The tourism sector has grown considerably thanks to digitalization, which facilitates planning and enables businesses and potential customers to connect more efficiently. This study analyzes the need for investment in Romanian tourism infrastructure and evaluates industry performance using data from 466 respondents who completed an online questionnaire about tourism attributes and outcomes based on their recent experiences. Through the triangulation method—including a content analysis, an analysis based on partial least squares structural equation modeling, and a combined importance–performance map analysis and necessary conditions analysis—this research identifies key elements of the tourism framework, the relationships established between them, and the priorities that require increased managerial attention to enhance customer-perceived performance. The study contributes to the scientific field by offering a novel customer-centric perspective on defining tourism infrastructure and provides practical insights for industry stakeholders to identify tourists’ needs and implement targeted strategies.
In developing countries, tourism has received increasing attention in the last decade, given its contribution to the economy (Gössling, 2000). Sainaghi et al. (2017) suggested that tourism productivity, efficiency, and performance are critical for the sector’s competitiveness. Similarly, to date, various researchers have tried to shed light on tourism sector performance either through studies on its determinants (Assaf and Josiassen, 2012; Corne and Peypoch, 2020) or by illustrating competitiveness as a representative element of the sector’s performance (Bazargani and Kiliç, 2021; Hanafiah and Zulkifly, 2019). Kim (2014) emphasized that destination attributes, which attract tourists and influence their decisions, enhance appeal by generating individual benefits. Similarly, research on Romanian tourism has addressed topics such as the determinants of international tourism demand for the country (Surugiu et al., 2011), the impact of the field on the sustainable development of rural areas (Ibănescu et al., 2018), tourist accessibility and satisfaction (Dumitrașcu et al., 2023), and tourist competitiveness (Băbăț et al., 2023).
Current studies in this area are focused on various determinants of tourism sector performance and competitiveness, such as sustainability (Vena-Oya et al., 2025), investments in digital infrastructure (Arici and Köseoglu, 2025), or various regional factors (Agiropoulos et al., 2024). Nevertheless, an integrated approach to these determinants is difficult to find. Therefore, this study proposes a holistic approach to the multiple attributes and effects of infrastructure, such as sustainability, time savings, accessibility, and safety, based on data collected directly from individuals who have benefited from the services of this industry, namely tourists. While a substantial body of literature on Romanian tourism exists, a key gap remains. Previous research has primarily focused on the sector’s overall performance and competitiveness, without adequately exploring how customers perceive tourism infrastructure performance. Consequently, a lack of clarity exists regarding which specific attributes are most representative of the sector’s performance and competitiveness. Therefore, the research problem stems from the need to enhance the competitiveness of tourist units and areas. This study intends to identify these priorities by examining the attributes and effects of tourist infrastructure, assessing customer perceptions and performance based on tourist experiences.
The research questions addressed in this paper are as follows:
RQ1. How can the performance of tourism infrastructure be assessed from the customers’ perspective?
RQ2. What are the attributes/dimensions/characteristics of tourism infrastructure that can lead to increased performance?
RQ3. What are the priorities for developing tourism infrastructure so that it becomes more efficient?
The first research question takes a qualitative approach to identify the fundamental concepts underpinning the tourism infrastructure framework. Building on this foundation, the second question adopts a quantitative lens to measure the impact of these concepts and the relationships between them. The final and most critical question synthesizes these findings to identify priority areas, offering actionable insights for key stakeholders such as managers and policymakers to strategically enhance the tourism sector. Therefore, this study analyzes the need for investment in Romanian tourism infrastructure by examining customer perceptions of its performance and identifying areas for improvement. The research follows a mixed, sequential exploratory approach (Ștefan et al., 2021), combining data derived from a qualitative analysis of the Web of Science (WoS; Clarivate, 2024) database with primary data collected through a survey administered to tourists.
The research is novel in two ways: 1) from a scientific perspective, it aims to find meaningful measures through which clients can quantify the performance of tourist destinations, formed by the characteristic attributes and outcomes, and 2) from a methodological perspective, it proposes a complex methodological framework, which allows triangulation of results, including content analysis (that supports the outline of the tourist framework), combined partial least squares structural equation modeling (PLS-SEM) (to evaluate the relationships between concepts), and a combined importance–performance map analysis (IPMA) and necessary conditions analysis (NCA) to identify managerial priorities for improving the sector.
In the following sections, the theoretical approaches related to the tourism infrastructure framework are expanded, focusing on illustrating the conceptual context of the research, highlighting the content analysis results, and illustrating the conceptual model, together with the development and argumentation of the research hypotheses. These are structured on two levels: (1) Attributes of tourism infrastructure and (2) Outcomes of tourism attributes. The third section presents the methodological aspects, including an overview of the research process, the particularities of the bibliometric analysis carried out, the data collection procedure through the questionnaire, and the measurement scales used. The fourth section outlines the research results, focusing on validating the hypotheses through structural relationships and highlighting the findings derived from the combination of IPMA and NCA. The fifth section offers in-depth discussions of the results. Finally, the conclusions section highlights the main conclusions of the research; underlines the theoretical, methodological, and practical implications of the study; and presents the limitations and possible future research directions.
Theoretical backgroundConceptual contextInfrastructure is essential for the economic and social development of a country and for improving quality of life. It comprises two types of capital: economic capital, which focuses on supporting productive activities, and social capital, which focuses on improving human capital through public social services (Mandic and Mrnjavac, 2018). The key to developing a successful tourism industry is ensuring efficient tourism infrastructure (Hesna et al., 2023). As tourism is a heterogeneous industry, defining tourism infrastructure is difficult (Dwyer et al., 2010). Tourism infrastructure can also be called the material basis of tourism and represents, along with the values and accessibility of communication, one of the key factors determining the attractiveness of a region (Kowalczyk and Gierczak-Korzeniowska, 2019). While tourism infrastructure includes facilities directly serving tourists, some components, such as public transport, serve the broader population as well (Žunić et al., 2023).
With the potential to increase competition and stimulate tourism, tourism infrastructure provides customers with a range of travel facilities (Suleiman and Albiman, 2014). Simultaneously, it enables the development of recreational activities and constitutes a solid support for increasing the attractiveness of tourist areas and, implicitly, of accommodation units. As a component of regional tourism, tourism infrastructure is of particular importance for the long-term development of tourism, as well as for the general progress of tourist destinations (Nguyen, 2021). As standards for accessible tourism have increased, infrastructure must ensure that tourism offers all people (regardless of age, disabilities/impairments, or abilities) the opportunity to travel without any impediments.
The development of a country’s tourism infrastructure can be influenced by several factors, such as the country’s cultural and natural potential, living standards, people’s general perception of tourism, and the existence of investment programs in tourism infrastructure at both the destination and national levels (e.g., investments in road and railway infrastructure, the opening of museums, or the creation of nature reserves). According to Apostol and Bălăceanu (2012), the need to develop tourism infrastructure is supported by arguments such as the following: (1) a harmonious development of tourism contributes to the economic and social growth of a country; (2) given the fact that tourism resources are practically inexhaustible, tourism represents a sector of the economy with real prospects for long-term development; and (3) tourism has a multiplier effect and acts as an element of the global tourism system, generating a specific demand for goods and services that determines an increase in their production, contributing to the diversification of the national economic sectors.
The more developed a country’s tourism infrastructure, the higher the interest of tourists in traveling will be. Simultaneously, the development and expansion of tourism infrastructure are important not only for improving living standards and greening the environment but also for the efficient functioning of a country’s economy. Adhuze et al. (2023) investigated the relationship between infrastructure development, tourism, and economic growth. Infrastructure development is essential for both promoting tourism and stimulating economic growth. Two important aspects emerged from this study: (1) the development of tourism infrastructure is a key factor in attracting visitors and increasing their satisfaction and tourist experience and (2) the development of tourism infrastructure positively impacts economic indicators such as GDP, employment, and the income growth of those engaged in tourism activities and foreign exchange. Focusing on customer-centricity, a recent study (Monteiro et al., 2023) emphasized the importance of involving customers in the value creation process, especially in highly competitive industries such as tourism. The authors deemed co-creation a powerful tool for building customer loyalty. Furthermore, Tuominen et al. (2023) highlighted in their research that an effective strategy goes beyond the traditional approach of merely understanding customer needs; it emphasizes building strong relationships with them and leveraging their characteristic information to maximize value. Finally, strengthening the competitiveness of destinations is vital for the sustainable development of the tourism industry, which directly contributes to regional growth (Zhang, 2025).
Analyzing the tourism infrastructure framework: content analysisA content analysis was conducted using the Ligre v.6.5.1 software program ( Logiciels Ex-l-tec, 2024) to map the structure of the tourism infrastructure according to its characteristic attributes and effects. The main results are presented in Table 1.
Tourism infrastructure framework.
Source: authors with the help of Ligre v.6.5.1 (Logiciels Ex-l-tec, 2024).
The attributes identified as the dimensions of tourism infrastructure refer to the sustainability, accessibility, safety, comfort, and quality of the tourism unit and area, as well as the price of the services provided by the tourism unit, the urbanization level of the area, and time savings achieved. The outcomes are the attractiveness and competitiveness of the tourist unit and area, along with the satisfaction, perceived value, and intention to return.
Conceptual model and research hypothesesAttributes of tourism infrastructureTo establish an adequate balance between tourist welfare and the needs of the natural and cultural environment, as well as to develop tourist destinations and organizational competitiveness, employing a global and integrated approach, where all interested parties share the same goals regarding the durability of tourism and the approached challenges, is necessary. The integrated approach of shared sustainability goals leads to a balanced outcome by addressing the needs of the natural and cultural environment, tourist welfare, organizational competitiveness, and the development of tourism destinations (Susanu et al., 2009). The adoption of sustainable practices by tourist establishments significantly contributes to increasing their attractiveness, as modern tourists are increasingly attentive to environmentally and socially responsible practices as well as the ecological and social impact of their vacations. Sustainable tourism aids in market differentiation by attracting tourists who appreciate and support ecological values (Mihalič, 2000). Thus, by promoting sustainability, tourist units can strengthen their reputation and attract new customer segments while ensuring long-term development (Mionel et al., 2024). According to specialists (Font and McCabe, 2017), implementing sustainable measures—such as reducing carbon footprint, using green energy, minimizing waste, and protecting biodiversity—will lead to an improved perception of the tourist establishment’s responsibility. Moreover, the recent period, marked by the coronavirus disease 2019 (COVID-19) pandemic, drastic climate change, resource depletion, and pollution, has led to changes in travel behavior, promoting a global reevaluation of people’s relationship with the environment. Consequently, with growing awareness of ecological footprints, green tourism is increasingly favored over unsustainable tourism (Ezeh and Dube, 2024). Based on these aspects, the following hypothesis was formulated:
H1. The sustainability of the tourist unit and area (SUS) contributes to increased attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP).
The accessibility of a tourist facility and area is a key determinant of its attractiveness, as it influences both tourists’ decisions to choose a particular destination and their experience. According to a recent study (Velastegui-Hernández et al., 2024), the perceived quality of tourist transport services significantly influences visitors’ overall satisfaction, highlighting the importance of accessibility for tourists’ experience. Tourist destinations that are well-connected in terms of accessibility are perceived as more convenient and attractive, contributing to a more pleasant travel experience (Page, 2019). Accessibility not only facilitates tourists’ movement but also improves the tourist facility’s competitiveness, attracting new tourist segments. Some researchers (Timothy and Boyd, 2015) believe that proximity to transport hubs, such as airports or train stations, as well as the availability of an efficient public transport system, significantly contributes to creating a favorable image of the destination (Yu et al., 2023). Prideaux (2000) suggests that destinations with efficient and accessible transport connections are perceived as more convenient, increasing tourist satisfaction and the perceived value of services. Likewise, Chen and Mohd Rosdi (2025) consider accessibility a fundamental factor in shaping a tourist experience, describing it as the combination of location convenience, available travel options, and associated costs. Calvo-Mora et al. (2015) reinforce these ideas by emphasizing accessibility as a quality factor in the tourist experience, highlighting its role in ensuring individuals’ right to enjoy their leisure time. Considering the above, the following hypothesis was formulated:
H2. The accessibility of the tourist unit and area (ACC) contributes to increased attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP).
Safety has become a primary requirement for tourists’ decisions to travel and is a vital concept for the tourism industry. Chan and Lam (2013) consider both safety and security to be relevant criteria for tourists when choosing a tourist facility. Although most accommodation units comply with national and local regulations regarding tourist safety and security, special attention must be paid to tourists’ expectations of safety and security (Preko and Gyepi-Garbrah, 2023). Pizam and Mansfeld (2006) believe that tourist destinations that implement effective security measures benefit from increased attractiveness owing to the sense of comfort provided to visitors. Similarly, tourists tend to perceive services as superior when tourist facilities offer a safe environment that allows them to fully enjoy the experience. In addition to these, the COVID-19 pandemic has posed major challenges, requiring tourism companies to redefine their relationships with partners and clients while prioritizing safety and health concerns (Matijević et al., 2025). Thus, the following hypothesis was formulated:
H3. The safety of the tourist unit and area (SIG) contributes to increased attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP).
Despite the fact that many urban areas were not originally structured to attract tourism, urbanization can serve as an important driver of the tourism industry, helping it respond effectively to both current and future challenges when properly managed (Madunezim et al., 2023). The level of urbanization contributes to the development of transportation and accommodation infrastructure while also creating a more favorable environment for memorable and authentic tourist experiences, which enhances the attractiveness of tourist facilities. According to Tisdell (2013), the urbanization level of a destination contributes to the development of modern transportation, facilitates tourists’ cultural and entertainment experiences, and improves communication networks. Another study (Gohar, 2021) supports the idea that urbanization and tourism have evolved interdependently, mutually influencing the development of infrastructure and the experiences offered to tourists. Tourist destinations located in urbanized areas benefit from better access to tourism markets and a more diverse range of activities and services that can meet the expectations of modern tourists (Sharpley and Telfer, 2014). Through a variety of cultural, gastronomic, and entertainment options, destinations with a high level of urbanization add perceived value to the tourist experience (Pearce, 2001). Based on these aspects, the following hypothesis was formulated:
H4. The urbanization level of the tourist area (URB) contributes to increased attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP).
The time spent traveling to a tourist destination often constitutes the largest transport cost. To make appropriate decisions regarding the mode and route of transport, travelers often have to compromise between vacation time and the overall cost of the trip (Javid et al., 2022). The time savings achieved by traveling quickly and efficiently to the destination significantly contribute to the attractiveness of the tourist unit and the perceived value of its services, as tourists prefer well-connected destinations that minimize logistical effort and maximize the time spent at the destination (Kim et al., 2023; Lumsdon and Page, 2004). Simultaneously, shorter travel durations allows tourists to devote more time to recreational activities, which enhances the attractiveness of tourist destinations (Lew and McKercher, 2006). Faster and easier access to tourist units is often perceived as an element of service quality, positively influencing tourist satisfaction and loyalty. Furthermore, Kim et al. (2023) reiterate the idea that modern time-saving technologies lead to changes in both the behaviors exhibited by travelers and the activities performed at the destination. Based on these aspects, the following hypothesis was formulated:
H5. The time savings achieved by traveling the route to reach the destination (ECT) contributes to increased attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP).
The comfort level offered by a tourist unit is a central element in increasing its attractiveness as tourists seek experiences that combine relaxation with high-quality standards. Simultaneously, the comfort perceived by tourists directly influences their decision to choose a tourist unit. According to specialists (Kotler and Keller, 2016), the comfort level of the tourist unit is an essential factor in increasing its attractiveness, as tourists are attracted to modern facilities and well-equipped rooms, as well as an environment that promotes relaxation. Comfortable facilities and attention to detail in the unit’s design create a positive experience that contributes to attracting tourists and subsequent recommendations (Baker and Crompton, 2000; Kim et al., 2021). Therefore, tourist units that invest in comfort and create a pleasant environment for tourists can attract more customers and strengthen their position in the tourism market. Furthermore, He and Timothy (2024) apply Maslow’s hierarchy of needs to argue that higher-order tourist needs, such as authenticity, can only be fulfilled after basic, lower-order needs, such as comfort, have been met. Based on this, the authors suggest that tourist destinations should strive for a balance between comfort and authenticity to provide a valuable and attractive experience for tourists. Based on these aspects, the following hypothesis was formulated:
H6. The comfort level of the tourist unit (CFO) contributes to increased attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP).
Every tourist establishment aims to increase its attractiveness, which can only be achieved if the respective tourist establishment offers a standard of service quality that leads to the satisfaction of the tourists visiting it. The interaction between the customer and staff, together with a high level of quality in the tourist establishment’s services, contributes to the formation of a positive perception of the value offered (Grönroos, 2007). The study by Regalado-Pezúa et al. (2023) analyzes three characteristic dimensions of the value perceived by travelers, among which they identify the functional value derived from the organization and quality of services. Thus, the quality of services offered by a tourist establishment represents an indicator of professionalism and is an essential strength that will attract guests and meet their expectations (Blazeska et al., 2015). Conversely, the perception of quality is determined not only by the technical performance of the services, but also by the personal interactions and experiences of the customers (Grönroos, 2007). Similarly, Kandampully and Suhartanto (2000) believed that tourists perceive the quality of tourist unit services through direct experiences, which influences both their immediate satisfaction and intention to return or recommend the respective unit. Thus, the following hypothesis was formulated:
H7. The quality of the tourist unit’s services (CLT) contributes to increased attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP).
The pricing of a tourist facility’s services is crucial in enhancing its attractiveness as tourists are drawn to offers that provide a balance between costs and benefits. A well-adjusted price that reflects the quality of services can lead to increased interest in and customer loyalty towards a tourist facility (Chen and Hu, 2010). According to specialists (Kotler and Keller, 2016), tourists are more likely to accept higher prices if justified by a high standard of service and exceptional experience. Additionally, a well-balanced pricing strategy that conveys value and accessibility can significantly improve customers’ positive perceptions of the services offered and contribute to the favorable market positioning of a tourist facility, attracting a larger number of customers (Chen and Chen, 2010). In addition, Zhang et al. (2023) note that customer-perceived value is typically evaluated from a one-dimensional perspective based on economic utility. Accordingly, the price paid, time spent, and effort expended are viewed as sacrifices made by customers to obtain a benefit. Based on the above, the following hypothesis was formulated:
H8. The price of the services offered by the tourist unit (PRS) contributes to increased attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP).
The attractiveness of a tourist unit and the perceived value of its services have significant positive effects on competitiveness, contributing to strengthening its position in the tourist market. Attractiveness is influenced by factors such as location, uniqueness of experiences, quality of facilities, and diversity of offers, which increase tourist interest and satisfaction (Wongsuwatt et al., 2024). In the same vein, Chin et al. (2025) emphasize that the main attractions play a crucial role in travelers’ decisions when selecting a vacation destination; the more attractive a destination is perceived to be, the more competitive it becomes in the tourism market. Moreover, according to Ritchie and Crouch (2003), the attractiveness and perceived value of a tourist unit’s services directly contribute to its competitiveness because tourists are more likely to choose and recommend units that offer a superior experience and favorable quality–price ratio. Porter (1990) emphasizes that well-differentiated tourist offers, which combine the attractiveness of a location with high-quality services, ensure a sustainable competitive advantage. Tourist units that prioritize the aforementioned aspects can increase their attractiveness and perceived value while strengthening their position against competitors. Likewise, Barrera-Martínez et al. (2025) link the value perceived by tourists—through the quality of the destination—to its competitiveness, which is measured by the economic performance indicator of tourists’ spending. Thus, the following hypothesis was formulated:
H9. The attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP) have positive effects on the competitiveness of the tourist unit (COM).
It is well known that the satisfaction a tourist obtains from the services provided by a tourist establishment is one of the determining factors of the attractiveness or image of the destination (Chaudhary, 2000). The attractiveness of a tourist establishment, determined by factors such as location, uniqueness of experiences, aesthetics of spaces, and quality of infrastructure, creates positive expectations and increases tourist interest. Simultaneously, perceived value, which is defined as a customer’s evaluation of the benefits received in relation to the price paid, plays a crucial role in strengthening the feeling of satisfaction. Studies (Chen and Chen, 2010) show that when a tourist establishment offers services perceived as being of high value and operates in an attractive environment, it significantly improves the overall experience of visitors, resulting in a high level of satisfaction (Regalado-Pezúa et al., 2023). Consistent with this view, Elshaer et al. (2025) establish a positive relationship between customer satisfaction and perceived value, defining perceived value as the evaluation of benefits compared to the costs incurred. According to studies (Ritchie and Crouch, 2003), tourist units with a high level of attractiveness generate positive expectations and greater emotional involvement from visitors (An et al., 2024). Based on these aspects, the following hypothesis was formulated:
H10. The attractiveness (ATR) and the perceived value of the tourist unit’s services (VAP) have positive effects on satisfaction with the services provided by the tourist unit (SAT).
The competitiveness level of a tourist establishment directly influences tourists’ intentions to return through the quality of the experiences offered and the overall image of the destination. A tourist establishment perceived as competitive is distinguished by high-quality services, well-trained staff, modern infrastructure, and the ability to respond to tourists’ individual needs. According to studies, destinations that manage to maintain a competitive position attract new tourists and a significant number of recurring customers, which contributes to long-term sustainability (Gomezelj and Mihalič, 2008). Research shows a positive relationship between the competitiveness of a tourist destination and tourist loyalty, with the latter being influenced by overall satisfaction and the value of the experience (Yoon and Uysal, 2005). Simultaneously, a remarkable tourist experience, determined by the competitiveness level of the unit, leads to the formation of an emotional bond and increased trust in the destination, enhancing visitor loyalty (Kim, 2011; Țigu and Țuclea, 2008). Furthermore, Chin et al. (2025) define the competitiveness of a destination as its ability to attract and retain travelers by offering experiences that are distinct from other available options. Thus, the following hypothesis was formulated:
H11. The competitiveness of the tourist unit (COM) determines the tourists’ intention to return (REV).
Tourist satisfaction is a key factor that influences their intention to return to a destination. A positive experience not only leaves a favorable impression on tourists but also creates emotional loyalty that motivates them to return. Additionally, high satisfaction generates loyalty by creating an emotional connection between the tourist and the destination. According to Cui and Zhang (2025) and Kim (2011), an outstanding tourist experience, driven by the competitiveness of a facility, leads to the formation of an emotional bond and increased trust in the destination, which enhances visitor loyalty. Moreover, satisfied tourists are more likely to return and recommend a destination to others, thus amplifying both the reputation and economic success of the tourist facility (Chi and Qu, 2008). Yoon and Uysal (2005) demonstrated that satisfaction acts as a mediator between the overall perception of a destination and future behaviors, including the intention to return to and recommend the destination to others. Along the same lines, Elshaer et al. (2025) position satisfaction as a predictor of customer loyalty. Based on these aspects, the following hypothesis was formulated:
H12. Satisfaction with the services provided by the tourist unit (SAT) determines the tourists’ intention to return (REV).
Following the identification of the main concepts that underline tourism infrastructure and the formulation of hypotheses about the relationships established between them led to the conceptual model presented in Fig. 1.
Materials and methodsResearch process
This research proposes a complex methodological framework using a mixed methods research design, which enables the triangulation of results. A mixed methods approach provides richer perspectives, a more detailed understanding of causal relationships among variables, and the identification of emerging issues (Jefferson et al., 2014). Its use in business studies supports the field’s growth by generating insights that enhance understanding of business problems, add value, and inform future research (Molina-Azorin, 2016). In this research, an exploratory mixed methods approach was adopted (Kurtaliqi et al., 2024), involving qualitative methods followed by quantitative ones to better understand contextual specificities, generate new ideas and concepts, and develop measurement scales for quantitative analysis. Accordingly, this research identifies important components of the tourism framework, the relationships among them, and the priorities requiring increased managerial attention to improve customer-perceived performance. The triangulation method employed comprises content analysis, PLS-SEM, and a combined IPMA and NCA.
Our research focused on three stages, as shown in Fig. 2, to achieve the results according to the research questions formulated. In the first stage, to answer the first question, the data analysis targeted a qualitative dimension. We conducted a content analysis that allowed for the observation of a variety of data and their classification into a series of defined categories to support the appropriate interpretation (Harwood and Garry, 2003). Therefore, using a series of scientific publications on the topic of tourism infrastructure, identified and selected through bibliometric analyses and the PRISMA methodology, a coding tree was developed. This tree served as the framework for identifying attributes and effects of tourism infrastructure, representing the dimensions through which customers evaluated the industry’s performance. These dimensions were subsequently used in quantitative analyses. Content analysis was conducted using the Ligre v.6.5.1 software program ( Logiciels Ex-l-tec, 2024).
The second step of this process aimed to evaluate the relationships assumed by the research hypotheses within a PLS-SEM model in which the attributes and outcomes of tourism infrastructure obtained by conducting content analysis were included, helping to obtain the answer to the second research question. PLS-SEM allows the estimation of results based on a predictive causal approach in the absence of certain data distribution assumptions (Hair et al., 2019). Other reasons for choosing PLS-SEM over other alternative methods were that (1) this research is in its early stages and aims to explore relationships between constructs, their directions, and strengths (Astrachan et al., 2014; Kurtaliqi et al., 2024); (2) it works efficiently with small sample sizes and complex models (Astrachan et al., 2014; Dash and Paul, 2021; Kurtaliqi et al., 2024); and (3) the models created are complex and involve predicting outcomes and theory development (Dash and Paul, 2021; Kurtaliqi et al., 2024). Therefore, a structural model was developed across four levels, starting with the attributes defining the structure and functionality of tourism infrastructure, followed by the outcomes that manifest their impact.
The third stage of analysis, which aims to answer the last research question, comprised a combined approach of the IPMA, a tool that shows the direction of the need to concentrate managerial efforts, and NCA, which highlights whether the antecedent constructs represent necessary conditions for target outcomes, regardless of the intensity of their power, with the two analyses complementing the PLS-SEM context (Hauff et al., 2024; Ishwara and Mekonnen, 2024). They shed light on how the examined concepts excel, as well as how relevant they are, revealing those on which it is necessary to focus our attention from a managerial perspective, and their improvement.
SPSS Statistics v.29.0 (IBM Corp., 2024) was used for the data preparation and preliminary analysis, while SmartPLS 4 software was used for the integrated application of PLS-SEM, IPMA, and NCA (Ringle et al., 2024).
Bibliometric data collectionThis study aims to analyze the need for investment in local tourism infrastructure by understanding tourists’ perceptions and subjective experiences. To achieve this, a preliminary qualitative analysis was conducted to identify the main factors shaping tourism infrastructure. Table 2 presents the data extraction strategy, according to which the analysis was launched, performing a search in the WoS Core Collection database (Clarivate, 2024), through the topic search filter, using “tourism infrastructure,” “tourism facilities”, and “tourism amenities” as keywords.
Data extraction strategy.
Source: authors' conception using data provided by WoS Core Collection (Clarivate, 2024).
The entire search and selection process of relevant scientific papers for our analysis is shown in Fig. 3, constructed according to the PRISMA methodology (Farrús, 2023), with the records identified in the first stage within the WoS Core Collection numbering 902.
Scientific works of the Article, Review Article, and Early Access types published between 1992 and 2024 and written in English were targeted, resulting in the exclusion of other types of documents (n = 236) and those written in other languages (n = 84). Moreover, to ensure an appropriate selection of publications, another criterion was considered: inclusion in the Social Sciences Citation Index and Science Citation Index Expanded.
The abstracts of the 343 resulting documents were checked to find matches between them and the analysis structure targeted by the study’s purpose regarding the customer-perspective factors that support the necessity for investments in tourism infrastructure. A total of 45 publications were identified. Based on their abstracts, continuing the qualitative analysis from the perspective of content was possible.
Questionnaire data collectionTo perform the quantitative analysis, an electronic questionnaire was developed to obtain the tourists’ opinions on their recent experiences with tourist destinations to analyze the need for investments in this field. The survey’s target population comprised people over the age of 18 years who had taken a tourist trip to Romania within the last two years. No other inclusion or exclusion criteria were applied, ensuring coverage of Romanian tourists from all development regions, regardless of gender, age, background, or any other characteristics. The questionnaire was administered online via Google Forms, and data were collected between September 1 and November 6, 2024, obtaining 501 responses. Of these, the following were excluded: (1) three responses were excluded because the respondents declined to participate in the study; (2) three more were excluded because the respondents’ last trip did not occur within the last two years, and (3) 29 responses that presented a suspicious pattern, such as identical answers across all items (indicated by a zero standard deviation calculated for each answer) were also excluded (Hair, jr et al., 2022). Thus, further analysis used data from 466 respondents.
The questionnaire included 13 scales measuring the key dimensions, attributes, and outcomes of tourism infrastructure, inspired by or adapted from various academic studies in the field (see Appendix 2). All items were rated on a 5-point Likert scale, where 1 represented “Strongly Disagree” and 5 represented “Strongly Agree.” These scales aimed to capture participants’ perceptions of the current state of the tourism sector in the country, and these are synthesized as follows. To quantify tourism infrastructure attributes, we employed (1) a scale to measure the sustainability of the tourist unit and area (SUS), with seven items adapted from Asmelash and Kumar (2019) and assessing biodiversity, environmental protection, and recycling practices; (2) a scale to measure accessibility of the tourist unit and area (ACC), with five items adapted from Rahmafitria et al. (2024) and evaluating the ease of travel, clarity of information provided by the tourism unit, and inclusiveness towards diverse visitors; (3) a scale to measure the safety of the facility and tourist area (SIG), comprising five items adapted from George (2003) and Popescu (2011) and evaluating security, emergency preparedness, transport safety; (4) a scale to measure the comfort level of the tourist unit (CFO), comprising five items adapted from Brochado and Pereira (2017) and evaluating order, cleanliness, tranquility, facilities, treatment, and the sense of homeliness; (5) a scale to measure the quality level of the tourist unit services (CLT), comprising five items adapted from Ramsaran-Fowdar (2007) and evaluating service usefulness, staff responsiveness and professionalism, and fulfillment of tourists’ needs; (6) a scale to measure the price of services offered by the tourist unit (PRS), comprising five items adapted from Gumussoy and Koseoglu (2016) and evaluating cost fairness, the quality–price ratio, willingness to pay more; (7) a scale to measure the urbanization level of the tourist area (URB), comprising five items adapted from Hall (2006) and focusing on the urban characteristics of the destination, transport networks, and commercial areas; and (8) a scale to measure time savings achieved (ECT) after traveling the route to reach the destination, comprising five items adapted from Kim et al. (2023) and evaluation tourists’ perceptions of travel efficiency.
To quantify tourism infrastructure outcomes, the following measurement scales were employed: (1) attractiveness of the tourist unit (ATR), comprising five items adapted from Cibinskiene and Snieskiene (2015) and Saravanan (2019), assessing aspects such as location and environment, online presence, tourists’ trust in the unit before arrival, general image, and interaction with customers; (2) satisfaction with the services provided (SAT), comprising five items adapted from Gumussoy and Koseoglu (2016) and Ramsaran-Fowdar (2007), assessing attention to customer needs, general well-being, satisfaction with the chosen destination; (3) competitiveness of the tourist unit (COM), comprising five items adapted from Cibinskiene and Snieskiene (2015) and Saravanan (2019), assessing offer attractiveness, perceived availability, booking convenience, and destination popularity; (4) perceived value of the tourist unit’s services (VAP), comprising five items adapted from Chen and Chen (2010) and Sánchez et al. (2006), assessing the general, emotional, and personal value of the trip and customer expectations and benefits, and (5) intention to return (REV), comprising five items adapted from Gumussoy and Koseoglu (2016), assessing loyalty towards the unit, overall positive impression, and willingness to recommend.
The questionnaire also included questions about the respondents’ demographic characteristics: (1) gender, (2) age range, (3) place of origin, (4) county of residence, (5) educational level, and (6) net monthly income of each family member.
ResultsData analysis through PLS-SEMPreliminary analysisAppendix 1 presents the structure of the study sample according to demographic characteristics. Most respondents were women (62.45 %), aged between 18 and 25 years (40.13 %), from an urban environment (79.61 %), residing in the Bucharest–Ilfov region (51.50 %), with a bachelor’s degree (37.98 %), and having a monthly net income per family member of >6000 RON (33.48 %).
Data analysis through PLS-SEM involved a preliminary analysis (Hair, Jr et al., 2022), regarding missing data, the existence of responses with a certain pattern, extreme values, data distribution, and potential errors arising from common method bias (CMB). Regarding missing data, since all items were marked as mandatory, the dataset was complete for all variables analyzed. Additionally, all research variables were examined to identify extreme values using box plots, and none were identified. The data distribution was then tested for normality by conducting the Kolmogorov–Smirnov and Shapiro–Wilk tests, which indicated statistically significant deviations from normality. However, the evaluation of distribution shape through skewness and kurtosis indicated that, with one exception, all values fell within the ± 2 range, supporting the suitability of PLS-SEM and indicating the results would not be affected by the analysis method selected (et al., 2022).
Consideration was given to reducing the possible effects of errors due to CMB (Podsakoff et al., 2003), and both procedural measures (placing items corresponding to exogenous and endogenous constructs in distinct sections of the questionnaire and ensuring the anonymity of responses) and statistical methods were employed. Harman’s single-factor test revealed eight factors resulting from the factor analysis, without applying any rotation method, with the first factor accounting for 29.000 % of the explained variance. Therefore, no evidence suggested a significant threat of CMB in this dataset.
Evaluation of the structural modelThe proposed structural model analyzed the relationship between the eight attributes of tourism infrastructure and the dimensions of tourism performance. The model was assessed in terms of internal consistency, as well as convergent and discriminant validity (Hair Jr. et al., 2020). Appendix 2 presents Cronbach’s coefficients (α), composite reliability (rho_A and rho_C), external loadings, and the average variance extracted (AVE) (Hair Jr. et al., 2017, 2020, 2023, ). According to Hair, Jr. et al. (2023), Cronbach’s coefficients (α) and composite reliability (rho_A and rho_C) did not fall below the minimum accepted threshold of 0.70. Additionally, all external loadings were at least 0.711, meeting the threshold of 0.7 recommended by Hair Jr. et al. (2017), except for five indicators with values as low as 0.615—still above the minimum accepted threshold of 0.600 proposed by Moores and Chang (2006). Convergent validity was also confirmed, as all AVE values exceeded the recommended minimum threshold of 0.50 (Hair Jr. et al., 2017, 2020, 2023; Shmueli et al., 2019). Thus, the measurement model can be considered both reliable and valid (Hair et al., 2019).
To evaluate discriminant validity, two indicators proposed by Hair et al. (2019) were used: the Fornell–Larcker criterion and the heterotrait–monotrait ratio (HTMT). According to the Fornell–Larcker criterion (Appendix 3), the square roots of the AVE values were higher than the correlations between the constructs. Furthermore, the HTMT ratio indicated that almost all values were below the recommended threshold of 0.90, except for the CLT construct (0.913), which was retained in the analysis due to its proximity to the maximum recommended threshold (Roemer et al., 2021). In addition, its bias-corrected confidence intervals were lower than 1 (Ab Hamid et al., 2017; Hair et al., 2019; Hair Jr. et al., 2023).
The structural model, presented in Fig. 4, was first evaluated using the variance inflation factor (VIF), and the results indicated no collinearity among the predictors used, as all VIF values were below 5, consistent with recommendations from previous studies ( Hair Jr. et al., 2017; Sarstedt et al., 2017).
Structural model of tourism infrastructure attributes.
In Fig. 4, representing the PLS-SEM structural model, it can be observed that the R2 coefficients of the attractiveness of the tourist unit (ATR) and the perceived value of the tourist unit’s services (VAP) have 44.1 % and 62.1 % of their variance explained, respectively, by ACC, SIG, SUS, URB, ECT, CFO, CLT, and PRS. Additionally, the services provided by the tourist unit (SAT) are explained in proportion to 64.7 % by ATR and VAP, while the competitiveness of the tourist unit (COM) is explained in proportion to 53.9 % by the same variables. Finally, all variables in the model influenced account for 68.9 % tourists’ intention to return (REV). Next, Table 3 presents the relationships between the eight tourism attributes, ATR, and VAP (H1–H8).
Assessing the direct effects of tourism attributes on ATR and VAP.
β - path coefficients; SE - standard errors; t - t-test value; p - p-value.
Source: authors with the help of SmartPLS 4 (Ringle et al., 2024).
According to the results obtained, ATR was positively and significantly influenced by SUS, ACC, URB, CFO, and CLT, while VAP had a significant positive impact on SUS, ECT, CFO, CLT, and PRS, thus fully supporting H1, H6, and H7 and partially supporting H2, H4, H5, and H8. Hypothesis H3 was completely rejected, as SIG did not significantly affect ATR or VAP. The effects on tourism outcomes, such as the competitiveness of the tourist unit (COM), tourist satisfaction (SAT), and intention to return (REV), were also assessed (H9–H12). The results are presented in Table 4.
Testing direct effects on performance determinants in tourism activity.
β - path coefficients; SE - standard errors; t - t-test value; p - p-value.
Source: authors with the help of SmartPLS 4 (Ringle et al., 2024).
The results indicate that both COM and SAT were significantly and positively influenced by ATR and VAP, which, in turn, positively influenced REV. Thus, H9, H10, H11, and H12 were fully supported.
Highlighting the need for investment in tourism infrastructureTo complete the analysis of the results obtained using PLS-SEM, IPMA and NCA were used to evaluate the level of importance and performance of the tourism attributes and to determine, based on the logic of necessity, the necessary level of each attribute to achieve a certain outcome (Hauff et al., 2024). Table 5 presents the IPMA results, including a four-quadrant matrix: (1) Q1: Keep up the good work; (2) Q2: Concentrate here; (3) Q3: Low priority; and (4) Q4: Possible over skill. This helps interpret the rescaled scores resulting from the PLS-SEM analysis, viewed as performance indicators, in contrast to the total effects generated, more precisely, with the specific importance of the target constructs (Sarstedt et al., 2024).
Importance - Performance Analysis.
Source: authors with the help of SmartPLS 4 (Ringle et al., 2024).
In terms of ATR, ACC, CFO, and CLT represent extremely relevant factors, achieving a performance level higher than the midpoint and are located in the Q1 area of the matrix. In this discussion, we included SIG, which, although a performing attribute, does not have a high importance. This indicates that it does not constitute a decisive factor in improving the tourist framework; thus, it is placed in the Q4 quadrant. However, the SUS, which we found in Q2, requires increased attention because, despite its relevance, it has not yet reached the desired performance.
Regarding VAP, the importance of ACC diminishes and remains constant at the performance level, taking shape in the Q4 quadrant. The circumstances surrounding the SIG (Q4) also remain constant, and the CFO and CLT continue to designate factors of great interest, which are categorized in the Q1 area. This time, ECT (Q2) and PRS (Q2), whose performance levels must increase because of their major importance, require managerial interventions.
COM exhibited patterns similar to ACC (Q4), CFO (Q1), CLT (Q1), SIG (Q4), ECT, and PRS, no longer representing factors of interest or impact. However, ATR and VAP occupied key positions along both coordinates of the analysis. SAT was positioned similarly to COM in the IPMA, with no notable changes in the contributions of the factors to its formation, except for SUS, which is “a concentrate here” attribute (Q2).
For REV, ATR, COM, and SAT emerged as the most relevant factors, also achieving a significant level of performance. In contrast, VAP required greater attention in terms of performance, representing an important aspect that has not yet reached its full potential. ACC (Q4), CFO (Q1), CLT (Q1), and SIG (Q4) lost relevance in the analysis despite maintaining their performance levels.
The research process then proceeded with NCA, which operates on the principle of necessity logic and assumes that a given outcome can only be achieved if certain conditions are met. This approach identified constraints or limits that had to be overcome to reach an 85 % level for each outcome. Following Hauff et al. (2024), the results presented in Table 6 include the effect size (d), the value of each necessary condition (on a scale from 0 to 100), and the percentiles representing the percentage of cases that did not reach the required condition.
Necessary Condition Analysis.
Source: authors with the help of SmartPLS 4 (Ringle et al., 2024).
To reach a level of 85 % in terms of ATR by the unit and area of the holiday destination, the highest necessary conditions to be met were at least 65.632 on a scale of 0 to 100 for CLT, 51.152 for ACC, and 48.585 for CFO. Furthermore, SIG and PRS had to reach at least 33.946 and 9.549, respectively. The largest share of cases not meeting these conditions was for CLT (14.163 %), whereas for other tourism attributes, fewer than 10 % failed to meet the minimum threshold. The situation for VAP was not significantly different, with the ACC, CFO, and CLT variables requiring values of at least 50.000, 58.760 and 9.295, respectively. For 6.009 %, 10.944 %, and 0.644 % of the respondents, these conditions were not satisfied. SIG completed the profile with a minimum value of 34.048, although 2.790 % of the tourists did not feel that the requirement was satisfied.
COM supported the need for a CFO of 26.415 and CLT of 26.647. SIG of at least 16.261, URB of 3.679, ATR of at least 34.617, and VAP of at least 35.462 represented the necessary conditions for achieving 85 % competitiveness. Fewer than 5 % of the cases failed to meet each of these thresholds. To achieve an effectiveness of 85 %, SAT—similar to the previous constructs targeted— required an ACC of at least 25.000, a CFO of at least 58.760, and a CLT of 9.295, which were not met by 2.575, 10.944, and 0.644 % of the cases. These were complemented by PRS with a value of 17.310, SIG of 26.869, ATR of at least 34.617, and, finally, VAP with a minimum value of 29.077. The highest percentage of cases that did not achieve the minimum threshold of 85 % satisfaction was CFO (10.944 %).
The final target construct, REV, was assumed to reach a threshold of 85 %, with ACC of 25.000, CFO of 58.760, and CLT of 68.046. PRS, with a minimum accepted threshold of 17.310 and SIG of 36.481, completed the analysis. The same applied to an ATR of at least 34.617 and VAP of at least 29.077. Additionally, SAT of at least 75.000 constituted the most significant condition to be achieved; 22.318 % of the respondents did not meet this criterion. The other antecedent variables, including ECT, SUS, and COM, did not represent the necessary conditions to be achieved to obtain the desired results.
DiscussionThe present study proposed a new theoretical approach that expands the conceptual framework of tourism infrastructure, addressing the theoretical gap regarding the performance of organizations in the tourism sector from the consumer’s perspective. Using content analysis, the most representative attributes and outcomes of infrastructure were identified, forming the foundation for the new model, which is characterized by a high degree of complexity due to the multitude of causal relationships among them. Additionally, one of the main contributions of this study is that it offers a measurable perspective on travel experiences as perceived by tourists and highlights the interdependence between tourism attributes and outcomes, specifically, the primary role of satisfaction and competitiveness in influencing return intention. Furthermore, from a methodological perspective, triangulation supported the development of a robust overall picture, as highlighted by the following.
Using content analysis, several tourist-perceived outcomes were identified, representing key elements for measuring the industry’s performance from tourists’ perspective and addressing the first research question. These outcomes include (1) attractiveness of the destination, which reflects its ability to generate individual benefits and feelings resulting from its ability to satisfy tourists’ needs (Vengesayi, 2003); (2) tourist satisfaction, which represents the balance between what tourists sacrifice and what they receive, being strongly influenced by their expectations (Correia et al., 2013); (3) competitiveness of the tourist unit, which denotes maintaining a profitable and sustainable position despite the presence of competitors within the industry (Vengesayi, 2003); (4) customers’ intention to return, which is most often determined by the level of satisfaction with the previous tourist experience, as well as by perceived quality (Alegre and Cladera, 2009); and (5) value perceived by tourists, which is viewed as a dynamic variable resulting from post-purchase evaluations, both in terms of the purchased tourist product and in terms of the tourism agency or unit that provided it (Sánchez et al., 2006). The movement of tourists between their place of residence and the intended destination constitutes the main energy flow of the system (El Kasrawy et al., 2020), representing the point that generates the fundamental elements constituting the concept of tourism.
The second research question was addressed by identifying tourism infrastructure attributes and evaluating the relationships between these attributes and the previously mentioned effects using PLS-SEM. These attributes represent the dimensions that clients consider when choosing the optimal option for their vacation: (1) sustainability, in which natural destinations stand out through the conservation of resources that contribute significantly (Štumpf and Kubalová, 2024); (2) accessibility, viewed as an intrinsic factor of responsibility aimed at creating the conditions that makes tourism possible for everyone (Sica et al., 2022); (3) safety, which does not necessarily have the ability to generate satisfaction, but whose absence automatically leads to feelings of dissatisfaction (Mikulić et al., 2024); (4) level of comfort, associated with the attitudes, behaviors, and emotions influenced by environmental elements such as other tourists or employees of the tourist establishment and tangible factors such as hygiene, temperature, and lighting, as well as overall atmosphere and comfort reflecting customer satisfaction and well-being (Cicerali et al., 2017); (5) quality, as a constitutive factor of the tourist product, increasingly recognized by customers and posing challenges for businesses due to the intangibility, perishability, heterogeneity, and diversity of services (Sharpley and Forster, 2003); (6) price, representing one of the main factors influencing travel decisions, with values generally differing according to the destination’s competitiveness (Forsyth and Dwyer, 2009); (7) urbanization, a phenomenon that has transformed the appearance of human societies from both spatial and social perspectives, serving as evidence of the development of production activities and service provision (Hall, 2006); and (8) time savings, associated with transport, with travel time variability being considered a feature of transport systems that may generate additional costs (Li et al., 2010).
The results revealed that the more tourist units and areas focus on recycling and environmental protection activities, the greater their attractiveness and the higher the value perceived by clients. These findings directly support H1 and are consistent with the research of Mihalič (2000) and Mionel et al. (2024), which, despite the time gap, endorse the idea that sustainability is a key factor in attracting environmentally conscious tourists. However, accessibility is not perceived by tourists as a superior attribute but rather as a basic element of the tourist experience. Therefore, it does not add value to the experience but merely facilitates it and increases the attractiveness of the tourist unit. This aligns with the findings of Chan et al. (2025), who consider accessibility in tourism services a basic condition for all people, rather than an element of added value. Safety is considered a fundamental standard in any tourism experience, and the lack of safe infrastructure or the lack of preparedness among tourism personnel for emergency situations does not act as a differentiating factor in determining destination attractiveness or shaping tourists’ perception. As noted by Jensen (2007), who drew on Herzberg’s theory from 1966, compared with motivational factors that have the capacity to generate satisfaction, hygiene factors, although they do not contribute to a sense of contentment, cause strong dissatisfaction when absent. In this case, both satisfaction and accessibility can be classified as hygiene factors.
Urbanized areas, which benefit from modern infrastructure and leisure facilities, have become increasingly attractive to tourists and tend to attract more visitors, although some tourists consider rural or less urbanized areas more attractive, and the perceived value of tourist units in these areas is much higher. Consistent with our results, Świdyńska and Witkowska-Dąbrowska (2021) argue that modern, urbanized infrastructure is a key element that draws tourists to such destinations. Similarly, time savings, characterized by the speed and ease with which one can travel to or reach a tourist attraction, are perceived by tourists as a factor that increases both the attractiveness of a tourist unit or area and the value they ascribe to it. In the same vein, Kim et al. (2021) note that people often consider the time spent on travel as wasted time and that reducing travel duration allows tourists to enjoy more vacation experiences by mitigating time constraints. In terms of comfort and quality, both are associated with increasing the attractiveness of the establishment and destination, as well as with the value perceived by customers. Similarly, Park and Jeong (2019) emphasize that the levels of quality and comfort directly influence how tourists perceive services, given that a comfortable atmosphere that meets their level of expectations leads them to recommend the services and even to return.
Furthermore, the results of the analysis of tourism infrastructure dimensions, combining IPMA and NCA (Hauff et al., 2024), are discussed, as illustrated in Fig. 5. These results helped answer the third research question.
In the Q1 quadrant, associated with a higher degree of importance and performance, the level of comfort and quality of the services provided by the travel establishment are fully represented. These elements represent essential conditions that must be met, especially the level of comfort, which influences perceived value, customer satisfaction, and intention to return (He and Timothy, 2024; Kotler and Keller, 2016), and the quality of the services, which plays a crucial role in shaping tourists’ intention to return and their perception of destination attractiveness (Kandampully and Suhartanto, 2000). However, a relatively high percentage of respondents indicated that these conditions are not yet fully satisfied. Moreover, the Q1 area also reflects the importance of accessibility from the perspective of attractiveness (Timothy and Boyd, 2015), emphasizing its relevance as a condition to be achieved and suggesting the need to maintain an overall strategic direction.
The highest priority is assigned to quadrant Q2 (high importance and low performance), highlighting the need for managerial efforts to strengthen the key characteristics of tourism infrastructure and revealing the significance of focusing on the price of tourism services (Chen and Hu, 2010) to achieve up to 85 % of the value perceived by customers. Sustainability, which is associated with perceived value, attractiveness, and satisfaction (Mihalič, 2000; Mionel et al., 2024), as well as time savings related to travel routes from the tourists’ perspective, is also identified (Kim et al., 2023).
The price of services provided by tourist units is situated in the Q3 quadrant, which typically indicates lower performance and importance. However, a significant percentage of respondents do not consider this condition to be met in terms of satisfaction, intention to return, and attractiveness. Consequently, a concerted effort is mandated to ensure that this factor meets the requisite minimum standard for this condition.
From the perspective of competitiveness, the price of services does not currently stand out as a relevant factor; therefore, it does not require additional attention and does not represent a constraint. This finding contrasts with the claims of Forsyth and Dwyer (2009). The Q3 quadrant also includes time savings, which are correlated with attractiveness, tourists’ intention to return, competitiveness, and satisfaction. However, similar to the observations noted previously regarding price, time savings do not constitute a necessary condition. This result contradicts the findings of Kim et al. (2023) and Lew and McKercher (2006). A similar pattern is observed for sustainability, in relation to the intention to return and competitiveness, as well as urbanization, which is correlated with all constructs.
Finally, the accessibility of the facility and travel area is positioned in quadrant Q4, considering the dimensions of perceived value, intention to return, satisfaction, and competitiveness. A considerable proportion of the respondents indicated that these conditions are not met. Safety concerning the tourist unit and area shows the same pattern. However, neither accessibility nor safety requires additional management efforts, as their current levels are already high, and further improvement would not significantly enhance tourism outcomes.
ConclusionsThis study investigated the need for investment in the Romanian tourism sector through the lens of tourists’ experiences. It evaluated the sector’s performance across several dimensions, including the attributes and resulting effects on the attractiveness and competitiveness of tourism establishments and destinations, as well as customer satisfaction and loyalty. The findings highlighted comfort and service quality as the primary factors influencing destination attractiveness and the perceived value by tourists. While accessibility was perceived as a basic requirement for tourism units, safety did not appear to generate a significant impact, being considered an implicit expectation. In contrast, sustainability, despite having lower performance scores, contributed significantly to both attractiveness and perceived value, representing a key area for targeted resource allocation. The IPMA and NCA analyses confirmed that achieving minimum levels of these attributes is essential for achieving superior outcomes in tourists’ satisfaction and destination competitiveness. Accordingly, investments aimed at enhancing quality and comfort should be prioritized for the sustainable development of tourism in Romania, while improvements in sustainability and urban infrastructure are recommended to align with evolving demands and expectations.
Theoretical implications: This study proposed a new theoretical approach based on the tourism infrastructure framework, in which the components are the attributes and dimensions considered by tourists when selecting their preferred options for a planned trip, as well as the effects that the holiday unit and destination have in the eyes of the tourists. The research highlighted the relationships established between these two components, leading to the final point of the analysis: tourists’ intention to return, which reflects the potential degree of loyalty among tourists.
Methodological implications: From a methodological perspective, this study employed a triangulation technique, which included (1) content analysis, enabling the identification of how tourism infrastructure performance can be evaluated from the customer’s perspective, with input data selected through the PRISMA methodology; (2) PLS-SEM, which facilitated the evaluation of relationships established between the attributes and effects of tourism infrastructure; and (3) IPMA and NCA, which highlighted the necessary conditions for improving the Romanian tourism sector and clarified how each dimension contributed to these outcomes. This comprehensive methodological combination significantly increased the robustness of the results by leveraging the complementary strengths of each technique. The triangulation of these methods not only supported the theoretical and empirical validation of the proposed model but also allowed the formulation of actionable recommendations with high practical relevance for decision-makers in the tourism sector.
Practical implications: This study provides valuable insights for managers, organizations, and decision-makers within the tourism industry by offering a new framework for developing effective strategies aimed at enhancing customer satisfaction and loyalty. The findings will enable these stakeholders to identify and understand the key factors influencing tourists’ vacation planning, thereby supporting more informed decisions regarding resource allocation, the implementation of measures and policies, and the design of marketing campaigns.
Research limitations. The study has several limitations that should be acknowledged. The findings may be characterized by a certain degree of subjectivity, as the data related to the dimensions of tourism infrastructure were collected from respondents who recalled their most recent vacation experience when completing the questionnaire. Furthermore, the tourism infrastructure framework encompasses numerous dimensions beyond the attributes and effects examined in this study. The sample was also predominantly urban and geographically concentrated in the Bucharest–Ilfov region, which may limit the national representativeness of the findings. As the study was conducted exclusively within the Romanian context, the results were inherently influenced by the country’s cultural and socioeconomic particularities, reducing their generalizability. Finally, the cross-sectional design of the study, which captured data at a single point in time, did not allow for the analysis of seasonal or contextual variations.
Future research directions. This research not only provides a solid framework for understanding tourism infrastructure from the customer’s perspective but also opens new avenues for research, encouraging further exploration of the identified relationships and the expansion of the methodological approach across various geographical and sectoral contexts. Continuous research in this direction can contribute to strengthening the overall performance of tourist destinations. Future studies could aim to identify additional components of the tourism infrastructure framework and examine the relationships established among them. Furthermore, investigations focused on specific destinations within Romania that present diverse tourism infrastructure characteristics could offer additional insights. Additionally, for more in-depth analysis, future research could include meaningful subgroup analyses (e.g., domestic vs. international tourists) to determine whether results differ across demographic groups. Finally, a comparative analysis between Romania and other countries, based on the defining elements of the tourism infrastructure framework, would be of significant interest.
CRediT authorship contribution statementȘtefan Cătălin POPA: Writing – review & editing, Supervision, Methodology, Investigation, Formal analysis, Conceptualization. Ana Alexandra OLARIU: Writing – review & editing, Visualization, Validation, Formal analysis, Conceptualization. Corina-Elena MIRCIOIU: Writing – original draft, Methodology, Investigation, Formal analysis.
Source: authors' processing.
| Items | Loadings | α | rho_a | rho_c | AVE |
|---|---|---|---|---|---|
| Sustainability (SUS) (Asmelash and Kumar, 2019) | |||||
| (SUS1) The environment around the tourist unit where I was accommodated was notable for its great diversity of animals and plants. | 0.668 | 0.906 | 0.908 | 0.930 | 0.728 |
| (SUS2) In the area I last visited, efforts to minimize environmental damage were notable. | 0.807 | ||||
| (SUS3) During my trip, I noticed the existence of areas dedicated to the selective disposal of waste (trash cans). | 0.810 | ||||
| (SUS4) On my journey, I identified extremely easy SGR packaging return systems. | 0.783 | ||||
| (SUS5) I believe that the tourist area where I last traveled is in continuous economic prosperity. | 0.800 | ||||
| (SUS6) Both residents and tourists have equal access to activities specific to the area we visited. | 0.711 | ||||
| (SUS7) In the place I last traveled, I believe that local cultural values contribute to the sustainable development of tourism. | 0.782 | ||||
| Safety (SIG) (George, 2003; Popescu, 2011) | |||||
| (SIG1) The staff at the tourist facility where we were staying provided us with information on the measures we should take in the event of an emergency. | 0.734 | 0.762 | 0.780 | 0.840 | 0.514 |
| (SIG2) We were able to visit the chosen tourist area safely. | 0.721 | ||||
| (SIG3) I believe that the tourist unit has emergency plans suitable for any potential unfavorable situations. | 0.832 | ||||
| (SIG4) Public transportation in the area I recently visited was safe/would have kept me safe during my trip. | 0.664 | ||||
| (SIG5) On vacation, I was able to go out for a walk after dark. | 0.615 | ||||
| Time saving (ECT) (Kim et al., 2023) | |||||
| (ECT1) The route chosen to reach the desired tourist destination did not require additional time to travel. | 0.859 | 0.897 | 0.903 | 0.924 | 0.708 |
| (ECT2) I felt like the time allotted for the vacation route passed quickly. | 0.819 | ||||
| (ECT3) I didn't experience any delays due to routes the last time I traveled. | 0.876 | ||||
| (ECT4) The time I allocated to vacation activities was used entirely without being affected by time to travel somewhere. | 0.880 | ||||
| (ECT5) The country's transportation networks helped me save time the last time I traveled. | 0.770 | ||||
| Quality level (CLT) (Ramsaran-Fowdar, 2007) | |||||
| (CLT1) The tourist services were provided on time and in an appropriate manner. | 0.876 | 0.935 | 0.935 | 0.951 | 0.794 |
| (CLT2) The staff of the tourist unit was characterized by promptness and experience. | 0.901 | ||||
| (CLT3) My requirements were understood and met appropriately. | 0.915 | ||||
| (CLT4) I believe that the tourist unit where I was accommodated offers quality services and prioritizes the needs of its customers. | 0.916 | ||||
| (CLT5) I felt like I was treated like a special customer throughout my stay. | 0.845 | ||||
| Accessibility (ACC) (Rahmafitria, Pratama & Miller, 2024) | |||||
| (ACC1) My trip was easy to accomplish due to the unit and the targeted tourist area. | 0.796 | 0.906 | 0.908 | 0.930 | 0.728 |
| (ACC2) I believe that the information provided by the tourism unit was extremely helpful in booking a stay. | 0.851 | ||||
| (ACC3) The way the space was organized by the tourist unit was ergonomic, favorable to tourist activity. | 0.894 | ||||
| (ACC4) I received sufficient directions to easily reach the tourist unit where I chose to stay. | 0.887 | ||||
| (ACC5) The tourist unit was open to receiving any category of customers. | 0.837 | ||||
| Urbanization (URB) (Hall, 2006) | |||||
| (URB1) I consider the destination I chose to travel to as a true center of urbanism. | 0.874 | 0.868 | 0.891 | 0.905 | 0.660 |
| (URB2) Where I last traveled, there are extensive networks for public transportation. | 0.887 | ||||
| (URB3) Shopping areas are everywhere in the places we visited. | 0.847 | ||||
| (URB4) The recently visited tourist area does not only focus on tourism, but also includes other main activities, such as manufacturing. | 0.807 | ||||
| (URB5) There are observed environmental pollution trends in the tourist area I visited as a result of the activities conducted there. | 0.617 | ||||
| Comfort level (CFO) (Brochado and Pereira, 2017) | |||||
| (CFO2) The accommodation unit was characterized by order and cleanliness. | 0.906 | 0.881 | 0.882 | 0.926 | 0.808 |
| (CFO3) I felt at home throughout my stay. | 0.894 | ||||
| (CFO5) The tourist unit is attractive and equipped with modern, easy-to-use facilities. | 0.896 | ||||
| Price of services (PRS) (Gumussoy and Koseoglu, 2016) | |||||
| (PRS1) I believe that the price of the tourist services was reasonable. | 0.898 | 0.913 | 0.922 | 0.936 | 0.745 |
| (PRS2) On my trip, I was surprised by the favorable quality-price ratio. | 0.901 | ||||
| (PRS3) In my opinion, the pricing policy of the tourist establishment where I spent my stay is fair. | 0.899 | ||||
| (PRS4) I would be willing to pay more for tourist services at the same quality level if necessary. | 0.767 | ||||
| (PRS5) The prices currently charged by the tourism unit are affordable for any category of customers. | 0.842 | ||||
| Attractiveness (ATR) (Cibinskiene and Snieskiene, 2015; Saravanan, 2019) | |||||
| (ATR1) The tourist unit is located in an area with a special landscape and countless natural attractions. | 0.642 | 0.815 | 0.839 | 0.880 | 0.650 |
| (ATR3) The website and the way the tourist units are presented online is aesthetically pleasing and attractive. | 0.799 | ||||
| (ATR4) Both the way it looks and the way it relates to the customers who cross its threshold make the tourist unit considered attractive. | 0.890 | ||||
| (ATR5) I was convinced that I had made an excellent choice of tourist facility before arriving at the destination. | 0.872 | ||||
| Perceived value (VAP) (Sánchez et al., 2006; Chen and Chen, 2010) | |||||
| (VAP1) I believe that the value of the tourist services I have received is significant. | 0.792 | 0.903 | 0.906 | 0.928 | 0.723 |
| (VAP2) Beyond the financial value, my trip came to mean much more than the services I received. | 0.883 | ||||
| (VAP3) I experienced cultural and social benefits as a result of my choice of tourist facility. | 0.780 | ||||
| (VAP4) I felt much better than I expected during my stay due to the services I received. | 0.885 | ||||
| (VAP5) The tourist experience I had gained more value for me than I imagined. | 0.902 | ||||
| Satisfaction (SAT) (Ramsaran-Fowdar, 2007; Gumussoy and Koseoglu, 2016) | |||||
| (SAT1) I felt very good throughout the entire trip. | 0.892 | 0.953 | 0.953 | 0.964 | 0.842 |
| (SAT2) I felt like my needs were taken into consideration at all times. | 0.909 | ||||
| (SAT3) I was treated well, which made me forget about my worries. | 0.923 | ||||
| (SAT4) Overall, I was satisfied with the services of the tourist establishment. | 0.929 | ||||
| (SAT5) The idea of staying at that tourist establishment was an excellent one. | 0.935 | ||||
| Competitiveness (COM) (Cibinskiene and Snieskiene, 2015; Saravanan, 2019) | |||||
| (COM1) The offers made available by the tourist establishment easily attract the attention of potential customers. | 0.798 | 0.860 | 0.863 | 0.899 | 0.641 |
| (COM2) Booking can be done quickly and easily compared to competitors. | 0.807 | ||||
| (COM3) The area where the unit is located is highly targeted by tourists. | 0.805 | ||||
| (COM4) The available places of the tourist unit are quickly occupied by customers. | 0.854 | ||||
| (COM5) I need to make a reservation well in advance to find an available place at the facility where I want to stay. | 0.736 | ||||
| Intention to return (REV) (Gumussoy and Koseoglu, 2016) | |||||
| (REV1) I would prefer to spend a stay at the facility where I was accommodated rather than somewhere else. | 0.883 | 0.929 | 0.937 | 0.946 | 0.779 |
| (REV2) I consider myself a loyal customer to the tourist establishment with which I had previous experience. | 0.808 | ||||
| (REV3) I was left with a positive impression of the place where I spent my stay so far. | 0.893 | ||||
| (REV4) I will definitely return to the same place at the next opportunity. | 0.918 | ||||
| (REV5) I will gladly recommend the tourist unit where I spent my stay to my acquaintances. | 0.906 |
α: Cronbach's Alpha. Source: authors with the help of SmartPLS 4 (Ringle et al., 2024).
Source: authors with the help of SmartPLS 4 (Ringle et al., 2024).
STATEMENTS AND DECLARATIONS
Competing Interests:
Authors declare no competing interests
Acknowledgement
The research presented in this paper was funded by the Bucharest University of Economic Studies trough the institutional research project “Modern approaches regarding the analysis of infrastructure investments for tourism development in the current economic context.” This study was partially conducted as a part of the doctoral and the advanced postdoctoral research program in the field of Management at the Bucharest University of Economic Studies.
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