Drawing on the conceptualization of corporate entrepreneurship strategy (CES), we analyze the impact of the interaction among its elements: entrepreneurial strategic intentionality (ESI), entrepreneurial climate (EC) and entrepreneurial orientation (EO), on sustainability actions performance (SP).
Our study employs symmetric (partial least squares structural equation modeling (PLS-SEM)) and asymmetric (fuzzy-set qualitative comparative analysis (fs-QCA)) approaches to analyze a sample of 132 firms.
The PLS-SEM results show a positive effect, and the fs-QCA analysis identifies two configurations that foster it. Firstly, the relevance of ESI lies in its ability to foster organizational flexibility, clarity and commitment. Secondly, it indicates that the presence of an EO and an EC also favors high levels of SP, with the presence or absence of ESI not being a determining factor.
This study offers a configurational and multi-analytical perspective on the interaction among the elements of CES, as well as its theoretical and practical implications for the development of more sustainable firms.
Introduction
Academic scholarship has established sustainability as a fundamental factor when analyzing organizational performance (Sancak, 2023). Organizational performance encompasses more than just economic and financial results (Richard et al., 2009). Sustainability has served as a differentiating value (Lazaretti et al., 2020). Research has shown increased interest among firms in sustainability-related actions, examined across social, economic and environmental dimensions.
A firm's entrepreneurial actions are highly relevant to organizational outcomes, as the relationships among the factors that comprise strategic corporate entrepreneurship (Kraus and Rigtering, 2017) underscore the direct link between actions taken and outcomes achieved within a firm (Kuratko et al., 2021). Recently, there has been a surge of interest in corporate entrepreneurship and its surrogate concept, intrapreneurship (Berisha et al., 2025).
Corporate entrepreneurship strategy (CES) plays a crucial role in catalyzing innovative and entrepreneurial responses to current business challenges (Kuratko and Morris, 2018). Though CES has established itself as a facilitator of competitive advantages, it is necessary to conceptualize how its components, entrepreneurial strategic intentionality (ESI), entrepreneurial climate (EC) and entrepreneurial orientation (EO), act as mechanisms that promote the organization's environmental and social commitment, as Kuratko (2024) points out. Evidence of this reality is the growing emphasis on sustainability and the consequences of utilizing natural and social resources in business management (Crossley et al., 2021). This has prompted firms to become more involved and committed to effective resource management in an entrepreneurial fashion (Mariappanadar, 2020). Nevertheless, to date, the literature on CES has advanced understanding of it as a driver of innovation and organizational renewal but has not clearly integrated it with strategic sustainability outcomes. Although seminal classic contributions by e.g. Ireland et al. (2009), Kuratko and Audretsch (2013) and Urbano et al. (2022) have been established CES as a means of driving competitive agility and new value creation, most empirical work has focused on performance outcomes in financial or innovation terms rather than on how CES aligns with environmental and social sustainability imperatives.
Previous research has addressed this gap by jointly analyzing the elements of strategic corporate entrepreneurship and sustainability initiatives. Thus, Provasnek et al. (2017) already highlighted the significant role of EO in improving sustainability outcomes. Even more recent studies, such as those by Ammirato et al. (2025) and Silvério et al. (2025), emphasize the importance of entrepreneurial processes within firms for creating sustainable value. Also important is the work of Ruiz-Ortega et al. (2025), who underscore how organizations' sustainability objectives can be aligned with their entrepreneurial actions. This reinforces the importance of an integrated strategic architecture within firms.
Furthermore, although recent studies highlight the growing link between corporate entrepreneurship and the Sustainable Development Goals (Rodríguez-Peña, 2025), they largely treat sustainability as an external outcome rather than integrating it into the core mechanisms and strategic configurations of CES implementation (Hosseini et al., 2018). To address this gap, our study focuses on three main contributions to the literature. First, we provide a configurational explanation of the CES, demonstrating how the interaction among its components, ESI, EC and EO, determines the sustainability actions performance (SP). The CES is now conceptualized as a systemic mechanism that improves sustainability outcomes. Second, the outcomes of sustainability actions are considered strategic, derived from the CES, rather than peripheral outcomes or consequences of external actions. Third, it expands prior knowledge through empirical testing of a multi-analytical model encompassing both symmetric (partial least squares structural equation modeling (PLS-SEM)) and asymmetric (fuzzy-set qualitative comparative analysis (fs-QCA)) relationships, offering a more nuanced understanding of how the CES leads to improved SP.
This study examines the relationships between variables traditionally considered in the context of CES and their impact on SP. Accordingly, to advance theoretical and practical understanding, our research question asks:
How are Entrepreneurial Orientation and Entrepreneurial Climate elements affecting the relationship between Entrepreneurial Strategic Intentionality and Sustainability Actions Performance?
To this end, a model is proposed and tested using data from 132 firms. The analysis of the results generally supports the presented theory, highlighting the proposed relationships and their effects on the SP. This leads to a discussion of these results, along with the main conclusions and the most relevant contributions of this work, such as the confirmation of CES's influence on SP through ESI, and the mediating effects of EO and EC become the most accurate evidence of how CES is a validated vehicle for improving SP in an organization.
Literature review and hypotheses
Firms' entrepreneurial actions reflect their conviction toward identifying and exploiting new opportunities (Ireland et al., 2003). Prior research has established that the elements of the CES, namely ESI, EO and EC (Kreiser et al., 2021); therefore, favor not only the identification and exploitation of new opportunities but also the generation of competitive advantages for the firm (Ireland et al., 2009). Thus, the implementation of these entrepreneurial actions and the resulting organizational outcomes is fostered. Nevertheless, it remains unexplored how the strategic alignment between these elements functions as a higher-order organizational mechanism that enables the entrepreneurial stance to converge into sustained competitive results (Karadayı et al., 2025). It is not the isolated presence of ESI, EO or EC that drives superior results but rather their systemic coherence within a CES architecture that allows firms to orchestrate the search for opportunities simultaneously, the recombination of resources and the renewal of capabilities, their systemic coherence within a CES architecture allows firms to orchestrate the search for opportunities simultaneously, the recombination of resources and the renewal of capabilities.
The CES responds to the need to align business activity with organizational strategy, orienting both objectives and actions toward the medium and long term (Kreiser et al., 2021). This alignment revitalizes organizations and strengthens their competitive position in the market, leading firms to pursue both opportunity exploration and the consolidation of competitive advantages (Kearney and Meynhardt, 2016). Its foundation lies in articulating an ESI, an organizational structure that fosters entrepreneurship and an EO across all hierarchical levels (Ireland et al., 2009).
The sequential relationships between ESI, EO and EC proposed in this study reflect the hierarchical nature of strategic processes in organizations. Thus, EO has served as a strategic orientation for the organization, manifesting itself in decision-making processes, actions and behaviors (Covin and Slevin, 1991; Lumpkin and Dess, 1996). It is therefore plausible to consider it a behavioral manifestation of a prior strategic intention. In the case of EC, it can be understood as an organizational condition shaped by EO-favored behaviors (Hornsby et al., 2002).
Regarding sustainability actions, recent studies show that the EO serves as a key mechanism for translating strategic priorities into sustainable outcomes, particularly through innovation processes and the exploitation of opportunities (Pacheco et al., 2024).
Entrepreneurial strategic intentionality and sustainability actions performance
A firm's ESI represents its commitment to seeking, identifying and exploiting opportunities that can lead to competitive advantages (Crawford and Kreiser, 2015; Ireland et al., 2003). According to Kreiser et al. (2021), this ESI encompasses flexibility, defined as the degree to which a firm can redefine and reorient its objectives and strategies when necessary. Clarity refers to the degree to which the organization communicates its vision, mission and objectives to its members. Commitment refers to the monitoring and control of the fulfillment of strategic objectives.
The time horizon conditions the pursuit of the best SP (Lazaretti et al., 2020). Through their strategy, organizations make decisions that transform their current and future concept. ESI provides a long-term approach to guide the firm's entrepreneurial processes and behaviors (Ireland et al., 2003; Kuratko and Morris, 2018). Specific strategic orientations will be the primary triggers, directly or indirectly, for achieving organizational outcomes (Andrews et al., 2009; George et al., 2019).
The organization's management should consider and analyze potential strategic renewal initiatives to enable it to achieve higher SP (Crossley et al., 2021). Therefore, the number of firms whose strategic management includes actions to promote more sustainable development, to generate products or services and to consume resources more fairly and equitably is increasing (Schuler et al., 2017).
In addition to the economic context, today's society faces challenges such as climate change, poverty eradication and the balance between economic and social progress. Firms must commit to better managing resources and stakeholder relations and to pursuing sustainable development that offers new opportunities to society (Mariappanadar, 2020). The reality of sustainability provides a foundation for successfully addressing society's challenges, focusing on three interdependent but complementary dimensions: economic, social and environmental (Di Vaio et al., 2022).
The economic dimension of sustainability is closely tied to financial strength, productivity and economic profit (Sartal et al., 2020). This vision has evolved to the point where economic sustainability is increasingly considered closely linked to good corporate governance (Mies and Gold, 2021). This is the case with B Corps (Kirst et al., 2021), which are characterized by a balance between the distribution of effort across their social and environmental impacts and their economic benefits. In the social dimension, sustainability aims to promote welfare processes related to the health, safety and quality of life of the firm's members. This dimension places those affected by the firm's products and services at the center. It encompasses both those who produce them and those who consume them, ensuring they receive decent wages, job security and diversity and inclusion, as well as a transparent, ethical and responsible supply chain (Gonçalves and Silva, 2021). The environmental dimension is linked to protecting the environment through the moral imperative to safeguard natural resources for future generations, as influenced by firms' actions (Camilleri, 2019). Traditionally, this dimension has been shaped by resource exploitation, pollutant emissions and environmental damage (Ruiz-Ortega et al., 2021). Entrepreneurship is recognized for addressing environmental issues and implementing sustainable actions that drive growth (Dhahri et al., 2021).
The preceding allows us to state our first hypothesis:
Entrepreneurial strategic intentionality directly and positively influences on sustainability actions performance.
The mediating effect of entrepreneurial orientation
The firm's EO comprises the set of attitudes and actions it develops to identify and capitalize on new opportunities (Kusa et al., 2021; Lee and Peterson, 2000), leading to several organizational outcomes (Crawford and Kreiser, 2015; Ireland et al., 2009). Existing scholarly evidence confirms that entrepreneurially oriented firms outperform conservatively oriented ones and that EO leads to higher performance and the achievement of organizational goals (Anderson et al., 2020). EO contributes significantly through innovativeness, proactiveness and risk-taking (Genc et al., 2019), fundamental elements that affect the outcomes (Covin and Slevin, 1991; Ireland et al., 2009; Kearney and Meynhardt, 2016; Kreiser et al., 2021).
EO is a phenomenon that occurs at both the organizational and individual levels (Covin and Slevin, 1991; Crawford and Kreiser, 2015; Lumpkin and Dess, 1996). Besides EO, the concept of Individual EO has extended the notion to the employee's perspective, capturing EO from this perspective (Forcadell and Úbeda, 2022). EO can be considered one of the most relevant issues in the business management literature, characterized by a constant search for new opportunities that align with societal needs. The influence of EO on firm performance is a well-researched area of study (Covin and Wales, 2018). Researchers have confirmed the pivotal role of EO in driving SP in governmental organizations, small and medium-sized firms, fashion industry firms, greenhouses and entrepreneurial universities (Deslatte and Swann, 2019; Pacheco et al., 2024; Yaghoubi Farani et al., 2024). There is growing evidence that EO dimensions enhance organizations' concern for the community (Guzmán et al., 2020), which, in turn, leads to coherent solutions to current social, economic and environmental challenges (Svensson et al., 2018). EO has been employed as an explanatory mechanism for the effects of a wide range of individual- and organizational-level antecedents on performance and outcomes (Khedhaouria et al., 2020).
The relevance of EO in ESI and its influence on SP allows the following research hypothesis to be put forward:
Entrepreneurial orientation positively mediates the effect of entrepreneurial strategic intentionality on sustainability actions performance.
The mediating effect of the entrepreneurial climate
Management's commitment to creating an appropriate environment favors the success of entrepreneurial action (Lee and Peterson, 2000; Sam Liu et al., 2021). The EC supports decision-making and the adoption of new approaches within the firm (Kuratko et al., 2014b), providing indispensable support for entrepreneurial initiatives (Hornsby et al., 2013). Thus, improving organizational performance is also relevant (Falahat et al., 2018).
Previous work has highlighted the role that internal organizational conditions, specifically EC, play in organizational outcomes (Kearney and Meynhardt, 2016). The existence of EC is founded on five stable dimensions (Hornsby et al., 2002; Kuratko et al., 2014a): Management support (for entrepreneurial and innovative actions); work autonomy (tolerance for failure and independence in tasks); reward system (to encourage entrepreneurial activity); time available (to develop innovations) and organizational boundaries (degree of formalization of procedures, tasks, objectives and expected performance). The internal environment of firms, facilitated by EC, encourages the development of innovative actions that yield financial results (Ireland et al., 2009; Kuratko et al., 2005, 2014b). Among these organizational outcomes are also those related to SP (Svensson et al., 2018).
In this context, the EC may foster more sustainable entrepreneurship by developing initiatives that leverage environmental opportunities (Johnson and Schaltegger, 2020). Viewing firms as a source of added value is essential for the comprehensive development of society and for the economic and environmental conditions of regions. It can be affirmed that EC has been posited as a fundamental component of firms' business actions, seeking not only greater productivity but also a more sustainable and lasting approach over time (Golsefid-Alavi et al., 2021). This has also been attested in corporate entrepreneurship contexts (Glińska-Neweś et al., 2025).
The preceding makes it possible to establish the following general hypothesis:
Entrepreneurial climate positively mediates the effect of entrepreneurial strategic intentionality on sustainability actions performance.
Some firms favor developing an EC through EO actions (Hornsby et al., 2002; Wales et al., 2020), given the importance of EC for the potential performance of entrepreneurial activities (Kang et al., 2016). The promotion of innovativeness, proactiveness and risk-taking (EO components) is associated with greater managerial support for entrepreneurial activities, the creation of rewards, greater task autonomy, more available time and less-rigid organizational boundaries (elements characteristic of EC). Likewise, EC will foster decision-making and the adoption of new business approaches (Kuratko, 2024), directly and positively influencing organizational outcomes, specifically SP (Kreiser et al., 2021).
Therefore, the ESI is related to the SP through the EO and EC. The following hypothesis is established:
Entrepreneurial strategic intentionality is related to the sustainability actions performance through entrepreneurial orientation and entrepreneurial climate.
Figure 1 illustrates the proposed research model.
A flowchart diagram representing the corporate entrepreneurship strategy. The diagram includes four main components: ESI (Entrepreneurial Strategic Intencionality), EO (Entrepreneurial Orientation), EC (Entrepreneurial Climate), and SP (Sustainability Actions Performance). ESI is connected to EO by arrow a1, to EC by arrow a2, and directly to SP by arrow c'. EO is connected to EC by arrow a3 and to SP by arrow b1. EC is connected to SP by arrow b2. The diagram also includes hypotheses H1 to H4, which describe the relationships between these components. H1 describes the direct relationship between ESI and SP. H2 describes the relationship from ESI to SP through EO. H3 describes the relationship from ESI to SP through EC. H4 describes the relationship from ESI to SP through both EO and EC.Research model. Source: Authors' own work
A flowchart diagram representing the corporate entrepreneurship strategy. The diagram includes four main components: ESI (Entrepreneurial Strategic Intencionality), EO (Entrepreneurial Orientation), EC (Entrepreneurial Climate), and SP (Sustainability Actions Performance). ESI is connected to EO by arrow a1, to EC by arrow a2, and directly to SP by arrow c'. EO is connected to EC by arrow a3 and to SP by arrow b1. EC is connected to SP by arrow b2. The diagram also includes hypotheses H1 to H4, which describe the relationships between these components. H1 describes the direct relationship between ESI and SP. H2 describes the relationship from ESI to SP through EO. H3 describes the relationship from ESI to SP through EC. H4 describes the relationship from ESI to SP through both EO and EC.Research model. Source: Authors' own work
Methodology
Sample
The sample was drawn from the report “Relevant firms in the social economy” by the Spanish Social Economy Business Confederation, which identified 674 firms with at least 50 employees. Finally, 132 firms responded to our request. To ensure the reliability of our research's sample size, we employed the G*Power Tool (Faul et al., 2009), with the following parameters: 80% statistical power and αerror prob. 0.05; 0.1 f2estimated, reaching a sample parameter of 125. Therefore, the sample size of 132 firms is reliable.
Measures and data collection
All variables were taken from previously validated scales, ensuring their validity and reliability. The constructs were measured using a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree), except for the control variables (number of employees and sector).
We adapted the measurement scale proposed by Kreiser et al. (2021), which includes three dimensions (ESI, EO and EC). To measure the dependent variable, SP, we employed the measurement scale developed by Gallardo-Vázquez and Sanchez-Hernandez (2014).
Of the 132 firms surveyed, the majority belong to the agriculture and livestock sector (45%), followed by the industry (in general) and energy sector (12%). The predominant profile of the survey respondents is male (78%), aged 51–60 (47%), holding managerial positions (34%) and with a length of service in the firm of 11–20 years (46%).
Data analysis
The proposed model has been tested using PLS-SEM (Ringle et al., 2022). PLS-SEM is particularly relevant for prediction-oriented purposes (Hair et al., 2017a, b) and outperforms various approaches when evaluating complex models involving high-order constructs (HOCs) (Sarstedt et al., 2019).
The constructs used in the general model are consistent with the composite measurement models (Henseler, 2021). Component scores were extracted from the primary model to construct HOCs using the two-stage approach. Data processing was performed with SmartPLS v.4.1.0.0 software (Ringle et al., 2022).
The nature of the constructs used in this research needs to be specified. ESI, EO and EC were studied in the reflective mode (Mode A) (Henseler, 2017). Regarding the SP construct, it was considered that since these are lower-order endogenous constructs, they should be measured in the formative mode (Mode B).
A qualitative fuzzy-set analysis was applied to test hypotheses and obtain more accurate conclusions about causal relationships. The fs-QCA analysis identifies patterns that lead to a specific outcome, rather than merely correlations between variables (Mikalef and Pateli, 2017). It enables the identification of combinations of conditions sufficient for a result to occur, using both qualitative and quantitative evaluations. The variables were directly calibrated by forming fuzzy sets over the range [0,1]. In addition, the analysis of needs or configurational elements elaborated a truth table with the variables ESI, EO, EC and SP, establishing a minimum consistency threshold of 0.75 (Pappas and Woodside, 2021).
Common method bias
Common method bias (CMB) can occur when people's answers are influenced by how the question is framed, with the instrument's impact surpassing their beliefs. To address this, we followed the ex ante recommendation of Podsakoff et al. (2003, 2012) by separating all independent and dependent variables to create a sufficient time lag between measurements. For this reason, the questionnaires were sent out at two different times during the fieldwork: to organizations that responded early and to those that responded later, in the final weeks of that period. Consequently, the sample was divided into two groups: (1) organizations that had responded in the first three months and (2) organizations that had responded in the last three months (Armstrong and Overton, 1977). Thus, the sample was divided into two waves, and the responses from the second wave would reveal the respondents' trends (Filion, 1976). In this way, we would determine whether there were significant differences in responses across the two waves.
Furthermore, guided by this established practice and the existing literature, we used a variance inflation factor (VIF) test to assess multicollinearity between variables. The results, as shown in Table 1, confirm the absence of collinearity issues in our research, underscoring the soundness of our approach in detecting possible CMB.
Common method bias
| VIF | |||||||
|---|---|---|---|---|---|---|---|
| Variables | ESI | EO | EC | SP | Age | Sector | Size |
| 2.251 | 2.227 | 2.852 | 2.161 | 1.282 | 1.174 | 1.105 | |
| VIF | |||||||
|---|---|---|---|---|---|---|---|
| Variables | ESI | EO | EC | SP | Age | Sector | Size |
| 2.251 | 2.227 | 2.852 | 2.161 | 1.282 | 1.174 | 1.105 | |
Note(s): VIF <3. Abbreviations: VIF: variance inflation factor; ESI: entrepreneurial strategic intentionality; EO: entrepreneurial orientation; EC: entrepreneurial climate; SP: sustainability actions performance
Results
Measurement model
The literature suggests that to assess the validity of the constructs specified in Mode A, the individual-level properties of the indicators, internal consistency, reliability and convergent validity of the constructs must be analyzed (Tables 4 and 5) (Benitez et al., 2020; Hair et al., 2012). As shown in Table 2, most indicators and dimensions (second-order constructs) show loadings above 0.7. The internal consistency reliability, as indicated by the “ρc” results, also exceeds 0.7, and all constructs demonstrate convergent validity (above 0.5) based on the average variance extracted.
Estimated model results
| Construct/dimension/indicator | Weights | Loadings | Consistent reliability ρA | Composite reliability ρC | Convergent validity AVE | VIF |
|---|---|---|---|---|---|---|
| Entrepreneurial strategic intentionality (ESI) (Mode A) | 0.853 | 0.905 | 0.762 | |||
| Flexibility | 0.348 | 0.838 | 0.826 | 0.893 | 0.736 | |
| ESI1 | 0.290 | 0.859 | ||||
| ESI2 | 0.375 | 0.858 | ||||
| ESI3 | 0.362 | 0.857 | ||||
| Clarity | 0.371 | 0.896 | 0.841 | 0.925 | 0.860 | |
| ESI4 | 0.561 | 0.933 | ||||
| ESI5 | 0.518 | 0.921 | ||||
| Commitment | 0.426 | 0.883 | 0.861 | 0.935 | 0.878 | |
| ESI6 | 0.540 | 0.938 | ||||
| ESI7 | 0.527 | 0.935 | ||||
| Entrepreneurial orientation (EO) (Mode A) | 0.814 | 0.880 | 0.711 | |||
| Innovativeness | 0.463 | 0.837 | 0.723 | 0.862 | 0.758 | |
| EO1 | 0.651 | 0.908 | ||||
| EO2 | 0.491 | 0.832 | ||||
| Proactiveness | 0.387 | 0.894 | 0.833 | 0.890 | 0.730 | |
| EO3 | 0.404 | 0.860 | ||||
| EO4 | 0.436 | 0.893 | ||||
| EO5 | 0.326 | 0.809 | ||||
| Risk-taking | 0.335 | 0.795 | 0.860 | 0.931 | 0.871 | |
| EO6 | 0.566 | 0.941 | ||||
| EO7 | 0.505 | 0.925 | ||||
| Entrepreneurial climate (EC) (Mode A) | 0.834 | 0.886 | 0.662 | |||
| Management support | 0.312 | 0.832 | 0.875 | 0.902 | 0.648 | |
| EC1 | 0.233 | 0.828 | ||||
| EC2 | 0.204 | 0.706 | ||||
| EC3 | 0.238 | 0.846 | ||||
| EC4 | 0.300 | 0.841 | ||||
| EC5 | 0.263 | 0.797 | 0.915 | 0.911 | 0.632 | |
| Work autonomy | 0.269 | 0.758 | ||||
| EC6 | 0.121 | 0.718 | ||||
| EC7 | 0.264 | 0.860 | ||||
| EC8 | 0.218 | 0.853 | ||||
| EC9 | 0.246 | 0.874 | ||||
| EC10 | 0.252 | 0.792 | ||||
| EC11 | 0.131 | 0.645 | ||||
| Recognition and rewards | 0.328 | 0.855 | 0.855 | 0.911 | 0.836 | |
| EC12 | 0.622 | 0.939 | ||||
| EC13 | 0.468 | 0.889 | ||||
| Time available | 0.318 | 0.806 | 0.883 | 0.944 | 0.894 | |
| EC14 | 0.541 | 0.948 | ||||
| EC15 | 0.516 | 0.943 | ||||
| Sustainability actions performance2 (SP) constructs/items | ||||||
| Sustainability actions performance (SP) (Mode B) | n.a | n.a | n.a | |||
| Economic sustainability (ECS) | 0.561*** | 0.858*** | 0.912 | 0.924 | 0.606 | 1.608 |
| SE1 | 0.171 | 0.824 | ||||
| SE2 | 0.164 | 0.818 | ||||
| SE3 | 0.129 | 0.696 | ||||
| SE4 | 0.133 | 0.661 | ||||
| SE5 | 0.157 | 0.812 | ||||
| SE6 | 0.177 | 0.858 | ||||
| SE7 | 0.179 | 0.818 | ||||
| Se8 | 0.168 | 0.719 | ||||
| Social sustainability (SOCS) | 0.603*** | 0.880*** | 0.930 | 0.938 | 0.604 | 1.446 |
| SS1 | 0.132 | 0.710 | ||||
| SS2 | 0.132 | 0.777 | ||||
| SS3 | 0.151 | 0.861 | ||||
| SS4 | 0.132 | 0.727 | ||||
| SS5 | 0.126 | 0.818 | ||||
| SS6 | 0.094 | 0.742 | ||||
| SS7 | 0.135 | 0.773 | ||||
| SS8 | 0.124 | 0.823 | ||||
| SS9 | 0.141 | 0.792 | ||||
| SS10 | 0.119 | 0.737 | ||||
| Environmental sustainability (ENS) | −0.023n.s | 0.553*** | 0.944 | 0.948 | 0.696 | 1.498 |
| SM1 | 0.177 | 0.851 | ||||
| SM2 | 0.157 | 0.774 | ||||
| SM3 | 0.151 | 0.834 | ||||
| SM4 | 0.148 | 0.876 | ||||
| SM5 | 0.170 | 0.883 | ||||
| SM6 | 0.153 | 0.867 | ||||
| SM7 | 0.123 | 0.779 | ||||
| SM8 | 0.116 | 0.800 | ||||
| Construct/dimension/indicator | Weights | Loadings | Consistent reliability ρA | Composite reliability ρC | Convergent validity AVE | VIF |
|---|---|---|---|---|---|---|
| Entrepreneurial strategic intentionality (ESI) (Mode A) | 0.853 | 0.905 | 0.762 | |||
| Flexibility | 0.348 | 0.838 | 0.826 | 0.893 | 0.736 | |
| ESI1 | 0.290 | 0.859 | ||||
| ESI2 | 0.375 | 0.858 | ||||
| ESI3 | 0.362 | 0.857 | ||||
| Clarity | 0.371 | 0.896 | 0.841 | 0.925 | 0.860 | |
| ESI4 | 0.561 | 0.933 | ||||
| ESI5 | 0.518 | 0.921 | ||||
| Commitment | 0.426 | 0.883 | 0.861 | 0.935 | 0.878 | |
| ESI6 | 0.540 | 0.938 | ||||
| ESI7 | 0.527 | 0.935 | ||||
| Entrepreneurial orientation (EO) (Mode A) | 0.814 | 0.880 | 0.711 | |||
| Innovativeness | 0.463 | 0.837 | 0.723 | 0.862 | 0.758 | |
| EO1 | 0.651 | 0.908 | ||||
| EO2 | 0.491 | 0.832 | ||||
| Proactiveness | 0.387 | 0.894 | 0.833 | 0.890 | 0.730 | |
| EO3 | 0.404 | 0.860 | ||||
| EO4 | 0.436 | 0.893 | ||||
| EO5 | 0.326 | 0.809 | ||||
| Risk-taking | 0.335 | 0.795 | 0.860 | 0.931 | 0.871 | |
| EO6 | 0.566 | 0.941 | ||||
| EO7 | 0.505 | 0.925 | ||||
| Entrepreneurial climate (EC) (Mode A) | 0.834 | 0.886 | 0.662 | |||
| Management support | 0.312 | 0.832 | 0.875 | 0.902 | 0.648 | |
| EC1 | 0.233 | 0.828 | ||||
| EC2 | 0.204 | 0.706 | ||||
| EC3 | 0.238 | 0.846 | ||||
| EC4 | 0.300 | 0.841 | ||||
| EC5 | 0.263 | 0.797 | 0.915 | 0.911 | 0.632 | |
| Work autonomy | 0.269 | 0.758 | ||||
| EC6 | 0.121 | 0.718 | ||||
| EC7 | 0.264 | 0.860 | ||||
| EC8 | 0.218 | 0.853 | ||||
| EC9 | 0.246 | 0.874 | ||||
| EC10 | 0.252 | 0.792 | ||||
| EC11 | 0.131 | 0.645 | ||||
| Recognition and rewards | 0.328 | 0.855 | 0.855 | 0.911 | 0.836 | |
| EC12 | 0.622 | 0.939 | ||||
| EC13 | 0.468 | 0.889 | ||||
| Time available | 0.318 | 0.806 | 0.883 | 0.944 | 0.894 | |
| EC14 | 0.541 | 0.948 | ||||
| EC15 | 0.516 | 0.943 | ||||
| Sustainability actions performance2 (SP) constructs/items | ||||||
| Sustainability actions performance (SP) (Mode B) | n.a | n.a | n.a | |||
| Economic sustainability (ECS) | 0.561*** | 0.858*** | 0.912 | 0.924 | 0.606 | 1.608 |
| SE1 | 0.171 | 0.824 | ||||
| SE2 | 0.164 | 0.818 | ||||
| SE3 | 0.129 | 0.696 | ||||
| SE4 | 0.133 | 0.661 | ||||
| SE5 | 0.157 | 0.812 | ||||
| SE6 | 0.177 | 0.858 | ||||
| SE7 | 0.179 | 0.818 | ||||
| Se8 | 0.168 | 0.719 | ||||
| Social sustainability (SOCS) | 0.603*** | 0.880*** | 0.930 | 0.938 | 0.604 | 1.446 |
| SS1 | 0.132 | 0.710 | ||||
| SS2 | 0.132 | 0.777 | ||||
| SS3 | 0.151 | 0.861 | ||||
| SS4 | 0.132 | 0.727 | ||||
| SS5 | 0.126 | 0.818 | ||||
| SS6 | 0.094 | 0.742 | ||||
| SS7 | 0.135 | 0.773 | ||||
| SS8 | 0.124 | 0.823 | ||||
| SS9 | 0.141 | 0.792 | ||||
| SS10 | 0.119 | 0.737 | ||||
| Environmental sustainability (ENS) | −0.023n.s | 0.553*** | 0.944 | 0.948 | 0.696 | 1.498 |
| SM1 | 0.177 | 0.851 | ||||
| SM2 | 0.157 | 0.774 | ||||
| SM3 | 0.151 | 0.834 | ||||
| SM4 | 0.148 | 0.876 | ||||
| SM5 | 0.170 | 0.883 | ||||
| SM6 | 0.153 | 0.867 | ||||
| SM7 | 0.123 | 0.779 | ||||
| SM8 | 0.116 | 0.800 | ||||
Note(s): CR: composite reliability. AVE: average variance extracted. MC: multidimensional construct. n.a.: non-applicable. n.s./*/**/***: non-significant/significant at p-value <0.05/0.01/0.001 (2 tails)
Regarding the constructs in Mode B, the literature suggests that they should be evaluated at two levels (Hair et al., 2014): at the construct level, by measuring convergent and discriminant validity, and at the dimension level, by assessing multicollinearity and weights. As shown in Table 4, the SP measures confirm that all the results are within the recommended limits (Hair et al., 2017a, b; Sarstedt et al., 2019). The convergent validity of 0.993 exceeds the minimum level of 0.8 reported by Hair et al. (2017a, b) for the specific model plotted.
Two connected representations of the same concept are assembled, and the path coefficient between them is measured. The discriminant validity of SP was examined using correlations between the SP construct and other constructs. All the values are below the recommended 0.7 (Table 3). To assess the weights and loadings, we employed a two-tailed bootstrap procedure to evaluate the significance of the dimensions (see Table 4).
Discriminant validity
| ESI | EO | EC | Age | Size | |
|---|---|---|---|---|---|
| ESI | 0.873 | 0.685 | 0.835 | 0.425 | 0.075 |
| EO | 0.580 | 0.843 | 0.869 | 0.245 | 0.153 |
| EC | 0.706 | 0.719 | 0.817 | 0.391 | 0.106 |
| Age | −0.398 | −0.213 | −0.361 | n.a | 0.072 |
| Size | 0.074 | 0.135 | 0.086 | 0.072 | n.a |
| ESI | EO | EC | Age | Size | |
|---|---|---|---|---|---|
| ESI | 0.873 | 0.685 | 0.835 | 0.425 | 0.075 |
| EO | 0.580 | 0.843 | 0.869 | 0.245 | 0.153 |
| EC | 0.706 | 0.719 | 0.817 | 0.391 | 0.106 |
| Age | −0.398 | −0.213 | −0.361 | n.a | 0.072 |
| Size | 0.074 | 0.135 | 0.086 | 0.072 | n.a |
Note(s): Fornell–Larcker criterion for all constructs below the diagonal (included). HTMT ratio for Mode A constructs above the diagonal. n.a.: non-applicable. HTMT inference confidence intervals (2.5%–97.5%) underneath HTMT values, extracted from a two-tailed bootstrapping procedure. Abbreviations: ESI: entrepreneurial strategic intentionality; EO: entrepreneurial orientation and EC: entrepreneurial climate
Results of the composite construct mode B
| Convergent validity | |
|---|---|
| Construct (≥0.8)* | Path coefficient |
| SP | 0.993 |
| Convergent validity | |
|---|---|
| Construct (≥0.8)* | Path coefficient |
| SP | 0.993 |
| Discriminant validity | |
|---|---|
| v Construct (≤0.7)** | SP |
| ESI | 0.649 |
| EO | 0.588 |
| EC | 0.658 |
| Discriminant validity | |
|---|---|
| v Construct (≤0.7)** | SP |
| ESI | 0.649 |
| EO | 0.588 |
| EC | 0.658 |
Note(s): *Hair et al. (2017a, b); Urbach and Ahlemann (2010). Abbreviations: ESI: entrepreneurial strategic intentionality; EO: entrepreneurial orientation; EC: entrepreneurial climate; SP: sustainability actions performance
Finally, model fit assessment (Benitez et al., 2020) was studied using a two-tailed bootstrap approach to obtain all the appropriate measures of the standardized root mean square ratio, unweighted least squares discrepancy (dULS) and geodesic discrepancy (dG) that affect the estimated model (Qiu and Zhang, 2021). The results confirmed that our model remains below the HI99 percentiles, as shown in Table 5. This allows us to infer that the composites act within a nomological network rather than as individual manifest variables (Henseler, 2017). These circumstances enable us to confirm that the model studied is reliable and accurately represents the data.
Tests of model fit
| Value | HI99 | |
|---|---|---|
| Estimated model | ||
| SRMR | 0.071 | 0.080 |
| dULS | 0.767 | 0.988 |
| dG | 0.282 | 0.312 |
| Saturated model | ||
| SRMR | 0.067 | 0.074 |
| dULS | 0.684 | 0.839 |
| dG | 0.269 | 0.285 |
| Value | HI99 | |
|---|---|---|
| Estimated model | ||
| SRMR | 0.071 | 0.080 |
| dULS | 0.767 | 0.988 |
| dG | 0.282 | 0.312 |
| Saturated model | ||
| SRMR | 0.067 | 0.074 |
| dULS | 0.684 | 0.839 |
| dG | 0.269 | 0.285 |
Note(s): Model's bootstrapping (10.000 samples), two-tailed
Structural model
In the structural model, the VIF is also analyzed, showing scores below the threshold of 3 (Hair et al., 2019) (Table 2). In addition to the VIF, Table 6 displays the signs, magnitudes and significance of the path coefficients. After performing a one-tailed bootstrap with 10,000 samples, the importance of the path coefficients was assessed (Roldán and Sánchez-Franco, 2012), yielding t-statistics and confidence intervals that support the three hypotheses regarding direct causal relationships.
Mediation study
| Coefficient | t statistics | p values | Bootstrap 90% confidence interval Percentile | VAF | |||
|---|---|---|---|---|---|---|---|
| Total effect of ESI on SP | 0.661 | sig*** | 10.992 | 0.000 | 0.562 | 0.761 | |
| Direct effects | |||||||
| H1(+): c' | 0.339 | sig*** | 4.090 | 4.090 | 0.000 | 0.205 | 51.29% |
| a1 | 0.580 | sig*** | 8.735 | 8.735 | 0.000 | 0.465 | |
| a2 | 0.448 | sig*** | 6.414 | 6.414 | 0.000 | 0.328 | |
| a3 | 0.448 | sig*** | 6.862 | 6.862 | 0.000 | 0.342 | |
| b1 | 0.205 | sig* | 2.195 | 2.195 | 0.014 | 0.055 | |
| b2 | 0.287 | sig** | 2.400 | 2.400 | 0.008 | 0.083 | |
| Indirect effects | Point estimate | ||||||
| H2 (+): a1 x b1 | 0.119 | sig* | 2.096 | 0.018 | 0.032 | 0.218 | 18.00% |
| H3 (+): a2 x b2 | 0.129 | sig* | 2.250 | 0.012 | 0.035 | 0.224 | 19.52% |
| H4 (+): a1 x a3 x b2 | 0.075 | sig* | 2.080 | 0.019 | 0.020 | 0.136 | 11.35% |
| Total indirect effect | 0.322 | sig*** | 4.319 | 0.000 | 0.200 | 0.444 | 48.71% |
| Coefficient | t statistics | p values | Bootstrap 90% confidence interval Percentile | VAF | |||
|---|---|---|---|---|---|---|---|
| Total effect of ESI on SP | 0.661 | sig*** | 10.992 | 0.000 | 0.562 | 0.761 | |
| Direct effects | |||||||
| 0.339 | sig*** | 4.090 | 4.090 | 0.000 | 0.205 | 51.29% | |
| a1 | 0.580 | sig*** | 8.735 | 8.735 | 0.000 | 0.465 | |
| a2 | 0.448 | sig*** | 6.414 | 6.414 | 0.000 | 0.328 | |
| a3 | 0.448 | sig*** | 6.862 | 6.862 | 0.000 | 0.342 | |
| b1 | 0.205 | sig* | 2.195 | 2.195 | 0.014 | 0.055 | |
| b2 | 0.287 | sig** | 2.400 | 2.400 | 0.008 | 0.083 | |
| Indirect effects | Point estimate | ||||||
| 0.119 | sig* | 2.096 | 0.018 | 0.032 | 0.218 | 18.00% | |
| 0.129 | sig* | 2.250 | 0.012 | 0.035 | 0.224 | 19.52% | |
| 0.075 | sig* | 2.080 | 0.019 | 0.020 | 0.136 | 11.35% | |
| Total indirect effect | 0.322 | sig*** | 4.319 | 0.000 | 0.200 | 0.444 | 48.71% |
Note(s): Partial sequential mediation (20%<variance accounted for (VAF)<80%)***
Total direct and indirect effects were estimated using control variables, such as age, sector and size, which affect SP. Coefficient, t-statistics, p-values and percentiles were determined by a percentile bootstrap confidence interval of 90% (one tail) based on n = 10,000 subsamples
*/**/***: significant at p-value <0.05/0.01/0.001; ***Hair et al. (2014), VAF: variance accounted for
Figure 2 also shows the coefficient of determination (R2). This is the proportion of the variance in the dependent variable that the independent variables can explain. The dependent variables achieve moderate but sufficient predictive power.
The diagram illustrates the relationships between entrepreneurial strategic intentionality, entrepreneurial orientation, entrepreneurial climate, and sustainability actions performance. It includes labeled components such as entrepreneurial strategic intentionality, entrepreneurial orientation, entrepreneurial climate, and sustainability actions performance. Arrows indicate the directional flow and relationships between these components, with annotations showing the significance levels of these relationships.Structural model results. Note(s): ns/*/**/***: non-significant/significant at p-value <0.05/0.01/0.001. Source: Authors' own work
The diagram illustrates the relationships between entrepreneurial strategic intentionality, entrepreneurial orientation, entrepreneurial climate, and sustainability actions performance. It includes labeled components such as entrepreneurial strategic intentionality, entrepreneurial orientation, entrepreneurial climate, and sustainability actions performance. Arrows indicate the directional flow and relationships between these components, with annotations showing the significance levels of these relationships.Structural model results. Note(s): ns/*/**/***: non-significant/significant at p-value <0.05/0.01/0.001. Source: Authors' own work
Mediating effect
The mediation model was evaluated to assess ESI's potential positive spillover effects on SP. For the mediation analysis (Roldán, 2021), a one-tailed bootstrap analysis (10,000 samples) was performed, confirming the significance of each hypothesized indirect effect and indicating that indirect effects on SP operate differently, all of which are valid. To study the type and magnitude of the effect, we used the variance accounted for (VAF = indirect effect/total effect), which indicates the proportion of the total effect attributable to the indirect effect (i.e. the sum of the direct and indirect effects).
As shown in Table 6, although the VAFs for each indirect relationship did not meet the 20% threshold (Hair et al., 2014), they are close to it. It can be concluded that the sum of the indirect effects offers a value higher than 48%, so the impact of the indirect effects of the ESI variable on the SP variable is relevant.
Model's predictive power
Shmueli and Koppius (2011) evaluated the model's predictive performance using an out-of-sample test. Considering our sample size, four sections (K = 4) of 30 cases each (n = 30) were created. We followed the steps proposed by Shmueli et al. (2016) (Table 7): First step: all Q2predict values of the dependent variables must be positive and statistically significant (Q2predict > 0). This shows that partial least squares (PLS) prediction errors are smaller than in linear regression, confirming its greater predictive power. Second step: symmetry in the distribution of errors is verified. All root mean square error (RMSE) values are observed to be less than 1 (RMSE - PLS linear model (LM) < 1). Third step: The difference in RMSE errors should be negative for most indicators. The results indicate that the proposed model exhibits moderate predictive power (Levis and Boettcher, 1982), sufficient to forecast future observations accurately.
Predictive power assessment
| PLS-predict out-of-sample | Q2 predict | PLS-SEM_ RMSE | PLS-SEM_MAE | LM_RMSE | LM_MAE | Error Dif. RMSE PLS-LM | Error diff. MAE PLS-LM | Absolute values of skewness |
|---|---|---|---|---|---|---|---|---|
| Assumption | 0.146 | 0.931 | 0.762 | 0.912 | 0.734 | 0.019 | 0.028 | −0.654 |
| Proactivity | 0.203 | 0.903 | 0.745 | 0.950 | 0.780 | −0.047 | −0.035 | −0.407 |
| Trend | 0.317 | 0.836 | 0.687 | 0.862 | 0.699 | −0.026 | −0.012 | −0.312 |
| Autonomy | 0.201 | 0.903 | 0.696 | 0.901 | 0.709 | 0.002 | −0.013 | −0.220 |
| Recognition | 0.381 | 0.793 | 0.638 | 0.829 | 0.658 | −0.036 | −0.020 | −0.576 |
| Support | 0.374 | 0.799 | 0.640 | 0.796 | 0.636 | 0.003 | 0.004 | −0.585 |
| Time | 0.313 | 0.839 | 0.674 | 0.864 | 0.703 | −0.025 | −0.029 | −0.292 |
| ECS | 0.276 | 0.858 | 0.683 | 0.882 | 0.698 | −0.024 | −0.015 | −0.484 |
| ENS | 0.122 | 0.944 | 0.749 | 0.966 | 0.756 | −0.022 | −0.007 | −0.916 |
| SOCS | 0.260 | 0.867 | 0.705 | 0.864 | 0.707 | 0.003 | −0.002 | −0.469 |
| 1st. Step | 2rd. Step | 3nd. Step | ||||||
| PLS-predict out-of-sample | Q2 predict | PLS-SEM_ RMSE | PLS-SEM_MAE | LM_RMSE | LM_MAE | Error Dif. RMSE PLS-LM | Error diff. MAE PLS-LM | Absolute values of skewness |
|---|---|---|---|---|---|---|---|---|
| Assumption | 0.146 | 0.931 | 0.762 | 0.912 | 0.734 | 0.019 | 0.028 | −0.654 |
| Proactivity | 0.203 | 0.903 | 0.745 | 0.950 | 0.780 | −0.047 | −0.035 | −0.407 |
| Trend | 0.317 | 0.836 | 0.687 | 0.862 | 0.699 | −0.026 | −0.012 | −0.312 |
| Autonomy | 0.201 | 0.903 | 0.696 | 0.901 | 0.709 | 0.002 | −0.013 | −0.220 |
| Recognition | 0.381 | 0.793 | 0.638 | 0.829 | 0.658 | −0.036 | −0.020 | −0.576 |
| Support | 0.374 | 0.799 | 0.640 | 0.796 | 0.636 | 0.003 | 0.004 | −0.585 |
| Time | 0.313 | 0.839 | 0.674 | 0.864 | 0.703 | −0.025 | −0.029 | −0.292 |
| ECS | 0.276 | 0.858 | 0.683 | 0.882 | 0.698 | −0.024 | −0.015 | −0.484 |
| ENS | 0.122 | 0.944 | 0.749 | 0.966 | 0.756 | −0.022 | −0.007 | −0.916 |
| SOCS | 0.260 | 0.867 | 0.705 | 0.864 | 0.707 | 0.003 | −0.002 | −0.469 |
| 1st. Step | 2rd. Step | 3nd. Step | ||||||
Note(s): PLS_predict: K = 4; n = 30; 1st. Step: Q2 predict >0; 2nd. Step: error difference RMSE – PLS LM < 1 for most indicators; 3rd. Step: absolute value of skewness <1. Abbreviations: ECS: economic sustainability; ENS: environmental sustainability; SOCS: social sustainability; MAE: mean absolute error and PLS-LM: difference between the PLS-SEM model and the linear model (LM)
Fuzzy-set qualitative comparative analysis
The analysis of fuzzy set results begins by evaluating the consistency scores for the different variables, as these values must exceed 0.9 to ensure the validity of the model (Kaya et al., 2020).
The consistency scores (Table 8) show that ESI is necessary to achieve a high level of SP. However, the remaining conditions show consistency between 0.278 and 0.876, placing them below the cut-off value of 0.90, indicating that although they are not necessary conditions, they allow the combination to perform the factor configuration analysis (Kang and Shao, 2023). The negation analysis confirms these claims, as the absence of the above conditions yields a lower consistency score (<0.90) for the three solutions produced by fs-QCA. For this reason, the intermediate solution is selected for analysis.
Analysis of necessary conditions
| High | Low (negation) | |||
|---|---|---|---|---|
| Configurational element | Consistency | Coverage | Consistency | Coverage |
| ESI | 0.912898 | 0.907090 | 0.835168 | 0.283478 |
| ∼ESI | 0.278890 | 0.832019 | 0.726272 | 0.740146 |
| EO | 0.809432 | 0.935730 | 0.808986 | 0.319469 |
| ∼EO | 0.411322 | 0.863084 | 0.837251 | 0.600128 |
| EC | 0.876004 | 0.939503 | 0.813448 | 0.298016 |
| ∼EC | 0.345462 | 0.844262 | 0.834871 | 0.696970 |
| High | Low (negation) | |||
|---|---|---|---|---|
| Configurational element | Consistency | Coverage | Consistency | Coverage |
| ESI | 0.912898 | 0.907090 | 0.835168 | 0.283478 |
| ∼ESI | 0.278890 | 0.832019 | 0.726272 | 0.740146 |
| EO | 0.809432 | 0.935730 | 0.808986 | 0.319469 |
| ∼EO | 0.411322 | 0.863084 | 0.837251 | 0.600128 |
| EC | 0.876004 | 0.939503 | 0.813448 | 0.298016 |
| ∼EC | 0.345462 | 0.844262 | 0.834871 | 0.696970 |
Note(s): ESI: entrepreneurial strategic intentionality; EO: entrepreneurial orientation; EC: entrepreneurial climate
The results of the fuzzy-set analysis are presented, along with three solutions that yield a high SP level (Table 9). Black circles (●) indicate the presence of a condition, crossed circles (⊗) indicate its absence and blank spaces indicate an indeterminate state. The overall consistency is 0.878, and the coverage is 0.962, both above the minimum standard (0.75), confirming the explanatory power and consistency of the configurations (Ragin, 2006). All solutions showed high consistency, demonstrating their reliability. Coverage reflects the degree to which they explain variations, as in regression or SEM. The first configuration has the highest coverage (0.912) and high consistency (0.907), making it the best for achieving high SP. The second also exhibits high consistency (0.957) and coverage (0.777), revealing that the EO and EC combination is key. The third, less consistent, is characterized by the absence of EO and EC and the relevance of ESI. Even though this third configuration shows somewhat lower coverage than the other configurations, its consistency is the highest of the three. This suggests that, although its explanatory power is reduced to a smaller number of cases, it remains a highly reliable and feasible way to achieve high levels of SP.
Configurations for achieving high levels of SP
| Solution | |||
|---|---|---|---|
| 1 | 2 | 3 | |
| ESI | ● | ||
| EO | ⊗ | ● | |
| EC | ⊗ | ● | |
| Consistency | 0.907090 | 0.860611 | 0.957801 |
| Raw coverage | 0.912898 | 0.306230 | 0.777416 |
| Unique coverage | 0.129993 | 0.021547 | 0.0221567 |
| Overall solution consistency | 0.878853 | ||
| Overall solution coverage | 0.962191 | ||
| Solution | |||
|---|---|---|---|
| 1 | 2 | 3 | |
| ESI | ● | ||
| EO | ⊗ | ● | |
| EC | ⊗ | ● | |
| Consistency | 0.907090 | 0.860611 | 0.957801 |
| Raw coverage | 0.912898 | 0.306230 | 0.777416 |
| Unique coverage | 0.129993 | 0.021547 | 0.0221567 |
| Overall solution consistency | 0.878853 | ||
| Overall solution coverage | 0.962191 | ||
Note(s): ESI: entrepreneurial strategic intentionality; EO: entrepreneurial orientation; EC: entrepreneurial climate; SP: sustainability actions performance
Discussion
This study examined how the components of CES affect performance in sustainability actions. It analyzed the effects of ESI on SP, both directly and through EO and EC. Beyond previous research that primarily linked corporate entrepreneurship to innovation or financial outcomes, our findings place SP at the core of CES's strategic architecture, rather than viewing it as a peripheral or incidental outcome.
The focus of our work is undoubtedly aligned with recent studies that highlight the fundamental role of entrepreneurial processes within firms in achieving sustainability goals. This is the case with Provasnek et al. (2017), who emphasize the importance of EO in this context. More recently, studies by Ammirato et al. (2025), Ruiz-Ortega et al. (2025) and Silvério et al. (2025) have demonstrated that firms' sustainability performance is not solely the result of isolated entrepreneurial processes.
Comparing the proposed model with fs-QCA, it was confirmed that ESI favors business involvement and commitment (Kreiser et al., 2021) in identifying and exploiting opportunities that generate SP. From these actions, the remaining elements that comprise the firm's internal environment will be derived, represented by the EO and the EC (Ireland et al., 2009; Ireland and Webb, 2009). ESI, manifested in flexibility, clarity and commitment, translates its external facet, giving rise to internal elements represented by EO and EC. These conditions within the EC include factors such as management support, reward systems, work autonomy, available time and organizational boundaries, as noted by Kearney and Meynhardt (2016) and Kreiser et al. (2021) and have a positive effect on sustainability actions.
ESI, therefore, has a strong direct effect on SP. This suggests that sustainability performance is unlikely to emerge without explicit and consistent strategic business intent. In this sense, ESI functions as a bottom-up strategic driver that integrates sustainability considerations into opportunity recognition, strategic renewal and long-term resource allocation. Rather than being merely aspirational, ESI demonstrates performance capabilities that translate into tangible sustainability outcomes even before EC and EO fully intervene. By showing the strong direct effect of ESI on SP, alongside only partial mediation through EO and EC, we contribute to the literature that advocates for greater systemic integration of sustainability actions in firms (Crossley et al., 2021).
EO, as manifested through risk-taking actions by the firm and its members, a tendency toward innovative activities and a proactive attitude, has a positive and direct influence on the performance of sustainable actions. This finding corroborates the existing literature and can be substantiated by the fact that both entail strategic capabilities (Akomea et al., 2023).
Furthermore, the results confirm the mediating roles of both EO and EC in ESI's influence on SP, although their effect is more modest. This reinforces our research approach, which posits that ESI has a positive, direct effect on SP. In this paper, the findings indicate that the multiple sequential mediation approach yields lower values than direct mediation, which may be due to organizations' difficulty in aligning the three variables, ESI, EO and EC, in the pursuit of SP.
The fs-QCA results add further nuance by demonstrating that high SP can be achieved through multiple configurations of ESI, EO and EC. The analyses provide compelling evidence that reinforces and refines the PLS-SEM findings. The fs-QCA analysis reveals two configurations that can lead to high SP. The first solution emphasizes ESI's presence through flexibility, clarity and commitment. The second solution suggests that EO and EC also foster high levels of SP, with the presence or absence of ESI not determining the level. This is undoubtedly a significant finding, as it highlights two potential combinations of compatible CES elements that could improve SP.
Theoretical implications
Our research and findings advance knowledge in the field of CES. In our work, we integrate theoretical and empirical comparisons to examine the reality of CES and the potential for sustainability improvements. Specifically, it is evident that the outcomes of sustainability initiatives are not the result of isolated entrepreneurial processes but rather of the coherent interaction among their components. Thus, our study offers a systemic and integrative explanation of how the CES translates into organizational outcomes.
Regarding the CES theory, our work expands it to account for how ESI is articulated as a fundamental strategic element through which sustainability actions are integrated into processes of recognizing new opportunities and strategic repositioning. The results of our work demonstrate how, rather than considering sustainability actions as an external constraint or as a mere reputational outcome for the firm's external environment, in the case of ESI, it can be considered as a driver capable of promoting the search for business opportunities in the medium and long term, with the creation of economic, social and environmental value. Our results are therefore in line with the latest calls for work in the field of entrepreneurship, where studies such as those by Karadayı et al. (2025) and Di Vaio et al. (2022) highlight the need to reconceptualize this reality as a phenomenon that is also capable of addressing the major challenges facing society today. By confirming the direct effect of ESI on SP, we contribute to the literature calling for greater systemic integration of sustainability actions within firms.
No less important are this study's contributions to a better understanding of CES at the configurational and multi-level levels. This is due to the empirical validation of the mediating effect of EO and EC. Previous work (e.g. Kuratko et al., 2021) highlights the need to understand better the internal mechanisms through which firms' entrepreneurial actions translate into organizational outcomes. In this study, the proposed model demonstrates that the outcomes of sustainability actions are not solely determined by ESI but are enhanced when ESI, EO and EC are coordinated. This finding reinforces the perspectives of configuration theory within CES (Kreiser et al., 2021) and addresses the most recent calls for more systemic explanations of business outcomes. These findings refine the view of CES as a purely sequential process. Our data show that ESI acts as a higher-level resource, influencing sustainability actions directly and indirectly. Top management can shift focus toward sustainability even if EO and EC are limited, while EO and EC amplify and stabilize the impact of strategic intent. In this sense, CES emerges not only as a systemic, fully aligned architecture but also as an adaptive configuration in which strategic intent and entrepreneurial mechanisms coevolve.
On the other hand, the combination of symmetric approaches, through PLS-SEM, and asymmetric approaches, through fs-QCA, contributes to the debate on the potential equifinality of entrepreneurship research. Thus, the results of the fs-QCA analysis indicate that better sustainability outcomes are possible across different configurations of the CES reality. Specifically, one solution emphasizes the primacy of ESI, while another highlights the joint presence of EO and EC, regardless of strong strategic intent. This finding, rather than being considered a contradiction, enriches research on the different configurations of entrepreneurial behaviors (Kusa et al., 2021) and supports the idea that the outcomes of sustainability actions may result from diverse internal entrepreneurial architectures within organizations. This is, therefore, an element to be considered when considering CES as a strategic reality of a combinatorial nature.
Finally, our study contributes to redefining the theoretical limits of CES by proposing a hybrid mechanism in which ESI exerts a strong direct influence on SP, while EO and EC act as complementary, though only partial, mediators. Thus, contrary to the positioning of the results of usual sustainability actions as non-priority or second-level in the firm, sustainability is now positioned as a strategic result for the firm as well, which is in line with current debates on the need to align the entrepreneurial dynamics of firms with responsible value creation (Karadayı et al., 2025).
Practical implications
The results have practical implications for firms seeking to improve their sustainability. Specifically, they aim to influence the mechanisms identified in the empirical model that act as key enablers of sustainability initiatives.
Promoting less rigid organizational structures that enable rapid reallocation of resources and priorities toward emerging sustainable initiatives would increase flexibility, enabling the creation of temporary cross-functional teams to explore opportunities and redefine objectives. Strategic clarity would foster transparent, consistent communication on sustainability objectives and their integration into corporate strategy, helping staff identify opportunities. This process can be reinforced by establishing measurable performance indicators and designing road maps to guide the implementation and monitoring of these initiatives.
Organizational commitment is strengthened when management actively supports these initiatives by participating in committees, funding actions and allocating resources to sustainable innovation projects and to sustainability-focused training programs such as hackathons, idea contests and cross-functional initiatives. Visible support from management reduces the perceived risk associated with innovation by creating channels for employees to present ideas to higher levels, implementing intrapreneurship programs and protecting innovative initiatives. In this regard, the role of middle management is fundamental to the proper transmission of the ESI and its translation into concrete operational practices, as they serve as conduits of organizational commitment.
Giving employees autonomy allows them to explore and develop sustainable ideas, fostering proactive behaviors associated with EO and enabling them to dedicate time to it. Additionally, reward systems or public recognition should be designed to incentivize participation in sustainability projects, recognizing both results and innovative efforts, even when these involve uncertainty or failure.
Managers should both prioritize sustainability in their strategy and foster an entrepreneurial environment to support ongoing initiatives. Our analysis shows that firms can achieve strong sustainability performance through various combinations of high ESI, EO and EC, enabling approaches tailored to their unique situations and resources.
Limitations and future lines of research
Like all research, this study has limitations. The first is organizational bias, as it is based on cooperatives, raising the question of whether the results would differ under other legal forms. In addition, these types of firms have a significant presence in the primary sector, specifically in agriculture and livestock, which could make it misleading to extrapolate entrepreneurship data to other types of organizations and productive sectors.
The second is the geographical context, as the population comes from Spain, which requires caution when generalizing to other areas.
Regarding future lines of research, the cross-sectional nature of the study suggests a longitudinal design, which is the only way to provide more robust evidence of causal relationships. Analyzing results over time would enable a more accurate examination of these relationships. Furthermore, this study examines the relationship between entrepreneurial intent and sustainability in an organization where both participation and decision-making are highly distinctive; in other words, it sheds light on the co-participation of employees and employers in managing the firm. We emphasize here that the organizations studied are governed by principles of co-governance and democracy, which can influence both entrepreneurial intent and the organizations' sustainability outcomes.
Conclusions
This study shows how ESI plays a key role in improving the results of sustainability actions. In other words, firms that combine flexibility, clarity and commitment in their entrepreneurial strategy are more likely to translate opportunity-seeking behavior into tangible performance, including sustainability.
The results also show how EO and EC act as complementary internal elements, reinforcing the role of ESI. Sustainability performance does not arise from isolated entrepreneurial behaviors, but from the consistent alignment between strategic intent, behavioral stance and organizational infrastructure. The results of sequential mediation indicate that achieving sustainability outcomes requires internal consistency among these components of CES.
It is also necessary to highlight that the study's configurational analysis identifies distinct paths that can lead to better sustainability outcomes. While it is true that ESI is a powerful catalyst, the combined presence of EO and EC yields better results, reinforcing the idea that firms can achieve sustainability not through a single prescriptive model but through internally coherent entrepreneurial architectures.
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