Sustainable development through frugal innovation: the role of leadership, entrepreneurial bricolage and knowledge diversity

Along with rich knowledge, knowledge diversity is required to spur innovation (Rodan and Galunic 2004; Felin and Hesterly 2007). Diversified knowledge represents diverse ideas that encourage a different understanding of the same problem (Zhao et al. 2021; p. 889); thus, it is hard to imitate and transfer (Hu and Randel 2014). DKS serves as a source of creativity (Wang et al. 2021). As it refers to the amalgam of different types of expertise, contextual differences, idea disparity, and various processes for different aspects of knowledge, DKS offers diverse possibilities for designing effective innovation activities (Tsoukas 1996; Iqbal and Piwowar-Sulej 2023a). In particular, multidisciplinary innovation is highly reliant on DKS (Purkayastha et al. 2021). FI represents such types of innovation (Dabić et al. 2022), where firms endeavour to offer value-added product and services at low cost by consuming minimal resources in collaboration with local partners (Wooldridge 2010).

FI is classified into three dimensions: FF, FC, and FE (Rossetto et al. 2017, 2023). FF focuses on the core function of a product aligned with the socioeconomic needs of the market (Pisoni et al. 2018). It emphasises product design (e.g. affordable, defeatured, and simple), product functioning (e.g. reduced complexity, ease of use, and removal of non-essential functions), and product performance (e.g. good enough, maximises value, and maintains quality) (Rossetto et al. 2023). FC concerns firms’ efforts to offer value-added products by rearranging organisational resources at a substantially lower operational level (Brem and Wolfram 2014). Pisoni et al. (2018) define FE as indispensable for the development of frugal solutions based on sustainable and eco-friendly processes in collaboration with local partners, such as end users, producers, and other stakeholders, which meet customers’ social-environmental and sustainable needs. FF’s socio-environmental sustainability attribute focuses on both environmental and social consumption and sustainable production (von Janda et al. 2020; Albert 2022; Iqbal and Piwowar-Sulej 2023b). Thus, such innovation requires the integration of knowledge diversity, which refers to the ways in which cost (e.g. initial cost, cost of ownership, and material usage) can be reduced, customers’ functional needs can be met (maintaining a user-friendly product even though its functions are reduced), and high-quality and environmentally friendly products can be secured (Du 2021; Iqbal and Piwowar-Sulej 2023a). DKS, a constitution of disparate ideas, various expertise, and contextual differences, can provide numerous possibilities for designing effective FI in terms of FF, FC, and FE.

Internal DKS concerns the different expertise and insights offered by a firm’s employees (Cummings 2004; Iqbal and Piwowar-Sulej 2023a). In a dynamic market, DKS is viewed as beneficial for introducing value addition (Rodan and Galunic 2004). Internal DKS ensures efficient information acquisition and dissemination among employees within and across units (Sheng et al. 2011), mandated for effective resource rearrangements and increasing the firm’s operational efficiency (Sosa 2011). Under internal DKS, firms can easily employ disruptive technologies to innovate, while using minimal resources (Wu and Peng 2022). Internal DKS, which results from employees’ job-related skill heterogeneity, benefits team-level outcomes in terms of collaboration, creativity, and performance (Tsai and Hsu 2018). It is valuable for strengthening inter-firm collaboration (Lee et al. 2020), enabling firms to balance diverse stakeholder needs and ultimately spur FF and FE (Rossetto et al. 2017). Therefore, a positive influence of internal DKS on firm’s FC, FF, and FE is likely.

Since FI is promoted for consumers with limited resources, the importance of external DKS is irrefutable. External DKS focuses on the knowledge diversity that comes from stakeholders outside the organisation (Felin and Hesterly 2007). From the company’s viewpoint, external DKS is not only a source of product-related information but also technology information (including eco-friendly solutions), market situations, competitors’ competence level, and solutions to improve partnerships with local firms in the operational process (Ye et al. 2016). External DKS that goes beyond firm cognition and passes through social boundaries is viewed as useful in the innovation process (Tsai and Hsu 2018). It enhances firms’ awareness of societal changes (Iqbal and Piwowar-Sulej 2023a), which keeps them ahead of their competitors in the FF and FE arenas, and facilitates firms’ knowledge of limited resources, market intelligence, legitimacy, and enhanced risk tolerance (Xuecheng and Iqbal 2022),which is vital for spurring FE and FC (Rossetto et al. 2023).

External DKS also unravels potential new business partners who might play a crucial role in FC and FF by offering modern technology (Zhang et al. 2019). Using external DKS, firms come across valuable ideas and novel approaches, and employ disruptive technologies to reduce their FC and enhance their FF (Sheng et al. 2011). External DKS, in the form of quality relationships with suppliers, positively affects firms’ operational costs and on-time delivery of quality raw materials and services. Through relationships with competitors, it enables firms to cope with implicit collusion and promote inter-firm collaboration (Li et al. 2014), which is mandatory for spurring FE. External DKS from diverse partners, such as universities and research institutes, also offer new knowledge that can be employed in process and product innovation (Fischer et al. 2021) to respond to consumers’ frugal lifestyles. It helps firms understand different local partnerships, which ultimately fosters open innovation processes and drives enhanced financial and operational efficiency, aligned with the socio-environmental needs of consumers (Iqbal and Piwowar-Sulej 2023b). Therefore, a positive impact on FF, FC, and FE is expected.

Considering the investment of time, energy, and fear of a loss of competitive advantage attached to diversified knowledge, employees and other stakeholders may hesitate to share their unique knowledge (Tønnessen et al. 2021). In such circumstances, leaders, especially sustainability-oriented ones, can play a vital role in encouraging different actors to share heterogeneous knowledge based on intrinsic stimulants (Janowicz-Panjaitan and Noorderhaven 2009). The appearance of DKS may be justified based on SET, which argues that positive organisational practices that equip employees with the necessary resources engender favourable employee behaviours (in this case, internal and external DKS) (Blau 1964).

The literature shows that the important enablers of internal knowledge sharing are empowerment (Abukhait et al. 2019) and psychological safety (Fischer et al. 2021), fostered by SL practices. Sustainability-oriented leaders also design creative work environments in which employees are free to share ideas, thoughts, and feedback (Iqbal and Piwowar-Sulej 2023a). Personal experience and training also play vital roles in DKS (Hu and Randel 2014). Sustainability-oriented leaders offer training programs to employees to develop their knowledge. Moreover, they promote employees (Avery and Bergsteiner 2011; Gerard et al. 2017) so that they have access to diverse knowledge, and enable the integration of knowledge assets located in different units within organisations (Tsai et al. 2014; Chuang et al. 2016). Thus, sustainability-oriented leaders invest in and receive returns from employees who invest in themselves and receive further returns from leaders.

However, DKS is based on reciprocal exchanges between actors who share knowledge. Trust and strong social capital (Brockmann and Anthony 2002; Pérez-Luño et al. 2011; Hu and Randel 2014) are required for both internal and external DKS. Trust prevents knowledge-hiding behaviours (Fischer et al. 2021). In turn, social capital is expected to encourage tacit knowledge sharing because of high-quality relationships among individuals (Janowicz-Panjaitan and Noorderhaven 2009). Sustainability-oriented leaders provide a shared vision, act ethically, build a culture of trust, are socially and environmentally responsible, focus on two-way communication, and develop strong amicable relations with employees and other stakeholders (Gerard et al. 2017). Moreover, the exchange of knowledge itself stimulates people to engage in knowledge sharing activities (Quigley et al. 2007).

Thus, sustainability-oriented leaders’ true interests in both employees and external stakeholders are highly likely to foster both internal and external DKS, integrate a firm’s knowledge base with external heterogeneous knowledge, and lead to high innovation performance (Ferraris et al. 2020). Therefore, the following hypotheses were formulated.

This study emphasises that DKS is essential for three dimensions of FI because it fosters problem-solving, creativity, risk mitigation, and resource optimisation. By leveraging a diverse range of perspectives and expertise, firms can develop innovative solutions that address sustainable development challenges and create value with limited resources for low-income customers. Based on SET, this study argues that people tend to reciprocate positive leaders’ behaviours by engaging in knowledge sharing and helping other company stakeholders. Sustainability-oriented leaders maintain lasting relationship with diverse stakeholders (Avery and Bergsteiner 2011; Dalati et al. 2017), enhancing both internal and external DKS. However, a relationship between SL and DKS exists under other conditions.

Effectuation theory emphasises the use of existing resources to create opportunities and shape outcomes (Sarasvathy et al. 2014). It encourages entrepreneurs to be adaptable and start with what they have, rather than focus solely on what they want to achieve. It has been shown to be particularly relevant in uncertain environments (Rapp 2022), such as when facing resource-constraints.

EB is the concept of ‘making something out of nothing’ (Wang et al. 2021), which is in line with effectuation theory. It is essential for SMEs because they usually operate under resource constraints and burdensome institutional environments, and must concentrate on what they have to offer in services and products (Simba et al. 2021). EB also affects a company’s knowledge stock, creativity, and innovation (including FI) (Iqbal et al. 2022). Underutilised resources can be recombined into productive resources. Knowledge is also an important resource. In the bricolage process, leaders scan available knowledge stocks and networks for their possible effects (Sarasvathy 2001). Bricoleurs also use their business networks as resources at hand (Chang and Webster 2019) and encourage employees and other company stakeholders to practice constant communication (Wang et al. 2021). The latter should bring opportunities for experimentation and increase the chance of developing novel combinations through knowledge exchanges between parties. Integration of parallel knowledge bases generates new knowledge under the umbrella of bricolage (Boxenbaum and Rouleau 2011). Bricolage also empowers employees to take initiative and contribute their ideas and insights to problem-solving and innovation efforts. Bricoleurs create an environment where employees feel encouraged to share their knowledge and expertise openly, leading to increased collaboration and learning within the organisation (Abukari et al. 2024). Hence, we posit that the effect of SL on DKS intensifies in the presence of higher bricolage, yielding the following hypotheses.

Based on the above discussion, the following research framework is adopted (see Fig. 1).

In Poland, SMEs are defined as firms with up to 250 employees (PARP 2021), similar to that in the European Union. As of 31 December 2022, the Polish SME sector covered 2255 companies and employed almost 6.8 million people, or 67.8% of the total number of employees in all businesses. In 2019, the majority of investments in Poland were financed by SMEs’ own funds (68%); funds from foreign sources were used in nearly 9.7% of investments, and domestic loans were used in 9% (PARP 2021). Most SMEs operate in the service industry (53.0%); nearly 21.6% operate in the trade industry, 15.5% in construction, and 10.0% in the manufacturing industry.

To ensure a sufficiently acceptable sample size, we ran the F test with an a priori power analysis in the G*Power application on the basis of four predictors: 0.15 as effect size, 0.05, significance level, and 0.80 as statistical power (Faul et al. 2009), and found that 85 was the required minimum number of responses to deliver reliable results. Moreover, the extant literature reports an average response rate of 35.50%, with a standard deviation in survey studies of social science (Baruch and Holtom 2008). Therefore, to ensure the minimum sample size requirements, the authors adopted a convenience sampling approach in the absence of a sampling frame and contacted 486 SME representatives. By leveraging networks, surveys were conducted through face-to-face meetings and phone calls. The SMEs’ representatives voluntarily participated in this study, and no sensitive data were required. During the data collection process, the authors adopted a time-lagged approach as a procedural remedy to cope with common method bias in which SMEs’ representatives rated both predictors and outcome variables at two points in time. The SMEs’ representatives were also requested to share three-digit arbitrary codes to match their responses in the two stages. At time T1, the SMEs’ representatives were asked to rate SL, EB, and internal and external DKS. At this stage, we had collected responses from 311 SME representatives. After one month, these 311 respondents were asked to evaluate the FF, FC, and FE practices in their respective firms and share their demographic information. Finally, the authors received 237 completed survey forms from SMEs representatives. After data screening, 223 valid survey forms remained. Thus, the response rate in this study was 45.88%.

Regarding demographics, male participants (n = 169, 69.29%) dominated the study compared to female participants (n = 54, 30.705). Most respondents (n = 108, 48.43%) were 25–35 years old, followed by those aged 36–45 years (n = 43, 19.28%); 33 and 32 participants were in the 46–55 range and < 25 years, respectively. Only seven respondents were older than 55 years. Most participants (n = 98, 43.94%) held a master’s degree, followed by those who had completed secondary education (n = 79, 35.43%). In this study, 56 bachelor’s or engineer’s degree holders participated. Most respondents (n = 198, 77.78%) worked in specialist positions (mainly customer service and sales specialists) at their respective firms.

The survey form was first prepared in English and back-translated into Polish to ensure accuracy. As previous studies had raised concerns about higher Likert scales in terms of cognitive constraints and reduced data quality (Robinson 2018), we adopted a five-point Likert scale ranging from strongly disagree to strongly agree.

The 15-item SL was adopted from McCann and Holt (2010). This measurement scale covers attributes such as credibility, persuasiveness, systematic thinking, adaptability, passion, change orientation, mentoring, and environmental and social consciousness. Iqbal and Piwowar-Sulej (2023c) has claimed validity of this scale in the context of Chinese manufacturing firms. The 5-item scale for external DKS and the 3-items scale for internal DKS were adopted from Ye et al. (2016) and Tsai et al. (2014), respectively. These two measurement scales were found to be highly reliable by Du (2021). SMEs rated FF, FC, and FE based on three items adopted from Rossetto et al. (2017). Finally, EB was measured using the 9-items scale from Davidsson et al. (2017). Appendix A presents all measurement items of the SL, EB, FF, FC, FE, and internal and external DKS.

Following previous recommendations (Iqbal and Piwowar-Sulej 2023; Lei et al. 2021), we included firm age, ownership type, and firm size as control variables to cope with variances across firms that may influence FI.

The explanatory nature and complexity of the framework and the presence of a moderator were sufficient justifications for applying the PLS-SEM methodology in this study (Mai et al. 2021). The application of PLS-SEM analysis requires the examination of both measurement and structural models. The measurement model focuses on the relationship between the indicators and construct. An analysis of the structural model revealed the relationship between the constructs in the research framework. Moreover, PLS-SEM requires the evaluation of the measurement model prior to structural model assessment (Ringle et al. 2020). We employed SmartPLS v.3.0 to conduct the PLS-SEM analysis, and the Statistical Package for Social Sciences (SPSS) version 24 for data screening, descriptive analysis, and demographic analysis. We also conducted a confirmatory factor analysis to assess the distinctive nature of the variables. The proposed model fit was evaluated on the basis on chi squared (χ2), goodness of fit index, comparative fit index (CFI), Tucker-Lewis index (TLI), root mean square error of approximation (RMSEA) values, and standardised root mean square residual (SRMR).

After data collection, we conducted data screening to examine the positions of missing values, outliers, normality, and common method bias. All items in the online survey form were checked before submission. This ensured the absence of missing values in the dataset. To determine potential outliers, we examined both univariate and multivariate outliers. The Z-scores of the eight cases were > 3.29, which presented them as univariate outliers. Therefore, eight responses were excluded from the dataset. The Mahalanobis test revealed the presence of six multivariate outliers. Therefore, the dataset contained 223 valid and reliable responses for further analysis. Considering the insensitive nature of Harman’s factor, the correlation matrix procedure (Bagozzi et al. 1991) was run to diagnose any common method bias in the current dataset. According to Harman’s one-factor test, the first factor accounted for only 20.56% of the total variance (less than 50%). This test confirms the absence of common method bias (Podsakoff 2003). The correlation matrix reveals that the highest correlation between any two items was 0.86 < 0.90. Therefore, both tests reveal common method bias as a non-issue for this study.

Descriptive analysis further revealed that the skewness values of all four continuous variables ranged from − 0.718 to + 0.055. The kurtosis values of SL, EB, FF, FC, FE internal, and external DKS are − 0.799, -0.737, -0.756, -0.538, -0.741, 0.640, and − 0.291 respectively. Skewness and kurtosis values are found within ± 3 range, which clearly indicates univariate normality (DeCarlo 1997). The present dataset also possesses multivariate normality because both Mardia’s kurtosis (β = 52.841, ρ < 0.05) and skewness (β = 14.679, ρ < 0.05) are significant.

In this study, the confirmatory factor analysis revealed that the proposed seven-factor model (SL, EB, FF, FC, FE, internal and external DKS) had a better fit (Chi square = 2365.432, CFI = 0.969 > 0.95, TLI = 0.973 > 0.95, RMSEA = 0.061 < 0.070, and SRMR = 0.076 < 0.080) than other alternative models.

All continuous variables were collected using a five-point Likert scale. The mean value indicates the low-, moderate-, and high-level presence of a variable with the value of 2.99, 3–3.99, and greater than 4, respectively (Sekaran and Bougie 2016). The mean values of SL, internal DKS, FF, FC, FE, and EB were 4.063, 4.139, 4.065, 4.222, 4.252, and 4.219, respectively, all greater than 3.99 (Table 1), indicating a high level of presence for these four continuous variables among Polish SMEs. However, external DKS (M = 3.949) was moderate.

SL, internal DKS, external DKS, FF, FC, FE, and EB were reflective of nature. For the reflective construct, the measurement model analysis focuses on indicator reliability, internal reliability, and construct validity. A factor loading value greater than 0.50 is the sign of acceptable indicator reliability. In this study, only one SL item was removed from the construct because its loading was < 0.50. The factor loading values of all items of the SL, internal DKS, external DKS, FF, FC, FE, and EB were in the range of 0.662–0.921. Therefore, all four reflective constructs have acceptable indicator reliability.

The composite reliability values of SL, EB, internal DKS, external DKS, FF, FC, and FE were 0.943, 0.945, 0.901, 0.932, 0.909, 0.851, and 0.870, respectively (Table 1), greater than 0.70, and signifying acceptable internal reliability. Acceptable construct validity requires an average variance extracted (AVE) value greater than 0.50 and factor loadings greater than 0.70. The AVE values of SL, EB, internal DKS, external DKS, FF, FC, and FE were 0.605, 0.721, 0.753, 0.735, 0.769, 0.656, and 0.691, respectively (Table 1). Therefore, all the reflective constructs had sufficient convergent validity.

According to the Fornell–Larcker criterion (Fornell and Larcker 1981), acceptable discriminant validity of a construct requires the square root of its AVE to be greater than its interconstruct correlation values. The square roots of the AVE values of SL, EB, and internal and external DKS were higher than their respective inter-construct correlation values (see Table 1). Therefore, all the reflective constructs had acceptable discriminant validity. Moreover, inter-construct correlation values revealed positive relationships between all variables.

The structural model analysis disclosed a lower impact of SL on internal DKS (β = 0.248, ρ < 0.05) compared with external DKS (β = 0.324, ρ < 0.05). However, both the results were statistically significant. The path analysis confirmed that the product of path coefficient from SL to internal DKS (0.248) and from internal DKS to FF (0.389) is significant and positive (β = 0.097, ρ = 0.024 < 0.05) (Table 2). This indicates that SL significantly and indirectly affects FF through internal DKS. The current empirical findings also offer support regarding indirect impact of SL on FC through internal DKS (β = 0.115, ρ = 0.001 < 0.05). Therefore, H1a and H1b are supported. Nevertheless, the internal DKS does not significantly affect FE (β = 0.203, ρ = 0.06 < 0.05) and SL does not indirectly affect FE through internal DKS (β = 0.050, ρ = 0.0130 < 0.05) (Table 2). Therefore, H1c is rejected.

The path analysis concluded with a significant positive impact of external DKS on FF (β = 0.292, ρ < 0.05), FC (β = 0.363, ρ < 0.05) and FE (β = 0.566, ρ < 0.05). The product of path coefficient from SL to external DKS (β = 0.324) with path coefficients from DKS to FF (β = 0.292) is significant and positive (β = 0.095, ρ = 0.015< 0.05). The current findings also confirmed the indirect impact of SL on FC through external DKS (β = 0.118, ρ = 0.029< 0.05). The empirical findings also unravelled the significant mediating impact of external DKS on the relationship of SL with FE (β = 0.183, ρ = 0.05) (Table 2). This implied that SL indirectly influenced FF, FC, and FE via external DKS. Therefore, H2a, H2b, and H2c are supported.

Regarding the moderating role of EB, we posited that the effect of SL on both internal and external DKS increases with increasing EB values. The results in Table 2 show that the interactive term of SL and EB significantly influences external DKS (β = 0.087, ρ = 0.001< 0.05). This indicates that the positive impact of SL on external DKS increases with increasing EB levels. Thus, H3b was supported. Yet, the increasing level of EB does not affect the ‘SL-internal DKS’ relationship (β = 0.046, ρ = 0.174< 0.05) (see Table 2). Therefore, EB did not moderate the effect of SL on internal DKS and H3a was rejected.

First, the study responds to the call by Hossain (2021); Iqbal and Piwowar-Sulej (2023b) to explore the antecedents of FI. Our findings regarding the role of DKS in FI enrich the literature on knowledge sharing as an antecedent of innovation. Prior research indicates that knowledge sharing is crucial for innovation (e.g. Castaneda and Cuellar 2020; Tønnessen et al. 2021). Other studies have emphasised the value of DKS in innovation processes (Purkayastha et al. 2021). These findings support Ferraris et al.’s (2020) argument that comprehensive innovation requires a combination of various internal and external perspectives. However, the present study not only distinguishes between internal and external DKS but also focuses on a specific type of innovation, FI, and its elements, such as FF, FC, and FE.

Second, by investigating the antecedents of the three elements of FI, this study contributes to a relatively limited body of research in this area (Shehzad et al. 2023). The examination of the role of both internal and external DKS in stimulating FI expands upon previous research that primarily focused on knowledge sharing within organisations (e.g. Arsawan et al. 2022). Weyrauch and Herstatt (2017) argue that the effective creation and implementation of FI is based on relevant cost reductions, focus on core functionalities, and optimised performance levels. We show that social and environmental sustainability (FE) reflect FI as well (Shehzad et al. 2023). As FI ‘can be deemed as a metaparadigm, which engenders an entirely novel way of thinking about innovation and value creation’ (Kaur 2020; p. 1), a combination of diversified knowledge is required to create ideas related to the aforementioned FI requirements. This study reveals that to ensure that an organisation produces FF and FC, a highly diversified knowledge base resulting from collaboration within the company and with external stakeholders is necessary. This supports the results obtained by Shehzad et al. (2023) regarding the association between knowledge-management processes (including knowledge sharing) and the two elements of FI (FF and FC). However, our empirical analyses also demonstrate that FE, which is related to social and environmental sustainability, can be achieved through knowledge exchange with external stakeholders. This finding contradicts that of Shehzad et al. (2023) who found no association between knowledge sharing and FE. Moreover, our results may indicate a lack of awareness about social and environmental needs among employees of the surveyed SMEs as a reason for the non-significant impact of internal DKS on FE. The lack of employees’ intrinsic motivation and environmental knowledge has been found to be a crucial source of Polish SMEs’ environmental entrepreneurship resistance (Pierscieniak et al. 2023). Another possible reason is the conceptualisation of FE, where firms are highly concerned about the socio-environmental aspects of any innovation (Hossain 2021; Iqbal and Piwowar-Sulej 2023a), about which external stakeholders could offer authentic knowledge.

Third, by demonstrating that an emerging leadership style, SL, is effective in stimulating both types of DKS, this study shows the positive impact of different leadership styles, such as knowledge leadership (Zhang and Cheng 2015) and empowering leadership (Lee et al. 2014), on knowledge sharing within organisations (associated with internal DKS in this study). Since SET has been used to explain how leaders enhance knowledge sharing, this study adds to the literature on the application of this theory in research on innovation (Muller and Peres 2019). Sustainability-oriented leaders equip their subordinates with resources, such as knowledge, trust, psychological safety, and a creative work environment based on open communication (Gerard et al. 2017; Iqbal and Piwowar-Sulej 2023). In these circumstances, social behaviour in the form of DKS is the result of an exchange process for the resources listed above. The actions of a leader evoke a response from others because people expect further benefits from the leader. Moreover, because DKS is based on communication, one can state that people communicate (share knowledge) with others with the expectation that their communication (knowledge sharing) will be equally reciprocated. Since SL is concerned with high-quality relationships between internal and external stakeholders (Dalati et al. 2017; Gerard et al. 2017), it creates a good environment for knowledge exchange between different companies’ stakeholders.

Furthermore, this study extends empirical evidence on the mediating role of knowledge sharing between leadership styles and FI. Previous studies have shown that knowledge sharing mediates the relationship between transformational leadership and FI (Lei et al. 2021; Le 2023). This study, through the verification of H1a, H1b, H2a, and H2b, demonstrates that both types of DKS positively mediate between SL and FF, and between SL and FC. In addition, only external DKS mediated SL and FE. The potential reason behind the non-significant mediating impact of internal DKS on the ‘SL–FE’ relationship is likely to be employees’ lack of awareness about consumers frugal lifestyle and environmental challenges.

Finally, this study shows that, in the presence of high EB, the effect of SL on external DKS increased. This supports Grivins et al. (2017), in that bricoleurs collect heterogeneous resources to use them at the right time. However, extant literature shows that bricoleurs interpret threats as opportunities, enhance their employees’ motivation and commitment to change, and practice team experimentation (Wang et al. 2021), which should have a positive impact on DKS among team members. The present study provides contradictory results because it found support on the moderating impact of EB only on the ‘SL–external DKS’ relationship. EB, associated with applying combinations of available resources to find solutions for problems and use opportunities, has emerged as a desired strategy in the context of enhancing external DKS and contributing to FF, FC, and FE. As Fisher (2012) states, in bricolage theory, resource environments are socially constructed, and social mechanisms make the creation of something new easier. This study proved that the social mechanisms in the surveyed companies rely mainly on external networking.

Innovation is an instrument that organisations use to increase business sustainability; however, it is typically associated with high costs. The latter is often a barrier for SMEs (Simba et al. 2021). However, a lower-cost approach, in the form of FI, is a feasible option for such companies. FI positively affects the quality of life in society by providing low-income customers with high-quality and cheap products. They also consume minimal natural resources, thereby contributing to environmental sustainability. Therefore, the surveyed SMEs, although using all three elements of FI at high levels (based on mean values), should focus on this type of innovation activity.

Moreover, this study shows that it is worth practising SL to stimulate different FI elements directly and through both types of DKS. Leaders’ direct contribution to creating added value in SMEs is more visible than in structures typical of larger organisations. Considering the need to develop SL in SMEs, one should measure whether candidates for leaders reflect sustainability-oriented leader attributes. For example, they should be familiar with engineering, social sciences, natural sciences, and health sciences, and have knowledge of the strategies and techniques that can be implemented for sustainable organisational development (Iqbal et al. 2022). Employee leaders should focus on the needs of different company stakeholders, support them, and build a culture of trust and collaboration. Then, both internal and external company stakeholders are given resources which can be reciprocated in the form of DKS. In turn, effective DKS will further stimulate knowledge sharing between various agents. Internal DKS is widely practiced in the surveyed companies (mean = 4.139), whereas external DKS is moderately practiced (mean = 3.949). We recommend that the companies focus on stimulating external DKS first, which would positively mediate the relationship between SL and FE.

Finally, EB has been found to be a positive moderator of the ‘SL–external DKS’ relationship. This result highlights the importance of monitoring and developing EB. Bricolage in the surveyed companies is now considerably high (mean = 4.219) but may be further developed. When recruiting leaders, one should assess whether they have features of entrepreneurial bricoleurs. For already employed leaders, a measure of entrepreneurial bricolage behaviour (Davidsson et al. 2017) can be used. Moreover, SME leaders should be supported through various courses and workshops to help them develop their skills in SL and EB.

This study has a few limitations. First, the concept of FI originated in emerging economies. This study offers empirical findings related to the ‘SL–FI’ relationship in developed countries such as Poland. Future studies could test the presented research model in developing countries to seek any potential insights related to mechanism and conditional factors of the ‘SL–FI’ relationship. Second, this study is cross-sectional in nature, and the collected data are from single sources at the firm level. Considering the scant multilevel research in the innovation management area (Kremer et al. 2019), future studies should collect multi-source data and conduct similar research at multiple levels. Third, this study enriches the literature by offering empirical findings for developed countries. Over the past decade, research on FI has largely concentrated on healthcare, IT, product development, and manufacturing, whereas livestock, agriculture, service, education, and other sectors that require frugal and sustainable approaches have received less attention (Melnikova and Gilsanz 2022). Future studies should explore the FI phenomenon in these neglected areas. Fourth, the findings of this study reinforce the idea that the relationship between SL and FI is complex and further exploration of their mechanisms is recommended. Thus, future research could investigate the potential impact of diversified knowledge sources on the proposed relationships. It should also go beyond the organisational boundaries and explore the role of different actors such as society, regulatory authority and government institutions in the entrepreneurial eco-system (Bouncken and Kraus 2022) in stimulating FI.