KEMU JOURNAL ARTICLE-APRIL 2010
Entrepreneurial Intention: Triggers of nascent entrepreneurs’ opportunity scanning.
2.0 Theoretical framework
Relevant researches on the behavior indicate that intentions has a better explanation ability on entrepreneurship than other factors such as personality traits( Wu and Wu, 2008), Therefore, understanding behavior intention is a necessary process before taking any action. This is because it is the decision to initiate behavior (Wu and Wu, 2008). Thus, entrepreneurial intention has become a key element for research in order to understand the new-venture creation process (Bird, 1988).
Several entrepreneurial researches have been conducted focusing both on the personality traits of the entrepreneur or the situational factors and currently on the influence of the contextual factors (Li��n, Urbano and Guerrero, 20090. From the first foci, it has resulted into a disappointingly small explanatory power and even smaller predictive validity (Turker and Selcuk, 2008). Cognitive basis have emerged to explain better the phenomenon: “why do some people chose to be self-employed or to start their own enterprises while others prefer traditional salary-based jobs”. Thus, entrepreneurial intention perspective has provided a new research focus and offers a means of explaining and predicting entrepreneurship (Wu and Wu, 2008).
The main theory-driver models adopted entrepreneurial intention researchers to analyze the potential entrepreneurs are: the Entrepreneurial Event (Shapero and Sokol, 1982) and the Theory of Planned Behavior (Ajzen’s, 1991). Shapero’s model focuses on the phenomenon of the entrepreneurial event and depends on the propensity to act. These perceptions are the product of cultural and social environments and they determine personal choice (Shapero and Sokol, 1982). On the other hand, Ajzen’s (1991) model explains how the cultural and social environment affects human behavior. It is based on individual’s intention, which is the results of three determinants: personal attitude towards the behavior, subjective norms and perceived behavioral control.
From this point of view, studies have compared theory of planned behavior and Shapero’s entrepreneurial events and pointed out that the two models overlap in two elements. Perceived behavior control in TPB is similar to Shapero’s perceived enterprise feasibility (Krueger and Brazeal, 1994) and they are conceptually associated with perceived self-efficacy (Bandura, 1997). TPB’s personal attitude towards behavior and subjective norms corresponds to SEE’s perceived enterprise desirability. Both approaches have been widely used to study entrepreneurship, and a number of studies have tried to compare their relative explanatory strengths (for example, Krueger, Reilly and Carsrud, 2000). The results have illustrated an inherent consistency in these two models.
The present study adopts the TPB as a valuable tool for understanding the process of new enterprise creation regardless of cultural differences. This is because of its versatility and robustness to support the broader use of entrepreneurship research (McMillan and Katz, 1992).
In the model, personal attitude toward behavior “refers to the degree to which a person has a favorable or unfavorable evaluation appraisal of the behavior in question”, subjective norms “refer to the perceived social pressure to perform or not to perform the behavior”, perceived behavioral control “refers to the perceived ease or difficulty of performing the behavior and it is assumed to reflect past experience as well as anticipated impediments and obstacles (Ajzen’s, 1991). The model was integrated by three types of factors: the motivational antecedent factors, the environmental (exogenous) factors and situational factors (control variables).
2.1 Motivational Factors.
Based on the theory of planned behavior (TPB) approach, it is argued that, individuals take decision to create a new venture based on three motivational factors (antecedent variables); the personal attitude towards the behavior, the subjective norms, and the perceived behavioral control (Ajzen, 1991). These antecedent variables clarify the influence that precedes the relationship. (Mugenda, 2008 pg 122). According to Ajzen (2002) and Kolvereid (1996), the personal attitude towards the behavior basically refers to the attractiveness of the proposed behavior or the degree of which the individual holds a positive or negative personal valuation about being an entrepreneur. Therefore, in this sense, the personal attitude towards the behavior is a key concept concerning the perception of desirability that affects entrepreneurial intention. Therefore, the following hypothesis is stated:
H1a. Personal attitude towards entrepreneurship has positive influence on entrepreneurial intentions on Kenyan university students.
The second motivational factor is subjective norms which measure the perceived social pressure from family, friends or significant others to perform the behavior at hand (Ajzen, 1991). This subjective norm refers to the perception that “reference people” may or may not approve the decision to become an entrepreneur (Ajzen, 2001). According to Armitage and Conner (2001), generally these subject norms tend to contribute more weakly to entrepreneurial intention for persons with strong internal locus of control than those with a strong action orientation (Ajzen, 2002 and Bagozzi, 1992). Several studies in entrepreneurship literature have found no significant direct relationship between subjective norms and entrepreneurial intentions (Wu and Wu, 2008, Krueger et al; 2000 and Autio, Keeley, Klofsten, Parker and Hay, 2001) While others have simply omitted subjective norms (Peterman and Kennedy, 2003; Veciana et al., 2005). However, social capital literature finds evidence indicating that these norms favorably affect the attitude towards the behavior and the perceived behavioral control (Cooper, 1993, Linen and Santos, 2007). Therefore, with the argument on the existence of interactions and indirect effects of subjective norms on intention, the second set of hypothesis is stated as follow:
H1b. Subjective norm has a positive impact on the Kenyan university students’ entrepreneurial intentions.
H1c. Subjective norm has a positive influence on the Kenyan university students’ personal attitude towards the entrepreneurial behavior.
H1d. Subjective norm has a positive influence on the Kenyan university students’ perceived behavioral control.
The third motivational factor is perceived behavioral control which refers to, the perceived easiness or difficulty of becoming an entrepreneur (Ajzen, 1991). The importance of this variable in the new-enterprise creation process is found in its predictive capacity as it is reflected in the perception that the individual will be able to control that behavior (Ajzen, 2002). This concept is quite similar to self -efficacy (Bandura, 1997), and perceived feasibility (Shapero and Sokol, 1982). All the three concepts refer to the sense of capacity regarding the fulfillment of venture -creation behaviors. However, according to Ajzen (2002), the recent work has emphasized the difference between perceived behavioral control and self -efficacy. Perceived behavioral control would include not only the feeling of being able, but also the perception about controllability of the behavior (Li��n and Chen, 2009). This element could be influenced by different processes, such as role modeling, social persuasion, enactive mastery and judgments (Bandura, 1997). This leads to the following hypothesis:
H1e. perceived behavioral control has a positive influence on the Kenyan university student’s entrepreneurial intention.
The relative contributions of these three motivational factors to explaining entrepreneurship intentions are not established beforehand (Li��n and Chen, 2009). The specific configuration of relationships between these constructs would have to be empirically determined for each specific behavior (Ajzen, 1991, 2002). These motivational elements have been constantly supported by several empirical studies (Kolvereid 1996; Krueger, et al; 2000).
2.2 Environmental factors.
The theoretical framework for the relationship between educational background and entrepreneurial intentions.
Educational levels and component of Theory of Planned Behavior (TPB). It is generally accepted that globalization has brought in its wake both positive and negative changes to the socio-economic and cultural infrastructure of developed and developing nations (Millman, Matlay and Liu, 2008). This impact on all aspects of society with a far reaching effect, and it actually affect younger individuals in transition from education into workforce (Millman et. al., 2008). According to ILO (2004b), in recent years, unemployment has increased globally and it is affecting young people and they are being faced with higher levels of economic and social uncertainty. Therefore, with such challenges, different education levels are expected to determine the personal attitude among the young people.
According to Wu and Wu (2008), this personal attitude includes emotional factors and factors to appraise. The former are based on person’s subjective psychological status, while the later are judged by “expectancy – value model”. According to Robinson, Stimpson, Huefner and Hunt (1991), these personal attitudes are open to change and therefore, educators and practitioners can influence the entrepreneurial attitudes. Therefore, cultivating an attitude of innovation, achievement, and self-esteem, educators can change the student’s perception and feeling of entrepreneurship. According to Wu and Wu (2008), highly educated people may not choose self-employment because of two reasons; (1) highly educated persons may be earning more as employees than they would as self-employed (2) due to the higher inherent risks in the operation of small enterprises compared to large ones, the earnings stream is less secure as self employment than as a mere employee. On the other hand, Kolvereid and Moen’s (1997) in their research results suggested that, graduates with entrepreneurship education have stronger entrepreneurial intentions than others without the entrepreneurship education. Therefore, based on the arguments above, the hypotheses to be tested in the present circumstance are:
H2a. It is expected that, Kenyan university students interest in entrepreneurship increases as one goes up the level of education (from; diploma-degree-master to PhD).
H2b. It is expected that Kenyan university students who have low level of education perceive more social pressure of not being entrepreneurs than those who have higher level.
H2c. It is expected that Kenyan students who have achieved higher level of education have more perceived behavioral control than those who have not.
2.3 Control Variables.
Mugenda (2008, pg 118) states that, if a researcher suspects that a certain variable is likely to influence the research results, the individual should control that variable in the study. In this present circumstance, the control variables refer to demographic information, age, gender, role models, self-employment experience, and job experience, place of birth, religion or denomination. According to Robinson, Stimpson, Huefner and Hunt (1991), these variables have been used to define a profile of a typical entrepreneur. The researcher should identify such variables whose omission from the study may influence the results. In the literature, the character of the relationship has been revealed. For example; the influences of role models on self -efficacy, personal attraction and subjective norms (Boyd and Vozikis, 1994); the relationship between gender and self-efficacy (Zhao, Hills and Siebert, 2005); age or job experience as factors affecting an individual’s natural tendency to launch an enterprise (Robinson et al; 1991); the influence of gender on personal attitudes towards new venture creation and relevancy of personal experience and social influences (Kolvereid, 1996). In this sense, this study will consider the inclusion of eight control variables in the analysis: age, gender, self- employment experience, job experience, role models, and place of birth, religion and denomination.
Methodology
In exploring the relationship between Kenyan university students’ education level and their entrepreneurial intentions, data for the analysis were collected from two public (University of Nairobi and Jomo Kenyatta university of Agriculture and Technology) and two private university (Kenya Methodist university and Daystar University) senior students. We regarded these respondents appropriate for this study as they are facing imminent career decisions. Entrepreneurial intention was investigated based on Ajzen’s (1991) model. This model is one of the robust models since it provides good results in very diverse fields including the choice of professional career (Li��n and Chen, 2006).
Educational level data were obtained by means of questionnaire and measured through a likert-type scale with seven items. In particular, close reference was made to the methods used in the EIQ developed by Li��n and Chen (2009). The questionnaire took 15 minutes to complete the anonymous questionnaire in class with prior arrangement with the professor. The analysis was made in two parts: descriptive statistics to examine the correlation of educational level and motivational antecedents of Entrepreneurial intention and path analysis to define the relationship between entrepreneurial intention and its antecedents,
Results and Discussion
Entrepreneurial Intentions and Its antecedents.
Reliability analysis of the questionnaire was computed by the more traditional Cronbach’s alpha and by the correlated item-total correlation (Nunnally, 1978). Inappropriate items were excluded and the following items were retained as the construction of the structural equation modeling analysis. The Cronbach’s alpha values obtained exceeded the 0.60 cut-off related to personal attitude, subjective norm, perceived behavioral control and entrepreneurial intentions. The value for reliability consistency in the constructs were as follow; 0.895, 0.744, 0.891, and 0.912 respectively. The correlated item-total correlations were positive and significant (Between 0.51 and 0.80). Therefore, the proposed constructs were considered as sufficiently reliable to measure the information for which they were designed for.