Monitoring Revenue Management Practices in the Restaurant Industry—A Systematic Literature Review

Abstract

The research of revenue management (RM) practices is widespread in the accommodation sector, but not in the restaurant industry. This study aims to ascertain which RM practices are the most used in the restaurant industry, organizing them by clusters, identifying those that imply profit maximization and describing the challenges of their implementation. Mixed methods were used as the methodology through a systematic literature review, which was submitted to a brief descriptive analysis and content analysis. Data were retrieved from the Scopus database, and, using the PRISMA diagram, 70 papers were collected for comprehensive analysis of their content. The results of the studies identified five main areas of RM and 21 practices, some specific to the restaurant industry, with reservations and meal duration management being the most used practices. Reservations have been implemented in many restaurants but are not a reality for all of them. A well-managed meal duration increases restaurant capacity. Furthermore, customer satisfaction implies the success of all other practices since customers must understand and accept the RM practices for their success. As a theoretical implication, this study contributes to the development of research into the RM practices of restaurants, and as practical implications, restaurant managers should implement the following practices: meal duration management, indicators, and table mix. This study contributes to future research, such as analyzing the relationship between sustainability and RM, applying RM to the beverages department, and including RM in consumer behavior in the context of future crises.

1. Introduction

RM, also known as “yield management”, emerged in the 1970s in the airline industry. Its focus is selling products or services to the right customer, at the right place, and at the right price to maximize an organization’s success (Kimes, 1989). Several RM practices have emerged over the years in airlines, hotels, and restaurant industries, as well as recently in other industries where the increase in revenue has been highlighted (Kimes & Wirtz, 2003; Tyagi & Bolia, 2022). According to Kimes and Wirtz (2003), RM is easier to apply to industries with fixed capacity, uncertain demand, perishable inventories, and high fixed-cost structures.

The initial concepts of RM that remain, are the following (Cross, 1997, p. 33): “focus on price rather than costs when balancing supply and demand; replace cost-based pricing with market-based pricing; sell to segmented micro markets, not to mass markets; reserve sufficient products for your most valuable customers; make decisions based on knowledge, not suppositions; exploit each product’s value cycle (i.e., price it according to its freshness and the urgency with which customers wish to purchase it); continually reevaluate your revenue opportunities”.

Regarding the application of RM practices in the airline, hotel, and restaurant industries, although there are similarities and identical RM practices for the different industries, the strategies adopted must always consider the individual characteristics of each industry (Thompson, 2015a). For example, airlines often use overbooking to maximize revenue, and sometimes hotels do as well; however, restaurants that take more reservations than they have available tables are not viewed as well by customers and can be considered an act of disrespect (Karmarkar & Dutta, 2011; Oh & Su, 2018). In addition, it is difficult for restaurants to apply this RM practice because the number of seats occupied may be lower than that resulting from the number of tables available; for example, a four-seater table may be considered occupied with only three seats (Bujisic et al., 2014). The same is true of price differences, where an airline or hotel may have a different price for a flight every day, while in a restaurant, if a regular customer pays different prices every week for the same dish, it may be considered unsatisfactory to them, and this may damage their loyalty (Jo et al., 2024). In this way, the application of RM has faced different challenges, and it is necessary to adopt various strategies to solve this problem (Kimes & Beard, 2013). The restaurant industry when compared to other subsectors of the tourism industry, it can be observed that the restaurant industry is characterized by fixed prices, while its duration is unpredictable (Kimes et al., 1998). Kimes is one of the authors who has contributed to the development of scientific research in the restaurant industry through her study on RM strategies (Kimes, 2004), where the restaurant industry encompasses two main revenue maximization strategies: pricing and meal duration management. Pricing can be based on demand, product availability, and other factors to dynamically adjust product and food prices. Meal duration management allows you to manage the amount of time a customer spends in a restaurant to optimize table turnover and maximize operational efficiency. The restaurant industry has very specific management decisions, such as combining prices to differentiate services while maintaining the consumer’s perception of fairness. In this context, Susskind et al. (2004) stated that basing pricing on demand is also difficult because no one knows what a customer is going to order when they arrive at the restaurant. Afterward, other authors came up with a greater number of practices that can be introduced in the restaurant industry (Heo, 2016; Seo & Hwang, 2014; Song & Noone, 2017; Thompson, 2011a), such as capacity/inventory management, price management, online delivery, and customer experience (Tyagi & Bolia, 2022).

According to Legohérel et al. (2013), capacity management allows strategic control by the number of tables available and should be the first RM strategy to be considered by the manager. Restaurants should provide for the possibility of extending service capacity during times of high demand. Although the restaurant’s space is limited, there is greater flexibility in the organization of tables, both from the point of view of layout and the capacity of each table. In this stage, the table mix is important because it balances the different types of tables and seating compositions to maximize the use of the available space. A restaurant’s reservation policy influences the table mix because there may be group restrictions or table preferences by customers, and this may or may not contribute to maximizing revenue (Kimes & Thompson, 2005; Tyagi & Bolia, 2022).

Price management is the technique used to strategically adjust and control prices; this tool is critical to RM and the success of any organization. When implemented well, this RM practice improves issues of high or low demand and discounting. In addition, managers can benefit from using differentiated products and foods for price matching. However, managers must ensure that customers are willing to pay higher prices and that price fences do not disadvantage customers who are not so willing to pay (Tyagi & Bolia, 2022). Other price management techniques can be implemented in the restaurant, such as bid price (Bertsimas & Shioda, 2003), dynamic price (Webb et al., 2023), menu pricing (Kimes & Wirtz, 2003), peak-load pricing (Herrera & Young, 2022), and price bundling (Heide et al., 2008). According to the previous authors, the bid price is the price a customer is willing to pay for a service. Dynamic price allows you to adjust the price of different items based on a variety of factors, such as demand, type of service, type of restaurant, etc. Menu pricing is the way in which the price of a restaurant’s menu is determined. This process considers a large number of factors, such as the cost of products, competition, and demand. Peak load pricing is an RM strategy that varies according to the demand for a restaurant at different times of the day. Price bundling, associated with marketing, offers a combination of products or services in a single package at a special price.

Online delivery, as a strategy of restaurant RM through distribution channels, has grown exponentially in recent years (Shroff et al., 2022). There has been almost exponential growth in online ordering, telephone and home ordering, the use of mobile applications to order food, and drive-through services (Tyagi & Bolia, 2022). Restaurants are increasingly looking to third-party websites to attract customers and “get away” from traditional sales, but it is difficult to retain customers, according to Xu et al. (2020). On the other hand, some authors argue that mobile applications and home delivery increase customer loyalty (Londono-Giraldo et al., 2024). This measure is interesting because customers who really like the atmosphere of the restaurant will come back, and the staff will be able to develop a close relationship with them and build loyalty (Tyagi & Bolia, 2022).

Some RM practices are based on efficient demand segmentation, which means knowing the market well and the segments that a restaurant wants to reach. In-depth knowledge of demand is essential for improving demand forecasting (Ampountolas et al., 2021; Legohérel et al., 2013). Restaurant managers must identify the most valued attributes and monitor both customer satisfaction and perceptions of the service. Without this connection, RM practices are in vain. Aspects such as willingness to pay, willingness to wait, elasticity, fairness regarding pricing, and reservation policies are aspects that cannot be overlooked and which, although they do not represent an RM practice, are inseparable.

The analysis of customer experience is of the utmost importance for the restaurant industry, as satisfied customers are more likely to return and recommend the establishment to other potential customers. Additionally, a positive experience can result in higher spending by customers. On the other hand, poor experience can lead to customer dissatisfaction, negatively impacting on the restaurant’s reputation and resulting in revenue loss. Therefore, ensuring a high-quality customer experience is essential to maximize revenues and financial success for a restaurant (Çakıroğlu et al., 2020; Kimes et al., 1999; McGuire & Kimes, 2006; Tyagi & Bolia, 2022; Vieveen, 2018; Gajić et al., 2023).

Restaurant performance analysis also improves a restaurant’s financial success. Managers need to evaluate the application of RM practices. Indicators such as revenue per available seat (RevPAS) (Herrera & Young, 2022), revenue per available seat hour (RevPASH) (Thompson & Sohn, 2009), spending per minute (SPM) (Seo & Hwang, 2014), and revenue per available space for a given time unit (RevPAST) (Song & Noone, 2017). According to the authors presented above, RevPAS calculates the revenue generated in a restaurant per available seat; RevPASH is an identical indicator but adds the time variable, in this case the hour; SPM measures the amount of money a customer spends per minute, i.e., the revenue a restaurant earns per customer per minute; RevPAST calculates the revenue of each available seat for a certain period of time, which can be set by the manager according to what he may want to analyze. These indicators, combined with other tools such as menu engineering (Barth, 2011), contribute to informed decision-making and feed the RM system by compiling data. Data collection is also key to forecasting, and these indicators can be shared with the whole team to involve human resources (Kimes, 2004).

According to the review, the RM areas could be classified into five major groups, which are the following: pricing, inventory management, distribution management, performance analysis, and consumer behavior. Within pricing, other subareas were highlighted in the scientific articles under study, such as price bundling, dynamic price, bid price, peak-load pricing, demand-based pricing, discounts, rate fences, and menu pricing. Inventory management is subdivided into four subareas, namely reservations, meal duration management, table mix, and overbooking. As far as the distribution management domain is concerned, there is still just one subdomain: online delivery. The performance analysis identified the menu engineering and the indicators. Finally, consumer behavior was divided into seven subareas, which are: customer satisfaction, customer relationship, fairness perception, willingness to pay, willingness to wait, forecast, and elasticity, as shown in Figure 1.

The practices were presented by areas, but practices are often related to each other, so it is sometimes impossible to explain a practice without referring to others that belong to a different area. From the above analysis, it is evident that RM is a research topic that encompasses several practices. However, it is pertinent to understand whether these tools are useful and applicable to the restaurant industry in the same way as they are to other areas, such as hotels (Abrate et al., 2019) and airlines (Büsing et al., 2019).

According to the National Restaurant Association (NRA, 2022), the restaurant industry is the second largest employer in the private sector in the United States, representing 10% of total employment. In addition, the restaurant industry is important for the global economy of the 21st century (Muller, 2020). The restaurant industry is considered a volatile sector because it operates in a competitive environment. It also struggles with economic crises and the need to maximize profits (Gomes et al., 2022). This industry has characteristics that deserve attention concerning management, as pointed out by Moser (2002) and Lima Santos et al. (2016). Yembergenov and Zharylkasinova (2019) state that managers in the restaurant industry are accountable for developing this economic activity to ensure success for the businesses they oversee. As highlighted by DiPietro (2017), scientific research in this sector has significantly evolved, encompassing areas such as RM (Kimes, 1999, 2011; Mhlanga, 2018; Palmer & McMahon-Beattie, 2008). However, there is a strong reluctance to apply RM among restaurant managers because their focus is on customer satisfaction (Kimes & Wirtz, 2003). Thus, there is a need to understand how RM practices are applied by the restaurant industry, and the following research question is therefore formulated:

Which are the most used RM practices in the restaurant industry?

Hence, the determination of the evolution of RM in the restaurant industry to date is crucial, and the main objective is to analyze which RM practices are the most used in the restaurant industry to provide profit maximization. To achieve the main purpose, the following specific objectives were formulated: To identify the most studied RM practices in the restaurant industry, organizing them by areas; To emphasize the RM practices that most contribute to profit maximization; To point out the challenges in implementing and adopting RM practices.

Furthermore, based on gaps identified in previous studies, this study seeks to make a significant contribution to research on RM strategies in the restaurant industry, namely their inputs to profit maximization. Thompson (2010) and Kimes and Beard (2013) studied this topic, but the research was carried out more than 10 years ago; X. Wang et al. (2015) also developed this topic in their study but compared the hotel and restaurant industries, not giving an exclusive character to the restaurant industry, as this study proposes, so it is also necessary to add more theoretical and innovative development on RM (X. Wang et al., 2015). More recent studies have been conducted on this topic (McGinley et al., 2020), but they analyzed a period of only 5 years and considered the hotel sector together with the restaurant industry, which, as mentioned above, have different RM strategies. Roy et al. (2022) also carried out a study on emerging practices and research opportunities in the restaurant industry, but they focused on information technology systems and technology and not so much on the adoption of RM practices that contribute to management accounting and decision-making. The studies by Kimes (2005) and Tyagi and Bolia (2022), both literature reviews, were also focused on this field, but the present study stands out since a systematic literature review approach that can be easily replicated by other researchers as it follows a rigorous process that guarantees the quality and reliability of the studies analyzed allows broader results (Paul et al., 2023; Tranfield et al., 2003). Also, Kimes’ study was conducted nearly 20 years ago, so research on RM restaurants is more advanced.

The article outlines all the necessary steps taken to obtain the results, enhancing its transparency and reproducibility. This article concludes with a discussion of the findings, including the main limitations encountered during the study and providing valuable insights for future research. By highlighting these limitations, the study opens opportunities for further research and improvement in the field of RM in the restaurant industry.

2. Materials and Methods

Qualitative and quantitative methods were applied, such as systematic review, content analysis, and metasummary. Bibliometric methods have been used in mapping scientific information. Also, these methods can increase not only the precision in literature reviews but also mitigate some of the researchers’ biases on this topic (Zupic & Čater, 2014; Herrera-Franco et al., 2020; Janowski & Martynyuk, 2023). According to Donato and Donato (2019), the systematic literature review has been growing significantly as a research methodology, being used and recommended by several authors (Campos et al., 2022b; Infantes-Paniagua et al., 2021; Lima Santos et al., 2022; Paul & Criado, 2020). In addition to the various advantages presented above, the systematic literature review is very beneficial to the study because, as well as being a rigorous and transparent process, this methodology investigates documents from the most reputable scientific journals in the world and is less tedious compared to other approaches (Hiebl, 2021). According to Tranfield et al. (2003) and Paul et al. (2023), a systematic literature review consolidates advances in each thematic field because it comprehensively gathers, organizes, and evaluates studies. This approach has gained exponential popularity. Hiebl (2021) states systematic literature reviews are divided into identification, screening, and disclosure of the review sample.

Data were extracted through the Scopus database, as in the studies by Campos et al. (2022b) and Cardoso et al. (2021). This database provides an extensive and relevant overview of peer-reviewed scientific production in different scientific areas around the world (Martins & Costa, 2017) “identifies experts and provides access to reliable data, metrics, and analytical tools” (Scopus, 2023). The study by Vicente et al. (2023) also used only one database to develop a systematic literature review.

The search took place on 17 January 2023. The literature review presented earlier assisted in the creation of the search string adopting these parameters—TITLE OR ABSTRACT OR KEYWORDS—to extract as many studies as possible that relate the restaurant industry to RM. Therefore, the following search string was created: (restaurant OR “restaurant sector” OR “restaurant industry” OR “food and beverage” OR F&B OR catering OR foodservice) AND (“revenue management” OR “yield management”). In this way, to reach the final sample based on the research question in an impartial approach, it was necessary to establish inclusion and exclusion criteria such as Campos et al. (2022a) and Kroon et al. (2021) established inclusion and exclusion criteria in their systematic literature review studies.

Regarding the exclusion criteria, to ensure the quality of the selected studies, gray literature such as books, book chapters, and conference papers were not considered (Hiebl, 2021). Since the aim of this paper is to identify which of the most used RM practices contribute to the profit maximization of restaurants, all studies that are based on or aimed at the accommodation sector were disregarded. Studies on RM that do not include the restaurant (i.e., marketing or casino) as their main objective were excluded.

Concerning the inclusion criteria, to cover all publications on RM applied to the restaurant industry, all years up to the day of the search were considered. To maintain the transparency of this study, all empirical and non-empirical studies were included (Hiebl, 2021). Studies that contribute to improving RM knowledge in the restaurant industry, as well as studies with well-defined research objectives, were considered.

The publishing dates of the documents considered spanned from the beginning of journal publication until 17 January 2023 (inclusion criteria TR–1). All the articles found were in English. In the initial sample, there were 135 documents from the Scopus database without duplicates.

Afterward, applying the exclusion criteria NR–1 (restricted to scientific articles only), 26 studies were eliminated, resulting in 109 documents. Then, the articles were extracted from the Scopus database to an Excel document to be analyzed independently by two researchers from the research team, both of whom have teaching experience in the hotel and restaurant industry, one of them for more than 15 years. The titles and abstracts of all documents were read. The opinions and reasons for the inclusion and exclusion of studies were discussed by each researcher, and the sample resulted in 79 studies: 29 studies were excluded by LR–1 (studies not based only on the restaurant industry), of which 26 studies discussed the accommodation sector, 1 combined the accommodation sector and aviation, 1 talked about marketing, 1 dealt with the golf industry, and 1 study was excluded by LR–2 (studies where the focus is on RM but does not include restaurants as the main object of study).

No previous publications were retrieved, resulting in 79 studies. Regarding eligibility and in accordance with the research question (Hiebl, 2021), all these studies were independently reviewed in full by two researchers from the research team to maintain the quality of this study as well as its impartiality. During this analysis, 9 articles were excluded for the following reasons: 8 studies because of LR–1 (5 studies discussed the accommodation sector, 2 only casinos, and 1 a different industry), and 1 study because of LR–2. Thus, considering the inclusion criteria TR–3 (studies based on empirical and non-empirical research), TR–4 (studies that contribute to the literature improve knowledge about restaurants and RM), and TR–5 (studies with (a) well-defined research objective(s)), the final sample included 70 studies. Observing the nature of the 70 documents (Appendix A), 20% are qualitative research, and 37% are simulations.

For a better understanding of the information, Figure 2 presents the procedures used in the PRISMA diagram. As a guideline “to more transparent, complete, and accurate reporting of systematic reviews, thus facilitating evidence-based decision-making” (Page et al., 2021). Several researchers have conducted a systematic literature review (SLR) in tourism, hotels, and restaurants using the PRISMA diagram (Asyraff et al., 2023; Campos et al., 2022b; Chesterton et al., 2021; Mirzaalian & Halpenny, 2019; Ogutu et al., 2023).

In this step, a content analysis was applied to extract data and a meta summary as a descriptive review type. Then, a quantitative element to summarize the literature was added since findings were extracted, and through descriptive analysis, the calculation and intensity effect sizes were made and represented by graphs (Xiao & Watson, 2019).

3. Results and Discussion

The articles (Appendix A) focus on one or more of the main themes, addressing specific RM practices that have been clearly identified and coded (Figure 1). Most of the articles focus on inventory management, followed by consumer behavior, pricing, performance analysis, and distribution management (this is the order in which the results of the study are presented). However, around 24% of the articles deal with RM in general, not focusing on a particular practice.

Also, 21 RM practices in the restaurant industry were analyzed (Figure 3). Some practices identified here are presented in more than one study at the same time. The most used practice is reservation, present in 68.6% of the studies. Meal duration management ranks second and is represented in more than half of the studies (58.6%). Forecasting ranks third, being mentioned in 47.1% of the studies. Practices such as peak-load pricing and bid price are the least used, appearing in 2 and 5 studies, respectively.

As can be seen in Figure 3, several RM practices are used exclusively in the restaurant industry, such as meal duration management, table mix, willingness to wait, menu pricing, menu engineering, and various performance indicators (RevPAS, RevPASH, RevPAST, and SPM). More information on these RM practices is presented below in the discussion of the results. It is important to note that, although it is not an RM practice, customer satisfaction is a common goal shared by most practices, being present in 50% of the studies analyzed.

3.1. Inventory Management

Reservation management is the most studied practice in restaurant RM. In some cases, models were created to simulate scenarios. In Thompson’s (2015a) research, programming models were used for restaurant reservations through simulations, and it was realized that specific scenarios may constitute limitations for planning; thus, future studies should focus on the flexible arrival of customers as well as on applying a simple and effective capacity management model. Walk-in arrivals must also be considered and require a good reservation policy understood and accepted by consumers (Gregorash, 2016). In the restaurant industry, although the need for reservations has been implemented in many restaurants, it is still not a reality for every restaurant. Unlike hotels, restaurants traditionally have a higher rate of walk-ins than customers with reservations. This may not apply to luxury restaurants at times of high demand, but as most of the sector is not composed of luxury restaurants, seasonality will continue affecting most of these businesses. Still, on bookings, the creation of discounts to reduce the no-show rate is recommended. Additionally, grouping reservations is more efficient than blocking them (Thompson & Kwortnik, 2008).

When a restaurant accepts reservations, several decisions need to be made, and one of them relates to overbooking (Karmarkar & Dutta, 2011; Oh & Su, 2018).

The table mix represents another inventory management practice and is directly linked to reservations since knowing in advance how many customers per table the restaurant is going to receive helps optimize space in advance, benefiting from the flexibility that restaurants have and that other industries, such as hotel or aviation, do not.

Proper table mix management can reduce waiting times and increase revenue, but it must consider the pressure caused by increasing the number of customers, which can lead to longer waiting times, to avoid customer dissatisfaction. However, managers should analyze historical data as needed to develop a combination of tables that allows for more movement and, consequently, profit maximization (Kimes & Thompson, 2005). It is therefore also important to increase the efficiency of processes, for example, by using technology and mobile devices to record orders and issue invoices or by improving cooking processes in the kitchen. Organizing a table mix with a large variety of possibilities is important, even if it has limitations due to the design of the restaurant (Kimes & Thompson, 2005).

Meal duration management can be influenced by the time of day (lunch or dinner) and the number of customers. The duration of the meal is an important part of inventory management, and while it must be reduced to increase capacity, it must never jeopardize the customer experience, and they must never feel under time pressure (Noone et al., 2007). Methods to reduce meal duration could include specific training for staff to improve the efficiency of the tasks they perform. The use of indicators to check the ‘exact’ time it takes a customer to eat lunch or dinner also helps to better manage meal duration.

3.2. Customer Behavior

Customer satisfaction seems to be a common concern that many RM practices depend on to be successful. Of the 70 studies analyzed, there are several that reflect customer satisfaction (Bertsimas & Shioda, 2003; Etemad-Sajadi, 2018; Kimes et al., 1999; McGuire & Kimes, 2006; Noone et al., 2012; Tang et al., 2019).

The study by Song and Noone (2017) emphasizes that the spacing between tables is essential for customer satisfaction, as tight spaces between tables can create a sense of discomfort for customers. Therefore, employees should receive training to effectively manage customer flow, as well as utilize physical barriers to create the appearance of greater distance between tables and customers (Noone et al., 2007; Song & Noone, 2017). To reduce customer waiting time, it is also suggested to use portable devices that can print invoices on the spot and enable credit card processing (Noone et al., 2007).

Different cultures have different fairness perceptions, meaning that what may work in one geographical region may not work in another (Kimes & Wirtz, 2003). Ensuring customers’ perception of fairness is considered an effective RM strategy to increase word-of-mouth referrals and customer loyalty (Tse & Poon, 2017).

Regarding willingness to pay conditions (Hwang & Yoon, 2009), customers could be willing to pay more for a prime location in a restaurant, but this willingness differs depending on various factors, such as the type of operation and the average check. Reducing the price or creating a bundled menu instead of purchasing items separately could allow for an increase in customers’ willingness to pay (Heide et al., 2008).

Customers’ willingness to wait can be influenced in various ways, one of which is by reducing meal duration. This practice can increase the willingness to wait, as stated by Thompson (2009), who found that a 20% reduction in meal duration increased the willingness to wait from one-third to two-thirds, resulting in a 5% increase in revenue. However, this practice may not be the most suitable in more complex environments.

3.3. Pricing

Some pricing practices, both due to their complexity and the specific nature of the restaurant industry, are difficult to adopt or implement in restaurants; however, price is a fundamental variable in RM, so strategies such as dynamic pricing can be implemented in restaurants, but preferably at times of lower demand (Webb et al., 2023). The ability to adjust prices based on demand, offering discounts during certain hours of the day or meal periods, is considered a fairer RM practice than premium prices or surcharges. As an example, a restaurant manager can “present the higher price as a premium over regular menu prices or position the regular menu price as a discount from the higher weekend prices” (Kimes & Wirtz, 2003, p. 129).

In the restaurant industry, price discrimination is lower, but discounts are one way of implementing this practice. The literature has made it clear that customers prefer discounts rather than paying higher prices for premium services. Discounts are well accepted when applied at specific times or during certain meal periods. Managers should improve their ability to inform customers in advance of price changes, but this practice is not compatible with fixed-price menus in which the duration of the meal is stable. Regarding the use of discounts, they often appear in rate fences (Etemad-Sajadi, 2018; Heo, 2016; Ng et al., 2018; Susskind et al., 2004). Discounts depend on the customer’s market segment, and the strategy applied by the restaurant depends on various factors that customers may or may not consider important, such as the table location (Denizci Guillet et al., 2018).

It also became clear that each establishment must study and understand the characteristics of its demand to adopt the different practices; for example, price bundling may or may not have a positive effect on revenue depending on the type of menu and customer (Mathe-Soulek et al., 2016; Von Massow & McAdams, 2015). It is important to focus on creating value for the customers so that efforts are directed towards the aspects they appreciate, and in this sense, the establishment of price fences becomes fundamental.

Customers must understand and accept pricing practices. Another example is peak-load pricing, which can be well accepted if the consumer feels it is justified (e.g., by the increase in staff costs) (Herrera & Young, 2022). As in the hotel industry, the bid price can also be established in restaurants with the help of mathematical models, but managers may not be prepared for this type of tool (Bertsimas & Shioda, 2003).

3.4. Performance Analysis

In the restaurant industry, performance analysis can be performed using various indicators such as RevPAS, RevPASH, RevPAST, and SPM. However, this is an area of RM in the restaurant industry with research potential, especially in terms of empirical studies (Heo, 2016). In addition, it is difficult to make robust benchmarking between different restaurant companies in different geographical regions because there is almost no statistical information available on them, or if there is, it is mostly linked to the accommodation sector, as if they operate as a single industry. In this way, we advocate valuing these indicators for a more efficient analysis of restaurant performance and, in this sense, managers will have an active role in improving revenue maximization and, consequently, in maximizing the profits of the restaurants they manage.

3.5. Distribution Channels

The use of third parties in distribution can be particularly important at times of lower demand, but customers expect discounts and commissions to represent an additional cost (Heo, 2016). Additionally, customers rely on these channels to obtain information about prices and other factors, establishing a sense of trust (Kimes & Wirtz, 2003).

According to Zheng and Guo (2016), customer relationships can be established through an online strategy; however, there are still restaurants that cannot partner with third-party websites and expand in this regard. Also, customer retention can be achieved through discounts that decrease as offline customer loyalty increases; thus, partnerships with third-party sites are only recommended when the ideal discount rate reaches zero.

Online delivery is the result of the impact of the growth of distribution channels and has seen huge growth rates with recent crises such as the COVID-19 pandemic (Belarmino & Repetti, 2022). This service is very practical for customers, who appreciate it because it is not only convenient but also saves time. Managers consider this tool to be very important for the restaurant business because, in addition to promoting sales and profit maximization, it allows managers to focus more on customers who prefer to be in the restaurant rather than ordering food online (Tyagi & Bolia, 2022). Online delivery is a way of minimizing customer costs, establishing competitive prices, and creating immediate brand recognition (Muller, 2020).

Nevertheless, Guo and Zheng (2017) argue that third-party websites harm loyal customers and, in the long run, do not promote revenue growth due to the offer of discounts. Furthermore, the quality of food is crucial in enhancing the relationship between customers and restaurants, as it is not worthwhile offering discounts on dishes when the food lacks quality. But, when introducing a new dish to the menu, offering a discount may make sense (Kwon & Jang, 2011).

3.6. The Challenges in Implementing and Adopting RM Practices in the Restaurant Industry

Based on the results provided by the literature review and its discussion, it is possible to list how RM practices can be applied to the restaurant industry, as well as describe the challenges in their adoption and implementation, which are shown in

Table 1. Restaurant RM application.

Code	Restaurant RM Practices	Restaurant Application	Challenges
IM1	Meal duration management	⋅ If managers can predict the meal duration, they decrease the waiting time for customers and increase capacity.	⋅ Analyze the average meal duration for the different periods and clients. ⋅ Use of indicators that consider the time variable (SPM and RevPASH).
IM2	Overbooking	⋅ Accept reservations beyond capacity.	⋅ Manage customer disappointment. ⋅ Must be avoided. ⋅ Do not leave out the hotel’s internal customers and impact their experience. ⋅ To combine with walk-ins.
IM3	Reservations	⋅ Better arrival management through reservations. ⋅ Use of credit card for booking guarantees ⋅ Grouping reservations instead of blocking tables. ⋅ Apply discounts for customers who book. ⋅ Reservations help control the most profitable timetable.	⋅ Managers should focus on flexible customer arrivals that allow accepting walk-ins. ⋅ Familiarize customers with the reservation policy. ⋅ To combine with an analysis of the best table mix, discounts, and waiting time.
IM4	Table mix	⋅ Reduce waiting time. ⋅ Restaurant design can influence the table mix.	⋅ Poor management of this practice leads to customer dissatisfaction. ⋅ Analyze the service’s responsiveness. ⋅ Related to meal duration.
CB1	Customer relationship	⋅ It can be established through a distribution channel, but it must be used with care to maintain the relationship with the customers. ⋅ All RM practices should consider this aspect.	⋅ RM practices that all others depend on to be successful and should relate to each other.
CB2	Demand forecasting	⋅ Able to predict execution time leads to significant increases in revenue. ⋅ Statistical methods improve long-term forecasting.	⋅ It involves statistical knowledge.
CB3	Elasticity	⋅ Analyze the effect of price changes on demand.	⋅ Consider the location, cuisine, and individual attributes of the restaurant. ⋅ Directly related to willingness to pay.
CB4	Fairness perception	⋅ Effective practice for increasing customer loyalty and word-of-mouth referrals.	⋅ Different cultures have different perceptions. ⋅ Customers should be familiar with RM practices and have a better fairness perception.
CB5	Willingness to pay	⋅ Customers are willing to pay more for a prime location. ⋅ Reducing the price or creating a menu instead of buying the products separately allows for increased willingness to pay.	⋅ Analyze the attributes that the customer values.
CB6	Willingness to wait	⋅ Reducing meal duration.	⋅ It is difficult to execute in complex environments. ⋅ Related to forecasting.
PR1	Bid price	⋅ Increase revenue without increasing customer waiting time.	⋅ Segmentation.
PR2	Demand-based pricing	⋅ Related to dynamic pricing. ⋅ Related to fairness perception.	⋅ Fairness perception is fundamental and should be preserved.
PR3	Discounts	⋅ Price decrease. ⋅ Related to rate fences.	⋅ Depending on the market segment and strategy worked on by managers. ⋅ Discounts should be applied on attributes valued by customers. ⋅ They must be applied with caution.
PR4	Dynamic price	⋅ Implementation of better price discrimination.	⋅ Price should be adjusted according to demand (segmentation). ⋅ Periods of high demand do not apply this practice. ⋅ Inability to communicate menu price variations in advance.
PR5	Menu pricing	⋅ When menu pricing and meal duration become variables, it becomes necessary to make choices and understand which customers benefit the company the most thorough cost analysis	⋅ It is important to prepare the customer cost analysis to establish the menu pricing.
PR6	Peak-load pricing	⋅ Price increase in high demand period.	⋅ It should consider customer satisfaction and return intentions.
PR7	Price bundling	⋅ Increased demand through a combined offer at a lower price than by selling elements separately.	⋅ It could create less willingness to buy on the part of the customer if they do not value it.
PR8	Rate fences	⋅ Define purchasing patterns and characteristics of the products and the customers. ⋅ It assists managers in creating value for the customer and protects the customer’s interests.	⋅ Segmentation.
PA1	Menu engineering	⋅ Scarcely explored in beverage management but with high development potential. ⋅ It can be related to other management tools, like indicators.	⋅ It involves cost accounting. ⋅ Explore beverage menu engineering.
PA2 PA3 PA4 PA5	Indicators	⋅ Generate more revenue for restaurant companies and maintain their success. ⋅ Detailed business interpretation. ⋅ RevPAS, RevPASH, SPM, and RevPAST are the most common.	⋅ It involves account management knowledge. ⋅ Lack of statistical information makes benchmarking difficult.
DC	Distribution channel	⋅ Helpful practice for restaurants beginning operations. ⋅ Valuable for low-period demand. ⋅ Allows attracting more customers.	⋅ Must be applied with care not to lose value for money. ⋅ Can damage loyalty. ⋅ Discounts can lower revenue.

. The table therefore shows the ways in which RM practices can be applied in the restaurant industry and also the challenges that managers can face in understanding which RM practices are appropriate for their restaurant companies, depending on the organization of their operations and their information needs. In addition to being innovative, this study consolidates previous studies by bringing together in a single document the different applications and challenges of RM practices for the restaurant industry in a structured and practical way for both academics and restaurant professionals.

In addition to the various limitations observed throughout the results and discussion, when looking at the overall analysis of the main gaps of the studies reviewed, it becomes clear that several authors express difficulties in replicating their studies, either because they were applied to only one restaurant or limited to one country (Legg et al., 2019; Noone & Mattila, 2009; Seo & Hwang, 2014; Tang et al., 2019).

Several studies have also been conducted using simulations, which some authors consider a limitation. In the case of customer relationships, it would be interesting to evaluate them in a real context, as it may not be possible to fully capture the dynamics and nuances of real interactions just through simulations (Kimes, 1999; Thompson, 2015b, 2019).

The challenges presented in Table 1 can also be seen as trends to improve the restaurant industry, such as familiarizing customers with the various RM strategies. Poor management of these strategies can lead to customer dissatisfaction and reduced revenue. If managers are aware of the restaurant’s capacity and workload, this will improve the process of accepting or refusing reservations (Vieveen, 2018).

The implementation of customer relationship management software helps to improve different RM practices and enhance the customer loyalty process. Through a continuous process, this specific software can optimize, among others, the prices without compromising the relationship with customers, the choice of where to seat the customer (table mix), the meal duration management, and the overbooking strategies (Tyagi & Bolia, 2022).

The development of new promotional strategies without considering only the price perspective could be a trend in RM applied to restaurants (Tyagi & Bolia, 2022), as well as the increase in practical studies on the success of these practices and not so focused on simulations. The implementation of more sophisticated methods that are easily used in restaurant practice to evaluate menu items can also be considered (Lai et al., 2019). Thus, there is a gap between the application of RM in academic research and the application of RM in restaurant companies, so research should be strengthened more practically with interviews and questionnaires with managers, employees, and customers for academic research to meet the real needs of the restaurant industry.

Regarding the distribution channel, this area is one of the most recent RM strategies. However, it can also become a problem if it is not applied properly due to the reduction in menu prices. Therefore, there is still a lot of work to be carried out in this area. The managers’ perspective on this strategy, the possibility of introducing software that allows online management, the reconciliation of marketing policies, and the use of upselling and online positioning to stimulate more spending by customers should be studied in more detail (Noone & Maier, 2015; Tyagi & Bolia, 2022).

Continuous employee training is considered an ongoing challenge, as it improves the service provided (Vieveen, 2018). A more holistic approach to all RM practices, as well as to the organization, will be key to improving restaurant business revenues.

The RM approach in the restaurant industry has positive effects when practices are established in an interconnected way, consumer behavior and segmentation are the basis of practices, and technology plays an important role. This type of practice requires investment on the part of the owner in training and also investment in technology if they want to optimize the potential of these practices in their business and, consequently, to maximize profits.

4. Conclusions

The main purpose of this study was to analyze which RM practices are the most used in the restaurant industry to provide profit maximization, identify research gaps, possibilities for future research, and practical insights for managers. This purpose was further divided into three specific objectives. The specific objectives of the study were to identify, through a systematic literature review, the most studied RM practices and organize them by area, to emphasize the RM practices that most contribute to profit maximization, and to point out the challenges in implementing and adopting RM practices.

In terms of the most used RM practices, the studies analyzed indicate that reservation, meal duration management, and forecasting are the most prominent practices. In terms of RM practices specific to the restaurant industry, the most used are meal duration management, indicators, and table mix. However, there is currently a lack of scientific literature on menu engineering for beverages (Barth, 2011), which is confirmed by the results that indicate less research on menu engineering, dynamic price, bid price, and peak-load pricing.

According to the results presented by the authors, no single RM practice works alone. It is necessary to analyze various factors, such as the type of restaurant, and consider other practices in conjunction to achieve better performance in the restaurant business. Additionally, focusing on the customers and their satisfaction is the most important element for the successful implementation of RM practices, as the revenue of a restaurant comes from its customers. Therefore, if customers understand the benefits associated with the implementation or application of RM practices, managers can effectively safeguard their business and avoid conflicts with customers (Etemad-Sajadi, 2018).

Introducing a new product, food, or beverage can impact the restaurant’s revenues, and thus, it is necessary to consider the additional costs, product performance, and consumer perception regarding health (Mathe-Soulek et al., 2016). Factors such as the restaurant’s size can also affect the performance of RM practices (Thompson, 2011b). Furthermore, although all these RM practices are important for the success of a restaurant, it is crucial to emphasize that RM should be implemented from the very beginning, in a collaborative manner, and with a solid organizational culture (Varini et al., 2012). Therefore, the motto should be training better professionals to make better decisions, as business opportunities should not be missed (Chan & Chan, 2008; Kimes, 2011a).

4.1. Theoretical Implications

According to all the research conducted, not all RM practices or the way they are applied in the accommodation or aviation sectors can be directly applied in the restaurant industry. This is because the restaurant industry has different characteristics compared to other sectors, and customers may not be fully prepared for the implementation of certain RM practices by restaurant managers. The same is true for the scarcity of research on restaurants, accommodation, and aviation, where there is 5 times more scientific information on hotels and 7 times more on aviation than on restaurants. Of all the documents analyzed, most referred to simulation studies or scenarios that may not reflect the operational reality of restaurants. Therefore, there is an urgent need for more empirical studies, such as the application of different RM practices in different restaurant companies.

This study has made it possible to develop and consolidate information on the most common RM practices used in the restaurant industry and those specific to this industry. In addition, several challenges that RM practices pose to the restaurant industry were identified; it was also possible to identify limitations of the studies analyzed and future theoretical trends.

4.2. Practical Implications

From the management perspective, it is important to emphasize that RM entails training managers and professionals in a sector characterized by small family-owned businesses (Noone et al., 2007; Song & Noone, 2017; Vieveen, 2018). This detail may not be considered a trend, but it is a constant challenge in this industry. Information technology systems, including software and mobile devices, play a crucial role in facilitating the application of these practices (Bujisic et al., 2014; Noone & Maier, 2015; Tyagi & Bolia, 2022); however, they require a substantial investment. It is also crucial to always keep in mind that each restaurant environment behaves differently, and customer satisfaction remains the most important aspect throughout the entire RM process.

In addition, the adoption of the various RM practices presented in this study leads to better profitability for managers, resulting in the maximization of firm returns. Studies by Belarmino and Repetti (2022) and Webb et al. (2023) support this view. The improved operational efficiency offered by RM practices allows for better adaptation to changing markets and the openness of an organization to changes in customer behavior, which also improves customer satisfaction. This information supports the studies of Belarmino and Repetti (2022) and Herrera and Young (2022).

4.3. Limitations and Future Research

Considering that the main limitation of the current study is the use of only one database for collecting studies, which may have limited the scope and comprehensiveness of the findings, in future research, the use of multiple databases or sources of information could provide a broader perspective on the topic and enhance the validity and generalizability of the findings.

As future research directions, it is suggested that studies examining the relationship between RM practices and sustainability (specifically environmental sustainability) in the restaurant industry could be conducted (Guo & Zheng, 2017; Karmarkar & Dutta, 2011). Additionally, it is proposed to explore the application of new mathematical models that facilitate the implementation of RM practices in restaurants. However, these models must be translated into strategies that managers can understand and implement. These avenues of research would contribute to a deeper understanding of how RM can be integrated with sustainable practices and provide more efficient tools for RM in the restaurant context.

A more detailed study of beverages can also be considered as a future research direction, as was observed in the present study that this area is still underdeveloped.

Studies about training managers to apply RM practices are also required in literature. There is still scope for innovation in the restaurant industry by adapting hotel management practices linked to RM; for example, in the same way, that the “run of the house” method of allocating rooms exists in hotels, a similar model could be explored for restaurants, which could be called “run of the tables”. Performing a Delphi study or interviews with restaurant managers could boost RM research applied to restaurants.

It is important to relate aspects of psychology to customer satisfaction, which, as mentioned above, may influence the implementation of different RM practices, given the recent changes in customer behavior due to the recent crises. The introduction of relationship marketing and the development of artificial intelligence technologies with these practices could also be considered in a future study. In this way, the exponential development of distribution channels, together with the technological development of RM practices, can be analyzed in more detail in the future.

Finally, due to the scarcity of information on the different indicators that make it possible to improve restaurant performance, this study suggests the development of empirical research in this area as a way of benchmarking different restaurants in different geographical areas according to financial performance, number of customers or any other common classification; the creation of an observatory to monitor the restaurant industry worldwide would also be a powerful study to address the scarcity of research on RM practices in restaurants. This observatory could also relate revenue and profit maximization to the costs faced by the restaurant industry.