Digital transformation and revenue management: Evidence from the hotel industry

Abstract

To maximize their revenues and protect their market share against traditional competitors (e.g. formal lodging businesses) and disruptive business models (e.g. Airbnb), the lodging industry increasingly relies on technology in various operations. However, the extent to which hotels adopt technology innovation in their revenue management (RM) operations, as well as the benefits of and barriers for digitalization, remains unclear. Moreover, the possible impacts of digital transformation on the future of revenue managers’ professions have been largely overlooked in previous studies. Drawing on qualitative data collected through 23 semistructured interviews with revenue managers in luxury and upscale hotels across Jordan, the findings suggest that RM is going through digital transformation with different levels of sophistication. While acknowledging the benefits of digital transformation in saving time, supporting the decision-making process, and yielding more revenues, the high cost of RM software emerges as a key barrier for digital transformation. The findings also reveal that the automation of various manual heuristics in RM is far from being possible, and therefore, digital transformation is unlikely to pose a threat to the future of the RM profession.

Keywords

digital transformation hotel industry innovation in tourism revenue management RM software

Introduction

The transformative impacts of digital technologies are evident in almost all industries and business environments (Chanias et al., 2019; Matt et al., 2015). In particular, information technology has transformed the tourism and hospitality landscape (Sigala, 2018) disrupting traditional operational techniques and giving rise to more sophisticated big-data-based operational models (Benckendorff et al., 2019; Ivanov, 2019). Technology and its implications are becoming ever important for the effective application of revenue management (RM) as well. Considering the perishability of lodging services, the amount of data to be processed, the complexity of managing pricing across channels, and the changing consumer expectations (Cetin et al., 2016; Guadix et al., 2010), RM has a crucial role in hotels’ financial success (Emeksiz et al., 2006) and therefore has become more strategic and widespread (Kimes, 2017). The changing distribution landscape driven by the increasing dominance of online distribution channels, the rise of platform economy-based business models, and the ever-growing impact of user-generated content has forced hotels to reconsider their RM techniques and pricing strategies (Cross, 2016; Klein et al., 2020). Yet the extent and impact of digital transformation, the benefits of and barriers for implementing high technology-driven tools, and the dependency they create remain unexplored. Moreover, increasingly assisted by sophisticated software, the future of RM as a profession is also subject to debate. With these thoughts in mind, the current study sets itself to achieve three key objectives: (i) understanding the extent to which hotels adopt technology innovation (e.g. rate shoppers, channel managers, recommender systems) in their RM-related decisions, (ii) identifying the benefits of and barriers for adopting technology innovation in RM operations, and (iii) understanding revenue managers’ evaluations of the possible impacts of digital transformation on the future of their professions.

The study makes several key contributions. First, it responds to calls for more research, addressing service innovations in the tourism and hospitality industry (Buhalis et al., 2019), and adds to an emerging stream of research, exploring the readiness of hotels for digital transformation (Lam and Law, 2019). Specifically, the study responds to the need for more research investigating the role of technology in RM (Denizci Guillet and Mohammed, 2015) and the intersection between digitalization and human intervention in RM operations (Ivanov and Zhechev, 2012). Second, the study reports on the state-of-the-art of RM practices in the era of digital transformation and assesses the future of RM as a profession. Finally, the study makes an incremental contribution by drawing on the perceptions of hotel revenue managers in a maturing economy, that is, Jordan. This is important considering observations by some researchers (e.g. Denizci Guillet and Mohammed, 2015; Domingo-Carrillo et al., 2020; Ivanov and Ayas, 2017), confirming that much of the empirical investigation on RM has been conducted in mature economies.

The remainder of this article is organized as follows: we review the literature on digital transformation in hospitality in general and in RM operations in particular. Then, we describe our research design and data collection procedure. Following that, we present and discuss the results. Finally, we conclude the article with conclusions and suggestions of promising areas for future research.

Literature review

Digital transformation in the hospitality industry

The increasing dependence on digital technology is acknowledged in many industries and tourism is no exception (Buhalis et al., 2019; Camilleri, 2018). As a dynamic process of transforming firms’ core activities, processes, and revenue models by effectively leveraging digital technologies (Lam and Law, 2019), digital transformation has become essential for firms to achieve key business goals including improvement of service quality, cost reduction, gaining competitive edge, knowledge creation, and maximizing revenues (Camilleri, 2018; Cohen and Olsen, 2013; Lam and Law, 2019; Law et al., 2009; Xiang, 2018). Deploying technologies, changes in value creation, corporate structural changes, and financial aspects are regarded as the key dimensions of digital transformation (Matt et al., 2015). According to Hinings et al. (2018), digital transformation is the outcome of different digital innovations that bring about novel actors, structures, practices, and values, that can change, disrupt, or complement existing rules of the game within organizations or industries. The influence of these digital innovations is reflected in firms’ operational models as well as firms’ relationships with customers (Cobos et al., 2016; Reinartz et al., 2019).

From the operational perspective, traditional hospitality business operations have been subject to disruption by innovative tools including increasing dominance of online distribution channels (e.g. online travel agencies (OTAs)), peer-to-peer platforms (e.g. Airbnb), and the unprecedented diffusion of smartphones and apps. For instance, OTAs constituted an opportunity for hotels as they increased visibility (billboard effect) and demand (Raguseo et al., 2017). However, they started to capture a significant channel share through booking commissions and restrict price-setting freedom of hotels (Romero and Tejada, 2020; Sharma and Nicolau, 2019). Today, the concept of best price guarantee and providing incentives for guests booking directly through the hotel are examples of how hotels fight back against OTAs (Lee et al., 2013). Technological innovation has also reshaped and disrupted the rules of the game of both sides, supply and demand in the lodging sector. The most recent challenge has emerged with the huge peer-to-peer room supply in many destinations over the globe and the increasing demand for Airbnb accommodations. While innovation adoption by some traditional lodging in response to the peer-to-peer lodging market can damage, in some cases, the firm’s market value (Zach et al., 2020), many hotels have started using peer-to-peer platforms as distribution channels (Alrawadieh et al., in press; Koh and King, 2017). In addition to these developments, there has been a recent debate on service automation and robotics in hospitality (Ivanov, 2019). Therefore, digital transformation will be likely to change the way core services are provided in the hospitality industry.

From the firm–customer relationship perspective, however, there seems to be a clear shift of power from firms to customers with the increasing influence of social media and electronic word of mouth (eWOM) and the growing importance of online reputation management (Ai et al., 2019; Alrawadieh and Dincer, 2019; Aureli and Supino, 2017). This shift of power has led researchers to redefine several established concepts in business and management scholarship, such as customer relationship management and service experience. The current high digital connectivity has leveraged the importance of managing relationships with customers over all stages of customer journey. Online reviews and ratings have been widely acknowledged as influential factors impacting the bottom line of the hospitality businesses (Ye et al., 2009). Customers’ reviews can be also deployed in RM operations to understand customers’ preferences, perceptions, and behavior (Xu et al., 2019). According to Reinartz et al. (2019), digitalization has introduced new tools for value creation (and cocreation) that better address the customer’s needs.

To conclude, for hospitality businesses to exist and thrive in a highly competitive environment, digital transformation has become a necessity (Lam and Law, 2019). Without effective implementation of technological innovation in business operations and customer relationship management, meeting the evolving customer expectations is likely to be challenging. Whether this holds true for RM or not remains, however, unclear.

Digital transformation in RM

Initiated in airline companies to forecast demand and set prices accordingly (Kimes, 1989), RM has expanded to most sectors within the hospitality industry, including hotels, restaurants, spas, and banquet services (Choi and Kimes, 2002; Kimes, 1999). RM has been particularly implemented by perishable service providers to manage their inventories and yield greater revenues (Cetin et al., 2016; Guadix et al., 2010; Kimes and Wirtz, 2003). The core principle of RM lies in ensuring that the right inventory unit is matched to the right customer, at the right time and for the right price (Kimes, 2002). The importance of RM in maximizing profits and reducing costs has been acknowledged (Altin et al., 2017; Elliott, 2003). However, RM can be complicated and may involve some risks. For example, misleading forecasts on potential demand may eventually result in a financial loss for the hotel property because of either overbooked or unsold rooms (Law, 2004). More importantly, the growing number of distribution channels and third-party travel platforms, the rise of peer-to-peer business models, and the huge volume of user-generated content have been among the key factors challenging current RM practices and putting more pressure on RM managers. This situation has alleviated the importance of digital transformation in RM operations (Guadix et al., 2010; Kimes, 2016, 2017).

Deploying technology in RM key operations has become a necessity. According to Emeksiz et al. (2006), hotels that use specific software in their RM decisions have a strategic advantage over hotels that do not. Technology helps hotel RM managers improve the financial performance of their properties (Kimes, 2017) and is regarded as a key driver for successful RM (Queenan et al., 2011). To illustrate, big-data is used when shaping RM strategies and business strategies as a whole, in an attempt to make them both more customer-oriented (Noone et al., 2011). Thus, the usage of specific software to process large databases is crucial for the success of RM (Guadix et al., 2010; Hormby et al., 2010). The intersection between online ratings and revenue maximization is also confirmed (Nieto-Garcia et al., 2019). Xu et al. (2019) advocated that, for hotels to better understand guests’ needs and forecast future demand, online customer reviews should be utilized, and accurate records of past customer demand and room occupancy should be kept. However, the degree of RM system sophistication in the hotel industry is affected by some factors, including organizational structure and competitive environment (Xu et al., 2019). The role of RM software in adopting right pricing strategies, measuring performance indicators (Navío-Marco et al., 2018), and choosing appropriate policies when dealing with issues, such as overstay, late checkout, and overbooking (Aydin and Birbil, 2018), is also acknowledged. Therefore, technology is influential in changing the way RM is seen and how RM performance is measured (Kimes, 2011). According to Kimes (2011), the key functions of technology-driven RM include pricing, forecasting, budget, group decision, and marketing. Digitalization can also contribute to facilitating the implementation of loyalty programs in hotels to ensure customer satisfaction and help generate higher revenues (Ozturk and Hancer, 2015). Moreover, technology can help hoteliers adopt the right upselling strategies to increase revenues (Denizci Guillet, 2020). The future of RM is likely be transformed and key factors, including information technology, data analytics, and mobile technology, will arguably play a key role in this process (Kimes, 2017).

While digital transformation may be regarded inevitable for hotels, the costs associated with hardware, software, recruitment, and training can be key constraints that prevent some businesses from digitalizing their RM operational models (Rodríguez-Algeciras and Talón-Ballestero, 2017). In their recent study on five-, four-, and three-star hotels in Madrid, Abad et al. (2019) suggested that some hotels were reluctant to use advanced software because of the high cost. Similar findings were reported in other studies (e.g. Rodríguez-Algeciras and Talón-Ballestero, 2017; Talón-Ballestero and González-Serrano, 2013). Moreover, some hotels may prefer to wait before purchasing new technology given the financial risk of purchasing a product, which might be surpassed by other updated and developed products in a short time (Buhalis and Leung, 2018). The lack of qualified RM staff to make use of all these support systems was also discussed by Kimes (2011). However, with the advent of sophisticated but user-friendly technology and data-driven solutions, the rate of adopting technology in RM will likely increase (Karadjov and Farahmand, 2007) creating new opportunities or challenges for RM (Wang et al., 2015). Therefore, to remain competitive, hotels should know how to harness the power of new technologies (Lam and Law, 2019).

Disruptive role of digital transformation on hospitality professions

Digital transformation can potentially threaten and replace existing structures and roles within organizations (Hinings et al., 2018). Specifically, the increasing reliance on technology has posed serious questions regarding the future of several professions within the tourism and hospitality industry. Some researchers (e.g. Buhalis et al., 2019; Ivanov, 2019; Rebecca and Yeoman, 2012; Webster and Ivanov, 2020) predict that digital transformation and its implications, including artificial intelligence and robotics, will result in jobs shifting from human to nonhuman employees (e.g. replacing housekeepers by robot attendants), thus transforming tourism and hospitality from a labor-intensive industry into a technology-intensive industry. In fact, using robotics and artificial intelligence was found to increase employees’ turnover intention in the hotel industry (Li et al., 2019). Therefore, digitalization will affect some types of jobs while others might completely disappear (Makridakis, 2017; Navío-Marco et al., 2018), forcing employees to adjust themselves to the newly emerging requirements, knowledge, and skill sets (Crittenden et al., 2017). According to Styvén and Wallström (2019), some businesses may be reluctant to adopt digitalization because of the lack of skilled employees. To cope with new technological advancement, new types of jobs may also emerge in the future and demand for highly skilled employees is likely to increase (Navío-Marco et al., 2018).

In the specific context of RM, while the role of digitalization is acknowledged, the human factor in making RM decisions remains crucial. Schwartz and Cohen (2004) proposed that using technology is unlikely to eliminate the role of the human factor in RM. While Cleophas and Frank (2011) noted that sophisticated and automated systems can contribute to the success of RM, they advocated that dedicated software systems are not a prerequisite for applying RM. This is also confirmed in a recent study by Abad et al. (2019). According to this study, having access to specific RM software does not correlate with higher RM implementation in hotels. Cetin et al. (2016) suggested that some revenue managers may be afraid of being dependent on new RM systems when making decisions. Bobb and Veral (2008) proposed that a hybrid system where technology and humans interact is more functional in RM. Although there seems to be a consensus on the role of the human factor in RM, the need for more sophisticated skills and a tech-savvy mindset to achieve key goals of the RM is acknowledged. For instance, Kimes (2011) investigated the future of the RM profession by surveying RM professionals and concluded that the profession would be more strategic and more technology-oriented. In her more recent study, Kimes (2017) has confirmed the importance of analytical and communication skills in future RM managers. She also found that future RM managers should develop their knowledge in some fields like data analytics, pricing, distribution, statistics, economics, website optimization, and social media.

Although it may be possible to digitalize several decisions in the RM process, such as pricing and overbooking, the human factor remains essential for the success of RM in hotels (Ivanov and Ayas, 2017). Even a fully automated RM system is fed by enormous amount of data (e.g. demand history, forecast, conversion rate, and competitor information). Most of these data are uploaded into the system by staff. For example, consider a reservation request has been uploaded into the system on the next day using the wrong market code, (or a confirmed group status is kept as pending for 2 weeks), using this flawed data, the RM software will calculate an inaccurate lead time and make wrong pricing decision. However, whether digital transformation can represent a threat to the profession of RM in the future is still unknown. Moreover, as observed in a relatively recent literature review of RM research in hospitality by Denizci Guillet and Mohammed (2015), employees and HR issues have received little attention (only 5 studies of 158). By exploring revenue managers’ assessment of the future of their profession, the current investigation delves into a largely overlooked issue in RM research.

Lodging market in Jordan

As an emerging destination in the Middle East, Jordan has a small lodging market consisting of 434 graded accommodation establishments and 156 unclassified hotel, hostel, motel, and camps. These 590 facilities have over 30,360 rooms and a capacity of about 56,170 beds (MoTA, 2019). The formal room supply is also supported by a small informal accommodation market encouraged by the emerging peer-to-peer accommodation business models (Alrawadieh and Alrawadieh, 2018). With regard to the luxury and upscale hotels, currently, there are 37 five-star hotels based in Jordan’s key destinations: Amman (17 hotels), Petra (6 hotels), Aqaba (7 hotels), and the Dead Sea (7 hotels). Most of these hotels (25 hotels) are affiliated to international hotel chains, while the others are independent or local-brand hotels (Personal Communication with an official in Jordan Hotel Association, November 2019). The capacity of these hotels is about 15,100 beds, which accounts for over one-quarter of the total bed capacity in Jordan (MoTA, 2019). In 2018, Jordan’s five-star hotels hosted over 1,632,600 guests and sold over 2.596.500 nights achieving an occupancy rate of around 55% (MoTA, 2018). Over the past few years, the luxury and upscale hotel market has experienced fluctuating revenue per available room (RevPAR) due to the economic and political instability in the region coupled with the growth in room supply (Choufany, 2019).

Methodology

The scarcity of qualitative inquiry on RM has been noted by some scholars (e.g. Denizci Guillet and Mohammed, 2015; Domingo-Carrillo et al., 2020). More importantly, theoretical framework and empirical investigation on digital transformation in hotels are limited (Lam and Law, 2019). In particular, very little is known about digital transformation in RM practices. Therefore, the current study adopted a qualitative research approach using semistructured interviews with hotel revenue managers. The qualitative approach fits the exploratory nature of the current study and is useful in providing a preliminary theoretical foundation for further empirical investigations.

Considering that RM is adopted more by luxury and upscale hotels (Abad et al., 2019; Ivanov and Ayas, 2017; Rodríguez-Algeciras and Talón-Ballestero, 2017), the sample was deliberately chosen from upper-tier hotels in Jordan. Hence, all five-star hotels across Jordan (37 hotels in March 2019) were contacted either by email, phone, or in person. Revenue managers or, in the case such a position did not exist, management-level staff in charge of RM were invited to participate in the study. Thirty-five managers were reached and 28 accepted to give an appointment for a face-to-face interview. In a later stage, however, five managers were unable to dedicate time for a face-to-face interview (2) or preferred to provide written answers for the interview questions (3). With 23 in-depth interviews, the authors agreed that a satisfactory level of saturation had been achieved and thus conducting additional interviews would have added minimal insights (Glaser and Strauss, 1967).

Semistructured interviews were conducted over 3 weeks during July 2019. Almost all of the interviews were conducted in the managers’ respective hotels. The interviews were digitally recorded, with consent, and lasted an average of 33 min. The interview protocol included two sections. The first section aimed to collect demographic and organizational data about informants and the hotels where they were based. The second section included eight open-ended questions in line with the study’s objectives. Interview questions were developed based on mainstream literature on digital transformation (Hinings et al., 2018; Ivanov, 2019; Lam and Law, 2019; Matt et al., 2015) and literature on hotel RM (Abad et al., 2019; Emeksiz et al., 2006; Ivanov and Ayas, 2017; Rodríguez-Algeciras and Talón-Ballestero, 2017; Talón-Ballestero and González-Serrano, 2013). For instance, revenue managers were initially asked to talk about the history and intersection of RM and technology and the importance of digital transformation in RM. Managers were then asked whether they used any specific RM software, the benefits of such software, and the barriers for introducing them in hotels’ RM operations. Other questions were asked to explore managers’ perceptions about the future of their job as revenue managers. For instance, managers were enquired as to whether technology would reduce reliance on revenue managers and whether their professions could be threatened by digital transformation.

Almost all interviews were conducted in Arabic and translated into English by a bilingual speaker of English and Arabic while a small portion (four interviews) were conducted in English when informants had limited knowledge of Arabic (two) or preferred to speak in English (two). The 23 interviews were transcribed verbatim, yielding a 115-page MS Word file (about 55,000 words). A six-stage thematic content analysis was employed to analyze the interview data (Braun and Clarke, 2006). The first and second authors independently read the interview transcripts several times, discussed their findings, and agreed on the final findings presented in this study. To enhance the reliability and validity of the findings, the member checking technique was employed (Creswell and Miller, 2000). The informants were asked to review their respective interview transcriptions and the final findings. All participants agreed that the transcriptions were accurate and the narrative account was realistic.

Findings and discussion

Table 1 presents the demographic profile of hotel managers interviewed. Most participants were middle-aged males. On average, the managers had over 13 years of work experience in the hospitality industry, including an average of about 5.5 years in their current management positions. Most informants had a BA degree, typically in a field related to tourism and hospitality. Except for three hotels, all were affiliated with international chains. Using the typology of hotel RM implementation strategies suggested by Altin (2017), most hotels in the sample applied either mixed strategy or in-house RM. Unlike findings reported in other studies (Emeksiz et al., 2006; Ivanov and Ayas, 2017) and given that the sample was selected from luxury and upscale hotels, all hotels either had a revenue manager as an independent position or this responsibility was incorporated with other managerial positions, such as sales and marketing or reservation manager. Chain-affiliated hotels are also likely to have well-established RM practices and independent RM departments (Mauri, 2016).

Table 1.

Descriptive profile of the participants (revenue managers).

No.	Gender	Age	Education	Total work experience	Position	Time in current position	Type
P1	Female	40	College Diploma	12 years	Reservation and revenue manager	10 years	Independent hotel
P2	Male	40	BA	17 years	Sales and revenue manager	6 years	Chain-affiliated
P3	Male	33	BA	12 years	Director of revenue	8 years	Chain-affiliated
P4	Male	30	BA	9 years	Assistant revenue and reservation manager	5 years	Local brand
P5	Male	38	BA	17 years	Director of revenue	9 years	Chain-affiliated
P6	Male	25	BA	2 years	Marketing and revenue manager	1 year	Independent hotel
P7	Male	46	BA	12 years	Revenue manager	4 years	Independent hotel
P8	Male	40	BA	18 years	Revenue manager	4 years	Chain-affiliated
P9	Male	45	BA	23 years	Director of revenue	19 years	Chain-affiliated
P10	Male	39	BA	16 years	Director of revenue	6 years	Chain-affiliated
P11	Female	30	BA	8 years	Reservation and revenue management assistant	2 years	Chain-affiliated
P12	Male	37	High school	13 years	Director of revenue	2 years	Chain-affiliated
P13	Male	29	BA	13 years	Revenue analyst	5 years	Chain-affiliated
P14	Female	31	Master’s degree	5 years	Reservation and revenue management assistant	2 years	Chain-affiliated
P15	Male	35	BA	12 years	Area director of revenue	3 years	Chain-affiliated
P16	Male	34	BA	11 years	Cluster revenue manager	3 years	Chain-affiliated
P17	Male	38	College Diploma	13 years	Director of revenue	7 years	Chain-affiliated
P18	Male	38	BA	20 years	Cluster director of revenue	13 years	Chain-affiliated
P19	Male	42	BA	23 years	Director of revenue	3 years	Chain-affiliated
P20	Male	35	BA	16 years	Revenue manager	10 years	Chain-affiliated
P21	Male	38	College Diploma	18 years	Revenue manager	3 years	Chain-affiliated
P22	Male	34	BA	10 years	Director of revenue	1 year	Chain-affiliated
P23	Female	34	BA	14 years	Director of revenue and reservation	1 year	Chain-affiliated

State-of-the-art of digital transformation in RM

According to most revenue managers, RM as an independent department in hotels seems to be as recent as 2005 and afterward. Sales and marketing team and reservation managers were traditionally responsible for RM. P19 noted:

Revenue management [in Jordan’s hotels] started in 2007 […], before that, maximizing revenues was the responsibility of the front office and sales & marketing departments. Initially, revenue management focused on yielding more revenues from room inventories, however, from 2015 onwards, things changed and the concept of total revenue management prevailed. Now, restaurant, function areas, and spa are also given attention by RM.

In a small lodging market such as that of Jordan, hotel managers used to exchange information about their perspective hotels’ occupancy rates and prices on a daily basis. Using spreadsheets in tracking historical data, forecasting, and setting rates was a common practice. With the advent of online distribution channels combined with restrictions from some international hotel chains on information sharing, hotels started to rely more on market intelligence. At this stage, revenue managers performed rate shopping manually using OTAs. P8 mentioned:

Technology is really important […]. Until 2010, I used to push or adjust the rates manually. I had to log into separate channels pushing the rates or controlling bookings on Booking.com and Expedia. So if you work for a five-star hotel like [X] where they use 40-50 channels, then it will be time consuming.

Revenue managers agree on the importance of technology and acknowledge the need for using specific computerized software in handling different RM tasks. Most revenue managers track the introduction of sophisticated RM software 10 years back, confirming the predictions of Karadjov and Farahmand (2007). The proliferation and increasing popularity of online distribution channels and OTAs like Booking.com and Expedia alleviated the need for specific software. Therefore, hotels started to use channel managers, such as TravelClick, and RezGain to manage availability, rates, inventory, and restrictions across several OTAs. Some revenue managers in the present study used more than one channel manager given that not all channel managers are configured to have access to all extranets. For instance, RezGain does not, at the moment, have configurations to access accommodation platforms, such as Airbnb and HomeAway (Personal Communication with an RM industry expert, August 2019).

To understand the current state-of-the-art of digital transformation in hotels, revenue managers were asked about the software they used in their RM operations. The qualitative data indicate that there are two key levels of digital transformation based on the level of sophistication. Almost all hotels used property management systems (PMSs) and channel managers in their RM operations while almost half of the sample (12 hotels) had specific RM software.

Hotels that did not have specific RM software deployed, although with a modest level of sophistication, technology in their RM operations. PMSs, such as Opera, were generally used to retrieve historical data. Hotels also used OTAs, such as Trivago and Booking.com, as rate shoppers to understand competitors’ rates and the demand in the market. OTAs were particularly appreciated since competitors’ rates can be monitored on a regular basis and even during different times during the same day. Reports of Smith Travel Research were also considered by revenue managers as a benchmark tool to understand their hotels’ performance and position against competitors.

The high cost of RM software, difficulty in convincing the owner, senior management, or the head office, and the small market size which implies a relatively smooth competition, were mentioned as key barriers for digital transformation. Most revenue managers in the sample mentioned that hotels can be challenged by the high prices of RM software. Understandably, the cost constitutes a larger barrier for independent hotels or local brands than it does for chain-affiliated hotels. P7 noted:

The cost [of RM software] is the most important barrier for our hotel while it is not for chain hotels because the head office purchases the system through a global agreement and implements it in all affiliated hotels. It is not the same for hotels that are not affiliated [with international chains] because you stand alone.

Closely related to the high-cost barrier, revenue managers willing to deploy RM software in their properties may face opposition from owners or senior management. Again, the opposition stems mainly from the high cost of these systems and the fear of not achieving significant return on investment (ROI). Moreover, most of these owners operate mainly in manufacturing or construction industries. Thus, they may not be aware of the principles of dynamic pricing and potential returns. In their study, Demirçiftçi et al. (2017) identified owner’s pressure on budget and prices as a key challenge faced by revenue managers.

The small size of the Jordanian lodging market in general, and the luxury and upscale segment in particular, was also highlighted by some managers as a key constraint for implementing RM software. For instance, P17 noted that “investing in RM systems is required when you have a dynamic market with many suppliers […]. This is not the case in Amman where the market is small.” Several managers compared luxury hotels in Jordan with those in other markets such as Dubai and suggested that the need for sophisticated RM software is greater in larger markets, where competition among luxury hotels is high.

Hotels, where digital transformation seems to have reached a sophisticated level, relied more on specific RM software to facilitate different operations, such as forecasting, budgeting, and pricing. IdeaS, Concerto, and One Yield were frequently mentioned as the most used software. These hotels used key RM software but also employed several supportive tools, such as rate shoppers, reputation management systems, and price optimizers. It is noted, however, that although digital transformation is taking place in these hotels’ RM operations, its introduction seems to be very recent. For instance, P18 mentioned that Concerto has been in use as recently as 2018, whereas P23 mentioned that her hotel had implemented One Yield in early 2019.

Whether they had specific RM software or not, hotel revenue managers relied on several digital tools and resources to perform different RM tasks, including rate shopping benchmarking; forecasting; search engine optimization and reputation management; understanding customers’ perceptions, expectations, and behaviors; and finally pricing. P23 estimated that “there are over 150 supportive tools and it depends on the chain and the type of hotel when deciding which tool should be implemented.” For instance, individual extranets (accounts) of different OTAs were considered as an important source of information to understand potential guests’ booking behaviors. P16, who worked for a hotel implementing One Yield, suggested:

I rely also on OTAs such as booking.com. There is something called extranet, that is to say user account, I can log in and print out the reports that I need. I can identify the websites of ten hotels visited by the guest before checking our hotel. The marketing team then investigates why guests look into our page but decide to book elsewhere.

Regardless of the level of sophistication, the benefits of digital transformation, such as speed, provision of accurate data, better understanding of the market, supporting the decision-making process, and eventually maximizing revenue, are acknowledged (Figure 1). P8 noted “this system [Channel Manager] saves both time and labor, you can update the rates with one click. In the past, this process could be time-consuming, it would take 3 to 4 hours.” RM software also provided managers with easy accessibility from personal PC and smartphones. P20 mentioned:

in the past when a group is confirmed [when a significant number of rooms are sold], I had to go back to the hotel to restrict booking from different online channels, now, I log on while at home and control online booking with one click.

Figure 1.

Benefits of and barriers for digital transformation in RM.

Future of the RM profession

As discussed earlier, few would disagree that digital transformation has potential disruptive effects on hospitality professions. It is unclear, however, whether this holds true in the case of the RM profession. In the current investigation, informants were asked whether technology would reduce reliance on revenue managers and whether digital transformation could end up threatening their professions in the future.

There is a consensus among informants that digital transformation does not diminish the role of revenue managers in the present and is unlikely to do so in the future. They agree that RM involves critical practices and decisions that require human intervention. Therefore, revenue managers perceive RM software as complementary rather than substitutional tools. For instance, P17 noted:

Software only reads numbers, revenue managers make decisions. Software facilitates the decision-making process, but still, it is a computerized system. Let’s assume that last October, the occupancy rate and average daily rates were high because of an event or one-time group, the software will recommend rates based on misinterpreted values, in such cases, as a revenue manager, I may override the software’s recommendations.

Even in hotels where sophisticated RM software is implemented, tracking events and gaining insights into the dynamics of the lodging market need constant monitoring by revenue managers. For instance, informants mentioned that software can misinterpret historical data on occasions, such as Ramadan and the religious holidays celebrated by Muslims, since these events, although recurring, do not occur in the same periods of the year. These findings confirm the central role of revenue managers and indicate that sophisticated software and algorithms cannot substitute for a revenue manager’s ability to predict forces in the market that can affect pricing (Ivanov and Ayas, 2017; Schwartz and Cohen, 2004; Smith and Kaminski, 2016). Yet, while almost all revenue managers do not perceive digital transformation having disruptive impacts on their profession, some suggested that it may bring about structural changes that may affect RM as a profession but is unlikely to threaten its existence. Specifically, some informants predicted that digital transformation can impact the RM implantation strategies whereby hotels may turn from in-house RM into corporate outsourcing. In other words, digital transformation may give rise to freelance revenue managers and more virtual RM solutions. These results support the notion that RM implantation strategies may be influenced by several external and internal factors including costs and resources (Altin, 2017). P21 suggested:

[Digital transformation] will not reduce reliance on revenue managers. However, in the future, we will have what is called ‘Revenue for Hire’. […]. Hotels that do not have revenue managers can implement ‘Revenue for Hire’ that will monitor their properties online. […]. I might work as a ‘Revenue for Hire’ in a corporate office. So currently our profession is not threatened but in the future, you never know.

Overall, the benefits of RM software in facilitating RM operations are acknowledged. However, these benefits cannot be a substitute for the human factor. There seems to be agreement among informants that the RM in the lodging industry is more complex than it is in other industries such as airlines to the point where full automation of RM operations can be detrimental. Total hotel RM includes managing capacity at optimum levels (e.g. cross-sale, up-sale) with high profitability (e.g. branding, loyalty) throughout the whole facility and this requires a team effort and coordination. Previous research also confirms that RM in hotels has its unique challenges stemming from the fragmented nature of the industry, the diverse characteristics of local markets, and the unclear end of service period in hotels (Klein et al., 2020; Vinod, 2004).

Conclusion

With the advent of technological innovations, considerable theoretical and empirical research has been conducted to address the size and influence of digital transformation and its implications for the tourism and hospitality industry (e.g. Buhalis et al., 2019; Lam and Law, 2019). Despite the fact that the role of RM in firms’ financial success is widely acknowledged, the current and future impacts of digital transformation in hotel RM practices have largely been overlooked in the relevant literature. Drawing on qualitative data collected through 23 semistructured interviews with revenue managers in luxury and upscale hotels across Jordan, the current investigation is one of the first studies aimed at providing empirical evidence on how digital transformation is reflected in hotels’ RM practices, the perceived benefits of and barriers for adopting technology innovation in RM operations, and how revenue managers evaluate the impacts of digital transformation on the future of their professions. Findings from the present study have significant theoretical and practical implications.

Theoretical implications

There has been recent attention to digital transformation in organizational structures and industries in general (Chanias et al., 2019; Matt et al., 2015). Yet, very little is known about the state-of-the-art of digital transformation in the hotel industry (Lam and Law, 2019). By delving into digital transformation in hotel RM, the current investigation adds theoretical development to both digital transformation scholarship and RM literature. The findings revealed that RM in hotels is going through digital transformation with different levels of sophistication. The divergent levels of sophistication are explained by key barriers, including the high cost of RM specific software, the divergence of views among revenue managers and senior management, and the market size. While previous research identifies cost as the principle constraint in the digital transformation in RM (Abad et al., 2019; Rodríguez-Algeciras and Talón-Ballestero, 2017; Talón-Ballestero and González-Serrano, 2013), the current study shows that other internal and external factors can also play a significant role.

The results confirm that sophisticated RM software can bring about several benefits thus facilitating revenue managers’ responsibilities (Guadix et al., 2010; Hormby et al., 2010; Kimes, 2017). Pricing is considered merely a function of RM and managing inventory at optimum profitability in the long run (RM) is considered a profession that needs various skills and experience. Thus, the human dimensions of RM (e.g. market knowledge, intuition, and coordination with other departments) will still prevail the technical innovation and software support systems. While there is now autopilot button options in all major pricing systems, findings from the current study support the notion that full automation of several RM operations such as pricing is far from being possible (Ivanov and Ayas, 2017; Schwartz and Cohen, 2004; Smith and Kaminski, 2016).

Managerial implications

Based on the perceptions of revenue managers in luxury and upscale hotels, RM in hotels has become more complicated and highly technology-driven. While deploying specific RM software does not appear to replace revenue managers, the level of transformation will demand a new set of competencies and future revenue managers will be required to have sophisticated high technological skills. Job descriptions and specifications will also be adopted to include additional tools and expertise on advanced RM related and data analytics software. Therefore, educators and curriculum designers may need to reconsider their RM programs to align with the contemporary developments and the possible progress in the near future.

The findings also have implications for RM software developers. The high price of RM software remains a major barrier for hotels wishing to leverage data-driven solutions in their RM operations. Therefore, RM software companies may need to offer segmented products with different options to target different hotels. By doing so, hotels with smaller budgets may be able to buy affordable software with limited options. Moreover, to persuade hotel chains and individual hotel companies to use these software systems, a strong emphasis should be placed to the ROI. This may be possible through presenting reliable and real success stories of hotels that have purchased and implemented RM software. Hotel brands or consultant companies that develop RM software may also need to extend the scope of their RM software by considering other revenue points, such as food and beverage and function areas.

Limitations and areas of future research

This study has some major limitations. Obviously, the qualitative research approach, the context (i.e. hotels in Jordan), and the specific setting of the study (luxury and upscale hotels) limit the generalizability of the findings. Digital transformation is a complex issue that requires strong synergy across different levels within the hotel management (Lam and Law, 2019), therefore, considering the perspectives of different players including IT managers and sales and marketing managers would provide a more comprehensive understanding of how revenue models are influenced and transformed by digital technologies. Delving into the skills, mindset, personality traits, and working culture of managers who are likely to adapt and adopt digital transformation is another area that is worth further investigation. The sample of the current investigation is biased toward revenue managers in chain-affiliated hotels, therefore, future research may also extend the findings by assessing whether the extent and effectiveness of digital transformation differ across different settings (e.g. hotel type, ownership, market stability, chain-affiliated vs. local brands). The sharing economy platforms, such as Airbnb, pose considerable challenges for the traditional hotels, however, it is unclear how RM systems respond to the informal lodging market. This issue may be worth further investigation.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was partially funded by Istanbul University Cerrahpasa Research Council (Project no: 33759).

ORCID iDs

Ziad Alrawadieh

Zaid Alrawadieh

Gurel Cetin

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