Evaluating Gastronomic Destination Competitiveness through Upscale Gastronomy

Abstract

Food has evolved from a basic necessity to a primary motivation for travel. While providing a high-quality gastronomic offer is still a restaurant’s primary function, quality is no longer enough; today’s demanding guests seek unique and memorable dining experiences. A restaurant’s competences play a significant role in shaping the guests’ overall perception of the quality and derived perceived value, both of which ultimately impact the competitiveness of both the restaurant and the gastronomic destination. The main contribution of this article is the development of a novel theoretical model—GADECOMP—which is designed to measure a gastronomic destination’s competitiveness by centering it around the destination’s gastronomic offer. Exploratory factor analyses confirmed that the instrument is reliable and valid. The model was tested on upscale restaurant guests in Slovenia, Italy, and Croatia. Additionally, the SERVQUAL model of quality measurement was transferred from the entrepreneurial level to the destination level. Our method uses a unique competence approach and expands and diversifies the existing quality concepts by using elements of innovativeness, creativity, sustainability, and local features. The GADECOMP model measures the perceived quality of a gastronomic destination through its competences, which are reflected in the gastronomic destination offer. A regression analysis was used to identify the strength of the effect that perceived value has on the gastronomic destination offer and gastronomic destination competences.

1. Introduction

Gastronomy has become an increasingly important resource for destination development, creating the need for gastronomy studies and generating the term gastronomic tourism. Thus, to be recognized as a gastronomic destination, gastronomy should be implemented into the destination’s strategy at all levels, including during analysis, planning, and execution (community policy) [1,2]. The evolution of gastronomy and gastronomic tourism from 2002 onwards, which has spurred the need for scientific research, is explained below.

The importance of gastronomy, as well as the term gastronomic tourism, was first discussed and introduced in 2002 when it was recognized that people specifically travel for gastronomy, seeking a quality experience beyond the basic physiological need to eat [3]; Slovenia, for example, developed its gastronomic tourism strategy in 2006 [4].

In 2012, the UNWTO acknowledged gastronomic tourism as one of the most dynamic and creative segments of tourism, which is underpinned by sustainability, high quality, and creativity. Gastronomy’s importance in the development of tourism destinations of the world is widely recognized [5,6,7].

In the Second Global Report on Gastronomy Tourism in 2017, the UNWTO Secretary-General Taleb Rifai stressed that people want to experience food in the same way that they want to experience art, music, and architecture; it is explained that gastronomic tourism offers enormous potential in stimulating local economies and enhancing sustainability and inclusion, therefore positively contributing to many levels of the tourism value chain [8].

Since 2016, the International Institute of Gastronomy, Culture, Arts and Tourism has been awarding the European Regions of Gastronomy Award. The program aims to (1) raise awareness about the importance of cultural and food uniqueness, (2) stimulate creativity and gastronomic innovation, (3) promote better nutrition, (4) improve sustainable tourism standards, (5) highlight distinct food cultures, and (6) create long-term benefits, such as attracting visitors to a destination, supporting European small- and medium-sized enterprises, and strengthening community well-being [9].

Moreover, the European Union has launched the Creative Europe program 2021–2027, which has a strong emphasis on innovation mobility schemes for artists and professionals and actions targeting the needs of specific creative sectors such as music, architecture, cultural heritage, gastronomy (as an art form that is a part of cultural tourism) with the creativity of chefs and restaurants [10,11].

The rise of gastronomic tourism has created new tourism destinations, the so-called foodscapes or foodiescapes, such as places featuring Michelin star restaurants [12]. Travelers may be motivated by status and prestige when choosing a destination due to its haute cuisine being awarded Michelin stars and Gault Millau toques or being mentioned on the San Pellegrino list, the “World’s 50 Best Restaurants” list [13].

Okumus [14] outlined future perspectives of gastronomic tourism over the next 75 years (2020–2095), where (1) tourists will be willing to spend more time and money on unique food and beverage experiences and (2) emphasis will be placed on designing a tourism experience based on authenticity, high creativity, sustainability challenges, technologies, and social media; meanwhile, Schwark et al. [15] expect that (3) haute cuisine tourism will grow, where most upscale restaurants will open in Asia and America, and (4) water sommeliers with sophisticated nonalcoholic pairings, 3D printed food, and entomophagy (eating insects) will remain a major trend.

Sustainability is a concept that is increasingly important in gastronomy and gastronomic tourism. When sustainable, tourism is “economically viable but does not destroy the resources on which the future of tourism will depend, notably the physical environment and the social fabric of the host community” [16]. Sustainable tourism therefore strengthens the quality of the destinations and their image. Environmentally conscious tourists are willing to pay higher prices for responsible and sustainable destination products [17]. Therefore, sustainable (destination) products are treated as upscale, which makes them especially important for upscale gastronomy and the gastronomic destination image. Many destinations see gastronomic tourism as a way to generate more sustainable tourism benefits for local businesses, local producers, and regions [18].

The primary contribution of this research is the development of the GADECOMP model, a novel theoretical framework that is specifically designed to measure the competitiveness of gastronomic destinations. The model assesses the perceived quality of a gastronomic destination (hereafter GD) based on its competences as reflected in the gastronomic destination offer (hereafter GDO). The main objective of creating this model was to link various elements of gastronomic tourism and competitiveness that have not yet been discussed in such/similar sets of interdependencies before. Our main question was: does a gastronomic destination offer reflecting competences (quality, innovativeness, creativity, sustainability, and local features) and impact the perceived quality and perceived value of the destination’s restaurants (referred to as destination gastronomy), thus assessing the overall competitiveness of the gastronomic destination? To assess the destinations’ competitiveness through the perceived quality perception, we employed a qualitative approach based on subjectively measurable indicators [19].

In addition to solely focusing on gastronomic resources, a (gastronomic) destination should develop a holistic accompanying offer to meet the demands of increasingly demanding consumers. Such an integrated offer should create a desirable perceived value in the eyes of (gastronomic) consumers. The GDO, which comprises core and supporting destination resources, reflects a wide array of competences. Competences such as quality, innovativeness, creativity, sustainability, and local features all play a vital role in helping destinations achieve their competitive advantages and enhance their competitiveness. These competences can be considered destination competences as they contribute to the competitiveness of a destination’s core and supporting resources. Given that the main focus of this article is gastronomy, which is an essential component of the destination’s offer, we define a destination as a gastronomic destination (GD) if it has developed a high-level gastronomic offer. The term gastronomic destination has been previously used by Yurtseven et al. [20]. There are certain criteria to meet in order to become a gastronomic destination and to attract gastronomic tourists: (1) culinary innovations must be continuous, (2) a comprehensive communication strategy must be developed, (3) appropriate competent resources must be present, and (4) it is crucial that it does not turn into a mass tourism market [8]. Therefore, if a destination comprises a critical amount of quality gastronomy providers (i.e., (upscale) restaurants) it becomes synonymous with excellent gastronomy and can be called a gastronomic destination (an example of such a destination is Tuscany). Accordingly, the competences associated with such a destination are referred to as gastronomic destination competences (hereafter GDCs); their presence has been previously measured by the original SERVQUAL model and its modified versions, which is a multiple-item scale that is based on a customer questionnaire survey [21,22,23]. Firstly, the scale’s reliability, factor structure, and validity on the basis of analyzing data were determined: (1) to test reliability, Cronbach’s alpha coefficients were calculated, where coefficients higher than 0.6 were considered acceptable, indicating internal consistency and reliability; (2) an exploratory factor analysis was used to derive factors from the destination and restaurant resources for the perception scale; and (3) to test validity, a principal component analysis with varimax rotation was used. Later, a Likert-type scale was adopted to assess respondents’ perceptions of the competences’ presence. Descriptive analysis was used, which evaluated customers’ perceptions in the selected destination’s restaurants, assessing the mean and standard deviation values [24,25]. As quality is a prerequisite for competitiveness, in this study, consumers’ evaluations were used to assess the competitiveness of GDs.

2. Literature Review, Model, and Hypotheses Development

2.1. Literature Review

Food is an essential component of travel; as it is a basic daily need, it constitutes a significant portion of travel expenses [26]. According to Wolf and the World Food Travel Association [27], travelers spend approximately 25% of their travel budget on food and beverage (F&B). This percentage can reach up to 35% in expensive destinations and drop to around 15% in more affordable ones. Because gastronomic tourists (i.e., tourists whose main reason for travel is to indulge in culinary experiences) do not merely eat to satisfy their hunger but also wish to explore the local gastronomy, they generally spend more than the average 25% that is spent by travelers [27,28,29].

Gastronomy has become an important feature of tourism. It is a creative part of cultural tourism, enabling tourists to discover a destination through its food, wine, and culture [30]. Experiencing gastronomy while on vacation has been compared with the “consumption of local heritage” [3]. One’s memories of a place can be strongly associated with the gastronomic experiences that they had there and the people that they shared them with. Destinations can be perceived not only visually but also in terms of soundscape, smellscape, and tastescape [31]. Certain foods become synonymous with specific locations, for example, hot dogs with New York, kebab with Istanbul, gyros with Greece, sauerkraut with Germany, and paella and tapas with Spain [32]. In Mediterranean destinations such as Italy and France, gastronomy holds a central role as a principal, core resource. This is the cradle of haute cuisine featuring upscale gastronomic establishments, luxury and gourmet restaurants, and fine dining. However, in most destinations, gastronomy is still considered a supporting resource as the destination’s image is associated with other resources such as culture or recreation; therefore, gastronomy can play a pivotal role in positioning and developing undifferentiated primary resources [5,33].

Gastronomic tourism is still a rather new topic within the tourism industry, and it has gained increased attention since the turn of the millennium; it establishes connections between tourists and the destination’s culture [34]. Bornhorst et al. [35] argue that a destination’s success hinges on a unique location, accessibility, attractive products and services, quality visitor experiences, and community support. Destinations thus face the challenge of shaping an appealing multidimensional offer, and it can be said that the success of a tourism business is the outcome of a destination’s competitive tourism offer [36].

(Service) quality can play a vital role in enhancing the competitiveness of a tourism destination as it serves as a source of competitive advantage. Martin [37] defines service quality as “the ability to consistently meet external and internal customer needs, wants, and expectations involving procedural and personal encounters”. Many scholars have employed modified versions of the original SERVQUAL model proposed by Parasuraman et al. [22] to measure service quality across various types of services (e.g., DINESERV: Stevens [23], DINESCAPE: Ryu and Jang [38], etc. [21,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57]) (

Table 1. Models for measuring various types of quality.

Modified SERVQUAL Models	Description
TANGSERV (Raajpoot, 2002) [51]	Measuring tangible quality in the food service sector (e.g., music, temperature, design, location, seating arrangement, food presentation, food variety)
DINESCAPE (Ryu and Jang, 2008) [38]	Measuring customers’ perception of dining environments, focusing on restaurant environments that are restricted to inside dining areas only
SERVICESCAPE (Bitner, 1992) [40]	Performance-only scale measuring man-made physical surroundings combining both internal and external environments and their impact on customers and employees
DinEX (Antun et al., 2010) [39]	Measuring diners’ expectations of importance by adding social connectedness and homophily
GRSERV (Chen et al., 2015) [21]	Measuring service quality in green restaurants
ECOSERV (Khan, 2003) [46]	Measuring service quality expectations in eco-tourism
LODGESERV (Knutson et al., 1990) [47]	Measuring service quality in the lodging sector
LODGQUAL (Getty and Thompson, 1994) [45]	Measuring customers’ perceptions of delivered quality in the lodging industry
HOLSERV (Wong et al., 1999) [55]	Model pursuing hotel guests’ perceptions of the quality that they receive compared with their expectation
HOLSAT (Tribe and Snaith, 1998) [53]	Measuring holiday satisfaction
DIVEPERF (O’Neill et al., 2000) [50]	Assessing perceptions of diving services
SERVPERF (Cronin and Taylor, 1992) [41]	Performance-based measure of service quality, investigating the relationships between service quality, consumer satisfaction, and purchase intentions
FESTPERF (Marković, Dorčić and Krnetić, 2015) [48]	Measuring festival performance based on local food festival quality
GASTROFEST (Campoverde-Aguirre, 2022) [57]	Evaluating service quality at gastronomic festivals
TOURQUAL (Mondo and Fiates, 2017) [49]	Model for the quality evaluation of services at tourist attractions (tourism destinations, attractions, and events)
HISTOQUAL (Frochot and Hughes, 2000) [42]	Model evaluating the service quality provided in historic houses (historical attractions, museums, and castles)
CERM-CSQ (Howat et al., 1996) [44]	Measuring customer service quality in sports and leisure centers
SERVPEX (Robledo, 2001) [52]	Model evaluating airline service quality
INTSERVQUAL (Frost and Kumar, 2000) [43] and INTQUAL (Zailani et al., 2006) [56]	Internal service quality models measuring employees’ perception of service quality in airlines and the hotel industry
CASERV (Wong and In Fong, 2012) [54]	Comprehensive instrument for measuring casino service quality

).

Quality is a prerequisite for perceived value, which is a multidimensional concept representing a “trade-off between benefits and sacrifices, as perceived by customers” [58] and which is also a prerequisite for competitiveness as well. If we transfer the concept of quality from the entrepreneurial level to the destination level, we can conclude that a destination that reflects overall quality is also competitive. Quality can thus be understood as “the ability to optimize the attractiveness of a destination’s resources in order to offer high-quality, unique, and destination-specific tourism services, resulting in effective and sustainable use of its resources” [59,60]. Morrison [61] argues that physical structures and their size are not as significant to visitors compared with their quality; the quality of services provided by the staff, including their hospitality, and the welcoming attitude of residents are also significant factors. Quality management therefore plays a crucial role in the development of a destination’s offer [61,62].

Competence is an important resource for determining competitive advantage; resource distinctiveness arises through the identification of a unique pattern of competences [63]. The quality of competitive advantage depends on the quality of interaction processes (coordination of resources and competences) and on the quality of resources and competences contributed by business partners [64,65]. By definition, competence (or competency) “is the ability to do something” and is “the quality of being competent”, with the primary focus being on competent individuals who possess the ability or capability to complete the task [66]. Competence can be categorized as: (1) individual competence that focuses on the personal and cognitive traits of competent managers or employees in relation to their job performance; (2) organizational competence that focuses on corporation-wide strategic competence and collective practices; and (3) comprehensive competence that integrates both individual and organizational strategic competences [67]. Therefore, “the factors governable by the organizations, which make them survive and succeed, are the competence factors—and of the whole of those factors from a work effort of the simplest floor person to the biggest technological breakthroughs and financing possibilities; everything within the boundaries of an organization that enables its performance, belongs to its competence” [68]. Because a destination, being a legal entity (a non-living thing), possesses organizational competences, it can also possess destination competences. Consequently, destination competences encompass everything within a destination’s boundaries that enables its performance and success. Based on this observation, we define destination competences in our model as everything within the boundaries of a destination that enables its performance and success, including: (1) destination resources (core and supporting resources), (2) gastronomic resources (restaurant quality and service quality), and (3) GDC (quality, innovativeness, creativity, sustainability, and local features).

Furthermore, Hjalager [69] argued that the destination serves as a repository of competence and knowledge, which is crucial for the development of products and services (i.e., the destination offer). Intellectual capital, being a set of intangible resources and capabilities comprising different categories of knowledge, contributes to a competitive advantage and consists of: (1) human capital (knowledge, experiences, skills, and motivation embedded in employees), (2) structural capital (methods, capabilities, routines, and procedures embedded in the organization), and (3) relational capital (capabilities, knowledge, and procedures embedded in the organization and arising from relationships with suppliers, customers, partners, and others) [70].

Destination competitiveness is a highly significant topic in tourism, and numerous studies have been conducted to study this element. A groundbreaking contribution is Ritchie and Crouch’s Conceptual model of destination competitiveness [71], which offers a comprehensive interpretation of destination competitiveness by asserting that a destination’s competitiveness depends on its ability to generate and/or increase tourism expenditure. Today, competition among destinations is no longer only focused “on the single aspects of the tourism product”; rather, it is viewed as an “integrated and compound” set of tourism services that form the destination offer [36,72]. Therefore, a destination that places a strong emphasis on gastronomic tourism with a high level of gastronomy can be referred to as a gastronomic destination.

2.2. Model Development

To measure the perceived quality of restaurants and hence of gastronomic destinations, we modified and upgraded the DINESERV model [23], which originates from the SERVQUAL model [22]. The new model is called GADECOMP (GAstronomic DEstination COMPetitiveness). It comprises selected dimensions of the following supplemented SERVQUAL model versions:

• DINESERV (Stevens et al.; Kim et al. [23,73]), which measured the quality of a restaurant’s services;
• DINESCAPE (Ryu and Jang, [38]), which measured the quality of a restaurant’s physical environment;
• GRSERV (Chen et al. [21]), which measured the service quality in green restaurants (and thus including sustainability) as well as parameters suggested by the author.

We combined the competence parameters from the three abovementioned service quality model versions that have best described restaurant services (DINESERV), the restaurant physical environment (DINESCAPE), and restaurant green practices (GRSERV). To eliminate the shortcomings of the three existing quality systems and achieve a more holistic service quality model, we added the following crucial competence parameters: local features (as part of social responsibility, which in this research is considered as imminent in sustainability) and innovativeness and creativity. The dimensions of innovativeness and creativity were described as crucial in previous research on restaurant innovativeness [74,75]. The competences examined in this study, namely quality, innovativeness, creativity, sustainability, and local features, are all crucial for the differentiation process and are thus crucial for competitiveness in today’s demanding and increasingly saturated tourism market.

The novel method applied herein relates to the transfer of perceived quality measurement from the entrepreneurial level to the destination level. The approach for GD competitiveness measurement was based on the quality measurement on the demand side. Unlike the famous destination competitiveness models ([71,76,77,78,79]) that employ a supply-side approach, we adopted a destination competitiveness model and applied it from the demand-side perspective. This allowed us to incorporate and put into a broader context selected dimensions from the following models: (1) Ritchie and Crouch’s conceptual model of destination competitiveness [71], (2) Goffi’s determinants of tourism destination competitiveness: a theoretical model and empirical evidence [79], and (3) Koch’s model of the dimensions of tourism quality in a destination [80], as well as (4) parameters suggested by the author.

According to the GADECOMP model, the destination resources create its comparative advantages (i.e., destination resources derived from nature, such as pristine nature, climate, cultural and social attractions) and competitive advantages (i.e., a skilled, creative, and sustainability-oriented workforce comprising restaurant chefs, highly competent local cooks, sommeliers, waiters, restaurant managers, restaurant owners, interior designers, supporting infrastructure, tourism facilities, DMOs, and local businesses) in or keep the to the GDO. These resources are categorized as core resources and supporting resources according to Ritchie and Crouch [71]. Sánchez-Cañizares and López-Guzmán [81] define gastronomy as a tourism resource. Because we assume that gastronomy is one of destination’s main pull factors, we define the gastronomic offer as a gastronomic resource and place it among the core resources of a tourism destination. Therefore, in the model, the destination offer includes core and supporting resources. Gastronomy (i.e., gastronomic resources and restaurants as the most important part of a GDO), sports and recreation (accompanying sports and recreational activities for gastronomic tourists in pristine natural environments and in a pleasant climate), and culture and entertainment (cultural attractions and entertainment options, including dance, music, festivals, workshops, etc.) are all considered core resources of a GD. Supporting resources consist of tourism facilities (accommodations, restaurants, attractions, and leisure activities), general infrastructure (accessibility, safety and security, proximity to other destinations, transportation quality, environmental quality, care for sanitation, and sewage and waste), and other destination assets (hospitability of local residents, presence of local businesses, destination image, and DMO).

To become competitive, a GDO must embody quality, innovativeness, creativity, sustainability, and local features as its indispensable competences. The destination’s resources were assessed using the GDCs mentioned above. The competences all collectively influence the customers’ perceived value of the destination through the perceived quality of restaurants. Perceived quality—as a prerequisite for competitiveness—allows us to measure a GD’s competitiveness using the novel GADECOMP model through the use of the consumers’ perception as a subjectively measurable indicator.

2.3. Hypotheses Development

In line with the introduction, literature review, and model development, the following hypotheses are proposed:

Hypothesis H1.

GDO has an impact on the perceived value of restaurants.

Hypothesis H1.1.

The destination’s core resources have an impact on the perceived value of restaurants situated in this destination.

Hypothesis H1.2.

The destination’s supporting resources have an impact on the perceived value of restaurants situated in this destination.

Destinations usually develop their offer based on the types of resources that they possess, which must all work together to create a destination that is competitive, attractive, creative, sustainable, authentic, and unique [82]. Gastronomy, for example, has recently been acknowledged as one of the most important destination resources [8]. Core resources, such as gastronomy, culture, sports and recreation, and entertainment, are the primary elements that attract tourists and motivate their decision to choose a specific destination. Supporting resources, such as tourism facilities, general infrastructure, and other destination assets, merely complement the core resources and are not the prime motive for travel; rather, they provide a foundation for a successful tourism offer [71,79]. This method of classifying destination resources was applied in this research.

Core and supporting resources must reflect quality. According to Henderson [83], gastronomy enhances guests’ sense of participation and attachment to a location, whereas a poor quality of the gastronomy offer (i.e., food and beverage (F&B) or service quality) can have a negative impact on the destination’s reputation.

To survive, thrive, and position themselves in an environment of fierce competition, destinations must know, understand, and satisfy their guests’ needs and use their resources effectively [84]. Dwyer and Kim [77] adopted an approach to measure destination competitiveness based on Porter’s diamond model [85] and Ritchie and Crouch’s model [71]. Moreover, Vengesayi [86], Ferreira and Estavo [87], Khin et al. [88], and the World Economic Forum [89] have used a similar categorization of supporting resources in the destination competitiveness models and indicators to our own; namely, they included attractions, general infrastructure, destination management, destination image, local business environment, human resources, environment, openness, etc. According to Chin [90], it is crucial for a destination’s competitiveness to bolster its supporting resources, which is especially true for rural tourism destinations. Bornhorst et al. [35] argued that a unique and accessible location, well developed infrastructure, quality visitor experience, attractive products and service offerings, and community support are crucial for a destination’s success. Destinations thus face the challenge of creating an appealing multidimensional offer that includes both core resources and supporting resources. In essence, the success of a tourism business is determined by the destination’s competitive tourism offer [36]. This shows that a holistic approach is essential for a successful destination offer development.

Hypothesis H1 aims to investigate whether a destination’s offer (i.e., its core and supporting resources) has any impact on the perceived value of restaurants through perceived quality, which is its prerequisite. A tourism destination is more appealing to tourists if it offers them great value. According to Gomezelj Omerzel and Mihalič [78], “destination management should take care in creating and integrating value in tourism products and resources so that a tourism destination can achieve a better competitive advantage”. Barney [91] and Mior Shariffuddin et al. [92] suggested that a destination’s competitive advantages, particularly the ones derived from unusual, precious, incomparable, or inimitable tangible and intangible resources, indeed strengthen the destination’s competitiveness. The availability of resources is of significant concern for destinations, businesses, or industries, as it helps them to sustain long-term competitiveness [93]. Therefore, mainly tourism destination competitiveness was measured by categorizing tangible and intangible core and supporting resources. Basle [94], however, adopted an approach to measure the competitiveness of a gastronomic destination based on the perceived quality of its resources, which is a prerequisite for competitiveness, as perceived and valued by tourists.

Quality is a prerequisite for perceived value [58]. If a destination’s offer reflects quality, it is perceived as more compelling to tourists. The research addressing quality and tourism has been approached by researchers in various contexts, e.g., perceived quality of a destination in connection to visitor satisfaction and their behavioral intentions [95,96,97,98]; quality of a tourism destination [99,100,101,102]; destination quality management best practices [103]; tourist judgement on the service quality of winter sport destinations [104]; analysis of the quality of service in gastronomic festivals in a tourist destination of Ecuador [57]; the overall quality of tourism services in Kashmir Valley [105]; the relationship between tourism service quality and destination loyalty through destination image in the Dead Sea tourism destination of Jordan [106]; the economics of reputation and quality decisions for a tourism destination with implications for competitiveness [107]; competitiveness through quality in the hospitality industry [60]; destination environment quality [108]; and quality tourism experience [109]. Moreover, some applications of the SERVQUAL model [22] were developed while measuring the service quality of destinations, such as the TOURQUAL model [49]; the HISTOQUAL model [42]; the LODGQUAL model [45]; the LODGSERV model [47]; the HOTELQUAL model [110]; and the HOLSAT model [53] (see Table 1).

Previous studies on value in tourism have primarily focused on the perceived value for tourists (since the 2000s); however, none of the studies have expanded and modified SERVQUAL application models to assess the quality of core and supporting resources within the destination offer (Ritchie and Crouch categorization, [71]) or transferred the model from the entrepreneurial level to the destination level to measure destination competitiveness based on perceived quality.

Hypothesis H2.

GDCs have an impact on the perceived value of restaurants.

Hypothesis H2.1.

The quality of upscale restaurant resources has an impact on the perceived value of restaurants.

Hypothesis H2.1.1.

The tangible upscale restaurant quality has an impact on the perceived value of restaurants.

Hypothesis H2.1.2.

The intangible upscale service quality has an impact on the perceived value of restaurants.

Hypothesis H2.2.

Innovativeness and creativity have an impact on the perceived value of restaurants.

Hypothesis H2.3.

Sustainability and local features have an impact on the perceived value of restaurants.

The destination offer should reflect competences. This is particularly true for gastronomic resources such as restaurants. In addition to offering quality F&B that is produced using local ingredients, restaurants should employ qualified staff that are able to offer quality services, keep pace with modern trends of sustainability, and be innovative and creative. Altogether, these factors generate the necessary added value to a restaurant and thus to gastronomic resources.

The link between quality and perceived value has been discussed in various studies on service quality perception in the restaurant and hotel industry [24,111,112,113,114] (see also Table 1), but not as much in the context of upscale restaurants. The importance of quality and tangible restaurant resources was researched by Ryu and Jang [38] in an applied quality model known as DINESCAPE. The quality of a restaurant’s tangible environment (price fairness, physical environment, and cleanliness) was explored from the perspective of customer retention [115]; however, the quality of intangible services, “the appropriateness of assistance and support provided to a customer and the value and benefits received for the price paid” [116], is difficult to judge. Reliable evaluation criteria in this regard include price, the physical environment of the service, and the taste of the F&B served, which create an overall perceived value. Service quality (sometimes also referred to as perceived quality) is an important antecedent of perceived value [117,118,119], which is a “customer’s overall assessment of the utility of a product based on perceptions of what is received and what is given” [120]. Perceptions are very subjective and depend upon cultural standards, individual cultural profiles, previous experiences, and guests’ expectations [116]. Consumers are no longer paying just for the basic service but for the complete experience; they are willing to pay a premium for the added value offered by experiences that are above standard services [121]. Experiences can touch people better than products and services. They are intangible, immaterial and tend to be expensive; however, they are memorable and highly appreciated [122]. Similarly to how the destination experience is a fundamental destination product, the dining experience is a crucial restaurant product [3]. Dining experiences are influenced by the overall service, i.e., what is served and how it is served, as well as where it is served [123]. This article therefore examines both the restaurant’s physical environment and service quality in upscale dining.

The main challenge of this century is innovation, which has encompassed both invention and its successful commercialization [124,125]. The terms innovation and innovativeness, although interchangeably used in the business and hospitality literature, significantly differ. “Innovation focuses on the outcomes of new elements or a new combination of traditional elements in a firm’s activities, while innovativeness refers to a firm’s capability to be amenable to new ideas, services and promotions” [75,126,127,128]. Creativity, which is closely linked to innovation and novelty, represents an organization’s ability to generate fresh and useful ideas at different stages of the innovation process, utilizing available knowledge to make new discoveries [129]. Although creativity and innovation are sometimes interchangeably used in the literature, they have distinct meanings. Creativity focuses on the generation of new and original ideas, while innovation involves the implementation of these creative ideas [130]. Additionally, diversity is seen as the main resource for fostering creativity [131]. Creativity without innovation is just one more idea, while innovation that is not based on new and novel ideas does not add value. Hence, creativity and innovation are integral components of the overall innovation process [130,132].

Innovation (innovativeness) is not only a precondition for improving business but also a means to express quality [133]. The higher the restaurants’ innovations in products and services, the higher the quality perceived by the guests [134] in fine-dining restaurants [74,135,136]. However, previous research on innovation in the restaurant sector is scarce, and it has mostly focused on new product development (e.g., molecular gastronomy) and technical innovations concerning cooking methods and the use of technology [137,138]. More recent studies on innovativeness in restaurants include innovation in restaurant management [137], innovative organizational culture in the restaurant industry to improve restaurants’ business performance [139], and innovative capabilities enhancing the internationalization of restaurants (i.e., developing new dishes, using modern equipment, using new technologies, and updating menus) [140]. The tourism and hospitality literature pays less attention to innovativeness compared with the general business literature [75]. Innovation has mostly been researched through the lens of companies and entrepreneurs in terms of profitability, success, and market value [141]; this same approach was used when analyzing the impacts of innovation in hospitality and tourism [142,143,144,145,146,147,148].

Dimensions of innovativeness and creativity were interlinked with studies on the perceived upscale restaurants’ image, the perceptions of price fairness and post consumption behavioral intention [135,136], and the perceived value of restaurant innovativeness [75] and creative tourism destinations [149]. Guan et al. [150] explored the relationship between customer knowledge sharing, creativity, and customer-perceived economic value creation. Some interesting research on restaurant innovativeness [151] was associated with customer perception [75].

According to Milfelner [152], theoretical contributions and empirical evidence show that innovation sources—both innovativeness and innovation capacity—are the sources that fulfil every requirement and have the potential to achieve competitive advantages. Competitiveness was explored in studies on innovativeness in tourism [153,154,155]. Evans [156] suggested that branding based on cultural and creative resources is crucial for the competitive position of businesses, regions, and cities.

Sustainability, whose concept originates in the 1970s but has roots dating back to Roman times, encompasses considerations for the environment, people, and economy, with a primary focus on environmental aspects [17]. Its fundamental goal is to ensure a better quality of life for both present and future generations [157]. Sustainability therefore aims to strengthen the quality of the destinations and their image. Moreover, environmentally conscious tourists are willing to pay higher prices for destination products that are responsible and sustainable [17,158]. Consequently, sustainable (destination) products are perceived as upscale, which makes them particularly important for upscale gastronomy. The concept of sustainability is intrinsically linked to local features (sometimes also referred to as locality; [159,160]). The term local is directly associated with sustainability, authenticity, quality, and community, and it holds the potential to create a destination’s competitive advantage [157,161]. While extensive research has been conducted on sustainability, local features within the context of tourism have not yet been widely explored.

Research on sustainability in restaurants is relatively recent. There is a growing interest in green consumption and environmental protection within the restaurant industry [162,163,164]. For instance, Filimonau et al. [165] explored innovative trends in menus that promote sustainability in terms of responsible consumer choices. Liu et al. [166] investigated how creative menus lead to favorable consumer responses, including positive attitudes towards the menu and enhanced perceptions of brand healthiness. Because of the growing environmental awareness among consumers, sustainable practices are being applied in food systems as well, including food miles, slow food, local food, etc. [167,168,169]. Sustainability has been linked with local features in various contexts [20,159,160,170,171]. The marketing literature has contributed to the understanding of consumer behavior towards green restaurants [172], while other research has focused on management aspects, such as green supply chain management [173] and sustainability management [174]. There is also a link between sustainability and competitiveness, as businesses are believed to benefit from adopting environmentally friendly practices [175,176]. Because sustainability is closely intertwined with local features, Malecki [177] suggested that creating and imitating competitiveness based on local knowledge and local culture can be difficult.

Hypothesis H2 aims to investigate whether GDCs (i.e., quality, innovativeness, creativity, sustainability, and local features) have any impact on the perceived value of restaurants. If a restaurant focuses on sustainability and local features in addition to being creative, innovative, and thus authentic, it undoubtedly creates value for guests; however, no research has yet focused on the above five concepts and perceived value in restaurants simultaneously in an integrated manner.

The link between sustainability and perceived value has not yet been thoroughly explored. Previous research has revealed how consumers perceive restaurants with green attributes and how this influences their behavioral intentions [178,179,180]. Further research has shown that sustainability practices contribute to competitiveness and consumer satisfaction [181], enhance customer value [182], strengthen the role of customer behavior in shaping a perceived value for restaurants [183], positively impact green restaurant image and revisit intention through perceived service quality [184], etc. Outside the restaurant sector, Flagestad and Hope [185] showed how a winter sport destination can create sustainable value to achieve strategic success, while Kataria et al. [186] focused on the perceived value of sustainable brands in India.

Likewise, local features have not yet been extensively explored in connection to perceived value. In the restaurant sector, consumers show great interest in green practices that directly affect their well-being, such as the use of organic and locally grown ingredients. These components increase their perceived value of restaurants [187]. Because local food is perceived as healthy, [188] illustrates how perceived food healthiness in restaurants influences value, satisfaction, and revisit intentions. Regarding traditional food as a type of local resource, Chen et al. [189] found that consumers who feel more nostalgic about traditional restaurants, thus being exposed to local features, tend to perceive a higher value of their dining experience. Konuk [190] investigated the role of perceived food quality, price fairness, perceived value, and customer satisfaction on consumers’ intentions to revisit organic food restaurants. The research has expanded to regional wines and has investigated wine consumers’ perceptions about regional environments, which are associated with their perceived value of purchasing regional wine [191].

The developed hypotheses and sub-hypotheses are presented in the following Figure 1.

3. Methodology

The quantitative analysis in this research was based on our own survey, which was conducted among upscale restaurant visitors in two selected gastronomic cross-border destinations. The data were collected through a self-administered, printed questionnaire (GADECOMP).

After conducting a literature review and studying the existing instruments, we designed the items for the GADECOMP questionnaire. We modified and upgraded the existing DINESERV model [23], which originated from the SERVQUAL model [22], by adding innovativeness, creativity, sustainability, and local features. Additionally, we incorporated Ritchie and Crouch’s conceptual model of destination competitiveness [71] to evaluate the quality of a destination’s (core and supporting) resources.

The content validity of the questionnaire was first assessed by three academics: two from the field of tourism and one from the field of marketing. For the purposes of this paper, we used the generally accepted SERVQUAL model and its modified versions [21,22,23,38,79], which have already been tested for validity and reliability, as their content assesses the restaurant’s physical environment and service quality. However, to eliminate the literature gap, we developed the following criteria: (1) the extended literature review was performed on the items that were previously neglected in the SERVQUAL model and its applications, namely sustainability, local features, innovativeness, and creativity; and (2) three professionals and scientists from the areas of marketing and tourism were invited to assess the content validity of the abovementioned items that were constructed from the literature review and author’s suggestions. All three experts did not have any additional comments and did not require any necessary changes to the written statements. The experts were provided with definitions and conceptualizations and asked to assess the content validity of the items in relation to their respective constructs. Following this, questionnaires were provided to a restaurant (Denk in Zgornja Kungota, Slovenia, awarded with one Michelin star) for preliminary testing on a small sample. An exploratory factor analysis was used to test the content validity and reliability of the instrument. The validity was tested using a principal component analysis with varimax rotation. To assess the scale reliability and internal consistency of each extracted factor, Cronbach’s alpha coefficients were calculated. At this point, some questions were eliminated and others were rephrased due to low factor scores or low communalities. The exploratory actor analysis was later repeated on the final sample as well.

The GADECOMP questionnaire consisted of two main parts that measured the comparative and competitive advantages and was divided into three sections. The first section assessed the perceived quality of the gastronomic destination (GD) by evaluating the competences of resources in the destination offer. The relevance of the given items was evaluated on a five-point Likert scale (1 = strongly disagree to 5 = strongly agree). A higher score indicated a greater perception of the quality of the destination’s resources and thus of the quality of the gastronomic destination offer (GDO). The second section measured the perceived quality of a specific restaurant by evaluating the competences of its gastronomic resources. Here, the relevance of the items was assessed on a five-point Likert scale as well (ranging from 1 to 5). A higher score indicated a greater perception of the quality of the gastronomic resources. In our research, the perceived quality of the destination and its gastronomic resources, which reflect the perceived quality of a GD’s offer, served as an indicator of the overall competitiveness of a GD’s offer. The third section of the questionnaire focused on assessing the demographic characteristics of the respondents: their country of residence, age, gender, level of education, and main motives for travelling to a destination. The questionnaire was originally written in English and was translated into German, Slovene, Croatian, and Italian (the most frequent nationalities of the guests in the selected regions) to ensure that respondents could understand the questions correctly. The back-translation procedure was used.

The designed GADECOMP questionnaire underwent further testing. A convenience sample of domestic and international upscale restaurant guests was asked to fill out the GADECOMP questionnaire by the restaurant owner. Data collection took place over a six-month period from September 2018 to March 2019 in a total of 12 upscale restaurants located in Slovenia, Italy, and Croatia. The selected restaurants were renowned for their exquisite, upscale cuisine, as acknowledged by well-known gastronomic guides such as the Michelin Guide and Gault Millau. A total of 335 valid questionnaires were completed from the 338 filled out questionnaires. The relevant database was developed using the SPSS 26.0 statistical program.

Data were gathered before the coronavirus disease 2019 (COVID-19) pandemic. Regarding upscale gastronomy and excellent/gourmet gastronomic tourism, the focus has stayed the same in the pre-COVID and post-COVID period; this means that there is a shift from mass tourism to boutique tourism, which presents a holistic, innovative, sustainable, and high-quality tourism offer. According to Schwark et al. [15], the COVID-19 pandemic has led to: (1) restaurant bankruptcies, (2) a rise in innovativeness and creativity among the remaining restaurants, (3) a rise in upscale (haute cuisine) gastronomic tourism, and (4) customers being the co-creators of the value in upscale gastronomy. On the other hand, according to the reports and forecasts of the UNWTO during the COVID-19 pandemic, they were very optimistic; after humanity has learned to live with the COVID-19 virus, tourism was expected to recover again and gastronomic tourism was expected to return to its former state. Therefore, our goal was to create a timeless model that could be applicable locally, internationally, and independently of the changing environment.

4. Factor Analysis Results

The exploratory factor analysis for the constructs, including destination resources, restaurant resources, sustainability and local features, innovativeness and creativity, and perceived value and their items, was repeated on the final sample to test the validity and reliability of the questionnaire. During this phase, certain items were eliminated due to low factor scores or low communalities; some were rephrased, which resulted in the final instrument version consisting of 14 items on a destination’s core resources, 21 items on a destination’s supporting resources, 22 items on restaurant quality, 17 items on service quality, 9 items on sustainability and local features, 14 items on innovativeness and creativity, and 4 on perceived value. In continuation, each construct is explained in detail in its own subchapter. We begin with destination resources, which comprise the core and supporting resources. Supporting resources are further categorized into tourism facilities, general infrastructure, and other destination assets.

4.1. Destination Resources: Core Resources

The first part of the questionnaire, which assessed the comparative advantage and measured the destinations’ resources, yielded four factors within the Section 4.1 (14 items; no items were excluded), including culture, sports and recreation, gastronomy, and entertainment. These four factors accounted for 73.63% of the variance of all items, which was higher than the suggested 60%. The Kaiser–Meyer–Olkin measure (KMO = 0.797) showed that the data were suitable for the factor analysis (

Table 2. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.797
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	2.839	20.278	20.278
2	2.708	19.344	39.622
3	2.392	17.087	56.708
4	2.368	16.917	73.625

). Bartlett’s sphericity test was statistically significant at p < 0.05. All communalities were greater than 0.4, indicating a high correlation between items. All loadings on the underlying factors were higher than 0.6, while the loadings on the other factors were lower than 0.3 (only loadings on underlying factors are shown in the following tables). The Cronbach’s alphas were all above the value of 0.6, indicating an adequate reliability of the scale (

Table 3. Destination resources: core resources.

Items	Factor Groups	Communalities	Cronbach’s Alpha
Cultural attractors are of high quality.	Culture	0.765	0.868
Historical and archaeological sites are of high quality.		0.808
Artistic and architectural features are of high quality.		0.797
The destination offers a variety of sports and recreational activities.	Sports and recreation	0.746	0.866
The sports and recreational activities are of high quality.		0.839
The sports and recreational activities are fun.		0.802
The destination offers a variety of gastronomy (cuisine and wine).	Gastronomy	0.651	0.821
The destination offers local gastronomy (cuisine and wine).		0.748
The gastronomy (cuisine and wine) is of high quality.		0.806
Typical local products are of high quality.		0.519
The shopping opportunities are of high quality.	Entertainment	0.470	0.849
The events are of high quality.		0.760
The evening entertainment is of high quality.		0.843
The nightlife is of high quality.		0.844

).

4.2. Destination Resources: Supporting Resources of Tourism Facilities

From the supporting resources section of tourism facilities, two factors emerged: the offer and facilities. The two factors combined accounted for 71.63% of the variance of all variables (

Table 4. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.818
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	2.906	41.508	41.508
2	2.108	30.118	71.626

).

Table 5. Destination resources: supporting resources of tourism facilities.

Items	Factor Groups	Communalities	Cronbach’s Alpha
The facilities at the destination are of high quality.	Tourism facilities	0.742	0.765
The accommodations are of high quality.		0.718
The restaurants are of high quality.		0.586
The tourism offer (attractions, leisure activities and facilities) is sustainably and locally oriented.	Tourism offer	0.704	0.880
The tourism offer (attractions, leisure activities and facilities) is innovative and creative.		0.790
The tourism offer (attractions, leisure activities and facilities) is of high quality.		0.835
There is a high level of professional skills in the tourism service offer.		0.639

presents the final set of seven items. Kaiser–Meyer–Olkin’s measure (KMO = 0.818) showed that it was appropriate to proceed with a factor analysis. Bartlett’s sphericity test indicated statistical significance (p < 0.05).

The communalities were above 0.4, which indicated a high correlation between the items. The Cronbach’s alpha coefficients demonstrated adequate scale reliability as they exceeded the value of 0.6 (Table 5).

4.3. Destination Resources: Supporting Resources of General Infrastructure

The final set of nine items in the supporting resources section of general infrastructure formed three factors: transportation, accessibility, and local environment. Kaiser–Meyer–Olkin’s measure (KMO = 0.794) showed that it was meaningful to proceed with a factor analysis, while Bartlett’s sphericity test also demonstrated statistical significance. The three factors together explained 67.72% of the variance of all variables (

Table 6. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.794
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	2.242	24.914	24.914
2	1.973	21.917	46.831
3	1.879	20.883	67.715

).

All of the communalities were above 0.4, indicating a high correlation between the items. The Cronbach’s alpha coefficients, which tested the reliability, were all higher than 0.6 (

Table 7. Destination resources: supporting resources of general infrastructure.

Items	Factor Groups	Communalities	Cronbach’s Alpha
The transportation (highways, railways, bus services, airports, ferries, etc.) is of high quality.	Transportation	0.754	0.799
The transportation is safe.		0.760
The transportation is environmentally friendly.		0.843
The destination is accessible.	Accessibility	0.470	0.707
The destination is safe and secure.		0.806
The destination is accessible to disabled persons.		0.748
Other tourist destinations are close.	Local environment	0.519	0.683
The destination’s environment is of high quality.		0.651
The destination takes good care of sanitation, sewage, and solid waste disposal		0.839

).

4.4. Destination Resources: Supporting Resources of Other Destination Assets

The supporting resources section of other destination assets yielded two factors: reputation and local features. Kaiser–Meyer–Olkin’s measure (KMO = 0.748) indicated that the data were suitable for a factor analysis (

Table 8. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.748
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	2.148	42.965	42.965
2	1.688	33.770	76.735

). Bartlett’s sphericity test was statistically significant at p < 0.05. The two factors together explained 76.74% of the total variance of all variables. All of the communalities were greater than 0.4, which showed a high correlation between items. The Cronbach’s alpha coefficients were above 0.6, indicating an adequate reliability of the scale (

Table 9. Destination resources: supporting resources of other destination assets.

Items	Factor Groups	Communalities	Cronbach’s Alpha
Local residents are very hospitable.	Local features	0.775	0.730
Local businesses are present.		0.787
The destination offers value for my money.	Reputation	0.652	0.822
The destination has a high image.		0.819
The destination management is successful		0.804

).

The next subchapter deals with gastronomic resources, which include: tangible upscale restaurant quality, which focuses on the restaurant’s physical environment; intangible upscale service quality, which evaluates the quality of the food and beverage (F&B) and service; the sustainability and local features that are used by the upscale restaurant; the creativity and innovativeness that is present in the restaurant’s performance, service, and appearance; and the perceived value of the upscale restaurant if it reflects all of the above.

4.5. Gastronomic Resources: Tangible Upscale Restaurant Quality: Facility Aesthetics, Ambience, Table Settings, Interior and Exterior Layout, and Cleanliness

The second part of the questionnaire, which measured gastronomic resources, yielded five factors from the tangible restaurant quality section: cleanliness, facility aesthetics, interior and exterior layout, ambience, and table settings, numbering twenty-two items in total. Kaiser–Meyer–Olkin’s measure (KMO = 0.874) showed that the data were suitable for a factor analysis. Bartlett’s sphericity test was statistically significant at p < 0.05. The five factors together explained 66.03% of the variance of all variables (

Table 10. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.874
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	3.220	14.638	14.638
2	3.168	14.401	29.039
3	3.050	13.864	42.902
4	2.605	11.839	57.741
5	2.484	11.292	66.033

).

Overall, the communalities were greater than 0.4 despite two of the loadings—"the furniture (e.g., dining table, chair) is of high quality (0.590)” and “the lighting creates a warm atmosphere” (0.580)—being slightly lower than the recommended value of 0.6. The Cronbach’s alpha coefficients showed adequate scale reliability as all values were above the value of 0.6 (

Table 11. Gastronomic resources: tangible upscale restaurant quality: facility aesthetics, ambience, table settings, interior and exterior layout, and cleanliness.

Items	Factor Groups	Communalities	Cronbach’s Alpha
The paintings/pictures on the wall are attractive.	Facility aesthetics	0.702	0.833
The wall decor is visually appealing.		0.763
The plants/flowers create a nice environment.		0.621
The colors are used create a warm atmosphere.		0.624
The furniture (e.g., dining table, chair) is of high quality.		0.451
The background music is relaxing.	Ambience	0.539	0.797
The temperature is comfortable.		0.730
The smell is pleasant.		0.758
The lighting creates a warm atmosphere.		0.494
The table linens (e.g., table cloths, napkins) are attractive.	Table settings	0.606	0.821
The table setting is visually appealing.		0.665
The menu is visually attractive.		0.760
The menu is easily readable.		0.641
The parking areas and the building’s surroundings are attractive.	Interior and exterior layout	0.712	0.819
The restaurant has enough parking space.		0.733
The restaurant is accessible to persons with disabilities.		0.596
The seating arrangement is sufficiently spacious.		0.639
The layout is comfortable and makes it easy for me to move around.		0.645
The restrooms are thoroughly cleaned.	Cleanliness	0.655	0.863
The dining area is clean.		0.727
The tableware is clean, and tables are freshly covered for every new guest.		0.757
The staff is neat and clean.		0.708

).

4.6. Gastronomic Resources: Intangible Upscale Service Quality

Comprising a total of 17 items, 4 factors from the intangible service quality section were formed: reliability, quality and taste, ability to adjust, and diversity. The four factors together accounted for 68.43% of the variance of all variables (

Table 12. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.897
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	3.932	23.130	23.130
2	3.253	19.136	42.266
3	2.334	13.727	55.993
4	2.115	12.439	68.432

). Kaiser–Meyer–Olkin’s measure (KMO = 0.897) suggested that it was appropriate to perform a factor analysis. The communalities in total were above 0.4, while the loading “the staff provides prompt and quick service” (0.581) was slightly lower than 0.6. Cronbach’s alpha coefficients were above the value of 0.6, which showed adequate scale reliability (

Table 13. Gastronomic resources: intangible upscale service quality.

Items	Factor Groups	Communalities	Cronbach’s Alpha
The staff provides prompt and quick service.	Reliability	0.423	0.873
The staff quickly corrects anything that is wrong.		0.564
The staff is reliable.		0.739
The staff is consistent.		0.730
The staff makes extra efforts to handle my special requests.		0.649
The staff makes me feel special.		0.632
The staff has the ability to adapt to different cultures of the guests.	Ability to adjust	0.642	0.772
The staff can speak and understand foreign languages.		0.648
The staff is sympathetic and keeps calm if something goes wrong.		0.629
The staff seems to enjoy the restaurant’s support and can thus do their job well.		0.586
The quality of food is excellent.	Quality and taste	0.828	0.902
The quality of beverages is excellent.		0.825
The beverages match the selection of food.		0.766
The taste of the food is excellent		0.726
The food is attractively presented.	Diversity	0.685	0.798
The selection of the food is varied.		0.794
The selection of the beverages is varied.		0.768

).

4.7. Gastronomic Resources: Sustainability and Local Features

With a total of nine items, two factors from the sustainability and local features section were formed: sustainability and local features. Kaiser–Meyer–Olkin’s measure (KMO = 0.864) indicated that the data were suitable for a factor analysis. The two factors together explained 71.47% of the total variance of all variables (

Table 14. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.864
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	3.508	38.981	38.981
2	2.924	32.492	71.473

).

All of the communalities were greater than 0.4, and the Cronbach’s alpha coefficients were above 0.6 (

Table 15. Gastronomic resources: sustainability and local features.

Items	Factor Groups	Communalities	Cronbach’s Alpha
The restaurant uses local ingredients.	Local features	0.680	0.857
The restaurant respects the local cultural/culinary heritage and uses traditional recipes.		0.737
The restaurant employs local workforce.		0.709
The restaurant perfectly fits the local environment.		0.710
The restaurant promotes the ideas and policies of environmental protection.	Sustainability	0.777	0.897
The restaurant is environmentally friendly.		0.800
The restaurant can ensure the sources of the food and organic certification.		0.722
The staff is able to answer questions concerning green food and beverage.		0.677
The restaurant offers organic food.		0.621

).

4.8. Gastronomic Resources: Innovativeness and Creativity

Comprising 14 items in total, 3 factors emerged from the innovativeness and creativity section: staff creative innovativeness, restaurant creative innovativeness, and trends creative innovativeness, which explained 65.38% of the total variance of all variables. Kaiser–Meyer–Olkin’s measure (KMO = 0.889) showed that the data were suitable for a factor analysis (

Table 16. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.889
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	3.878	27.702	27.702
2	3.310	23.643	51.345
3	1.964	14.032	65.376

). Bartlett’s sphericity test was statistically significant at p < 0.05.

All of the communalities exceeded 0.4, and the Cronbach’s alpha coefficients were above 0.6 (

Table 17. Gastronomic resources: innovativeness and creativity.

Items	Factor Groups	Communalities	Cronbach’s Alpha
The restaurant generates new ideas.	Restaurant creative innovativeness	0.717
The restaurant provides an innovative environment that makes it unique.		0.778	0.893
The restaurant is using creative ways to attract customers.		0.762
The restaurant provides a very creative service.		0.736
The sommelier (waiter specialized in wine) is creative.	Staff creative innovativeness	0.611	0.881
The chef interacts with the guests, enquires about their preferences, and makes recommendations and suggestions.		0.621
The sommelier interacts with the guests, enquires about their preferences, and makes recommendations and suggestions.		0.702
The staff’s recognitions and awards create a higher level of quality for the restaurant.		0.544
The restaurant offers current technologies.		0.621
The restaurant offers new flavors.		0.616
The restaurant offers new combinations of food.		0.580
The restaurant does not use menus at all.	Trends creative innovativeness	0.592	0.626
The restaurant is on the leading edge of current trends in menus.		0.648
It is creative that nutritional value (calories) is marked on the menu.		0.625

).

4.9. Gastronomic Resources: Perceived Value

In this section, there is a total of four items. One factor derives from the perceived value section—the perceived value—and explains 66.81% of the variance of all variables. Kaiser–Meyer–Olkin’s measure (KMO = 0.729) showed that it was appropriate to proceed with a factor analysis (

Table 18. Total variance explained and KMO result.

Kaiser–Meyer–Olkin Measure of Sampling Adequacy: 0.729
Rotation Sums of Squared Loadings
Component	Total	% of Var.	Cum. %
1	2.672	66.810	66.810

). Bartlett’s sphericity test was statistically significant at p < 0.05. All of the communalities were greater than 0.4, and the Cronbach’s alpha coefficients were above 0.6, which showed adequate scale reliability (

Table 19. Gastronomic resources: perceived value.

Items	Factor Groups	Communalities	Cronbach’s Alpha
The dishes have a suitable price.	Perceived value	0.578	0.830
I have paid as much as I intended to.		0.569
The prices reflect the restaurant’s image.		0.773
The prices reflect the quality of the food and service in this restaurant.		0.753

).

5. Regression Analysis Results

A regression analysis was conducted to determine whether: (1) the gastronomic destination offer (GDO: core and supporting resources) has an impact on the perceived value of restaurants; and (2) the gastronomic destination competences (GDC: quality, innovativeness, creativity, sustainability, and local features) have an impact on the perceived value of restaurants (

Table 20. Hypotheses H1 and H2 and their sub-hypotheses, summarized.

H1	GDO Has an Impact on the Perceived Value of Restaurants.	Rejected
H1.1	The destination’s core resources have an impact on the perceived value of restaurants situated in this destination.	Rejected
H1.2	The destination’s supporting resources have an impact on the perceived value of restaurants situated in this destination.	Rejected Except for: - Offer - Local features - Reputation
H2	GDCs have an impact on the perceived value of restaurants.	Accepted
H2.1	The quality of upscale restaurant resources has an impact on the perceived value of restaurants.	Accepted
H2.1.1	The tangible upscale restaurant quality has an impact on the perceived value of restaurants.	Accepted Except for: - Facility aesthetics - Ambience
H2.1.2	The intangible upscale service quality has an impact on the perceived value of restaurants.	Accepted Except for: - Ability to adjust - Quality and taste
H2.2	Innovativeness and creativity have an impact on the perceived value of restaurants.	Accepted Except for: - Staff creative innovativeness
H2.3	Sustainability and local features have an impact on the perceived value of restaurants.	Accepted

). Second-order constructs were calculated by averaging the mean values of single items according to the results of the factor analysis. In the regression analysis, the following predominance rule was adopted: if more than 50% of items that showed the impact of the independent variable on the dependent variable had p < 0.05, the hypothesis was accepted. The opposite rule was also adopted: if less than 50% of items showed an impact, the hypothesis was rejected.

Hypothesis H1, which stated that GDO has an impact on the perceived value of restaurants, was rejected. Hypothesis H1.1 was rejected, with the destination core resources showing no impact on the restaurants’ perceived value. The same applied to Hypothesis H1.2, as no impact of a destination’s supporting resources on the restaurants’ perceived value was found, except for the offer, local features, and reputation. Therefore, the overall GDO had no impact on a restaurant’s perceived value; the destination’s core resources had no impact on (gastronomic) tourists’ perceived value regarding the restaurants. The same applied for a destination’s supporting resources, although some items did show a certain impact on the restaurants’ perceived value, such as the tourism offer in a destination, the presence of local businesses, hospitable residents, as well as the destination image.

Hypothesis H2 and its sub-hypotheses were accepted, showing: (1) an impact of (tangible and intangible) the quality of (upscale) restaurant resources on the restaurants’ perceived value, (2) an impact of restaurants’ innovativeness and creativity on the restaurants’ perceived value, and (3) an impact of a restaurants’ sustainability and local features on the restaurants’ perceived value, therefore proving that (4) GDCs have an impact on the perceived value of restaurants.

Below is a presentation of the results for each hypothesis and its sub-hypotheses.

Hypothesis H1.1.

The destination’s core resources have an impact on the perceived value of restaurants situated in this destination.

Based on the findings presented in

Table 21. Model summary ²—core resources and perceived value of restaurants.

Model	R	R2	Std. Error of the Estimate	Durbin–Watson
1	0.137 1	0.019	0.55901	1.743

¹ Constant: entertainment, gastronomy, sports and recreation, culture. ² Dependent variable: perceived value of restaurants.

,

Table 22. ANOVA ¹—core resources and perceived value of restaurants.

Model	Sum of Squares	Mean Square	F	Sig.
1 Regression	1.811	0.453	1.449	0.218 2

¹ Constant: entertainment, gastronomy, sports and recreation, culture. ² Dependent variable: perceived value of restaurants.

and

Table 23. Coefficients ¹—core resources and perceived value of restaurants.

Model	B	Std. Error	Beta	t	Sig.
Constant	4.341	0.256		16.950	0.000
Culture	0.085	0.047	0.124	1.818	0.070
Sports and recreation	−0.034	0.044	−0.050	−0.780	0.436
Gastronomy	0.049	0.053	0.054	0.924	0.356
Entertainment	−0.069	0.041	−0.108	−1.675	0.095

¹ Constant: entertainment, gastronomy, sports and recreation, culture. Dependent variable: perceived value of restaurants.

, we concluded that a destination’s core resources do not have an impact on the perceived value of restaurants. Firstly, the R-squared (R²: the coefficient of determination) revealed that only 1.9% of the total variation in the dependent variable (i.e., perceived value of restaurants) could be explained by the independent variable (i.e., core resources, comprising entertainment, gastronomy, sports and recreation, and culture). Secondly, the R (the coefficient of correlation) also indicated a low degree of correlation, as it should ideally be closer to a value of one. Thirdly, the Durbin–Watson statistics indicated a positive autocorrelation (values were between zero and two), but inside an appropriate range. Furthermore, the regression model did not accurately predict the dependent variable as the significance value of the ANOVA test was higher than 0.05; it should be lower (p < 0.05). Moreover, the beta coefficients revealed that none of the core resources were statistically significant (p > 0.05). Thus, Hypothesis H1.1 was rejected. In summary, the results suggest that the destination’s core resources have no significant impact on guests’ perceived value of restaurants.

Hypothesis H1.2.

The destination’s supporting resources have an impact on the perceived value of restaurants situated in this destination.

According to the results (

Table 24. Model summary ²—supporting resources and perceived value of restaurants.

Model	R	R2	Std. Error of the Estimate	Durbin–Watson
1	0.354 1	0.125	0.53223	1.703

¹ Constant: offer, reputation, accessibility, facilities, transport., local feat., local env. ² Dependent variable: perceived value of restaurants.

,

Table 25. ANOVA ¹—supporting resources and perceived value of restaurants.

Model	Sum of Squares	Mean Square	F	Sig.
1 Regression	11.847	1.692	5.975	0.000 2

¹ Constant: offer, reputation, accessibility, facilities, transport., local feat., local env. ² Dependent variable: perceived value of restaurants.

and

Table 26. Coefficients ¹—supporting resources and perceived value of restaurants.

Model	B	Std. Error	Beta	t	Sig.
Constant	3.137	0.279		10.558	0.000
Facilities	0.047	0.050	0.059	0.937	0.349
Offer	−0.147	0.051	−0.194	−2.877	0.004
Accessibility	0.042	0.057	0.049	0.748	0.455
Local entertainment	0.100	0.059	0.114	1.698	0.091
Transportation	−0.004	0.046	−0.006	−0.087	0.931
Local Features	0.136	0.053	0.162	2.555	0.011
Reputation	0.139	0.049	0.186	2.817	0.005

¹ Constant: offer, reputation, accessibility, facilities, transport., local feat., local env. Dependent variable: perceived value of restaurants.

), a destination’s supporting resources did not have an impact on the restaurants’ perceived value either. R, the coefficient of correlation, indicated a low degree of correlation (R = 0.354). The correlation coefficient, R-squared (R²), showed that only 12.5% of the total variation in the dependent variable (i.e., perceived value) could be explained by the independent variable (i.e., supporting resources such as offer, reputation, accessibility, facilities, transportation, local features, and local environment). Again, the Durbin–Watson statistics indicated a positive autocorrelation; values were between 0 and 2 within the appropriate range between 1.5 and 2.5. The regression model generated a significant prediction of the dependent variable, as indicated by the ANOVA test’s significance value being lower than 0.05 (p < 0.05). According to the beta coefficients, some of the included supporting resources had a statistically significant impact (p < 0.05) on the restaurants’ perceived value. These included the offer, local features and reputation which, however, accounted for less than 50% of the constructs that showed an impact; as a result, hypothesis H1.2 was rejected as well. It can be concluded that none of the destination’s supporting resources had a significant impact on the perceived value of restaurants for (gastronomic) tourists in a destination.

Hypothesis H2.1.

Upscale restaurant resources’ quality has an impact on the perceived value of restaurants.

This hypothesis is further divided into two Hypotheses H2.1.1 and H2.1.2, as quality in our model comprises both tangible upscale restaurant quality and intangible upscale service quality:

Hypothesis H2.1.

The quality of upscale restaurant resources has an impact on the perceived value of restaurants.

Hypothesis H2.1.1.

The tangible upscale restaurant quality has an impact on the perceived value of restaurants.

Hypothesis H2.1.2.

The intangible upscale service quality has an impact on the perceived value of restaurants.

Table 27. Model summary ²—restaurant quality and perceived value of restaurants.

Model	R	R2	Std. Error of the Estimate	Durbin–Watson
1	0.468 1	0.219	0.50076	1.775

¹ Constant: cleanliness, fac. aesthetics, int. and ext. layout, ambience, table settings. ² Dependent variable: perceived value of restaurants.

,

Table 28. ANOVA ¹—restaurant quality and perceived value of restaurants.

Model	Sum of Squares	Mean Square	F	Sig.
1 Regression	20.838	4.168	16.621	0.000 2

¹ Constant: cleanliness, fac. aesthetics, int. and ext. layout, ambience, table settings. ² Dependent variable: perceived value of restaurants.

and

Table 29. Coefficients ¹—restaurant quality and perceived value of restaurants.

Model	B	Std. Error	Beta	t	Sig.
Constant	1.770	0.330		5.359	0.000
Facility aesthetics	−0.028	0.060	−0.031	−0.475	0.635
Ambience	0.070	0.068	0.068	1.030	0.304
Table settings	0.140	0.064	0.148	2.188	0.029
Internal and external layout	0.223	0.059	0.239	3.804	0.000
Cleanliness	0.200	0.077	0.239	2.607	0.010

¹ Constant: cleanliness, fac. aesthetics, int. and ext. layout, ambience, table settings. Dependent variable: perceived value of restaurants.

indicate that the tangible quality of upscale restaurant resources (i.e., restaurant quality) had a significant impact on the restaurants’ perceived value. The R-squared (R²) value showed that 21.9% of the total variation in the dependent variable (i.e., perceived value of restaurants) could be explained by the independent variable (i.e., tangible upscale restaurant quality including cleanliness, facility aesthetics, internal and external layout, ambience, and table settings). Again, the Durbin–Watson statistics showed a positive autocorrelation (values were between zero and two), but still within an appropriate range. The regression model predicted the dependent variable significantly well (the significance value of the ANOVA test was lower than 0.05 (p < 0.05)). According to the beta coefficients, cleanliness, internal and external layout, and table settings had a statistically significant impact on the restaurants’ perceived value (p < 0.05), accounting for more than 50% of statistically significant constructs. Therefore, Hypothesis H2.1.1 was accepted. Interestingly, facility aesthetics (paintings, colors, flowers, and furniture) and ambience (music, temperature, smell, and lightning) did not have a statistically significant impact on the restaurants’ perceived value.

Table 30. Model summary ²—service quality and perceived value of restaurants.

Model	R	R2	Std. Error of the Estimate	Durbin–Watson
1	0.462 1	0.213	0.50057	1.849

¹ Constant: diversity, reliability, quality and taste, ability to adjust. ² Dependent variable: perceived value of restaurants.

,

Table 31. ANOVA ¹—service quality and perceived value of restaurants.

Model	Sum of Squares	Mean Square	F	Sig.
1 Regression	20.374	5.093	20.327	0.000 2

¹ Constant: diversity, reliability, quality and taste, ability to adjust. ² Dependent variable: perceived value of restaurants.

and

Table 32. Coefficients ¹—service quality and perceived value of restaurants.

Model	B	Std. Error	Beta	t	Sig.
Constant	1.486	0.341		4.359	0.000
Reliability	0.212	0.082	0.183	2.598	0.010
Ability to adjust	0.095	0.072	0.089	1.306	0.192
Quality and taste	0.048	0.077	0.042	0.621	0.535
Diversity	0.294	0.076	0.251	3.870	0.000

¹ Constant: diversity, reliability, quality and taste, ability to adjust. Dependent variable: perceived value of restaurants.

indicate that the intangible upscale restaurant resources’ quality (i.e., service quality) had an impact on the restaurants’ perceived value. The R-squared (R²) statistic showed that 21.3% of the total variation in the dependent variable (i.e., perceived value) could be explained by the independent variable (i.e., intangible upscale service quality, including diversity, reliability, quality and taste, and ability to adjust). The Durbin–Watson statistics indicated a positive autocorrelation (values were between zero and two, but again, inside the appropriate range). The regression model yielded a significant prediction of the dependent variable again as the significance value of the ANOVA test was lower than 0.05 (p < 0.05). According to the beta coefficients’ results, diversity of food and reliability of staff had a statistically significant (p < 0.05) impact on restaurants’ perceived value, representing exactly 50% of the statistically significant items. Therefore, Hypothesis H2.1.2 was accepted as well. Interestingly, the staff’s ability to adjust (the staff’s language and cultural competences and restaurant’s support), and the quality and taste of the F&B did not have a statistically significant impact on the restaurants’ perceived value.

H2.2. 

Innovativeness and creativity have an impact on the perceived value of restaurants.

This study introduces creative innovativeness, a concept that captures both creativity and innovativeness, as we did not come across such a concept during the literature review. This term expands the notion of the important restaurant competences that are offered from the restaurant’s side without considering guests as co-creators of value (experiences). Creative innovativeness includes elements such as chefs’ and sommeliers’ creativity, culinary innovation (new food combinations, new flavors), the creative service provided by restaurants, an innovative environment, new ideas, the creative ways used to attract customers, the use of modern technologies, the current trends in menus, and staff recognition and awards.

According to the results presented in

Table 33. Model summary ²—innovativeness and creativity and perceived value of restaurants.

Model	R	R2	Std. Error of the Estimate	Durbin–Watson
1	0.362 1	0.131	0.52846	1.768

¹ Constant: trend, restaurant and staff creative innovativeness. ² Dependent variable: perceived value of restaurants.

,

Table 34. ANOVA ¹—innovativeness and creativity and perceived value of restaurants.

Model	Sum of Squares	Mean Square	F	Sig.
1 Regression	12.457	4.152	14.869	0.000 2

¹ Constant: trend, restaurant and staff creative innovativeness. ² Dependent variable: perceived value of restaurants.

and

Table 35. Coefficients ¹—innovativeness and creativity and perceived value of restaurants.

Model	B	Std. Error	Beta	t	Sig.
Constant	3.089	0.220		14.041	0.000
Trend creative innovativeness	0.144	0.057	0.175	2.537	0.012
Restaurant creative innovativeness	0.219	0.063	0.256	3.476	0.001
Staff creative innovativeness	−0.043	0.035	−0.076	−1.245	0.214

¹ Constant: trend, restaurant and staff creative innovativeness. Dependent variable: perceived value of restaurants.

, innovativeness and creativity had an impact on the perceived value of restaurants.

The R-squared (R²) statistic showed that 13.1% of the total variation in the dependent variable (i.e., perceived value of restaurants) could be explained by the independent variable (i.e., trend creative innovativeness, restaurant creative innovativeness, and staff creative innovativeness). The Durbin–Watson statistics indicated a positive autocorrelation (values were between zero and two, but within the appropriate range). The regression model demonstrated a significant prediction of the dependent variable, as evidenced by the significance value of the ANOVA test being lower than 0.05 (p < 0.05). According to the beta coefficients, trend creative innovativeness and restaurant creative innovativeness had a statistically significant impact (p < 0.05) on the perceived value of restaurants, accounting for over 50% of the statistically significant items. Therefore, Hypothesis H2.2 could be accepted. However, staff creative innovativeness (chef’s and sommelier’s creativity, restaurant offering new flavors and new food combinations, staff recognitions and awards) did not have a statistically significant impact on the restaurants’ perceived value.

H2.3. 

Sustainability and local features have an impact on the perceived value of restaurants.

It can be concluded that sustainability and local features had an impact on the restaurants’ perceived value (

Table 36. Model summary ²—sustainability and local features and perceived value of restaurants.

Model	R	R2	Std. Error of the Estimate	Durbin–Watson
1	0.322 1	0.104	0.53382	1.689

¹ Constant: sustainability, local features. ² Dependent variable: perceived value of restaurants.

,

Table 37. ANOVA ¹—sustainability and local features and perceived value of restaurants.

Model	Sum of Squares	Mean Square	F	Sig.
1 Regression	9.978	4.989	17.508	0.000 2

¹ Constant: sustainability, local features. ² Dependent variable: perceived value of restaurants.

and

Table 38. Coefficients ¹—sustainability and local features and perceived value of restaurants.

Model	B	Std. Error	Beta	t	Sig.
Constant	3.073	0.262		3.510	0.000
Sustainability	0.175	0.050	0.222	2.308	0.001
Local features	0.148	0.064	0.146	3.510	0.022

¹ Constant: sustainability, local features. Dependent variable: perceived value of restaurants.

). The R-squared (R²) statistic showed that 10.4% of the total variation in the dependent variable (i.e., perceived value of restaurants) was explained by the independent variable (i.e., sustainability and local features). The Durbin–Watson statistics indicated a positive autocorrelation (values were between zero and two, but within an appropriate range). The regression model offered a significant prediction of the dependent variable, with the significance value of the ANOVA test being lower than 0.05 (p < 0.05). According to the beta coefficients, sustainability and local features had a statistically significant impact on the perceived value of restaurants (p < 0.05). Therefore, Hypothesis H2.3 was accepted.

6. Discussion

The key contribution of this article is the introduction of the novel GADECOMP model, which was designed to measure the competitiveness of gastronomic destinations. Gastronomy plays a significant role in attracting gastronomic tourists. When combined with other attributes of gastronomic tourism, gastronomy creates the GD’s competitive offer (which, of course, reflects its competences). The interconnectedness of a destination’s competences, including innovativeness, creativity, sustainability, and local features, is crucial for the success and unique positioning of a destination. (Upscale) Gastronomic tourists are sensitive to quality, sustainability, local features, creativity, and innovativeness, which further impact the perceived value of restaurants, thus impacting the perceived value of the destination’s gastronomic resources. The stronger the interconnectedness between the GDC and GDO, the greater the competitive advantage and overall competitiveness of a GD.

A destination can be considered competitive and of high quality when it boasts a critical mass of quality gastronomy providers, becoming synonymous with excellent gastronomy. Such destinations can be referred to as gastronomic destinations (e.g., Tuscany, Catalonia, Bordeaux, etc.). To measure the competitiveness of such destinations, we transferred a selection of competences from the restaurant (i.e., entrepreneurial) level to the destination level by creating the GADECOMP model. In doing so, we view the entire destination as a virtual enterprise, where providers holistically collaborate to achieve competitiveness.

6.1. Theoretical Implications

The previous research summarized in Table 1 introduced various modified versions of the original SERVQUAL model [22] to measure service quality across various industries, sectors, and services. However, none of the previous models contained our holistic approach to quality measurement. We combined competence parameters from the three service quality model versions relating to (1) the restaurant’s physical environment (DINESCAPE [38]), (2) the restaurant’s services (DINESER [23]), and (3) the restaurant’s green practices (GRSERV [21]). To address the limitations of existing quality systems and create a more holistic service quality model, we incorporated what we observed to be crucial competence parameters that were previously lacking: local features and innovativeness and creativity. The dimensions of sustainability and local features lacked a broader perspective, while innovativeness and creativity were not previously included in the modified SERVQUAL models; they were, however, described as crucial in the studies on restaurant innovativeness [74,75].

The novel method that was applied transfers the perceived quality measurement from the entrepreneurial level to the destination level and encompasses selected dimensions from the following three models: (1) Ritchie and Crouch’s conceptual model of destination competitiveness [71], (2) Goffi’s determinants of tourism destination competitiveness: a theoretical model and empirical evidence [79], and (3) Koch’s model of the dimensions of tourism quality in a destination [80], as well as parameters suggested by the author. Here, the approach to gastronomic destination competitiveness measurement was based on quality measurement on the demand side, whereas all previous destination competitiveness models have relied on the supply-side perspective.

To achieve competitiveness, a gastronomic destination’s offer should reflect its competences, namely quality, innovativeness, creativity, sustainability, and local features. The destination’s resources are assessed through the evaluation of gastronomic destination competences, which in turn impact the customers’ perceived value of the destination through the perceived quality of restaurants. Perceived quality, being a prerequisite of competitiveness, allows us to measure gastronomic destination competitiveness through the novel GADECOMP model using consumers’ perception as a subjectively measurable indicator.

Various studies on destination competitiveness can be found in the existing scientific and professional literature; some of them measure destination quality as a prerequisite of competitiveness [60,98,99,102,103,107,192]. However, to the best of our knowledge, there has not yet been an approach to measure destination competitiveness by combining two models, as was attempted in this paper. We merged and upgraded Ritchie and Crouch’s conceptual model of destination competitiveness [71] and Parasuraman et al.’s SERVQUAL model [22]. The main contribution of this article is thus the unique model of destination competitiveness measurement that comprises elements and concepts that were not previously combined in this manner.

6.2. Practical Implications

Upscale gastronomy undoubtedly is an appealing tourism resource for modern and novelty-seeking tourists; therefore, our model can help restaurant managers, owners, and DMOs understand what consumers perceive and value to increase their competitive advantage. We expect this model to serve as a tool for destinations and, even more, for the stakeholders on the supply side (DMOs, owners and managers of restaurants, hotels, and other core and supporting resources, e.g., sports and recreation facilities owners, providers/managers of culture, entertainment, etc.). This model was structured to evaluate the level of gastronomic destination competences (GDCs) based on the consumers’ quality perception. After gathering these data, destinations (and the entire supply side) would thus be able to react to the current market requirements. We also expect this model to serve as basis for further research on the competitiveness of contemporary gastronomic destinations (GDs).

6.3. Limitations

The main research field of this thesis is gastronomy. Within this field, we focused on upscale restaurants. The approach used was multi- and interdisciplinary; we intended to interlink the topic gastronomy with destination competences, quality, innovativeness, creativity, sustainability, and local features, as well as perceived value, as factors of GD competitiveness.

We limited the research to three geographically comparable European GDs in the cross-border regions between Slovenia/Italy and Slovenia/Croatia. The comparison criteria were their geographic location, culture, and GDP. Our limitation was also the upscale destination gastronomy; only the finest restaurants were included into the sample of restaurants, as they are often the main reason/motive for tourists to visit the destination.

Furthermore, the original SERVQUAL and DINESERV questionnaires measure expectations in the first part and perceptions in the second part of the questionnaire. This would allow for a better comparison of the data gathered before and after dining. Due to the selected data collection strategy for the upscale gastronomy, consumers were only assessing their perceptions at the end of the meal.

6.4. Future Research

Each limitation may be subject to new research. The timeless model can be used to compare countries, destinations, and individual gastronomy providers locally and internationally. Future research recommendations include the use of the GADECOMP model to assess the competitiveness of both the destinations and gastronomy providers. In further research, it is possible to use the model separately to assess only the competitiveness of a GD or a restaurant by:

(1)

Testing the model on emerging gastronomic destinations to identify the presence of GDCs, the potential improvements for their success, and their competitiveness;

(2)

Testing the model on gourmet GDs for the international comparison of their excellence and competitiveness;

(3)

Testing the model in upscale city restaurants to identify the presence of GDCs, compare urban to rural environments, and compare their competitiveness;

(4)

Testing the model in new creative and sustainably oriented restaurants that offer edible insects on their menus and/or novel 3D printed food to assess their perceived quality and the perceived value by guests, thus assessing such restaurants’ competitiveness.

7. Conclusions

We have studied the impact of a destination’s resources on the perceived value of its restaurants. Interestingly, we did not find evidence to support the notion that a destination’s gastronomy influences the perceived value of restaurants located in this destination. It is possible that the selected destinations (Slovenia and Croatia) may not yet have the reputation (image) of a gastronomic destination (although the destinations’ image was perceived as high) and are therefore not perceived as such, even if the perceived value of their restaurants is high. These destinations can be regarded as emerging gastronomic destinations. However, we have chosen Italy because it has the image of one of the most renowned GDs in the world on account of its pristine indigenous cuisine. Slovenia, on the other hand, has made a huge step forward in promoting its gastronomy during the last 1.5 decades; it started by issuing the Strategy of Gastronomy Development in 2006, which resulted a decade later, among others, in the nomination of the best female cook in 2017 from Slovenia (Ana Roš) and in the nomination of Slovenia as the European GD of 2021 (in 2018). Moreover, Slovenia received its first Michelin Guide in March 2020. Croatia is an emerging gastronomic tourism destination, and it was included in the Michelin Guide before Slovenia. For decades, tourism has been concentrated on the coastal region; only in the last few years have inland and some non-coastal destinations received more attention from the NTO, and gastronomic tourism has recently enjoyed a considerable emphasis in Croatia’s promotion.

However, a destination’s tourism offer (attractions, leisure activities, and facilities), its reputation (destination’s image, DMO’s success, and the offer of the right value for the tourists’ money), and its local features (hospitability of local residents and the presence of local businesses) did have an impact on the perceived value of restaurants. It is thus important for the destination management to enhance the destination’s appearance, develop a positive local image, foster local businesses (and thus opposing the globalization), and promote respect and hospitality of local residents towards tourists. All of these contribute to a higher perceived value of a destination’s services (such as restaurants). Interestingly, general infrastructure (accessibility, transportation, safety and security, etc.) and tourism facilities had no impact on the perceived value of restaurants. This suggests that gastronomy (restaurants) is such a strong pull factor to a gastronomic destination that gastronomic tourists do not perceive the accompanying infrastructure as crucial enough to affect their perception of the destination’s gastronomy. On the other hand, how much of the destination resources do gastronomic tourists actually experience other than the gastronomy offered in upscale restaurants? The answer is probably none, or very little, especially if they are daily, transit, or domestic tourists. This points to the difficulty of linking the restaurant and its perceived value and destination levels in some resources.

Furthermore, our research explored the impact of GDCs on the perceived value of restaurants. We found that the quality of table settings, internal and external layout, and cleanliness had an impact on the perceived value of restaurants, while the ambience and facility aesthetics did not. Gastronomic tourists prioritized comfort (enough parking space, sufficiently spacious seating arrangement, comfortable layout) over the aesthetics and ambience of the restaurant. The cleanliness of the tableware, dining area, staff, and restrooms scored high as well. The space available to each gastronomic tourist (the table setting) was evaluated as higher than the general restaurant’s appearance.

Moreover, we discovered that the reliability of the staff and the diversity of the menu had an impact on the perceived value of the restaurants, whereas the staff’s ability to adjust and the quality and taste of the F&B did not. Surprisingly, the impact of a varied selection of F&B was positive on the overall value, while the quality and taste of the F&B was not related. Because our research focused on the environment of upscale restaurants, it is likely that the respondents already had high expectations for quality. Therefore, their priority and criteria were centered on diversity. Gastronomic tourists value having a wide selection of choices and do not like to be limited to only a modest F&B selection.

With respect to the competences of staff, it is crucial for gastronomic tourists to receive a reliable, consistent, prompt, and quick service, and it is also important that the staff makes an extra effort to handle their special requests, make them feel special, and quickly improve anything that possibly went wrong. Interestingly, the staff’s language and cultural competences, their sympathetic and calm attitude, and the fact that they seem to be enjoying the restaurant’s support in performing their job did not have an impact on the restaurant’s perceived value. This may also be an indicator that most of the guests of selected upscale restaurants were domestic gastronomic tourists at the moment of the surveying, wherein language and cultural competences were not important (as this is their usual environment). The fact that there was no impact on the perceived value might also be explained by the Herzberg’s motivator hygiene theory [193], where satisfaction depends on what the author calls dissatisfiers (also known as hygiene factors). Only when such dissatisfiers are fulfilled does it make sense to increase guest satisfaction with things known as motivators (satisfiers). Increasing the dissatisfiers does not increase satisfaction, as they are typically considered as standard features of upscale restaurants (such as the quality and taste of the F&B, facility aesthetics, ambience, staff’s reliability, etc.) and are hence expected by gastronomic tourists. As a result, they did not affect their perception.

Among innovativeness and creativity, trend creative innovativeness (menu trends) and restaurant creative innovativeness had an impact on the perceived value of restaurants, which makes them important restaurant competences; meanwhile, staff creative innovativeness did not have any impact. Creative menus are obviously important to gastronomic tourists as they are seen to have a direct impact on the restaurant’s perceived value. A restaurant’s innovative and unique environment (its creative ways of attracting customers, generating new ideas, and providing creative services) has an impact on the perceived value as well. Interestingly, staff creativity and innovativeness (active roles of the sommelier and chef when interacting with the guests, staff’s recognitions and awards, new combinations of food, and the offer of current technologies) do not impact the perceived value of gastronomic tourists. Here again, the results indicate that most of the interviewed upscale restaurant guests likely regard these as standard features.

Furthermore, sustainability and local features are important restaurant competences that contribute to the restaurant’s perceived value. Environmental friendliness (promoting environmental protection, ensuring local food sources and organic certification, staff competence in answering questions concerning green F&B, organic food offer, employment of the local workforce, the fact that the restaurant perfectly fits the local environment, respect of the local cultural/culinary heritage, and the use of traditional recipes and local ingredients) indeed impacts the perceived value of restaurants. Among these features, the following were rated the highest: the restaurant’s fit with the local environment, the restaurant’s respect for the local cultural/culinary heritage (the use of traditional recipes and local ingredients), and the employment of the local workforce. We can conclude that it is highly recommended for restaurants to pursue sustainability practices and integrate local features into their offer. This can make them unique and distinguishable from their competitors and potentially provide a sustainable competitive advantage.