THE ROLE OF ANTICIPATED AFFECTIVE AMBIVALENCE IN THE ENTREPRENEURIAL PROCESS

Transcription

1 THE ROLE OF ANTICIPATED AFFECTIVE AMBIVALENCE IN THE ENTREPRENEURIAL PROCESS Leonidas Zampetakis - lzabetak@dpem.tuc.gr TECHNICAL UNIVERSITY OF CRETE, DEPARTMENT OF PRODUCTION ENGINEERING & MANAGEMENT Manolis Lerakis - TECHNICAL UNIVERSITY OF CRETE, DEPARTMENT OF PRODUCTION ENGINEERING & MANAGEMENT Konstantinos Kafetsios - k.kafetsios@psy.soc.uoc.gr UNIVERSITY OF CRETE, DEPARTMENT OF PSYCHOLOGY Vassilis Moustakis - vmoustakis@gmail.com TECHNICAL UNIVERSITY OF CRETE, DEPARTMENT OF PRODUCTION ENGINEERING & MANAGEMENT SIG: ENTREPRENEURSHIP TRACK: ENTREPRENEURSHIP GENERAL TRACK - ENTREPRENEURSHIP EDUCATION Acknowledgements: The research reported in this paper was fully supported by the ARISTEIA Action ( EMO-ENTRE program) of the Operational programme Education and Life Long Learning and is co-funded by the European Social Fund (ESF) and National Resources. The views, opinions and results are the sole responsibility of the authors. Access to this paper is restricted to registered delegates of the EURAM 2013 (European Academy of Management) Conference.

2 The role of anticipated affective ambivalence in the entrepreneurial process ABSTRACT Recent theoretical and empirical studies suggest that emotions play a significant role in the entrepreneurial process. In the present study, we investigated the role of anticipated affective ambivalence (that is, future oriented affect relating to the expectancy of feeling both positive and negative affect) from nascent entrepreneurship in students entrepreneurial intent. Based on extant theory, we propose that students anticipated affective ambivalence moderates the impact of attitudes towards entrepreneurship, perceived behavioral control and subjective norm, on entrepreneurial intent. We empirically tested our propositions using a sample of 1624 students from different universities in Greece and data were analyzed using structural equation modeling. We discuss the implications of our results in the light of the increasing interest of universities in Europe to promote entrepreneurship and develop suitable educational programs. Keywords: Affect, ambivalence, entrepreneurial intent

3 The role of anticipated affective ambivalence in the entrepreneurial process. ABSTRACT Recent theoretical and empirical studies suggest that emotions play a significant role in the entrepreneurial process. In the present study, we investigated the role of anticipated affective ambivalence (that is, future oriented affect relating to the expectancy of feeling both positive and negative affect) from nascent entrepreneurship in students entrepreneurial intent. Based on extant theory, we propose that students anticipated affective ambivalence moderates the impact of attitudes towards entrepreneurship, perceived behavioral control and subjective norm, on entrepreneurial intent. We empirically tested our propositions using a sample of 1624 students from different universities in Greece and data were analyzed using structural equation modeling. We discuss the implications of our results in the light of the increasing interest of universities in Europe to promote entrepreneurship and develop suitable educational programs. Keywords: Affect, ambivalence, entrepreneurial intent, nascent entrepreneurship 1

4 1. Introduction Entrepreneurship and entrepreneurial culture are receiving an increased amount of attention in both academic research and practice. Entrepreneurship is linked with value creation and as such, it is thought to have a significant impact on economic growth, continuous business renewal, and employment. Empirical research supports positive links between entrepreneurial activity, economic growth and innovation. Thus, it is apparent why there is an increased interest in educational programs designed to encourage entrepreneurship and to provide a better infrastructure for business start-ups (Kuratko, 2005; Vesper and Gartner, 1997). However and despite the high level of activity, results on the effectiveness of formal entrepreneurship education, remain inconclusive (Gibb, 2002; Oosterbeek, et al., 2010; Hindle and Klyver, 2007; Zampetakis et al., 2011). Educational programs of entrepreneurship tend to place more emphasis on technical skills (i.e. business plan creation) than the person as a whole or the management of the very often stressful entrepreneurial process. Studies also tend to be inconclusive on whether entrepreneurship programmes actually promote entrepreneurship or whether this influence is attributable to selection and self-selection in these programmes of students with entrepreneurial potential (Zampetakis et al., 2011). Affect is a key aspect of entrepreneurship (Baron, 2008). Entrepreneurs experience a variety of emotions during the process of identifying, founding, developing and exiting from their businesses. The term emotion involves both cognitive and affective processes (Lazarus, 1991; Roseman and Smith, 2001). Here, we use the term affect as a broad general term involving first person experience which is closely linked to action tendencies. Affect may represent important explanation of entrepreneurial belief, perception, and intention. Affect may be extremely important for business start-up as it influences how individual process information 2

5 (Baron, 2008). Although, it is now understood that affective states exert a significant influence on decision making and behavior (e.g., Forgas, 1995; Lazarus, 1991; Roseman and Smith, 2001) the comprehensive and systematic study of affect is just emerging in the field of entrepreneurship (e.g., Cardon et al., 2009; Hayton and Cholakova, 2011; Foo, 2011; Foo et al., 2009). Yet these sources of beliefs, perceptions, and intentions are not captured in existing models of the process (e.g., the theory of planned behavior- TPB (Ajzen, 1991). Up to date, the role of affect in entrepreneurship education research has received little attention. The present paper aims at bridging the gap between advances in affect theory and entrepreneurial inclination. The paper is structured as follows. First, we provide a brief synthesis of the existing literature and explain the role of affect in the entrepreneurial process, along with the potential role of anticipated affect and affective ambivalence on the theory of planned behavior. We then explain our methodology and present our research findings. The paper ends with a discussion of the implications and limitations of the study. 2. Literature review 2.1 The role of affect in the entrepreneurial process. New venture creation is a key issue in the field of entrepreneurship (Shook et al., 2003) with the entrepreneur lying at the heart of the entrepreneurial process. Shane and Venkataraman (2000) define an entrepreneur as an individual who recognizes or discovers an opportunity to create something new (e.g. new products or services, new markets, new production processes or new ways of organizing existing technologies) and who uses various means to exploit or develop this opportunity. 3

6 Entrepreneurial research focuses basically, on the trait and cognitive perspective of entrepreneurship, presenting an incomplete picture of the functioning of the entrepreneurial mind (Baron, 2008). The trait perspective (i.e., the notion that entrepreneurs are individuals with unique personality characteristics and abilities) (Forbes, 1999) and the cognitive perspective (i.e., the notion that entrepreneurs possess knowledge structures that help them to identify opportunities and that they differ from those of others (e.g., Baron and Ward, 2004) although they have advanced the theory of entrepreneurship research still have not proven to be strong predictors of who will start a business, lacking the necessary discriminant and criterion validity. An extensive body of research indicates that affect exerts strong effects on cognition (i.e. the processes through which information is entered into memory, processed, and retrieved for later use (e.g., Forgas, 1995; Isen, 1999). Taken as a whole, this literature indicates that the interface between affect and cognition is both continuous and pervasive. Yet, the majority of the research that examines the influence of affect on cognition was conducted in large, established organizations and with employees rather business founders. This raises the following question: Do such effects also occur in new ventures and among entrepreneurs? Although little empirical evidence on this issue is currently available, there appear to be two major reasons for suggesting that affect may indeed be relevant to the entrepreneurial process (Baron, 2008). First, the environments in which entrepreneurs function are often highly unpredictable and filled with rapid change. As a result, such environments are not ones in which individuals can follow well-learned scripts or prescribed sets of procedures. Rather, as many entrepreneurs put it, they must often make it up as they go along. In contexts involving high uncertainty and unpredictability, affect can readily tip the balance toward specific actions or decisions - effects it 4

7 might not produce in environments that are more certain and predictable (Forgas, 1995). In highly uncertain and ambiguous situations such as establishing a new firm, emotions strongly influence individuals strategic judgment (Forgas, 1995). Emotions shape information processing, including risk assessment and strategy formulation (Mittal and Ross, 1998). In fact, emotions can sometimes outweigh rational considerations in decision making and other cognitive processes (Baron, 2008). In uncertain situations, emotions may push an individual toward one action (e.g., deciding to pursue an opportunity) vs. another (e.g., waiting for more information). A second reason why affect may often exert strong effects in the domain of entrepreneurship relates to the specific tasks entrepreneurs perform in starting new ventures. These tasks are highly varied in nature and change significantly as the process unfolds (Baron, 2006). However, many of these activities are ones that have previously been shown to be strongly influenced by affect (e.g., creativity, opportunity recognition, tolerance of high levels of stress). In addition to Baron s recent review (Baron, 2008) of the potential that various streams of research into affect have for informing the field, several scholars have begun to apply affect and constructs pertaining to affect to understanding entrepreneurial phenomena. For example, recent studies have examined the significance of affective states for entrepreneurial motivation (Cardon, et al., 2009; Foo et al., 2009). Souitaris et al. (2007) in their study about the role of entrepreneurship programs in raising science and engineering students entrepreneurial intention found that inspiration comes from the emotional chemistry between students and particular opportunities, which affects their decision to exploit matters beyond the rational models presented in previous entrepreneurship research. Inspiration has an emotional element, implying elicited emotions and encompassing motivation directed towards a new target (e.g. a behavior, 5

8 or a personal goal). The researchers concluded that whereas knowledge and resources might increase the likelihood of success for those who are going to start a new venture, it is the inspiration that raises attitudes and intention and increases the chances that students will actually attempt an entrepreneurial career at some point in their lives (Souitaris et al., 2007, p. 567). In the same vein, Zampetakis et al (2011) found that the link between individual creativity and entrepreneurial intent is stronger for business students who did not attend an entrepreneurship course. The researchers suggested that entrepreneurship should focus not only on the technical aspects of entrepreneurship, but also on the person as a whole. Affect has been shown to exert strong effects on creativity. Mobilizing creativity in university students may not only influence their intention to start a business, but also, potentially, the degree and type of novelty that they introduce to the economy. Nevertheless, contemporary studies on the role of affective influences in the entrepreneurial process have mainly focused on immediate affect (i.e emotions experienced at the time of decision making) and not anticipated affect (i.e. predictions or forecasts about the emotional consequences that will be experienced when outcomes materialize in the future) (Loewenstein and Lerner, 2003). 2.2 The role of anticipated affect in entrepreneurial intent Cognition-behavior models have identified intention as the most immediate and important cognitive antecedent of behavior. Intention refers to an individuals decision to act and is assumed to reflect the effort that that person is likely to exert in order to achieve a goal or perform a behavior. In a meta-analysis, Kim and Hunter (1993) suggested that attitudes successfully predict intentions and intentions successfully predict behavior. The importance of 6

9 entrepreneurial intentions as antecedents of planned behavior (such as founding a new business) has been emphasized in recent years (e.g. Kolvereid, 1996; Krueger, et al., 2000; Peterman and Kennedy, 2003; Lee and Wong, 2004). According to Thompson (2009, p.676) entrepreneurial intention is a self-acknowledged conviction by a person that they intend to set up a new business venture and consciously plan to do so at some point in the future. One of the most influential theory driven models for intentions that have been proposed in the literature is Ajzen s (1991) Theory of Planned Behavior (TPB). According to the TPB, there are three key factors that influence an individual's intention (INT) to perform a given behavior, these being (i) the attitude towards the act (ATT), (ii) subjective norms (SN), and (iii) perceived behavioral control (PBC). Briefly, ATT refer to a person s overall assessment of the advantages and disadvantages of performing a given behavior. The terms attitudes and affect have been used inconsistently in the literature. Cohen and Areni (1991) suggested that the term affect refers to valenced feeling states, with emotions and moods as specific examples, whereas attitude refers to global evaluative judgments rather than emotional states. In addition, factor analytic analysis provided evidence for the discriminant validity of anticipated emotions and attitudes (e.g. Abraham and Sheeran, 2004). The final component of the TPB is the SN. The SN examines a person s perception of the social pressure from significant others to perform the behavior while PBC relates to self-efficacy and is dependent on the perceived ease or difficulty of performing an action. Although the TPB is considered a parsimonious model with a good predictive ability several researchers have proposed that broadening and deepening the model with new variables would increase its predictive value. In their meta-analysis concerning the efficacy of the TPB, Armitage and Conner (2001) found that the TPB accounted for 27% and 39% of the variance in 7

10 behavior. Prior applications of the TPB in the entrepreneurship literature suggest that attitude, subjective norms, and PBC typically explain 30% 45% of the variance in intentions (Kolvereid, 1996; Krueger et al., 2000; Linan and Chen, 2009). This suggests that there exists room for improvement. Conner and Armitage (1998) in their study about the extension of TPB, proposed that some evidence exists across behaviors to support a role for anticipated affect (i.e., what respondents would expect to feel about the consequences of a behavior) within the TPB. The authors state that such anticipated affective reactions to the performance or nonperformance of a behavior may be important determinants of attitudes and intentions (p. 1446). In the same vein, Perugini and Bagozzi (2001), in their model of goal directed behavior (MGB) proposed that intention to perform a behavior is primarily motivated by the desire to perform the behavior, and this behavioral desire is assumed to reflect the effects of attitude, subjective norms, perceived behavioral control, and anticipated emotions, and to mediate their influence on intention. Furthermore, Parker et al. (1996) report that an intervention based on increasing the salience of anticipated affect was more effective than interventions directed at influencing attitudes, subjective norms, or PBC. According to Baumgartner et al (2008) anticipated affect is future oriented affect that refers to the prospect of feeling positive or negative affect after performing or not performing a behavior. The researchers distinguished anticipated from anticipatory affect, with the latter referring to currently experienced affect due to the prospect of a future event. Rivis et al. (2009) suggested that anticipated affect is the construct for understanding the emotional aspect and insisted that it could make an independent contribution to the prediction of intentions. These 8

11 authors also found that anticipated affect increased the variance explained in intentions by 5%, after controlling for TPB variables. In the context of entrepreneurship one recent study by Li (2011) investigated the anticipated emotions that affect value and probability judgment of a new venture under uncertainty. Specifically, Li (2011) using a Chinese sample, found that the anticipated surprise, regret, and fear significantly influence value judgment; whereas individual differences in probability judgment are significantly influenced by the anticipated surprise, regret, contempt, and anger of failure of the new venture. 2.3 Anticipated affective ambivalence Generally, anticipated affect can be distinguished as positive and negative. Previous research addressing anticipated emotion in the context of the TPB has focused primarily on negative anticipated emotion, such as anticipated regret (Moan and Rise, 2005), because people place greater weight on avoiding losses, risks, and negative consequences than approaching gains and positive consequences. In the present research we focus on both positive and negative anticipated affect. Specifically we theorize that when students face entrepreneurship as a career choice both starting a business and not starting should generate positive affect from one source (e.g., starting a business and feel happy because iam a boss of myself or not starting and feel happy because I have not bank depts ) but also negative affect from the other source (e.g., not starting a business and a lost opportunity to exploit or develop my idea or starting a business and an unpleasant feeling of the risks iam taking ). This conflict that is induced by the pleasure evoked from satisfying ones desires versus negative emotions from such satisfaction creates mixed emotion 9

12 contexts (Siemer, et al., 2007). Mixed emotions (or ambivalence) refer to emotional states defined by both positive and negative emotions (Williams and Aaker, 2002). As previously stated, affective ambivalence refers to states where individuals experience blends of emotions. Research suggests that this is the rule, rather than the exception in peoples reactions to everyday life (Larsen et al., 2001; Williams and Aaker, 2002). And, some research has identified specific situations or stimuli that are likely to elicit the experience of mixed emotions. For example, mixed emotions can be felt in response to some advertising campaigns (Williams and Aaker, 2002). Larsen et al., (2001) also identified three situations when college students are likely to report a co-occurrence of happiness and sadness: graduation day, dormitory move out day, and after watching the film Life is Beautiful. Although there still exists and interesting controversy in the literature on whether people can experience positive and negative affect at the same time we have no reasons to believe that this will not also be true for anticipated affect in the context of entrepreneurship an emotional complex process (Larsen s et al. 2001). Moreover, although predicting one s own future feelings (i.e. making affective forecasts) isn t easy because people often make small, but systematic errors in forecasting their own emotional responses (e.g. Wilson and Gilbert, 2003), still however the size of this mis-prediction effect (r) has been found to be very small. Thus, anticipated affect and experienced affect are typically correlated (Gilbert et al. 1998). In the present research, we examined students anticipated affect when asked to imagine nascent entrepreneurship. Nascent entrepreneurs (i.e. individuals that are involved in on-going but not yet operational business start-up efforts in which they are going to be owners) engage in a wide variety of vastly varying in duration and in composition gestation activities, that may 10

13 grouped into different categories of behavior. In this situation no money has been invested, no income has been made and the firm in not a legal entity (Carter, et al., 1996). When university students are asked to imagine nascent entrepreneurship it is plausible that they will anticipate feeling both positive affect (i.e. passion, excitement, happiness, independence, interest) and negative affect (i.e. fear, anxiety, loneliness, and mental strain). This reflects Larsen s et al (2001) suggestion that affective ambivalence might be most likely in emotionally complex situations. Furthermore, even in the case where students have generally only positive or only negative reactions towards nascent entrepreneurship it is likely anticipated affective ambivalence to occur. Priester at al. (2007) empirically demonstrated that even if people are unaware of any specific attributes that are opposite to their thoughts and feelings, they may be concerned that such information exists. That is to say, a student with positive anticipated affect from nascent entrepreneurship that she is unaware of any negative features, she may anticipate that such features exist. The same holds for students with negative reactions towards entrepreneurship. Failing to consider the possibility of anticipated ambivalence we believe that leads to the misinterpretation of students reactions to nascent entrepreneurship such that individuals who are presently perceived as indifferent about entrepreneurship may actually hold strong, yet conflicting, views about the entrepreneurial process. Having said that, what are the consequences of anticipated ambivalence in students entrepreneurial intent? We argue that anticipated affective ambivalence moderates the influence of ATT, SN, and PBC on entrepreneurial intent. Ambivalence is perceived as an unusual occurrence (Larsen et al., 2001; Williams and Aaker, 2002). This is likely to hold true for anticipated affective ambivalence. Most people believe that positive and negative are opposites, and therefore cannot coexist. Anticipated 11

14 emotional ambivalence may signal that the future condition imagined may also contain stimuli and conditions that are not usually linked. Thus, the prospect of future nascent entrepreneurship may be viewed as an unusual situation where seemingly unrelated concepts can co-occur. This may results in increased levels of discomfort, and ambiguity especially for young students, who compared to older individuals, are less able to deal with complex emotional situations (Williams and Aaker, 2002). 3. Overview of study aims The study aimed to investigate the extent to which, anticipated affective ambivalence from nascent entrepreneurship moderates the effects of ATT, SN, and PBC to student entrepreneurial intent. We expect that anticipated affective ambivalence moderates the effect of ATT, SN, and PCB, on entrepreneurial intent such that for students with low anticipated affective ambivalence the effects of the aforementioned variables are stronger compared to students with high levels of anticipated emotional ambivalence. We used Multi-group Analysis of Structural Invariance (MASI for short) to test for differences in structural weights of ATT, SN, and PBC on entrepreneurial intent across students with hi and low anticipated emotional ambivalence. 4. Methodology 4.1 Participants and Procedure Survey data were collected from 1624 students from six Greek universities. The majority (36.7%) were engineering students followed by social science students (e.g. psychology, education) (25%), business students (22.8%), and science students (e.g. chemistry, physics, medicine) (15.5%). Surveys were administrated individually to students, through personal contact by the study authors. Students were randomly located during leisure activities and asked 12

15 to voluntarily participate in a research project regarding factors influencing their future career choice. There were no monetary incentives or extra course credits. Data collection took place at the end of the 2012 spring semester and lasted seven weeks. In sum, the sample consisted of 764 male students (47%), the mean sample age was years (SD = 2.37). Ninety eight participants (6%) were postgraduate students. Thirty eight percent (38%) of the participants reported that one of their parents owned full time business most of the time, while they were growing up, seventy eight percent reported that they know an entrepreneur in their close environment. The survey instrument contained items representing the theoretical constructs along with demographic data. Items referring to the same construct were positioned in different locations throughout the questionnaire. Furthermore, approximately half of the items were negatively worded. As far as the anticipated affect from nascent entrepreneurship is concerned, participants were asked to imagine a situation where they were involved in on-going but not yet operational business start-up. They had invested no money, no income has been made and the firm was not a legal entity. 4.2 Measurement of theoretical constructs All the main constructs included in the analysis were assessed with self-report measures based on multi-item scales. Because participants were Greek students, all the scales used were first translated into Greek by two translators, who compared their versions until agreeing on the most correct translation, and then back-translated into English by a bilingual, native English speaking translator, following the procedure recommended by Brislin (1980). The few discrepancies between the original English version and the back-translated version resulted in adjustment in the Greek translation based on direct discussion between the translators. The specific measures used in the analysis, along with sample items of the relevant constructs, are outlined. 13

16 Entrepreneurial Intention (INT). We assessed students entrepreneurial intent using the scale originally developed by Thompson (2009). This is a reliable and internationally applicable individual entrepreneurial intent scale. It includes ten items, four of which are distracter items that act as red herrings and were not included in scale analyses. Sample items are: Intend to set up a company in the future, I have no plans to launch my own business (reverse scored). Responses to the six items were made on 7-point Likert-type scales (1 = strongly disagree, 7 = strongly agree). Coefficient alpha for this scale was Attitudes towards entrepreneurship (ATT). We assessed students ATT using the five item scale from Linan and Chen (2009). Sample items are: A career as entrepreneur is attractive for me, Among various options, I would rather be an entrepreneur. Responses to the five items were made on 7-point Likert-type scales (1 = strongly disagree, 7 = strongly agree). Cronbach s reliability for this scale was 0.91 Subjective Norm (SN). We assessed students SN using the three item scale from Linan and Chen (2009). Students were asked: If you decided to create a firm, would people in your close environment approve of that decision? Items were (a) Your close family, (b) Your friends and (c) your fellow students. Responses to the three items were made on 5-point Likert-type scales (1 = total disapproval, 5 = total approval). Cronbach s reliability for this scale was Perceived Behavioral Control (PBC). We assessed students PBC using five items from the scale of Linan and Chen (2009). Sample items are: To start a firm and keep it working would be easy for me, I can control the creation process of a new firm. Responses to the five items were made on 7-point Likert-type scales (1 = strongly disagree, 7 = strongly agree). Cronbach s reliability for this scale was

17 Anticipated Positive and Negative Affect. To assess students anticipated affect from nascent entrepreneurship we used 20 items (ten positive and ten negative) from the Positive Affect and Negative Affect Schedule (PANAS) (Watson et al., 1988). Respondents were asked to indicate their anticipated experience of positive and negative affect from nascent entrepreneurship on a 5-point scale (1-very slightly or not at all to 5-extremely). The ten positive affective states (PA) are: interested, excited, strong, enthusiastic, proud, alert, inspired, determined, attentive and active. Cronbach s reliability coefficient for PA was The ten negative affective states (NA) are: Distressed, upset, guilt, scared, hostile, irritable, ashamed, nervous, jittery, and afraid. Cronbach s reliability coefficient for NA was Anticipated affective ambivalence (AMB). To assess students AMB, we used the Gradual Threshold Model (GTM) of ambivalence and the GTM formula suggested by Priester and Petty (1996) as the most appropriate measure of subjective ambivalence. According to the GTM ambivalence increases in a negatively accelerating manner as the number of conflicting reactions (whichever of the positive or negative reactions are fewer in number) increases. The formula used was 5C p D 1/C, where C is equal to the magnitude of conflicting reactions, D is equal to the magnitude of dominant reactions, p is less than 1 (0.5 in the present instance), and a constant of 1 is added to C and D (Priester and Petty, 2001). Control variables. Student s gender, age, and entrepreneurial role models (having a parent that is an entrepreneur) were used as control variables in the present study. Previous research suggests that demographic characteristics appear to influence perceptions of desirability (Shook, et al., 2003). Moreover, having a parent that owns a business is associated with entrepreneurial intent and male students are more likely to have higher entrepreneurial intent compared to females (Crant, 1996). 15

18 4.3 Statistical Method Considerations-Analytical Strategy Prior analysis data screening was performed and data were tested for deviation from normality. Analysis of Moment Structures (AMOS software, version 7.0) (Arbuckle, 2006) was used for the MASI equivalence. In order to avoid problems associated with common method variance often found in cross sectional survey research, several steps described in the literature (Podsakoff, et al., 2003) were taken. First, all participants were informed that their participation was completely voluntary and confidential. Second, items referring to the same construct were positioned in different locations throughout the questionnaire and several items were reverse phrased. Third, we adopted Harman's one-factor test. Following recommendations set forth by Anderson and Gerbing (1988), we tested the model using a two-stage analytic procedure. Specifically, a structural equation model is composed of a measurement model and a structural model. In the first step of analyses step, we fitted a measurement model to the data and in the second step we tested the underlying structural model. During the first step, a measurement model was assessed, which allowed the underlying latent constructs to correlate freely and constrained each item to load only to the factor for which it was a proposed indicator. To further assess discriminant validity of the constructs, we compared the measurement model with a model that constrained the correlations among the constructs to be equal and examined the change in chi-square (χ 2 ). A non-significant χ 2 value indicates acceptance of the more parsimonious of the nested models. Evidence that common method variance does not account for the observed relationships would be provided if a four factor model, representing each variable as a separate construct, is superior to a one-factor model. 16

19 Because the χ 2 statistic is highly sensitive to sample size, we employed several statistics to assess model fitness (Shook, et al. 2004): (a) Root Mean Square Error Approximation (RMSEA): 0 = an exact fit, < 0.05 = a close fit, = a fair fit, = a mediocre fit, and > 0.10 = a poor fit (AMOS also computes a 90% confidence interval around RMSEA); (b) Comparative Fit Index (CFI): best if above 0.9; (c) Akaike Information Criterion (AIC). For model comparisons, smaller values in AIC represent a better fit of the model. 4.4 Invariance analysis method We eliminated all medium responses on the GTM ambivalence index by deleting students that had an average score within one standard deviation of the mean. This procedure of eliminating all medium responses reduced the sample size from 1624 to 592 (300 individuals belonging to the low ambivalence group and 292 to high ambivalence group). In order to examine whether anticipated affective ambivalence has an effect on the model with the best fit to the data, multi-sample analysis of AMOS was then applied. First we tested the invariance of factorial measurement across groups (Byrne, 2001). The measurement model, in which all parameters were freely estimated, was compared to the one in which all factor loadings, were constrained to be equal across groups (weak factorial invariance) (Byrne, 2001). Parameters found to be invariant across groups were cumulatively constrained. Then analysis tested group differences in structural pathways. This procedure provides evidence that group differences in structural pathways are not a function of differences in other parts of the underlying theoretical structure, or instability of the model (Byrne, 2001). Furthermore, for model comparison the CFI index can also be used, because it is not influenced by sample size and model complexity and does not correlate with overall measures of fi. A change in the CFI 17

20 value less than or equal to indicates that the null hypothesis of invariance should not be rejected (Cheung et al. 2002) 5. Results 5.1 Data screening and descriptive summary for the total sample Table 1 presents mean, standard deviation and correlation across selected variables. According to rules proposed in the literature (West et al., 1995), moderately non-normal data (univariate kurtosis < 7 and univariate skewness < 2) are acceptable. That is to say, robust standard errors provide generally accurate estimates. In our data, univariate skewness of each indicator variable was less than 1.19 in absolute value. Univariate kurtosis of each variable was less than 1.16 in absolute value. Therefore, non-normality was not a major issue for our data. Furthermore, we found no evidence of severe multicollinearity, as the mean variance inflation factor (VIF) was 1.81, a value below the suggested cut-off of 4.0. Thus the maximum likelihood estimator was used Insert Table 1 approximately here Confirmatory Factor Analysis for the whole sample Results from the confirmatory factor analysis, suggest an adequate fit to the data: χ 2 (146, N =1624) = , p = 0.000; RMSEA = (90% CI: ); CFI = 0.903; AIC = All factor loadings are significant at the level. A model comparison between the unconstrained measurement model and a model that constrained the correlations among the constructs to be equal produces a significant difference in χ 2, suggesting the presence of 18

21 discriminant validity among the selected constructs (Δχ 2 = , Δdf=5, p<0.001). In summary, these results support the multidimensionality of the measurement model. Moreover, we examined the discriminant and convergent validity of the attitude towards entrepreneurship and anticipated affect (positive and negative) measures were assessed using confirmatory factor analysis. The measurement model with the three latent variables suggests an adequate fit to the data: χ2 (272, N =1624) = , p = 0.000; RMSEA = (90% CI: ); CFI = 0.865; AIC = All factor loadings are significant at the level. A model comparison between the unconstrained measurement model and a model that constrained the correlations among the constructs to be equal, produces a significant difference in χ 2, suggesting the presence of discriminant validity among anticipated affect and attitude towards entrepreneurship (Δχ 2 = , Δdf=3, p<0.001). 5.3 Assessment of the Structural Model for the whole sample The next step in our analysis was to consider the structural model for the whole sample. Results suggest that this model revealed a good fit to the data (see Figure 1) Insert Figure 1approximately here Examining the findings the structural model for the whole sample model postulated that ATT and PBC has statistically significant direct effects on EI (0.43, p < 0.001, two tailed and 0.51, p<0.001, two tailed, respectively). The standardized direct effect of SN on EI although it was very small, it was found to be statistically significant (-0.07, p<0.001, two tailed). In summary, the proportion of variance (squared multiple correlations) in EI that was explained by the 19

22 collective set of predictors was 67 percent, which is highly satisfactory compared to previous research that used the TPB to explain student entrepreneurial intentions. Furthermore, we examined the possibility that the structural model where the effects of SN are fully mediated and partially by ATT and PBC had a better fit to the data (see Linan and Chen, 2009). Our analysis results suggest that these models fitted the data worse than our model with SN having a direct effect on EI (full mediation of SN: AIC= ; partial mediation of SN: , our model: AIC = ). 5.4 Multi-group analysis of structural invariance (MASI) To test the structural invariance across student groups with hi versus low anticipated affective ambivalence, we conducted a multi-group analysis of structural invariance. First we tested Model 1 (the configural invariance model) with no equality constrains for both groups. This model revealed an adequate fit to the data: χ 2 (306, N = 592) = , p = 0.000; RMSEA = (90% CI: ); CFI = 0.892; AIC = , thus supporting the configural invariance. Model 2 (the metric invariance model) also displayed an adequate fit to the data (Table 2). Examination of the probability level associated with the chi-square test for each item loading constraint separately, showed that one item loading associated with the item B12, was not invariant across the two groups, indicating the condition of partial metric invariance. We used model 2 (the metric invariance model) for testing the structural weights, since it was the model with the better fit (Δχ 2 = 11.11, Δdf=17, p>0.05). Model 3 (the structural weights invariance model) also displayed an adequate fit to the data (Table 2). Examination of the probability level associated with the chi-square test for each structural weight among the latent variables constraint separately, showed that the structural weight between PBC and EI was not invariant across hi and low ambivalent groups, indicating 20

23 the condition of partial structural invariance. In Figures 2 and 3 we present the standardized structural weights for both groups Insert Figures 2 and 3 approximately here For the group with low anticipated ambivalence, the proportion of variance (squared multiple correlations) in EI that was explained by the collective set of predictors was 79 percent. For the group with hi anticipated affective ambivalence, the proportion of variance in EI that was explained by the collective set of predictors was 56 percent. In summary our results, suggest that anticipated affective ambivalence moderates the effects of ATT and SN on EI but not the effect of PCB on EI. Furthermore, the effect of SN in the hi ambivalence group is non-significant, while it is significant and negative in the low ambivalence group. 6. Discussion In the present study we used a large sample of students from several Greek universities in order to explore the effects of anticipated affective ambivalence in the variables predicting entrepreneurial intention according to the theory of planned behavior (TPB). Structural equation modeling (SEM) and multi group analysis of structural invariance (MASI) analyses were conducted. In our analyses initially we tested the standard TPB, in the whole sample, in order to facilitate the comparison for future studies and then we conducted the multi group analysis model. Our results, support previous studies that used TPB to predict entrepreneurial intentions, which suggest that, students attitudes towards entrepreneurship (ATT) are related to their 21

24 intention to start a business (EI). In addition perceived behavioral control (PBC) is a strong predictor of EI. As far the role of subjective norm (SN) is concerned, results of the present study suggest that it has a negative and statistically significant effect. Nevertheless, the magnitude is very small, suggesting a weal role for this variable, which is in line with previous studies (e.g. Krueger et al., 2000). Although we examined the possibility of an indirect effect of SN on EI through ATT and PBC, the resulting model had a worse fit to the data. The inclusion of anticipated affective ambivalence from nascent as a moderator variable shed some light in the aforementioned results concerning the role of SN. More specifically, we have found that affective ambivalence moderates the effect of SN on EI, such that for students with hi ambivalence the effect of SN on is non significant. Furthermore, for students with low ambivalence the effect of SN is negative. These results suggest that reference people (i.e. close family, friends, and fellow students) have no role to play in the decision to start a business. Moreover, in the case of students with low ambivalence the perception that reference people would approve of the decision to become an entrepreneur, has negative results. This raises questions regarding the ways that individuals in general and students in particular perceive the influences, behavioral patterns and actions of their social environment. Our results also suggest that the impact of ATT on EI is lower for students with anticipated ambivalence. This suggests that for entrepreneurship education, raising students attitudes towards entrepreneurship is not enough. More attention should be paid to the effect of anticipated affect from the nascent entrepreneurship. Therefore, the case for a wider- not only business plan -entrepreneurship education program is strengthened. Content specifically designed to decrease the anticipated affective ambivalence should be included. This, combined with the fact that the sense of capacity regarding the fulfillment of firm-creation behaviors (i.e. 22

25 PBC) is not influenced by anticipated ambivalence should better clarify the focus of entrepreneurship education: not only on the technical aspects of entrepreneurship, but also on the person as a whole (Zampetakis and Moustakis, 2006; Zampetakis et al. 2011) Although our study sheds some light on the influence of anticipated affect on the entrepreneurial intention of young people, it has several limitations that further research can seek to address. First, our study was limited to a sample of students from Greek universities. To extend the generalizability of our results, we encourage scholars in this area to examine our proposed model with students across different countries. Future research could also look into the influence of subjective ambivalence on the TPB variables. Subjective measures are distinct from objective measures of ambivalence because they tap directly into the amount of conflict or ambivalence experienced by the participants, as opposed to simply identifying co-activation of opposing affective states. These limitations represent, in any case, opportunities to advance in our efforts to better understand students entrepreneurial intent. 23

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