The Influence of Competitiveness Factors on Sustainable Business Performance in the Hotel Industry: From the Perspective of the Perception of Hotel Service Users

Abstract

The aim of this study is to examine the impact of key competitiveness factors on sustainable business performance in the hospitality sector through the application of an integrated approach, from the perspective of hotel service users. The research was conducted on a sample of 1640 hotel guests who stayed in hotels operating in the Republic of Serbia, Croatia, and Slovenia. Utilizing a structural equation modeling (SEM) framework, the study meticulously analyzed various competitiveness factors: service quality, service, service recovery, hotel user satisfaction, loyalty and discretionary behavior and dysfunctional consumer behavior. The results of the research reveal that all identified key factors significantly impact the sustainable performance of hotel operations. The findings suggest that hotels must prioritize these elements to enhance their competitiveness and ensure ongoing success in a challenging market environment. Notably, one intriguing finding is that loyalty does not serve as a buffer in the relationship between customer dissatisfaction and dysfunctional behavior, indicating that even loyal customers can exhibit negative behaviors when their expectations are not met. This underscores the importance of addressing guest satisfaction proactively to mitigate potential adverse outcomes and retain a loyal customer base. Moreover, this study provides valuable insights for hotel management, highlighting the necessity for holistic strategies that not only aim to improve guest experiences but also consider the intricate dynamics between various competitiveness factors that ultimately contribute to the sustainability and profitability of the hospitality industry. Rejecting the sub-hypothesis that loyalty among hotel service users moderates the impact of dissatisfaction on the expression of dysfunctional consumer behavior indicates the need to review certain theories that comprise the dominant theoretical framework in the field of hospitality. This implies the need for further analysis of the validity of the dominant theories in the hospitality industry, especially in defining the conditions under which their postulates hold indisputably. Second, further examination of the role of loyalty is needed, since there are different types of loyalty.

1. Introduction

The immaterial nature of services and the involvement of service recipients in their creation contribute to the absence of a standardized process for assessing their value [1], making the evaluation reliant on personal experience. Consequently, studying competitive factors in the hospitality industry necessitates a focus on those elements that influence personal experience and user satisfaction [2]. Numerous empirical studies indicate that service quality [3,4], delivery failures [5,6], and service recovery [7,8,9] are key factors affecting the personal feelings of service users. Thus, it becomes reasonable to consider these factors and their impact on satisfaction when examining the influence of competitive factors on business performance in the hospitality sector.

However, given that satisfaction significantly impacts intentions (loyalty) and consumer behavior [10], as well as the fact that consumer behavior (both discretionary and dysfunctional) has a substantial effect on operational costs [11,12], it becomes essential to incorporate both factors into studying the influence of competitive factors on business performance in the hospitality industry.

On the other hand, the interdependence and mutual conditioning among competitive factors necessitate their simultaneous study. This implies that investigating the impact of these factors in hospitality requires a more complex approach than examining the individual and direct effects of factors on hotel performance. Therefore, it is crucial to consider the simultaneous influence of these factors when studying the impact of competitive factors on business performance in the hospitality sector. Hence, an integrated approach becomes imperative [13]. Such an approach enables the recognition of interaction effects among competitive factors, their interdependence, and ultimately their synergistic effects on hotel business performance.

Starting from this perspective, and based on the prevailing theoretical viewpoints in hospitality, it becomes necessary to emphasize that the study of competitive factors in the hospitality industry should be rooted in the simultaneous examination of the impacts of service quality, delivery failures, service recovery, customer satisfaction, and loyalty as competitive factors that precede and shape consumer behavior and its influence on business performance in hospitality. The significance of this approach in studying the effects of competitive factors on business performance in the hospitality sector also stems from its ability to consider the individual trajectories of the influence of the highlighted factors, as well as specific combinations among them. Thus, the subject of research is the study of the influence of competitive factors on business performance in the hospitality industry, considering the complex dynamics of interrelations and dependencies among factors that directly and indirectly affect hotel performance through their impact on consumer behavior. Of course, to be completely precise in presenting the research goal, it is important to emphasize an approach that examines the influence of the mentioned factors through the lens of the perception of hotel service users, as it is not possible to investigate their direct impact.

This research was conducted using examples of hotels operating in the Republic of Serbia, the Republic of Croatia, and the Republic of Slovenia. The fact that no research has been conducted studying these issues in the context of hotels operating in these countries underscores the imperative to explore this topic. Alongside the deficiencies of studies focusing on the impact of selected competitive factors on hotel performance, the need for such research arises from the understanding that different strategies must be employed to enhance loyalty in various countries [14]. In the context of the research subject, the findings from [14] suggest that the specific operating conditions in different countries influence how competitive factors affect subsequent consumer behavior (loyalty) in distinct ways. The unique operating conditions of hotels in these countries emerge from distinctive legislation governing the establishment and operational conditions of hotels, specific macroeconomic environments, incomplete processes of privatization of existing hotel enterprises, and the modernization of tourism and hospitality offerings in accordance with global standards and categorization. Additionally, the lack of internationally qualified hotel and tourism managers and the necessity for establishing suitable educational institutions for training future professionals according to international standards, among other factors, contribute to these conditions [14,15]. The implication of this is that findings from different studies cannot suffice to draw universal and definitive conclusions, thereby creating an opportunity for this study to contribute to the subject matter. Given the insights from the research in [16] regarding the dichotomous mediating role of loyalty in the influence of competitive factors on consumer behavior in hotel services, studying this issue through an integrated approach appears highly justified.

In addition to what has been previously stated, it should be noted that the occupancy of hotels in these countries ranges from 73% to 92%. The exception is during the peak season. Therefore, the research findings can contribute to improving capacity occupancy even outside this season. Regardless of this, strong competition, which increases day by day, means that hotels, regardless of their current position, must continuously work on improving their business.

2. Literature Review

The significant interest of both the professional and academic communities in studying competitive factors in the hospitality industry is not unexpected, given that hospitality is a key segment of this sector. Hospitality represents the fastest-growing area in tourism, which has experienced rapid growth over the past three decades [17]. This growth was only temporarily slowed due to the pandemic caused by the COVID-19 virus. According to the World Travel and Tourism Council and the United Nations World Tourism Organization, tourism directly or indirectly supports around 320 million jobs, accounting for 10% of all employment [18], and generates approximately 9.1% of the global gross domestic product [19]. A quarter of all newly created jobs in recent years have been in this sector [20]. This sector is vital for economic growth and the economy of 191 countries and 25 regions worldwide [21]. The direct impact of tourism on GDP ranges from 5% to 14%, depending on whether it concerns highly developed or underdeveloped countries [21]. Furthermore, tourism is recognized as the most profitable sector of the tertiary industry [22], and it is expected to continue to experience rapid growth, although occasional slowdowns in growth rates may occur due to various negative factors such as recessions, economic crises, conflicts, terrorist attacks, and pandemics.

The share of hospitality in this regard is significant, both in terms of revenue generation and workforce engagement [23]. The importance of hospitality is reflected not only in its direct contribution to national economies through income generation and unemployment reduction but also in its role in diversifying national economies and reducing dependency on exploitative sectors of primary and secondary industries. This is particularly significant for developing countries aiming to promote more equitable economic development and the growth of rural and marginalized regions, thereby preventing migration from these areas and improving the living standards of the local population.

Therefore, considering the significance of tourism for the development of national economies and the role of hospitality in advancing tourism, as well as the pivotal contribution of hospitality businesses to generating substantial revenues and engaging a large workforce, it is not surprising that emphasis is placed on studying the methods and factors influencing competitiveness in hospitality. Ref. [24] emphasizes that interest in hotel operations arises from the significance of their performance for various stakeholders. The result of this considerable interest in competitive factors in hospitality is the emergence of three major groups of research within the literature. The first group consists of studies examining the impact of service quality and quality-related factors, such as service delivery failures and service recovery, on hotel performance. Such studies have been conducted by authors including those of [3,4,6,9,23]. The findings of these studies uniformly position service quality as a significant factor for business success in hospitality. This is attributed to the absence of a standardized process for hotel rating assessment, leading to hotels worldwide being evaluated based on the quality of the content and services they offer, which is considered to have a significant influence on guest satisfaction. Among these authors, there is no consensus regarding which dimension of service quality has the greatest impact. Refs. [25,26] argue that the tangible dimensions of service quality are the most significant factors, while [3,23,27] suggest that the intangible dimensions of service quality are more important. Authors such as those of [2,5,28,29] stress that service recovery may be as important, if not more important, than service quality itself as a competitive factor. This is explained by the fact that the intangible nature of services often leads to delivery failures in hospitality, making efficient recovery a key factor in retaining service customers.

Regardless of whether emphasis is placed on service quality or service recovery, the findings of the studies indicate a clear inverse relationship between service quality and service failures, highlighting the opposite impact of service quality and service failures on hotel guest satisfaction, and consequently, on hotel competitiveness. Despite a multitude of studies, few have simultaneously explored the influence of both competitive factors on hotel performance, whether directly or indirectly through customer satisfaction and loyalty. Interestingly, there are no studies that have incorporated service failures into their models within the hospitality sector, although such research has been conducted in the context of e-commerce.

The second major group of studies focuses on the impact of customer satisfaction and loyalty in hotel services on hotel performance. These studies have been conducted by authors of studies such as [14,30,31,32,33,34]. The findings from these studies indicate that while satisfaction is a necessary condition for customer loyalty, it is not sufficient on its own. Loyalty emerges as a significant competitive factor in hospitality, serving as a stable source of revenue for hotels and as a cost-free promotional asset.

The third group of studies examines not only the aforementioned factors but also consumer behavior in a broader sense. Research within this category has been conducted by the authors of [11,12,16,35] and others. The increase in interest regarding dysfunctional consumer behavior in hospitality arises from the recognition that such behavior significantly impacts the operating costs of service enterprises. However, a notable outcome of this body of studies is the lack of a unified perspective on the mediating role of loyalty in enhancing positive and mitigating negative consumer behavior. From the standpoint of dominant theoretical frameworks in hospitality, such as social exchange theory and theories of aggression and frustration, loyalty should act as a positive mediator between customer satisfaction and discretion behavior, while it should serve as a negative mediator between customer satisfaction and dysfunctional behavior. Nevertheless, the studies [16,35] present contrary findings, suggesting that loyalty plays no role in the relationship between customer satisfaction and dysfunctional behavior, which contradicts both social exchange theory and theories of aggression and frustration. Given the previously mentioned insights, there are currently no studies that analyze all these factors simultaneously. The complexity and interdependence among these factors underscore the need for an integrated approach. In other words, it is necessary to examine the influence of all these factors simultaneously to fully understand their interactions and the synergistic effects they produce. Supporting this perspective is the research conducted in [13], which highlights the necessity for an integrated approach. Such an approach allows for consideration of the interaction effects among competitive factors, their interdependence, and ultimately their synergistic effects on hotel business performance.

Starting from this perspective, and based on dominant theoretical viewpoints in hospitality, it becomes evident that the study of competitive factors in hospitality should be anchored in an integrated approach that combines the influences of key competitive factors. This comprehensive framework aims to provide a clearer understanding of how various aspects interact and contribute to the overall competitiveness and performance of hotels in a dynamic and evolving market.

3. Materials and Methods

Based on the analysis of empirical research, it can be concluded that hotels can influence consumer (dis)satisfaction by providing services that align with consumer expectations or by ensuring that service failures are compensated in accordance with those expectations. This will affect customer loyalty, consumer behavior, and ultimately, hotel competitiveness. It is important to consider that the incidence of complaints and grievances depends on the cultural background of consumers [36], that the severity of service failures influences the type of emotional reaction [37], and that users react differently to service failures [38]. This indicates that the environment and social context in which the interaction occurs play a significant role.

Building on these observations and the understanding that satisfaction and loyalty summarize the influence of key competitive factors—service quality, service failures, and service recovery—that determine consumer behavior and intentions, which subsequently impacts the success of hotel operations and competitiveness in hospitality, a research model is presented in the rest of this paper.

The research model is illustrated in Figure 1. The model provides a graphical depiction of an integrated approach to studying the complex issues surrounding the impacts of competitive factors on business performance. It simultaneously examines the influences of service quality, service failures, service recovery, customer satisfaction, and loyalty as competitive factors that precede and shape consumer behavior and its impact on hotel business performance. The significance of this approach in studying the effects of competitive factors on hotel performance arises from its ability to consider the individual trajectories of the impact of the highlighted factors, as well as certain combinations of these factors.

To test the established hypotheses, SEM (structural equation modeling) was used. The application of the SEM model in examining the influence of competitiveness factors on the success of hotel business is beneficial, as it allows researchers to better understand the complex relationships among various variables. This method enables the simultaneous testing of multiple hypotheses and the analysis of both direct and indirect effects, providing deeper insights into the dynamics of competitiveness within the hotel industry. The SEM model also facilitates the evaluation of latent constructs, such as perceptions of service quality or customer loyalty, which are crucial for formulating strategic decisions aimed at improving hotel business performance. Furthermore, this methodology enables researchers to assess the validity and reliability of the model, thereby enhancing the credibility of the research findings.

3.1. Data and Sample of the Research

The research was conducted on a sample of 1640 hotel guests who stayed in 1 of the 94 hotels operating in the Republic of Serbia, the Republic of Croatia, and the Republic of Slovenia, which share a common socialist historical heritage that shapes the operating conditions in hospitality. We note that we only included properly filled-out questionnaires in the further analysis. A significant percentage of the questionnaires were omitted from further analysis because they did not contain answers to the questions asked, which primarily concerned negative service experiences, compensation, and others. Therefore, it is reasonable to assume that respondents who correctly completed the questionnaire had experience with service failures and service recovery and possessed sufficient knowledge to assess other items. Business performance was evaluated in accordance with the business excellence methodology. It is noteworthy that the hotels were grouped by star rating to ensure that each category was adequately represented in the sample. Additionally, it is important to highlight that half of the total number of respondents was used for testing the validity of the questionnaire through principal component analysis, while the other half was utilized for confirmatory factor analysis. The respondents were randomly divided, as conducting exploratory and confirmatory factor analyses on the same dataset is not appropriate [39]. Slovenia is recognized as a well-known alpine destination, with tourism contributing approximately 12% to its gross social product. Croatia is also a prominent tourist destination, with tourism accounting for around 10.3% of its total gross social product. In contrast, the share of tourism in Serbia is significantly lower, at about 1.3% before the onset of the pandemic, but Serbia wants to leverage its tourism potential for economic development.

Data were collected throughout 2024 using random sampling methods, specifically employing stratified sampling. Participants in the study were categorized into three groups of tourists: leisure tourists, business travelers, and digital nomads. This differentiation among respondents was made to ensure that each category was adequately represented in the sample. The distinction between digital nomads and business travelers is based on a study conducted by [40], which identifies digital nomads as individuals who have permission to stay in a foreign country for a longer period. Their length of stay is not determined by business obligations, but rather by the desire to experience a different culture and customs. Subsequently, participants within each category were selected through random sampling. This approach enabled a balance among different categories of hotel service users and ensured their proportional representation in the research, corresponding to their share of the total number of hotel guests. Detailed structural information about the hotel guests who participated in the study is presented in

Table 1. Respondent structure.

Country	Ser	Cro	Slo	Ser	Cro	Slo	Ser	Cro	Slo
Hotel Category	3			4			5
Leisure tourists	87	102	125	35	49	46	27	78	39
Business travelers	65	47	49	67	89	79	57	55	56
Digital nomads	65	139	132	22	51	31	18	22	28
Males	122	151	190	72	116	89	78	103	95
Females	95	137	116	52	83	57	24	52	28
Average length of stay in the hotel	3.9	6.8	4.3	3.6	5.8	6.3	1.87	3.1	3.5

Source: author’s calculations.

.

As can be seen from Table 2, the structure of the respondents predominantly consists of hotel service users motivated by leisure and recreation, followed by digital nomads. The participation of these tourists is particularly pronounced in the Republic of Croatia and the Republic of Slovenia, as both countries are members of the European Union, which significantly facilitates their arrival and extended stays. Most of these respondents are tourists from Western European countries. In contrast, business travelers represent the smallest segment; however, they are the most frequent visitors in five-star hotels.

When interpreting the findings of the research, it is important to consider the structure of the respondents, as the perception of hotel ratings influences the expectations of hotel service users. In other words, the number of stars a hotel has is linked to quality, hotel ratings, brand value, and so forth, which in turn affects the cognitive components of hotel guests’ perceptions and their expectations. Numerous studies confirm the existence of a positive correlation between hotel ratings and the number of stars, as well as guests’ expectations [4,41,42,43,44]. Furthermore, research by Makuljevic and Radivojevic [45] indicates that the motivation for and company during travel influence hotel guests’ expectations regarding the quality of accommodation at the destination. Data were collected throughout 2024 using a structured questionnaire developed based on relevant claims from the analyzed literature. Specifically, the items in the questionnaire were defined by considering theoretical and empirical studies related to competitive factors in hospitality [12,14,23,46,47]. The questionnaire is presented in Table 2.

Table 2. The questionnaire.

	Items	Label	Source
Service quality (QS)	Rooms are pleasant	Q1	[23]
	Rooms are easily accessible	Q2
	Rooms are clean and tidy	Q3
	Hotel exterior is attractive	Q4
	Interior decor is attractive	Q5
	Employees are willing to help guests	Q6
	Employees are never too busy to respond to guest requests	Q7
	Employees perform their tasks professionally	Q8
	They are well trained and knowledgeable	Q9
	Telephone and internet systems are efficient	Q10
	Billing system is accurate	Q11
	Reservation system is efficient	Q12
	Sports and recreational facilities are diverse and of high quality	Q13
	Other services are available	Q14
	Food and beverage prices are reasonable	Q15
	Gastronomy is authentic	Q16
	Food is of high quality	Q17
Service recovery (SR)	Employees show empathy	Q18	[2,9]
	Management expresses sincere apology	Q19
	Employees and management express other positive emotions, offering compensation	Q20
	Compensation is adequate	Q21
Service failure (SF)	I encountered unethical employee behavior	Q22	[48]
	Service was not provided	Q23
	I paid with a larger price than agreed	Q24
	I experienced inconvenience because I was unfairly accused of a service failure	Q25
Satisfaction (SAT)	I am satisfied with my overall experience with the hotel	Q26	[49]
	Overall, I am not satisfied with the hotel	Q27
	Overall, I am satisfied with the quality of the hotel	Q28
	I am satisfied with the behavior of the employees in resolving the problem	Q29	[16]
	I am satisfied with the procedure and resources used to resolve the problem	Q30
	I am satisfied with the amount and type of compensation	Q31
	I am satisfied with the speed and efficiency of resolving the problem and service failure	Q32
Loyalty (LOY)	I say positive things about this hotel	Q33
	I encourage friends to stay at this hotel	Q34
	I consider this hotel my first choice for accommodation	Q35
	I will choose this hotel even if the price of the stay increases by 10%	Q36
Dysfunctional behavior (DFB)	I have spoken to employees in an inappropriate manner	Q37	[12]
	I have threatened and insulted employees	Q38
	I have engaged in arguments with employees	Q39
	I have made unreasonable demands	Q40
	I have demanded special treatment	Q41
	I have demanded to speak to senior management	Q42
	I have asked employees to make me a special offer	Q43
	I have warned employees that their behavior is not in accordance with hotel policy	Q44
	I have made an illegitimate complaint	Q45
	I have blamed employees for a problem I caused	Q46
	I have been angry with employees even for small things	Q47
	I have complained without reason	Q48
	I have continued to complain despite employees’ efforts to help me	Q49
	I have complained to employees about the value of the service	Q50
Discretionary behavior (DB)	I take steps to protect the hotel from potential problems	Q51	[16]
	I take steps to reduce hotel costs	Q52
	I show concern for the efficient operation of the hotel	Q53
Business Performance (BP)	The hotel is using its full potential in all relevant areas and activities	Q54	[50]
	Hotel business can serve as a model for other organizations	Q55
	“Best in class” in many areas	Q56

Table 2. The questionnaire.

	Items	Label	Source
Service quality (QS)	Rooms are pleasant	Q1	[23]
	Rooms are easily accessible	Q2
	Rooms are clean and tidy	Q3
	Hotel exterior is attractive	Q4
	Interior decor is attractive	Q5
	Employees are willing to help guests	Q6
	Employees are never too busy to respond to guest requests	Q7
	Employees perform their tasks professionally	Q8
	They are well trained and knowledgeable	Q9
	Telephone and internet systems are efficient	Q10
	Billing system is accurate	Q11
	Reservation system is efficient	Q12
	Sports and recreational facilities are diverse and of high quality	Q13
	Other services are available	Q14
	Food and beverage prices are reasonable	Q15
	Gastronomy is authentic	Q16
	Food is of high quality	Q17
Service recovery (SR)	Employees show empathy	Q18	[2,9]
	Management expresses sincere apology	Q19
	Employees and management express other positive emotions, offering compensation	Q20
	Compensation is adequate	Q21
Service failure (SF)	I encountered unethical employee behavior	Q22	[48]
	Service was not provided	Q23
	I paid with a larger price than agreed	Q24
	I experienced inconvenience because I was unfairly accused of a service failure	Q25
Satisfaction (SAT)	I am satisfied with my overall experience with the hotel	Q26	[49]
	Overall, I am not satisfied with the hotel	Q27
	Overall, I am satisfied with the quality of the hotel	Q28
	I am satisfied with the behavior of the employees in resolving the problem	Q29	[16]
	I am satisfied with the procedure and resources used to resolve the problem	Q30
	I am satisfied with the amount and type of compensation	Q31
	I am satisfied with the speed and efficiency of resolving the problem and service failure	Q32
Loyalty (LOY)	I say positive things about this hotel	Q33
	I encourage friends to stay at this hotel	Q34
	I consider this hotel my first choice for accommodation	Q35
	I will choose this hotel even if the price of the stay increases by 10%	Q36
Dysfunctional behavior (DFB)	I have spoken to employees in an inappropriate manner	Q37	[12]
	I have threatened and insulted employees	Q38
	I have engaged in arguments with employees	Q39
	I have made unreasonable demands	Q40
	I have demanded special treatment	Q41
	I have demanded to speak to senior management	Q42
	I have asked employees to make me a special offer	Q43
	I have warned employees that their behavior is not in accordance with hotel policy	Q44
	I have made an illegitimate complaint	Q45
	I have blamed employees for a problem I caused	Q46
	I have been angry with employees even for small things	Q47
	I have complained without reason	Q48
	I have continued to complain despite employees’ efforts to help me	Q49
	I have complained to employees about the value of the service	Q50
Discretionary behavior (DB)	I take steps to protect the hotel from potential problems	Q51	[16]
	I take steps to reduce hotel costs	Q52
	I show concern for the efficient operation of the hotel	Q53
Business Performance (BP)	The hotel is using its full potential in all relevant areas and activities	Q54	[50]
	Hotel business can serve as a model for other organizations	Q55
	“Best in class” in many areas	Q56

Respondents rated their perceptions of the competitiveness factors using a Likert scale from 1 (completely disagree) to 5 (completely agree). Before testing the validity of the questionnaire as a measuring instrument, an analysis of the frequency and quality of the data was conducted. The results indicated that the data were not normally distributed. For this reason, a transformation was performed using the Box–Cox transformation.

3.2. Testing the Reliability and Validity of the Questionnaire

A sample of 820 randomly selected respondents was utilized to test the validity of the questionnaire through principal component analysis. Since the first step in this process involves assessing the adequacy of the samples, the Kaiser–Meyer–Olkin (KMO) test was conducted initially (0.797), followed by Bartlett’s test of sphericity on the entire sample $({\chi }_{1540}^2=-\mathrm{209,685.97}; p\mathrm{-value}=-0.001)$. The KMO test result clearly indicates a strong correlation among the factors, while the result of Bartlett’s test of sphericity suggests that the correlation matrix is indeed an identity matrix. Therefore, the results of both tests confirm the adequacy of the sample for further analysis.

The results of the principal component analysis indicate that the factors were grouped according to expectations, noting that an oblique Promax rotation was utilized, which is common in the field of social research. Promax rotation was selected due to the expectation of significant correlations among the latent factors. Specifically, it was anticipated that there would be substantial correlations among the latent factors in the model, such as quality, satisfaction, service failures, and others. Accordingly, the application of factor analysis was based on the covariance method. From the further analysis, items Q17 and Q27 were excluded because their factor loadings were less than 0.4, a commonly accepted validity criterion in principal component analysis [51,52].

Hence, items were organized into eight factors (sub-scales): QS—service quality, SR—service recovery, SF—service delivery failure, SAT—customer satisfaction with hotel services, LOY—customer loyalty, DFB—dysfunctional behavior of hotel service users, DB—discretionary behavior of hotel service users, and PB—business performance. These factors each had eigenvalues greater than one, which is a commonly accepted criterion for validity [51,52].

The internal consistency among the items was tested using Cronbach’s alpha coefficient. The value of this coefficient ranges from a minimum of 0.770, for BP, indicating acceptable internal consistency, to a maximum of 0.989 for QS, indicating excellent internal consistency. In all cases, the sub-scales passed the reliability test of the questionnaire (0.916 for SR; 0.907 for SF; 0.880 for SAT; 0.889 for LOY; 0.968 for DFB; 0.811 for DB). The overall questionnaire also demonstrated strong reliability, with a Cronbach’s alpha coefficient of 0.924.

The convergent and discriminant validity of the questionnaire, as a measurement instrument, was tested using confirmatory factor analysis. This type of factor analysis was chosen because it allows for a more detailed examination of the specific representations and relationships among factors. For this purpose, the second half of the respondents was utilized. The fit indexes shown in

Table 3. Fit indexes.

Name of Index	Value
Comparative Fit Index (CFI)	0.892
Tucker-Levis Index (TLI)	0.885
Bentler-Bonett normalized fit index (NNFI)	0.885
Relative non-central index (RNI)	0.892
Root Mean Square Error (RMSEA)	0.029
Standardized root mean square error (SRMR)	0.038

Source: author’s calculation.

, while the results of the confirmatory factor analysis are presented in

Table 4. Results of confirmatory factor analysis.

Latent Factor	Item	Factor Loadings	St. Error	Z-Test	p	AVE	CR
QS	Q4	0.631	0.026	24.27	<0.001	0.52	0.91
	Q5	0.787	0.026	30.27	<0.001
	Q6	0.797	0.026	30.65	<0.001
	Q7	0.736	0.027	27.26	<0.001
	Q8	0.816	0.027	30.22	<0.001
	Q9	0.634	0.027	23.48	<0.001
	Q10	0.693	0.028	24.75	<0.001
	Q11	0.696	0.028	24.86	<0.001
	Q12	0.677	0.03	22.57	<0.001
SR	Q18	0.849	0.029	29.28	<0.001	0.58	0.80
	Q19	0.614	0.047	13.06	<0.001
	Q20	0.807	0.029	27.83	<0.001
SF	Q22	0.747	0.032	23.34	<0.001	0.57	0.84
	Q23	0.822	0.032	25.69	<0.001
	Q24	0.777	0.032	24.28	<0.001
	Q25	0.664	0.032	20.75	<0.001
SAT	Q27	0.759	0.03	25.30	<0.001	0.52	0.74
	Q28	0.823	0.031	26.55	<0.001
	Q29	0.656	0.03	21.87	<0.001
	Q30	0.637	0.031	20.55	<0.001
	Q31	0.699	0.031	22.55	<0.001
LOY	Q33	0.899	0.035	25.69	<0.001	0.51	0.80
	Q34	0.549	0.036	15.25	<0.001
	Q35	0.541	0.037	14.62	<0.001
	Q36	0.806	0.035	23.03	<0.001
DFB	Q37	0.551	0.035	15.74	<0.001	0.51	0.86
	Q38	0.792	0.033	24.00	<0.001
	Q39	0.778	0.035	22.23	<0.001
	Q40	0.627	0.035	17.91	<0.001
	Q41	0.885	0.032	27.66	<0.001
	Q43	0.567	0.034	16.68	<0.001
DB	Q52	0.874	0.074	11.81	<0.001	0.87	0.93
	Q51	0.985	0.082	12.01	<0.001
BP	Q54	0.948	0.016	59.25	<0.001	0.51	0.74
	Q55	0.523	0.016	32.69	<0.001
	Q56	0.598	0.018	33.22	<0.001

Source: author’s calculation.

. The first step in applying confirmatory factor analysis is to examine the fit indexes to determine whether the developed model aligns with theoretical propositions. Given that different indices provide various perspectives and insights into the data structure, it is advisable to use multiple indices. For this reason, the paper employs fit indices from different groups. All indices exhibit satisfactory values, as suggested by the literature [35,53].

As can be seen from Table 3, all factor loadings are statistically significant. It is common practice to eliminate all items with factor loadings below 0.4 from the questionnaire; however, ref. [16] suggests that only items with factor loadings greater than 0.5 should be used in further analysis. In addition to factor loadings, the average variance extracted (AVE) is also a good indicator of the convergent validity of the questionnaire. While it is generally accepted that AVE values greater than 0.5 indicate good convergent validity [54], authors of studies such as [55] emphasize that lower values are also acceptable, as the AVE is a very conservative measure and considerably more rigorous compared to composite reliability (CR). In this study, composite reliability was used to assess the reliability of the questionnaire in the confirmatory factor analysis, as the application of Cronbach’s alpha coefficient is not as reliable in the context of principal component analysis. The results of the AVE and composite reliability ratios are presented in the last columns of Table 4.

Despite the claims that an AVE of 0.5 and above represents a stringent indicator of convergent validity and that slightly lower values are permissible, the very low value of this indicator in the case of service quality, along with the significantly lower factor loadings for this factor compared to the criterion of 0.4, indicates a potential issue with the convergent validity of the model. For this reason, only those items with factor loadings greater than 0.5 were considered.

The discriminant validity of the scales was tested based on the Fornell–Larcker criterion [56]. The square root of the AVE for each latent factor was compared with the correlations between the constructs, as shown in

Table 5. Results of the discriminant analysis.

Latent Factor	QS	SR	SF	SAT	LOY	DFB	DB	BP
QS	0.722
SR	0.557	0.762
SF	−0.223	−0.004	0.755
SAT	0.697	0.503	−0.182	0.718
LOY	0.656	0.302	−0.115	0.460	0.714
DFB	−0.253	−0.060	0.754	−0.362	−0.177	0.714
DB	0.620	0.649	−0.227	0.635	0.523	−0.332	0.933
BP	0.532	0.633	−0.009	0.509	0.282	−0.102	0.592	0.714

Source: author’s calculation.

. It is important to note that the square root of the AVE for each latent factor is displayed along the main diagonal. The results supported discriminant validity, as the correlations between each latent factor were lower than the square root of their respective AVE.

Since the questionnaire met the conditions for the convergent and discriminant validity of the measuring instrument, as well as reliability, it can be concluded that it is suitable for further analysis. In other words, in the continuation of the paper, the validity of the hypotheses was tested by applying structural equation modeling (SEM). SEM was utilized to determine the validity of the proposed research model and the relationships among the variables within that model. The paper employed the so-called SEM model based on covariances.

4. Results and Discussion

4.1. Results

As previously emphasized, the validity testing of the research model utilized structural equation modeling for testing the proposed hypotheses. The first step in validating the model, as well as in assessing the validity of the measurement component, involves examining the fit indexes; this step was initiated accordingly. The same indexes used in the measurement component of the model had good values. This implies that the testing of the proposed hypotheses can proceed. The results of the application of the SEM model are presented in

Table 6. SEM model results.

Latent Factor	Coefficient	St. Error	Z-Test	p-Value	Results
SAT-QS	0.331	0.029	11.414	0.000	H1 is accepted
QS-SF	−0.251	0.109	−2.303	0.021	H2 is accepted
SAT-SF	−0.375	0.095	−3.947	0.000	H3 is accepted
SR-SF	−0.116	0.051	−2.275	0.023	H4 is accepted
SAT-SR	0.304	0.105	2.895	0.004	H5 is accepted
LOY-SAT	0.284	0.037	7.676	0.000	H6 is accepted
DB-SAT	0.173	0.088	1.966	0.049	H7 is accepted
DB-(SAT * LOY)	0.249	0.059	4.220	0.000	H8.1 is accepted
DFB-(SAT * LOY)	−0.149	0.254	−0.587	0.557	H8.2 is rejected
BP-LOY	0.017	0.008	2.125	0.034	H9 is accepted
BP-DB	0.029	0.014	2.071	0.038	H10 is accepted
Indirect effect SF on SAT:
SF → QS → SAT	−0.083	0.009	−9.222	0.000	Partial effect
SF → SR → SAT	−0.035	0.008	−4.375	0.000
Total Indirect effect	−0.118	0.012	−9.833	0.000
Direct effect SF on BP *:	−0.005	0.019	−0.273 **	0.785	Non-significant
Indirect effect SF on BP:
SF → SAT → LOY → BP	−0.002	0.001	−2.022	0.043	Full effect
Indirect effect SAT on BP:
SAT → LOY → BP	0.005	0.002	2.526	0.011
SAT → DB → BP	0.005	0.002	2.500	0.012	Partial effect
Total Indirect effect	0.01	0.005	2.083	0.037
Direct effect SAT on BP *:	0.250	0.015	17.121	0.000	significant
Fit index: CFI = 0.892; TLI = 0.885; NNFI = 0.885; RNI = 0.892; RMSEA = 0.029; SRMR = 0.038

Note: * regression model; ** value of t test. Source: author’s calculations.

.

As can be seen from Table 6, the values of all coefficients are statistically significant at the 0.05% confidence level, which is standard in this type of research. The exception is sub-hypothesis H8.2, where the p-value of the coefficient representing the influence of loyalty in the relationship between the dysfunctional behavior of hotel service users and their satisfaction is 0.557, which is significantly higher than the established criterion. In other words, this result indicates that the coefficient is not significant, implying that loyalty does not contribute to alleviating dissatisfaction in the manifestation of dysfunctional behavior among hotel service users.

From the perspective of accepting or rejecting the hypotheses, the results indicate that all hypotheses can be accepted as valid, except for hypothesis H8. Specifically, hypothesis H8 cannot be accepted as valid because sub-hypothesis H8.2 has not been proven. The validity of hypothesis H8 relies on the validity of both sub-hypotheses H8.1 and H8.2. Since only sub-hypothesis H8.1 has been validated, hypothesis H8 cannot be accepted. This finding suggests the need to modify hypothesis H8 to read: ‘The loyalty of hotel service users has a modeling effect in the relationship between hotel service user satisfaction and positive consumer behavior’. Formulated this way, hypothesis H8 suggests the modeling role of loyalty in the relationship between the discretionary behavior of hotel service users and their satisfaction. Thus, hypothesis H8, as redefined, includes negative consumer behavior, known as dysfunctional consumer behavior. Hypothesis H8 could be accepted as valid if defined in this manner.

In the second part of Table 6, the results related to the indirect influence of SF on SAT are presented, which is achieved through QS and SR. The overall indirect effect of SF on SAT indicates the existence of a partial effect, which further implies the necessity to integrate the two individual models (the research stream that studies the influence and significance of SF, SQ, and SR) and the research stream related to satisfaction and loyalty. The finding that SF has no statistically significant effect on BP (when examined through the individual regression model) but that there is an indirect effect through SAT and LOY indicates the presence of a total effect. This further supports the importance of integration.

In the third part of Table 6, the findings related to the indirect influence of SAT on BP, achieved through LOY and DB, are presented. The direct effect of SAT (regression model) indicates that SAT influences BP; however, there is also an indirect effect through LOY, as well as DB. An interesting finding is that these two indirect effects are identical, suggesting that DB has an equally as significant influence as LOY but should not be considered without acknowledging the impact of loyalty, as loyalty has a positive moderating effect on the relationship between satisfaction and discretionary behavior.

The obtained results from the application of the SEM model have several significant implications that require more detailed analysis and clarification. Some findings align more or less with previous empirical research and the theoretical framework that predominates in the field of hospitality.

4.2. Managerial Implications

The findings presented in the previous section have several significant managerial and theoretical implications. First, it is important to emphasize that the key implication is that all factors must be observed simultaneously through an integrated approach. The findings highlight that service quality is a crucial factor in competitiveness within the hospitality sector, which aligns with the research of authors of studies such as [27,47,57]. For this reason, the focus must be on maintaining high service quality.

The significant influence of service failures on the perceived quality of service has two managerial implications. First, special attention must be given to reducing the number of service failures, as well as carefully shaping the expectations of potential service users. According to theory, expectations regarding service quality are formed by potential hotel users under the influence of numerous factors, including all types of promotion, advertising, and communication from the hotel to the target market. Therefore, in the case of inadequate hotel promotion, unrealistic expectations may be created among potential users, leading to a significant gap between the expected and perceived experience with the hotel following the consumption of the service. Since any discrepancy between expected and delivered service quality can lead to potential dissatisfaction for the service user, a larger gap between expected and perceived quality will have a stronger impact on the risk of reduced satisfaction and loss of loyal customers. Ultimately, the consequences of this will be reflected in the erosion of the hotel’s competitiveness. This finding aligns with the results of the Forbes (2018) study [58]. For this reason, it is crucial to form realistic expectations among potential users. Doing so will help reduce the risk of excessive discrepancies between expected and actual quality to some extent. Secondly, the findings highlight the importance of service recovery. The understanding that effective service recovery can transform angry and frustrated hotel service users into satisfied and loyal guests, along with the reality that service failures are an inevitable occurrence, means that hotel management must place special emphasis on service recovery as a mechanism for mitigating the consequences of service failure. Service recovery must be treated as an equally important factor of competitiveness as quality itself. However, when accepting this attitude, one should always keep in mind the riskiness and unpredictability of the positive effect of recovery on consumer satisfaction and intentions. This is especially important to keep in mind when knowing the results of the research in [59], according to which an adequate recovery process (compensation amounts and other aspects of service recovery) should be chosen, which will lead to the paradox of service recovery.

The positive relationship between satisfaction and loyalty not only further emphasizes the importance of customer satisfaction but also shapes business strategy in the service industry. Satisfied and loyal customers share their positive experiences [60,61,62,63], activating word-of-mouth promotion mechanisms for hotels, which results in attracting new guests, significantly reducing marketing costs, and facilitating hotel positioning and differentiation. In the era of dominance of social media, writing positive reviews as a form of loyalty has a huge impact on the attitudes and behavioral intentions of potential users of hotel services. Therefore, hotels should actively encourage guests to share their positive experiences, recognizing word of mouth as one of the strongest and most effective marketing strategies. At the same time, they should find ways to utilize loyal guests as brand ambassadors [64]. Through loyalty programs, hotels can further enhance relationships with these guests [65,66]. This will also lead to an improvement in the hotel’s reputation, which affects hotel guests’ discretionary behavior, according to [67,68,69,70,71].

Since guest satisfaction can be enhanced through personalized service, the focus should be on strategies that enable this, as well as on staff engagement, which also plays an important role in increasing satisfaction and loyalty. Furthermore, satisfaction plays a key role in shaping consumer behavior. An explanation for this can easily be found in social exchange theory or expectancy theory. According to these theories, consumers make decisions based on the perception of benefits and costs, analogous to the satisfaction they obtain in exchanges between themselves and service companies. In this context, the satisfaction that users obtain from the services should be considered as an “attributable value”, in relation to the “costs” represented by shortcomings or uncertainties in that experience. When user satisfaction is high, the probability that they will be ready to participate in different forms of consumer behavior increases. Encouraging hotel service users to exhibit discretionary behaviors is particularly important in light of research that suggests that consumer citizenship behavior is behavior that creates value for companies and represents behavior that goes beyond the role expected of them [63,64,65,66]. In this context, discretionary behavior should be seen as a means of exploiting the talent and abilities of hotel service users in creating additional value for the hotel. The fact that they promote the hotel, consider the efficient use of resources, point out omissions, or help other users means that they actively participate in the maintenance and creation of value for the hotel, through the manifestation of their talents and abilities in performing these activities.

The significance of the above can best be understood in light of recent research findings by [72], which indicate that energy consumption represents a substantial portion of the total costs of hotel operations. Therefore, the rational behavior of hotel service users regarding energy consumption is a critical factor in the success of the hotel business. Additionally, the findings of the research in [73,74] should be included in this discussion, as they indicate that implementing measures to achieve sustainable hotel operations can have negative consequences on the success of hotel operations due to the significant investments required. Hotels are compelled to adopt these measures for various reasons, ranging from legal regulations to the necessity of maintaining and building a positive image as a socially responsible business entity. Consequently, any rational behavior exhibited by hotel guests contributes to alleviating this pressure on hotels, thereby enhancing their competitiveness.

4.3. Theoretical Implication

Not accepting hypothesis H8 as completely valid has several significant implications. According to social exchange theory and frustration theory, loyalty should have statistically significant modeling effects in the relationship between satisfaction and consumer behavior. According to the first theory, it should enhance the effect of satisfaction on the manifestation of positive consumer behavior; that is, it should lessen the impact of lack of satisfaction on the manifestation of dysfunctional behavior, according to the second theory. The fact that the coefficient describing the modeling effect between satisfaction and positive consumer behavior has a positive value of 0.249 and is statistically significant (p-value: 0.000) testifies to the validity of sub-hypothesis H8.1. Accepting this sub-hypothesis as valid has several significant implications. First, according to social exchange theory, when service users feel that the hotel has made significant efforts to meet their needs, they feel an obligation to reciprocate. As a result, they will undertake activities that fall within the domain of positive consumer behavior, even though they are in no way forced to behave in this way. In this way, they maintain the dynamics of social exchange with the hotel [35]. In this mechanism, loyalty influences them to find cognitive reasons to justify both their actions and the hotel’s actions in the case of possible service failures. The theoretical implications of this finding are reflected in the treatment of loyalty. Namely, the finding suggests that loyalty should not be treated only because of satisfaction, but also as a driver of positive behavior. This perspective suggests that loyalty is fundamental to the cognitive and affective experiences of hotel service users, influencing their behavior. However, adopting this point of view requires consideration of the factors that shape the cognitive and affective perceptions of tourists.

However, the fact that the coefficient describing the modeling effect between satisfaction and dysfunctional behavior is not statistically significant (p-value: 0.557) implies that sub-hypothesis H8.2. has not been proven valid and must be rejected. The implication of this is the finding that loyalty does not act as a shock absorber in the relationship between dissatisfaction and dysfunctional behavior. This indicates that loyal users of hotel services do not feel a moral obligation to help the hotel when the hotel does not provide the service in an unsatisfactory manner. The implication of this is reflected in the re-examination of the dominant theoretical framework in the hotel industry, or at least the definition of the conditions under which it is absolutely valid, because according to the leading theories, the moral obligation to help the hotel and display positive civic behavior and/or refrain from displaying dysfunctional behavior stems from an emotional connection which loyal guests establish with the hotel. This connection affects their ability to find cognitive reasons not to condemn the hotel in circumstances when they deliver inadequate service. The result of this should be a decision not to exhibit dysfunctional behavior and thus preserve the advantages of their relationship with the hotel, even when they are dissatisfied. Thus, the dominant body of theory suggests that emotions arising from loyalty should moderate their current dissatisfaction. However, rejecting sub-hypothesis H8.2 as non-governmental means acknowledging that loyalty does not mediate this relationship. A further implication is that rejecting this sub-hypothesis means that loyal guests, as well as disloyal ones, can harm the hotel with the same moral imperative and intensity, even when they are aware of their actions. In other words, nothing prevents them from finding valid reasons to reject the hotel as a victim and not to take retaliatory measures against it. In fact, it may be easier for them to “deny the hotel as a victim” and exhibit dysfunctional behavior. This further suggests that the immediate dissatisfaction caused by the provision of inadequate service outweighs the cognitive reasons that justify the maintenance of a long-term positive relationship between the hotel and the users of its services. In other words, negative emotions resulting from dissatisfaction with the service provided can outweigh positive emotions resulting from loyalty. This suggests that emotions caused by an ineffective service recovery process can further increase dissatisfaction and have a stronger impact on immediate behavior compared to loyalty that develops from long-term affective and cognitive responses in the guest–hotel relationship.

Furthermore, this implies that any failure to implement efficient service recovery increases the risk of (loyal) users exhibiting dysfunctional behavior and increases the risk of failure to promote further loyalty. At the same time, this finding indicates that relying on loyalty as a shock absorber in this context is a risky strategy, because its mediating role in the relationship between has not been confirmed. Therefore, it is crucial to foster an organizational climate and culture among employees that emphasizes the importance of adequately solving service failures and maintaining constant service quality. Such failures will affect the performance of the hotel in the short term only if they are effectively managed and resolved quickly. When handled properly, they should not affect future return visits. Employees must understand that repeat visits will occur only if guests believe that they have made sincere efforts to correct any mistakes and maintain the quality of service at a satisfactory level.

4.4. Research Limitations

A key limitation of this research pertains to the issue of selection bias among respondents, as it did not consider the type of experience with service failure and service recovery. It was assumed that the general experiences, knowledge, perceptions, and expectations of the respondents influence their evaluations of the quality of various elements of the hotel offerings, which in turn affects their brand experience. The validity of this assumption underscores the necessity of considering this limitation when interpreting the findings of this research. Furthermore, it is recommended that future researchers utilize specific models, such as the two-step Heckit model.

The second limitation stems from the fact that the research is based on ordinal data. In contrast to interval data, where there are clear differences between any two values, with ordinal data obtained using a Likert scale, the differences between ratings, or divisions on the scale, are a matter of subjective assessment by the participants in the survey. This means that the difference between ratings one and two for the same respondent does not have to be the same as the difference between ratings two and three, and so on. In addition, different respondents perceive the values of the marks on the scale differently. As a consequence, the collected data do not meet the assumption of linearity, which is equivalent to the assumption of normality in the data distribution. Since the application of factor analysis requires that the data be normally distributed, a transformation was performed in this paper. It is expected that during data normalization, there will be certain losses in the dataset concerning causality and the structure of relationships between latent factors.

The third limitation stems from the fact that during the collection of data and their processing and later interpretation, the influence of the respondents’ national cultures on their evaluations was not considered. Namely, culture and its multiple layers play an important role in shaping customers’ needs and preferences in the hospitality industry [75]. By surveying customers from Belgrade, Manchester, Thessaloniki, and Porto, it was found that customers have meaningfully different expectations and preferences and consequently value and assess the same dining service differently [76]. This is particularly important to mention in the context of the finding that loyalty should not be seen exclusively as an outcome or result of the satisfaction of hotel service users, but also as a driver of their later behavior in terms of displaying consumer civic behavior. The finding that loyalty is the driver of this behavior implies cognitive and affective feelings on behalf of the guests, which influence the behavior of the guests. However, accepting such a perspective implies that factors that influence the cognitive and affective perceptions of tourists must be considered. Bearing in mind that in some cultures people are more inclined to publicly express satisfaction or dissatisfaction, while in other cultures this is less common, this implies that national culture plays an important role in evaluating the attitudes of tourists. For example, in some Asian cultures, hotel guests may be reserved in expressing dissatisfaction to preserve harmonious relationships. This can lead to a lower service dissatisfaction rating, even if guests are not completely satisfied. In addition, cultural differences can influence how guests perceive and value certain aspects of the service. In some cultures, guests may value staff friendliness and attention to detail more, while others may be more focused on the efficiency and functionality of the service. This can result in different ratings of satisfaction in the same situations. The consequence of all this is that culture and its multiple layers affect the attitudes of the guests. For this reason, it is important to keep in mind this research limitation.

The list of limitations of the research certainly includes the structure of the respondents. The survey included mainly members of the millennial and Zen generation of tourists, while there was a relatively small participation of members of the so-called baby boom generation. The influence of the same exogenous and endogenous factors on the attitudes and perceptions of respondents depends to some extent on their age, (belonging to a certain generation of tourists), or life experience. Therefore, the structure of the respondents can have an impact on the research results.

When studying the role of loyalty in the relationship between the satisfaction of service users and the consumer behavior of hotel guests, the type of loyalty was not considered. Considering different types of loyalty, future research should take this diversity into account. In this way, it would contribute to a more comprehensive understanding of the role of loyalty as a mediator between satisfaction resulting from service recovery and consumer behavior as a citizen. Specifically, since loyalty is based on two fundamental dimensions—attitudinal, which refers to the emotional attachment of customers to a specific brand, and behavioral, which refers to the frequency of brand consumption due to the level of emotional attachment to the brand—when studying the mediating role of loyalty, it would be useful to consider all possible combinations of these two dimensions. Understanding which of the possible combinations of these two dimensions can contribute to better personalization of marketing efforts for each group of loyal guests is important.

When interpreting the findings of this study, it is important to consider the period in which the study was conducted. The study was conducted after COVID-19, when COVID-19 protection measures in hotels were no longer in effect. We note this because research [77,78,79,80] shows that during COVID-19, hotel guests showed problems with respecting the rules of behavior, showing selfishness and disregard for the safety of others. This behavior can be treated as a form of dysfunctional behavior.

Overall, since it is not possible to directly examine the impact of competitiveness factors on the sustainable performance of hotels, as such research would require a methodology that is currently not available, the research results should be accepted with caution, as they reflect the opinions and perceptions of the respondents. Given that their perceptions and opinions are influenced by various factors, and that these may change depending on changes in circumstances and those factors, the research results should be interpreted with this fact in mind.

5. Conclusions

The research was conducted on a sample of 1640 hotel service users who stayed in 1 of 94 hotels operating in the Republic of Serbia, the Republic of Croatia, and the Republic of Slovenia during 2024. The hotels were grouped by star rating, ranging from three to five stars. The reason for selecting only these hotels was the practicality of distributing the questionnaire. For this research, a special questionnaire was developed based on the relevant professional literature. The questionnaire was initially tested using principal component analysis and then confirmed through factor analysis, with the adequacy of the sample for assessing the validity and reliability of the questionnaire also evaluated. The results obtained from the research largely align with expectations. Specifically, all established hypotheses were proven valid, except for the hypothesis related to the mediating role of loyalty in the relationship between satisfaction and the consumer behavior of hotel service users. The rejection of the sub-hypothesis stating that loyalty among hotel service users mitigates the impact of customer dissatisfaction on the expression of dysfunctional consumer behavior indicates that the immediate emotions caused by dissatisfaction with the provided service outweigh those resulting from loyalty, which is a consequence of long-term relationships with the hotel brand. There are two implications of this finding. First, a re-examination of certain theories that represent a dominant theoretical corpus in hospitality is warranted. This implies the need for further analysis of the validity of these dominant theories, specifically to define the conditions under which their postulates hold unconditionally. The second implication is a deeper examination of the role of loyalty, since there are different types of loyalty. It should be determined which type of loyalty, in accordance with dominant theories in hospitality, mitigates dissatisfaction and prevents dysfunctional behavior. Other findings were consistent with expectations and the results of previous empirical research. The key finding of the study is the confirmation of the validity of the integrated approach to the study of the key factors of hotel competitiveness.

Overall, it should be emphasized that given the increasing integration of modern IT and AI into all aspects of life, future researchers are encouraged to include this variable in their research as a factor of competitiveness. This is particularly highlighted in light of the findings presented in [80].