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    SHOULD I QUIT MY DAY JOB?: A HYBRID PATH TOENTREPRENEURSHIP

    JOSEPH RAFFIEEUniversity of Wisconsin–Madison

    JIE FENGUniversity of Wisconsin–Madison

    Research suggests that the risk and uncertainty associated with entrepreneurial activ-ity deters entry and contributes to the high rates of new business failure. In this study,we examine how the ability to reduce these factors by means of hybrid entrepreneur-ship—the process of starting a business while retaining a “day job” in an existingorganization—influences entrepreneurial entry and survival. Integrating insights fromreal options theory with logic from the individual differences literature, we hypothe-size and find that individuals who are risk averse and have low core self-evaluation

    are more likely to enter hybrid entrepreneurship relative to full-time self-employment.In turn, we argue and find that hybrid entrepreneurs who subsequently enter full-timeself-employment (i.e., quit their day job) have much higher rates of survival relative toindividuals who enter full-time self-employment directly from paid employment. Add-ing support to our theory that the survival advantage is driven by a learning effect thattakes place during hybrid entrepreneurship, we find that the decrease in exit hazardis stronger for individuals with prior entrepreneurial experience. Taken together, ourfindings suggest that individual characteristics may play a greater role in determiningthe process of how (rather than if) entrepreneurial entry occurs, and that the processof how entrepreneurial entry transpires has important implications for new businesssurvival.

    Research indicates that entrepreneurial activityis a key driver of economic growth, but only if entrepreneurial entrants are able to avoid early ex-odus (Santarelli & Vivarelli, 2007). Not surpris-ingly, therefore, understanding the determinants of entrepreneurial entry and dynamics of venture sur-vival has attracted the interest of numerous organ-izational scholars (e.g., Elfenbein, Hamilton, &Zenger, 2010; Evans & Leighton, 1989; Geroski,Mata, & Portugal, 2010; Ozcan & Reichstein, 2009;Patel & Thatcher, 2012). As evidenced by the highfrequency of new business failure (Shane, 2003),understanding entry implies explaining why some

    individuals opt to start businesses despite the riskyand uncertain returns associated with doing so(Kihlstrom & Laffont, 1979). Likewise, understand-ing survival entails identifying how and why someentrepreneurs are able to overcome these risks tosurvive (Santarelli & Vivarelli, 2007). As such, pin-pointing ways in which the risk and uncertaintyassociated with entrepreneurship can be managedor reduced should offer further insight regardinghow these processes unfold (see Folta, 2007).

    One such way is through hybrid entrepreneur-ship—the process of initiating a business while

    simultaneously remaining employed for wages(Folta, Delmar, & Wennberg, 2010). By launching a business while retaining their “day job,” hybridentrepreneurs implicitly reduce (or eliminate) theopportunity cost (i.e., earnings from paid employ-ment) associated with starting the venture (Folta,2007; Folta et al., 2010). As such, by reducing whatis put “at risk,” starting a business via hybrid en-trepreneurship is inherently less risky than doingso full time. Recognizing this, scholars have re-cently noted that hybrid entrepreneurs represent a

    We are deeply grateful to our editor Gerard George andthree anonymous AMJ  reviewers for their insightful com-ments and guidance throughout the review process. Wealso wish to thank Russ Coff, Barry Gerhart, Randy Dun-ham, Jon Eckhardt, Ken Kavajecz, Phil Kim, and HartPosen for their helpful feedback and suggestions. Thefirst author graciously acknowledges financial supportprovided by the Robert W. Pricer PhD student fellowshipat the University of Wisconsin-Madison. Of course, allerrors remain our own.

    936

      Academy of Management Journal 

    2014, Vol. 57, No. 4, 936–963.

    http://dx.doi.org/10.5465/amj.2012.0522

    Copyright of the Academy of Management, all rights reserved. Contents may not be copied, emailed, posted to a listserv, or otherwise transmitted without the copyright holder’s express

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    significant and growing component of total entre-preneurial activity (Burke, FitzRoy, & Nolan, 2008;Folta et al., 2010; Petrova, 2012). According to theU.S. Bureau of Labor Statistics, in 2011, roughly10 percent of self-employed workers were also em-

    ployed by existing firms. Going a step further, re-search shows that many hybrid entrepreneurs ulti-mately decide to commit to their ventures full time(Folta et al., 2010). Indeed, anecdotal evidence in-dicates that some of the world’s most innovativeand successful entrepreneurs started their compa-nies as hybrid entrepreneurs. For example, SteveWozniak remained an employee at Hewlett–Pack-ard long after co-founding Apple (Wozniak &Smith, 2006), Pierre Omidyar launched eBay whileworking for the software development companyGeneral Magic (Cohen, 2002), and, with the help of 

    investors, Henry Ford founded the Detroit Automo- bile Group while employed by the Edison Illumi-nating Company (Ford & Crowther, 1922). In 1997,20 percent of CEOs on  Inc. magazine’s 500 fastest-growing private companies list indicated that theycontinued to work a paying job long after foundingtheir organization (Inc. staff, 1997). Yet, despitethese observations, extant entrepreneurship theorylargely assumes that entrepreneurial entry is anall-or-nothing phenomenon (Folta et al., 2010),and, because empirical testing is driven by theory,the treatment of labor force status as a mutuallyexclusive dichotomy is generally considered “un-controversial” in the literature (Sørensen & Fas-siotto, 2011: 1,323).1

    In this article, we depart from this trend and addto an emerging stream of literature (e.g., Burke etal., 2008; Folta et al., 2010; Petrova, 2012) by con-sidering the theoretical implications of hybrid en-trepreneurship for theories of entrepreneurial entryand survival. For example, extant theory suggestsentrepreneurs have high tolerances for risk (Kihl-strom & Laffont, 1979) and/or perceive less risk dueto greater confidence in their abilities (Moore,

    Oesch, & Zietsma, 2007). However, considering hy- brid entrepreneurship reduces (or eliminates) theneed for risk-bearing when starting a business,these theories may not adequately explain entry.Likewise, once an individual enters hybrid entre-

    preneurship, the uncertainty surrounding the fu-ture returns and viability of the business lessens(Folta et al., 2010). As a result, hybrids that opt toenter full-time self-employment do so under con-ditions of greater certainty (relative to those whoenter directly from paid employment). However,despite numerous theoretical explanations (e.g.,Geroski et al., 2010; Santarelli & Vivarelli, 2007),scholars have yet to consider how staged entry intofull-time self-employment via the pathway of hy-

     brid entrepreneurship influences venture survival.To reconcile these issues, we turn to logic from

    real options theory (Trigeorgis, 1996). Conceptual-izing hybrid entrepreneurship as analogous to theestablishment of a real option—a small initial com-mitment that creates the right, but not the obliga-tion, to subsequently commit full time to the ven-ture (Folta et al., 2010; Wennberg, Folta, & Delmar,2006)—we integrate insights from real options the-ory with logic from the individual differences lit-erature (Funder, 2001) to theorize that risk-averseand less confident individuals will be more likelyto enter hybrid entrepreneurship relative to full-time self-employment. In turn, using real optionslogic that emphasizes the benefits of learning fromsmall investments (Roberts & Weitzman, 1981), weargue staged entry into full-time self-employmentthrough hybrid entrepreneurship will relate posi-tively to venture survival. Finally, emphasizing theinherent heterogeneity among real options decisionmakers (e.g., Barnett, 2008), we posit that individ-ual characteristics (cognitive ability and entrepre-neurial experience) that influence the hybrid entre-preneur’s ability to evaluate the prospects of theirventure during hybrid entrepreneurship will mod-erate this relationship.

    The present study makes several contributions.

    First, acknowledging that hybrid entrepreneurshipimplicitly reduces the risk associated with startinga business (Folta et al., 2010), our study suggests forthe first time that individual characteristics per-taining to risk preferences and risk perception mayinfluence  how  rather than   if  entrepreneurial entryoccurs. Second, despite a substantial literature onventure survival (Santarelli & Vivarelli, 2007) andmounting evidence that entry into full-time self-employment is endogenous to hybrid entrepreneur-ship (Folta et al., 2010), the current study is the first

    1 Hybrid entrepreneurship is common in academic en-trepreneurship (e.g., Jain, George, & Maltarich, 2009),where academics often form firms to commercialize re-search while retaining their academic position (as op-posed to exiting the institution to pursue the venture fulltime) (Nicolaou & Birley, 2003a). However, perhaps dueto the uniqueness of the university setting, few studieshave accounted for this distinction theoretically or em-pirically (see Nicolaou & Birley, 2003a, 2003b for notableexceptions). Ultimately, this broadens the contributionsof our study.

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    to argue and show that entering full-time self-em-ployment incrementally via hybrid entrepreneur-ship increases the odds of survival. Third, we ex-tend recent research (Autio & Acs, 2010; Folta et al.,2010; O’Brien, Folta, & Johnson, 2003) by testing

    predictions from real options theory using individ-ual characteristics as explanatory and moderatorvariables. By doing so, our work contributes to thereal options literature by theoretically arguing andempirically demonstrating that individual charac-teristics influence both the likelihood and efficacyof real options reasoning.

    THEORY AND HYPOTHESES

    Motivated by the importance of the phenome-non, scholars from a variety of backgrounds,

    including sociology (Sørensen, 2007), economics(Hamilton, 2000), and psychology (Hmieleski &Baron, 2009), have sought to explain entrepreneur-ial activity. While the multidisciplinary approachhas greatly contributed to our understanding of theentrepreneurial process (Shane, 2003), it has alsoled to areas of disagreement, particularly with re-gards to how entrepreneurship should be concep-tualized and defined (see Sørensen & Fassiotto,2011). In this article, our interest is in understand-ing entrepreneurship in terms of labor force status(i.e., self-employment versus paid employment).Defined this way, entrepreneurship encompassesthe entire array of entrepreneurial activity, rangingfrom the small self-employed sole proprietor to thelarge venture-backed start-up, making the implica-tions of our theory generalize to all entrepreneurialentrants, not just those with a specific type or via-

     ble entity (Yang & Aldrich, 2012). Accordingly, toremain consistent with prior hybrid entrepreneur-ship studies (e.g., Folta et al., 2010), we use theterms “entrepreneurship” and “self-employment”interchangeably.

    Despite the definitional divergence, there exists arelative consensus within the literature that entre-

    preneurial activity involves risk and uncertainty(Folta, 2007; McMullen & Shepherd, 2006). For ex-ample, even if entrepreneurs are able to shift allfinancial risk to other actors (e.g., investors), “inevery case, the entrepreneur risks the opportunitycosts associated with starting the venture” (Folta,2007: 98). Thus, by entering self-employment, it istypically assumed that individuals transform theirsource of income from a relatively safe asset (i.e.,earnings in paid employment) into a more riskyasset (i.e., returns to self-employment), as reflected

     by the high dispersion in self-employed earnings(Hamilton, 2000) and likelihood of business failure(Shane, 2003). In turn, the risk associated with thistransformation has been argued to be a key deter-rent of entrepreneurial entry (Amit, Muller, & Cock-

     burn, 1995). However, this logic overlooks the factthat individuals can circumvent this trade-off bymeans of hybrid entrepreneurship (Folta et al.,2010). Hence, by starting a business without quit-ting one’s day job, hybrid entrepreneurs need notput their “certain” earnings from paid employmentat risk. Accordingly, recognizing that hybrid entre-preneurship represents a smaller-scale and lessrisky (i.e., less sunk commitment) entrepreneurialentry path, scholars at the forefront of the hybridentrepreneurship literature have argued that realoptions theory is a theoretical perspective well-

    suited to provide insights into the hybrid phe-nomenon (Folta et al., 2010; Wennberg et al.,2006). In the next section we briefly reviewreal options theory and its link to hybridentrepreneurship.

    Real Options Theory and HybridEntrepreneurship

    Real options theory is a framework for makinginvestments in risky and uncertain contexts (Dixit& Pindyck, 1994). In real options theory, the “op-tion” typically refers to a small initial investmentthat creates the possibility, but not the obligation,to make subsequent larger investments (McGrath,1997). A key benefit of investing in real options isthat it allows decision makers to gather informationand learn, thereby reducing the uncertainty sur-rounding the investment, prior to making largercommitments (Majd & Pindyck, 1987; Roberts& Weitzman, 1981; Weitzman, Newey, & Rabin,1981). Should the information generated from theoption appear favorable (unfavorable), subsequentcommitments can be made (ceased). Thus, becausethe potential upside gain has no ceiling, but the

    downside loss (i.e., risk) is limited to the cost of theoption, real options become more valuable in situ-ations characterized by high uncertainty (i.e., highvariance in returns) (McGrath, 1997). Accordingly,while real options theory predicts that high uncer-tainty dissuades large commitments, it also sug-gests that it can encourage small commitments inthe form of real options. For instance, O’Brien et al.(2003) find the likelihood of full-time entrepre-neurial entry is lower in industries characterized

     by greater uncertainty. Ziedonis (2007) concludes

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    that firms interested in university technology aremore likely to purchase an option contract (smallcommitment) prior to committing to a licensingagreement (large commitment) when the uncer-tainty embedded in the technology is high.

    The commonalities between real options and hy- brid entrepreneurship are twofold. First, as noted by O’Brien et al. (2003), it is difficult to surmise acontext in which risk and uncertainty are moresalient than entrepreneurship. Second, much like areal option, hybrid entrepreneurship allows indi-viduals to start a business on a smaller scale withless sunk costs and downside risk (Folta et al.,2010). Empirical findings support this connection.For example, in accord with real options theory,Wennberg et al. (2006) find that individuals aremore likely to enter hybrid entrepreneurship as

    opposed to full-time self-employment in more un-certain industries. Similarly, noting that hybrid en-trepreneurship is akin to a real option to invest,Folta et al. conclude that many hybrid entrepre-neurs ultimately enter full-time self-employment,indicating that hybrid entrepreneurship is oftenused as a means to “test the entrepreneurial waters”prior to committing to the venture full time (Foltaet al., 2010: 253).2 Hence, as these studies demon-strate, real options theory has the power to explain

     both entrepreneurial entry and entrepreneurial out-comes. On the one hand, real options theory sug-gests that the ability to reduce the risk associatedwith starting a business can entice entrepreneurialentry (Lee, Peng, & Barney, 2007). On the otherhand, the learning benefits associated with hybridentrepreneurship (Roberts & Weitzman, 1981) im-ply that starting a business through a pathway of paid employment   ¡   hybrid   ¡   full-time self-em-ployment should be associated with positive out-comes. As a result, real options theory provides asingle unifying framework suitable to explain theentire entrepreneurial process. However, given itsemphasis on the effects of investment risk and un-certainty, real options theory is built on the as-

    sumption of a risk-neutral and preference-free de-cision maker (Dixit & Pindyck, 1994). Yet, in mostreal-world scenarios, these assumptions are unre-

    alistic, leading to a scholarly push for researchers toincorporate decision maker characteristics and pref-erences into real options theory (e.g., Barnett, 2008).For instance, O’Brien et al. argue it is time to “shift thefocus of research away from macroeconomic mea-

    sures and towards using firm-specific (or even  indi-vidual-specific ) determinants of entry thresholds”(O’Brien et al., 2003: 515, emphasis added). We do soin this study, beginning by using individual charac-teristics that influence individual thresholds for riskand uncertainty to generate real options predictionsregarding entrepreneurial entry.

    Risk Aversion, Core Self-Evaluation, and Entryinto Hybrid Entrepreneurship

    Given that entrepreneurial activity is generally

    assumed to include the bearing of risk and uncer-tainty, the notion that entrepreneurs are comfort-able with risk has a long theoretical tradition in theacademic literature (Kihlstrom & Laffont, 1979;Knight, 1921). Nevertheless, empirical evidence re-garding risk preferences and entrepreneurial entryis largely mixed (see Brockhaus, 1980; Cramer, Har-tog, Jonker, & Van Praag, 2002; Miner & Raju, 2004).The majority of studies, however, do not theoreti-cally or empirically account for the fact that entryinto hybrid entrepreneurship inherently involvesless downside risk. As a result, it is possible thatrisk aversion influences the process of how, ratherthan if, an individual decides to start a new busi-ness. Along these lines, operating on the logic thatestablished businesses are less risky than start-upventures, Block, Thurik, van der Zwan, and Walter(2013) find that risk-averse individuals are morelikely to purchase an existing business rather thanstart a new venture from scratch. Likewise, by ac-knowledging the fact that hybrid entrepreneurshipallows individuals to reduce what is put at risk(i.e., earnings from paid employment) when start-ing a new venture (Folta et al., 2010), logic fromreal options theory can provide a more nuanced

    picture regarding the relationship between riskaversion and entrepreneurial entry.

    A central prediction of real options theory is thathigh levels of risk and uncertainty dissuade largecommitments (O’Brien et al., 2003). However, the-ories of risk aversion highlight heterogeneity withregards to individual comfort thresholds for riskand uncertainty. As a result, we expect that invest-ment behavior of a risk-averse individual should besimilar to the behavior of a risk-neutral decisionmaker facing high levels of exogenous uncertainty.

    2 Folta et al. (2010) also conclude that individuals mayenter hybrid entrepreneurship to generate non-monetary

     benefits, but found no indication that people becomehybrids to earn supplemental income. Similar findingswere reported by Petrova (2012), who concluded thatpart-time entrepreneurs are not impacted by financialconstraints.

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    Thus, extending insights from real options theoryto incorporate risk preferences would suggest that,in accordance with traditional equilibrium modelsof risk aversion and self-employment (Kihlstrom &Laffont, 1979), risk-averse individuals should be

    less willing to make the large commitments associ-ated with entry into full-time self-employment. Inother words, risk aversion effectively increases thevalue associated with deferring full-time entry (Hu-gonnier & Morellec, 2007). However, as uncertaintyrises, so too does the value of holding a real option(McGrath, 1997). Thus, while real options theorysuggests individuals with high risk aversion should

     be less likely to make the large commitments asso-ciated with direct entry into full-time self-employ-ment, they should be more willing to make smallercommitments associated with entry into hybrid en-

    trepreneurship. Indeed, by entering hybrid entre-preneurship, risk averse individuals can start a business and reduce what is at risk/the amount of risk-bearing. Thus, we suggest the following:

    Hypothesis 1. Individuals with higher risk aversion are more likely to enter hybrid entrepreneurship in comparison to full-timeself-employment.

    In addition to risk aversion, a number of otherindividual characteristics have been argued to in-fluence entrepreneurial entry. For instance, build-ing on the notion that entrepreneurs are highlyconfident (Knight, 1921), researchers have shownthat internal locus of control (Evans & Leighton,1989), self-efficacy (Zhao, Seibert, & Hills, 2005),and emotional stability (Zhao, Seibert, & Lumpkin,2010) relate positively to entrepreneurial entry.However, various elements of personality are oftentreated as entirely separate constructs, with little (if any) discussion regarding the interrelationshipsamong traits or acknowledgement that related ele-ments of personality may all be tapping the samehigher-order construct (Judge, Erez, Bono, & Thore-sen, 2003; Judge, Locke, & Durham, 1997). To that

    end, our study focuses on core self-evaluation(CSE), a broad dispositional trait manifested byfour elements of personality: self-esteem, general-ized self-efficacy, locus of control, and emotionalstability (Judge et al., 1997).

    Independent of context and time, CSE is theo-rized to reflect the fundamental appraisals individ-uals make about themselves, their capabilities, andtheir competence (Judge et al., 1997). For example,Chang, Ferris, Johnson, Rosen, and Tan write thatCSE is “proposed to be the most fundamental eval-

    uations people hold, reflecting a baseline appraisalthat is implicit in all other beliefs and evaluations”(Chang et al., 2012: 83, emphasis added). Thus, CSErepresents an individual’s overarching generalevaluations, not specific evaluations regarding any

    particular context (e.g., organizational, entrepre-neurial, etc.). Accordingly, research has demon-strated CSE to have predictive validity regarding awide variety of work- and life-related outcomes(Chang et al., 2012). Anchored in a real optionsframework, we add to this literature by developingtheory to explain how CSE influences real optionsreasoning and the process of entrepreneurial entry.

    Given that individuals high in CSE are confidentin their ability to successfully complete tasks andcontrol their environment (Judge et al., 2003), theseindividuals should be less deterred by the risk anduncertainty associated with starting a business.Stated differently, because individuals high in CSEare confident in their capabilities, they should per-ceive entering self-employment as less risky anduncertain (i.e., perceive less variance in outcomes).In contrast, individuals with low CSE tend to beunsure of themselves and their capabilities, makingthem more likely to perceive entering self-employ-ment as a high-risk endeavor (i.e., perceive morevariance in outcomes). Accordingly, a predisposi-tion to perceive entry into self-employment as morerisky and uncertain would, in effect, raise the valueassociated with using an option approach. Thus,consistent with Caves (1998), who argued that lessconfident entrepreneurs will tend to start their

     businesses on a smaller scale, our logic suggeststhat individuals with low CSE who enter self-em-ployment will be more likely to do so incremen-tally via hybrid entrepreneurship.

    The upper echelons literature provides somesupport for our reasoning. For example, Hiller andHambrick (2005) argue that CEOs high in CSE aremore likely to launch large-scale, quantum strategic

    initiatives, while CEOs low in CSE favor a smaller,incremental approach. Chatterjee and Hambrick(2007) found support for a positive relationship

     between the CSE of a firm’s CEO and the likelihoodthat the firm pursues entrepreneurial opportuni-ties. Simsek, Heavey, and Veiga (2010) concludethat CEO CSE is positively related to a firm’sentrepreneurial orientation. As we detailed above,we expect a similar relationship regarding entre-preneurial entry. Accordingly, we suggest thefollowing:

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    Hypothesis 2. Individuals with low core self-evaluation are more likely to enter hybrid entrepreneurship in comparison to full-timeself-employment.

    Staged Entry into Full-Time Self-Employmentand Survival

    The previous section uses insights from real op-tions theory and the individual differences litera-ture to predict hybrid entry. However, for manyindividuals, entry into hybrid entrepreneurshiprepresents just the first step on the path to full-timeself-employment. For example, Folta et al. (2010)argue that entry into full-time self-employment isendogenous to hybrid entrepreneurship, conclud-

    ing that hybrid entrepreneurs are thirty-eight timesmore likely than wage earners to enter full-timeself-employment. A prediction from real optionstheory is that hybrid entrepreneurs will enter full-time self-employment only when they perceive theoption to do so to be “in the money” (Trigeorgis,1996). Indeed, a key benefit of real options is theability to postpone decision making until the un-certainty surrounding the investment has been re-solved (Dixit & Pindyck, 1994). In the context of entrepreneurship, the uncertainty resolved duringthe option period (i.e., hybrid entrepreneurship) istypically endogenous—meaning that it can be re-duced by actions of the entrepreneur (see Folta,1998, for a detailed discussion). In other words, byentering hybrid entrepreneurship, individuals areable to learn about their venture, thereby reducingthe uncertainty surrounding its prospects, prior todeciding if they want to increase commitment(Roberts & Weitzman, 1981). As such, because in-dividuals enter self-employment after consideringthe relative costs and benefits (Muller & Arum,2004), absent positive information, hybrid entre-

    preneurs should see no reason to forego the benefitsassociated with their job in paid employment(Becker, 1960). The underlying logic is driven bythe fact that real options entail less sunk cost. As aresult, options that do not yield favorable informa-tion can be quickly abandoned while those thatappear promising can be exercised (O’Brien &Folta, 2009). Specifically, we focus on informationhybrid entrepreneurs accrue that reduces the un-certainty surrounding two components of a sustain-able business: (1) the quality of the business idea

    and (2) the entrepreneur’s skills, capabilities, andfit within the entrepreneurial context.3

    First, hybrid entrepreneurs benefit from the abilityto learn about the quality, potential, and feasibility of their business idea. Indeed, prior to the introduction

    of a new product (or service), it is difficult to knowwith certainty if one will be able to physically pro-duce the product or if the product will meet thecharacteristics of market demand (Autio, Dahlander,& Frederiksen, 2013). Over time, however, the uncer-tainty surrounding the value and feasibility of theventure lessens, making the prospects of the businessmore salient (Sorenson & Stuart, 2001). In other cases,

     business ideas may be difficult to fully understandwithout actually “starting the commercialization pro-cess” (George & Bock, 2012: 69). As such, the onlyway to determine the value and feasibility of these

    ideas is to go forth and attempt to exploit them.Second, hybrid entrepreneurs benefit from theability to learn about their entrepreneurial skills, ca-pabilities, and fit within the entrepreneurial context(Folta et al., 2010). Indeed, a lack of fit betweenfounder and company is a major reason for new busi-ness failures (Holmes & Schmitz, 1995). Much likedetermining the prospects of a business idea, only bystarting the business are individuals able to fully eval-uate if they have the necessary skills required to runthe business (Jovanovic, 1982). However, even if thehybrid entrepreneur does not possess these skills exante, hybrid entrepreneurship provides a low-risksetting where the necessary capabilities can belearned prior to committing to the venture full time.Furthermore, hybrid entrepreneurship provides a re-alistic preview of life as an entrepreneur, illuminatingthat many of the glamorous portrayals of entrepre-neurship are largely myths (Shane, 2008) and that

     being self-employed is a time-consuming and chal-lenging process.

    Given that hybrid entrepreneurs have no obliga-tion to enter full-time self-employment (McGrath,1997), that the cost of abandoning the venture hasless sunk cost (O’Brien & Folta, 2009), and that

    hybrid entrepreneurs learn about the merits of theirventure idea, skills, and entrepreneurial fit prior to

    3 As an aside, it is crucial to note that the learning benefits associated with hybrid entrepreneurship applyto all   hybrid entrepreneurs, including those with no ex-ante intention to enter full-time self-employment (Foltaet al., 2010). For example, when Omidyar founded eBay,he had no intention of ever quitting his day job. However,after a positive market reaction, he felt he had no choice

     but to focus on eBay full time (Cohen, 2002).

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    committing to the business full time (Roberts &Weitzman, 1981), real options theory suggests thathybrid entrepreneurs who “exercise” the optionand enter full-time self-employment have reason to

     believe their business is sustainable and holds

    promise (i.e., the option is in the money). Accord-ingly, we suggest the following:

    Hypothesis 3. Individuals who transition into full-time self-employment in a staged entry  process via hybrid entrepreneurship will sur-vive longer than individuals who transitioninto full-time self-employment directly from paid employment.

    Moderators of the Staged Entry–SurvivalRelationship

    In the previous section, we use logic from realoptions theory to argue that hybrid entrepreneurs ex-ercise the option to enter full-time self-employmentwhen they believe the option to be in the money.However, unlike financial options where proper ex-ercise thresholds are intuitive, determining if realoptions are in the money is subjective, less straight-forward, and heavily reliant on decision-maker in-sight (e.g., Barnett, 2008). As such, we expect that thesurvival benefit associated with staged entry into full-time self-employment will vary with the hybrid en-trepreneur’s ability to make effective assessments

    regarding the venture’s potential. Specifically,we focus on two characteristics that influencethis ability: (1) cognitive ability (i.e., general in-telligence) (Schmidt & Hunter, 2004) and (2) spe-cific knowledge accumulated through prior (en-trepreneurial) experience (Cohen & Levinthal,1990; Zahra & George, 2002).

    Cognitive Ability

    Cognitive ability is conceptualized as the generalability to think abstractly, learn from experiences,comprehend surroundings, and “figure things out”

    (Lubinski, 2004). Indeed, not all individuals areable to learn, process, and apply new knowledgeequally (Hunter, 1986). Empirical research hasdemonstrated that individuals with high general in-telligence are better able to assimilate information toapply it in new situations (Jensen, 1998) and acquirenew skills (Gottfredson, 1997). As a result, Schmidtand Hunter (2004) argue that general mental ability isthe primary factor responsible for turning experienceinto knowledge and the single most important attri-

     bute explaining variance in job performance.

    Surprisingly, however, studies regarding the rela-tionship between intelligence and entrepreneurial ac-tivity are rare (Baum & Bird, 2010; Vinogradov &Kolvereid, 2010). Nevertheless, scholars have longhinted that cognitive ability plays an important role

    in entrepreneurial process. For example, Knight(1921) argued that intellectual ability would lead tothe identification of more valuable opportunities.Similarly, Vinogradov and Kolvereid (2010: 153) sug-gest that, since intelligence represents a “broader anddeeper capability for comprehending surroundings,”it should be particularly useful when evaluating newopportunities. Along these lines, while scholars haveargued that creativity is important for generating busi-ness ideas, analytical intellectual ability is most im-portant when assessing an idea’s merits and potential(Baum & Bird, 2010). For example, entrepreneurial

    researchers have noted that intelligence increases theability to see value embedded within new informa-tion (Shane, 2003), and that analytical ability is par-ticularly helpful when interpreting and making senseof complex information in an entrepreneurial setting(Baum & Bird, 2010). As a result, the benefit of cog-nitive ability should be particularly salient duringhybrid entrepreneurship, where hybrid entrepre-neurs accrue a wealth of information about their busi-ness that can be used to determine if the business isworth pursuing full time (i.e., if they should exercisethe option). Stated differently, because intelligenceincreases a hybrid entrepreneur’s ability to “analyzeand evaluate multiple and complex courses of ac-tion” (Baum & Bird, 2010: 399), we expect intelligenthybrid entrepreneurs to make better exercise deci-sions, being more likely to exercise the option when itis in the money and abandon it when it is not. Thus,we suggest the following:

    Hypothesis 4. Cognitive ability moderates the positive relationship between staged entry and  full-time self-employment survival such that the relationship is stronger for individuals withhigh cognitive ability.

    Entrepreneurial Experience

    The ability to assess, assimilate, and make senseof new information is also a function of an organi-zation or individual’s prior experience and stock of knowledge (Cohen & Levinthal, 1990; Zahra &George, 2002). Given that repeat entrepreneurs areable to draw on their prior experiences foundingventures, scholars have posited that entrepreneur-ial experience should be particularly useful whenevaluating the prospects of a new business (Wright,

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    Westhead, & Sohl, 1998). For instance, Toft-Kehler,Wennberg, and Kim (2014) argue that experiencedentrepreneurs are able to use their knowledge re-garding past entrepreneurial ventures to make moreeffective connections and deduce inferences re-

    garding the prospects of a new venture. Similarly,the literature on entrepreneurial cognition suggestsexperienced entrepreneurs develop expert scriptsand knowledge structures allowing them to useinformation more effectively than inexperiencedentrepreneurs (Mitchell et al., 2007). Indeed, re-search suggests that experienced entrepreneursthink differently than novice entrepreneurs whenevaluating and assessing opportunities (Baron &Ensley, 2006; Ucbasaran, Westhead, & Wright,2009). For example, Baron and Ensley (2006) findthat experienced entrepreneurs emphasize more

    mundane characteristics indicating venture feasi- bility and the likelihood of positive financial re-turns, while novice entrepreneurs focus on charac-teristics reflecting a greater degree of novelty andexcitement.

    Despite this evidence, empirical studies linkingentrepreneurial experience and venture survivalhave generally reported mixed findings (Delmar &Shane, 2006; Gimeno, Folta, Cooper, & Woo, 1997;

     Jørgensen, 2005). One explanation is that the rela-tionship is more complex than a simple main ef-fect. In other words, ex ante, the outcomes of thefounding process remain highly uncertain even forrepeat entrepreneurs (Aldrich, 1999). However,given the chance to amass information about theirventure through hybrid entrepreneurship, repeatentrepreneurs can utilize their knowledge regard-ing what worked and what did not when assessingthe new venture’s prospects (Toft-Kehler et al.,2014). Moreover, the opportunity characteristicsexperienced entrepreneurs look for when assessingthe quality of business ideas, such as positive cashflow, high margins, and the ability to quickly gen-erate revenue (Baron & Ensley, 2006), are moresalient and quantifiable once the business has ac-

    tually been started. Accordingly, by drawing onprior business experiences and focusing on quanti-fiable metrics that indicate business feasibility, weexpect experienced entrepreneurs to make moreeffective exercise decisions, exercising the optionto commit full time to the business when the optionis in the money and abandoning the option when itis not. Accordingly, we suggest the following:

    Hypothesis 5. Entrepreneurial experiencemoderates the positive relationship between

    staged entry and full-time self-employment survival such that the relationship is stronger  for experienced entrepreneurs.

    METHODS

    Data

    We use data from the National Longitudinal Sur-vey of Youth, 1979 cohort (NLSY79). The NLSY79survey is sponsored and directed by the U.S. Bu-reau of Labor Statistics and conducted by the Cen-ter for Human Resource Research at The Ohio StateUniversity. Interviews are conducted by the Na-tional Opinion Research Center at the University of Chicago. The data has been used by managementscholars to study issues such as self-employment(Schiller & Crewson, 1997), employee turnover

    (Lee, Gerhart, Weller, & Trevor, 2008), and careeroutcomes (Judge & Hurst, 2007, 2008). The NLSY79consists of a nationally representative sample of 12,686 men and women aged between 14 and 22years when first surveyed in 1979. The cohort wasinterviewed annually until 1994, and bienniallythereafter.

    Several features of the NLSY79 make it particu-larly attractive to test our hypotheses. First, it con-tains rich information on individual preferences,attitudes, and socioeconomic status. Second, thedata contain comprehensive employment historiesfor each participant. During each survey, partici-pants are allowed to report up to five jobs. For eachjob, the date (month/day/year) when the job beganas well as the date if/when the job ended is re-corded. Hence, by comparing job start and stopdates, we can determine if any participant held twojobs simultaneously (i.e., if a new job begins beforean existing job ends). This allows us to overcome amajor challenge when studying hybrid entrepre-neurship—the ability to identify true hybrids (Foltaet al., 2010).4 The NLSY79 codes jobs into the fol-

    4

    In many datasets used to study self-employment, laborforce status or income is reported on an annual basis.Therefore, in a given year, if the data indicate that a personwas employed in both paid and self-employment, it is un-clear if the person entered hybrid entrepreneurship or if they transitioned from paid employment to self-employ-ment sequentially. To overcome this issue, Folta et al.(2010) identified individuals as hybrids only if they re-ported the same paid job and same self-employed job fortwo consecutive years. Although conservative, a limitationof this approach is that individuals with short stints inhybrid entrepreneurship are potentially excluded.

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     biases estimates (Cook & Campbell, 1979). Survivalanalysis considers information up to the point of censoring, thereby minimizing such concerns (Al-lison, 1984).

    To test Hypotheses 1 and 2, we used a compet-

    ing-risks framework. In a competing-risks model,individuals are assumed to be at risk to experiencea number of potential events. In the context of thisstudy, participants who hold paid jobs are at risk toenter hybrid entrepreneurship or full-time self-em-ployment. Therefore, we model the amount of timea participant survives at a given paid job prior toentering hybrid entrepreneurship (Path 1 in Figure1) or full-time self-employment (Path 2 in Figure 1).Participants who remained at their paid job at theend of the survey window, exited their paid job totake another paid job, or entered unemployment

    were treated as right censored (Path 3 in Figure 1).Once a participant entered self-employment (orwas censored), he or she was removed from the riskset until they began a new paid job, at which timethey again became at risk to enter self-employment.We estimate separate event-specific survival mod-els (hybrid versus full-time entry), thereby allowingus to test the equality of parameters across modelsvia the test statistic developed by Narendranathanand Stewart (1991).

    To test Hypotheses 3 to 5, we used a single-riskframework to model the amount of time a partici-pant survives in a full-time self-employed job. Forparticipants who transitioned into full-time self-employment from hybrid entrepreneurship (i.e.,staged entry), survival time does not include thetime spent as a hybrid entrepreneur. Moreover,since research has demonstrated that entrepreneurswho hold a secondary paid job are able to persistfor longer periods in self-employment (Gimeno etal., 1997), we treated participants who began a sec-ondary paid job as if they exited full-time self-employment.5 Participants who remained in theirself-employed job at the end of the survey windowwere treated as right censored. Once a participant

    exited their full-time self-employed job, he or shewas removed from the risk set until they began anew full-time self-employed job, at which timethey re-entered the risk set.

    We use Cox semiparametric proportional hazardsmodels to test our hypotheses. Since participantscan experience multiple employment (self-employ-

    ment) spells, we used robust estimators to calculatestandard errors clustered by each participant (Lin &Wei, 1989) and the Efron method in cases of eventties. Cox proportional hazards models produce

     both hazard ratios and regression coefficients. Ex-

    ponentiating the unstandardized regression coeffi-cient (using the formula: 100 * [е 1]) from a Coxmodel eases interpretation by producing thepercent change in risk of experiencing an eventassociated with a one-unit change of the predictorvariable.

    When testing Hypotheses 3 to 5, we addressedthe possibility of selection effects (Shaver, 1998) byestimating a shared frailty model (Gutierrez, 2002),specifying the frailty to be shared among partici-pants who entered full-time self-employment fromhybrid entrepreneurship (i.e., staged entry). The

    shared frailty captures the effects of unobservedcharacteristics common among individuals whotransitioned from hybrid entrepreneurship intofull-time self-employment, which would also influ-ence survival time (Allison, 2009; Song, 2010). Anadvantage of the shared frailty model is that itdoes not rely on the use of instruments (as Heck-man’s (1979) selection correction does), therebyavoiding the problem of identifying instrumentsthat properly satisfy theoretical assumptions (Pu-hani, 2000). The likelihood ratio test from theshared frailty model failed to reach statistical sig-nificance ( p .5), suggesting that unobserved het-erogeneity was not present (Gutierrez, 2002). Ac-cordingly, we report results without the frailty.

    Measures

     Independent variables.   We followed Barsky, Juster, Kimball, and Shapiro (1997) and measuredrisk aversion using an index based on responses tothree hypothetical occupational income gambles(see Appendix). Participants were asked the in-come gamble questions in the 1993, 2002, 2004,and 2006 surveys. We constructed a time-varying

    measure using the responses from each of the foursurveys. Specifically, we used responses from the1993 survey from 1994 to 2002, the 2002 responsesuntil 2004, the 2004 responses until 2006, and the2006 responses until 2008. Results were unchangedwhen we used the 1993 measure as a time-invarianttrait and when we limited our sample to the 2002–2006 surveys where risk aversion is updated

     biennially.For core self-evaluation, we followed Judge and

    Hurst (2007, 2008) and used 12 questions from the

    5 Results were unchanged when the stop date of thefull-time self-employed job was used.

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    NLSY79 to measure CSE. Since the NLSY79does not include a measure of CSE, these questionswere selected because they reflect the 12 items onthe CSE scale developed by Judge et al. (2003). Themeasure demonstrates high construct validity, con-

    tent validity, discriminant validity, and reliability(see Judge & Hurst, 2007, 2008, for extensive scalevalidation procedures). CSE is time invariant.

    We measured staged entry two ways. First, weused a dummy variable to indicate whether a par-ticipant transitioned into full-time self-employ-ment from hybrid entrepreneurship (“1”    transi-tion occurred). We call this measure the   staged entry dummy . Second, for those who entered full-time self-employment from hybrid entrepreneur-ship (i.e., staged entry     “1”), we calculated theamount of time, measured in years, each partici-

    pant spent in hybrid entrepreneurship immediatelyprior to transitioning into full-time self-employ-ment. Participants who transitioned to full-timeself-employment directly from paid work (i.e., di-rect entry) were coded as “0.” We call this measurethe staged entry duration.

    We measured   cognitive ability   with the ArmedForces Qualifications Test (AFQT), which mea-sures quantitative and verbal skills. Prior studieshave demonstrated the AFQT to be a reliable mea-sure (     .9) (Bock & Moore, 1986), correlatinghighly (.95 or higher) with the  g   factor, an alterna-tive measure of cognitive ability (Stauffer, Ree, &Carretta, 1996), and stable over time (Gottfredson,1986). Cognitive ability is time invariant.

    For entrepreneurial experience, we followed re-cent research (e.g., Eesley & Roberts, 2012; Gregoire& Shepherd, 2012; Hmieleski & Baron, 2009; Toft-Kehler et al., 2014) and measured it as the cumu-lative number of businesses started. In addition, wefollowed Folta et al. (2010) and differentiated be-tween full-time self-employment experience andexperience as a hybrid entrepreneur. We call thesevariables no. full SE experience  and  no. hybrid SE experience. Additionally, we used the duration of 

    the participant’s most recent prior entrepreneurialspell: duration full SE experience  and duration hy-brid SE experience.

    Controls.   Guided by existing research, we in-cluded a series of control variables theorized toinfluence entrepreneurial entry and survival. Toaccount for socioeconomic and demographic fac-tors (Kim, Aldrich, & Keister, 2006), we includedcontrols for gender  (male “1,” female “0”); age,measured in years; education, measured as the totalyears of schooling; family net income, measured as

    the logged value of total family income; and region(urban “1,” rural “0”). We also included loggedhourly rate of   pay , logged number of years of   in-dustry experience, and a count of the total  no. of  previous jobs to account for opportunity costs, abil-

    ity, and labor market experience (Shane, 2003).Firm size   was included as the logged number of employees to control for the small firm effect,which may influence entry decisions (Elfenbein etal., 2010), and for the fact that larger ventures mayhave better chances of survival (Geroski et al.,2010).   Industry   and   occupation   differences werecontrolled for with fixed effects based on the U.S.Census Bureau’s three-digit industry codes and theone-digit occupational codes, respectively.   Year fixed effects were included to account for macro-economic conditions.

    RESULTS

    Table 1 shows descriptive statistics and correla-tions for all variables.

    Models 1 to 4 (M1–M4) in Table 2 display theunstandardized regression coefficients from thecompeting-risks Cox proportional hazards model.Models 5 and 6 (M5, M6) display the unstandard-ized regression coefficients from a single-risk Coxmodel (i.e., pooled model) where we treat hybridentry as synonymous with entry into full-time self-employment. Column 7 (M7) shows Wald chi-square tests of coefficient equality (using boot-strapped standard errors) between Models 2 and 4.

    Hypothesis 1 predicts that individuals withhigher risk aversion are more likely to enter hybridentrepreneurship relative to full-time self-employ-ment. Results from Models 2 and 4 support thishypothesis. The coefficient for risk aversion pre-dicting full-time self-employment entry was nega-tive and statistically significant (   .178; p .001). In terms of percentage change, a one-unitincrease in risk aversion is associated with a 16.3%decrease in the hazard of entering full-time self-

    employment. In contrast, the coefficient for riskaversion predicting hybrid entry was not signifi-cant (   .005; n.s.). Column 7 of Table 2 con-firms the statistical difference between coefficients( p    .05), providing further support for Hypothe-sis 1.

    Hypothesis 2 predicts individuals with low CSEare more likely to enter hybrid entrepreneurshiprelative to full-time self-employment. Results fromModels 2 and 4 provide support for this hypothesis.The coefficient for CSE predicting entry into full-

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        T    A    B    L    E    1

        D   e   s   c   r    i   p    t    i   v   e    S    t   a    t    i   s    t    i   c   s   a   n    d    C   o   r   r   e    l   a    t    i   o   n   s

        V   a   r    i   a    b    l   e

        M   e   a   n

         S     D

        1

        2

        3

        4

        5

        6

        7

        8

        9

        1    0

        1    1

        1    2

        1    3

        1    4

        1    5

        1    6

        1    7

        1    8

        1    9

        1    S   u   r   v    i   v   a    l   o    f   w   a   g   e    j   o    b

        (    H   y   p   o    t    h   e   s   e   s    1 ,    2    )    a

        1    8    2 .    7    9    0    1    7    8 .    5    6    0

      —

        2    S   u   r   v    i   v   a    l   o    f    S    E    j   o    b

        (    H   y   p   o    t    h   e   s   e   s    3  –    5    )      b ,    c

        2    7    7 .    8    8    0    2    7    4 .    0    5    0

       n    /   a

      —

        3    R    i   s    k   a   v   e   r   s    i   o   n

        2 .    8    6    0

        1 .    2    4    0

     .    1    0    6

     .    0    5    5

      —

        4    C    S    E      d

        3 .    2    5    0

     .    3    4    0

     .    0    4    2

     .    0    6    9    .    0    0    3

      —

        5    C   o   g   n    i    t    i   v   e   a    b    i    l    i    t   y

     .    4    4    0

     .    2    6    0

     .    0    4    8

     .    0    9    3    .    0    5    2

     .    3    8    9

      —

        6    G   e   n    d   e   r    (   m   a    l   e    

        “    1    ”    )

     .    5    3    0

     .    5    0    0    .    0    0    8

     .    1    6    5

     .    1    0    0

     .    0    5    6

        .    0    7    9

      —

        7    A   g   e

        3    9 .    3    4    0

        4 .    9    8    0

     .    3    5    5

     .    1    3    5

     .    1    0    6

     .    0    6    8

     .    0    9    2

     .    0    3    3

      —

        8    E    d   u   c   a    t    i   o   n

        1    3 .    5    6    0

        2 .    3    1    0

     .    0    4    7    .    0    7    1    .    0    3    9

     .    3    3    9

     .    3    3    9

     .    0    1    0

     .    0    5    4

      —

        9    F    i   r   m   s    i   z   e    (    l   o   g   g   e    d    )

        3 .    9    2    0

        2 .    0    7    0

     .    1    1    3    .    0    5    6

     .    0    4    3

     .    0    4    2

     .    0    5    5

     .    0    1    5

     .    0    7    9

     .    1    3    4

      —

        1    0    P   a   y

        7 .    1    5    0

     .    7    9    0

     .    1    6    3

     .    0    5    7

     .    0    1    0

     .    2    0    5

     .    2    7    5    .    2    0    1

     .    1    8    9

     .    2    6    4

     .    1    4    7

      —

        1    1    N   o .   o    f   p   r    i   o   r    j   o    b   s

        2 .    0    5    0

        1 .    1    4    0    .    3    7    8    .    2    8    4    .    0    6    3    .    0    3    2

        .    0    3    8    .    0    2    7    .    1    4    2    .    0    4    5    .    0    8    1   

     .    1    1    4

      —

        1    2    F   a   m    i    l   y   n   e    t    i   n   c   o   m   e

        (    l   o   g   g   e    d    )

        1 .    9    0    0

        1 .    0    2    5

     .    1    6    7

     .    1    2    2

     .    0    4    2

     .    1    8    8

     .    2    5    6    .    0    3    6

     .    2    4    0

     .    2    7    2

     .    1    1    3

     .    3    4    8    .    1    1    0

      —

        1    3    N   o .   o    f    f   u    l    l    S    E

       e   x   p   e   r    i   e   n   c   e

        1 .    2    9    1

        2 .    5    7    1    .    0    4    5    .    1    7    0

     .    0    1    7

     .    0    0    3

     .    0    2    9

     .    0    1    0

     .    1    6    0

     .    0    8    9

     .    0    0    4

     .    0    1    8

     .    2    2    0 .    0    5    4

      —

        1    4    N   o .   o    f    h   y    b   r    i    d    S    E

       e   x   p   e   r    i   e   n   c   e

     .    2    3    1

        1 .    0    3    1    .    0    2    0    .    0    7    6

     .    0    3    3

     .    0    0    1

     .    0    6    0

     .    0    3    8

     .    0    9    6

     .    0    2    6

     .    1    3    5

     .    0    7    1

     .    1    0    2 .    1    0    2

     .    2    9    3

      —

        1    5    H   y    b   r    i    d    t   r   a   n   s    i    t    i   o   n

        d   u   m   m   y

     .    1    9    9

     .    3    9    9

       n    /   a

     .    0    9    9

     .    0    8    6

     .    0    2    9

     .    0    6    2

     .    0    4    4

     .    1    6    4

     .    0    6    2

     .    2    5    6

     .    0    7    0

     .    1    7    7 .    0    8    8    .    0    8    0 .    0    8    0

      —

        1    6    H   y    b   r    i    d    t   r   a   n   s    i    t    i   o   n

        d   u   r   a    t    i   o   n    (   y   e   a   r    )

        2 .    0    6    2

        5 .    1    8    1

       n    /   a

     .    0    8    5

     .    0    8    0

     .    0    6    2

     .    0    5    3

     .    0    2    6

     .    1    8    1

     .    0    5    1

     .    2    0    7

     .    0    6    4

     .    1    2    3 .    0    7    3    .    0    6    0 .    0    0    8

     .    7    7    9

      —

        1    7    D   u   r   a    t    i   o   n    f   u    l    l    S    E

       e   x   p   e   r    i   e   n   c   e    (   y   e   a   r    )

        1 .    9    5    6

        2 .    3    2    3

       n    /   a

        .    1    1    3

     .    0    1    3

     .    0    4    8

     .    0    7    3

     .    0    9    1

     .    1    1    8

     .    0    3    4    .    0    2    5

     .    0    3    3

     .    1    0    3 .    0    5    6

     .    7    2    3 .    2    9    5    .    0    6    7    .    0    2    3

      —

        1    8    D   u   r   a    t    i   o   n    h   y    b   r    i    d    S    E

       e   x   p   e   r    i   e   n   c   e    (   y   e   a   r    )

        1 .    1    3    1

        1 .    4    7    2

       n    /   a

        .    0    7    2    .    0    0    4    .    0    0    7

     .    0    7    9

     .    0    4    1

     .    1    1    4

     .    0    4    3

     .    1    2    5

     .    0    8    7

     .    1    2    4 .    1    1    2

     .    3    5    2 .    8    0    4

     .    0    6    3

     .    0    0    0 .    3    8    5

      —

        1    9    I   n    d   u   s    t   r   y    t   e   n   u   r   e    (   y   e   a   r    )

        5 .    2    5    9

        1    1 .    4    7    3    .    0    5    2

     .    2    6    3

     .    0    5    3

     .    0    1    7

     .    0    5    5

     .    1    2    3

     .    2    3    1    .    0    2    2    .    0    2    3

     .    0    7    4    .    1    7    2 .    1    1    4

     .    0    3    3 .    0    1    2

     .    0    7    0

     .    0    6    3 .    0    3    4    .    0    1    0  —

        a

         n

        

        3    1 ,    9    1    9 .

          b

         n

        

        2 ,    1    9    8 .

        c

        S    E    

       s   e    l    f  -   e   m   p    l   o   y   m   e   n    t .

          d

        C    S    E    

       c   o   r   e   s   e    l    f  -   e   v   a    l   u   a    t    i   o   n .

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    time self-employment is positive and statisticallysignificant ( .398; p .05). In terms of percent-age change, a one-unit increase in CSE increasesthe hazard of entering full-time self-employment byroughly 32.8%. In contrast, the coefficient for CSEpredicting entry into hybrid entrepreneurship isnegative and statistically significant (   .473; p    .05). Column 7 of Table 2 confirms the differ-

    ence between coefficients ( p .01), providing fur-ther support for Hypothesis 2.

    Next, we compared the competing-risks modelwith a single-risk (i.e., pooled) model in terms of variance explained. To do so, we computed thepseudo-R2 m, a measure of variance explainedused in Cox modeling similar to   R2 in multiplelinear regression (Maddala, 1983). Comparing the

    TABLE 2Results of Competing- and Single-Risk Cox Regression Analysis: Self-Employment Entry

    Variables

    Full-Time SE Entry Hybrid SE Entry Pooled SE EntryaCoefficient

    Comparison b

    M1

    (Baseline)

    M2

    (Main Effect)

    M3

    (Baseline)

    M4

    (Main Effect)

    M5

    (Baseline)

    M6

    (Main Effect)

    M7

    (M2 vs. M4)

    Hypothesized EffectsRisk aversion   .178***   .005   .078   *

    (.050) (.062) (.041)CSE .398*   .473*   .078 **

    (.199) (.233) (.159)Individual ControlsCognitive ability   .000   .142 .489 .609 .256 .274  

    (.284) (.296) (.422) (.426) (.280) (.285)Gender   .064   .093   .230   .215   .144   .158

    (.149) (.150) (.205) (.206) (.136) (.135)Age .011 .007 .034 .042 .023 .024

    (.028) (.028) (.041) (.041) (.027) (.027)Education .141*** .126*** .063 .078 .101** .101**

    (.033) (.033) (.049) (.050) (.031) (.031)Family net income   .032   .011   .051   .028   .042   .019

    (.049) (.049) (.063) (.062) (.043) (.044)Employment ControlsFirm size   .088*   .086*   .026   .026   .052 .053

    (.035) (.034) (.037) (.037) (.027) (.027)Pay   .107   .107 .041 .055   .015   .009

    (.076) (.076) (.077) (.076) (.056) (.056)No. of previous jobs .524*** .519*** .636*** .637*** .586*** .583*** *

    (.042) (.041) (.046) (.042) (.036) (.036)Industry tenure   .035   .038 .014 .018   .013   .013  

    (.023) (.023) (.024) (.025) (.023) (.023)No. of full SE

    experience.120   .100 .232** .271** .185** .183**  

    (.072) (.072) (.075) (.075) (.057) (.057)No. of hybrid SE

    experience.026   .015   .020   .021   .021   .018

    (.049) (.049) (.061) (.062) (.046) (.046)Model FitPseudo-R2

    m  .128 .132 .126 .127 .105 .106 Equality of all

    parameters

    c

    ***BIC 7155.41 7719.572 9623.884 9634.812 16751.020 16764.034Pseudo log likelihood   3396.213   3211.601   4137.830   4132.923 7540.648   7536.784Model ( 2) 3497.269 1810.321 1480.724 1454.056 1833.835 1936.741Wald test ( 2)    2 (2) 7.151*    2 (2) 53.872***    2 (2) 4.170

    Note:  n    31,191. All models include 3-digit industry, 1-digit occupation, region, and year fixed effects. CSE     core self-evaluation.SE self-employment. Robust standard errors clustered by participant in parenthesis.

    a Single-risk model where hybrid entry is treated as synonymous with full-time self-employment entry (“pooled”). b Wald tests for coefficient equality. Because, in competing risks models, it is possible that two censoring situations may not be

    independent, we compute the standard errors using the bootstrapping method (Preacher & Hayes, 2008), a simulation approach (re-sampling 200 times from the original data).

    c  2 (13). Test statistic from Narendranathan and Stewart (1991).Two-tailed tests for significance for all effects.  p .10.* p .05.

    ** p .01.*** p .001.

    948 AugustAcademy of Management Journal 

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    pseudo-R2 m from the competing-risks model withthe pseudo-R2 m from the single-risk model showsthat the competing-risks model explains almosttwo and a half the variance (i.e., .259/.106) as thepooled model, providing additional support that

    the determinants of hybrid entrepreneurship andfull-time self-employment entry are distinct.

    Tables 3a and 3b display the unstandardized re-gression coefficients from single-risk Cox modelsestimating full-time self-employment survival. Hy-pothesis 3 predicts individuals who enter full-timeself-employment in a staged entry process via hy-

     brid entrepreneurship will survive longer than in-dividuals who enter full-time self-employment di-rectly from paid employment. Results fromModel 2 (Table 3a) and Model 2 (Table 3b) providesupport for this hypothesis. The coefficient for

    staged entry dummy in Model 2 (M2) in Table 3a isnegative and statistically significant (   .405; p .001), implying that the hazard of exit is 33.3%lower for individuals who enter full-time self-em-ployment in a staged process relative to those whoenter directly from paid work. Likewise, the coef-ficient for staged entry duration in Model 2 (M2) inTable 3b is negative and statistically significant(   .025;   p     .001), meaning that a one-unitchange in staged entry duration is associated with a2.5% reduction in the hazard of exit.

    Hypothesis 4 predicts that the positive effect of staged entry on full-time self-employment survivalis stronger for individuals with high cognitive abil-ity. Model 7 (M7) in Table 3a shows that the inter-action between staged entry dummy and cognitiveability is not statistically significant ( .153; n.s.).In Model 7 (M7) of Table 3b, the interaction be-tween staged entry duration and cognitive ability ispositive and statistically significant ( .053; p .01), which is the opposite of Hypothesis 4. Asdemonstrated by a comparison of the slopes inFigure 2, the decrease in hazard of exit (i.e., sur-vival benefit) associated with longer stays in hybridentrepreneurship is stronger for individuals with

    low cognitive ability. Thus, we do not find supportfor Hypothesis 4.

    Hypothesis 5 predicts that the positive effect of staged entry on full-time self-employment survivalis stronger for individuals with entrepreneurial ex-perience. Models 3 to 6 (M3–M6) in Table 3a pro-vide the coefficients for the interactions betweenour measures of entrepreneurial experience andstaged entry dummy. Models 3 to 6 (M3–M6) inTable 3b display the coefficients for the interac-tions between entrepreneurial experience and

    staged entry duration. All interactions are negative,and, in the majority of models, reach statisticalsignificance. Thus, as demonstrated by the slopesin Figure 3, the decrease in hazard of exit (i.e.,survival benefit) associated with staged entry is

    stronger for experienced entrepreneurs. Thus, over-all, we find support for Hypothesis 5.

    Robustness Checks and Supplementary Analysis

    We conducted several robustness checks. To be-gin, we took steps to determine if our results arerobust when using measures of entrepreneurshipother than self-employment (Carter, 2011). Thus,we re-tested our hypotheses using two narrowermeasures of entrepreneurship.

    First, we focused our analysis on participants

    who started a business and reported having em-ployees (i.e., multi-person firms). By doing so, wetreated entrepreneurship as the creation of organi-zations, classically defined as the “coordinated ac-tivities of two or more people” (Barnard, 1938: 73).Specifically, we treated participants as entrepre-neurs only if they reported being self-employed intheir own business and a firm size greater than two.To test Hypotheses 1 and 2, we treated participantswho entered self-employment but reported a firmsize less than two as right censored. Since the sam-ple used to test Hypotheses 3 to 5 is comprised of participants already in full-time self-employment,individuals who reported being full-time self-em-ployed but did not report their self-employed firmsize to be greater than two were excluded fromanalysis.

    Second, we categorized participants as entrepre-neurs only if they reported being self-employedand that their business was incorporated. Incorpo-rating a business results in a distinct legal entityseparate from the founder, requires the founder topay various legal fees, comply with governmentmandates, and often signifies entry into the formaleconomy (Kim & Li, 2014). Consequently, focusing

    on incorporated business is similar to other com-mon measures of entrepreneurship, such as identi-fying new firms through the Dun & Bradstreet(D&B) database (e.g., Batjargal, Hitt, Tsui, Arregle,Webb, & Miller, 2013; Hmieleski & Baron, 2009),which rely on signals that the business intends toengage in commercial activity. For Hypotheses 1and 2, participants who entered unincorporatedself-employment were treated as right censored. Totest Hypotheses 3 to 5, participants with unincor-porated businesses were excluded from analysis.

    2014 949Raffiee and Feng 

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        T    A    B    L    E    3   a

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     .    0    6    8    *    *    *

        .    0    6    5    *    *    *

        .    0    6    7    *    *    *

        .    0    6    7    *    *    *

        .    0    6    6    *

        *    *

        .    0    6    8    *    *    *

        ( .    0    1    5    )

        ( .    0    1    6    )

        ( .    0    1    6    )

        ( .    0    1    6    )

        ( .    0    1    6    )

        ( .    0    1    6    )

        ( .    0    1    6    )

        M   o    d   e    l    F    i    t

        P   s   e   u    d   o  -    R

          2   m

     .    0    3    4

     .    0    3    6

     .    0    3    8

     .    0    3    7

     .    0    3    8

     .    0    3    6

     .    0    3    6

        B    I    C

        3    0    2    6    3 .    1    2    2

        3    0    2    1    6 .    6    7    0

        3    0    1    6    6 .    0    8    4

        3    0    1    9    4 .    4    7    3

        3    0    1    6    4 .    7    2    1

        3    0    2    1    4 .    3    8    9

        3    0    2    3    1 .    7    3    6

        P   s   e   u    d   o    l   o   g    l    i    k   e    l    i    h   o   o    d

           1    4    2    2    3 .    5    1    5

           1    4    1    9    6 .