This study examines how sustainability strategies contribute to sustained competitive advantage in small restaurants, using an integrated framework that combines the Resource-Based View (RBV), Stakeholder Theory and Dynamic Capabilities (DC).
A mixed-methods study of 128 restaurants in Barcelona assesses environmental and social sustainability commitments and analyzes how restaurant size, responsible practices and certifications relate to competitive advantage.
Despite limited resources, small restaurants achieve sustainable competitive advantage by strategically leveraging stakeholder trust and eco-certifications as DC, reconfiguring resources and relationships to adapt to evolving sustainability demands and market conditions.
The study is context-specific to Barcelona, limiting generalizability to other regions.
Restaurant owners can strengthen sustainability performance by developing adaptive capabilities that convert certifications and stakeholder relationships into strategic assets. Policymakers should simplify eco-certification schemes and tailor them to SME needs.
Strengthening stakeholder relationships can foster community engagement, promote fair labor practices and enhance social cohesion in the hospitality sector.
This study advances a hybrid framework integrating the RBV, Stakeholder Theory and DC, showing that small restaurants achieve sustainable competitive advantage from the strategic orchestration of key resources in response to evolving stakeholder and environmental pressures.
1. Introduction
Tourism is resource-intensive and a notable contributor to the climate crisis, making sustainability essential (Raab et al., 2018). The restaurant sector, which generates 4% of global GDP and 11 million jobs (Lew, 2020), consumes significant energy, food and water, creating environmental and social impacts. Sustainability has therefore shifted from a niche concern to a strategic priority under regulatory and stakeholder pressures (Dani et al., 2022) but strategies for growth and resilience through co-creation remain limited (Dube et al., 2020). While sustainable practices can improve customer satisfaction, loyalty and competitiveness (Kim and Hall, 2020) and food waste reduction is increasingly adopted for cost benefits (Blum, 2020), social initiatives remain scarce and precarious employment persists (Ariza-Montes et al., 2019; Bi et al., 2021). Regarding the economic dimension of sustainability, restaurants are crucial to the economy of many destinations due to their capability of creating jobs and generating income (Font et al., 2023), but they are vulnerable to crises like COVID-19 (Maynard et al., 2021). Effective sustainability indicators are crucial for assessing performance and competitiveness (Rasoolimanesh et al., 2023), particularly in small and medium-sized restaurants (Jansson et al., 2017). However, research has focused mainly on environmental metrics, overlooking aspects like accessibility, diversity, labor conditions and stakeholder relationships (Madanaguli et al., 2022). Finally, certification processes for small enterprises are also underexplored (Flagstad et al., 2022). While large hospitality groups can invest heavily in sustainability, SMEs face resource constraints that demand adaptable strategies (Tandon et al., 2024). Despite these challenges, small restaurants are finding ways to turn sustainability into a competitive advantage, yet little research has examined how this occurs through the interaction of resources, stakeholder relationships and adaptive capabilities.
This study integrates Resource-Based View (RBV) (Barney et al., 2001), Stakeholder Theory (Freeman, 2023) and Dynamic Capabilities (DC) (Teece, 2007) into a hybrid framework to examine how small restaurants convert sustainable practices and certifications into competitive advantage, focusing on 128 restaurants in Barcelona. The research explores how resource constraints are mitigated through stakeholder trust, eco-certifications and adaptive capabilities, noting that certification value varies by practice. Barcelona’s EU context offers insights for Latin American markets where sustainability regulations and certification requirements are expanding. Practical recommendations are suggested not only by their role as competitive resources but also by the practices that most strongly influence certification outcomes. This is seen in how restaurants adapt to sustainability pressures despite limited financial and human capital. Our study builds on this tension by examining when certifications become strategic resources and when they require adaptive stakeholder engagement to yield competitive value.
2. Literature review
2.1 Strategic foundations: RBV and stakeholder relationships in sustainability
The RBV explains how firms gain advantage through resources that are valuable, rare, inimitable and non-substitutable by exploiting them in the most efficient and differentiated way will determine success (Barney et al., 2001). In sustainability, RBV highlights how green practices and certifications can enhance differentiation, performance and reputation (Khanra et al., 2022). In the hospitality sector, resources such as staff training, environmentally friendly operations and sustainability certifications have been linked to improved performance and reputational gains (Gerhart and Feng, 2021; Martinez-Martinez et al., 2019). These include tangible assets (e.g. location, menu) and intangibles (e.g. brand reputation, supplier trust and certifications) in restaurants. However, RBV is criticized as static and inward-focused, overlooking relational and adaptive aspects crucial in dynamic markets.
Stakeholder Theory complements RBV by framing value creation as relational, with trust and collaboration as strategic assets (Freeman et al., 2021). Thus, customers, suppliers, employees and communities are not merely passive beneficiaries but active partners who help shape and sustain the resources that underpin competitive advantage. Although strategic management scholars did not widely use the stakeholder theory to explain competitive advantages, emerging literature incorporates this approach in business, ethics and society. In small hospitality firms, socially embedded relationships foster innovation and legitimacy (Barakat and Wada, 2021), while stakeholder engagement in sustainability builds trust and acceptance of environmental and social initiatives (Font and Lynes, 2018).
Freeman (2023) advocates for integrating both theories to enhance performance and social-environmental impact by valuing stakeholder relationships as strategic assets that contribute to long-term competitiveness and success. Similarly, McGahan (2023) proposes that stakeholders act as binders of resources to organizations, suggesting that competitive advantage emerges not only from the possession of strategic assets but also from the relationships that sustain and co-develop them. While both theories identify key resources and stakeholders, they offer little on how these are reconfigured over time, but recent RBV research highlights its dynamic nature. Greve (2021) identifies overlaps between RBV and organizational learning, underscoring how problematic search and interorganizational imitation contribute to the ongoing reconfiguration of resources. In parallel, Burt and Soda (2021) conceptualize network brokerage as a mechanism for resource integration across closed, loose and recombinatory configurations, enabling learning, resilience and innovation. Additionally, Furr and Eisenhardt (2021) introduce uncertainty as a boundary condition for RBV’s explanatory power, suggesting that in volatile environments, resource-based logic must be complemented by adaptive strategic approaches. The Stakeholder–RBV framework balances competition and cooperation, enabling SMEs to amplify influence, create shared value and sustain viability (Martin and Phillips, 2022), though it benefits from the process perspective of dynamic capabilities (Porter and Kramer, 2011). This study contributes by integrating DC to explain how SME restaurants adapt resources and relationships to meet sustainability challenges.
2.2 Toward a dynamic resource–relationship framework for sustainability in SMEs
Dynamic Capabilities theory complements RBV and Stakeholder Theory by emphasizing a firm’s ability to sense opportunities, integrate resources and transform capabilities amid change (Teece, 2007). Scholars have explored how dynamic capabilities interconnect with both theories, particularly in sustainability contexts. A combined theoretical lens shows that stakeholder pressure (external) and resource orchestration (internal) are not mutually exclusive but co-evolve as firms pursue legitimacy and competitive advantage in volatile environments (Dai et al., 2021). Capabilities such as anticipating expectations, pursuing eco-certifications and reconfiguring supply chains shift RBV–Stakeholder integration from static to adaptive (Fatoki, 2021), with recent work framing them as managerial, process-driven skills for innovation (Furr and Eisenhardt, 2021). In hospitality, a processual view is vital as sustainability norms, consumer expectations and certification standards shift rapidly. For small restaurants, DC include adapting menus to seasonal produce, meeting evolving certification demands and strengthening community ties. While eco-certification can offer legitimacy and differentiation, SMEs face significant financial, administrative and operational barriers, with schemes often complex, costly and poorly aligned to their needs (Chkanikova and Sroufe, 2021). This situation becomes even more complex in emerging economies like Latin America or urban contexts like Barcelona, where eco-certification schemes are expanding yet remain complex, expensive and often misaligned with SME needs (Flagstad et al., 2022).
Our study builds on this evolving hybrid by examining how small restaurants operationalize sustainability practices and certifications not just as strategic resources, but as outcomes of sensing, seizing and transforming stakeholder expectations. Thus, this tension reinforces the need to understand certifications not merely as strategic assets, but as contingent resources whose effectiveness depends on firms’ adaptive capabilities.
2.3 Restaurants commitment to sustainability as a competitive advantage
Studies identify multiple drivers of environmentally and socially friendly practices in restaurants, including regulatory frameworks and global initiatives like the SDGs (Chaturvedi et al., 2024; Higgins-Desbiolles et al., 2019; Minuzzo and Santos, 2024).
Financial incentives and cost savings often outweigh initial investments in eco-friendly practices (Jacobs and Klosse, 2016; Kiefhaber et al., 2020). Such initiatives enhance differentiation, performance, reputation and customer satisfaction, supported by growing green consumption trends (Madanaguli et al., 2022; Teng and Wu, 2019). Stakeholder pressure, media influence and managers’ or employees’ values also drive adoption (Meager et al., 2020). Persistent barriers to sustainable practice adoption include cost, time, supply chain inaction, limited knowledge, skepticism and low awareness of negative impacts, alongside managerial ambivalence, logistical issues and resource constraints (Luo et al., 2021; Meager et al., 2020). Consumer indifference can further deter investment and in high-end sectors, green practices may be seen as less luxurious (Peng, 2020).
Large restaurants can lead sustainability efforts due to greater resources, reach and influence, benefiting from investments that improve efficiency and reduce environmental impact (Bianco et al., 2023; Chkanikova and Sroufe, 2021; Nagarajan et al., 2019). Nevertheless, the size of the company seems a key aspect to consider when analyzing sustainable transition and competitiveness (Robinson et al., 2023; Youn et al., 2015). SMEs, which dominate the restaurant industry (Alberca and Parte, 2018), face resource, knowledge and time constraints, often acting only under regulatory pressure (Cantele and Cassia, 2020). Barriers include limited understanding of long-term benefits, financial constraints and perceptions of high costs, which hinder the adoption of sustainable practices (Calisto et al., 2021). Raab et al. (2018) also explain that the lack of economic resources to invest in eco-friendly equipment is associated with the small size of companies. From this, the hypotheses to evaluate are:
The restaurant’s size impacts the commitment to sustainable indicators as a valuable competitive advantage.
The restaurant’s size impact on the commitment to sustainable indicators for Water and Energy Management (WATENERG).
The restaurant’s size impact on the commitment to sustainable indicators for Sustainable Materials (SUSTMATER).
The restaurant’s size impact on the commitment to sustainable indicators for Sustainable Production (SUSTFOODPROD).
The restaurant’s size impact on the commitment to sustainable indicators for Food Waste Management (WASTEMANAG).
The restaurant’s size impact on the commitment to sustainable indicators for Social sustainability (SOCIALSUST).
2.4 Sustainable certifications as competitive advantages
Hospitality companies use certifications to differentiate, attract customers and validate sustainability in areas such as energy, water and waste (Bianco et al., 2023; Madanaguli et al., 2022). Certifications enhance legitimacy (Paelman et al., 2021), reduce costs, improve access to resources (Rhou and Singal, 2020) and are viewed favorably by investors, lowering risks and capital costs while supporting better financial performance (Qian and Yu, 2024; Sandberg et al., 2023).
In emerging economies, eco-certification is used to enhance credibility, trust and competitiveness but faces challenges from weak enforcement, high costs and limited stakeholder engagement. Effective programs must be credible and context-sensitive for SMEs (Cantele and Cassia, 2020; Font and Lynes, 2018). Studies stress aligning global standards with local practices and highlight both benefits and barriers (Buhalis et al., 2023). In the case of Colombia, Furumo et al. (2020) provide evidence of how certification can positively influence sustainability practices among smallholders but also note persistent socioeconomic barriers. Research in Mexico found that while regulatory pressure often motivates ISO 14001 adoption, such certifications may not lead to sustained compliance improvements without stronger institutional support (Blackman, 2012). Similarly, Carvalho et al. (2022) explore the potential of B Corp certification as a design opportunity in SME, emphasizing how value chain structures influence implementation feasibility. Further studies, such as Grèzes-Bürcher and Grèzes (2024), underscore how sustainability efforts in restaurants are increasingly tied to circular economy principles, waste reduction strategies and consumer-facing eco-labels that influence brand positioning and customer loyalty. In the case of Spain, Arbelo et al. (2025) show that eco-certification not only enhances environmental performance but can also yield financial benefits through price premiums in competitive tourism destinations like the Canary Islands. In the context of Barcelona, a city with a dynamic SME hospitality sector, eco-certification is often perceived as both a signal of quality and a response to stakeholder pressures, though its adoption remains uneven (Arenado Rodríguez et al., 2017). These findings highlight the importance of understanding eco-certification not only as a symbolic or regulatory tool but also as a strategic asset shaped by local institutional and market dynamics.
For small restaurants, obtaining sustainable certification is often hindered by high costs, time demands, complex procedures and limited resources or expertise, sometimes leading to weak or misleading certifications. Moreover, low-recognition seals and rigid, bureaucratic processes can turn certifications into a disadvantage (Flagstad et al., 2022). Given the variety of sustainability practices, certain dimensions may influence certification more strongly, reflecting both scheme design and operational priorities. From this, the hypotheses are:
Commitment to sustainability leads to achieving sustainable certifications as sustainable competitive advantages (CEERTIF).
Commitment to sustainability for Water and Energy Management (WATENERG) leads to achieving sustainable certifications (CEERTIF).
Commitment to sustainability for Sustainable Materials (SUSTMATER) leads to achieving sustainable certifications (CEERTIF).
Commitment to sustainability for Sustainable Food Production (SUSTFOODPROD) leads to achieving sustainable certifications (CEERTIF).
Commitment to sustainability for Waste Management (WASTEMANAG) leads to sustainable certifications (CEERTIF).
Commitment to sustainability for social sustainability (SOCIALSUST) leads to achieving sustainable certifications (CEERTIF).
3. Materials and methods
3.1 Methodology
This study used a mixed-method design: a quantitative analysis examined how restaurant size relates to sustainability commitment and certification attainment, while a qualitative analysis explored managers’ perspectives on underlying mechanisms, stakeholder dynamics and adaptive strategies.
Barcelona was chosen for its dense, tourism-driven restaurant market dominated by SMEs, similar to many Latin American cities. With over 6,700 restaurants and one restaurant for every 240 residents, the sector faces growing sustainability demands from stakeholders (UVE DATA Market Horeca, 2023). These pressures mirror those faced in Latin American capitals such as Bogotá, Mexico City and Lima, where SMEs dominate, resources are constrained and certification uptake is inconsistent. As part of the EU, Barcelona also operates under stricter regulations, making it a relevant case and strategic proxy for resource-constrained urban hospitality markets. Eligible restaurants had fewer than 250 employees and offered table service. Surveys targeted middle managers, managers or owners, given their central role in implementing sustainability at strategic and operational levels (Filimonau et al., 2020). Participation was voluntary, with informed consent and guaranteed anonymity. Table 1 presents the profile of the 128 participants by number of employees.
Survey’s profile of the participants considering their number of employees
| Number of employees | Restaurants |
|---|---|
| Information not provided | 2 |
| 1–50 emp. | 59 |
| 51–150 emp. | 26 |
| 151–250 emp. | 41 |
| Total | 128 |
| Number of employees | Restaurants |
|---|---|
| Information not provided | 2 |
| 1–50 emp. | 59 |
| 51–150 emp. | 26 |
| 151–250 emp. | 41 |
| Total | 128 |
The quantitative survey, adapted from established scales (Maynard et al., 2021), measured five sustainability constructs: Water and Energy, Sustainable Food Production, Waste Management, Sustainable Materials and Social Sustainability (see Table A1 in Annex 1). The survey employed binary (yes/no) indicators to capture whether specific sustainability practices were implemented. This format was chosen for both theoretical and practical reasons. Conceptually, the binary format aligns with the study’s focus on the presence or absence of concrete ESG actions rather than attitudes or perceptions. Practically, binary items reduce respondent burden, avoid Likert-scale ambiguity and facilitate clear operationalization of sustainability indicators in the SME restaurant context. Although alternative approaches such as Likert scales or tetrachoric-based estimation were considered, they were not applied to maintain consistency with prior sustainability research in hospitality SMEs (Maynard et al., 2021) and with common eco-certification checklist formats. Items were tailored to the restaurant context and aligned with UN SDGs (Minuzzo and Santos, 2024). The qualitative phase used semi-structured interviews (see Annex 2) guided by the RBV–Stakeholder framework Freeman et al. (2021). Thematic saturation was reached after 25 interviews which were either owners, managers, or middle managers directly involved in implementing sustainability practices, confirming the sample’s adequacy (see Table A2 in Annex 3). Quantitative and qualitative findings were integrated to provide a comprehensive understanding of how small restaurants achieve competitive advantage through sustainability.
3.2 Quantitative data analysis
The quantitative approach focuses on exploring the connections between latent variables defined in the theoretical framework. The data were processed and analyzed using SmartPLS 4, a software tool designed for partial least squares structural equation modeling (PLS-SEM) (Hair et al., 2019).
Given the study’s exploratory focus, PLS-SEM was deemed a suitable analytical technique, as it enables the simultaneous estimation of both measurement and structural components of the model (Hair et al., 2022). This makes it particularly effective for examining complex interrelations among latent constructs.
The analysis was conducted in two sequential phases (Chin, 2010). First, the reflective measurement model was assessed to ensure the validity and reliability of the scales used. Once the constructs were validated, the second phase focused on evaluating the structural model, specifically analyzing the hypothesized relationships between the latent variables.
To determine the statistical significance (p-values) of these relationships, a bootstrapping procedure was implemented (Chin et al., 2003), involving 5,000 resamples of the original dataset (Efron and Tibshirani, 1994).
3.2.1 Measurement model assessment
Table 2 presents descriptive statistics, factor loadings, reliability coefficients and variance inflation factors (VIF) for the sustainability constructs to determine whether the latent constructs were reliably represented by their respective observed variable.
Descriptive statistics, correlations and variance inflation factors
| Statistics | Mean | SD | ʎ | s.e. | VIF | Cronbach’s alpha | Composite reliability | Average variance extracted (AVE) |
|---|---|---|---|---|---|---|---|---|
| Water and energy | 0.723 | 0.807 | 0.381 | |||||
| WE1 | 0.194 | 0.389 | 0.452 | 0.127 | 1.289 | |||
| WE2 | 0.637 | 0.473 | 0.546 | 0.109 | 1.274 | |||
| WE3 | 0.256 | 0.431 | 0.644 | 0.099 | 1.497 | |||
| WE4 | 0.243 | 0.392 | 0.493 | 0.113 | 1.334 | |||
| WE5 | 0.222 | 0.397 | 0.614 | 0.088 | 1.32 | |||
| WE6 | 0.307 | 0.435 | 0.788 | 0.056 | 1.77 | |||
| WE7 | 0.405 | 0.477 | 0.713 | 0.078 | 1.707 | |||
| Sustainable food production | 0.644 | 0.752 | 0.263 | |||||
| SFP1 | 0.764 | 0.423 | 0.677 | 0.137 | 1.388 | |||
| SFP2 | 0.827 | 0.377 | 0.257 | 0.18 | 1.175 | |||
| SFP3 | 0.408 | 0.486 | 0.518 | 0.172 | 1.196 | |||
| SFP4 | 0.891 | 0.312 | 0.36 | 0.146 | 1.088 | |||
| SFP5 | 0.579 | 0.49 | 0.635 | 0.151 | 1.241 | |||
| SFP6 | 0.647 | 0.461 | 0.558 | 0.173 | 1.34 | |||
| SFP7 | 0.575 | 0.479 | 0.554 | 0.186 | 1.375 | |||
| SFP8 | 0.683 | 0.45 | 0.435 | 0.206 | 1.242 | |||
| SFP9 | 0.44 | 0.458 | 0.488 | 0.166 | 1.192 | |||
| Waste management | 0.620 | 0.743 | 0.33 | |||||
| WM1 | 0.835 | 0.361 | 0.514 | 0.157 | 1.177 | |||
| WM2 | 0.75 | 0.426 | 0.715 | 0.139 | 1.423 | |||
| WM3 | 0.848 | 0.355 | 0.497 | 0.176 | 1.406 | |||
| WM4 | 0.592 | 0.486 | 0.63 | 0.155 | 1.114 | |||
| WM5 | 0.667 | 0.468 | 0.592 | 0.193 | 1.128 | |||
| WM6 | 0.69 | 0.459 | 0.458 | 0.219 | 1.142 | |||
| Sustainable materials | 0.803 | 0.851 | 0.453 | |||||
| SM1 | 0.368 | 0.439 | 0.665 | 0.093 | 1.641 | |||
| SM2 | 0.342 | 0.448 | 0.643 | 0.096 | 1.446 | |||
| SM3 | 0.328 | 0.458 | 0.608 | 0.114 | 1.368 | |||
| SM4 | 0.314 | 0.414 | 0.568 | 0.103 | 1.35 | |||
| SM5 | 0.282 | 0.443 | 0.614 | 0.089 | 1.359 | |||
| SM6 | 0.52 | 0.494 | 0.769 | 0.081 | 1.603 | |||
| SM7 | 0.472 | 0.489 | 0.811 | 0.061 | 1.821 | |||
| Social sustainability | 0.682 | 0.786 | 0.353 | |||||
| SS1 | 0.439 | 0.486 | 0.739 | 0.068 | 1.858 | |||
| SS2 | 0.569 | 0.471 | 0.756 | 0.071 | 2.133 | |||
| SS3 | 0.624 | 0.479 | 0.451 | 0.133 | 1.226 | |||
| SS4 | 0.472 | 0.493 | 0.576 | 0.101 | 1.326 | |||
| SS5 | 0.476 | 0.496 | 0.535 | 0.117 | 1.400 | |||
| SS6 | 0.341 | 0.465 | 0.586 | 0.100 | 1.317 | |||
| SS7 | 0.242 | 0.422 | 0.433 | 0.124 | 1.159 | |||
| Certificate | 0.328 | 0.458 | 1.000 | 0.000 | 1.000 | |||
| Size | 1.594 | 0.605 | 1.000 | 0.000 | 1.000 |
| Statistics | Mean | SD | ʎ | s.e. | VIF | Cronbach’s alpha | Composite reliability | Average variance extracted (AVE) |
|---|---|---|---|---|---|---|---|---|
| Water and energy | 0.723 | 0.807 | 0.381 | |||||
| WE1 | 0.194 | 0.389 | 0.452 | 0.127 | 1.289 | |||
| WE2 | 0.637 | 0.473 | 0.546 | 0.109 | 1.274 | |||
| WE3 | 0.256 | 0.431 | 0.644 | 0.099 | 1.497 | |||
| WE4 | 0.243 | 0.392 | 0.493 | 0.113 | 1.334 | |||
| WE5 | 0.222 | 0.397 | 0.614 | 0.088 | 1.32 | |||
| WE6 | 0.307 | 0.435 | 0.788 | 0.056 | 1.77 | |||
| WE7 | 0.405 | 0.477 | 0.713 | 0.078 | 1.707 | |||
| Sustainable food production | 0.644 | 0.752 | 0.263 | |||||
| SFP1 | 0.764 | 0.423 | 0.677 | 0.137 | 1.388 | |||
| SFP2 | 0.827 | 0.377 | 0.257 | 0.18 | 1.175 | |||
| SFP3 | 0.408 | 0.486 | 0.518 | 0.172 | 1.196 | |||
| SFP4 | 0.891 | 0.312 | 0.36 | 0.146 | 1.088 | |||
| SFP5 | 0.579 | 0.49 | 0.635 | 0.151 | 1.241 | |||
| SFP6 | 0.647 | 0.461 | 0.558 | 0.173 | 1.34 | |||
| SFP7 | 0.575 | 0.479 | 0.554 | 0.186 | 1.375 | |||
| SFP8 | 0.683 | 0.45 | 0.435 | 0.206 | 1.242 | |||
| SFP9 | 0.44 | 0.458 | 0.488 | 0.166 | 1.192 | |||
| Waste management | 0.620 | 0.743 | 0.33 | |||||
| WM1 | 0.835 | 0.361 | 0.514 | 0.157 | 1.177 | |||
| WM2 | 0.75 | 0.426 | 0.715 | 0.139 | 1.423 | |||
| WM3 | 0.848 | 0.355 | 0.497 | 0.176 | 1.406 | |||
| WM4 | 0.592 | 0.486 | 0.63 | 0.155 | 1.114 | |||
| WM5 | 0.667 | 0.468 | 0.592 | 0.193 | 1.128 | |||
| WM6 | 0.69 | 0.459 | 0.458 | 0.219 | 1.142 | |||
| Sustainable materials | 0.803 | 0.851 | 0.453 | |||||
| SM1 | 0.368 | 0.439 | 0.665 | 0.093 | 1.641 | |||
| SM2 | 0.342 | 0.448 | 0.643 | 0.096 | 1.446 | |||
| SM3 | 0.328 | 0.458 | 0.608 | 0.114 | 1.368 | |||
| SM4 | 0.314 | 0.414 | 0.568 | 0.103 | 1.35 | |||
| SM5 | 0.282 | 0.443 | 0.614 | 0.089 | 1.359 | |||
| SM6 | 0.52 | 0.494 | 0.769 | 0.081 | 1.603 | |||
| SM7 | 0.472 | 0.489 | 0.811 | 0.061 | 1.821 | |||
| Social sustainability | 0.682 | 0.786 | 0.353 | |||||
| SS1 | 0.439 | 0.486 | 0.739 | 0.068 | 1.858 | |||
| SS2 | 0.569 | 0.471 | 0.756 | 0.071 | 2.133 | |||
| SS3 | 0.624 | 0.479 | 0.451 | 0.133 | 1.226 | |||
| SS4 | 0.472 | 0.493 | 0.576 | 0.101 | 1.326 | |||
| SS5 | 0.476 | 0.496 | 0.535 | 0.117 | 1.400 | |||
| SS6 | 0.341 | 0.465 | 0.586 | 0.100 | 1.317 | |||
| SS7 | 0.242 | 0.422 | 0.433 | 0.124 | 1.159 | |||
| Certificate | 0.328 | 0.458 | 1.000 | 0.000 | 1.000 | |||
| Size | 1.594 | 0.605 | 1.000 | 0.000 | 1.000 |
Note(s): SD: Standard Deviation; λ: Standardized loadings; s.e.: standard error; α: Cronbach’s alpha. AVE: Average Variance Extracted. CR: Composite Reliability. ***: All the loadings are significant at a p < 0.01 level
The dimensionality of each construct was verified using factor loadings, which indicate the strength of association between each indicator and its corresponding latent variable (Hair et al., 2011). A factor loading value of 0.5 or higher is generally considered acceptable for confirming that the indicator appropriately reflects the construct.
Convergent validity, which reflects how closely related the indicators of a construct are, was assessed using the Average Variance Extracted (AVE) (Fornell and Larcker, 1981). According to Werts et al. (1974), an AVE value above 0.50 is generally considered indicative of acceptable convergent validity, as it suggests that a latent construct explains more than half of the variance in its indicators. In our analysis, some constructs exhibited AVE values marginally below this threshold. While these lower values suggest somewhat weaker convergence, it is important to note that such results are not uncommon in applied research – particularly when using binary indicators. Furthermore, given the exploratory nature of our study and the theoretical coherence of the constructs, we considered the measurement model acceptable, although with caution in interpretation. Complementary reliability indicators (e.g. composite reliability) were also used to support the validity of the constructs.
To test the internal consistency of each construct, we examined composite reliability, which is especially relevant for reflective measurement models (Chin, 1998). Following the threshold of 0.7 or above recommended by Nunnally and Bernstein (1994), all constructs demonstrated acceptable to high levels of composite reliability, indicating consistent measurement.
When evaluating reliability and internal consistency, Cronbach’s alpha values of 0.7 or above are generally accepted as satisfactory (Nunnally and Bernstein, 1994). Nonetheless, Fornell and Larcker (1981) suggest that if both composite reliability and Cronbach’s alpha exceed 0.6, the construct can still be considered reliable. As presented in Table 2, all constructs demonstrate strong internal consistency, with Cronbach’s alpha scores at or above the recommended levels.
Lastly, we assessed the possibility of multicollinearity among indicators by reviewing their VIF scores. All values were well below the conservative threshold of 3.0, supporting the absence of problematic multicollinearity (Hair et al., 2019).
Table 3 reports the discriminant validity assessment, which verifies whether each construct is distinct from the others in the model to ensure that our latent variables measure unique concepts rather than overlapping dimensions. Discriminant validity was evaluated using the AVE approach, as it was explained before, which is suitable for reflective measurement models (Barclay et al., 1995). In this study, all constructs fulfilled this requirement. Moreover, discriminant validity is further confirmed when the square root of each construct’s AVE is higher than its correlations with other constructs in the model, as Table 4 shows later (Chin, 1998).
Discriminant validity
| Fornell-Larcker | Certification | Waste management | Size | Social sustainability | Sustainable materials | Sustainable food production | Water and energy |
|---|---|---|---|---|---|---|---|
| Certification | 1.000 | ||||||
| Waste management | 0.199 | 0.574 | |||||
| Size | 0.227 | 0.263 | 1.000 | ||||
| Social sustainability | 0.344 | 0.423 | 0.326 | 0.594 | |||
| Sustainable materials | 0.169 | 0.333 | 0.319 | 0.535 | 0.673 | ||
| Sustainable food production | 0.209 | 0.499 | 0.234 | 0.493 | 0.361 | 0.513 | |
| Water and energy | 0.367 | 0.307 | 0.319 | 0.385 | 0.301 | 0.402 | 0.617 |
| Fornell-Larcker | Certification | Waste management | Size | Social sustainability | Sustainable materials | Sustainable food production | Water and energy |
|---|---|---|---|---|---|---|---|
| Certification | 1.000 | ||||||
| Waste management | 0.199 | 0.574 | |||||
| Size | 0.227 | 0.263 | 1.000 | ||||
| Social sustainability | 0.344 | 0.423 | 0.326 | 0.594 | |||
| Sustainable materials | 0.169 | 0.333 | 0.319 | 0.535 | 0.673 | ||
| Sustainable food production | 0.209 | 0.499 | 0.234 | 0.493 | 0.361 | 0.513 | |
| Water and energy | 0.367 | 0.307 | 0.319 | 0.385 | 0.301 | 0.402 | 0.617 |
Note(s): Fornell–Larcker criterion: squared-root of AVE in diagonal (cursive) and factor correlations below the diagonal. HTMT ratios over the diagonal (italic)
Inner model assessment indicators
| Constructs | Q2predict | R-square |
|---|---|---|
| Certification | 0.029 | 0.186 |
| Waste management | 0.005 | 0.069 |
| Social sustainability | 0.020 | 0.106 |
| Sustainable materials | 0.029 | 0.102 |
| Sustainable food production | 0.002 | 0.055 |
| Water and energy | 0.032 | 0.102 |
| Constructs | Q2predict | R-square |
|---|---|---|
| Certification | 0.029 | 0.186 |
| Waste management | 0.005 | 0.069 |
| Social sustainability | 0.020 | 0.106 |
| Sustainable materials | 0.029 | 0.102 |
| Sustainable food production | 0.002 | 0.055 |
| Water and energy | 0.032 | 0.102 |
3.2.2 Structural model evaluation
Table 4 summarizes the model’s predictive relevance (Q2 values) and explanatory power (R2 values) for the endogenous constructs. This evaluation helps determine how well the model explains variation in sustainability dimensions and certification outcomes. Firm size was measured based on the number of employees and treated as an ordinal predictor variable in the PLS-SEM model. Specifically, firms were categorized as follows: 1 = fewer than 10 employees, 2 = 10–49 employees and 3 = 50–250 employees. This classification is consistent with standard SME definitions and provides a meaningful gradient to differentiate scale-related effects across restaurant firms.
Partial Least Squares (PLS), a method grounded in variance-based analysis as noted by Chin (1998) assesses the structural model through three primary indicators: the R-square (R2) values of the endogenous latent constructs (Cohen, 1988), the Stone–Geisser Q2 statistic (Geisser, 1975; Stone, 1974) and the statistical significance of the path coefficients (Hair et al., 2022).
To assess the robustness and predictive power of the model, we employed the PLSpredict procedure (Shmueli et al., 2019). The Stone–Geisser Q2 values were obtained through the blindfolding procedure. These values are expected to be greater than zero (Hair et al., 2022), indicating predictive relevance. In this model, as shown in Table 5, the cross-validated communality values were greater than zero, confirming that the model demonstrates relevant predictive capability.
Structural model: path coefficients and P-values of direct, indirect effect and total effect
| Original sample (O) | Sample mean (M) | Standard deviation (STDEV) | T statistics (|O/STDEV|) | p-values | |
|---|---|---|---|---|---|
| Direct effect | |||||
| Waste management → Certificate | 0.036 | 0.044 | 0.115 | 0.317 | 0.751 |
| Size → Waste management | 0.114 | 0.126 | 0.05 | 2.298 | 0.022 |
| Size → Social sustainability | 0.155 | 0.163 | 0.043 | 3.604 | 0 |
| Size → Sustainable materials | 0.148 | 0.157 | 0.036 | 4.14 | 0 |
| Size → Sustainable production | 0.103 | 0.121 | 0.04 | 2.602 | 0.009 |
| Size → Water and energy | 0.138 | 0.144 | 0.035 | 3.921 | 0 |
| Social sustainability → Certificate | 0.257 | 0.252 | 0.11 | 2.345 | 0.019 |
| Sustainable materials → Certificate | −0.058 | −0.057 | 0.112 | 0.518 | 0.604 |
| Sustainable production → Certificate | −0.034 | 0.014 | 0.136 | 0.252 | 0.801 |
| Water and energy → Certificate | 0.301 | 0.298 | 0.109 | 2.762 | 0.006 |
| Specific indirect effect | |||||
| Size → Waste management → Certificate | 0.004 | 0.004 | 0.015 | 0.273 | 0.785 |
| Size → Water and energy → Certificate | 0.042 | 0.043 | 0.02 | 2.071 | 0.038 |
| Size → Sustainable production → Certificate | −0.004 | 0.000 | 0.017 | 0.214 | 0.83 |
| Size → Sustainable materials → Certificate | −0.009 | −0.009 | 0.018 | 0.492 | 0.623 |
| Size → Social sustainability → Certificate | 0.04 | 0.041 | 0.021 | 1.915 | 0.056 |
| Total indirect effect | |||||
| Size → Certificate | 0.073 | 0.079 | 0.024 | 3.049 | 0.002 |
| Total effect | |||||
| Waste management → Certificate | 0.036 | 0.044 | 0.115 | 0.317 | 0.751 |
| Size → Certificate | 0.073 | 0.079 | 0.024 | 3.049 | 0.002 |
| Size → Waste management | 0.114 | 0.126 | 0.05 | 2.298 | 0.022 |
| Size → Social sustainability | 0.155 | 0.163 | 0.043 | 3.604 | 0 |
| Size → Sustainable materials | 0.148 | 0.157 | 0.036 | 4.14 | 0 |
| Size → Sustainable production | 0.103 | 0.121 | 0.04 | 2.602 | 0.009 |
| Size → Water and energy | 0.138 | 0.144 | 0.035 | 3.921 | 0 |
| Social sustainability → Certificate | 0.257 | 0.252 | 0.11 | 2.345 | 0.019 |
| Sustainable materials → Certificate | −0.058 | −0.057 | 0.112 | 0.518 | 0.604 |
| Sustainable production → Certificate | −0.034 | 0.014 | 0.136 | 0.252 | 0.801 |
| Water and energy → Certificate | 0.301 | 0.298 | 0.109 | 2.762 | 0.006 |
| Original sample (O) | Sample mean (M) | Standard deviation (STDEV) | T statistics (|O/STDEV|) | p-values | |
|---|---|---|---|---|---|
| Direct effect | |||||
| Waste management → Certificate | 0.036 | 0.044 | 0.115 | 0.317 | 0.751 |
| Size → Waste management | 0.114 | 0.126 | 0.05 | 2.298 | 0.022 |
| Size → Social sustainability | 0.155 | 0.163 | 0.043 | 3.604 | 0 |
| Size → Sustainable materials | 0.148 | 0.157 | 0.036 | 4.14 | 0 |
| Size → Sustainable production | 0.103 | 0.121 | 0.04 | 2.602 | 0.009 |
| Size → Water and energy | 0.138 | 0.144 | 0.035 | 3.921 | 0 |
| Social sustainability → Certificate | 0.257 | 0.252 | 0.11 | 2.345 | 0.019 |
| Sustainable materials → Certificate | −0.058 | −0.057 | 0.112 | 0.518 | 0.604 |
| Sustainable production → Certificate | −0.034 | 0.014 | 0.136 | 0.252 | 0.801 |
| Water and energy → Certificate | 0.301 | 0.298 | 0.109 | 2.762 | 0.006 |
| Specific indirect effect | |||||
| Size → Waste management → Certificate | 0.004 | 0.004 | 0.015 | 0.273 | 0.785 |
| Size → Water and energy → Certificate | 0.042 | 0.043 | 0.02 | 2.071 | 0.038 |
| Size → Sustainable production → Certificate | −0.004 | 0.000 | 0.017 | 0.214 | 0.83 |
| Size → Sustainable materials → Certificate | −0.009 | −0.009 | 0.018 | 0.492 | 0.623 |
| Size → Social sustainability → Certificate | 0.04 | 0.041 | 0.021 | 1.915 | 0.056 |
| Total indirect effect | |||||
| Size → Certificate | 0.073 | 0.079 | 0.024 | 3.049 | 0.002 |
| Total effect | |||||
| Waste management → Certificate | 0.036 | 0.044 | 0.115 | 0.317 | 0.751 |
| Size → Certificate | 0.073 | 0.079 | 0.024 | 3.049 | 0.002 |
| Size → Waste management | 0.114 | 0.126 | 0.05 | 2.298 | 0.022 |
| Size → Social sustainability | 0.155 | 0.163 | 0.043 | 3.604 | 0 |
| Size → Sustainable materials | 0.148 | 0.157 | 0.036 | 4.14 | 0 |
| Size → Sustainable production | 0.103 | 0.121 | 0.04 | 2.602 | 0.009 |
| Size → Water and energy | 0.138 | 0.144 | 0.035 | 3.921 | 0 |
| Social sustainability → Certificate | 0.257 | 0.252 | 0.11 | 2.345 | 0.019 |
| Sustainable materials → Certificate | −0.058 | −0.057 | 0.112 | 0.518 | 0.604 |
| Sustainable production → Certificate | −0.034 | 0.014 | 0.136 | 0.252 | 0.801 |
| Water and energy → Certificate | 0.301 | 0.298 | 0.109 | 2.762 | 0.006 |
Results show that water and energy efficiency and social sustainability are the strongest predictors of certification, while waste management, sustainable materials and sustainable food production do not show significant direct effects. This pattern suggests certification schemes may prioritize certain indicators over others. According to Falk and Miller (1992), R2 values should exceed 0.10 to be deemed meaningful. In the current model, while some constructs (e.g. Certificate and Social Sustainability) meet or slightly exceed this threshold, others (such as Waste Management and Sustainable Food Production) fall short. This suggests that the structural model has limited explanatory power for these specific endogenous variables. However, even when R2 is low, if Q2 is > 0 (which it is for all constructs), it shows predictive relevance (Hair et al., 2022).
Table 5 presents the path coefficients, significance levels and effect sizes for the direct, indirect and total relationships in the structural model. This table provides the key statistical evidence for testing our hypotheses on how restaurant size and sustainability practices influence certification outcomes.
By applying the bootstrapping procedure with 5,000 resamples, the path coefficients and their statistical significance were estimated for the relationships within the structural model (see Figure 1). As advised by Chin (1998), standardized path coefficients should exceed 0.10 to be considered meaningful. The effect size (f2) was analyzed to assess the practical contribution of firm size to ESG practices, as well as the influence of ESG dimensions on certification attainment. Based on Cohen’s (1988) guidelines, f2 values of 0.02, 0.15 and 0.35 represent small, medium and large effect sizes, respectively. Values below 0.02 indicate that the predictor has a negligible practical effect on the endogenous construct. Results indicate that all non-significant paths (p > 0.05) are also associated with f2 values below the 0.02 threshold, confirming their negligible practical relevance. These low effect sizes reinforce the conclusion that these predictors exert minimal influence on the respective endogenous constructs. In contrast, all statistically significant paths exhibit f2 values within acceptable limits, supporting their substantive explanatory power.
The flowchart begins with a left text box labeled “Company’s size”. Five text boxes are arranged vertically in the center, labeled from top to bottom: “Water and Energy”, “Sustainable Food Production”, “Waste Management,”, “Sustainable Materials”, and “Social Sustainability”. A final text box on the right is labeled “Certification”. Rightward arrows extend from “Company’s size” to each of the five central boxes, labeled respectively: “p-value: 0.138 triple asterisks, F squared: 0.139 double caret”, “p-value: 0.103 double asterisks, F squared: 0.021 double caret”, “p-value: 0.114 single asterisk, F squared: 0.074 double caret”, “p-value: 0.148 triple asterisks, F squared: 0.120 double caret”, and “p-value: 0.155 triple asterisks, F squared: 0.100 double caret”. Rightward arrows extend from the five central boxes to “Certification”, labeled respectively: “p-value: 0.301 double asterisks, F squared: 0.071 double caret”, “p-value: negative 0.034, F squared: 0.000 caret”, “p-value: 0.036, F squared: 0.008 caret”, “p-value: negative 0.058, F squared: 0.014 caret”, and “p-value: 0.257 double asterisks, F squared: 0.035 double caret”.Tested model: path coefficients, p-value and effect size f2. Source: Authors’ own work
The flowchart begins with a left text box labeled “Company’s size”. Five text boxes are arranged vertically in the center, labeled from top to bottom: “Water and Energy”, “Sustainable Food Production”, “Waste Management,”, “Sustainable Materials”, and “Social Sustainability”. A final text box on the right is labeled “Certification”. Rightward arrows extend from “Company’s size” to each of the five central boxes, labeled respectively: “p-value: 0.138 triple asterisks, F squared: 0.139 double caret”, “p-value: 0.103 double asterisks, F squared: 0.021 double caret”, “p-value: 0.114 single asterisk, F squared: 0.074 double caret”, “p-value: 0.148 triple asterisks, F squared: 0.120 double caret”, and “p-value: 0.155 triple asterisks, F squared: 0.100 double caret”. Rightward arrows extend from the five central boxes to “Certification”, labeled respectively: “p-value: 0.301 double asterisks, F squared: 0.071 double caret”, “p-value: negative 0.034, F squared: 0.000 caret”, “p-value: 0.036, F squared: 0.008 caret”, “p-value: negative 0.058, F squared: 0.014 caret”, and “p-value: 0.257 double asterisks, F squared: 0.035 double caret”.Tested model: path coefficients, p-value and effect size f2. Source: Authors’ own work
The results reveal that Company size has a positive and very significant effect on Waste Management, Sustainable Materials and Social Sustainability, meanwhile Sustainable Food Production and Water and Energy are still significant at a lower level (as p-value is lower than 0.05 but higher than 0.001). These paths meet the minimum threshold and demonstrate significant p-values, supporting their respective hypotheses and suggesting that larger firms are more engaged in these sustainability practices.
Regarding the impact on Certification, the model shows that only Social Sustainability and Water and Energy have significant positive effects on achieving certification, with path coefficients above the 0.10 benchmark and p-values below 0.05, indicating robust relationships. In contrast, Waste Management, Sustainable Materials and Sustainable Food Production, while positively related to firm size as their path coefficients are low and p-values exceed 0.05, do not significantly predict certification attainment. Certification was measured as a binary variable (yes/no) indicating whether the restaurant held any formal sustainability-related certification. While the survey did not distinguish between certification types, interview responses referenced schemes such as Biosphere, ISO 14001 and B Corp. These varied in focus, from environmental management to social responsibility, highlighting the diversity of motivations and benefits perceived by restaurant managers. These findings suggest that while company size influences several sustainability dimensions, only specific practices – particularly those linked to social and resource efficiency aspects – translate into a meaningful effect on certification outcomes. This also suggests that certification bodies and programs may prioritize certain environmental efficiency and social responsibility indicators over other sustainability dimensions, a finding we explore further in the discussion.
3.3 Qualitative data analysis
The qualitative analysis was intended to explain and contextualize the quantitative findings. For example, where statistical models reveal significant or non-significant effects, interview data are used to shed light on the practical reasons for these patterns. We followed a multi-stage coding protocol inspired by Gioia et al. (2013). First, we conducted open coding of interview transcripts to identify initial descriptive labels (first-order codes). Next, we engaged in axial coding to group these into broader second-order themes that captured recurring patterns in how small restaurants respond to sustainability pressures. Finally, we distilled these into aggregate dimensions that informed our theoretical framework: Sustainability as a Strategic Resource (RBV), Relational Stakeholder Strategies and Dynamic Capabilities for Sustainability. Coding was conducted manually using Excel and results were discussed collaboratively among the authors to ensure intersubjective reliability. Concepts were mainly identified in the first 10 interviews and no new concepts emerged after interview 20, confirming that thematic saturation was achieved by this point.
Table 6 presents the full coding structure, showing how each theme and concept is grounded in the interview data and how it relates to the specific interview questions used during data collection. The resulting coding structure illustrates how small restaurants strategically respond to sustainability by leveraging certifications and stakeholder relationships such as VRIN resources, building cooperative local networks and embedding sustainability into daily operations through waste reduction, responsible sourcing and social impact initiatives. These practices reflect a dynamic capability to adapt to stakeholder pressures and regulatory shifts while maintaining competitiveness in resource-constrained environments.
Combined Gioia-style coding table that integrates the interview insights and the theoretical frameworks
| Aggregate dimension | Second-order theme | First-order concepts (codes) | Related interview questions |
|---|---|---|---|
| Sustainability as a strategic resource (RBV) | Certifications as VRIN resources |
| Q3, Q4 |
| Stakeholder relationships as intangible assets |
| Q2, Q3 | |
| Healthy, inclusive and seasonal menu |
| Q3, Q5 | |
| Use of sustainable materials |
| Q1, Q5 | |
| Relational stakeholder strategies | Strategic supplier relationships |
| Q2, Q3 |
| Cooperative advantage through local ties |
| Q2, Q3 | |
| Trade-offs in local sourcing |
| Q1, Q3 | |
| Waste reduction and circular practices |
| Q1, Q5 | |
| Community engagement and social impact |
| Q5 | |
| Workforce sustainability training |
| Q5 | |
| Dynamic capabilities for sustainability | Adapting to external stakeholder pressures |
| Q1, Q2, Q4 |
| Monitoring and adapting operational practices |
| Q1, Q5 | |
| Water reuse and efficiency |
| Q1, Q5 | |
| Strategic use of certifications |
| Q3, Q4 |
| Aggregate dimension | Second-order theme | First-order concepts (codes) | Related interview questions |
|---|---|---|---|
| Sustainability as a strategic resource (RBV) | Certifications as VRIN resources | ‐ Enhance brand image ‐ Build stakeholder trust ‐ Hard to imitate in small firm context | Q3, Q4 |
| Stakeholder relationships as intangible assets | ‐ Long-term supplier trust ‐ Local community reputation ‐ Customer loyalty | Q2, Q3 | |
| Healthy, inclusive and seasonal menu | ‐ Healthy dish options ‐ Diet-inclusive menus ‐ Seasonal/local products ‐ Organic produce ‐ Non-GMO ingredients | Q3, Q5 | |
| Use of sustainable materials | ‐ Organic uniforms ‐ Rechargeable batteries ‐ Eco cleaning products ‐ Paints and office equipment | Q1, Q5 | |
| Relational stakeholder strategies | Strategic supplier relationships | ‐ Certified animal welfare and seafood sources ‐ Documented sustainability in sourcing | Q2, Q3 |
| Cooperative advantage through local ties | ‐ Collaboration with other SMEs ‐ Shared supply chains ‐ Community strengthening | Q2, Q3 | |
| Trade-offs in local sourcing | ‐ Freshness and flexibility ‐ Cost challenges of local suppliers | Q1, Q3 | |
| Waste reduction and circular practices | ‐ Food waste monitoring ‐ Inventory control ‐ Waste reduction goals ‐ Minimizing disposables ‐ Encouraging customer waste reduction | Q1, Q5 | |
| Community engagement and social impact | ‐ Food bank donations ‐ Healthy eating education ‐ Support for social enterprises ‐ Documented community efforts | Q5 | |
| Workforce sustainability training | ‐ Staff training on sustainability and nutrition | Q5 | |
| Dynamic capabilities for sustainability | Adapting to external stakeholder pressures | ‐ Certifications required to meet indicators ‐ Regulations and compliance burdens ‐ Stakeholder pressure (customers, gov’t, competitors) | Q1, Q2, Q4 |
| Monitoring and adapting operational practices | ‐ Energy audits ‐ Use of renewables ‐ Carbon reduction targets ‐ Zero emissions partnerships ‐ Reduction of LPG/natural gas | Q1, Q5 | |
| Water reuse and efficiency | ‐ Rainwater harvesting ‐ Thermal water reuse ‐ Flushing and outdoor cleaning with recycled water | Q1, Q5 | |
| Strategic use of certifications | ‐ Certifications as competitive differentiators ‐ Quality and responsibility signaling ‐ Value for multiple stakeholders | Q3, Q4 |
4. Discussion
This study explored how small independent restaurants seek competitive advantage by leveraging internal resources, managing stakeholder relationships and adapting practices to overcome sustainability challenges. While all restaurants can contribute to environmental and social goals (Higgins-Desbiolles et al., 2019; Madanaguli et al., 2022), operational scale influences their ability to implement such initiatives (Khatter, 2023). Results show a significant relationship between restaurant size and five sustainability dimensions, with smaller firms often constrained by limited budgets, space, time and expertise (Jansson et al., 2017). These constraints were vividly echoed by participants. Participant 1 noted: “The primary barriers to adopting sustainable practices are high upfront costs and the lack of immediate financial return. Given my financial struggles, it’s hard to prioritize sustainability while managing debts and payroll.”
Despite limitations, results indicate that certifications and relational assets – such as supplier trust and customer loyalty – can act as VRIN resources, enabling small firms to differentiate despite limited scale. Certifications tied to social or environmental commitments were reported to boost brand credibility and stakeholder trust, though the link between practices and certification is uneven. Our analysis shows that while sustainability factors depend on company size, not all are significantly associated with certification attainment. This may reflect small firms’ preference for initiatives that cut costs, are easier to implement and are more widely recognized (Freeman, 2011). Participant 10 noted “Certifications can differentiate you from competitors. Customers may perceive your company differently; they perceive quality and social responsibility. Certifications force you to meet certain indicators that you would not otherwise meet.”
While practices like waste management or sustainable menus are common, they do not always lead to certification. Our findings show certification is mainly driven by two factors: water and energy efficiency and social sustainability. The emphasis placed by certification programs on environmental resource efficiency and social responsibility may explain why only Water and Energy and Social Sustainability significantly predict certification. Although our survey used a general binary certification variable, qualitative data revealed that restaurants referenced a mix of certification types, including Biosphere, B Corp and ISO 14001. Each of these prioritizes different aspects of sustainability, which may influence adoption depending on firm capabilities, values and perceived stakeholder expectations. Efficient water use is a key challenge in hospitality (Gössling et al., 2024), with energy and water initiatives improving performance and eligibility for funding (Keliuotyte-Staniuleniene and Mironenko, 2019). Social sustainability through decent jobs, training, workplace improvements and community well-being has gained importance, though certification programs have historically prioritized environmental issues (Michael et al., 2010). Restaurants show dynamic capabilities to adapt, learn and reconfigure resources in response to external change. Several interviewees described adapting procurement strategies, engaging in staff training or rethinking waste management in response to regulatory or social pressures. For instance, Participant 15 explained: “Although it can be challenging to keep up with new regulations, especially without sufficient resources, we strive to stay informed and proactive to ensure the security and welfare of employees and clients.” These responses reflect not only survival strategies but also innovation under constraint, which is central to dynamic capabilities theory in resource-limited contexts. However, as prior studies suggest, accurate and consistent certification programs are required to promote valuable competitive advantages for companies (Font and Harris, 2004). Participant 2 says: “It is also true that many certifications’ agencies don’t apply rigorous audits.”
Qualitative findings underscore the value of relational strategies. SME owners and managers often collaborate with stakeholders, building trust with local suppliers, partnering with other SMEs and engaging communities to create intangible assets that enhance competitiveness. Several participants described sustainability practices embedded in their supply chain relationships, such as sourcing organic ingredients from small local producers, prioritizing seasonal availability and working with suppliers who hold recognized animal welfare certifications. These practices not only reduce environmental impact but also enhance brand differentiation through ethical positioning, aligning with findings from Balarezo Nunez et al. (2024), who illustrate how gastronomic firms can pursue growth while maintaining commitments to humane treatment standards. As Participant 7 noted “Working with local suppliers has benefits, such as fresher ingredients and more personalized and flexible services. However, sometimes they cannot offer competitive pricing, which makes it difficult to keep costs down. Nevertheless, these relationships help strengthen the local economy and create a sense of community.” Nevertheless, there is a room for improvement as Participant 18 noted, “If there was more of a spirit of cooperation, we could all have better relationships with suppliers, lower costs, and compete more effectively with big chains.” These relationships, central to Stakeholder Theory, serve as relational capital and legitimacy mechanisms (Freeman, 2023). Figure 2 maps the multi-layered stakeholder relationships driving sustainability.
The figure consists of a central circle labeled “S M E s restaurants”. Twelve surrounding circles are arranged in a ring around it. Starting from the top and moving clockwise, the circles are labeled: “Government”, “Community”, “Providers”, “Clients”, “Certification agencies”, “People (employees)”, “Competitors”, “Environment”, “Unions”, “Trade associations”, “Political groups”, and “Financial community”. Two-way arrows extend between the central circle and each surrounding circle, indicating bidirectional relationships.Multi-layered stakeholder relationships are driving sustainability based on Freeman (2023). Source: Authors’ own work
The figure consists of a central circle labeled “S M E s restaurants”. Twelve surrounding circles are arranged in a ring around it. Starting from the top and moving clockwise, the circles are labeled: “Government”, “Community”, “Providers”, “Clients”, “Certification agencies”, “People (employees)”, “Competitors”, “Environment”, “Unions”, “Trade associations”, “Political groups”, and “Financial community”. Two-way arrows extend between the central circle and each surrounding circle, indicating bidirectional relationships.Multi-layered stakeholder relationships are driving sustainability based on Freeman (2023). Source: Authors’ own work
Finally, participants stressed the need for public and institutional support to overcome barriers such as financial fragility, limited incentives and inconsistent audits. Suggested measures included subsidies, streamlined certification and training to bridge the gap between ambition and action. Participant 11 noted “Tax breaks or grants for sustainable practices, like subsidies for energy-efficient equipment, sourcing locally or hiring employees, would greatly ease the financial burden. These incentives would make it easier to adopt sustainability without compromising the restaurant’s financial stability and competitiveness”. Literature supports the role of tax incentives and tailored regulations in promoting ecological sustainability (Weick, 2016).
5. Conclusions
This study explored how small restaurants enhance competitiveness by integrating sustainability within a hybrid RBV–Stakeholder–DC framework. From the RBV perspective, assets such as credible certifications, trusted supplier relationships and distinctive menus can serve as valuable, rare, inimitable and non-substitutable (VRIN) resources, strengthening differentiation and signaling quality. Strong community ties and local sourcing provide intangible resources that support sustained advantage, though these are often unevenly distributed and underused due to financial, informational and institutional constraints. Restaurant size shapes sustainability outcomes, with smaller firms hindered by limited economic and human capital. From the Stakeholder Theory lens, small restaurants navigate complex relationships with suppliers, customers, regulators and communities; while positive engagement enhances legitimacy and resilience, it can also bring compliance costs and operational burdens. From the DC perspective, small restaurants demonstrate the ability to sense opportunities and challenges, seize them through actions such as adapting procurement to regulatory requirements or investing in water and energy efficiency and transform operations by reconfiguring supply networks toward socially responsible sourcing. Embedding DC into the RBV–Stakeholder framework shifts the focus from static resource ownership to ongoing reconfiguration – critical in volatile hospitality contexts where adaptability determines whether sustainability yields lasting competitive advantage. The study contributes to theory by showing how small hospitality firms do not merely possess ESG-related resources but actively reconfigure stakeholder relationships and certifications in ways that reflect dynamic capabilities.
Our mixed-methods findings show that sustainability’s competitive potential in small restaurants depends not only on possessing valuable resources but also on managing stakeholder relationships and maintaining the agility to adapt to external pressures. Although this study is based in Barcelona, its restaurant sector shares structural characteristics with many urban hospitality markets in Latin America. Barcelona’s position within the European Union provides a forward-looking perspective for emerging economies, where sustainability regulations and certification requirements are on the rise. Observing how Barcelona’s SMEs respond to such pressures offers valuable lessons for businesses preparing for similar regulatory and market shifts. While the results cannot be statistically generalized beyond this case, they provide theoretically transferable insights for comparable competitive contexts. The findings offer guidance for restaurant owners, policymakers and certification bodies aiming to advance sustainability in the sector. For restaurant managers, embedding sustainability into both strategic positioning and daily operations can strengthen resilience, enhance reputation and increase long-term viability (Iraldo et al., 2017). Beyond firm-level gains, sustainable practices contribute to destination competitiveness and the regeneration of local economies, societies and environments (Font et al., 2023). Policymakers should collaborate with industry actors to develop targeted incentives, capacity-building programs and simplified certification schemes, alleviating financial barriers through measures such as tax reductions for waste reduction or improved working conditions (Falavigna and Ippoliti, 2021). Efforts should address social issues – such as equality plans and enhanced labor agreements – recognizing employees as key stakeholders. Strengthening cooperation with suppliers and competitors can help overcome the challenges of a fragmented sector, reduce costs and drive innovation (Freeman, 2023). Certification bodies should refine frameworks and indicators to reflect SME realities, adopting globally recognized yet flexible protocols that cover all dimensions of sustainability (Cantele and Cassia, 2020). By tailoring requirements to different firm sizes and contexts, certification systems can increase adoption and impact. In particular, emphasis on water and energy efficiency aligns the sector with urgent climate priorities and the need for targeted interventions (Scott, 2021).
This study has several limitations. First, it was conducted exclusively in Barcelona, which may limit the applicability of the findings to other regions or contexts. The focus on small and medium-sized restaurants also excludes perspectives from larger establishments, narrowing the scope of conclusions. In the qualitative phase, the participation rate may have constrained the richness and diversity of insights. Finally, revenue data from participating restaurants was unavailable, limiting the ability to link sustainability practices directly to financial performance.
Future studies should address the challenges of applying global sustainability standards in the hospitality industry to ensure consistency and comparability across jurisdictions and contexts. Certification processes should be adapted to the capabilities of SMEs, promoting broader and more equitable adoption of sustainable practices and emphasizing cooperation as a driver of social sustainability. Greater attention should be given to the role of consumers and employees as key stakeholders, exploring how joint value creation occurs. Longitudinal studies could track the impact of certification on business performance and competitive positioning over time, testing the persistence of VRIN resources in dynamic markets. Multi-stakeholder surveys involving suppliers, customers and regulators would offer deeper insight into how relational strategies are perceived and implemented. Comparative research between emerging and developed economies could reveal contextual factors shaping the value and adoption of sustainability practices. Finally, integrating financial performance metrics with qualitative assessments of stakeholder trust and adaptive capacity could advance theoretical integration at the intersection of RBV, Stakeholder Theory and Dynamic Capabilities in hospitality SMEs.
The authors would like to express their sincere gratitude to the Barcelona City Council for its ongoing commitment to fostering innovative, responsible, and sustainable tourism development. Its institutional support has been fundamental in advancing initiatives that promote research, knowledge transfer, and the adoption of tourism models aligned with principles of sustainability and social well-being.
Annex 1 Questions from the survey organized by categories
The questionnaire contains a list of 35 questions related to the following categories: Water and Energy; Sustainable Food Production, Waste Management, Sustainable Materials and Social Sustainability.
| Question yes/no | Water and energy |
|---|---|
| WE1 | Rainwater is collected and/or water from thermal counters that use water is recycled for use in activities where the use of drinking water is not required (e.g. flushing, washing outside areas) |
| WE2 | The company has documentation for the assessment and/or inspection of energy use for energy conservation |
| WE3 | The company uses some form of renewable energy (wind, solar, or photovoltaic) in the production area |
| WE4 | The company achieves zero greenhouse gas emissions with proven partnerships (e.g. commercial energy and vehicle fuel use) |
| WE5 | The company has a documented program to reduce carbon emissions (by at least 5% per year) |
| WE6 | The company has documented targets for reducing the use of liquefied petroleum gas |
| WE7 | The company has documented targets for reducing the use of natural gas |
| Sustainable food production | |
| SFP1 | The company offers ≥5% of its proven healthiest (less salt, sugar and oil) dishes |
| SFP2 | The company offers a separate menu or substitutions to meet diet restrictions, such as gluten-free preparations, vegetarian cuisine, vegan menu, or preparations to meet religious restrictions |
| SFP3 | The company has documented commitments, with a defined term, to reduce the use of sugar, salt, or saturated fat on the menu |
| SFP4 | The company includes seasonal products in its menu, changing it throughout the months of the year |
| SFP5 | At least 5% of the fruits and vegetables that the company buys are certified organic |
| SFP6 | Suppliers of products of animal origin have certificates that prove that animals are raised without the application of antibiotics or organics |
| SFP7 | The company only purchases products of animal origin that have an animal welfare certification seal |
| SFP8 | The company has a policy of purchasing sustainable seafood |
| SFP9 | The company does not use ingredients or products with transgenic ingredients in its composition in the production of meals |
| Waste management | |
| WM1 | The company assesses its food waste during food preparation |
| WM2 | The company carries out smart ordering systems, inventory monitoring, inventory rotation and/or other inventory management strategies to avoid food waste |
| WM3 | The company has goals for reducing/controlling food waste |
| WM4 | The company has an operational policy that contains a documented strategy on solid (non-food) waste management |
| WM5 | The company does not use disposables and/or adopts strategies to minimize the use of these materials as much as possible, with documented goals |
| WM6 | The company adopts measures to encourage its customers to reduce waste (for example: maintaining glasses, reducing disposable packaging and eliminating plastics or straws) |
| Sustainable materials | |
| SM1 | The paints used for building are environmentally sustainable |
| SM2 | The tablecloths (if any) and/or employees’ uniforms are made of organic or environmentally sustainable materials |
| SM3 | The company uses rechargeable batteries for battery-powered devices and equipment, including flashlights, handheld vacuum cleaners and others |
| SM4 | Office equipment replaced or purchased is certified |
| SM5 | The company uses only ecological cleaning products |
| SM6 | The company uses cleaning concentrates and dilution control systems and/or employee training and monitoring for adequate dilution to minimize the use of chemicals |
| SM7 | The company exclusively uses environmentally sustainable hand cleaners in the bathrooms of customers and employees |
| Social sustainability | |
| SS1 | The team has already undergone environmental training (energy efficiency and water efficiency) |
| SS2 | The team has already undergone environmental training (fundamentals of sustainability) |
| SS3 | The staff has undergone some training on healthy eating and the health impact of what they are producing |
| SS4 | The company has a strategy regarding donations or support to its community |
| SS5 | The company donates to food banks or charities to avoid wasting food from products suitable for consumption |
| SS6 | The company has initiatives to promote healthy eating education for the local community (schools, colleges, community groups) |
| SS7 | Does the company purchase one or more products from a charitable foundation or a social enterprise that provides social impact? (For example, a product made from leftover food, bread from a social |
| Question yes/no | Water and energy |
|---|---|
| WE1 | Rainwater is collected and/or water from thermal counters that use water is recycled for use in activities where the use of drinking water is not required (e.g. flushing, washing outside areas) |
| WE2 | The company has documentation for the assessment and/or inspection of energy use for energy conservation |
| WE3 | The company uses some form of renewable energy (wind, solar, or photovoltaic) in the production area |
| WE4 | The company achieves zero greenhouse gas emissions with proven partnerships (e.g. commercial energy and vehicle fuel use) |
| WE5 | The company has a documented program to reduce carbon emissions (by at least 5% per year) |
| WE6 | The company has documented targets for reducing the use of liquefied petroleum gas |
| WE7 | The company has documented targets for reducing the use of natural gas |
| Sustainable food production | |
| SFP1 | The company offers ≥5% of its proven healthiest (less salt, sugar and oil) dishes |
| SFP2 | The company offers a separate menu or substitutions to meet diet restrictions, such as gluten-free preparations, vegetarian cuisine, vegan menu, or preparations to meet religious restrictions |
| SFP3 | The company has documented commitments, with a defined term, to reduce the use of sugar, salt, or saturated fat on the menu |
| SFP4 | The company includes seasonal products in its menu, changing it throughout the months of the year |
| SFP5 | At least 5% of the fruits and vegetables that the company buys are certified organic |
| SFP6 | Suppliers of products of animal origin have certificates that prove that animals are raised without the application of antibiotics or organics |
| SFP7 | The company only purchases products of animal origin that have an animal welfare certification seal |
| SFP8 | The company has a policy of purchasing sustainable seafood |
| SFP9 | The company does not use ingredients or products with transgenic ingredients in its composition in the production of meals |
| Waste management | |
| WM1 | The company assesses its food waste during food preparation |
| WM2 | The company carries out smart ordering systems, inventory monitoring, inventory rotation and/or other inventory management strategies to avoid food waste |
| WM3 | The company has goals for reducing/controlling food waste |
| WM4 | The company has an operational policy that contains a documented strategy on solid (non-food) waste management |
| WM5 | The company does not use disposables and/or adopts strategies to minimize the use of these materials as much as possible, with documented goals |
| WM6 | The company adopts measures to encourage its customers to reduce waste (for example: maintaining glasses, reducing disposable packaging and eliminating plastics or straws) |
| Sustainable materials | |
| SM1 | The paints used for building are environmentally sustainable |
| SM2 | The tablecloths (if any) and/or employees’ uniforms are made of organic or environmentally sustainable materials |
| SM3 | The company uses rechargeable batteries for battery-powered devices and equipment, including flashlights, handheld vacuum cleaners and others |
| SM4 | Office equipment replaced or purchased is certified |
| SM5 | The company uses only ecological cleaning products |
| SM6 | The company uses cleaning concentrates and dilution control systems and/or employee training and monitoring for adequate dilution to minimize the use of chemicals |
| SM7 | The company exclusively uses environmentally sustainable hand cleaners in the bathrooms of customers and employees |
| Social sustainability | |
| SS1 | The team has already undergone environmental training (energy efficiency and water efficiency) |
| SS2 | The team has already undergone environmental training (fundamentals of sustainability) |
| SS3 | The staff has undergone some training on healthy eating and the health impact of what they are producing |
| SS4 | The company has a strategy regarding donations or support to its community |
| SS5 | The company donates to food banks or charities to avoid wasting food from products suitable for consumption |
| SS6 | The company has initiatives to promote healthy eating education for the local community (schools, colleges, community groups) |
| SS7 | Does the company purchase one or more products from a charitable foundation or a social enterprise that provides social impact? (For example, a product made from leftover food, bread from a social |
Annex 2 Semi-structured interview guide
Q1. What are the main barriers you face in transitioning to more sustainable practices and commitment to sustainable indicators? How do you think these challenges can be overcome?
Q2. Who are your main stakeholders? How do you currently manage relationships with them?
Q3. What measures do you take to stay competitive against larger chains while maintaining your commitment to quality and sustainability?
Q4. Do you consider sustainable certifications to be a competitive advantage for your restaurant, and if so, how have they impacted your business?
Q5. What types of strategies/initiatives would encourage you to adopt more sustainable practices?
Annex 3 Thematic saturation by interview groups
Thematic saturation by interview groups (n = 25)
| Interview group | New first-order concepts identified | New second-order themes | New aggregate dimensions | Saturation status |
|---|---|---|---|---|
| Interviews 1–5 | 14 | 5 | 2 | Substantial theme development |
| Interviews 6–10 | 6 | 2 | 1 | New ideas still emerging |
| Interviews 11–15 | 3 | 1 | 0 | Refinement, few new concepts |
| Interviews 16–20 | 2 | 0 | 0 | Minor additions |
| Interviews 21–25 | 0 | 0 | 0 | Saturation achieved |
| Interview group | New first-order concepts identified | New second-order themes | New aggregate dimensions | Saturation status |
|---|---|---|---|---|
| Interviews 1–5 | 14 | 5 | 2 | Substantial theme development |
| Interviews 6–10 | 6 | 2 | 1 | New ideas still emerging |
| Interviews 11–15 | 3 | 1 | 0 | Refinement, few new concepts |
| Interviews 16–20 | 2 | 0 | 0 | Minor additions |
| Interviews 21–25 | 0 | 0 | 0 | Saturation achieved |

