerning service failure and recovery. More importantly, we offer some actionable insights derived from existing academic research. The key takeaway is that while service failure is inevitable, proper service recovery effort will not only fix the problem but also enhance customer satisfaction beyond the current as well as potential customer’s expectation.

Insights from Classic Service Failures and Recovery Research

Service failure refers to an instance when customers experience dissatisfaction as a result of an actual service performance not meeting expectation. There are some factors that can reduce consumer dissatisfaction in service failures. For example, a clean and organized service environment, a pre-existing customer-company relationship, and the type of service failure.

Service Environment

One classic research has showed that simply providing a clean, neat and organized service environment can reduce consumer dissatisfaction when service failures happen. (Bitner 1990). Interestingly, a clean and organized environment conveys a professional image that make consumers attribute the cause of the failure as a random event. Consequently, they are less likely to blame the firm for the mistake. If the service environment is unclean and disorganized, the reverse is true: consumers become more dissatisfied with the mistake.

Customer Relationship

Building positive and strong customer rapport is another important strategy because customers tend to be more forgiving of mistakes when they have a positive, pre-existing relationship with a service provider (Jones, Mothersbaugh, and Beatty 2000).  This is especially true for consumers from Asian cultures (Hui, Ho, and Wan 2011).

If a customer treats a service provider as a friend (as opposed to a business partner), he/she will be even more tolerant of the service mistakes due to trust (Goodwin 1996). This trust, however, can be a double-edged sword. When customers have high trust for the service company and it fails to deliver on an explicit promise (e.g., “I guarantee you”), customers would feel betrayed and become angrier (Wan, Hui, and Wyer 2011). But if the service promise is implicit (i.e., “I try my best to help”), customers would be more forgiving. Perhaps counterintuitively, this implies that companies are best to avoid offering service guarantees to loyal customers who consider them more than just a business partner, but as a friend.

The Type of Service Failure

Service failures can be classified into outcome and process failures (Chan and Wan 2008; Smith et al. 1999). An outcome failure involves a loss of economic resources (i.e., money, time) and a process failure involves a loss of social resources (i.e., social esteem). To illustrate, a flight delay would be an outcome failure but an inhospitable flight attendant would be a process failure.

Cross-cultural research has shown that when an outcome failure happens, Asian consumers are less dissatisfied than their Western counterparts. When a process failure occurs, however, the reverse is true (Chan and Wan 2008; Chan et al. 2009). The main reason is because, when compared to Western consumers, Asians are more sensitive to social resources and face concern (i.e., care about one’s social image in front of others), but they pay relatively less attention to economic resources.

The two types of service failures also have implications for service recovery. Consumers prefer to receive recovery resources that match the type of failure that they suffer (Smith et al., 1999). Consumers prefer compensation and a speedy recovery when an outcome failure happens. However, they prefer an apology and an organization-initiated recovery when a process failure happens. Moreover, offering a compensation accompanied by a personal handwritten note (vs. an impersonal typewritten note) from the service provider would boost consumer recovery satisfaction and even reciprocal customer behaviors like more tips (Roschk and Gelbrich 2017).

In fact, the majority of previous research has focused on customers who are directly involved in service failures, scant attention has been paid to studying observers’ reactions to service failures. Observers are the potential customers for a service firm. In the digital age, it is very easy for an unhappy customer to post a negative review online via messaging apps, and this online complaint can be viewed by many others. Notably, customer online complaints have increased 800% over the years between 2014 and 2015 (Causon 2015), and this definitely captures much research and practitioner’s attention.

Insights about the Role of Observers (Potential Customers) in Service Failure Recovery

Since service failure is defined as incidents between the focal service provider and customer, past service recovery strategies research has largely focused on the effectiveness of the various means of recovery efforts for the focal customer’s loss and in restoring this customer’s satisfaction level (Wan, Chan, and Su 2011). While it is important to know how a customer involved in a service failure responds to different recovery strategies, recent research suggests that it is also crucial to examine how an observer (potential customer) witnessing a service failure evaluates the recovery effort. Although there is no reported figure of the financial cost associated with service failure, the consequence of service failure and ineffective service recovery are expected to be increasingly costly due to the prevalence and influence of online distribution and social media channels (e.g., TripAdvisor, booking.com, Instagram, Twitter, etc.).  The monetary costs of losing a hotel guest or restaurant patron can include a direct cost represented as in the short term as the value of a repeat customer and in the long term as customer lifetime value. But the prevalence of online channels, such as TripAdvisor, and Booking.com, implies that the monetary costs of a service failure could also include an indirect social cost due to negative word-of-mouth permeated through negative online reviews. As such, it is expected that the detrimental effects of ineffective service recovery may go beyond those impacts on the customer involved to the observers (e.g., potential customers reading online reviews; Chan, Wan, and Chu 2018; Noone and McGuire 2013; Wan, et al. 2011).

In general, the scant research which focused on the observer (potential customer) has found that a service failure which happened to another customer does have an impact on the observer’s evaluation of, and by extension, intention to engage with the service provider (Chan et al. 2018; Wan, et al. 2011; Wan and Wyer, forthcoming). More interestingly, the contagion impact of a service failure to the observing (potential) customers has been shown to have psychological rather than rational underpinnings. One study showed that the extent to which an observing customer assigns blame to the service provider reflects a defensive mechanism. In particular, when the observing customer witnesses a negative event (i.e., saw or read about a negative service experience), feeling of threat would arise. This feeling would trigger a self-protective motive manifested as the observing customer’s heightened motivation to avoid possible future harm by assigning more blame to the perpetuator of the negative event (i.e., the service provider; Wan, Chan, and Su 2011).

The robustness of the defensive mechanism in the role of an observing customer in service failure is further supported by the finding that an observing customer’s perceived personal similarity with the customer involved accentuates the blame assignment for the service provider. Past research reported that when the observing customer perceived more personal similarity with the focal customer of the service failure, more blame was assigned to the service provider (Chan et al. 2018; Wan, et al. 2011). Moreover, the psychological state that drives this pattern of blame attribution is a sense of vulnerability felt towards the chance that the same failure would befall oneself, as opposed to negative emotions felt towards the negative experience associated with the observed service failure (Chan et al. 2018). In addition, this line of research suggests that personal similarity can be instigated by a variety of factors, such as the focal customer’s age (e.g., a younger person vs. an elderly) and ethnicity (e.g., Asian vs. Cassian), customer status (e.g., VIP status at the focal service company). More importantly, the increased blame assignment to the service provider in the aforementioned studies would further hinders key customer outcomes, such as perceived service quality, likelihood to use the service, and intention to choose the focal service provider, which could hurt the company’s bottom line.

Taken together, this body of research suggests that a company’s service recovery should not be limited to the customer involved in the failure, but extended to those who observed it. For example, service firms can consider offering a public apology or recovery on social media channels after service failures, it may help in alleviating the feeling of threats that the observing customer may experience. Moreover, after the service recovery had been performed to the customer involved, extra attention maybe devoted to other customers as well. If a food order has been placed incorrectly, for example, after apologizing to the patron involved, the server may ask those sitting nearby about their orders and food. This act of concern may soothe any uneasiness emerged out of witnessing someone else’s negative experience.

Service Failure and Recovery in the Technology-Infused Era

The recent surge in technology-infused services has brought new opportunities and challenges to the service industry as a whole. But what are the implications, if any, with respect to service failure, and by extension, service recovery? There is admittedly very limited research in this area. But we hope to offer a few key takeaways for mangers based on our current knowledge:

  1. Companies must remember that while technology-enabled service standardization does not curb service failure. But service failure resulted from service technologies may often be the customers’ own fault (e.g., inability to use technology, not following instructions, etc.). Companies’ must focus on how to better educate customers on the operations of the service technologies and assist customers to prevent such service failure.
  2. Customers using self-service technologies tend to attribute success to themselves but failure to the company. To illustrate, a recent study found that Apple Pay users became more satisfied with the service provider if the payment was successful because it made them look cool; on the contrary, those users became more dissatisfied if the payment was unsuccessful because they felt embarrassed (Liu and Mattila, forthcoming). This suggests that companies’ service recovery effort would not only need to fix the problem but also to alleviate the negative emotions (e.g., embarrassment, anger, etc.) the customer experienced.
  3. Recent market studies have repeatedly found that many customers consider themselves reluctant participants in adopting service technologies. Companies may need to handle service failure and recovery differently for customers who are receptive to technology from those who are reluctant participants. One may expect that those who felt that they did not have a choice may be even more dissatisfied and thus require extra recovery effort.

 PDF Version Available Here.


REFERENCES
Bitner, Mary Jo (1990), “Evaluating Service Encounters: The Effects of Physical Surroundings and Employee Responses,” Journal of Marketing, 69-82.
Causon, Jo (2015), “Customer Complaints Made via Social Media on the Rise,” The Guardian, May 21, https://www.theguardian.com/media-network/2015/may/21/customer-complaints-social-media-rise/.
Chan, Elisa, Lisa C. Wan, and Maggie Chu (2018), “How Potential Customers Respond to Service Recovery Strategies,” Conference Proceeding, the SERVSIG Conference, June 14-16, Paris, France.
Chan, Haksin, and Lisa C. Wan (2008), “Consumer Responses to Service Failures: A Resource Preference Model of Cultural Influences.” Journal of International Marketing, 16 (1), 72-97.
Chan, Haksin, Lisa C. Wan, and Leo Yat-ming Sin (2009), “The Contrasting Effects of Culture on Consumer Tolerance: Interpersonal Face and Impersonal Fate,” Journal of Consumer Research, 36 (2), 292-304.
Goodwin, Cathy (1996), “Communality as a Dimension of Service Relationships,” Journal of Consumer Psychology, 5 (4), 387–415.
Hospitality Technology (2011), “2011 Hospitality Industry Self Service Tech Study,” Research Report, June, http://ncrpr.ncr.com/web/rsdmkt/docs/Hospitality_technology_report.pdf.
Hui, Michael K., Candy K. Y. Ho, and Lisa C. Wan (2011), “Prior Relationships and Consumer Responses to Service Failures: A Cross-Cultural Study,” Journal of International Marketing, 19 (1), 59-81.
Jerger, Christina and Jochen Wirtz (2017), “Service Employee Responses to Angry Customer Complaints: The Roles of Customer Status and Service Climate.” Journal of Service Research, 20 (4), 362-378.
Jones, Michael A., David L. Mothersbaugh, and Sharon E. Beatty (2000), “Switching Barriers and Repurchase Intention in Services,” Journal of Retailing, 76 (2), 259-74.
Liu, Stephanie Q. and Anna S. Mattila (forthcoming), “Apple Pay: Coolness and Embarrassment in the Service Encounter,” International Journal of Hospitality Management.
Mick, David Glen and Susan Fournier (1998), “Paradoxes of Technology: Consumer Cognizance, Emotions, and Coping Strategies.” Journal of Consumer Research, 25 (2), 123-143.
Noone, Breffni M. and Kelly A. McGuire (2013), “Pricing in a Social World: The Influence of Non-Price Information on Hotel Choice.” Journal of Revenue and Pricing Management, 12 (5), 385-401.
Roschk, Holger and Katja Gelbrich (2017), “Compensation Revisited: A Social Resource Theory Perspective on Offering a Monetary Resource After a Service Failure.” Journal of Service Research, 20 (4), 393-408.
Smith, Amy K., Ruth N. Bolton, and Janet Wagner (1999), “A Model of Customer Satisfaction with Service Encounters involving Failure and Recovery,” Journal of Marketing Research, 36 (3), 356–372.
Su, Lei, Lisa C. Wan, and Robert S. Wyer (2018), “The Contrasting Influences of Incidental Anger and Fear on Responses to a Service Failure?” Psychology & Marketing, 1-10.
Wan, Lisa C. (2013), “Culture’s Impact on Consumer Complaining Responses to Embarrassing Service Failure,” Journal of Business Research, 66 (3), 298-305.
Wan, Lisa C., Elisa K. Chan, and Lily L. Su (2011), “When Will Customers Care about Service Failures that Happened to Strangers? The Role of Personal Similarity and Regulatory Focus and Its Implication on Service Evaluation,” International Journal of Hospitality Management, 30, 213-220.
Wan, Lisa C., Michael K. Hui, and Robert S. Wyer (2011), “The Role of Relationship Norms in Responses to Service Failures,” Journal of Consumer Research, 38 (2), 260-77.
Wan, Lisa C. and Robert S. Wyer (forthcoming), “The Influence of Incidental Similarity on Observers’ Causal Attributions and Reactions to a Service Failure?” Journal of Consumer Research
Zeithaml, Valarie A., A. Parasuraman, and Leonard L. Berry (1990), Delivering Quality Service: Balancing Customer Perceptions and Expectations, New York: Free Press.

Lisa C. Wan (Ph.D. The Chinese University of Hong Kong) is an Assistant Professor of the School of Hotel and Tourism Management at Faculty of Business Adminitration, The Chinese University of Hong Kong. She also is the Director for the Centre for Hospitality and Real Estate Research at The Chinese University of Hong Kong. Her research focuses on services marketing and service failure, cross-cultural consumer behavior, and online consumer behavior. Her work has been published in Journal of Consumer Research, Annals of Tourism Research, International Journal of Hospitality Management, Journal of Hospitality and Tourism Research, Journal of International Marketing, Journal of Business Research, and Psychology & Marketing etc.

 

Elisa Chan (Ph.D. Cornell University) is an Assistant Professor in Marketing at the École hôtelière de Lausanne, HES-SO // University of Applied Sciences Western Switzerland. Her research focuses on consumer value and experience in service settings, social and external influences on consumer evaluation and choice, and internal marketing. Her work has been published in Cornell Hospitality Quarterly, International Journal of Hospitality Management, Journal of Consumer Behavior, and Journal of Applied Psychology. She also serves on the Advisory Board of the Hospitality Sales and Marketing Association International (HSMAI) for the Culture and People division in Europe.

A Detailed Study of the Expected and Actual Use of Hotel Amenities

March 20th, 2019 in Hotels, Winter 2019 0 comments

By Chekitan S. Dev and Prateek Kumar[1]

Introduction

Choosing hotel amenities is a critical task for hotel owners and operators.  Offering too few amenities, or the wrong kind of amenities, can negatively affect the brand positioning of the hotel and the guest’s service experience. Offering too many amenities can waste capital, increase operating costs, and put unnecessary burdens on service delivery. This results of this study will provide information to hotel owners and operators to help them decide what amenities to offer, to whom, and under what circumstances.

Prior Research

In three previous studies of predicted and actual use of fifty hotel amenities reported by 724 guests in thirty-three hotels operated by six hotel brands—one upscale, two upper upscale, and three luxury—belonging to one hotel company (Hamilton, Rust, Wedel and Dev 2017; Dev, Hamilton and Rust 2017; Hamilton, Rust and Dev 2017), we developed a mathematical method that enables hotel brand managers and property owners to calculate the return on investment (ROI) for individual amenities.[2] In these two prior studies, we focused on three amenities: free in-room internet access, free bottled water, and fitness center. We found that expected use of particular amenities play a role in the consumer’s choice of choosing the right hotel, and the actual use of particular amenities plays a role in attracting repeat visitors.[3]

In a fourth study, we conducted a detailed analysis of the over predictions and under predictions of all fifty amenities (Dev, Hamilton, Rust and Valenti 2018) which focused on expected and actual use of each amenity.[4] In this fourth study, amenities that were highly over-predicted were an alarm clock, a spa, and in-room dining for dinner and late-night snacks. That is, a much larger percentage of guests expected to use these amenities than actually did so (although they still were used by some guests). Unexpected under predictions included lobby seating, valet parking, and concierge service, for which the percentage of guests expecting to use the service was noticeably smaller than the percentage who did use them.

 

This Study

In this fifth study, we extend prior research to further understand the intention and behavior of hotel guests’ expected and actual use of amenities in a more detailed way.  Specifically, we examine amenity prediction and utilization based on multiple combinations of chain scale, gender, purpose of travel, brand type, length of stay and location.

Results

Exhibit 1: Amenity use by length of stay

1 – 2 nights 3-4 nights 5+ nights
Expected Actual Percentage

Difference

Expected Actual Percentage

Difference

Expected Actual Percentage

Difference

Valet Service 0.17 0.28 -65% 0.10 0.19 -90% 0.14 0.20 -43%
Early check in 0.45 0.33 27% 0.29 0.22 24% 0.36 0.29 19%
Auto check in 0.11 0.01 91% 0.08 0.01 88% 0.08 0.01 88%
Bell desk 0.17 0.22 -29% 0.14 0.27 -93% 0.30 0.44 -47%
Lobby seating 0.26 0.41 -58% 0.28 0.42 -50% 0.33 0.48 -45%
Lobby internet 0.34 0.21 38% 0.36 0.25 30% 0.43 0.29 33%
Lobby food 0.28 0.29 -4% 0.27 0.29 -7% 0.36 0.27 25%
Concierge 0.28 0.36 -29% 0.29 0.42 -45% 0.44 0.64 -45%
Business Center 0.09 0.11 -22% 0.18 0.15 17% 0.16 0.22 -38%
Laundry 0.04 0.02 50% 0.04 0.02 50% 0.11 0.07 36%
Wakeup call 0.38 0.21 45% 0.39 0.25 36% 0.34 0.31 9%
Gift Shop 0.27 0.21 22% 0.28 0.27 4% 0.39 0.33 15%
Restaurant breakfast 0.41 0.26 37% 0.49 0.33 33% 0.60 0.49 18%
IRD Breakfast 0.22 0.11 50% 0.25 0.14 44% 0.28 0.13 54%
Restaurant Lunch 0.21 0.10 52% 0.27 0.19 30% 0.46 0.31 33%
IRD Lunch 0.10 0.16 -60% 0.11 0.29 -164% 0.11 0.50 -355%
Restaurant dinner 0.35 0.02 94% 0.45 0.04 91% 0.71 0.01 99%
IRD Dinner 0.18 0.07 61% 0.19 0.11 42% 0.24 0.10 58%
IRD Midnight smacks 0.23 0.07 70% 0.19 0.06 68% 0.27 0.06 78%
Bar 0.48 0.36 25% 0.51 0.45 12% 0.58 0.54 7%
Minibar 0.12 0.07 42% 0.10 0.10 0% 0.10 0.07 30%
Fridge 0.51 0.31 39% 0.48 0.36 25% 0.69 0.57 17%
Mineral Water 0.54 0.43 20% 0.45 0.37 18% 0.59 0.50 15%
Coffee maker 0.61 0.44 28% 0.56 0.43 23% 0.63 0.53 16%
Room Internet 0.66 0.36 45% 0.71 0.43 39% 0.61 0.40 34%
TV 0.90 0.84 7% 0.92 0.85 8% 0.92 0.93 -1%
Radio 0.40 0.20 50% 0.36 0.20 44% 0.47 0.18 62%
MP3 0.39 0.15 62% 0.30 0.14 53% 0.31 0.16 48%
Alarm 0.63 0.33 48% 0.63 0.39 38% 0.72 0.34 53%
Room desk 0.77 0.70 9% 0.83 0.72 13% 0.84 0.67 20%
Room light 0.79 0.70 11% 0.77 0.72 6% 0.84 0.78 7%
Phone in 0.37 0.33 11% 0.34 0.35 -3% 0.41 0.38 7%
Phone out 0.24 0.13 46% 0.25 0.14 44% 0.29 0.16 45%
Movie on Demand 0.20 0.08 60% 0.14 0.06 57% 0.19 0.13 32%
Hair Dryer 0.68 0.61 10% 0.60 0.57 5% 0.74 0.70 5%
Iron & Ironing board 0.56 0.41 27% 0.53 0.42 21% 0.64 0.53 17%
Closet 0.89 0.81 9% 0.93 0.90 3% 0.99 0.93 6%
Packaged soap 0.81 0.86 -6% 0.85 0.85 0% 0.81 0.89 -10%
Dispensing soap 0.40 0.27 33% 0.43 0.22 49% 0.44 0.24 45%
Bath robe 0.42 0.27 36% 0.39 0.24 38% 0.50 0.37 26%
Safe 0.62 0.43 31% 0.59 0.44 25% 0.71 0.61 14%
Pool 0.36 0.21 42% 0.41 0.30 27% 0.61 0.52 15%
Spa 0.15 0.04 73% 0.19 0.13 32% 0.36 0.16 56%
In room fitness equipment 0.15 0.01 93% 0.14 0.02 86% 0.07 0.02 71%
Fitness Center 0.46 0.18 61% 0.47 0.20 57% 0.43 0.26 40%
Express checkout 0.45 0.29 36% 0.48 0.31 35% 0.52 0.31 40%
Late checkout 0.46 0.28 39% 0.33 0.20 39% 0.37 0.20 46%
Folio under door 0.61 0.60 2% 0.60 0.69 -15% 0.73 0.77 -5%
Boarding pass printing 0.39 0.21 46% 0.59 0.31 47% 0.67 0.46 31%

 Studying the expected and actual usage of amenities based on the length of stay of the guests revealed some interesting insights and confirmed some of our intuitive perceptions regarding amenity use. Here are some notable insights from Exhibit 1:

  • In-room dining (IRD) lunch is the most under predicted amenity where 11% expected to use this facility, however 50% of the guests who stay for more than 5 nights ended up ordering room service for lunch at least once during their stay. We see a steady decline in the usage of this amenity as the length of stay gets shorter.
  • An area where hoteliers can leverage resident guests to increase revenue is the restaurant dinner, which is highly over predicted by guests as less than 5% guests eat dinner at the restaurant. 71% long stay guests expected to use the restaurant for dinner but only 1% guests used which can be potential opportunity for hotel managers to entice the long stay guests to eat in the restaurant and bring in incremental revenue.
  • We see a counter intuitive trend however, in terms of usage of the business center. Contrary to our reasonable hypothesis that long stay guests travel with their office and should have minimal requirement for a business center, 22% of the 5+ night guests tend to use the business center, which is higher than guests staying 1-2- or 3-4-night guests.
  • The usage of laundry has been over predicted by all guests across all length of stay, and even though 11% guests expected to use the laundry services while staying for more than 5 nights, only 7% guests used the laundry services. Only 2% of the guests staying for 1-4 nights used for the laundry. This may make a case for outsourcing the laundry by more hotels to save on labor and capital costs.
  • The long stay guest effect can also be seen in the usage of bell desk which is an under predicted amenity by all guests and 44% of the 5+ night stay guests use the bell desk services.
  • The television remains one of the most used amenity, which creates an opportunity for hotels to upgrade and customize this amenity by investing in smart next generation TVs and offer personalized content.

Exhibit 2: Amenity Use by Hotel Location

URBAN SUBURBAN RESORT
Expected Actual Percentage

Difference

Expected Actual Percentage

Difference

Expected Actual Percentage

Difference

Valet Service 0.12 0.2 -67% 0.16 0.26 -63% 0.15 0.27 -80%
Early check in 0.38 0.28 26% 0.39 0.24 38% 0.37 0.3 19%
Auto check in 0.09 0.01 89% 0.14 0.02 86% 0.09 0.01 89%
Bell desk 0.16 0.27 -69% 0.14 0.14 0% 0.21 0.32 -52%
Lobby seating 0.28 0.43 -54% 0.31 0.37 -19% 0.25 0.42 -68%
Lobby internet 0.321 0.23 28% 0.43 0.21 51% 0.388 0.25 36%
Lobby food 0.28 0.27 4% 0.41 0.35 15% 0.24 0.28 -17%
Concierge 0.29 0.45 -55% 0.21 0.27 -29% 0.36 0.44 -22%
Business Center 0.12 0.11 8% 0.12 0.10 17% 0.16 0.18 -13%
Laundry 0.05 0.03 40% 0.06 0.02 67% 0.05 0.02 60%
Wakeup call 0.41 0.26 37% 0.35 0.17 51% 0.36 0.23 36%
Gift Shop 0.25 0.22 12% 0.25 0.13 48% 0.34 0.33 3%
Restaurant breakfast 0.41 0.24 41% 0.42 0.29 31% 0.55 0.42 24%
IRD Breakfast 0.24 0.14 42% 0.27 0.17 37% 0.23 0.11 52%
Restaurant Lunch 0.2 0.08 60% 0.14 0.05 64% 0.39 0.32 18%
IRD Lunch 0.1 0.03 70% 0.11 0.02 82% 0.11 0.03 73%
Restaurant dinner 0.34 0.15 56% 0.33 0.19 42% 0.59 0.42 29%
IRD Dinner 0.19 0.08 58% 0.23 0.09 61% 0.18 0.1 44%
IRD Midnight smacks 0.22 0.05 77% 0.27 0.09 67% 0.2 0.07 65%
Bar 0.48 0.4 17% 0.42 0.33 21% 0.57 0.47 18%
Minibar 0.1 0.08 20% 0.14 0.1 29% 0.12 0.08 33%
Fridge 0.45 0.27 40% 0.59 0.32 46% 0.59 0.48 19%
Mineral Water 0.48 0.35 27% 0.58 0.52 10% 0.52 0.45 13%
Coffee maker 0.58 0.4 31% 0.67 0.51 24% 0.58 0.49 16%
Room Internet 0.69 0.42 39% 0.72 0.36 50% 0.63 0.36 43%
TV 0.92 0.85 8% 0.91 0.82 10% 0.9 0.87 3%
Radio 0.39 0.2 49% 0.33 0.23 30% 0.4 0.18 55%
MP3 0.34 0.12 65% 0.45 0.21 53% 0.32 0.14 56%
Alarm 0.67 0.4 40% 0.6 0.26 57% 0.61 0.33 46%
Room desk 0.83 0.75 10% 0.83 0.71 14% 0.77 0.65 16%
Room light 0.83 0.75 10% 0.81 0.76 6% 0.74 0.66 11%
Phone in 0.35 0.33 6% 0.4 0.37 8% 0.36 0.35 3%
Phone out 0.23 0.16 30% 0.3 0.12 60% 0.26 0.12 54%
Movie on Demand 0.17 0.07 59% 0.22 0.06 73% 0.15 0.09 40%
Video games 0.02 0.01 50% 0.03 0.01 67% 0.02 0 100%
Hair Dryer 0.67 0.62 7% 0.68 0.57 16% 0.64 0.6 6%
Iron & Ironing board 0.57 0.42 26% 0.52 0.39 25% 0.56 0.45 20%
Closet 0.92 0.86 7% 0.9 0.8 11% 0.91 0.87 4%
Packaged soap 0.83 0.85 -2% 0.77 0.82 -6% 0.85 0.89 -5%
Dispensing soap 0.39 0.21 46% 0.4 0.41 -2% 0.47 0.22 53%
Bath robe 0.39 0.25 36% 0.44 0.23 48% 0.45 0.31 31%
Safe 0.62 0.45 27% 0.59 0.31 47% 0.65 0.52 20%
Pool 0.15 0.06 60% 0.5 0.24 52% 0.71 0.58 18%
Spa 0.06 0.02 67% 0.08 0.02 75% 0.39 0.2 49%
In room fitness equipment 0.11 0.01 91% 0.2 0.04 80% 0.14 0.01 93%
Fitness Center 0.46 0.15 67% 0.49 0.25 49% 0.46 0.24 48%
Express checkout 0.48 0.31 35% 0.51 0.33 35% 0.47 0.28 40%
Late checkout 0.39 0.24 38% 0.5 0.24 52% 0.39 0.23 41%
Folio under door 0.62 0.62 0% 0.58 0.66 -14% 0.63 0.7 -11%
Boarding pass Printing 0.48 0.24 50% 0.45 0.19 58% 0.58 0.36 38%

Here are some insights from the analyses of amenity prediction and use organized by location type presented in Exhibit 2:

  • Across all locations, valet service is one of the highly under predicted amenity. A quarter of all guests use this amenity, slightly less in urban locations (presumably with mostly business travelers carrying a roller bag and laptop) and slightly more in resorts (presumably with leisure travelers with large bags).
  • In contrast, auto check in is among the most over predicted amenity with less than 2% of all guests actually using this amenity. Investing in a cluttering hotel lobbies with multiple auto check in station may therefore be misplaced and investing in efficient and effective check in protocols may be more fruitful.
  • While suburban resorts have the least utilization of lobby seating, they have maximum utilization of lobby food, hinting towards the popularity of grab and go trends from cafes in the hotel lobbies.
  • The gift shop, bar, pool and spa have the maximum utilization in resorts as expected. On the other hand, business center utilization has been the maximum in resorts where up to 18% of the guests end up using the business center, compared to 11% and 10% in urban and suburban respectively. Our hypothesis is that while business travelers to urban hotel travel with their own ‘business center’ (laptops, even portable printers), resort guests are less likely to do so and so need the business center. Plus, from personal experience, we found resort business centers being used a lot by children.

Exhibit 3: Amenity Use by Gender (Female) and Chain Scale

Female

Amenity Midscale Upscale Luxury
Expected Actual Percentage Difference Expected Actual Percentage Difference Expected Actual Percentage Difference
Valet Service 0 0 0% 0.04 0.07 -75% 0.06 0.11 -83%
Early check in 0.09 0.05 44% 0.12 0.1 17% 0.17 0.09 47%
Auto check in 0.03 0.01 67% 0.03 0.01 67% 0.04 0 100%
Bell desk 0.01 0 100% 0.06 0.08 -33% 0.09 0.12 -33%
Lobby seating 0.07 0.03 57% 0.1 0.14 -40% 0.12 0.16 -33%
Lobby internet 0.13 0.07 46% 0.12 0.07 42% 0.13 0.08 38%
Lobby food 0.12 0.11 8% 0.09 0.1 -11% 0.09 0.08 11%
Concierge 0.01 0.04 -300% 0.09 0.14 -56% 0.15 0.18 -20%
Business Center 0.04 0.01 75% 0.04 0.05 -25% 0.06 0.04 33%
Laundry 0.03 0 100% 0.01 0.01 0% 0.02 0.01 50%
Wakeup call 0.16 0.11 31% 0.12 0.08 33% 0.14 0.08 43%
Gift Shop 0.07 0.03 57% 0.11 0.10 9% 0.12 0.06 50%
Restaurant breakfast 0.13 0.07 46% 0.14 0.09 36% 0.15 0.09 40%
IRD Breakfast 0.05 0.01 80% 0.09 0.03 67% 0.13 0.07 46%
Restaurant Lunch 0.05 0 100% 0.1 0.05 50% 0.09 0.06 33%
IRD Lunch 0.04 0 100% 0.04 0.01 75% 0.05 0.01 80%
Restaurant dinner 0.11 0.03 73% 0.14 0.08 43% 0.16 0.09 44%
IRD Dinner 0.04 0.01 75% 0.08 0.04 50% 0.09 0.06 33%
IRD Midnight smacks 0.04 0.01 75% 0.07 0.01 86% 0.1 0.03 70%
Bar 0.08 0.11 -38% 0.14 0.1 29% 0.23 0.2 13%
Minibar 0 0 0.03 0.03 0% 0.09 0.04 56%
Fridge 0.17 0.08 53% 0.19 0.12 37% 0.22 0.16 27%
Mineral Water 0.19 0.21 -11% 0.17 0.11 35% 0.2 0.18 10%
Coffee maker 0.2 0.19 5% 0.22 0.18 18% 0.19 0.07 63%
Room Internet 0.21 0.17 19% 0.21 0.1 52% 0.2 0.11 45%
TV 0.32 0.29 9% 0.3 0.27 10% 0.31 0.28 10%
Radio 0.17 0.09 47% 0.13 0.05 62% 0.17 0.09 47%
MP3 0.13 0.03 77% 0.11 0.03 73% 0.17 0.08 53%
Alarm 0.24 0.16 33% 0.23 0.12 48% 0.23 0.11 52%
Room desk 0.25 0.19 24% 0.27 0.22 19% 0.27 0.24 11%
Room light 0.32 0.21 34% 0.27 0.25 7% 0.28 0.24 14%
Phone in 0.16 0.09 44% 0.13 0.12 8% 0.15 0.16 -7%
Phone out 0.11 0.03 73% 0.08 0.04 50% 0.1 0.05 50%
Movie on Demand 0.08 0 100% 0.05 0.02 60% 0.08 0.04 50%
Hair Dryer 0.24 0.15 38% 0.26 0.25 4% 0.27 0.26 4%
Iron & Ironing board 0.16 0.05 69% 0.21 0.15 29% 0.21 0.13 38%
Closet 0.31 0.15 52% 0.31 0.3 3% 0.32 0.29 9%
Packaged soap 0.28 0.27 4% 0.27 0.28 -4% 0.29 0.29 0%
Dispensing soap 0.16 0.13 19% 0.13 0.06 54% 0.12 0.1 17%
Bath robe 0.11 0.01 91% 0.13 0.06 54% 0.22 0.21 5%
Safe 0.2 0.05 75% 0.21 0.14 33% 0.26 0.18 31%
Pool 0.19 0.04 79% 0.12 0.09 25% 0.18 0.1 44%
Spa 0 0 0% 0.05 0.02 60% 0.11 0.06 45%
In room fitness equipment 0.05 0 100% 0.05 0 100% 0.06 0 100%
Fitness Center 0.15 0.07 53% 0.13 0.04 69% 0.18 0.07 61%
Express checkout 0.19 0.12 37% 0.16 0.11 31% 0.17 0.09 47%
Late checkout 0.15 0.04 73% 0.12 0.07 42% 0.16 0.09 44%
Folio under door 0.17 0.21 -24% 0.21 0.24 -14% 0.20 0.19 5%
Boarding pass Printing 0.17 0.07 59% 0.17 0.1 41% 0.19 0.1 47%

In order to develop a deeper understanding of actual and expected use, we further analyzed our data to examine use of amenities based on gender and the chain scale of the hotel. Because many hotel owners have a portfolio mix of midscale, upscale and luxury properties, here we analyze intent and behavior across these three different property types. Here are the insights from an examination of amenity use by gender (female) and chain scale:

  • Concierge service is the only amenity that is under predicted across all chain scales with the maximum under prediction at the midscale level and the maximum usage at the luxury level. Predictably, concierge service use increases in luxury hotels as compared to midscale hotels.
  • Gift shop use is over predicted across all hotels. However, in upscale hotels, almost as many female guests used the amenity as expected to do so. What this could tell us is that, for midscale and luxury hotels, while female guests anticipated using the gift shop, they ultimately did not use it nearly as much as they expected to do so perhaps because of the type and quality of merchandise offered.
  • When it comes to the coffee maker, we see that 19% of the female guests in midscale hotels use it. The usage drops marginally to 18% in midscale, but to only 7% in luxury. The trend to place high end coffee makers in luxury hotel rooms could change this usage level where guests make their own espressos, cappuccinos and lattes, instead of room service where, in most luxury hotels, the only way to get a cup of specialty coffee is to order one.
  • It is interesting to observe that among the female guests who participated in this survey, almost none of them used the in-room fitness equipment, although 4 to 7 percent of these guests did use the fitness center in the hotel. This could mean that female guests prefer working out in a community setting in the common fitness center at the hotel with a complete set of equipment rather than having their personalized limited fitness equipment in the room. A similar trend can be seen among the male guests as well as per the data shared in the forthcoming part of this report.

Exhibit 4: Amenity Use by Gender (Male) and Chain Scale

Male

Midscale Upscale Luxury
Expected Actual Percentage

Difference

Expected Actual Percentage

Difference

Expected Actual Percentage

Difference

Valet Service 0.02 0 100% 0.03 0.07 -133% 0.08 0.13 -63%
Early check in 0.19 0.13 32% 0.11 0.09 18% 0.11 0.08 27%
Auto check in 0.07 0 100% 0.03 0 100% 0.04 0 100%
Bell desk 0.04 0 100% 0.04 0.08 -100% 0.08 0.13 -63%
Lobby seating 0.09 0.11 -22% 0.07 0.13 -86% 0.09 0.17 -89%
Lobby internet 0.15 0.09 40% 0.12 0.08 33% 0.09 0.08 11%
Lobby food 0.17 0.17 0% 0.08 0.09 -13% 0.1 0.08 20%
Concierge 0.04 0 100% 0.09 0.13 -44% 0.12 0.17 -42%
Business Center 0.02 0 100% 0.05 0.04 20% 0.03 0.07 -133%
Laundry 0 0 0% 0.02 0.01 50% 0.02 0.02 0%
Wakeup call 0.11 0.04 64% 0.14 0.08 43% 0.11 0.09 18%
Gift Shop 0.06 0.04 33% 0.08 0.10 -25% 0.09 0.05 44%
Restaurant breakfast 0.19 0.13 32% 0.17 0.13 24% 0.16 0.12 25%
IRD Breakfast 0.02 0.02 0% 0.05 0.03 40% 0.1 0.09 10%
Restaurant Lunch 0.04 0 100% 0.08 0.07 13% 0.09 0.06 33%
IRD Lunch 0 0 0% 0.02 0.01  50% 0.03 0.01 67%
Restaurant dinner 0.09 0.04 56% 0.15 0.09 40% 0.14 0.12 14%
IRD Dinner 0.04 0 100% 0.05 0.02 60% 0.05 0.02 60%
IRD Midnight smacks 0.09 0.02 78% 0.06 0.01 83% 0.08 0.05 38%
Bar 0.15 0.13 13% 0.16 0.14 13% 0.21 0.18 14%
Minibar 0.04 0 100% 0.02 0.02 0% 0.05 0.05 0%
Fridge 0.17 0.15 12% 0.15 0.1 33% 0.15 0.13 13%
Mineral Water 0.15 0.24 -60% 0.13 0.11 15% 0.21 0.19 10%
Coffee maker 0.17 0.20 -18% 0.17 0.16 6% 0.19 0.09 53%
Room Internet 0.28 0.17 39% 0.25 0.15 40% 0.22 0.17 23%
TV 0.30 0.26 13% 0.3 0.29 3% 0.31 0.29 6%
Radio 0.09 0.04 56% 0.11 0.06 45% 0.12 0.07 42%
MP3 0.13 0.04 69% 0.09 0.03 67% 0.14 0.11 21%
Alarm 0.17 0.09 47% 0.21 0.12 43% 0.17 0.10 41%
Room desk 0.22 0.19 14% 0.29 0.26 10% 0.24 0.25 -4%
Room light 0.26 0.24 8% 0.26 0.23 12% 0.22 0.23 -5%
Phone in 0.06 0.07 -17% 0.1 0.09 10% 0.11 0.14 -27%
Phone out 0.04 0.06 -50% 0.08 0.05 38% 0.07 0.05 29%
Movie on Demand 0.04 0.02 50% 0.05 0.02 60% 0.07 0.02 71%
Video games 0.02 0 100% 0 0 0% 0.01 0 100%
Hair Dryer 0.19 0.17 11% 0.17 0.16 6% 0.17 0.16 6%
Iron & Ironing board 0.17 0.15 12% 0.16 0.15 6% 0.17 0.14 18%
Closet 0.26 0.26 0% 0.3 0.29 3% 0.30 0.29 3%
Packaged soap 0.31 0.26 16% 0.28 0.29 -4% 0.28 0.28 0%
Dispensing soap 0.24 0.19 21% 0.15 0.08 47% 0.15 0.07 53%
Bath robe 0.09 0.02 78% 0.11 0.05 55% 0.17 0.14 18%
Safe 0.13 0.09 31% 0.17 0.14 18% 0.25 0.21 16%
Pool 0.15 0.11 27% 0.11 0.08 27% 0.18 0.13 28%
Spa 0 0 0.05 0.02 60% 0.09 0.05 44%
In room fitness equipment 0.02 0 100% 0.04 0.01 75% 0.03 0.01 67%
Fitness Center 0.2 0.07 65% 0.15 0.07 53% 0.19 0.11 42%
Express checkout 0.15 0.09 40% 0.17 0.12 29% 0.14 0.04 71%
Late checkout 0.13 0.07 46% 0.11 0.07 36% 0.2 0.13 35%
Folio under door 0.19 0.19 0% 0.2 0.24 -20% 0.22 0.15 32%
Boarding pass Printing 0.15 0.04 73% 0.18 0.1 44% 0.14 0.07 50%

Another remarkable finding from studying the usage pattern of the above amenities for male guests was observed in the business center. While the use of a business center was overpredicted in the midscale and the upscale segment, it was considerably underpredicted in the luxury segment by male guests. Only 3% guests expected to use the business center but more than double of that used it during their stay. This may be a clear signal for luxury brands which are focused on attracting male business travelers to invest in a cutting-edge technology equipped business center which would could promote their repeat guest business.

Lobby seating was underpredicted across all chain scales and to a much greater extent among upscale and luxury hotels, with an underprediction of over 80%. As the concept of co-working become more and more popular, we believe that this trend of working in a social environment will only increase in the coming years. Hotel lobbies, which were once seen merely as ‘in transit’ non-revenue generating areas can now be seen as co-working spaces allowing guests to network with other guests of the hotel.

As observed in the data for female guests, in room fitness equipment does get much attention from the male counterparts as well. Only 1% of the male guests used in room fitness equipment but 7-11% guests used the hotel fitness center, which again point towards the preference for a social atmosphere adopted by the guests.

Exhibit 5a: Amenity use by travel purpose and chain scale (Midsale)

Midscale

Business Leisure
Expected Actual Percentage

Difference

Expected  Actual Percentage

Difference

Valet Service 0 0 0% 0.01 0 100%
Early check in  0.1 0 100% 0.15 0.1 33%
Auto check in 0.05 0.05 0% 0.04 0 100%
Bell desk 0.05 0 100% 0.01 0 100%
Lobby seating 0.14 0.05 64% 0.05 0.06 -20%
Lobby internet 0.14 0.1 29% 0.14 0.06 57%
Lobby food 0.24 0.14 42% 0.11 0.11 0%
Concierge 0.05 0 100% 0.02 0.02 0%
Business Center 0.05 0.05 0% 0.03 0 100%
Laundry 0.05 0 100% 0.01 0 100%
Wakeup call 0.14 0.1 29% 0.11 0.06 45%
Gift Shop 0.1 0.1 0% 0.04 0.02 50%
Restaurant breakfast 0.24 0.1 58% 0.14 0.09 36%
IRD Breakfast 0.1 0 100% 0.02 0.02 0%
Restaurant Lunch 0.1 0 100% 0.03 0 100%
IRD Lunch 0.1 0 100% 0.01 0 100%
Restaurant dinner 0.19 0.05 74% 0.06 0.02 67%
IRD Dinner 0.1 0 100% 0.02 0 100%
IRD Midnight smacks 0.1 0 100% 0.06 0.02 67%
Bar 0.05 0.19 -280% 0.13 0.11 15%
Minibar 0 0 0% 0.02 0 100%
Fridge 0.14 0.14 0% 0.19 0.11 42%
Mineral Water 0.24 0.14 42% 0.18 0.25 -39%
Coffee maker 0.19 0.14 26% 0.2 0.22 -10%
Room Internet 0.33 0.24 27% 0.23 0.15 35%
TV 0.33 0.33 0% 0.3 0.27 10%
Radio 0.1 0 100% 0.14 0.08 43%
MP3 0.1 0.1 0% 0.13 0.13 0%
Alarm 0.14 0 100% 0.2 0.04 80%
Room desk 0.33 0.14 58% 0.2 0.17 15%
Room light 0.29 0.29 0% 0.29 0.19 34%
Phone in 0.1 0 100% 0.12 0.09 25%
Phone out 0.05 0 100% 0.08 0.04 50%
Movie on Demand 0.05 0.05 0% 0.05 0 100%
Video games 0.05 0 100% 0 0 0%
Hair Dryer 0.1 0.14 -40% 0.24 0.15 38%
Iron & Ironing board 0.29 0.24 17% 0.13 0.06 54%
Closet 0.33 0.24 27% 0.28 0.18 36%
Packaged soap 0.33 0.33 0% 0.28 0.23 18%
Dispensing soap 0.14 0.19 -36% 0.19 0.15 21%
Bath robe 0.14 0.05 64% 0.08 0.01 88%
Safe 0.19 0.1 47% 0.17 0.06 65%
Pool 0.1 0.05 50% 0.18 0.08 56%
In room fitness equipment 0.1 0 100% 0.01 0 100%
Fitness Center 0.29 0.19 34% 0.14 0.05 64%
Express checkout 0.19 0.1 47% 0.16 0.11 31%
Late checkout 0.1 0 100% 0.15 0.08 47%
Folio under door 0.24 0.29 -21% 0.16 0.19 -19%
Boarding pass Printing 0.19 0.05 74% 0.13 0.05 62%

 Exhibit 5b: Amenity use by travel purpose and chain scale (Upscale)

 Upscale

Business Leisure
Expected Actual Percentage

Difference

Expected Actual Percentage

Difference

Valet Service 0.02 0.05 -150% 0.05 0.09 -80%
Early check in  0.08 0.08 0% 0.14 0.11 21%
Auto check in 0.03 0 100% 0.03 0.01 67%
Bell desk 0.03 0.05 -67% 0.07 0.11 -57%
Lobby seating 0.08 0.13 -63% 0.1 0.14 -40%
Lobby internet 0.12 0.08 33% 0.13 0.07 46%
Lobby food 0.08 0.09 -13% 0.1 0.10 0%
Concierge 0.06 0.1 -67% 0.12 0.16 -33%
Business Center 0.07 0.05 29% 0.03 0.04 -33%
Laundry 0.01 0 100% 0.02 0.01 50%
Wakeup call 0.14 0.09 36% 0.11 0.06 45%
Gift Shop 0.08 0.08 0% 0.11 0.11 0%
Restaurant breakfast 0.14 0.09 36% 0.17 0.11 35%
IRD Breakfast 0.05 0.03 40% 0.08 0.03 63%
Restaurant Lunch 0.08 0.06 25% 0.1 0.05 50%
IRD Lunch 0.02 0.01 50% 0.05 0.01 80%
Restaurant dinner 0.13 0.08 38% 0.15 0.08 47%
IRD Dinner 0.07 0.04 43% 0.07 0.02 71%
IRD Midnight smacks 0.05 0.01 80% 0.09 0.02 78%
Bar 0.12 0.09 25% 0.18 0.15 17%
Minibar 0.02 0.02 0% 0.03 0.02 33%
Fridge 0.13 0.07 46% 0.19 0.14 26%
Mineral Water 0.13 0.09 31% 0.17 0.13 24%
Coffee maker 0.17 0.15 12% 0.21 0.18 14%
Room Internet 0.26 0.17 35% 0.2 0.09 55%
TV 0.3 0.29 3% 0.3 0.29 3%
Radio 0.11 0.05 55% 0.13 0.07 46%
MP3 0.08 0.13 -63% 0.11 0.11 0%
Alarm 0.23 0.02 91% 0.21 0.04 81%
Room desk 0.3 0.26 13% 0.25 0.21 16%
Room light 0.26 0.25 4% 0.26 0.22 15%
Phone in 0.11 0.09 18% 0.11 0.12 -9%
Phone out 0.07 0.05 29% 0.09 0.05 44%
Movie on Demand 0.04 0.01 75% 0.07 0.04 43%
Video games 0 0 0% 0.01 0 100%
Hair Dryer 0.17 0.16 6% 0.25 0.23 8%
Iron & Ironing board 0.18 0.14 22% 0.19 0.15 21%
Closet 0.3 0.29 3% 0.31 0.29 6%
Packaged soap 0.26 0.28 -8% 0.28 0.3 -7%
Dispensing soap 0.13 0.05 62% 0.14 0.08 43%
Bath robe 0.1 0.04 60% 0.14 0.07 50%
Safe 0.16 0.11 31% 0.22 0.17 23%
Pool 0.07 0.02 71% 0.15 0.13 13%
Spa 0.03 0 100% 0.07 0.03 57%
In room fitness equipment 0.06 0.01 83% 0.04 0 100%
Fitness Center 0.15 0.05 67% 0.14 0.06 57%
Express checkout 0.17 0.12 29% 0.15 0.10 33%
Late checkout 0.12 0.08 33% 0.13 0.07 46%
Folio under door 0.2 0.26 -30% 0.21 0.22 -5%
Boarding pass Printing 0.2 0.11 45% 0.15 0.09 40%

Exhibit 5c: Amenity use by travel purpose and chain scale (Luxury)

Luxury

Business Leisure
Expected Actual Percentage

Difference

Expected Actual Percentage

Difference

Valet Service 0.05 0.09 -80% 0.08 0.13 -63%
Early check in  0.06 0.03 50% 0.16 0.1 38%
Auto check in 0.04 0 100% 0.04 0 100%
Bell desk 0.06 0.06 0% 0.09 0.13 -44%
Lobby seating 0.11 0.18 -64% 0.11 0.15 -36%
Lobby internet 0.09 0.08 11% 0.12 0.08 33%
Lobby food 0.10 0.10 0% 0.09 0.07 22%
Concierge 0.08 0.10 -25% 0.14 0.19 -36%
Business Center 0.06 0.05 17% 0.03 0.06 -100%
Laundry 0.01 0.01 0% 0.02 0.01 50%
Wakeup call 0.12 0.1 17% 0.11 0.06 45%
Gift Shop 0.07 0.02 71% 0.11 0.06 45%
Restaurant breakfast 0.18 0.08 56% 0.13 0.10 23%
IRD Breakfast 0.10 0.05 50% 0.10 0.08 20%
Restaurant Lunch 0.04 0.04 0% 0.08 0.06 25%
IRD Lunch 0.02 0.01 50% 0.04 0.01 75%
Restaurant dinner 0.15 0.07 53% 0.14 0.1 29%
IRD Dinner 0.06 0.04 33% 0.06 0.03 50%
IRD Midnight smacks 0.07 0.03 57% 0.09 0.04 56%
Bar 0.17 0.13 24% 0.23 0.2 13%
Minibar 0.06 0.02 67% 0.07 0.05 29%
Fridge 0.19 0.08 58% 0.19 0.16 16%
Mineral Water 0.19 0.15 21% 0.19 0.18 5%
Coffee maker 0.19 0.02 89% 0.19 0.09 53%
Room Internet 0.26 0.18 31% 0.19 0.12 37%
TV 0.31 0.26 16% 0.3 0.29 3%
Radio 0.14 0.09 36% 0.15 0.07 53%
MP3 0.13 0.13 0% 0.16 0.09 44%
Alarm 0.2 0.1 50% 0.19 0.09 53%
Room desk 0.3 0.29 3% 0.23 0.22 4%
Room light 0.28 0.28 0% 0.23 0.22 4%
Phone in 0.13 0.15 -15% 0.13 0.14 -8%
Phone out 0.07 0.06 14% 0.08 0.05 38%
Movie on Demand 0.07 0.03 57% 0.06 0.02 67%
Video games 0 0 0.01 0 100%
Hair Dryer 0.15 0.12 20% 0.25 0.24 4%
Iron & Ironing board 0.2 0.15 25% 0.19 0.13 32%
Closet 0.33 0.3 9% 0.3 0.29 3%
Packaged soap 0.28 0.27 4% 0.27 0.29 -7%
Dispensing soap 0.12 0.08 33% 0.14 0.08 43%
Bath robe 0.21 0.15 29% 0.19 0.19 0%
Safe 0.26 0.14 46% 0.25 0.2 20%
Pool 0.10 0 100% 0.19 0.14 26%
Spa 0.04 0.04 0% 0.11 0.05 55%
In room fitness equipment 0.07 0.01 86% 0.04 0 100%
Fitness Center 0.21 0.08 62% 0.17 0.08 53%
Express checkout 0.19 0.06 68% 0.15 0.06 60%
Late checkout 0.15 0.04 73% 0.18 0.12 33%
Folio under door 0.29 0.19 34% 0.2 0.16 20%
Boarding pass Printing 0.20 0.07 65% 0.16 0.08 50%

Disaggregating the data by chain scale type and purpose of stay revealed a few insights on technology use, that sometimes is overrated. For instance, the auto check in facility in luxury hotels was barely used by business or leisure travelers in luxury and midscale hotels. The express checkout facility was used by around 6% of the guests in the luxury segment but was expected to be used by 19% of business guests and 15% of leisure guests. In the case of upscale properties, the actual usage of express checkout service was reduced to almost 12% for business guests and to 10% for leisure guests. These findings make us rethink the willingness of travelers to adapt to innovations of technology which makes them drift from the conventional norms and replaces the element of human interaction with the guests. As seen from this data, majority of hotel guests are still adapting to these automated systems, it may be a while before technology can replace the human element of hotel services completely, if ever. We saw a similar trend in the hotel reservation processes, which took almost a decade to move from a  human-assisted process to an almost completely digitized one.

Examining some other amenities, we observe that the bell desk usage is much higher among the leisure guests across all chain scales, as leisure travelers tend to travel with more luggage and probably need this assistance. Around 13% of leisure guests used the bell desk services in luxury hotels and almost 11% in upscale hotels.

Lobby seating remains an underpredicted amenity in every chain scale. Almost 18 % luxury business travelers actually used the lobby seating, and almost 15% of leisure guests used lobby seating in upscale and luxury hotels. As discussed earlier in this report, we believe that this trend may rise in the future as guests actively seek out social interactions with other hotel guests and as more hotel make the lobby a more functional and social space. Most guests who used lobby seating used lobby food with usage varying from 7% to 14%, with the highest being at the midscale level by business guests.

Another amenity which was overpredicted among all chain scales was late check out. In luxury hotels, while 15% of business guests expected to use a late check out facility, only 4% actually did so, either because they did not need it or it was not offered. In comparison, 18% of leisure guests expected to use a late check out and 12% actually used it, again because they wanted to spend more time in the destination and/or were able to secure it. One possible insight here is that late check out could affect a buying decision of more than 15% travelers while shopping for hotel rooms, something we intuitively knew but now can put a number on it.

Summary and Conclusions

 As with any study, we caution the reader to use these results with caution. One limitation of our data is that some of the amenities have been significantly enhanced since we conducted our survey. For example, even though more than 80% of the guests overpredict auto check in or mobile check in services, in our study it is used by 2% guests in suburban locations and even lesser in urban and resort. Today, many more hotel brands are now offering keyless entries[5]. However, it certainly has a long way to go before auto check in becomes the norm. Moreover, as seen from our previous studies, technology related amenities are one of the most overpredicted amenities[6] which may suggest that even though travelers are willing to accept new technology in hotels, it may take time for travelers to completely adapt to newer ways of service delivery.

Other key learnings from this study reveal the growing popularity of common spaces in the hotels such as the lobby and a considerable usage of the concierge service as guests are looking for personal recommendations and customized services. The in-room television still remains of highest used amenity by guests in all types of hotels, thus offering an opportunity for marketers to promote targeted content and for hotel managers to add value through a highly customized and personalized offering. Hilton’s recent announcement offering Netflix in the rooms is one such enhancement of this amenity.[7]

Hotel amenities, which can make or break a guest’s hotel stay, and which cost hotel owners a lot of money to install and deliver, are continuously evolving.  Offering the right amenities to the right guest, in the right location, for the right trip purpose, in the right type of hotel, for the right length of stay, continues to be a puzzle owners and operators are continually trying to solve. We expect that the results of our study will help hotel owners, asset managers, brand managers, operators, designers and consultants make optimal decisions regarding what amenities to offer, when and to whom.


PDF Version Available Here.


REFERENCES
[1] Chekitan S. Dev is Professor of Marketing at Cornell University’s School of Hotel Administration in the SC Johnson College of Business where Prateek Kumar is a candidate for the Master of Management in Hospitality (MMH) degree.
[2] Hamilton, Rebecca W., Roland T. Rust, Michel Wedel and Chekitan S. Dev (2017), “Return on Service Amenities,” Journal of Marketing Research, 54(1), 96-110. Dev, Chekitan S., Rebecca W. Hamilton and Roland T. Rust (2017), “Hotel Brand Standards: How to Pick the Right Amenities for your Property,” Cornell Hospitality Report, 17(3), 3-7.
[3] Hamilton, Rebecca W., Roland T. Rust and Chekitan S. Dev (2017), “Which Features Increase Customer Retention?” MIT Sloan Management Review, 58(2), 79-84.
[4] Dev, Chekitan S., Rebecca W. Hamilton, Roland T. Rust and Matthew Valenti (2018), “What Do Hotel Guests Really Want? Anticipated Versus Actual Use of Amenities, Cornell Hospitality Report, 18(8), 1-24.
[5] https://skift.com/2016/06/29/the-current-state-of-keyless-entry-at-big-hotel-brands/
[6] Dev, Hamilton, Rust and Valenti 2018
[7] https://variety.com/2019/digital/news/netflix-pacts-with-hilton-on-hotel-in-room-streaming-but-only-for-small-fraction-of-rooms-1203116640/

Chekitan S. Dev is a professor of marketing at Cornell University’s School of Hotel Administration in the SC Johnson College of Business. A winner of several teaching and research awards, Professor Dev is a globally renowned thought leader and the leading expert on hospitality marketing and branding. An active consultant, expert witness, keynote speaker, and workshop leader, Professor Dev has served corporate, government, education, advisory, legal, and private equity organizations in over 40 countries on 6 continents. He can be contacted at chekitan.dev@cornell.edu.

 

Prateek Kumar is a graduate student at Cornell University’s School of Hotel Administration in the SC Johnson College of Business where he is pursuing a Masters degree with a concentration in real estate and finance. He has worked with Aman Resorts, Oberoi Hotels and Relais & Chateaux in luxury hotel operations, financial analysis and hotel investments. Driven by a passion for adding value to hospitality businesses, Prateek plans to work in hotel acquisitions and development with the ultimate goal of creating his own hotel company. He can be reached at pk559@cornell.edu.

Airbnb and the Hotel Industry: The Past, Present, and Future of Sales, Marketing, Branding, and Revenue Management

October 31st, 2018 in Business Practices, Fall 2018, Hotels, Marketing, Sharing Economy, Technology, Trends 0 comments

By Makarand Mody and Monica Gomez

For a long time, the hotel industry did not consider Airbnb a threat. Both the industry and Airbnb claimed they were serving different markets and had different underlying business models. Over the years, as Airbnb become more successful and grown to being larger than the companies in the hotel industry, the rhetoric has changed. The hotel industry began to realize they had something to worry about.

A stage of denial was followed by the American Hotel & Lodging Association (AH&LA) attacking Airbnb by sponsoring research to demonstrate its negative impacts on the economy and lobbying governments to impose taxes and regulations on homesharing. The association is arguing for a level playing field between homesharing and hotels (and rightly so). The next stage of this battle involves competition and integration. Not only are hotels looking to add homesharing-like attributes and experiences to their properties, to more effectively compete with Airbnb, but are also looking to tap into the platform-based business model that underlies Airbnb’s success.

 

The Past: How does Airbnb impact the hotel industry?

Airbnb’s disruption of the hotel industry is significant, both existentially and economically. A recent study by Dogru, Mody, and Suess (2018) found that a 1% growth in Airbnb supply across 10 key hotel markets in the U.S. between 2008 and 2017 caused hotel RevPAR to decease 0.02% across all segments. While these numbers may not appear substantial at first, given that Airbnb supply grew by over 100% year-on-year over this ten year period means that the “real” decrease in RevPAR was 2%, across hotel segments. Surprisingly, it was not just the economy but also the luxury hotel segment that was hard hit by Airbnb supply increases, experiencing a 4% real decline in RevPAR. The impact of Airbnb on ADR and occupancy was less severe. In Boston, RevPAR has decreased 2.5%, on average, over the last ten years due to Airbnb supply increases. In 2016 alone, this 2.5% decrease in RevPAR amounted to $5.8 million in revenue lost by hotels to Airbnb. Brands that felt the impact the most were those in the midscale and luxury segments, with a decrease in RevPAR of 4.3% and 2.3% respectively. These supply increases are also fueling Airbnb taking an increasing share of the accommodation market pie. For example, in New York City, Airbnb comprised 9.7% of accommodation demand, equaling approximately 8,000 rooms per night in Q1 2016 (Lane & Woodworth, 2016). As a whole, Airbnb’s accommodated demand made up nearly 3% of all traditional hotel demand in Q12016.

Buoyed by a growth rate of over 100% year on year, Airbnb now has over 4 million listings, with the U.S. being its largest market. The company also has significant room to grow in other countries, particularly emerging markets in Africa and India. The company has run into some competition in China, with local rivals Tujia and Xiaozhu. Also, within the U.S., the good news is that Airbnb will not grow at 100% indefinitely and will eventually plateau as it reaches a saturation point (Ting, 2017a). In view of this, the company has turned to alternative strategies to continue to increase supply. It is now targeting property developers to turn entire buildings into potential Airbnb units, through its newest hotel-like brand, Niido. Currently, there are two Airbnb branded Niido buildings in Nashville, TN and Orlando, FL with over 300 units each and Airbnb plans to have as many as 14 home-sharing properties by 2020 (Zaleski, 2018). Niido works by encouraging tenants to list their units on Airbnb, with Airbnb and Niido taking 25% of the revenue generated.  Airbnb has also clearly evolved from its original premise of “targeting a different market” to attracting segments traditionally targeted by hotels, such as the leisure family market, business travelers, and the upscale traveler, as evidenced through its latest offering, Airbnb Plus. These homes have been verified for quality, comfort, design, maintenance, and the amenities they offer. They also have easy check in, premium internet access, and fully equipped kitchens. Their hosts are typically rated 4.8+, and go above and beyond for their guests. Through Airbnb Experiences, travelers can partake in everything from the great outdoors—hiking and surfing—to “hidden” concerts and food and wine tours.  In addition to these products, Airbnb has also “created” its own segments of travelers: novelty and experience seekers who are looking for unique and unconventional accommodation like yurts, treehouses, and boats, all things that a traditional hotel company cannot provide.

 

The Present: Understanding what consumers want lies at the heart of the battle between hotels and Airbnb

There are larger societal trends that are impacting what consumers seek travel, and we think this has implications for the Airbnb and hotel dynamic. These trends include:

  • A shift to a “new luxury”—seeking out unique, authentic experiences that serve as a launchpad for self-actualization—fueled by an increased wealth gap in the United States.
  • An increased mobility, particularly among previously under-represented groups in the United States (the black travel movement, for example) and the global traveler (more Indian and Chinese international travelers than ever before).
  • The changing nature of brand loyalty: from long-term relationships to consumers’ needs for instant gratification and personalization.
  • Changing nature of “ownership”: In a post-consumerist society, the emphasis on “access-based consumption” has put a spotlight on wellness and well-being, beyond materialism.
  • A co-everything world where work, play, and life blend into one seamless mosaic: Technology has changed the way we live our lives, and how we are connected to work, to each other and to the things that drive us. An upcoming 5G world and the IOT is only likely to accelerate the pace of change. Take LiveZoku (https://livezoku.com/), for example: is it a residence? A hotel? A WeWork? A space for the local community? A thriving food and beverage destination? It’s all of these things.

What do these trends mean? They require marketers and experience designers to re-think what the travel experience means to the customer. The notion of the experience economy was created by Pine and Gilmore in 1998, and included four dimensions: escapism, education, entertainment, and esthetic. Leveraging one, or ideally, more of these dimensions creates memorable experiences for customers, which in turn results in brand loyalty. This dynamic has been fairly well-established in the academic literature. However, Airbnb has changed the game for the experience economy by emphasizing the sharing lifestyle and a sense of community, cleverly incorporating the above highlighted trends into its communications with customers. Because of Airbnb popularity and success, six new dimensions have been incorporated into the experience economy, in the context of the travel experience: personalization, communitas, localness, hospitableness, serendipity, and ethical consumerism, as was presented by Mody in 2016.

Interestingly, in a recent study by Mody and colleagues (Mody, Suess, & Lehto, 2017), the researchers found that Airbnb outperformed hotels on all the dimensions of this new, expanded, accommodation experiencescape. Airbnb outperforms hotels in the personalization dimension because of its wide array of homes and locations, enabling genuine micro-segmentation and the “perfect match” between guest and host (Dolnicar, 2018). Moreover, no one home is similar to another, giving customers a unique experience every time, enhancing the serendipity associated with an Airbnb stay. Airbnb elevates the sense of community that consumers seek, particularly when sharing space with other travelers and/or with the host, and allows consumers unparalleled access to “the local”—that café or cute little store that only locals know about. However, there are areas where hotels hold their own. For example, the pathways between these dimensions and memorability were just as strong for hotels as for Airbnb, emphasizing the need for hotels to engage customers by leveraging the “right” dimensions for the brand—dimensions that align with the brand’s mission, story, and personality.

One such dimension where hotels perform just as well as Airbnb is hospitableness, as confirmed in a study by Mody, Suess, and Lehto (2018). More “investor units” on the Airbnb platform means that the host is often not present when guests arrive to the home; moreover, all communication is done electronically and with someone who “manages” the Airbnb unit and doesn’t necessarily own or live in it. In turn, hotels that leverage the human factor—the welcome of a friendly check-in agent, the helpfulness of the concierge,  the warm greeting and genuine interaction between guest and food and beverage staff—create more positive emotions, which subsequently lead to higher brand loyalty. It is imperative that hotel brands really think about the high-tech, high touch experience they are looking to provide, particularly in the golden age of brand proliferation that we live in.

 

From a non-experience standpoint, regulation is another bone of contention that merits close inspection. After years of denying that Airbnb was a competitor, in 2016, the American Hotel & Lodging Association first began an extensive lobbying effort for the imposition of taxes and regulations on Airbnb that level the playing field. Over the last couple of years, the voices of the hotel lobby and other community groups have translated into governments taking some action, in the U.S. and abroad. However, in a study of regulation across 12 European and American cities, Nieuwland and van Melik (2018) found that governments have been fairly lenient towards short-term rentals with little to no (meaningful) regulations thus far. Moreover, regulations have been designed to alleviate the negative externalities of Airbnb on neighborhoods and communities rather than to level the playing field between Airbnb and hotels. Another challenge with regulating the peer to peer economy has been enforcement. In New York City, under the Multiple Dwelling law, it is illegal for a unit to be rented out for less than 30 days unless the owner is present in the unit at the time the guest is renting. However, it is still possible to find “entire homes” on Airbnb in New York City, even though, in principle, these typically include homes where the host is not present during the guest’s stay. Moreover, Nieuwland and van Melik (2018) and Hajibaba and Dolnicar (2017) have found that regulations tend to be very similar across cities, without accounting for the specificities of a particular location, which makes the process perfunctory and superficial. There also remains the danger of over-regulating Airbnb, given that there is still very little knowledge about effective ways of regulating these innovations in the sharing economy, thus stifling their potential. Avoid over-regulation is critical, since Airbnb has significant welfare effects in the economy. In addition to stimulating travel to previously inaccessible markets, Airbnb also creates customer surplus (Farronato & Fradkin, 2018), an important economic value measure. Moreover, other research has suggested that the average resident is not as negative towards the Airbnb as media rhetoric might suggest (Mody, Suess, & Dogru, 2018). The need for a data-driven approach to Airbnb regulation remains paramount.

 

The Future: Competing with the sharing economy requires re-thinking the brand and the experience

While regulation is outside the control of the hotel industry, the brand and the customer experience are not. We contend that these are the areas where hotel companies’ efforts need to be focused. Hotels need to re-think the brand promise, both for the parent brand as well as individual brands in the portfolio, and how it defines and shapes the guest experience. Recent research by Mody and Hanks (2018) indicates that while Airbnb leverages the authenticity of the travel experience—by enabling local experiences that provide a sense of self and sense of place, hotel brands that are perceived as being authentic—original, genuine, and sincere—can generate higher brand loyalty. Thus, while it’s hard to compete with homesharing in terms of experiential authenticity, brand authenticity is a pillar on which hotels can build a strong foundation for loyal brand relationships. This is particularly important because while Airbnb promotes experiential authenticity as a key reason to use the brand, most travelers tend to stay with the brand for much more functional requirements, such as space and price (Chen & Xie, 2017; Dogru & Pekin, 2017)

There is no one definition for or manifestation of an “authentic” brand. It’s a perception, a feeling that consumers have about what you stand for. An authentic brand has at its core the brand promise, an authentic value proposition that gives consumers a raison d’etre for associating with the brand. However, what an authentic brand does require is effective storytelling. A brand is perceived to be authentic, if it has an authentic story that feeds it. Brand stories can come from many sources: a brand’s values, personality, heritage, uniqueness, or its quest and purpose. What is important is telling compelling and coherent stories across the brand’s various touchpoints to engage consumers at a visceral, emotional level. Taking off industry blinders, and looking for inspiration outside the hotel industry, is critical. Tom’s Shoes is an excellent example of leveraging its quest—One for One—in creating a compelling brand story. As another example, in an industry typically focused on the in-store, “physical” experience, Burberry has set the gold standard for authentic, digitally-led and emotive storytelling, by looking within and leveraging over 150 years of history (Watch the YouTube Video here). In this vein, we think that Fairfield Inn and Suites’ return to “where it all began”—the Marriott family’s Fairfield Farm in the Blue Ridge Mountains of Virginia— to craft the brand experience of the future, from a design and communications standpoint, is an excellent example of leveraging authenticity and crafting a compelling brand promise (Ting, 2017b).

Another idea that lies at the heat of the brand promise is what we call the experiential value proposition, or EVP. For the longest time, hotel marketers have relied on the guest room as the primary source of value for the guest. But think about the last time you traveled. Was it the prospect of the hotel room that got you excited about your trip? Or was it everything that the hotel enables you to do – the experience outside the guestroom? From experiencing art and music in the lobby to its proximity to the must-do craft beer garden, hotel marketers must realize that it’s the complete package—what’s inside and outside the room—that customers use as cues for making  their decision to choose an accommodation. We call this proposition offered by the hotel—what’s inside and outside the guest room, enclosed within an experience of hospitableness and a connection to humanity—its EVP. We present the EVP in Figure 1.  The EVP mirrors the value paradigm of the modern traveler, something that must be reflected in the hotel brand’s sales, marketing and pricing and revenue management efforts. Thinking about a brand through the lens of the EVP paradigm has the power to re-orient the customer’s mindset from one of price-shopping to experience-shopping.

 Figure 1. The Experiential Value Proposition Framework

How does a hotel marketer apply the EVP paradigm? Its application can open up many avenues. Hotels can start by rethinking the design of their primary digital channels, led by the website by adding more rich, vivid content that goes beyond the guestroom, in order to better integrate aspects of the wider hotel and local experience. The Standard Hotels serves as an excellent example (http://www.standardhotels.com/) Its website feels more like a local lifestyle and culture magazine than a digital media property “selling” a hotel room. The website’s rich images and stories draw the visitor into wanting to learn more about what the brand has to offer. While not every hotel can or would want to go the Standard way, since the brand has its own distinct voice and personality, there is a case to be made for going beyond static images of beds in guestrooms, which tend to blend into one indistinguishable whole after a point, particularly on OTA websites. When was the last time the image of a hotel bed excited you to want to stay there? Yet, when you look at the imagery put out by most hotels, this is what marketers still focus on.

Placing an emphasis on humanity and providing a sense of hospitableness can also enhance a brand’s EVP. Instead of technology replacing the human connection, the industry needs to look for ways in which technology can actually free up employees so that they can spend their time crafting more personal and unique experiences, delighting guests instead of performing routine transactions. Moreover, if the human connection is what people seek out when traveling with Airbnb, why is it that hotel confirmation emails still get sent out by automated systems that highlight the “facelessness” of the hotel entity. Why not use that as an opportunity to truly welcome the guest; a simple touch such as a welcome letter from the GM with his/her photo, or that of an employee who is “assigned” as “your personal host” during your stay can go a long way in emulating the human connection that the sharing economy enables.

The design of the hotel’s public spaces can be used to enhance the guest’s experience of “communitas”. Ian Schrager would agree (Schaal, 2017). After all, with much of Airbnb’s supply being dominated by investor units that provide little or no host contact, what better an opportunity for hotel brands to show that they are the original connectors of human beings? Sheraton has been wise in incorporating some of these communal elements into its brand makeover by introducing productivity tables and studio spaces and a day-time coffee bar that transforms into a bar at night. In terms of another design element, Airbnb’s attractiveness to family and group travelers can be offset by offering connecting and/or multiple rooms for one price, with other experience value-adds thrown in (as with the Marriott family room connecting rooms package.

Finally, the role of the loyalty program cannot be emphasized enough. Loyalty programs must move beyond programmatic levels to being able to leverage data from guest history, social media, and other marketing data sources, powered by predictive analytics, to personalize and individualize the guest experience of the brand. In an age of instant gratification, the loyalty program has to be gamified to unlock value-adds and offer creative bundling.

At the level of the hotel company, beyond the individual brand, the hotel industry has started participating in the home sharing business and is increasingly looking to integrate these platform business models. For example, while Accor purchased Onefinestay, Marriott has teamed up with Hostmaker to create Tribute Portfolio Homes, a partnership that was recently expanded to four European cities (Fox, 2018). From an organic brand development standpoint, Accor’s newest Jo & Joe brand mimics the sharing economy within the confines of a traditional hotel space. Other, more innovative and bold ways of integrating the sharing economy ethos into a hotel could include offering an “Airbnb floor”, an antithesis to the club floor, one that would not offer housekeeping and other hotel services and thus be offered at a lower price. With hotel brands becoming “branded marketplaces” for accommodation and not just hotel rooms, perhaps there is merit in listing hotel rooms on alternative accommodation platforms. HomeAway is already adding hotels to its platform through the Expedia Affiliate Network, while Airbnb is making a push for bed-and-breakfasts and boutique hotels. Homesharing providers hope that by adding these options to their listings, they will fulfill their goal of being “for everyone”, while allowing independent and boutique hotels to reap the benefits of branded distribution at a lower cost than traditional OTA brands.

In sum, hotels must adopt a sales, marketing, and revenue management approach that is both strategic and tactical.

At a strategic level, hotel brands need to re-think their story, and how they portray and fulfill their authenticity and brand promises. At a tactical level, it’s the experience and value beyond the guestroom that must be factored into what is presented to current and potential guests, what they are charged for it, and how it is leverage to create “memorable memories” that lead to higher net promotor scores and brand loyalty. We present a graphical summary of the past, present, and future of Airbnb vs. hotels in Figure 2.

Figure 2. Summarizing the past, present and future of Airbnb vs. hotels


PDF Version Available Here


References
Chen, Y., & Xie, K. (2017). Consumer valuation of Airbnb listings: a hedonic pricing approach. International Journal of Contemporary Hospitality Management, 29(9), 2405–2424. http://doi.org/10.1108/IJCHM-10-2016-0606
Dogru, T., Mody, M., & Suess, C. (2018). Adding evidence to the debate: Quantifying Airbnb’s disruptive impact on ten key hotel markets.
Dogru, T., & Pekin, O. (2017). What do guests value most in Airbnb accommodations? An application of the hedonic pricing approach. Boston Hospitality Review.
Dolnicar, S. (2018). Unique Features of Peer-to-Peer Accommodation Networks. In S. Dolnicar (Ed.), Peer-to-Peer Accommodation Networks: Pushing the boundaries (pp. 1–14). Oxford: Goodfellow Publishers Ltd.
Farronato, C., & Fradkin, A. (2018). The Welfare Effects of Peer Entry in the Accommodation Market: The Case of Airbnb.
Fox, J. (2018). Marriott expands homesharing program in Europe. Hotel Management. Retrieved from https://www.hotelmanagement.net/own/marriott-expands-homesharing-program-to-3-european-cities
Hajibaba, H., & Dolnicar, S. (2017). Regulatory Reactions Around the World. In S. Dolnicar (Ed.), Peer-to-Peer Accommodation Networks: Pushing the boundaries (pp. 120–136). Oxford: Goodfellow Publishers Ltd.
Lane, J., & Woodworth, M. (2016). The Sharing Economy Checks In: An Analysis of Airbnb in the United States. Retrieved from http://www.cbrehotels.com/EN/Research/Pages/An-Analysis-of-Airbnb-in-the-United-States.aspx
Mody, M. A., Suess, C., & Lehto, X. (2017). The accommodation experiencescape: a comparative assessment of hotels and Airbnb. International Journal of Contemporary Hospitality Management, 29(9), 2377–2404. http://doi.org/10.1108/IJCHM-09-2016-0501
Mody, M., & Hanks, L. (2018). Parallel pathways to brand loyalty: Mapping the consequences of authentic consumption experiences for hotels and Airbnb.
Mody, M., Suess, C., & Dogru, T. (2018). Not in my backyard? Is the anti-Airbnb discourse truly warranted? Annals of Tourism Research. http://doi.org/10.1016/j.annals.2018.05.004
Mody, M., Suess, C., & Lehto, X. (2018). Going back to its roots : Can hospitableness provide hotels competitive advantage over the sharing economy ? International Journal of Hospitality Management. http://doi.org/10.1016/j.ijhm.2018.05.017
Nieuwland, S., & van Melik, R. (2018). Regulating Airbnb: how cities deal with perceived negative externalities of short-term rentals. Current Issues in Tourism, 0(0), 1–15. http://doi.org/10.1080/13683500.2018.1504899
Schaal, D. (2017). Ian Schrager Calls Out Hotel Industry’s Airbnb Strategy as Misguided. Skift. Retrieved from https://skift.com/2017/12/08/ian-schrager-calls-out-hotel-industrys-airbnb-strategy-as-misguided/
Ting, D. (2017a). Airbnb Growth Story Has a Plot Twist — A Saturation Point. Skift. Retrieved from https://skift.com/2017/11/15/airbnb-growth-story-has-a-plot-twist-a-saturation-point/
Ting, D. (2017b). Marriott and Choice Take Varied Approaches to Reviving Classic Midscale Brands. Skift.
Zaleski, O. (2018). Airbnb and Niido to Open as Many as 14 Home-Sharing Apartment Complexes by 2020. Retrieved from https://www.bloomberg.com/news/articles/2018-08-14/airbnb-and-niido-to-open-as-many-as-14-home-sharing-apartment-complexes-by-2020

Makarand Mody, Ph.D. has a varied industry background. He has worked with Hyatt Hotels Corporation in Mumbai as a Trainer and as a Quality Analyst with India’s erstwhile premier airline, Kingfisher Airlines. His most recent experience has been in the market research industry, where he worked as a qualitative research specialist with India’s leading provider of market research and insights, IMRB International. Makarand’s research is based on different aspects of marketing and consumer behavior within the hospitality and tourism industries. He is published in leading journals in the field, including the International Journal of Contemporary Hospitality Management, Tourism Management Perspectives, Tourism Analysis and the International Journal of Tourism Anthropology. His work involves the extensive use of inter and cross-disciplinary perspectives to understand hospitality and tourism phenomena. Makarand also serves as reviewer for several leading journals in the field. In fall 2015, he joined the faculty at the Boston University School of Hospitality Administration (SHA). He received his Ph.D. in Hospitality Management from Purdue University, and also holds a Master’s degree from the University of Strathclyde in Scotland.

 

Monica Gomez is a graduate student in the School of Hospitality Administration at Boston University. She received her Bachelor’s degree in Tourism, Recreation, and Sport Management from the University of Florida and has held previous internship positions in hotel operations and event management. She is a member of the Hospitality Sales and Marketing International Association and is interested in hotel revenue management.

How Does My Neighbor Feel About my Airbnb?

February 13th, 2018 in Finance, Hotels, Winter 2018 0 comments

 

By Makarand Mody, Courtney Suess & Tarik Dogru

The sharing economy and Airbnb in particular, has drawn significant media attention. A major disruptor to a global hospitality and tourism industry that remained relatively static for decades, the sharing economy has deeply divided its proponents and critics. The industry’s initial response was to shrug off the threat of the sharing economy by highlighting it as a fundamentally different business model serving a completely new set of customers and therefore not directly competing with the hotel industry. However, there is now growing evidence that Airbnb is fast emerging as a substitute to the conventional hotel product (Guttentag & Smith, 2017). This recognition among hoteliers has elicited sharp criticism of Airbnb, particularly in the United States.

The American Hotel & Lodging Association (AHLA) has been most vocal in its opposition to Airbnb, arguing that Airbnb does not play by the same rules as it does and thus has an unfair competitive advantage. Its argument against Airbnb has two key prongs: first, that Airbnb is filled with commercial operators who are quietly running “illegal hotels” out of residential buildings and that these and other Airbnb hosts are not levied and/or do not collect taxes, thus creating an unfair economic advantage for the company. Second, on the back of a spate of incidents reported in the media, the hotel industry argues that Airbnb is not held to the same safety and customer protection standards as it is, and can thus grow exponentially and unchecked (Benner, 2017).

Media Discourse

Relatedly, a great deal of media discourse has surrounded Airbnb’s negative impacts on destinations and communities. For example, a New York Times story highlights how “Airbnb pits neighbor against neighbor in tourist-friendly New Orleans” (Walker, 2016). Similarly, a headline in Australian publication The Chronicle reads “Residents powerless to stop Airbnb ‘party houses’” (Chung, 2017), illustrating how Airbnb threatens residents in their own neighborhoods. These unwilling residents are individuals who do not host themselves using Airbnb, but are often neighbors to those who do. Stories in the media have highlighted a host of resident complaints and concerns pertaining to Airbnb.  These issues include: the security threat posed by strangers in their backyard (“Airbnb Has Come to a Vermont Town and Some Residents Are Worried,” 2017), an undermining of job growth (“Illegal Hotels,” 2017), the disruption caused by “party houses” (“Nashville Residents Grapple With Their Own Airbnb Challenges,” 2017), and the museumization of neighborhoods that  character (Anderson, 2016). Many of these stories emphasize the negative impacts of Airbnb on residents’ quality of life in destinations across the world (Shankman, 2017).

 

While some of this discourse is perhaps warranted, much of it is anecdotal and/or selective in its representation of how residents at large feel about Airbnb. To date, there is little empirical evidence to make generalizable assertions of residents’ perceptions of Airbnb (Jordan & Moore, 2018). To address this gap, examination of how the average resident in the United States perceives Airbnb’s positive and negative impacts, how these perceptions influence residents’ sense of empowerment, and whether this empowerment (or lack thereof) has an impact on residents’ support for more Airbnb tourism was conducted. Residents were defined as those individuals who have never hosted using Airbnb themselves, but have and are aware of Airbnb activity in their neighborhoods. Following media discourse, it was hypothesized that:

H1: Residents perceive higher negative than positive impacts of Airbnb.

H2: Airbnb’s negative impacts make residents feel less empowered more so than Airbnb’s positive impacts increase residents’ sense of empowerment through Airbnb.

H3: Residents empowerment does not translate into support for Airbnb tourism.

Relatedly, if Airbnb’s negative impacts dampen residents’ sense of empowerment more than Airbnb’s positive impacts increase their sense of empowerment, as predicted by hypothesis 2, this dampening effect should carry forward into resident responses to Airbnb. With this in mind, a positive relationship should not exist between empowerment and residents’ support for Airbnb tourism, a relationship that has been previously validated in the literature.

Methodology

The sample for the study was drawn from an extensive panel provided by the online research company Qualtrics and consisted of residents who have never hosted using Airbnb themselves, but have and are aware of Airbnb activity in their neighborhoods. A total of 415 usable responses from residents across the United States was collected, including those who reside in urban, suburban, and rural settings.

Results

The profile of the respondents is presented in Table 1. Nearly two-thirds (64.3%) of the respondents were female. The majority of the sample was comprised of Millennials, between 18 and 34 years of age (42.4%), and members of Generation X, between 35 and 54 years of age (39.3%). Nearly half of the sample had a college degree (47.7%), with a large percentage having completed some level of formal university education (30.5%). A majority of respondents was Caucasian (77.1%), and nearly half of the sample had an annual household income of at least $60,000. Relevant to the context of the present study, a majority (61.2%) of the sample owned the accommodation in which they currently live, with nearly half of the respondents (47.9%) living in suburban settings.

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Most respondents (93%) indicated that they were aware of between 1 and 5 active Airbnb hosts in their neighborhoods and more than two-thirds (67.7%) felt that this was the right number of neighbors hosting on Airbnb. Only 9% felt that there were too many Airbnb hosts in their neighborhoods. It is also worth noting that more than two-thirds (67.7%) of the sample had never used Airbnb as guests themselves; these numbers are consistent with research reported by Morgan Stanley. These findings’ implications have two main points. First, despite high awareness levels of Airbnb, its adoption rates continue to be relatively slow (Ting, 2017a). Second, it seems as though the sample for the present study is likely to be representative of the general resident who is not overly biased towards Airbnb, neither positively due to having used the service extensively themselves, nor negatively through a perception that there is too much Airbnb activity in their neighborhoods. As previously indicated, it appears that most of the resident attitude discourse in popular media is based on anecdotal and/or selective evidence supporting a particular stance against Airbnb and does not provide a true assessment of residents’ perceptions of Airbnb. The findings thus allow for more data-driven and informative decisions about how residents truly perceive Airbnb to be made.

Table 1.  Respondent Profile

Demographic Category n = 415 %
Age
  18-25 79 19.0
26-34 97 23.4
35-54 163 39.3
  55-64 51 12.3
65 and over 25 6.0
Gender
  Male 148 35.7
  Female 267 64.3
Education
  High school 90 21.8
  Some college 126 30.5
  College 135 32.7
  Graduate school 62 15.0
Income
  Less than $15,000 41 9.9
  $15,000-$29,999 82 19.8
  $30,000-$59,999 127 30.6
  $60,000-$89,999 74 17.8
  $00,000-$119,999 51 12.2
  $120,000 or more 40 9.7
Ownership Status
  Own 161 38.8
  Rent 254 61.2
Neighborhood Setting
  Urban 112 27.0
  Suburban 199 47.9
  Rural 104 25.1
Airbnb Hosts in the Neighborhood (Attitudinal)
  Too few 97 23.3
  About the right numbers of

neighbors

281 67.7
  Too many 37 9.0
Airbnb Stays (as Guests)
  0 281 67.7
  1 or more 134 32.3

Table 2 presents the summary statistics for the items used to measure Airbnb’s positive and negative impacts, and the various other constructs used in the regression models. It is interesting to note that each of the individual items for the positive impacts are higher than each of the individual items for the negative impacts.

Table 2.  Summary Statistics and Literature Sources

(Items used to measure perceived positive and negative impacts)

Constructs and Measurement Itemsa Sample Size

(n = 415)

Mean SD
Positive impacts of Airbnb
  Creates opportunities for residents to participate in local culture 3.61 .95
  Fosters community pride 3.52 .97
  Fosters a feeling of belonging to the community 3.41 .96
  Enables an understanding of different cultures 3.64 .93
  Contributes to an improvement in neighborhood/housing appearance 3.66 .93
  Improves the local economy 3.82 .88
  Provides more business for local people and small businesses 3.85 .85
  Creates more job opportunities for local residents 3.65 .92
  Provides opportunities for cultural exchange between tourists and residents 3.70 .92
  Improves image of the community and culture 3.54 .95
  Helps improve the quality of community services such as local police, utilities, roads etc. 3.45 .97
  Provides incentives for the preservation/restoration of local/historic buildings 3.59 .94
  Positively impacts the cultural identity of the community 3.56 .95
  Tourism through Airbnb encourages development of a variety of cultural activities by local residents 3.66 .93
Negative impacts of Airbnb
  Leads to improper zoning/land use 2.85 1.09
  Makes the community less safe 2.71 1.13
  Increases the crime rate in the community 2.64 1.09
  Contributes to an increase in the cost of living 2.93 1.12
  Results in more vandalism 2.62 1.08
  Creates traffic problems in the community 2.89 1.11
  Increase in the number of Airbnb visitors results in noise and pollution/litter 2.95 1.14
  Negatively affects the community’s way of life 2.67 1.13
  Results in overcrowding and congestion 2.86 1.11
  Puts a burden on community services such as local police, utilities, roads etc. 2.83 1.08
  Makes the community too expensive to live in 2.70 1.08
  Leads to friction between local residents and visitors 2.75 1.07
  Increases the prices of buying and renting homes in the community, making it too expensive to live in 2.90 1.09
  Local residents are the ones who suffer from the development of Airbnb 2.82 1.08
  Airbnb visitors have little consideration for the local population 2.80 1.10
Psychological Empowerment
  Airbnb makes me proud to be a resident in my neighborhood 3.39 .92
  Airbnb makes me feel special because people travel to see my neighborhood’s unique features 3.38 .98
  Airbnb makes me want to tell others about what we have to offer in my neighborhood 3.40 .97
  Airbnb reminds me that I have a unique culture to share with visitors 3.57 1.00
  Airbnb makes me want to work to keep my neighborhood special 3.60 .97
Social Empowerment
  Airbnb makes me feel more connected to my neighborhood 3.21 1.05
  Airbnb fosters a sense of community spirit within me 3.27 1.06
  Airbnb provides ways for me to get involved in my neighborhood 3.28 1.04
Political Empowerment
  I have a voice in neighborhood decisions related to Airbnb development 2.99 1.09
  I have access to the decision making process when it comes to Airbnb in my neighborhood 2.98 1.08
  My vote makes a difference in how Airbnb is developed in my neighborhood 3.22 1.04
  I have an outlet to share my concerns about Airbnb in my neighborhood 3.30 1.04
Trust in Local Government
  I trust local elected officials to make the right decisions pertaining to the development and regulation of Airbnb 3.25 1.07
  I trust local government to do what is right in the case of Airbnb development and regulation 3.25 1.04
  I trust local government to look after the interests of the community as it pertains to Airbnb development and regulation 3.29 1.08
  I trust the decisions made by local government pertaining to the development and regulation of Airbnb 3.26 1.04
Support for Tourism
  Tourism helps my neighborhood grow in the right direction 3.59 1.03
  I am proud that tourists are coming to my neighborhood 3.64 .98
  Tourism continues to play an important economic role in my neighborhood 3.66 1.04
  I support the development of tourism as it is vital to my neighborhood 3.68 1.01
  My neighborhood should attract more tourists 3.54 1.04
Support for Airbnb
  Airbnb helps my neighborhood grow in the right direction 3.44 .90
  I am proud that Airbnb visitors are coming to my neighborhood 3.50 .92
  Airbnb will continue to play an important economic role in my neighborhood 3.57 94
  I support the development of Airbnb as it is vital to my neighborhood 3.47 1.00
  My neighborhood should attract more Airbnb visitors 3.43 .98

aMeasured on a 5 point Likert scale, where 1 = Strongly disagree and 5 = Strongly agree

Hypothesis 1 Testing

Airbnb’s positive impacts, as perceived by residents, was significantly higher than Airbnb’s perceived negative impacts (Positive impacts: x̅ = 3.62; Negative impacts: x̅ = 2.79; p < 0.001). Thus, evidence exists to contradict hypothesis 1; this finding is the opposite of what is often portrayed in the media.

Hypothesis 2 Testing

Table 3. Results of Regression 1: This table is representative of the dependent variables—i.e.  psychological empowerment and social empowerment—and their individual regression on Airbnb’s positive and negative impacts.

Coefficient Std. Error Standardized Coefficients (Beta) t Sig.
Dependent Variable: Psychological Empowerment (R2 = .696; Adjusted R2 = .695)
(Constant) .243 .153 1.594 .112
Positive Impacts .947 .032 .816 29.379 .000
Negative Impacts -.072 .027 -.075 -2.699 .007
 

Dependent Variable: Social Empowerment (R2 = .584; Adjusted R2 = .582)

(Constant) -.486 .205 -2.365 .019
Positive Impacts 1.024 .043 .767 23.616 .000
Negative Impacts .012 .036 .010 .323 .747


Table 4.
Results of Regression 2 (including control variables): Here the results of the second set of regression equations, in which the dependent variables were individually regressed on Airbnb’s positive and negative impacts, are recorded. This includes the control variables: age; gender; income; education; previous Airbnb use; perception of the number of Airbnb hosts in neighborhood; urban, rural, or suburban setting; perceived political empowerment; trust in local government; and general support for tourism.

Coefficient Std. Error Standardized Coefficients (Beta) t Sig.
Dependent Variable: Psychological Empowerment (R2 = .734; Adjusted R2 = .724)
(Constant) .398 .224 1.781 .076
Positive Impacts .744 .044 .641 16.790 .000
Negative Impacts -.092 .027 -.096 -3.451 .001
Age -.068 .021 -.089 -3.186 .002
Gender .038 .047 .022 .808 .419
Education .009 .025 .010 .348 .728
Income -.014 .010 -.045 -1.453 .147
Number of Airbnb hosts (attitudinal) -.009 .030 -.009 -.317 .751
Airbnb stay .082 .050 .045 1.633 .103
Urban .021 .063 .011 .329 .742
Suburban -.010 .056 -.006 -.176 .860
Own accommodation .017 .052 .010 .324 .746
Political empowerment .118 .029 .127 4.013 .000
Trust in local government .041 .025 .048 1.663 .097
Support for tourism .123 .033 .125 3.770 .000
 

Dependent Variable: Social Empowerment (R2 = .641; Adjusted R2 = .629)

(Constant) -.168 .299 -.562 .575
Positive Impacts .743 .059 .557 12.575 .000
Negative Impacts -.033 .036 -.030 -.918 .359
Age -.037 .029 -.042 -1.292 .197
Gender -.081 .063 -.040 -1.283 .200
Education -.011 .034 -.011 -.330 .742
Income -.030 .013 -.083 -2.302 .022
Number of Airbnb hosts (attitudinal) -.007 .040 -.005 -.166 .868
Airbnb stay .085 .067 .041 1.273 .204
Urban -.118 .084 -.054 -1.396 .164
Suburban -.080 .075 -.041 -1.074 .284
Own accommodation .021 .070 .011 .303 .762
Political empowerment .232 .039 .217 5.903 .000
Trust in local government .058 .033 .059 1.758 .080
Support for tourism .097 .044 .085 2.219 .027

The results for both regression equations (Tables 3 and 4) clearly indicate that the magnitude of the relationships between Airbnb’s positive impacts and residents’ psychological and social empowerment is significantly higher than that of the relationships between Airbnb’s negative impacts and residents’ psychological and social empowerment. In fact, Airbnb’s negative impacts do not significantly affect social empowerment in either set of equations. These findings contradict hypothesis 2, and further highlight the average resident’s generally positive disposition towards Airbnb, contrary to what is often portrayed in the media.

 

Table 4 also indicates the importance of political empowerment’s relationship to psychological and social empowerment. When residents perceive that they have a say in how Airbnb develops in their neighborhoods, this sense of empowerment works in conjunction with Airbnb’s perceived positive impacts to make residents feel psychologically and socially empowered vis-à-vis Airbnb. In fact, the magnitude of these associations between political, psychological, and social empowerment is stronger than that of the (negative) relationship between Airbnb’s negative impacts and residents’ empowerment. Moreover, these associations are found to hold true even after controlling for residents’ general support for tourism, indicating that the Airbnb phenomenon by itself elicits a generally positive response by the average resident, irrespective of how favorably they perceive tourism development as a whole. Relatedly, older residents perceived somewhat lower psychological empowerment, and those with higher income perceived marginally lower social empowerment. These marginal effects are unsurprising given the largely Millennial and Generation Z demographic that Airbnb as a brand would resonate with (Airbnb Citizen, 2017).

Hypothesis 3 Testing

Table 5 presents how support for Airbnb was regressed on psychological and social empowerment. Both psychological and social empowerment were significant predictors of residents’ support for Airbnb, indicating that there was no carry-forward dampening effect of Airbnb’s negative impacts, as predicted by hypothesis 3.

Table 5. Results of Regression 3: The dependent variable “support for Airbnb was regressed on psychological and social empowerment

Coefficient Std. Error Standardized Coefficients (Beta) t Sig.
Dependent Variable: Support for Airbnb (R2 = .688; Adjusted R2 = .687)
(Constant) .723 .095 7.581 .000
Psychological Empowerment .595 .045 .613 13.359 .000
Social Empowerment .213 .039 .253 5.512 .000


Implications

This study addresses the lack of empirical research on the impact of Airbnb on residents, as perceived by the residents themselves. It is a more representative account of the average resident in the United States and sets the foundation for future research on this important issue.

No evidence to support the hypotheses that underlie the rhetoric portrayed in the media against Airbnb was found. In fact, these observations support the opposite: that residents view Airbnb’s impacts positively more than they do negatively. Moreover, these positive impacts lead to residents feeling psychologically and socially empowered more strongly than the negative impacts detract from residents’ sense of empowerment. These relationships remained the same even after we controlled for a number of demographic and situational variables. Finally, both types of empowerment contribute to residents’ support for Airbnb, indicating their generally positive disposition towards the phenomenon.

These findings are particularly interesting in the context of the anti-Airbnb propaganda of the hotel industry, and Airbnb’s own public relations efforts, particularly through Airbnb Citizen, the company’s platform to showcase the power of home sharing as a “solution” that promotes positive economic, social, and community impact across the world (“Airbnb Citizen,” n.d.). The ongoing battle between the hotel industry and Airbnb “to win the hearts and minds of the American people” (Ting, 2017b) is one that is centered on creating the right kind of knowledge, one that supports or rejects Airbnb’s legitimacy. As is the case with marketing to customers, perception is reality. To advance its agenda, the hotel industry must ramp up its PR efforts at a time when jurisdictions across the country and the world are trying to determine the best way to regulate Airbnb and the sharing economy. Resident support can be a key factor in who wins this battle.

PDF Version Available Here


Mody
Makarand Mody, Ph.D. has a varied industry background. He has worked with Hyatt Hotels Corporation in Mumbai as a Trainer and as a Quality Analyst with India’s erstwhile premier airline, Kingfisher Airlines. His most recent experience has been in the market research industry, where he worked as a qualitative research specialist with India’s leading provider of market research and insights, IMRB International. Makarand’s research is based on different aspects of marketing and consumer behavior within the hospitality and tourism industries. He is published in leading journals in the field, including the International Journal of Contemporary Hospitality Management, Tourism Management Perspectives, Tourism Analysis and the International Journal of Tourism Anthropology. His work involves the extensive use of inter and cross-disciplinary perspectives to understand hospitality and tourism phenomena. Makarand also serves as reviewer for several leading journals in the field. In fall 2015, he joined the faculty at the Boston University School of Hospitality Administration (SHA). He received his Ph.D. in Hospitality Management from Purdue University, and also holds a Master’s degree from the University of Strathclyde in Scotland.

Suess Raeis New

Courtney Raeisinafchi, Ph.D spent 6 years designing and developing hotels and restaurants with Jordan Mozer and Associates, Ltd., an architecture firm based in Chicago, IL, after completing a bachelors degree at the School of the Art Institute of Chicago where she studied architecture. Some notable projects she was involved in includes Marriott’s Renaissance Hotel, Times Square and Hotel 57 in Manhattan, NY; both hotels have received the International Hotel , Motel and Restaurant Society’s Golden Key Awards for Best hotel design. While drafting new proposals for hospitality projects for Jordan Mozer and Associates in Southeast Asia, she began a masters degree, studying hospitality administration, at the University of Nevada, Las Vegas (UNLV) in Singapore. After graduating, she continued to complete her doctoral degree in Hospitality Administration at UNLV in Las Vegas and studied towards a second masters degree in architecture at UNLV’s School of Architecture. Courtney joined the Boston University School of Hospitality Administration in 2013, where taught the Design and Development Class as well as Lodging Operations and Technology. In 2017, she joined Texas A&M University Department of Recreation, Parks and Tourism Sciences as an Assistant Professor. She is an active quantitative researcher on the topics of hospitality development and built environments, as well as design and atmospherics impacts on consumer behavior.

Dogru Headshot

Tarik Dogru earned his Ph.D. in Hospitality Management from University of South Carolina, and holds Master’s degree in Business Administration from Zonguldak Karaelmas University in Turkey.Prior to joining the Boston University School of Hospitality Administration faculty, he was an adjunct faculty at University of South Carolina (2013-2016) and research assistant at Ahi Evran University (2009-2012) in Turkey. He has taught a variety of courses, including Economics, Finance, Accounting, Hospitality, and Tourism in business and hospitality schools. He is a Certified Hospitality Educator (CHE) and holds Certification in Hotel Industry Analytics (CHIA) from American Hotel & Lodging Educational Institute. Tarik’s research interests span a wide range of topics in hospitality finance, corporate finance, behavioral finance, real estate investment trusts (REITs), hotel investments, tourism economics, and climate change.

References

  • Airbnb Citizen. (n.d.). Retrieved January 12, 2018, from https://www.airbnbcitizen.com/
  • Airbnb Citizen. (2017). Airbnb’s highlights and 2017 trends we’re watching. Retrieved February 26, 2018 from https://www.airbnbcitizen.com/airbnbs-2016-highlights-and-2017-trends-were-watching/
  • Airbnb Has Come to a Vermont Town and Some Residents Are Worried. (2017). Skift. Retrieved from https://skift.com/2017/05/21/airbnb-has-come-to-a-vermont-town-and-some-residents-are-worried/
  • Anderson, B. (2016). How Airbnb Could Change Life for City Residents. The Wall Street Journal.
  • Benner, K. (2017). Inside the Hotel Industry’s Plan to Combat Airbnb. The New York Times. Retrieved from https://www.nytimes.com/2017/04/16/technology/inside-the-hotel-industrys-plan-to-combat-airbnb.html
  • Burdeau, C. (2016). New Orleans’ Growing Airbnb Inventory Sparks Debate Over City’s Soul. Skift.
  • Chung, F. (2017). Residents powerless to stop Airbnb “party houses.” The Chronicle.
  • Guttentag, D. A., & Smith, S. L. J. (2017). Assessing Airbnb as a disruptive innovation relative to hotels: Substitution and comparative performance expectations. International Journal of Hospitality Management, 64, 1–10. http://doi.org/10.1016/j.ijhm.2017.02.003
  • Illegal Hotels. (2017). Retrieved January 4, 2018, from https://www.ahla.com/issues/illegal-hotels
  • Jordan, E. J., & Moore, J. (2018). An in-depth exploration of residents’ perceived impacts of transient vacation rentals. Journal of Travel and Tourism Marketing, 35(1), 90–101. http://doi.org/10.1080/10548408.2017.1315844
  • Nashville Residents Grapple With Their Own Airbnb Challenges. (2017). Skift. Retrieved from https://skift.com/2017/01/07/nashville-residents-grapple-with-their-own-airbnb-challenges/
  • Shankman, S. (2017). Documentary: Barcelona and the Trials of 21st Century Overtourism. Skift. Retrieved from https://skift.com/2017/08/01/video-barcelona-and-the-trials-of-21st-century-overtourism/
  • Ting, D. (2017a). Airbnb Growth Story Has a Plot Twist — A Saturation Point. Skift. Retrieved from https://skift.com/2017/11/15/airbnb-growth-story-has-a-plot-twist-a-saturation-point/
  • Ting, D. (2017b). What’s Really Behind the Hotel Industry’s Plans to Combat Airbnb. Skift. Retrieved from https://skift.com/2017/04/18/whats-really-behind-the-hotel-industrys-plans-to-combat-airbnb/
  • Walker, R. (2016). Airbnb Pits Neighbor Against Neighbor in Tourist-Friendly New Orleans. The New York Times.

A (Diamond) Cut Above the Rest: Improving Hotel Operations Based on TripAdvisor Rating Attributes

October 5th, 2017 in Fall 2017, Hotels, Uncategorized 1 comment

The TripAdvisor Inc. homepage is displayed on a computer screen for a photograph in Tiskilwa, Illinois, U.S., on Tuesday, Oct. 22, 2013. TripAdvisor Inc. is scheduled to release earnings on Oct. 23, 2013. Photographer: Daniel Acker/Bloomberg via Getty Images

Photographer: Daniel Acker/Bloomberg via Getty Images

By Suzanne Bagnera

While TripAdvisor has been in operation since 2000 (TripAdvisor, 2012), the adoption of the website by hospitality industry professionals was rather delayed. However, in more recent years, hotel operators and other hospitality institutions have acknowledged the benefits that this service can provide and have embraced it more fully. With the advanced review management capabilities of the site’s dashboard, the ability to open a conversation between the innkeeper and the guest in a public social format has become available. The emergence of social technologies has created an environment in which businesses can be rated and reviewed in an open market for potential future customers to read, and the development of user-generated content has become a more trusted and credible source of product and service information. Lodging operators are now seeking best practices and ways to use these social platforms, including TripAdvisor, to their advantage.

A recent study by Dr. Suzanne Markham-Bagnera examined the impact that a posted online review rating has on the financial performance of a hotel room. The popularity ratings of hotels in the Boston, Massachusetts market, as posted on the popular online travel review website TripAdvisor, were analyzed against the hotel performance metrics of average daily rate (ADR), occupancy, and revenue per available room (RevPar). The study found that review attributes had varying levels of impact, all significant, on ADR, occupancy, and RevPar. Based on the luxurious nature of the lodging properties in Boston, value was found to be statistically significant across all categories analyzed.

boston-1448339_960_720

Hotel Classifications Systems

There is no international hotel rating or classification system. The two most commonly found in the US include the Forbes Travel Guide and the American Automobile Association (AAA). The Forbes Travel Guide provides ratings that are a combination of facility inspection scores and a service evaluation (Bagdan, 2013).

Hotel Attributes

Numerous attributes can be found in studies as they connect back to satisfaction. For the purposes of this study, the focal attributes will be those ranked on the TripAdvisor website: value, location, room, cleanliness, service, and staff.

1

 

2

Value

Value is essentially the price paid for the room, which often shapes the expectations for the experience. Frequently, it is identified in the text comment analysis of review studies as a negative factor.

Location

The old adage ‘location, location, location’ is crucial within the hospitality industry. The geographic location of a hotel is the most unchangeable attribute of a hotel, as it cannot be changed or improved by the staff once the property has been built, and generally, efforts to relocate are unlikely. A hotel’s proximity to public transportation services, the airport, city center, shops, restaurants, and tourist attractions are all key attractors for potential visitors.

Room

Room quality was found to be an influential determinant of customer satisfaction. Customers spend most of their time in their hotel room during their stay; hence, it can be viewed as the core of hotel service. Comments about the view from the room were one of the common themes discussed in reviews regarding location; these were followed by space, comfort, great beds, and cleanliness.

Cleanliness

Hotel cleanliness is an attribute that lies directly in the hands of hotel management and the employee initiatives to maintain it. Cleanliness was a controllable variable by the host and led to higher negative commentary in reviews when not addressed properly.

Service

The various service components that make customers satisfied may conversely make them dissatisfied if they are not provided or found to have delivery problems. Approximately 25% of the guest comments in the service experience category were accounted for in the staff category by having a friendly employee interaction. Customers typically refer to facilities, amenities, and conveniences offered by hotels to mean service (e.g., room upgrade, late check-out, umbrellas, special gifts, free shuttle, etc.).

Staff

Staff members that are both friendly and helpful upon first contact and throughout the stay generate a higher level of customer satisfaction. The most common components of both negative and positive reviews are the staff, in which specific comments that refer to attitude, misbehavior, lack of knowledge, and skill and passion can make or break the perception of the hotel. When a reviewer is providing a positive recommendation, they tend to focus on the staff performance with details, such as including names, and then go into the room details.

Results

This study examined the comparison of hotels based on their diamond level status, a designation awarded to each hotel by the third-party American Automobile Association (AAA). For this particular study, only hotels ranked between two-diamond to five-diamond were examined; Image 1 displays the details.

diamonds

Two-Diamond Hotels

In the ADR category, the room, staff, and overall variables provided an influence for two-diamond hotels. Occupancy percentage of two-diamond hotels only had two variables to provide an impact, which were location and value. RevPar had several variables that provided impact: value, location, staff, room, and overall.

In general, a two-diamond hotel should focus its efforts on ensuring that value is well appointed for the hotels. Location would be the second variable to focus on, and advertising location-centric advantages can drive the occupancy percentage and the RevPar in their competitive marketplace.

Three-Diamond Hotels

This status reflected four variables of impact on ADR: location, overall, value, and cleanliness. For the category of occupancy, the variables of value and overall had an impact. The variables to impact RevPar included value, overall, location, and cleanliness. When the rate charged was higher, the guest ranked the location lower for a three-diamond property. When guests found that the property did not meet their cleanliness expectations, the property was also typically charging a higher rate for their rooms.

For three-diamond hotels, value and overall proved to be two of the variables that operators should pay most attention to when they would like to be able to see an impact on their revenue operations.

Four-Diamond Hotels

The variables that provided an impact on ADR included value, location, staff, overall, cleanliness, and sleep.  This means, for example, that guests who encountered a hotel room that they felt was clean and afforded them a good sleeping experience were willing to accept a higher daily rate.

The occupancy category was impacted by the value as well as location. In terms of RevPar, the influential variables included value, location, staff, and cleanliness.

For four-diamond hotels, the two most important variables for a property to consider were value and their location. The positive aspects of location for these properties should be highlighted.

Five-Diamond Hotels

The room and overall variables were the primary factors that affected ADR.  This conclusion makes sense, since the guest of a luxury hotel is going to have high expectations for their room experience. When the ADR increased in a five-diamond hotel, the overall rating provided by guests decreased. The overall variable was also the only variable to impact occupancy; when the occupancy increased at the hotel, the guest provided a lower rating for the overall experience encountered. Several variables proved to influence RevPar, including room and overall.

There was a gap in the research on AAA diamond ranking of hotels in terms of customer satisfaction—for that matter, a gap also exists in the research on star rankings. This study concluded that a guest seeking a luxury hotel is searching for an experience that will exceed their expectations; hence, the overall rating is one of the most influential factors with their rating.

Attribute Discussion

The summary of all diamond levels compared to the TripAdvisor attributes can be seen in Table 2. In a five-diamond setting, a guest is seeking a more luxurious set of accommodations.  Hence, value is not a variable found to have an impact. Instead, both room and overall are more critical for this level of hotel. Once the diamond rank decreases, the value expected would increase. However, guests staying in properties ranked with two to four diamonds are expecting value for their stay across all dependent variables. The importance of location is most common amongst guests staying in a three- or four-diamond property.

Value was found to be the most important attribute to impact the financial performance of a hotel. The study indicates that the higher the value ranking, the higher the revenue potential to be recognized. Since a hotel cannot be relocated once built, it must focus on the marketing materials, distribution channels, and responses posted in online review portals in order to positively influence the location attribute, or at least the perception thereof. They should explain reasons for failed location due to poor public transportation experience, and they can capitalize on a good location in marketing materials.

The reason that a traveler is staying at the hotel is a factor to consider as well. A private tourist, a solo traveler, a couple, or a family may move to a variety of attractions, thus spending more time at other destinations; whereas a business traveler may not take part in tourist activities, hence staying at the destination hotel for a longer period of time.

Cleanliness is in the control of management, which must accordingly have strict cleaning standards. Supervisors should conduct inspections to ensure that what the guest sees meets their expectations. A decline in standards could have a direct negative impact on the financial performance of the hotel.

Direct Industry Example

In order to understand the practicality of this research as a tool for the lodging industry, we examined a specific hotel as an example. The Excelsior Hotel*, a prestigious hotel located in the city, is ranked as a three-diamond property. In this case, the top three focal attributes after value would be location, sleep, and overall.

The Hotel is a property challenged with offering value for its nightly rate, since, despites its excellent location in the city and historical connection, the average guestroom size is very small compared to other hotels in the city. However, they do offer numerous different types of rooms to their guests, so they need to market themselves well on this, as well as stress the location and its historical component. According to the, general manager, “the market research indicates that the highest ratings we earn come from a mother of a family with children that have come to the city to see the sites. They rate the hotel high on its location based on the historical nature of their visit and then how friendly the staff were to their needs. It is evident that these mothers have done their research prior to booking and are pleased with the location.”

While this property is rated by AAA as a three-diamond location, many of the guests tend to rate the hotel as though it were a four-diamond hotel. Based on the ratings found on public channels, “the bubbles available on the TripAdvisor website are found to be more valuable than the diamonds of AAA,” according to the Excelsior’s GM.   “Essentially, the higher the price, the more the guest expects for their money, regardless of the rating the hotel achieves,” the manager explains. The value attribute is where the balance must be found between what is charged and the interpretation of what is received by that guest, which supports the study of Markham-Bagnera (2016).

Given all of the above and insight from industry partners, I ask you to ponder these questions:

  1. Where does your hotel rank?
  2. What platforms do you consider to be the most relevant?
  3. What can you do to improve your financial performance based on the rated attributes on TripAdvisor

PDF Version Available Here

*The name of the hotel has been change to protect confidentiality.


BagneraSuzanne Markham Bagnera is Associate Clinical Professor at Boston University School of Hospitality Administration where she specializes in teaching hotel operations and human resources. She has held positions as General Manager at Holiday Inn Hotel & Suites, Staybridge Suites, and Holiday Inn Express. She has been an adjunct instructor for the Masters program in Hospitality Management at Johnson & Wales University and was previously an Assistant Professor at Endicott College in the School of Hospitality Management. Prior to that, she was the Program Director of the Hospitality Management program at Mount Ida College and has also taught classes at Bunker Hill Community College in the Hotel & Restaurant Management Department and for the Massachusetts Lodging Association (MLA). Presently she is on the Board of Directors for the MLA’s Education Foundation and serves as the Chairperson on their Educational Committee. She is a member of the International Council of Hotel, Restaurant, & Institutional Education (I-CHRIE) and serves as Secretary for the North East North American Federation, Nomination Committee member, Bylaw Committee member, in addition to several special interest groups. She is the Social Media Coordinator for the International Hospitality Information and Technology Association (iHITA). Suzanne serves as a peer reviewer for the Journal of Hospitality and Tourism Technology and for multiple special interest groups for the I-CHRIE annual conference. She holds numerous certifications in hospitality training; Certified Hotel Administrator (CHA) and ServSafe. Suzanne earned her M.B.A. in Management and B.S. in Hotel/Restaurant Management from Johnson & Wales University where she graduated Summa Cum Laude with membership into the Eta Sigma Delta honor society. In October 2016, she received her doctorate from Iowa State University in Hospitality Management. Her dissertation topic examined the impact that hotel reviews on TripAdvisor have on the revenue in the Boston market of hotels. Her area of research interest includes customer service, training, teamwork, and lodging operation management.
References
American Automobile Association. (2016, January). Diamond ratings: Hotel facts 2016. Retrieved July 14, 2016, from http://newsroom.aaa.com/diamond-ratings/
American Automobile Association. (n.d.). Diamond rating definitions [AAA]. Retrieved July 14, 2016, from http://www.aaa.com/AAA/Publishing/Diamonds/2015/images/hotel_rating_full_definition.png
Bagdan, P. (2013). Guest Service in the Hospitality Industry (First). Hoboken, New Jersey: Wiley.
Madlberger, M. (2014). Through the eyes of the traveler: Consumer evaluation of hotels in eastern European capitals compared with Western, Southern, and Northern Europe. Journal of Eastern European and Central Asian Research, 1(2), 1–9. https://doi.org/10.15549/jeecar.v1i2.65
Markham-Bagnera, S. D. (2016). An examination of online ratings on hotel performance indicators: An analysis of the Boston hotel market (Ph.D.). Iowa State University, United States — Iowa. Retrieved from http://search.proquest.com/docview/1860237612/abstract/378545CA6A25405CPQ/1
TripAdvisor. (2012, July 29). TripAdvisor fact sheet. Retrieved July 29, 2012, from http://www.tripadvisor.com/PressCenter-c4-Fact_Sheet.html

 

A Place for Everything and Everything in Its Place: The Application of Feng Shui to Hotels

October 5th, 2017 in Asia, Design, Fall 2017, Health and Wellness, History, Hotels, Real Estate, Uncategorized 1 comment

 

By Ingrid Lin

You wouldn’t build anything in most parts of Asia without having feng shui consultants come in and help you.” – Neil Jacobs, the president of global hotel operations for Starwood Capital.

Feng Shui:  real, phony, or magic?

The western world might consider feng shui to be a mystical and mysterious art, or perhaps even a sham, but an exploration of its origins reveal that it is neither of these—feng shui is both more nuanced and more relevant than most expect. Feng shui is an authentic, 3,000-year-old Chinese system of art and science practices that consists of a set of beliefs and rules regarding the inter-dependence and inter-influence of the person-environment fit. It can be viewed from many different perspectives, ranging from philosophical and psychological to spiritual to practical. The direct Chinese-English translation of “feng” means wind, and “shui” refers to water. Thus, the combined construct explains the interactive energy of wind and water, or “chi,” that flows through nature and the universe. Chi should not be impeded but balanced so that any negative forms (“sha chi” or poisoned arrows) may be offset with positive adjustments (Schaefer, n.d.).

Feng shui is used to identify features in individuals’ surroundings that make them feel relaxed and calm or, conversely, uneasy and irritable; basically, the practice suggests that individuals’ relationships with their surroundings is fundamental to their health and well-being.  Feng shui is not a religion, nor is it a magic. It is simply a set of principles that helps individuals to create a harmonious environment with optimal comfort and aesthetic satisfaction, thus leading to improved health and well-being. It also guides the placement of objects based on the flow of chi and on patterns of yin and yang.  All phenomena in the universe are the result of endless interactions between the two opposing natures of yin and yang (Mak & So, 2010).

The Elements and Tools of Feng Shui

There are many schools of feng shui. The core concept of Feng Shui entails the five elements: metal, wood, water, fire, and earth. Each element is associated with specific color and direction (See Figure 1), which serve as a guide to enhance the flow of the energy and improve the balance of the five elements in the surrounding environment. The relationships among the five elements can enhance or disrupt good feng shui. Please see Table 1 for the specific applications of the five elements in hotel servicescape design.

Table 1. Application of the five elements of Feng Shui to promote positive hotel servicescape design and décor (Locke, n.d.; Tchi, 2017)

Element Meaning Direction Colors Shape Season Design & Décor Objects convey positive chi DON’Ts
1. Earth Trust, reliability, grounded, centered, balanced, sturdy, good at handling money. Center Light yellow, beige, peach, light brown Square Indian Summer Accessories & Artwork that features or depicts landscapes, earth; featuring touches of yellow, beige, or brown tone colors. As for selecting furniture, (e.g., select tables & seating that are square-shaped). Fabrics/texture: Plaid patterns Objects that are made out of crystals, ceramic, clay, brick, rock, sand Earth elements should not be incorporated in conference rooms if want to evoke challenging or controversial conversation.
2.Wood Growth, creativity, change, adventure, healing, new beginnings East Green, brown Rectangle Spring Accessories & Artwork that depicts plants, trees, flowers; featuring green color and rectangle-shaped tables.  Fabrics/texture: Flowers, vegetation, vertical stripes/cotton, linen, silk. Plants, flowers, trees, paper, any wooden or green items. Wood elements should not be incorporated too much if want to encourage conservative thinking and avoid risky endeavors.
3. Fire Inspiration, understanding, passion, motivation, positive action South Red, strong yellow, orange, magenta, reddish purple, pink Triangle Summer Accessories & Artwork that features or depicts animals ; decorating touches of red.  Fabrics/texture: Leather, real or faux fur, suede, wool, down-fill. Lamps, candles, sunlight, steeples, spires, or items that generate heat. Limit the use of fire elements if want to encourage rest (e.g., spa, guest room)
4. Water Introspection, wisdom, deep thought. North Black, blue Undulating winter Accessories that feature glass or water (e.g., waterwall). Artwork that depicts water scenes ; decorating touches of black or dark blue.  Fabrics/texture: swirls or wavy patterns. Things that made of glass; water fountains, or fountains, bird baths), curvy & winding paths. Water elements should be incorporated accordingly to the purpose of the space.  For example, avoid too much of the water elements in active public areas, as they tend to restrain lively, loud, and action-oriented behaviors.
5. Metal Precision, ethics, focus, control, concentration, appreciation of beauty & form, mortality West White, ivory, gray, silver, any metallic shade Circular or round Autumn Accessories & Artwork that feature metal or depict architectural elements (domes & arches).  Fabrics/texture: circles or metallic sheen.  Furniture: select circular-shaped tables. Architectural elements, any item made of metal, any round item, electrical item, concrete gold, silver, metal based coins, knives, pots, pans, metal trays, utensils. Metal elements should not be used if want to promote creative thinking or a relaxing environment.

Ancient Chinese masters rely on two useful tools, ba-gua and lo-pan, to practice feng shui. The direct translation of ba-gua from Chinese to English refers to eight divinatory trigrams or areas (See Figure 1). The eight areas include the following: (1) health and family (east); wealth and abundance (southeast); (3) fame and reputation (south); (4) love and marriage (southwest); (5) creativity and children (west); (6) helpful or supportive people and blessings (northwest); (7) career & path in life (north); and (8) spiritual growth and cultivation (northeast).  These areas correspond to the most important parts of an individual’s life and the areas that matter the most for health, happiness, and well-being.  Ba-gua presents the energy framework of the relationship between one’s space regarding specific areas of his or her life.

Another important tool that all feng shui masters use is lo-pan, which translates to “everything in a plate or a bowl.” Like a compass, lo-pan is used to define the eight areas of ba-gua and determine favorable or unfavorable areas, directions, and colors used between feng shui areas of a site in connection to specific areas of people’s lives. It decides what adjustments need to be made to create a good balance or enhance specific areas of the divinatory trigrams.

Different people have different sensitivities towards the influence of Feng Shui. Some people strongly believe in feng shui, practice the principles of it, and rely on it as a guide to maximize their luck and prosperity. Some treat feng-shui as part of their deep-rooted cultural identification and include its principles as part of their lifestyle and spiritual life. And there are still others who view feng shui as superstitious, unreal, or bizarre, so they choose to ignore completely, believe lightly, or treat is as a necessary evil. While it was once regarded as an obscure philosophy by westerners, feng shui is now a tool of the trade for real estate brokers and a marketing hook for hotel owners, investors, and operators to gain a competitive advantage while attracting Asian consumers.

What can feng shui do for hotel businesses?

Today, more and more businesses are turning to feng shui because it helps to build a foundation for stability, effectiveness, and prosperity in business. Besides hotels, companies such as Coca Cola, Orange, HSBC, and British Airways have all adopted feng shui in the past (Feng Shui London, n.d.). A list of hotels that incorporate feng shui design is listed in Tables 2 & 3.

Table 2. Hotels advertised as feng shui hotels

  1. Viana Hotel and Spa, Westbury, New York, USA
  2. Metropolitan Hotel, Vancouver Waterfront, Canada
  3. Melarose Feng Shui Hotel, Brandenburg Gate, Berlin
  4. De La Mer Feng Shui Hotel, Tel Aviv, Israel
  5. 414 Hotel, New York, New York, USA
  6. The Lucky Dragon Hotel and casino, Las Vegas, Nevada, USA

Table 3. Hotels that incorporate feng shui design

  1. The Peninsula Hotel, Hong Kong, China
  2. Hong Kong Shangri-La Hotel, Hong Kong, China
  3. Sheraton Hotel, Tianjin, China
  4. Gold Coast Hotel, Hainan, China
  5. Wangfu Hotel, Beijing, China
  6. Genting Hotel, Malaysia,
  7. Trump International Hotel, New York, New York, USA
  8. Baccarat Hotel & Residences, New York, New York, USA

Good feng shui is believed to help improve a company’s prosperity and success. Conversely, bad feng shui is believed to disrupt and detriment a business enterprise. A hotel’s business success depends highly on not only its management and operations, but also on the hotel’s feng shui and whether the hotel incorporated feng shui design appropriately.

There is very limited information relating to hotel feng shui design, with the exception of feng shui master Liu’s (2012) recommended strategies in Chinese. Based on Liu’s (2012) suggestions, the following includes a few practical applications and fundamental advice for hotel owners and operators to ensure the stability, effectiveness, and prosperity of their hotel operations

1.The location or construction site of the hotel

The feng shui design of the hotel site is closely related to its construction site and basic structure. The basic structure and the hotel’s surrounding environment in an urban location depends on the requirements and constraints of the overall urban design of the city, the history and culture of the surrounding buildings, the terrain and topography of the base, the main landscape, the roads, the water flow, and the layout of the hotel (Liu, 2012).

The front of the hotel should entail a widespread and spacious lobby that embraces the road “chi” or energy.  In order to select a prime location that will represent good fortune and a thriving residence, the hotel’s exterior appearance or outlook must have a clear cut and square shape design; this implies that guests coming into the open square space will fill the room and wealth will surge.

Lobby and Reception area in the 5-star Oberoi Mumbai Hotel at Nariman Point, Mumbai, formerly Bombay, Maharashtra, India (Photo by Tim Graham/Getty Images)

It is against the feng shui norm for a hotel front entrance to face ominous things. The hotel also should not face a narrow gap between two buildings, light pillars, traffic signs, trees,  other buildings or objects that contain sharp corners or angles (known as the “sharp shot evil”), chimneys, toilets, etc. If a hotel commits to any one form of evil, conflicts between hotel executives may arise more frequently than expected, strange occurrences will disrupt the smoothness of the operation again and again, and eventually, the business will fail.

The hotel also should not be located too closely to churches or temples because money and good luck will be difficult to gather. Because churches and temples are spiritual places of worship, the nearby “chi” will be disturbed and affect the ecology. Similarly, hotels also should not be built close to cemeteries or funeral homes, which are filled with negative yin “chi” and hence will inevitably cause adverse effects.

2. The position of the hotel front door or main entrance.

From the exterior design perspective, a hotel’s main entrance is of vital importance to determining the good fortune of the hotel, as it represents a channel between customers and the business. This accounts for thirty to fifty percent of the feng shui role. The door position also determines the popularity of the hotel. The best main entrance position will coordinate with the water direction to enhance the flow of chi; this promotes the wealth and popularity of the hotel.
The position of the front door should not fall between two words that appears on lo-pan because it represents falling and death. Further, it implies that the elements within the divinatory trigrams or “gua” will be chaotic; hence, it will cause trouble for the hotel.  The front entrance door also should not touch the stairs or elevators, nor should the door be located directly below the toilet or stove. These easily lead to a higher risk of illness and injury in employees and financial failure.

The design of the door should also be in line with the local climate conditions, people’s habits, religious beliefs, magnetic orientation, and hotel’s positioning requirements. For example, the Hong Kong Kowloon Peninsula Hotel door decoration is very modern in style.  The design of the door consists of a tall Chinese folk door god, it seems uncoordinated, but this door god has historical meanings. The original Peninsula Hotel was located in front of the old railway station site; the railway station got removed after the completion of the Hong Kong Cultural Center and Space Museum. The space museum is an egg-shaped building, it is facing the Peninsula Hotel, the hotel guests mentioned they often see ghosts appear above the egg-shaped building in the middle of the night; they described the scene as like a big graveyard.  This haunted mystery scared many visitors who would not dare to stay. Management attempted to reverse the downturn, but after several unsuccessful efforts, the management turned to feng shui masters.  The management was told that they had to follow the feng shui home of the will, and please the door god to exorcism. Sure enough, after following the feng shui tips to please the door god, the hotel business had since thrived and successful.

The Peninsula Hong Kong Hotel. Photo by  Justin Chin/Bloomberg via Getty Images

The lobby should be bright in style and decoration, as well as reflecting the local culture. If the front door leads directly to the front desk, it should add stone lions in the lobby to avoid evil happenings. Displays that depict unicorns, turtles, elephants, or Buddha figurines demonstrate bravery as well.

3. Guest room feng shui design

The feng shui of a hotel guest room can directly affect hotel operations. Service to guests is the core mission of the hotel; it is also the main source of hotel revenue. Thus, guest room feng shui design represents one of the most important aspects of the hotel design process throughout the entire project.

It is best to consider designing the guest rooms in the higher or upper part of the main building.  Dining, entertainment, leisure and other functional areas that tend to bring huge source of noise vibration such as a nightclub or a sports bar, must be strictly separated from the room area. The height of the room is generally 2.8 meters:  any taller and it will give the impression of emptiness, while too much lower may promote a sense of depression. The room decoration in general is recommended to utilize light-colored elements, since these promote wealth and create a calm and tranquil environment in which the guests can relax. Guest room design should also take advantage of all windows, natural light, and the landscape, so that guests feel comfortable and at ease (e.g., The Beijing Capital Hotel, Shanghai New Jinjiang Hotel, Shenzhen Bay Hotel, Hong Kong Mandarin Hotel).

 

The bathroom is also an important part of feng shui because it can directly affect the health of the guests. Good feng shui suggests that the bathroom door should not face the bed, nor should the upper floor of the bathroom pressure travel toward the headrest of the bed, or downstairs in the direction of the front desk, the administrative offices, the hotel restaurant, or the kitchen, because it will produce adverse consequences. Finally, small green flowers in the bathroom can improve the feng shui effect of the whole room

4. Front desk and cashier

Hotel operators should pay great attention to the position of the hotel front desk or cash register.  In addition, per feng shui principles, the back of the cash register must be a solid wall or cabinet, meaning the hotel can easily gain expert support and customer patronage to produce a booming business. The cashier should be placed on the mountain plate shown on the lo-pan compass  and on the hotel’s left side, the position of finance and wealth. Feng shui pays attention to the fact that “money should not be revealed explicitly,” so the money should be kept mysterious. If the cashier area lacks lighting and is located in a dark corner, its operating efficiency is expected to be poor, whereas lighting implies vibrancy and big profits.

5. Kitchen

Kitchen feng shui is also considered the core of the hotel and merits the recruitment and selection of skilled chefs, high-quality food, and work efficiency. The essence of the kitchen is fire, so the kitchen must avoid gold, which melts easily.  The stove needs to be placed in an unlucky position to suppress the fierce god; at the same time, the oven door must face toward the auspicious position to collect and accommodate positive chi.

6. Executive and administrative offices

Hotel executive and administrative offices are more auspicious if they are either square-shaped or rectangular-shaped, which imply cooperative employees, smooth hotel operations, a bright future, and prosperity for the hotel. The main door of the office should not face any stairs directly. This is called “door chongsha” and is considered the biggest feng shui taboo, as all the good energy will flow right through the door. It is also against good feng shui to have the front office door directly facing the back office door.

The office should provide bright and pleasant lighting to foster positive yang energy, energetic employees, and thriving performance. On the contrary, if the office lacks lighting, it can produce obstacles, low employee morale, disturbance to the business, and ultimately unfavorable business development and performance.

7. Hotel name, color, and style

The style, color tone, and name of the hotel are all considered part of the feng shui design elements. They are also part of the hotel’s cultural connotation, business ideas, and feng shui pattern summary and expression. The style and name of the hotel guide to the consumer culture, while the color tone can illustrate the interactive relationships among the five elements of feng shui. Of course, these and many other elements  show the convergence of the five elements of feng shui. Basically, in a way, all design elements incorporated into the hotel have some relationship with feng shui.

The Lucky Dragon Hotel & Casino in Las Vegas, Nevada includes a nine-story hotel with 203 rooms, 27,500 square feet of casino space and five Asian-inspired restaurants. The fire element is heavily represented through its bright red, yellow, and orange design elements.

Feng shui case studies: haunted hotels, symbols of success, and benefits of feng shui

The Grand Hyatt Hotel in Taipei, Taiwan, has been listed as one of the top ten haunted hotels in Taiwan: said to be built on a World War II military warehouse or execution ground, there are purportedly lingering restless spirits. Many guests claimed that they saw a ghost on the top floor and refused to ever stay there again. When this story went viral worldwide, the first thing that the hotel management did was to consult a reputable feng shui master and ask him to conduct a site evaluation and recommend possible solutions.  The feng shui master recommended hanging two Chinese calligraphy scrolls next to the elevator in the lobby and other specific areas of the hotel (e.g., some guest rooms) to avert those restless spirits. The Grand Hyatt Hotel has since undergone a complete revitalization and renovation of the entire hotel by incorporating feng shui.

Another example relates to a casino hotel in Las Vegas, where Chinese visitors refused to enter the casino via its front entrance (Frazier, 2012). According to one of the fundamental feng shui principles for any businesses, the position of the front door entrance accounts for a big portion of the success or failure of the hotel; and in the case of the MGM Grand Hotel in Las Vegas, the front entrance, which featured a huge lion’s mouth, nearly led it to failure. When the hotel first opened in 1993, many wealthy Chinese guests considered to the entryway’s decoration to be bad luck and would enter the casino through the side entrance or avoid the MGM Grand completely (Young, 2013).  Chinese visitors thought that the lion would eat them and/or their profits and believed that gambling in the MGM Grand guaranteed a definite loss. In 1998, the MGM Grand responded to the perception of bad feng shui and replaced its main entrance. A large bronze statue was added above the entrance to keep with the MGM lion theme, while not scaring away guests.

Now, the lion statue in front of the MGM Grand Hotel sits with a closed mouth.

Believe it or not, President Donald Trump has adopted feng shui strategies. He hired a father-daughter pair of feng shui masters, Tin-Sun and Pun-Yin (von Oldershausen, 2016). When Pun-Yin first saw the Trump International Hotel and Tower, she commented that the energy was extremely bad; she insisted that Trump must follow her directions completely (von Oldershausen, 2016). Trump complied, telling the New York Times in 1994: “It is just another element in which you can have the advantage over your competitors… Asians are becoming a big part of our market and this is something we can’t ignore” (von Oldershausen, 2016, p. 2).

Feng shui strategies to fix the Trump International’s bad energy included:

1. Placing a metal globe before the building to deflect the negative energy produced by the oncoming traffic in Columbus Circle. Pun-Yin said, “’The instability of energy caused by traffic coming at the building—it’s almost like bullets flying at you all the time. It’s not stable.  It’s not calm’” (von Oldershausen, 2016, p. 2).

2. Utilizing tea-colored glass for its exterior, which reflects the surrounding sky and would absorb the negative energy caused by the wind’s sway upon the building.

3. Changing the direction of the building’s entrance. Pun-Yin suggested the entrance of the building should face Central Park instead of Columbus Circle since Central Park is “the green dragon of New York City’” (von Oldershausen, 2016, p. 2).

The main entrance of Trump International Hotel and Tower (right of Columbus Circle) faces Central Park rather than Columbus Circle.

Finally, the Lucky Dragon Hotel and Casino, a 203-room boutique resort off the northern end of the Las Vegas Strip, was the first Asian-themed resort in Las Vegas that heavily implemented feng shui into the overall casino design to prevent and limit any negative superstitious beliefs (Pierson, 2016).  For example, “the rose-colored resort’s front entrance is designed in a dragon motif.  A feng shui master blessed its kitchens.  The main bar is eight-sided for good fortune” (Pierson, 2016, p. 1). Since the casino is funded heavily by the Chinese and their primary target market includes middle-class Chinese gamblers and Chinese Americans, the casino purposely avoided using the unlucky number four within the casino—guests will not find number four anywhere in the property (e.g., no fourth floor, no fours for room numbers, and no fours in the phone directory).

Conclusion

There is no scientific evidence to prove that implementing feng shui can change destiny like magic. However, businesses can simply view feng shui as a positive reinforcement of the relationship between the customer and the environment within the organization. If feng shui is applied correctly, the hotel should have a balanced and coordinated environment; it is supposed to accentuate operation efficiency, stable growth, and greater satisfaction from not only external customers, but also internal customers. Feng shui is supposed to induce an optimal, comfortable, and stress-free work environment while reducing the overall workload and employee absenteeism (Feng shui London, 2015).  More importantly, feng shui should also ensure a productive environment to increase output and profits, and to sharpen managers’ decision-making skills, encourage inspiration, motivation, and innovation.

All in all, the feng shui design system has been applied and emphasized more and more worldwide. Hotels do not have to follow the full complex path of feng shui principles, but can incorporate its main purpose of enhancing guests’ well-being by giving them peace, balance, and appreciation within the hotel environment. Should hotels implement feng shui and use it as a marketing tool? It can’t hurt; and perhaps it truly does have the potential to guide the currents of fortune for the hotels that embrace this design element.

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Ingrid Lin Cropped
Ingrid Y. Lin, is an Associate Professor of the School of Travel Industry Management at University of Hawai‘i at Mānoa and is an alumnus of Boston University School of Hospitality. Her area of expertise includes services/hospitality marketing and consumer behavior.  She teaches hospitality- and marketing-related courses at both the graduate and undergraduate level.  Her research work and interests include servicescape aesthetics and design, environmental psychology, sensory marketing, luxury marketing and branding, consumer experience (emotions, perception, evaluation, and behaviors), cross-cultural studies, inter-cultural service encounter, luxury resort spa management and education, consumer/tourists’ shopping behaviors, and restaurant tipping systems. Her publications can be found in several reputable business, hospitality and tourism journals.

References

The hotel industry’s Achilles Heel? Quantifying the negative impacts of Airbnb on Boston’s hotel performance

October 5th, 2017 in Fall 2017, Finance, Hotels, Sharing Economy 2 comments

Photo by Michael Ivins/Boston Red Sox/Getty Images

By Tarik Dogru, PhD, Makarand Mody, PhD, Courtney Suess, PhD

Airbnb is the largest firm in the sharing economy marketplace, with about 3 million listings, including entire homes, shared rooms, and private rooms—more than the world’s largest three hotel chains combined (IHG, Marriott, Hilton, 2.58 M listings). It has hosted about 50 million guests in 5 years, 30 million of whom were hosted in 2015 alone (Airbnb Summer Travel Report, 2015). Furthermore, Airbnb is valued at around $31 billion. Due to its meteoric rise in popularity and, more importantly, its uncalculated potential impact, it has been in the center of discussions in the world of hospitality and beyond. Specifically, Airbnb might negatively affect the hotel industry if visitors were to shift their demand from hotels to Airbnb accommodations. However, it is not clear whether Airbnb is taking a part from the existing pie or increasing the size of the pie itself.

The increasing number of Airbnb listings might also have undesirable effects on the residential housing market. Homeowners might simply turn their properties into Airbnb listings if they believe they could make more money, which may exacerbate already existing housing problems in cities (Lee, 2016). Furthermore, Airbnb could have an adverse impact on the residents’ quality of life because of nuisances caused by visitors.

The course and the magnitude of these impacts, however, do not go beyond speculation, with the exception of some empirical evidence on the economic impacts supporting both proponents and critics of Airbnb. The results from the most comprehensive study analyzing the effects of Airbnb on the hotel industry showed that a 1% increase in Airbnb listings decreases hotel revenue by 0.04% (Zervas, Proserpio, & Byers, 2016). However, a recent study conducted by STR reported that Airbnb listings did not affect hotel demand and revenues (Haywood, Mayock, Freitag, Owoo, & Fiorilla, 2017). As such, the jury is still out on this issue.

While there are limited studies from which to draw definite conclusions about the effects of Airbnb on the hotel industry, Airbnb founder Brian Chesky claims that the company does not directly compete with the hotel industry because Airbnb guests are not typical hotel customers, but rather those who would have stayed with friends and family during the regular course of their travels (Intelligence, 2017). Although Airbnb argues that it brings new visitors to the markets and that 70% of its listings are outside of hotel districts, a report by Morgan Stanley indicates that about 42% and 36% of Airbnb guests switched from hotels and bed and breakfasts, respectively, whereas only 31% of Airbnb guests are those who would have stayed with friends and family (Intelligence, 2017), thus countering Mr. Chesky’s claims. Furthermore, a recent study conducted in Los Angeles showed that more than 60% of the properties listed on Airbnb are solely used for commercial purposes and are thus excluded from the residential real estate market (Lee, 2016). According to a recent report by CBRE, revenue generated by hosts renting two or more units was about $1.8 billion, and hosts renting ten or more units generated $175 million in 13 major US markets in 2016 (CBRE, 2017).

Airbnb is considered to be one of the major competitors of the traditional lodging industry, considering its market share, value, and potential economic impacts. In a recent study, we analyzed whether Airbnb directly competes with hotels in Boston (see Dogru, Mody, & Suess, 2017). We simply compared Airbnb dynamics with those of the hotel market, including supply, demand, occupancy, ADR, RevPAR, and market share. This study was descriptive in nature mainly due to the unavailability of data and was thus limited in its ability to draw a conclusion about the causal effects of Airbnb on hotels in Boston. We have now obtained a comprehensive dataset that allows us to analyze the effects of Airbnb on hotels. Therefore, we examine the extent to which Airbnb supply affects hotel room revenues (RevPAR), average daily rate (ADR), and occupancy rates (OCC) in the Boston hotel market for the period between July 2008 and June 2017.

Airbnb and Hotel Data          

In our analyses, we consider Airbnb an alternative accommodations company to analyze the effects of Airbnb supply on hotels. The cumulative number of listings created (including entire homes and private and shared rooms) since the introduction of Airbnb constitutes Airbnb supply (hereafter referred to as “total cumulative listings”). Further, we also measure the cumulative number of listings created (including entire homes and private and shared rooms) since the introduction of Airbnb that were active within the past twelve months. That is, an Airbnb unit must have been rented at least once within the past twelve months to be included in our alternative measure of Airbnb supply (referred to hereafter as “active cumulative listings”).

The Airbnb data were obtained from Airdna, a company that provides data and analytics to entrepreneurs, investors, and academic researchers. Hotel data, inclusive of hotels within the Boston metropolitan statistical area (MSA), were provided by Smith Travel Research (STR). The Airbnb data also includes listings from MSA. Put simply, the Airbnb supply and Boston hotel market goes beyond the city of Boston and comprise hotels from the “Greater Boston” area.

Airbnb host Jennifer Lawrence offers a pull-out couch with nearby toiletries that she rents in the living room of her Somerville home on July 12, 2014. Photo source: Boston Globe.

Airbnb host Jennifer Lawrence offers a pull-out couch with nearby toiletries that she rents in the living room of her Somerville home on July 12, 2014. Photo source: Boston Globe.

Column 1 (i.e., All Listings) of Table 1 presents the cumulative total number of listings (i.e., Airbnb supply) as of June 2017, including entire homes, private rooms, and shared rooms, created from the introduction of Airbnb in Boston in July 2008. Column 5 of Table 1 presents the cumulative total Airbnb listings as of June 2017 that were created since the introduction of the Airbnb and were still active within the past 12 months. As the data shows, 16,160 out of 28,957 listings created were still active as of June 2017. Airbnb supply has increased dramatically from 4 units in July 2008 to 28,957units in June 2017. The extreme increase in Airbnb supply is due to the superior flexibility in adding existing residential properties in the market. Indeed, this gives an unfair advantage to Airbnb in competing against the hotel industry because adding a new hotel to the market might take several years.

Table 1. Total number of listings created from the introduction of Airbnb as of June 2017
Total cumulative listings Active cumulative listings*
Year All Listings (1) Entire Home

(2)

Private Room

(3)

Shared Room (4) All Active Listings (5) Entire Home (6) Private Room (7) Shared Room (8)
2008  4  2  2  –  3  2  1  –
2009  59  34  25  –  43  25  18  –
2010  169  90  79  –  119  60  59  –
2011  371  177  189  5  252  118  130  4
2012  861  432  414  15  526  265  253  8
2013  2,214  1,082  1,094  38  1,221  601  604  16
2014  6,295  3,162  3,009  124  2,673  1,372  1,267  34
2015  14,392  7,126  6,882  384  6,202  3,214  2,883  105
2016  23,981  11,890  11,389  702  13,980  7,149  6,498  333
2017  28,957  14,288  13,798  834  16,160  8,152  7,593  395
*Listings with at least one booking within the past 12 months as of June 2017

In addition to the total number of Airbnb listings, it is also important to see the extent to which entire homes, private rooms, and shared rooms constitute the total Airbnb supply. Columns 2, 3, and 4 of Table 1 present cumulative Airbnb supply for entire homes, private rooms, and shared rooms, while Columns 6,7, and 8 present respective figures for our alternative metric of Airbnb supply, active cumulative listings.

To put these figures in perspective, we present the percentages of the supply of entire homes, private rooms, and shared rooms since the introduction of Airbnb in Table 2. Entire home listings comprised the majority of the total listings in Airbnb in most years. While the number of shared rooms appears to be negligible, the supply of private rooms constitutes the second largest Airbnb supply in the market.

Table 2. The percentage of entire home, private room, and shared room listings in Airbnb
Total cumulative listings Active cumulative listings*
Year Entire Home Private Room Shared Room Entire Home Private Room Shared Room
2008 50% 50% 0.0% 66.6% 33.3% 0.0%
2009 57.6% 42.3% 0.0% 58.1% 41.8% 0.0%
2010 53.2% 46.7% 0.0% 50.4% 49.6% 0.0%
2011 47.7% 50.1% 1.3% 46.8% 51.5% 1.6%
2012 50.2% 48.1% 1.7% 50.3% 48.1% 1.5%
2013 48.8% 49.4% 1.7% 49.2% 49.4% 1.3%
2014 50.2% 47.8% 1.9% 51.3% 47.4% 1.2%
2015 49.5% 47.8% 2.6% 51.8% 46.4% 1.7%
2016 49.5% 47.4% 2.9% 51.1% 46.4% 2.4%
2017 49.3% 47.6% 2.89% 50.4% 46.9% 2.4%
*Listings with at least one booking within the past 12 months as of June 2017

 

While the number of listings has reached a striking level within a relatively short period of time, the speed at which new properties are added to the market is even more striking. Figure 1 presents the year-over-year change in Airbnb supply that has remained active within the past 12 months in Boston. Accordingly, the number of total listings that were still active as of June 2017 has increased dramatically by more than 100% each year. The ability to add existing residential properties to the market as part of the Airbnb property supply increases the potential for adverse effects on hotels. As an accommodations platform, Airbnb offers properties that are alternatives to hotels but does not play by the same rules as hoteliers. Adding properties with a pace of 100% increase every year makes hotels vulnerable to the adverse economic effects of Airbnb. Therefore, we further examined the extent to which Airbnb affects the key performance metrics for the hotel industry in Boston.

Figure 1. Year over year change in Airbnb supply

The percentages shown are the year-over-year supply changes in All active listings

The effects of Airbnb on Hotel RevPAR, ADR, and OCC

We utilized a panel data fixed effect regression technique to examine the effects of Airbnb supply on hotel revenues. Similar to the methodology employed in Zervas et al. (2016), we treated Airbnb supply as a variable intervention in time against hotel data in Boston. In particular, this technique allows for the analysis of Airbnb’s effects on hotel revenues by comparing differences in hotel revenues before and after Airbnb’s entry in Boston. We examine the effects of Airbnb supply on hotel room revenues using two measures of Airbnb supply. First, we use cumulative total Airbnb listings that were created since the introduction of Airbnb. Second, we use cumulative total Airbnb listings that were created since the introduction of Airbnb and were still active within 12 months prior to June 2017. We consider an Airbnb listing active if the unit had been booked at least once within the prior 12 months. We also include a number of control variables that might potentially affect hotel room revenues regardless of Airbnb’s entry in these markets. Specifically, we control for the effects of hotel room supply, number of employees in the hospitality sector, population, unemployment rate, and number of airport arrivals in Boston. Table 3 presents the results from the DD regression for the effects of Airbnb supply, both total and active Airbnb supply, on hotel RevPAR, ADR, and OCC.

Table 3. The effects of Airbnb on Hotel Performances in Boston
  Total Airbnb Supply Active Airbnb Supply
RevPAR ADR OCC RevPAR ADR OCC
Log Airbnb Supply -0.025a

(-4.64)

-0.019a

(-4.30)

-0.003c

(-1.67)

-0.027a

(-4.70)

-0.022a

(-4.86)

-0.002

(-1.22)

Log Hotel Supply -2.32a

(-5.75)

0.03

(0.09)

-1.55a

(-9.34)

-2.26a

(-5.66)

0.04 (0.13) -1.52a

(-9.23)

Log Population 1.98c

(1.70)

-0.96

(-1.01)

1.93a (4.00) 1.86

(1.59)

-1.10

(-1.18)

1.93a (3.99)
Log Hospitality Employees 2.13a

(4.91)

1.50a (4.28) 0.41b (2.30) 2.12a

(4.95)

1.61a (4.69) 0.35b (1.98)
Log Airport Arrivals 0.63a

(3.63)

0.26c (1.85) 0.25a (3.53) 0.64a

(3.71)

0.27c (1.95) 0.25a (3.53)
Unemployment Rate -0.05

(-0.04)

-0.74

(-0.81)

0.49

(1.05)

-0.02

(-0.02)

-0.52

(-0.58)

0.38

(0.83)

Constant -39.26a

(-2.84)

0.01

(0.00)

-24.71a

(-4.35)

-37.73a

(-2.74)

1.09 (0.10) -24.45a

(-4.29)

Adjusted R-Square 0.97 0.91 0.97 0.97 0.91 0.97
t-statistics are in parenthesis. a, b, and c denote 1%, 5%, and 10% statistical significance levels, respectively.

The results show that hotel RevPAR, ADR, and OCC were negatively affected by Airbnb. Specifically, a 1% increase in Airbnb supply decreases hotel RevPAR by 0.025% and ADR by 0.02%. These effects might be seen as marginal if Airbnb supply was increasing at only a 1% level. However, our data showed that Airbnb has been increasing more than 100% year-over-year. Thus, a 100% increase in Airbnb supply (as has been the case consistently since 2008) decreases hotel RevPAR by around 2.5%.

We further examined the effects of active Airbnb supply on hotel RevPAR because some of the existing listings might have been inactive and hence might not necessarily affect hotels. Nevertheless, the findings were similar to those of all Airbnb supply. That is, a 100% increase in Airbnb supply decreases hotel RevPAR by 2.7%.

In addition to the examination of Airbnb’s effect on overall Boston hotel market, we also analyzed the effects of Airbnb on the various hotel class segments. The results show that each class segment is negatively impacted by Airbnb. Specifically, a 1% increase in Airbnb decreases hotel RevPAR by 0.015%, 0.043%, 0.021%, 0.024%, 0.032%, and 0.034% in the economy, midscale, upscale, upper upscale, luxury, and independent hotel categories, respectively. Again, these effects might be considered minimal if Airbnb supply was increasing at only a 1% level, but Airbnb supply has been increasing by over 100% year-over-year. Therefore, a 100% increase in Airbnb supply (as has been the case consistently since 2008) decreases hotel RevPAR by 1.5%, 4.3%, 2.1%, 2.4%, 3.2%, and 3.4% in the economy, midscale, upscale, upper upscale, luxury, and independent hotel categories, respectively. Surprisingly and as opposed to the expectations, Airbnb seems to affect luxury hotels more than it affects economy-scale hotels. While midscale hotel room revenues are the most affected by Airbnb, independent hotel room revenues also receive a major hit from Airbnb.

Table 4. The effects of Airbnb on Hotel Performances in Boston: Scales
Economy Mid Upscale Upper Upscale Luxury Independent
Log Airbnb Supply -0.015b

(-2.36)

-0.043a

(-5.61)

-0.021a

(-3.47)

-0.024a

(-3.66)

-0.032a

(-3.68)

-0.034a

(-5.28)

Log Hotel Supply -4.12a

(-8.65)

-1.43b

(-2.62)

-1.67a

(-4.00)

-1.75a

(-3.76)

-3.71a

(-6.02)

-2.64a

(-5.78)

Log Population 2.38c

(1.71)

-0.04

(-0.03)

2.10c

(1.71)

-0.55

(-0.40)

1.32 (0.73) 2.38c

(1.78)

Log Hospitality Employees 2.51a

(4.92)

2.12a

(3.62)

1.59a

(3.54)

2.38a

(4.76)

2.40a (3.62) 2.43a

(4.97)

Log Airport Arrivals -0.82a

(-3.98)

0.37

(1.58)

0.51a

(2.81)

0.95a

(4.67)

0.76a (2.83) 0.67a

(3.38)

Unemployment Rate -3.28b

(-2.44)

-0.01 (0.00) -1.46

(-1.24)

1.10

(0.84)

-2.74

(-1.57)

1.14

(0.88)

Constant -0.61

(-0.04)

-8.01a

(-2.93)

-41.94a

(-2.91)

-6.31

(-0.39)

-11.26

(-0.53)

-47.14a

(-3.00)

Adjusted R-Square 0.95 0.95 0.96 0.96 0.95 0.97
t-statistics are in parenthesis. a, b, and c denote 1%, 5%, and 10% statistical significance levels, respectively.

Discussion and Conclusions

The results from the analyses on the effects of Airbnb on hotel room revenues showed that Airbnb significantly affects hotel room revenues. These effects are not only statistically but also economically significant. For example, in Boston, the 2.5% decrease in RevPAR would amount to a decrease of approximately $4.00 in RevPAR in 2016, given a 100% increase in Airbnb supply in Boston. Based on these results, the economic impact in terms of a loss of total hotel revenues would be $5.8 million in 2016 alone in Boston. The effects of Airbnb on hotel room revenues also influence tax revenues. That is, revenues lost by hotels are likely to reduce tax revenues for cities and local governments. The economic impacts of Airbnb might be better observed once the sharing economy market is regulated. Therefore, future studies are necessary to analyze the tax implications of Airbnb listings.

Nevertheless, Airbnb has become a major phenomenon as an alternative platform for potential hotel guests. Moreover, while Airbnb may provide economic benefits to consumers, it may also offer social benefits (Dogru & Pekin, 2017). Also, Airbnb accommodations may provide substantial economic and social benefits to the city of Boston if these listings are used to accommodate additional tourists. During peak seasons or in the cases of mega-events like the Olympics, the availability of supplementary Airbnb rentals may be more beneficial than building hotels that will later not be utilized at optimal levels (Dogru, 2016).

The sharing economy phenomenon and the economic, social, and technological changes fueling its growth have challenged the hotel industry to rethink its experiential value proposition to the customer (Mody, Suess, & Lehto, 2017). Therefore, traditional hotels should create more opportunities for unique experiences, post more photos of the hotel and guest rooms, provide a family friendly environment, and offer activities for families. In particular, hotel firms might offer alternative packages to attract Airbnb guests, especially when operating at lower occupancies.

This study was an overall investigation of Boston hotel market at the MSA level. Further analyses are necessary to investigate the effects of Airbnb at neighborhood and property levels. Also, additional analysis is required to determine the extent to which Airbnb’s effects on asset-heavy REITs or franchising and management companies vary. Most importantly, overall economic and social impacts of Airbnb on the greater economy (e.g.tax revenues and residents’ quality of life) need to be examined. Therefore, further investigations are necessary to measure the economic and social impacts of Airbnb.

Summary of key findings

  • Airbnb supply has increased dramatically and consistently by over 100% each year, between 2008 and 2017. The majority of this supply has been entire home listings. The flexibility and ease of adding new supply, owing to the lack of government regulation, gives Airbnb an unfair advantage in competing against the hotel industry, because adding a new hotel to the market might take several years.
  • Using a difference in difference (DD) regression analysis, and controlling for a variety of hotel demand and revenue drivers, we found that a 1% increase in Airbnb supply decreases hotel RevPAR by 0.025% and ADR by 0.02%. Thus, a 100% increase in Airbnb supply (as has been the case consistently since 2008) decreases hotel RevPAR by around 2.5%. The effects of “active” Airbnb supply on hotel revenue are higher (2.7% decrease in RevPAR).
  • Similarly, a 100% increase in Airbnb supply (as has been the case consistently since 2008) decreases hotel RevPAR by between 1.5% and 4.3% across the various hotel class segments. While the impact is most pronounced for midscale hotels (4.3%), somewhat surprisingly, luxury hotels have also taken a significant hit (3.2% decrease in RevPAR).
  • The loss in RevPAR has significant economic implications for the hotel industry. For example, the 2.5% decrease in RevPAR in 2016 alone would amount to a total loss in hotel revenues of $5.8 million in Boston and, consequently, a loss of taxation for city and state governments. Over time, at a 100% increase in Airbnb supply every year, these losses add up, and their resulting impacts on other economic vitality indicators for the industry, such as employment rate, and social impact indicators can be significant and must be examined in future research.

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Dogru Headshot

Tarik Dogru earned his Ph.D. in Hospitality Management from University of South Carolina, and holds Master’s degree in Business Administration from Zonguldak Karaelmas University in Turkey.Prior to joining the Boston University School of Hospitality Administration faculty, he was an adjunct faculty at University of South Carolina (2013-2016) and research assistant at Ahi Evran University (2009-2012) in Turkey. He has taught a variety of courses, including Economics, Finance, Accounting, Hospitality, and Tourism in business and hospitality schools. He is a Certified Hospitality Educator (CHE) and holds Certification in Hotel Industry Analytics (CHIA) from American Hotel & Lodging Educational Institute. Tarik’s research interests span a wide range of topics in hospitality finance, corporate finance, behavioral finance, real estate investment trusts (REITs), hotel investments, tourism economics, and climate change.

 

Mody
Makarand Mody, Ph.D. has a varied industry background. He has worked with Hyatt Hotels Corporation in Mumbai as a Trainer and as a Quality Analyst with India’s erstwhile premier airline, Kingfisher Airlines. His most recent experience has been in the market research industry, where he worked as a qualitative research specialist with India’s leading provider of market research and insights, IMRB International. Makarand’s research is based on different aspects of marketing and consumer behavior within the hospitality and tourism industries. He is published in leading journals in the field, including the International Journal of Contemporary Hospitality Management, Tourism Management Perspectives, Tourism Analysis and the International Journal of Tourism Anthropology. His work involves the extensive use of inter and cross-disciplinary perspectives to understand hospitality and tourism phenomena. Makarand also serves as reviewer for several leading journals in the field. In fall 2015, he joined the faculty at the Boston University School of Hospitality Administration (SHA). He received his Ph.D. in Hospitality Management from Purdue University, and also holds a Master’s degree from the University of Strathclyde in Scotland.

 

Suess Raeis New

Courtney Raeisinafchi, Ph.D spent 6 years designing and developing hotels and restaurants with Jordan Mozer and Associates, Ltd., an architecture firm based in Chicago, IL, after completing a bachelors degree at the School of the Art Institute of Chicago where she studied architecture. Some notable projects she was involved in includes Marriott’s Renaissance Hotel, Times Square and Hotel 57 in Manhattan, NY; both hotels have received the International Hotel , Motel and Restaurant Society’s Golden Key Awards for Best hotel design. While drafting new proposals for hospitality projects for Jordan Mozer and Associates in Southeast Asia, she began a masters degree, studying hospitality administration, at the University of Nevada, Las Vegas (UNLV) in Singapore. After graduating, she continued to complete her doctoral degree in Hospitality Administration at UNLV in Las Vegas and studied towards a second masters degree in architecture at UNLV’s School of Architecture. Courtney joined the Boston University School of Hospitality Administration in 2013, where taught the Design and Development Class as well as Lodging Operations and Technology. In 2017, she joined Texas A&M University Department of Recreation, Parks and Tourism Sciences as an Assistant Professor. She is an active quantitative researcher on the topics of hospitality development and built environments, as well as design and atmospherics impacts on consumer behavior.

References
  • CBRE. (2017). Hosts with Multiple Units – A Key Driver of Airbnb Growth. Retrieved from https://www.ahla.com/sites/default/files/CBRE_AirbnbStudy_2017.pdf
  • Dogru, T. (2016). Development of the Hotel Industry in China: Mega-Events, Opportunities, and Challenges. E-review of Tourism Research, 13.
  • Dogru, T., Mody, M., & Suess, C. (2017). Comparing apples and oranges? Examining the impacts of Airbnb on hotel performance in Boston. Boston Hospitality Review, 5(2).
  • Dogru, T., & Pekin, O. (2017). What do guests value most in Airbnb accommodations? An application of the hedonic pricing approach. 2017, 5(2).
  • Haywood, J., Mayock, P., Freitag, J., Owoo, K. A., & Fiorilla, B. (2017). Airbnb & Hotel Performance: An analysis of proprietary data in 13 global markets. Retrieved from http://www.str.com/Media/Default/Research/STR_AirbnbHotelPerformance.pdf
  • Intelligence, B. (Producer). (2017). Airbnb CEO speaks on disrupting hotel industry. Retrieved from http://www.businessinsider.com/airbnb-ceo-speaks-on-disrupting-hotel-industry-2017-3
  • Lee, D. (2016). How Airbnb Short-Term Rentals Exacerbate Los Angeles’s Affordable Housing Crisis: Analysis and Policy Recommendations. Harvard Law and Policy Review, 10, 229-253.
  • Mody, M., Suess, C., & Lehto, X. (2017). The Accommodations Experiencescape: A Comparative Assessment of Hotels and Airbnb. International Journal of Contemporary Hospitality Management.
  • Zervas, G., Proserpio, D., & Byers, J. W. (2016). The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry. Journal of Marketing Research, Research In-Press. doi:http://dx.doi.org/10.1509/jmr.15.0204