Journal of Innovation & Knowledge 6 (2021) 69–77 Journal of Innovation & Knowledge https://www.journals.elsevier.com/journal-of-innovation-and-knowledge Effects of sociocultural and economic factors on social entrepreneurship and sustainable development María-Teresa Méndez-Picazoa,∗, Miguel-Angel Galindo-Martínb, María-Soledad Castaño-Martínezc a University Complutense of Madrid, Faculty of Economics and Business, Campus de Somosaguas, 28223 Madrid, Spain b University of Castilla-La Mancha, Faculty of Law and Social Sciences, Ronda de Toledo, 13003 Ciudad Real, Spain c University of Castilla-La Mancha, Faculty of Economics and Business, Plaza de la Universidad 1, 02071 Albacete, Spain a r t i c l e i n f o Article history: Received 29 March 2020 Accepted 9 June 2020 Available online 20 June 2020 JEL classification: L26 L31 O40 Q01 O43 E02. Keywords: Social entrepreneurship Sustainable development Sociocultural factors Corruption Partial least squares (PLS) a b s t r a c t Concern about environmental problems has led to more attention being paid to the sustainable devel- opment objective. Social entrepreneurship, and entrepreneurship in general, show a direct relationship with this objective, due mainly to the activities carried out by entrepreneurs regarding the development of new products, the search for new markets, and the introduction of innovations. Because of this, it is important to identify the variables that influence both types of entrepreneurship to adequately design measures to stimulate sustainable development through these activities. These variables can be grouped into two groups: sociocultural factors and economic factors. The objective of this paper is to analyze the behavior of these two groups over general entrepreneurship and social entrepreneurship, in addition to the impact of these two types of entrepreneurship on sustainable development. To carry out this analy- sis, we have developed an empirical analysis with structural equations for the case of 15 OECD countries between 2015 and 2016. La preocupación por los problemas ambientales ha llevado a que se preste más atención al objetivo de desarrollo sostenible. El emprendimiento social, y el emprendimiento en general, muestran una relación directa con este objetivo, debido principalmente a las actividades llevadas a cabo por los emprendedores en relación con el desarrollo de nuevos productos, la búsqueda de nuevos mercados y la introducción de innovaciones. Debido a esto, es importante identificar las variables que influyen en ambos tipos de emprendimiento para diseñar adecuadamente medidas para estimular el desarrollo sostenible a través de estas actividades. Estas variables se pueden agrupar en dos grupos: factores socioculturales y factores económicos. El objetivo de este trabajo es analizar el comportamiento de estos dos grupos sobre el emprendimiento general y el emprendimiento social, además del impacto de estos dos tipos de emprendimiento en el desarrollo sostenible. Para llevar a cabo este análisis, hemos desarrollado un análisis empírico con ecuaciones estructurales para el caso de 15 países de la OCDE entre 2015 y 2016. © 2020 Journal of Innovation & Knowledge. Published by Elsevier España, S.L.U. This is an open access he CC B R M A R t p article under t Introduction In recent decades, the study of entrepreneurship has been studied from different perspectives. One approach is to analyze the potential effects of entrepreneurship on economic growth, in respect of the benefits that greater economic growth has on employment and the well-being of society, especially in times of crisis. This has been the focus of a considerable body of research (e.g., Audretsch & Keilbach, 2004a, 2004b; Audretsch, 2005; Alpkan, Bulut, Gunday, Ulusoy, & Kilic, 2010; Acs, Audretsch, ∗ Corresponding author. E-mail address: mmendezpi@ccee.ucm.es (M.-T. Méndez-Picazo). d g t a g t https://doi.org/10.1016/j.jik.2020.06.001 2444-569X/© 2020 Journal of Innovation & Knowledge. Published by Elsevier España creativecommons.org/licenses/by-nc-nd/4.0/). BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). raunerhjelm, & Carlsson, 2012; Méndez-Picazo, Galindo-Martín, & ibeiro-Soriano, 2012; Nissan, Galindo, & Méndez, 2012; Castaño, éndez, & Galindo, 2016; Doran, McCarthy, & O’Connor, 2018; eeni, Motavaseli, Sakhdari, & Dehkordi, 2019; Stoica, Roman, & usu, 2020). These analyses conclude that there is a direct rela- ionship entrepreneurship and economic growth. Therefore, the olicy maker can add the factor of entrepreneurship to the tra- itional ones, such as public spending and taxes, for stimulating rowth. For this reason, interest has arisen as to what factors would, in urn, influence entrepreneurship to determine the most appropri- te actions to stimulate these factors and, thus, stimulate economic rowth. Various factors have been considered, with special atten- ion on innovations (e.g., Galindo & Méndez, 2013, 2014; Ferreira, , S.L.U. This is an open access article under the CC BY-NC-ND license (http:// https://doi.org/10.1016/j.jik.2020.06.001 https://www.journals.elsevier.com/journal-of-innovation-and-knowledge http://crossmark.crossref.org/dialog/?doi=10.1016/j.jik.2020.06.001&domain=pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ mailto:mmendezpi@ccee.ucm.es https://doi.org/10.1016/j.jik.2020.06.001 http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ r O S T E a d 2 2 S t o i n a n l u s a t o t w 1 b t s t r g i t o g a b P s 2 w t p M G 2 s r a g & M.-T. Méndez-Picazo, M. -A, Galindo-Mart, M.-S. Castaño-Martínez et al. Fernandes, & Ratten, 2017; Mazzarol & Reboud, 2017; Schmitz, Urbano, Dandolini, de Souza, & Guerrero, 2017; Betts, Laud, & Kretinin, 2018; Malerba & McKelvey, 2019; Medeiros, Marques, Galvão, & Braga, 2020), institutions (Acemoglu & Robinson, 2008; Acemoglu, 2003; Acs, Estrin, Mickiewicz, & Szerb, 2018; Bosma, Content, Sanders, & Stam, 2018; Boudreaux, Nikolaev, & Klein, 2019; Elert & Henrekson, 2017; Galindo-Martín, Méndez-Picazo, & Castaño-Martínez, 2019; Urbano, Turro, & Aparicio, 2019), human capital (Autio & Acs, 2010; Capelleras, Contin-Pilart, Larraza- Kintana, & Martin-Sanchez, 2019; Nasiri & Hamelin, 2018) and other aspects, even considering the feedback effects in the analy- sis. Among others, these elements could indicate how the economic growth could have a positive effect on entrepreneurship (Galindo & Méndez, 2014). These analyses conclude that there is a direct relationship between entrepreneurship and economic growth. Therefore, the political decision-maker has an additional factor to the traditional ones, public spending, taxes, etc., to stimulate growth. That is why the interest has arisen to know what factors would influence entrepreneurship in turn, to specify what would be the most appro- priate actions to stimulate this factor and thus stimulate it through economic growth. The worrisome environmental situation of many countries has aroused growing interest in establishing actions to combat current problems without compromising the situation of future genera- tions. This has caused rethinking of the objective to be achieved, which has led to increasing attention being paid to sustainable development, and the emergence of new activities that foster the appearance of new economic agents in economic activity; in our case, social entrepreneurship. Thus, sustainable development has become the essential objec- tive of political decision-makers. And, from this new perspective, it is important to know, as happened in the case of economic growth, the factors that influence said development. In this sense, contri- butions arise that consider social entrepreneurship as a new factor to consider in changing the objective of economic growth for sus- tainable development (Johnson & Schaltegger, 2019; Schaltegger, Hörisch, & Loorbach, 2020) to avoid compromising the situation of future generations through current policies designed to achieve present-day well-being. Therefore, taking the previous comments into account, one of the first questions to consider is the relationship between both general and social entrepreneurship and sustainable development. But it is also interesting to ascertain the factors that can stimulate both types of entrepreneurship, as this would help in designing appropriate measures to promote sustainable develop- ment through business activity. In this case, unlike the analyses that have been carried out, the main factors are going to be grouped into two main categories: sociocultural and economic. This choice is essentially due to the fact that both the social and cultural and the economic environment influence entrepreneurial activity. There- fore, it is important to determine the relationship of these factors with each of the types of entrepreneurship considered and show the relevance in each of the cases. Therefore, the objective of this paper is to conduct a double empirical analysis. Firstly, to analyze the relationship between both general entrepreneurship and social entrepreneurship and sustainable development and, secondly, to study the relation- ship of sociocultural and economic factors with both types of entrepreneurship. The empirical analysis proposes a struc- tural equation modeling with partial least squares, allowing the introduction of latent variables and the estimation of multiple relationships, thus improving upon multivariate tech- niques that can only examine one relationship at a time (Barclay, Higgins, & Thompson, 1995; Chin, Marcolin, & Newsted, 2003). i i r a 70 Journal of Innovation & Knowledge 6 (2021) 69–77 Section 2 explains the main theoretical aspects related to these elationships. In section 3 the empirical analysis for the case of 15 ECD countries is developed for the period between 2015–2016. ection 4 provides the conclusions. heoretical analysis ntrepreneurship and social entrepreneurship Entrepreneurship has had positive effects on economic growth, nd this relationship has been analyzed thoroughly in recent ecades (e.g., Audretsch & Keilbach, 2004a, 2004b; Audretsch, 005; Alpkan et al., 2010; Acs et al., 2012; Méndez-Picazo et al., 012; Nissan et al., 2012; Castaño et al., 2016; Doran et al., 2018; toica et al., 2020). This positive relationship is due mainly to he activities of entrepreneurs regarding, for example, the devel- pment of new products, the search for new markets, and the ntroduction of innovations, which have positive effects on eco- omic growth, which, in turn, has positive effects on job creation nd social well-being. Given this possibility of stimulating eco- omic growth through entrepreneurial activity, the specialized iterature has also focused on determining the factors that can stim- late entrepreneurship to design appropriate economic policy. Furthermore, the increasing interest in environmental problems uffered by economies has led to attention being paid to other vari- bles and objectives that take these problems into account. For his reason, the objective of economic growth gives way to the bjective of “sustainable development,” which refers to the attempt o achieve economic development that will satisfy current needs ithout compromising the situation of future generations (UN, 987). This implies, among other issues, the alteration of traditional usiness practices that are considered environmentally unsus- ainable, replacing them with others that are environmentally ustainable, thus reducing environmental damage. Therefore, the erm sustainable development implies the use of non-renewable esources in such a way as to make them viable and usable by future enerations. As in the case of economic growth, entrepreneurial activ- ty could develop activities that respect the environment and, herefore, it could also be a stimulating factor for sustainable devel- pment. Consideration of environmental problems has led to the emer- ence of other activities of and other ways of operating by economic gents. The concept of social entrepreneurship has arisen and has een considered gradually in analyses (Middermann, Kratzer, & erner, 2020). Though different definitions of social entrepreneur- hip have been offered (Dees, 1998; Hockerts, 2017; Light, 2006, 009; Mair & Martí, 2006), from the perspective of this paper, e can consider it in general terms as a process involving oppor- unities and actions that try to solve social and environmental roblems by searching for innovative solutions (Brooks, 2009; éndez-Picazo, Ribeiro-Soriano, & Galindo-Martín, 2015; Miller, rimes, McMullen, & Vogus, 2012; Miska, Stahl, & Mendenhall, 013; Nga & Shamuganathan, 2010). As in the case of general entrepreneurship, social entrepreneur- hip has a positive effect on sustainable development through its elated activities, facilitating job creation, and, thus, increasing the ggregate demand of the economy that will stimulate economic rowth. In enhancing sustainable development, both general (Doran Ryan, 2016; Liao, 2018) and social entrepreneurship play an mportant role (Johnson & Schaltegger, 2019). Both are interested n achieving the objective of sustainable development, as envi- onmental responsibility represents a good business opportunity nd will allow entrepreneurs access new markets, improve their a I t t a t n e P m e d p p d t r a c e n s c a t e p 2 m a w s d e i o d E D s u m u l o ( a t r t a d M.-T. Méndez-Picazo, M. -A, Galindo-Mart, M.-S. Castaño-Martínez et al. image with stakeholders, and differentiate their products (Ambec & Lanoie, 2008). In short, general and social entrepreneurship have a positive relationship with sustainable development. For this rea- son, it is interesting to determine the factors that influence both types of entrepreneurship. In this sense, different factors, such as institutions (Acemoglu & Robinson, 2008; Acemoglu, 2003; Acs et al., 2018; Bosma et al., 2018; Boudreaux et al., 2019; De Beule, Klein, & Verwaal, 2019; Diab & Metwally, 2019; Urbano, Aparicio, & Audretsch, 2019; Elert & Henrekson, 2017; Galindo-Martín et al., 2019), education, and social climate have been considered. From the perspective of this paper the different factors are grouped in two categories: sociocultural and economic. Sociocultural factors Regarding sociocultural factors, it must be considered that the social environment is of great importance in stimulating entrepreneurial activity, basically from two perspectives. From the institutional perspective, without efficient institutions that try to protect property rights, few economic agents would be interested in developing an entrepreneurial activity. The institutions are in charge of establishing the rules of the game by which this activity will be carried out. If these rules are either not clear or involve a delay in decision-making, due to excessive bureaucracy, for exam- ple, entrepreneurial activity will be affected negatively. For this reason, some studies indicate that the structure of institutions influences the type of entrepreneurship existing in society (Baumol, 1990; Boettke & Coyne, 2003; Gregori, Wdowiak, Schwarz, & Holzmann, 2019; Sobel, 2008), whereas other papers indicate that such structure may discourage entrepreneurial activity (Baumol, 1990; Johnson, Kaufmann, & Shleifer, 1997; Hall & Sobel, 2008). The structure of institutions can be divided into two large groups: formal and informal. Formal institutions are characterized by hav- ing a very strong cultural component (North, 1990), which is what encourages entrepreneurs to carry out their activities. For this rea- son, the rules designed by this type of institution are aimed at increasing economic freedom (Powell & Rodet, 2012), and reduc- ing corruption would have a positive effect on entrepreneurship (Anokhin & Schulze, 2009; Avnimelech, Zelekha, & Sharabi, 2014; Berdiev & Saunoris, 2018; Cherrier, Goswami, & Ray, 2018; Zhang, 2019). In this group, the role of education and skills’ improvement must also be considered (Gavron, Cowling, Holtham, & Westall, 1998; Reynolds, Hay, & Camp, 2000), as a higher educational level makes it easier for individuals to favor the introduction of and desire for innovations and to make more efficient use of the different instruments and tools necessary to carry out their activity by allow- ing entrepreneurs to identify the market opportunities that may arise (Barreneche García, 2013; Portuguez Castro, Ross Scheede, & Gómez Zermeño, 2019; Rashid, 2019). In this case, the variable to consider would be schooling, as a proxy variable for education and human capital. Economic factors The second group of factors to consider are economic. In this area, there are different variables that could stimulate entrepreneurial activity, both general and social. The first factor is the fiscal policy designed by the government. In general, govern- ment activity can stimulate entrepreneurship (Audretsch & Link, 2019; Audretsch, 2003) by correcting failures that can occur in mar- kets due to either external shocks or misallocation of resources. Therefore, the government can stimulate entrepreneurial activity through its spending policies (McMullen, Bagby, & Palich, 2008; Gnyawali & Fogel, 1994), for example, by improving income distri- bution and investing in education and R&D. These two possibilities & R 1 71 Journal of Innovation & Knowledge 6 (2021) 69–77 re considered in the model estimated in the following section. nvestment in education has been included as a sociocultural fac- or, since, as indicated, what is intended is that entrepreneurs use he different instruments more efficiently to conduct their activities nd can better identify the opportunities offered by markets. Regarding income distribution, its importance lies in the fact hat an adequate social climate is generated that facilitates eco- omic activity, which supposes an additional incentive to stimulate ntrepreneurship, both general and social (Galindo Martin, Méndez icazo, & Alfaro Navarro, 2010; Castaño et al., 2016). Government easures can also stimulate entrepreneurship indirectly through mployment policy. A reduction in unemployment is a stimulus to emand in the market and, therefore, a greater quantity of already roduced are demanded and new products can be offered. This rovides the possibility of increasing production of activities in evelopment and also provides new possibilities and market niches hat would stimulate the appearance of new entrepreneurs. For this eason, a positive relationship between employment and general nd social entrepreneurship is expected. However, there are also detractors of government policies, onsidering that public measures can allow non-productive ntrepreneurs to continue operating in the market, which would egatively affect economic growth (Campbell & Mitchell, 2012). The other two economic factors to consider are investment pending and research and development (R&D). As already indi- ated, both variables allow entrepreneurs to be more competitive nd, especially, to be able to create and implement technology hat is less harmful to the environment, even prompting other ntrepreneurs to include these advances in their own production rocesses (Amorós, Poblete, & Mandakovic, 2019, Urbano et al., 019b, Duguet, 2004; Yun, Kwon, & Choi, 2019). Considering all these theoretical aspects, the model to be esti- ated in the following section includes two groups of sociocultural nd economic factors. Both factors have a positive relationship ith general entrepreneurship and social entrepreneurship. The ociocultural variables considered are corruption, economic free- om, schooling, and human capital. The variables considered as conomic factors are income distribution, employment, spend- ng on fixed capital, and spending on R&D. Finally, both types f entrepreneurship have a positive relationship with sustainable evelopment. mpirical analysis ata and methods A quantitative, correlational, and explanatory empirical analy- is is carried out to identify causal relationships among variables by sing a structural equation model (SEM). To calculate the proposed odel, a multiple regression with Partial Least Squares (PLS) is sed. This technique allows one to build research models by estab- ishing latent variables. Latent variables are variables that are not bserved directly but are inferred from other observed variables indicators) (Haenlein & Kaplan, 2004). PLS is model validation mainly oriented to causal-predictive nalysis and is usually used in situations of high complexity, but low heoretical information (Roldán & Sánchez-Franco, 2012). It is also ecommended for use with variables with non-normal distribu- ions, non-experimental research with data obtained from surveys, not very large study sample, and a theory that has not yet been eveloped in a solid way (Aldás-Manzano, 2012; Rigdon, Sarstedt, Ringle, 2017; Sarstedt, Bengart, Shaltoni, & Lehmann, 2018; Hair, isher, Sarstedt, & Ringle, 2019). To contrast the previous theoretical relationship, data from 5 OECD countries (Belgium, Finland, Germany, Italy, Nether- p k “ h b f i r s e a f e 2 t g a i e o e t D t s h d d D R m o s h t c d u v v r o a v c 2 a i l M.-T. Méndez-Picazo, M. -A, Galindo-Mart, M.-S. Castaño-Martínez et al. lands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, United Kingdom, United States) from between 2015–2016 have been used, providing a sample of 30 records, although a small sample is suitable for a PLS estimate (Hair, Hult, Ringle, & Sarstedt, 2016). The SEM model has been estimated using the PLS technique with SmartPLS software 3. (Ringle, Wende, & Becker, 2015). The SEM has two elements (Henseler, Ringle, & Sarstedt, 2015; Henseler, Ringle, & Sinkovics, 2009): (a) the structural model or inner model that represents constructs (circles) or latent variables and the relationship between exogenous and endogenous vari- ables, and (b) measurement models or outer models that show constructs and the indicator variables (rectangles) (2016, Hair, Ringle, & Sarstedt, 2011). The two proposed models are reflective (Fig. 1 and Fig. 2). A reflective model is common in social sciences, and it is directly based on classical test theory. According to Nunnally and Bernstein (1994), the measurement model represents the effects (or mani- festations) of an underlying construct (Diamantopoulos, Riefler, & Roth, 2008). Table 1 shows the indicators that have been assigned to each of the latent variables. Three different indicators have been used to measure the latent variable “Sustainable Development.” AI shows the adjusted net national income calculated by gross national income minus con- sumption of fixed capital and natural resources’ depletion; The Human Development Index (HDI) is a statistical indicator of human development that is produced each year by the United Nations. It measures three dimensions: health, education, and having a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions; the GDPpc variable is GDP per capita in constant 2010 U.S. dollars (World Bank, 2020a). To measure “Entrepreneurship,” the indicator TEAOPP is the percentage of the population aged 18–64 years who are entrepreneurs and whose main motivation is to benefit from an opportunity. This kind of entrepreneur claims to be driven by opportunity, as opposed to finding no other option for work. Conversely, “social entrepreneurial activity” (SEA).1 The GEM define SEA as any kind of activity, organization, or initiative that has a particularly social, environmental, or community objective. This might include providing either services or training to socially deprived or disabled persons, activities aimed at reducing either pollution or food-waste, and organizing self-help groups for com- munity action (Bosma, Schott, Terjesen, & Kew, 2015). Finally, the latent variable “Socio-cultural Factor” comprises four indicators: The Economic Freedom Index (EFI) from The Heritage Foundation, control of corruption (CC) from the World Bank (2020b), and two indicators to measure human capital (HC). According to Wennekers, Van Wennekers, Thurik, and Reynolds (2005)) greater control of corruption favors business activity in developed countries, opportunity entrepreneurship in particular, and, in addition, excessive bureaucratic procedures indicate the inadequate functioning of institution. This is one of the main obstacles to entrepreneurial activity, which is why we chose the EFI indicator, as better functioning markets, protection of prop- erty rights, and better regulation favor entrepreneurship (Jacob & Michaely, 2017; Chambers & Munemo, 2019). As already men- tioned in theoretical analysis, human capital and knowledge also play a key role in innovation and allowing the entrepreneur to be more competitive and introduce innovations in the market that indirectly favor sustainable development (Malerba & McKelvey, 2019; Poschke, 2018). 1 The latest available SEA data is from 2015, SEA 2016 data has been estimated as a proportion, using data from SEA 2015, TEA 2015 and 2016. s u a F r s e 72 Journal of Innovation & Knowledge 6 (2021) 69–77 The CC indicator includes the opinions of individuals on how ublic power performs its functions for private, considering all inds of corruption, both petty and grand types, in addition to the capture” of the state by elites and private interests. The indicator as values from 0–100, with the lowest rank being 0 and the highest eing 100 (World Bank, 2020b). The EFI indicator is a complex index that measures economic reedom based on 12 quantitative and qualitative factors, grouped nto four broad economic freedom categories: rule of law (property ights, government integrity, judicial effectiveness), government ize (government spending, tax burden, fiscal health); regulatory fficiency (business freedom, labor freedom, monetary freedom), nd open markets (trade freedom, investment freedom, financial reedom). Each of the twelve economic freedoms within these cat- gories is graded on a scale of 0–100 (The Heritage Foundation, 020). HC1 is gross enrollment rate in tertiary education with respect o total enrollment at all levels of education, and HC2 is the sum of ross public expenditures in education and in health, expressed as percentage of GDP. Finally, we present the latent variable “Economic Factor.” the ndicators for this variable are: Gross fixed capital formation, xpressed as a percent of GDP (GFCF); gross domestic expenditures n research and development, expressed as a percent of GDP (R&D); mployment to population ratio, which is the proportion of a coun- ry’s population that is employed (N); and the indicator Income istribution (ID) which is calculated like hundred minis GINI index o achieve internal coherence of the construct; this indicator mea- ures how the distribution of income among either individuals or ouseholds within an economy deviates from a perfectly equal istribution. Therefore, a high value of ID shows a better income istribution. These indicators come from the World Bank’s World evelopment Indicators database (World Bank, 2020a). esults Figs. 1 and 2 show the graphic representation of the considered odel. To calculate this relationship, some constructs are delayed ne year, due to entrepreneurship needing some time to influence ustainable development, and social factor and economic factor ave to in the same period that entrepreneurship; to represent hat the constructs are delayed, the subscript (t-1) is added to the onstructs in Figs. 1 and 2. Therefore, the construct sustainable evelopment uses data from 2016 to 2017, and the other constructs se data from 2015 to 2016. This model follows the theoretical framework set out in the pre- ious section. This diagram represents the relation among latent ariables and the main results of the estimation. This graphical rep- esentation shows two statistical models: (a) the structural model r inner model, which represents constructs (circles) or latent vari- bles and the relationship between exogenous and endogenous ariables, and (b) the measurement models or outer models of the onstructs and the indicator variables (rectangles) (2016, Hair et al., 011). The study of cross loading appears in Table 2. As cross-loads re always greater for the latent variables on which the respective tems are loaded, the indicators would be assigned correctly to each atent variable. The reliability and validity of the measurement model are pre- ented below. The internal consistency reliability is measured by sing Jöreskog (1971) composite reliability. Higher values gener- lly indicate higher levels of reliability (Diamantopoulos, Sarstedt, uchs, Wilczynski, & Kaiser, 2012). Another important measure of eliability is the relationship between each indicator and its con- truct, which is measured by the value of Cronbach’s alpha. It is stablished that the construct has internal consistency when the M.-T. Méndez-Picazo, M. -A, Galindo-Mart, M.-S. Castaño-Martínez et al. Journal of Innovation & Knowledge 6 (2021) 69–77 Fig. 1. Estimated model of entrepreneurship. Note: p-value * = p ≤ 10%; **= p ≤ 5%; ***= p ≤ 1% Source: Own elaboration No c F a n t n l l Fig. 2. Estimated model of social entrepreneurship. value of Cronbach’s alpha is greater than 0.7 (Barclay et al., 1995; Nunnally & Bernstein, 1994). However, Cronbach’s alpha is a less precise measure of reliability than is composite reliability, as the items are unweighted. Conversely, with composite reliability, the items are weighted based on the construct indicators’ individual loadings and, hence, this reliability is higher than is that of Cron- bach’s alpha (Hair et al., 2019). Thus, as can be observed in Table 3, all the latent variables have a Cronbach’s Alpha higher than 0.7 and a Composite Reliability higher than 0.8. In addition, Average Variance Extracted (AVE) indicates the variance extracted from the indicators, including the common vari- ability absorbed by the latent variable. A value greater than 0.5 e e M 73 te: p-value * = p ≤ 10% Source: Own elaboration an be accepted as a good measure to fit (Fornell & Larcker, 1981; ornell, 1982). Also, it is observed that this criterion is fulfilled for ll the latent variables of both models (see Table 3). The R2 coefficient represents the combined effects of exoge- ous latent variables on the endogenous latent variable. Thus, he coefficient represents the amount of variance in the endoge- ous construct that is explained by all of the exogenous constructs inked to it. This coefficient is calculated as the squared corre- ation between the actual and the predictive value of a specific ndogenous construct (Rigdon, 2012; Sarstedt et al., 2018). All the ndogenous latent variables have values greater than 0.1 (Falk & iller, 1992), except for sustainable development in model 2. How- M.-T. Méndez-Picazo, M. -A, Galindo-Mart, M.-S. Castaño-Martínez et al. Journal of Innovation & Knowledge 6 (2021) 69–77 Table 1 Definition of variables. LATENT VARIABLE INDICATORS Sustainable Development AI: Adjusted net national income per capita (constant 2010 US$) (World Bank, 2020a) HDI: Human Development Index (United Nations Development Programme (UNDP, 2020). GDPpc: GDP per capita (constant 2010 US$) (World Bank, 2020a) Entrepreneurship TEAOPP: Entrepreneurship by opportunity (GEM, 2020). Social Entrepreneurship SEA: Social entrepreneurship activity (GEM, 2020). Socio-cultural Factor CC: Control of Corruption (World Bank, 2020b). EFI: Economic Freedom Index (The Heritage Foundation, 2020). HC1: Gross enrollment rate in tertiary education (% of GDP) (World Bank, 2020a) HC2: Public expenditure in education and in health (World Bank, 2020a) Economic Fac- tor GFCF: Gross fixed capital formation (% of GDP) (World Bank, 2020a) ID: Income Distribution (World Bank, 2020a) N: Employment to population ratio. (World Bank, 2020a) R&D: Gross domestic expenditures on research and development (% of GDP) (World Bank, 2020a) Table 2 Cross-loads for convergent validity. CulturalFactor Economic Factor Entrepreneurship SustainableDevelopment Model 1 AI 0.82 0.78 0.73 0.99 CC 0.93 0.81 0.63 0.79 EFI 0.83 0.73 0.48 0.72 GDPpc 0.83 0.82 0.72 0.98 GFCF 0.53 0.76 0.36 0.64 HC1 0.36 0.07 0.12 0.23 HC2 0.91 0.76 0.68 0.80 HDI 0.85 0.82 0.71 0.95 ID −0.06 0.21 −0.03 0.06 N 0.75 0.87 0.59 0.71 R&D 0.80 0.89 0.65 0.75 TEAOPP 0.67 0.66 1.00 0.74 Model 2 AI 0.82 0.80 0.23 0.99 CC 0.88 0.77 0.20 0.76 EFI 0.77 0.75 0.18 0.69 GDPpc 0.84 0.83 0.26 0.98 GFCF 0.51 0.83 0.29 0.66 HC1 0.44 0.03 0.09 0.25 HC2 0.95 0.73 0.44 0.81 HDI 0.84 0.78 0.12 0.93 ID −0.12 0.21 −0.06 0.04 N 0.70 0.89 0.30 0.70 R&D 0.79 0.80 0.14 0.70 SEA 0.35 0.33 1.00 0.25 Table 3 Reliability and validity of the outer models. Cronbach’s Alpha Composite Reliability AVE R Square MODEL 1 Cultural Factor 0.78 0.86 0.63 Economic Factor 0.74 0.81 0.55 Entrepreneurship 1.00 1.00 1.00 0.48 Sustainable Development 0.97 0.98 0.95 0.53 MODEL 2 Cultural Factor 0.78 0.86 0.62 u i T F t Economic Factor 0.74 Social Entrepreneurship 1.00 Sustainable Development 0.97 ever, the values for R2 in model 1 are estimated at approximately 0.5, which indicates a determining effect of the exogenous variables on the endogenous variable. For evaluating the statistical significance of the latent regression coefficients, PLS used a bootstrapping technique. Such a technique analyses the significance of the relationships between variables. Fig. 1 shows that all relationships among variables are signifi- cant, (p-value * = p ≤ 10%; **= p ≤ 5%; ***= p ≤ 1%). In most settings, researchers choose a significance level of 5%, which implies that the p-values must be lower than 0.05 to render the relationship p a t 74 0.81 0.54 1.00 1.00 0.13 0.98 0.94 0.05 nder consideration significant. However, in exploratory studies it s common to use a significance level of 10% (Hair et al., 2016). Table 4 shows the total indirect effects between latent variables. hese indirect effects are added to the direct effects that appear in ig. 1. These effects are positive and higher in model 1. The main results obtained by comparing the two models show hat both types of entrepreneurship, general and social, have a ositive effect on sustainable development, as shown by Ambec nd Lanoie (2008) and Liao (2018), but the effect is greater in he case of general entrepreneurs (0.73 and significance of p ≤ 1%) M.-T. Méndez-Picazo, M. -A, Galindo-Mart, M.-S. Castaño-Martínez et al. Table 4 Indirect effects between latent variables. Specific Indirect Effects MODEL 1 Cultural Factor -> Entrepreneurship -> Sustainable Development 0.27 Economic Factor -> Entrepreneurship -> Sustainable Development 0.26 MODEL 2 Cultural Factor -> Social Entrepreneurship -> Sustainable Development 0.06 Economic Factor -> Social Entrepreneurship -> Sustainable 0.03 e h C f e t s e e t a b e r f e i s a a r o t t F o I i a t e l c t e i s e e t e i m i t h t d w c p Development than in the case of social entrepreneurs (0.23 and significance of p ≤ 10%). On the one hand, sociocultural factors are observed to be posi- tively related to general entrepreneurial activity, with a coefficient of 0.37 and significance of p ≤ 10%, whereas, in the case of social entrepreneurs, the coefficient is less than 0.25. If the outer loads are compared, CC and EFI are observed to have high outer loads in both models, but the outer loads are higher in the case of gen- eral entrepreneurs. Therefore, proper management of institutions would have a positive effect in both types of entrepreneurship, in line with the findings of Sobel (2008) and Powell and Rodet (2012). On the other hand, with respect to human capital, we verify that the indicator HC2 has a greater weight than does HC1 in both cases, and this is more prominent in the case of social entrepreneurs. Thus, public policies aimed at investing in human capital through public education and public health will stimulate both types of entrepreneurial activity. Finally, economic factors are related positively to general entrepreneurial activity, showing a coefficient of 0.35 and sig- nificance of p ≤ 5%. The coefficient is lower in the case of social entrepreneurs (0.13). Regarding the analysis of the outer loads, employment ratio presents higher values in both cases; that is the greater the employment, the greater the stimulation of demand, which has a positive effect on entrepreneurial activity. On the other hand, income distribution is less important than are the other indicators. Finally, investment and R&D investment also have remarkable effects in both cases. Therefore, public spend- ing policies that improve employment, income distribution, and investment in R&D would stimulate both types of entrepreneur- ship. Entrepreneurship is one of the variables that has been consid- ered when analyzing the factors that improve economic growth. Increased awareness of environmental problems has changed the goal to be achieved, considering the effects on sustainable devel- opment. And the role of the social entrepreneur in this relationship has also been considered. In short, the estimated models show that both factors, sociocultural and economic, have a greater impact on general entrepreneurship than on social entrepreneurship. On the one hand, sociocultural factors, corruption, and economic freedom have a greater effect on general entrepreneurship, whereas variables related to training and human capital have a greater impact on social entrepreneurship. Therefore, measures aimed at improving the development of institutions and designed to reduce corrup- tion and provide a greater margin for action in the markets would have a greater impact on general entrepreneurship, whereas mea- sures aimed at improving education and health would have a higher effect on social entrepreneurship. In the case of economic factors, spending on gross fixed capital training and employment has a greater effect on social entrepreneurship, whereas spending on R&D would have a greater R U 75 Journal of Innovation & Knowledge 6 (2021) 69–77 ffect on general entrepreneurship. The income distribution would ave a more or less similar effect in both cases. onclusions and discussion Entrepreneurship is one of the variables chosen to analyze the actors that stimulate economic growth. Increased awareness of nvironmental problems has led to an alteration in the objective o be achieved, introducing analysis of the effects of entrepreneur- hip on sustainable development. In this area, the role of the social ntrepreneur in this relationship has also been considered. Due to the positive relationship between both types of ntrepreneurship on sustainable development, it is important to try o find out who has the greatest impact on sustainable development nd what the factors are that stimulate this entrepreneurial activity y grouping these factors into two main groups: sociocultural and conomic. To achieve this objective, an empirical analysis has been car- ied out for the case of 15 OECD countries that shows the ollowing results: Both types of entrepreneurial activity, gen- ral and social, stimulate sustainable development, although the mpact of general entrepreneurship is greater than is that of ocial entrepreneurship. From this perspective, measures aimed t stimulating entrepreneurial activity would indirectly favor the chievement of greater sustainable development. Taking this result into account, it is necessary to consider the ole played by the factors in favoring entrepreneurship. The results btained show that both groups of factors are positively related o the two types of entrepreneurship analyzed, but the sociocul- ural factor shows a greater impact than does the economic one. aced with this common result, it should be noted that the weight f the indicators is different depending on the type of entrepreneur. n the case of general entrepreneurship, the proper functioning of nstitutions and the control of corruption show a greater effect, nd in the case of social entrepreneurship the control of corrup- ion and measures aimed at education and health have a higher ffect. This implies that in both cases, measures aimed at control- ing and improving the behavior of institutions aimed at reducing orruption would have a beneficial effect. Regarding economic factors, spending on gross fixed capi- al training and employment have a greater effect on social ntrepreneurship, whereas R&D and unemployment show a high mpact on general entrepreneurship. Income distribution shows a imilar effect in both cases. Therefore, public sector actions aimed at stimulating ntrepreneurship can have different effects on both types of ntrepreneurship. Policies aimed at promoting human capi- al, employment, and investment aid would favor more social ntrepreneurship, whereas those that increase innovation and mprove institutions and are aimed at reducing corruption and aking the market freer and more effective would have a greater mpact on general entrepreneurship. On the other hand, redis- ributive policies aimed at improving income distribution would ave a similar impact on both types of entrepreneurship. This study is subject to improvement by introducing more coun- ries in the sample to compare the situation of countries with ifferent structures. 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factors Empirical analysis Data and methods Results Conclusions and discussion References