Small Business Entrepreneurship And The Internal ...



Small Business Entrepreneurship

and the Internal Determinants of International Behaviour

Michela C. Mason,

Department of Biology and Agro-industrial Economics, University of Udine, Italy, +39 0432 558325

Rubens Pauluzzo,

Department of Economic Sciences, University of Udine, Italy, +39 0432 249590

ABSTRACT

The role of Italian small and medium enterprises (SMEs) in the international economic environment has attracted many scholars for its peculiarities. In particular, their development and longevity paths are critical to a better understanding of the main characteristics of the global economy. Although they manage many of the same issues of other companies, they must also face specific problems, mainly related to their status and to the entrepreneurial behaviour of the firm owners.

Nevertheless, few empirical studies have stressed the importance of human resources and entrepreneurial behaviour for the performance and growth of Italian SMEs, especially in the international environment, where keen competition and difficulties of reaching the necessary resources are often insuperable barriers for SMEs.

The main goal of this study is to suggest a “holistic” model, in order to analyze the relations between the internal determinants of the internationalization process of SMEs, by integrating the individual-level with the firm-level features. The analysis, based on the theories of individual cognitive aspect, international expansion and business strategy, explores the process of internationalization of SMEs from a cognitive perspective. Therefore, the study aims to provide a better understanding of the deepest reasons that lead entrepreneurs towards distinctive paths of international development.

Finally, the present study stresses the central role played by individual expectations and risk perception in understanding the international expansion strategies of SMEs. In particular, it considers some significant relationships between international processes, human capital and the role played by the firm owner.

1. INTRODUCTION

Export Marketing literature has distinguished the main determinants of firm export behaviour in two categories: internal and external determinants. Macroeconomic literature has widely considered the external determinants, whereas Management scholars have mainly focused on the internal determinants. The growing importance of these internal factors, to support the international development of SMEs, offers interesting research ideas. The organizational structure, together with management characteristics, entrepreneurial behaviour and human capital represent some of the most relevant elements tightly linked to the international performance of the firms.

Although SMEs manage many of the same issues as other companies, they must also face specific problems, mainly related to their status and to the entrepreneurial behaviour of firm owners.

Nevertheless, few empirical studies have stressed the importance of human resources and entrepreneurial behaviour for the performance and growth of Italian SMEs, especially in the international environment, where keen competition and difficulties of reaching the necessary resources are often insuperable barriers for SMEs.

The main goal of this study is to suggest a “holistic” model, in order to analyze the relations between the internal determinants of the internationalization process of SMEs, by integrating the individual-level with the firm-level features. The analysis, based on the theories of individual cognitive aspect, international expansion and business strategy, explores the process of internationalization of SMEs from a cognitive perspective. Therefore, the study aims to provide a better understanding of the deepest reasons that lead entrepreneurs towards distinctive paths of international development.

Finally, the present study stresses the central role played by individual expectations and risk perception in understanding the international expansion strategies of SMEs. In particular, it considers some significant relationships between international processes, human capital and the role played by the firm owner.

Our sample frame consisted of 150 SMEs from the Italian region of Friuli Venezia Giulia, with particular regard to the provinces of Udine and Pordenone, associated with the family business centers of the most significant sectors. The surveys were submitted to a panel of 1509 firms, with an overall response rate of about 10%.

2. LITERATURE REVIEW

The analysis aimed at deepening what are the main factors of international success for SMEs.

In fact, the openness towards foreign markets is a strategic choice for SMEs, aimed at, on the one hand, supporting fundamental development paths, and, on the other hand, protecting their businesses (Skrt and Antoncic, 2004). The literature offers a vast and composite theoretical framework, in which the various approaches agree in suggesting the central role and influence played by the family ownership in this process. In particular, at the SMEs level, the human capital, mainly due to the owner, is the main source of competitive advantage. In these companies, in fact, the owner does not only invest in the firm activity, but also acts as the main, though not exclusive, decision maker and business manager (Glancey, 1998; Miesenbock, 1988; Prince and Van Dijken, 1998; Reid, 1981; Westhead, Binks, Ucbasaran, and Wright, 2002). Several contributions on this matter highlight different aspects of the entrepreneurial role, such as the strategy followed (Baird, Lyles, and Orris, 1994; Tyebjee, 1994), managers attitudes (Bijmolt and Zwart, 1994; Ogbuehi and Longfellow, 1994), responsibilities (Dhanaraj and Beamish, 2003) and international experiences (Qian, 2002; Reuber and Fischer,1997) as well as other elements of human capital (Andersson, 2000; Bilkey and Tesar, 1977; Cavusgil, 1993; Herrmann and Datta, 2002; Manolova, Brush, Edelman, and Greene, 2002; McAuley, 1999; Moini, 1995; Trevino and Grosse, 2002)[i].

Considering the studies focused on identifying the success factors of internationalization, it is therefore possible to detect an evolutionary path characterized by the gradual transition from tangible determinants (foreign markets, export incentives) to more intangibles dimensions, such as demographic features and psycho-cognitive aspects of management (Dichtl, Koglmayr and Muller 1990; Muller 1991).

In order to better understand the main reasons for success in the international markets, it is necessary to develop a model able to consider several variables explaining the complexity of the phenomenon. The number of variables is a fundamental prerequisite in business studies, because the development of these organizations is influenced by various factors which constantly interact with each other and with the external environment (Macharzina and Engelhard, 1991).

In order to analyze the international performance of SMEs is therefore necessary to, on the one hand, select a suitable set of variables and, on the other hand, to apply a specific statistical method. Several studies suggested different methods to identify the dependent variable (international performance) because, since its introduction (Tookey, 1964), a universally shared conceptualization has not been developed (Cavusgil e Zou 1994; Shoham, 1998).

As a result, we would like to suggest a frame of reference of the most important studies focused on the determinants of export success. Some of these analysis are presented in table 1.

With reference to the theoretical framework presented, we have developed a multi-dimensional model able to integrate two levels of analysis: the firm level and the individual characteristics level. In particular, the analysis has distinguished between the “observable” or objective management dimension and the subjective one, emphasizing the relevance of psycho-cognitive aspects. In accordance with the upper echelon theory (Hambrick and Mason, 1994), the study has therefore accepted the assumption that the individual characteristics affect business attitudes, strategic choices and business performance.

Revising the approach suggested by some authors (Aabay and Slater, 1989; Bijmol and Zwart, 1994; Holzmüller and Stottinger 1996, 2001), the model identifies several explanatory variables, emphasizing the importance of subjective entrepreneurial characteristics, international activity, firm characteristics and objective entrepreneurial characteristics that have a direct and mediated effect on international performance. The study also deepens an issue only marginally considered by the literature: the bond between firm characteristics and international activity.

In particular, with reference to the results of various studies (Katsikeas, Deng and Wortzel, 1997; Wolff and Pett, 2000[ii]), the analysis has accepted the assumption that smaller dimensions (small number of employees) are positively related to international activity. This suggests that SMEs do not follow competitive paths based on their dimensions, as larger companies usually do, but, in order to find the needed resources at lower costs, they show an interesting orientation to international activity. This supports the hypothesis that the international activity of SMEs is dominated by a resource seeking orientation, influenced by the comparative advantages that can be reached in terms of factor costs and especially of labour costs.

The model analyses the relationships between the following set of variables and international performance[iii]:

Firm Characteristics (company size, age, degree of innovation/technology);

Objective Entrepreneurial Characteristics OGG (education, age, work experience, international experience);

Subjective Entrepreneurial Characteristics SOG (proactivity, risk acceptance, tolerance for ambiguity, initiative, personal development, relationship with uncertainty);

International Activity INT (internationalization methods, expansion strategies, international planning, internationalization motivations, resource seeking orientation, foreign procurement).

International Performance IP (export sales/total turnover, international market share) [iv].

Structural equation modeling (SEM) was used to test the relationships between observed and latent variables. In particular, the analysis focused on a latent structure model with explicit causal relations, developed with LISREL 8.51 (Jöreskog and Sörbom, 2001, Corbetta, 2002).

LISREL is particularly suitable for the purpose of the analysis, because the explanatory investigation requires an identification of those variables that can be considered as “cause” and those variables that can be considered as “effect”.

The model identified with the relevant determinants of international performance is presented in Figure 1.

3. RESEARCH METHODOLOGY

From a panel of 1509 small and medium enterprises from the Italian region of Friuli Venezia Giulia (853 from the province of Udine and 656 from the province of Pordenone), 150 SMEs, associated with the family business centers of the most significant sectors, have been surveyed. Data were collected by submitting a questionnaire to firm owners in the period January-December 2007.

The empirical analysis is based on multivariate statistics. Factor analysis with varimax rotation has been performed to identify the five dimensions: firm characteristics (IMP), objective entrepreneurial characteristics (OGG), subjective entrepreneurial characteristics (SOG), international activity (INT) and international performance of the firm (IP).

The reliability of each factor has been tested with Cronbach’s α coefficient.

Table 2 shows the results of factor and reliability analysis

4. MEASURES AND RESULTS

The estimated structural equation modeling (SEM), analyzed with LISREL 8.51, follows a logic based on two steps. The first one is related to the process for estimating parameters, which takes place through an interactive procedure aimed at minimizing the gap between data produced by the model and observed data. The second step is based on a comparison of the theoretical model with the data observed. If the gap between the matrix of the observed covariance and the expected matrix, generated by the program, is higher than the gap attributable to the stochastic error, the model is rejected. The analysis will then determine if the model is able to represent the examined phenomenon, through four different kinds of fir indices.

These indices are represented by the χ ² test, the Overall model fit indices[v], the Incremental fit indices[vi] and the Residuals indices[vii].

LISREL model consists of two parts: the structural model and the measurement model. The structural model submits all the causal relations between endogenous and exogenous latent variables. The measurement model analyzes the links between latent and observed variables. The abbreviations commonly used by LISREL are listed in table 3.

The measurement model aims at explaining if the observed variables can effectively measure the latent variables. With reference to our study, the measurement model analyzes the bonds between the subjective entrepreneurial characteristics (SOG), the international activity of the firm (INT), the performance of the firm on the international markets (IP), the objective entrepreneurial characteristics (OGG), the firm characteristics (IMP) and their observed variables.

As we stated above, Structural equation modeling (SEM) is a statistical technique for testing and estimating causal relationships using a combination of statistical data and qualitative causal assumptions. In order to provide the fullest evidence of measurement efficacy, before testing the complete model, it should be useful to test also each latent variable.

Subjective entrepreneurial characteristics (SOG) has been conceptualized as a second-order model, explained by six observed variables. The fit statistics for the model are RMSEA = 0, 90% Confidence Interval for RMSEA (0; 0.0062), NFI = 0.96, NNFI = 1, GFI = 0.99, AGFI = 0.97, confirming a very good model-data fit.

International activity (INT) has been conceptualized as a second-order model, explained by six observed variables. The fit statistics for the model are RMSEA = 0.046, 90% Confidence Interval for RMSEA (0.02; 0.0097), NFI = 0.77, NNFI = 0.74, GFI = 0.94, AGFI = 0.87, confirming a reasonable model-data fit.

International performance (IP) has been conceptualized as a second-order model, explained by two observed variables. The fit statistics for the model has not been calculated by LISREL due to the small number of observed variables.

Firm characteristics (IMP) has been conceptualized as a second-order model, explained by three observed variables. The fit statistics for the model are RMSEA = 0.058, 90% Confidence Interval for RMSEA (0; 0.25), NFI = 0.88, NNFI = 0.86, GFI = 0.99, AGFI = 0.96, confirming a good model-data fit.

Objective entrepreneurial characteristics (OGG) has been conceptualized as a second-order model, explained by four observed variables. The fit statistics for the model are RMSEA = 0.017, 90% Confidence Interval for RMSEA (0; 0.18), NFI = 0.93, NNFI = 0.98, GFI = 0.99, AGFI = 0.96, confirming a very good model-data fit.

Tables 4 and 5, and figures 2 and 3, show the relationships between observed and latent variables and the fit indices of latent variables.

The structural model confirms, on the one hand, the existence of a direct relationship between the firm characteristics (IMP), the objective entrepreneurial characteristics (OGG) and the international performance (IP) and, on the other hand, the existence of an indirect link, mediated by the subjective entrepreneurial characteristics (SOG) and by the international activity (INT).

It seems useful to stress the importance of the mediating role played by the subjective entrepreneurial characteristics (SOG) and by the international activity (INT). In fact, the firm characteristics (IMP) and the objective entrepreneurial characteristics (OGG) affect directly and indirectly the international performance (IP).

Table 6, and figure 4, show the relationships between latent variables.

The integrated exam of the fit indices allows to confirm whether the model is able to fit the data or not.

χ ² scores 298.53 with 180 degrees of freedom, p-value 0. Overall model fit indices show reasonable fit results. GFI (Goodness of fit index) scores 0.82, while AGFI (Adjusted goodness of fit index) 0.77. CN (Critical N) scores 290.

Incremental fit indices show lower values, but able to support the conceptual model. NFI (Normed fit index) scores 0.59, NNFI (Non-normed fit index) 0.71, while CFI (Comparative fit index) scores 0.75 .

Residuals indices show low values, confirming that the assumed model is able to explain most of the observed data. RMR (Root mean square residual) index scores 0.15, while RMSEA (Root mean square error of approximation) index 0.042, with 90 % confidence interval between 0.027 and 0.086 (Figure 5 and 6).

5. CONCLUSION

The analysis carried out with LISREL allowed us to examine more precisely the determinants of international performance of SMEs, through the assumptions made with reference to the structural model.

The results are as follows:

1) There is a positive direct effect between the firm characteristics (firm size, age, degree of innovation/technology) and the international performance.

The direct positive effect between firm characteristics and the international performance can be explained considering that larger companies, with more experience, especially on the international markets, together with a higher degree of innovation tend to achieve better results on the international markets.

2) Objective entrepreneurial characteristics (education and age of the owner, his/her work and international knowledge) are positively and directly linked to the international performance of the firm.

The education level and the experience gained by the owner tend to have particular importance in fostering better results on the international markets. This confirms the core role played by the owner in leading SMEs towards successful development paths, especially at the international level.

3) Some firm characteristics have a positive direct effect on the subjective entrepreneurial characteristics (proactivity, risk acceptance, tolerance for ambiguity, initiative, personal development, relationship with uncertainty).

The positive direct effect between some firm characteristics and the subjective entrepreneurial characteristics can be explained considering that in larger firms, with higher degrees of experience and innovation, the owner tends to be more proactive and tolerant for ambiguity and risk.

4) Objective entrepreneurial characteristics are positively and directly linked to subjective entrepreneurial characteristics.

The model confirms that owners with a higher level of education, maturity and experience tend to have a more tolerant approach for risk and ambiguity and to be more oriented towards personal development.

5) Subjective entrepreneurial characteristics have a direct positive effect on the international performance of the firm.

The analysis has confirmed the hypothesis that higher degrees of proactivity, risk acceptance and initiative by the owner tend to encourage better international results of the SMEs. The confirmation of this hypothesis stresses the importance that, not only objective factors, but also subjective determinants have in supporting SMEs’ activities towards successful growing paths on the international markets.

6) International activity (internationalization methods, expansion strategies, international planning, internationalization motivations, resource seeking orientation, foreign procurement) has a positive direct effect on international performance of SMEs.

The development of a clear internationalization strategy and the complete awareness of the reasons that lead the company towards international activities tend to promote the achievement of better results, in terms of turnover achieved and market share gained.

7) Firm characteristics are negatively and directly linked to the international activity.

The analysis has revealed that some firm characteristics, such as firm size, have a negative effect on the international activity of SMEs. In particular, SMEs with larger size but without a sufficient level of resources can find several obstacles along their international development paths. Larger sizes involve more complex organizational structures, often characterized by a lower degree of flexibility. Under these circumstances, it can be more difficult to quickly meet market changes. As stated before, SMEs tend not to follow competitive paths based on their dimension, as larger companies usually do, but tend to have an international orientation based on resource seeking approaches. This confirms that SMEs tend to implement strategies based on foreign countries comparative advantages in terms of factor costs, with particular reference to labour costs.

8) Objective entrepreneurial characteristics have a positive direct effect on the international activity of SMEs.

Higher levels of education, maturity and experience of the owner, especially on the international stage, tend to promote the development of strategies or action plans able to support the international activity of the firm and better awareness of the reasons of international investments. This analysis can have different managerial implications. On the one hand, better international performances are not only influenced by hard factors, such as firm and objective entrepreneurial characteristics, but also by determinants linked to the cognitive sphere, such as values, attitudes and norms. On the other hand, the flexibility of SMEs, due to their small sizes, tend to promote internationalization strategies based on joint-ventures, cooperation agreements, technology transfers, rather than those based on direct and indirect exports or FDIs.

The analysis tends to confirm that the owner is still a fundamental determinant in leading SMEs’ international strategies.

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❖ Suárez-Ortega, S.M., & Alamo-Vera, F.R. (2005) “SMEs’ Internationalisation: Firms and Managerial Factors”, International Journal of Entrepreneurship Behaviour and Research, 11(4):258-279;

❖ Thirkell, P. C. & Dau, R. (1998), “Export Performance: Success Determinants for New Zealand Manufacturing Exporters”, European Journal of Marketing, vol. 32, no. 9/10, pp. 813-829;

❖ Tookey, D. A. (1964) “Factors Associated with Success in Exporting”, Journal of Management Studies, 1(1): 48-66;

❖ Trevino, L.J., & Grosse, R. (2002). “An analysis of the firm specific resources and foreign direct investment in the United States”. International Business Review, 11(4), 431^52;

❖ Wagner, J. (1995), “Export, Firm Size, and Firm Dynamics”, Small Business Economics, vol. 7, pp. 29-39;

❖ Westhead, P., & Wright, M. & Ucbasaran, D. (2001) “The Internationalisation of New and Small Firms: A Resource-Based View”, Journal of Business Venturing, 16(4):333-358;

❖ Wood, V. R. & Robertson, K. R. (1997), “Strategic Orientation and Export Success: An Empirical Study”, International Marketing Review, vol. 14, no. 6, pp. 424-444;

❖ Wolff, J. A. & Pett, T. L.(2000), “Internationalization of Small Firms: An Examination of Export Competitive Patterns, Firm Size, and Export Performance”, Journal of Small Business Management, vol. 38, no. 2, pp. 34-47.

TABLES

Table 1: Frame of reference

|Author |Method |Variables |

| | |Dependent variable |Independent varible |

| | |International Performance |EV |IMP |OGG and|INT |

| | | | | |SOG | |

|Axinn (1988) |Regression |ER |no |yes |yes |no |

|Diamantopoulos and Inglis (1988) |Discriminant |ER (dichotomous) |no |yes |no |yes |

|Koh and Robicheaux (1988) |ANOVA |EP perceived vs. domestic |no |no |no |yes |

|Culpan (1989) |Discriminant |composite |no |yes |no |no |

|Bourantas and Halikias (1990) |Regression |ER |no |no |no |yes |

|Dichtl, Köglmayr and Müller (1990) |Regression |∆ER |no |yes |yes |no |

|Lee and Yang (1990) |ANOVA |Average ER, average ∆ES vs. domestic, |no |no |no |yes |

| | |evaluation ∆ES vs domestic, | | | | |

| | |evaluation ∆ES vs industry, | | | | |

| | |average EP vs. domestic, | | | | |

| | |evaluation EP vs. industry | | | | |

|Samiee and Walters (1991) |T-test / χ2 |ER, number of markets, EP |no |yes |no |yes |

|Holzmüller and Kasper (1991) |Regression |ER |no |yes |yes |yes |

|Koh (1991) |SEM: PLS |composite (ER and ∆ER) |yes |yes |yes |yes |

|Beamish, Craig and OGG e SOG Lellan (1993) |χ2 and ANOVA |EP perceived vs. domestic |no |yes |yes |yes |

|Donthu and Kim (1993) |Correlation |ER in UK, EP in UK, ER in Canada, |yes |no |no |yes |

| | |EP in Canada | | | | |

|Kaynak and Kuan (1993) |Discriminant |∆ES |no |yes |yes |yes |

|De Luz (1993) |Discriminant |Annual ES, annual EP, ER,EP -ratio |yes |yes |yes |yes |

|Walters (1993) |Correlation |5 year ∆EP |no |no |no |yes |

|Bijmolt and Zwart (1994) |T-test, ANOVA |ES, ER, after tax EP margins |no |yes |no |yes |

|Evangelista (1994) |SEM: LISREL |composite ( ER, relative EP, development |no |yes |yes |yes |

| | |5 year ES and satisfaction with ES) | | | | |

|Naidu and Prasad (1994) |Discriminant |satisfaction with IP |no |yes |yes |yes |

|Johnson and Arunthanes (1995) |Logistic regression |3 year trend ES and EP |yes |yes |yes |no |

|Moini (1995) |Regression |EP and EMS, ES |yes |no |no |yes |

|Wagner (1995) |ANOVA, Duncan’s test |composite ( ER and ∆ER) |no |yes |yes |yes |

|Das (1994) |Tobit |ER |no |yes |no |no |

|Holzmüller and Stöttinger (1996) |Discriminant |ER |yes |yes |yes |yes |

|Katsikeas, Piercy and Ioannidis (1996) |SEM: PLS |composite ( ER and ∆ER) |yes |yes |yes |yes |

|Shoham (1996) |Regression ( 3 steps) |composite ( EMS, ES,EP) |no |yes |yes |yes |

|Katsikeas, Deng and Wortzel (1997) |Regression |composite ES, EP, ∆ES, ∆EP |no |no |no |yes |

|Wood and Robertson (1997) |MANCOVA,ANOVA |international degree |yes |yes |no |yes |

|Leonidou and Kaleka (1998) |Regression |ER, expected ER, composite (actual ER |no |yes |yes |no |

| | |Expected ER) | | | | |

|Nakos, Brouthers and Brouthers (1998) |ANOVA, Scheffe’s test |international degree |no |no |no |yes |

|Stump, Athaide and Axinn (1998) |Regression |ER, perceived EP |si |si |si |si |

|Shoham and Kropp (1998) |Regression |ER, EP |no |si |si |si |

|Thirkell and Dau (1998) |Regression |Composite ES (ER and satisfaction , |no |no |no |yes |

| | |ES and satisfaction., EMS) composite ∆ES | | | | |

| | |( ER and satisfaction ES and satisfaction | | | | |

| | |EMS) | | | | |

| | |Composite EP ( ROA and satisfaction ROI and | | | | |

| | |profit margin and satisfaction) composite ∆EP| | | | |

| | |( ∆ROA, ∆ROI and satisfaction ∆ profit | | | | |

| | |margins) | | | | |

|Beamish, Karavis, Goerzen and Lane (1999) |Regression ( 2 steps) |composite (5 year ER, 5 year ∆ER, |no |yes |yes |yes |

| | |Strategic importance and self-assessment | | | | |

| | | EMS, EP, market diversification, | | | | |

| | |customer satisfaction) | | | | |

|Shoham (1999) |Regression |ES,ER,∆ES |no |yes |no |yes |

|Baldauf, Cravens and Wagner (2000) |SEM: LISREL |Composite IP and 5 year composite ∆IP |yes |no |no |yes |

|Dean, Mengüç and Myers (2000) |Regression |ES, ER, composite Export effectivness |yes |yes |no |yes |

|Francis and Collins–Dodd (2000) |Discriminant |ES, ∆ES, ER |no |yes |yes |yes |

|Robertson and Chetty (2000) |Regression |ER, ES, ∆ER, Export gross profit margins |no |yes |no |yes |

|Shoham (2000) |Regression |composite (impostance and satisfaction EP,ER,|yes |no |no |yes |

| | |diversification, ∆ES and evaluation IP) | | | | |

|Wolff and Pett (2000) |Regression |ER |no |no |no |yes |

|Balabanis and Katsikea (2003) |SEM: LISREL |composite (self assessment EP, ROI, IP |yes |yes |yes |no |

| | |Overall 5 years vs competitors) | | | | |

|Julien and Ramangalahy (2003) |SEM: PLS |composite (reputation, ∆ES, EP, ER). |no |yes |yes |yes |

Notes: EV = Environment, IMP = Firm characteristics, OGG e SOG = Objective and subjective entrepreneurial characteristics, INT = International activity, IP = International performance, ER = Export ratio/intensity, ES = Export sales, EP = Export profitability, EMS = Export market share.

Table 2: Factor and reliability analysis

|ITEMS |M |SD |FL |CA |

|FIRM CHARACTERISTICS - IMP | | | | |

|DIMENSION 1 – Firm size (X1) | | | |0,903 |

|Number of employees 2004-2006 |1,606 |0,546 | | |

|Total turnover 2004-2006 |7,002 |0,498 | | |

|DIMENSION 2 – Age (X2) | | | | |

|Number of generations of the firm |1,589 |0,856 | | |

|DIMENSION 3 – Degree of innovation/technology (X3) | | | | |

|% R&D expenses/total costs |4,437 |7,413 | | |

|OBJECTIVE ENTREPRENEURIAL CHARACTERISTICS - OGG | | | | |

|DIMENSION 1 – Education (X4) | | | | |

|Education of the owner |1,943 |0,663 | | |

|DIMENSION 2 – Age (X5) | | | | |

|Age of the owner |1,722 |0,086 | | |

|DIMENSION 3 – Work experience (X6) | | | | |

|Work experiences of the owner |1,667 |0,474 | | |

|DIMENSION 4 – International experience (X7) | | | |0,621 |

|Number of languages spoken by the owner |1,679 |0,471 |0,805 | |

|International experiences of the owner |1,634 |0,485 |0,690 | |

|SUBJECTIVE ENTREPRENEURIAL CHARACTERISTICS - SOG | | | | |

|DIMENSION 1 - Proactivity (Y1) | | | |0,789 |

|To resolve a problem I have to study each part of it in detail |5,195 |1,207 |0,805 | |

|People consider me to be a logical thinker |4,509 |1,329 |0,673 | |

|I believe that rational thinking is the only basis for decision making |4,698 |1,353 |0,603 | |

|I always look for better ways of doing things |5,525 |1,019 |0,592 | |

|I can see opportunities way before others do |4,602 |1,347 |0,480 | |

|DIMENSION 2 – Risk acceptance (Y2) | | | |0,898 |

|My firm has a high probability of success in foreign markets |4,460 |1,961 |0,909 | |

|International activity is a positive thing in my business |4,898 |1,738 |0,902 | |

|Exports are an important opportunity for my firm |4,857 |1,921 |0,870 | |

|DIMENSION 3 – Tolerance for ambiguity (Y3) | | | |0,754 |

|I enjoy the challenges of uncertain situations |3,453 |1,511 |0,777 | |

|I enjoy working in uncertain situations |2,313 |1,459 |0,746 | |

|I enjoy the challenges of uncertain situations |3,543 |1,574 |0,742 | |

|Selling products in foreign markets implies high risks |3,639 |1,445 |0,574 | |

|Most of my decisions are based on my intuition |4,034 |1,231 |0,440 | |

|DIMENSION 4 – Initiative (Y4) | | | |0,724 |

|If I believe in an idea, no obstacle will prevent me from implementing it |4,698 |1,403 |0,678 | |

|I love when my idea win, even when opposing other views |4,675 |1,526 |0,670 | |

|I am very good at identifying opportunities |4,672 |1,304 |0,614 | |

|No matter the odds, if I believe in something I will make it happen |4,670 |1,197 |0,504 | |

|DIMENSION 5 – Personal development (Y5) | | | |0,750 |

|I am always at the lookout for things that will improve my life |5,274 |1,215 |0,839 | |

|At any situation I have always been an important factor for constructive change |5,137 |1,159 |0,748 | |

|If I see something I don’t like it, I fix it |5,703 |1,007 |0,548 | |

|Nothing is more exciting than seeing my ideas turn into reality |5,783 |1,106 |0,512 | |

|DIMENSION 6 – Relationship with uncertainty (Y6) | | | |0,650 |

|The uncertainty surrounding my firm prevents me from doing my best |3,684 |1,775 |0,793 | |

|I often get irritated when unexpected events ruin my plans |4,052 |1,798 |0,781 | |

|INTERNATIONAL ACTIVITY - INT | | | | |

|DIMENSION 1 – Internationalization methods (Y7) | | | | |

|Internationalization method |1,114 |0,319 | | |

|DIMENSION 2 – Expansion strategies (Y8) | | | | |

|Development of internationalization strategy |2,351 |1,316 | | |

|DIMENSION 3 – International planning (Y9) | | | | |

|Strategy or action plan |1,526 |0,503 | | |

|DIMENSION 4 – Internationalization motivations (Y10) | | | |0,727 |

|Competitors already in the foreign market |2,650 |1,132 |0,785 | |

|Wide market |1,862 |1,116 |0,733 | |

|Follow customers in their internationalization processes |2,883 |1,121 |0,723 | |

|Geographical position for further investments in the region |2,850 |1,102 |0,694 | |

|DIMENSION 5 – Resource seeking orientation (Y11) | | | |0,767 |

|Low raw materials costs |2,855 |1,006 |0,866 | |

|Low semi finished goods costs |3,066 |0,981 |0,796 | |

|Low labour costs |2,787 |1,226 |0,787 | |

|DIMENSION 6 – Foreign procurement (Y12) | | | | |

|Foreign procurement |1,760 |0,722 | | |

|INTERNATIONAL PERFORMANCE - IP | | | | |

|DIMENSION 1 – Export sales/total turnover (Y13) | | | | |

|% Export sales/total turnover (average years 2004-06) |0,326 |0,305 | | |

|DIMENSION 2 – International market share (Y14) | | | | |

|International market share |2,683 |0,534 | | |

Notes: M=mean, SD=standard deviation, FL=factor loading, CA= Cronbach’s α.

Table 3: Main LISREL abbreviations

|ABBR. |MEANING |ABBR. |MEANING |

|Y |Endogenous observed variables |β |Structural coefficients between η and η |

|X |Exogenous observed variables |γ |Structural coefficients between ξ and η |

|η |Endogenous latent variables |ζ |Stochastic errors η |

|ξ |Exogenous latent variables |ε |Stochastic errors Y |

|λx |Structural coefficients between η and Y |δ |Stochastic errors X |

|λy |Structural coefficients between ξ and X | | |

Table 4: The bonds between observed and latent variables

|Observed variables/Latent Variables |SOG (η1) |INT (η2) |IP (η3) |IMP (ξ1) |OGG (ξ2) |

|Y1 |λy11 | | | | |

|Y2 |λy21 | | | | |

|Y3 |λy31 | | | | |

|Y4 |λy41 | | | | |

|Y5 |λy51 | | | | |

|Y6 |λy61 | | | | |

|Y7 | |λy72 | | | |

|Y8 | |λy82 | | | |

|Y9 | |λy92 | | | |

|Y10 | |λy102 | | | |

|Y11 | |λy112 | | | |

|Y12 | |λy122 | | | |

|Y13 | | |λy133 | | |

|Y14 | | |λy143 | | |

|X1 | | | |λx11 | |

|X2 | | | |λx21 | |

|X3 | | | |λx31 | |

|X4 | | | | |λx42 |

|X5 | | | | |λx52 |

|X6 | | | | |λx62 |

|X7 | | | | |λx72 |

Table 5: Fit indices of latent variables

|Latent variables |Observed variables |Fit indices |

|Subjective entrepreneurial characteristics |Proactivity |RMSEA = 0 |

| |Risk acceptance |90 % CI RMSEA = (0 ; 0.062) |

| |Tolerance for ambiguity |NFI = 0.96 |

| |Iniziative |NNFI = 1 |

| |Personal development |GFI = 0.99 |

| |Relationship with uncertainty |AGFI = 0.97 |

|International activity |Internationalization methods |RMSEA = 0.046 |

| |Expansion strategies |90 % CI RMSEA = (0.02 ; 0.097) |

| |International planning |NFI = 0.77 |

| |Internationalization motivations |NNFI = 0.74 |

| |Resource seeking orientation |GFI = 0.94 |

| |Foreign procurement |AGFI = 0.87 |

|International performance |Export sales/total turnover |Not calculated by LISREL due to the small |

| |International market share |number of observed variables. |

|Firm characteristics |Firm size |RMSEA = 0.058 |

| |Age |90 % CI RMSEA = (0 ; 0.25) |

| |Degree of innovation/technology |NFI = 0.88 |

| | |NNFI = 0.86 |

| | |GFI = 0.99 |

| | |AGFI = 0.96 |

|Objective entrepreneurial characteristics |Education |RMSEA = 0.017 |

| |Age |90 % CI RMSEA = (0 ; 0.18) |

| |Work experience |NFI = 0.93 |

| |International experience |NNFI = 0.98 |

| | |GFI = 0.99 |

| | |AGFI = 0.96 |

Table 6: The bonds between latent variables

|Latent varibles/latent variables |SOG (η1) |INT (η2) |IMP (ξ1) |OGG (ξ2) |

|SOG (η1) | | |γ11 |γ12 |

|INT (η2) | | |γ21 |γ22 |

|IP (η3) |β31 |β32 |γ31 |γ32 |

FIGURES

Figure 1: Model of the determinants of International Performance

Figure 2: Y-Measurement model Figure 3: X-Measurement model

Figure 4: Structural model

Figure 5: Main fit indices of LISREL model

| |

|Degrees of Freedom = 180 |

|Minimum Fit Function Chi-Square = 326.57 (P = 0.00) |

|Normal Theory Weighted Least Squares Chi-Square = 298.53 (P = 0.00) |

|Minimum Fit Function Value = 2.55 |

|Root Mean Square Error of Approximation (RMSEA) = 0.042 |

|90 Percent Confidence Interval for RMSEA = (0.027 ; 0.086) |

|P-Value for Test of Close Fit (RMSEA < 0.05) = 0.0092 |

|Normed Fit Index (NFI) = 0.59 |

|Non-Normed Fit Index (NNFI) = 0.71 |

|Comparative Fit Index (CFI) = 0.75 |

|Critical N (CN) = 290.00 |

|Root Mean Square Residual (RMR) = 0.15 |

|Standardized RMR = 0.10 |

|Goodness of Fit Index (GFI) = 0.82 |

|Adjusted Goodness of Fit Index (AGFI) = 0.77 |

Figure 6: LISREL model

[pic]

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[i] The influence of managerial characteristics on the internationalization process has been analyzed by Leonidou and Katsikeas, (1996); Leonidou, Katsikeas and Percy, (1998) and Manolova , Edelman and Greene, (2002).

[ii] The authors confirm the hypothesis that there is a direct link between the number of employees and the international activity of the firm.

[iii] Since SMEs are not able to influence significantly the external environment, due to their small dimension (Bijmolt e Zwart, 1994), we have excluded the environment dimension from the analysis.

[iv] See also Sousa C.M.P., 2004.

[v] Overall model fit indices include GFI (Goodness of fit index) and AGFI (Adjusted goodness of fit index), by Jöreskog and Sörbom (1986).

The goodness-of-fit index (GFI) is defined as:

GFI=1-[Ti/max (Ti)] (1)

The numerator in (1) is the minimum of the fit function after the model has been fitted; the denominator is the fit function before any model has been fitted, or when all parameters are zero.

The goodness-of-fit index adjusted for degrees of freedom, or the adjusted GFI, AGFI, is defined as:

AGFI=1-(k/df)(1-GFI) (2)

where df is the degrees of freedom of the model. This corresponds to using mean squares instead of total sums of squares in the numerator and denominator of 1 - GFI. Both of these measures should be between zero and one, although it is theoretically possible for them to become negative. This should not happen, of course, since it means that the model fits worse than no model at all.

We should also consider CN index (Critical N). It underlines if the sample size is adequate.

CN= [Dz(1-±)/F]-1 (3)

where Dz is the 1 - a percentile of the chi-square distribution. This is the sample size that would make the obtained chi-square just significant at the significance level a.

[vi] Incrementalχ²(1-α)/F]-1 (3)

where χ² is the 1 - a percentile of the chi-square distribution. This is the sample size that would make the obtained chi-square just significant at the significance level a.

[vii] Incremental fit indices include NFI (Normed fit index), by Bentler and Bonnet (1980), NNFI (Non-normed fit index), by Bollen (1988) and CFI (Comparative fit index).

NFI compares the improvement in the minimum discrepancy for the specified (default) model to the discrepancy for the independence model. A value of the NFI below 0.90 indicates that the model can be improved.

NFI=1-F/Fi (4)

NNFI adjusts NFI for the dgrees of freedom.

NNFI=(fi-f)/(fi-1) with f=nF/df and fi=nFi/dfi (5)

NNFI close to 1 indicates a good fit.

CFI compares the existing model fit with a null model which assumes the latent variables in the model are uncorrelated. CFI close to 1 indicates a very good fit.

CFI=1-τ/τi with τ=max(nF-d,0) and τi=max(nFi-di, nF-d, 0) (6)

[viii] Residuals indices include RMR index (Root mean square residual) and RMSEA index (Root mean square error of approximation). Residuals are the part of observed data that the estimated model is not able to explain.

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INTERNATIONAL PERFORMANCE

INTERNATIONAL ACTIVITY

OBJECTIVE ENTREPRENEURIAL CHARACTERISTICS

FIRM CHARACTERISTICS

SUBJECTIVE ENTREPRENEURIAL CHARACTERISTICS

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