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The Role of MixedEmotions in theRisk Perception ofNovice and SerialEntrepreneursKsenia PodoynitsynaHans Van der BijMichael Song

This study examines the role of mixed emotions in the risk perception of entrepreneurs, animportant determinant of entrepreneurial decision making. We extend the literature on mixedemotions by applying the cognitive appraisal tendency approach and contrasting it withambivalence stemming from the valence-based approach. We test our hypotheses on a dataset of 253 entrepreneurs from the United States. We show that mixed and conflictingemotions are an important predictor of the risk perception of entrepreneurs. At the sametime, we find that emotional reactions of entrepreneurs on strategic issues change substan-tially as they found more ventures and become habitual entrepreneurs.

Introduction

Imagine how much easier life would be if we felt only one emotionpositive ornegativeat a time. Luckily and unfortunately, this is often not the case. Entrepreneurs,in particular, are people who are likely to experience mixed rather than single basicemotions in their decision making, including their evaluation of opportunities and assess-ment of risks. In this study, we focus on the relationship between mixed emotions and therisk perception of entrepreneurs.

We define entrepreneurs as individuals who recognize and exploit new businessopportunities by founding new ventures (Baron, 2008; Shane & Venkataraman, 2000).Because opportunity recognition and evaluation are key phenomena of entrepreneurship(Alvarez & Barney, 2007; Shane & Venkataraman), it is important to understand whatmakes entrepreneurs pursue opportunities. Risk perception plays an important role in thiscontext. Empirical research has demonstrated that risk perception strongly influences riskbehavior in general (Sitkin & Pablo, 1992; Sitkin & Weingart, 1995), and opportunityevaluation and the decision to start a venture in particular (Keh, Foo, & Lim, 2002; Simon,Houghton, & Aquino, 2000). However, recent literature reviews have called for more

Please send correspondence to: Ksenia Podoynitsyna, tel.: (40) 247-3640; e-mail: k.s.podoynitsyna@tue.nl.

PTE &

1042-2587 2011 Baylor University

115January, 2012DOI: 10.1111/j.1540-6520.2011.00476.x

research to refine our understanding of the role of entrepreneurial risk taking (Ireland &Webb, 2007). Until now, empirical research has emphasized risk-taking propensity(Forlani & Mullins, 2000; Mullins & Forlani, 2005) and cognitive biases (Keh et al.;Simon et al.) as determinants of entrepreneurial risk perception. A recent study by Foo(2011) finds that certain background emotions can also influence risk perception. Indeed,because entrepreneurs tend to rely heavily on their intuition in making decisions (e.g.,Simon et al.) and emotions are one of the main drivers of intuitive thinking (Epstein, 1994;Kahneman, 2003), emotions are meant to play a key role in entrepreneurial decisionmaking.

Entrepreneurs likely experience mixed rather than single basic emotions in theirdecision making. Similar to the executives of established firms, entrepreneurs often dealwith ambiguous situations (Eisenhardt & Sull, 2001; Walsh, Meyer, & Schoonhoven,2006). They operate in environments that are highly unpredictable and filled with rapidchange (Lichtenstein, Dooley, & Lumpkin, 2006), while entrepreneurial tasks are highlyvaried in nature and change significantly as the entrepreneurial process unfolds (Baron,2006). When performing variable tasks in highly uncertain and unpredictable environ-ments, an entrepreneurs affect may play an important role in judgment and decisionmaking (Baron, 2008). Moreover, the greater the ambiguity in their working environment,the more likely that entrepreneurs will experience different emotions at the same time(Folkman & Lazarus, 1985; Larsen, McGraw, Mellers, & Cacioppo, 2004). Thus, study-ing the relationship between mixed emotions and risk perception can provide valuableinsights for entrepreneurs.

The extant research on mixed emotions has concentrated on the simultaneous expe-rience of positive and negative affect (Folkman & Lazarus, 1985; Fong, 2006; Fong &Tiedens, 2002; Larsen, McGraw, & Cacioppo, 2001; Larsen et al., 2004; Priester & Petty,1996, 2001; Schwarz & Weinberger, 1980). We will build on research examining thecognitive appraisal tendency approach to emotions and contrast it with the valence-basedapproach. The former approach focuses on the differences between emotions of the samevalence, which can be attributed to various cognitive appraisal patterns associated withthese emotions, such as uncertainty and controllability, among others (Keltner, Ellsworth,& Edwards, 1993; Lerner & Keltner, 2000, 2001; Smith & Ellsworth, 1985, 1987). Forexample, happiness and hope are two positive emotions, but happiness tends to beappraised as certain and controllable while hope tends to be appraised as uncertain anduncontrollable. Following the logic of these two approaches to affect, mixed emotionsmay emanate from the simultaneous experience of positive and negative emotions(ambivalence) or from the coexistence of emotions with different associated cognitiveappraisal patterns.

In this study, we examine 16 emotion adjectives, half of which have a positive valence(related to the basic emotions of happiness and hope) and half of which have a negativevalence (related to the basic emotions of anger and fear). The emotion adjectives wereselected in such a way that half of them also have a positive association with certainty andcontrollability cognitive appraisal dimensions (related to the happiness and anger basicemotions), and the other half have a negative association with these dimensions (related tothe hope and fear basic emotions). These dimensions are shown to mediate the relation-ship between emotions and risk estimates (Lerner & Keltner, 2001).

This study contributes to the literature by (1) conceptualizing mixed emotions usingthe cognitive appraisal tendency approach, (2) contrasting this approach with the mixedemotions conceptualization based on the valence-based approach on the example of riskperception of entrepreneurs, and (3) exploring the moderating effect of experience infounding ventures on these relationships.

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Theoretical Framework and Hypotheses

Entrepreneurial Risk Perception and its DriversEntrepreneurial risk perception is defined as the entrepreneurs assessment of the risk

inherent in a situation. This definition is consistent with previous work of Dutton andJackson (1987), Jackson and Dutton (1988), Sitkin and Pablo (1992), and Sitkin andWeingart (1995). A situation is considered risky when it is more negative than positive,there is more potential for loss than for gain, and it is seen more as a threat than as anopportunity (Highhouse, Paese, & Leatherberry, 1996; MacGrimmon & Wehrung, 1985;Sitkin & Weingart).

In the entrepreneurship and management literatures, several individual and organiza-tional drivers of risk perception have been proposed and tested. Sitkin and Pablo (1992)suggest that individuals risk propensity will mediate the relationship between their riskpreference, inertia, and outcome history and their risk perception. Moreover, theseresearchers suggest that organizational characteristics like control systems, problemdomain familiarity, social influence, top management team homogeneity, and problemframing can all influence an individuals risk perception. Sitkin and Weingart (1995) alsofind empirical support for the mediation effect of risk propensity on the outcome historyrisk perception relationship and the direct effect of problem framing on risk perception.Forlani and Mullins (2000) also find an effect of risk propensity on risk perception. At thesame time, Mullins and Forlani (2005) find that risk propensity influenced entrepreneurschoices related to the probability of gain and loss, while risk perception influencedentrepreneurs choices related to the magnitude of gains and losses. Simon et al. (2000)and Keh et al. (2002) examine the role of cognitive biases in entrepreneurial risk percep-tion. Illusion of control and belief in the law of small numbers were found to be negativelyassociated with risk perception.

In considering affect as another antecedent of risk perception, Johnson and Tversky(1983) find that the experience of negative affect equally inflated individuals estimatesfor all types of negative events. Mayer, Gaschke, Braverman, and Evans (1992) findsimilar results. We refer to the review of Blanchette and Richards (2010) for an in-depthdiscussion of these two and related studies. Finally, Foo (2011) finds that the experienceof four induced emotions (anger, fear, happiness, and hope) unrelated to the venturedecision had a differential influence on students risk perceptions of entrepreneurialventure scenarios. Foo also finds a positive relationship between dispositional happinessand anger (i.e., happiness and anger as traits) and the risk-taking propensity of entrepre-neurs. However, despite the likelihood that entrepreneurs experience mixed emotions dueto the variable and uncertain nature of their environment (e.g., Lichtenstein et al., 2006),to date, no study has examined the relationship between mixed emotions and risk percep-tion of entrepreneurs. In our study we will focus on this link.

Valence-Based and Cognitive Appraisal Tendency ApproachesMost studies on entrepreneurship that focus on emotions and affect follow the

valence-based approach by distinguishing between positive and negative affect. Forinstance, Baron (1998, 2008) conceptually clarifies the role of positive and negativeaffect in basic cognitive processes of entrepreneurs and the potential influences on keyaspects of the entrepreneurial process. Foo, Uy, and Baron (2009) examine conse-quences of positive and negative affect and find that they both impact venture effort.Brundin, Patzelt, and Shepherd (2008) show that entrepreneurs displays of positiveand negative emotions influence their employees willingness to act entrepreneurially.

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Shepherd and Cardon (2009) propose that negative emotional reactions due to projectfailure impact learning from the failure and the motivation to try again. Cardon,Zietsma, Saparito, Matherne, and Davis (2005) and Cardon, Wincent, Singh, andDrnovsek (2009) explain the concept of entrepreneurial passion by using a parenthoodmetaphor in the entrepreneurial process and by linking entrepreneurial passion to threerole identities (inventing, founding, and developing) and conceptually exploring theeffects of entrepreneurial passion on goal-related cognitions, entrepreneurial behavior,and entrepreneurial effectiveness.

The cognitive appraisal tendency approach represents a viable and promising alter-native to the valence-based approach. It focuses on the differences between the emo-tions of the same valence due to dissimilar cognitive appraisals. Smith and Ellsworth(1985) summarize the patterns of appraisal for a range of emotions. Keltner et al.(1993) confirm that not only the valence of an affect, but also its associated cognitiveappraisal patterns have an important influence on causal judgments. In particular, theyfind a dissimilar impact of sadness and anger. Lerner and Keltner (2000, 2001) elabo-rate on these results and present an appraisal tendency framework, in which eachemotion is defined by a tendency to perceive new events and objects in ways that areconsistent with the original cognitive appraisal dimensions of the emotion. They findthat fearful people made risk-averse choices, while angry people made risk-seekingchoices. Moreover, risk judgments of angry people more closely resemble those ofhappy people than those of fearful people. Lerner and Tiedens (2006) elaborate furtheron the differences between anger and other emotions and depict the anticipatory plea-sure of anger that triggers the positive subjective sense. Foos (2011) research alsosupports the appraisal tendency approach.

Both the valence-based approach and the cognitive appraisal tendency approach canbe used to study mixed emotions, which are the focus of this study. We build further onthese two streams of research by examining mixed emotions as a potential antecedent ofentrepreneurial risk perception. In order to build our hypotheses, we use the affectinfusion model (AIM; Forgas, 1995, 1998) describing the mechanisms of how affect mayinfuse judgments.

Mechanisms Explaining the Role of Affect in Judgment andDecision Making

In this study, we define affect as a generic label to refer to both moods and emotions.Moods are low-intensity, diffuse, and relatively enduring affective states without a clearantecedent cause and therefore little cognitive content. Emotions are more intense, shortlived, and usually have a definite cause and a clear cognitive content (Forgas, 1995).Researchers on basic (as opposed to mixed) emotions have embraced the AIM depictinga set of mechanisms explaining the influence of moods and emotions on judgment anddecision making (e.g., Baron, 1998, 2008; Forgas, 1995, 1998). The AIM distinguishesbetween judgment processes where a relatively closed information search is required andprocesses where a much more open information search is needed. In general, entrepre-neurs are involved in the latter processes. These processes have a higher probability ofaffect infusion, that is, affectively loaded information exerts an influence on and becomesincorporated into the judgment process, entering into the judgmental deliberations andeventually coloring the judgment outcome (Forgas, 1995). The affect infusion worksthrough two different, but complementary mechanisms: affect as information and affectpriming.

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The affect-as-information mechanism describes direct affect infusion: Instead ofmaking a judgment on the basis of recalling features of a target, the individual askshimself how he feels about it. So, in fact the affect itself is the information. In doing so,individuals may mistake feelings due to a preexisting state for a reaction to the target(Forgas, 1995). DeSteno, Petty, Wegener, and Rucker (2000) find empirical support for theaffect-as-information mechanism in making likelihood estimates of future events. Loe-wenstein, Weber, Hsee, and Welch (2001) show that emotional reactions to risky situationsoften diverge from cognitive assessments of those risks.

The affect-priming mechanism suggests that affect can indirectly inform social judg-ments by priming the encoding, retrieval, and selective use of information in the judgmentprocess. Affect priming can be enacted through four submechanisms. The first one isselective attention, which means that given the overload of information in a judgmentprocess and the necessity of making selections, particular information is selected that iscongruent with the current affect. Second, in the process of encoding new information,more attention may be given to the affect-congruent information. Third, most judgmentprocesses involve the retrieval and use of prior knowledge structures to interpret incominginformation. Affect can selectively influence these retrieval processes, because affect-congruent information may have a greater likelihood of being retrieved (Forgas, 1995).Forgas also finds empirical support for the affect-priming mechanism in complex bar-gaining tasks (Forgas, 1998).

HypothesesWe first focus on mixed emotions with dissimilar valences. In general, emotion

adjectives that are associated with the basic emotions of happiness and hope are con-sidered to be positive, while emotion adjectives associated with the basic emotions ofanger and fear are considered to be negative (see, e.g., Lerner & Keltner, 2000, 2001).Following the literature on attitudinal ambivalence (Fong, 2006; Fong & Tiedens, 2002;Priester & Petty, 1996, 2001), we distinguish between dominant emotions and conflict-ing emotions for each entrepreneur. Dominant emotions are those positive or negativeemotions that are experienced in greater numbers, while conflicting emotions are thosethat are experienced in lesser numbers. For example, when an entrepreneur experiencesfive positive and two negative emotions, the five positive emotions are dominant and thetwo negative emotions are conflicting. Another entrepreneur, experiencing three positiveand four negative emotions, has four dominant (negative) emotions and three conflicting(positive) emotions.

A prominent argument in the mixed emotions literature (Priester & Petty, 1996, 2001)is that the conflicting (rather than dominant) emotions make the difference in cases ofmixed emotions. Priester and Petty (1996) and Priester, Petty, and Park (2007) suggest thegradual threshold model (GTM) as the most appropriate formula to calculate mixedemotions (i.e., ambivalence) on the basis of particular reactions of the respondents. Belowa certain threshold, ambivalence is a function of both dominant and conflicting reactions.Above that threshold, ambivalence is a positive and negatively accelerating function of theconflicting reactions. That is, although feelings of ambivalence generally increase asconflicting reactions increase, the initial conflicting reactions produce a greater increase inambivalence than subsequent conflicting reactions. In the GTM, the threshold graduallyemerges as conflicting reactions become more numerous (Priester & Petty, 1996; Priesteret al.). Furthermore, it does not matter whether conflicting reactions are positive ornegative (Priester et al.)thus, for some entrepreneurs the conflicting reactions (i.e.,emotions) will be positive, for others negative.

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We also consider emotions based on different associated cognitive appraisal pat-terns, in accord with the cognitive appraisal tendency approach (Keltner et al., 1993;Lerner & Keltner, 2000, 2001; Smith & Ellsworth, 1985). We assume that each emotionactivates a cognitive predisposition appraising future events in line with the centralappraisal dimensions that triggered the emotion (Lerner & Keltner, 2000). In this view,there is a strong relation between how a person interprets a situation along certainemotion-relevant dimensions and what the person feels and how the person appraisesfuture events (Smith & Ellsworth, 1987). These dimensions include (1) pleasantnessthe extent to which the situation is perceived as being pleasant or unpleasant; (2) antici-pated effortthe extent to which the person feels a need to expend effort (eitherphysical or mental) in the situation; (3) attentional activitythe extent to which theperson wants to attend to or shut out the situation; (4) certaintythe extent to which theperson understands or is sure of what is happening or going to happen in the situation;(5) responsibilitywho or what the person perceives as having brought about the situ-ation, either oneself or someone or something else; (6) controlwho or what the personperceives as currently being in control of the situation, either oneself, some other personor persons, or uncontrollable circumstances; (7) legitimacythe extent to which thesituation is perceived as fair or unfair; and (8) perceived obstaclethe extent to whichthe person perceives problems or obstacles in the situation that are hampering the attain-ment of an desired goal. In line with Lerner and Keltner (2000, 2001) and Foo (2011),we focus on two of these dimensions, certainty and control, which mediate the rela-tionship between emotions and risk perception (Lerner & Keltner, 2001) and are thus ofgreat importance in the entrepreneurial setting (Baron, 1998). In general, emotion adjec-tives that are associated with the basic emotions of happiness and anger score high onthe control and certainty dimension, while adjectives associated with hope and fear havea low score on control and certainty (Smith & Ellsworth). For instance, fear is triggeredby the perception that negative events are unpredictable and uncontrollable (Foo; Lerner& Keltner, 2000, 2001).

The ambivalence literature is quite neutral to what constitutes conflicting and domi-nant reactions to the researched issues (Priester & Petty, 1996, 2001). Although thevalence-based approach to emotions can be more easily fit into the ambivalence concep-tualization (e.g., Fong, 2006; Fong & Tiedens, 2002), one can also distinguish dominantand conflicting reactions on the basis of the cognitive appraisal approach. If, for anentrepreneur, the number of experienced emotional adjectives that score highly on cer-tainty and controllability exceeds the number of experienced adjectives that have a lowscore on certainty and controllability, we call the former emotions dominant and the latterconflicting (and vice versa). The arguments from the ambivalence literature regarding theprominence of conflicting emotions influence should also hold in case of cognitiveappraisals approach (Priester & Petty, 1996, 2001).

Following the AIM, the effect of conflicting emotions on judgments in general andrisk perception in particular works through two complementary mechanisms. First, withdirect affect-as-information mechanism, where feelings are used as if it was informationabout the issue in question, as the level of conflicting emotions regarding a certain issueincreases, entrepreneurs will experience this odd mixture of emotions more strongly andtherefore recognize it more easily. As a result, entrepreneurs will more likely experiencethe focal issue as unusual and feel uncomfortable about it (Fong, 2006). Feeling uncom-fortable will lead to a cautious, conservative judgment on the issue, resulting in a higherperception of risk.

With the indirect affect-priming mechanism, where feelings determine the typeof information used to assess a certain issue, the more entrepreneurs experience and

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recognize conflicting emotions, the more they will be sensitive to unusual associations(Fong, 2006). Facing an overload of information in the judgment process, entrepreneursimplicitly or explicitly have to make choices regarding what information to retrieve,encode, and use. This may lead to overly simplistic analyses of complex situations,directing attention to a limited set of variables and exclusion of other important variables(Simon & Houghton, 2002). Moreover, it often leads to the retrieval of success stories andpositive information, neglecting failures and negative information (Golder & Tellis, 1993;Simon et al., 2000). Normally, such selection will result in too-optimistic judgments anda lower perception of risk. However, when entrepreneurs become more sensitive tounusual associations, they are more likely to take more variables into account and accessthe less-obvious knowledge structures, thus enriching the information search process(Fong). This will lead to a richer set of associations and interpretations including bothpositive/success stories and negative/failure stories. Therefore, mixed emotions are likelyto be associated with a higher perception of risk.

Both mechanisms indicate that an increase in the level of conflicting emotions willlead to a higher perception of entrepreneurial risk. Moreover, experiencing conflictingemotions is associated with a feeling of indecisiveness (Priester & Petty, 1996, 2001). Thehigher the level of indecisiveness, the greater the level of risk entrepreneurs are likely toperceive. Therefore, we hypothesize:

Hypothesis 1a: Conflicting emotions in terms of valences (i.e., positive vs. negativeemotions) will have a stronger association with the risk perception of entrepreneursthan dominant emotions in terms of valences will.Hypothesis 1b: Conflicting emotions in terms of cognitive appraisal tendencies (i.e.,certain and controllable vs. uncertain and uncontrollable) will have a stronger asso-ciation with the risk perception of entrepreneurs than dominant emotions in terms ofcognitive appraisals will.Although the concepts of dominant and conflicting emotions can be applied to both

valence-based and cognitive appraisal tendency approaches, there are numerous argu-ments suggesting the superiority of the latter approach in explaining the connectionbetween emotions and risk perception. First, researchers note that the mere ability offeeling distinct emotions should result in their differential influence on many cognitiveand motivational processes (cf. DeSteno, Petty, Rucker, Wegener, & Braverman, 2004).Second, because the occurrence of a certain type of event roughly predicts the occurrenceof other events of the same type and because particular specific emotions mark suchcategories of events, the impact of affect is likely to be emotion specific rather thanvalence specific (DeSteno et al., 2000; Fessler, Pillsworth, & Flamson, 2004). It isunlikely that emotions sharing the same valence would necessarily have the same effect onrisk taking because valence is not uniformly associated with different classes of functionalgoals (Fessler et al.). Studies show that different emotions of the same valence can havecompletely opposite effects in a variety of decision-making situations and that emotionswith the same cognitive appraisal tendency are more alike than emotions of the samevalence (e.g., DeSteno et al.; Fessler et al.; Lerner & Keltner, 2000, 2001; Raghunathan &Pham, 1999). Likewise, dissimilarity in terms of cognitive appraisal tendency should bemore influential than dissimilarity in terms of valence. For risk judgments, certainty andcontrollability appraisals are shown to be most essential (Lerner & Keltner, 2000, 2001).Because these two appraisal tendencies produce opposing effects on risk judgments (e.g.,Foo, 2011), conflicting emotions with contrasting certainty and controllability should alsoproduce a greater feeling of discomfort and irregularity than conflicting emotions basedon contrasting valences. Once again, feelinguncomfortable will lead to a cautious,

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conservative judgment on the issue, resulting in a higher perception of risk. Therefore, wehypothesize:

Hypothesis 2: Conflicting emotions in terms of cognitive appraisal tendencies (i.e.,certain and controllable vs. uncertain and uncontrollable) will have a stronger asso-ciation with the risk perception of entrepreneurs than conflicting emotions in terms ofvalences (i.e., positive vs. negative emotions) will.Promoting entrepreneurship as the driver of economic growth aims to increase the

number of entrepreneurs founding new ventures. Having past experience as an entrepre-neur can increase the probability of actually transitioning from paid employment toentrepreneurship by 12%, while serial entrepreneurs can account for as many as 30% ofsuch transitions (Hyytinen and Ilmakunnas, 2007). Serial (also referred to as habitual)entrepreneurs therefore represent a very valuable population from a policy perspective(Wiklund & Shepherd, 2008). Moreover, serial entrepreneurs can play an important rolein promoting economic growth as they can potentially build upon their experience andstart more successful ventures. One of the executive forums of the Journal of BusinessVenturing (1986) was called To really learn about entrepreneurship, lets study habitualentrepreneurs, which accurately reflects the relevance of the study of serial entrepreneursto practitioners and the popularity of success stories of serial entrepreneurs.

As entrepreneurs found more new ventures and gain more experience in creating andrunning new businesses, their intuition develops as well (Mitchell, Friga, & Mitchell,2005). Although entrepreneurs newly accumulated insights and expert knowledge struc-tures are pillars supporting intuition (Mitchell et al.; Shane, 2000), emotions are also oneof the characteristic features of intuition (Epstein, 1994; Kahneman, 2003). Moreover,intuition is often depicted as being primarily nonverbal and intimately associated withaffect (Denes-Raj & Epstein, 1994). Consequently, as serial entrepreneurs tend to relymore on intuition in their judgments, they are also more likely to engage emotions in theirjudgments. Accordingly, both valence-based and cognitive appraisal tendency perspec-tives on emotions should play greater roles in the judgment processes of more experi-enced, serial entrepreneurs. Thus, we hypothesize:

Hypothesis 3a: Conflicting emotions in terms of valences (i.e., positive vs. negativeemotions) will play a greater role in risk judgments of serial entrepreneurs than in riskjudgments of novice entrepreneurs.Hypothesis 3b: Conflicting emotions in terms of cognitive appraisal tendencies (i.e.,certain and controllable vs. uncertain and uncontrollable) will play a greater role inrisk judgments of serial entrepreneurs than in risk judgments of novice entrepreneurs.

Control VariablesIn this study, we use the basic emotions of anger, fear, happiness, and hope as control

variables. On the basis of past research, we expect these emotions to be associated withentrepreneurial risk perception. However, the direction of the associations is not clear. Thevalence-based approach would predict a positive association of anger and fear withentrepreneurial risk perception and a negative association of happiness and hopewith entrepreneurial risk perception (Johnson & Tversky, 1983). The cognitive appraisaltendency approach would generally predict a positive association of fear and hope withentrepreneurial risk perception and a negative association of anger and happinesswith entrepreneurial risk perception (Lerner & Keltner, 2000, 2001). At the same time, not

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all of the cognitive appraisal dimensions show a stable link between emotions and theirappraisal tendencies, making these predictions preliminary (Smith & Ellsworth, 1987;Tong et al., 2009). Another factor making these predictions more difficult is the nature ofour sample. We also control for entrepreneurs who are familiar with the case we presentin the study and their entrepreneurial experience.

Method

Sample and Data CollectionThe participants for this study were drawn from the list of 6,359 founders of venture-

backed firms provided by VentureOne, a leading venture capital (VC) research companybased in San Francisco. VentureOne began tracking equity investment in 1992. It collectsdata by surveying VC firms for recent funding activities and portfolio updates, gatheringinformation through direct contacts at venture-backed companies, and investigatingvarious secondary resources such as company press releases and initial public offeringprospectuses from VentureOne 2001. We randomly selected 1,100 entrepreneurs withcomplete contact information for the study.

In administering the scenario and the related questionnaire, we followed the totaldesign method for survey research (Dillman, 1978). The first mailing packet included apersonalized letter, a project fact sheet, the survey, a priority postage-paid envelope withan individually typed return-address label, and a list of research reports available toparticipants. The package was sent by priority mail to each randomly selected entrepre-neur. As a result of some packages being undeliverable for name or address reasons, theadjusted sample comprised 776 entrepreneurs.

To increase the response rate, we sent four follow-up mailings to the companies. Oneweek after the mailing, we sent a follow-up letter. Two weeks after the first follow-up, wesent a second package with the same content as the first package to all nonrespondingcompanies. After two additional follow-up letters, we received completed questionnairesfrom 255 entrepreneurs, representing a response rate of 32.9%. Two respondents indicatedthat they had no active experience as venture founders and were omitted from the analysis.In our final sample, 181 were male and 72 were female. The highest degree obtained for46 of the entrepreneurs was high school; for 124, bachelor degree; for 74, masters degree;and for 9, doctoral degree. The mean age of the respondents was 42.4 years. On average,they founded 4.4 ventures, were currently involved in 2.1 ventures, and had 14.5 years ofentrepreneurial experience.

MeasurementsIn our study, we used existing cases and scales from the literature. We conducted a

pretest by extensively interviewing 12 entrepreneurs. At the beginning of each interview,entrepreneurs told us about the background of their ventures, how they started, how theydiscovered the opportunity, and how the business idea developed over time. This allowedus to get the conversation started and better interpret their answers on the questionnaire.In the last part of the interview, we used the protocol method and asked the entrepreneursto think aloud as they filled out the questionnaire (Hunt, Sparkman, & Wilcox, 1982).The interviews were recorded and two researchers made careful notes of the verbaliza-tions and the thinking process of the entrepreneurs. The analysis of interviews led to minorchanges in the wording of the instructions and cases description.

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For the sake of ecological validity of our results, we chose to center measures of allthe variables in our study around a strategic issue, signifying an important environmentalevent, trend, or development for which future resolution will be sought (Dutton &Jackson, 1987). The selected issue was extensively pretested in earlier studies to be surethat it represents an ambiguous event that could be interpreted both as a positive and as anegative change in the competitive environment (Highhouse et al., 1996). As a result, themeaning of the strategic issue is not inherent in the external environment and it is up tofirms decision makers to interpret the event (Dutton & Jackson). Meanings attached tostrategic issues color the subsequent affective and cognitive decision processes of thedecision makers. This ambiguity allowed us to maximize the chance that entrepreneurs inour sample will experience mixed emotions, the focus of our study (Folkman & Lazarus,1985; Larsen et al., 2004).

The strategic issue we chose was originally used by Dutton and Jackson (1987) as ananecdotal example that everybody can easily relate to. Considering the potential differ-ences in the backgrounds of entrepreneurs, this seems to be the most appropriate choice.Highhouse et al. (1996) adapted the issue in their study of strategic-issue framing. In ourstudy, we used the version found in Highhouse et al. It reads as follows:

Imagine that you are the owner of a retail clothing store. You have historicallyprospered by occupying a choice downtown location. You have just found out thatplans are underway to construct a large suburban shopping mall ten miles from yourcurrent place of business. (p. 97)Highhouse et al. (1996) found that the description above is a neutral description of the

strategic issue; it is neither representing a positive situation nor a negative one. Thus,positive or negative assessments of this situation are interpretations of the decisionmakers.

Dependent Variable. To measure risk perception, we asked the respondents to character-ize on 7-point scales whether they saw the strategic issue as an opportunity or as a threatand as having a potential for loss or a potential for gain. We also asked whether theycharacterized the issue as a positive or a negative situation (Jackson & Dutton, 1988;MacGrimmon & Wehrung, 1985; Sitkin & Weingart, 1995). Cronbachs a for the riskperception construct is 0.81.

Independent Variables. To objectively assess mixed emotions (Priester & Petty, 1996),respondents were asked to rate on 7-point scales the extent to which each of 16 emotionadjectives described how they were feeling about the strategic issue, allowing for naturallyoccurring emotions. This approach differs from the priming technique to make the par-ticipants feel a certain emotion that is unrelated to the specific issue involved (e.g., Foo,2011; Lerner & Keltner, 2001). Sixteen emotion descriptors were selected from a list of25 adjectives presented by Smith and Ellsworth (1987); eight positive and eight negativefeelings were selected to allow for contrasting the valence-based and cognitive appraisaltendency approaches. Also, eight of the 16 adjectives were associated with high certaintyand controllability appraisals and eight were associated with relatively low certainty andcontrollability appraisals (Lerner & Keltner, 2000, 2001; Smith & Ellsworth, 1985, 1987).Table 1 summarizes the valences and dimensions for each emotion adjective.

By employing a mean split, we determined whether a particular emotion adjective wasexperienced (1) or not (0). This served as the basis for calculating the mixed emotionsmeasures for both the valence-based and cognitive appraisal tendency approaches.Because the ambivalence literature shows that conflicting emotions drive ambivalence, we

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first computed the separate dominant and conflicting emotions scores in order to test theirrelative importance for entrepreneurs. For the valence-based approach, we calculated thedominant emotions for each respondent on the basis of positive and negative valence bytaking the greater of either the sum of experienced positive adjectives or the sum ofexperienced negative adjectives (Priester & Petty, 1996, 2001). For the cognitive appraisaltendency approach, we calculated dominant emotions associated with dissimilar cognitiveappraisals by taking the greater of either the sum of experienced emotions with highcertainty and controllability appraisals or the sum of experienced emotions with lowcertainty and controllability appraisals. For conflicting emotions, we followed the sameprocedure, but took the lesser instead of the greater of the sums of experienced emotions(Priester & Petty, 1996, 2001).

In order to calculate mixed emotions for both approaches, we used the GTM formulasuggested by Priester and Petty (1996) as the most appropriate measure of ambivalence:

5C Dp 1/C

where C is equal to the magnitude of conflicting reactions, D is equal to the magnitude ofdominant reactions, p is less than 1 (0.5 in the present instance), and a constant of 1 isadded to C and D (Priester & Petty, 2001).

Control Variables. The findings of Smith and Ellsworth (1987) demonstrate that the 16emotion adjectives correspond to four basic emotions: anger, fear, happiness, and hope.Anger was depicted by such adjectives as resentful, angry, surprised, and scornful; fearby nervous, afraid, restless, and anxious; happiness by elated, happy, amused, and proud;and hope by expectant, hopeful, challenged, and interested. After the exploratory factoranalysis we dropped the adjective anxious from the fear construct and the adjectiveinterested from the hope construct due to their cross loadings. On the basis of the

Table 1

Characteristics of 16 Emotional Adjectives

Emotionaladjective Valence

Certaintyappraisal

Controllabilityappraisal

Afraid Negative Low LowAmused Positive High HighAngry Negative High HighAnxious Negative Low LowChallenged Positive Low LowElated Positive High HighExpectant Positive Low LowHappy Positive High HighHopeful Positive Low LowInterested Positive Low LowNervous Negative Low LowProud Positive High HighResentful Negative High HighRestless Negative Low LowScornful Negative High HighSurprised Negative High High

125January, 2012

remaining adjectives, Cronbachs a for anger, fear, happiness, and hope were 0.83, 0.83,0.79, and 0.78, respectively, suggesting good reliabilities (Nunnally, 1978). Finally,although emotions are one of the characteristic features of intuition (Epstein, 1994;Kahneman, 2003), entrepreneurial intuition can also be based on prior knowledge andexpert knowledge structures (Mitchell et al., 2005; Shane, 2000). We thus added theentrepreneurs familiarity with the strategic issue and number of ventures founded ascontrols to our model in order to distinguish knowledge-based effects from our findings.We measured familiarity by the extent to which entrepreneurs could relate the strategicissue to one of the decisions they had made in the past. Number of ventures founded wasmeasured by the number of ventures in which the entrepreneurs were actively involved asa founder. Finally, we added the common control variables of age, gender, type, and levelof education.

Analysis and Results

Prior to testing the hypotheses, we examined the correlation matrix, shown inTable 2. The measures of mixed, conflicting, and dominant emotions appear to behighly correlated (0.740.96), so we do not include any two of these variables in thesame regression model. The correlations between these types of emotions and basicemotions are also quite large, although lower (i.e., ranging between 0.47 and 0.70 withthe majority around 0.60). In models combining basic and mixed emotions, we mean-centered all emotion variables in order to eliminate the nonessential multicollinearitydue to the computation formula of mixed emotions components (Aiken & West, 1991;Cohen, Cohen, West, & Aiken, 2003; Kenny & Judd, 1984). An application of Belsley,Kuh, and Welsch (1980) diagnostic tests indicated no serious multicollinearity problemsin the mean-centered regression models (maximum variance inflation factor was5.5 < 0; maximum condition index was 22.3 < 30, while the proportion of varianceinflated for emotions did not exceed 0.05 < 0.50). However, because the maximum vari-ance inflation factor does not exceed 1.83 in other models, caution is necessary wheninterpreting the results when both basic emotions and mixed emotions are entered intothe same models.

To test the hypothesized relationships, we performed hierarchical regression analysis(Cohen & Cohen, 1983; Cohen et al., 2003). This method examines the effects of addi-tional variables above and beyond the effects of the variables in the previous model. InTable 3, we present a summary of the results of eight regression models.

All the regression models were highly significant, with F-values ranging between 4.29and 8.71 (p < .001). In the first baseline model, we only examined the effects of the controlvariables on entrepreneurial risk perception. In model 2, we added the basic emotionsbased on positive and negative valence. In model 3, we added the mixed emotions basedon positive and negative valence. In models 4 and 5, we split the mixed emotions frommodel 2 into dominant and conflicting emotions in order to determine their relative effecton mixed emotions. In model 6, we added the mixed emotions associated with differentcognitive appraisals. Finally, in models 7 and 8, we split the mixed emotions from model6 into dominant and conflicting emotions in order to determine their relative effect onmixed emotions. The results from the hierarchical regressions suggest that all modelsrepresent significant improvements over model 1.

We also conducted regressions by adding the basic emotions to models 3 to 8 (notreported in Table 3). Only mixed and conflicting emotions in terms of cognitive appraisaltendencies remained significant with a coefficient (standard error) of 0.065 (0.035),

126 ENTREPRENEURSHIP THEORY and PRACTICE

Tabl

e2

Des

crip

tive

Stat

istic

s(N=

253)

Cons

truct

sM

ean

SD1

23

45

67

89

1011

1213

1415

16

1.R

iskpe

rcep

tion

4.22

1.33

2.M

ixed

(Val

.)7.

873.

600.

263.

Confl

ictin

g(V

al.)

3.11

2.32

0.33

0.96

4.D

omin

ant(

Val.)

4.89

2.30

0.35

0.74

0.82

5.M

ixed

(Cog

n.A

ppr.)

7.93

3.53

0.37

0.78

0.84

0.82

6.Co

nflic

ting

(Cog

n.A

ppr.)

3.13

2.33

0.41

0.83

0.91

0.88

0.96

7.D

omin

ant(

Cogn

.App

r.)4.

872.

350.

260.

850.

890.

910.

680.

778.

Ang

er4.

331.

250.

220.

650.

670.

640.

600.

650.

649.

Fear

4.53

1.39

0.26

0.69

0.70

0.64

0.62

0.65

0.67

0.49

10.

Hap

py3.

681.

480.

430.

470.

560.

570.

560.

610.

500.

320.

3211

.H

ope

4.93

1.14

0.07

0.61

0.65

0.61

0.51

0.59

0.66

0.43

0.41

0.21

12.

Age

42.3

812

.76

0.02

0.02

0.04

0.01

0.01

0.04

0.02

0.05

0.02

0.07

0.03

13.

Bus

ines

sde

gree

0.60

0.49

0.06

0.24

0.29

0.30

0.23

0.27

0.31

0.13

0.16

0.08

0.35

0.01

14.

Deg

ree

level

2.18

0.77

-0.0

20.

120.

150.

140.

090.

120.

160.

090.

120.

000.

200.

090.

2015

.Fa

mili

arity

with

issue

5.22

1.57

0.07

0.14

0.18

0.21

0.15

0.19

0.19

0.08

0.15

-0.0

70.

20-0

.06

0.27

0.01

16.

Fem

ale

entr

epre

neur

1.28

0.45

-0.1

10.

090.

100.

030.

020.

060.

070.

000.

020.

03-0

.02

0.05

0.02

0.01

0.10

17.

Num

bero

fven

ture

s4.

402.

820.

260.

470.

540.

510.

450.

520.

510.

380.

460.

240.

470.

040.

480.

240.

290.

07

Note

:Co

rrela

tions

of|0

.13|an

dab

ove

are

signi

fican

tatp