Action and Action-Regulation in Entrepreneurship ... · Action and Action-Regulation in...

Action and Action-Regulationin Entrepreneurship:

Evaluating a Student Trainingfor Promoting Entrepreneurship

MICHAEL M. GIELNIKLeuphana University of Lüneburg, Germany

MICHAEL FRESENational University of Singapore and Leuphana University, Lüneburg, Germany

AUDREY KAHARA-KAWUKIMakerere University Business School and Solutions Ltd, Uganda

ISAAC WASSWA KATONOUganda Christian University, Kampala, Uganda

SARAH KYEJJUSAMUHAMMED NGOMA

JOHN MUNENEREBECCA NAMATOVU-DAWA

FLORENCE NANSUBUGALAURA OROBIA

Makerere University Business School, Kampala, Uganda

JACOB OYUGIKyambogo University, Kampala, Uganda

SAMUEL SEJJAAKAARTHUR SSERWANGA

Makerere University Business School, Kampala, Uganda

THOMAS WALTERGIZ, Arusha, Tanzania

KIM MARIE BISCHOFFTHORSTEN J. DLUGOSCH

Leuphana University of Lüneburg, Germany

Action plays a central role in entrepreneurship and entrepreneurship education. Based onaction regulation theory, we developed an action-based entrepreneurship training. Thetraining put a particular focus on action insofar as the participants learned actionprinciples and engaged in the start-up of a business during the training. We hypothesizedthat a set of action-regulatory factors mediates the effect of the training onentrepreneurial action. We evaluated the training’s impact over a 12-month period usinga randomized control group design. As hypothesized, the training had positive effects on

� Academy of Management Learning & Education, 2015, Vol. 14, No. 1, 69–94. http://dx.doi.org/10.5465/amle.2012.0107

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action-regulatory factors (entrepreneurial goal intentions, action planning, actionknowledge, and entrepreneurial self-efficacy) and the action-regulatory factors mediatedthe effect of the training on entrepreneurial action. Furthermore, entrepreneurial actionand business opportunity identification mediated the effect of the training on businesscreation. Our study shows that action-regulatory mechanisms play an important role foraction-based entrepreneurship trainings and business creation.

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Entrepreneurship occurs because entrepreneurstake actions to pursue business opportunities (Bird& Schjoedt, 2009; Shane, Locke, & Collins, 2003).Scholars have consistently emphasized that actionis a central construct to understand entrepreneur-ship (Baron, 2007a; McMullen & Shepherd, 2006).Action is important because starting a new busi-ness requires continuous actions to gather re-sources and to set up viable business structures(Gartner, 1985). Entrepreneurs who initiate morestart-up activities and who are more active in theprocess of starting a new business are more likelyto successfully launch one (Carter, Gartner, &Reynolds, 1996; Kessler & Frank, 2009; Lichtenstein,Dooley, & Lumpkin, 2006; Newbert, 2005). Given thecentral role of action in entrepreneurship, an im-portant question discussed in the literature isabout the best method to train entrepreneurial ac-tion (Edelman, Manolova, & Brush, 2008; Neck &Greene, 2011). We seek to contribute to this discus-sion in two ways. First, our study presents a train-ing program that combines an action-based and atheory-based training method. Second, and this isour main focus, we present a theoretical model onthe short- and long-term effects of the training toexplain how the training exerts an influence onstarting a new business.

Regarding the training method, scholars havenoted that many entrepreneurship trainings put astrong focus on developing a business plan butlack a method that involves active engagement bythe participants (Honig, 2004; Pittaway, Missing,Hudson, & Maragh, 2009). Active engagementmeans that the training emphasizes learning byaction and involves performing start-up activities

that correspond to the activities performed by en-trepreneurs (Edelman et al., 2008; Neck & Greene,2011). Rasmussen and Sorheim (2006) have calledsuch trainings action-based or action-oriented en-trepreneurship trainings. Action-based entrepre-neurship trainings (i.e., engaging in start-up activ-ities and starting a business in the training) havebecome a popular method to train students in en-trepreneurship (Asvoll & Jacobsen, 2012; Barr,Baker, & Markham, 2009; Fiet, 2001a; Gorman, Han-lon, & King, 1997; Honig, 2004; Oosterbeek, vanPraag, & Ijsselstein, 2010; Pittaway et al., 2009; Ras-mussen & Sorheim, 2006). Furthermore, scholarshave criticized the fact that many training pro-grams lack a solid theoretical foundation (Fiet,2001b). A theoretical basis is important because itgives the training participants guidance in whatthey should do instead of only describing whatother entrepreneurs have done (Fiet, 2001b). Oneway to include theory in trainings is to use actionprinciples. Action principles are derived from the-ory and scientific evidence and provide knowledgeabout how to do something (Frese, Bausch,Schmidt, Rauch, & Kabst, 2012). Our training ac-knowledges the importance of both action and the-ory for training entrepreneurship. Our training isaction-based because the participants engage instart-up activities and start a microbusiness in thetraining. The training is theory-based because theparticipants learn action principles of how to suc-cessfully start and run a business.

Regarding the theoretical model underlying theshort- and long-term effects of entrepreneurshiptrainings, scholars have noted that there are sev-eral issues that previous research has not yet ad-dressed in detail (Martin, McNally, & Kay, 2013).First, a recent meta-analysis has concluded thatmany evaluation studies have no or only an incon-sistent theoretical grounding, and more studiesthat develop a better theoretical understanding ofentrepreneurship trainings are needed (Martin etal., 2013). Second, most studies investigating theimpact of entrepreneurship education and train-ings focus only on short-term outcomes, such as

This paper was supported by Deutscher Akademischer Aus-tausch Dienst (DAAD; ID 50020279 and ID 54391079). Furthermore,the work on this article was (partially) supported by grants fromMOE/National University of Singapore (AcRF Tier 1 R-317-000-084-133 and AcRF Tier 1 R-317-000-095-112). We would also like tothank the German Commission for UNESCO for supporting theproject. We thank Eike Hedder, Andreas Heese, RebeccaKernert, Marie-Luise Lackhoff, Kay Turski, Melanie von derLahr, and Kristina Zyla for their support in collecting the data.

70 MarchAcademy of Management Learning & Education

knowledge, attitudes, and intentions, or only onlong-term outcomes, such as start-up or survival.The studies seldom integrate short- and long-termoutcomes into a general model presenting thecausal flow of effects from the training over short-to long-term outcomes (e.g., Cruz, Escudero, Bara-hona, & Leitao, 2009; Henry, 2004; Ladzani & vanVuuren, 2002; Lee, Chang & Lim, 2005; Saks &Gaglio, 2002; Souitaris, Zerbinati, & Al-Laham,2007; von Graevenitz, Harhoff, & Weber, 2010). Com-bining short- and long-term outcomes is importantto develop a general theoretical framework ex-plaining why and how trainings work. Last, thestudies focusing on short-term outcomes to evalu-ate the impact of trainings usually argue thatshort-term outcomes, such as intentions, have pos-itive effects on long-term outcomes, such as entre-preneurial behavior and success (e.g., Peterman &Kennedy, 2003; Souitaris et al., 2007). However,these effects are far from being established (Da-vidsson & Honig, 2003; Katz, 1990). Pittaway andCope (2007) concluded from their review that entre-preneurship trainings have an effect on propensityand intentionality but to what extent these effectsthen translate into effective entrepreneurship isunclear. Therefore, a long-term evaluation is im-portant to understand the lasting effects of train-ings and their impact on entrepreneurship.

In our study, we seek to overcome some short-comings of previous research. We develop a theo-retical model based on action regulation theory(Frese, 2009; Frese & Zapf, 1994; Karoly, 1993) toinvestigate a set of mediators that explains whyand how our action-based entrepreneurship train-ing has a positive effect on entrepreneurial actionand business creation (see Figure 1). Identifying aset of mediators that explains the underlyingmechanisms has important theoretical implica-tions. Davidsson (2007) has noted that in recentyears the strongest theoretical contributions toentrepreneurship research have been made bystudies investigating action-related mediators thatelucidate the causal mechanisms affecting entre-preneurship. We integrate short- and long-termtraining outcomes to show that four action-regulatory factors (i.e., entrepreneurial goal inten-tions, action planning, entrepreneurial self-efficacy, and action knowledge) have a mediatingfunction linking the action-based entrepreneur-ship training with entrepreneurial action. Thesefour factors build the space of action-regulatoryfactors (Bandura, 1989; Frese & Zapf, 1994). We thusprovide a theoretical grounding for the short-

and long-term effects of the training in an inte-grated model. Furthermore, our 12-month long-term evaluation shows that entrepreneurial actionand business opportunity identification mediatethe effect of the training on business start-up. Wethus show how the training translates into busi-ness creation in the long-run.

THEORY AND HYPOTHESES

Effects of the Action-BasedEntrepreneurship Training

Scholars have noted that entrepreneurial action iskey for business creation (Baron, 2007a; McMullen& Shepherd, 2006) and that action-based entrepre-neurship trainings are particularly effective in pro-moting entrepreneurial action (Barr et al., 2009). Inline with Rasmussen and Sorheim’s (2006) concep-tualization, we developed an action-based entre-preneurship training that involved starting a busi-ness in the course of the training. Our didacticalapproach was based on an action regulation theoryperspective on training (Frese & Zapf, 1994). Two im-portant features of this approach are teaching thetraining content in form of action principles and ac-tive learning (learning-by-doing). Empirical evi-dence shows that trainings designed in accordancewith this approach are effective in changing andfacilitating action (Bell & Kozlowski, 2008, 2010;Burke, Sarpy, Smith-Crowe, Chan-Serafin, Salvador,& Islam, 2006; Frese, Beimel, & Schoenborn, 2003;Keith & Frese, 2008). In our case, the aim of the train-ing was to facilitate performing entrepreneurial ac-tions and starting a new business after the training.

The first training feature—teaching principles ofaction—means that students do not learn abstracttheoretical knowledge but guidelines for dealingwith entrepreneurial tasks. Action principles canbe considered as “rules of thumb,” providingknowledge that can be easily implemented. Actionprinciples facilitate taking action to accomplishtasks because they provide specific knowledge ofwhat to and how to do something. This knowledgeis an important antecedent of taking action (Frese& Zapf, 1994). Research has shown that simplerules are more effective in changing and facilitat-ing action because they are easier to apply (seeDrexler, Fischer, & Schoar, 2011; Holcomb, Ireland,Holmes, & Hitt, 2009). It is important to note thataction principles are not derived from individualexperiences but from theory and scientific evi-dence about how to be successful in entrepreneur-

2015 71Gielnik, Frese, Kahara-Kawuki, et al.

ship. Action principles give students direction andshow them an optimal approach toward entrepre-neurial tasks without the need to learn the fulltheory (see also Fiet, 2001b). To develop actionprinciples, we identified theories and scientific ev-idence about factors contributing to success in en-trepreneurship and management (see Table 1). Wethen formulated theory-based action principles.For example, our module on “the psychology ofplanning and implementing plans” included prin-ciples derived from action theory (Frese & Zapf,1994), such as to formulate action plans in the formof when, where, and how to perform actions toachieve a goal and use the action plan flexibly.This form has been shown to be related to success-ful initiation of action and performance (Gollwit-zer, 1999; Mumford, Schultz, & Van Doorn, 2001).

The second training feature—active learning orlearning-by-doing—means that students are notpassive recipients of the training content, but per-form actively the target behavior. Active learningpromotes entrepreneurial action and business cre-ation for two reasons. The first reason is thatthrough active learning, the action principles areconnected with concrete behavior. Thus, more con-crete action knowledge is generated with benefi-cial effects for taking action (Frese & Zapf, 1994).The second reason is that through active learning,the students get real-life feedback, which helpsthem to better understand what the action princi-ples mean and how to apply them. This refines andimproves their action knowledge, and thus, con-tributes to taking action (Frese & Zapf, 1994). In ourtraining, we requested the students form entrepre-neurial teams of four to six students in which theystarted a microbusiness in the course of the train-ing. The goal was to start and operate this micro-business such that it makes profit within the train-ing period of 12 weeks under real businessconditions. The students were to go through theentire entrepreneurial process from preparing tolaunching and managing a business. To this end,each team received approximately $100 US as seedcapital that was to be repaid at the end of the12 weeks. In the course of the training, the studentsacquired equipment and raw materials, dealt withsuppliers, and entered the market to offer theirproduct or service to customers. Examples of busi-nesses started by the entrepreneurial teams in thetraining were producing fruit juices or salads, of-fering statistical software trainings, and produc-ing African jewelry.

In conclusion, the features of action principlesand active learning facilitate taking entrepreneur-ial action and eventually business creation. Wetherefore hypothesize:Hypothesis 1: The action-based entrepreneurship

training has a positive effect on (a)entrepreneurial action and (b) busi-ness creation.

Action-Regulatory Factors:Mediators in the Effect of the Training on Action

We seek to develop and investigate a theoreticalmodel that explains why and how an action-basedentrepreneurship training has a positive effect onentrepreneurial action and business creation.Based on action regulation theory (Frese, 2009; Fr-ese & Zapf, 1994), we hypothesize that the action-based entrepreneurship training has a direct effecton a set of action-regulatory factors that mediatethe effect of the training on entrepreneurial ac-tion. More specifically, we hypothesize that thetraining positively influences students’ entrepre-neurial goal intentions, action planning, entrepre-neurial self-efficacy, and action knowledge. Thesefour action-regulatory factors are short-term out-comes of the training that transmit the effect of thetraining on the long-term outcome of entrepreneur-ial action (Bandura, 1989; Frese & Zapf, 1994;Karoly, 1993). Action regulation theories (Frese,2009; Frese & Zapf, 1994; Karoly, 1993) state that, foractions, it is necessary to have goal intentions,action plans, action knowledge, and self-efficacy.Goal intentions capture what people want toachieve, action plans are mental simulations ofactions outlining how people go about achievingtheir goals, action knowledge refers to people’sknowledge about the relevant actions, and self-efficacy refers to people’s belief in their compe-tences to perform the actions (Bandura, 1989; Frese& Zapf, 1994). Also important to note is that thesefour factors are rooted in people’s cognitions; thefour factors are not actions themselves, but theyare antecedents that regulate actions.

First, we hypothesize that the action-based en-trepreneurship training has a positive effect onentrepreneurial goal intentions. During thetraining, the students start and operate a busi-ness. Thus, the students learn to successfully setup and operate a business and that they canexpect positive outcomes from starting a busi-ness. Experiencing this has positive effects ontheir attitudes toward entrepreneurship, which


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translate into stronger entrepreneurial goal inten-tions (Ajzen, 1991). Second, we hypothesize that theaction-based training has a positive effect on stu-dents’ action planning. The training included amodule on “planning and implementing plans” toput a particular focus on action planning. More-over, during the training the students had to planand execute the start-up of a real business. Thishelps the students to develop skills in action plan-ning, which then translates into better action-planning performance outside the training setting.Third, we hypothesize that the action-based train-ing has a positive effect on students’ entrepreneur-ial self-efficacy. As noted above, the students en-gaged in the start-up process of a real businessduring the training. This functions as a masteryexperience, increasing students’ entrepreneurialself-efficacy (Bandura, 1989; Gist & Mitchell, 1992).Finally, we hypothesize that the training has apositive effect on students’ action knowledge. Thetraining content provided input for developing ac-tion knowledge that contains information aboutthe operational steps to successfully start and op-erate a new business (what to do and how to do it;Edelman et al., 2008). In addition, because actionknowledge is best learned and built by activelearning (Frese & Zapf, 1994), engagement in theset-up of the real business contributes to develop-ing correct and sophisticated action knowledge.Therefore, the training increases students’ actionknowledge about entrepreneurship and businesscreation.Hypothesis 2: The action-based entrepreneurship

training has positive effects on (a)entrepreneurial goal intentions, (b) ac-tion planning, (c), entrepreneurial self-efficacy, and (d) action knowledge.

We hypothesize that the four action-regulatory fac-tors have an effect on entrepreneurial action. Wehypothesize that entrepreneurial goal intentionspositively influence entrepreneurial action be-cause goal intentions capture the motivational ef-fort people are willing to invest into a specificaction and how hard they are willing to performthe action (Ajzen, 1991). Studies have provided ev-idence for the positive effect of goal intentions onaction and performance (Baum & Locke, 2004; Kolv-ereid & Isaksen, 2006; Locke & Latham, 2002). How-ever, scholars have also noted that the effect ofgoal intentions on actions is contingent on actionplanning (Brandstatter, Heimbeck, Malzacher, &Frese, 2003; Frese & Zapf, 1994; Miller, Galanter, &Pribram, 1960). Gollwitzer (1999) has argued and

shown empirically that a goal intention is trans-lated into an implementation intention once a goalintention is met by an action plan. By developingaction plans, people get into an implementalmind-set with an immediate tendency to put theintention into effect (Brandstatter, Lengfelder, &Gollwitzer, 2001). With regard to entrepreneurship,this means that action planning moderates theeffect of entrepreneurial goal intentions on entre-preneurial action. Entrepreneurs, who have thegoal intentions to start a new business, are morelikely to initiate and maintain entrepreneurial ac-tion when they complement their goal intentionswith action plans (Frese, 2009; Frese & Zapf, 1994). Itis important to note that action plans are distinctfrom business plans. Business plans are writtendocuments that describe the economic viability ofa business concept (Honig & Karlsson, 2004). Actionplans are mental simulations of actions that spec-ify the substeps (what to do) and the operationaldetails (how to do it) relevant for goal attainment.By specifying the substeps and operational de-tails, action plans control and direct the effort thatis captured by goal intentions. Action plans thushelp to initiate and maintain goal-directed actions(Frese, 2009; Frese & Zapf, 1994). Furthermore, byspecifying the operational sequence of one’s goalpursuit, action planning helps to focus the atten-tion on the relevant activities; thus, the effort spec-ified by goal intentions is not wasted. Last, devel-oping action plans helps people to stay on trackeven when faced with distractions, and they arethus more likely to persistently pursue their goalintentions (Locke & Latham, 2002). In conclusion,we hypothesize that action planning moderatesthe effect of entrepreneurial goal intentions on en-trepreneurial action: the higher action planning,the stronger the effect.

Apart from goal intentions and action planning,action regulation theory (Frese, 2009; Frese & Zapf,1994) states that action knowledge has an impor-tant function in the process that leads to action.Action knowledge is the cognitive basis underly-ing efficient action, and it is represented in peo-ple’s cognitive schema (Frese & Zapf, 1994). In thecontext of entrepreneurship, action knowledgecomprises knowledge about relevant entrepre-neurial actions. Furthermore, action knowledgecomprises information about the principles andcausal processes involved, as well as informationabout anticipated outcomes and consequences ofone’s actions. Action knowledge influences the ef-ficiency of people’s actions: the better and more


sophisticated people’s action knowledge, the moreefficient their actions (Frese & Zapf, 1994). For ex-ample, better knowledge about operational andformal steps necessary to establish a new busi-ness leads to more frequent and efficient actions inthese areas. We therefore hypothesize that actionknowledge has a positive effect on entrepreneurialaction.

Last, we investigate entrepreneurial self-efficacy as an antecedent of entrepreneurial ac-tion. In general, self-efficacy has a strong impacton action (Bandura, 1989; Stajkovic & Luthans,1998). Self-efficacy is task specific; we thereforefocus on entrepreneurial self-efficacy (Bandura,1989). Entrepreneurial self-efficacy reflects an indi-vidual’s confidence in his or her capabilities toaccomplish the tasks of an entrepreneur (Chen,Greene, & Crick, 1998). We hypothesize that entre-preneurial self-efficacy has a positive effect onentrepreneurial action because it influences peo-ple’s initial choice of activities, the goal level andgoal commitment, and the amount of effort andpersistence people invest in pursuing entrepre-neurial activities (Boyd & Vozikis, 1994; Gist &Mitchell, 1992). Believing themselves to be capableof successfully performing entrepreneurial activi-ties increases the likelihood that people will makethe decision to engage in entrepreneurial actions.Once they have made the decision, they are morelikely to show higher commitment, effort, and per-sistence in performing these actions (Bandura,1989; Boyd & Vozikis, 1994). Research provides evi-dence for the positive effect of entrepreneurial self-efficacy on entrepreneurial action (De Clercq &Arenius, 2006; Rauch & Frese, 2007; Townsend,Busenitz, & Arthurs, 2010).Hypothesis 3: (a) Entrepreneurial goal intentions,

(b) entrepreneurial self-efficacy, and(c) action knowledge have positiveeffects on entrepreneurial action.

Hypothesis 4: The positive effect of entrepreneur-ial goal intentions on entrepreneur-ial action is moderated by actionplanning: the higher action plan-ning, the stronger the effect.

We hypothesize that the four action-regulatory fac-tors (entrepreneurial goal intentions, action plan-ning, entrepreneurial self-efficacy, and actionknowledge) form a set of mediators that transmitthe effect of the training on entrepreneurial action.We have argued that the training positively affectsthese four factors (H2). These four factors, in turn,form the space of action-regulatory processes lead-

ing to actions (Frese, 2009; Frese & Zapf, 1994;Karoly, 1993). Therefore, the effect of the action-based training on entrepreneurial action (H1) isindirect through the four action-regulatory factors.Hypothesis 5: The set of the four action-regulatory

factors (entrepreneurial goal inten-tions, action planning, entrepreneur-ial self-efficacy, and action knowl-edge) mediates the effect of theaction-based training on entrepre-neurial action.

Mediators of the Effect of the Training onBusiness Creation

We seek to investigate the long-term effects of theaction-based training on business creation. Whileother outcomes are also valuable (see Martin et al.,2013), we focus on increasing the probability ofnew start-ups because this is a prevalent objectiveof entrepreneurship education (Edelman et al.,2008; Pittaway & Cope, 2007). We argue that busi-ness opportunity identification and entrepreneur-ial action mediate the effect of the action-basedentrepreneurship training on starting a new busi-ness. Identifying and acting on opportunities iskey for starting a new business (Shane & Venkat-araman, 2000).

First, “to have entrepreneurship, you must firsthave entrepreneurial opportunities” (Shane & Ven-kataraman, 2000: 220). A business opportunity canbe defined as the discovery of new means–endsrelationships to introduce a new product, service,or process to the market (Shane & Venkataraman,2000). Also important to note is that not all businessopportunities lead to a new business; entrepre-neurs have to take action to implement the oppor-tunities (McMullen & Shepherd, 2006). Yet, strongtheoretical arguments that opportunity identifica-tion is related to business creation exist. Ucbasa-ran, Westhead, and Wright (2008) have argued thatidentifying more opportunities is related to identi-fying an opportunity which is sufficiently innova-tive for starting a new business. This line of rea-soning is based on Simonton (1989), who hasargued that the generation of innovative outcomescan be described as a stochastic process; gener-ating more ideas increases the likelihood of gen-erating an exceptionally innovative one. Indeed,research showed that the number of identified op-portunities is positively related to the innovative-ness of identified opportunities (Gielnik, Krämer,Kappel, & Frese, 2014; Shepherd & DeTienne, 2005).


Entrepreneurs are more likely to exploit an oppor-tunity when it is more innovative because moreinnovative opportunities promise a higher return(Baron & Ensley, 2006; Choi & Shepherd, 2004; Fiet,2002). Therefore, higher levels of opportunity iden-tification increase the likelihood of business cre-ation. In our training, we included modules partic-ularly focusing on the identification of businessopportunities (e.g., modules on “Business opportu-nity identification” and “Marketing”). In the mod-ule on business opportunity identification, wefocused mainly on principles derived from thecreativity literature (e.g., Ward, 2004). To someextent, we also developed principles based onthe effectuation literature (Sarasvathy, 2001),such as “use your personal strengths (who youare, what you know, whom you know).” In themodule on marketing, we discussed (apart fromother topics relevant in marketing) principles re-garding the importance of identifying customerneeds and wants.

Second, starting a new business requires thatentrepreneurs perform start-up activities to assem-ble the necessary resources and develop viablestructures (Gartner, 1985). The exact sequence ofstart-up activities is not determined (Lichtenstein,Carter, Dooley, & Gartner, 2007), but a high rate ofinitiating and completing start-up activities in-creases the likelihood of successfully starting anew business (Carter et al., 1996; Gatewood,Shaver, & Gartner, 1995; Kessler & Frank, 2009;Lichtenstein et al., 2006; Newbert, 2005). The UnitedStates Panel Study of Entrepreneurial Dynamicslists 27 start-up activities performed by entrepre-neurs in the first years of the start-up process(Reynolds, 2007). The list includes activities suchas developing and defining a new product or ser-vice, organizing the necessary resources (e.g.,starting capital, equipment), and fulfilling the le-gal requirements (e.g., obtaining licenses, register-ing). Performing these activities helps getting thenecessary resources for starting and operating thebusiness. Therefore, entrepreneurs who showhigher levels of entrepreneurial action and per-form more start-up activities are more likely tosuccessfully start a new business.

In conclusion, we argue that the training influ-ences entrepreneurial action and business oppor-tunity identification which in turn have positiveeffects on business creation. Thus, the causal flowis from the training to business opportunity iden-tification and entrepreneurial action and finally tobusiness creation. We therefore hypothesize:

Hypothesis 6: The effect of the action-based entre-preneurship training on businesscreation is mediated by business op-portunity identification and entre-preneurial action.

METHODS

The Action-Based Entrepreneurship Training

We have described two important didactical fea-tures of our training—action principles and activelearning—in the theory section to argue why thetraining has a positive effect on entrepreneurialaction. With regard to the didactical approach, wealso took into consideration the target group andthe content (“what should be taught”) in the devel-opment of the training (Kuratko, 2005). The targetgroup of the training was students in the last yearof their undergraduate studies from all disciplinesexcept business administration. We excluded thatparticular group of students because our aim wasto enable entrepreneurship among students whohave not been previously encouraged to think ofself-employment as a career option. With regard tothe content, the entrepreneurship literature sug-gests that the field of entrepreneurship includestopics from the domains of entrepreneurship, psy-chology, and business administration (Baron,2007b). We decided to include topics from all threedomains in our training to provide our target groupwith comprehensive skills in entrepreneurship.Drawing from the domains of entrepreneurship,business administration, and psychology, we in-cluded 12 different modules in our entrepreneur-ship training: (1) identifying business opportuni-ties, (2) marketing, (3) leadership and strategicmanagement, (4) the psychology of planning andimplementing plans, (5) financial management, (6)persuasion and negotiation, (7) acquiring startingcapital, (8) networking, (9) accounting, (10) personalinitiative, (11) business plan, and (12) legal andregulatory issues (see Table 1). The modules werechosen on the basis of comprehensive literaturereviews of relevant topics and content in entrepre-neurship education (Fiet, 2001b; Solomon, 2007;Vesper & Gartner, 1997). The 12 modules weretaught on a weekly basis over a period of 12 weeks.The weekly sessions were 3 hrs long.

Design of the Evaluation Study

To evaluate the training, we conducted a random-ized controlled field experiment comparing a treat-


ment group with a nontreatment control group(waiting group). The treatment was the action-based entrepreneurship training. We randomly as-signed the students to the training or controlgroup. To take part in the training and to create acertain degree of commitment to participatethroughout the training, the students had to pay adeposit of approximately $10 US which was re-funded at the end of the training if all moduleswere attended. To collect our data, we employed apretest–posttest design and conducted three mea-surements waves (T1, T2, & T3). The first measure-ment wave (T1), took place in the month before thetraining. The second measurement wave (T2), tookplace in the month directly after the training. Thethird measurement wave (T3), took place 12 monthsafter T1. The pretest–posttest design with a ran-domization of participants controls for problems ofmaturation, testing, history, and self-selection(Campbell, 1957).

All data were collected with personal inter-views and questionnaires. The interviewers re-ceived a comprehensive interviewer training in-cluding sessions on interview techniques to probeparticipants’ answers, the use of prompts to clarifyabstract statements, note taking, and typical inter-viewer errors (e.g., nonverbal signs of agreement).The interviewers were told to take verbatim notesof participants’ responses to open questions. Par-ticipants’ responses to the interview question-naires were subsequently rated by two indepen-dent raters on the basis of standardized ratingguidelines. Calculations of intraclass correlationcoefficients (ICC; Shrout & Fleiss, 1979) showedgood interrater reliabilities ranging from ICC � .88to ICC � .97.

The trainers were lecturers from four universitieslocated in Kampala, Uganda. All lecturers had sev-eral years of experience in teaching undergradu-ates and have been involved in the development ofthe modules. The lecturers received a train-the-trainers workshop to familiarize them with the di-dactical approach of the training. Each trainer wasresponsible for one module. The trainers deliveredthe sessions, presented the training exercises,guided the students’ presentations and discus-sions of the exercises, and gave feedback on thestudents’ presentations.

Participants

The training was conducted at two Ugandan uni-versities located in Kampala (University A) and

Mukono (University B). The recruitment procedureincluded the following steps: The deans of the fac-ulties of the universities received a letter inform-ing them of the voluntary entrepreneurship train-ing. Accompanying the letter were applicationforms to be handed to the students. The deansdistributed the application forms through the lec-turers and professors, who also collected themfrom the students. The training was independent ofthe regular university programs, and it was notpart of the curriculum; the participants did notreceive any credits or grades for participating inthe training. However, they received a certificateat the end of the training. It is important to mentionthat we emphasized that the training was a volun-tary training and that it provided the students withskills for an alternative career option as entrepre-neurs. We explicitly told the students that theycould also attend the training if they intended toseek employment and if they do not opt to becomean entrepreneur after graduation. In total, we re-ceived 651 applications (424 from University A and227 from University B). The total number of trainingspots was limited to approximately 200. We ran-domly selected 203 students for the training group.The students could select 1 of 4 classes to haveclass sizes of approximately 50 students. From theremaining list of applications, we randomly se-lected 203 students to form the control group. Thecontrol group was a waiting control group, whichmeans that they did not receive any treatment dur-ing the study. Only after the end of the evaluationstudy, the students received the same training asthe students in the training group. Thirteen stu-dents who were assigned to the control grouphad not participated in the first measurementwave resulting in a total of 190 students in thecontrol group. Nine students from the training groupfailed to show up for more than seven sessions ofthe training. We therefore excluded them fromthe analyses, leaving a total of 194 studentsin the training group. The total sample at thefirst measurement wave (T1; the month beforethe training) was thus 384 (194 in the traininggroup and 190 in the control group). We comparedthe training group and the control group on allvariables. There were no significant differenceson any measure, indicating that the randomiza-tion was successful and the two groups wereequivalent.

For the second measurement wave (T2; themonth directly after the training), we were able totrace 337 participants from our initial sample (184


from the training group and 153 from the controlgroup). To test whether nonresponse biased thedata in one direction (i.e., in favor of the traininggroup or in favor of the control group), we analyzedwhether the nonrespondents of the training groupdiffered significantly from the nonrespondents ofthe control group (test for differential loss of par-ticipants across training and control group). Therewere no significant differences between the non-respondents from the training group and thosefrom the control group on any sample characteris-tic or dependent measure at T1, indicating thatthe nonrespondents did not bias the data at T2.At the third measurement wave (T3; 12 months af-ter the first measurement wave), we were able tocollect data from 304 participants of our initialsample (162 from the training group and 142 fromthe control group). Again, we compared the nonre-spondents from the training group with those fromthe control group. The analyses revealed no statis-tical differences between the two groups. The rea-sons for nonresponse were either lack of time toconduct the interview or lack of motivation to fur-ther participate in the study.

Measures

Action Knowledge

We measured action knowledge at T1 and T2. Fol-lowing Kraiger, Ford, and Salas (1993), we mea-sured action knowledge as skill-based cognitionsusing a situational interview. The situational in-terview captures knowledge about how to achievea desired goal (Latham, Saari, Pursell, & Campion,1980). During the interview, we presented one oftwo scenarios in counterbalanced and randomizedorder across T1 and T2. Scenario A read that thepopulation is constantly growing older in Ugandaand that there is the business idea of opening aclub or a bar particularly for older people. ScenarioB read that a new technology was invented, whichcan print three-dimensional solid objects fromcomputer drawings, and that there is the businessidea to use this technology to produce models forarchitects (see Shane, 2000). We then asked, “Whatwould be your next steps if you decided the ideamight be worth pursuing?” Two independent ratersrated the participants’ responses on the basis of alist of 35 activities to elaborate a business idea andto start a business. The 35 activities were derivedfrom the entrepreneurship literature (Davidsson &Honig, 2003; Dimov, 2007; Reynolds, 2007) and in-

cluded activities such as “gather informationabout the market,” “buy or rent equipment,” or“acquire starting capital.” This list thus contains acomprehensive set of preparatory start-up activi-ties useful to start a business. Participants re-ceived a score of “1” for an activity if they men-tioned that they would perform the activity. Theyreceived a score of “2” if they described in detailwhat they would do and how they would do it. Theyreceived a score of “0” for this activity if they did notmention it. The total score over all 35 activitiesformed the participants’ score of action knowledge.Interrater reliabilities for the two raters were good atT1 (ICC � .88) and T2 (ICC � .88). T tests showed thatthe two scenarios did not lead to significant differ-ences in participants’ responses.

Entrepreneurial Self-Efficacy

We measured entrepreneurial self-efficacy at T1and T2 using 12 questionnaire items. We used theitems developed by Krauss, Frese, Friedrich, andUnger (2005) on the basis of Bandura’s (1989) theo-retical conceptions. We used this scale because ofits predictive validity in African settings (Frese etal., 2007). The scale corresponds to the scales byChen and colleagues (1998) and Zhao, Seibert, andHills (2005) insofar as it asks respondents to indi-cate how confident they are of performing certainentrepreneurial tasks. Bandura (1989) has arguedthe need to develop scales for specific contexts.Our items cover different tasks relevant in entre-preneurship. An example item is “How confidentare you that you can identify business opportuni-ties well?” The participants answered the items onan 11-point Likert scale ranging from “not at allconfident” (0) to “very confident” (10). The mean ofthe 12 items formed the score for entrepreneurialself-efficacy. The internal consistency of the scaleat T1 (Cronbach’s alpha � .93) and T2 (Cronbach’salpha � .94) was good.

Entrepreneurial Goal Intentions

We measured entrepreneurial goal intentions at T1and T2 using five questionnaire items. We devel-oped the five items using the stem “do you intendto” as recommended by Gollwitzer (1999) and Ajzen(1991). All items asked “Within the next six months,do you intend to” followed by specific start-up ac-tivities derived from Davidsson and Honig (2003).The five specific start-up activities were “discussyour business idea with business professionals,”


“organize a start-up team or look for partners,” “domarket research for your business idea,” “look forequipment or a location for your business,” and“work on a business plan for your business idea.”The participants answered the five items on a5-point Likert scale ranging from “not at all” to“very much.” The internal consistency of the scaleat T1 (Cronbach’s alpha � .83) and T2 (Cronbach’salpha � .77) was good.

Action Planning

We measured action planning at T1 and T2 duringthe interview and based our approach on mea-sures by Frese and colleagues (Frese et al., 2007;Frese, van Gelderen, & Ombach, 2000) and Brand-statter and colleagues (2003). We first asked theparticipants whether they were currently trying tostart a business and if they affirmed, we asked theparticipants to tell us more about the next stepsthey were planning to take. When the participantsstopped, we asked once whether there was any-thing else they were planning to do. We repeatedthe same procedure on whether they were intend-ing to start a business in the next 12 months. If theparticipants were currently trying to start a busi-ness, the second question asked whether theywere intending to start an additional business in

the next 12 months. Thus, we asked all participantsabout two potential start-ups. Participants’ re-sponses to the questions of what they were plan-ning to do were rated by two independent ratersusing the list of 35 start-up activities derived fromthe literature (see Action Knowledge above). Weapplied the following rating procedure: For eachstart-up activity, participants received a score of“1” if they had a rough plan of what they wanted todo and how they wanted to do it; they received ascore of “2” if they had a detailed plan regardingthe start-up activity; and they received a score of“0” if they did not plan to perform the start-upactivity. The total score over both questions andover the 35 start-up activities formed the score ofaction planning. Interreliabilities between thetwo raters at T1 (ICC � .87) and T2 (ICC � .88)were good.

Entrepreneurial Action

In our theoretical model, entrepreneurial action isboth a dependent variable and a predictor of busi-ness creation (see Figures 1 and 2). We measuredentrepreneurial action at T1, T2, and T3 during ourinterview. We used the T1 measure as control, themeasure at T2 to investigate the effect of entrepre-neurial action on business creation, and the mea-

FIGURE 1The Theoretical Model with the Hypothesized Effects of the Action-Based Entrepreneurship Training on

Entrepreneurship (waves of measurement in parentheses)


sure at T3 to investigate entrepreneurial action asan outcome of the action-regulatory factors of en-trepreneurial self-efficacy, action knowledge, en-trepreneurial goal intentions, and action planning.We asked whether the participants were currentlytrying to start a business, and if they affirmed weasked: “So far, what did you do to get the businessup and running?” If participants stopped explain-ing this, we asked once whether there was any-thing else they had done to get the business upand running. We repeated these questions regard-ing whether they intended to start a business inthe next 12 months. If the participants had alreadyaffirmed the question of currently trying to start abusiness, we asked them whether they were in-tending to start an additional business in the next12 months. We rated participants’ answers usingthe list of 35 start-up activities derived from theliterature (see Action Knowledge above). For eachof the 35 start-up activities, the participants re-ceived a score of “1” if they had put effort into thisactivity, of “2” if their response showed that they

had put much effort into this activity, of “0” if theyhad not put any effort into this activity. The totalscore over both questions and over the 35 start-upactivities formed the score of entrepreneurial ac-tion. Interreliabilities between the two raters at T1(ICC � .90), T2 (ICC � .92), and T3 (ICC � .96)were good.

Business Opportunity Identification

We measured business opportunity identificationat T1 and T2 during our interview. We adaptedquestions from Hills, Lumpkin, and Singh (1997)and Ucbasaran and colleagues (2008) and askedthree open questions: “How many opportunities forcreating a business have you identified (spotted)within the last 3 months,” “Out of all those oppor-tunities, how many were in your opinion promisingfor creating a profitable business,” and “How manyopportunities for creating a business have you pur-sued, that is committed time and resources to,within the last 3 months?” In line with Ucbasaran

FIGURE 2Specified Models and Standardized Path Coefficients. Note. (a) The model includes the following control variables:university, action planning (T1), entrepreneurial goal intentions (T1), action knowledge (T1), entrepreneurial self-efficacy (T1), andentrepreneurial action (T2); Satorra-Bentler corrected �2 (37) � 53.05; RMSEA � .04; SRMR � .05; CFI � 0.95; * p � .05; ** p � .01. Note.(b) The model includes the following control variables: university, entrepreneurial action (T1), business opportunity identification (T1),and business creation (T2); �2 (6) � 11.22; RMSEA � .06; SRMR � .03; CFI � 0.97; * p � .05; ** p � .01


and colleagues (2008), responses larger than “6”were recoded as “6” to eliminate extreme re-sponses and to bring the distribution of responsesin line with a normal distribution. The averagescore over the three questions formed our mea-sure of business opportunity identification. Theinternal consistency of the scale at T1 (Cron-bach’s alpha � .67) and T2 (Cronbach’s alpha � .70)was satisfactory for such a short scale (Cortina, 1993).Gielnik and colleagues (2014) have provided evi-dence for the predictive validity of this measure forinnovativeness of product or service innovations.

Business Creation

We measured whether the participants had starteda business by asking at T1, T2, and T3 during theinterview: “Are you currently the owner of a busi-ness.” We coded responses as “1” if the answerwas “yes” and “0” if the answer was “no.” In ouranalyses, we controlled for being a businessowner at the previous measurement wave, whichmeans that our dependent variable reflects changeand thus business creation.

Control Variables

We measured the following control variables totest whether our randomization was successfuland the training group was equivalent to the con-trol group: We used the digit span test forward andbackward, which is a subtest of the Wechsler test,as a rough measure of working memory capacity orgeneral mental ability (Colom, Rebollo, Palacios,Juan-Espinosa, & Kyllonen, 2004). Participantswere requested to repeat from memory rows ofthree to nine numbers read aloud. The four items(two times forward and two times backward) had agood internal consistency (Cronbach’s alpha � .77)and were averaged to form a proxy of cognitiveability. We further asked the participants whetheranybody in the family owns a business (yes � 1,no � 0) and whether they had taken any businesscourses prior the training (yes � 1, no � 0) becausethese variables influence starting a business (Da-vidsson & Honig, 2003). We measured entrepre-neurial experience by asking whether they werecurrently the owner of a business or whether theyhad started a business in the past (yes � 1, no � 0).We measured employment experience by askingwhether the participants were currently employedor whether they had had any employment in thepast (yes � 1, no � 0). Last, we measured age,

gender (female � 0, male � 1), and the university atwhich the participants studied (University A � 0,University B � 1).

RESULTS

Table 2 presents the descriptive statistics and cor-relations of the study variables. We conductedt tests to find if there were significant differencesbetween the training group and the control groupon any variable at T1. None of the t tests weresignificant, which indicates that the randomiza-tion was successful and the groups were equiva-lent. Because we sampled students from two dif-ferent universities, we tested whether they differedon any measure. We found significant differencesfor business courses taken (University A: M � 0.12vs. University B: M � 0.05, p � .05); employmentexperience (University A: M � 0.57 vs. University B:M � 0.42, p � .05); cognitive ability (University A:M � 3.06 vs. University B: M � 2.60, p � .01); actionknowledge (University A: M � 2.67 vs. University B:M � 3.45, p � .01); and entrepreneurial goal inten-tions (University A: M � 4.13 vs. University B:M � 4.33, p � .05). Although we used a randomizedsampling approach, we included university as acovariate in our analyses to be able to combine thetwo universities.

Test of Hypotheses

We tested our hypotheses using structural equa-tion modeling, which allowed us to simultaneouslytest our hypotheses regarding the direct and me-diating effects. We had to specify two models be-cause we had two measures for entrepreneurialaction. We used the measure of entrepreneurialaction at T3 as an outcome of the action-regulatoryfactors measured at T2 (action planning, entrepre-neurial goal intentions, action knowledge, and en-trepreneurial self-efficacy). We used the measureof entrepreneurial action at T2 as a mediator in therelationship between the training and businesscreation at T3. By using two different measures, wetested all hypotheses in a longitudinal design.

First, we specified the model to test our hypoth-eses regarding the effects of the action-basedtraining on entrepreneurial action (H1a) and on theaction-regulatory factors (H2a–2d) as well as theeffects of the action-regulatory factors on entrepre-neurial action (H3a–3c and 4) and the mediatingeffect of the action-regulatory factors in the rela-tionship between the training and entrepreneurial


TABL

E2

Inte

rcor

rela

tion

san

dD

escr

ipti

veSt

atis

tics

ofth

eSt

udy

Var

iabl

es

Var

iabl

eTi

me

MSD

12

34

56

78

910

1112

1314

1516

1718

1920

2122

2324

1.T

rain

ing

gro

up

(0�

con

trol

,1�

tra

inin

g)

T1

0.51

0.50

2.A

ctio

nkn

owle

dg

eT

12.

841.

59.0

13.

Act

ion

know

led

ge

T2

3.96

1.87

.29*

*.0

54.

En

tre.

self

-eff

ica

cyT

17.

831.

19.0

2.0

0�

.01

5.E

ntr

e.se

lf-e

ffic

acy

T2

8.09

1.13

.21*

*.0

0.0

5.6

2**

6.E

ntr

e.g

oal

inte

nti

ons

T1

4.17

0.76

.01

�.0

3.0

6.3

8**

.20*

*7.

En

tre.

goa

lin

ten

tion

sT

24.

190.

69.1

4**

.03

.09

.35*

*.4

5**

.32*

*8.

Act

ion

pla

nn

ing

T1

2.38

1.56

.06

.35*

*.1

3*.1

1*.0

5.1

3*.1

09.

Act

ion

pla

nn

ing

T2

3.04

1.71

.23*

*.0

8.4

2**

.10

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action (H5). In the model, we controlled for univer-sity and for the action-regulatory factors at T1 andentrepreneurial action at T2 to have a true predic-tion model. The model included an interaction ef-fect between action planning and entrepreneurialgoal intentions. To account for the fact that weincluded an interaction effect in a structural equa-tion model, we followed the recommendations byCortina, Chen, and Dunlap (2001) and Williams,Edwards, and Vandenberg (2003). We computed ag-gregate measures of our variables as described inthe section on the study measures. We then com-puted the interaction term for action planning andentrepreneurial goal intentions by multiplying therespective centered aggregate measures. We de-termined the factor loadings and measurement er-rors for our aggregate measures and for our inter-action terms to fix the respective values in ourmodel. The factor loadings are set equal to thesquare roots of the measures’ reliabilities, and themeasurement errors are set equal to the measures’variance multiplied by one minus their reliabili-ties. We calculated the reliability of the interactionterms according to the approach developed byBohrnstedt and Marwell (1978) and used the reli-abilities to determine the factor loadings and mea-surement errors for the interaction terms. To testthe fit of our model, we used the Satorra andBentler (1994) correction which adjusts standarderrors and �2 statistics according to the degree ofnon-normality in case an interaction term is in-cluded in the model. We evaluated the fit of ouroverall model with the root mean square error ofapproximation (RMSEA), the squared root meanresidual (SRMR), and the comparative fit index(CFI). According to recommendations by Hu andBentler (1999) an RMSEA smaller than .06, an SRMRsmaller than .08, and CFI larger than .95 indicategood model fit.

The results for the model showed a good fit (Sa-torra & Bentler corrected �2(37) � 53.05; RMSEA � .04;SRMR � .05; CFI � 0.95). We examined the pathcoefficients to test our hypotheses (see Figure 2a).We found significant effects of the training on allfour action-regulatory factors, supporting H2a–2d.Specifically, we found positive effects on actionplanning (� � .22, p � .01); entrepreneurial goalintentions (� � .16, p � .05); action knowledge(� � .32, p � .01); and entrepreneurial self-efficacy(� � .27, p � .01). With regard to the effects of theaction-regulatory factors on entrepreneurial ac-tion, we found a positive and significant path fromaction knowledge to entrepreneurial action sup-

porting H3c (� � .15, p � .05). We did not findsupport for H3a, which stated that entrepreneurialgoal intentions has a positive effect on entrepre-neurial action (� � .08, ns.) or for H3b, stating thatentrepreneurial self-efficacy has a positive effecton entrepreneurial action (� � .07, ns.). The find-ings supported H4, that action planning moderatesthe effect of entrepreneurial goal intentions on en-trepreneurial action. The path coefficient of theinteraction term between action planning and en-trepreneurial goal intentions on entrepreneurialaction was positive and significant (� � .15,p � .05). To interpret the interaction, we created aplot (see Figure 3) by adapting the procedure de-scribed by Aiken and West (1991). Figure 3 shows apositive relationship between entrepreneurialgoal intentions and entrepreneurial action incases of high action planning but not in cases oflow action planning.

Last, we calculated the indirect effect of thetraining on entrepreneurial action through theaction-regulatory factors. The indirect effect waspositive and significant (indirect effect: .27,p � .05), supporting H1a that the training has an(indirect) effect on entrepreneurial action. A signif-icant indirect effect indicates a mediation effect(Preacher & Hayes, 2004). To further examine themediation effect, we included a path from thetraining to entrepreneurial action. The additionalpath did not lead to a significant improvement inmodel fit (Satorra-Bentler corrected �2 (36) � 52.78;corrected �2-difference (1) � 0.27, ns.) and the path

FIGURE 3The Moderating Effect of Action Planning on the

Effect of Entrepreneurial Goal Intentions onEntrepreneurial Action


was not significant (� � .02, ns.). Our findings thussuggest that the action-regulatory factors fully me-diate the effect of the training on entrepreneurialaction, supporting H5.

We specified a second model to test our hypoth-eses regarding the effects of the action-basedtraining on business creation (H1b) and the medi-ating function of business opportunity identifica-tion and entrepreneurial action in this relationship(H6). In the second model, the dependent variablewas business creation at T3. We controlled for uni-versity, for entrepreneurial action, and for busi-ness opportunity identification at T1, and for busi-ness creation at T2 to have a true prediction model.The initial model did not result in a satisfactorymodel fit (�2(7) � 16.93; RMSEA � .07; SRMR � .03;CFI � 0.94). Including a direct path from the train-ing to business creation significantly improved themodel fit (�2 difference (1) � 5.17, p � .05). Themodified model showed a good fit (�2(6) � 11.22;RMSEA � .06; SRMR � .03; CFI � 0.97). We exam-ined the path coefficients of the modified model totest our hypotheses (see Figure 2b). The direct ef-fect of the training on business creation was pos-itive and significant (� � .14, p � .05) supportingHypothesis 1b. Furthermore, we found significantpaths from entrepreneurial action (� � .14, p � .01)and from opportunity identification (� � .14,p � .05) to business creation. We also found asignificant effect of the training on business oppor-tunity identification (� � .25, p � .01). The directeffect of the training on entrepreneurial actionwas not significant (� � .09, ns.); this correspondsto our findings that there is no direct effect but anindirect effect of the training on entrepreneurialaction through the action-regulatory factors. Fur-thermore, we found a significant indirect effect ofthe training on business creation through entrepre-neurial action and business opportunity identifica-tion (indirect effect � .05, p � .05). Given that themodel with a path from the training to businesscreation showed a better model fit and that thepath was significant, the findings suggests thatentrepreneurial action and business opportunityidentification partially mediate the effect of thetraining on business creation (Preacher & Hayes,2008). Thus, H6 was partially supported.

DISCUSSION

Our aim here was to investigate how an action-based entrepreneurship training transmits its ef-fects on entrepreneurial action and business cre-

ation. We developed a general model integratingshort- and long-term training outcomes (i.e.,action-regulatory factors, entrepreneurial action,business opportunity identification, and businesscreation). We postulated that the training has aneffect on entrepreneurial action through action-regulatory mechanisms and thus, that action-regulatory mechanisms play an important role inthe process leading to business creation. We de-veloped an action-based entrepreneurship train-ing following guidelines by action regulation the-ory (Frese & Zapf, 1994). We evaluated the trainingin a randomized controlled field experiment. Our12-month evaluation study showed that the train-ing had a significant impact on business creation:Students in the training group were significantlymore likely to start a new business than studentsin the control group. In line with our hypotheses,the training had significant effects on entrepre-neurial goal intentions, action planning, actionknowledge, and entrepreneurial self-efficacy. Ac-tion knowledge and the interaction between entre-preneurial goal intentions and action planningwere significant predictors of entrepreneurial action.The action-regulatory factors fully mediated the ef-fect of the training on entrepreneurial action. Fur-thermore, the training had positive effects on busi-ness opportunity identification; business opportunityidentification and entrepreneurial action partiallymediated the effect of the training on starting a newbusiness. We think that our findings have severaltheoretical and practical implications.

Theoretical Implications

Several scholars have emphasized that entrepre-neurship trainings should be action-based to pro-mote entrepreneurial action and business creation(Barr et al., 2009; Fiet, 2001a; Gorman et al., 1997;Honig, 2004; Oosterbeek et al., 2010; Rasmussen &Sorheim, 2006). In general, entrepreneurship train-ings have a positive effect (Martin et al., 2013);however, the theoretical questions of why and howsuch trainings exert an effect have not been inves-tigated. We showed that action-regulatory factorsmediated the effect of the training on entrepre-neurial action. To our knowledge, we present thefirst study that investigates a comprehensive set ofmediators linking an action-based entrepreneur-ship training and entrepreneurial action. Thestudy thus contributes to developing a theory ofaction-based entrepreneurship trainings that ex-plain why and how these trainings work. Our find-


ings suggest that action-regulatory factors are im-portant mechanisms underlying the relationshipbetween action-based entrepreneurship trainingsand entrepreneurial action. We thus provide anaction-regulatory explanation for the positive ef-fects of such trainings.

Our study also adds to the extant literature ondrivers of entrepreneurial action. Scholars haverecently emphasized that entrepreneurial action isfar from being understood, and they have calledfor more research shining a spotlight on it (Venkat-araman, Sarasvathy, Dew, & Forster, 2012). Previ-ous studies on drivers of entrepreneurial actionhave more or less explicitly referred to expectancy-value models to explain entrepreneurial action.For example, theoretical and empirical studieshave investigated the role of uncertainty by sug-gesting that assessments of feasibility and desir-ability influence entrepreneurial action (McKelvie,Haynie, & Gustavsson, 2011; McMullen & Shep-herd, 2006). Similarly, scholars have examinedvalue and expectations in the form of images(Mitchell & Shepherd, 2010); perceptions (Edelman& Yli-Renko, 2010); or outcome and ability expecta-tions (Cassar, 2010; Koellinger, Minniti, & Schade,2007; Townsend et al., 2010). The line of reasoningunderlying this research is that more positive val-ues and expectations translate into stronger entre-preneurial goal intentions and eventually lead toentrepreneurial actions (Ajzen, 1991; Bird, 1988;Kolvereid & Isaksen, 2006; Krueger, Reilly, &Carsrud, 2000).

However, scholars have questioned the strengthof the relationship between intentions and actions,calling for a broader view on predictors of entre-preneurial action (Davidsson & Honig, 2003; Katz,1990; Souitaris et al., 2007). Scholars have arguedthat intentions are the starting point of entrepre-neurial actions, but other action-regulatory factorsare necessary to translate intentions into actions(Frese, 2009; Gollwitzer, 1999). We elaborated howaction-regulatory factors beyond entrepreneurialgoal intentions influence entrepreneurial action.Our theoretical model thus adds to the literatureby providing a more comprehensive framework ondirect antecedents of entrepreneurial action. Thetheoretical model goes beyond other theories thatseek to explain action, such as goal-setting theory(Locke & Latham, 2002) or the theory of plannedbehavior (Ajzen, 1991) because these theoriesdo not discuss the importance of action planning oraction knowledge as explicitly as does action reg-ulation theory.

Specifically, the significant finding of the inter-action between entrepreneurial goal intentionsand action planning contributes to the extant liter-ature, which assumed a direct effect of goal inten-tions on action (e.g., Bird, 1988; Krueger et al., 2000).We found that entrepreneurial goal intentionsalone had only a weak (nonsignificant) effect onentrepreneurial action. Our finding suggests thatentrepreneurial goal intentions must be comple-mented with action plans to lead to entrepreneur-ial actions. This finding is in line with researchdemonstrating how implementation intentions re-duce the gap between goal intentions and actions(Ajzen, Czasch, & Flood, 2009; Gollwitzer, 1999). Im-plementation intentions are related to action plansas they are formed through specifying the when,where, and how of actions (Gollwitzer, 1999). Con-sequently, theoretical models predicting entrepre-neurial action increase their validity by consider-ing the combined effects of goal intentions andaction planning. Furthermore, the significant find-ing of action knowledge adds to research that hasstudied the importance of critical know-how forentrepreneurial action (Baum & Bird, 2010; Edel-man et al., 2008). Action knowledge is an importantaction-regulatory factor that provides the cognitivebasis for smooth and efficient actions.

With regard to our findings that entrepreneurialgoal intentions in combination with action plan-ning are two factors important for entrepreneurialaction, we note that other entrepreneurship schol-ars have suggested that approaches focusing lesson goals and planning might be more effective.For example, Sarasvathy (2001) has suggestedthat effectuation is a promising approach for en-trepreneurs to take action because it helps to dealwith uncertainties and contingencies. Effectuationmeans that entrepreneurs do not specify a goaland then look for the means they need to achievethe goal, but start with the means available tothem and then set out to test what effects they cancreate with those means. Similarly, Baker and col-leagues (Baker & Nelson, 2005; Baker, Miner, & Ee-sley, 2003) have described the usefulness of brico-lage for entrepreneurship. Bricolage emphasizesthe importance of not planning in detail but impro-vising and making do by recombining the re-sources at hand. We do not think that action plan-ning on the one hand and effectuation andbricolage on the other are two opposing ap-proaches. In effectuation, entrepreneurs must haveat least a rough idea of what they want to achievewith their available means. This requires a certain


degree of action planning about how to employ theresources. Also in bricolage, entrepreneurs’ ac-tions are not random or based on trial and error;rather, planning and execution of action converge,which means that entrepreneurs do some short-term planning that is particularly responsive toenvironmental demands. This means that actionplanning has an important function also in effec-tuation and bricolage.

The significant effects of entrepreneurial actionand business opportunity identification on busi-ness creation support theories ascribing a centralrole to business opportunity identification and ex-ploitation (entrepreneurial action) for entrepre-neurship (Shane & Venkataraman, 2000). Further-more, our findings showed that these two factorsonly partially mediated the effect of the training onstarting a new business. There was still a signifi-cant direct effect of the training. This means thatthe training affected additional factors relevant forstarting a business. For example, it may be thecase that the groups formed in the training pro-vided social capital that lasted even beyond thetraining, which then helped to successfully start abusiness (Davidsson & Honig, 2003).

Last, we think that the context of our study alsocontributes to the entrepreneurship literature. Weconducted our study in a developing country,where entrepreneurship plays an important rolefor economic development and wealth creation(Mead & Liedholm, 1998). Developing countriesneed to establish a sound base of small enter-prises to create a sufficient number of job opportu-nities and to boost their economic development(Nelson & Johnson, 1997). Scholars note that entre-preneurship research has so far almost exclusivelyfocused on North America and Europe (Bruton, Ahl-strom, & Obloj, 2008); however, people living indeveloping countries form the majority of the world(Arnett, 2008). Therefore, developing and testingtheoretical models that explain successful entre-preneurship in developing countries is an impor-tant scholarly task. Our study is a step in thisdirection.

Practical Implications

Promoting entrepreneurship is a key issue onmany policy agendas in both developing and de-veloped countries (Nelson & Johnson, 1997; Nkirina,2010). Entrepreneurial firms contribute to the cre-ation of new jobs, growth in productivity, and tonational GDP growth (Carree & Thurik, 2003, 2008;

Van Praag & Versloot, 2007). Governments haveintroduced regulatory reforms and more entrepre-neurship courses to promote entrepreneurship, butthe question is which of these interventions arereally effective? We evaluated our training over aperiod of 12 months and provided evidence that thetraining is effective in promoting entrepreneur-ship. The training increased the number of entre-preneurs. The training put a particular focus onaction. Based on action regulation theory (Frese &Zapf, 1994) our training method was particularlyhelpful in changing students’ behavior and inprompting them to become entrepreneurs after thetraining course. This training may offer an optionfor governments and development or aid agenciesthat seek to further establish entrepreneurship ed-ucation. Particularly in countries such as Uganda,where the unemployment rate is very high, action-based entrepreneurship trainings may provide thenecessary skills and knowledge to start a businessand to pursue the career option of an entrepreneur.

It is important to note, however, that action-based courses may be in conflict with the require-ments of academic courses. Courses that aregraded as part of the credit system have to meetacademic standards, which may be difficult tocombine with the more open setting of a trainingthat requires students to go back and forth in theentrepreneurial process; starting a new businessis an idiosyncratic process that requires flexibility.It may be difficult to put such a course into stan-dardized grading schemas (Rasmussen & Sorheim,2006; Solomon, 2007). We suggest to offer add-on,practical courses for students about to finish theirstudies.

Our study has also practical implications forfuture studies evaluating the effectiveness ofentrepreneurship trainings. Entrepreneurial goalintentions alone may have a positive effect on ac-tion; however, this effect is not so strong. We foundthat entrepreneurial goal intentions are necessarybut not sufficient predictors of action; entrepre-neurial goal intentions instigate actions only whenentrepreneurs specify what they will do and howthey will do it. This finding implies that interven-tion programs focusing only on increasing thestrength of entrepreneurial goal intentions withoutincreasing the level of action planning do not havea positive impact on entrepreneurship. In addition,entrepreneurial goal intentions and action plan-ning must be part of the evaluation to assess theeffectiveness of training interventions.


Strengths, Limitations, and Implications forFuture Research

We think that the methodology of our study is acontribution to the literature. By conducting a ran-domized field experiment with a control group, weprovide a rigorous test of the hypothesis thataction-regulatory factors have an important func-tion for entrepreneurial action and starting a busi-ness. Martin and colleagues (2013) have noted thatmore evaluation studies are needed that use a pre-posttest design with a randomized control group.We employed a longitudinal design with a ran-domized control group examining the participantsbefore the training and two times after the train-ing. This design allowed us to make causal con-clusions regarding the impact of the training. Ourstudy thus contributes to the growing body of en-trepreneurship education research in higher (ter-tiary) education (Bechard & Gregoire, 2005; Ka-bongo & Okpara, 2010; Katz, 2003; Klandt, 2004;Solomon, 2007) and overcomes some methodologi-cal problems of previous research evaluating en-trepreneurship education, such as lack of basiccontrols in the form of pretesting, lack of longitu-dinal designs, lack of randomized control groups tocompare the intervention to a nontreatment controlgroup, or an overreliance on subjective measuresinstead of objective performance measures to as-sess the impact of the intervention (Glaub & Frese,2012; Henry, 2004; Honig, 2004; McMullan, Chris-man, & Vesper, 2001; Souitaris et al., 2007; VonGraevenitz et al., 2010).

We note that the context of our study might be apotential limitation. We conducted it in Uganda,which is among the top countries in entrepreneur-ial activity (Namatovu, Balunywa, Kyejjusa, &Dawa, 2011) and ranks 193rd in gross national in-come (US $460 per capita; World Bank, 2010). Animportant question is whether our findings aregeneralizable and whether they also hold in more-developed countries. The higher propensity inUganda to engage in entrepreneurial activity mayfacilitate starting a real venture. Students inUganda are probably more inclined toward entre-preneurship than those in other parts of the world.In fact, we observed in the training that the stu-dents quickly responded to our request to engagein real entrepreneurial activities outside the class-room. However, research shows that in other set-tings, students also have a positive attitude to-ward becoming involved in the start-up process ofa real business during a training course (Barr et

al., 2009; Oosterbeek et al., 2010; Rae, 2009; Rasmus-sen & Sorheim, 2006). This suggests that the gen-eral concept of the training is applicable in differ-ent contexts.

We also note that depending on the context, dif-ferent aspects of the four action-regulatory factorsmight be more or less important. For example, ac-tion planning might be more important in cultureswith high uncertainty-avoidance (Rauch, Frese, &Sonnentag, 2000). Also, in countries with a highlyregulatory business environment, action knowl-edge about how to deal with legal and regulatoryissues might be more important than in countrieswhere the regulatory framework is less pro-nounced (e.g., Uganda). In the latter countries, ac-tion knowledge about more informal proceduresmight be more important, for example, how to pro-tect business concepts independent of legal regu-lations. Furthermore, we note that there might bedynamic relationships between the action-regulatory factors (Lord, Diefendorff, Schmidt, &Hall, 2010). For example, there may be recursiveeffects between action knowledge, entrepreneurialgoals, and action planning. Future research inves-tigating these relationships would contribute toour understanding of how action-regulatory factorsdynamically influence entrepreneurial action.

Related to the question of the generalizability ofour findings is the fact that we were able to ob-serve an increase in business owners within aperiod of 12 months. We think that the generallyhigh level of entrepreneurial activity and the eco-nomic conditions of a developing country foster anaccelerated accomplishment of the entrepreneur-ial process. Thus, we expect that in other contexts,it may take longer for the training to show itspositive impact on entrepreneurship. This calls forlonger evaluation periods in more developed con-texts, such as the United States or Europe. We alsonote that all students applied for the training,meaning that they were generally interested inentrepreneurship. This might contribute to theirfast implementation of new businesses. Further-more, it might be possible that our training is par-ticularly effective in combination with studentswho are inclined toward entrepreneurship. Al-though discussions with the students revealed thatsome had not considered entrepreneurship to be acareer option before the training, it is important toreplicate our study with students of a more generalpopulation.

Also important is to consider some measurementissues. Our measure of entrepreneurial goal inten-


tions may be cleaner than some other measures,and thus, it may be more conservative. Some mea-sures of goal intentions include a prediction, suchas “It is likely that I will personally own a smallbusiness in the relatively near future” (Crant, 1996)or “How likely are you to be working full-time forthe new business in one year from now?” (Kolver-eid & Isaksen, 2006). Such a prediction probablyincludes not only the intention, but also actionplanning, which means that these measures maycover aspects of both constructs.

With regard to our findings, we note that theeffects may have been partly caused by trainers’heightened attention toward or expectations of thestudents (see Eden, 1990; Rosenthal, 1994). Re-search has shown that these effects may increasesubjects’ performance on a given task. It is impor-tant to note that in the research on attention andexpectation effects, the subjects show higher per-formance on tasks they are regularly working on.Starting a new business, however, is a life-changing event with implications for one’s entirefuture career. We therefore think that attention orexpectation effects play only a minor role in ourstudy. It is also possible to argue that the signifi-cant effects are due to demoralization or discour-agement in the control group, as they did not re-ceive the training. However, examining the meansof the training group and the control group indi-cates that the significant effects are driven by anincrease in the training group rather than a de-crease in the control group.

With regard to the general objective of our train-ing to increase the start-up rate, we have to notethat some scholars have questioned the approachof generally increasing the number of start-ups(Shane, 2009). Instead, a general objective of entre-preneurship education should be to generate moreeconomic and social value (Neck & Greene, 2011).We conducted our study in a developing country,and our training participants were undergradu-ates. In developing countries, entrepreneurship isan important alternative because of unfavorablejob market conditions (Mead & Liedholm, 1998).However, a major problem in developing countriesis that a large of part of entrepreneurship isnecessity-motivated or marginal businesses withlittle potential for creating wealth (Van Stel, Car-ree, & Thurik, 2005). Research has shown that en-rollment in tertiary education has a positive effecton entrepreneurship that is not motivated by ne-cessity (Van Stel, Storey, & Thurik, 2007). Similarly,higher education has a positive effect on trans-

forming informal businesses into formal ones(Sonobe, Akoten, & Otsuka, 2011). Thus, increasingthe number of start-ups among undergraduatesshould promote the type of entrepreneurship thatcreates economic and social value.

CONCLUSIONS

Our study showed that action-regulatory mecha-nisms are of central importance in entrepreneur-ship, and they help to explain how action-basedentrepreneurship trainings have a positive impacton entrepreneurship. Promoting entrepreneurshipis possible if during trainings, trainers take intoconsideration action-regulatory mechanisms im-portant for entrepreneurial action.

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Michael M. Gielnik ([email protected]) is a professor for HR Development at theLeuphana University of Lüneburg, where he received his PhD. Gielnik’s research interests areentrepreneurship, in particular action-based entrepreneurship trainings and the entrepre-neurial process. He has taken a special interest in entrepreneurship in developing countries.

Michael Frese holds a joint appointment at NUS Business School and at the University ofLüneburg. Frese received his doctorate from the Technical University of Berlin. His researchincludes the psychology of entrepreneurship, innovation, personal initiative, training, andlearning from errors. Guiding concepts are evidence-based management and action regula-tion theory.

Audrey Kahara-Kawuki is an enterprise development consultant with Zebra Solutions, Ltd. inUganda. Kahara-Kawuki holds a master’s in business administration majoring in smallbusiness management/entrepreneurship. Her research interests are entrepreneurship, gen-der, and innovation.

Isaac Wasswa Katono holds an MBA from Makerere University and is a PhD candidate(Entrepreneurship) of the University of Cape Town. Wasswa Katono is the associate dean offaculty of Business and Administration, Uganda Christian University, as well as head, De-partment of Management and Entrepreneurship. His research interest is culture andentrepreneurship.

Sarah Kyejjusa is a lecturer in the Department of Accounting at Makerere University BusinessSchool. She is also a trainer at the MUBS Entrepreneurship Centre. Kyejjusa holds an MSc inaccounting and finance.

John C. Munene is an industrial/organisational psychologist working in Makerere UniversityBusiness School as a PhD Programme director. Munene received his PhD in occupationalpsychology from Birkbeck College, London University. His research interests and consultingexperience are in personnel, management, and organizational psychology. He is currentlyexploring relational human resources for people management in micro- and small enterprisesin East Africa.

Muhammed Ngoma is the dean of the faculty of Graduate Studies and Research at MakerereUniversity Business School, Uganda. Ngoma earned his PhD in business administration fromMakerere University. His research interests are firm internationalization, international entre-


preneurship, business planning and start-ups, strategic planning, and marketingmanagement.

Rebecca Namatovu-Dawa is a PhD candidate at Gordon Institute of Business Science in theUniversity of Pretoria. Namatovu-Dawa holds a teaching position in Makerere UniversityBusiness School and is a board member of the Global Entrepreneurship Research Association.Her research interests revolve on the entrepreneurial process, specifically resource mobiliza-tion in constrained environments.

Florence Nansubuga is a senior lecturer at Makerere University School of Psychology. Sheholds a PhD in organizational psychology from Makerere University. Her research areas ofinterest include strategic management for small-scale entrepreneurs and organizationallearning through reflection, employee engagement, competence development, and talentmanagement.

Laura Orobia is a certified public accountant and a senior lecturer at Makerere UniversityBusiness School. Orobia holds a PhD from Makerere University, Uganda. Her research interestis small-business management in a developing country context; in particular access tofinance, financial management, business planning, and improving management issues.

Jacob L. Oyugi is a senior lecturer in the Department of Management Science, School ofManagement and Entrepreneurship, Kyambogo University, and associate consultant withUganda Management Institute. Oyugi earned his PhD from Kenyatta University, Nairobi. Hisresearch interest is entrepreneurship focusing on entrepreneurship education, training, anddevelopment in universities.

Samuel Sejjaaka is the deputy principal of the Makerere University Business School andassociate professor in accounting and finance. He is also a fellow of the Association ofChartered Certified Accountants and a Certified Public Accountant of Uganda. Sejjaaka holdsa PhD in accounting and finance from Makerere University. His working experience includesover 20 years as a financial consultant.

Arthur Sserwanga is the vice chancellor of Muteesa 1 Royal University. Sserwanga earned hisPhD in entrepreneurship from Makerere University. His current research interest is entrepre-neurial quality.

Thomas Walter is a senior advisor to the EAC Secretariat on Industrialisation and Pharma-ceutical Sector Promotion and to the GIZ Programme Support to the EAC Integration Process.Walter received his Habilitation in business administration from Philipps-University Mar-burg, Germany. His research interests are entrepreneurship, regional integration, healthfinancing, and pharmaceutical sector promotion.

Kim Marie Bischoff is currently a PhD student at Leuphana University of Lüneburg, Germany.She graduated in psychology from the University of Giessen. Bischoff’s research interests arein the field of entrepreneurship: entrepreneurship trainings, entrepreneurship in developingcountries, and the interaction of individual and economic factors in predictingentrepreneurship.

Thorsten Dlugosch is currently a consultant for planning and controlling of rollouts with DBNetz AG. Dlugosch earned his diploma in psychology from the Justus Liebig University ofGießen. His research interests are entrepreneurship, training and education, and faking.


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