Measuring Entrepreneurial Self Efficacy to Understand the Impact of Creative Activities for Learning Inn

The International Journal of Management Education xxx (2014) 1e13

Contents lists available at ScienceDirect

The International Journal of Management Education

journal homepage: www.elsevier .com/locate/ i jme

Measuring entrepreneurial self-efficacy to understand theimpact of creative activities for learning innovation

Shima Barakat a, *, Monique Boddington a, b, Shailendra Vyakarnam a, b

a Centre for Entrepreneurial Learning, University of Cambridge Judge Business School, 10 Trumpington St, Cambridge CB2 1QA, UKb Centre for Entrepreneurial Learning, University of Cambridge Judge Business School, UK

a r t i c l e i n f o

Article history:Received 27 January 2014Received in revised form 11 April 2014Accepted 20 May 2014

Keywords:Entrepreneurship educationSelf-efficacyMeasuring impactCreativityInnovation

* Corresponding author. Tel.: þ44 1223 766900.E-mail address: [email protected] (S. BaraURL: http://www.cfel.jbs.cam.ac.uk

http://dx.doi.org/10.1016/j.ijme.2014.05.0071472-8117/© 2014 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Barakat,activities for learning innovation, The Ij.ijme.2014.05.007

a b s t r a c t

It has been argued that if increased entrepreneurial activity is the outcome objective, thenself-efficacy provides a legitimate and robust construct that can be used to evaluate theimpact of entrepreneurial education (Barakat, McIellan, & Winfield, 2010). This is becauseself-efficacy influences the motivation and ability to engage in specific activities (Bandura,1977) and is a strong, necessary condition of creative productivity, and in discovering newknowledge (Bandura, 1997). Although the concept of self-efficacy can be used as apromising tool to understand creativity and has been practically tested by Tierney andFarmer (2002), entrepreneurial self-efficacy (ESE) as a multi-dimensional construct re-mains under theorized. The aim of this paper is to provide details of a study and meth-odology in order to offer an example of a usable survey tool plus preliminary results fromthe data collected through a specific project called CAL4INO.Creative Activities in Learningfor Innovation (CAL4INO) is a European Union funded project that focuses primarily onidentifying the impact of different types of learning activities on the innovation potentialof participants. CAL4INO aims to review different education and training methods andexplore the impact different programmes have on entrepreneurship and innovation bothin the short term and long term. As part of this research a survey tool has been validatedthat measures different factors of entrepreneurial self-efficacy (ESE).Further, the rela-tionship between different dimensions of ESE are considered to build a better under-standing of the multi-dimensional structure of ESE.

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Creativity is viewed as central to entrepreneurship (Timmons,1994) and entrepreneurial intentions (Hamidi, Wennberg,&Berglund, 2008). Many entrepreneurial programmes now include learning activities designed to make the student think andact more creatively. As education in this area moves away from more traditional approaches it is no longer sufficient tomeasure courses by how well they teach students to write business plans or complete case study assignments or on studentfeedback, employability and financial returns. Creative learning activities aim to change the very behaviour of individuals ascreativity is strongly associated with entrepreneurship and innovation (Amabile, 1997). There is a need for a new type of

kat).

S., et al., Measuring entrepreneurial self-efficacy to understand the impact of creativenternational Journal of Management Education (2014), http://dx.doi.org/10.1016/

mailto:http://www.cfel.jbs.cam.ac.uk

mailto:[email protected]

mailto:http://www.cfel.jbs.cam.ac.uk

www.sciencedirect.com/science/journal/14728117

http://www.elsevier.com/locate/ijme

http://dx.doi.org/10.1016/j.ijme.2014.05.007



S. Barakat et al. / The International Journal of Management Education xxx (2014) 1e132

measurement. With the growing number of creative learning activities now being taught there is a need to better understandwhat impact they are having and if they are filling the theoretical remit of making individuals more creative, innovative andentrepreneurial.

Creative Activities in Learning for Innovation (CAL4INO), a European wide, EU funded project aims to investigate the roleof creative learning activities to enhance innovation within the context of entrepreneurship. The rationale behind this isthat people as teams, not lone “geniuses”, develop meaningful innovations by blending designs, technology and businessthrough creative activities synthesizing diverse perspectives, experiences and skills. To study and measure such activities,instruments need to be flexible enough to measure any creative learning activity that aims to enhance innovation and byextension, entrepreneurial activity. The Centre for Entrepreneurial Learning at the University of Cambridge was (andcontinues to be) responsible for designing and developing tools that are capable of studying and measuring creativelearning activities that aim to enhance innovation. Over the duration of the CAL4INO project a range of different pro-grammes have been measured that use a mixture of different approaches. The overall aim of the tool is that by analysingand comparing different creative learning activities it will be possible to enhance innovation at the technical, social andinstitutional level. The tool must be sufficiently robust to compare and measure a range of different creative learning ac-tivities across Europe. It must also be adaptive and sensitive to the different socio-cultural contexts, interdisciplinary andcross-sector nature of the study so that it is possible to compare creative activities across these boundaries. Within thestudy reported here, a tool was used to measure educational initiatives using creative activities to enhance innovation.Further categories were supplemented to allow for the measurement of enterprise and entrepreneurship education ingeneral.

The chosen method of measurement chosen was entrepreneurial self-efficacy (ESE). ESE is defined as an individual's ownbelief in his/her skills and abilities linked to entrepreneurial activity. It stands among the important personal factors thatinfluence the abilities and chances of entrepreneurs as it is a prerequisite for these groups to persist in their daily activitiesand in the achievement of their goals. It is no surprise that ESE has been receiving an increasing amount of attention in theliterature (for example Chen, Green & Crick, 1998; Forbes, 2005; McGee, Peterson, Mueller, & Sequeira, 2009). ESE has beenidentified as having a role in new venture creation (Barbosa, Gerhardt, & Kickul, 2007; Boyd & Vozikis, 1994; Chen, Greene,& Crick, 1998; Zhao, Siebert, & Hills, 2005) and is seen as an important antecedent to entrepreneurial action (Chen et al.,1998). Positively influencing self-efficacy can hence be a major goal in entrepreneurship education, especially with regard topromoting self-belief on efficacy in producing innovation and staying creative throughout the cumbersome innovationprocess.

Despite the growing body of literature, ESE remains empirically underdeveloped (McGee et al., 2009) with many calls forfurther refinement (for example Forbes, 2005; Kolvereid & Isaksen, 2006). There is a lack of understanding of the multi-dimensionality of ESE as the dimensionality of the construct has yet to be fully established (McGee et al., 2009). Thereforefurther work is needed to explore and determine the different dimensions of ESE.

This paper focuses on the design, implementation and validation of the survey tool (using both exploratory and confir-matory factor analysis) and preliminary findings. This is a valuable and powerful tool as it provides entrepreneurship edu-cators with a tool to understand the impact of different learning activities. The first sectionwill focus on the backgroundworkto the tool in terms of defining creativity and innovation and also previous work on how to measure the impact of enterpriseand entrepreneurial courses. This will be followed by a discussion of ESE, the chosen construct used for measurement andtherefore provides a context for the tool validated in this paper. Beforemoving on to showing how the tool has been validatedand some preliminary results from data gathered for the CAL4INO project.

2. Defining creativity and innovation

The first issues in measuring the impact of enterprise and entrepreneurship programmes is defining ‘what is beingmeasured?’: ‘how do we define creativity in relation to innovation?’. Given the remit of the CAL4INO project an un-derstanding of creativity for innovation is required that is contextualized within entrepreneurship. One major issue, asKaufmann (2003) notes, is that there is a lot of research that has focused on a “’bottom-up’ perspective, where devel-opment of tests of creativity have taken priority over the clarification of basic conceptual and theoretical issues.”(Kauf-mann, 2003, 236) Without defining basic conceptual and theoretical constructs there is a real danger of underminingany tool.

Referring to creativity, there are numerous models for creativity and a definition has been a matter of debate for decades,this is a complex issue and one that is not detailed here (for more detailed discussion refer to Berg, 2011). For the purposes ofdesigning a measurement tool the project team began by debating and researching the concept of creativity. While anydefinition of creativity is fraught with controversy, creativity in general can be defined as: “The development of a novelproduct, idea, or problem solution that is of value to the individual and/or larger social groups” (Hennessey & Amabile, 2010).General consensus in the field supports this definition (See also, Fisher & Amabile, 2009; George & Zhou, 2001; Sternberg,Kaufman, & Pretz, 2002; Tierney, Farmer, & Green, 1999).

Research has also indicated that creativity has a heuristic character within which, not only is the outcome novel, so too isthe process within which it is created (George & Zhou, 2001, 514). Within team creativity it is argued that creativity involvesinteraction between individuals and environment (Sternberg et al. 2002). Further, given the rise of technology andspecialization, creativity has become more a product of organizational effort than lone geniuses (Fisher & Amabile, 2009).

Please cite this article in press as: Barakat, S., et al., Measuring entrepreneurial self-efficacy to understand the impact of creativeactivities for learning innovation, The International Journal of Management Education (2014), http://dx.doi.org/10.1016/j.ijme.2014.05.007

S. Barakat et al. / The International Journal of Management Education xxx (2014) 1e13 3

Creativity as related to innovation within the entrepreneurial process is therefore defined as:

Pleasactivj.ijme

“the ability to develop novel products, ideas, or problem solutions which are of value to the entrepreneurial individualand/or team in their pursuit of an entrepreneurial opportunity and that take place in a heuristic environment”

Berg, 2011; CAL4INO theoretical framework.

This is a very brief overview of the theoretical background and constructs related to creativity but a working definitionmakes it possible tomove on situating creativity in terms of innovation. A number of themes can be drawn out when thinkingabout creativity learning activities for innovation: Firstly the skills and abilities of an individual are crucial as part of thecreative process and in particular creative skills which is of a malleable nature (Hennessey & Amabile, 2010). Personalitycharacteristics impact the creative process (Bull, Montgomery, & Baloche, 1995), particularly focused on here is confidence inperforming specific tasks including creative tasks and attitude and views around risk (particularly relevant to the context ofentrepreneurship). As noted earlier and within the definition above it not lone creativity but also team creativity that plays acrucial role in innovation. Creativity involves the interaction between individuals (Sternberg et al, 2002) particularly in aworld of rising specialization, more sophisticated technology and dispersed knowledge (Fisher& Amabile, 2009) The tool wasto be framed in terms of innovation and including measurements for creativity and entrepreneurship as these are so closelyrelated to innovation.

2.1. How do we measure creativity and innovation?

We therefore move on, from considering what is being measured to how to do it? How do we measure creativity andinnovation if that is our outcome objective? Many different methods have been used to measure creativity and innovation.We had to decide on the one that fitted best with the needs and resources of the project. We also wanted to move away frommore traditional methods that focused on longitudinal research, for example value of businesses created, towards an impactmeasure that could produce results in the short term and also one that could capture impact on a more nuanced level. Forexample measuring purely in terms of financial value of start-ups does not capture the value of individuals starting up forexample social enterprises or intrapreneurship.

Looking first at creativity, the most common method of measurement is psychometric testing (Plucker & Makel, 2010;Plucker & Runco, 1998). It is suggested that the predominance of psychometric testing is due to researchers extendingtheir research from other areas, for example aptitude and ability scores, and extending themethodology tomeasure creativity(Plucker&Makel, 2010, 49). Historically the most popular form of testing has been divergent thinking (DT) tests, for examplethe Torrance Test of Creative Thinking (Torrance, 1974) and Wallach and Kogan (1965) Test. While DT tests do vary, theygenerally ‘ask for multiple responses to either figural or verbal prompts, and responses are scored for fluency, flexibility,originality, and elaboration of ideas.” (Plucker & Makel, 2010, 52) However, these tests are undermined by their lack ofpredictive validity (Baer, 1993; Gardner, 1993; Wiesberg, 1993). Nonetheless a number of studies have demonstrated thediscriminate and predictive validity of DT tests though the response is mixed (Plucker & Makel, 2010, 54). Further de-velopments in recent years in this area have emphasised the importance of implicit theories towards social validation ofcreativity tests (Plucker & Runco, 1998).

Within an innovation/entrepreneurial setting there are a number of studies that use a range of techniques to test creativityTaggar (2002), studying individual and group creativity within an organizational background, tested creativity through theuse of case study questions (relevant to the background of individuals) analysed by observational scale measures and writtenwork scoring. Forms of psychometric testing continue to be popular (Hirst, Van Knippenberg, & Zhou, 2002; Liao, Liu, & Loi,2002; Pirola-Merlo & Mann, 2004).

While the tool had to be both robust and able to create meaningful indicators, one of the biggest deciding factors was thatit had to be easy to implement and use across multiple programmes and multiple countries. It was therefore felt that mostmethods of psychometric testing, specifically DT tests, required too much in terms of man hours and other resources to bepractical. Alternative measurement tools that score individual creativity through observation andwritten tests were again tooresource heavy and arguably, results from different studies would be incommensurable (with different people producingdifferent ratings).

Innovation has been generally measured in a more traditional manner, for example return on investment. To analyseinnovation there have been three broad areas of indicators: the use of R & D data, data from patent applications and scientificpublication and citation (Smith, 2005). However looking at creativity for innovationwewanted, as stated previously, to moveaway from such markers and look at how to measure the change in the individual becoming more innovative. We thereforeturned to a form of psychometric test different to those detailed above.

3. Self-efficacy

The survey tool adopted is rooted in the concept of self-efficacy which is best understood as a person's confidence intheir own ability to perform a specific task (Bandura, 1977). It is argued that self-efficacy provides a legitimate androbust construct that can be used to evaluate entrepreneurial education (Barakat, McIellan, & Winfield, 2010; Chen et al.,1998; Lucas & Cooper, 2005). Self-efficacy influences the motivation and ability to engage in specific activities (Bandura,1977) and is a strong, necessary condition of creative productivity and in discovering new knowledge (Bandura, 1997). It

e cite this article in press as: Barakat, S., et al., Measuring entrepreneurial self-efficacy to understand the impact of creativeities for learning innovation, The International Journal of Management Education (2014), http://dx.doi.org/10.1016/.2014.05.007


has been argued, that the concept of self-efficacy can be used as a promising construct to understand creativity (Tierney& Farmer, 2002). This has been practically tested (Farmer, Tierney, & Kung-McIntyre, 2003; Tierney & Farmer, 2002) byfocussing on the practical implications of Ford's (1996) theory that self-efficacy influences employees' creativity. Fordpresented a theory of individual creative action within organizational settings. Creativity and innovation are seen asclosely interlinked and creativity plays different roles across different layers of the innovation process. Creativity isfacilitated and constrained by a number of mechanisms including: sensemaking, motivation, knowledge, ability andcapability beliefs or as referred here self-efficacy. The findings of the study supported Ford's theory that self-efficacyinfluences employees creative decision making in their work and compared to other factors was the only one to havealone a ‘main effect’. (Tierney & Farmer, 2002). This research practically demonstrates that self-efficacy is an effectivemarker of creativity.

The tool focuses on entrepreneurial self-efficacy (ESE) in particular and thus measuring creativity and innovation withthe context of entrepreneurship. Within the context of entrepreneurial education, ESE is strongly correlated to newventure creation (Zhao et al., 2005). Entrepreneurial self-efficacy is linked to certain behaviours, for example opportunityrecognition and innovation associated with entrepreneurship (Chen et al., 1998). Lucas and Cooper (2005) have arguedthat self-efficacy, more than any other psychological construct, is linked to commitment to accomplish goals. Determi-nation is an essential for would-be entrepreneurs who often take many risks and spend many years in the face ofadversity.

Self-efficacy has been researched extensively within social science disciplines but only more recently within managementand entrepreneurial research. As a method of measurement it has been employed in only a few studies. Given the clear linksbetween self-efficacy and entrepreneurship, and in particular creative self-efficacy and entrepreneurial education, it is clearlya powerful concept that can be used to better understand creative learning activities for innovation in entrepreneurial ed-ucation and enhance teaching within this area. Further, given the nature of survey tools, participants are asked about theirperceptions and with self-efficacy being one's own confidence in one’s own ability it is therefore an ideal construct for asurvey based tool that collects self-reported data.

4. The tool

The tool to be designed needed to be able to measure the impact of creative learning activities on innovation within thecontext of entrepreneurship. Therefore the tool needed to understand the impact on ESE as related to creativity, innovationand other factors of ESE as related to the more general context of entrepreneurship. Rather than designing a new, untestedand untried survey tool, we chose to identify and collate existing survey elements that have been shown to measure thedifferent aspects that we sought. The first part of the survey is made up of the EGHI group/Cambridge-MIT Institute ques-tionnaire, which has been tested and employed in various studies (e.g.: Barakat, McLellan, & Winfield, 2010; Cave, Cooper,Good, & Ward, 2006; Lucas & Cooper, 2005). McGee et al. (2009) contend that although the majority of theorists advocatea multi-dimensional concept in their theoretical framework, the research itself relies on a construct of ESE which is verylimited in scope. They argue that the level of dilution is increased when such studies fail to take into account the underlyingdimensions of ESE. When there is a lack of variety among the sample populations tested, as is often the case, this can lead to atheoretically impoverished construct (for a more comprehensive review of the tensions in the literature around the ESEconstruct and its measurement please seeMcLellan, Barakat,&Winfield, 2009). Therefore, both the tool development and thesample data in our database have taken these concerns into account. Firstly, the tool was used to assess the underlying di-mensions of ESE and secondly, the measurement of individuals from across Europe taking part in different learning activitiestherefore increasing the variety of the sample population.

To account for this multi-dimensionality the tool employed here has a number of sections. An additional five sectionswere added to the original EGHI survey, all directly related to the literature review of creativity and innovation, as brieflydiscussed earlier. On 5-point and 6-point scales, questions ranged from the more general (for example, applying creativesolutions to problems) to the more specific (for example, finding new uses for existing methods or equipment). Three ofthe sections relate to individual creative self-efficacy and two sections relate to group self-efficacy. In consultation withother project partners it was felt that both individual and group self-efficacy needed to be considered. These questionswere adopted from several previous successful studies. Questions were adapted from the study of George and Zhou(2001) into understanding how different traits, including creative behaviour, related to behaviour in the workplace.Further questions were adapted from the study of Tierney et al (1999) which looked at the effects of manager andemployee creativity within a large chemical company. The section on innovation was also adapted from the George andZhou (2001) study.

The final questionnaire has seven sections containing items related to ESE and attitude measurements. From the originalEGHI instrument: skills and abilities related to entrepreneurship, peer reviewed (6 point scale), confidence in specific tasks(percentage scales) and attitude towards starting up and risk (7 point scale) (for more details see McLellan et al., 2009).Additional sections were crucial for helping with both the measurement and theorising of ESE. The additional new sectionsfocussed on accounting for the role of creativity as related to innovation within the entrepreneurial process (in terms of theindividual and teams): creativity (6 point scale), creativity in a teams (6 point scale), teamwork (5 point scale) and innovation(6 point scale). Further sections collected demographic information and information on future career intentions.


Fig. 1. Major area of study


To gauge the impact of different creative learning activities, the survey was designed to be taken before the learningactivity being measured, after and 6 months after that. All three surveys are almost identical to allow for comparison. Certainquestions related to demographic questions were removed from the post surveys as there was no need to ask for this in-formation multiple times. The post survey also contained additional questions related feedback for the course the participanthad completed. This would make it possible able to compare and benchmark different types of courses across Europe, in linewith the original aims of CAL4INO.

4.1. Validating the survey tool

Data was gathered from entrepreneurial programmes in Europe as part of the CAL4INO project and a subset of this will beused for this paper. Data was gathered using the online survey tool, Qualtrics. Surveys were disseminated through courseconvenors and supervisors and the survey completionwas optional. Our sample for this paper is made up of 1086 data pointsfrom 28 enterprise and entrepreneurship programmes delivered to postgraduate students. Themajority of these programmesequated to roughly 40 h of contact time, directed at would be entrepreneurs and included creative learning activities. A goodbenchmark example of the programmes measured is the Enterprisers Programme at the University of Cambridge, anentrepreneurial programme that aims to build self-confidence and self-belief.1 Geographically the majority of these pro-grammes were held in the United Kingdom, 21 in total. A further 2 programmes from Greece, 4 programmes from Finland, 1programme from Ireland and 1 programme from Portugal are also included in the dataset. A breakdown of the programmesmeasured including target group, duration and a brief description of aim of the programme and teachingmethods is providedin the appendix to this paper. However all groups had a multinational makeup in terms of the participants. 54.6% of oursample group was male and 45.4% female. Individuals had a wide variety of educational backgrounds (see Fig. 1) with themost coming from a maths and sciences background but still a large number from the social sciences and engineering. Justunder a half (42.7%) of the sample had taken previous enterprise module or course. Age of the sample group ranged from 18 to74 with an average age of 30.35.

The tool was validated using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Principle axesfactoring was used, with rotation to simplify and produce cleaner analyses. However we recognise that behaviours are notneatly portioned into separate boxes but function dependently on each other. In addition, the use of orthogonal methods onfactors that are correlated leads to the loss of information regarding the factors. For this reason the results of direct oblimrotation are presented here and factor scores were calculated using the Bartlett method (Bartlett, 1937).

To test if factor analysis is appropriate for the data set Kaiser-Meyer-Olkin Measure of sampling adequacy (KMO)(Kaiser, 1970) and the Bartlett's Test of Sphericity (Bartlett, 1950) were run. The Bartlett test of sphericity was highlysignificant (approx. chi-sq. 62806.792; df. 2701, sig.000) indicating that there is a high probability that the relationshipbetween variables is significant and that the correlation matrix is not an identity matrix. The KMO measure (0.970)expresses the proportion of common variance among variables. Nine factors were extracted (explaining 63% of

1 For more information see http://www.cfel.jbs.cam.ac.uk/programmes/enterprisers/.


http://www.cfel.jbs.cam.ac.uk/programmes/enterprisers/

Table 1Exploratory Factor Analysis statistics including Cronbach's alpha.

Factor 1 2 3 4 5 6 7 8 9

Cronbach's a 0.935 0.942 0.818 0.788 0.909 0.909 0.752 0.927 0.802% of variance 36.020 6.448 5.274 4.633 2.945 2.138 1.192 1.696 1.622Eigenvalue 27.015 4.836 3.955 3.475 2.209 1.603 1.437 1.272 1.216


the variance, all with Cronbach alpha values above or close to 0.8 indicating a healthy level of reliability. Please seeTable 1).

The model provided by EFA was further analysed using confirmatory factor analysis (maximum likelihood in AMOS 21).Experimentation showed that all factor loadings extracted from EFA under 0.40 were of a poor model fit and therefore werediscarded in the CFA Model. The Comparative Fit Index (CFI) compares the hypothesized model with a null model, the CFI of0.916 indicated an acceptable fit of the data to the model (Bentler, 1992). CMIN/DF (minimum discrepancy/degrees offreedom) of 3.283 also indicated a good model fit. A value of under 5 for CMIN/DF is considered indicative of a goodmodel fit.AGFI (which again compared the hypothesized model to a null model) of 0.828 indicated an acceptable fit (Wu & Wang,2006). RMSEA (the root mean square error of approximation) of 0.046 also indicated the model was a good fit for thedata, since it is under 0.08 (Browne & Cudeck, 1993) and even under 0.05 (Steiger, 1990). These measures indicate that themodel is a good fit, confirming the 9 factors identified during EFA. Seven ESE dimensions and two entrepreneurial attitudedimensions were identified as shown in Table 2.

The survey based self-efficacy tool has been validated using both EFA and CFA giving strong support for the 9 underlyingfactors (7 entrepreneurial self-efficacy items and 2 attitude scales). Within this, creativity dimension of ESE items are thoselinked to the generation of novel and original ideas both individually and within a team (for example, generating ideasrevolutionary, demonstrating originality). In comparison items that load on to the innovation ESE factor are about theapplication of new ideas (for example new ways of applying technologies, achieving objectives, solving problems that havecaused other problems) Startup processes ESE factor was also extracted, in comparison to the innovation and creativity ESEfactors which loaded on more specific skills and abilities, this factor loaded on more generalized skills and abilities (forexample, understanding what it takes to start your own business, start a successful social enterprise). It is no surprise thatthese three factors strongly correlate, as seen in table 3, there is a strong crossover. Creativity ESE and innovation ESEcorrelate at 0.730, start up processes ESE and creativity ESE at 0.644 and innovation and start up processes at 0.619. It canbe argued that there is a circularity to ESE, that raising an individual's self-efficacy related to creativity will also impact theirconfidence in their skills and abilities in innovation or start up processes and vice versa. These different factors of ESEcannot be considered as separate entities but are entwined in a complex structure, which clearly requires future work tounderstand. It is also important to not focus just on the creativity and innovation, but on other factors that validated in thetool (finance, teamwork, product development, leadership and the two entrepreneurial attitude measures: appetite andrisk). For example one of the most interesting correlations is possibly the very high correlation between startup processesand finance of 0.739.

Table 2Questionnaire items and factors (ESE and attitude dimensions).

Factor Example items

Innovation: applying new ideas and new ways of doing,including problem solving. (ESE)

Apply new and practical ideas.Apply a fresh approach to problems.

Financial Value: valuation, pricing, and negotiatingterms. (ESE)

Know how much to place the proper financial value on a start-up company.Estimate the number of people who are likely to buy a new product or service.

Attitude to Risk. (Attitude) It would kill my career if I helped form a new business that failed.Starting a company is too much like betting against the odds.

Teamwork; ability to work in and with teams/otherpeople. (ESE)

I find it easy to balance different ideas within a team.I find it easy to solve problems within a team

Product development: understanding and translatingcustomer needs into a product. (ESE)

Lead a technical team developing a new product to a successful result.Hear a product concept based on a technology and have a rough idea if it is practical.

Startup processes. (ESE) Understand what it takes to start your own enterprise.Understand the language of new venture creation.

Leadership: motivating, negotiating and recruitinga team. (ESE)

Find an approach that resolves a group conflict and gets your own team movingforward on a taskMotivate others to work long hours and to meet a deadline.

Creativity: generating novel ideas individually andwithin a team. (ESE)

Generate ideas revolutionary to the field you are in.Generate novel but operable work-related ideas.

Appetite for starting up. (Attitude) At least once I will have to take a chance and start my own company.If I see an opportunity to start a company, I’ll take it.


Table 3Pearsons correlations between constructs (all values significant at p < 0.01).

Finance <–> StartUp Proc 0.739Finance <–> Productdev 0.705Finance <–> Leadership 0.571Finance <–> Creativity 0.557Finance <–> Innovation 0.517Finance <–> Appetite 0.472Finance <–> Risk 0.274Finance <–> Teamwork 0.197Risk <–> Appetite 0.701Risk <–> Innovation 0.354Risk <–> StartUp Proc 0.347Risk <–> Creativity 0.340Risk <–> Productdev 0.241Risk <–> Leadership 0.228Risk <–> Teamwork 0.200Creativity <–> Innovation 0.816Creativity <–> StartUp Proc 0.644Creativity <–> Productdev 0.583Creativity <–> Leadership 0.558Creativity <–> Appetite 0.468Creativity <–> Teamwork 0.233Teamwork <–> Leadership 0.466Teamwork <–> Innovation 0.269Teamwork <–> Appetite 0.234Teamwork <–> StartUp Proc 0.209Teamwork <–> Productdev 0.158Productdev <–> Innovation 0.614Productdev <–> StartUp Proc 0.592Productdev <–> Leadership 0.584Productdev <–> Appetite 0.349Leadership <–> Innovation 0.545Leadership <–> StartUp Proc 0.544Leadership <–> Appetite 0.342Appetite <–> StartUp Proc 0.483Appetite <–> Innovation 0.437Innovation <–> StartUp Proc 0.619


5. Results

The examples used in this section are mainly for illustrative purposes, to show what the tool is capable of. To demonstratethe tool in practice, three Cambridge Entrepreneurial programmes are compared (Figs. 2 and 3). All three programmes haveroughly an equal number of contact time (about 5 days). Programmes b and d were residential. Programme b and c aredirected at individuals who are interested in entrepreneurship but may not have a concrete business idea yet. Both pro-grammes b and c were directed at mainly postgraduates though programme c was for women only. Programme d is at in-dividuals who are already putting together business plans and their own ideas towards setting up a business who come fromacross europe. Comparing the marginalized means of different factors show how the aims of the different courses are rep-resented in the ESE scores.

The time points refer to the different surveys: 1 (pre-programme), 2 (post-programme) and 3 (6 month post). Forexample for innovation we see how with programme d we see higher ESE among participants at the start compared toparticipants on b and c then a steady rise to the post programme results which are then followed by a further increase inESE as can be seen at the 6 months post results. If we look at creativity we see a slightly different pattern, with the pro-grammes directed earlier in the entrepreneurial journey (b and c) we see sharper growth with ESE levelling off towards the6 month point. Programme d on the other hand shows less dramatic increase but ESE raises both at the post and 6 monthpost stage indicating a more subtle and yet potentially a more fundamental course impact. Programme d is quite different toprogramme b and c, so the impact change is not surprising. For course d, individuals have already quite well formedbusiness plans and therefore, it is unsurprising that they have higher ESE and increases both post and 6 m month post. Forcourse b and c there is more dramatic increase, arguably as they are exploring new ideas but once back in the real world 6months later there is a drop in confidence. The women’s only group appear to have had a more extreme reaction, with amuch sharper increase and then a drop off at 6 months after the course, arguably, this is in some way gender linked. Thiswould suggest that educators could perhaps consider follow on initiatives for those earlier in there entrepreneurial journeyto facilitate increase ESE. Figs. 2 and 3 also suggest that gender is a moderating variable of ESE and worthy of futureresearch.


Fig. 2. Changes in Innovation ESE item of three Cambridge entrepreneurship programmes


Alternatively it is also possible to look at differences in the entire dataset. For example if we look at appetite for start upbetween peoplewho have a parent who has their own business and thosewho do not, there is a marked difference in appetitefor start up (Fig. 4).

These results offer evidence as to why people who have a parent who has their own business tend to be more likely tostart their own business (Krueger Jr. 1993) Having that parental influence results in a higher tolerance of risk and operatingunder uncertainty in participants even before they undergo a course. It is particularly interesting to see the results ofeducation and training where the parent-influenced course appear to be impacted more acutely by their chosen inter-vention, but even more significantly appear even more secure in the longer term whereas the other group appear to losemuch of their enhanced attitude to risk beyond the course(s). These results indicate that frame of mind of participants aswell as their contexts (and the interplay between them) may well influence the impact of education more than we have beaccounting for in either design or evaluation of programmes. This is a very complex area with on-going debate and mixedreports (see Athayde, 2009; Kim, Aldrich, & Keister, 2006; Mungai & Velamuri, 2011) and therefore needs further unpackingin terms of understanding the moderating impact of background on ESE and the possible ramifications this has forentrepreneurial education: for example, comparing the above to the impact of longer programmes of immersion.

Fig. 3. Change in Creativity ESE Item of three Cambridge entrepreneurship programmes


Fig. 4. Change in Risk Attitude Item for parents who run their own businesses.


The two examples in this section have aimed at highlighting possible applications of measuring ESE and attitudes usingthe survey instrument. Comparisons can be made between courses to understand how different courses impact differentpeople. Using the entire database it is possible to add new insights (that clearly need much more research) into themoderating variables and the nature of their influence on ESE and entrepreneurial attitudes.

6. Conclusions

This paper has discussed the design and validation of a tool based on entrepreneurial self-efficacy. The validation of thetool is a step forward empirically developing and refining our understanding of ESE. As noted earlier in this paper, there isa lack of understanding of the multi-dimensionality of ESE (McGee et al. 2009). Within the tool discussed in this paper,ESE is broken down into seven factors, with a further two attitude measures. Looking at the correlations between thesedifferent factors enriches our understanding of the multi-dimensionality and may also feed into education based on ESE.For example innovation SE highly correlates with creativity SE. Another high correlation is between finance SE and startupprocesses SE, something which would merit study. If we look at Innovation ESE more closely we see that it highly cor-relates with product dev ESE and Leadership ESE but correlates a lot less with Teamwork ESE. Further work will aim tolook more closely at these correlations through structural equation modelling and more specifically second orderconfirmatory factor analysis.

Early analysis also indicated the value of the tool in both understanding the impact of different entrepreneurial pro-grammes. These impact measures are not designed to produce right and wrong results but to better understand the impact ofa programme and allow these to be compared to the aims of the programme. Therefore this tool provides a new and valuabletool for entrepreneurship educators in designing and evaluating different learning activities. By understanding the impact ofdifferent learning activities can also be used by entrepreneurial educations to guide future students towards specificeducational progammes.

Thirdly this tool has broader use for both educators and policy makers in understanding area where education may beparticularly effective or on the contrary failing certain groups. Similarly, this methodology and tool can be used toidentify how policy and resources for education can be better directed. Increased transparency and understandingaround impact would allow resources to be allocated in line with policy objectives. For example, for increased innovationin a certain region, funding could be channelled towards initiatives that have measured increases in innovation self-efficacy. Or, if a particular group is of political interest, the policies and funds can be channelled towards initiativesthat have been shown to have the highest impact on the target group e.g. women, specific ethnic minorities, scientists,social scientists etc. This is in area which will require further research and a more nuanced image will only emerge withfurther data collection.

It is important to remember that this method is not a measure of student satisfaction which is becoming increasinglyimportant as students are perceived and treated more like customers instead of the more traditional product or even co-creators of knowledge. With increasing reliance on student paying premium fees, this is not surprising and though wewould not advocate using feedback as a measure of impact, it is important not to discount it and to note that high impact maywell comewith a significant proportion of negative feedback from students that are uncomfortablewithin exercises. This may



occur during exercises they perceive as ‘uncool’ and refrain from engaging fully or where they fail to perform a task that theyimagined they were naturally talented at. Creativity activities where students struggle to generate quality ideas are a typicalexample of this phenomenon. As are team-working activities where students struggle with addressing tensions in teamdynamics e especially with students who are the source of the problem(s). Considering the relationship between Impact andstudent satisfaction may provide interesting insights, particularly in light of programme and institutional objectives andperformance measures.

In the same vein, measuring the impact of a course or programme on ESE offers an indication of the probability of futureactivity. ESE offers a tool that can be used in the short-term and requires a lot less resources (particularly man-power).However, it does not offer an exact metric of the number of ventures that will be founded in the future, nor does it offer atimeline for this. Measuring changes in ESE is particularly powerful when the educational objective is to increase entre-preneurial activity in all sectors and time is of less significance. If the aim of a programme is specifically to increase the rate ofstartup as soon as possible, then additional metrics need to be taken into account. Measuring changes in ESE and especiallythe start-up dimensionwill give a good indication of whether the education or training being measured is having the desiredimpact on individuals but then a closer monitoring of actual activity beyond the programme needs to take place. This is ofparticular importance if the course or programme is being supported and resourced based on the number of ventures created.We would argue that focussing on measuring the start-up dimension of ESE as well as its interactions with the other di-mensions is sufficient to drawmeaningful conclusions about future start-up activity and that the temporal dimension is not asimportant as the likelihood of success of the entrepreneur and their venture but we do not discount the importance of thenumber of ventures founded since it is currently a very important measure for many different groups and bodies at all levelsfrom programme directors to policy makers.

To address some of the limitations as well as develop this knowledge area, future research would do well to considermixed methods that start to offer more answers to the ‘how’ and ‘why’ questions of the impact of entrepreneurship edu-cation. At the broad level, future research needs to start clearly considering the different needs and outcomes of under-graduate, postgraduate and professional education. Why are their differences? What are the implication of this for educationand training design? What are the implications for the practice of entrepreneurship? Looking at the links between educa-tional stage, intervention design and deliver, impact on ESE and resulting activities/actionwould be very interesting and maystart to offer the sorts of answers that ESE skeptics might appreciate. Moving beyond the idea that entrepreneurship is for alland that education is of equal benefit to all. As per the work of McLellan et al. (in preparation) and the earlier version of theresults in Barakat, McLellan, & Winfield (2011), there are strong indications that entrepreneurship education impactsdifferent student groups differently and both the education and policy communities would benefit from understandingfurther the differences in impact as well as how and why they take place. This will be invaluable for recruitment, resourcing,designing and assessing/evaluating entrepreneurship and enterprise education.

This paper has also contributed to the under-theorised multi-dimensionality of ESE by advancing a tool that measures theimpact of programmes on different dimensions of ESE. Prelimanary theoretical findings have been unpacked to understandhow these different dimensions may relate to each other, however, as noted earlier, much more work needs to be done tounderstand how these different dimensions relate to each other and how different learning activities impact different di-mensions of ESE.

Finally, measuring ESE changes as an impact indication and other complementary methods to explore the impact ofenterprise and entrepreneurship education by research full cohorts of students, made up of students engaged in differenttypes of enterprise and entrepreneurship education, extra-curricular activities or none at all would start to offer theevidence that many enterprise educators take for granted e that we do have an impact and that this impact comesthrough our education whether curricular or extra-curricular. There is now sufficient evidence that there are differenceand that the interaction between student type and type of intervention is significant and therefore more clarity andanalysis of this would benefit all involved: students, educators, education providers (organisations) and policy/resourcedecision makers.

Funding source

This project has been funded with support from the European Commission (Project Number: 512448-LLP-1-2010-1-LV-KA1-KA1SCR, Grant Agreement: 2010-5014/001-001). This publication reflects the views only of the author, and theCommission cannot be held responsible for any use which may be made of the information contained therein.

Acknowledgements

The authors would like to acknowledge and are deeply grateful for the training session organised by EEUK (then UKSEC)and delivered by the EGHI groupwhere their questionnaire instrument was disseminated. We are particularly grateful for thehelp and support of Prof. William Lucas of the EGHI group, his insights and contributions at the early stages of using the EGHIquestionnaire were invaluable.


Appendix

Table 4Programmes measured.

Programmeidentifier

Target group Duration Country Brief description (aim of programme and teaching methods)

A Postgraduate and postDoc 4 days (FT) UK Professional development for STEM women and increaseentrepreneurial confidence, mixture of interactive exercises andmotivational speakers.

B Postgraduate and Postdoc 4 days (FT) UK Raise entrepreneurial intentions and develop a general businessknow-how, convergent and divergent thinking exercises,mentoring, peer learning

C Postgraduate and Postdoc 4 days (FT) UK Women only course, raise entrepreneurial intentions, lectures byfemale role models, interactive practice sessions in groups,facilitator led training.

D Any with own venture 1 week (FT) UK Help build business plan though working in small groups, mentoring,one to one workshops, lectures, prepare and present business pitch

E Graduate early stageentrepreneurs

1 year (PT) UK Provide students with knowledge, skills and confidences requiredto be a successful entrepreneur. Use of lecture, mentor, companyvisits, virtual learning environment, pitching.

F Graduate early stageentrepreneurs

1 year (PT) UK Provide students with knowledge, skills and confidences requiredto be a successful entrepreneur. Use of lecture, mentor, companyvisits, virtual learning environment, pitching.

G Students or recent graduates 3 days (FT) UK Provide students with skills and knowledge to turn good ideas intobusiness venture. Equip with personal skills. Use of interactivesessions, group work, case studies and practicals.

H Postgraduate 1 term (6 weeks)(PT)

UK Course focussing on creativity and innovation at theoretical level.Lectures and case studies.

I Postgraduate 3 months (PT) Greece Help students to creatively design and implement learningprogrammes Lecturing, creativity design studios, group project.

J Postgraduate 3 months (PT) Greece Learning and problem solving around the design of interactivecomputational systems, creative design and innovation. Lecturing,creativity design studios, group project.

K Undergraduate 3 years (Onlypre data) (FT)

Finland Bachelor's degree in Business management, including competenciesaround management and entrepreneurship. Teamworking,mentoring, guidance, real life projects.

L Undergraduate and postgraduate 3 weeks (PT) Finland Aim to generate international growth entrepreneurship, tools todevelop and grow business ideas and start-ups. Lectures,workshops, peer to peer learning, mentoring.

M Senior Management 1 year (PT) Finland Leadership training to be more creative and innovative.Role playing, reflective learning.

N Professional 2 months (PT) Finland Professional development for teachers, utilising technology,creative approaches to service culture, identify needs andresources. Mixture lectures, role playing, peer to peer learning.

O Postgraduate and early stageentrepreneurs

1 year (PT) UK Enhance entrepreneurial effectiveness of young entrepreneurs.Internship with leading entrepreneur, interactive workshops,group work and practical exercises.

P Postgraduate and early stageentrepreneurs

1 year (PT) UK Enhance entrepreneurial effectiveness of young entrepreneurs.Internship with leading entrepreneur, interactive workshops,group work and practical exercises.

Q Postgraduate, postdocs andresearchers

5 days (FT) Portugal Introduce students to the concepts and practices of entrepreneurialthinking. Lectures, guest speakers, team exercises and presentation,workshop.

R Postgraduate and Postdoc 1 day (FT) UK Develop emotional intelligence and personal skills to deal withdifficult situations and risk management. Role playing, groupdiscussion and practical case studies.

S Undergraduates and graduates 3 days (FT) UK Aim to fast track business idea and build action plan to movebusiness forward. Interactive group work, peer review,case studies and networking

T Undergraduates and graduates 3 days (FT) UK Aim to fast track business idea and build action plan to movebusiness forward. Interactive group work, peer review,case studies and networking

U Undergraduates and graduates 1 day (FT) UK Finding innovative and creative solution to set problem.Design thinking, problem solving, group work.

V Undergraduates and graduates 1 day (FT) UK Finding innovative and creative solution to set problem.Design thinking, problem solving, group work.

W Undergraduates, postgraduatesand graduates

1 day (FT) UK Opportunity recognition around business models, get ready forlaunch. Group work based around business model canvas,peer to peer learning, facilitator led.

X Undergraduate 1 day (FT) UK Aim to get students to think about setting up their own business.Facilitated panel sessions, interactive group work.

(continued on next page)



Table 4 (continued )

Programmeidentifier

Target group Duration Country Brief description (aim of programme and teaching methods)

Y Postgraduate 1 day (FT) UK To make students think more broadly, creativity and innovatively.Working in groups around movie theme with some post coursementoring

Z Postgraduate and Postdoc 3 weeks PT Ireland Develop confidence in creative thinking and communication,evolve innovative ideas in teams. Team based ideas, designthinking challenges, guest speakers.

AA Postgraduate 6 months (PT) UK Focus on writing business plans and industry awareness,ability to sell. Lecture, tutorials, role playing, team work,create marketing adverts and other practical exercises.

AB Postgraduate and Postdoc 4 days FT UK Women only course, raise entrepreneurial intentions,lectures by female role models, interactive practice sessionsin groups, facilitator led training.


References

Amabile, T. M. (1997). Motivating creativity in organizations: on doing what you love and loving what you do. California Management Review, 40(1), 39e58.Athayde, R. (2009). Measuring enterprise potential in young people. Entrepreneurship Theory and Practice, 33, 481e500.Baer, J. (1993). Why you shouldn't trust creativity tests. Educational Leadership, 51(4), 80e83.Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84, 191e215.Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.Barakat, S., McIellan, R., & Winfield, S. (August 2010). Examing the impact of programmes for entrepreneurship using self-efficacy. In Working paper,

presented at the Academy of Management Conference. Montreal: Canada.Barakat, S., McLellan, R., & Winfield, S. (2011). The impact of programmes for entrepreneurship: lessons from examining self-efficacy. In Institute of Small

Business and Enterprise (ISBE) Annual Conference, London, UK.Barbosa, S., Gerhardt, M., & Kickul, J. (2007). The role of cognitive style and risk preference on entrepreneurial self-efficacy and entrepreneurial intentions.

Journal of Leadership & Organizational Studies, 13(4), 86e104.Bartlett, M. S. (1937). The statistical conception of mental factors. British Journal of Psychology, 28, 97e104.Bartlett, M. S. (1950). Test of significance in factor analysis. The British Journal of Psychology, 3, 77e85.Bentler, P. M. (1992). On the fit of models to covariances and methodology to the bulletin. Psychological Bulletin, 112, 400e404.Berg, H. (2011). Theoretical framework CAL4INO.Boyd, N. G., & Vozikis, G. S. (1994). The influence of self-efficacy on the development of entrepreneurial intentions and actions. Entrepreneurship Theory and

Practice, 18(4), 63e77.Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen, & J. S. Long (Eds.), Testing structural equation models (pp.

136e162). Newsbury Park, CA: Sage.Bull, K. S., Montgomery, D., & Baloche, L. (1995). Teaching creativity at the college level: a synthesis of curricular components perceived as important by

instructors. Creatvity Research Journal (Vol 8), 83e89.Cave, F. D., Cooper, S. Y., Good, D., & Ward, A. E. (June 2006). Developing self-efficacy and entrepreneurial intent for technology entrepreneurship: the

influence of role models. In Paper presented at the Babson College entrepreneurship research conference. Bloomington, USA: (BCERC) held at IndianaUniversity.

Chen, C. C., Greene, P. G., & Crick, A. (1998). Does entrepreneurial self-efficacy distinguish entrepreneurs from managers? Journal of Business Venturing, 13,295e316.

Farmer, S. M., Tierney, P., & Kung-McIntyre, K. (2003). Employee creativity in Taiwan: an application of role identity theory. Academy of Management Journal,46(5), 618e630.

Fisher, C. M., & Amabile, T. M. (2009). Creativity, improvisation and organizatons. In T. Rickards, M. A. Runco, & S. Moger (Eds.), The Routledge companion tocreativity (pp. 13e24). London: Routledge.

Forbes, D. (2005). The effects of strategic decision making on entrepreneurial self-efficacy. Entrepreneurship Theory and Practice, 29(5), 599e626.Ford, C. (1996). A theory of individual creative action in multiple social domains. Academy of Management Review, 21, 1112e1142.Gardner, H. (1993). Creating minds. New York: Basic Books.George, J. M., & Zhou, J. (2001). When openness to experience and conscientiousness are related to creative behavior: an interactional approach. Journal of

Applied Psychology, 80(3), 513e524.Hamidi, D. Y., Wennberg, K., & Berglund, H. (2008). Creativity in entrepreneurship education. In SSE/EFI working paper series in business administration, No

2008, 4.Hennessey, B. A., & Amabile, T. M. (2010). Creativity. Annual Review of Psychology, 2010(61), 569e598.Hirst, G., Van Knippenberg, D., & Zhou, J. (2002). A cross-level perspective on employee creativity: goal orientation, team learning behavior, and individual

creativity. Academy of Management Journal, 52(2), 280e293.Kaiser, H. F. (1970). A second generation Little Jiffy. Psychometrika, 35, 401e415.Kaufmann, G. (2003). What to measure? A new look at the concept of creativity. Scandinavian Journal of Educational Research, 47(3).Kim, P. H., Aldrich, H. E., & Keister, L. A. (2006). Access (not) denied: the impact of financial, human, and cultural capital on entrepreneurial entry in the

United States. Small Business Economics, 27(1), 5e22.Kolvereid, L., & Isaksen, E. (2006). New business start-up and subsequent entry into self-employment. Journal of Business Venturing, 21(6), 866e885.Krueger, N. F., Jr. (1993). “Growing up entrepreneurial?”: developmental consequences of Earlt exposure to entrepreneurship. In Academy of management

best papers proceedings 1993 (pp. 80e84).Liao, H., Liu, D., & Loi, R. (2002). Looking at both sides of the social exchange coin: a social cognitive perspective on the joint effects of relationships quality

and differentiation on creativity. Academy of Management Journal, 53(5), 1090e1109.Lucas, W. A., & Cooper, S. Y. (2005). Measuring entrepreneurial self-efficacy. In Paper presented at the EDGE conference "bridging the gap: Entrepreneurship in

theory and practice".McGee, J., Peterson, M., Mueller, S. P., & Sequeira, J. M. (2009). Entrepreneurial self-efficacy: refining the measure. Entrepreneurship, Theory & Practice, 33(4),

965e988.McLellan, R., Barakat, S., & Winfield, S. (2009). The impact of entrepreneurial programmes: the case for examining self-efficacy. In The Institute of Small

Business and Enterprise (ISBE) Annual Conference, Liverpool, UK.McLellan, R., Barakat, S., & Winfield, S. (2014). The differential effects of enterprise education programmes. Intended for submission to the Academy of

Management Learning and Education (in preparation).


http://refhub.elsevier.com/S1472-8117(14)00031-7/sref1





















































































Mungai, E., & Velamuri, S. R. (2011). Parental entrepreneurial role model influence on male offspring: is it always positive and when does it occur?Entrepreneurship Theory and Practice, 35(2), 337e357.

Pirola-Merlo, A., & Mann, L. (2004). The relationship between individual creativity and team creativity: aggregating across people and time. Journal ofOrganizational Behavior, 25, 235e257.

Plucker, J. A., & Makel, M. C. (2010). Assessment of creativity. In J. C. Kaufman, & R. Sternberg (Eds.), The Cambridge handbook of creativity (pp. 48e73).Cambridge: Cambridge University Press.

Plucker, J. A., & Runco, M. A. (1998). The death of creativity measurement has been greatly exaggerated.Smith, K. (2005). Measuring innovation. In J. Fagerberg, D. C. Mowery, & R. R. Nelson (Eds.), The Oxford handbooks of innovation (pp. 148e177). Oxford:

Oxford University Press.Steiger, J. H. (1990). Structural model evaluation and modification: an interval estimation approach. Multivariate Behavioral Research, 25(2), 173e180.Sternberg, R. J., Kaufman, J. C., & Pretz, J. E. (2002). The creativity conundrum e A propulsion model of kinds of creative contributions. Essays in cognitive

psychology. Psychology Press.Taggar, S. (2002). Individual creativity and group ability to utilize individual creative resources: a multilevel model. Academy of Management Journal, 45(2),

315e330.Tierney, P., & Farmer, S. M. (2002). Creative self-efficacy: its potential antecedents and relationship to creative performance. Academy of Management Journal,

45(6), 1137e1148.Tierney, P., Farmer, S. M., & Green, G. B. (1999). An examination of leadership and employee creativity: the relevance of traits and relationships. Personnel

Psychology, 52, 591e620.Timmons, J. (1994). New venture creation. Chicago: Irwin.Torrance, E. P. (1974). Torrance Tests of Creative Thinking: Norms-technical manual. Lexington, MA: Ginn and Company.Wallach, M. A., & Kogan, N. (1965). Modes of thinking in young children: A study of the creativity-intelligence distinction. New York, Holt: Rinehart and

Winston.Wiesberg, R. W. (1993). Creativity: Beyond the myth of genius. New York, W. H: Freeman and Company.Wu, J.-H., & Wang, Y.-M. (2006). Measuring KMS success: a respecification of the DeLone and McLean's model. Information & Management, 43, 728e739.Zhao, H., Siebert, S. E., & Hills, G. E. (2005). The mediating role of self-efficacy in the development of entrepreneurial intentions. Journal of Applied Psy-

chology, 90(6), 1265e1272.








































Documents

Measuring Entrepreneurial Self Efficacy to Understand the Impact of Creative Activities for Learning Inn