Increasing the Efficiency of the Value-Chain for Non-Manufacturing Processes: Analytical Approach
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The implementation of lean manufacturing principles into both the manufacturing and non-manufacturing sectors makes it possible to achieve a high level of efficiency in many indicators. The presented article deals with the influence of lean production on the methodology of measuring the performance of enterprises in the non-production sphere. Part of the methodology is the analysis of key performance indicators, which serve to calculate the main quantities related to the efficiency of the operation and its optimization. In connection with the definition of different types of losses that have been identified and are successfully reviewed in the production sphere, the most common causes of losses and waste that can occur in the non-production sphere have been defined. Even though the principles of lean production were primarily developed for the production sphere, in the presented article it is possible to see the positive influence of lean principles in the non-production sphere. Customers expect a quick transformation of their requirements into products in the form of a product or service with a certain degree of personalization. Businesses focused on the non-manufacturing sector meet potential customers who are largely active and personalize products for which they are willing to pay. The path of implementing innovative solutions is one of those paths that contributes to positive change and creates prerequisites for moving towards the so-called smart business also in the non-production sphere.
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Introduction
The creation of a new business model for an enterprise means starting the implementation of the innovation process. Business model innovation can be defined as the creation of a concept and the implementation of new business models into the enterprise system. This is either the development of completely new business models, the division into other business models, the acquisition of new business models, or the transformation from one business model to another. The transformation will be felt throughout the value chain. It has an impact on the owner of the process and the implementer of the process, it affects the mutual relations between individual elements, and it also has an impact on pricing, creation of added value, etc. A pre-designed concept facilitates subsequent analysis and planning of transformations from one business model to another. Effective innovation of the business model will ensure an increase in the company’s reflection on changes in the environment in which it is implemented, which can significantly contribute to increasing the competitiveness of the company in the given industry. The presented dissertation is oriented to the field of modelling and optimization of non-production business processes, where the goal was to propose a method of increasing the efficiency of non-production processes and verifying it on the model of a selected company. The author Cuatrecasas (2004), based on the classic model of transformation of the production system into a lean production system, developed a methodology of a lean approach in the service sector, where the methodology also includes a system of calculating the main quantities related to the efficiency of operation and its optimization. Hsiehet al. (2010) modelled the demand channel and supply channel in the hotel industry. They proposed a model of the consumer cycle of the demand chain so that hotels, as well as customers, can achieve a win-win strategy. In addition, production and consumption costs are reduced, customer needs are met, and hotel productivity and consumer purchasing power are increased.
Bowen and Youngdahl (1998) described the characteristics of a lean approach in hotel operations, which compares the lean characteristics proposed by Siguaw and Enz (1999) and Younnes (2023) with hotel best practices widely used in the hotel industry to eliminate waste and flexibly respond to customer demand. The aim of the research by Raid and Matloub (2018), which was carried out on a sample of 30 hotels (3*, 4*, and 5*), was to arrive at the identification of specific types of losses that can arise in the hotel value chain. This survey was focused primarily on 5* hotels due to the established quality management systems and greater focus on efficiency. The results of that survey can be generalized and applied in the analysis and design of measures to eliminate losses for a specific hotel value chain. Plans to increase the awareness of customers, visitors, and guests and to make decisions about choosing green and reliable suppliers are initiatives that can achieve these goals. However, loss reduction is under the control of the hotel management system. That is where most of the engineering and operational excellence efforts should be directed. When processing the presented study, it was necessary to think in the context of lean principles, i.e., proceed to the analysis of losses that arise in the entire value chain.
Certain specifics within non-production processes increase value-adding activities and eliminate activities that do not add value, which is significant in connection with increasing the quality of non-production processes (Raid & Matloub, 2018; Gupta & Sunder, 2016; Vlachos & Bogdanovic, 2013;Vlachos and Bogdanovic (2013). Tortorellaet al., 2019; Bednarova, 2020). The works of the authors (Grznaret al., 2022; Strakaet al., 2022; Gregoret al., 2022; Rosovaet al., 2020) point to the importance of using simulation tools in finding optimal solutions in the production sector. As there is currently a high emphasis on speed and flexibility in fulfilling personalized customer requirements, and there is evidence of securing them in this way, it is important to think in this direction also for non-production processes, as the specificity for the non-production sector is that contact with is direct to the customer. Grabis and Kampars (2018) elaborated on a cloud-based capability management model that supports multi-tenant and private modes. It is the architecture and technology of a cloud environment for developing and delivering capabilities. The use of cloud applications in the non-manufacturing sector is currently and also in the future of great importance in the context of digitization (Revilla-Camachoet al., 2019; Sánchez-Franco & Aramendia-Muneta, 2023). These are studies that are the basis of knowledge in the field of improving the quality of accommodation services. This is Airbnb compared to classic providers of accommodation services in hotels (Sánchez-Franco & Aramendia-Muneta, 2023). In their studies, the authors (Glovaet al., 2018; Herzog & Grabowska, 2021; Kabele & Edl, 2020) deal with efficiency and the impact of costs on its increase. These are important works that, in their essence, point to specific solutions that can also be used to optimize costs and increase the efficiency of non-production processes. Emphasis is placed on the quality of processes, which is an essential part of a high level of non-production processes. In connection with the environmental approach, a study was prepared (Alreahiet al., 2023), which identifies the main barriers that can be encountered when applying Green supply chain management (GSCM) in the hotel industry.
Materials and Methods
The value chain within the hotel industry is commonly conceptualized as a network of vital connections interlinking entities and their respective functions, all aimed at achieving synergy. These encompass activities involved in the conversion and distribution of goods and services, alongside the circulation of finances and information, all geared towards fulfilling the needs of end consumers. For instance, a hotel’s value chain delineates a network comprising entities such as suppliers, logistics services, and other stakeholders, all collaborating to deliver diverse hotel amenities to patrons. This network operates through the exchange of information (e.g., reservations, hotel services), monetary transactions (e.g., payments, fees), and tangible goods (e.g., food and beverages).
Providing quality products and services throughout the value chain while increasing efficiency, reducing waste and costs, and environmental responsibility are typical challenges faced by hotels in this context. There is a need for research in the hotel value chain to analyse and categorize the losses and link the identified losses to lean techniques and green practices. Most of the existing research is focused primarily on the evaluation and modelling of the environmental and economic impacts of hotel services and the establishment of action plans and policies to reduce the negative impact. A comparison of selected lean approaches with selected best hotel practices is processed in Table I.
Lean tips in the hotel industry | Best practices in the hotel industry |
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• Reducing access to compromises • Focusing goals on internal efficiency and external flexibility • Creation of processes with added value and implementation of JIT customer approach • Elimination of losses from the value chain from the creation of the hotel product to delivery • Intensification of the customer to the process of creation and expansion of the offer of provided hotel products • Increasing the quality of workers and teams | • Maintaining quality within the entire value chain • Identifying working time requirements to reduce labour costs • Created process to streamline processes in resource-intensive hotels • Elimination of non-value-added activities that allow you to focus on quality, cost efficiency, and increasing profit • In most hotel processes, customers play an integral role • Strengthening of specific departments |
Design of Performance Measurement Methodology and Scheme of Key Performance Indicators in the Non-Production Sphere
The issue of measuring and choosing the right key indicators of non-production processes is a difficult task that requires software coverage. The design of the process performance measurement methodology follows on from the process analysis. A correctly and consistently carried out analysis is the first step to finding bottlenecks and identifying potential for improvement. When looking for an optimal solution, it is necessary to focus on:
- The nature of the activity-routine, secondary, exceptional, creative, etc.,
- Degree of repeatability of the activity–high, medium, low repeatability,
- Defining unproductive activities and waste, defining irrational activities and work procedures,
- Determination of mutual relations between individual productive and non-productive activities,
- Identifying possibilities for increasing the productivity of non-production processes,
- Identifying the potential for improving non-production processes, etc.
In connection with the definition of different types of losses that have been identified and are successfully reviewed in the production sphere, it is necessary to define the most common causes of losses and waste that can occur in the non-production sphere. According to a study by the Fraunhofer Institute in the subject area, the following causes of waste in the non-production sphere can be summarized:
- Internal problems in communication between departments and employees in the company,
- Software problems–connection, functionality, malfunctions, incompatibility with other software used in the company,
- Communication problems in the relationship with customers, suppliers, and other partners,
- Uneven input of customer requests and fluctuations in the workload of individual departments, or employees,
- A queue of pending requests with associated long waiting times,
- Frequent meetings without productive output,
- High bureaucracy in securing activities, long approval procedures,
- Collection and processing of data and creation of statistics with low informative value,
- Lack, or surplus of employees, etc.
When looking for the potential for increasing the productivity of non-production processes, it is possible to state a higher complexity, which is related to:
- With more difficult identifiability of processes and tasks due to the variety of actions, in contrast to production activities or actions that are often repeated,
- Downstream processes are often not implemented at the same pace, in contrast to the production sphere, which creates a great potential for optimization,
- In the service sector, it is usually a random event in connection with the customer’s requirements, which cannot always be predicted in advance,
- As a result of the diversity of customer requirements, there is an interweaving of work tasks and processes in time, etc.
The data obtained from the analysis can then be used to:
- Identification of waste and losses,
- Specification of inefficient activities,
- Creating a system for performance planning and control,
- Capacity planning, taking into account the dynamics of Non-production processes,
- Measuring productivity,
- Creating a remuneration system.
Results
Selection of Key Indicators for Measuring the Performance of Non-Production Processes
When creating a scheme of key performance indicators, it is necessary to take into account the fact that the indicators apply either to the entire company or to specific business processes or process attributes. Also, each company is specific in its process structure and size.
Some indicators measure the performance of individual systems and processes in the hotel and are specific to the industry, while others are more general and relate to the financial health of the company (e.g., profitability and liquidity indicators, cash flow, etc.). This will also be related to the adaptation of the selection of specific indicators according to the company’s own needs.
Table II shows the genral indicators that can be used when creating your own company performance evaluation model focused on the non-manufacturing sector. A clear scheme was created, which divides the indicators into individual groups according to the nature of the activity and the measurement of which they are supposed to cover. For the selection of key indicators to be effective, it must copy the assessment of the fulfillment of the company’s strategic objectives.
Overview of the proposed key indicators for measuring the performance of non-production processes | |
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Design and development | • Time to introduce a new product to the market • User effect from using the new product • Changes in the measure of customer value • Turning point • Productivity per design and development worker |
Maintenance | • Average time of performing one maintenance intervention • Average time from the detection of the fault to the start of the repair • Capacity utilization of maintenance workers • Maintenance efficiency index |
Purchase | • The share of supplier audit costs in total purchase costs • Average response time to requests from internal customers • Share of requests for inputs that can be satisfied e.g., within 24 hours to stock • Volume of losses in performance of other organizational units caused by non-conforming deliveries • Average inventory commitment • Inventory turnover |
After-sales service | • The speed of response to notification of non-conformity by the customer • Share of new requests for service to the total sweat of requests over time • Average periods of guarantees provided by customers • Utilization of service worker capacity • Share of fulfilled customer service commitments to total commitments |
Customer satisfaction and loyalty | Customer and business perception: |
• Image • Quality, reliability, customer value, compliance with delivery times, environmental profile • Sales and after-sales services • Loyalty | |
Perception of the company: | |
• Structure of customers • Share of new customers • Performance vs. Prices • Share of sales of individual products | |
Employee satisfaction | Perception by employees: |
• Motivation • Satisfaction-working conditions, workplace equipment and services • Social benefits | |
Perception of the company: | |
• Employee productivity • Costs vs. success of training, certification • Motivation and commitment • Employee satisfaction • Employee turnover • Number and quality of improvement proposals • IInjuries, morbidity |
Important performance indicators used to evaluate performance within the provision of hotel services will be analytically described below. Selected indicators were processed according to the authors (Kaplan & Northon, 2007; Maalimet al., 2023; Saniuket al., 2022).
Key performance indicators for room rating:
- Number of overnight stays: the most elementary statistic utilized within the hotel industry, albeit its simplicity, proves to be an invaluable metric, as it quantifies the tangible utilization of rooms. This metric serves as a fundamental component within hotel revenues. A variant of this metric termed the “number of occupied rooms,” is commonly employed, denoting the count of rooms occupied during a specific time frame, irrespective of the occupancy per room.
- Rate of occupancy: the assessment of the occupancy rate and the utilization rate of hotel room capacities can be conducted through two distinct methodologies: the calculation of overnight stays per individual and the room occupancy rate. Notably, hotels feature diverse room categories with varying bed capacities, while the demand for these differing room types may not be uniform. Additionally, certain rooms may offer the provision of extra beds. The occupancy rate serves as an indicator of a hotel’s revenue-generating potential by augmenting the count of guests, nights, and rooms sold. Typically, the occupancy rate fluctuates based on:
- Regarding the influence of the day of the week, occupancy rates typically exhibit an increase during weekdays for business-oriented hotels, while experiencing a decrease on weekends. Conversely, for leisure-focused establishments, the pattern is reversed, with higher occupancy rates observed on weekends and lower rates during weekdays.
- Seasonality: Accounting for tourism patterns across seasons, with coastal areas experiencing heightened activity during summer months and mountainous regions catering to visitors both in summer and winter seasons.
- Market segmentation: Business travelers typically prefer single occupancy accommodations; however, as hotels often have limited single-room capacities, individual guests may be accommodated in double rooms. While this practice does not directly impact room occupancy rates, which are measured by room count, it does affect occupancy rates calculated based on overnight stays.
- Special events: Events such as sports competitions, exhibitions, conferences, congresses, festivals, and similar gatherings draw substantial numbers of visitors to destinations, consequently elevating the demand for accommodations and hotel occupancy rates.
- Miscellaneous factors: Considerations encompassing availability, competitive actions, marketing strategies, hotel operations, product quality, and other determinants influencing the demand for hotel services.
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Average daily price: A straightforward metric that is easily comprehensible by hotel stakeholders, including managers, staff, and investors, and is the average price per person or room per overnight stay. This metric, widely utilized due to its simplicity and ease of calculation, signifies the price charged by the hotel on average for each guest or room occupied overnight. It serves as an indicator of the hotel’s capacity to generate revenue from room occupancy or guest count. This metric can be computed individually for various room types (e.g., standard, business, deluxe, studios, apartments) or for the entire hotel. The variability in this metric is primarily contingent upon:
- Weekday and weekend pricing dynamics: Business-oriented hotels typically exhibit higher prices on weekdays and lower prices on weekends, mirroring the trends observed in occupancy rates. Conversely, leisure-focused properties tend to command higher prices on weekends and lower prices on weekdays.
- Seasonal variations: Prices tend to be elevated during peak tourist seasons and reduced during off-peak periods.
- Market segmentation: Price differentials are often implemented based on the market segment, reflecting varying levels of service and amenities.
- Impact of special events: Special events such as Oktoberfest or world championships contribute to increased demand for accommodations, obviating the necessity for promotional efforts to stimulate demand and consequently boosting pricing indicators.
- Contractual agreements: Pricing levels and booking conditions negotiated through distribution channels utilized by the hotel can influence pricing indicators. Higher rates secured through contracts with intermediaries can result in an increase in pricing indicators.
- Room type preferences: Booking of more upscale room categories tends to elevate pricing indicators.
- Miscellaneous factors: Various other factors, such as those affecting the demand for a particular hotel’s product, can also impact pricing indicators.
Nonetheless, the primary limitation of this metric lies in its exclusive focus on revenue generated from room sales. For luxury business or leisure hotels, room revenue may represent only a fraction—around or less than half—of the total revenue. Consequently, this necessitates the adoption of the following metric:
- Total revenue per occupied room: This metric offers the advantage of encompassing revenue derived from ancillary services, thus providing a comprehensive assessment of overall hotel revenue. It accounts for turnover generated from various additional services provided by the hotel.
- Length of stay: This metric denotes the average duration of guests’ overnight stays at the hotel. For instance, motels and airport hotels typically exhibit low length-of-stay statistics, averaging around one night. In contrast, business hotels typically observe stays of approximately 2–3 nights, while leisure-oriented establishments may experience stays of 5–7 nights or longer. The length of stay correlates with both costs and income; longer guest stays necessitate less frequent linen changes, thereby marginally reducing variable costs. Additionally, extended stays offer increased opportunities for hotel staff to promote and sell additional services to guests. Moreover, longer stays contribute to a decrease in the number of check-ins and check-outs, subsequently alleviating the workload on departments such as reception, front office, and housekeeping. Consequently, hotels often incentivize longer stays by offering discounts, either through reduced room prices or complimentary additional nights (e.g., “stay 7 nights, pay for 6”).
In Table III, other characteristics are processed. indicators that influence the level of profitability in the hotel industry and need to be considered when creating products that the hotel offers to customers from the point of view of market segmentation.
Market segment | Characteristics of revenue management |
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Independent travelers | • Frequently travel by automobile • Weekend or paid holiday travel • Direct bookings or via travel agencies • Shorter duration of stay - 1–6 overnight stays |
Leisure travelers (charter programs, bus excursions) | • Groups with fixed arrival and departure dates • Longer length of stay-7–14 nights • Reservations through tour operators • High seasonality of demand |
Senior traveler | • High price elasticity |
Leisure tourists (bus tours) | • Groups with a brief stay-1 to 3 nights • Reservations predominantly made through travel agencies, with direct bookings being rare (e.g., school trips) • Tourists often exhibit shared characteristics such as interests, educational institutions, or workplaces • Accommodations typically situated near tourist attractions or offering excellent transport accessibility, often located on the periphery of urban areas • Demand characterized by high seasonality |
Business travelers (business trips, special events, teambuildings) | • Brief stay-1 to 3 nights • Accommodation primarily sought during weekdays • Reservations made either directly or through a travel agency • Preference for lodging near their workplace in the destination • Reduced seasonality in demand • Low price elasticity • Utilization of additional business services such as fax, copier, and scanner • Rooms equipped with a desk and internet access |
Families with children | • Significant price elasticity • Traveling during weekends, holidays, and school breaks • Utilization of various additional services including babysitting, video games, and retail offerings |
Sports teams | • Booking a substantial quantity of rooms for the team and accompanying individuals such as coaches and doctors • Dtays ranging from 1 night (during competitions) to 14–21 overnight stays (during training camps) • Emphasis placed on comfort and training needs over price considerations • Utilization of various additional serviced |
Music/movie stars | • The duration of stay varies depending on the purpose of the trip, ranging from one night for concerts to several months for film shoots • Luxurious accommodation in apartments is preferred • Provision of multiple rooms for accompanying persons • Utilization of several additional services • Femonstrates low price elasticity |
Tourists with pets | • Low price elasticity • Typically, a high willingness to pay • Low competition within the segment, as not all hotels accommodate pets • Stays may be extended if pets are participating in competitions |
When obtaining information and the necessary input data for an effective analysis of the effectiveness of processes with a good reporting ability, the following requirements should be reflected:
- Accuracy— the data reflect the real situation,
- Timeliness— data is provided when necessary,
- Adequacy— detailed enough to make an informed decision-not too small a volume of data, as in-depth analysis is not possible, and not too large, as this can lead to misinformation,
- Low acquisition cost— the data are authorized for use only if they significantly increase the accuracy of forecasts and the quality of revenue management decisions.
Data can be obtained from various sources. The main source of operating data is the hotel’s internal accounting system and its asset and revenue management software. Operating data are usually easily available or can be easily obtained or calculated. They are also visualized by corporate information software through the use of appropriate graphic tools, which are a supporting tool in the decision-making process.
All guest reservations and transactions must be promptly recorded in the hotel’s internal database to provide hotel managers with real-time access to financial and operational statistics. However, achieving this necessitates a sophisticated property and revenue management system that seamlessly integrates all departments and maintains real-time connectivity with the website and all point-of- sale (POS) terminals within the hotel. The utilization of QR codes and RFID tags could streamline the automatic input and retrieval of data to and from the information system. In Table IV, information necessary for the process of managing the company’s profitability is processed.
Data specification | Key performance indicators | Data source |
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Operation | • Quantity of reservations on a specific date (total, per date, per distribution channel/room type/segment) • Duration of stay (average, per distribution channel/room type/segment) • Pricing information (average per distribution channel/room type/segment) • Number of cancellations of confirmed reservations (average, per distribution channel/room type/segment) • Quantity of booking requests for a given date • Number of rooms per reservation (average, per distribution channel/room type/segment) • Instances of rejections (per date, distribution channel/room type/segment) • Utilization of supplementary services-categorized by type, period, and segment • Frequency of repeat customer visits • Demographic attributes of guests-age, gender, nationality, etc. • Variable costs per night/room night • Analysis of webpage/website visits | • Hotel revenue management system/software • The website of the hotel, or chain • Accounting documentation of the hotel, or chain • Google Analytics service data for the hotel website, or chain • Ad hoc marketing research |
Customers | • Size and volume of sales • Criteria for hotel selection-location, pricing, quality, price-to-quality ratio, availability of specific amenities, brand affiliation, etc. • Level of loyalty towards hotel chain brands • Demographic attributes of market segments • Teservation characteristics-timeframe, duration of stay, group size • Price elasticity and willingness to pay within segments • Preferred distribution channels | • Reports, datasets and publications of international organizations (UNWTO, OECD, UNO, Eurostat, WTTC, IATA, etc.) • Reports, datasets and publications from government bodies and national statistical offices • Reports, datasets and publications by national, regional and local tourism organizations (destination marketing |
Competition | • Size and volume of sales • Category, location, services offered • Prices and booking conditions • Positioning in the market • Used distribution channels • Current promotions | organisations, convention and visitor bureaus, tourism boards, tourism• boards, associations, etc.) • Hospitality reports (Keynote, Mintel, Euromonitor, Datamonitor)• Websites of competitors, distributors |
Sellers, distribution network | • Business model-merchant or agency • Commission/surcharge levels • Quantity and geographical coverage of hotels listed on their websites • Size and volume of sales • Number of offices • Geographical distribution of customers • Positioning in the market • Current promotions | and customers • Social media pages/profiles of competitors, distributors and customers (Facebook, Twitter, Google+, LinkedIn, Foursquare, YouTube, TripAdvisor, etc.) • Annual financial reports of competitors and distributors |
Macro environment-PESTEL factors | Trends, developments and statistical data on various factors: • Political • Economical • Socio-cultural and demographic • Technological • Environment • Legal | • Search engines Kayak.com, Hotelscombined.com, Trivago.com, etc. • Visits to the distributor’s or customer’s office, in competing hotels • Advertisements from competitors and distributors • Tourism trade fairs • Blogs, forums, technology news • Bulletins of consulting companies • Academic publications • Press publications • Databases of legal regulations • Ad hoc marketing research |
Discussion
The goal in connection with increasing the hotel’s profitability should not be to maximize revenue at any cost. Various metrics related to increasing profitability in the hotel industry, as listed in Table IV, should be used in the analysis and setting of company goals. Gross operating profit can be calculated as the difference between net revenues and costs related to the provision of services to customers, e.g., cost of goods sold, marketing, administrative costs, and human resources costs. However, the optimal level of profitability does not necessarily mean that the gross operating profit is at its potentially maximum level, as it could be the result of a cost-cutting strategy, which, although sometimes necessary and necessary, often leads to a deterioration in service quality, customer dissatisfaction, or employees, which leads to potential losses of customers and subsequently revenues. Profitability management includes various processes, actions, and techniques.
From the above-mentioned facts, as well as from the practical experience of the authors, a conceptual diagram of the effects on profitability management in the hotel industry was developed, Fig. 1. The core of the conceptual scheme presented are the relationships between different concepts of profitability management in the context of prices, pricing techniques, the number and structure of hotel customers.
Fig. 1. Conceptual diagram of influences on profitability management in the hotel industry.
Conclusion
Demand in the field of tourism is quite diverse, which gives room for hoteliers to actively use various techniques to increase profitability. Hoteliers need to focus on the basic elements of the marketing mix, do their analysis, and, based on the results, develop an optimal strategy suitable for the given hotel:
- Right customer: Not all customers provide equal benefits to the hotel. Some may be deemed too costly due to their demanding requirements that the hotel cannot easily or profitably fulfill, while others may only seek low prices that fail to cover the hotel’s expenses. The identification of the ‘real’ customer is a subject of debate in marketing, as it should be aligned with the target market segment identified by the hotel’s marketing manager, whose needs influence the creation of the hotel’s product. Implementing the concept of the ‘real’ customer necessitates the use of diverse marketing strategies to attract customers. Hotels often enforce minimum stay requirements during specific busy periods (e.g., fairs, exhibitions, and world championships), which dissuade customers from seeking short stays in favor of more lucrative guests with longer durations.
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Right product: The determination of the optimal product involves collaboration between customers and hoteliers. It entails creating a product that:
- Delivers value to the “right” customers by meeting their needs, desires, and demands,
- Aligns with the customer’s willingness to pay,
- Ensures profitability for the hotel partner.
Providing hotel services and amenities that do not align with the needs of the target market segment or offering services/equipment beyond their financial means is futile. Such offerings would not only fail to generate profit for the hotel but also risk alienating potential customers.
- Right price: Price constitutes one of the pivotal instruments in profitability management as it correlates directly with revenue generation. The optimal price is defined as the one that aligns with both customer willingness to pay and the hotel’s profitability objectives. Naturally, customers aim for lower prices, whereas hotels strive to maximize charges. Any discrepancy between the perceived value of the service and the price paid jeopardizes future interactions between the parties involved.
- Right timing: Timing emerges as a paramount concept within profitability management. The perception of the same offer can vary significantly based solely on the timing of its implementation. For instance, a pre-Christmas promotion introduced in July would likely pass unnoticed due to its premature release. Similarly, launching the same offer at the onset of December might prove ineffective as it could be too late for customers to capitalize on the promotion by booking a hotel. The optimal timing hinges upon the booking patterns within specific market segments. For instance, if a target segment typically finalizes most bookings within two weeks preceding the registration date, the ideal release date for the promotion maybe 2 to 3 weeks before registration, ensuring its visibility to potential customers.
- Right communication: In the realm of profitability management, a hotel’s marketing communication plays a pivotal role in shaping the perception of its products and pricing. The manner in which information is conveyed on a hotel’s website, or the presentation of prices, can profoundly influence customers’ perceptions regarding the value proposition of the hotel’s offerings and the fairness of pricing structures. Consequently, this impacts the perceived “price/value” ratio and influences customer satisfaction with their purchase, subsequently influencing their intentions for future purchases.
References
-
Alreahi, M., Bujdosó, Z., Dávid, L. D., & Gyenge, B. (2023). Green supply chain management in hotel industry: A systematic review. Sustainability, 15, 5622. https://doi.org/10.3390/su15075622.
Google Scholar
1
-
Bednarova, L., Simkova, Z., & Pavolova, H. (2020). Internal benchmarking in slovak SME: A case study. Polish Jounal of Managment Studies, 21(21), 104–118.
Google Scholar
2
-
Bowen, D. E., & Youngdahl, W. E. (1998). Lean service: In defense of a production-line approach. International Journal of Service Industry Management, 9(3).
Google Scholar
3
-
Cuatrecasas, L. (2004). A lean management implementation method in service operations. International Journal of Services Technology and Management, 5(5–6), 532–544.
Google Scholar
4
-
Glova, J., Mrazkova, S., & Dancakova, D. (2018). Measurement of intangibles and knowledge: An empirical evidence. AD Alta-Journal of interdisciplinary research, 8, 76–80.
Google Scholar
5
-
Grabis, J., & Kampars, J. (2018). An approach for implementation of project management information systems. Conference on Advanced Information Systems Engineering (CAiSE).
Google Scholar
6
-
Gregor, M., Hodon, R., Grznar, P., & Mozol, S. (2022). Design of a system for verification of automatic guided vehicle routes using computer emulation. Applied Sciences, 12(7), 1–25.
Google Scholar
7
-
Grznar, P., Gregor, M., Gola, A., Nielsen, I., Mozol, S., & Seliga, V. (2022). Quick workplace analysis using simulation. International Journal of Simulation Modelling, 21(3), 465–476.
Google Scholar
8
-
Gupta, S., & Sunder, MV. (2016). Lean services: A systematic review. International Journal of Productivity and Performance Management, 65(8), 1025–1056. https://doi.org/10.1108/IJPPM-02-2015-0032.
Google Scholar
9
-
Herzog, I., & Grabowska, M. (2021). Quality cost account as a framework of continuous improvement at operational and strategic level. Management and Production Engineering Review, 12(4), 122–132.
Google Scholar
10
-
Hsieh, Y. -H., Chen, H., & Chang, W. (2010). The application of lean concept combines. Demand Channel and Supply Channel in Service Industry, IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 1309–1313.
Google Scholar
11
-
Kabele, P., & Edl, M. (2020). Increasing the efficiency of the production process due to using methods of industrial engineering. 2nd International Conference on Design, Simulation, Manufacturing - The Innovation Exchange (DSMIE), Lutsk, Ukraine, pp. 126–137.
Google Scholar
12
-
Kaplan, R. S., & Northon, D. P. (2007). Balanced Scorecard. 5th ed. Czech Republic Praha: Management Press.
Google Scholar
13
-
Knapcikova, L., Behunova, A., & Behun, M. (2020). Using a discrete event simulation as an effective method applied in the production of recycled material. Advances in Production Engineering & and Management, 15(4), 431–440. https://doi.org/10.14743/apem2020.4.376.
Google Scholar
14
-
Maalim, B. M., Ndolo, J., & Kibe, L. W. (2023). Influence of altruistic strategy on organizational commitment in five star hotels in Kenya. European Journal of Business and Management Research, 8(3), 176– 182. https://doi.org/10.24018/ejbmr.2023.8.3.1957.
Google Scholar
15
-
Raid, A., & Matloub, H. (2018). Waste analysis and categorization in the construct of hotels supply chain. Tourism Management, 69, 553– 565. https://doi.org/10.1016/j.tourman.2018.06.030.
Google Scholar
16
-
Revilla-Camacho, M. -A., Rey-Moreno, M., Gallego, A., & Casanueva, C. (2019). A resource generator methodology for hotels. Journal of Innovation & Knowledge, 4, 78–87. https://doi.org/10.1016/j.jik.2017.10.002.
Google Scholar
17
-
Rosova, A., Behun, M., Khouri, S., Cehlar, M., Ferencz, V., & Sofranko, M. (2020). Case study: The simulation modeling to improve the efficiency and performance of production process. Wireless Networks, 28(3), 1–10.
Google Scholar
18
-
Saniuk, S., Grabowska, S., & Straka, M. (2022). Identification of social and economic expectations: contextual reasons for the transformation process of industry 4.0 into the industry 5.0 concept. Sustainability, 14(3), 1–20.
Google Scholar
19
-
Sharma, R. (2020). View: Five winners of the post-pandemic global economy, and a dark horse [Online].
Google Scholar
20
-
Siguaw, J. A., & Enz, C. A. (1999). Best practices in food and beverage management. Cornell Hotel and Restaurant Administration Quarterly, 40(5), 50.
Google Scholar
21
-
Straka, M., Sofranko, M., Glova, J., Vegsoova, O., & Kovalcik, J. (2022). Simulation of homogeneous production processes. International Journal of Simulation Modelling, 21(2), 214–225.
Google Scholar
22
-
Sánchez-Franco, M., & Aramendia-Muneta, M. E. (2023). Why do guests stay at Airbnb versus hotels? An empirical analysis of necessary and sufficient conditions. Journal of Innovation & Knowledge, 8, 78–87.
Google Scholar
23
-
Tortorella, G. L., Rosa, M. V. L. L., Caiado, R., Nascimento, D., & Sawhney, R. (2019). Assessment of lean implementation in hotels’ supply chains. Production, 29, e20190044. https://doi.org/10.1590/0103-6513.20190044.
Google Scholar
24
-
Vlachos, I., & Bogdanovic, A. (2013). Lean thinking in the European hotel industry. Tourism Management, 36, 354–363. https://doi.org/10.1016/j.tourman.2012.10.007.
Google Scholar
25
-
Younnes, D. (2023). The impact of lean manufacturing practices on green sustainability: The case of Abdulghani company. European Journal of Business and Management Research, 8(3), 62–67. https://doi.org/10.24018/ejbmr.2023.8.3.1905.
Google Scholar
26
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