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UNIVERSITAS NEGERI PADANG
REVIEW
INTERNATIONAL JOURNAL
FAKULTAS TEKNOLOGI PENDIDIKAN & KEJURUAN
06
TUGAS
MATAKULIAH
KEWIRAUSAHAAN Semester III TA 2018/2019
DOSEN : Prof. Dr. Ganefri, MT - Dra. Asmar Yulastri, M.Pd.,Ph.D
Oleh : DILSON - 17193034
Tugas Review Jurnal Internasional – Enterpreneurship | Dilson - 17193034
LITERATUR REVIEW ENTERPRENEURSHIP INTERNATIONAL JOURNAL
21
Type Title
Authors & Department
Journal
Ringkasan
: Journal : ENTREPRENEURSHIP EDUCATION IN HUMANITIES AND SOCIAL SCIENCES: ARE STUDENTS QUALIFIED TO START A BUSINESS : Jose Luis Vazquez-Burgete1, Ana Lanero2, Agota Giedre Raisiene3, Maria Purificacion Garcia4 1, 2, 4 University of Leon, Campus de Veganzana s/n, 24071 Leon, Spain 3Mykolas Romeris University, Ateities g. 20, LT-08303 Vilnius, Lithuania E-mails: [email protected]; [email protected] (corresponding author); [email protected]; [email protected] : Verslas: Teorija ir praktika Business: Theory and Practice Issn 1648-0627 print / Issn 1822-4202 online 2012 13(1): 27–35 doi:10.3846/btp.2012.03 :
Kurangnya pendidikan kewirausahaan di universitas-universitas Spanyol adalah karena banyak faktor yang mempengaruhi sebagian besar lembaga pendidikan tinggi di negara-negara Eropa, terutama kekurangan sumber daya manusia dan keuangan yang tersedia untuk semacam pengejaran, struktur organisasi yang kaku dari institusi pendidikan tinggi, tradisi multidisiplin yang buruk dalam organisasi program akademik, dan rendahnya motivasi dan pelatihan staf akademik dalam masalah kewirausahaan (EIDG 2008a, 2008b). Dalam hal ini, secara tradisional diasumsikan bahwa tingkat pendidikan yang diperoleh harus memenuhi syarat mahasiswa untuk mempraktikkan aktivitas profesional, yang pada gilirannya harus memenuhi tuntutan modal manusia yang dibutuhkan oleh sektor produktif, untuk berkontribusi pada kesejahteraan sosial-ekonomi. Untuk menutup kesenjangan antara pengetahuan yang diperoleh siswa dan kebutuhan pasar tenaga kerja, dan memberikan cakupan penuh kebutuhan semua pengguna universitas dan, dengan ekstensi, masyarakat, kewirausahaan dapat dilihat sebagai pilihan yang menjanjikan untuk penyisipan kerja dan pengembangan profesional lulusan universitas baru-baru ini, untuk melayani tujuan yang lebih luas dari kesejahteraan sosio-ekonomi yang berkelanjutan. Pada artikel ini penulis mengkaji konsep kompetensi kewirausahaan dan menggunakannya untuk menganalisis perbedaan dalam pendidikan kewirausahaan di berbagai disiplin ilmu Sosial dan Humaniora. Langkah yang dilakukan penulis adalah meninjau panduan yang ditandai oleh kebijakan umum Eropa sehubungan dengan masuknya pendidikan kewirausahaan sebagai bagian dari misi akademis universitas dan memberikan gambaran global tentang keadaan saat ini dalam lembaga pendidikan tinggi Eropa dan Spanyol, kajian literatur sebelumnya tentang pendidikan kewirausahaan dan menentukan konstruk kompetensi kewirausahaan dalam hal pengetahuan, keterampilan, dan sikap khusus. Penelitian dilakukan di dua universitas Spanyol dengan menyebarkan kuisioner kepada 448 mahasiswa dipilih secara car (random sampling). Berdasarkan jenis kelamin, sampel ini terdiri dari 337 perempuan (75,2%) dan 111 laki-laki (24,8%), berusia 20 hingga 47 tahun (M = 23,10, DT = 2,95). Di sisi lain, 21,7% responden menunjukkan latar belakang akademis utama di bidang Bisnis, 21,9% dalam Administrasi Publik dan Hukum, 40,8% dalam Ilmu Pengetahuan Manusia, dan 15,6% dalam Humaniora
Tugas Review Jurnal Internasional – Enterpreneurship | Dilson - 17193034
Variabel yang diukur adalah pengetahuan kewirausahaan, keterampilan dan sikap, menggunakan skala Likert yang terdiri dari sebelas poin dari 0 ("tidak penting sama sekali") sampai 10 ("sangat penting"). Alat bantu yang digunakan dalam analisis data adalah SPSS untuk menganalisis tiga faktor yang sebelumnya diidentifikasi sebagai pembeda kelompok mahasiswa sarjana dengan pengalaman belajar kewirausahaan, menggunakan Analisis Multivariat Varians (MANOVA) dengan latar belakang akademis sebagai variabel independen dikategorikan dalam empat kelompok Ilmu Bisnis, Administrasi Publik dan Hukum, Ilmu Pengetahuan Manusia, dan Humaniora. Hasil penelitian mendukung perbedaan antara tiga komponen yang dicakup oleh pengajaran formal kewirausahaan yang dirasakan oleh siswa, dalam hal pengetahuan, keterampilan dan sikap yang ditentukan dalam Kerangka Eropa tentang Kompetensi Utama untuk Pembelajaran Seumur Hidup (Rekomendasi 2006). Menurut perbedaan itu, iklim perubahan yang mencirikan pembentukan program gelar baru saat ini yang disesuaikan dengan EHEA menawarkan kesempatan yang sangat baik untuk bekerja pada desain program pengajaran yang memenuhi persyaratan untuk mendorong kewirausahaan. Untuk melayani upaya perencanaan kurikuler ini, dan dengan cara saran untuk praktik yang baik, model empiris yang timbul dari pekerjaan yang dijelaskan di atas menetapkan penerapan model pengajaran berbasis keterampilan yang menempatkan pengetahuan, keterampilan, dan sikap yang diperlukan untuk pengembangan kewirausahaan yang memadai di jantung dari setiap intervensi pendidikan.
** end of file - 21**
Verslas: Teorija ir praktika Business: Theory and Practice Issn 1648-0627 print / Issn 1822-4202 online
2012 13(1): 27–35 doi:10.3846/btp.2012.03
ENTREPRENEURSHIP EDUCATION IN HUMANITIES AND SOCIAL SCIENCES: ARE STUDENTS QUALIFIED TO START A BUSINESS? José Luis Vázquez-Burgete1, Ana Lanero2, Agota Giedre Raisiene3, María Purificación García4 1, 2, 4
University of León, Campus de Veganzana s/n, 24071 León, Spain Mykolas Romeris University, Ateities g. 20, LT-08303 Vilnius, Lithuania E-mails: [email protected]; [email protected] (corresponding author); 3 [email protected]; [email protected] 3
Received 8 December 2011; accepted 30 December 2011 Abstract. Over the last decade, entrepreneurship education has been acknowledged by European governments as a promising way to improve the work insertion of young people and, at the same time, contribute to general purposes of social and economic welfare. Particularly, social entrepreneurship is considered an emerging area of growth which provides the opportunity to make a difference in global community contexts. From this view, this paper proposes a model of entrepreneurship education based on the European Framework on Key Competences for Lifelong Learning to analyze the involvement of universities in related actions as perceived by students within Humanities and Social Sciences. Data was collected from a total sample of 448 students at two Spanish universities. Descriptive analysis was used to examine the development of entrepreneurship-related knowledge, skills and attitudes among students and its implications for labor insertion of future graduates in Humanities and Social contexts. Further conclusions of the study are discussed. Keywords: social entrepreneurship, entrepreneurship education, entrepreneurship competence, European Higher Education Area (EHEA), Social Sciences, Humanities, entrepreneurship education in Spain. JEL Classification: M54, I23, I25.
VERSLUMO UGDYMAS HUMANITARINIŲ IR SOCIALINIŲ MOKSLŲ STUDIJOSE: AR STUDENTAI YRA PASIRENGĘ PRADĖTI SAVO VERSLĄ? José Luis Vázquez-Burgete1, Ana Lanero2, Agota Giedrė Raišienė3, María Purificación García4 1, 2, 4
Leono universitetas, Campus de Veganzana s/n, 24071 Leonas, Ispanija Mykolo Romerio universitetas, Ateities g. 20, LT-08303 Vilnius, Lietuva El. paštas: [email protected]; [email protected]; 3 [email protected]; [email protected]
3
Įteikta 2011-12-8; priimta 2011-12-30 Santrauka. Pastarąjį dešimtmetį verslumo ugdymas Europos šalių vyriausybių pripažintas kaip perspektyvus būdas, galintis padėti pagerinti jaunų žmonių įsitraukimą į darbo rinką ir paskatinti ES socialinės bei ekonominės gerovės augimą. Tad socialinio verslumo vystymas tampa itin aktualus, siekiant pokyčių pasaulio visuomenės kontekste. Remdamiesi šiuo požiūriu ir mokymosi visą gyvenimą gairėmis, straipsnio autoriai domisi, kokią įtaką studijos universitete turi formuojant humanitarinių
http://www.btp.vgtu.lt/en
J. L. Vázquez-Burgete et al. Entrepreneurship education in humanities and social sciences...
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ir socialinių mokslų studentų verslumo kompetencijas. Pristatomi empirinio tyrimo, kuriame dalyvavo 448 dviejų Ispanijos universitetų absolventai, rezultatai. Remiantis aprašomosios statistikos metodais analizuojama, kokių žinių ir įgūdžių, nuostatų, leidžiančių komercializuoti būsimus savo darbo rezultatus, yra įgiję studentai, diskutuojama, kiek verslumo kompetencijos gali padėti įsitraukimo į darbo rinką aspektu. Tyrimo rezultatai rodo, kad į verslo aplinką geriau pasiruošę integruotis socialinių mokslų krypties absolventai, o humanitarinių studijų krypties atstovai, nors ir pasižymi teigiamomis nuostatomis asmeninio verslumo ugdymo požiūriu, stokoja tam būtinų žinių ir gebėjimų. Reikšminiai žodžiai: socialinis verslumas, verslumo ugdymas, verslumo kompetencijos, Europos aukštojo mokslo erdvė, socialiniai mokslai, humanitariniai mokslai, verslumo ugdymas Ispanijoje.
1. Introduction In the last few years, adaptation of university systems to the requirements of the European Higher Education Area (EHEA) are entailing significant transformations in surrounding countries, in an effort to deliver a better response to the social needs and expectations frequently assigned to these institutions. In this respect, it has been traditionally assumed that the educational level acquired must qualify college students to practice a professional activity, which in turn must satisfy the demands of human capital required by the productive sector, in order to contribute to socio-economic welfare. Nevertheless, the traditional flow of transactions between higher education and labor market has been proved to be insufficient in contemporary occidental societies, since unemployment, flexibility and over-qualification are considered the more representative descriptors of young people’s work insertion over the last decade in Europe (Eurostat 2009; García-Montalvo, Peiró 2009; OECD 2009a, 2009b). For this reason, different academics and researchers agree that European universities face the challenge of orienting their academic programs to new social demands (Flavián, Lozano 2004; Michavila 2009; Zabalda 2009), in an attempt to close the gap between students’ acquired knowledge and labor market exigencies, and provide full coverage of the needs of all university users and, by extension, those of society. Looking for this purpose, entrepreneurship can be seen as a promising option of work insertion and professional development of recent university graduates, at the service of broader objectives of sustainable socio-economic welfare. Not in vain, in the context of the wide-ranging social and economic changes that have been occurring in industrialized countries over recent decades, new, small enterprises have become a key element in creating employment, innovation and social welfare in all modern, competitive economies (Acs et al.1994; Thurik 1999; Audretsch et al. 2002; Bosma et al. 2008). This is true to such an extent that encouragement for entrepreneurship is currently at the heart of a host of requirements and public standards in the countries of the European Union (EU), in an effort that has reached out to affect economic, social, educational and employment policies (COM 2000, 2003, 2008).
From this general framework, this paper reviews the concept of entrepreneurial competence and uses it to analyze differences in entrepreneurship education across various Social and Humanities disciplines. In doing that, we first review the guidelines marked by the European common policy with regard to the inclusion of entrepreneurship education as part of the university academic mission and provide a global description of the current state of the matter in European and Spanish institutions of higher education. Next, we review previous literature on entrepreneurship education and define the construct of entrepreneurial competence in terms of specific knowledge, skills and attitudes. According to that, we present an empirical study carried out in two Spanish universities aimed to validate the model proposed and analyze differences in entrepreneurship education between students in the various Social and Humanities areas. Finally, conclusions and implications of the study are discussed.
2. Entrepreneurship education in the European Higher Education Area Encouragement for entrepreneurship education is currently at the heart of a host of political requirements in the countries of the European Union (EU), in an effort to develop a dynamic enterprising culture and foster new firm creation as a source of sustainable competitiveness in the continent (European Parliament 2000; COM 2010). An outcome of that has been the inclusion of the sense of initiative and entrepreneurship in a European Framework on Key Competences for Lifelong Learning (Recommendation 2006). From this view, it is recognized that entrepreneurship acts as a source of personal and professional self-realization, active citizenship and social inclusion for individuals, and that’s why entrepreneurial competences should be developed by the end of compulsory school or training, acting as a foundation for further lifelong learning. In this context, contemporary educational systems are seeing their training missions expanded by the assignment of a further responsibility to provide a socio-economic boost, taking the form of the channeling of future generations of the working population towards entrepreneurial goals in accordance with the new needs of the productive sector. Among all educational institutions, the universities’
Verslas: teorija ir praktika, 2012, 13(1): 27–35
response to this aim is of particular relevance, as they are the principal agents for generating and disseminating specialized knowledge in the context of a social reality in which access to higher education is more and more generalized in developed countries. In fact, the advisability of promoting entrepreneurial mindsets has extended to the current Bologna Process aimed to build a modern degree structure adapted to the professional profiles required by the current EU society through the establishment of a common European Higher Education Area (EHEA). In this context, the project Tuning educational structures in Europe (González, Wagenaar 2003), devoted to the identification of learning results and desirable competences by thematic area, has included entrepreneurship into the group of systemic transversal competences to be trained along all levels of university higher education. Despite this political commitment, it is estimated that more than half of university students in Europe do not have access to entrepreneurial education, some differences existing by country (EIDG 2008b). Based on the results of the Survey of entrepreneurship in higher education in Europe, whereas more and more European universities have nowadays some institutional system to disseminate the entrepreneurial culture and give support to new venture creation, entrepreneurship education at a curricular level seems to be influenced by type of institution, years of experience and geographic location. As expected, European students are more likely to obtain access to entrepreneurial education if they attend a business school or a multidisciplinary institution with a business department. Moreover, the way in which these institutions conduct entrepreneurial education seems to be also different and more elaborate. This can be explained, to some degree, by the fact that these types of institutions have been frontrunners in taking on entrepreneurial education and have therefore worked with it for a longer period of time. In the same line, time is a factor for implementing entrepreneurship in higher education in Europe, in the sense that the longer an institution has been engaged in entrepreneurial education, the more elaborate it is. And with regard to geographic location, the survey also points to a difference in access to entrepreneurship education depending on students’ country of residence. In general, students in the countries members of the EU have better access to entrepreneurial education than students in nonmember countries or in those which have recently joined the EU. In short, more institutions in Western Europe offer entrepreneurship education compared to Eastern Europe. However, the study doesn’t support the assumption that entrepreneurial education in the last countries is less elaborate than in the former. In fact, more institutions in Eastern Europe have a broader model of entrepreneurial education, with more institutions having specialized professors
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and degrees and providing recognition for achievements in entrepreneurial competences. However, more resources seem to be allocated to entrepreneurship education in Western institutions (EIDG 2008a). Particularly in Spain, most universities have developed and implemented specific extracurricular actions to give support to potential entrepreneurial initiatives of students, in the form of University-Enterprise foundations, business chairs, spin-off programs or specific institutional programs and centers on entrepreneurship (Directorate General of SME Policy 2006; ANECA 2007). However, the specific impact of those institutional initiatives on the entrepreneurial projections of Spanish graduates seem to be largely unknown, when not some disappointing. In this regard, previous evidence point to the general conclusion that students perceive a scarce consideration of entrepreneurship topics within university programs (Vazquez et al. 2010b), and since academic courses focus on the wage-employment paradigm, the transit through university has a poor effect on the entrepreneurial vocations of students (Vazquez et al. 2009, 2010a). Further, formal instruction in knowledge and abilities concerning new venture creation is usually limited to academic programs within Business and Economics disciplines, it being practically absent in the curriculum of other academic fields, especially within Humanities and Non-Business Social areas (Vazquez et al. 2010a, 2010b). In these cases, starting a new firm isn’t even considered as possible labour option for students, thus there is no awareness of the need of teaching basic entrepreneurial competences in the lecture hall, neither a structured action which allows students to learn them in a regulated way. All of these leads to a lack of receptivity and support to potential entrepreneurial initiatives of students, and lots of brilliant business ideas are forced to oblivion. This lack of entrepreneurship education in Spanish universities is due to many factors affecting most institutions of higher education in the European countries, particularly the shortage of human and financial resources available for such a kind of pursuits, the rigid organizational structure of higher education institutions, the poor multidisciplinary tradition in the organization of academic programs, and the low motivation and training of the academic staff in entrepreneurship issues (EIDG 2008a, 2008b).
3. The entrepreneurship competence In terms of curricular design, a competence can be defined as a dynamic combination of attributes that together permit a competent performance in a field, as the result of an educational process (González, Wagenaar 2003). From this view, three components are often identified in any competence: i) a conceptual component referred to the acquisition
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J. L. Vázquez-Burgete et al. Entrepreneurship education in humanities and social sciences...
of theoretical knowledge about a specific academic field; ii) a procedural component, based on the development of practical skills to apply the conceptual knowledge acquired; and iii) an attitudinal component of learned values, rules and personal attributes (Bolívar 1996; González, Wagenaar 2003; Biggs 2005). According to this specification, European guidelines remark three fundamental objectives of entrepreneurship teaching programs at the university (EIDG 2008a, COM 2003): i) developing entrepreneurial drive among students and raising their awareness of self-employment as a career option; ii) providing the technical and business skills that are needed to identify and exploit business opportunities, set up a new firm and manage its growth; and iii) promoting the development of personal qualities such as creativity, risk-taking and responsibility. In the same line, specialized literature is full of attempts for determining the more appropriate contents to be included in entrepreneurship training programs (Cotton, Gibb 1992; Gibb 1993; Hood, Young 1993; Kourilsky 1995; Hisrich, Peters 1998; Smith et al. 2006; Soutaris et al. 2007; Liñán 2007; Pittaway et al. 2009). As a point of reference for all these divergent approaches, the European Framework on Key Competences for Lifelong Learning (Recommendation 2006) specifies the essential knowledge, skills and attitudes related to the sense of initiative and entrepreneurship as a competence, as it is summarized in Table 1. In short, sense of initiative and entrepreneurship is defined as “an individual ability to turn ideas into action. It includes creativity, innovation, and risk taking, as well as the ability to plan and manage projects in order to achieve objectives” (Recommendation 2006: 17). Beyond that specification, there is a growing awareness of the need of orientating entrepreneurship education according to the needs of students with different academic background (COM 2010; Anderson, Jack 2008; Hofer, Potter 2010). For instance, within Business schools and Economic studies it is assumed that, since many business contents are offered separately (i.e., marketing, management, etc.), entrepreneurship programs should have a very narrow focus, stressing the start-up phase and the growth of small enterprises. Otherwise, experts agree that students in other Social and Humanities areas are usually good in technical aspects and frequently have very strong business ideas, their weaknesses concentrating in the development of specific business knowledge and abilities. From this view, the focus could be on social entrepreneurship as emerging area of growth which provides the opportunity to make a difference in community contexts. However, very little is known about entrepreneurship education in Non-Business Social and Humanities disciplines in European universities. To fill this gap, we next describe an empirical study in two Spanish universities to analyze the perceptions and experiences of students in the various Social disciplines.
Table 1. Entrepreneurship competence Knowledge Available opportunities for personal, professional and/or business activities Workings of the economy Organizational opportunities and challenges Ethical position of enterprises Fair trade and social entrepreneurship...
Skills Proactive project management (ability to plan, organize, manage, lead and delegate, analyze, communicate, de-brief, evaluate and record) Representation and negotiation Autonomous and collaborative work Self-knowledge Risk taking and assessment
Attitudes Initiative Pro-activeness Independence Innovativeness Motivation and determination to meet objectives...
Source: Adapted from Recommendation 2006/962/EC of the European Parliament and of the Council (Recommendation 2006)
4. Sampling and measures To make it possible the generalization of results to different institutional contexts, the study sample consisted of undergraduates in Social and Legal Sciences at two Spanish universities: the Complutesian University of Madrid and the University of León. Participants were registered from the final year of their academic programs, in order to provide evidence in undergraduates with enough previous university experience. The total sample comprised a total of 448 university students, ensuring a criterion of representativeness of 95% (being e = ± 5%; p = q = 0.50). By gender, this sample was composed of 337 females (75.2%) and 111 males (24.8%), aged 20 to 47 years old (M = 23.10, DT = 2.95). On the other hand, 21.7% of respondents indicated a main academic background in Business areas, 21.9% in Public Administration and Law, 40.8% in Human Sciences, and 15.6% in Humanities. Data collection was based on a procedure of collective voluntary self-administration of a questionnaire in scheduled university classes randomly selected, in the presence of a researcher trained for this end. The questionnaire administered comprised three scales for measuring perceived education of entrepreneurial knowledge, skills and attitudes. Particularly, students were asked to report their academic experiences in learning ten conceptual contents (e.g., “economic contribution of entrepreneurship”, “business structure and functioning”, “business start-up as a career choice”, etc.), eleven skills (e.g., “planning and organization”, “management”, “risk taking and assessment”, etc.), and eight attitudes (e.g., “initiative”, “pro-activeness”, “creativity”, etc.) specified according to the European Framework on Key
Verslas: teorija ir praktika, 2012, 13(1): 27–35
Competences for Lifelong Learning (Recommendation 2006). Respondents were asked to rate the perceived importance assigned to each content in their respective academic programs, on a eleven-point Likert-type scale from 0 (“not important at all”) to 10 (“very important”).
5. Results Once data was collected and processed, we used principal components factor analysis with program SPSS 15.0 to test the construct validity of the variables included in the model. Prior to performing factor analysis, the suitability of data was assessed. Inspection of the correlation matrix revealed the presence of many coefficients of .30 and above. Also, the Kaiser-Meyer-Oklin value was .946, exceeding the recommended value of .60 (Kaiser 1970, 1974) and the Barlett’s Test of Sphericity (Barlett 1954) reached statistical significance, supporting the factorability of the correlation matrix.
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Principal components analysis revealed the presence of four factors with eigenvalues exceeding 1, explaining a 64.88% of the total variance. Nevertheless, using Catell’s scree test (Catell 1966), it was decided to retain only three components for further investigation. To aid in the interpretation of the three components identified and its discriminant validity, Varimax rotation was performed. The rotated solution presented in Table 2 revealed the multidimensionality of the scales, according to the three dimensions of knowledge, skills and attitudes adopted in the European Framework on Key Competences for Lifelong Learning (Recommendation 2006). In this sense, every item had a loading above .40 in its respective construct, explaining the 22.66%, 20.12%, and 18.02% of the variance. Moreover, all the scales retained were associated to Cronbach’s α values of reliability over the recommended .70 (Nunnally 1978).
Table 2. Factor analysis Business start-up as a career choice Identification of business opportunities Steps to start a business Entrepreneurship local resources Entrepreneurs’ work functions Economic contribution of entrepreneurship Business structure and functioning Factors of business success Business models by academic area Social contribution of entrepreneurship Planning and organization abilities Executive abilities and leadership Negotiation abilities Analysis and assessment abilities Management abilities Communication abilities Delegation abilities Team work abilities Risk-taking and assessment Self-knowledge abilities Autonomous work abilities Creativity Independence Innovativeness Pro-activeness Responsibility Initiative Goal self-direction Change flexibility % Variance explained Cronbach’s α reliability
Knowledge .807 .746 .755 .715 .713 .704 .702 .690 .673 .646
Skills
Attitudes
.742 .679 .670 .648 .639 .626 .614 .606 .562 .530 .446
22.66% .921
20.12% .925
.756 .753 .750 .741 .739 .738 .704 .697 18.02% .921
Mean 2.95 3.19 2.64 2.46 4.57 4.30 4.02 4.53 4.18 4.01 4.64 4.42 4.00 4.93 4.14 5.06 3.55 5.46 4.06 3.93 3.78 4.16 4.45 4.14 4.52 5.68 4.49 4.95 4.23
J. L. Vázquez-Burgete et al. Entrepreneurship education in humanities and social sciences...
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Table 2 also displays the mean scores obtained by the total sample in the components of the three factors identified. In short, students reported a poor experience of education of entrepreneurship contents, with mean scores under the intermediate 5 in the ten-point scale, with the only exception of communication abilities (M = 5.06) and responsibility (M = 5.68). In aggregate terms, mean scores were higher for the skills (M = 4.36) and attitudes scales (M = 4.58) than in the knowledge scale (M = 4.58). In order to analyze the usefulness of the three factors previously identified to discriminate between groups of undergraduate students with different entrepreneurship learning experiences, we performed a Multivariate Analysis of Variance (MANOVA) with academic background as independent variable categorized in the four groups of Business Sciences, Public Administration and Law, Human Sciences, and Humanities. Results displayed in Table 3 showed a statistically significant difference between students within the academic disciplines considered on the combined dependent variables: F (9, 1075) = 16.53, p < .001; Wilks’ Lambda = .730; partial eta squared = .100.
When the results for the dependent variables were considered separately, differences in perceived teaching of entrepreneurship knowledge (F (3, 444) = 34.51; partial eta squared = .189), skills (F (3, 444) = 10.03; partial eta squared = .063), and attitudes (F (3, 444) = 6.45; partial eta squared = .042) were statistically significant according to a Bonferroni adjusted alpha level of .017 (.05/3). HSD Tukey post hoc test was performed to analyze the differences between students in specific academic areas more in deep. Statistically significant differences obtained by using an alpha level of .05 are shown in Table 4. In a general way, students within Business-related areas reported higher scores than their partners in other fields in the three dimensions analyzed. Undergraduates within Public Administration and Law also reported moderated learning experiences of entrepreneurship knowledge, while displayed the lowest mean scores in the attitudes scale. Opposite, Human Sciences students had relatively high perceptions of education of skills and attitudes when compared to other academic fields. Finally, students in Humanities obtained the lowest punctuations in most scales. These results are also summarized in Figure 1.
Table 3. Results from MANOVA Variable
Wilks’ Lambda
F
Partial Eta Squared
.730
16.53***
.100
Knowledge Skills Attitudes
F
Partial Eta Squared
34.51*
.189
10.03*
.063
6.45*
.042
* p < .017 (Bonferroni adjusted alpha level); *** p < .001
Table 4. HSD Tukey post hoc analysis Dependent variable Knowledge
Skills
Attitudes
Independent variable Academic area (J)
Mean dif. (I-J)
Std. Error
Sig.
Public Adm. and Law
1.31
.255
.001
Human Sciences
1.59
.223
.001
Humanities
2.77
.279
.001
Public Adm. and Law
Humanities
1.46
.279
.001
Human Sciences
Humanities
1.17
.250
.001
Public Adm. and Law
1.02
.274
.001
Humanities
1.46
.300
.001
Human Sciences
Humanities
1.05
.269
.001
Business Sciences
Public Adm. And Law
1.13
.292
.001
Human Sciences
Public Adm. and Law
0.98
.255
.001
Academic area (I) Business Sciences
Business Sciences
Verslas: teorija ir praktika, 2012, 13(1): 27–35
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6 5 4
5.05
4.97
4.98
4.82
4.57
4.44
3.96
3.74
3.84 3.52
3.46
3 2.29 2 1 0 Knowledge Business Sciences
Skills Publid Administration and Law
Attitudes Human Sciences
Humanities
Fig. 1. Mean differences by academic area
6. Discussion and conclusions Entrepreneurial activities act as one main driving force for economic and social development world around. European governments have gained awareness of that in the last decade and a great amount of political measures have been suggested to include entrepreneurship education as part of academic curricula in higher education institutions. However, most high level programs seem to be much more centred on training wage-earner managers or technicians than offering qualified and responsible entrepreneurs and enterprises to society. Given this relatively early stage of development of entrepreneurship education in European universities, this paper has reviewed the construct of entrepreneurship competence to analyze differences in entrepreneurship education between groups of students in the various Social and Humanities disciplines. In general, the results obtained support the distinction between the three components encompassed by entrepreneurship formal teaching as perceived by students, in terms of the knowledge, skills and attitudes specified in the European Framework on Key Competences for Lifelong Learning (Recommendation 2006). According to that distinction, the climate of change characterizing the current establishment of new degree programs adapted to the EHEA offers an excellent opportunity to work on the design of teaching programs meeting the requirements to encourage entrepreneurship. To serve this curricular planning effort, and by way of suggestions for good practices, the empirical model arising from the work described above sets the adoption of a skill-based
teaching model placing the knowledge, skills and attitudes necessary for an adequate development of entrepreneurship at the very heart of any educational intervention. Furthermore, the structure of entrepreneurship education validated in this work can be taken as a prescriptive framework for evaluating the effectiveness of the programs implemented in European universities, from the personal experiences of undergraduate students with different learning experiences. In this regard, results from the study presented here state a clear underconsideration of entrepreneurship competences in the Spanish universities analyzed, as showed by the poor assessments of the last-year students interviewed in terms of entrepreneurship knowledge, skills and attitudes. However, this picture seems to be different for students with different academic background. As expected, students within Business, followed by Human sciences, reported the most positive perceptions of entrepreneurship education in the university, whereas undergraduates in Humanities disciplines were found to be the less satisfied with the learning experiences provided. From this pattern of results, it can be stressed the lack of attention paid to the entrepreneurial potential of students within non-Business areas, in the sense that promising patterns of non-traditional social business opportunities aren’t being recognized as desirable and feasible work options for future graduates. While the fact that the empirical study reported here was carried out in two different Spanish universities demonstrates that the conclusions drawn from it are sufficiently solid, further studies are required to allow generalization of the results to other Spanish or European institutions.
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It would be even appropriate to consider other models of higher education with the aim of gaining greater precision in the identification of the educational factors determining the effectiveness of academic programs to foster entrepreneurship in the youth.
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Verslas: teorija ir praktika, 2012, 13(1): 27–35 research in entrepreneurship education (Vol. 1). Cheltenham, UK: Edward Elgar Publishing, 230–247. Michavila, F. 2009. Nuevos contenidos, nuevas metodologías, in Toledo, F.; Michavila, F. (Eds.). Empleo y nuevas titulaciones en Europa. Castellón: Tecnos Universitat Jaume I, 37–51. Nunnally, J. C. 1978. Psychometric Theory. NY: McGraw-Hill. OECD. 2009a. Education at a Glance. Paris: Organization for Economic Co-operation and Development (OECD). OECD. 2009b. Organization for Economic. Paris: Organization for Economic Co-operation and Development (OECD). Pittaway, L.; Hannon, P.; Gibb, A.; Thompson, J. 2009. Assessment practice in enterprise education, International Journal of Entrepreneurial Behaviour and Research 15: 71–93. http://dx.doi.org/10.1108/13552550910934468 Recommendation 2006/962/EC of the European Parliament and of the Council of 18 December 2006 on key competences for lifelong learning, Official Journal of the European Union L 394: 10–18. Smith, A. J.; Collins, L. A.; Hannon, P. D. 2006. Embedding new entrepreneurship programmes in UK higher education institutions. Challenges and considerations, Education and Training 48: 555–567. http://dx.doi.org/10.1108/00400910610710001
35 Soutaris, V.; Zerbinati, S.; Al-laham, A. 2007. Do entrepreneurship programmes raise entrepreneurial intention of science and engineering students? The effect of learning, inspiration and resources, Journal of Business Venturing 22: 566–591. http://dx.doi.org/10.1016/j.jbusvent.2006.05.002 Thurik, R. 1999. Entrepreneurship, industrial transformation and growth, in Libercap, G. D. (Ed.). The sources of entrepreneurial activity. Stanford, CA: JAI Press, 29–66. Vázquez, J. L.; Georgiev, I.; Gutiérrez, P.; Lanero, A.; García, M. P. 2010a. Promoting regional development from university. Students’ perceptions on entrepreneurship motivation and training programs, Trakia Journal of Sciences 8(1): 1–7. Vázquez, J. L.; Lanero, A.; Gutiérrez, P.; García, M. P.; Alves, H.; Georgiev, I. 2010b. Entrepreneurship education in the university: does it make the difference?, Trakia Journal of Sciences 8(3): 64–70. Vázquez, J. L.; Naghiu, A.; Gutiérrez, P.; Lanero, A.; García, M. P. 2009. Entrepreneurial potential in the University: intentions and attitudes towards new venture creation, Bulletin UASVM 66(2): 507–512. Zabalda, M. A. 2009. La nueva misión académica, in Toledo, F.; Michavila, F. (Eds.). Empleo y nuevas titulaciones en Europa. Castellón: Tecnos Universitat Jaume I, 73–105.
José Luis VÁZQUEZ-BURGUETE (PhD, PhD HC) is a Titular Professor on Marketing in the Faculty of Economic and Management Sciences at Leon University, Spain; Holder of the Bancaja Chair on Young Entrepreneurship; President of the International Association on Public and Nonprofit Marketing (IAPNM/AIMPN). Ana LANERO (PhD) is a Research Assistant on Marketing and Market Research in the Faculty of Economic and Management Sciences at Leon University, Spain. Agota Giedre RAISIENE (PhD) is an Associate Professor on Organizational Behaviour in the Faculty of Politics and Management at Mykolas Romeris University, Lithuania; President of the Academical Management and Administration Association. María PURIFICACIÓN GARCÍA (PhD) is an Assistant Professor in the Faculty of Labor Sciences at Leon University, Spain.
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LITERATUR REVIEW ENTERPRENEURSHIP INTERNATIONAL JOURNAL
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: Journal : The Impact of Entrepreneurship Education in Higher Education: A Systematic Review and Research Agenda : GHULAM NABI Manchester Metropolitan University, United Kingdom FRANCISCO LIÑA´ N University of Seville, Spain, and Anglia Ruskin University, United Kingdom ALAIN FAYOLLE EM LYON Business School, France NORRIS KRUEGER University of Phoenix, United States, and Entrepreneurship Northwest, United States ANDREAS WALMSLEY Plymouth University, United Kingdom : Academy of Management Learning & Education, 2017, Vol. 16, No. 2, 277–299. https://doi.org/10.5465/amle.2015.0026 :
Pendidikan kewirausahaan (Enterpreneurship Education) atau disingkat dengan EE telah berkembang secara pesat di universitas yang ada diseluruh negara. Hal ini didapat berdasarkan dari 157 artikel yang telah dirujuk mulai dari tahun 2004 s.d 2016. Pertumbuhan ini mencerminkan peningkatan pengakuan bahwa program EE berbasis universitas (selanjutnya disebut sebagai program EE) menjanjikan untuk mendukung berbagai potensi hasil wirausaha. Misalnya, peningkatan keterampilan, pengetahuan, dan sikap penciptaan usaha siswa (Greene & Saridakis, 2008) dan memulai bisnis pascasarjana dan penciptaan lapangan kerja secara keseluruhan (Greene, Katz, & Johannisson, 2004; Rideout & Gray, 2013) pada akhirnya berkontribusi pada ekonomi pertumbuhan dan perkembangan (Bosma, Acs, Autio, Coduras, & Levine, 2008). Dalam artikel ini penulis meninjau secara sistematis bukti empiris tentang dampak EE berbasis pendidikan tinggi diterbitkan dalam dekade terakhir. Dengan menggunakan kerangka model pengajaran, penulis memusatkan pada penilaian berbagai hasil EE dalam studi dampak. Tujuan sekunder adalah untuk menguji sejauh mana hubungan antara metode pedagogis yang digunakan dan hasil spesifik yang dicapai, pertama penulis menawarkan gambaran luas dari bukti dampak EE, yang terakhir mengeksplorasi apakah hasil campuran dalam studi dampak terkait dengan metode pedagogis yang berbeda. Untuk memajukan pemahaman tentang bagaimana meneliti dampak EE, kita membutuhkan keduanya. Kekuatan artikel terlihat dari mayoritas artikel yang dirujuk diterbitkan dalam 5 tahun terakhir dan didominasi oleh sampel mahasiswa Eropa, sarjana, dan kewirausahaan / bisnis. Mayoritas berasal dari 2011 dan seterusnya (100 artikel, 63%) dan tidak tercakup dalam tinjauan sebelumnya atau meta-analisis (mis., Martin et al., 2013; Rideout & Gray, 2013). Data berasal dari 38 negara, didominasi oleh Eropa (81 artikel, 51%, terutama Inggris dengan 28/18%); AS (27/17%); Asia (26/16%); dan kemudian diikuti oleh Afrika (16/10%); Australia (2/1%); dan perbandingan internasional (5/3%). Siswa yang dijadikan sampel sebagian besar sarjana (53%) atau pascasarjana (12%), atau alumni atau mahasiswa universitas yang tidak ditentukan. Mayoritas belajar kewirausahaan dan bisnis (35%) atau kursus kombinasi bisnis (24%)
Tugas Review Jurnal Internasional – Enterpreneurship | Dilson - 17193034
Penulis menemukan bahwa penggunaan metode pedagogis yang berbeda setidaknya menjawab pertanyaan bahwa adanya ketidakkonsistenan dampak dalam studi. Namun, mengingat bahwa temuan trsebut didasarkan pada sebagian sampel dari populasi artikel kami, mereka indikasi daripada konfirmasi. yang terbaik dari pengetahuan kami, ini adalah tinjauan sistematis pertama yang menggunakan kerangka model pengajaran untuk menilai dampak EE. Dalam pandangan penulis, ini memberikan wawasan baru dan bermakna. EE membuat klaim kuat untuk memiliki dampak yang signifikan dan bias yang kuat terhadap pedagogi pengalaman. Sementara mengkonfirmasikan kelemahan dalam studi dampak EE (misalnya, dominasi pada pengukuran dampak sikap dan tingkat kearah yang lebih rendah, dan kurangnya detail kunci mengenai pedagogi), penulis juga mengidentifikasi tiga cara utama untuk bergerak maju. 1) penulis menambahkan nilai dengan memberikan panggilan yang mutakhir dan secara empiris berakar untuk penelitian masa depan dalam pendidikan tinggi. 2) menerapkan kerangka model pengajaran, kami menawarkan beberapa saran yang menarik dan kurang ditekankan untuk meningkatkan penelitian EE., dan 3) penulis memberikan beberapa wawasan penting ke dalam alasan untuk temuan yang bertentangan dalam penelitian EE (misalnya, kelangkaan penelitian lintas budaya, gender-spesifik dan pedagogis-perbandingan) yang dapat digali lebih lanjut melalui studi tunggal / intervensi, sehingga kita dapat memahami bagaimana EE benar-benar bekerja dalam teori dan praktik
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Q Academy of Management Learning & Education, 2017, Vol. 16, No. 2, 277–299. https://doi.org/10.5465/amle.2015.0026
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The Impact of Entrepreneurship Education in Higher Education: A Systematic Review and Research Agenda GHULAM NABI Manchester Metropolitan University, United Kingdom ´ FRANCISCO LIÑAN University of Seville, Spain, and Anglia Ruskin University, United Kingdom ALAIN FAYOLLE EM LYON Business School, France NORRIS KRUEGER University of Phoenix, United States, and Entrepreneurship Northwest, United States ANDREAS WALMSLEY Plymouth University, United Kingdom Using a teaching model framework, we systematically review empirical evidence on the impact of entrepreneurship education (EE) in higher education on a range of entrepreneurial outcomes, analyzing 159 published articles from 2004 to 2016. The teaching model framework allows us for the first time to start rigorously examining relationships between pedagogical methods and specific outcomes. Reconfirming past reviews and meta-analyses, we find that EE impact research still predominantly focuses on short-term and subjective outcome measures and tends to severely underdescribe the actual pedagogies being tested. Moreover, we use our review to provide an up-to-date and empirically rooted call for less obvious, yet greatly promising, new or underemphasized directions for future research on the impact of university-based entrepreneurship education. This includes, for example, the use of novel impact indicators related to emotion and mind-set, focus on the impact indicators related to the intention-to-behavior transition, and exploring the reasons for some contradictory findings in impact studies including person-, context-, and pedagogical model-specific moderators.
........................................................................................................................................................................ Since the first entrepreneurship course at Harvard Business School was delivered in 1947, entrepreneurship education (EE) programs in higher education have grown rapidly and globally (Kuratko, 2005; Solomon, 2007). This growth reflects increasing recognition that university-based EE programs (hereafter referred to as EE programs) promise to support a range of potential entrepreneurial outcomes (Nabi
Prof. Fayolle, Prof. Krueger, and Prof. Walmsley made an equal contribution to the paper. The authors thank Associate Editor Prof. Siri Terjesen and the anonymous reviewers for providing constructive and helpful guidance throughout the review process. We ´ also thank Prof. Bechard, Prof. Henry, and Prof. Solomon for their comments on earlier drafts of this paper, and Dr. Christina Purcell and Imran Akhtar for their technical support. Address all correspondence to: Dr. Ghulam Nabi, Department of Management, Business School, All Saints Campus, Oxford Road, Manchester, M15 6BH, UK. Email: [email protected] 277
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´ 2011; Rideout & Gray, 2013). For example, & Liñan, enhanced student venture creation skills, knowledge, and attitudes (Greene & Saridakis, 2008) and graduate business start-ups and overall job creation (Greene, Katz, & Johannisson, 2004; Rideout & Gray, 2013) ultimately contributing to economic growth and development (Bosma, Acs, Autio, Coduras, & Levine, 2008). Synthesizing this fast-growing body of empirical research and reviews on EE outcomes suggests three main patterns. First, reviews highlight a focus on short-term, subjective impact measures such as entrepreneurial attitudes and intentions, rather than longer term ones such as venture creation behavior and business performance, and call for future research to address this gap (e.g., Garavan & O’Cinneide, 1994; Henry, Hill & Leitch, 2005; Pittaway & Cope, 2007). Promoting and implementing EE programs entails substantial investment of time and resources, so it is critically important to take stock of what we currently know about the range of EE outcomes and provide benchmarks for further research. Second, recent reviews suggest that the impact of EE programs on attitudes and behavior is equivocal because studies suggest both positive and negative outcomes (Dickson, Solomon, & Weaver, 2008; Fayolle, 2013; Martin, McNally, & Kay, 2013; Thompson, JonesEvans, & Kwong, 2010). These reviews tend to argue that the contradictory findings of EE impact studies may be due in part to methodological or statistical artifacts such as cross-sectional survey methodology and lack of control groups; notably, Rideout and Gray’s (2013) review and recent meta-analytical studies by Martin et al., (2013) and Bae, Qian, Miao, and Fiet (2014). However, also likely are other substantial reasons for the contradictory findings in EE impact research that can be teased out with single studies/interventions: for example, the nature and context of pedagogical interventions as well as contextual factors. In their extensive 1970–2004 review of EE research, Pittaway and Cope (2007) conclude there is a lack of research that directly links student/graduate entrepreneurial outcomes to different pedagogical methods and call for deeper investigation. Pedagogical methods may emphasize, for example, “exploration, discussion, or experimentation (e.g., library, web or other interactive searches, labs, field trips, simulations)” (B´echard & Gr´egoire, 2005:111). As well as examining a range of EE impact measures, it is therefore necessary to examine the different pedagogical methods that underpin them, not just methodological issues. Confusion regarding the
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impact of EE may result from the wide diversity of pedagogical methods employed in EE programs (Fretschner & Weber, 2013). This is further complicated by the lack of detail on pedagogical interventions studied (Martin et al., 2013), and the need for a stronger, more theory-driven framework for assessing the impact of such interventions (cf. Baptista & Naia, 2015; Fayolle & Gailly, 2008; ´ Krueger, 2015; Lackeus, 2015; Neergaard, Tanggaard, Krueger, & Robinson, 2012). It is therefore important to take stock of research on the pedagogy-entrepreneurial outcomes link within a coherent framework. Third, few reviews focus on EE specifically in higher education. Notable exceptions are Pittaway and Cope (2007) and Rideout and Gray (2013), but the former is limited to data from over a decade ago and the latter focuses on articles until 2010/2011. We cover 100 articles published in the past 5 years, which have not been covered in previous reviews of university-based EE impact (e.g., Rideout & Gray, 2013) or meta-analyses of EE outcomes of education in general (e.g., Martin et al., 2013). There is still, therefore, a need for a current review that focuses on EE pedagogy and outcomes in higher education. These three distinct yet related research gaps form the rationale for this article. Our aim is to review systematically the empirical evidence on the impact of higher education-based EE published in the last decade. Using the teaching model framework outlined below, we focus on assessing the range of EE outcomes in impact studies. A secondary aim is to examine the extent of the relationship between the pedagogical methods used and the specific outcomes achieved. While the former offers a broad overview of the evidence of EE impact, the latter explores whether the mixed results in impact studies are related to different pedagogical methods. To advance understanding of how to research EE impact, we need both. We believe that the main strength of our work here is the adoption of an integrated teaching model framework (Figure 1) to offer a coherent, overarching theoretical structure that covers both a broad range of entrepreneurial outcomes and pedagogical ´ ´ methods (Bechard & Gregoire, 2005; Fayolle & Gailly, 2008). Our teaching model framework integrates a range of impact measures and pedagogies. This is particularly useful here because for the first time we can now evaluate not only the range of EE outcomes in higher education impact studies, but also any patterns that connect specific types of pedagogical methods and impact measures. Our
´ Fayolle, Krueger, and Walmsley Nabi, Liñan,
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Nature of EE Pedagogical Methods (Béchard & Grégoire, 2005; Fayolle & Gailly, 2008) • • • •
Supply model focusing on reproduction methods such as lectures, reading, and so forth. Demand model focusing on personalized/ participative methods (e.g., interactive searches, simulations). Competence model focusing on communication, discussion, and production methods (e.g., debates, portfolios). Hybrid models (i.e., mixture of above).
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Impact Indicators (Jack & Anderson, 1998) Operational Level • • • • •
Level 1: Current and on-going measures during the program (e.g., interest and awareness). Level 2: Pre- and postprogram measures (e.g., knowledge, entrepreneurial intentions). Level 3: Measures between 0 and 5 years postprogram (e.g., number and type of start-ups). Level 4: 3 to 10 years postprogram (e.g., survival of start-ups). Level 5: 10 years plus postprogram (e.g., contribution to society and economy).
FIGURE 1 An Integrated Teaching Model Framework Encompassing EE Impact and Underpinning Pedagogy framework therefore permits empirical review with a pedagogical slant and responds to calls for more rigorous research to explore reasons for the contradictory findings in EE research (cf. Martin et al., 2013). The teaching model approach provides critical grounding for researchers and practitioners in the field of EE. Conceptual Framework Pedagogical research highlights how the evaluation of impact should be a key dimension of any teaching program and therefore needs to be considered at the program design stage (Fayolle & Gailly, 2008). In our research, types of EE impact have been integrated into the broader context of ´ ´ a teaching model framework (Bechard & Gregoire, 2005, 2007; Fayolle & Gailly, 2008). We explore two dimensions in our review—types of impact and underpinning pedagogy—given the paucity of research that directly links student/graduate entrepreneurial outcomes to different pedagogical methods (Pittaway & Cope, 2007). In the absence of a single impact measure within the teaching model framework, Henry, Hill, and Leitch (2003, building on Jack & Anderson, 1998) propose an impact classification system (incorporating several types of impact measures) that can be employed to assess the level of impact of EE programs. This classification system draws on earlier research on entrepreneurship (Block & Stumpf, 1992) and educational impact (Kirkpatrick, 1959), and complements the impact dimension of the teaching model framework because it highlights a range of impact measures from the beginning to the end of an EE program and beyond (see Figure 1 for a more
detailed explanation), thereby providing a basis for the systematic evaluation of EE impact studies. Reflection on different types of EE impact measures raises the issue of underpinning pedagogical ´ ´ methods. Bechard and Gregoire (2005) address this issue through identifying three “archetypical” teaching models in higher education: the supply model, the demand model, and the competence model, plus two hybrid teaching models. The supply model focuses on pedagogical methods highlighting a behaviorist paradigm, in terms of the “transmission and reproduction of knowledge and application of procedures” (e.g., lectures, reading, ´ ´ watching/listening; Bechard & Gregoire, 2005: 111). The demand model focuses on pedagogical methods highlighting a subjectivist paradigm, involving personalized meaning through participation in terms of “exploration, discussion and experimentation” (e.g., library use, interactive ´ ´ searches, simulations; Bechard & Gregoire, 2005: 111). The competence model focuses on pedagogical methods, highlighting an interactionist theoretical paradigm, in terms of active problem solving in reallife situations, where “teaching is conceived as a strategic intervention to allow for—and influence—how students organize the resources at their disposal (e.g., knowledge, abilities) into competences ´ that can be mobilized for action” (Bechard & Gr´egoire, 2005: 115–116). This model focuses on methods emphasizing “communication and discussion” (e.g., seminar, presentations, debates) and knowledge “production” (e.g., essays, modeling, portfolios). In contrast to the supply model, which emphasizes a behaviorist perspective, both the demand and competence models fit within the constructivist
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¨ approach to EE (Lobler, 2006; Neergaard et al., 2012). Behaviorism assumes learning is primarily the passive transfer of knowledge from the teacher to the student, while constructivism assumes that learning involves actively participating in the construction of new understanding. Often, pedagogical methods in EE in higher education are highly behaviorist: lectures, homework, quizzes, and so forth, that focus on knowledge acquisition, rather than the deeply experiential approaches of the constructivist ´ perspective (Neergaard et al., 2012). Bechard and ´ Gregoire (2005) apply these teaching models (supply, demand, competence) in EE to a higher education context. This allows us to classify and analyze various pedagogical models and review empirical evidence on the link between EE pedagogy and impact. Systematic Review Methodology We analyze 159 EE impact studies published from 1 February 2004 to 2 January 2016, continuing where Pittaway and Cope’s (2007) study left off. Following best practice from the methodological (Tranfield, Denyer, & Smart, 2003), synthesis (Cooper, 1989; Fink, 2009), and entrepreneurship literature (Pittaway & Cope, 2007; Wang & Chugh, 2014), we use a “systematic review process.” Initially, we use the root word “education” to search through all 11 entrepreneurship journals listed in the Association of Business Schools (ABS) as medium- and high-ranking entrepreneurship journals (Harvey, Kelly, Morris, & Rowlinson, 2010).1 We then use three databases (ABI ProQuest, Emerald, and Science Direct) to search for a broader range of keywords/search terms. The highest number of hits were from search terms including “entrepreneurship education,” “higher education,” “pedagogy,” “educational interventions,” “graduate,” “undergraduate,” or Boolean variations of these terms and an extensive range of others. Only article citations that met the following criteria were included: (a) empirical in nature rather 1
The ABS incorporates blind peer-reviewed journals for ranking entrepreneurship journals and expert assessment of journal quality (Harvey et al., 2010). Our 11 ABS journals include: Journal of Business Venturing, Entrepreneurship Theory and Practice, Journal of Small Business Management, International Small Business Journal, Small Business Economics, Entrepreneurship and Regional Development, Strategic Entrepreneurship Journal, Family Business Review, Journal of Small Business and Enterprise Development, International Journal of Entrepreneurial Behaviour and Research, and Venture Capital: An International Journal of Entrepreneurial Finance.
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than purely conceptual; (b) peer-reviewed published journal articles rather than working/conference papers or unpublished material; (c) primarily focused on higher education in terms of entrepreneurship education (or elements thereof) and its empirical impact on entrepreneurship outcomes (broadly defined to include both attitudinal and behavioral outcomes); (d) sampled recipients of EE from higher education institutions (rather than primary/secondary school, or nonhigher education level); and (e) analyzed primary rather than secondary data (Bae et al., 2014 and Martin et al., 2013 were included because of their use of meta-analysis, but reviews or research agendas were excluded). We also added searches for articles from bibliographies, key authors, and Google Scholar, as well as checking relevant references in recent reviews of EE outcomes (e.g., Bae et al., 2014; Martin et al., 2013; Rideout & Gray, 2013). We screened these additional candidates using our selection criteria. For example, Martin et al. (2013) includes articles that are unpublished or focus on schoolchildren, and were therefore excluded from our review.2 Two coauthors independently read the original collection of articles. We identified two first-order themes: (1) Types of Impact and (2) Pedagogical Methods. We then identified second-order themes by mapping our articles onto Henry et al.’s (2003) classification for im´ pact measures (Levels 1 to 5) and Bechard and ´ Gregoire’s (2005) framework of pedagogical models (e.g., supply, demand, and competence). For example, traditional lectures and business plan writing suggested a supply model, active participation in seminars, events or out-of-class projects reflected a demand model, and real-life entrepreneurial situations indicated a competence model. REVIEW FINDINGS: THEMES AND TRENDS We begin by examining background characteristics of our articles. This is useful when interpreting general patterns, for example, the most prominent journal outlets, country contexts, and types of students/graduates. We then analyze our articles regarding types of EE impact and relationships between types of impact and different pedagogical methods.
2
Further examples of excluded articles (with reasons for exclusion) are available from the authors.
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´ Fayolle, Krueger, and Walmsley Nabi, Liñan,
Background Characteristics of the Data Set Our sample covers research published in 61 journals, predominantly in entrepreneurship and small business journals (39%) and management and education journals (47%). The eight journals publishing the most EE impact articles account for 86 out of the 159 articles (54%).3 Overall, the majority of our articles were published in the last 5 years and are dominated by European, undergraduate, and entrepreneurship/ business student samples. A majority are from 2011 onward (100 articles, 63%) and were not covered in previous reviews or meta-analyses (e.g., Martin et al., 2013; Rideout & Gray, 2013). Data comes from 38 countries, dominated by Europe (81 articles, 51%, especially the UK with 28/18%); US (27/17%); Asia (26/ 16%); and then followed by Africa (16/10%); Australia (2/1%); and international comparisons (5/3%). Students in our sample are mostly undergraduate (53%) or postgraduate (12%), or alumni or unspecified university students. The majority studied entrepreneurship and business (35%) or business combination courses (24%). Types of Impact In the articles reviewed (see Table 1), we distinguish between studies focusing largely on our framework’s (see Figure 1) lower level impact indicators (typically short-term/subjective indicators at Levels 1 and 2) and on higher level ones (typically longer term/objective indicators at Level 3 or above). More specifically, the most common impact indicators are related to lower level indicators of subjective/ personal change: attitude (32 articles), skills and knowledge (34 articles), perceived feasibility (42 articles), and entrepreneurial intention (81 articles). By contrast, higher level indicators of longer term, objective, or socioeconomic impact are much less frequent: 21 articles study start-ups and 8 articles consider venture performance, both typically within 10 years of the program. Last, 41 articles report results not falling into any of these categories. These articles measure impact in terms of other variables, such as subjective norms (Souitaris, Zerbinati, & Education 1 Training (31 articles), The International Journal of Management Education (12), Journal of Small Business and Enterprise Development (10), International Journal of Entrepreneurial Behavior & Research (9), Journal of Small Business Management (7), International Entrepreneurship and Management Journal (6), International Small Business Journal (6), Academy of Management Learning & Education (5).
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Al-Laham, 2007), dispositional optimism (Crane, 2014), or satisfaction with the EE program (Rae & WoodierHarris, 2012). Most articles in the review claim a positive link between an EE program and subjective (e.g., personal change) or objective (e.g., business start-up activity) impact indicators (205 instances overall, see Table 1). Regarding lower level impact indicators, the most common indicator by far is entrepreneurial intentions (Level 2 in our framework). Most of the reviewed articles (61 articles out of 81, 75%) report a positive link between EE and participants’ start-up intentions. Nonetheless, several studies report mixed, negative, or nonsignificant/ambiguous results for the link with entrepreneurial intentions (18 articles or 22%, see Table 1). Of these, some articles suggest that EE reduces entrepreneurial intention for certain groups, for example, male German students (Packham, Jones, Miller, Pickernell, & Thomas, 2010), female Finish ¨ & Tornikoski, students (Joensuu, Viljamaa, Varamaki 2013), Greek students (Petridou & Sarri, 2011), students with previous entrepreneurial exposure (Fayolle, Gailly, & Lassas-Clerc, 2006b), or students with a weaker entrepreneurial university culture (Wang & Verzat, 2011). Our results suggest we know considerably more about the direct EE-intentions relationship in general than about the moderating role of gender (e.g., Joensuu et al., 2013; Shinnar, Hsu, & Powell, 2014), culture- (e.g., Bernhofer & Han, 2014; Crane, 2014), or context-specific patterns (e.g., Piperopoulos & Dimov, 2015; Turker & Selçuk, 2009), with only nine studies focusing clearly on such relationships. Further, using a meta-analysis of 73 studies, Bae et al. (2014) report a small but significantly positive EE–entrepreneurial intentions relationship, but that cultural values act as a moderator. For example, a high collectivistic culture or a low uncertainty avoidance culture reinforces the impact of EE. They also report that after controlling for pre-education entrepreneurial intentions, the EE-intentions relationship is not significant nor is gender a significant moderator. Although their research does not focus specifically on the impact of EE in higher education (they look at average effects across all education levels), we include them here because their findings provide some indicative evidence. Compared to entrepreneurial intentions (51%), far fewer studies exist on the relationship between EE and other subjective impact indicators (Levels 1 and 2 of our framework) including psychological variables such as attitude (20%, e.g., Boukamcha, 2015; Chang, Benamraoui, & Rieple, 2014; Vorley & Williams, 2016);
2b. Feasibility (42 articles, 26%)
2c. Entrepreneurial intention (81 articles, 51%)
3. Business startup (21 articles, 13%)
Other (41 articles, 26%)
Azim & Akbar, 2010 P; Alarape 2007 P; Bell, 2015, P; Donnellon et al., Burrows & Wragg, 2014 P; Gordon 2013 P; Crane, 2014 et al., 2012 P; Henry P; Crane & Meyer, et al., 2004 P; Lange 2007 P; Cruz et al., et al., 2014 P; 2009 P; Donnellon et Martin et al., 2013 P; al., 2014 P; Matlay 2008 P; Gilbert, 2012 P; Voisey et al., 2006 P Gordon et al., 2012 P; Groenewald 2012 P; Hamidi et al., 2008 P; Harris & Gibson, 2008 N; Hegarty, 2006 P; Heinonen et al., 2011 A; Hussain et al., 2010 N; Kirby & Ibrahim, 2011 P; Lackeus, 2014 P; Lanero et al., 2011 P; Lean, 2012 P; Li & Liu, 2011 P; Lourenço & Jayawarna, 2011 PI; Lourenço et al., 2013 PI; Martin et al., 2013 P; Matlay, 2011 P; McCrea, 2013 P; Millman et al., 2008 P; Mueller & Anderson, 2014 P; Newbold & Erwin, 2014 P; Ohland et al., 2004 P; Pittaway et al., 2011 P; Pittaway et al., 2015 P; (table continues)
4/5. Performance & Socio-econ. (8 articles, 5%)
Business
Ahmed et al., 2010 N; Burrows & Wragg, Bakotic & Kruzic, 2010 Brink & Madsen, 2015 Abaho et al., 2015 P; Almobaireek & Manolova, Armstrong, 2014 P; M; Burrows & 2013 P; Connolly P; Basu, 2010 P; 2012 P; Armstrong, 2014 P; Barakat et al., 2014 Wragg, 2013 P; et al., 2006 P; Boukamcha, 2015 P; Aslam et al., 2012 P; Azim & P; Basu, 2010 P; Chang & Rieple, Daghbashyan & Byabashaija & ˚ Akbar, 2010 P; Bakotic & Boukamcha, 2013 M; Chang et Harsman, 2014 P; Katono, 2011 P; Kruzic, 2010 P; Barakat et 2015 P; Burrows & al., 2014 P; Collins et Dominguinhos & Canziani et al., 2015 al., 2014 P; Basu, 2010 P; Wragg, 2013 P; al., 2006 PI; Carvalho, 2009 P; P; Chang et al., 2014 Bernhofer & Han, 2014 P; Byabashaija & DeTienne & Donnellon et al., P; Fayolle & Gailly, Boukamcha, 2015 P; Katono, 2011 P; Chandler, 2004 P; 2014 P; Dutta 2015 P; Fretschner & Byabashaija & Katono, Diaz-Casero Diaz-Casero et al., et al., 2010 P; Weber, 2013 P; 2011 P; Canziani et al., 2015 et al., 2012 PI; 2012 PI; Gielnik et al., Friedrich & Visser, P; Chang & Rieple, 2013 M; Fayolle & Gailly, Dominguinhos & 2015 P; Gilbert, 2006 P; Gerba, 2012 Cheng et al., 2009 N; 2015 P; Gerba, Carvalho, 2009 P; 2012 P; Henry P; Harris et al., 2007 Coduras et al., 2008 P; 2012 P; Gielnik Faoite et al., 2004 N; et al., 2004 P; A; Henry et al., 2004 Crane, 2014 P; De Clercq et et al., 2015 P; Galloway et al., Jansen et al., 2015 P; Hietanen, 2015 P; al., 2013 P; De George & Gilbert, 2012 P; 2005 P; Garalis & P; Karlsson & Idogho & Barr, Fayolle, 2008 P; DiazHarms, 2015 P; Strazdiene, 2007 P; Moberg, 2013 P; 2011 P; Izquierdo & Casero et al., 2012 PI; Harris et al., Gielnik et al., 2015 Lange et al., 2014 Buelens, 2011 P; Farashah, 2013 P; Fayolle 2007A; Hattab, P; Gilbert, 2012 P ; P; Martin et al., Karlsson & Moberg, 2014 N; Heinonen et Gondim & Mutti, 2013 P; 2013 P; Kassean et & Gailly, 2015 M; Fayolle et al., 2011 A; 2011 A; Gundry et McAlexander al., 2015 P; Kenny, al., 2006a P; Fayolle et al., Henry et al., 2004 P; al., 2014 P; Harms, et al., 2009 P; 2015 P; Kirby & 2006b M; Florin et al., 2007 Izquierdo & 2015 P; Henry et al., Pei-Lee & ChenHumayun, 2013 P; P; Franco et al., 2010 P; Buelens, 2011 P; 2004 P; Jones & Chen, 2008 P; Lanero et al., 2011 A; Friedrich & Visser, 2006 P; ´ 2004 P; Jones & Jones, Jones, 2011 P; Poblete & Liñan, Gerba, 2012 P; Gielnik et 2011 P; Karimi Kirkwood et al., Amoros 2013 A; Mentoor & al., 2015 P; Gilbert, 2012 P; et al., 2016 P; 2014 P; Klapper, Premand et al., Friedrich, 2007 N; Hamidi et al., 2008 P; Karlsson & 2014 P; Lans et al., 2016 P; Rauch & Packham et al., 2010 Hattab, 2014 P; Henry et al., Moberg, 2013 P; 2013 A; Lee et al., Hulsink, 2015 P; M; Petridou & Sarri, 2004 P; Heuer & Kolvereid, Kassean et al., 2005 P; Martin et al., Støren, 2014 A; 2011 M; Pittaway et 2014 P; Hytti et al., 2010 A; 2015 N; Kirkwood 2013 P; Morris et al., Vincett & Farlow, al., 2015 P; Shariff et Ismail et al., 2009 P; et al., 2014 P; 2013 P; Munoz et al., 2008 P; Wilson al., 2010 P; Solesvik, Joensuu et al., 2013 N; Jones Lanero et al., 2011 P; 2011 P; Ohland et et al., 2009 P 2013 P; Souitaris et et al., 2008 P; Jones et al., Laviolette al., 2004 P; Premand al., 2007 A ; 2011P; Bae et al., 2014 A; et al., 2012 P; et al., 2016 P; Tan & Stamboulis & Karimi et al., 2016 P; Lima et al., 2015 N; Ng, 2006 P; Thursby Barlas, 2014 P; Karlsson & Moberg, 2013 P; ´ 2004 P; ` Liñan, et al., 2009 P; Tounes Vorley & Williams, Kassean et al., 2015 P ; Keat Mentoor & et al., 2014 P; 2016 P; Walter & et al., 2011 P; Kirby & Friedrich, 2007 N; Ulvenblad et al., Dohse, 2012 P; Humayun, 2013 P; Lanero Newbold & 2013 PI; von Walter et al., 2013 P et al., 2011 P; Laviolette et
1. Attitude (32 articles, 20%)
2a. Skills and knowledge (34 articles, 21%)
Personal change
TABLE 1 Main Types of Impacts in Impact Studies
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P = 25 PI = 3 M=3 N=1 A=2 Total = 34
Graevenitz et al., 2010 M; Vorley & Williams, 2016 P; Watts & Wray, 2012 P
al., 2012 P; Lee et al., 2005 P; ´ Lima et al., 2015 N; Liñan, 2004 P; Martin et al., 2013 P; Miller et al., 2009 P; Mohamad et al., 2014 N; Mohamed et al., 2012 P; Muofhe & du Toit, 2011 P; Newbold & Erwin, 2014 P; Packham et al., 2010 M; Petridou & Sarri, 2011 M; Piperopoulos & Dimov, 2015 P; Raposo et al., 2008 P; Rauch & Hulsink, 2015 P; ´ Sanchez, 2011 P; Shariff et al., 2010 P; Smith & Beasley, 2011 A; Solesvik, 2013 P; Solesvik et al., 2013 P; Solesvik et al., 2014 P; Souitaris et al., 2007 P; Støren, 2014 P; Turker & ¨ et Selcuk, 2009 P; Varamaki al., 2015 A; Von Graevenitz et al., 2010 M; Walter & Dohse, 2012 P; Walter et al., 2013 M; Wang & Verzat, 2011 M; Westhead & Solesvik, 2015 M; Wilson et al., 2009 P; Yaghmaei et al., 2015 PI; Zainuddin & Rejab, 2010 P; Zainuddin et al., 2012 P; Zhang et al., 2014 P; Zhao et al., 2005 P P = 61 PI = 2 M=9 N=5 A=4 Total = 81
Erwin, 2014 P; PeiLee & Chen-Chen, 2008 P; Piperopoulos & Dimov, 2015 P; Rauch & Hulsink, 2015 P; Saeed et al., ´ 2015 P; Sanchez, 2011 P; Shinnar et al., 2014 M; Solesvik, 2013 P; Souitaris et al., 2007 A; Toledano & Urbano, 2008 A; Wilson et al., 2007 P; Wilson et al., 2009 P; Zainuddin & Rejab, 2010 P; Zainuddin et al., 2012 P
P = 32 PI = 1 M=1 N=4 A=4 Total = 42
2c. Entrepreneurial intention (81 articles, 51%)
2b. Feasibility (42 articles, 26%)
P = 19 PI = 0 M=0 N=0 A=2 Total = 21
3. Business startup (21 articles, 13%)
P=8 PI = 0 M=0 N=0 A=0 Total = 8
4/5. Performance & Socio-econ. (8 articles, 5%)
Business
P = 34 PI = 4 M=0 N=2 A=1 Total = 41
Premand et al., 2016 P; Rae & WoodierHarris, 2012 PI; ´ Sanchez, 2011 P; Souitaris et al., 2007 P; Tan & Ng, 2006 P; Vincett & Farlow, 2008 P; Wee, 2004 P; Man & Farquharson, 2015 P; Woodier-Harris, 2010 PI; Yusoff et al., 2012 P
Other (41 articles, 26%)
´ Fayolle, Krueger, and Walmsley Nabi, Liñan,
Note: In first row, number of papers (and percentage of total) indicated. Percentages rounded up. Some articles consider more than one impact measure, and are, therefore, included more than once in the table. Findings: P = positive; PI = positive indirect; M = mixed; N = negative; A = ambiguous/not significant.
P = 26 PI = 0 M=2 N=1 A=3 Total = 32
1. Attitude (32 articles, 20%)
2a. Skills and knowledge (34 articles, 21%)
Personal change
TABLE 1 Continued 2017 283
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perceived feasibility (26%, e.g., Rauch & Hulsink, 2015; or skills and knowledge (21%., e.g., Burrows & Wragg, 2013; Premand, Brodmann, Almeida, Grun, & Barouni, 2016). Most studies suggest a positive link between the program and these variables, but some articles report results that are not significant or negative. These include, for example, the absence of a significant link between EE and entrepreneurial attitudes ´ ´ among Spanish students (Lanero, Vazquez, Gutierrez, & Garc´ıa, 2011), and a negative link between EE and attitudes toward entrepreneurship among South African students (Mentoor & Friedrich, 2007), or perceived entrepreneurial and management skills among British students (Chang & Rieple, 2013). So again, limited studies explore the context-specificity of EE’s impact. Novel ways of assessing EE impact in higher education are limited. Only four studies explore emotion or related approaches to assessing EE impact. For example, inspiration (not learning) emerges as the most important benefit of EE, implying a “change of heart” as well as a positive link to entrepreneurial intentions (Souitaris et al., 2007). A few other studies also suggest a positive EE-outcomes link regarding uncertainty and ambiguity tolerance (Lack´eus, 2014); dispositional optimism (Crane 2014); and sense of psychological ownership (Man & Farquharson, 2015). Similarly, four studies focus on EE impact on intention-to-nascent start-up activity or entrepreneurial identity. These suggest either a nonsignificant impact of EE on nascency (Souitaris et al., 2007), or a positive link through a dynamic process of internal self-reflection and social engagement ´ (Donnellon, Ollila, & Middleton, 2014; Lackeus, 2014), and personal development, for example, a multiple sense of responsibility, independent thinking, and connecting to one’s own and others’ needs (Mueller & Anderson, 2014). Other emotion- or transition-based indicators are also completely absent from our review. For example, outside of our review, research highlights EE’s role in developing the importance of entrepreneurial passion (intense positive emotion and drive, see Cardon, Wincent, Singh, & Drnovsek, 2009), yet it is strikingly missing from the articles in our review. Our review suggests 29 instances (corresponding to 25 articles, see Table 1) focusing on objective impact indicators, typically over a longer timeframe corresponding to the higher Levels 3 (0–5 years), 4 (3–10 years), or 5 (over 10 years) in our framework. Because these types of studies are limited in our review, some examples are given. Such studies include the positive impact of undergraduate (Pei-Lee & Chen-Chen, 2008)
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and postgraduate (Dominguinhos & Carvalho, 2009) EE programs on start-up rates at Level 3 of our framework. Furthermore, Lange, Marram, Jawahar, Yong, and Bygrave (2014) provide a notable example of the long-term positive impact of EE on Babson graduate performance over a 25-year period, including a major economic contribution, for example, 1,300 new full-time businesses were started, with average annual revenues of $5.5 million and an average of 27 employees. Last, using a meta-analytical approach (including pre- and posteducation data, N 5 16,657), Martin et al. (2013) found small but positive relationships between EE and entrepreneurial outcomes incorporating nascent behavior, and start-up and venture performance (e.g., financial success and personal income). As with Bae et al., (2014), they do not specifically focus on higher education (they look at average effect across all educational levels), but we include them here because their findings provide some indicative evidence. Most of our higher impact studies report a positive link between EE and objective indicators, but one suggests a relationship that is not significant. Using a sample of 2,827 university graduates in Norway, Støren (2014) reports graduates who have had EE are not more frequently selfemployed than other graduates. Thus, our review suggests high-impact studies are scarce and need not show positive impact. A final finding relates to the measurement methodology of the articles. Typically, articles use crosssectional survey methodology (68%). Nonetheless, some notable exceptions employ a longitudinal design and/or a control group. These generally demonstrate a pattern of positive EE impact for entrepreneurial intentions (Souitaris et al., 2007), competencies ´ (Sanchez, 2011), and start-ups (Karlsson & Moberg, 2013). However, even in more methodologically rigorous studies, a few still report a lack of significant results for entrepreneurial self-efficacy (Souitaris et al., 2007) or significantly negative impact on entrepreneurial attitudes (Mentoor & Friedrich, 2007). Overall, the review suggests reasonable evidence of positive EE impact. This holds especially for entrepreneurial attitudes and intentions (impact Levels 1 and 2 of our framework), but even here some examples demonstrate differential impact depending on context and the background of participants (Fayolle & Gailly, 2015; Fayolle et al., 2006b). Pedagogical Methods Underpinning Impact Next, we examine the extent of the relationship between the pedagogical methods used and the
3. Business start-up
´ Sanchez, 2011 P; Crane 2014 P; ´ Shinnar et al., 2014 Sanchez 2011 P; M Solesvik et al., 2013 P; Solesvik et al., 2014 P Henry et al., 2004 P; Hamidi et al., 2008 P; Henry et al., 2004 P Henry et al., 2004 Izquierdo & ´ 2004 P; P; Liñan, Buelens, 2011 P; ´ 2004 P Liñan, Shariff et al., 2010 P
2b. Feasibility
2c. Entrepreneurial intention
Boukamcha, 2015 P; Fayolle & Gailly, 2015 P; Souitaris et al., 2007 A
Boukamcha, 2015 P; McAlexander et al., 2009 P; Premand Fayolle et al., et al., 2016 P 2006a P; Fayolle & Gailly, 2015 M; Kirby & Humayun, 2013 P; Miller et al., 2009 P; Souitaris et al., 2007 P; ¨ et al., Varamaki 2015 A Abaho et al., 2015 P; Armstrong, 2014 P; Burrows & Wragg, Demand- Friedrich & Visser, Burrows & Wragg, Chang & Rieple, Armstrong, 2014 P; 2013 P; Chang & Compet. 2006 P; Harris 2013 P; Dutta et al., 2013 M; De George Burrows & Wragg, Rieple, 2013 M; et al., 2007 A; 2010 P; Jansen & Fayolle, 2008 P; 2013 P; Harms, DeTienne & Hietanen, 2015 P; et al., 2015 P; 2015 P; Harris Chandler, 2004 P; Kasseann et al., Rauch & Hulsink, Florin et al., 2007 P; et al., 2007 A; Jones Garalis & 2015 P; Kenny, 2015 2015 P Friedrich & Visser, & Jones, 2011 P; Strazdiene, 2007 P; P; Vorley & 2006 P; Kassean Kassean et al., Gondim & Mutti, Williams, 2016 P et al., 2015 P; 2015 N; Kirkwood 2011 A; Harms, Piperopoulos & et al., 2014 P; 2015 P; Jones & Dimov, 2015 P; Piperopoulos & Jones, 2011 P; Rauch & Hulsink, Dimov, 2015 P; Kirkwood et al., 2015 P Rauch & Hulsink, 2014 P; Morris 2015 P et al., 2013 P; ` et al., 2014 Tounes P Vorley & Williams, 2016 P
SupplyFretschner & Weber, Henry et al., 2004 P; Klapper, 2014 P; Demand 2013 P; Henry Thursby et al., et al., 2004 P; 2009 P Izquierdo & Buelens, 2011 P; ´ 2004 P; Liñan, Shariff et al., 2010 P; Stamboulis & Barlas, 2014 P Demand Boukamcha, 2015 P; Lans et al., 2013 A; Fayolle & Gailly, Munoz et al., 2011 2015 P; Kirby & P; Premand et al., Humayun, 2013 P; 2016 P Souitaris et al., 2007 A
Types of Supply Teaching Model Pedagogya
1. Attitude
2a. Skills and knowledge
Types of Impactb
TABLE 2 Overview of Alternative Pedagogies, Comparison Studies, and Types of Impact
Crane 2014 P; ´ Sanchez 2011 P
Other
´ Fayolle, Krueger, and Walmsley Nabi, Liñan, (table continues)
Burrows & Wragg, 2013 P; Man & Farquharson, 2015 P; Tang & Ng, 2006 P; Wee, 2004 P
Bell, 2015 P; Millman et al., 2008 P; Mueller & Anderson, 2014 P; Pittaway et al., 2011 P; Premand et al., 2016 P; Souitaris et al., 2007 P
Henry et al., Crane & Meyer, 2007 2004 P P; Hamidi et al., 2008 P
4/5. Perform. & socioecon.
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Lange et al., 2014 P
Other Donnellon Donnellon et al., et al., 2014 2014 P; Gordon P; Gordon et al., 2012 P; et al., 2012 Lackeus, 2014 P; P McCrea, 2013 P; Pittaway et al., 2015 P Lange et al., 2014 P
4/5. Perform. & socioecon.
Note: Articles without teaching model information not shown (13 for Level 1, 13 for L2a, 21 for L2b, 53 for L2c, 9 in L3, 4 in L4/5 and 22 in other). Some articles consider more than one impact measure, and are, therefore, included more than once in the table. a ´ ´ Based on our framework drawing on Bechard & Gregoire (2005). b Based on our framework drawing on Henry et al.’s (2003) classification. See Table 1 for details on the sign of impacts (positive, negative, mixed, or ambiguous). For the comparison studies (Lange et al., 2014; Walter & Dohse 2012; Wang & Verzat 2011), supply models are consistently found to have less positive impact.
Walter & Dohse, 2012 P; Wang & Verzat, 2011 M
Walter & Dohse, 2012 P
Compar isons
3. Business start-up
Chang et al., 2014 P; Brink & Madsen, Gielnik et al., 2015 P; Bae et al., 2014 A; Donnellon et al., Pittaway et al., 2015 M; Chang Gilbert, 2012 P; Gielnik et al., 2015 2014 P; Gielnik 2015 P et al., 2014 P; Toledano & P; Gilbert, 2012 P et al., 2015 P; Gielnik et al., 2015 Urbano, 2008 A Gilbert, 2012 P; P; Gilbert, 2012 P Vincett & Farlow, 2008 P
2b. Feasibility
2c. Entrepreneurial intention
Compet.
1. Attitude
2a. Skills and knowledge
Types of Impactb
TABLE 2 Continued
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´ Fayolle, Krueger, and Walmsley Nabi, Liñan,
specific outcomes achieved (see Table 2). In our review, studies that provide sufficient pedagogical detail are limited. Only 72 of our 159 articles (45%) provide enough detail for us to determine their pedagogical approach. The following section focuses on these 72 articles. Supply and Supply–Demand Model Pedagogy Only five articles can be classified in terms of supply model pedagogy. These are positively re´ lated to self-efficacy (Sanchez, 2011) and entrepreneurial intentions (e.g., Crane, 2014; Solesvik et al., ´ 2013, 2014). For example, Sanchez (2011) focuses on transmitting knowledge to students so that they “know about entrepreneurship,” and this mainly behaviorist course has a positive impact on a range of student perceptions (at Level 2 of our framework, e.g., intention, self-efficacy). This suggests a supply model link to lower level impact indicators, although Shinnar et al., (2014) find mixed results, primarily at Level 2, based on a moderating effect of gender. In turn, programs that combine pedagogies from the supply and demand model tend to be positively related to lower levels of our framework. Of the 12 supply–demand articles, only one (Henry et al., 2004) addresses impact at higher levels. A typical example of a supply–demand article is the program analyzed by Hamidi, Wennberg, and Berglund (2008) which despite concentrating on knowledge transmission, includes some experiential learning, in this case, creativity development exercises whereby the authors report a positive link with entrepreneurial intentions.
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needs and interests. Moreover, these studies largely suggest a positive link of this model’s pedagogy with lower level impact indicators—our framework’s Level 2 indicators (entrepreneurial intention, Fayolle et al., 2006a; Souitaris et al., 2007), or other personal change, such as satisfaction with the course or participation (Millman, Matlay, & Liu, 2008; Pittaway et al., 2011). Of the EE programs studied in the review, 27 are consistent with demand–competence model pedagogy. They share the inclusion of an important element of realism, such as real-life problems to be solved. This is powerful, because despite the challenges to the learner, the learning is more transferable to the real world (cf. outside our review, Neergaard et al. 2012). In the articles in this stream, the pedagogical methods are experiential and entail working side by side with, for example, entrepreneurs (e.g., Chang & Rieple, 2013); realistic entrepreneurial exercises (e.g., Gondim & Mutti, 2011); starting and running a “real” business (e.g., Burrows & Wragg, 2013); and problem-based learning (e.g., Kirkwood, Dwyer, & Gray, 2014). Again, these studies report a positive link with lower level impact measures (skills and knowledge, and feasibility, e.g., Jones & Jones, 2011). However, ambiguous or mixed results are also found for intention and feasibility (Chang & Rieple, 2013; Harris, Gibson, & Taylor, 2007). Overall, the pattern suggests a positive link between demand and demand–competence model pedagogy and primarily lower level impact indicators. Competence Model Pedagogy
Demand and Demand–Competence Model Pedagogy Fifteen articles analyze interventions adhering to demand model pedagogy. These typically focus on short-term intensive experiential programs (e.g., Fayolle & Gailly, 2015), or longer experiential residential-based programs (e.g., Boukamcha, 2015). They also include student-led entrepreneurship clubs that allow students to work on collaborative projects and gain awareness from experienced entrepreneurs (Pittaway, Rodr´ıguez-Falcon, Aiyegbayo, & King, 2011), and a pedagogical method that goes beyond formal classroom teaching, incorporating, for example, network events and interaction with entrepreneurs (Souitaris et al., 2007). All these studies share a focus on exploration, discussion, and experimentation, with a preoccupation on students’
Twelve articles fall into this category. Pedagogical methods entail students who are starting up businesses by consulting external experts, typically for legal, accounting, and sales help (Vincett & Farlow, 2008) or dealing with real-world problems or opportunities in industry-engaged environments to enhance social interaction and deeper learning (Gilbert, 2012). These articles are positively related to Level 2 (skill development, learning; Gilbert, 2012), Level 3 (actual start-ups; Gilbert, 2012; Vincett & Farlow, 2008), and Level 4 of our framework (positive changes in the person and business that run 5 years after the course: e.g., increase in social capital and socioeconomic bonds; Gordon, Hamilton, & Jack, 2012). Given the limited number of articles in this category, we see our results as indicative rather than confirmatory.
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Comparison Studies Only three articles compare EE programs using competing pedagogical methods. Lange et al. (2014) suggest that experiential courses (featuring demand and competence models) better predict multiple entrepreneurial behaviors: The rare behaviorist courses in their study (“how to write a business plan”) are essentially a negative predictor. They measure impact at the highest impact level of our framework (Level 5) and show a positive socioeconomic impact up to 25 years postprogram. Similarly, Walter and Dohse (2012) compare active learning (constructivist) to traditional learning (behaviorist) in locations with either weak or already-strong entrepreneurial cultures, finding the constructivist model to have a stronger impact in terms of, for example, entrepreneurial intention. Overall, our review highlights that each category of pedagogical methods (supply, demand, competence, hybrids) has some positive relationship with the lower level impact indicators of our teaching model framework (e.g., attitudes and intentions). However, the demonstrated pattern of pedagogy impact depends to an extent on the aims of researchers. Although articles featuring fewer experiential programs (supply, supply–demand, demand) focus more on basic or lower levels of our framework, articles examining more experiential programs (demand–competence and competence) also focus on impact at higher levels (e.g., actual start-ups and socioeconomic impact over time). These latter studies ask more from their programs and typically obtain higher impact. DISCUSSION Guided by a unique, theory-driven teaching model framework, we undertook a systematic review of a range of EE impacts in higher education, drawing on empirical evidence published since 2004. This entailed a thematic analysis of the evidence using our adopted teaching model framework to classify different types of outcomes and pedagogies. We also explored the extent of the relationship between pedagogical methods and outcomes achieved. Reaffirmation of Past Reviews Despite the increase in the amount of research on EE and entrepreneurial outcomes in higher education
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over the past 12 years (nearly two thirds of our 159 articles are published in the last 5 years), there is still a general focus on lower level, short-term, subjective impact indicators, especially the EE– entrepreneurial intentions link (51%), and the lack of specifying even minimal pedagogical detail (55%). Hence, in general, we reconfirm the findings and repeat the calls of previous reviews for more research on entrepreneurial behavior (e.g., Pittaway & Cope, 2007) and greater pedagogical detail (cf. Martin et al., 2013). Our teaching model framework urges a focus on higher level impacts such as startups, firm survival rates, business performance, and societal contribution. Furthermore, it also means that future researchers provide detailed information about the pedagogical methods, so we can understand the impact of pedagogical designs and methods. Extending previous reviews, our findings lead us to focus on new or underemphasized calls for future research. As a general pattern from our findings, progress on the previous calls outlined above has been slow, and EE impact research continues to be limited. For example, in our review, it is rare to see articles on novel EE impact measures or exploring the reasons behind the contradictory findings in higher education-based EE research that go beyond statistical/artifactual reasons (cf. Martin et al., 2013; Rideout & Gray, 2013). Table 3 presents our recommendations for future research and these are discussed in more detail below. Types of EE Impact Focus on Novel Impact Indicators Related to Emotion-Based Approaches Given the dominance of entrepreneurial intentions as an impact indicator in our research, we suggest it is important to understand alternative impact measures. Although entrepreneurship is considered a “journey of the heart” and the importance of understanding entrepreneurial emotion (affect, emotions, feelings), especially during the new venture creation process is acknowledged (Cardon, Foo, Shepherd, & Wiklund, 2012), there is surprisingly little empirical research in our review that focuses on emotion-based impact indicators. We therefore urge scholars to pursue the following important avenues. First, we are surprised by the scarcity of research that addresses emotion or affect. Given the growing consensus on their importance in entrepreneurial
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TABLE 3 Future Research Directions: Types of EE Impact and Pedagogical Models Reaffirmation of past reviews 1. Ongoing requirement for increased research on higher level impact indicators by examining objective and higher level measures at Levels 4 and 5 of our teaching model framework (see Figure 1) including entrepreneurial behavior. 2. More detail about the specifics of the pedagogy in impact studies. New or underemphasized research directions 1. Types of Impact A. Focus on novel impact indicators related to emotion-based and mind-set approaches i. Explore role of EE program-derived inspiration in higher education as an impact indicator and a mediator between EE and a range of other impact measures. For example, does inspiration mediate the EE-behavior relationship? ii. Examine the development of the entrepreneurial mind-set in higher education such as dispositional optimism, uncertainty and ambiguity tolerance. B. Focus on impact indicators related to the intention-to-behavior transition i. Build on Souitaris et al. (2007) to generate new knowledge about why there is (or is not) a transition from entrepreneurial intentions into nascent or start-up behavior, specifically for example, why do some recipients of higher education-based EE with high entrepreneurial intentions start up their own businesses after graduating, while others (despite high intentions) do not? What is the role of EE in higher education in this process? ii. Explore the development of entrepreneurial identity in higher education. C. Explore contextual reasons for some contradictory findings in impact studies i. Explore individuals’ background in terms of previous entrepreneurial exposure and pre-educational intentions to clarify the impact of higher education-based EE. ii. Directly examine if the impact of EE programs in higher education on a range of entrepreneurial outcomes is gender-specific and for which outcomes. iii.Consider contextual factors in higher education, e.g., type of course, type of institution. iv. Expand existing research by looking at relationship between culture and national context in EE impact studies. For example, how do cultural values moderate the impact of EE on outcomes? What outcomes are culture specific? Our teaching model framework could be expanded to incorporate culture-specific frameworks (e.g., Hofstede, 2003; Schwartz, 2004). v. Explore underexamined fast-growing/emerging countries/continents in our sample e.g., Brazil, Russia, Africa, and Australia. vi. Examine double-moderator interaction effects. For example, does EE impact outcomes as a function of culture and gender? 2. Pedagogical methods underpinning impact A. Investigate competence model-related pedagogical methods to determine if they are truly more effective than other models, and why they are effective. B. Building on our teaching model framework, directly compare and contrast a broad range of pedagogical models (supply, demand, competence, and hybrids) in terms of their impact on a range of impact indicators (from Levels 1 to 5). General recommendations 1. Explore EE at other levels, i.e. other than higher education. 2. Explore impact of university-based EE on stakeholders other than students and graduates. For example, university faculty, donors/ investors, and community.
thinking, for example, passion (Cardon et al., 2009, 2012; Gielnik et al., 2015), this is startling. For example, only one empirical study in our sample measures EE program-derived entrepreneurial inspiration (Souitaris et al., 2007) that identifies emotional inspiration (not learning or incubation resources) as the most important EE “programme benefit” with inspiration also positively related to entrepreneurial intentions (Souitaris et al., 2007). Moreover, they define it as “a change of hearts (emotion) and minds (motivation) evoked by events or inputs from the programme and directed towards considering becoming an entrepreneur” (Souitaris
et al., 2007: 573). Thus, we consider it of central importance as both an impact indicator in its own right (i.e., if EE increases inspiration), and as a predictor of other impact measures. Indeed, Souitaris et al. (2007: 587) conclude: “Universities that want to assess the effectiveness of their programmes should capture not only how much their students learn about entrepreneurship or whether they are satisfied with the courses, but also whether they are inspired from the programme.” Despite its importance, inspiration from EE programs in higher education remains an under-researched phenomenon and warrants further research attention.
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A second key knowledge gap centers on impact measures focusing on the development of the entrepreneurial mind-set, defined here as cognitive phenomena deeper than intent4 (Krueger, 2007, 2015; ´ Lackeus, 2015). Few studies in our review even reference this phenomenon. One rare example (Crane, 2014) suggests dispositional optimism as a key indicator of EE impact because of its self-regulatory function and dealing with uncertainty and setbacks. They find their program improves such optimism, suggesting another fruitful avenue to explore. Similarly, under OECD’s Entrepreneurship360 initia´ tive, Lackeus (2015) identifies the importance of uncertainty/ambiguity tolerance as impact indicators for action-based EE programs that tie back to the issue of emotions in entrepreneurial thinking. Focus on Impact Indicators Related to the Intention-to-Behavior Transition Our findings also suggest a paucity of studies of EE in higher education that bridge the transition from intention to behavior, that is Levels 2 to 3 in our teaching model framework. This is an important avenue because intention does not always translate into entrepreneurial behavior and little is known about this transition. Indeed, Pittaway and Cope (2007: 498) conclude “what is not known . . . is whether propensity or intentionality is turned into ‘entrepreneurial behavior’, either in its broad sense or when focused narrowly on venture creation.” Although we re-emphasize their claim here, we also extend their call, by suggesting two specific avenues that we encourage more scholars to pursue. First, our review suggests very little empirical attention on analyzing how entrepreneurial intention translates into nascent or start-up activities. Although this relationship is examined in our review regarding start-up activities for nascency after an EE program (e.g., Souitaris et al., 2007), the lack of a positive significant relationship (albeit via entrepreneurial intentions) suggests more research is required on how intention follows through to action (or not). For example, why do some recipients of EE with high entrepreneurial intentions start up their own businesses after graduating, while others (despite high intentions) do not? What is the role of EE in this process? Second, very few studies in our review analyze the development of entrepreneurial Education researchers often refer to “noncognitive skills” to differentiate from more surface level learning such as facts and rote-learned skills (e.g., Krueger, 2015).
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identity, although we see hints that EE relates to personal development beyond knowledge and skill acquisition, for example, by a change in thinking style (Mueller & Anderson, 2014), internal selfreflection, and external engagement (Donnellon ´ et al., 2014; Lackeus, 2014). Given how little we know of how intent becomes behavior, this is exceptionally important for further research. Explore Contextual Reasons for Contradictory Findings: Background, Gender, and Culture As our results report, most papers suggest positive results between EE and a broad range of impact indicators, but with some contradictory studies (consistent with Martin et al., 2013). These authors advance methodological concerns as an explanation of such contradictory results; however, it would be remiss not to also assess person- and context-specific factors. Concerning student backgrounds, for those who have less exposure to entrepreneurship, the general effect tends to be positive, because they usually increase their entrepreneurial intention, attitudes, and self-efficacy by participating in the programs (e.g., Fayolle & Gailly, 2015; Fayolle, Gailly, & Lassas´ Clerc, 2006a; Sanchez, 2011). In contrast, for those students who already have entrepreneurial experience, family background, or high previous entrepreneurial intention, the effects are generally weaker and may even be negative (see, e.g., Fayolle et al., 2006b; Von Graevenitz, Harhoff, & Weber, 2010). Similarly, Bae et al. (2014) found that after controlling for preeducational entrepreneurial intentions, the relationship between EE and postprogram entrepreneurial intentions is not significant. However, given that Bae et al.’s (2014) meta-analysis did not focus specifically on higher education, we encourage more studies to focus on the role of student background in this context. Regarding students’ background, gender-specific differences are also an important source of contradictory findings. Few studies in our review focus on the differential impact of EE for male and female students/graduates, although those that did identify gender-specific effects. For example, Wilson, Kickul, and Marlino (2007) show that EE has a stronger impact on self-efficacy among females than males. Other studies also suggest the impact of EE on entrepreneurial intentions is gender-specific (e.g., Joensuu et al., 2013; Packham et al., 2010), although there are too few studies to indicate if this favors males or females. A controversial finding in Bae et al.’s (2014) article concludes that gender does not significantly moderate the EE–entrepreneurial intention
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relationship. However, Bae et al. (2014) did not specifically examine studies of EE in higher education (as we do), but rather looked at averages from a metaanalysis across educational levels. Furthermore, unlike Bae et al. (2014), we look at higher level impact in terms of entrepreneurial behavior. Although we did not find any reported gender-specific effects at this level, in our view, this does not mean that they do not exist, merely that studies have not specifically focused on these effects. Looking at further aspects of context (e.g., type of program: optional or compulsory; type of institution), there is evidence from our review that initial positive attitudes toward entrepreneurship, which are, however, not fully formed, change once they are confronted with the complexities and pitfalls of business start-up during EE. In our review, Hytti, Stenholm, Heinonen, and Seikkula-Leino (2010) analyze the motivations of students taking a compulsory EE program, finding that students with intrinsic motivation report lower learning and less satisfaction with the course (they expected more). Those taking the program with extrinsic motivation express a greater degree of satisfaction. Similarly, Petridou and Sarri (2011) find that attitudes and intentions are raised by an EE program in a generalist university, but lowered in a technology institute. The latter can be explained by the realization of the complexities involved in starting up a technology venture. Similarly, culture and national context are likely significant factors but rarely tested directly because almost all studies in our review focus on a singlecountry or culture (or at least do not investigate cultural differences). However, Bae et al.’s (2014) metaanalysis suggests some salient cultural dimensions, at least with respect to entrepreneurial intentions. For example, some national or cultural contexts may be higher on some cultural dimensions, on average, like uncertainty avoidance (level of comfortableness with uncertainty and ambiguity; Hofstede, 2003, also see ´ & Nabi’s, 2013 Special Issue in this Krueger, Liñan, area). This suggests culture-specific moderators are worthy of further consideration. In addition, our sample is dominated by studies in the United Kingdom, United States, and Asia, but only 5% are from the fast-growing emerging BRIC (Brazil, Russia, India, and China) economies. There are no studies from Russia or India, and Africa and Australia are also under-represented, suggesting such countries and continents are largely absent from studies. Moreover, culture is also likely to exhibit interaction effects with other impact factors like gender as implied in a handful of our articles regarding
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culture- and gender-specific findings. Packham et al. (2010), for example, suggest findings that EE negatively relates to entrepreneurial intentions for male German students. This double-moderator effect is consistent with limited research outside our review, for example, Shneor, Camg¨oz, and Karapinar (2013), who look at gender effects in two cultural settings, while analysis of Culture x Gender effects is absent from the studies reviewed here. Considering our discussion on how student background and context (the “audience” dimension of the teaching model; Fayolle & Gailly, 2008) seem to explain contradictory findings in previous studies, future research in this field is especially promising. Knowing the background and the profile of the students (e.g., prior entrepreneurial knowledge and skills, motivators, gender) and context (e.g., type of program, type of institution, program and country context) can also lead to better design and implementation of EE programs, and ultimately to more efficient learning processes, environments, and ´ ´ hence, impact (Bechard & Gregoire, 2005; Fayolle & Gailly, 2008, 2015). It also opens the door for future impact research that is more mindful of potential moderating factors and exploring a range of related questions. For example, to what extent is the impact of EE programs in higher education on a range of entrepreneurial outcomes gender-, culture-, and context-specific? Which impact indicators in our framework are dependent on moderator effects and which are more universally applicable? Our teaching model framework could also be expanded to incorporate culture-specific frameworks (e.g., Hofstede, 2003; Schwartz, 2004) allowing further consideration of the impact of higher education-based EE programs in different international and cultural contexts.
Pedagogical Methods Underpinning Impact Pedagogical Reasons for Contradictory Findings: Differences in Pedagogical Methods Our review suggests that all the pedagogical methods (supply, demand, competence, hybrids) have positive impact at Levels 1 and 2 of our teaching model framework (e.g., attitudes and intentions). However, our reviewed studies suggest that pedagogical methods based on competence are better suited for developing higher level impact. The evidence suggests that competence model pedagogy is associated with both subjective measures at Level 2 (e.g., entrepreneurial intention), and objective ones at Levels 3 (e.g., actual start-ups up to 5 years
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postprogram) and 4 (longer term impact on business up to 10 years postprogram). To put it more simply, such deeper, more experiential pedagogies seem to have the most potential to have impact at higher levels because students focus on developing behavioral competency in solving problems in real-life entrepreneurial situations. Our findings suggest that the use of different pedagogical methods is at least partially responsible for the inconsistent findings in impact studies. However, given that our findings are based on a partial sample of our population of articles, they are indicative rather than confirmatory.5 To the best of our knowledge, this is the first systematic review that uses a teaching model framework to assess the impact of EE. In our view, this provides novel and meaningful insights. EE makes strong claims to have significant impact and a strong bias toward experiential pedagogies. This review confirms that we need to focus strongly in this direction. For example, it is essential to expand research on competence-model-related pedagogical methods. Do they really have stronger impact than other models, especially at higher levels of our teaching model framework? How do they work regarding underlying processes? Focus on Comparison Studies to Compare Pedagogical Methods Our review reveals very few comparison studies that directly compare the impact of different pedagogical methods. Considering the growing number of EE programs and the growing demand to assess them, should we not ask for evidence of what pedagogical methods work, desired impact, and actual impact? We thus encourage researchers to compare types of impact across different teaching pedagogical methods. This is the only way for us to understand EE impact in an incremental and meaningful way. Our review includes comparison studies that link EE pedagogical methods in higher education to a broad range of impact measures using a teaching model framework. However, comparison studies in our review only tend to compare pedagogical methods in a limited way (e.g., supply versus competence; Lange et al., 2014; Walter & Dohse, 2012; Wang & Verzat, 2011). In our review, we identify five different pedagogical models 5
Reduced from 159 to 72 due to insufficient pedagogical information from 55% of our articles. Further, we suspect that it could be extremely valuable to assess the quality of pedagogy, not just its intended characteristics.
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including hybrid versions (supply, supply–demand, demand, demand–competence, competence). We urge scholars of future comparison studies to directly compare the impact of a broader range of pedagogical methods using a teaching model framework. We believe that such a comparative approach offers great opportunities to explore a number of theoretically, practically, and empirically meaningful research questions that may help to explain the contradictory findings on the impact of higher education-based EE programs and increase generalizability. For example, what pedagogical models work for which types of impact and in which contexts? We encourage future researchers to rigorously isolate the impact of a pedagogical intervention, controlling for the context- and person-specific factors outlined earlier. Limitations and General Recommendations Three limitations of our review are noteworthy. First, we only cover EE in higher education, although EE also flourishes in high school programs, and adult (nondegree and non-academic) education. Focusing on other educational levels and means of delivery outside higher education was outside the scope of our research, but our findings do open the door for assessing EE impact at other levels. Second, data on whether an individual is exposed to multiple training before, during, and after higher education is limited. However, some articles in our review do use more sophisticated research designs, for example, adopting a pretest–posttest control group design (e.g., Souitaris et al., 2007), or controlling for prior entrepreneurial exposure (e.g., Fayolle & Gailly, 2015). Although focusing on methodological designs is outside the primary scope of our research and is covered elsewhere (e.g., Rideout & Gray, 2013), we still include a range of articles with different methodologies in our research, and our findings confirm those of existing reviews with an emphasis on methodological rigor (e.g., Martin et al., 2013; Rideout & Gray, 2013). Rather than reiterate the methodological weaknesses that other reviews found, we sought to identify perhaps less obvious, yet greatly promising new or underemphasized directions for future research. Third, our review focuses on the recipients of university-based EE programs and their entrepreneurial attitudes, knowledge, skills, and behaviors. However, such programs obviously also influence a wider set of stakeholders, such as the instructors themselves and, in the case of field projects, the
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individuals and organizations involved. For example, “real-life cases” where students work on various consultancy tasks (such as market validation studies). The impact of EE can be on entrepreneurial behavior of staff and lecturers, when teaching entrepreneurship influences academics to become engaged in it themselves (whether in commercializing research or in nonresearch-based entrepreneurial activity at the side of academic work). EE programs where students engage in market validation studies and so forth also expose students to the entrepreneurial community. This can be built into higher levels of our teaching model framework to examine stakeholder impact. For example, we can assess the value of EE to university faculty, donors/investors, and communities at Levels 3, 4, and 5 of our framework (cf. Duval-Couetil, 2013). CONCLUSIONS While confirming the weaknesses in EE impact studies (e.g., dominance on lower level attitudinal and intentionality impact measures, and a lack of key detail concerning pedagogy), we also identify three main ways of moving forward. First, as indicated in Table 3, we add value by providing an up-to-date and empirically rooted call for future research in higher education. Second, by applying a teaching model framework, we offer several intriguing and underemphasized suggestions for improving EE research. Last and relatedly, we provide some critical insights into the reasons for the contradictory findings in EE research (e.g., rarity of cross-cultural, gender-specific and pedagogical-comparison research) that can be further teased out through single studies/interventions, so we can understand how EE really works in theory and practice. REFERENCES Abaho, E., Olomi, D. R., & Urassa, G. C. 2015. Students’ entrepreneurial self-efficacy: Does the teaching method matter? Education 1 Training, 57(8/9): 908–923. Ahmed, I., Nawaz, M. M., Ahmad, Z., Shaukat, M. Z., Usman, A., & Rehman, W. 2010. Determinants of students’ entrepreneurial career intentions: Evidence from business graduates. European Journal of Social Sciences, 15(2): 14–22. Alarape, A. A. 2007. Entrepreneurship programs, operational efficiency and growth of small businesses. Journal of Enterprising Communities: People and Places in the Global Economy, 1(3): 222–239. Almobaireek, W. N., & Manolova, T. S. 2012. Who wants to be an entrepreneur? Entrepreneurial intentions among Saudi university students. African Journal of Business Management, 6(11): 4029–4040.
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Ghulam Nabi (PhD, University of Central Lancashire, UK) is a senior lecturer in entrepreneurship and organizational behavior, Manchester Metropolitan University Business School, UK. Current research interests include student-to-entrepreneur transition, entrepreneurial intentions, entrepreneurship education, and the role of mentoring in entrepreneurial development. Ghulam has published over 18 articles in leading international journals. ´ (PhD, University of Seville, Spain) is professor of entrepreneurship and inFrancisco Liñan novation at Anglia Ruskin University (UK), and University of Seville. Francisco’s main research interests include entrepreneurship as a process, entrepreneurial intentions, and culture’s role in entrepreneurship. He has published over 25 articles in international journals and edited books. Alain Fayolle (PhD, University of Lyon, France) is a professor and Research Centre director, EM Lyon Business School, France. Alain is also the Academy of Management ENT Division Chair. His research interests are entrepreneurship education, corporate entrepreneurship, entrepreneurial intention, and behavior. Norris Krueger (PhD, The Ohio State University, US) is a senior research fellow of the Center for Management and Entrepreneurship, University of Phoenix. Norris is passionate about developing entrepreneurial thinking, the most cited author on entrepreneurial intentions, and is now researching deeper cognitive phenomena (e.g., “neuroentrepreneurship”). He is equally passionate about growing entrepreneurial ecosystems (Entrepreneurship Northwest; organized Startup Weekends, & 1 Million Cups). Andreas Walmsley (PhD, Leeds Beckett University, UK) is an associate professor at Plymouth University, UK. Andreas’s current research revolves around entrepreneurship education, entrepreneurship in tourism and hospitality, and employment in the service industries.
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Tugas Review Jurnal Internasional – Enterpreneurship | Dilson - 17193034
LITERATUR REVIEW ENTERPRENEURSHIP INTERNATIONAL JOURNAL 23
Type Title
Authors & Department Journal Ringkasan
: Journal : Social Cognitive Theory, Entrepreneurial Self-Efficacy and ntrepreneurial Intentions: Tools to Maximize the Effectiveness of Formal Entrepreneurship Education and Address the Decline in Entrepreneurial Activity1 : Carmen England Bayrón, Ed.D. Universidad de Puerto Rico [email protected] : Revista Griot (ISSN 1949-4742) Volumen 6, Número. 1, Diciembre 2013 :
Terlepas dari peran penting yang dimainkan oleh kewirausahaan dalam ekonomi suatu negara, data dari program BLS Business Dynamics Dinamika (BED) mengungkapkan bahwa jumlah perusahaan bisnis baru pada Maret 2010 lebih rendah daripada tahun-tahun lainnya (Biro Statistik Tenaga Kerja AS, 2012). Data BED juga menunjukkan bahwa jumlah pekerjaan yang dibuat oleh perusahaan dalam setahun terakhir telah menurun. Temuan-temuan ini menjadi perhatian dan membutuhkan tindakan segera untuk membantu merangsang ekonomi AS. Urgensi untuk mendidik kaum muda dan melatih mereka dalam berwirausaha adalah nyata, mendorong mereka untuk mengejar karir kewirausahaan untuk meningkatkan efisiensi ekonomi, membawa inovasi ke pasar, menciptakan lapangan kerja baru, dan mempertahankan tingkat pekerjaan (Carswell, 2001). Tinjauan pustaka ini berasal dari kebutuhan untuk mengatasi penurunan aktivitas kewirausahaan yang memaksimalkan efektivitas pendidikan kewirausahaan formal. Literatur yang ada mengungkapkan perlunya program pendidikan untuk menangani implikasi penelitian di bidang kewirausahaan. Penasihat karir dan penasihat karir mengajar, melatih dan mendidik kompetensi sangat membantu untuk pendidikan kewirausahaan. Tujuan dari makalah ini adalah untuk memeriksa literatur yang ada pada Teori Kognitif Sosial, kewaspadaan kewirausahaan, dan kompetensi dan niat kewirausahaan, untuk memahami keadaan lapangan saat ini, merancang kerangka teoritis baru untuk membantu menentukan strategi pengajaran terbaik dan mengidentifikasi karir kompetensi konselor dan kontribusi yang mungkin untuk bidang pendidikan kewirausahaan. Efikasi diri yang berwirausaha diusulkan sebagai suatu konstruk yang berguna untuk meningkatkan niat kewirausahaan dan kompetensi siswa. Teori kognitif sosial, self-efficacy, dan self-efficacy kewirausahaan dimasukkan ke dalam kerangka teoritis terapan untuk meningkatkan efektivitas pendidikan kewirausahaan formal. Secara khusus, model ini menghubungkan empat sumber self-efficacy dengan self-efficacy dan wirausaha; yang mengarah pada hasil program pendidikan wirausaha yang efektif. Penulis menyarankan penggunaan konstruk self-efficacy kewirausahaan dalam kurikulum (lokakarya) dan kegiatan ekstrakurikuler untuk memberikan pengaruh yang besar pada siswa; agar siswa dapat bertindak berdasarkan pikiran, perasaan, dan perilaku wirausaha mereka. Jika siswa memvisualisasikan diri dengan kontrol pribadi yang tinggi sebagai wirausahawan (tugas dan peran) mungkin mereka akan memilih jalur karier wirausaha. Pengajar kewirausahaan (termasuk konselor karir) dapat mengambil manfaat dari penerapan konstruk self-efficacy ke proses pembelajaran. Tingkat self-efficacy yang tinggi dapat membantu mereka menghasilkan lebih banyak wirausahawan (Bird 1988; Boyd & Vozikis 1994), sebuah tujuan penting dari pendidikan kewirausahaan dan ekonomi nasional. ESE adalah konstruk yang menjanjikan, dengan potensi untuk memprediksi kinerja kewirausahaan dan untuk meningkatkan laju kegiatan kewirausahaan melalui pelatihan (Mueller & Goic 2003; Zhao, Seibert dkk. 2005; Florin, Karri et al. 2007)
Tugas Review Jurnal Internasional – Enterpreneurship | Dilson - 17193034
Strategi lain yang dapat membantu meningkatkan self-efficacy, niat dan pembelajaran kewirausahaan pada siswa adalah paparan kepada orang lain dengan pengalaman kewirausahaan sebelumnya; ini dapat memberikan wirausahawan yang sedang berkembang dengan pengetahuan yang bermanfaat (Boyd & Vozikis, 1994, Chen, Green & Crick, 1998, Krueger & Brazeal, 1994) dan mengurangi ketidakpastian mereka (Bandura, 1978). Proses pembelajaran yang harus dikembangkan oleh entrepreneur untuk kepercayaan diri siswa dalam karir tersebut didasarkan pada pengetahuan dan keterampilan yang dikembangkan dalam program (De Clercq & Arenius, 2006). Pendidik (konselor karir) perlu memaksimalkan penggunaan self-efficacy kewirausahaan dalam kurikulum karena merupakan anteseden yang mempengaruhi pilihan kewirausahaan (Boyd & Vozikis 1994; Krueger & Brazeal 1994); tingkat self-efficacy yang tinggi secara konsekuen akan mengarah pada munculnya perilaku kewirausahaan dan pada akhirnya menuju tindakan kewirausahaan (McGee, Peterson dkk., 2009, Chen, Greene & Crick, 1998). Program kewirausahaan dan konselor karir harus mencapai kombinasi faktor yang tepat dari atribut pribadi, sifat, latar belakang, pengalaman, dan disposisi yang dibutuhkan siswa untuk mengejar ide menjadi wirausaha (Krueger Jr dan Brazeal 1994; Krueger Jr, Reilly dkk. 2000; Shane , Locke dkk. 2003; Baron 2004; Arenius dan Minniti, 2005). Hasil penelitian sampai saat ini menunjukkan bahwa SCT, self-efficacy, self-efficacy kewirausahaan, niat kewirausahaan dan pengukuran kompetensi kewirausahaan dapat membantu meningkatkan pengajaran kewirausahaan, dan mengajar akan meningkatkan pembelajaran (Angelo & Cross, 1993). Budaya penilaian dalam program dan kursus kewirausahaan dapat membantu meningkatkan pembelajaran, memantau hasil, tumbuh melalui refleksi diri dan umpan balik, bereksperimen dengan modifikasi dan menyesuaikan praktik terbaik, memetakan tren dan paradigma (Hytti & Kuopusjarve, 2004). SCT, self-efficacy, dan konstruk self-efficacy kewirausahaan mungkin dapat membantu menunjukkan hubungan yang jelas antara pendidikan kewirausahaan dan siswa menjadi wirausaha, dan meningkatkan proporsi orang yang memulai bisnis setelah lulus. Penulis menyarakan penelitian selanjutnya dilakukan untuk menetapkan apakah self-efficacy kewirausahaan berhubungan positif dengan niat siswa untuk memulai bisnis mereka sendiri (Chen, Greene, dan Crick, 1998) dan tentang kepribadian dan faktor lingkungan dimasukkan dalam selfefficacy kewirausahaan ; prediktor kuat dari niat kewirausahaan dan, akhirnya, tindakan (Bird 1988; Boyd & Vozikis, 1994). Serta mempelajari interaksi antara belajar dan kewirausahaan (kompetensi konselor karir); efektivitas pendidikan kewirausahaan; dan hubungan antara pendidikan kewirausahaan dan siswa menjadi pengusaha (Hostager & Decker, 1999 dan Luthje & Franke, 2003).
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Social Cognitive Theory
Social Cognitive Theory, Entrepreneurial Self-Efficacy and Entrepreneurial Intentions: Tools to Maximize the Effectiveness of Formal Entrepreneurship Education and Address the Decline in Entrepreneurial Activity1 Carmen England Bayrón, Ed.D. Universidad de Puerto Rico [email protected] Abstract The purpose of this paper is to examine existing literature on Social Cognitive Theory, entrepreneurial self-efficacy, and entrepreneurial competencies and intentions, to understand the current state of the field, design a new theoretical framework to help determine the best teaching strategies and identify career counselor competencies and possible contributions to the entrepreneurial education field. Entrepreneurial self-efficacy is proposed as a useful construct to increase the entrepreneurial intentions and competencies of students. Social cognitive theory, self-efficacy, and entrepreneurial self-efficacy are incorporated into an applied theoretical framework to improve the effectiveness of formal entrepreneurship education. Specifically, the model links the four sources of self-efficacy with entrepreneurial self-efficacy and entrepreneurial intentions; which lead to effective entrepreneurial education program outcomes. Keywords: self-efficacy, entrepreneurship, education, career counselors Resumen El objetivo de este escrito es examinar la literatura existente sobre la Teoría Social Cognoscitiva, la autoeficacia emprendedora, y las competencias e intenciones emprendedoras, entender el estado corriente del campo, diseñar un nuevo marco teórico para ayudar determinar las mejores estrategias de enseñanza e identificar las competencias del consejero de carrera y posibles contribuciones al campo de la educación emprendedora. La autoeficacia emprendedora se propone como un constructo para aumentar las intenciones emprendedoras y las competencias de los estudiantes. La teoría social cognoscitiva, la autoeficacia, y la autoeficacia emprendedora son incorporados en un marco teórico para aplicado para mejorar la eficacia de la educación emprendedora formal. Específicamente, el enlace de las cuatro fuentes de la autoeficacia con la autoeficacia emprendedora e intenciones emprendedoras; las cuales conducen a resultados efectivos de un programa de educación emprendedora. Palabras clave: autoeficacia, emprendedor, educación, consejeros de carrera
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Sometido: 15 de agosto de 2013 Sometido a Revisión: 22 de agosto de 2013 Aceptado: 29 de octubre de 2013
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lanchflower (2000) indicates that entrepreneurship is an important factor for the development of an economy. Hindle & Rushworth (2002) established that entrepreneurship is a driver of economic growth and national prosperity and the U.S. Bureau of Labor Statistics (BLS) states on its webpage that “entrepreneurship plays a vital role in the growth of the U.S. economy” (U.S. Bureau of Labor Statistics, 2012). BLS is the primary source for information on U.S. labor markets as well as the federal government’s datacollection agency on new businesses and job creation. Despite the important role that entrepreneurship plays in a nation’s economy, data from the BLS’s Business Employment Dynamics (BED) program reveals that the number of new business establishments in March 2010 was lower than any other year (U.S. Bureau of Labor Statistics, 2012). BED data also shows that the number of jobs created by establishments in the last year has decreased. These findings concern and require immediate action in order to help stimulate the U.S. economy. The urgency to educate young people and train them in entrepreneurship is evident, encouraging them to pursue an entrepreneurial career to increased economy efficiency, bring innovation to market, create new job opportunities, and sustain employment levels (Carswell, 2001). This literature review stems from the need to address the decline of entrepreneurship activity maximizing the effectiveness of formal entrepreneurship education. The existing literature reveals the need for education programs to deal with the implications of research in the entrepreneurship field. Career counselors and career advisors teaching, training and educating competencies are helpful for the entrepreneurial education. Young, (1997) observed that in entrepreneurship three education researches areas concern, social-cognitive, psycho-cognitive, and spiritualist or ethical. He suggests that the implications of these dimensions for entrepreneurship education are not drawn out yet, in spite of previous calls to integrate them into the research agenda (e.g., Young, 1997). I suggest to focus on developing a research agenda on the social-cognitive preoccupations of Social Cognitive Theory (1986) to help entrepreneurship educators maximize the effectiveness of formal entrepreneurial education that helps to address the decline in entrepreneurial activity. Linking learning, teaching entrepreneurship effectively and Entrepreneurship The important role of higher education in stimulating job creators is discussed in Article 7 of “The World Declaration on Higher Education for the Twenty-First Century: Vision and Action,” adopted in 1998 by The World Conference on Higher Education. This article states that “developing entrepreneurial skills and initiative should become major concerns of higher education, in order to facilitate employability of graduates who will increasingly be called upon to be not only job seekers but also and above all to become job creators. Thus, universities should offer their students the opportunity to fully develop their potential abilities with a sense of social responsibility, educating them to become full participants in a democratic society and promoters of changes that will foster equity, justice, and national economic wellbeing.” The professional counselors are professionals of higher education institutions that can contribute to the students development as job seekers and job creators. According to the National Association of Colleges and Employers career counselors can contribute to entrepreneurship education with the following competencies:
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Needs assessment
Program/workshop design and delivery
Researching, evaluating, and integrating information
Effective teaching strategies
Career mentoring
Work with individuals an d groups
Work with diverse populations
Use of technology for delivery of content
Career counselors are professionals that can contribute to development of the new generation of entrepreneurs in today’s economy and also create new knowledge of the interaction between learning and entrepreneurship and effective entrepreneurship teaching strategies. Solomon, et al., (1994, cited in Kuratko, 2003) inform that by the early 1980s over 300 universities were reporting courses in entrepreneurship and small business, and by the 1990s that number had grown to 1,050 schools. Cone (in 2008) mentioned that more than 2,000 institutions offer courses in entrepreneurship. The Kauffman Foundation (2010) indicates that formal programs (majors, minors and certificates) in entrepreneurship have more than quadrupled, from 104 in 1975, to more than 500 in 2006. But at present there is very limited knowledge and understanding of the interaction between learning and entrepreneurship, and the process remains one of the most neglected areas of entrepreneurial research and understanding. There are also gaps in our knowledge about the effectiveness of entrepreneurship education (Soloman, Duffy & Torabishy, 2002, Clark, Davis, & Harnish, 1984; Wallenstein in 1993). Some research shows that four years after having taken entrepreneurship courses, interest in creating new ventures tends to dissipate (Whitlock and Master, 1996) and others observed that no clear relationship has been demonstrated between entrepreneurship education and students becoming entrepreneurs (Hostager & Decker, 1999 and Luthje & Franke, 2003). In order to address this situation, first I want to point out the words of Angelo & Cross (1993) because of the timeless of those words with the current state of affairs. These researchers said that the most promising ways to improve learning is to improve teaching. Kuratko pointed out that “In the midst of this huge expansion of courses, the challenge of teaching entrepreneurship more effectively remains.” Some authors reported that it is not clear what to teach in entrepreneurship, and there is a lack of detailed consideration of how entrepreneurs learn (Garavan & Cinnedide, 1994 and Solomon, 2007); others reported that there is no substantive agreement about what entrepreneurship means in educational settings, and that the appropriate content of programs is under permanent discussion (Gibb, 2002). More recently some authors identified that the components of a balanced entrepreneurship program should contain the following: (a) lectures on business concepts; (b) business-planning practices, including competitions and coaching; (c) interaction with practitioners and networking opportunities; and (d) university support such as market-research resources, meeting spaces, seed funding, patenting advice, etc. (Al-Laham, Revista Griot (ISSN 1949-4742)
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Social Cognitive Theory Souitaris & Zerbinati, 2007). But to improve entrepreneurship learning is not sufficient. With these components having been identified, it is necessary to prove the existence of a link between learning and entrepreneurship, and in teaching entrepreneurship more effectively. The Role of Social Cognitive Theory The Social Learning theory of Albert Bandura (1986) establishes that the environment causes behavior, but behavior also causes the environment. Bandura calls this concept reciprocal determinism, where the world and the behavior of persons are mutually caused. Bandura believes that human conduct must be explained in terms of the reciprocal interaction between cognitive, behavioral, and environmental determinants. The social cognitive theory of Bandura (SCT) centers on the concepts of reinforcement and observation, giving more importance to the mental internal processes as well as to the interaction of the subject with others. The SCT postulates that observation and imitation is given across models that can be parents, educators, and friends, and can even be heroes taken from television. The only requirement for learning can be that one person observes another individual, or models behavior to carry out a certain conduct. The observation and imitation intervene upon the cognitive factors and help the subject decide whether or not the observed behavior is to be imitated. The cognitive factors are the capacity of reflection and symbolization as well as the prevention of consequences based on processes of comparison, generalization, and auto-evaluation. One of the aims of the SCT is the development of the self-evaluation and the self-reinforcement constructs. According to Bandura, individuals possess an auto-system that allows them to measure the control on their own thoughts, feelings, motivations and actions. This system exercises self-regulation to enable individuals with aptitude to influence their own cognitive processes and actions and in this way to alter their environment. If we applied the concepts I have just discussed to entrepreneurship education programs, we can infer that the student’s observation and interaction with previous entrepreneurs can reinforce entrepreneurial behavior. The observation and imitation of former entrepreneurs will intervene upon the cognitive factors of the students and can help them – students or alumni – to decide if the observed behaviors should be imitated or not. SCT can be helpful to the entrepreneurial behavior field, but educators (career counselors) need to apply this theory to the curriculum (workshops, extracurricular activities) and to students’ interactions. Social Cognitive Theory and Self-Efficacy Self-efficacy is a construct defined by Albert Bandura (1982) as “self-judgment of one’s ability to perform a task in a specific domain.” The belief in self-efficacy provides a great influence on human beings, since they act on their thoughts, feelings and behaviors (Bandura, 1995). Garcia et al., 1991 defines self-efficacy as “self-appraisal of one’s ability to accomplish a task and one’s confidence in possessing the skills needed to perform that task.” The SCT explains that an individual’s sense of self-efficacy can be influenced through four processes: enactive mastery, role modeling and vicarious experience, social persuasion, and judgments of one’s own physiological states, such as arousal and anxiety (Bandura, 1986). The self-efficacy construct influences an individual’s choice of activities, goal levels, persistence, and performance Revista Griot (ISSN 1949-4742)
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Social Cognitive Theory in a range of contexts. Self-efficacy is a motivational factor that educational research from the social cognitive approach establishes. Bandura mentioned that self-efficacy affects some of the factors that predict motivation. Krueger et al (2000) pointed out that experience influences the entrepreneur’s intention, and that there is also a direct relationship between entrepreneur’s experience on perceived feasibility and perceived desirability; feasibility and desirability existing in the environment that influences the entrepreneur’s experience, so perceived feasibility and perceived desirability partially serve as key elements in forming entrepreneurial experiences and entrepreneurial intentions. Krueger et al (2000) observed that entrepreneurs’ experiences directly influence the entrepreneur’s intention to start a new venture. Self-efficacy has an important effect on the choice of behavior setting. Individuals tend to choose situations in which they anticipate high personal control but avoid situations in which they anticipate low control (Bandura 1977, 1982; Bandura & Schunk, 1981; Wood & Bandura, 1989, 2012). Consequently, to the extent that people plan and choose their career paths, they assess their personal capabilities against the requirements of different occupations (Chen, Greene & Crick, 1998). This assessment of their personal capabilities therefore directs people to prepare for and enter occupations in which they feel successful, but at the same time avoid occupations in which they feel a lack of competence (Betz and Hackett 1981, 1986, Miura 1987; Scherer et al. 1989). Empirical evidence establishes that entrepreneurial self-efficacy was positively related to students’ intentions to start their own business (Chen, Greene & Crick, 1998). Entrepreneurial Self-Efficacy and Intentions In the past, some authors have provided evidence of the increasing emphasis on the role of self-efficacy in the study of entrepreneurship, including areas such as entrepreneurial career preferences, intentionality, and performance (Boyd & Vozikis 1994; Chandler & Jansen 1992; Gartner 1989; Krueger & Brazeal 1994; Scherer et at., 1989). Entrepreneurial self-efficacy (ESE) is defined as an individual’s confidence in his or her ability to successfully perform entrepreneurial roles and tasks (Chen, Greene et al. 1998; De Noble, Jung et.al. 1999). ESE is also defined as a construct measuring a person’s belief in his ability to successfully launch an entrepreneurial venture (McGee, Peterson et al., 2009). Entrepreneurial self-efficacy is a variable useful for increasing students’ convictions that they can execute the necessary entrepreneurial behavior to produce the desired result; a new venture. The measure of entrepreneurial self-efficacy has been widely adopted for identifying entrepreneurial intentions and consequently entrepreneurial conduct, and for investigating how education and training can be used to improve entrepreneurial action (Føleide, 2011). Perceived desirability constitutes the primary component of entrepreneurial intention (Liñan et al. 2011, p. 205). Azjen (1991) observed that three attitudinal antecedents are necessary to trigger the action of starting a business: (a) the desire to start the business, (b) the belief that the business contributes to wellbeing of the society, and that (c) success is possible. I suggested the use of the entrepreneurial self-efficacy construct in the curriculum (workshops) and extracurricular activities to provide a great influence on the students; they will act on their thoughts, feelings and entrepreneur behaviors. If the students visualize themselves with high personal control as entrepreneurs (task and roles) maybe they will choose an entrepreneurial career path. Entrepreneurship educators (include career counselors) can Revista Griot (ISSN 1949-4742)
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Social Cognitive Theory benefit from the implementation of self-efficacy construct to the learning process. A high level of entrepreneurial self-efficacy can help them produce more entrepreneurs (Bird 1988; Boyd & Vozikis 1994), an important goal of entrepreneurship education and national economies. ESE is a promising construct, with the potential to predict entrepreneurial performance and for improving the rate of entrepreneurial activities through training (Mueller & Goic 2003; Zhao, Seibert et al. 2005; Florin, Karri et al. 2007). Personality and environmental factors are incorporated into entrepreneurial selfefficacy, and are thought to be strong predictors of entrepreneurial intentions and ultimately action (Bird 1988; Boyd and Vozikis 1994). Forbes 2005; Kolvereid and Isaksen 2006 observed that nevertheless, the construct remains empirically underdeveloped and many scholars have called for refinements of the construct. The development of the ESE construct can help to improve the entrepreneurial learning process and increase the rate of entrepreneurial activities. The assessment of personality and explanation of the educational environmental factors of entrepreneurship programs can improve the students’ entrepreneurial self-efficacy, and predict entrepreneurial intentions. As a strategy, business schools, entrepreneurship programs and career counselors can assess the entrepreneurial self-efficacy of their students and develop special activities for students with the highest entrepreneurial self-efficacy levels, and also activities for students with low entrepreneurial self-efficacy. This strategy can help to attend to the special learning and entrepreneurial needs of all students. Another strategy that can help increase entrepreneurial self-efficacy, intentions and learning in students is the exposure to others with previous entrepreneurial experience; this can provide emerging entrepreneurs with useful knowledge (Boyd & Vozikis, 1994, Chen, Green & Crick, 1998, Krueger & Brazeal, 1994) and reduce their uncertainties (Bandura, 1978). The learning process that entrepreneurs have to develop for students’ confidence in that career is based on the knowledge and skills developed in the program (De Clercq & Arenius, 2006). Educators (career counselors) need to maximize the use of entrepreneurial self-efficacy in the curriculum because it is an antecedent that influences the entrepreneurial choice (Boyd & Vozikis 1994; Krueger & Brazeal 1994); high levels of self-efficacy would consequently lead to emergingnt entrepreneurial behavior and ultimately to entrepreneurial action (McGee, Peterson et al., 2009, Chen, Greene & Crick, 1998). Entrepreneurship programs and career counselors need to reach the right factor combinations of personal attributes, traits, background, experiences and disposition that students need to pursue the idea of becoming entrepreneurs (Krueger Jr and Brazeal 1994; Krueger Jr, Reilly et al. 2000; Shane, Locke et al. 2003; Baron 2004; Arenius and Minniti, 2005). More research on personal attributes, such as traits, background, experiences and disposition, and factors that influence an individual to pursue the idea of becoming an entrepreneur and entrepreneurial self-efficacy (Boyd & Vozikis 1994; Krueger & Brazeal 1994) can help improve the learning process and the entrepreneur career choice. Longitudinal studies in entrepreneurship programs can help provide evidence of the impact of entrepreneurial programs in entrepreneurial self-efficacy and intentions, and according to the results, allow for the necessary adjustments to be made to the program. Entrepreneurial Competencies and Entrepreneurial Self-Efficacy
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Social Cognitive Theory Entrepreneurial competencies that are developed in educational programs have been neglected for a long time, yet they are essential variables in entrepreneurial development (Inyang & Enough, 2009). The literature points out that areas in which entrepreneurs need to acquire greater competencies are: managing time effectively, communication, human resources management, business ethics, social responsibility, developing effective leadership qualities, decision making skills, marketing and financial management. Entrepreneurship programs and career counselors need to evaluate and assess their instructional approach and curriculum to determine if they include all entrepreneurial competencies. They also need to evaluate if the instructional approach and curriculum have a positive impact on the development of entrepreneurial competencies (outcomes) and the entrepreneurial self-efficacy of their students (Izquierdo & Buyens, 2008). The entrepreneurship program can use the Theory of Planned Behavior, generally used to for the assessment of their programs as a framework (Ajzen, 1991); and then make the necessary adjustments. Bandura (1986) claims that a high level of self-efficacy may influence students’ choice of activities, goal levels, persistence and performance in a range of contexts. This increase of entrepreneurial self-efficacy can also positively influence the students’ choice of entrepreneurial activities, entrepreneurial goal levels, entrepreneurial persistence and performance in an entrepreneurship context. Theoretical and empirical literature expose why some exploit opportunities and some do not (Begley & Boyd, 1987; Brockhaus, 1980; Cooper & Dunkleberg, 1987, cited in De Carolis, & Saparito, 2006). Sexton & Bowman, 1984). The majority of this literature proposes that psychological variables, personality traits and demographic factors may distinguish entrepreneurial activity. Yet, the results of these findings are equivocal (Brockhaus & Robert Horowitz, 1986; Low & MacMillan, 1988; Shaver & Scott, 1991). Entrepreneurship education can benefit from teaching techniques that incorporate entrepreneurial self-efficacy, entrepreneurial intentions and competencies. I consider that techniques that incorporate SCT and the principal sources of self-efficacy are important, and that they will help students develop positive judgments about their self-capacities, obtain successful and vicarious experiences, receive verbal persuasion or social persuasion and manage their somatic and emotional state. I believe this will lead to an increase in their entrepreneurial self-efficacy, be positively related with entrepreneurial intentions and those entrepreneurial intentions, in turn, can increase the entrepreneurial activities needed in the economy, and thus propose the following framework for use in experimental design and assessment of these outcomes for entrepreneurship programs:
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Figure 1: A Theoretical Framework for assessing Entrepreneurship Education Effectiveness
The research to date suggests that SCT, self-efficacy, entrepreneurial self-efficacy, entrepreneurial intentions and entrepreneurial competencies measurement can help improve entrepreneurship teaching, and teaching will improve learning (Angelo & Cross, 1993). A culture of assessment in entrepreneurship programs and courses can help to improve learning, monitoring outcomes, growing through self-reflection and feedback, experimenting by modification and adjusting best practices, mapping the trends and paradigms (Hytti & Kuopusjarve, 2004). SCT, self-efficacy, and the entrepreneurial self-efficacy construct might be able to help demonstrate a clear relationship between entrepreneurship education and students becoming entrepreneurs, and increase the proportion of people starting a business after graduation. The research suggests that after the completion of an entrepreneurship education program, students may have higher entrepreneurial self-efficacy (Izquierdo & Buyens, 2008). Career counselors can studied the role of generalized self-efficacy, entrepreneurial selfefficacy in entrepreneurial education programs in order to enhance the level of student entrepreneurial intentions and competencies could be designed as follows in Table 1: Students Entrepreneurship Students Regular Students Revista Griot (ISSN 1949-4742)
General Self-Efficacy Pre/Post
Entrepreneurial Self-Efficacy Pre/Post
Entrepreneurial Intentions Pre/Post
Entrepreneurial Competencies Pre/Post
Pre/Post
Pre/Post
Pre/Post
Pre/Post
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Social Cognitive Theory Table 1: Proposed Research Design This design would test the following theoretical propositions developed herein, such as: P1: Entrepreneurial self-efficacy of students who complete an entrepreneurship program will be higher than students who do not complete such a program. P2: Entrepreneurial intentions of students who complete an entrepreneurship program will be higher than students who do not complete such a program. P3: Entrepreneurial competencies of students who complete an entrepreneurship program will be higher than students who do not complete such a program. Implications and Conclusion Social Cognitive Theory (Bandura, 1986) and entrepreneurial self-efficacy can be very useful as applied tools for developing entrepreneurship learning, competencies and intentions. Regarding future research, I believe it is necessary to establish whether entrepreneurial self-efficacy is positively related to students’ intentions to start their own business (Chen, Greene, and Crick,1998) and about personality and environmental factors incorporated in entrepreneurial self-efficacy; a strong predictor of entrepreneurial intentions and, ultimately, of action (Bird 1988; Boyd & Vozikis, 1994). Also, it is necessary to study the interaction between learning and entrepreneurship (career counselor competencies); the effectiveness of entrepreneurship education; and the relationship between entrepreneurship education and students becoming entrepreneurs (Hostager & Decker, 1999 and Luthje & Franke, 2003).
References Arenius, P. & Minniti, M. (2005). "Perceptual Variables and Nascent Entrepreneurship," Small Business Economics, Springer, vol. 24(3), pages 233-247, 02. Retrived from http://business2.fiu.edu/1660397/www/Participation%20in%20Entrepreneurship/Arenius_ Minniti_2005.pdf on July 4, 2012. Bandura, A. (1978). Reflections on self-efficacy. Advances in Behavioral Research and Therapy, 1(4), 237-269. doi: 10.1016/0146-6402(78)90012-7 Bandura, A. (1986a). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1986b). The explanatory and predictive scope of self-efficacy theory. Journal of Clinical and Social Psychology, 4, 359-373. doi: 10.1521/jscp.1986.4.3.359 Bandura, A. (Ed.) (1995), Self-efficacy in changing societies. New York: Cambridge University Press. Bandura, A., & Locke, E. (2003). Negative self-efficacy and goal effects revisited. Journal of Applied Psychology, 88, 87-99. doi: 10.1037/0021-9010.88.1.87 Bandura, A. (2012). Psychologists and Their Theories for Students. Ed. Kristine Krapp. Vol. 1. Detroit: Gale, 2005. 39-66. Gale Virtual Reference Library. Web
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Tugas Review Jurnal Internasional – Enterpreneurship | Dilson - 17193034
LITERATUR REVIEW ENTERPRENEURSHIP INTERNATIONAL JOURNAL 24
Type Title Authors & Department
Journal Ringkasan
: Journal : Drivers of entrepreneurial intentions among business students in Macedonia : Ana Tomovska Misoskaa, Makedonka Dimitrovab and Jadranka Mrsika aSchool of Business Economics and Management, University American College Skopje, Skopje, Republic of Macedonia; bUAKS Entrepreneurship and Leadership Development Institute, Skopje, Republic of Macedonia : Economic Research-Ekonomska Istraživanja, 2016 VO L. 29, NO . 1, 1062– 1074 http://dx.doi.org/10.1080/1331677X.2016.1211956 :
Sebelum Republik Makedonia memperoleh kemerdekaannya pada tahun 1991, lingkungan bisnis menekan niat wirausaha sebagai bagian dari warisan komunis, tetapi hari ini mereka berjuang untuk mengingatkan pentingnya bisnis kecil bagi pertumbuhan ekonomi negara secara keseluruhan. Tingkat pengangguran pada kuartal pertama 2015 di antara orang-orang antara usia 15 dan 24 adalah 47,5%, sedangkan di antara usia 25–49 adalah 26% (Kantor Statistik Negara, 2015). Melihat lebih dekat pada tingkat pendidikan total orang yang menganggur di Makedonia pada periode yang sama menunjukkan bahwa 19% memiliki tingkat pendidikan yang lebih tinggi dan 21% memiliki gelar universitas. Tingkat pengangguran rata-rata Uni Eropa pada bulan April 2015 adalah 9,7%; Namun, tingkat pengangguran kaum muda (penduduk berusia 15-24) adalah 20,7% (Eurostat, 2015). Meskipun langkah-langkah dekade diperkenalkan untuk meningkatkan semangat kewirausahaan, aktivitas ekonomi di antara populasi yang lebih muda masih rendah, terutama di Italia, rata-rata 40,9%. Republik Makedonia, sebuah negara dalam transisi ekonomi yang berkepanjangan, menghadapi tantangan luar biasa dalam memberi inspirasi dan memungkinkan generasi muda untuk berkomitmen terhadap wirausaha atau pendirian bisnis wirausaha. Studi menemukan bahwa niat kewirausahaan menentukan kemungkinan memulai bisnis sedangkan Teori Perilaku Berencana menunjukkan bahwa niat menangkap aspek motivasi perilaku dan bergantung pada keyakinan perilaku, normatif dan kontrol. Penelitian ini berusaha untuk mengidentifikasi faktor-faktor yang mendorong niat kewirausahaan di kalangan mahasiswa bisnis Makedonia. Penelitian ini menggunakan pendekatan Partial Least Square (PLS) untuk Structural Equation Modeling. Structural Equation Modeling adalah teknik yang sangat berguna dalam penelitian yang menggunakan sejumlah indikator (variabel yang diamati) untuk mengukur variabel laten - konstruksi (Chin, 1998) dan menguji hubungan antara variabel laten pada tingkat teoritis (Hair, Sarstedt, Ringle, & Mena, 2012). Pengujian hubungan antara variabel laten (model dalam) didasarkan pada penilaian variabel laten pada tingkat observasional (model luar atau pengukuran) menurut Hair et al. (2012). Ada dua pendekatan yang berbeda untuk SEM: SEM berbasis kovarian (CB-SEM) (Joreskog, 1978) dan SEM berbasis varians (PLS-SEM) (Wold, 1985). Mengingat bahwa penelitian ini memiliki model teoritis yang rumit dengan sejumlah indikator dan variabel laten serta model yang relatif baru untuk diuji, itu menggunakan pendekatan PLS-SEM karena pendekatan yang direkomendasikan dalam situasi seperti itu (Chin, 1998) . Lebih khusus lagi, penelitian ini menggunakan program SmartPLS (Ringle, Wende, & Will, 2005). Untuk menguji model luar - penilaian variabel laten - indikator berikut digunakan: pemuatan luar untuk memeriksa keandalan indikator; keandalan konsistensi internal; validitas konvergen; validitas diskriminan; dan lintas beban. Menurut Wong (2013), model dalam diakses menggunakan koefisien determinasi (R2) yang menunjukkan berapa banyak varians dari variabel endogen dijelaskan oleh variabel lain dari model dan prosedur bootstrap digunakan untuk menguji signifikansi statistik (Koefisien jalur yang signifikan secara statistik adalah yang dengan nilai
Tugas Review Jurnal Internasional – Enterpreneurship | Dilson - 17193034
T lebih besar dari 1,96 untuk uji dua-ekor pada tingkat signifikansi 95%). Temuan menyoroti dampak pendidikan kewirausahaan, sistem pendukung dan iklim bisnis yang menguntungkan pada niat kewirausahaan, yang sesuai dengan mayoritas negara-negara Eropa serta kecenderungan global. Penulis menyimpulkan bahwa sistem pendidikan harus berfungsi sebagai sumber utama dukungan bagi siswa mengenai basis pengetahuan mereka tentang kewirausahaan. Hal ini penting karena pendidikan semacam itu dapat menghasilkan sikap yang lebih positif terhadap kewirausahaan, perasaan kontrol yang lebih baik dan persetujuan sosial kewirausahaan yang lebih tinggi. Faktorfaktor tersebut kemudian mengarah ke tingkat niat kewirausahaan yang lebih tinggi (Sieger et al., 2011). Temuan ini sejalan dengan temuan GEM untuk niat wirausaha di Makedonia, menyarankan kerja lebih lanjut diperlukan pada modernisasi sistem pendidikan baik di sektor formal dan informal. Upaya kami membentuk sikap universitas, pemerintah, dan pusat pemula, serta keluarga, terhadap kegiatan untuk meningkatkan niat kewirausahaan di kalangan mahasiswa bisnis. Basu dan Virick (2008) juga menyimpulkan bahwa ada penekanan yang kuat pada niat kewirausahaan melalui pendidikan dan paparan praktis untuk proses kewirausahaan. Ini berarti bahwa sistem pendidikan harus memuat informasi serta pengalaman praktis bagi siswa yang akan membangun pengetahuan dan keterampilan mereka untuk usaha wirausaha. Penelitian OECD juga menyarankan pendekatan yang sama terhadap pendidikan kewirausahaan, menempatkan fokus pada universitas dan institusi pendidikan tinggi dan penerapan metode pengajaran interaktif serta konseling bisnis dan sistem pendukung UKM yang ditargetkan untuk meningkatkan niat kewirausahaan (Martinez-Fernandez & Weyman, 2010) . Selain itu, siswa harus mendapatkan lebih banyak informasi tentang berbagai sistem pendukung yang tersedia untuk memulai usaha baru karena jenis pengetahuan ini secara langsung memengaruhi niat kewirausahaan. Sebuah penelitian terbaru tentang 27 negara Uni Eropa juga mengidentifikasi bahwa pengalaman terbatas dalam jaringan bisnis dan modal sosial dapat mempengaruhi pengaturan dan menjalankan bisnis, dan akses ke pembiayaan (Halabisky, 2012).
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Economic Research-Ekonomska Istraživanja
ISSN: 1331-677X (Print) 1848-9664 (Online) Journal homepage: http://www.tandfonline.com/loi/rero20
Drivers of entrepreneurial intentions among business students in Macedonia Ana Tomovska Misoska, Makedonka Dimitrova & Jadranka Mrsik To cite this article: Ana Tomovska Misoska, Makedonka Dimitrova & Jadranka Mrsik (2016) Drivers of entrepreneurial intentions among business students in Macedonia, Economic Research-Ekonomska Istraživanja, 29:1, 1062-1074, DOI: 10.1080/1331677X.2016.1211956 To link to this article: http://dx.doi.org/10.1080/1331677X.2016.1211956
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Date: 28 December 2016, At: 09:35
Economic Research-Ekonomska Istraživanja, 2016 VOL. 29, NO. 1, 1062–1074 http://dx.doi.org/10.1080/1331677X.2016.1211956
OPEN ACCESS
Drivers of entrepreneurial intentions among business students in Macedonia Ana Tomovska Misoskaa, Makedonka Dimitrovab and Jadranka Mrsika a
School of Business Economics and Management, University American College Skopje, Skopje, Republic of Macedonia; bUAKS Entrepreneurship and Leadership Development Institute, Skopje, Republic of Macedonia
ABSTRACT
Studies find that entrepreneurial intentions determine the likelihood of starting a business whereas the Theory of Planned Behaviour suggests that intentions capture the motivational aspect of behaviour and are dependent on behavioural, normative and control beliefs. This research endeavours to identify factors that drive entrepreneurial intentions among Macedonian business students. The Partial least square approach to the Structural equation modelling was applied. Findings highlight the impact of entrepreneurship education, support systems and a favourable business climate on entrepreneurial intentions, which correspond to the majority of the European countries as well as global tendencies.
ARTICLE HISTORY
Received 18 May 2016 Accepted 8 July 2016 KEYWORDS
Entrepreneurship; entrepreneurial intentions; theory of planned behaviour; business students; Macedonia JEL CLASSIFICATIONS
L26; M13; J23; I29
1. Introduction Before the Republic of Macedonia gained its independence in 1991, the business environment suppressed entrepreneurial intentions as part of the communist legacy, but today it’s fighting to bring to attention the importance of small businesses for the overall economic growth of the country. The unemployment rate in the first quarter of 2015 among people between the ages of 15 and 24 was 47.5%, while among the ages of 25–49 it was 26% (State Statistical Office, 2015). A closer look at the education level of the total unemployed people in Macedonia in the same period shows that 19% have a higher level of education and 21% hold a university degree. The European Union average unemployment rate in April 2015 was 9.7%; however, the youth unemployment rate (population aged 15–24) was 20.7% (Eurostat, 2015). Despite the decades of measures introduced to boost entrepreneurial spirit, the economic activity among the younger population is still low, especially in Italy, averaging 40.9%. The Republic of Macedonia, a country in prolonged economic transition, is facing a tremendous challenge in inspiring and enabling younger generations to commit to self-employment or the establishment of entrepreneurial businesses. Moreover, choosing a career option in SME or self-employment also supports the general attitude towards an entrepreneurial career as a majority of the companies in Macedonia are SMEs (97.9%), of CONTACT Makedonka Dimitrova
[email protected]
© 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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which 85.2% represent companies of up to ten employees. Even though academia differentiates between the self-employment measures and entrepreneurial behaviour, the Government of the Republic of Macedonia considers both as entrepreneurial activities and promotes them as such. Following the trends in modern economies and their educational systems, entrepreneurship education has been introduced at both high school and higher education levels in the new millennium in support of economic activities. The business schools were the first adopters of the entrepreneurship curricula but it gradually spread to other disciplines, integrated accordingly with aspects of innovations. The key role in the current and future development of job creation in Macedonia belongs to the entrepreneur, whereas entrepreneurial education has been argued about among the researchers and practitioners as an effective way to promote and create entrepreneurial orientation among university students (Yoon, Kin, & Liang, 2011). The institutional context influences the performance of economies, with an emphasis on the impact on the entrepreneur’s behaviour, and therefore it should be further researched (Veciana, Marinés, & Urbano, 2005). There is hardly any study that investigates the entrepreneurial intention of existing entrepreneurs; dedicated empirical studies on entrepreneurial intentions amongst university students are almost non-existent, with the exception of the Global Entrepreneurship Monitor (GEM) research that the Republic of Macedonia took part in, in 2008, 2009, 2012 and 2013. GEM’s total early entrepreneurial activities were at 6.6%, putting Macedonia in line with other GEM countries. According to GEM, the average Macedonian entrepreneur is male between the age of 25–34 with a higher education degree and a relatively high income. GEM reiterates that despite the increase in entrepreneurial opportunities, the number of start-ups remained the same. This may be influenced by the dominant mindset preference for public sector jobs or job placements in big companies (Global Entrepreneurship Monitor, 2015).
2. Theoretical background Researchers argue that the reason behind the growing interest in entrepreneurship education is its impact on job creation and economic growth and, in fact, research proves that there is a strong link between entrepreneurial activity and economic performance (Lado & Vozikis, 1996; Kuratko, 2005). Moreover, Lado and Vozikis (1996) stress the need to stimulate the entrepreneurial culture on a global level. One of the ways to achieve greater interest in entrepreneurial activities is through entrepreneurship education at the levels of university, public servants and teaching staff. In the wider societal context, there are certain systematic and cultural dimensions that craft entrepreneurial activities, i.e., the intentions of the young population. In the search for these dimensions we construct the main research question as such: which factors drive entrepreneurial intentions among business students in Macedonia? A specific line of research explored the cognitive aspects of entrepreneurship and various factors connected to starting a business among university students. A number of authors emphasised that becoming an entrepreneur is an intentional and planned behaviour and, as such, intentions are best predictors of behaviour, not attitudes, beliefs, personality or demographics (Audet, 2004; Krueger, Reilly, & Carsrud, 2000; Kolvereid, 1996; Mboko, 2011; Tkachev & Kolvereid, 1999). In addition, researchers have attempted to find the relationship between the students’ values, attitudes and behaviours and their entrepreneurial potential, if it could help them start up a company, to self-employ or, in the last instance, have the intention to do so. Krueger et al. (2000) defined intentions as planned target behaviour
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to start a business, but the point of venture realisation in the future is not determined. It might happen that they never actually start a business because other factors might intervene. Intentions are also known to predict behaviour in long-run tendencies thus cancelling variation in actual behaviour over time; Audet (2004) researched how entrepreneurial perceptions and intentions evolve over time. However, people with higher entrepreneurial intentions have a higher likelihood of actually starting a business than those with lower intentions (Thompson, 2009). There are also other dimensions that determine the likelihood of becoming an entrepreneur, such as previous experience in family business or motivation by a sibling to become involved in entrepreneurial activity (Van Auken, 2006). One study on entrepreneurial intentions among business school students conducted in Macedonia and Slovenia suggested that the majority of those students who had experience in a family business plan to establish a business in the near future or already run one (Dimitrova, Vadnjal, Petrovska, & Bojadziev, 2014). Moreover, a large study of over 1 million students all over the world showed that students prefer organisational employment directly after studies, although the preference weakens after 5 years of university education (Sieger, Fueglistaller, & Zellweger, 2011). Therefore, intentions are considered a good predictor of behaviour, especially at times where there is a time lag between the stated preference to become an entrepreneur and the actual behaviour. Moreover, intentions offer a unique opportunity to explain and predict entrepreneurial activity but they have explanatory and predictive power, as shown in a number of studies (Guerrero, Rialp, & Urbano, 2006; Kolvereid, 1996; Linan, Urbano, & Guerrero, 2011; Tkachev & Kolvereid, 1999; Veciana et al., 2005). The intentions are especially useful when it comes to predicting the career choices of students (Kolvereid, 1996; Veciana et al., 2005). In order to enhance the understanding of entrepreneurial intentions, many authors use two models: Shapero’s Model of Entrepreneurial Event (Shapero & Sokol, 1982) and Theory of Planned Behaviour (TPB) (Ajzen, 1991). Shapero’s (1982) model is specific to the field of entrepreneurship and is based on the premise that the intention to become an entrepreneur is derived from perceptions of desirability as well as feasibility and propensity to act upon opportunities. On the other hand TPB was founded on the theoretical developments in psychology and is applied in a number of other fields, which makes the theory more robust (Krueger, 2000). A number of studies used TPB to study entrepreneurial intentions in various countries and settings (Guerrero et al., 2006; Kolvereid, 1996; Linan et al., 2011; Mboko, 2011; Tkachev & Kolvereid, 1999). According to the TPB as presented in Figure 1, intentions capture the motivational aspect of behaviour and are dependent on three different beliefs: beliefs about the likely consequences of the behaviour – behavioural beliefs; beliefs about the normative expectations of other people – normative beliefs; and beliefs about the presence of factors that might hinder behaviour – control beliefs (Ajzen, 1991, 2002, 2012). Behavioural beliefs result in perceived behavioural control, which represents the extent to which people think that they will be successful in performing certain behaviour if they want to do so and this is closely related to self-efficacy and also the perceived controllability of behaviour (Ajzen, 1991). The normative beliefs result in a subjective norm, which means the perceived social pressure to perform with a particular behaviour while the control beliefs result in an attitude towards certain behaviour (Ajzen,1991). This means that the entrepreneurial intentions are based on the positive or negative personal appraisal about being an entrepreneur – attitude towards behaviour; perceived difficulty in becoming an entrepreneur – perceived behavioural control; and perceived approval or disapproval of family, friends and
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Attitude towards behaviour: Would becoming an entrepreneur be attractive? Perceived behavioural control:
Intentions: How
Do you think you can be
likely you are to
successful as entrepreneur?
start a business?
Behaviour
Subjective norm: Would starting a business be judged positively by people who matter to you?
Figure 1. Ajzen’s Theory of Planned Behaviour.
significant others of the decision to become an entrepreneur – subjective norm. Therefore, Ajzen (1991) reiterates that the control beliefs result in attitude towards behaviour, which means the attractiveness of the outcomes of certain behaviour. Moreover, the theory suggests that the appraisal of the business climate, education experience and support knowledge are keys to understanding the entrepreneurial intentions of students. These points might have direct influence on the intentions or indirect influence through influencing the behavioural control, attitude towards behaviour or social norm. Basu and Virick (2008) suggest that educational support may positively reflect on the entrepreneurial attitudes among students. Other studies reinforce the importance of knowing about various support systems, as well as student’s knowledge of various support mechanisms and their appraisal of business climates. Therefore, entrepreneurial activity depends largely on how people perceive the feasibility of the undertaking based on the desirability of the activity in the social context (Kolvereid, 1996) and perceived support (Mboko, 2011). Studies have pointed out that students are more willing to consider becoming entrepreneurs if they have knowledge about the various support mechanisms as financial risks were one of the important barriers in starting a company (Sieger et al., 2011). Research also identifies that increased structural support was more conducive to entrepreneurial intentions (Turker & Selcuk, 2009). In addition, a number of studies have shown that entrepreneurial spirit and intentions can be stimulated in properly planned educational interventions (Basu & Virick, 2008; Jakubczak & Rawowska, 2013). Thus, the study of Turker and Selcuk (2009) found that if a university provides adequate knowledge and inspiration for entrepreneurship, the possibility of choosing an entrepreneurial career might increase among young people. To gain a deeper understanding of the entrepreneurial intentions, we conducted an empirical study on business students’ entrepreneurial intentions in Macedonia. The main interest was to understand the influence of students’ appraisal as a result of their education experience, the business climate and knowledge of support mechanisms, as these are factors that are indicated as being important in the entrepreneurial intentions of the students. The study involved not only seeing whether these factors stimulate entrepreneurial intentions but also showing how they do this, through utilising the Theory of Planned Behaviour.
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3. Methodology The empirical analysis was carried on a sample of university students in the spring semester of the academic year 2012/13. The instrument used in the study was based on an instrument developed by Linan and Chen (2009) and Linan et al. (2011). The instrument was developed with TPB in mind and cross-checked with other measures of entrepreneurial intentions as well as a cross-cultural check. Besides using the original items of the instrument, some other sections were added to the instrument to enable gathering data that will portray the situation in Macedonia and enable gathering data about the perceptions of students regarding different aspects connected to entrepreneurial intentions and entrepreneurship. The added sections served to understand the student’s views and experiences that can be connected to their entrepreneurial intentions. The questions linked to the model of entrepreneurial intentions were measured on a seven-point Likert-type scale. All of the questions were positively worded, but in order to avoid acquiescence to the questions some items measure in one direction whereas others measure in the opposite direction (Thompson, 2009). The questions used in the study for model testing are given in Appendix 1. The sample of the study consisted of students at Business Schools from two different universities in the Republic of Macedonia. The study was carried out using convenient sampling of first-year undergraduate students, final-year undergraduate students and students in the final year of their graduate studies. This method of sampling enabled us to portray the views of the students at different stages of their schooling. The students have different experiences regarding subjects connected to entrepreneurship as well as differences in their thinking about their future careers and career options. The sample consisted of 213 students in total, 84.1% were undergraduate students and 15.9% were graduates. Most of the students in the sample were females 60.9% and the rest were males (39.1%). The average age of the students was 20.5 years. This study used the Partial Least Square (PLS) approach to Structural Equation Modelling. Structural Equation Modelling is a technique that is especially useful in research that uses a number of indicators (observed variables) to measure latent variables – constructs (Chin, 1998) and test relationships between latent variables on a theoretical level (Hair, Sarstedt, Ringle, & Mena, 2012). The relationship testing between the latent variables (inner model) is based on the assessment of the latent variables at observational level (outer or measurement model) according to Hair et al. (2012). There are two different approaches to SEM: covariance-based SEM (CB-SEM) (Joreskog, 1978) and variance-based SEM (PLS-SEM) (Wold, 1985). Having in mind that the study had a complicated theoretical model with a number of indicators and latent variables as well as a relatively new model to test, it used the PLS-SEM approach as it is a recommended approach in such situations (Chin, 1998). More specifically the study utilised the programme SmartPLS (Ringle, Wende, & Will, 2005). To test the outer model – assessment of the latent variables –the following indicators were used: outer loadings to check for indicator reliability; internal consistency reliability; convergent validity; discriminant validity; and cross-loadings. According to Wong (2013), the inner model was accessed using the coefficient of determination (R2) which shows how much of the variance of the endogenous variable is explained by other variables of the model and the bootstrapping procedure was used to test for statistical significance (statistically significant path coefficients are the ones with T values larger than 1.96 for a two-tailed test at a 95% significance level).
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Table 1. Confirmatory analysis of the outer model. Latent variable Attitude towards behaviour Perceived behavioural control Subjective norm Entrepreneurial intentions Business climate
Education experience
Support knowledge
Indicator A15 A18 A01 A07 A14 A03 A08 A11 A04 A06 A13 A17 B1 B2 B3 B4 B5 E1 E2 E3 E6 E7 E8 E9 E10 S1 S2 S3 S6 S7 S8 S9
Loading 0.8833 0.8223 0.6501 0.8261 0.8369 0.8002 0.8315 0.7977 0.7817 0.7885 0.8052 0.7444 0.6792 0.7537 0.8097 0.7495 0.6432 0.7297 0.7452 0.688 0.6389 0.7534 0.787 0.794 0.7593 0.6596 0.7852 0.7301 0.8059 0.6935 0.6873 0.7794
Indicator reliability (squared loading) 0.78021889 0.67617729 0.42263 0.682441 0.700402 0.64032 0.691392 0.636325 0.611055 0.621732 0.648347 0.554131 0.461313 0.568064 0.655614 0.56175 0.413706 0.532462 0.555323 0.473344 0.408193 0.567612 0.619369 0.630436 0.576536 0.435072 0.616539 0.533046 0.649475 0.480942 0.472381 0.607464
Composite reliability 0.8424
AVE 0.728
0.817
0.6013
0.8513
0.6562
0.8615
0.6088
0.8496
0.5321
0.9053
0.5454
0.8919
0.5422
Source: Research results.
4. Results In the initial stage, we have tested the outer model to check which indicators (questions) satisfy the required criteria. The results of this confirmatory factor analysis are shown in Tables 1 and 2. The model was accepted when the indicators satisfied the requirements mentioned in the literature. Namely the indicators that were deemed to have satisfactory reliability had square loadings higher than 0.4 (Hulland, 1999). The internal consistency reliability was deemed satisfactory when the model reached a composite reliability of over 0.6 (Bagozzi & Yi, 1988). For the convergent validity, an AVE number of over 0.5 was deemed an appropriate finding according to the above-mentioned authors. The discriminant validity was accessed using the Fornell and Larcker (1981) criterion by which the square root of the AVE should be higher than the correlations among the latent variables. 4.1. Inner model testing As a result of the confirmatory factor analysis, only the questions (indicators) with satisfactory statistical outcomes were used in further analysis and the inner model testing. This means that the attitude towards behaviour was tested with two questions, Perceived
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Table 2. Fornell–Larcker criterion for discriminant validity.
Attitude towards behaviour Business climate Education experience Entrepreneurial intentions Perceived behavioural control Subjective norm Support knowledge
Attitude towards behaviour 0.8533
Business climate 0
Education experience 0
Entrepreneurship intentions 0
Perceived behavioural control 0
Subjective norm 0
Support knowledge 0
0.1551
0.7294
0
0
0
0
0
0.2067
0.1276
0.7385
0
0
0
0
0.6352
0.1167
0.2481
0.7802
0
0
0
0.3893
0.1317
0.1547
0.5476
0.81
0
0
0.3752
0.0192
0.1787
0.3824
0.3561
0.7363
0
0.0643
0.2226
0.1552
0.1987
0.1585
0.0474
1
Source: Research results.
Table 3. Attractiveness of career options for students. Public administration Big company SME Entrepreneur Family business Self-employed
Not attractive 44.8 10.7 29.4 22.9 11.3 43.7
Undecided 16 16.4 24.5 14.8 10 14.6
Attractive 29.2 72.8 46.1 62.3 78.6 41.8
Source: Research results.
behavioural control was tested with three questions, Subjective norm with three questions, Entrepreneurial intentions with four questions, Business climate with five questions, Education experience with eight questions and Support knowledge with seven questions. To obtain a better insight into the students’ thinking about entrepreneurship, the study also asked the students to provide answers on the attractiveness of certain career options. Table 3 outlines the answers of the students. As can be seen, becoming an entrepreneur is one of the more attractive options for the students, with 62.3% of the students choosing it as attractive employment option. However, working in their own family business, an option compatible with entrepreneurship, was chosen as attractive by a majority of the students as well (78.6%). Having in mind the structure of the students, their opinions about entrepreneurship as an attractive career option, as well the results of the confirmatory factor analysis, the study proceeded with testing the model of entrepreneurial intentions of the students. This testing enabled us to get a better insight into the variables that influence the entrepreneurial intentions of the students. The results of the testing are shown in Figure 2 and Table 4. Figure 2 shows only the statistically significant path coefficients, while Table 4 shows all the coefficients, with the statistically significant ones in bold. As can be seen from Figure 2 and Table 4, the model explains 53.5% of the variance in Entrepreneurial intentions. This means that there are other factors that also contribute to
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Figure 2. Model of entrepreneurial intention with business climate, education experience, entrepreneurial skills and support knowledge. Table 4. Path coefficients of the tested model of entrepreneurial intentions. Attitude → Entrepreneurial Intentions Business climate → Attitude Business climate → Entrepreneurial Intentions Business climate → Perceived behaviour control Business climate → Subjective norm Education experience → Attitude Education experience → Entrepreneurial Intentions Education experience → Perceived behaviour control Education experience → Subjective norm Perceived behaviour control → Entrepreneurial Intentions Subjective norm → Attitude Subjective norm → Entrepreneurial Intentions Subjective norm → Perceived behaviour control Support knowledge → Attitude Support knowledge → Entrepreneurial Intentions Support knowledge → Perceived behaviour control Support knowledge → Subjective norm
Path coefficient 0.4662 0.1325 −0.0328 0.0919 −0.0081 0.1275 0.0763 0.0653 0.1764 0.3134 0.3499 0.0777 0.3374 −0.0016 0.1108 0.1119 0.0218
Source: Research results.
Entrepreneurial intentions but the model has a good predictive value. The model reiterates once again the TPB (Ajzen, 1991) by uncovering statistically significant paths from perceived behavioural control, subjective norm and attitude towards behaviour to entrepreneurial intentions. Subjective norm influences the perceived behavioural control and attitude which is in line with the Linan and Chen (2009) research conducted on business students in Spain and Taiwan that suggests promotion of entrepreneurial culture to support the entrepreneurial intentions of students. In addition, the model shows how the broader drivers impact students’ entrepreneurial intentions. The model indicates that the educational experiences that develop knowledge about entrepreneurship have a statistically significant influence on subjective norms, attitudes towards behaviour and perceived behavioural control. This means students that appraise a higher level of preparedness for entrepreneurship through educational experiences, demonstrate a more positive attitude towards entrepreneurship, perceive that
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entrepreneurship is valued higher by their significant others and perceive that they can be more successful as entrepreneurs. These elements mediate the relationship between their educational experience and their entrepreneurial intentions. The findings about the ability of education to stimulate entrepreneurial intentions and entrepreneurship are in line with other studies (Basu & Virick, 2008). For example, GUESSS global research concludes that from students’ point of view there is strong demand for workshops, participation in entrepreneurship networks, lectures in innovation and contact persons for problems related to entrepreneurship (Sieger et al., 2011). Interestingly, the model shows a direct link between knowledge of support systems and entrepreneurial intentions (Mboko, 2011; Sieger et al., 2011). This means that, regardless of the other factors, being more aware about support systems will lead to a higher level of entrepreneurial intention among business students from Macedonia. A recent empirical study was carried out by the Network of Business Start Up Centres on the territory of the Western Balkans where 72% of the respondents said that knowledge of the support systems has a great impact on their entrepreneurial activities (Hajdukov, 2011). The model shows a statistically significant influence on perception of the business climate and entrepreneurship towards attitude and perceived behavioural control. This means that students that express a more positive perception about the business climate also express a more positive attitude towards entrepreneurship and think that they can be more successful as entrepreneurs.
5. Conclusion This study is a first of its kind in Macedonia. Although it is limited in scope and uses only students from business schools it highlights important findings about the drivers of entrepreneurial intentions among students. This study again emphasises that the educational system should serve as the main source of support for students regarding their knowledge base about entrepreneurship. This is important since such education can result in more positive attitudes towards entrepreneurship, feeling of better control and higher social approval of entrepreneurship. Those factors then lead to higher levels of entrepreneurial intentions (Sieger et al., 2011). The findings go along with the GEM finding for entrepreneurial intention in Macedonia, suggesting further work is required on educational system modernisation both in the formal and the informal sector. Our endeavour shapes the attitude of the universities, governments, and start-up centres, as well as families, towards activities to increase entrepreneurial intention among business students. Basu and Virick (2008) also conclude that there is a strong emphasis on entrepreneurial intentions through the education and practical exposure to entrepreneurship processes. This means that the educational system should contain information as well as practical experiences for students that will build their knowledge and skills for entrepreneurial ventures. OECD studies also suggest a similar approach to entrepreneurial education, putting a focus on the university and higher education institutions and implementation of interactive teaching methods as well as business counselling and targeted SME support systems to increase entrepreneurial intentions (Martinez-Fernandez & Weyman, 2010). In addition, students should get more information about the various support systems available for starting new ventures as this type of knowledge directly influences entrepreneurial intentions. A recent study on the EU 27 countries also identifies that limited experience in business networks and social capital may influence the setting up and running businesses, and access to finance (Halabisky, 2012).
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Fostering a good business climate will stimulate more positive attitudes and the feeling of being more in control, which will lead to higher entrepreneurial intentions. Future research in this field should target students enrolled in programmes other than business to serve as a solid basis for future policy interventions and increased self-employment in Macedonia.
Disclosure statement No potential conflict of interest was reported by the authors.
Acknowledgement The extended abstract of this paper was originally presented at the Seventh International Scientific Conference ‘European Union Future Perspectives: Innovation, Entrepreneurship and Economic Policy’, Pula, Croatia, 21–23 May 2015.
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Appendix 1. Survey questions Entrepreneurial intentions, attitude towards behaviour, perceived behavioural control and subjective norm A01. Starting a firm and keeping it viable would be easy for me A02. A career as an entrepreneur is totally unattractive to me A03. My friends would approve of my decision to start a business A04. I am ready to do anything to be an entrepreneur A05. I believe I would be completely unable to start a business A06. I will make every effort to start and run my own business A07. I am able to control the creation process of a new business A08. My immediate family would approve of my decision to start a business A09. I have serious doubts about ever starting my own business A10. If I had the opportunity and resources, I would love to start a business A11. My colleagues would approve of my decision to start a business A12. Amongst various options, I would rather be anything but an entrepreneur A13. I am determined to create a business venture in the future A14. If I tried to start a business, I would have a high chance of being successful A15. Being an entrepreneur would give me great satisfaction A16. It would be very difficult for me to develop a business idea A17. My professional goal is to be an entrepreneur A18. Being an entrepreneur implies more advantages than disadvantages to me A19. I have a very low intention of ever starting a business A20. I know all about the practical details needed to start a business Business climate B1. In my country there are enough financial resources for starting a business B2. In my country the procedure for starting a new business is straightforward B3. The legal system in my country is conducive for doing business B4. The tax system in my country is conducive for doing business B5. The government of the country directly supports the creation of new businesses (financial incentives, advising) B6. The government in my country supports women entrepreneurs B7. The infrastructure in my country is conducive for doing business (roads, power, water, transport links, telecommunications, industrial land, estates and incubators) Education experience – How much has the educational system helped you to develop the following aspects E1. Knowledge about the entrepreneurial environment E2. Generation of idea for business and recognising opportunities E3. Development of Business Plan for Start-up Business E4. Setting up a new venture team E5. Avoiding legal issues at start-up E6. Growing a business E7. Greater recognition of the entrepreneur’s figure E8. The preference to be an entrepreneur E9. The necessary abilities to be an entrepreneur E10. The intention to be an entrepreneur E11. Skill for succession of family business, if any Support knowledge – Assess your level of knowledge about the following S1. Private associations (e.g., Economic Chamber, Yes Incubator, etc.) S2. Public support bodies (e.g., Agency for promotion of entrepreneurship of the Republic of Macedonia, etc.)
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S3. Specific training for young entrepreneurs S4. Loans at specially favourable terms S5. Technical aid for business start-ups S6. Business start-up centres S7. Business Angel Networks S8. Venture Capital Funds S9. Regional or local Business Plan Competitions on regular basis
