An Emotional Experience of Entrepreneurship

Abstract

According to Bandura’s social cognitive theory, emotions constitute important sources of information for people to judge own efficacy to accomplish specific tasks. The present research employed a laboratory task to assess career starters’ anticipatory emotions and associations with chronic self-construal and emotion regulation strategies. The intensity of facial emotional expressions was assessed while participants were responding to scenarios regarding envisaged business start-up activities. Results from Bayesian path analysis found that independent self-construal was associated with lower intensity of facial expressions of fear; interdependence was associated with higher intensity of anger and disgust. Emotion suppression was associated with lower intensity of happiness and higher intensity of anger. Emotion reappraisal fully mediated relationships between independent self-construal and intensity of expressions of fear in women but not in men. Results add to an emerging literature that highlights the significance of emotions and cultural orientation in the entrepreneurial process.

Keywords

cultural orientation emotion regulation facial expression entrepreneurship

Despite wide held understanding and support for the value of entrepreneurship (Van Praag & Versloot, 2007), there is, still, limited willingness from different parts of the population, to engage into entrepreneurial activities and an entrepreneurial career (Ahl, 2006). According to the Global Entrepreneurship Monitor project, almost twice as many men as women become entrepreneurs; these differences are consistent across countries (Kelley, Brush, Greene, & Litovsky, 2013), and this raises questions on the factors that can explain differences on the career decision-making processes including differences between men’s and women’s venture creation intentions (Zhao, Hills, & Seibert, 2005).

One barrier in such a career decision-making process that may hold many people (and especially women) back from choosing entrepreneurship as a career and acting on this decision has been a difficulty to translate thought into action (Gartner, 1985). Action is important since new business creation requires various start-up activities in gathering resources and the setup of the new venture creation (Baron, 2007). Entrepreneurs who initiate more start-up activities (gestation activities) and who are more active in the process of starting a new venture are more likely to successfully launch a business (Carter, Gartner, & Reynolds, 1996). Yet, there is a limited understanding of what drives choosing entrepreneurship as a career and entrepreneurial action consequently (Venkataraman, Sarasvathy, Dew, & Forster, 2012).

A prominent theory considers self-efficacy as an important aspect of translating entrepreneurial intentions into action (Bandura, 1986; Boyd & Vozikis, 1994; Zhao et al., 2005). According to Bandura’s social cognitive theory, emotional arousal is a potent source of self-efficacy cognitions. Negative emotions contribute to lower self-efficacy and can constitute a barrier to entrepreneurial action, whereas positive emotions are associated with increased self-efficacy (e.g., Arenius & Minniti, 2005; Welpe, Spörrle, Grichnik, Michl, & Audretsch, 2012). Although emotion is considered a key factor in career decision-making process more generally (Ackerman & Beier, 2003; Kidd, 1998), examining emotions is important in the context of entrepreneurial intentions and actions, since emotions precede one’s appraisals about his or her likelihood to successfully carry out entrepreneurial tasks and activities.

One source of arousal relevant to self-efficacy cognitions regarding entrepreneurship career development and decision-making is anticipatory emotions (Bagozzi & Pieters, 1998). Anticipatory emotions are actual emotions experienced at the present time due to something that could happen in the future and can have positive or negative implications for the self (e.g., fear if one thinks that she might lose the money invested in the start-up of her business; Baumgartner, Pieters, & Bagozzi, 2008). Anticipatory emotions are distinguished from anticipated emotions with the latter referring to predictions of emotional reactions that a person may imagine experiencing in the future when certain events have occurred (Baumgartner et al., 2008). Anticipatory emotions of entrepreneurial actions may have informative value concerning individuals’ personal competency and as such they constitute a source of information that can affect perceived self-efficacy.

Although most people experience a variety of emotional responses to entrepreneurial start-up activities (e.g., Kato & Wiklund, 2011; Welpe et al., 2012), people’s anticipatory emotions are likely in part determined by individual difference variables such as independent and interdependent self-construal and emotion regulation. Self-construal refers to how people perceive themselves to be connected with others (independence) or distinct from others (interdependence; Markus & Kitayama, 1991). Independence places a primary emphasis on values of individual needs, autonomy, and self-fulfillment whereas interdependence emphasizes relationships with others, the role of groups, especially obligations to in-groups (e.g., family, nation) and the related norms of group behavior (Oyserman, Coon, & Kemmelmeier, 2002; Singelis, 1994). Individuals in any given culture can vary considerably in their independent and interdependent views of the self (Oyserman et al., 2002; Singelis, 1994).

Self-construal is one potent source of differences in emotion experience and expression (Markus & Kitayama, 1991; Mesquita, 2001) since experienced emotions are primarily relational; emotions concern processes that shape and are shaped by relations with others (Frijda, 1986). Self-construal, therefore, can very much determine social relationships between self and other. Individualistic values and independent self-construal are associated with more intense and more frequent positive affect, whereas interdependent views of the self are associated with lower positive affect within (Van Hemert, Poortinga, & Van de Vijver, 2007) and between peoples’ relationships (Kafetsios & Nezlek, 2012). This implies that differences in independent and interdependent self-construal may determine the way individuals experience venture creation. Self-construal is also associated with emotion regulation, the process by which people influence which emotions they have, when they have them, and how they experience and express these emotions (Gross, 2007).

Emotion regulation refers to processes whereby people manage their emotional states, including specific emotions such as anger or fear (Gross, 1998; Gross & John, 2003). Emotion regulation processes influence the emotions individuals experience and how and whether people eventually express these emotions (Gross, 1998), and the ways they may increase, maintain, or decrease positive and negative emotions. According to Gross’ process model of emotion regulation (Gross, 1998; Gross & John, 2003), two basic emotion regulation strategies chronically affect a person’s behavior: expressive suppression and cognitive reappraisal. Cognitive reappraisal is a strategy that leads to emotion regulation through reinterpretation of the meaning of a stimulus or a situation. Expressive suppression on the other hand refers explicitly to not showing to others what one is feeling (Gross, 1998; Moore, Zoellner, & Mollenholt, 2008).

A large body of research has demonstrated the costs of expressive suppression relative to cognitive reappraisal in the affective domain. Reappraisal has been associated with reduced negative and increased positive affective states as well as enhanced psychological flexibility and well-being, while suppression has been associated with negative emotion, anxiety, and depression, as well as with decreased positive affect and life satisfaction (Moore et al., 2008). Moreover, reappraisal but not suppression efficiently reduces the experience of fear, which results in lower levels of emotion-related biases on rational decision-making (Heilman, Crişan, Houser, Miclea, & Miu, 2010).

Emotion regulation processes help people attain the culturally appropriate emotional experiences (De Leersnyder, Boiger, & Mesquita, 2013). In the same vein, Trommsdorff and Rothbaum (2008) suggest that emotion regulation is related to a person’s self-construal and to his or her goals. In their review, the authors integrate evidence on culture-specific construals of the self. Emotion regulation should, therefore, depend upon these different conceptions of the self. There is evidence that the strategy of suppression is adhered to more in collectivistic cultures than in individualistic cultures (Matsumoto, Yoo, Nakagawa, & 37 members, 2008). Similar to between-country differences in emotion regulation and self-construal relationships, there is evidence for within-country chronic independent and interdependent self-construal differences (Kafetsios & Karagiannopoulos, 2011).

Regulatory strategies of negative emotions are particularly relevant for entrepreneurs at the early stages of business creation. Business creation is intimately related to risk taking and uncertainty, and fear is a potent factor inhibiting entrepreneurial entry (Arenius & Minniti, 2005; Welpe et al., 2012). There is limited research that examines negative emotions, fear in particular, resulting from the anticipation of the possibility of failure (e.g., Welpe et al., 2012). Moreover, as noted by Cacciotti and Hayton (2015), there is limited knowledge of how individuals experience fear of and cope with it (failure) throughout the entrepreneurial process.

Fear results from the prospect of an undesirable future outcome and leads to unfavorable attitudes and avoidance behaviors (Clore, Gasper, & Garvin, 2001), is associated with higher risk perceptions (Lerner & Keltner, 2001), and is inversely related to business opportunity evaluation and exploitation (Welpe et al., 2012). The research focus with respect to fear in entrepreneurial processes has been almost exclusively related to failure (Cacciotti & Hayton, 2015). Additionally, the majority of empirical research conceptualizes fear of failure as a stable disposition (i.e., a disposition to avoid failure or as a general attitude to risk, Arenius & Minniti, 2005). The present research adopts a social-contingent perspective on entrepreneurs’ emotional reactions toward the prospect of business creation.

Lastly, research about gender differences in entrepreneurship-related emotion regulation is scarce. Existing studies in the domain of emotion regulation suggest that men and women do not report differences in the frequency with which they utilize cognitive emotion regulation in everyday life (Gross & John, 2003). However, these studies employed self-report measures that are subject to stereotypic biases. It could be possible that men and women use different emotion regulation strategies to cope with anticipatory emotions related to business start-up behaviors.

Purpose of the Study

The present study aimed, firstly, to assess how within-culture individual differences in self-construal and emotion regulation are related to the experience of anticipatory emotions. Based on recent research evidence and theory (Matsumoto et al., 2008; Trommsdorff & Rothbaum, 2008), we expected that individual differences in self-construal would be associated with emotional reactions indicated in facial expressions. Specifically, we expected that chronic independent self-construal will be associated with experiencing and expressing engaging, approach-oriented emotions in line with research connecting independence with positive affect. Conversely, interdependent self-construal was expected to be associated with experience and expression of disengaging emotions in line with related research linking interdependence with negative affect (Kafetsios & Karagiannopoulos, 2011; Van Hemert et al., 2007).

Moreover, we aimed to test whether the emotion regulation strategies of reappraisal and suppression are associated with interdependent self-construal as expected on the basis of cross-cultural research and whether these are involved in relationships between self-construal and anticipatory emotions. Based on previous research on the relationship between the two regulatory strategies and emotions, we expected that emotion suppression would be positively associated with disengaging emotions and negatively associated with approach-oriented emotions. The inverse was expected regarding emotion reappraisal. However, we did not have any hypotheses with regard to the relative strength of reappraisal and suppression in this model. We applied a structural equation model approach taking a Bayesian perspective (see Muthén & Asparouhov, 2012) in order to clearly distinguish the mediatory power of emotion regulation.

In the present study, we evaluated anticipatory emotions in a way that overcomes known limitations, especially limitations stemming from the use of self-reported emotions (Robinson & Clore, 2002). We introduced a novel research method that assesses emotional experience through captured facial expressions. Participants’ facial expressions were recorded while contemplating a series of activities relevant to business creation. The link between facial emotion expressions and the emotional states that underlie expressions is known and established (Keltner & Ekman, 2000; Keltner, Ekman, Conzaga, & Beer, 2003).

Method

Participants and Procedure

Participants were 147 undergraduate students from two large public universities in southern Greece. The sample included 74 females and 73 males, aged 18–39 (M = 21.07 years, SD = 3.23). The majority of participants (62%) were undergraduate engineering students, followed by social science (e.g., psychology; 38%) students. Thirty-four percent of participants reported that one of their parents owned a full-time business most of the time, while they were growing up, and 81% reported that they knew an entrepreneur in their close environment. Data collection was completed in two time periods: December 2013 and November 2014. Information about the research was announced in lectures and classes. Appointments were arranged individually.

Data collection took place in two stages. In Stage 1, after introducing the research as a study that examines the role of emotions in the entrepreneurial process and signed the informed consent form, participants completed an off-line questionnaire that included demographic data, the self-construal, and emotion regulation scales. After a 2-week interval (Stage 2), each participant visited the laboratory where they sat in front of a personal computer running the FaceReader™ Version 3.0 (Den Uyl & van Kuilenburg, 2005) together with webcam in order to be able to capture and record his or her face video. (In the second time period, FaceReader Version 1.1 was used due to technical problems.)

Entrepreneurial Scenarios/Actions

Participants’ facial expressions were recorded while responding to scenarios/questions concerning activities that entrepreneurs engage in at the early stages of their business creation process (gestation activities). Seven activities were presented: (1) investing own money in the start-up and opening a bank account for the start-up, (2) first use of rented space, (3) beginning to collect information on competitors, (4) hiring an accountant, (5) developing financial projections, (6) beginning talking to customers and promote good or service, and (7) seeking external funding for the start-up.

Participants read the following short story about being in a position to start their own business: “Imagine that you are in a position where you have successfully finished your university degree studies and through seminars and internships you have accumulated enough experience in your filed of studies. Compared to your fellow students, you decide to be self-employed and start your own business.” After reading this short story, participants were asked to read each activity (one at a time) on the computer screen and respond to two questions on: (1) the level of tension and stress that each activity is expected to cause to them and (2) how capable each respondent would be to complete a particular activity, using 10-point scales (1 = not at all, 10 = very much).

Measures

Self-construal

We used Singelis’s (1994) Self-Construal Scale (SCS), a measure of chronic independent and interdependent self-construal. The SCS is one of the most widely used measures consistent with the theoretical concepts of independent and interdependent self (Markus & Kitayama, 1991). Responses were made on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). The Independent Self-construal subscale comprises 15 items that assess uniqueness in social behavior and related cognitions and emotions (e.g., “I do my own thing, regardless of what others think”). Cronbach’s α for this subscale was .61. The Interdependent Self-construal Subscale includes 15 items that assess connectedness in social behavior especially emotions, cognitions, and behavior concerning in-groups (e.g., “It is important to me to respect decisions made by the group”). α for this subscale was .68. Previous studies have demonstrated the validity of the Greek version of the SCS (e.g., Zampetakis, Kafetsios, Lerakis, & Moustakis, 2015b). Moreover, in the present study, independent self-construal scores were positively related to participants’ self-reported capability ratings (Cronbach’s α = .87; r = .19, p < .05), in line with theory suggesting that independent self-construal relates to one’s tendency to focus on uniqueness and self-expression of one’s abilities or traits (Oyserman et al., 2002; Singelis, 1994).

Emotion regulation assessment

We used the Emotion Regulation Questionnaire (ERQ; Gross & John, 2003), a 10-item scale to assess students’ tendency to regulate their emotions in two ways: (1) cognitive reappraisal—ERQ-R (e.g., “When I want to feel more positive emotion, such as joy or amusement, I change what I’m thinking about”) and (2) expressive suppression—ERQ-S (e.g., “I keep my emotions to myself”). Respondents answer each item on a 7-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). αs were .72 for cognitive reappraisal and .74 for expressive suppression, and the two subscales were significantly correlated. Previous studies have demonstrated the validity of the Greek version of the ERQ Scale (Kafetsios, Anagnostopoulos, Lempesis, & Valindra, 2014).

Analysis of facial expressions

The FaceReader assesses facial expressions of six basic emotions (happy, angry, sad, surprised, scared, and disgusted; Ekman, 1970). Each emotion is expressed as a value between 0 and 1, indicating the intensity of the emotion; “0” means that the emotion is not visible in the facial expression and “1” means that the emotion is fully present. The emotion with the highest value is considered the dominant one. Each time the dominant emotion is active for at least 0.5 s, a record is written to a file. All emotional expression values (3 times per sec) are written on another detailed file. In this study, only dominant emotions are taken into account. The global mean average score of the top 10% peak values of facial expressions of emotions to perform all the calculations was used. Robustness and reliability of the FaceReader output were tested in different studies, including studies by Terzis, Moridis, and Economides (2013) and Den Uyl and Van Kuilenburg (2005). Terzis et al. showed that FaceReader output agrees with the judgments of trained observers in up to 89% of cases.

Analyses of facial expressions are less affected by social desirability compared to self-report methods and allow not only for the measurement of the valence of the emotional reaction but emotion itself. Unlike facial emotion expression, emotion self-reports might be influenced by reporting biases, that is, they measure the subjective perception of the emotional reaction and not the emotional response itself. Moreover, results from self-reports may be affected by respondents’ social desirability concerns or might not represent accurate measures of affective valence because they may conflate motivational with affective components.

To provide evidence about the construct validity of our facial expressions measure, we tested the association between participants’ self-reported stress (Cronbach’s α = .81) and capability ratings (Cronbach’s α = .87) with the FaceReader emotion scores. On average, the correlations were not statistically significant yet, there was evidence of validity when examining correlation for each separate activity. For example, for the activities entitled “Actually invested own money in the start-up and open bank account for the start-up” and “Developed financial projections,” the correlation between participants’ capability ratings and sadness detection rates was negative (r = −.28, p < .001; and r = −.22, p < .001), respectively. For the activities “hired an accountant” and “began talking to customers and promote good or service activities,” the correlation between participants’ capability ratings and surprise detection ratings was also negative (r = −.158, p < .05; r = −.20, p < .001, respectively).

Analytic Strategy

We used Analysis of Moment Structures (AMOS, Version 7.0) software (Arbuckle, 2006) taking a Bayesian approach to estimate the proposed theoretical model, using Markov Chain Monte Carlo for model fit. Bayesian modeling does not rely on asymptotic theory, making it particularly useful with nonnormal data (Muthén & Asparouhov, 2012). In Bayesian estimation, a point estimate of a parameter is the mean of the posterior distribution. Furthermore, unlike the conventional confidence interval, the Bayesian credible interval is interpreted as a probability statement about the parameter itself; Prob (a ≤ θ ≤ b) = 0.90 literally means that we are 90% sure that the true value of θ lies between a and b. The adequacy of a Bayesian model can be assessed using posterior predictive p value (PP p value). PP p value should be near .5 for a correct model, with values toward the extremes of 0 or 1 indicating that a model is not plausible (Muthén & Asparouhov, 2012).

Results

Descriptive Statistics and Intercorrelations

In Table 1, we present means, standard deviations, and variable intercorrelations. Measures of univariate skewness and kurtosis suggest that dependent measures were not normally distributed; hence, we present both Pearson’s and Kendall’s correlation coefficients. In Table 2, we present variable intercorrelations separately for male and female participants. Happiness was negatively related to all negative emotions, but fear. Higher level of suppression was negatively related to happy (r = −.33, p < .01) and positively related to angry (r = .31, p < .01) expressions (Gross, 1998). Moreover, higher scores of reappraisal were negatively related to fearful facial expressions (r = −.16, p < .01). Consistent with prior research, suppression was negatively related to happiness (r = −.33, p < .01; Gross, 1998; Gross & John, 2003).

Table 1.
Descriptive Statistics and Intercorrelations for Total Sample.

Variable M SD Skewness Kurtosis 1 2 3 4 5 6 7 8 9 10 11 12

1. Gender 1.50 0.50 −0.014 −2.028 1 −0.32 0.42 0.53 −0.30 0.04 0.47 0.05 0.14 −0.23 −0.02 −0.06

2. Age 21.07 3.23 3.007 10.812 −0.05 1 −0.20 −0.17 0.16 −0.07 −0.11 0.05 0.05 0.12 0.03 0.03

3. Happy 0.03 0.03 1.628 4.006 0.43 0.13 1 0.04 −0.44 −0.08 0.22 −0.10 0.06 −0.24** 0.10* −0.07

4. Sad 0.22 0.21 0.732 −0.390 0.57 0.03 −0.06 1 0.04 0.04 0.55 0.25 0.02 −0.07 −0.03 −0.07

5. Angry 0.38 0.23 0.423 −0.953 −0.42 0.03 −0.57 −0.06 1 −0.15 −0.10 0.29 −0.09 0.22 −0.04 0.10*

6. Surprise 0.10 0.09 2.265 6.691 −0.08 0.01 −0.23** −0.04 −.020* 1 0.16 −0.11 −0.02 −0.03 −0.01 0.09

7. Fear 0.03 0.06 3.753 19.011 0.32 0.23 0.11 0.51 −0.06 0.04 1 0.17 −0.11* 0.06 −0.11* 0.02

8. Disgusted 0.08 0.07 2.227 6.259 −0.11 0.07 −0.22 0.06 0.38 −0.08 0.02 1 −0.02 0.06 0.01 0.04

9. ERQ-R 4.95 0.93 −0.554 1.337 0.13 0.18 0.09 −0.05 −0.10 −0.09 −0.16 0.01 1 −0.15* 0.24 0.08

10. ERQ-S 3.22 1.15 0.224 −0.600 −0.29 −0.04 −0.33 −0.03 0.31 0.04 −0.06 0.09 −0.16 1 −0.13 −0.05

11. IND 4.66 0.56 −0.240 0.652 −0.03 0.09 0.076 −0.09 −0.06 −0.06 −0.22 0.10 0.42** −0.16* 1 0.19**

12. INTER 4.52 0.64 −0.519 0.145 −0.05 0.00 −0.13 −0.09 0.10* 0.05 −0.02 0.15* 0.21 −0.09 0.15 1

Note. N = 147. Pearson product moment correlations are below the diagonal. Kendall’s τ-b is above the diagonal. Gender is coded as 1 = male and 2 = female. ERQ-R = emotion regulation reappraisal; ERQ-S = emotion regulation suppression; IND = independent self-construal; INTER = interdependent self-construal.

*p < .05. **p < .01 (two-tailed).

Table 2.
Descriptive Statistics and Intercorrelations for Male and Female Participants.

Variable Men Women 1 2 3 4 5 6 7 8 9 10 11

M SD M SD

1. Age 21.22 2.02 20.92 4.11 1 0.17 0.10 −004 −0.04 0.29* 0.20 0.26* −0.05 0.09 −0.01

2. Happy 0.02 0.02 0.04 0.03 0.17 1 −0.62 −0.63 −0.35** −0.07 −0.24* 0.06 −0.35 0.02 −015

3. Sad 0.10 0.14 0.34 0.20 −0.03 −0.02 1 0.53 0.23* 0.45** 0.55 −0.11 0.27* −0.06 0.08

4. Angry 0.48 0.26 0.29 0.15 0.07 −0.43 −0.04 1 0.21 0.03 0.42 0.07 0.32** −0.07 0.25*

5. Surprise 0.11 0.11 0.09 0.07 0.06 −0.11 −0.18 −0.43^* 1 0.29* −0.10 −0.16 0.26* −0.15 −0.17

6. Fear 0.01 0.03 0.05 0.07 0.09 0.05 0.34** 0.18 0.17 1 0.24* −0.27* −0.02 −0.21 −0.22

7. Disgusted 0.08 0.09 0.07 0.04 −0.02 −0.21* −0.04 0.36** −0.09 0.06 1 0.04 0.23 −0.04 0.21

8. ERQ-R 4.83 0.82 5.07 1.03 0.02 0.02 −0.21* −0.16 −0.02 −0.10 0.03 1 −0.04 0.55 0.19

9. ERQ-S 3.55 1.14 2.89 1.07 −0.08 −0.11 −0.05 0.17 −0.13 −0.13 −0.02 −0.23 1 −0.15 0.03

10. IND 4.68 0.51 4.65 0.61 0.06 0.22 −0.13 −0.15 −0.04 −0.26* 0.19 0.22** −0.21 1 0.11

11. INTER 4.56 0.66 4.49 0.63 0.02 −0.09 −0.28* 0.05 0.19* −0.35 0.13 0.27 −0.24* 0.41** 1

Note. Male n = 73 and female n = 74. Pearson product moment correlations are below the diagonal for men and below for women. ERQ-R = emotion regulation reappraisal; ERQ-S = emotion regulation suppression; IND = independent self-construal; INTER = interdependent self-construal.

*p < .05. **p < .01 (two-tailed).

Cognitive reappraisal was positively and strongly related to independent self-construal (r = .42, p < .01). A negative correlation was found between independent self-construal and suppression (r = −.16, p < .05). However, a smaller but also positive correlation was found between reappraisal and interdependent self-construal (r = .21, p < .01, two-tailed). Finally, higher scores on independent self-construal were negatively related to the intensity of the emotion of fear (r = −.22, p < .05).

There were significant gender differences in the facial expression of happiness, sadness, anger, and fear. Women expressed more happiness, F(1, 146) = 33.756, p < .01; sadness, F(1, 146) = 70.369, p < .01; and fear, F(1, 146) = 16.997, p < .01, in relation to the entrepreneurial scenario compared to men. Men felt more angry compared to women, F(1, 146) = 30.610, p < .01. Finally, we have found no statistically significant gender differences in cognitive reappraisal; however, men had higher scores in expressive suppression compared to women, F(1, 146) = 12.869, p < .01.

Assessment of Structural Models

We proceeded by testing whether the reappraisal emotion regulation strategy mediated the link between self-construal and the facial expression of fear, for the whole sample (N = 147). We began the Bayesian mediation analysis without using any prior information, that is, noninformative priors were used for unknown parameters in the mediation model. We used 1,000 iteration to burn in and collected the 10,000 posterior draws to make inference.

Independent self-construal was positively related to reappraisal, a = 0.41, 90% credible interval [0.30 – 0.52]. After adjusting for independent self-construal, reappraisal was negatively related to the intensity of fear, β = (−0.09), 90% credible interval [−0.23 to −0.09]. Finally, reappraisal mediated the link between self-construal and the facial expression of fear, aβ = (−0.05), 90% credible interval [−0.10 to −0.03] (see Figure 1a). The partial mediation model provided a better fit to the data (PP p value = .50, deviance information criterion [DIC] = 17.53), compared to the full mediation model (PP p value = .25, DIC = 20.64).

Figure 1.
Standardized regression coefficients for the relationship between independent self-construal and fear as mediated by reappraisal emotion regulation. Bolded standardized regression coefficients. (a) All participants, (b) female participants, and (c) male participants.

We also performed gender multigroup analysis. We found that for female students (n = 74), reappraisal fully mediated the effect of independent self-construal on fear (see Figure 1b). The partial mediation model provided an adequate fit to the data (PP p value = .48, DIC = 18.28); however, the standardized direct effect of self-construal on fear was not statistically significant, β = (−0.09), 90% credible interval [−0.32, 0.13]; the alternative full mediation model provided a better fit in terms of DIC (PP p value = .52, DIC = 16.77). Thus, our data provide evidence for the full mediation model. For male students (n = 73), reappraisal was not a mediator of the independent self-construal–fear relationship. The mediator variable (reappraisal) is not significantly related to the outcome variable (fear), β = (−0.09), 90% credible interval [−0.32–0.13] (see Figure 1c).

Discussion

Recent studies have demonstrated the importance of emotions for entrepreneurs’ cognitions and behavior; emotions impact opportunity evaluation and exploitation (e.g., Foo, 2011; Welpe et al., 2012), risk perception (Podoynitsyna, Van der Bij, & Song, 2012), and the use of information for value creation through cognitive processes that influence how individuals prefer to act (Baron, 2008). Nevertheless, researchers have paid less attention to emotional processes in the entrepreneurial process. Equally, relatively little is known about the role of emotions in vocational behavior including career decision-making (Ackerman & Beier, 2003; Kidd, 1998).

The present study examined currently experienced emotions due to the prospect of a future event (i.e., business start-up). Our study differs critically from earlier research in that we used assessments of facial expressions of emotion during appraisal of future goals to convey students’ internal state from gestation activities. Previous studies have used self-reports (such as the positive and negative affect schedule, Watson, Clark, & Tellegen, 1988) in order to assess anticipatory emotions. These designs do not allow to distinguish between discrete emotions (e.g., fear from other negative emotions) and ignored the unique features that each specific emotion has (Lerner & Keltner, 2001). Accordingly, in the present study, we used a behavioral measure of emotion expression detection that allowed to identify the relative prevalence of each discrete emotion. We found that the fundamental emotions of anger, sadness, and surprise are expressed with the highest intensity followed by those of disgust, fear, and happiness. This is a finding which is in line with appraisal theories of emotion (Smith & Ellsworth, 1985) and suggestions that the appraisal component of emotions is important to the entrepreneurial process (Foo, 2011). Appraisals relate to the subjective perception of the stimulus and not to its objective characteristics; facial expressions of emotions can be considered as a more direct readout of appraisals than are self-reports.

Importantly, results from the current study support expected relationships between individual differences in the cultural understanding of the self (chronic interdependent self-construal) and expressions to anticipatory emotions. Relatively limited research has examined links between specific anticipatory emotions and individual differences predictors of those emotion strategies for regulating those emotions. Higher scores on independent self-construal were negatively related to the intensity of the emotional expression of fear while higher scores on interdependence were positively related to the intensity of anger and disgust expressions. This finding is in line with contemporary descriptions of the properties of independent versus interdependent self-construal. For instance, placing emphasis on values of autonomy and self-fulfillment, individuals with independent self-construal are less likely to experience anticipatory emotions of resignation (e.g., fear, sadness), during the business start-up process. Resignation emotions lead to reduced activities and efforts, little innovation and internal focus (Smith & Ellsworth, 1985). On the other hand, individuals with higher interdependent self-construal tend to define themselves more in terms of their relationships with others and thus are more concerned about maintaining social harmony in those relationships (Kim, Sherman, Ko, & Taylor, 2006).

The results also provide evidence about the importance of emotion regulation strategies in relationships between cultural understanding of the self and the anticipatory emotion of fear. Fear is an important emotion during the start-up process (Kato & Wiklund, 2011; Welpe et al., 2012). In line with our hypotheses, emotion suppression was associated with disengaging/negative facial emotion expressions. Emotion reappraisal was associated with lower fear expressions. However, reappraisal fully mediated the relationships between interdependent self-construal and intensity of fearful facial expressions in females but not in males. That is, one means of decreasing negative emotion, fear in particular, is for female students to utilize cognitive strategies and change their appraisals of the relevance of events to their goals. For female participants, reappraising the significance of emotion-eliciting events from the entrepreneurial process (e.g., thinking of a negative future event as unimportant) and by reappraising its outcome (e.g., thinking about how things could get better) were associated with interdependent self-construal and affected their facial emotion expressions.

Related, the results of the study highlight a typically found gender difference in emotion expression (Fischer, Rodriguez Mosquera, Van Vianen, & Manstead, 2004; LaFrance & Banaji, 1992). Compared to men, women were found to express emotions signifying powerlessness (fear, sadness) whereas men expressed more anger. Typically, such differences are explained in terms of socialization and women’s social roles. To our knowledge, this is the first study that demonstrates this well-replicated phenomenon in the area of anticipatory emotions with regard to entrepreneurship and with the use of behavioral measures of assessing those emotions.

Although the entrepreneurial career development pathways are very ambiguous, entrepreneurship implies a career choice (Douglas & Shepherd, 2002). This is important for career counselors in order to effectively conceptualize individuals’ decision to enter into an entrepreneurial career and preparation for such a career. From a career-counseling practice standpoint, the present research suggests that reappraisal is an effective strategy in helping students, especially female students, regulate the fear of conducting entrepreneurial gestation activities. The idea is that no situation in and of itself generates an emotion. It is the individuals’ appraisal of the situation that generates emotions. As such, reappraisal involves changing a situation’s meaning in a way that alters its emotional impact.

Reappraisal is an antecedent-focused strategy of emotion regulation because it intervenes before the emotion tendencies have been fully generated (Gross & John, 2003). Career counselors may suggest and use this technique as an effective tool in building well-adjusted expectations toward the entrepreneurial career. For example, seeking external funding for the start-up might be appraised by students as a chance to fail and suffer criticism by experts and financial administrators but could instead be reappraised as an opportunity to receive feedback that will improve the business idea. Moreover, developing financial projections could be appraised by potential entrepreneurs as a process that requires extreme effort and is related to uncertainty about the outcome—a situation related to the expression of fear (Smith & Ellsworth, 1985); however, they could be encouraged to try to see the positive side and try to learn from the experience of the financial projection preparation and that this is good practice for them and even if things go wrong in the development of the appropriate plan it’s not the end of the world! Finally, a potential entrepreneur may fail a series of tests in developing his innovative product and think negatively about his or her performance upon first receiving the results. She could be instructed to revisit her emotional response to the situation and later views the results as a way to challenge and better herself.

In the same vein, career counselors could focus on increasing the possibilities of the expression of positive emotions (i.e., happiness). Our results suggest that the expression of the emotion of happiness relates negatively to the suppression emotion regulation strategy. Thus, it should be made clear that inhibiting the emotion-expressive behavior (as suppression suggests) is not an effective strategy when conducting entrepreneurial gestation activities.

Limitations

This study is not without limitations. First, although our study is probably the first to examine students’ anticipated experience of entrepreneurship, it has an obvious, cultural focus. Future research should attempt to generalize findings to other cultures. Second, the study did not apply a random sampling technique. Most participants were nonbusiness students. As such, results have to be interpreted with caution while future research could attempt to replicate the findings with a sample of individuals who are known to be considering entrepreneurial careers. Third, we have found that self-reported stress and capability ratings were on average unrelated to the facial expressions; future research will need to address which is more strongly related to actual entrepreneurial activity. Fourth, in our analyses, we used the global mean average score of the facial expressions. As such, we had no information on the types of scenarios that students were responding to when they became fearful or angry, something that could be addressed in future research. Finally, although it is difficult to eliminate the possibility that the effects in our study are spurious, the present research is guided to a large extent by some a priori theoretical considerations. This minimizes to the possibility of spurious effects. Moreover, we have adopted a Bayesian approach for the assessment of structural equation model, which offers an improved inferential paradigm over the traditional null hypothesis testing framework (Muthén & Asparouhov, 2012).

Conclusion

The present study provides essential insights into the anticipatory emotions in the business start-up process and their relationships to individual differences in cultural orientations and emotion regulation. According to Bandura’s social cognitive theory, emotional arousal is a potent source of self-efficacy cognitions. As such, analyzing the relationship between anticipatory emotions and self-construal is important in order to gain insight into the barriers that may hold many people (and especially women) back from choosing entrepreneurship as a career and acting on this decision. In addition, such analyses help us understand the differences that exist within students with regard to the regulation of negative anticipatory emotions. Specifically, fear is often seen as an impediment to starting a business and thus choosing an entrepreneurial career (Shepherd, Patzelt, & Wolfe, 2011; Welpe et al., 2012). We have found that the relationship between independent self-construal and fear was fully mediated by the emotion regulation strategy of reappraisal for female students. Future research could apply this mediation model to various domains such as entrepreneurship education (e.g., Lackéus, 2014; Zampetakis, Kafetsios, Lerakis, & Moustakis, 2015a).

Variable	M	SD	Skewness	Kurtosis	1	2	3	4	5	6	7	8	9	10	11	12
1. Gender	1.50	0.50	−0.014	−2.028	1	−0.32**	0.42**	0.53**	−0.30**	0.04	0.47**	0.05	0.14**	−0.23**	−0.02	−0.06
2. Age	21.07	3.23	3.007	10.812	−0.05	1	−0.20**	−0.17**	0.16**	−0.07	−0.11	0.05	0.05	0.12**	0.03	0.03
3. Happy	0.03	0.03	1.628	4.006	0.43**	0.13	1	0.04	−0.44**	−0.08	0.22**	−0.10	0.06	−0.24**	0.10*	−0.07
4. Sad	0.22	0.21	0.732	−0.390	0.57**	0.03	−0.06	1	0.04	0.04	0.55**	0.25**	0.02	−0.07	−0.03	−0.07
5. Angry	0.38	0.23	0.423	−0.953	−0.42**	0.03	−0.57**	−0.06	1	−0.15**	−0.10	0.29**	−0.09	0.22**	−0.04	0.10*
6. Surprise	0.10	0.09	2.265	6.691	−0.08	0.01	−0.23**	−0.04	−.020*	1	0.16**	−0.11**	−0.02	−0.03	−0.01	0.09
7. Fear	0.03	0.06	3.753	19.011	0.32**	0.23**	0.11	0.51**	−0.06	0.04	1	0.17**	−0.11*	0.06	−0.11*	0.02
8. Disgusted	0.08	0.07	2.227	6.259	−0.11	0.07	−0.22**	0.06	0.38**	−0.08	0.02	1	−0.02	0.06	0.01	0.04
9. ERQ-R	4.95	0.93	−0.554	1.337	0.13	0.18**	0.09	−0.05	−0.10	−0.09	−0.16**	0.01	1	−0.15*	0.24**	0.08
10. ERQ-S	3.22	1.15	0.224	−0.600	−0.29**	−0.04	−0.33**	−0.03	0.31**	0.04	−0.06	0.09	−0.16	1	−0.13**	−0.05
11. IND	4.66	0.56	−0.240	0.652	−0.03	0.09	0.076	−0.09	−0.06	−0.06	−0.22**	0.10	0.42**	−0.16*	1	0.19**
12. INTER	4.52	0.64	−0.519	0.145	−0.05	0.00	−0.13	−0.09	0.10*	0.05	−0.02	0.15*	0.21**	−0.09	0.15**	1

Variable	Men	Women	1	2	3	4	5	6	7	8	9	10	11
1. Age	21.22	2.02	20.92	4.11	1	0.17	0.10	−004	−0.04	0.29*	0.20	0.26*	−0.05	0.09	−0.01
2. Happy	0.02	0.02	0.04	0.03	0.17	1	−0.62**	−0.63**	−0.35**	−0.07	−0.24*	0.06	−0.35**	0.02	−015
3. Sad	0.10	0.14	0.34	0.20	−0.03	−0.02	1	0.53**	0.23*	0.45**	0.55	−0.11	0.27*	−0.06	0.08
4. Angry	0.48	0.26	0.29	0.15	0.07	−0.43**	−0.04	1	0.21	0.03	0.42**	0.07	0.32**	−0.07	0.25*
5. Surprise	0.11	0.11	0.09	0.07	0.06	−0.11	−0.18	−0.43^*	1	0.29*	−0.10	−0.16	0.26*	−0.15	−0.17
6. Fear	0.01	0.03	0.05	0.07	0.09	0.05	0.34**	0.18	0.17	1	0.24*	−0.27*	−0.02	−0.21	−0.22
7. Disgusted	0.08	0.09	0.07	0.04	−0.02	−0.21*	−0.04	0.36**	−0.09	0.06	1	0.04	0.23	−0.04	0.21
8. ERQ-R	4.83	0.82	5.07	1.03	0.02	0.02	−0.21*	−0.16	−0.02	−0.10	0.03	1	−0.04	0.55**	0.19
9. ERQ-S	3.55	1.14	2.89	1.07	−0.08	−0.11	−0.05	0.17**	−0.13	−0.13	−0.02	−0.23	1	−0.15	0.03
10. IND	4.68	0.51	4.65	0.61	0.06	0.22	−0.13	−0.15	−0.04	−0.26*	0.19	0.22**	−0.21	1	0.11
11. INTER	4.56	0.66	4.49	0.63	0.02	−0.09	−0.28*	0.05	0.19*	−0.35**	0.13	0.27**	−0.24*	0.41**	1

Footnotes

Authors’ Note

The views, opinions, and results are the sole responsibility of the authors.

Acknowledgments

The authors acknowledge the support by the “ARISTEIA” Action (“EMO-ENTRE” program: code 2511) of the “Operational Program Education and Life Long Learning” and cofund by the European Social Fund (ESF) and National Resources.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research reported in this article was fully supported by the “ARISTEIA” Action (“EMO-ENTRE” program: code 2511).

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