Sustainability of Supply Chains Through Digitalization: A Study on the Romanian Restaurant Industry

Abstract

The paper investigates the role of digitalization in strengthening the sustainability of supply chains in the Romanian restaurant sector. The starting point is the intersection between the pressures for digital transformation and the integration of sustainability principles. Digitalization, through advanced digital solutions, can strengthen traceability, reduce waste, and optimize resources, strengthening responsibility for economic efficiency and the environment. However, the implementation of these solutions in HoReCa remains disproportionate and faces barriers such as lack of digital skills, high costs, and resistance to change. The authors conducted a quantitative research study among restaurant managers in Romania. The research was complemented with two Principal Component Analyses (PCA) and a TwoStep Cluster Analysis. The role of the TwoStep Cluster Analysis was to identify a typology of restaurants according to managerial behaviors related to digitalization from a sustainable perspective. The results showed that digitalization is applied predominantly in inventory management, but less in the relationship with consumers and supply chain, where it would bring considerable benefits for sustainability. The study provides theoretical and practical contributions, highlighting the role digitalization has as a facilitator of sustainability and indicating recommendations for managers and decision-makers regarding professional training and financial support policies dedicated to sustainable digitalization.

1. Introduction

Amid increasing global concern for digital transformation and sustainability, the supply chain has become a main object of multilateral processes of continuous modernization [1]. By digitalizing the supply chain, there is allowed an integration of digital solutions such as blockchain, ERP systems, Internet of Things (IoT), and last but not least, viable real-time data analysis solutions, which can offer significant benefits on traceability, efficiency, and environmental responsibility [2,3]. However, from the point of view of implementing digitalization in the HoReCa industry, the specialized literature highlights divergent perspectives [4]. Some studies highlight important aspects such as the obvious benefits of adopting digital solutions for sustainability and efficiency, while other studies draw attention to challenges such as resistance to change among employees, high costs, and the lack of an appropriate technological infrastructure, especially in emerging markets such as Romania [5,6,7].

Furthermore, numerous studies have highlighted the fact that digital transformation can contribute to operational or logistical sustainability objectives, in particular by minimizing waste, strengthening existing relationships between the social actors involved, and, at the same time, by optimizing processes [8,9].

The restaurant market has begun to play a dynamic role in the agri-food supply chain [10,11]. This dynamic role does not only refer to the final point of delivery, but in principle, it refers to the strategic actor that can influence the process by which suppliers are selected, the adoption of digital solutions and the promotion of responsibility [12]. Consumer pressures related to transparency, the increased pace of adaptation to digital technologies, and the requirements of compliance with legal environmental protection standards have increasingly begun to transform restaurants in the market toward critical points of operational sustainability [13,14,15]. As a result, the HoReCa industry has become an industry more vulnerable to supply disruption risks, sensitive to unpredictable variations in demand and to logistical efficiency challenges [16]. Hence, this can make digitalization an important tool for restaurant performance [17].

In Romania, the level of supply chain digitalization associated with the HoReCa industry varies considerably, and the empirical research already existing on this topic is quite limited [18]. Therefore, the main objective of this study is to investigate how digitalization could contribute to the sustainability of the supply chain in Romanian restaurants, with a certain emphasis on the realities of local markets.

In order to achieve the purpose of the study, a quantitative research study was conducted on a sample of 280 restaurant managers from Romania. In addition to this research, two Principal Component Analyses (PCA) and a TwoStep Cluster Analysis were conducted. The role of the TwoStep Cluster Analysis was to identify a typology of restaurants according to managerial behaviors related to digitalization. Moreover, complementary statistical methods were applied in the research, such as descriptive analysis, contingency tables (crosstab) with the Chi-Square test, and the KMO and Bartlett’s test.

The results of this research highlight the fact that the level of digitalization related to the supply chain in the analyzed restaurants in Romania is at an intermediate point, and in this sense it is stated that digitalization is adopted in operational areas but quite limited in the direct relationship with the customer or in the specific stage of supply. At the same time, it is specified that no statistically significant link was identified between digitalization and sustainability, but the managerial perception tends to recognize the positive potential that technology has in promoting sustainable practices.

Through the results, the study makes a practical contribution to managers in the HoReCa industry, supporting them in making strategic decisions regarding the integration of digital technologies within the restaurant and in the supply chain. Simultaneously, this study provides important information to public authorities interested in promoting sustainable measures in the HoReCa industry, as well as to suppliers or developers of digital technologies. Further, this analysis certainly contributes to a consolidation of the scientific literature regarding the role of digitalization in the restaurant market and its importance for sustainable development.

Based on the results, the authors developed a conceptual model that can classify restaurants according to their level of digitalization. This level of digitalization is also correlated with the sustainability measures adopted.

The authors organized the paper in the following sections: Section 2. Literature Review; Section 3. Research Method; Section 4. Results and Discussion; and the final Section 5. Conclusions, where the limitations of the study are also presented.

2. Literature Review

Sustainable supply chain management is defined as “the management of material, information, and capital flows, as well as cooperation between companies along the chain, considering the objectives of the three dimensions of sustainable development—economic, environmental, and social—that derive from the requirements of customers and stakeholders.” According to Kumar et al. [19], sustainable supply chain management will guide future research, given that more and more chains aim for sustainable development and the implementation of the UN sustainability goals.

To ensure a sustainable supply chain, the literature emphasizes the need to balance the three dimensions of sustainability by introducing practices oriented towards the sustainability of production systems [20,21,22].

In the restaurant industry, sustainability directly depends on how supplier relationships and supply chain flows are managed, and is not limited to the responsible use of resources. Sourcing decisions influence operational costs, product quality, and environmental impact, which positions the supply chain in ensuring the sustainable performance of restaurants [23].

In the context of the evolution towards a sustainable and digitalized economy, the HoReCa industry faces multiple pressures to adopt modern technologies that ensure both operational efficiency and alignment with the objectives of social responsibility and environmental protection [24].

In Romania, where the HoReCa sector has experienced rapid development after 2020, digitalization is no longer merely just a trend, but a necessity for meeting European sustainability requirements and responding to consumers who are increasingly attentive to social and environmental impacts [25]. According to the DESI indicator [26], Romania ranks among the last member states of the European Union in terms of digitalization of companies, including in HoReCa [27].

The supply chain is a system made up of organizations, people, activities, information, and resources involved in the delivery of a product or service from the supplier to the final customer [28]. Supply chain management aims to meet customer needs and achieve high performance within the organization, with the objectives of reducing costs, reducing waste, compressing delivery times, increasing operational flexibility, and avoiding stockouts [29,30,31].

The way the supply chain is organized can have direct consequences on the economic performance and sustainability of restaurants. In this context, digitalization becomes an important and strategic tool for increasing efficiency and traceability [32].

Baltescu et al. [33] highlighted, in a study conducted on 56 restaurants in Romania, that the majority pursue ingredient traceability and prefer local suppliers, not only for quality, but also for sustainability reasons. The use of digital order planning and management systems allows for more accurate demand estimation and, implicitly, the reduction in food waste [17,34].

Digitalization contributes to the sustainability of supply chains through four main mechanisms: increasing transparency and traceability, optimizing resources, reducing waste, and strengthening supplier relationships [35,36]. Technologies such as the Internet of Things (IoT), RFID, blockchain, and cloud solutions allow real-time monitoring of product flows, facilitating rapid interventions to avoid losses and minimize environmental impact [37].

Digital collaboration platforms between producers, distributors, and restaurants provide access to real-time data, facilitating rapid decision-making in situations of chain disruption [38]. This practice is becoming increasingly common in large cities in Romania.

At the same time, the process of digital transformation highlights the difference between restaurants with strong financial and managerial resources and small ones with reduced innovation capacity [39,40,41,42]. These discrepancies can influence both the level of operational efficiency and the ability of restaurants to implement sustainable strategies [43]. The specialized literature highlights that digitalization and sustainability are interdependent processes, but not inherently convergent [44]. Digitalization provides the technological infrastructure necessary for optimizing and efficiently monitoring supply chain flows, while sustainability represents the strategic framework aimed at reducing environmental impact and creating value for all parties involved in the process [45]. In other words, digitalization can support sustainability, but its effects depend on the sub-set through which technologies are integrated and used in practice [46].

Digitalization contributes to sustainability in the restaurant supply chain through several mechanisms [47]. First, digital traceability systems allow for real-time quality control of ingredients and significantly reduces the risk of losses in the supply chain. This is particularly relevant in the food industry, where transparency and food safety are essential aspects [48]. Second, digital solutions for demand forecasting and inventory management support the reduction in food waste, which represents one of the main sustainability challenges for restaurants [49].

At the same time, digital technologies can facilitate strategic collaboration between suppliers and restaurants, working together to strengthen short supply chains and use local ingredients, which reduces the carbon footprint associated with transportation. Therefore, it is clear that digitalization not only optimizes internal processes, but can also maintain more socially and environmentally responsible supply models [50].

However, the literature highlights that digitalization does not automatically guarantee improved sustainability performance. The contribution to sustainability that digital technologies can make depends on factors such as the availability of financial resources, organizational culture, the level of digital competence of staff, and the degree of openness to change [51]. In particular, small and medium-sized restaurants, face considerable difficulties in integrating advanced technologies, either due to cost constraints or limited operational capacity for adaptation [52].

Therefore, the relationship between the two interconnected components, digitalization and sustainability, can be understood as a hypothetical relationship: digitalization provides the necessary tools, and sustainability provides the direction [53]. When there is a well-defined management strategy aimed at using technology to optimize resources, reduce waste, and strengthen responsible partnerships, digitalization produces significant sustainable effects in the restaurant supply chain [54].

Considering this interdependent relationship, the literature highlights the effects that digitalization has on sustainability, through the way technology is integrated into supply chain management and operational processes [55]. Digital technologies that are integrated into the supply chain contribute to improving sustainable performance by streamlining traceability, increasing operational efficiency, and, last but not least, by reducing waste [56]. The use of predictive analytics and real-time monitoring systems allows for better management of inventories based on demand, reducing logistics costs and food losses [57]. Moreover, digital platforms that facilitate ingredient quality control and the identification of problems along the supply chain also contribute greatly to food safety and transparency [58]. Additionally, using digital solutions for effective collaboration with suppliers can support the development of responsible resource consumption and short supply chains, which strengthens the social and ecological dimensions of sustainability [59,60]. However, the impact of digitalization on sustainability depends on the level of integration and the extent to which these solutions are internalized within the operational and decision-making processes of restaurants. This point is also emphasized in recent research, which shows that digital integration produces positive effects only when it is aligned with organizational objectives and adopted strategically [61]. There is also a need for investment readiness, specific skills, and an organizational framework oriented towards continuous improvement to implement digital technologies [62]. If these conditions are not in place, digitalization remains at an early and superficial stage, and this does not generate sustainable transformations that can be measured [63]. Therefore, the link between digitalization and sustainability essentially depends on the ability of organizations to leverage technology strategically, aimed at strengthening supply chain efficiency and reducing environmental impact [64].

Based on the theoretical framework that was presented, the first research hypothesis is formulated:

Hypothesis 1 (H1).

There is an association between the use of digital technologies within the supply chain and the implementation of sustainable measures in restaurants.

Existing literature has highlighted that the adoption of digital technologies in restaurants is essentially influenced by organizational characteristics [65]. These characteristics are the size of the organization, the management structure, the chain membership, and the available resources. Moreover, restaurants that are part of large networks, such as fast-food chains or international franchises, have more developed technological infrastructure, investment capital, and managerial skills that usually allow for the integration of digital solutions into the supply chain [66]. On the other hand, independent, casual, or small restaurants tend to adopt technology to a lesser extent, due to the lack of technological knowledge and investment capital [67]. Therefore, these differences related to the structure are directly reflected in the level of integration of digital technologies [68].

Following the above, the second research hypothesis is reformulated, which concerns the relationship between the level of adoption of digital technologies and the type of restaurant:

Hypothesis 2 (H2).

The type of restaurant influences the adoption of digital technologies in the supply chain.

3. Research Method

In this study, quantitative research, which has an exploratory nature, was conducted. Figure 1 illustrates the research design. The research method adopted in this study is similar to that used by Türkeș, Bănacu, and Stoenică [69], who used a questionnaire and quantitative analysis to demonstrate the impact of supply chain sustainability and the performance of Romanian companies.

The aim of the present research is to identify various aspects regarding the digitalization of the Romanian restaurant supply chain, with a focus on the sustainability component.

In order to achieve the purpose of the study, the following objectives were established:

• O1—Identifying the level of digitalization in the supply chain of restaurants in Romania;
• O2—Determining the relationship between the level of digitalization and the concern for sustainability;
• O3—Identifying the main barriers that prevent digitalization in the supply chain of restaurants in Romania;
• O4—Identifying the main factors that influence the adoption of digitalization in the supply chain.

3.1. Data Collection and Study Sample

The research instrument that formed the basis of the quantitative marketing research was the questionnaire. The questionnaire was first tested on 10 respondents to avoid possible ambiguities. After the pre-testing stage, the questionnaire in its final form was distributed to the final respondents.

Data collection was carried out using the Computer Assisted Web Interviewing (CAWI) method. This technique is widely used and allows for the administration of questionnaires in an electronic format, where respondents can complete the information directly on the web page [70]. This approach reflected a more diverse sample and presented a certain flexibility in the answers provided [71].

Data were collected from respondents during the period of March—April 2025, and within this interval, they were invited to complete the questionnaire. The sampling method that was chosen by the authors was the non-probabilistic one, being considered the most appropriate for this study. The questionnaire was sent by e-mail to 530 restaurant managers, inviting them to complete it through accessing a link. Finally, after eliminating missing cases, a sample of 280 restaurant managers from Romania was obtained. The sample structure showing the type of restaurant, size, and duration of activity in the industry is available in

Table 1. Sample structure.

Type of Restaurant	Frequency	Percent	Valid Percent	Cumulative Percent
Fast-Food Restaurant	112	39.9	40.0	40.0
Casual Restaurant	56	19.9	20.0	60.0
Premium Restaurant	56	19.9	20.0	80.0
Cafe	56	19.9	20.0	100.0
Total	280	99.6	100.0
Restaurant Size	Frequency	Percent	Valid Percent	Cumulative Percent
1–5 employees	56	19.9	20.0	20.0
6–15 employees	168	59.8	60.0	80.0
Over 15 employees	56	19.9	20.0	100.0
Total	280	99.6	100.0
Activity Duration in The Restaurant Industry	Frequency	Percent	Valid Percent	Cumulative Percent
1–5 years	56	19.9	20.0	20.0
6–10 years	168	59.8	60.0	80.0
Over 10 years	56	19.9	20.0	100.0
Total	280	99.6	100.0

Source: Data from own research.

.

The sample consisted of 280 respondents, but in the case of certain filter questions applied in the questionnaire, the number of cases analyzed varied. Therefore, it is specified that in some analyses the number of respondents is smaller than the initial sample.

3.2. Data Analysis Techniques

For a deeper analysis, the quantitative research was completed by two Principal Component Analyses (PCA) and a TwoStep Cluster Analysis. The Principal Component Analysis allows a reduction in the number of variables through the identification of factors that group the variables initially analyzed according to the correlations between them [72]. This statistical method is often used to highlight certain structures that are usually hidden in a larger data set and this greatly simplifies their interpretation, without dilating on important information [73].

In the context of this research, through the first Principal Component Analysis (PCA), the dimensions that influence the adoption of digital solutions within the supply chain were identified. Therefore, in this case, managers’ perceptions of the associated benefits and decision-making factors were analyzed. The purpose of this approach was to understand how these factors group and how they can contribute to the decision-making process regarding restaurant digitalization.

The second Principal Component Analysis (PCA) was used to highlight fundamental dimensions of the barriers perceived by the study respondents in the restaurant digitalization process. In this regard, a new set of information was analyzed. Therefore, the purpose of this approach was to pursue a better understanding of how the responding managers group and perceive certain obstacles they encountered.

The research also applied complementary statistical methods, such as descriptive analysis, contingency tables (crosstab) with the Chi-Square test, and the KMO and Bartlett’s test to verify the validity of the PCA.

Simultaneously, a cluster analysis (TwoStep Cluster Analysis) was used. This method aimed to identify restaurant typologies based on the level of digitalization. This analysis was evaluated using the Silhouette measure. Last but not least, two synthetic indicators of the level of digitalization were constructed: the first synthetic indicator was based on the areas of application of digital solutions and the second was based on the number of digital solutions used within the supply chain.

To test Hypothesis 1 (H1) and Hypothesis 2 (H2), the Chi-Square test is used. The results show that both hypotheses were rejected (H1: ${\mathsf{\chi }}_{calculated}^2$ = 0.083 < ${\mathsf{\chi }}_{0.05;1}^2$ = 3.841; H2: ${\mathsf{\chi }}_{calculated}^2$ = 0.085 < ${\mathsf{\chi }}_{0.05;3}^2$ = 7.815).

4. Results and Discussion

The obtained results were grouped according to the objectives established within the research. It is mentioned that this approach allowed for a clearer and more coherent analysis of the data, in relation to the research directions pursued by the authors.

O1. 

Identifying the level of digitalization in the supply chain of restaurants in Romania.

The results indicate a predominant application of digital solutions in essential operational processes (80%). Therefore, it is found that inventory management is most frequently digitalized (71%), immediately followed by electronic payments and invoicing, with a percentage of 67.9%, and the relationship with suppliers, with a percentage of 47.3%. Paradoxically, from the point of view of the application of digital solutions, areas such as online deliveries through platforms (21.4%) and marketing and customer loyalty (15.2%), were less addressed by the responding managers.

The distribution of answers shows that 75% of respondents do not use digital technologies in supply management.

The results show that half of the respondents mentioned that they use artificial intelligence to optimize orders within the restaurant. This suggests an increased interest in anticipatory process efficiency and the use of new technologies that have appeared on the market. Also mentioned by the responding managers were inventory management (30.4%) and traceability systems (26.8%), reflecting a concern for the control and transparency of the supply chain. These results also confirm the observations of Alt [66], which highlights the fact that digitalization in restaurants mainly varies in increasing operational transparency and optimizing internal processes.

Naturally, the duration (age) of using digital technologies in procurement was identified, and the results show that most of the responding managers stated that they have been using them for over 3 years (78.6%). At the same time, only 21.4% of the responding managers indicated a duration under 3 years old. Last but not least, it is found that all the responding managers who use digital solutions in the restaurant supply state that they use them daily. This obtained result indicates an advanced integration of digital solutions in the operational processes of the analyzed restaurants. In this sense, it can be confirmed that digitalization is essentially a permanent and essential tool in daily activity.

The benefits of digitalization in supply mentioned by the responding managers within the restaurant supply process are improved traceability and food safety (26.5%) stock optimization and waste reduction (23.1%). This highlights that the digitalization process is associated with much better control over product quality and safety, not just operational efficiency. Other benefits specified by the responding managers are the following: reduction in the time required to place orders and better collaboration with suppliers, in proportions of 10.3%. The results obtained align with the conclusions of An and Galera-Zarco [74], who specify that digitalization aims to increase transparency in the supply chain and improve operational efficiency by optimizing logistical processes and reducing waste.

Based on the results obtained in the analyses carried out for the study, the level of digitalization of the restaurants included in the research was highlighted depending on the type of restaurant. To make this possible, the answers regarding the areas of application of digital solutions within the analyzed restaurants were processed. Therefore, following the process, a synthetic indicator of the level of digitalization was defined, which was then used in a comparative analysis of the restaurants. The main purpose of this approach was to evaluate the degree of digitalization of the restaurant from a technological perspective in the different operational processes. In other words, the more a restaurant among those analyzed uses digital solutions in more areas of activity, the more strongly digitalized it is. Furthermore, the new variable entitled “level of digitalization based on areas of application” was analyzed in direct relation to the type of restaurant managed (

Table 2. The relation between the level of digitalization based on areas of application and the type of restaurant managed.

The Restaurants’ Level of Digitalization Based on Application Areas	Type of Restaurant
	Fast-Food	Casual Restaurant	Premium Restaurant	Cafe	Total
1—Very low level	47.7%	15.9%	18.2%	18.2%	100.0%
2—Low level	39.6%	20.9%	19.8%	19.8%	100.0%
3—Moderate level	32.4%	23.5%	26.5%	17.6%	100.0%
4—High level	28.6%	14.3%	14.3%	42.9%	100.0%
5—Very high level	39.6%	20.8%	18.8%	20.8%	100.0%
Total	39.7%	20.1%	20.1%	20.1%	100.0%

Source: Data from own research.

).

It is found that, in the categories with very low and low digitalization, fast-food restaurants predominate, where they represent 47.7% of the total establishments with very low digitalization, and 39.6% of those with low digitalization. The distribution at each level of the other types of restaurants is quite balanced in these two categories, which may result in a general trend towards reduced digitalization, regardless of the type of establishment. At the same time, it is observed that as the level of digitalization increases, the proportions begin to become much more dispersed between the types of restaurants analyzed, but the percentage values become lower in general. This suggests a much more limited presence of restaurants in the categories with high or very high digitalization. Moreover, it is highlighted that certain types of restaurants, such as cafes (42.9% at high level) and fast-food restaurants (39.6% at very high level), are also represented in the categories with a high level of digitalization.

Following the outlined results, the analysis was deepened and aimed at the existence of a possible association between the use of digital technologies for supply management and the type of restaurant managed (

Table 3. The relation between restaurant type and the use of digital technologies for supply management.

Does Your Restaurant Use Digital Technologies for Supply Management?	Type of Restaurant
	Fast-Food	Casual Restaurant	Premium Restaurant	Cafe	Total
Yes	39.3%	19.6%	19.6%	21.4%	100.0%
No	39.9%	20.2%	20.2%	19.6%	100.0%
Total	39.7%	20.1%	20.1%	20.1%	100.0%

Source: Data from own research.

).

From the data obtained, it is evident that the use of digital technologies for supply management is quite balanced among the types of restaurants managed in the sample. Therefore, 39.7% of fast-food restaurants use such digital technologies, with a similar percentage among premium, casual, and cafe restaurants. Furthermore, to verify Hypothesis 2 (restaurant type influences the adoption of digital technologies in the supply chain) the Chi-Square test was applied (

Table 4. The Chi-Square test on the relation between the restaurant type and the use of digital technologies for supply chain.

	Chi-Square Tests
	Value	df	Asymptotic Significance (2-Sided)
Pearson Chi-Square	0.085 a	3	0.994
Likelihood Ratio	0.084	3	0.994
Linear-by-Linear Association	0.054	1	0.817
N of Valid Cases	224

^a Zero cells (0.0%) have expected count less than 5. The minimum expected count is 11.25.

).

According to the data obtained, it is found that the value of ${\mathsf{\chi }}_{calculated}^2$ = 0.085 is lower than the critical value ${\mathsf{\chi }}_{0.05;3}^2$ = 7.815, and the significance level p-value = 0.994 > 0.05. Therefore, it is found that there is no statistically significant association between the use of digital technologies in the supply process and the type of restaurant managed, so H2 is rejected. Finally, the type of restaurant (fast-food, premium, casual, and cafe) does not influence the probability of using digital solutions in supply management, at the level of the sample that was analyzed.

Continuing the analysis, the level of digitalization of the restaurants included in the sample was assessed, this time, depending on the digital solutions that are used in the supply chain, but in direct relation to the type of restaurant managed. It is mentioned that the question included a list of multiple options. Therefore, each option corresponded to a specific technology (inventory management platforms, product traceability systems, ERP, mobile applications for procurement, and artificial intelligence for order optimization). As a result, a synthetic indicator of the level of digitalization was built according to the digital solutions used in the supply. The indicator directly highlighted the number of digital solutions used in the supply chain by each type of restaurant that was analyzed. Then, this synthetic indicator was transformed into an ordinal variable organized into five levels of digitalization, where 1 signifies a very low level of digitalization and 5 signifies a very high level of digitalization. Thus, if the restaurant uses fewer digital solutions in the supply chain, it is less digitalized, and if it uses more digital solutions in the supply chain, it is more digitalized. In order to complete the analysis, the distribution of the level of digitalization according to the type of restaurant managed was evaluated (

Table 5. The level of digitalization of restaurants depending on the technologies used in supply and the type of restaurant managed.

The Level of Digitalization of Restaurants According to the Technologies Used in Supply	Type of Restaurant
	Fast-Food	Casual Restaurant	Premium Restaurant	Cafe	Total
2—Low Level	42.5%	17.5%	22.5%	17.5%	100.0%
3—Moderate Level	42.9%	28.6%	14.3%	14.3%	100.0%
4—High Level	22.2%	22.2%	22.2%	33.3%	100.0%
Total	39.3%	19.6%	21.4%	19.6%	100.0%

Source: Data from own research.

). The purpose of this approach was to identify a possible association between the level of restaurant digitalization depending on the number of digital solutions used in the supply chain and the type of restaurant managed.

In Table 5 it is observed that restaurants with a low level of digitalization are the best represented, being usually associated with fast-food establishments (42.5%). The following types of restaurants have a lower level of digitalization as well: premium (22.5%) and cafe (17.5%). The moderate level of digitalization is found in a higher proportion in casual restaurants (28.6%). It is also noted that the high level of digitalization is mostly found in cafes (33.3%). A complete absence of the analyzed restaurants can be noted in the extreme categories (level 1 and level 5). This distribution (Table 5) may suggest that the analyzed restaurants are still in the early stages of digitalization of supply processes.

O2. 

Determining the relationship between the level of digitalization and concern for sustainability.

Managers from 224 analyzed units (80%) declared that they implement sustainable measures in the supply chain and only managers from 56 restaurants (20%) out of the total of 280 declared that they do not implement such measures in the supply chain.

Next, the responding managers had the possibility to select multiple options regarding the sustainable strategies they apply in the supply process. The strategy entitled collaboration with suppliers that use biodegradable packaging was the most mentioned by the responding managers (70.5%). This was immediately followed by the purchase of certified organic/bio products (54.9%). It is noteworthy that the responding managers mentioned that they source from local suppliers to reduce their carbon footprint (33.9%), and 29.9% stated that they use digital technologies to optimize orders and reduce waste. These results may indicate an openness to concrete and visible digital solutions from a sustainable point of view (organic products, eco-friendly packaging).

Managers consider the supply chain (and its digitalization) to play an important role in ensuring the long-term sustainability of a restaurant, 75% of them indicated that a sustainable supply chain is very important, while 25% mentioned that it is important.

Furthermore, to investigate whether there is a certain relationship between the level of digitalization and the concern for sustainable aspects within the supply chain, a bivariate analysis was performed to identify the extent to which digitalization is associated with the environmentally responsible approach in the activity of the analyzed restaurants.

Following the results obtained, it is found that 79.9% of managers mentioned that they implement sustainable measures, and 20.1% stated that they do not. It is found that 80.4% of the restaurants analyzed do not use digital technologies in supply management, but still implement sustainable measures within the process. It is also observed that 78.6% of the managers of the responding restaurants stated that they use digital technologies for supply management and that they also implement sustainable solutions. Therefore, following the distribution of the answers, the question arises whether there is a statistically significant association between the use of digital technologies in the supply chain and the implementation of sustainable measures within this process (

Table 6. Contingency table on the relation between digitalization and sustainability applied in the supply chain.

Does Your Restaurant Use Digital Technologies for Supply Management?	Does Your Restaurant Implement Sustainable Measures in Its Supply Chain?
	No	Yes	Total
Yes	19.6%	80.4%	100.0%
No	21.4%	78.6%	100.0%
Total	20.1%	79.9%	100.0%

Source: Data from own research.

).

In order to verify Hypothesis 1 (there is a statistically significant association between the use of digital technologies and the implementation of sustainable measures in the supply chain) the Chi-Square test was applied (

Table 7. The Chi-Square test results for the association between the use of digital technologies and the implementation of sustainable measures in the supply chain.

	Chi-Square Tests
	Value	df	Asymptotic Significance (2-Sided)	Exact Sig. (2-Sided)	Exact Sig. (1-Sided)
Pearson Chi-Square	0.083 a	1	0.773
Continuity Correction b	0.009	1	0.923
Likelihood Ratio	0.083	1	0.774		0.454
Fisher’s Exact Test				0.848
Linear-by-Linear Association	0.083	1	0.773
N of Valid Cases	224

^a Zero cells (0.0%) have expected count less than 5. The minimum expected count is 11.25. ^b Computed only for a 2 × 2 table.

). The results obtained indicated an ${\mathsf{\chi }}_{calculated}^2$ = 0.083 (df = 1), with a significance level of p-value = 0.773. Given that the p-value > 0.05, there is no statistically significant association between the two variables analyzed, and therefore H1 is rejected. Although these results do not indicate a significant relationship between sustainability and digitalization, Zaid et al. [75] showed that this connection becomes relevant only when digitalization is accompanied by efficient information exchange and responsiveness within the supply chain.

Managers believe that the supply chain plays an important role in ensuring the long-term sustainability of a restaurant, especially its digitalization. Thus, 75% of the managers interviewed stated that they have implemented sustainability measures in their restaurant through digital technologies.

The responding restaurant managers were asked, through a multiple-choice question, what types of sustainable measures they had implemented through the use of digital technologies. In this regard, the answers highlighted a diversity of practices. The most frequently adopted practice is the implementation of digital solutions to optimize transportation and reduce CO₂ emissions (74.4%), when it comes to sustainable measures implemented through digital technologies. The responding restaurant managers also mentioned in proportions of 63.7% the use of monitoring and analysis systems for resource consumption, and in proportions of 51.8% and 51.2%, the use of digital platforms for sourcing from local suppliers and digital inventory management to reduce food waste. To a lesser extent, digitalization of menus is implemented to reduce paper consumption (35.1%). Thus, it is mentioned that the results may indicate a trend of integrating digital technologies into the sustainable strategies of the analyzed restaurants.

It is found that the most frequently mentioned benefit in the study responses was increased energy efficiency and resource saving (61.9%). This benefit is immediately followed by optimizing supply and reducing product surplus (43.5%) and reducing operational costs (42.9%). Other benefits mentioned by respondents to the study are creating relationships with sustainable suppliers (36.9%) and reducing food waste (25.6%). It stands out that the least transparent benefit was increased transparency within the supply chain, as it was mentioned by only 13.7% of respondents. The results obtained may indicate that digital technologies are seen as a means of streamlining and reducing resources rather than a vector based on transparency or extended collaboration within the supply chain.

O3. 

Identifying the main barriers that hinder digitalization in the restaurant supply chain in Romania.

The analysis of the data allowed the classification of managers into four categories. Therefore, 35 managers fall into the first category of those who do not use digital solutions at all in the restaurant. Thus, the most common barrier identified was the difficulty of integration with existing systems (60%) and 40% mentioned that they do not consider digitalization necessary, and this may suggest a rather low perception of its benefits. Reasons that were mentioned by the responding managers include: high implementation costs (20%), lack of digital skills of staff (20%), and, last but not least, resistance to change from employees.

The second category includes 224 managers, who use digital solutions in several operational processes of the restaurant but had different challenges in the digitalization process. Hence, the biggest challenge for the responding managers was employee resistance to change (48.7%). This challenge is immediately followed by the high costs of software (41.5%), lack of training of the employed staff (37.9%), integration with current digital systems (32.1%), and technical problems that are frequent (21%). These details are very important, because they actually reflect certain financial and educational barriers.

The third category includes 56 managers who use digital solutions only within the supply chain but have difficulties with implementation. Thus, 50% mentioned the lack of training of personnel to use digital systems, the lack of compatibility between systems (37.5%), and the reluctance of suppliers to adopt certain digital solutions (28.6%). Also, 25% mentioned the high cost of implementation and maintenance, and 26.1% mentioned the difficulties of integration with existing management systems (ERP, CRM).

The fourth category includes 168 managers who use digital solutions for sustainable purposes. It is noteworthy that 34.5% of respondents assessed the process of digitization for sustainable purposes as very difficult and 32.7% stated that the process was moderately difficult.

O4. 

Identifying the main factors influencing the adoption of digitalization in the supply chain.

In order to highlight the main factors that can influence the adoption of digital solutions in the supply chain, items related to decision-makers and perceived benefits were considered. It is noted that this approach is justified, as these items are complementary. Decision-makers target important aspects such as costs, ease of use, market, or regulatory pressure, and perceived benefits include reducing food waste, improving the relationship with suppliers, and increasing product transparency and traceability. In order to better understand the main dimensions that influence the adoption of digital technologies in the supply chain, the answers provided to the two categories of items were analyzed.

Table 8. Descriptive statistics on factors influencing the adoption of digital technologies in the supply chain.

	Descriptive Statistics
	Mean	Std. Deviation	Analysis N
The cost of technology	4.2000	0.74967	280
Ease of use	4.0000	0.63359	280
Market or regulatory pressure	3.4714	0.69244	280
Reducing food waste	3.5536	1.09609	280
Improving the relationship with suppliers	3.0893	1.01735	280
Increasing product transparency and traceability	4.0000	0.63359	280

Source: Data from own research.

shows the descriptive statistics obtained for the items that assess the perception of the managers responding to the study regarding the importance of factors in adopting digital solutions within the supply chain. It is important to note that the level of importance of the factors was measured on a 5-point Likert scale, where 1 means not at all important and 5 means very important. Following the results obtained, it is clear that the most important factors perceived by the respondents are the following: the cost of technology (M = 4.2), ease of use (M = 4), and increased transparency and traceability of products (M = 4). Factors with a lower impact, but still perceived as important, are the following: reducing food waste (M = 3.55), pressure from the market or regulations (M = 3.47), and improving the relationship with suppliers (M = 3.08).

Furthermore, after identifying the factors that can influence the use of digital technologies within the supply chain, a Principal Component Analysis (PCA) was conducted in order to investigate the latent structure of these factors and to highlight the correlations between them.

In

Table 9. KMO and Bartlett’s tests on factors influencing the adoption of digital technologies in the supply chain.

KMO and Bartlett’s Test
Kaiser–Meyer–Olkin Measure of Sampling Adequacy		0.541
Bartlett’s Test of Sphericity	Approx. Chi-Square	541.693
	df	15
	Sig.	0.000

Source: Data from own research.

it is observed that the KMO test provided a value equal to 0.541, indicating a medium level of adequacy. It is also observed that the Bartlett test indicated χ²(15) = 541.693, p-value < 0.05), so the results are statistically significant and Principal Component Analysis (PCA) can be performed.

In

Table 10. Total variance explained for factors influencing the adoption of digital technologies in the supply chain.

Total Variance Explained
Component	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	2.337	38.948	38.948	2.337	38.948	38.948	2.334	38.894	38.894
2	1.335	22.250	61.198	1.335	22.250	61.198	1.338	22.304	61.198
3	0.968	16.136	77.333
4	0.735	12.258	89.592
5	0.497	8.286	97.877
6	0.127	2.123	100.000

Extraction Method: Principal Component Analysis.

it is observed that after applying the principal components analysis, two components were retained out of the ten analyzed. Therefore, the first component explains 38.94% of the total variance and the second component that was retained explains 22.25% of the total variance. It can be noted that both components explain 61.19% of the total variance.

After the analysis of the principal components was carried out (

Table 11. The Rotated Component Matrix regarding the factors influencing the adoption of digital technologies in the supply chain.

Rotated Component Matrix a
	Component
	1	2
The cost of technology	0.886	−0.063
Ease of use	0.722	0.343
Market or regulatory pressure	0.189	0.747
Reducing food waste	0.403	−0.553
Improving the relationship with suppliers	−0.026	0.570
Increasing product transparency and traceability	0.911	−0.167

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. ^a Rotation converged in three iterations.

), two clear directions were identified in the perception of the factors that can influence the decision of the responding managers to integrate digitalization in the restaurant supply chain. Therefore, it can be observed that the following variables contribute to the first identified component: Technology cost (0.886), Ease of use (0.722), and Increasing product transparency and traceability (0.911). These obtained results highlight a concern related to the accessibility, efficiency, and value of digital solutions from an economic and functional point of view. In this sense, the first identified component can be called “Internal factors of efficiency and technological transparency”.

In the second identified component, the following variables predominate: Market or regulatory pressure (0.747) and Improving the relationship with suppliers (0.570). In this sense, it can be seen that these variables express external and relational influences and indicate a market evolution in accordance with the collaborations of social actors in the industry. Finally, the second component can be called “External pressure factors and collaboration in the supply chain”.

Therefore, two clear directions can be discussed. First, we discuss a direction that is more directed towards technological characteristics and internal perceptions of the entire digitalization process, and secondly, we discuss a direction directed towards the restaurant’s relations with the business environment.

The following data was obtained: 65.5% of the responding managers stated they are actively analyzing new solutions to expand the use of various digital solutions in the direction of restaurant sustainability. It is observed that there is a fairly high inclination of restaurant managers towards integrating digitalization for sustainable purposes.

Based on the results obtained, the authors observed that the responding managers encountered difficulties in the process of digitalizing the restaurant supply chain. To better understand the nature of the difficulties, all managers in the sample were asked to evaluate a series of statements that actually represent barriers to the implementation of digital solutions in the supply chain. Considering the need to identify common patterns and the complexity of the responses, a Principal Component Analysis (PCA) was conducted. The purpose of this analysis was to highlight fundamental dimensions of the barriers perceived by the study respondents in the restaurant digitalization process.

Following the results obtained regarding the perceived barriers to adopting digital solutions in the supply chain, it was highlighted that “Lack of customized technological solutions for the restaurant industry” was identified as an important barrier in the perception of the respondents, with an average of 4.20 points on a scale from 1 to 5 (

Table 12. Perceived barriers to adopting digital technologies in procurement.

	Descriptive Statistics
	Mean	Std. Deviation	Analysis N
Lack of digital skills of staff	3.8000	1.60286	280
Difficulties in integrating digital technologies with existing systems	3.6000	0.49078	280
Employee resistance to change	3.0321	1.06207	280
High initial investments for implementation	3.5036	0.99820	280
Lack of customized technological solutions for the restaurant industry	4.2000	0.74967	280

Source: Data from own research.

). Other important barriers perceived by the responding managers are “Lack of digital skills of the staff” (M = 3.80), “Difficulties in integrating digital technologies with existing systems” (M = 3.60), and “High initial investments for implementation” which recorded an average of 3.50 points.

In

Table 13. KMO and Bartlett’s tests for principal components analysis regarding perceived barriers to the adoption of digital technologies.

KMO and Bartlett’s Test
Kaiser–Meyer–Olkin Measure of Sampling Adequacy		0.565
Bartlett’s Test of Sphericity	Approx. Chi-Square	383.775
	df	10
	Sig.	0.000

Source: Data from own research.

it can be seen that the value of KMO is 0.565. From this it can be concluded that it has moderate adequacy, but it is acceptable for factor analysis. Also, the Bartlett test was statistically significant for (χ²(10) = 383.775, p-value < 0.05), so the Principal Component Analysis (PCA) can be performed.

It is found that, following the analysis, two principal components were retained out of the five analyzed. The first component explains 44.12% of the total variance and the second component explains 21.63% of the total variance. It is noted that both components explain 65.76% of the total variance (

Table 14. Total variance explained for perceived barriers to adopting digital technologies.

Total Variance Explained
Component	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	2.206	44.127	44.127	2.206	44.127	44.127	1.945	38.904	38.904
2	1.082	21.637	65.764	1.082	21.637	65.764	1.343	26.860	65.764
3	0.988	19.760	85.524
4	0.520	10.409	95.933
5	0.203	4.067	100.000

Extraction Method: Principal Component Analysis.

).

In

Table 15. Rotated Component Matrix of perceived barriers to adopting digital technologies.

Rotated Component Matrix a
	Component
	1	2
Lack of digital skills of staff	0.333	0.762
Difficulties in integrating digital technologies with existing systems	0.876	0.245
Employee resistance to change	0.402	0.558
High initial investments for implementation	−0.351	0.625
Lack of customized technological solutions for the restaurant industry	0.885	0.001

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. ^a Rotation converged in three iterations.

it can be seen that the principal components analysis highlighted two main components in the perception of barriers to the adoption of digital technologies within the supply chain. Therefore, the first component is made up of the following variables: Difficulties in integrating digital technologies with existing systems (0.876) and Lack of customized technological solutions for the restaurant industry (0.885). This identification may suggest a structural problem regarding the compatibility of digital solutions that are newer in the industry and the first component can be called “Lack of adapted solutions and technological limitations”.

It can also be seen that the following variables contribute to the second component: Lack of digital skills of staff (0.762), Employee resistance to change (0.558), and High initial investments for implementation (0.625). In this case, it can be said that these variables reflect more human barriers, but also internal financial barriers. They also suggest a certain resistance on the part of the organization, while also indicating a lack of training of the staff employed to adapt to new technologies. The second component can be called “Internal reserves and organizational barriers”. It is important to state that these results indicate different directions in the perception of barriers. Meaning that, one component is closely related to external technological adaptability, while another component is more related to the internal preparation and openness of the restaurant actors towards change.

Furthermore, in order to deepen the analysis, a typology of restaurants was identified according to the level of digitalization applied to the supply chain and organizational features. To identify the level of digitalization applied to the supply chain, a synthetic indicator was built based on the responses regarding the digital sustainable measures implemented. This indicator was based on options such as digital inventory management to reduce food waste, the use of platforms for local suppliers, solutions for optimizing transportation and reducing CO₂ emissions, resource consumption monitoring systems, as well as the digitalization of menus. Therefore, this synthetic indicator highlighted a restaurant’s capacity to actively integrate digital technologies to support environmental and restaurant sustainability and ultimately operational efficiency.

Based on the synthetic indicator that was mentioned and based on three other variables (type of restaurant and its size, expressed in number of employees and length of service in the industry), the TwoStep Cluster segmentation algorithm was used. Through this approach, the study authors created a typology of restaurants and laid a foundation for the analysis of managerial behaviors related to the digitalization of restaurant supply chain processes.

In Figure 2 it is observed that the algorithm automatically identified five clusters, and the criterion for selecting the ideal number of groups was the Bayesian indicator (BIC). It is noted that this approach allowed for a relevant, and also rigorous, segmentation of restaurants. The approach also provided a certain basis for the differentiated analysis of managerial behaviors that are related to the introduction of digital solutions in the supply chain, with an emphasis on the sustainability component.

In Figure 3, a Silhouette value of over 0.5 can be observed. This indicates a satisfactory level of internal cohesion, but also of separation between the clusters created. It is important to state that in the specialized literature, if the Silhouette value is between 0.5 and 0.7, the structure is considered consistent [76], which shows that the respondents were grouped in a fairly coherent way within each determined cluster, and the differences between the groups formed are clear enough to support a different interpretation of them. Therefore, the value supports the validity of the segmentation model and suggests that the typologies determined following the analysis can be used to describe the differences between the analyzed restaurants in terms of strictly the level of digitalization they have and the organizational characteristics.

Following the TwoStep Cluster Analysis, five different clusters of restaurants were determined. It is stated that these were classified according to size, experience they have in the industry, type of restaurant, and the digital sustainable measures implemented. It was identified that all clusters have a moderate level of digitalization, as the averages obtained are between 2.97 and 3.35 points, on a scale from 1 to 5. This finding highlights quite well the need for relevant measures and policies, which would accelerate a direction from the moderate level of sustainable digitalization to the advanced level (

Table 16. Organizational characteristics and level of digitalization of the supply chain based on sustainable measures for each identified cluster.

Cluster	Type of Restaurant	Size of Restaurant	Industry Experience	Digitalization Level (Based on Sustainable Measures)
1	Cafe (100.0%)	1–5 employees	1–5 years (100.0%)	Mean =2.97	Moderate level of digitalization
2	Premium Restaurant (100.0%)	6–15 employees	Over 10 years	Mean =3.35	Moderate level of digitalization
3	Fast-food (100.0%)	Over 15 employees	6–10 years (100.0%)	Mean =3.26	Moderate level of digitalization
4	Fast-food (100.0%)	6–15 employees	6–10 years (100.0%)	Mean =3.24	Moderate level of digitalization
5	Casual Restaurant (100.0%)	6–15 employees	6–10 years (100.0%)	Mean = 3.12	Moderate level of digitalization

Source: Data from own research.

).

Finally, based on the results obtained, the authors propose a conceptual model through which restaurants can be classified according to the level of digitalization (Figure 4). This level of digitalization is also correlated with the sustainable measures adopted. It is important to note that this approach does not only aim at a descriptive segmentation of restaurants, but essentially provides an explanatory and integrated framework, which directly correlates the level of digitalization with the perceived barriers, the benefits that have been identified, and the sustainable practices that have been implemented through the digital solutions adopted.

Thus, the results obtained materialized and were highlighted in three different groups of restaurants (Figure 4).

First, we discuss restaurants that have a low level of digitalization. These restaurants have quite great difficulties in adopting digital solutions, that are usually caused by various internal barriers such as lack of digital skills, resistance to change on the part of employees, and lack of financial resources. Moreover, these restaurants perceive in a much deeper way the risks and complexity of switching to digital solutions. This can significantly limit the implementation of modern technologies in the supply chain or in other activities of the restaurant.

Secondly, we can mention restaurants that have a moderate level of digitalization. In this case, these restaurants partially implement digital solutions, but only in certain activities. They implement digital solutions for more specific purposes such as “cost efficiency” or in order “to reduce food waste”. These restaurants, even if they have certain barriers in the process of implementing digital solutions, have a certain degree of adaptability and a tendency that is quite inclined towards innovation. At the same time, it is specified that these restaurants hesitate to fully integrate digitalization.

Finally, we can discuss restaurants that have an advanced level of digitalization. Restaurants that fall into this category actively and strategically integrate digital solutions, generally to support sustainable objectives and to streamline processes. The perceived barriers when implementing digital solutions are reduced by these restaurants, and their culture is deeply directed towards innovation. It is worth noting that the structure of these restaurants, which have an advanced level of digitalization, is generally flexible and has a dynamic direction towards the continuous evolution of digital solutions.

This classification made by the authors brings applicative and theoretical value. This is possible because it allows an advanced understanding of the different stages of digitalization in the restaurant sector. At the same time, the classification can facilitate the formulation of more specific interventions for the following different categories: public policies, professional training, and financial support. Finally, it can be said that this classification can represent a basis for continuous monitoring of digital progress over a long period of time among similar units.

5. Conclusions

Following the obtained results, it can be concluded that the digitalization process of the supply chain of the analyzed Romanian restaurants analyzed is at a relatively intermediate stage and has certain trends that lead to an evolution. Therefore, the study highlighted the fact that digitalization is used in the most essential processes of the analyzed restaurants (relations with suppliers, inventory management, payments), but is little implemented in the components that target the direct relationship with the buyer or the supply area. Even though a fairly large number of the analyzed restaurants use digital solutions, especially artificial intelligence for order optimization, the level of digitalization of the supply process still remains quite low.

These results are also supported by the study conducted by Radu Rugiubei and Florina Pînzaru [77], which showed that supply chain practices are partially digitalized and require constant development and improvement—a finding that is likewise confirmed by the research carried out for the present article.

From the point of view of sustainability, the vast majority of the responding restaurants indicated that they implement sustainable measures in this direction, but no statistically significant relationship was identified between digitalization and sustainability. In other words, it was found that managerial perception had only began to recognize a relatively positive role of technology in promoting sustainable practices. However, there are studies in the specialized literature that have managed to demonstrate this phenomenon, for example, the article How Digitalization Drives Supply Chain Performance in the Romanian Industry: The Roles of Sustainability, Resilience, Risk Management, and Integration [69], shows that digitalization exerts a significant positive influence on sustainability.

Simultaneously, barriers that hinder digitalization were also highlighted; these are organizational, which include low skills and resistance to change on the part of employees, and structural, which include the lack of adapted solutions and integration with existing systems. It was also observed that the main factors that can influence the adoption of digital technologies were perceived from the perspective of external pressures and from the perspective of internal efficiency.

Finally, the classification of restaurants, which was carried out according to the level of digitalization, highlighted a need for differentiated policies, adapted to the current level of digitalization of each restaurant analyzed, with a particular emphasis on financial support and continuous professional training.

These results are important and valuable for entrepreneurs and managers in the HoReCa industry, who can understand more clearly and concisely how they can integrate digital solutions into their strategies regarding sustainability. At the same time, the results are essential for consultations in digital transformation for suppliers and for those who are clearly interested in a more efficient and responsible supply chain.

This study has certain limitations that need to be mentioned. First, the research was conducted on a limited sample, and the sampling method was non-probabilistic, which means that the results cannot be extrapolated to the entire HoReCa industry in Romania. Nevertheless, the results remain valuable for the academic world, but also for restaurant managers, because they reveal a series of realities that the restaurant industry faces in the Romanian market. Moreover, because only one country was studied, it is only possible to present the particularities of this market. Second, the approach was exclusively quantitative, and this did not allow for a deep understanding of the reasons and contexts behind the answers provided by the respondents. It is also noted that the opinions of suppliers were not included. Their opinions could have provided a more complete perspective on the relationships created in the supply chain. Thus, these aforementioned aspects can be taken into consideration for future research, in which a qualitative dimension or comparison data between different restaurants can be explored.