The Impact of Entrepreneurship Education: A Study ofIranian Students’ Entrepreneurial Intentions andOpportunity Identificationby Saeid Karimi, Harm J. A. Biemans, Thomas Lans, Mohammad Chizari,and Martin Mulder

Building on the theory of planned behavior, an ex ante and ex post survey was used to assess theimpacts of elective and compulsory entrepreneurship education programs (EEPs) on students’entrepreneurial intention and identification of opportunities. Data were collected by questionnairefrom a sample of 205 participants in EEPs at six Iranian universities. Both types of EEPs hadsignificant positive impacts on students’ subjective norms and perceived behavioral control. Resultsalso indicated that the elective EEPs significantly increased students’ entrepreneurial intention,although this increase was not significant for the compulsory EEPs. The findings contribute to thetheory of planned behavior and have implications for the design and delivery of EEPs.

IntroductionDuring the past few decades, entrepreneur-

ship has become an important economic andsocial topic as well as an often-researchedsubject around the world (Fayolle and Gailly2008). According to research, entrepreneurshipis an intentional and planned behavior thatcan increase economic efficiency, bring innova-tion to markets, create new jobs, and raiseemployment levels (Shane and Venkataraman2000). Most empirical studies indicate thatentrepreneurship, or at least some aspects of it,

can be taught and that education can be con-sidered one of the key instruments for fosteringentrepreneurial attitudes, intentions, andcompetences (Falkang and Alberti 2000; Harrisand Gibson 2008; Henry, Hill, and Leitch 2005;KuratKo 2005; Martin, McNally, and Kay 2013;Mitra and Matlay 2004). This view has led to adramatic rise in the number and status of entre-preneurship education programs (EEPs) in col-leges and universities worldwide (Finkle andDeeds 2001; Katz 2003; KuratKo 2005; Matlay2005); investment in these programs is still onthe increase (Gwynne 2008). Nevertheless, the

Saeid Karimi is an entrepreneurship PhD student in the Department of Social Sciences, Education, andCompetence Studies Group at the Wageningen University.

Harm J. A. Biemans is an associate professor of education in the Department of Social Sciences, Education,and Competence Studies Group at the Wageningen University.

Thomas Lans is an assistant professor of entrepreneurship in the Department of Social Sciences, Education,and Competence Studies Group at the Wageningen University.

Mohammad Chizari is professor of agricultural education in the Department of Agricultural Education andExtension at the Tarbiat Modares University.

Martin Mulder is professor of education in the Department of Social Sciences, Education, and CompetenceStudies Group at the Wageningen University.

Address correspondence to: Saeid Karimi, Department of Social Sciences, Education, and CompetenceStudies Group, Wageningen University, Wageningen 6702 PJ, The Netherlands. E-mail: saeid.karimi@wur.nl.

Journal of Small Business Management 2014 ••(••), pp. ••–••

doi: 10.1111/jsbm.12137

KARIMI ET AL. 1

impact of these programs has remained largelyunexplored (Bechard and Gregoire 2005;Peterman and Kennedy 2003; Pittaway andCope 2007; von Graevenitz, Harhoff, andWeber 2010). Moreover, the results of previousstudies are inconsistent. Some of these studiesreported a positive impact from EEPs (e.g.,Athayde 2009; Fayolle, Gailly, and Lassas-Clerc2006; Peterman and Kennedy 2003; Souitaris,Zerbinati, and Al-Laham 2007), whereas othersfound evidence that the effects are statisticallyinsignificant or even negative (Mentoor andFriedrich 2007; Oosterbeek, van Praag, andIjsselstein 2010; von Graevenitz, Harhoff,and Weber 2010).

Methodological limitations may be the causeof these inconsistent results (von Graevenitz,Harhoff, and Weber 2010). Some studies, forinstance, are ex post examinations that there-fore do not assess the direct impact of an EEP(e.g., Kolvereid and Moen 1997; Menzies andParadi 2003), or have small sample sizes (e.g.,Fayolle, Gailly, and Lassas-Clerc 2006; Joneset al. 2008); this has led Martin, McNally, andKay (2013) to conclude that entrepreneurshipeducation researchers must include pre- andpostentrepreneurship interventions. Previousstudies also have not differentiated betweenelective and compulsory programs, andresearch on the important role of compulsoryversus voluntary participation in EEPs has beenneglected; therefore, Oosterbeek, van Praag,and Ijsselstein (2010) call for the testing ofdifferent program variants. In addition, there isno agreement on what would constitute a well-defined method and a suitable conceptualmodel for assessing the effects of EEPs(Falkang and Alberti 2000; von Graevenitz,Harhoff, and Weber 2010). Moreover, non-business university students have receivedlimited attention in previous studies (Lans et al.2013), despite the fact that this population rep-resents the bulk of young adults pursuing aneducation program. Finally, there is no studyregarding the impact of entrepreneurship edu-cation for Iranian universities.

The present study has attempted to reducethese theoretical and methodological gaps andmake four contributions to the existing litera-ture. First, we applied an intention model toassess the impact of EEPs. As a second contri-bution, we studied the effects of large-scalecompulsory and elective entrepreneurshipcourses at different universities. The third con-tribution is our use of a pretest plus post-test

design to study these effects. And the fourthcontribution is to assess the effect of entrepre-neurship education on non-business universitystudents in a developing country, namely Iran.This paper is organized as follows. In the nextsection, we explain entrepreneurial intentions(EIs) and the theory of planned behavior (TPB).We then discuss the relationships betweenintentions, their antecedents, and opportunityidentification, and point out how EEPs mayaffect these factors. Next, we describe themethod and findings. Finally, we discuss ourresults and their implications both for the prac-tice of entrepreneurship education and forfuture research.

Theoretical FrameworkEIs. In the social psychology literature, inten-tions have proved to be the best predictor ofplanned individual behaviors, especially whenthe target behavior is rare, difficult to observe,or involves unpredictable time lags (Krueger,Reilly, and Carsrud 2000). Entrepreneurship isa typical example of such planned and inten-tional behavior (Bird 1988; Krueger andBrazeal 1994). EI refers to a state of mind thatdirects and guides the actions of the individualtoward the development and implementationof a new business concept (Bird 1988). There isa vast body of literature arguing that EI playsa very pertinent role in the decision to start anew business (Linan and Chen 2009). As aconsequence, in recent years, employmentstatus choice models that focus on EI have beenthe subject of considerable interest in entrepre-neurship research (e.g., Engle et al. 2010;Iakovleva, Kolvereid, and Stephan 2011; Karimiet al. 2013a, 2014). Krueger, Reilly, and Carsrud(2000) found that intention models offer a greatopportunity to increase our understanding andpredictive ability for entrepreneurship.

The TPB. Among intention models, one of themost widely researched is the TPB, originallypresented by Ajzen (1991). This model has beenwidely applied in entrepreneurship research,and its efficacy and ability to predict EI andbehaviors have been demonstrated in a numberof studies on entrepreneurship (for example,Karimi et al. 2014; Kolvereid and Isaksen 2006).The central factor of the TPB is the individualintention to perform a given behavior (e.g., theintention to become an entrepreneur). Conse-quently, the model stresses that intention isaffected by three components or antecedents

JOURNAL OF SMALL BUSINESS MANAGEMENT2

(Ajzen 1991): (1) subjective norms (SN), refer-ring to perceived social pressures to perform orrefrain from a particular behavior (e.g., becom-ing an entrepreneur); (2) attitudes toward thebehavior, that is, the degree to which a personhas a favorable or unfavorable evaluation aboutperforming the target behavior (e.g., being anentrepreneur); and (3) perceived behavioralcontrol (PBC), that is, the perceived difficulty orease of performing the behavior (e.g., becomingan entrepreneur). PBC is conceptually similar toperceived self-efficacy as proposed by Bandura(1997). In both concepts, the sense of capacity toperform the activity is important (Ajzen 2002).

HypothesesResearchers have empirically applied the

TPB to students’ EI and confirmed the theory’spredictions regarding the effects of SN, PBC,and attitude toward entrepreneurship (ATE) ontheir intentions (e.g., Engle et al. 2010; Linanand Chen 2009; Iakovleva, Kolvereid, andStephan 2011). However, these findings as awhole do not represent a conclusive and con-sistent picture. Linan and Chen (2009) testedthe TPB among university students in Spainand Taiwan. Their results showed that bothATE and PBC had significant effects on EI;however, PBC was the strongest predictor of EIin Taiwan, whereas in Spain, ATE was thestrongest predictor of EI. Even though SN hadno significant direct effect on intention, SNindirectly affected intention through ATE andPBC. Engle et al. (2010) tested the ability of theTPB to predict EI in 12 countries. The resultssuggested that the TPB model successfully pre-dicted EI in each of the study countries,although, as foreseen by Ajzen and just illus-trated in empirical work, the significant contrib-uting model elements differ among countries.Engle et al. (2010) reported that SN was a sig-nificant predictor of EI in every country,whereas ATE was a significant predictor in onlysix countries (China, Finland, Ghana, Russia,Sweden, and the United States), and PBC was asignificant predictor in only seven countries(Bangladesh, Egypt, Finland, France, Germany,Russia, and Spain). Finally, Iakovleva,Kolvereid, and Stephan (2011) used the TPB topredict EI among students in five developingand eight developed countries. The findingsprovided support for the applicability of theTPB in both developing and developed coun-tries. They found the three antecedents to besignificantly related to EI in all 13 countries. In

sum, these findings together support Ajzen’s(1991) assertion that all three antecedents areimportant, although their explanatory power isnot the same in every situation and country.Therefore, it is hypothesized that

H1: (1) SN, (2) ATE, and (3) PBC are positivelyrelated to university students’ EI.

Opportunity Identification. Opportunity iden-tification or recognition has been defined asthe ability to identify a good idea and trans-form it into a business concept (or the consid-erable improvement of an existing venture)that adds value to the customer or society andgenerates revenues for the entrepreneur(Lumpkin and Lichtenstein 2005). Opportunityidentification has long been accepted as a keystep in the entrepreneurial process (Ozgenand Baron 2007). In fact, without businessopportunity identification, there is no entre-preneurship (Short et al. 2010). For thisreason, opportunity identification has becomea required element of scholarly research andstudies of entrepreneurship, and there hasbeen considerable interest in studying thefactors, processes, and dynamics that foster it(Gregoire, Shepherd, and Lambert 2010). Theliterature provides two main theories regard-ing opportunity identification: the discoverytheory and the creation theory (Alvarez andBarney 2007). Recent research has providedevidence that both the discovery and creationapproaches can occur in entrepreneurial prac-tice and that research is moving toward amiddle ground position (Bhave 1994; Shortet al. 2010).

The TPB and Opportunity Identification.Although three attitudinal antecedents areknown to influence a wide range of behaviors,prior studies conducted in different areas (e.g.,Bagozzi, Moore, and Leone 2004; Conner andArmitage 1998; Haustein and Hunecke 2007;Hsu et al. 2006; Perugini and Bagozzi 2001)argued that additional variables could enhancethe power of the TPB to predict and explain anindividual’s intention and behavior. Within thedomain of entrepreneurship, opportunity iden-tification can be added to the TPB as an addi-tional fundamental element. As mentioned,opportunity identification is a crucial compo-nent of the entrepreneurial process (Ardichvilia,Cardozob, and Ray 2003; Gaglio and Katz 2001;Shane and Venkataraman 2000), and it is an

KARIMI ET AL. 3

intentional process (Krueger, Reilly, andCarsrud 2000). In fact, the act of entrepreneur-ship and the creation of a new business firm arebased on the joint occurrence of two events(Krueger and Brazeal 1994; Reitan 1997a). Thefirst event is the presence of a suitable entrepre-neurial opportunity, whereas the second eventrepresents a person who is able and willing totake advantage of an entrepreneurial opportu-nity. When these two events coincide, entrepre-neurial behaviour may take place; thus, a newfirm can be founded. According to Reitan(1997a), “a potential entrepreneur is a personwho perceives a venture opportunity and/orintends to start a new venture, but has not (yet)taken any steps regarding venture start-up.” Theargument is that opportunity identification andEI are key characteristics of potential entrepre-neurs, and both must be present for new busi-ness creation to take place.

Edelman and Yli-Renko (2010) also statedthat perceptions and other cognitive factorsplay a fundamental role in both the discoveryand creation views of entrepreneurship. Theyargued that the perception that opportunitiesexist in the market rather than the actual envi-ronment or the objective changes in technologyor consumer needs is important in predictingefforts to create a new business. In otherwords, perceptions of opportunity will stimu-late an individual’s efforts to start a new busi-ness. Stronger perceptions will increase theintention to create a new firm and the energy ofpotential entrepreneurs to start a firm (Edelmanand Yli-Renko 2010). A perception of an oppor-tunity can spark an intention-based cognitiveprocess that leads to entrepreneurial action(Krueger, Reilly, and Carsrud 2000). It has beenshown that the opportunity identification per-ception (OIP) and EI are closely connected(Bird 1988). That is, a person who finds anopportunity desirable and feasible is likely tocreate a business (Bhave 1994).

On the basis of the previous discussion andin line with Reitan (1997b) and Edelman andYli-Renko (2010), we propose the followinghypothesis:

H2: Those students who have higher OIP willhave greater intentions to start up a newbusiness.

In the last decade, researchers have pre-sented numerous models of entrepreneurshipand opportunity identification that are

grounded in the TPB (e.g., Dutton and Jackson1987; Krueger 2003). In addition, researchershave made considerable efforts to understandthe antecedents of opportunity identification(e.g., Ardichvilia, Cardozob, and Ray 2003;Baron and Ensley 2006; Casson and Wadeson2007; Gaglio and Katz 2001; Ozgen and Baron2007; Shane 2000). These attempts have con-tributed greatly to our understanding of oppor-tunity identification; however, they fall short ofoffering a comprehensive understanding of theprocess. Dutton and Jackson (1987) firstmapped out an elegant model of opportunityperception in a study with similarities to theTPB. They argued that a situation is perceivedas an opportunity when an individual’s percep-tion of the outcomes is positive and the situa-tion is perceived as controllable. Jackson andDutton (1988) tested this model successfully.Based on Shapero’s and Sokol (1982) modeland Dutton and Jackson (1987), Krueger (2000,2003) and Krueger and Brazeal (1994) devel-oped a complementary EI model that includesthe perception of opportunity. According tothis model, the perception of opportunity isdependent on the same two crucial antecedentsof EI, perceptions of desirability (attitude in theTPB) and perceptions of feasibility (PBC orself-efficacy in the TPB). In other words, ifindividuals perceive entrepreneurship as desir-able and feasible, they are more likely to see anopportunity and, thus, form an EI. Reitan(1997b) conducted an empirical study andfound that opportunity identification has someof the same antecedents as EI. Specifically, per-ceptions of desirability and feasibility werestrong predictors of both, whereas SN wasimportant for understanding EI only.

Although the relationship between OIP andATE is less clear and research on this relation-ship is scant, previous empirical studies indi-cate that PBC may be positively related to OIP.According to Ajzen (2002), PBC includes self-efficacy and controllability. Research has dem-onstrated that self-efficacy (Krueger andDickson 1994) and controllability (Dutton1993) are positively linked to opportunity iden-tification. Studies have also found that self-efficacy is a remarkable predictor of OIP(Ardichvilia, Cardozob, and Ray 2003; Gibbs2009; Gonzalez-Alvarez and Solis-Rodriguez2011; Krueger 2000; Mitchell and Shepherd2010; Ozgen and Baron 2007; Ucbasaran,Westhead, and Wright 2009). For example, thestudy by Krueger and Dickson (1994) found a

JOURNAL OF SMALL BUSINESS MANAGEMENT4

direct correlation between an increase in self-efficacy and an increase in perceptions ofopportunity. Increasing entrepreneurial self-efficacy should increase perceived feasibility ofstarting a business, thus increase perceptions ofopportunity (Krueger, Reilly, and Carsrud2000). Ozgen and Baron (2007) believe thatindividuals with high self-efficacy tend to havebroader social networks and to be morepopular due to high self-confidence and self-assurance; as a result, these people will receivemore information. Therefore, these authorsbelieve that high self-efficacy may indeed belinked to opportunity recognition in thismanner. Moreover, individuals with high self-efficacy believe that they can successfullydevelop the opportunities they discover. As aresult, they may be more proactive in searchingfor such opportunities (e.g., Gaglio andKatz 2001) and, in particular, in seekingopportunity-relevant information from otherpersons (Ozgen and Baron 2007). Accordingly,their study demonstrates that self-efficacy ispositively related to opportunity recognition.Drawing on the results and arguments in thestudies just mentioned, we propose that stu-dents’ PBC and ATE influence their perceptionof new business opportunity identification.

H3: (1) ATE and (2) PBC will be positivelyrelated university students’ OIP.

Entrepreneurship Education. Entrepreneurialeducation is a rapidly growing area and a hottopic in colleges and universities all around theworld, and its supposed benefits have receivedmuch praise from researchers and educators.Nevertheless, the outcomes and effectiveness ofEEPs have remained largely untested (Pittawayand Cope 2007; von Graevenitz, Harhoff, andWeber 2010). According to Alberti, Sciascia,and Poli (2004), the first and most importantarea for further investigation should includeassessing the effectiveness of these programs.However, this raises an important question:How should entrepreneurship education beassessed? One of the most common ways toevaluate an EEP is to assess individuals’ inten-tions to start a new business. Intentionality iscentral to the process of entrepreneurship (Bird1988; Krueger 1993), and studies show that EIis a strong predictor of entrepreneurial behav-ior. Nonetheless, the impact of EEPs on EI toset up a business is at present poorly under-stood and has remained relatively untested

(Athayde 2009; Peterman and Kennedy 2003;Souitaris, Zerbinati, and Al-Laham 2007; vonGraevenitz, Harhoff, and Weber 2010). Severalscholars (e.g., Fayolle, Gailly, and Lassas-Clerc2006; Weber 2012) suggest that the TPB isappropriate for the evaluation of EEPs such asentrepreneurship courses. The main purpose ofsuch an intervention is to bring about a changein students’ entrepreneurial attitudes and inten-tions, and the TPB promises to deliver a soundframework for assessing this change systemati-cally. The TPB has been empirically used bysome researchers to assess the impact of EEPson the students’ EI, and its value has beensuccessfully demonstrated (Fayolle, Gailly, andLassas-Clerc 2006; Souitaris, Zerbinati, andAl-Laham 2007). As such, the TPB is consideredto provide a useful framework for both analyz-ing how EEPs might influence students withregard to their EI and, in particular, for definingand measuring relevant criteria.

Entrepreneurship Education Effectson EIs

Krueger and Carsrud (1993) were the first toapply the TPB in the specific context of entre-preneurship education. They pointed out thatan education program can have an impact onthe antecedents of intention identified by theTPB. Fayolle, Gailly, and Lassas-Clerc (2006)found that although entrepreneurship educa-tion has a strong and measurable effect onstudents’ EI, it has a positive, but not verysignificant, impact on their PBC. Souitaris,Zerbinati, and Al-Laham (2007) used the TPB inorder to test the impact of EEPs on the attitudesand intentions of science and engineering stu-dents. They found that EEPs significantlyincreased students’ EI and subjective norms.However, they did not find a significant rela-tionship between EEPs and attitudes and PBC,whereas Peterman and Kennedy (2003) andAthayde (2009) found a positive effect of EEPson intentions and perceived feasibility, or ATE,among high-school students. Walter and Dohse(2012) reported that EEPs were positivelyrelated only to ATE, not to SN or PBC. Resultsregarding entrepreneurship education initia-tives are therefore somewhat inconclusive, andmore detailed research is needed to get a fullunderstanding of the relationship betweenentrepreneurship education and attitudes/intentions. Notably, in their recent meta-analysis, Martin, McNally, and Kay (2013)found overall positive effects of EEPs on

KARIMI ET AL. 5

knowledge and skill, perceptions of entrepre-neurship, and entrepreneurship outcomes.Thus, we propose that

H4: Students who have followed an EEP willhave higher (a) SN, (b) ATE, (c) PBC, and(d) EI after the program than before theprogram.

H4e: Students whose SN, ATE, and PBC haveincreased will also have increased theirEI.

Entrepreneurship Education Effects onOpportunity Identification

If entrepreneurs are to be successful in cre-ating and operating new ventures, they mustnot only develop an EI but also be successful atdiscerning opportunities that others ignore orfail to notice and then exploit these opportuni-ties in a timely and effective manner (Dutta, Li,and Merenda 2011). Therefore, developingopportunity identification abilities is a keyelement of the entrepreneurship process, andentrepreneurship education should enhancethis competency (Linan, Rodríguez-Cohard, andRueda-Cantuche 2011; Lumpkin, Hills, andShrader 2004). According to the entrepreneur-ship education literature, opportunity identifi-cation could and should be taught, and itshould be a central topic in programs that aimto train future entrepreneurs (Saks and Gaglio2002). Along the same lines, DeTienne andChandler (2004) state that the entrepreneurshipclassroom is an appropriate place for fosteringthe skills required to enhance opportunity iden-tification competency. Despite a growingamount of literature on opportunity identifica-tion and its importance in the entrepreneurshipprocess, there is a dearth of research regardingthe effects of education on students’ ability toidentify business opportunities. The results of astudy by DeTienne and Chandler (2004) indi-cate that entrepreneurship education led to theidentification of more opportunities and moreinnovative opportunities. Munoz, Mosey, andBinks (2011) also reported that entrepreneur-ship education develops students’ opportunityidentification capabilities. Moreover, entrepre-neurship education can increase the entrepre-neurial knowledge of students (Martin,McNally, and Kay 2013), and it has been indi-cated that there is a positive relationshipbetween entrepreneurial knowledge and iden-

tification of entrepreneurial opportunities(Shepherd and DeTienne 2005). Thus, wepropose that

H5: Students who have followed an EEP willhave higher OIP after the program thanbefore the program.

Elective versus Compulsory EntrepreneurshipEducation. As already mentioned, empiricalstudies have yielded mixed results aboutthe effects of EEPs on entrepreneurship.Oosterbeek, van Praag, and Ijsselstein (2010)and von Graevenitz, Harhoff, and Weber (2010)found that the EEPs had a negative impact onEI. Both studies examined compulsory EEPs.Oosterbeek, van Praag, and Ijsselstein (2010)argued that the effects of EEPs may have beennegative because participation in EEPs wascompulsory. In this study, we assess the effectsof two types of EEPs (voluntary, or elective,and compulsory EEPs) on students’ EI. Com-pulsory programs are given to every studentenrolled in a certain degree program; therefore,they include both those interested and thoseuninterested in entrepreneurial activity andeducation. However, participants in electiveEEPs have an interest in entrepreneurship edu-cation and seek out further knowledge andskills in entrepreneurship. Moreover, motivatedstudents will more actively participate in learn-ing activities than students forced to take thecourse. Therefore, we can expect that an elec-tive EEP has a greater influence on participantsthan does a compulsory one.

H6: An elective EEP will have a greater effecton students’ ATE, SN, PBC, OIP, and EI com-pared with a compulsory EEP.

Research MethodEEPs. Over the past decades, many develop-ing countries including Iran have faced variouseconomic problems, in particular the excessivenumber of university graduates unable to findgovernment or private sector work opportuni-ties. Over the last decade, Iran has expressedincreasing interest in various entrepreneur-ship fields (in higher education settings,policymaking, and business) as a fundamentalsolution for the unemployment problem andimproving the economy. The government isspending more than ever to promote andencourage entrepreneurship and innovation.Accordingly, measures and mechanisms have

JOURNAL OF SMALL BUSINESS MANAGEMENT6

been proposed to develop entrepreneurshipin the public and private sectors as well as inuniversities. The first official step was taken in2000 with the establishment of a comprehen-sive program for entrepreneurship develop-ment in universities, called KARAD, as part ofthe Third Economic and Social DevelopmentProgram. The main goals of KARAD were topromote an entrepreneurial spirit and culturein academic communities; familiarize studentswith entrepreneurship as a career choice and asspecific facets aimed to encourage and trainthem on how to prepare a business plan; andstart and manage a new business. To achievethis goal, several programs and strategies wereconsidered including establishing entrepre-neurship centers and introducing entrepreneur-ship courses such as “fundamentals ofentrepreneurship” into undergraduate educa-tion (Karimi et al. 2010).

“Fundamentals of entrepreneurship” as acompulsory or elective course is taught toundergraduate students in their last two yearsof college in various faculties/departments. Itaims to increase university graduates’ knowl-edge about entrepreneurship, influencing theirentrepreneurial attitudes and intentions, andencourage them to be job creators rather thanjob seekers. According to Linan’s (2004) EEPcategorization, these criteria allow the course inwhich this study’s survey was conducted to beclassified in the category of “entrepreneurialawareness education.” Although the coursedescription is almost the same at every univer-sity, educators might use various teachingmaterials and methods for this course. Themethods most often employed are lectures,readings, class discussion, business plans, casestudies, and guest speakers.

Participants and Procedures. During the2010–2011 academic year, an ex ante and expost survey was used to measure the change instudent EI and opportunity identification per-ceptions over approximately a four-monthperiod in “fundamentals of entrepreneurship”courses at six Iranian universities. Our researchused a quantitative method, including a ques-tionnaire that was handed out at the beginningof the first session (t1) and at the end of thefinal session (t2) of the courses. Undergraduatestudents who enrolled in the entrepreneurshipcourses at six Iranian public universities servedas the sample for the study (n = 320). Thereason for including several different universi-

ties was the objective of covering a wide rangeof different class characteristics and of differentrankings of Iranian universities. As not all thestudents in the university were allowed to takeentrepreneurship courses, respondents for ourquestionnaire were selected on a purposivebasis. The students surveyed were told that thequestionnaires were for research purposes onlyand that their answers would not affect theircurriculum in any way; participation wasalways presented as a voluntary choice. In thefirst survey (t1), 275 students participated(response rate of 86 percent), and in the secondsurvey (t2), 240 students (response rate of 75percent). We were able to match the two ques-tionnaires (at t1 and at t2) for 205 students.These represent 64 percent of total enrollmentin the entrepreneurship courses at the selecteduniversities. The sample consisted of 86 malestudents (42 percent) and 119 female students(58 percent), with ages ranging from 19 to 31,with a mean of 22.08 years. There is a greaterproportion of females in the sample becausemore females than males enroll in the degreeswhere the data were collected. There was nocontrol group; only students participating inthe course filled out the two questionnaires. Ingeneral terms, the breakdown of the sampleaccording to college major is as follows: agri-cultural sciences (49.8 percent), engineeringsciences (21.5 percent), Humanistic Science(21.5 percent), and Basic Sciences (7.2percent).

Measurement of Variables. All construct mea-sures were adopted from existing scales. Allitems (aside from demographic characteristics)were measured using a seven-point Likert scaleranging from 1 representing “strongly disagree”to 7 representing “strongly agree.” These itemsand the sources from which the items wereadopted are summarized in Table 1. Severalcontrol variables were used in the study: age,gender (coded as 1 = male and 0 = female), uni-versity ranking (coded as 3 = high ranking,2 = intermediate ranking, and 1 = low ranking),university (categorical variable for the sixselected universities), and academic major (cat-egorical variable for the four academic majors).

Statistical Analysis. The obtained data wereanalyzed using SPSS 18 (SPSS Inc., Chicago,Illinois, USA) and AMOS 18 (IBM, New York,USA). As a first step, an exploratory factoranalysis (EFA) was performed on the items.

KARIMI ET AL. 7

Tab

le1

Det

ails

,R

elia

bil

ity,

and

Val

idit

yof

the

Mea

sure

s

Const

ruct

Res

earc

hR

efer

ence

No.

of

Item

αC

RA

VE

Pre

Post

Pre

Post

Pre

Post

Entr

epre

neu

rial

Inte

ntions

Linan

and

Chen

(200

9)(e

.g.,

“Ihav

eve

ryse

riousl

yth

ough

tof

star

ting

afirm

”)6

0.84

0.85

0.89

0.90

0.50

0.52

Attitude

tow

ard

Entr

epre

neu

rship

Linan

and

Chen

(200

9)(e

.g.,

“Bei

ng

anen

trep

reneu

rim

plies

more

adva

nta

ges

than

dis

adva

nta

ges

tom

e”).

50.

780.

850.

860.

910.

550.

66

Subje

ctiv

eN

orm

Adopte

dfr

om

Kolv

erei

d(1

996)

,w

hic

hhas

bee

nuse

din

Kolv

erei

dan

dIs

akse

n(2

006)

,K

rueg

er,

Rei

lly,

and

Car

srud

(200

0),

and

Souitar

is,

Zer

bin

ati,

and

Al-La

ham

(200

7).

This

scal

ein

cluded

two

separ

ate

ques

tions:

bel

ief

(e.g

.,“I

bel

ieve

that

my

close

stfa

mily

thin

ks

that

Ish

ould

star

tm

yow

nbusi

nes

s”)

and

motiva

tion

toco

mply

(e.g

.,“I

care

about

my

close

stfa

mily’

sopin

ion

with

rega

rdto

me

star

ting

my

ow

nbusi

nes

s”).

The

bel

ief

item

sw

ere

reco

ded

into

abip

ola

rsc

ale

(fro

m−3

to+3)

and

multip

lied

with

the

resp

ective

motiva

tion-to-c

om

ply

item

s.The

subje

ctiv

enorm

vari

able

was

calc

ula

ted

by

addin

gth

eth

ree

resu

lts

and

div

idin

gth

eto

tal

score

by

thre

e.

60.

820.

910.

900.

950.

580.

74

Per

ceiv

edB

ehav

iora

lContr

ol

Linan

and

Chen

(200

9)(e

.g.,

“Sta

rtin

ga

firm

and

kee

pin

git

viab

lew

ould

be

easy

for

me.

”)6

0.88

0.88

0.93

0.93

0.60

0.61

Opport

unity

Iden

tifica

tion

Per

ception

Sele

cted

from

the

lite

ratu

reon

opport

unity

iden

tifica

tion

(Hills

1995

;N

icola

ou

etal

.20

09;

Ozg

enan

dB

aron

2007

;Si

ngh

etal

.19

99;

Ucb

asar

anet

al.

2003

),ga

ugi

ng

both

the

self-p

erce

ived

ability

tore

cogn

ize

opport

unitie

s(e

.g.,

“Iam

able

tore

cogn

ize

new

busi

nes

sopport

unitie

sin

the

mar

ket

”)an

dal

ertn

ess

toopport

unitie

sw

hen

they

exis

t(“

Ihav

ea

spec

ial

aler

tnes

sor

sensi

tivi

tyto

war

dbusi

nes

sopport

unitie

sin

my

envi

ronm

ent”

)

90.

830.

810.

890.

880.

460.

42

AV

E,

aver

age

vari

ance

extr

acte

d;

CR,

const

ruct

reliab

ility.

JOURNAL OF SMALL BUSINESS MANAGEMENT8

EFA helps explain the variability among observ-able variables and thus served to eliminateproblematic items with significant cross load-ings or loading to the wrong factor; itemsremaining after this filtering exercise wereselected to build each of the constructs used inthe structural equation modeling (SEM) in thesecond step. SEM was employed to define therelationship between EI and its antecedents(H1) and to test the relationships between PBC,ATE, OIP, and EI (H2 and H3). Furthermore,the paired samples t-test was used to test theimpact of the programs on the students’ entre-preneurial attitudes, OIP, and intentions (H4and H5). Finally, the independent samplest-test was utilized to compare the effects ofelective and compulsory courses (H6).

ResultsSEM

The SEM approach was used to validate theresearch model and test the effects in thehypotheses. According to Hair et al. (2006), it isappropriate to adopt a two-step approach inSEM: (1) the assessment of the measurementmodel and (2) the assessment of the structuralmodel.

The Assessment of theMeasurement Model

The first step, involving confirmatory factoranalysis, was to test the goodness-of-fit indices,and the reliability and validity of the proposedmeasurement model. The measurement modelincludes 23 items describing five latent con-structs: ATE, SN, PBC, OIP, and EI. Goodness-of-fit indicators suggest a very good fit of theproposed model for the pretest (χ2 = 284.432,p = .001; χ2/df = 1.323; GFI = 0.893; TLI = 0.962;CFI = 968; IFI = 0.968; RMSEA = 0.04) and post-test data (χ2 = 278.022, p = .003; χ2/df = 1.287;GFI = 0.898; TLI = 0.972; CFI = 0.976; IFI =0.977; RMSEA = 0.038). Therefore, on the basisof the results obtained, the hypothesized modelof five constructs is a suitable measurementmodel for this study.

The convergent and discriminant validitiesof the constructs can be assessed by referring tothe measurement model. According to Fornelland Larcker (1981), convergent validity isevaluated for the measurement model based onthree criteria: (1) factor loadings; (2) the scalecomposite or construct reliability (CR); and (3)the average variance extracted (AVE). The find-ings showed that all items’ critical ratio values

exceed 6.117 (p < .01), and all loadings aremore than 0.5. Moreover, all constructs had aconstruct reliability (CR) value, ranging from0.86 to 0.95, higher than the recommendedlevel of 0.70. With respect to the AVE estimate,the results revealed that the AVE estimate forall constructs is above or close to the recom-mended threshold of 0.50 (Table 1). Discrimi-nant validity was assessed by comparing thesquare root of the AVE for a given constructwith the correlations between that constructand all other constructs. The square roots of theAVE of each construct, listed on the diagonal ofTable 2, all exceed the correlation sharedbetween the construct and other constructs inthe model, indicating adequate discriminantvalidity between each construct.

The Assessment of the Structural ModelWith the construct validity and reliability

measures established, all the constructs wereused as input to form a structural model repre-senting the hypothesized model depicted inFigure 1. As shown in Figure 2, the overallgoodness-of-fit statistics show that the structuralmodel fits the pretest and post-test data well.Having assessed the fit indices for the measure-ment models and structural models, the esti-mated coefficients of the causal relationshipsbetween constructs were examined. Table 3shows the coefficient of each hypothesized pathand its corresponding CR (known as thet-value). It can be seen from this table that thepredictive positive effect of SN on EI is sup-ported (pretest: β = 0.22, CR = 3.299, p < .001;post-test: β = 0.20, CR = 3.056, p < .01), an effectwhich corresponds to H1a. H1b is also sup-ported: ATE has a positive effect on EI(pretest: β = 0.28, CR = 3.969, p < .001; post-test:β = 0.30, CR = 4.078, p < .001). As the PBCalso has a significant effect on EI (pretest:β = 0.45, CR = 5.684, p < .001; post-test:β = 0.47, CR = 5.212, p < .001), H1c is sup-ported. The results also show that OIP positivelyinfluence EI (pretest: β = 0.22, CR = 3.169,p < .01; post-test: β = 0.14, CR = 1.970, p < .05),supporting H2. H3a and H3b presume that ATEand PBC would influence OIP. As hypothesized,the estimate of the paths coefficients of ATE(pretest: β = 0.20, CR = 2.261, p < .05; post-test: β = 0.21, CR = 2.414, p < .05) and PBC(pretest: β = 0.31, CR = 3.636, p < .001; post-test:β = 0.34, CR = 3.481, p < .001) on OIP was posi-tive and statistically significant, which providedsupport for H3a and H3b. Overall, the TPB

KARIMI ET AL. 9

Tab

le2

The

Corr

elat

ion

Mat

rix

and

Dis

crim

inan

tV

alid

ity

Var

iable

Mea

nS.D

.1

23

45

67

89

10

11

12

13

14

15

16

17

18

EI

(t1)

4.85

1.43

(0.7

1)

ATE

(t1)

5.13

0.95

30.

33**

(0.7

4)

SN(t

1)2.

255.

670.

36**

0.11

(0.7

6)

PB

C(t

1)4.

351.

320.

60**

0.21

**0.

24**

(0.7

7)

OIP

(t1)

4.31

1.15

0.43

**0.

25**

0.15

*0.

32**

(0.6

9)

EI

(t2)

5.06

1.31

0.47

**0.

130.

25**

0.31

**0.

28**

(0.7

2)

ATE

(t2)

5.22

1.04

0.25

**0.

32**

0.16

*0.

17*

0.21

*0.

57**

(0.8

1)

SN(t

2)4.

077.

070.

24**

0.13

0.34

**0.

17*

0.18

*0.

43**

0.30

**(0

.86)

PB

C(t

2)4.

681.

270.

38**

0.12

0.09

0.40

**0.

21*

0.67

**0.

47**

0.42

**(0

.78)

OIP

(t2)

4.38

0.95

40.

29**

0.08

0.12

0.23

**0.

35**

0.42

**0.

34**

0.23

**0.

41**

(0.6

5)

EI

(t2-

t1)

0.21

31.

66−0

.57*

*−0

.21*

−0.1

3−0

.32*

*−0

.18*

0.46

**0.

28**

0.16

*0.

24**

0.10

ATE

(t2-

t1)

0.08

31.

31−0

.05

−0.5

4**

0.06

−0.0

2−0

.02

0.40

**0.

64**

0.16

*0.

32**

0.24

**0.

42**

SN(t

2-t1

)1.

827.

86−0

.04

0.05

−0.4

4**

−0.0

20.

060.

22**

0.16

*0.

69**

0.33

**0.

130.

25**

0.10

PB

C(t

2-t1

)0.

337

1.65

−0.2

2**

−0.0

9−0

.14*

−0.5

7**

−0.1

20.

32**

0.26

**0.

22**

0.53

**0.

16*

0.52

**0.

35**

0.32

**O

IP(t

2-t1

)0.

074

1.41

−0.1

8*−0

.18

−0.0

5−0

.12

−0.6

6**

0.07

0.07

0.01

130.

47**

0.25

**0.

21**

0.04

0.23

**A

ge22

.08

1.72

0.15

*0.

110.

020.

070.

010.

08−0

.03

0.05

0.06

−0.0

2−0

.07

−0.1

00.

03−0

.02

−0.0

3G

ender

0.42

0.49

0.06

−0.2

2**

−0.0

70.

080.

04−0

.09

−0.0

8−0

.04

−0.0

10.

13−0

.12

0.10

0.02

−0.0

70.

060.

05Se

lect

ion

0.37

0.46

0.04

0.09

0.02

0.11

0.02

0.22

**0.

070.

080.

130.

090.

14*

−0.0

20.

070.

020.

05−0

.30*

*−0

.20*

Ran

kin

g2.

140.

92−0

.09

−0.0

3−0

.01

−0.0

6−0

.04

0.15

*0.

030.

110.

24*

0.17

*0.

100.

040.

110.

100.

12−0

.22*

*−0

.06

0.22

**

*p<

.05.

**p

<.0

1.n

=20

5;Tw

o-tai

led

test

sof

sign

ifica

nce

wer

euse

d.

The

squar

ero

ots

of

AV

Ees

tim

ates

are

inbold

on

the

dia

gonal

.A

TE,

attitu

de

tow

ard

entr

epre

neu

rship

;A

VE,

aver

age

vari

ance

extr

acte

d;

EI,

entr

epre

neu

rial

inte

ntion;

OIP

,opport

unity

iden

tifica

tion

per

ception;

PB

C,

per

ceiv

edbeh

avio

ral

contr

ol;

S.D

.,st

andar

ddev

iation;

SN,

subje

ctiv

enorm

s.

JOURNAL OF SMALL BUSINESS MANAGEMENT10

model explained respectively 60 and 63 percentof the variance in the EI in the pretest andpost-test samples (R2

pretest = 0.60; R2post-test = 0.63).

To test the relationships between the controlvariables and the change in ATE, SN, PBC, EIand OIP, a correlation and a general linearmodel (GLM) procedure were employed. Theresults of correlation indicated that age, gender,

and university ranking did not have significantcorrelations with the difference values of ATE,SN, PBC, EI, and OIP (Table 2). The GLM resultsalso showed no significant differences in ATE,SN, PBC, EI, and OIP, controlling for the cat-egorical variables (university and academicmajor), suggesting that the findings of this studywere not affected by these control variables. In

Figure 1The Proposed Research Model

H3a

H5

H4a

H2

H3b

H4c

H4bEEPs

OIP

H1b

H1c

H1a

PBC

EIATE

SN

ATE, Attitude toward Entrepreneurship; EEP, Entrepreneurship Education Programs; EI,Entrepreneurial Intention; OIP, Opportunity Identification Perception; PBC, PerceivedBehavioral Control; SN, Subjective Norms.

Figure 2The Proposed Research Model

R2 = 0.60/0.63

R2 = 0.18/0.24

H3a = 0.20/0.22

H5

H4a

H2 = 0.22/0.14

H3b = 0.31/0.34

H4c

H4bEEPs

OIP

H1c = 0.45/0.47

H1b = 0.28/0.30

H1a = 0.22/0.20

0

PBC

7

EIATE

SN

Pretest/Post-Test; ATE, Attitude toward Entrepreneurship; EEP, Entrepreneurship Educa-tion Programs; EI, Entrepreneurial Intention; OIP, Opportunity Identification Perception;PBC, Perceived Behavioral Control; SN, Subjective Norms. Goodness-of-Fit Indices (Pretest):χ2 = 284.862; χ2/df = 1.319; GFI = 0.893; TLI = 0.963; CFI = 0.968; IFI = 0.969;RMSEA = 0.040. Goodness-of-Fit Indices (Post-Test): χ2 = 278.125; χ2/df = 1.282;GFI = 0.897; TLI = 0.973; CFI = 0.977; IFI = 0.977; RMSEA = 0.037.

KARIMI ET AL. 11

Tab

le3

Res

ult

sof

the

Str

uct

ura

lEquat

ion

Model

ing

Hyp

oth

eses

Tes

ted

Est

imat

e(β

Val

ue)

S.E

.aC

Rb

(t-V

alue)

p

Model

att1

H1a

:Su

bje

ctiv

eN

orm

→Entr

epre

neu

rial

Inte

ntion

0.22

0.01

43.

299

0.00

0**

H1b

:A

ttitude

tow

ard

Entr

epre

neu

rship

→Entr

epre

neu

rial

Inte

ntion

0.28

0.19

13.

969

0.00

0**

H1c

:Per

ceiv

edB

ehav

iora

lContr

ol

→Entr

epre

neu

rial

Inte

ntion

0.45

0.07

15.

684

0.00

0**

H2:

Opport

unity

Iden

tifica

tion

→Entr

epre

neu

rial

Inte

ntion

0.22

0.07

93.

196

0.00

1**

H3a

:A

ttitude

tow

ard

Entr

epre

neu

rship

→O

pport

unity

Iden

tifica

tion

0.20

0.18

62.

261

0.02

4*H

3b:

Per

ceiv

edB

ehav

iora

lContr

ol

→O

pport

unity

Iden

tifica

tion

0.31

0.06

63.

636

0.00

0**

Model

att2

H1a

:Su

bje

ctiv

eN

orm

→Entr

epre

neu

rial

Inte

ntion

0.20

0.01

23.

056

0.00

2**

H1b

:A

ttitude

tow

ard

Entr

epre

neu

rship

→Entr

epre

neu

rial

Inte

ntion

0.30

0.08

44.

078

0.00

0**

H1c

:Per

ceiv

edB

ehav

iora

lContr

ol

→Entr

epre

neu

rial

Inte

ntion

0.47

0.09

65.

212

0.00

0**

H2:

Opport

unity

Iden

tifica

tion

→Entr

epre

neu

rial

Inte

ntion

0.14

0.09

71.

970

0.04

9*H

3a:

Attitude

tow

ard

Entr

epre

neu

rship

→O

pport

unity

Iden

tifica

tion

0.22

0.07

52.

414

0.01

6*H

3b:

Per

ceiv

edB

ehav

iora

lContr

ol

→O

pport

unity

Iden

tifica

tion

0.34

0.07

43.

481

0.00

0**

*p<

.05.

**p

<.0

1.a S

.E.

isan

estim

ate

of

the

stan

dar

der

ror

of

the

cova

rian

ce.

bC.R

.is

the

critic

alra

tio

obta

ined

by

div

idin

gth

eco

vari

ance

estim

ate

by

its

stan

dar

der

ror.

JOURNAL OF SMALL BUSINESS MANAGEMENT12

order to test H4e, we employed a correlationanalysis, as summarized in Table 2. As expected,a change in SN, ATE, PBC, and OIP was signifi-cantly related to an increased intention to startone’s own business. Therefore, H5e wasaccepted.

Impact of EEPs on Students. In order to assessthe impacts of the entrepreneurship courses onthe students’ entrepreneurial attitudes, inten-tions, and OIP, we conducted the pairedsamples t-test. Table 4 summarizes the resultsof this test. The results showed a positive andsignificant difference in the pretest (M = 2.25)and post-test value (M = 4.08) of SN (t = 3.28,p = .001 < .01). The significant differencebetween the pretest (M = 4.35) and post-testdata (M = 4.68) was also evident for PBC(t = 2.92, p = .004 < .01). However, the meanscore of ATE in the pretest sample (M = 5.13)was not significantly different from the meanscore in the post-test sample (M = 5.22)(t = 0.904, p = .367 > .05). In addition, for OIP,the mean score in the pretest sample (M = 4.31)was not significantly different from that in thepost-test sample (M = 4.38). The results alsorevealed that the post-test value of EI(M = 5.06) was increased compared withthe pretest value (M = 4.851), though thisincrease was not very significant (t = 1.83,p = .068 > .05). The GLM procedure of ANOVAalso indicated significant differences betweenthe pre and post-test values for SN (F = 10.77,p = .001) and PBC (F = 8.51, p = .004) but not

for EI, ATE, and OIP. The results thereforedemonstrate that there are positive and signifi-cant differences in pre and post-test values ofSN and PBC, confirming H4a and H4c;however, there are not significant differences inpre and post-test values of ATE, OIP, and EI,rejecting H4b, H4d, and H5.

Differences in EEP Impacts in Relation to theSelection Mode. In order to examine whetherattitudes, intention, and opportunity identifica-tion change are equally likely for the two typesof EEPs (elective versus compulsory), we com-pared the effects of these different programs byusing the independent samples t-test. For eachstudent, a gain score was calculated for each ofthe five scales, which consisted of the student’sscore on the scale in the post-test survey minushis/her score on the same scale in the pretestsurvey. As can be seen in Table 5, in the pretestsample, the students in elective courses exhib-ited higher scores on all five scales comparedwith the students in compulsory courses, butnone of these differences is statistically signifi-cant. In the post-test sample, the two groupsdiffered significantly in their EI, such that thestudents in the elective courses have greater EIthan the students in the compulsory courses.The elective courses had a significantly greaterpositive impact on the students’ EI as the gainin EI was significantly higher for the students inthe elective courses than for the students in thecompulsory courses. The results of the pairedsamples t-test (Table 6) also showed significant

Table 4Results of Paired t-Test for the Program Impacts (n = 205)

Scale Pretest Post-Test Difference

M S.D. M S.D. t(204) p

EI 4.85 1.43 5.06 1.32 1.83 0.068SN 2.25 5.67 4.08 7.07 3.28 0.001*ATE 5.13 0.95 5.22 1.04 0.90 0.367PBC 4.35 1.32 4.68 1.28 2.92 0.004*OIP 4.31 1.15 4.38 0.97 0.75 0.453

*p < .01.ATE, attitude toward entrepreneurship; EI, entrepreneurial intention; OIP, opportunity identifi-cation perception; PBC, perceived behavioral control; S.D., standard deviation; SN, subjectivenorms.

KARIMI ET AL. 13

Tab

le5

Dif

fere

nce

sin

the

EEP

Impac

tsA

ccord

ing

toSel

ecti

on

Mode

(Com

puls

ory

vers

us

Ele

ctiv

e)

Sca

leP

rete

stP

ost

-Tes

tG

ain

Com

puls

ory

(n=

127)

Ele

ctiv

e(n

=78)

Dif

fere

nce

Com

puls

ory

(n=

127)

Ele

ctiv

e(n

=78)

Dif

fere

nce

Com

puls

ory

(n=

127)

Ele

ctiv

e(n

=78)

Dif

fere

nce

MS.

D.

MS.

D.

t(203)

pM

S.D

.M

S.D

.t(

203)

pM

S.D

.M

S.D

.t(

203)

p

EI

4.80

1.39

4.93

1.50

−0.5

90.

550

4.84

1.33

5.44

1.22

−3.2

30.

001*

0.03

1.67

0.51

1.59

−2.0

10.

046*

SN2.

195.

772.

355.

53−0

.19

0.84

43.

654.

064.

777.

08−1

.10

0.27

21.

468.

212.

427.

54−0

.84

0.40

3A

TE

5.07

0.96

5.24

0.93

−1.2

50.

212

5.16

1.04

5.31

1.04

−1.0

50.

297

0.09

1.32

0.07

1.32

0.08

0.93

8PB

C4.

241.

274.

521.

39−1

.52

0.13

14.

551.

284.

891.

25−1

.84

0.06

80.

321.

700.

371.

57−0

.20

0.83

9O

IP4.

301.

164.

331.

15−0

.18

0.86

14.

320.

994.

490.

93−1

.28

0.20

30.

021.

410.

171.

40−0

.74

0.46

2

*p<

.05.

**p

<.0

1.A

TE,at

titu

de

tow

ard

entr

epre

neu

rship

;EI,

entr

epre

neu

rial

inte

ntion;O

IP,opport

unity

iden

tifica

tion

per

ception;PB

C,per

ceiv

edbeh

avio

ral

contr

ol;

S.D

.,st

andar

ddev

iation;

SN,

subje

ctiv

enorm

s.

JOURNAL OF SMALL BUSINESS MANAGEMENT14

differences in pre and post-values of EI, SN,and PBC for the elective courses, but for thecompulsory courses, they showed significantdifferences only in pre- and post-values of SNand PBC.

DiscussionThe purpose of this study was to assess the

impact of EEPs on students’ EI, drawing on theTPB. Moreover, the proposed model incorpo-rates the perception of opportunity identifica-tion into the TPB. To address this purpose, weemployed an ex ante and ex post survey, with205 participants in elective and compulsoryEEPs at six Iranian universities.

The findings were in line with earlierstudies on the effects of EEPs but neverthelessalso present some differences. We found con-firmation for the impact of (both types of) EEPson SN (Souitaris, Zerbinati, and Al-Laham 2007;Weber 2012). For both voluntary and compul-sory EEPs, the postprogram mean value of PBCwas increased in relation to the preprogramvalue (Peterman and Kennedy 2003; Weber2012), something that Souitaris, Zerbinati, andAl-Laham (2007) were not able to confirm.However, this study did not provide evidencethat EEPs have a significant effect on students’EI in the sample as a whole. This conflicts withthe idea that participating in EEPs fosters indi-

viduals’ intentions to start a new business(Souitaris, Zerbinati, and Al-Laham 2007).Notably, the comparison of elective and com-pulsory EEPs indicated that intention change isnot equally distributed across these programs.The elective EEPs had a significantly greaterpositive impact on students’ EI. Moreover, thisstudy could not find a significant effect ofeither elective or compulsory EEPs on ATE:The programs failed in developing students’ATE. This finding is in line with the results ofSouitaris, Zerbinati, and Al-Laham (2007), andWeber (2012), but it is not consistent with thefindings of Peterman and Kennedy (2003).Contrary to our expectation, neither type ofEEP led to a significant increase in OIP, whichcontradicts the results of DeTienne andChandler (2004).

The significant increase in the mean value ofSN may reflect the emphasis within both pro-grams on teamwork (e.g., working together inteams of four to six to create business plans)and on giving students the opportunity to builda network with entrepreneurially-mindedfriends and peers, and with entrepreneurs. Apossible explanation for the increase in PBCcould be related to mastery experience andvicarious experience (role modeling), whichmight be gained by the students during theprograms. Most EEPs try to emphasize the

Table 6Results of Paired t-Test for the Impacts of Elective and

Compulsory Programs

Scale Compulsory (n = 127) Elective (n = 78)

Pretest Post-test Difference Pretest Post-test Difference

M S.D. M S.D. t p M S.D. M S.D. t p

EI 4.80 1.39 4.84 1.33 0.21 0.833 4.93 1.50 5.44 1.22 2.80 0.006**SN 2.19 5.78 3.65 7.06 2.00 0.047* 2.35 5.53 4.77 7.08 2.83 0.006**ATE 5.07 0.96 5.16 1.04 0.76 0.450 5.24 0.93 5.31 1.01 0.49 0.622PBC 4.24 1.27 4.55 1.28 2.10 0.037* 4.52 1.39 4.89 1.25 2.06 0.043*OIP 4.30 1.16 4.32 0.99 0.14 0.892 4.33 1.15 4.49 0.93 1.05 0.298

*p < .05.**p < .01.ATE, attitude toward entrepreneurship; EI, entrepreneurial intention; OIP, opportunity identifi-cation perception; PBC, perceived behavioral control; S.D., standard deviation; SN, subjectivenorms.

KARIMI ET AL. 15

“learning-by-doing” component (such aswriting a business plan and field work) and toexpose the students to the real world. In addi-tion, the teachers tell success stories aboutentrepreneurs or invite guest entrepreneurs asspeakers who can serve as successful rolemodels for students.

The reason for the lack of a significant effectof EEPs on ATE is not fully clear, and thiswarrants future research. A few possibilities areexplored here. The first plausible explanation isthat the students had relatively high scores forthis variable at the beginning of the program,so there was not much room left for improvingtheir attitudes. It should be noted that smalldifferences in the mean do not imply that thereis no change at all in these variables. Anotherexplanation could be related to the programdesign. EEPs may have not been designed suf-ficiently well with regard to persuasion andattitude change.

The effects of compulsory EEPs on EI mayhave been insignificant because participationwas compulsory, as the comparison analysisshowed. A second possibility is that studentsmay have gained a realistic picture of boththemselves and being an entrepreneur anddecided, in this light, that they do not want tobecome an entrepreneur. In this sense, wecannot say that the programs did not affectstudents’ EI; the programs may have enhancedthe awareness of entrepreneurship amongthese students and led them to assess theirfuture as entrepreneurs. A similar explanationwas provided by Oosterbeek, van Praag, andIjsselstein (2010), who argue that the reasonmay have been that some participants had losttheir excessive optimism about entrepreneur-ship and rejected the idea of becoming anentrepreneur after the program had finished.von Graevenitz, Harhoff, and Weber (2010) alsoargue that EEPs provide individuals withsignals about their entrepreneurial ability andaptitude. As a result, some students maybecome aware that they are not well suited forentrepreneurship.

With respect to opportunity identification,one explanation for this result could be relatedto the fact that despite the emphasis of EEPs onopportunity identification, most teachers didnot pay the necessary attention to fostering thiscompetency in their classes. The results ofinterviews with some students and teachersafter the post-test measurement indicated thatthis competency was often ignored or received

less emphasis during the courses. Neck andGreene (2011) point out that the majority ofentrepreneurship courses are focused on theexploitation of opportunities and assume thatthe opportunity has already been identified.Where this is the case, very little time andattention are given to creativity, the idea gen-eration process, and how to identify new busi-ness opportunities.

ImplicationsTheoretical Implications. This study hasseveral theoretical implications. It providesfurther supporting evidence for the applicationof the TPB in predicting and understanding EIin non-Western countries such as Iran. Further-more, this study contributes to the TPB byexamining the effect of entrepreneurship edu-cation as an exogenous influence on EI and itsantecedents, and it shows that the TPB canprovide a useful framework to assess the effec-tiveness of EEPs. In addition, this study devel-ops and extends the TPB model byincorporating the OIP as a proximal cause ofEI, and it examines the relationship betweenthis variable and EI and its antecedents.

Practical Implications. In terms of practice,the study provides valuable information andinsight for those who formulate, deliver, andevaluate educational programs aimed atincreasing the EI of students. The findings indi-cate that PBC is the strongest predictor of EI,and as this study confirmed, PBC can be fos-tered through EEPs. Therefore, educatorsshould focus more on the use of appropriateteaching methods in order to enhance students’PBC more effectively. According to Bandura(1997), an individual’s sense of self-efficacy canbe built and strengthened in four ways: masteryexperience or repeated performance accom-plishments, vicarious experience or modeling,social persuasion, and judgments of one’s ownphysiological states, such as arousal andanxiety. Entrepreneurship education can play asignificant role in developing students’ entre-preneurial self-efficacy in these ways by apply-ing the educational activities and teachingmethods presented next (Segal, Schoenfeld,and Borgia 2007). Our findings stronglysuggest that participation in both elective andcompulsory EEPs can positively influence stu-dents’ PBC or self-efficacy, confirming that uni-versities can shape and foster entrepreneurialself-efficacy through EEPs.

JOURNAL OF SMALL BUSINESS MANAGEMENT16

Educational activities providing “real-world”experience or “virtual reality” experiences inthe classroom, including the use of roleplaying, case methods, and business simula-tions, facilitate the development of decision-making skills and strengthen entrepreneurialself-confidence through mastery experiencesor repeated performance accomplishments.Vicarious learning can be increased througheducational activities such as successful entre-preneurs as guest speakers, video profiles ofwell-known entrepreneurs, case studies,student internships, and participation in busi-ness plan competitions. Encouraging com-ments, positive feedback, and praise from—andpersuasive discussions with—teachers and pro-fessionals in educational programs can increaseself-efficacy through social persuasion. Theseactivities can also reduce stress levels andanxiety.

In particular, the findings suggest that uni-versities can develop students’ EI through elec-tive rather than compulsory EEPs. Therefore,educators should differentiate between com-pulsory courses offered to all students andcourses offered as electives for students whoare interested in entrepreneurship. Accordingto von Graevenitz, Harhoff, and Weber (2010)and Oosterbeek, van Praag, and Ijsselstein(2010), the primary aim for compulsory pro-grams, with a mix of participants interested inentrepreneurship and participants who areuninterested, is a sorting effect: Studentsattending these programs become informedabout entrepreneurship as an alternative careerchoice and gain more realistic perspectives,regarding both themselves and what it takes tobe an entrepreneur. Therefore, after complet-ing EEPs, some students will learn that they arewell suited for entrepreneurship and bestrengthened in their decision to become entre-preneurs, whereas others will learn that theyare not. In elective courses, on the other hand,self-selection will lead to a higher level of EIand increase the likelihood of participantsbecoming entrepreneurs.

The findings also showed that SN influencesEI, and we can improve SN through EEPs.Some previous studies (e.g., Linan and Chen2009) found that SN also has a relevant effecton EI through ATE and PBC. In particular,in a collectivistic culture such as Iran wherefamily life and relationships with close friendsand relatives are important (Javidan andDastmalchian 2003; Karimi et al. 2013b), SN

appears to play a significant role. Therefore, itis suggested that teaching methods and con-tents specifically designed to improve SNshould be included in EEPs. SN can beimproved by means of teamwork and by pro-viding opportunities for students to build anetwork with entrepreneurial-minded friendsand peers, and with role models and entrepre-neurs (Mueller 2011; Souitaris, Zerbinati, andAl-Laham 2007; Weber 2012). It was concludedthat EEPs did not influence ATE because themean score of this variable was high at thebeginning of EEPs. Therefore, we can suggestthat if an EEP has attendees who are alreadyhighly motivated about entrepreneurship andhave high attitudes and EI, the aim of such aprogram should be “education for start-up”rather than “entrepreneurial awareness educa-tion” (according to the classification by Linan2004). As discussed earlier, the objective of thelatter program is to provide information forstudents about entrepreneurship so that theyconsider entrepreneurship as a possible andalternative choice of career. The formerprogram aims at the preparation of individualsfor running conventional small businesses andfocuses on the practical aspects related to thecreation of a new business, such as how toobtain financing, legal regulations, and taxa-tion (Curran and Stanworth 1989). Entrepre-neurial awareness education can be offered asa compulsory or elective program, whereaseducation for start-up can be offered only as anelective.

Although opportunity identification isthe core of entrepreneurship (Shane andVenkataraman 2000), very little is done to traina student in how discover or create new busi-ness opportunities (Neck and Greene 2011).The findings of the present study also showedthat the EEPs did not significantly influencestudents’ perception of opportunity identifica-tion. Therefore, in both compulsory and elec-tive courses, enhancing this competencyshould be a particularly important componentof entrepreneurship education and a funda-mental design principle in EEPs. In addition,students should be equipped with toolsenabling them to find opportunities and makeopportunities (Neck and Greene 2011;Sarasvathy 2008). Lumpkin, Hills, and Shrader(2004) argue that teaching creativity skillscan enhance opportunity identification compe-tency. According to Sardeshmukh andSmith-Nelson (2011), students’ ability to

KARIMI ET AL. 17

identify new business opportunities can beenhanced by means of a combination of class-room activities (e.g., activities associated withcreativity such as divergent thinking and ideageneration exercises) and experiential activities(e.g., internships and engaging students withcommunity entrepreneurs by way of guest lec-tures by entrepreneurs, mentoring by localentrepreneurs, and live case studies). Anotherfactor which needs to be considered by edu-cators is the role of networking in identifyingopportunities. Social networks have beenfound to be important in the opportunity iden-tification process (Ozgen and Baron 2007).Social networks are significant sources ofknowledge (Johannison 1990) and of newideas (Christensen and Peterson 1990) andhave been associated with the number of per-ceived new opportunities (Hills 1995; Ozgenand Baron 2007; Singh et al. 1999). Therefore,educators should devote attention to develop-ing students’ network skills in EEPs and shouldgive them more opportunities to network withpeers and other entrepreneurs (Lumpkin, Hills,and Shrader 2004).

As mentioned already, policymakers anduniversity faculties should recognize the dif-ferential effects of various types of EEPs andthat the effects will not be the same across allprograms. Although we cannot recommendone type over the other in general terms,policymakers and instructors who want toproduce more and better entrepreneurs whilesubject to cost constraints should keep inmind that elective programs may yieldbetter results than compulsory programs.Policymakers and educators should also beaware that cultural context and values play animportant part in EEPs. Studies show that theIranian culture has changed over the last fourdecades (Tajaddini and Mujtaba 2011). Forinstance, the recent study by Karimi et al.(2013b) reported that although Iranian stu-dents are relational and show great affectiontoward family members, close friends andrelatives (high family collectivism), they alsotend to embrace individualistic values (such aspersonal success and autonomy) to a greaterdegree than the older generations. Javidanand Dastmalchian (2003) also reported thatthe Iranian culture is a mix of family ties andconnections and a high degree of individual-ism, and it has strong orientations towardachievement and performance. Therefore,policymakers and educators should develop

EEPs that accommodate these different cul-tural values.

Limitations and Future ResearchThe current study has several limitations that

provide future research opportunities. Thisstudy assessed only the effects of participatingin the EEPs on intention and opportunity iden-tification; future research should examine thespecific characteristics, design elements, con-tents, and teaching approaches of the EEPs,and their relationships to these outcomes.Future researchers may also address the ques-tion of why the EEPs foster PBC and subjectivenorms but not attitude toward entrepreneur-ship or opportunity identification.

As we did not have control groups tocompare with our treatment groups, we areunable to determine the exact impact of EEPson students’ EI. We can assume that these sig-nificant pretest/post-test differences are theresults of participating in EEPs because thecontent of the EEPs is very specific and notduplicated in other courses; however, the avail-ability of a control group would have strength-ened our findings. It should be noted that wedid not want to conduct an artificial random-ized trial; we preferred a study in a naturalisticacademic setting that would not deprive any ofthe undergraduate students in that departmentof the potential benefits of participating inEEPs.

Finally, future research should focus onthe intention–behavior relationship as thiscrucial link has been studied even less thanthe one between antecedent attitudes and EIs.Consequently, a longitudinal study is recom-mended for future research to be able tocapture the changes in entrepreneurial atti-tudes and intention over time and the subse-quent formation of entrepreneurial behaviorfrom intention.

ConclusionsThis paper aimed to investigate the impact

of EEPs on students’ EI and opportunity iden-tification using the TPB. The data support boththe measurement and the structural model.Our study indicated that the EEPs significantlyinfluenced subjective norms and PBC but thatthese programs did not have significantimpacts on students’ attitude toward entrepre-neurship and their perceptions of opportunityidentification. The study also showed that theelective EEPs significantly increased students’

JOURNAL OF SMALL BUSINESS MANAGEMENT18

EI but that this increase was not significant forthe compulsory EEPs. We recommend thatothers investigate if our findings can be repli-cated in different educational institutions andEEPs, perhaps using designs comparing theoutcomes of EEP participants with those ofnonparticipant groups. As noted earlier, futureresearch might also assess whether differentteaching methods and learning environmentswould have different effects on the outcomesand whether course educator differences suchas skills or academic background would influ-ence the outcomes. In conclusion, this researchprovides evidence that EEPs are effective, butthe current form needs improvement. It isimperative that we begin to understand how toimprove EEP learning outcomes, especiallyregarding opportunity identification. If we donot tackle these issues, we may end up withgraduates who lack the abilities and knowl-edge needed in order to identify new businessopportunities and, as a result, fail in the firststep of the entrepreneurship process. We hopethat our study will encourage further explora-tion of the results of EEPs and that it mayguide and inspire policymakers and entrepre-neurship educators alike to design and deliversuccessful EEPs.

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