Entrepreneurial intention, cognitive social capital and culture: empirical analysis for Spain and Taiwan

Documents de Treball ENTREPRENEURIAL INTENTION, COGNITIVE SOCIAL CAPITAL AND CULTURE: EMPIRICAL ANALYSIS FOR SPAIN AND TAIWAN Francisco Liñán Francisco J. Santos José L. Roldán Document de Treball núm. 08/3 Departament d'Economia de l'Empresa © Francisco Liñán, Francisco J. Santos, José L. Roldán. Coordinador / Coordinator Documents de treball: David Urbano http://selene.uab.es/dep-economia-empresa/dt e-mail: [email protected] Telèfon / Phone: +34 93 5814298 Fax: +34 93 5812555 Edita / Publisher: Departament d'Economia de l'Empresa http://selene.uab.es/dep-economia-empresa/ Universitat Autònoma de Barcelona Facultat de Ciències Econòmiques i Empresarials Edifici B 08193 Bellaterra (Cerdanyola del Vallès), Spain Tel. 93 5811209 Fax 93 5812555 ISSN: 1988-7736. Documents de Treball (Departament d’Economia de l’Empresa, Universitat Autònoma de Barcelona) Febrero / February, 2008 ENTREPRENEURIAL INTENTION, COGNITIVE SOCIAL CAPITAL AND CULTURE: EMPIRICAL ANALYSIS FOR SPAIN AND TAIWAN Francisco Liñán Francisco J. Santos José L. Roldán Document de Treball núm. 08/3 La sèrie Documents de treball d'economia de l'empresa presenta els avanços i resultats d'investigacions en curs que han estat presentades i discutides en aquest departament; això no obstant, les opinions són responsabilitat dels autors. El document no pot ser reproduït total ni parcialment sense el consentiment de l'autor/a o autors/res. Dirigir els comentaris i suggerències directament a l'autor/a o autors/res, a la direcció que apareix a la pàgina següent. A Working Paper in the Documents de treball d'economia de l'empresa series is intended as a mean whereby a faculty researcher's thoughts and findings may be communicated to interested readers for their comments. Nevertheless, the ideas put forwards are responsibility of the author. Accordingly a Working Paper should not be quoted nor the data referred to without the written consent of the author. Please, direct your comments and suggestions to the author, which address shows up in the next page. ENTREPRENEURIAL INTENTION, COGNITIVE SOCIAL CAPITAL AND CULTURE: EMPIRICAL ANALYSIS FOR SPAIN AND TAIWAN Francisco Liñán, Universidad de Sevilla, Av. Ramón y Cajal, 1. 41018-Sevilla (Spain). Tel.: +34.954554487. Fax: +34.954551636. Email: [email protected] Francisco J. Santos Universidad de Sevilla, Av. Ramón y Cajal, 1. 41018-Sevilla (Spain). Tel.: +34.954557641. Fax: +34.954551636. Email: [email protected] José L. Roldán Universidad de Sevilla, Av. Ramón y Cajal, 1. 41018-Sevilla (Spain). Tel.: +34.954554458. Fax: +34.954556989. Email: [email protected] -1 - ENTREPRENEURIAL INTENTION, COGNITIVE SOCIAL CAPITAL AND CULTURE: EMPIRICAL ANALYSIS FOR SPAIN AND TAIWAN Abstract Objectives: The main purpose of this paper is building a research model to integrate the socioeconomic concept of social capital within intentional models of new firm creation. Nevertheless, some researchers have found cultural differences between countries and regions to have an effect on economic development. Therefore, a second objective of this study is exploring whether those cultural differences affect entrepreneurial cognitions. Research design and methodology: Two samples of last year university students from Spain and Taiwan are studied through an Entrepreneurial Intention Questionnaire (EIQ). Structural equation models (Partial Least Squares) are used to test the hypotheses. The possible existence of differences between both sub-samples is also empirically explored through a multigroup analysis. Main outcomes and results: The proposed model explains 54.5% of the variance in entrepreneurial intention. Besides, there are some significant differences between both subsamples that could be attributed to cultural diversity. Conclusions: This paper has shown the relevance of cognitive social capital in shaping individuals’ entrepreneurial intentions across different countries. Furthermore, it suggests that national culture could be shaping entrepreneurial perceptions, but not cognitive social capital. Therefore, both cognitive social capital and culture (made up essentially of values and beliefs), may act together to reinforce the entrepreneurial intention. -2 - 1.- Introduction The entrepreneurship research programme, among its different fields of study, has recently been focused on the analysis of potential entrepreneurs’ behaviour, and how they carry out the process of opportunity recognition and firm creation (Krueger and Brazeal, 1994, Reynolds, Hay and Camp, 1999, Krueger 2003, Shane and Eckhardt, 2003). However, as it is well known, one of the main difficulties in analysing entrepreneurial behaviours is the need for multidisciplinary research. From a psychological point of view, some scholars had been elaborating different models to explain why some persons choose to become entrepreneurs and others do not (McClelland, 1961, Brockhaus, 1980, Cooper and Dunkleberg, 1987). From a sociological point of view, other scholars have emphasized the influence of some social factors and networks (social structure) to gain access to a variety of resources very important for the creation of new firms and for the consolidation of existing firms (Wilken 1979, Birley 1985, Butler and Hansen 1991, Johannisson, 1995, Jack and Anderson, 2002, Hoang and Antoncic, 2003, Greve and Salaff, 2003). Nevertheless, few studies have attempted to connect both the psychological and the sociological views of entrepreneurship. Advances in social cognition, such as those derived from Bandura’s (1977) social learning theory, may be applied to the field of entrepreneurship. They offer new possibilities to better understand the role played by social relationships in the intention-creation and opportunity-recognition cognitive processes (Krueger and Carsrud 1993, Krueger 2003). However, the links between social structure and cognitive process has remained in a secondary position in these models. -3 - One possibility to better analyse this link could be inserting into these models some constructs from the cognitive dimension of social capital. Social capital is a concept in an emerging phase which could be defined as capital captured in the form of social relationships (Lin 2003). Its cognitive dimension, that is to say, cognitive social capital, could be defined as the values, attitudes, beliefs and trust transmitted through those social relationships (Naphiet and Ghoshal, 1998, Uphoff, 2000, Grootaert and Bastelaer, 2001). Therefore, in an attempt to shed some light into the process of entrepreneurial emergence and firm creation, this paper firstly tries to build a research model which includes cognitive social capital into an entrepreneurial intention model. This model will be empirically tested using the Partial Least Square statistic technique. This model is expected to be cross-culturally robust. Nevertheless, some social researchers have found clear cultural differences among countries and regions which influence economic development. Therefore, a second objective of the paper is to explore whether these cultural differences could have some influence on entrepreneurial cognitions. To reach these objectives, two samples of young undergraduate students in the last year of their degree from Spain and Taiwan will be used. This will allow us to explore whether cultural differences could also play some relevant influences on entrepreneurial cognitions. Therefore, in addition to testing the hypotheses of the research model, an exploratory analysis (multigroup analysis) will be performed to look for possible differences among the target population of both countries. -4 - After this introduction, the paper is organized in six additional parts. In the following section, the entrepreneurial intention models and the meaning of the cognitive dimension of social capital will be presented. In section three, social capital will be introduced into entrepreneurial intention models, leading to our research model. The specific hypotheses to be tested are then made explicit. In section four, the possible relationship between culture and entrepreneurial activity will be considered. The fifth section describes the methodology used for sample selection, data gathering and for the statistical analysis. Main results are presented in section six. The paper ends up with a discussion and interpretation of those results and their implications. 2. - Theoretical background a) Entrepreneurship and intention-based models Much research has tried to explain why some persons but not others choose to become entrepreneurs. They started paying attention to psychological characteristics and personality traits which might differentiate entrepreneurs from the rest of the population (McClelland, 1961, Collins and Moore, 1964, Borland, 1975). Later on, other research works emphasized the importance of different demographic factors among entrepreneurs. Age, gender, birth, religion, ethnic group, education, socioeconomic status or professional experience would be among these factors (Cooper and Dunkelberg, 1987, Veciana 1989, Reynolds, Storey and Westhead, 1994, Storey 1994). Nevertheless, from a theoretical point of view, these approaches have been criticised both for their methodological and conceptual problems and for their weak explanatory -5 - capacity (Gartner 1989, Shaver and Scott ,1991, Krueger, Reilly and Carsrud, 2000). In this sense, Bandura’s (1977) social learning theory attributes great importance to the influence of environmental factors over higher cognitive processes and learning. Behaviours would thus be the results of environmental stimuli, feed-back processes (reward and punishment) and, mainly, observational learning. Along this line, the entrepreneurial intention approach has recently emerged. Unlike previous entrepreneurship models, this one emphasizes the individual’s cognitive process (Shapero and Sokol, 1982, Krueger and Carsrud, 1993, Kolvereid, 1996, Tchakev and Kolvereid, 1999, Baron, 2004, Liñán and Chen forthcoming). The central factor of this theory is the individual intention to become an entrepreneur. Intentions capture the motivational factors which influence behaviour, becoming measures of the effort the individual plans to exert to perform the behaviour. So, the higher the intention to become an entrepreneur, the higher the probability of its effective performance will be. The most important early contribution to this approach within the field of entrepreneurship is the ‘entrepreneurial event’ theory (Shapero and Sokol, 1982). According to it, individuals decide to create a firm (become potential entrepreneurs) when the entrepreneurial activity is perceived as more desirable and more feasible than other alternatives. Thus, perceived desirability would be the degree of attraction towards becoming an entrepreneur. Perceived feasibility, in turn, would refer to the perception about the self-capacity or selfefficacy (Bandura, 1997) to perform the entrepreneurial behaviour. -6 - Salaff, 2003). Besides, those elements generate trust in the ability to perform a specific behaviour because they enhance combination capabilities (Naphiet and Ghoshal, 1998). Therefore, our first two hypotheses are (see figure 1): H1: Bonding CSC positively influences perceived desirability to become an entrepreneur. H2: Bonding CSC positively influences perceived feasibility to become an entrepreneur. Secondly, bridging cognitive social capital based on weak ties could also generate, through the acquisition of information and experience, favourable values and beliefs towards firm start-up (Jack and Anderson, 2002, Hoang and Antoncic, 2003). This influence would derive from informal relationships established, for instance, in previous employee positions (Ray, 1993, Ozgen and Baron, 2007). Nevertheless, It could also derive from informal relationships with specific business networks, such as entrepreneurial promotion agencies, certain entrepreneurial organizations or certain entrepreneurial networks (Bryson et al., 1993). It may be reasonably assumed that having this kind of contacts derived from one’s own experience may contribute to higher entrepreneurial self-efficacy (Ozgen and Baron, 2007). Therefore, the third hypothesis is (see figure 1): H3: Bridging CSC positively influences perceived feasibility to become an entrepreneur. The last two additional hypotheses would derive directly from Shapero and Sokol’s (1982) and Ajzen’s model (1991). These have been consistently supported by the empirical evidence (Autio et al., 2001, Erikson, 1999, Kolvereid, 1996, Kolvereid and Isaksen, 2006, Krueger, 1993, Krueger et al., - 13 - 2000, Lee and Wong, 2004, Peterman and Kennedy, 2003, Tchakev and Kolvereid, 1999). Specifically, they are (see figure1): H4: Perceived desirability towards start-up positively influences the entrepreneurial intention. H5: Perceived feasibility towards start-up positively influences the entrepreneurial intention. Insert figure 1 about here 4.- The moderating role of culture on entrepreneurial intention. Can the influence of CSC on entrepreneurial intention be different across countries and regions? Obviously, the consideration of culture is an important element to take into account to answer this question. The research model proposed is expected to be cross-culturally robust because many factors underlying entrepreneurial behaviour are common across cultures (McGrath and MacMillan, 1992, McGrath et alia, 1992). Nevertheless, some social researchers see clear cultural differences between countries and even regions of a same country (Inglehart 1997, Hofstede’s 2003). Therefore, some entrepreneurship researchers consider these cultural differences as influencing the differences in entrepreneurial behaviour across countries and regions (Shane et alia, 1991, Davidsson, 1995, Mueller and Thomas, 2001, Hayton et alia, 2002). According to Spilling (1991), the cognitive concept of culture is related to ideas, values and norms common to a group of people. In the same sense, - 14 - Inglehart (1997) defines culture as the set of basic common values which contribute to shaping people’s behaviour in a society. According to Hofstede (2005), the notion of culture also includes patterns of thinking, feeling and acting, which are learned and shared by people living within the same social environment. He calls those patterns of behaviour software of the mind and, thus, defines culture as «the collective programming of the mind which distinguishes the members of a group of people from others» (Hofstede, 2005: XXX). Cultural factors must be considered as a variable, not a constant, within whatever empirical research. Their changes throughout time exert an influence on economic development. Weber´s (1969) theory about protestant ethic and the origin of capitalism, Hoselitz´s (1960) and Hagen´s (1962) theories about social change and development, or McClelland´s (1961) theory about need of achievement and development are pioneers in this line of research. Nevertheless, if we analyse carefully all these theories, they have something in common: they consider entrepreneurship as one of the most important links between culture and economic development. More recently, this link has been emphasized by researchers both on Italian Industrial Districts (Becattini, 1979) and on local endogenous development theory (Vázquez, 2002; Romero and Santos, 2007). According to Davidsson (1995), culture may influence entrepreneurship both through social legitimation (at the aggregate level) and through promoting on individuals certain positive attitudes related to firm creation. As Hofstede (1980) pointed out, the reason why this happens is that culture shapes people’s - 15 - cognitive schemas, programming behavioural patterns which are consistent with the cultural context. Entrepreneurs’ cognitive schemas derived from culture can help entrepreneurs in several aspects (Busenitz and Lau, 1996): reducing the uncertainty of taking a decision, identifying cause/effect relationships to advance the development of ideas and opportunities, facilitating fortcasts and predictions about outcomes and, what is most important in this study, increasing the intention to start-up. Starting from Krueger and Casrud (1993) and Shapero and Sokol (1982), Mitchell’s et alia (2002) propose that cultural values exert a direct influence on arrangement, ability and willingness cognitions and, only then, on the decision to start-up. This model has some similarities with the model proposed above. On the one hand, ability and willingness cognitions are very similar to perceptions of feasibility and desirability in our model. On the other hand, arrangement cognitions are related to our concept of CSC. Nevertheless, the specific position of culture within the model proposed in this paper is difficult to establish. In principle, there could be two possibilities (figure 2). Firstly, culture could exert a direct influence only on CSC, which in turn would affect perceptions (option A in figure 2). Secondly, CSC and culture could both exert their own independent influence directly on perceptions, since values and beliefs are the essence of both constructs (option B). Insert figure 2 about here In the empirical analysis that follows, the entrepreneurial intention research model proposed in section 3 is going to be tested in a population from two - 16 - different countries, Spain and Taiwan. Both countries are quite different in many aspects and national culture is not an exception. In fact, according to Inglehart et al. (2004), Taiwan’s culture is slightly more secular-rational than that of Spain and, according to Hofstede (2005), Spain would be characterized by higher individualism and uncertainty avoidance than Taiwan. Then, although we expect the model to be cross-culturally robust, an exploratory analysis will be performed to look for possible differences among both sub-samples. Results will be discussed, suggesting some implications for the role of culture in the entrepreneurial intention model with CSC. 5.- Data and methodology. a) Sample selection The empirical analysis was carried out through a questionnaire to last-year undergraduate students. The selection of this target population was due to three reasons: Firstly, this kind of population is commonly used in entrepreneurship research (Autio et al., 2001, Tkachev and Kolvereid 1999, Krueger et al. 2000, Fayolle and Gailly 2004, Veciana, Aponte and Urbano, 2005). Secondly, according to Reynolds et al. (2002), university graduates from 25 to 34 years old are the segment of the population showing higher probability to become entrepreneurs. Finally, these students are at the point of facing their own choice of professional career. Therefore, their answers could be expected to be more careful and pondered. The Spanish sample has been obtained from three public universities in Andalusia. Two of them (Seville and Pablo Olavide universities) are located within the Seville metropolitan area, with more than 1.2 million inhabitants. The - 17 - third one is Jaen University, located in a middle-sized rural-area town. The final Spanish sample was composed of 400 students: 46 from Jaen University, 31 from Pablo Olavide University, and the 323 remaining ones from Seville University. 69’2% of the sample corresponds to Management students and the rest to Economics. In particular, all the questionnaires from Jaen and Pablo Olavide Universities correspond to Management students, because the Economics degree is not on offer there. 55% of respondents are women, while the average age is 23.7 years old. These percentages broadly correspond with the general characteristics of the students at both degrees. Therefore, the sample can be considered as representative. The Taiwanese sample answered a Chinese version of the questionnaire, translated using the double-back translation system. They are participants of the Technology Innovation Competition. This is the most important businessplan competition for university students in Taiwan. One of the steps consists on a 3-day winter camp. It was during this stage that the fieldwork was carried out. Two people were randomly selected from each competing team and asked to answer the questionnaire. 133 valid questionnaires were thus collected. Average age is 23.1 years and 42.1% of respondents are female. Again, business is the most common degree (60.6%), followed by engineering (24.4%), the rest being mostly health and life sciences students. Some differences do arise between both samples, as might be expected. In the first place, the Spanish sample includes significantly more women. Similarly, knowing an entrepreneur is more common in Spain (86% compared to 48.5% of the Taiwanese sample). This difference is consistent for all possible sources of entrepreneurial role models: family (66.0% in Spain, 27.8% in Taiwan); friends - 18 - (57.3% to 23.3%) or boss/foreman (17.5% to 4.5%). On the other hand, even though the proportion of respondents having work experience is broadly similar (43.5% to 36.8%), Taiwanese students have much higher self-employment experience (2.5% in Spain, 8.5% in Taiwan). b) Measures The Entrepreneurial Intention Questionnaire (EIQ) used for the analysis has been carefully developed starting from the literature and specifically designed to allow its statistical validation. For its construction, a rigorous analysis of other instruments used in the literature has been performed. The possible existing discrepancies between those other instruments have been solved resorting to Ajzen’s (1991, 2001, 2002) theory of planned behaviour. The EIQ items used in this analysis are included in the appendix. Social capital measures are essentially multidimensional (Granovetter, 1983, 1985, Woolcock and Narayan, 2000, Uphoff, 2000, Grootaert and Bastelaer, 2001). Thus, bonding CSC has been measured as a second order dimension, encompassing four first-order constructs: family role-model, other role-models, valuation of entrepreneurship in the closer environment, and closer-environment approval for start-up. Bridging CSC, in turn, has also been measured as a second-order dimension encompassing two first-order constructs: knowledge of the institutional entrepreneurial environment, and labour experience. The EIQ used in this analysis has already been statistically validated with satisfactory results (Liñán and Chen, forthcoming). The central elements of the entrepreneurial intention model (Krueger et al., 2000, Kolvereid, 1996, Ajzen, 1991, Liñán, 2004) are relatively well established. They have been measured - 19 - through 7-point likert-type scales with five (desirability) and six items (feasibility and intention). c) Assessment of epistemic relationships Epistemic relationships describe the link between theory (constructs) and data (indicators) (Fornell, 1982). Basically, there are two types of epistemic relationships (Jarvis, McKenzie and Podsakoff, 2003, McKenzie, Podsakoff and Jarvis, 2005). On the one hand, ‘reflective’ indicators are assumed to reflect the unobserved theoretical construct and, hence, covary with the level of the latent variable. On the other hand, ‘formative’ indicators produce or jointly influence the composite latent variable. Manifest variables, named formative indicators, give rise to the latent variable. Therefore, formative indicators are not necessarily correlated (Chin and Gopal, 1995). Consequently, traditional reliability and validity assessment have been argued as inadequate (Bagozzi, 1994, Bollen, 1989). Thus, the constructs in our model have been assessed according to the four criteria proposed by Jarvis, McKenzie and Podsakoff (2003) and McKenzie, Podsakoff and Jarvis (2005). Most constructs and first order dimensions have been measured through reflective indicators (approval, valuation, contact, desirability, feasibility and intention). Only the construct dimension regarding non-family role models and the two second-order constructs (bonding and bridging CSC) present formative relationships with regard to its indicators and dimensions, respectively. d) Statistical technique used in the empirical analysis. - 20 - Given the characteristics of the model proposed in section three, a structural equation model will be used to test the hypotheses presented there. In particular, a multivariate analysis technique based on Partial Least Squares (PLS) will be used. According to Gefen, Straub and Boudreau (2000), when exploratory studies are carried out and relatively small samples are used, this multivariate statistical technique is more suitable than others, such as LISREL, based on the covariance analysis. The PLSGraph V. 3.00 Build 1126 (Chin and Frye, 2003) software has been used. PLS analysis provides results for both the structural model (hypothesized relationships) and the measurement model (reliability and validity of indicators), according to Sánchez-Franco and Roldán (2005). PLS is especially appropriate for analysis of measurement and structural models when both formative and reflective constructs are used (Diamantopoulos and Winklhofer, 2001). Second order constructs have to be built prior to operate the full structural model. The items measuring those social capital constructs used as first-order dimensions are optimally weighted and combined using the PLS algorithm to create latent variable scores. These latter scores, in turn, are then used as indicators to more accurately form the second-order construct (Chin and Gopal, 1995, Calvo-Mora, Leal and Roldán, 2005). Additionally, with the purpose of exploring possible differences in the results between both countries, a multigroup analysis has been performed. This technique looks for statistically significant differences in path coefficients between sub-samples (Chin, 2000). If they are found, they may be attributed to differences in national culture, at least partly. - 21 - 6.- Results A PLS model is analysed and interpreted in two stages. The first one refers to the assessment of the measurement model (reliability and validity analysis). Only then conclusions regarding structural relationships among the constructs may be logically derived (Barclay, Higgins and Thompson, 1995). a) Measurement model Reliability analysis may be carried out using item loadings. In this sense, individual reflective-item reliability is considered adequate when item loadings are above 0.707 on their respective constructs. It means that shared variance between the construct and its indicators, is greater than the error variance (Sánchez-Franco and Roldán, 2005). Table 1 presents item loadings for our model. The three reflective constructs has item loadings well above that threshold level. Insert table 1 about here For formative constructs, on the other hand, weights provide information about the make up and relative importance of each indicator in the creation/formation of the component (Chin, 1998). In this respect, a customary precaution is checking for multicollinearity (Sánchez-Franco and Roldán, 2005). This has been done through the analysis of variation inflation factors (VIF), which are well below the usual threshold level (VIF < 5), indicating multicollinearity is not a concern in this case. - 22 - kind of entrepreneurial values and beliefs transmitted by CSC in each country, as option A in figure 2 suggested. Instead, these national cultural values would exert a parallel influence on perceptions (along with CSC), as shown by option B in figure 2. Further research is undoubtedly needed to explore the specific ways through which values, beliefs and trust affect perceptions. In particular, this study should be repeated using alternative samples from diverse cultural contexts and including different indicators for national cultural values. The present study has a number of limitations that should be acknowledged. To start with, this is a first attempt to introduce CSC variables into entrepreneurial intention models. Therefore, alternative measures should be developed and tested. Another area of concern is the effect of a family rolemodel in forming the bonding CSC construct. Previous literature suggests that it contributes to the formation of values and beliefs towards entrepreneurship (Cooper and Dunkelberg, 1987, Greve and Salaff, 2003, Matthews and Moser, 1995). Since no multicollinearity problems were found, it may be the case that the influence of a family role model is distinct from the other bonding CSC measures. Alternatively, as Scherer et al. (1991) suggest, this influence may depend on personal relationships with parents and the evaluation made about how successful these parents are as entrepreneurs. Acknowledgements We are most grateful to Notes - 29 - References Ajzen, I. (1991): The theory of planned behaviour, Organizational Behaviour and Human Decision Processes, 50, 179-211. Ajzen, I. (2001): Nature and operation of attitudes, Annual Review of Psychology, 52, 27-58. Ajzen, I. 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(1994): Cross-national comparison of the variation in new firm rates, Regional Studies, 28, 443-456. Reynolds, P.D., Hay, W.M. and Camp, S.M. 1999. Global entrepreneurship monitor 1999, executive report. London: London Business School and Babson College - 38 - Table 4. Multigroup analysis βSpain βTaiwan βSpain - βTaiwan t-student Bonding Æ desirability 0.407 0.554 -0.147ns -1.52454 Bonding Æ feasibility 0.266 0.41 -0.144ns -1.55182 Bridging Æ desirability 0.067 0.063 0.004ns 0.04357 Bridging Æ feasibility 0.295 0.209 0.086ns 0.90396 Desirability Æ intention 0.663 0.302 0.361*** 5.36718 Feasibility Æ intention 0.183 0.579 -0.396*** -4.79557 Note: ns = not significant. Levels of significance based on a Student t(531) distribution with two tails. *p<.05, t(.05, 531) = 1.964, **p<.01, t(.01, 531) = 2.585, ***p<.001, t(.001, 531) = 3.308 - 45 - Figure1: Research model and hypotheses BONDING COGNITIVE SOCIAL CAPITAL BRIDGING COGNITIVE SOCIAL CAPITAL PERCEIVED DESIRABILITY PERCEIVED FEASIBILITY ENTREPRENEURIAL INTENTIONS H 1 H 2 H 3 H 4 H 5 Figure 2 A tentative cross-cultural model of entrepreneurial intention Culture Cognitive social capital Desirability Feasibility Entrepreneurial intention B B A - 46 - Figure 3. Structural model results Intention Bridging CSC Bonding CSC Feasibility Desirability Approval Valuation Family RM Other RM Instit.Knw. Work Exp. Spain Combined Taiwan 0.592 0.595 0.740 0.159 -0.073 -0.167 0.616 0.511 0.278 0.673 0.674 0.694 0.670 0.702 0.731 0.266 0.264 0.410 0.067 0.116 0.063 0.407 0.359 0.554 0.295 0.298 0.209 0.663 0.589 0.302 0.183 0.272 0.579 0.313 0.373 0.269 R 2=0.183 R2=0.156 R2=0.327 R 2=0.567 R2=0.548 R2=0.579 R 2=0.19 5 R2=0.184 R2=0.253 Note: figures below the constructs indicate explained variance - 47 -