How Government,Social and Personnel Support Leverage the Sustainability in Start-ups: The Moderating Role of Board Gender Diversity

Abstract

This study aims to provide a comprehensive understanding of start-up’s sustainable development by integrating systems theory and gender schema theory. We examined the impact of support systems created by government (SFGS), social (SFSS) and human capital (SFHC) on the corporate sustainability of start-ups (SS). Additionally, this study explored the moderating role of board/founders’ gender (G) in these dynamics. To address this gap, data were collected from a sample of 350 start-ups. The researcher employed exploratory factor analysis and confirmatory factor analysis to assess and validate the proposed hypotheses. Findings represented the positive impact of support systems created by human capital on the sustainable development of rural Indian start-ups. Notably, the research also revealed that the founders’ gender moderated two of the three identified effects. It shows sustainability supports start-ups, including the role of gender in sustainability and entrepreneurship literature. Managerially, it highlights the significance of network building, gender equity and skill development. The government needs to put more effort into excluding gender-related barriers in developing countries. This study suggests the integration of system and gender schema theories for start-up corporate sustainability in developing nations. The moderating role of founders’ gender and the use of start-ups as sample units make this research more original and novel.

Keywords

Start-ups social capital human capital government sustainability gender female entrepreneurs rural entrepreneurship

Introduction

Start-ups are the higher-risk institutions/firms during the period of infancy, and entrepreneurial support is a mandatory factor for the survival of start-ups (Ezema et al., 2021). The researcher has convoyed the present trend of research on start-ups, innovation and sustainability; hence, this research is a scholarly understanding of the start-up support system because the findings available show that new firms grow faster and contribute more employment than the older firms (Haltiwanger, 2015; Ratinho et al., 2020). The supported sources identified by Ratinho et al. (2020) are from the government, incubators, investors, universities, internal business environment and personnel. These sources create the following three major factors: government support comprises support from initiatives and policies offered by the government; social capital comprises support available from incubators, networks, universities, etc.; and human capital support comprises support from the skills and talent of personnel of the firm. Government support for sustainable entrepreneurship plays a significant role (Brown & Mason, 2014; Hall et al., 2012). Worldwide, the government is devoting huge resources to creating and steering start-ups and small businesses, incubation centres and entrepreneurial education for the younger generations (Audretsch et al., 2018; Zaidi et al., 2021). Sustainable development goals set by the United Nations (UN) for the 2030 agenda include gender equality in the 5th goal (Filho et al., 2022; Queisser, 2016). Globally, sustainable entrepreneurship has become a burning topic (Peng & Walid, 2022). In India, a huge gender gap is found in entrepreneurship (Jameel & Ahmed, 2022).

Academic interest in social and human capital in corporate sustainable entrepreneurship has emerged (Garrigos-Simon et al., 2018). Therefore, efforts by rural start-ups are essential for the UN’s sustainability goals to encourage corporate sustainability and gender perspectives (Domecq et al., 2020). India has multiple opportunities for entrepreneurship since growing up to 35% of the millennial population (Juneja & Banerjee, 2022), as well as huge diversity in culture, language, ethnicity and natural and human resources (Korreck, 2019).

Moreover, start-up opportunities have increased since the government of India started the ‘Start-up India Scheme’ in 2016 (Singh, 2021). However, sustainability issues exist and start-ups are unable to cope with these challenges. Therefore, spurring the start-up’s sustainability will help India achieve its 2030 sustainable development target (Roy & Pramanick, 2019), with social capital serving as a contributor to corporate sustainability (Garrigos-Simon et al., 2018).

System theory is commonly used to study intermediaries’ connections, including the domains of entrepreneurial support, formal and informal networks, leadership, marketing, human capital and government aids, and it provides distinguish resources and knowledge to develop sustainable ecosystems in the local area (Theodoraki et al., 2017). It creates an entrepreneurship ombudsman to involve the local community in sustainable development by assisting new ventures towards sustainability (Hayter, 2016). Gender equality among board members is a major global provocation and social barrier that must be prevented through entrepreneurship in order to adhere to corporate sustainable development opportunities (Kato, 2019). In this context, gender theory explains a crucial aspect of the mental image of gender, society and community. This theory is based on the establishment and development of individual abilities like thinking, speaking, behaving and perceiving over time (Gupta et al., 2020).

The primary objective of this study is to investigate the support system framed through the government, social capital and human capital, with the added complexity of corporate sustainability in start-ups. The study displays the novelty of advancing the knowledge of start-up sustainability while including gender diversity.

This study addresses the following research gaps: There is less evidence, particularly in the context of corporate sustainability; rather, focus has been drawn on supporting factors of the success of start-ups (Kee et al., 2019). It is noteworthy that extensive research has been conducted on various aspects related to the influence of social and human capital on sustainability within entrepreneurship, particularly in countries such as the USA, England, the Netherlands, China and Australia. Surprisingly, out of a substantial pool of 653 documents, only 16 were centred on India. This significant disparity underscores the pressing need for empirical investigations in these specific areas (Garrigos-Simon et al., 2018).

This study focused on the Indian context. To the best of our knowledge, no comprehensive study has been conducted in India focusing on these frameworks, particularly for start-ups. By contrast, international evidence exists (Dickel & Eckardt, 2020; Elmhirst, 2013; Gaweł & Krstić, 2021). Numerous studies have explored the gender gap in entrepreneurship (Guzman & Kacperczyk, 2019; Yang & Aldrich, 2014). However, they are relatively underexplored as potential moderating factors for start-up corporate sustainability (Outsios & Farooqi, 2017).

Hence, this study initiates novelty by combining system theory and gender theory on start-up sustainability. To address this gap, we developed the following research question:

How do the components of the support system, as represented by the three pillars of social capital, human capital and government initiatives, contribute to and influence the sustainability of start-ups?

How is the concept of sustainability shaped by gender-related factors in start-ups?

To what extent does gender operate as a moderating variable in the relationship between the support system, characterised by three pillars (social capital, human capital and government support), and the sustainability of start-ups?

Literature Review

Extensive literature describes the role of three aspects of support systems that impact start-up growth along with sustainable development, which are important components of entrepreneurial empowerment (Bell-Masterson & Strangler, 2015). Gender always remains a researchable topic in entrepreneurship (Shinnar et al., 2012). New venture development faces gender discrimination and lack of government support (Korreck, 2019). In the past few years, a growing body of literature has highlighted the necessity of social capital for entrepreneurs (Cox et al., 2021). Social capital can vary from region to region; thus, it is important to study regional social capital to mobilise the resources and abilities of entrepreneurs. Stam’s (2015) system theory presents a business firm as composed of various subsystems, networks and formal and informal relations to acquire different talent skills in the venture creation process. The system for start-ups consists of social networks, incubators and accelerator support, government, marketing support, outsourcing of talent, experience and job knowledge expertise teams that resemble social, human capital and government support, which has a deep impact on corporate sustainability (Theodoraki et al., 2017).

Human Capital Support

The human capital theory is extensively used in entrepreneurship (Unger et al., 2011). Human capital plays a significant role in economic growth, and intellectual human capital provides a return on investment in skills by reducing production costs and increasing productivity (Schlepphorst et al., 2020). Human capital offers various advantages in entrepreneurship as it provides resources to new ventures that help diminish risk and spur innovation, ultimately leading to firm success in raising venture capital and network connections (Pierrakis & Owen, 2022). Human capital has been argued to be highly utilised when it applies to specific tasks that need to be performed, including the work skills required for the current task of the venture, such as industrial and start-up experiences. However, as non-task-related human capital includes formal education of human resources (staff), most of the literature (about 51%) is based on non-task-related concepts (Marvel et al., 2016), and both forms of human capital affect the venture creation process (Aboobaker & Renjini, 2020) and play a vital role in start-up formation.

Social Capital Support

The literature review has identified several dimensions of social capital, both formal and informal, as well as strong and weak ties with other organisations (Theodoraki et al., 2017). Thomas & Autio (2014) proposed social ties with members with specialised resources, where each member contributes via their competency and collaboration to strengthen the performance of the venture (Garrigos-Simon et al., 2018). A bibliometric study on social and human capital and sustainability stated ‘social capital’ as the trending term in the literature from 1981 to 2017. Social capital strongly impacts entrepreneurial activities among Turkish women entrepreneurs (Kawamorita et al., 2021) and immigrant entrepreneurship. Social capital determinants include network interpersonal trust and institutional trust, and it has been shown that social capital can cause variation in entrepreneurial intention (Turkina & Thai, 2013).

Government Support (SFGS)

Any venture receives multifarious support from the government, which could include tax exceptions, subsidies, loans and technological support (Burt, 2000; Li et al., 2020; Peng & Walid, 2022). If a firm has strong ties with the government, it becomes stronger to access essential resources that spur the chances of venture survival (Yang et al., 2018). Several studies have assessed the direct impact of government support on the performance, survival and growth of start-ups; however, it has also been found that the government has some united negative effects on the social and environmental domains (Bryant et al., 2017). Previous studies on start-ups emphasise that government support is vital for entrepreneurship; it boosts entrepreneurial intention and competencies (Lee & Ha, 2015), and firms obtain support from the government to survive and sustain longer, as it reduces the heterogeneity of the external environment and social embeddedness (Li et al., 2020; Shivhare et al., 2023).

Start-up Corporate Sustainability

Sustainable entrepreneurship is an emerging need in entrepreneurship to achieve competitiveness, but sustainability must be kept above the political boundary of sustainable development goals. It is essential for the planet’s well-being, and the start-up is considered a solution for sustainable development (Horne & Fichter, 2022) and profitability with the betterment of society, environment and economy (Peng & Walid, 2022). Corporate sustainability has a multitude of theories and approaches; it is essentially rooted in the intersection of economic, social and environmental sustainability culture or practices among business enterprises (Olteanu & Fichter, 2017). When it applies to the company or firm, it encompasses corporate firm sustainability (Wijethilake, 2017). Corporate sustainability makes a firm grow and profitable for its survival with minimal or no side effects on the natural and social environment. Hence, green, eco-friendly, social and sustainable start-ups are emerging to enhance sustainable culture from the very early age of businesses (Souto, 2021). Various business models are adopted by nascent venture entrepreneurs to see opportunities in sustainable ventures, such as sustainable innovation model, sustainable model and circular innovation model (Shivhare & Shunmugasundaram, 2023).

Gender

Several studies have evaluated the impact of gender on corporate sustainability practices, reporting and disclosure (Bananuka et al., 2022). Entrepreneurship is strongly embedded in the traditional notion of masculinity (Kato, 2019). However, arguments made by contemporary scholars break this stereotype: social ventures are key entrepreneurial areas owned by women (Gupta et al., 2020); gender schema theory studies the psychological difference in masculine and feminine traits, individuals when they acquire gender-specific characteristics as per their culture (Hyde et al., 2019), which create differences in behaviour among males and females in the sector of business and entrepreneurship, and it causes mental development, perceptions, motivations, attention and other circumstantial causes (Fan et al., 2021).

Globally, nascent ventures/start-ups are more often established and operated by males than females (Dickel & Eckardt, 2020; Kelley et al., 2012). Women perceived less human capital and comparatively less entrepreneurial behaviour at the early stage (Domecq et al., 2020); instead, it was found that women were able to raise the economic status of low-income families by utilising their social capital stock in the form of social networks in the social environment (Achmad et al., 2022). The gender perspective for sustainable venture development needs to be understood to increase corporate sustainability in a business (Zahra et al., 2014).

Hypothesis Development

SFSS and SS

Social capital is an important factor for sustainable development (Mishchuk et al., 2022). The evidence of social capital was assessed on promotion of sustainable development (Zhang et al., 2023). To test the impact of social capital on the sustainable competitiveness of business firms, Lontchi et al. (2022) assessed the role of social capital on sustainable development through financial inclusion in the USA. Haque et al. (2019) statistically analysed the impact of social capital on the corporate sustainability of micro-enterprises owned by women in a cross-cultural manner to explore the contribution of micro-training and non-financial services. Social capital can increase the adoption of sustainable management (Rust et al., 2020). Kim et al. (2020) assessed that sustainable intention is impacted by social capital in consumer purchase decisions of fashion products, and Richardson et al. (2017) analysed the relationship between social capital, career and sustainability. Business incubators have a significant impact on sustainability (De Azevedo Marques et al., 2022). Jamil and Rasheed (2023) have found similar results from the research conducted on 266 stock exchange-listed firms in Pakistan that revealed the substantial association between firm sustainability and social capital.

H₁: SFSS has a positive impact on SS.

SFHC and SS

The entrepreneurial journey should combine the skills, efficiency and knowledge of potential entrepreneurs to explore business opportunities, as in the case of sustainable entrepreneurship (Crnogaj et al., 2014), it is necessary to carefully recruit and train staff to obtain maximum performance along with the environment and social mission (Pierrakis & Owen, 2022). Furthermore, Griggio and Oxenswärdh (2021) in their study found a relationship between human capital and sustainability in American lifestyle start-ups; however, similar evidential studies are also available in developing countries, where Nauman and Hussain (2017) found that similar relations exist between human capital and corporate sustainability in Pakistan’s banking sector.

Similarly, Gharib et al. (2022) assessed the impact of green human capital as a type of green intellectual capital on environmental sustainability in the famous cement and methanol industry of Oman. Similar relations are found not only in business firms but also in the agricultural sector, which postulated the impact of human capital on sustainable food crop production and technical efficiency (Hoang-Khac et al., 2021).

H₂: SFHC positively impacts SS.

SFGS and SS

Start-ups are not only in securing enough growth for the economic development of the country but also have a crucial impact; thus, major countries such as the USA, Japan, China and Korea are actively supporting start-ups that have a significant impact on their corporate sustainability (Lee & Kim, 2019). In addition, a study conducted in China examined the government resources that support environmental investment and sustainable development, including loans and tax benefits (Quan et al., 2018). The study recognised that government regulations and policies encourage firms’ sustainability in supply chain start-ups in a turbulent environment (Chatterjee & Chaudhari, 2021). Yasmeen et al. (2019) outlined the role of the government in both civil and corporate sustainability concerning the environment, arguing that government initiatives significantly increase implementation sustainability in organisations. Moreover, Dickel and Eckardt (2020) assessed the effect of perceived desirability and social and sustainable entrepreneurial intentions in general entrepreneurship as well as in entrepreneurship with governmental support.

H₃: SFGS positively impact SS.

Gender as a Moderator

Gender has been used as a moderating variable in various studies in different areas of the literature, such as psychology, education and entrepreneurship. In sustainability literature, a moderator such as board gender diversity moderates the relationship between corporate social responsibility and the environmental and social performance of listed companies in Europe (Orazalin & Baydauletov, 2020). Customer gender has been considered a moderator in the relationship between motivational factors and sustainable behaviours of customers (Fan et al., 2021). Romano et al. (2020) examined the role of board gender diversity in performance and corporate sustainability practices. Javeed et al. (2022) claimed the moderating role of diversity of gender on corporate financing and green innovative strategies in Chinese manufacturing firms. Gender has a substantial moderating effect on opportunity recognition and start-up entrepreneurial intention (Ryu & Kim, 2020). Refer Figure 1 for hypothesis and relations among variables.

Figure 1.

Conceptual Framework.

H₄: Gender has a significant moderating effect on the relationship between SFGS and SS.

H₅: Gender has a significant moderating effect on the relationship between SFSS and SS.

H₆: Gender has a significant moderating role in the relationship between SFHC and SS.

Research Methodology

Questionnaire and Sample

This research follows a quantitative methodology and is exploratory. The objective of this type of methodology is to generalise the result based on the results obtained through the use of statistical tools. Questionnaires were prepared to analyse start-ups’ perceptions of sustainability through social capital, human capital and government support (refer Appendix B).

After preparing the questionnaire, founders of start-ups in India were selected as the respondents for this study. For this, the definition of a start-up given by the Department of Promotion of Industry and Internal Trade (DPIIT, GOI) is as follows: a start-up is a business firm established within the past ten years, having turnover under ₹1,000 million and not more than 250 employees. Thus, the final respondents of the study were the chief executive officer/owner/founders/partners and other key persons of the start-up firm.

To calculate the sample size for this study, we applied the criteria for the sample variable ratio suggested by Memon et al. (2020), which stated that there must be a minimum of 20 respondents for each independent variable in this study (20:1). This study had three independent constructs with 14 independent variables (5 + 5 + 4 = 14). Hence, the minimum sample size was calculated as 280 (20 × 14 using the 20:1 formula).

The researcher contacted 600 prospective respondents at their convenience using Google Forms and thoroughly explained the purpose of the survey. It was also mentioned that the information given by them was anonymous, confidential and solely used for research purposes. Of the 600, 480 respondents agreed to participate, with a good response rate of 80%. However, only 350 valid and complete questionnaires were taken as the sample for this study (the final respondent profile is discussed in Table 2). The studies by Shahbaz et al. (2020) and Aftab et al. (2020) also explored the moderation impact of gender using 283 and 250 valid samples, respectively. Thus, it ensures a balanced sample for addressing the moderating impact of gender of board members.

Instrument and Measures

The measurement items were adopted from various previously validated studies, with slight modifications. The items for independent variables, including social capital, human capital and government support, were adopted from the studies by Baptista et al. (2007), Scillitoe and Birasnav (2021) and Vidotto et al. (2017). For dependent constructs, the scale was adopted from a study by Shivhare et al. (2023). Each item is measured on a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). For the moderating variable gender, scale 1 for males and scale 2 for females were used based on a study by Westhead and Solesvik (2016) (details of the source are provided in Table 1 and Appendix E).

Table 1.

Instruments and Measures Used.

Constructs	Items	Operationalisation	Source
Social capital support	5	Support from society and local community available for start-ups	(Baptista et al., 2007)
Human capital support	5	Talent, skill, knowledge of man-power and team for creation of start-ups	(Vidotto et al., 2017)
Government support	5	Government initiatives, policies and aids available for start-ups	(Scillitoe & Birasnav, 2021)
Start-up sustainability	9	Environment, social and economic factors for sustainable entrepreneurial development	(Shivhare et al., 2023)
Gender	1	Respondent biological sex	(Westhead and Solesvik, 2016)

Statistical Tools

This study applied exploratory factor analysis (EFA) using the principal component method with varimax rotation to evaluate the minimum number of common factors required to adequately reproduce the item correlation matrix based on the methodology of Rodrigues et al. (2020). We applied EFA using SPSS tools for the analysis because the scale adopted was slightly modified from the perspective of startupreneurs. To ensure validity and reliability, EFA and confirmatory factor analysis (CFA) were applied using structural equation modelling (SEM) on SmartPLS 4.0. As suggested by Hair et al. (2020), the use of partial least squares (PLS)-SEM is justified by the presentation of reflective and formative indicators, and it also overcomes the apparent dichotomy between explanation and prediction and also provides managerial implication development (Hair et al., 2020).

Common Method Bias

A single-factor Harman test was implemented to check for the existence of common method bias in the dataset. The explained variance was less than 50%, which justifies the absence of common method bias in this study (Sivathanu & Pillai, 2019).

Data Analysis

Demographic Profiles of the Respondents

Of the 350 start-ups, male and female were taken in equal proportion. Regarding age, 56.6% of the respondents were between 25 and 35 years old, and 24.3% were between 35 and 45 years old. However, only 6.3% of start-ups were older than 45 years, and most start-ups were owned by younger people. More than half of the startupreneurs (65.4%) were enrolled in graduate programmes, the remaining 14.3% were high school educated and 13.1% were post-graduate and above. Only 3.1% of respondents were illiterate and showed great literacy among entrepreneurs of start-ups. Regarding the respondents’ family types, the response was dicey, as approximately the same percentage was obtained for the nuclear and joint families to which start-up owners belonged. Moreover, more than half of the respondents (58.9%) were married, and only 6.3% were divorced. Regarding their annual income, 47.4% had an annual income between ₹400,000 and ₹500,000, and 29.4% had an annual income of more than ₹500,000. Only 4.9% have a very low annual income of less than ₹100,000 (see details in Table 2).

Table 2.

Demographic Profile of the Startupreneurs.

Variables	Classification	N	%
Age (in years)	Less than 25	45	12.9
	25–35	198	56.6
	35–45	85	24.3
	More than 45	22	6.3
	Total	350	100
Gender	Male	175	50
	Female	175	50
	Total	350	100
Marital status	Single	122	34.9
	Married	206	58.9
	Divorced	22	6.3
	Total	350	100
Family type	Nuclear	174	49.7
	Joint	176	50.3
	Total	350	100
Annual income (in rupees)	Less than 100,000	17	4.9
	100,000–300,000	64	18.3
	400,000–500,000	166	47.4
	Above 500,000	103	29.4
	Total	350	100

Source: Primary data.

EFA

The collected data were analysed using SPSS software. EFA was conducted on 23 items to identify latent factors (Churchill, 1979; Jha et al., 2018). A factor analysis was performed to empirically identify the variables that form a particular construct.

EFA was conducted to identify underlying factors. First, it measures the sample adequacy through a test such as Bartlett’s test of sphericity and the KMO test, where Bartlett’s test scored ꭓ² = 9734.829, degree of freedom (df) = 253, significance level = 0.000 and KMO sampling adequacy value 0.915 that ensures the fitness of the dataset for factor is more than the standard KMO value of 0.6 (Loewen & Goulal, 2015), using principal component analysis (PCA) with varimax rotation. The commonalities of all the measures were above 0.5 (Watkins, 2018; refer to Appendix A).

However, the commonalities of all the standards were greater than 0.5, except for one statement from the construct of government support and one statement from the construct of sustainability. These two statements were excluded from further analysis. The factor loadings of all the measures were above 0.5 (Hair et al., 2019). Four factors were extracted, explaining 76.217% of the total variance (Jha & Alam, 2021). These factors were government (SFGS), social capital (SFSS), human capital (SFHC) and start-up corporate sustainability (SS; presented in Table 3). In addition, the overall Cronbach’s alpha of the 29 items was 0.936, and Cronbach’s alpha was calculated after examining the items constructing four constructs.

Table 3.

Pattern Matrix EFA.

	1	2	3	4	Construct-wise (α)
SFSS1				0.577	0.966
SFSS2				0.692
SFSS3				0.778
SFSS4				0.695
SFSS5				0.627
SFG2		0.796			0.878
SFG3		0.883
SFG4		0.903
SFHC1			0.826		0.937
SFHC2			0.902
SFHC3			0.855
SFHC4			0.820
SFHC5			0.871
SS1	0.899				0.967
SS2	0.879
SS3	0.899
SS4	0.856
SS5	0.875
SS6	0.893
SS8	0.844

Source: Computed by primary data using SPSS.

Note: Extraction method: PCA. Rotation method: varimax with Kaiser normalisation.

CFA

To conduct CFA, PLS-SEM software (version 4.0; Hair et al., 2020) was used to develop and improve the reflecting measured construct based on the domain sampling model for primary data analysis. The measurement characteristics of SEM in the final model were calculated to determine the relationship between latent constructs. We conducted bootstrapping with 5,000 samples, and the r² value of the model was obtained at 35.3% (Sivathanu & Pillai, 2019; Appendix D).

Convergent Validity and Internal Consistency

The convergent validity of the dataset was investigated through factor loading, average variance extracted (AVE), composite reliability and Cronbach’s alpha value. All the extracted constructs confirm that the factor-loading value of more than 0.5 (Hair et al., 2020; Sivathanu & Pillai, 2019) and AVE is more than 0.5 (Hair et al., 2020; Benitez et al., 2020). Along with a Cronbach’s alpha score of more than 0.7, which ensures convergent validity and high internal consistency of the data, factor-loading scores are greater than 0.6, which ensures high internal consistency (Aburumman et al., 2022) (refer Table 4).

Table 4.

Factor Loading and Reliability.

	Factor Loading	Factor Loading	Cronbach’s Alpha	Composite Reliability	Average Variance Extracted (AVE)	VIF
SFG	SFG2	0.891	0.923	0.931	0.866	1.762
	SFG3	0.960
	SFG4	0.940
SFHC	SFHC1	0.879	0.938	0.944	0.802	1.297
	SFHC2	0.939
	SFHC3	0.870
	SFHC4	0.874
	SFHC5	0.919
SFSS	SFSS1	0.778	0.908	0.915	0.732	1.726
	SFSS2	0.866
	SFSS3	0.899
	SFSS4	0.881
	SFSS5	0.851
SS	SS1	0.934	0.967	0.968	0.836	–
	SS2	0.928
	SS3	0.928
	SS4	0.887
	SS5	0.857
	SS6	0.656
	SS8	0.855

Source: Primary data.

Multicollinearity

It is essential to check the presence of multicollinearity for formative scale type, and, for this purpose, the weight and variance inflator factor (VIF) was used by Becker et al. (2012). The VIF value must be more than 3.3, which explains the presence of multicollinearity in the dataset. The present study reported all VIF scores less than 3.3, which ensures that multicollinearity is not present in this study (Diamantopoulos & Siguaw, 2006; see Appendix C).

Discriminant Validity

To establish discriminant validity, it must be noted that the construct of the model is distinct from each other. Rasoolimanesh’s (2022) study uses the Fornell–Larcker and HTMT ratio (Henseler et al., 2015), while the Fornell–Larcker criterion assesses discriminant validity by calculating the square root of the AVE score of each underlying factor; it must be higher than its correlation with other underlying factors (Hami et al., 2017). Another measure of discriminant validity is the HTMT test, which measures the correlation between two latent constructs. The standard value of the HTMT score must be under 9.0 (Chan & Lay, 2018); if any value exceeds this low discriminant validity, the underlying construct is less than 0.90, which displays the discriminant validity of the data in the present study (Tables 5 and 6).

Table 5.

Fornell–Larcker Criterion.

	SFG	SFHC	SFSS	SS
SFG	0.931
SFHC	0.44	0.896
SFSS	0.624	0.405	0.856
SS	0.395	0.4	0.544	0.915

Source: Primary data

Table 6.

HTMT Discriminant Validity.

	SFG	SFHC	SFSS	SS	Gender	Gender × SFG	Gender × SFSS	Gender × SFHC
SFG
SFHC	0.473
SFSS	0.685	0.431
SS	0.417	0.417	0.578
Gender	0.016	0.059	0.047	0.076
Gender × SFG	0.045	0.032	0.027	0.01	0.041
Gender × SFSS	0.031	0.01	0.092	0.124	0.152	0.592
Gender × SFHC	0.035	0.02	0.031	0.028	0.103	0.433	0.269

Source: Primary data.

Structural Model

The relationship between the underlying constructs was assessed through path analysis using SEM. Table 7 shows the path coefficient value, T-score and its significance level, and the theoretical model presented in Figure 2 has been texted.

Figure 2.

Source: SmartPLS 4.0.

Table 7.

Hypothesis Testing.

Hypothesis	Path	Coefficients	Standard Error	T-score	p Value	Decision
H ₁	SFGS↓SS	−0.004	0.076	0.051	.959	Rejected
H ₂	SFHC↓SS	0.223	0.062	3.628	.000	Supported
H ₃	SFSS↓SS	0.471	0.08	5.875	.000	Supported
H ₄	G-SFG↓SS	−0.097	0.052	2.304	.049	Supported
H ₅	G-SFSS↓SS	0.12	0.055	2.359	.010	Supported
H ₆	G-SFHC↓SS	0.001	0.045	0.102	.918	Rejected

Source: Computed from primary data through PLS.

Table 7 reveals the hypothesis that H₁ tested the relationship between SFGS and SS and found no significant relationship between the two (β = −0.004, p > .05). H₂ was supported by the result that displayed a positive relationship between the SFHC and SS (β = 0.23, p < .01). H₃ represents the relationship between SFSS having a direct and positive impact on SS (β = 0.47, p < .01). Thus, H₂ and H₃ were supported by the results of the hypothesis testing, whereas H₁ was rejected (Table 7).

Moderating Effect

H₄, H₅ and H₆ show the moderating effect of board gender on SS through SFG, SFSS and SFHC, respectively. The results showed a negative moderating impact of gender on the relationship between SFG and SS (β = −0.097, p < .05) and a positive moderating impact of gender on the relationship between SFG and SS (β = 0.120, p < .01). However, gender had no moderating impact on the relationship between SFHC and SS (β = 0.001, p > .05). Hence, out of the three hypotheses on the moderating impact of gender, hypotheses H₄ and H₅ have a significant moderation effect and H₆ does not show a significant moderation result.

Discussion and Implications

Direct Impact

The results confirmed that there is no effect that startupreneurs have with government support on their start-up corporate sustainability (H₁), and the corresponding findings by Bryant et al. (2017) discussed the united negative impact of government when discussing social and environmental concerns. However, this result contradicts that reported by Lee and Kim (2019). The results revealed a positive and significant impact of human capital on start-up sustainability (H₂), which is in agreement with Griggio and Oxenswärdh (2021) and Verma et al. (2023) that show the positive impact of human capital on societal sustainability in green start-ups of high-contact services, and lifestyle entrepreneurs such as findings show that social capital has a positive impact on the sustainability of start-ups. H₃ is accepted, and similar findings available in studies such as Mishchuk et al. (2022) found a similar result in enterprises in Ukraine, and more evidence is available that shows that social capital is an enabler of sustainable development (Lontchi et al., 2022). These findings are beneficial for sustainable development, as the results show no discrimination based on the gender of sustainability. Studies conducted on the tourism sector show that there is no sustainability without gender equality (Alarcón & Cole, 2019). However, this result is inconsistent with the findings due to the heterogeneity of demographics and industrial areas (Sifers et al., 2022).

Moderating Effect

Regarding the moderating impact of gender on the sustainability of start-ups, we find support for H₅; that is, gender has a moderating role in the relationship between government support and start-up sustainability, despite no direct impact revealed by the findings of H₁, where government support has an insignificant impact on start-up sustainability. The findings support H₅, which depicts gender diversity as a moderating variable between social capital support and start-up sustainability that shows the social skills of women can enhance the more sustainable outcome in nascent ventures (Mohr et al., 2022). For H₆, unfortunately, the result is not confirmed with this, that there is no discernible between human capital support and sustainability. However, this result is heterogenous with the study of Ploum et al. (2017), which shows women tend to have low human capital and are less competent (Lohani and Aburaida, 2017) in sustainable entrepreneurial behaviour. A similar result was found by Abbas et al. (2021) that shows recruitment selection and sustainability are not moderated by gender.

Implications

Theoretical Implications

In terms of theoretical implications, this study uncovers previously unexplored associations between support systems and start-up corporate sustainability. It builds upon existing literature by providing empirical evidence (Domecq et al., 2020; Garrigos-Simon et al., 2018; Quan et al., 2018). Moreover, it demonstrates the relevance of demographic factors in the context of sustainable entrepreneurship by examining the moderating impact of gender on start-up sustainability (Barrachina et al., 2021; Outsios & Farooqi, 2017). This study contributes significantly to the theoretical underpinnings of gender in entrepreneurship (Marlow, 2020; Shneor et al., 2013). Additionally, it emphasises the importance of a combined approach to social and human capital support for enhancing sustainability in nascent ventures.

Managerial Implications

Regarding the managerial implications of this research, the study delivers a practical tool to assist startupreneurs and managers. It suggests that network building should be a part of strategic decisions, considering resource needs and collaborative network opportunities (Passaro et al., 2020). Managers and startupreneurs can benefit from the model by promoting gender equality in start-ups. This implies that managers and leaders should be mindful of potential gender-related challenges in accessing government support. Furthermore, managers can leverage the positive moderating effect of gender on social capital support by fostering diverse teams and networks. Initiatives for skill development should be adopted by startupreneurs, including regular training and upskilling, which can improve human capital and enhance the collective capabilities of start-ups for long-term sustainability.

Practical Implications

The interpretative framework developed in this study can serve as a practical tool for policymakers to design government-sponsored accelerator programmes aimed at training startupreneurs and connecting them with skilled accelerators and networking events for sustainable planning (Owen, 2023). Founders and investors should prioritise investments in human capital development through training, education and skill enhancement programmes. A knowledgeable team remains a cornerstone of sustainable start-ups, regardless of other external factors (Barendsen et al., 2021). Gender-inclusive policies and support mechanisms for women startupreneurs should be implemented, as the study reveals the positive moderating effect of gender on sustainability through government support and social capital. Thus, promoting and fostering gender diversity in collaborative networks becomes imperative in practical scenarios. These implications underscore the practical significance of this study’s findings for both managers and policymakers, offering guidance on how to enhance start-up sustainability through strategic support systems and gender-inclusive practices.

Conclusions and Delimitations

The study examined how government support, social capital and human capital all have significant contributions to the sustainability of start-ups. This emphasises the importance of strong human resource needs in interpersonal networks, skills and expertise. Government support does not have a direct impact on sustainability, raising questions about government support in the Indian start-up ecosystem. The study also examined the role of gender, which, while not directly affecting sustainability, plays a crucial role through its interaction with social and government support. This calls for further research with a robust moderating and mediating impact of new variables such as social awareness and owner’s commitment. Longitudinal study design with large datasets may be beneficial.

Appendices

Appendix A.

Sphericity and Reliability.

Total variance explained		76.217
KMO		0.915
Bartlett’s test of sphericity	Chi-square	9734.829
	df	253
	Sig	0.00
Reliability of data	Cronbach alpha (α)	0.936
	N	29
	Observations	350

Source: Primary data.

Appendix B.

Model Fit.

	Saturated Model	Estimated Model
SRMR	0.046	0.046
d_ULS	0.485	0.481
d_G	0.438	0.44
Chi-square	987.509	981.313
NFI	0.881	0.882

Source: Primar data.

Appendix C.

VIF.

	SFG	SFHC	SFSS	SS
SFG				1.762
SFHC				1.297
SFSS				1.726
SS
Gender				1.054
Gender × SFG				1.772
Gender × SFSS				1.609
Gender × SFHC				1.259

Source: Primary data.

Appendix D.

R².

	R ²	R² adjusted
SS	0.353	0.341

Source: Primary data.

Appendix E.

Measures of Questionnaire.

	Construct	Statements
Independent variables	Social capital support system	The firm gets support from incubators and accelerators for new start-ups to succeed
		Firm has proper co-working space with different companies
		There is availability of mentors to provide perspectives for the formation of start-ups
		There is a great role of print and electronic media in the promotion of the start-up firm
		The entrepreneurial events are helpful for better formation of the start-up
	Government support	In my country, a wide range of government assistance for new and growing firms can be obtained through contact with a single agency
		In my country, science parks and business incubators provide effective support for new and growing firms
		In my country, almost anyone who needs help from a government program for a new or growing business can find what they need
		In my country, government programmes aimed at supporting new and growing firms are effective
	Human and social capital	Availability of a talented and experienced team helps in the formation of a start-up
		Work-related specific skills in employees help in start-up forming
		The youth of my locality is aware and interested towards entrepreneurship
		Social network ties help to form the start-up
		Shared vision, commitment and togetherness within the team would help in a start-up formation
Dependent variables	Sustainability	It is a profitable and well-managed start-up
		The company has a financial accounting balance at the date of the final results
		The company includes references to sustainability in the statement documents of vision, mission and values
		It conveys the image of a responsible and reliable start-up
		The start-up has specific policies to deal with issues related to human rights
		The start-up has community support
		It complies with ethical and clear criteria
		The company seeks to know the possible impacts of climate change on its business.
		The company carries out specific initiatives to reduce material
Moderating variable	Gender	Male
Moderating variable	Gender	Female

Source: Literature.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iD

Shivani Shivhare

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How Government,Social and Personnel Support Leverage the Sustainability in Start-ups: The Moderating Role of Board Gender Diversity

Abstract

Keywords

Introduction

Literature Review

Human Capital Support

Social Capital Support

Government Support (SFGS)

Start-up Corporate Sustainability

Gender

Hypothesis Development

SFSS and SS

SFHC and SS

SFGS and SS

Gender as a Moderator

Conceptual Framework.

Research Methodology

Questionnaire and Sample

Instrument and Measures

Instruments and Measures Used.

Statistical Tools

Common Method Bias

Data Analysis

Demographic Profiles of the Respondents

Demographic Profile of the Startupreneurs.

EFA

Pattern Matrix EFA.

CFA

Convergent Validity and Internal Consistency

Factor Loading and Reliability.

Multicollinearity

Discriminant Validity

Fornell–Larcker Criterion.

HTMT Discriminant Validity.

Structural Model

Hypothesis Testing.

Moderating Effect

Discussion and Implications

Direct Impact

Moderating Effect

Implications

Theoretical Implications

Managerial Implications

Practical Implications

Conclusions and Delimitations

Appendices

Sphericity and Reliability.

Model Fit.

VIF.

R2.

Measures of Questionnaire.

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References

R².