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Entrepreneurial Success As Determined By An Evaluation Of Premarket Entry Risks


Doctoral Dissertation

Doctoral Dissertation

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  • 1. ENTREPRENEURIAL SUCCESS AS DETERMINED BY AN EVALUATION OF PREMARKET ENTRY RISKS by J. Phillip Harris A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Business Administration UNIVERSITY OF PHOENIX April 2011
  • 3. ENTREPRENEURIAL SUCCESS AS DETERMINED BY AN EVALUATION OF PREMARKET ENTRY RISKS by J. Phillip Harris April 2011 Approved: William Stokes, D.B.A., Mentor Donald Bronsard, Ph.D., Committee Member Timothy Clifton, Ph.D., Committee MemberAccepted and Signed: William Stokes, DateAccepted and Signed: Donald Bronsard DateAccepted and Signed: Timothy Clifton Date __________________Jeremy Moreland, Ph.D. DateDean, School of Advanced StudiesUniversity of Phoenix
  • 4. ABSTRACTThe purpose of this quantitative study sought to use discriminant analysis to learn ifawareness of antecedent risks can improve success rates of entrepreneurs by earlydevelopment of risk management strategies. The basis for this idea comes from the beliefthat public firms that go through underwriting have an improved chance of success.Because underwriting forces those companies to plan for early stage risk, public firmshave a better chance to succeed. Discriminant analysis separates successful fromunsuccessful firms by using ratio analysis. The firms in the study’s sample showed wheneach firm started to plan certain types of risks as noted in Securities and ExchangeCommission (SEC) Form S-1. The study’s results revealed surprising information. Thebiggest surprise came from companies’ resistance to take part in the study because ofsensitivity about disclosing information about risks. Entrepreneurial firms do considerplanning for risk important, but plan for risk as needed when necessary. Other issues takeon greater importance such as the window for exploiting new opportunities. The resultsbenefit prospective entrepreneurs by offering some general guidelines for dealing withspecific types of early stage risks. Little evidence exists that underwriting improved thesuccess rates of the firms subjected to the process. This study revealed the surprisingimplication that firms that go public are not necessarily any better-off than firms that stayprivate. Holding off going public may contribute to creativity and growth conditions.Entrepreneurs may find these results important in planning for financing anddevelopment of their companies. Further study about these conditions may help confirmthe results. Another study may also develop more specific guidelines for dealing withearly stage risks.
  • 5. v DEDICATION I would like to dedicate this work to my wife, Rebecca Hendrickson, and familyto express my sincere appreciation for allowing me to take part in completing thisresearch. I could not have carried out fulfilling this journey without them. I am gratefulfor this opportunity and for the support I received in the process. I also want to thank myLabrador retrievers, Nike and Abby, who walked me through the process.
  • 6. vi ACKNOWLEDGMENTS I want to express my gratitude to my mentor, Dr. William Stokes, for guiding methrough the research process. I found Dr. Stokes always available when I neededguidance. I want also to express my gratitude to the other members of my committee. Iwant thank Dr. Donald Bronsard for his encouragement and guidance. I want to thank Dr.Timothy Clifton for his support and advice. I could not have succeeded this projectwithout both my committee members. I also want to thank Dr. Michael Fellner at SouthDakota State University, who provided valuable guidance and advice with my surveyresults and statistical analysis. I am grateful to all these people for their help.
  • 7. vii TABLE OF CONTENTSLIST OF TABLES .................................................................................................... xiLIST OF FIGURES ................................................................................................. xiiCHAPTER 1: INTRODUCTION .............................................................................. 1Background of the Problem ....................................................................................... 1Statement of the Problem ........................................................................................... 5Purpose of the Study .................................................................................................. 6Significance of the Problem ....................................................................................... 8 Significance of the Study .................................................................................... 8 Significance of the Study to Leadership ............................................................. 8Nature of the Study .................................................................................................... 9 Overview of the Research Method ..................................................................... 9 Overview of the Design Appropriateness ........................................................... 9Research Questions .................................................................................................. 10Theoretical Framework ............................................................................................ 12 Broad Theoretical Area..................................................................................... 12 Theoretical Gap Filled by the Study ................................................................. 13Definition of Terms.................................................................................................. 14 Entrepreneurial Terminology............................................................................ 14 Risk Terminology ............................................................................................. 15Assumptions............................................................................................................. 15Scope, Limitations, and Delimitations ..................................................................... 16Plan of Study ............................................................................................................ 17
  • 8. viii Chapter 2, Literature Review ............................................................................ 17 Chapter 3, Research Methodology ................................................................... 21 Presentation and Analysis of Generated Data .................................................. 22Summary .................................................................................................................. 23CHAPTER 2: REVIEW OF THE LITERATURE .................................................. 25Title Searches, Articles, Research Documents, and Journals .................................. 25Literature Review..................................................................................................... 26 Historic Overview ............................................................................................. 26 Review of Current Results ................................................................................ 36 Defining and Extracting Risk from Uncertainty ............................................... 42 Dependent Variable: Determinants of Success................................................. 49 Independent Risk Variables: Determined from Form S-1 Filings .................... 51 Entrepreneurial Entry and Success in Green Energy Industry ......................... 52Conclusions .............................................................................................................. 57Summary .................................................................................................................. 58CHAPTER 3: METHOD ......................................................................................... 59Research Method and Design Appropriateness ....................................................... 60Research Questions and Hypotheses ....................................................................... 67Population, Sampling, and Data Collection Procedures .......................................... 68 Population ......................................................................................................... 68 Sampling Frame ................................................................................................ 68Validity and Reliability ............................................................................................ 71 Internal Validity ................................................................................................ 71
  • 9. ix External Validity............................................................................................... 73 Reliability ......................................................................................................... 74Data Analysis ........................................................................................................... 75Summary .................................................................................................................. 78CHAPTER 4: COLLECTION AND ANALYSIS OF DATA ................................ 79Pilot Study................................................................................................................ 80Limitations ............................................................................................................... 81Factor Analysis ........................................................................................................ 83Discriminant Analysis .............................................................................................. 86Kruskal Wallis H Test .............................................................................................. 91Summary of Results of Hypotheses Testing and Results ........................................ 91 Research Question and Hypotheses Tests ........................................................ 91 Limitations ........................................................................................................ 93Summary .................................................................................................................. 93CHAPTER 5: SUMMARY AND CONCLUSIONS ............................................... 95Overview of the Results ........................................................................................... 95 Pilot Study ........................................................................................................ 95 Limitations ........................................................................................................ 96 Factor Analysis ................................................................................................. 97 Discriminant Analysis ...................................................................................... 98 Kruskal-Wallis H Test ...................................................................................... 99 Hypothesis Testing and Results ........................................................................ 99Implications of the Results..................................................................................... 103
  • 10. xRecommendations for Future Study ...................................................................... 111Summary ................................................................................................................ 112REFERENCES ...................................................................................................... 114APPENDIX A: SURVEY INSTRUMENT ........................................................... 139APPENDIX B: INFORMED CONSENT FORM ................................................. 141APPENDIX C: SURVEY INSTRUMENT USED ................................................ 142APPENDIX D: TABLES ....................................................................................... 149
  • 11. xi LIST OF TABLESTable 1 Structure Matrix…………………………………………………………….…88Table 2 Standardized Canonical Discriminant Function Coefficients…………….……..88Table 3 Tests of Equality of Group Means…………………………………………………...89Table 4 Classification Results………………………………………………………….………90Table D1 Calculation of Ratios……………………………………………………….149Table D2 Risk Factors and Hypotheses Tests Using Z Test…………………………..150Table D3 Eigenvalues………………………………………………………………....151Table D4 Correlation Matrix………………………………………………………….152Table D5 Altman z-scores……………………………………………………………..153Table D6 Group Descriptive Statistics………………………………………….……..154Table D7 Kruskal-Wallis H Test………………………………………………….…...155Table D8 Hypothesis Testing………………………………………………………….156Table D9 Risk Priorities Based on Mean Rank……………………….………………157
  • 12. xii LIST OF FIGURESFigure 1. Scree Plot of Eigenvalues……………………………………………………………85Figure 2. Scatterplot Covariance Matrices for Each Group…………………………….87
  • 13. 1 CHAPTER 1: INTRODUCTION Entrepreneurial success rates falter because entrepreneurs overlook risks before marketentry (Proimos & Murray, 2006). Entrepreneurs might improve the chance of success byidentifying antecedent risks and devising strategies to mitigate such risks. Addressing theessential causes of risk at an early stage improves a firm’s wherewithal to gain the financingneeded to continue. By balancing both the opportunities and the risks, the entrepreneur can directattention to the most fitting procedures critical to launching a new venture. In this research study,the goal sought to examine the risks evaluated in underwriting by firms preparing to “go public”and make a comparison with the premarket entry risks faced by entrepreneurial firms. The resultsof this examination helps entrepreneurial firms develop risk management plans before enteringthe market. Background of the ProblemSocial Concern Classical characterizations of entrepreneurial business owners include responsibility foraccretion of capital, innovation, and a close alliance of a business owner’s skills with the firm’swork. Although entrepreneurs encompass only seven to eight percent of the population in theUnited States (U.S.), they account for roughly 30% of the top decile of wealth. Such individualsintroduce new products, contribute skills and ideas, and develop new business strategies throughrisk-taking. Entrepreneurs pioneer innovation through business knowledge and directly managethe firms created. Because entrepreneurs usually invest in a firm from personal wealth, thefounders take a more active role in management (De Nardi, Doctor, & Krane, 2007). With the fiscal benefits of entrepreneurship in focus, the Global EntrepreneurshipMonitor for North America reported net business creation provides an excellent measure of
  • 14. 2entrepreneurism for firms with fewer than 10 employees (Bosma, Acs, Autio, Coduras, & Levie,2008). For firms in the United States during 2002-2003, Nevada topped the list of statesproducing the highest rate of net business creation with 5.21%, followed by Florida with 4.67%,and Utah with 4.46%. Of total businesses, small businesses with 10 or fewer employees rankedhighest in Montana with 79.2%, followed by Quebec with 78.9%, and Newfoundland with78.6% for the years 2003-2004. The list showed the next highest ranking U.S. states as Wyomingwith 78.4% and Florida with 77.6% (Godin, Clemens, & Veldhuis, 2008). In venture capitalinvested for each person for 2005, Massachusetts ranked highest with $379.39 followed byCalifornia with $295.50, Colorado with $134.99, Washington with $123.14, and Utah with$102.06. Despite the economic boost entrepreneurism provides, Sternberg and Wennekers (2005)showed that entrepreneurism varies among countries in different stages of development.Entrepreneurism unleashes a positive effect on the growth of developed countries, whereaspoorer countries benefit less from entrepreneurial pursuits because mostly nascent entrepreneursare present. In a more developed country, other entrepreneurs innovating new and existingproducts are also part of the mix. Well-developed countries should promote business start-upsbecause they stimulate fiscal growth (Sternberg & Wennekers, 2005). Wong, Ho, and Autio(2005) noted that in particular, high-growth businesses and opportunity entrepreneurshippromote monetary growth. Gelderen, Thurik, and Bosma (2006) recognized that promotion ofentrepreneurial development contributes to innovation, economic growth, job creation, andcompetition.
  • 15. 3Theoretical Interest Although entrepreneurism promotes fiscal benefits, a disparity exists betweenentrepreneurs and the venture capitalists that serve to fund them. Proimos and Murray (2006)argued the disparity occurs because venture capitalists have a different idea of when a ventureproves “investor ready” (p. 23). Venture capitalists evaluate the management team, the market,and technology to assess investor readiness. Venture capitalists rely on “intuition” in financingventures early in development, creating frustration for the entrepreneur. In assessing investorreadiness, venture capitalists have less tolerance for risk-taking than do entrepreneurs. Risk andreturn play an integral role in the venture capitalists’ evaluations. Entrepreneurs can growdisillusioned by this practice (Proimos & Murray, 2006). Similar to venture capitalists, angel investors also provide risk capital to entrepreneurs,but spoon-feed it in small amounts as a project progresses. Agency theory reflects diverginginterests between the investor and the investee. Angel investors manage such risk by adjustingexpected rates of return to compensate for added risks, by setting milestones to providecontinuing funding during the project. Angel investors specify contractual rights and duties, andwatch progress while working with investees on new projects (Kelly & Hay, 2003). Because of the divergence in seeing risk between entrepreneurs and the investors servingto fund new projects, entrepreneurs experience difficulty accurately assessing the risk and returnof new ventures. By viewing entrepreneurial ventures through a different lens, both investors andinvestees can garner new insight in evaluating the likelihood of survival, assessing riskmanagement, and in forecasting realistic projections of expected returns. Through makingentrepreneurs aware of risk at an earlier stage, individuals can develop risk managementstrategies to achieve more success in gaining financing and benefiting the United States
  • 16. 4economy. Stifling the innovation provided by entrepreneurism only serves to hold back fiscalprogress. With these divergent views in mind, America continues to serve as one of the mostvibrant economies for entrepreneurs ("Seed capitalism," 2008). Easterly (2001) inferred thatthose countries that have a larger middle class find such a group serves as the backbone of theeconomy. Economies with a larger middle class grow more rapidly than economies without alarger middle class, provided the constituent population is not too ethnically diverse. Max Weber(2001) remarked that entrepreneurs rise from the middle class because of a tolerance for delayedrewards. Entrepreneurs provide employment and growth in productivity for the entire society(Banerjee & Duflo, 2008). With the outcome of entrepreneurism contributing to the financialadvancement of the United States, the goal of this study is to examine how addressing risk beforeentering the market leads to improved entrepreneurial success. Although entrepreneurs contribute heavily to well-developed economies, Parhankangasand Hellstrom (2007) viewed several approaches entrepreneurs use to deal with risk in theliterature. Parhankangas and Hellstrom noted plans for managing such risk associated withoriginal entry to the market remains a mystery. Proimos and Murray (2006) found that a disparityexists between entrepreneurs and those who serve to fund them because of a different view ofwhen a venture proves “investor ready.” Diverse views may account for entrepreneursunintentionally ignoring risk because overconfidence exceeds the distaste for risk (Busenitz,1999; Gelderen, Thurik, & Bosma, 2006; Wu & Knott, 2006). Unlike those companies seekingpublic financing, many entrepreneurs lack professional managers to plan for risk and deal withmisgivings. Resultantly, many entrepreneurs address risks only after exposure to them.
  • 17. 5 Because of this inattentiveness to premarket entry risk, the entrepreneur faces high failurerates (Singh, Corner, & Pavlovich, 2007). Further, entrepreneurs can grow disenchanted by anysuggestion that risk remains unnoticed and insist new ventures are not risky (Proimos & Murray,2006). Coping with such blind risk creates a major challenge (Busenitz, 1999). Besides,Busenitz’s observation suggests that by making entrepreneurs aware of risk, an opportunityexists to engage in risk management to improve the likelihood of success. Statement of the Problem Although risk-taking is a prime characteristic of entrepreneurs, such firms fail more oftenthan those that “go public” because public firms are aware of the risks and prepare to deal withrisks earlier. By “going public,” a firm complies with underwriting procedure improving thelikelihood of success because it may cause a firm to identify and address early stage risks(Corwin & Schultz, 2005; Hebb & MacKinnon, 2004). The problem is that entrepreneurs fail toidentify and plan for risk before entering the market (Gelderen, et al., 2006; Parhankangas &Hellstrom, 2007). Despite the benefits offered by providing employment and invigoratingmonetary growth, high failure rates hamper entrepreneurs because of the lack of attention toearly stage risks. Ill-prepared entrepreneurs fail to achieve satisfactory levels of financingbecause of the inability to deal effectively with investors. The goal in this quantitative study sought to compare risks identified throughunderwriting of public firms with the awareness and risk management practices of more nascententrepreneurs. The objective of this comparison is to discover if unrecognized risks inhibitentrepreneurial success rates. The study draws on a sample of alternative energy firms filingForm S-1 with the Securities and Exchange Commission (SEC). The plan of this study is to usethis sample to decide if an association exists between risks identified by underwriting practices
  • 18. 6with the success of more nascent firms. Similarly, in the conduct of the study the objective is todevelop a survey to give to a sample of nascent alternative energy firms taken from the UnitedStates Department of Energy website ("U. S. Department of Energy," 2008). Purpose of the Study The purpose of this quantitative study sought to use discriminant analysis to learn ifawareness of antecedent risks can improve success rates of entrepreneurs by early developmentof risk management strategies. Classification of risks ranging from antecedent to the time offunding influences the success or failure of entrepreneurs because the earlier the firm starts riskmanagement, the greater the chance of success. The population sought to include nascententrepreneurs in the alternative energy industry from a list on the Department of Energy website("U. S. Department of Energy," 2008). Companies with headquarters in the United States asidentified on the website provide the sample for a survey to find how the identified risksinfluence self-reported success rates. To identify antecedent risks, the research included an examination of a sample of filingsof Form S-1 from the Securities and Exchange Commission website for 2009. The sample soughtto include alternative energy firms applying to “go public.” For example, some of the risksidentified are as follows: 1. The dependency on few suppliers of critical services or products may present a problem. 2. Environmental risks and rules may have an unfavorable effect on business. 3. Strong competition from competitors may create difficulty gaining enough of a share of the market. 4. Local, legal, and political risk may hinder the firm’s ability to market products.
  • 19. 7 5. Limited financing may hamper the firm’s ability to preserve the expense to uphold regulatory needs. 6. The power may not exist for the company to achieve market acceptance for products. 7. Difficulty attracting key management and board members may hinder the ability to carry out business plans and manage growth. 8. Technological changes could make products and services obsolete. 9. Safety and product liability could result in unforeseen damages. 10. The company may find gaining necessary licenses for products difficult.Gilmore, Carson, and O’Donnell (2004) found that major determinants of risk arose from cashflow, company size, entry into new markets, and entrusting staff. Each of the risks can fall intoone of these categories. With an idea of the risk involved, this study sought to conduct a survey by querying asample of alternative energy firms to decide if any firms took steps to manage risks before start-up or within the first year. Alternative energy firms are those companies dealing inunconventional energy sources not attributed to fossil fuels. The study incorporated a factoranalysis to decide which identified risks bear the greatest influence on success rates. Creswell(2005) asserted that a quantitative method presents an opportunity for descriptive research andanalysis. A quantitative study using multiple discriminant analysis provided a proper researchmethod to perform the stated objective. This method is proper because discriminate analysisstudies simplify describing early stage risk and aid in deciding the influence of risks onentrepreneurial success rates.
  • 20. 8 Significance of the ProblemSignificance of the Study Because entrepreneurs neglect risk mitigation in the early stages of firm development,high failure rates hinder overconfident entrepreneurs (Wu & Knott, 2006). Opportunisticentrepreneurs miss a chance to mitigate risks before entering the market. Proimos and Murray(2006) asserted that early mitigation of risk prepares entrepreneurs for discovering newopportunities for financing by making them “investor ready.” Taking risk readiness into consideration, investors are more likely to invest in a firm thathas identified potential risks and has developed plans to address them. Identifying potential risksand developing plans for risk management helps the investor build confidence in the talents ofthe entrepreneur. Conversely, potential investors view entrepreneurs who have neglected riskplanning as too risky and may select other investment alternatives.Significance of the Study to Leadership Leaders take the lead in developing a vision by learning to transform a mission throughnew business enterprises laden with risk (Becherer, Mendhall, & Eickhoff, 2008; Kotter, 1996).Leaders surface among individuals with a high tolerance for the risk-taking (Becherer, et al.,2008; Kets de Vries, 1997). Schumpeter (1951b) credited early stage risks to “a phenomenon thatcomes under the wider aspect of leadership” (p. 259). People without a high tolerance for riskrarely rise to a leadership position. To develop a reasonable open-mindedness about risk, the nascent entrepreneur must havemany leadership qualities. The qualities include vision, creativity, achievement, tenacity, self-confidence, assertiveness, risk taking, and an inclination for power and control (Becherer, et al.,2008). Thus the objective of the study is to prepare the nascent entrepreneur for leadership
  • 21. 9challenges. Without such qualities, a new entrepreneur has a difficult time taking the venturefrom birth to an enduring existence. Nature of the StudyOverview of the Research Method Apart from the leadership significance of examining premarket risks, a suitable method isimportant to detect the relationships among the independent and dependent variables. Neuman(2003) asserted that “correlation” research often relies on surveys as a rigorous test for cause andeffect and providing alternative explanations. Using surveys involves six distinct steps. The firststep involves designing an instrument to address research questions and theories and the mediumused to give the survey. Methods can include personal interviews, direct mail, telephoneinterviews, e-mail invitations, or web-based surveys. The next step involves deciding how torecord and test the results. Next, the research protocol entails extracting a sample from asampling frame of the entire target population. Once sample selection is complete, the next step entails finding respondents, conductinginterviews, and recording data. After entering the data into computer software such as SPSS, thedata is ready for statistical analysis. Finally, the cleaning procedure allows a discussion of themethods and results of the statistical analysis. In essence, a quantitative analysis gives aresearcher the opportunity to test a theory by using statistical inference (Neuman, 2003).Overview of the Design Appropriateness In this quantitative analysis, the testing procedure affords a method to assess if a strongassociation exists between identified risks and the success or failure rates. The 10 risksindentified earlier came from SEC Form S-1. The SEC uses this form for firms to discloseimportant information about their intent to “go public.” In designing the study, these risks
  • 22. 10appeared most often with comments expressing a concern. To perform an assessment, the plan ofthe study sought to examine success and failure rates of nascent entrepreneurial ventures withinthe alternative energy industry. Further, a Pearson correlation coefficient statistical analysishelped to uncover the relationships of each independent variable to the dependents variable andto each of the other independent variables (Neuman, 2003) As an alternative to qualitative analysis that explores a broad theoretical problem areaand converges on a central phenomenon, quantitative analysis provides a deeper analysis byfocusing on more specific relationships among variables (Creswell, 2005). Because the literaturealready identified broad theoretical research, the purpose of this research sought to achieve amore specific focus about the influence of risk on improving entrepreneurial success. Theobjective of the study is to contribute to existing research by extending the literature on risk tofocus on ways in which early stage risks affects the success of entrepreneurs. Discriminantanalysis offered a research method useful in separating entrepreneurs into successful andunsuccessful groups through analysis of the variables (StatSoft, 2007b). Research Questions Although entrepreneurs provide many positive benefits to the economic environment,overconfidence and undisciplined preparation are an enigma to their success. Larger firms havethe opportunity to identify and mitigate risk before entering the market because of theunderwriting process. For example, larger firms that decide to go public and identify premarketentry risks through underwriting procedures develop plans for risk management, and improve thefirm’s chances of long-term success (Corwin & Schultz, 2005; Hebb & MacKinnon, 2004). In aquantitative study, the objective is to address the obvious disparity by looking at the relationship
  • 23. 11of risk to the success and failure of divergent firms in the United States’ alternative energyindustry. The disparity between success and failure rates for such groups leads to the followingquestion:Q. How does the timing of gaining awareness of risk affect entrepreneurial success rates in thealternative energy industry? Hypotheses Such questions imply a cause and effect association exists between the timing of riskawareness and risk management with entrepreneurial success rates. The research questionssuggest the following theories are possible (Creswell, 2005):Set One: DirectionalHo1. No difference exists between entrepreneurs gaining an awareness of risks before and afterentry to the market resulting in a significant improvement in their success rates within the UnitedStates’ alternative energy industry.Ha1. A difference exists between entrepreneurs gaining an awareness of risks before marketentry and after entry to the market resulting in a significant improvement in their success rateswithin the United States’ alternative energy industry.Set Two: NondirectionalHo2. No difference exists between entrepreneurs gaining an awareness of risks before and afterentry to the market resulting in a significant improvement in their success rates within the UnitedStates’ alternative energy industry.
  • 24. 12Ha2. A difference exists between entrepreneurs gaining an awareness of risks before and afterentry to the market resulting in a significant improvement in their success rates within the UnitedStates’ alternative energy industry. Theoretical FrameworkBroad Theoretical Area Adam Smith distinguished the capitalist from the entrepreneur by noting the sole role ofthe capitalist is to provide capital and bear the risk of loss (Schumpeter, 1951). By contrast, anentrepreneur does not always supply capital or bear the risk of loss. Although often suchconditions do exist for the entrepreneur, the true defining characteristic of an entrepreneur stemsfrom uncertain conditions. Montanye (2006) defined entrepreneurs as talented individualsconfronted with doubt and scarcity with a goal to capture monetary returns beyond thoseprovided by perfect competition. Through such efforts entrepreneurs are able achieve a superiorlifestyle (Montanye, 2006). Although Schumpeter (1951) singled out uncertain conditions as a defining characteristicof entrepreneurs, others credit entrepreneurs for risk management responsibilities. Bernstein(1996) described how the French mathematician, Jules Henri Poincare, explained risk by causeand effect as a way to protect against sizable losses. Poincare argued a firm can allay riskthrough insurance to cover significant losses, but must pay a small loss in the form of a premiumto do so. A firm should take measures to reduce the doubt involved by addressing the source ofthe risk. Such actions decrease the small loss incurred in the form of insurance premiums tolessen the payment for a potential large loss (Bernstein, 1996; Knight, 1921). Risk-aligningbehavior works to lower risk exposure and moderate the cost of a disastrous loss.
  • 25. 13 Beyond protecting against a disastrous loss by addressing the source of risk and movingmore from the uncertain to the certain, identifying risks should also improve the chance ofsuccess. Knight suggested one should distinguish risk from the uncertain conditions because anentrepreneur can appease risk through insurance, hedging, and diversification. Conversely,uncertain conditions stem from ignorance or acting on opinion rather than knowledge (Knight,1921). Max Weber described the motivation inspiring the capitalist as the pursuit of profitthrough rational restraint and supported such an attitude over the pursuit of profits for greed(Mises, 1944; Weber, 2001). Compatible with the need to balance risk management with optimism, entrepreneuriallifestyles benefit the economy by fostering innovation and creativity, providing growth inproductivity, and employment for the entire society (Banerjee & Duflo, 2008). Sternberg andWennekers (2005) agreed that promotion of business start-ups stimulates fiscal growth. Byaligning entrepreneurial optimism with suitable risk management improves success ratescontributing to improved monetary conditions for society.Theoretical Gap Filled by the Study Because risk-taking and opportunism characterizes the entrepreneur, improving thechances of success by early risk management initiatives benefits society. The objective is toidentify early stage risks to relieve potential losses and improve entrepreneurs’ abilities to seesuch risks. Geldren et al. (2006) noted only limited literature exists about risk management plansfor people with ambitions to launch new business ventures, and the literature would benefit frommore research. Parahankangas and Hellstrom (2007) noted, “interrelations between theantecedents of risk taking, investment decisions and risk reduction strategies still remain alargely unexplored territory” (p. 184). Ottesen and Gronhaug (2006) asserted that exploiting
  • 26. 14opportunities with an uncertain future remains a difficult task, but surprisingly little literatureexists on why some firms succeed in the search to exploit opportunities, while the majority fail.The insights gained by exploring the problem can lead to improved success rates. In response to the gap in the literature, the goal of the study sought to address antecedentrisk. Addressing early stage risks depends on ways to improve entrepreneurial success rates byidentifying risks at an earlier stage and starting risk management sooner. An inference exists inthe study that entrepreneurs who balance an opportunistic vision with attendant early stage risksstand a better chance of surviving. Displaying this ability allows entrepreneurs to earn enoughfinancing to propel new ventures through start-up. Such research only addresses a small part ofthe total population of entrepreneurs as the study limits the results to alternative energycompanies. Companies in other industries may find the risks in such industries are different fromthe alternative energy industry. The results in this study only address a small part of newventures by the entire population of entrepreneurs. This research may justify further expansion togain insight into other parts of the population. Definition of Terms Certain terms are particular to the study of entrepreneurs and risk management. Suchterms warrant further definition. Other terms vary in meaning, depending on the author. For thesake of clarity, this section defines terms for use here. To define such terms helps impel clarityand consistency.Entrepreneurial Terminology Bootstrapping. The term refers to an effort to conserve cash when a firm cannot raisecapital through conventional sources such as issuing stock or bonds. Entrepreneurs use
  • 27. 15bootstrapping by bartering and sharing supplies to aid survival when conventional financing isunavailable (Ebben, 2009; Ekanem, 2007; Winborg & Landström, 2001). Nascent. Nascent is a term often found in the literature used to mark the emergence orbirth of an organization.(Diochon, Menzies, & Gasse, 2007; Gelderen, et al., 2006) Nascentrefers to emergent organizations in an embryonic stage of development. Entrepreneurs launchembryonic organizations and lead new firms during the beginning stage.Risk Terminology Risk. According to Knight (1971) risk is anything resulting in a known hazard that canresult in a loss if insurance is not present. Risk is any danger or condition subject to an insurancepolicy. Without such a policy, loss is a more likely result. Uncertainty. The term uncertainty arises from a lack of knowledge resulting insuspicion, doubt, skepticism, or mistrust. Uncertainty means a condition in which risk isunknown or has gone undetected because of a lack of knowledge. Unlike risk, uncertainty isuninsurable (Knight, 1971). Assumptions In this research study, the assumption is that entrepreneurs wish to improve success ratesand are open to balancing the pursuit of opportunities with the attendant risks. Such anassumption suggests that an awareness of premarket entry risks leads entrepreneurs to riskmanagement. Entrepreneurs may still believe in beating the competition by taking a first-moverposition despite the risks. Besides the possibility of entrepreneurs taking such a position, the central question of thestudy suggests the entrepreneur is expert with planning to address risk cutting. Some
  • 28. 16entrepreneurs may not have the proper experience and may not have any idea how to find help.Further, the entrepreneur may not have the financial ability to deal with such problems. Scope, Limitations, and Delimitations Although entrepreneurial ventures in the alternative energy industry limit the scope of theresults, other industries face similar risks by “going public.” This study also only extends tocompanies within the United States and does not include foreign entrepreneurs engaged inalternative energy ventures. Ventures in other locations may present other risks besides those inthe domestic domain. Because the study includes only domestic ventures, risk present in theglobal domain remains unexamined. On the other hand, some of the companies listed on the U.S.Department of Energy website used to decide the sampling frame are either divisions of globalcompanies or domestic subsidiaries ("U. S. Department of Energy," 2008). The study hereexcludes risks present in business outside the United States. Because the study only extends to companies that have either gained renewable energycertificates or applied for such certificates, the study excludes other companies that have not yetreached that point. The results in the study rest on the assumption that a firm without renewableenergy certificates would not have yet reached a stage in which it can reach profitability in thealternative energy market. Similarly, the results rely on the assumption that a firm must findways to raise or produce enough capital before reaching profitability. Because the alternativeenergy industry is new, the results presume the industry can achieve profitability by providing asupplement or replacement for conventional fossil fuels. Most important, the major underlyingassumption for the companies in the industry rests in the ability to convert such energy intoelectrical power. Transmitting this energy depends on the ability to carry the power by an energygrid with enough capacity (Walter, 2009).
  • 29. 17 Despite the industry’s embryonic existence, the study excludes firms solely engaged inexploration as the growth of the industry depends on the products drawn from explorationalready successful. Thus the study only considers firms able to convert existing sources intoelectric power. Plan of StudyChapter 2, Literature Review Although some scholars argue that self-employment via entrepreneurship may not offerthe benefits the self-employed expect, such a notion depends on the location, the entrepreneur’smotivations, and the specific need. Besides, many people working as employees of others wantto work for themselves, but one of the most significant obstacles facing the entrepreneur comesfrom the lack of capital. Another significant result is that self-employment increases with age(Blanchflower, 2004). Because “baby boomers” are overabundant and depressed economic conditions exist,entrepreneurism offers an opportunity that otherwise is unavailable. Self-employment in theUnited States is highest among men, Whites with larger families, and people with a highereducation. For example, Organization for Economic Cooperation and Development (OECD) datashows that people with no education have almost no chance of reaching self-employment. Peoplewho finish eighth grade have a probability of 0.0141 of achieving self-employment. Conversely,people who earn a bachelor’s degree have a probability of 0.1959, and people who earn adoctorate degree have a probability of 0.4195 of achieving self-employment (Blanchflower,2004). As a further illustration, according to the 2008 Global Competitiveness report a study of43 countries classified the countries by stage of economic development as factor-driven,
  • 30. 18efficiency-driven, and innovation-driven. This study used12 pillars to rank the countries. Theleast developed nations fall into the factor-driven classification, while the most sophisticatedcountries fall into the innovation-driven group as determined by the rankings within each pillar.The pillars characterizing the factor-driven group include an institutional environment,communications networks, macroeconomic endeavors, health, and primary education. Besidesthese pillars, efficiency-driven economies complement these features with higher education,market efficiency for goods, labor market efficiency, a sophistication of financial markets, atechnologically ready environment, and a large market size. The innovation-driven groupcomplements these fundamentals with innovation and business sophistication (Bosma, et al.,2008; Porter & Schawb, 2008). Considering these rankings, Bosma et al. (2008) determined the rate of the adult-agedpopulation most actively engaged in nascent entrepreneurism arises from the factor-driven groupfollowed by the efficiency-driven group. For example, in the 25-34 age group 23% of thepopulation engage in nascent entrepreneurial occupations, whereas in the efficiency-drivengroup only 14% take on such occupations followed by the innovation group with only 10%participation. Concurrently, between 2001 and 2008 a slightly upward-to-static trend supportsthese rates (Bosma, et al., 2008). In all classifications the self-employed category is significant tothe other parts of the population working for others. The central question of the study proposesthat improving success rates through early knowledge of risk management eventually contributesto more efficient conditions for the community. Participation in nascent entrepreneurial pursuits is lower in innovation-driven economiesbecause monopolistic disincentives such as patent protection discourage nascententrepreneurism. Monopolies with patent protection wish not to compete with nascent
  • 31. 19entrepreneurs who have innovative ideas. As a result, the genuinely novel entrepreneur finds itdifficult to compete with firms engaged in temporary monopolies. The more sophisticated theeconomy, the less likely the small creative entrepreneur is to compete (Baumol, Litan, &Schramm, 2007 ). Baran (2009) argued the efficient planning and managing of practicesimproves conditions for entrepreneurial decision-makers and reduces misgivings enabling theentrepreneur to aid the existence of the firm. Similarly, if entrepreneurial faculty rates are a sign of the need for training, thepercentages of both primary and secondary advertised faculty positions steadily rose from 1989through 2005. For example, primary positions have risen from roughly 5% to 95% of advertisedpositions and secondary positions have grown from about 12% to 64% over the same time frame(Finkle, 2007). Finkle commented the demand for entrepreneurial faculty has outstripped thesupply. Because of such gaps in entrepreneurial support, self-employment continues to decline inthe United States. In 1997, the United States had a self-employment rate of 8.2%, which hasfallen to 7.2% in 2007, far below the OECD total in such years of 16.8% and 15.5%, respectively("OECD in Figures 2009," 2009). Baumol et al. (2007) recommended tearing down barriersstanding in the way of promoting entrepreneurial innovation. For example, Baumol et al.suggested bankruptcy reform, lowering the cost of start-up, improved protection of property andcontract rights, and minimizing overzealous taxation. Baumol et al. also recommended keeping abalance of rules and deregulation, providing rewards for university innovations, providingincentives for imitation, and disincentives for unproductive entrepreneurs (Baumol, et al., 2007). In line with heightened demand for entrepreneurial education, Collins, Smith, andHannon (2006) asserted that entrepreneurs need certain “pre-programme” capacities to engage
  • 32. 20effectively in nascent entrepreneurial activity (p. 188). Collins et al. argued that action-orientedentrepreneurs rely on adaptive learning or learning by doing. Entrepreneurs not only representthe owners but all stakeholders and participants, and manage change and uncertain conditions inan environment laden with risks (Collins, et al., 2006). The programmed approach involves usingnascent entrepreneurs, existing entrepreneurs, and trainers to teach different entrepreneurial skills(Collins, et al., 2006). An evaluation of premarket entry risks ties into the capacity-buildingapproach and benefits many stakeholders. Thus beneficiaries of this training consist of diversestakeholder groups including employees, venture capitalists, angel investors, finance companies,banks, suppliers, and customers. As noted, different groups of investors represent a major category of stakeholders whohave employed various risk-reducing strategies. Such strategies include forming investmentsyndicates, closely watching projects while releasing small infusions of capital, and asking forpreferred stock to ensure satisfactory compensation for investments (Parhankangas & Hellstrom,2007; Proimos & Murray, 2006). Venture capitalists finance fewer than 5% of entrepreneurs whoapproach such firms because the entrepreneurs are not “investor ready” (Berlin, 1998; Proimos &Murray, 2006). Sweeney (2006) reported that an emerging trend is to hire well-connectedinvestment banking firms to round up a group of angel investors compatible with theentrepreneur. Another strategy stems from more nascent entrepreneurs using bootstrapping tomake it through the early stage of development. Bootstrapping approaches emerge whenconventional equity and debt financing is unavailable, too costly, or dilutes ownership control ofthe firm. Bootstrapping includes bartering, sharing supplies, and other methods to conserve cashflow (Ebben, 2009; Ekanem, 2007; Winborg & Landström, 2001).
  • 33. 21 Although such methods have varying degrees of success, the presumption underlying thestudy proposes that addressing risk management early may improve effectiveness and result inimproved success rates. Some scholars have studied the problem of risk perception through theeyes of potential funding sources (Busenitz, Fiet, & Moesel, 2004; Fiet, 1995; Parhankangas &Hellstrom, 2006; Yoshikawa, Phan, & Linton, 2004). Other scholars have looked at theassociation between risk preferences and risk perceptions (Sitkin & Pablo, 1992).Chapter 3, Research Methodology The research plan included running a survey of alternative energy firms drawn from a liston the United States Department of Energy website ("U. S. Department of Energy," 2008). Thesurvey listed risks gathered from Form S-1 of the Securities and Exchange Commission (SEC).The survey asked respondents to provide data necessary to calculate the ratio of earnings to fixedcharges as described in §229-503 of the instructions for preparing a prospectus under the SECregistration statement. The self-reported data served as a proxy for discovering the likelihood ofsuccess of surveyed respondents. Similarly, the procedure called for respondents to say if suchfirms by filing Form S-1 have sought or filed for public financing. The survey asked respondentsto rank the risks by noting when awareness and planning for risk management started by using aseven-point, Likert-scale. Discriminant analysis decided which respondents fell into successfuland unsuccessful groups of entrepreneurs. After finding which respondents belong to such groups, the next step entailed analyzinghow these risks affect the self-reported success rates for each group. The procedure includedrecording the data for each respondent and coding the data for those respondents by whenawareness of the risks and planning effort began. Thus the procedure called for entering theresults for all respondents into SPSS and running descriptive statistics for each group.
  • 34. 22Concurrently, the procedure called for an analysis of the results to detect if a difference exists insuccess rates between the groups. The analysis employed multiple discriminant analysis to testthe proposed theories (Leech, Barrett, & Morgan, 2007). Multiple discriminant analysis is atechnique that classifies observations into groupings by looking at individual characteristics onwhich the groups depend (Altman, 1968). Altman used ratio analysis to classify new venturesinto firms likely to go bankrupt and firms likely to continue. Similarly, the SEC uses the ratio ofearnings to fixed charges on Form S-1 to analyze the riskiness of investments in new ventures byassessing the firm’s chance of surviving. Multiple discriminate analysis provided a linearcharacterization of reasons that best discriminate between groups (Altman, 1968). In this studyof successful and unsuccessful entrepreneurs, the two groups needed such an analysis.Presentation and Analysis of Generated Data Once the analysis is complete, a comparison of the groups with the risks helps decide ifthe group seeking public financing fares better than the group not seeking public financing. Fromthe analysis, the expectation is for the group seeking public financing to have higher successrates because underwriting brings attention to risk identification and management. Similarly, theanalysis helps decide if any of the risks have more of an effect than others and whether the risksinfluence one another. The analysis uses the identified risks and the self-reported statistics to testthe following theories:Set One: DirectionalHo1. No difference exists between entrepreneurs gaining an awareness of risks (IV) before andafter entry to the market resulting in a significant improvement in their success rates (DV) withinthe United States’ alternative energy industry.
  • 35. 23Ha1. A difference exists between entrepreneurs gaining an awareness of risks (IV) before marketentry and after entry to the market resulting in a greater significant improvement in their successrates (DV) within the United States’ alternative energy industry.Set Two: NondirectionalHo2. No difference exists between entrepreneurs gaining an awareness of risks (IV) before andafter entry to the market resulting in a significant improvement in their success rates (DV) withinthe United States’ alternative energy industry.Ha2. A difference exists between entrepreneurs gaining an awareness of risks (IV) before andafter entry to the market resulting in a significant improvement in their success rates (DV) withinthe United States’ alternative energy industry.The analysis helps decide the priority in which to plan for the identified risks to help improvesuccess rates. With the results of the analysis in mind, entrepreneurs from other industries may notagree with the results for alternative energy. A researcher may find other risks more relevant inother industries, and such risks can bring different results. Thus a researcher should have anawareness that some of the same risks may apply, while others do not. Summary In summary, the analysis of the study aims to concentrate on making the risks associatedwith the launch of a new venture more visible to the nascent entrepreneur so the founder canbegin risk management sooner rather than later. Usually, opportunism and enthusiasm clouds theentrepreneur’s vision so opportunity overshadows the related risks involved in such ventures(Busenitz, 1999; Gelderen, et al., 2006; Wu & Knott, 2006). Because entrepreneurs representonly seven to eight percent of the United States population but account for roughly 30% of the
  • 36. 24top decile of wealth, an expansion of entrepreneurism is worthwhile. As a result, the growth ofentrepreneurism provides society employment and stimulates fiscal growth (De Nardi, et al.,2007; Sternberg & Wennekers, 2005). By balancing opportunities and risks, heightenedentrepreneurism provides an important first step in filling this void.
  • 37. 25 CHAPTER 2: REVIEW OF THE LITERATURE In the review of the literature, the objective is to query the literature about the history anddevelopment of risk management. The review of the literature also queries the role of theentrepreneur, developing the study of risk, and alternatives improving risk management. Severalstrands have developed in the literature about risk management. These strands includedistinguishing between risky and uncertain events, and the lack of ability to detect early stagerisk because opportunism overshadows the sight of risk. Similarly, other risk managementmethods have developed such as alternative funding mechanisms provided by angel investorsand venture capitalists, and the use of prediction and control. Although the literature has developed distinct threads of research about risk managementfor the entrepreneurial venture, researchers have yet to develop much about risk managementbefore market entry. This study helps to fill the void in the literature about the effects of riskmanagement before entering the market. This study evaluates early risk management rather thanwaiting until after the entrepreneur launches a venture. The intent is to continue to develop theliterature to improve entrepreneurial success rates. Title Searches, Articles, Research Documents, and Journals To fill such a void, the objective of the review of the literature is to scan current literatureabout the history of entrepreneurism and risk management. The chapter provides an analysis ofthe recent strands of risk management literature. These strand include types of risk faced byfounders of firms whether seen or not, and characteristics marking a successful launch of aventure. The historic development of entrepreneurism and risk management serves as afoundation to understand the need for more research about improvement of entrepreneurial
  • 38. 26success rates by starting early to plan for applicable risks. Such research helps frame the researchproblem about risk and uncertain conditions by distinguishing between the two. After reviewing the literature, a classification of alternative types of risks forms the basisfor deciding applicable features that affect the successful launch of the business. A look at recentliterature helped discover applicable risks. With this review, a view of the underwriting for firmsseeking to “go public” provided an improved backdrop for analyzing the timing of such risks.Thus in the conduct of the research, a scan of the Securities and Exchange Commission (SEC)Form S-1 for firms applying to “go public” helped decide on risks revealed in the underwritingprocedure. Both an awareness of such risks and a plan to deal with the risks are critical outcomesof such analysis. The analysis helped isolate proper risks serving as independent variables for thestudy. Similar to indentifying suitable risks, the objective of the analysis is to identify riskcharacteristics believed proper to settle on the causes of a successful business launch. Such acourse of action helped identify characteristics from the literature and from the SECrequirements for firms seeking to “go public.” Thus the research analysis looked at the needs ofSEC §229.503 of Regulation C to discover proper measures for deciding success to supplementthe measures found in the literature. The combined measures formed the basis for decidingsuccess and failure rates, the dependent variables for the study. Literature ReviewHistoric Overview Risk management. Modern risk-taking theory has roots in the Hindu-Arabic numberingthat emerged in the Western world in the 1200 to1300s (Bernstein, 1996, p. 218). Two prominentFrench mathematicians, Blaise Pascal and Pierre de Fermat engaged in a new game of chance in
  • 39. 27the summer of 1654 discovering the modern theory of probability. The “unfinished game”sometimes known as “the problem of points” resulted in the first try to quantify how to managerisk (Bell, 1998; ORourke, 2008). Pascal and Fermat used chance to forecast the likelihood offuture events. Before this time, probability analysis had no place in risk management (Bernstein,1996). Quantifying such a game of chance prompted Chevalier de Mere, a gambler, andchallenged Pascal and de Fermat. This revelation could not have happened without the discoveryof the Hindu-Arabic numbering. In 1202, the Italian mathematician, Leonardo Pisano, alsoknown as Fibonacci, visited the Algerian city of Bugia in which his father served as Pisanconsul. An Arab mathematician introduced the Hindu-Arabic numbering to Fibonacci, whichFibonacci later published in Liber Abaci or the Book of Abacus (Bernstein, 1996; Danesi, 2005).The numbering has its roots in India where the Hindus developed the technique and the Arabsbecame familiar with the method during India’s invasion (Bernstein, 1996). Quantifying risk through probability analysis further developed through the efforts ofGirolamo Cardano, a gambling scholar and prominent doctor. Cardano provided one of the firstdefinitions of probability before Pascal and de Fermat’s time in the 1550s. Cardano did not havethe work published until after death. Cardano defined probability as the result found by dividingthe number of favorable outcomes by the number of possible cases (Bernstein, 1996; Ekert,2008). Shortly after Pascal and Fermat, other notable individuals began applying probability todifferent applications. John Graunt, a merchant, used probability to estimate the population andapplied the idea to demographic information. William Petty, a doctor, aided Graunt with studiesof population statistics (Bernstein, 1996; Kreager, 1988). Edmund Halley, an astronomer, used
  • 40. 28probability to predict when comets would appear and to calculate the value of annuities based onlife expectancies (Bernstein, 1996; Ciecka, 2008). Further development of the use of probability analysis came from the Bernoulli family. In1703, Jacob Bernoulli became the first to build on the theory from sample data (Bernstein, 1996).Jacob introduced epistemic probability and used the idea of guessing about the future by lookingat data from the past (Hon, 2008). By watching what happened in the past, a reasonableexpectation exists for the same to happen in the future. Bernoulli also developed utility theorythat relies on a person’s power to measure utility. Utility theory enables one to decide on rationalalternatives to avoid uncertain conditions and conquer risks (Bernstein, 1996). For example, onecould decide to either lease or buy a piece of equipment. Leasing preserves cash and reduces thechance of running out of cash. Similar to the work on probability analysis, Jacob’s nephew, Nicholas continued Jacob’swork and invited the French mathematician, Abraham de Moivre to help. De Moivre developedthe normal distribution or bell-shaped curve from such work by using a sample. This innovationhelped discover the degree of dispersion about the mean and the related standard deviation(Bernstein, 1996). Pierre Remond de Montmort claimed credit for the same innovation and deMoivre and de Montmort both complained of plagiarism. Both men worked with Bernoulli andeventually began working collegially (Bellhouse, 2008). In the early 1800s, a prominentmathematician, Carl Friedrich Gauss, named the bell-shaped curve. Gauss used the bell-shapedcurve to study the curvature of the earth and taking measurements forming a distribution of therecorded measures (Bernstein, 1996). Today research uses the bell-shaped curve and normaldistributions extensively in scientific inquiry for hypothesis testing.
  • 41. 29 In line with such analysis, risk-taking theory further developed with another innovationwidely credited to Sir Francis Galton in the late 1800s (Bernstein, 1996). Such innovationoriginated from the law of regression or return to the mean published in 1885 (Bernstein, 1996;Bulmer, 1998; Sandall, 2008). Such an idea motivates most forecasting involved in managingrisk-taking (Bernstein, 1996). In, 1901, Karl Pearson worked as a student of Galton anddeveloped the chi-square or goodness-of-fit technique to improve accuracy of predictions(Magnello, 1998). For instance, business today relies on such techniques to help predict manyissues such as market demand, defect rates in products, warranty claims, and many otherapplications. To frame the history of risk management, Bernstein (1996) decided the fundamentalnature of risk management rests in increasing the areas in which a person has control (risks). Atthe same time, Bernstein settled on lessening such areas in which a person has no control(uncertainties) or in which envisaging cause and effect is difficult. Bernstein’s revelationprovides a foundation for the study on how timing affects risk management by identifying risksearly and minimizing uncertain conditions by culling out and controlling risks. For example, afirm might wish to exert control over its supply chain or its procurement and distribution tasks.By vertically integrating, the firm can bring such applications under its control. The role of the entrepreneur. In framing the context of risk management, capitalismemerged to underpin modern entrepreneurism. In 1732, Cantillon, an Irish-banker working inFrance, introduced classical entrepreneurship. Cantillon argued entrepreneurship emanates fromsupply and demand differences (arbitrage) by setting up equilibrium models between buying andselling prices leading to a more stable economic environment. Cantillon’s forethought using suchmodels helped deal with uncertain conditions and risk (Minniti & Lévesque, 2008; Murphy,
  • 42. 30Liao, & Welsch, 2006; Sobel, 2008). In 1848, John Stuart Mill in his book, Principles of thePolitical Economy, expanded on the role of the entrepreneur to include management of the firm(Sobel, 2008). Although both Cantillon and Mill helped develop the place of the entrepreneur inthe fiscal environment, the literature widely recognizes Adam Smith as the father of capitalism(Bassiry & Jones, 1993; Renesch, 2008). Apart from Cantillon’s equilibrium models, Smith launched capitalism from a utilitarianperspective. This perspective intended to avoid the Marxist economic model largely present atthe time as opposed to the state-based capitalistic model that exists today (Bassiry & Jones,1993). Smith rooted the capitalistic model based on John Locke’s notion of human liberty. ThusSmith condemned the authoritarian economic models in favor of a model highlighting the rightsof the people (Wren, 2005). For example, supply and demand equilibrium models aid inregulating the transfer of wealth to the people rather than the state arbitrarily granting wealth tomonopolies. Concentrating power in monopolies shielded by the state Smith feared most aboutthe capitalistic model. The Western world viewed capitalism as a more efficient economic modelto provide for the needs of the average citizen (Bassiry & Jones, 1993; Renesch, 2008).Consistent with such a view of capitalism, both Weber and Mises explained the capitalistmotivation as coming from the pursuit of profit through rational restraint. Weber and Misesfavored the approach over the pursuit of profits for greed (Mises, 1944; Weber, 2001). With such a foundation in mind, Smith distinguished the entrepreneur from the capitalistby noting the sole role of the capitalist is to make capital available to the firm and bear the risk ofloss (Schumpeter, 1951a). Montanye (2006) described entrepreneurship as a person facingscarcity and uncertain conditions. An entrepreneur successfully produces and seizes “economicrents” to achieve economic rewards surpassing the rents existing from perfect competition in
  • 43. 31which the forces of equilibrium are in balance. Under such conditions, the gifted entrepreneurreaps the rewards of a higher standard of living (Montanye, 2006). Thus the ability to competesuccessfully in the market offers motivation to the entrepreneur to achieve such rewards. Recognizing this definition, the entrepreneur differs from the capitalist because theentrepreneur competes by managing scarce supplies and uncertain conditions fraught with risks.The entrepreneur’s role emanates from managing risky conditions in such a way to earn a returnon the capital invested in the firm. Knight (1971) asserted that an entrepreneur should distinguishrisk from uncertain conditions as a person can mitigate risk through insurance, hedging, anddiversification. Conversely, uncertain conditions stems from ignorance or acting on opinionrather than knowledge (Knight, 1971). By identifying risks and removing risks from theunknown to the known, the presumption is the entrepreneur can improve the likelihood ofstarting successful ventures through risk management. Mises (1944) confirmed the thinking thesuccess or failure of a venture depends on how good an entrepreneur anticipates uncertainoutcomes. Although Knight expressed the entrepreneur’s role by separating risk from uncertainconditions, Coase (1937) argued that entrepreneurs are unnecessary. Coase believed thisargument because a firm can substitute for such a role within the firm, which makes the firmmore competitive. Coase in his theory on transaction costs viewed the market pricing apparatusesas the outlet for controlling scarce supplies and managing risk. Kirzner (1999) argued the pricingapparatuses are imperfect and stresses “mutually gainful exchanges” instead of the false restingequilibrium prices inferred by Mises (p. 218). Mises (1944), similar to Knight, credited theentrepreneurs with responsibility for dealing with uncertain conditions and argued managerialwork represented only part of the entrepreneur’s role.
  • 44. 32 In line with Knight’s perspective, Mises separated entrepreneurism from promotion bynoting how entrepreneurs set up the reasons for production. Such a view is consistent with JeanBabtiste Say’s classical view of the entrepreneur’s role in directing and spreading goods’creation from unproductive domains to more productive ones (Murphy, et al., 2006; Sobel,2008). Mises believed consumer sovereignty caused a controlled economic model becauseconsumer preferences decide production and entrepreneurs serve as agents of the consumers(Kirzner, 1999). Alternatively, Kirzner (1999) believed pure profit based on “the best currentinformation” served to motivate the entrepreneur and government intervention is unnecessary (p.226). For example, today supply side economics avoids consumer sovereignty as the consumerlacks satisfactory information to make more educated choices. As a result, business controlsinformation, and gains comparative advantage over consumers. For example, until recentlybusiness has found it could withhold country of origin information on various foods and drugs. In contrast to the notion the entrepreneur serves as an agent to support consumersovereignty, Coase (1937) denigrated the entrepreneur to a mere marketer, while both Knightand Mises assigned the entrepreneur’s role to other unique purposes. Knight argued the lifebloodof the entrepreneur emanates from facing uncertain conditions (Knight, 1971; Mises, 1966;Montanye, 2006). Schumpeter (1975), on the other hand, noted risk-bearing belonged to thecapitalist rather than the entrepreneur because the entrepreneur does not necessarily have to riskcapital. However, Schumpeter assigned responsibility for “creative destruction” and innovationto the entrepreneur. Such advances come through improvement of goods and services,production variations, unique organizational structures, expanded markets, and unique supplysources. In other words, the entrepreneur disrupts the economic environment by creatinginnovative replacements for existing goods, services, processes, and structures. In contrast to the
  • 45. 33Schumpeterian notion of “creative destruction,” Kirzner believed the entrepreneur’s primemotivation is exploitation of undiscovered opportunities. Such opportunities serve to bring themarket into equilibrium as opposed to disrupting the equilibrium as suggested by Schumpeter(Sobel, 2008). A recent example of exploiting such opportunities comes from the financialservice industry selling risky subprime mortgage products. Schumpeterian thought would put therisk on the financial institutions by allowing them to fail. The Kiznarian notion promotesexploiting the consumer without the risk and by proclaiming these institutions “too big to fail.” In line with such ideas, Schumpeter recognized separating ownership and control isimportant and suggested that eventually institutions would reform the roles of the entrepreneur asinternal tasks. To strip such roles from the entrepreneur removes the threat resulting from“creative destruction” (Montanye, 2006, p. 553). In his work, Entrepreneurship, management,and the structure of payoffs, Baumol shed suspicion on the rent-seeking opportunities ofentrepreneurs. Baumol also viewed how some corporate managers destroyed value ofentrepreneurial firms by churning out bad takeovers or overpaying for other ventures that hadlittle chance of succeeding (Caves, 1995). Baumol’s revelation suggested a place still exists forthe entrepreneur because, unlike the corporate manager, the entrepreneur cannot find protectionby hiding under the corporate veil. The association between risk and return rests squarely on theentrepreneur’s shoulders. Consistent with the idea that a place exists for the entrepreneur, Baumol (1993)characterized the entrepreneur as a participant in the economy. Baumol argued the entrepreneuruses boldness, imagination, ingenuity, leadership, determination, and persistence to chase profits,power, and wealth. Baumol believed that both the Schumpeterian view of innovation andKirznerian notion of arbitrage transactions offered prospects for entrepreneurs seeking pure
  • 46. 34economic profit opportunities (Baumol, 1990; Sobel, 2008). Besides, Baumol (1990) made nomention in the historic case study of the “rational restraint” proposed by Mises and Smith toprevent unproductive entrepreneurism leading to “creative destruction” (Mises, 1944;Schumpeter, 1975; Smith, 1904). Baumol did note that rent-seeking entrepreneurs could pose abarrier to competition (Baumol, 1990). As Mehlum, Moene, and Torvik (2003) proposed,“Entrepreneurs must find it profitable to create rather than to destroy” (p. 3). By showing a place exists for the entrepreneur, Leibenstein supported Baumol’s claimthe entrepreneur takes up nonroutine tasks in developing the “X-efficiency” theory. Leibensteinnoted that within a firm incentives are necessary to motivate an employee to take on the tasksusually taken on by the entrepreneur (Leibenstein, 1983; Montanye, 2006). If extra incentives arenecessary to do these tasks within the firm, Coase’s (1937) transaction cost theory is irrelevant.This condition exists because the firm does not remove the cost to the firm by erasing theentrepreneur. Instead, the firm simply replaces the cost internally. Mises also noted thatconsumer sovereignty only neglects achieving a harmony between owners and consumers undermonopolistic conditions. In such case, consumers must appeal to politicians (Kirzner, 1999;Mises, 1966). Although Kirzner (1999) argued for pure profits and the absence of governmentintervention, Adam Smith’s vision of mercantilism stressed heightening the power of the nation-state in pursuit of self-sufficiency. Smith argued the nation-state should “maximize exports andminimize imports” (Bassiry & Jones, 1993, p. 622). Smith feared monopolistic conditions andstressed democratic government to foster self-sufficiency and serve as a watchdog againstmonopolistic conditions. Smith argued monopolistic conditions shielded the entrepreneur fromthe need to compete (Bassiry & Jones, 1993).
  • 47. 35 Because of these opposing views of the entrepreneur, one can argue replacing theflexibility and creativity of the entrepreneur with the politics and bureaucracy does not offer abetter solution. Creating an environment conducive to innovating new ideas and stimulatingheightened productive methods is unique to the entrepreneur. Conversely, the corporate worldpresents an environment more apt to stymie and frustrate the traditional role of the entrepreneur.Casson (2005) asserted the routine of the manager cannot serve to replace entrepreneurialimprovisation. Improving conditions for entrepreneurs should afford a better strategy fordeveloping innovations and improved productive methods than absorbing this role in thecorporate environment. The motivation for corporate interest in the entrepreneurial role emanatesmore from control and fear of competition than from removing transaction costs. In line with improving the competitive environment, Baumol, Litan, and Schramm (2007)recommended several ideas to tear down some of the barriers imposed on entrepreneurs. Suchrecommendations included start-up cost cuts, encouraging imitation through incentives, andimproving protection of property and contract rights. Similarly, the recommendations includedbankruptcy reform, lessening obsessive taxation, preserving a balance between law andderegulation, providing inducements for university innovations, and disincentives forwastefulness (Baumol et al., 2007). Baumol’s major contribution arose from distinguishinginnovative productive entrepreneurship that provides economic growth, jobs, and wealth creationfrom unproductive political behavior emanating from lobbying and lawsuits (Sobel, 2008).Baumol (1990) charged today’s lack of economic growth and prosperity to the rules of the gamenot favoring the entrepreneur because of unproductive rent-seeking, political, and legal actions.Thus Baumol suggested reforms that support changing the rules of the game to improveproductive entrepreneurship and entrepreneurial success rates.
  • 48. 36 Although corporate control fails to provide an environment conducive for theentrepreneur to succeed, a lesson from corporate risk management offers entrepreneurs anopportunity to improve. In “going public,” underwriting compels companies to become moreaware and begin to plan to manage risks. Instead, entrepreneurs neglect this important stepbecause of the inability to extract risks from existing unknown conditions. This inability to findrisks drives the entrepreneur to deal with more uncertain conditions and reduces the likelihood ofsuccess (Ugur, 2005). Mohan-Neill (2008) provided evidence that takeover by a public companyserved as a source of funding for firms in the biotechnology industry. However, investee firmsneed an improved state of readiness to achieve financing through this source of capital.Review of Current Results Risk perception, risk-taking propensity, and entrepreneurial opportunism. Inharmony with entrepreneurs overlooking risks during early stages in a firm’s development,venture capitalists shy away from investing in such ventures despite holding a reputation asdaring risk-takers (Parhankangas & Hellstrom, 2007). Casson (2005) asserted the view of theentrepreneur taking undue risk emanates from inaccurate opinions. These opinions arise becausethe entrepreneur may hold information that if known to the investor and outsiders may counterthe view of extravagant risk-taking. Thus the optimism of the entrepreneur may arise fromholding “privileged information” (Casson, 2005, p. 330). For example, in the airline industrypricing fares is not common knowledge to the public. Once again, this example shows supplyside economics resulting in a comparative advantage. Similarly, Janney and Dess (2006) arguedthat risk perceptions of entrepreneurs stem not only from the risk of loss, but from the risk of alost opportunity. Obviously, the positive nature of opportunism may temper the negativity of
  • 49. 37risk. Janney and Dess play down risk as a variance through statistical and ratio analysis such asrequired returns expected by investors or by raising funds through a public offering. Although entrepreneurs’ view of opportunity is often unclear, Ottesen and Gronhaug(2006) reduced such opportunities to the following formula: “P(S/A) > P(S/ Ā) where P =probability, S = success, A = action, and Ā = no action” (p. 102). Thus entrepreneurs seeopportunities positively as circumstances in which an opportunity for gain exists and result fromapplying some action to an observation that results in a gain. However, the entrepreneur’s viewsof opportunities typically are overoptimistic, which poses a threat in predicting a sensed outcome(Ottesen & Gronhaug, 2006). To explain the influence of opportunism on pursuit of opportunities, Ottesen andGronhaug (2006) studied how one successful firm in the fishing industry achieved success whenother firms found difficulty in surviving. The successful firm restricted investment while othersin the industry saw a chance to beat the competition and tried to capitalize on the opportunitybefore the sensed conditions happened. The general manager of the successful firm explained therationale is not to invest money when the future looks bright, but to hold capital to support atleast three years when experiencing difficult times. This explanation implies timing influencesrisk taking. How a person views an opportunity may not result in the most fitting time to investin a new venture. The entrepreneur may find improved chances for success in times when othersfind conditions difficult to invest in an opportunity. Preservation of capital provides a valuablelesson to the excessively enthusiastic entrepreneur (Ottesen & Gronhaug, 2006). With such a lesson in mind, in a study of risk-taking behavior at start-up point, Grichnik(2008) studied 252 entrepreneurs and entrepreneurial students. Grichnik found the higher theoverconfidence, the lower the risk awareness and the higher the risk selected. Similarly, Grichnik
  • 50. 38found the risk-taking inclination plays a minor role with a 95% chance of no change in the risklevel. In other words, making the entrepreneur aware of risk is of prime importance to improvingentrepreneurial success rates. The entrepreneur’s appetite for risk-taking has little effect. Theseresults infer that making the entrepreneur more aware of antecedent risk should improve thesuccess rate of entrepreneurs launching new ventures. Although Grichnik (2008) found that risk-taking inclination plays a small part inentrepreneurial risk taking, the literature on risk-taking propensity offers conflicting evidence.For example, Gilmore, Carson, and O’Donnell (2004) determined that several articles found nodifference between the general population and entrepreneurs about risk-taking inclination(Brockhaus, 1980; Caliendo, Fossen, & Kritikos, 2009). Other articles did find differencesexisted (Begley & Boyd, 1987; Hull, Bosley, & Udell, 1980). In another study, Gilmore et al.(2004) noticed how valuable tools emerged from managerial competence and networking inmanaging risk to improve the risk-taking inclination of entrepreneurs. Despite society and educational sources playing down individualism and stressingteamwork and community, Alstete (2008) determined in a study of 159 entrepreneurs self-employment is the prime motivation (44% of the people surveyed). The attraction to self-employment arose from the desire for individual independence. Besides, the survey found theability to control one’s own destiny important to another 19% of the people surveyed. One of thebenefits of the reliance on individual efforts emanated from the capacity to benefit thecommunity. Only 13% of entrepreneurs surveyed suggested risk acted as a major deterrent. Ofthe people surveyed, 21% advised aspiring entrepreneurs to engage in a thorough planning effortbefore starting a new business (Alstete, 2008).
  • 51. 39 In line with balancing entrepreneurial opportunism with risk perception, Bishop andNixon (2006) asserted that evaluating opportunities with antecedent goals would help to predictthe likelihood of entrepreneurial success. Bishop and Nixon noted the literature lacksinformation about prenascent venture evaluation. For example, venture capitalists rely oninformation contained in business plans and market research to evaluate such ventures. Analysisof strength, weaknesses, opportunities, and threats (SWOT) helps the venture capitalist decide onplans. The literature lacks evidence of planning by the entrepreneur in performing suchevaluations. Not enough attention to the addressing what venture capitalists consider criticalsuccess factors may contribute to the high failure rates of entrepreneurs (Bishop & Nixon, 2006;Proimos & Murray, 2006). Related to needed venture planning by nascent entrepreneurs, Gelderen, Thurik, &Bosma (2006) determined that nascent entrepreneurs with limited experience benefit fromstarting small. Gelderen et al. noted people with experience understood how seeking guidanceand knowledge is important. Similarly, Geldren et al. also found that employing a plancontributes to a firm’s future success. This study included a sample of 517 nascent entrepreneursover a three-year period. Gelderen et al. used logistic regression analysis to test whether aventure is successful or unsuccessful using four variables. The variables included the presence ofa business plan, perception of market risk, part-time or full-time start-up, and a team versus soloeffort. The study divided the results between people with high and low ambition. The researchersdetermined that start-up capital and market risk provided the highest contribution to success orfailure (Gelderen, et al., 2006). Although the study confirmed the need for venture planning as applied to riskmanagement, the study did not deal with the cause of the risk perception. Neither did the study
  • 52. 40settle on the influence of the timing of risk awareness nor management influence on successrates. The researchers did recognize that risk management strategies should lead to lowerperception of risk (Gelderen, et al., 2006). Similarly, Gelderen et al. showed further that riskmanagement improves the potential for earning more start-up capital from sources other thanconventional lenders. Geldren et al. noted that such results run counter to Delmar and Shane(2004) in which the planning efforts mainly contribute to legitimizing efforts rather thanpredicting success. Gelderen et al. finished by noting that a need exists for more research in theprestart-up phase about the use of predictors to evaluate performance. In harmony with Gelderen’s assertion, Wiltbank, Read, Dew, and Sarasvathy (2009)found investors who focused on opportunities at an earlier stage realized fewer negative exits. Inuncertain settings, prediction and control of risk take on a greater role in planning for success.Investors who stress prediction invest greater amounts; whereas investors who focus on controlhave fewer negative exits. The study implies investors do not all have the same appetites for riskand return. Some investors focus on high-risk, high-return ventures, and others focus onachieving a greater number of lower-risk, lower-return successes. Investors focusing onprediction invest higher amounts, and those who concentrate on lower risk-return investmentsstress control (Wiltbank, et al., 2009). In contrast to the view risk management is more a matter of strictly risk perception,traditional economic literature views risk as either stand-alone risk that a firm can manage or thesystematic risk credited to market conditions. A firm has little control over market risk becausean individual firm cannot control market volatility (Brigham & Houston, 2001; Ross,Westerfield, & Jaffe, 2005). Casson (2005) asserted that competition spurs volatility of marketdemand and that demand shocks caused by competition provides a source of risk to the
  • 53. 41entrepreneur. Casson suggested that such shocks cause a “flow of information” problem for theentrepreneur to watch to assess demand volatility. Janney and Dess (2006) described thisinformation flow as “idiosyncratic knowledge and opportunities” or specialized knowledgewithout value to others (p. 391). One can find in economic literature that a firm should expectsuch shocks. A firm’s stock price builds in the influence of demand volatility (Brigham &Houston, 2001). Without public financing the entrepreneur bears the risk of such demandinfluences. With the influence of uncertain demand, Wu and Knott (2006) studied nascententrepreneurs in the banking industry by using the Federal Deposit Insurance Corporation(FDIC) data for newly chartered banks (170,859 observations). Wu and Knott tested the theorythat entrepreneurs are risk averse about uncertain demand, but overconfident or risk-seeking inmanaging cost and realizing a profit stream. The results of the study showed that entry to theindustry increased with uncertain cost, but decreased with uncertain demand (Wu & Knott,2006). The study explained that although uncertain demand represents systematic market risk(diversifiable), the entrepreneur senses such risk as necessary to deal with demand influences andtempers market entry decisions if the risk is too high. Wu and Knott’s results make obvious thenotion that an early awareness of the uncertain demand provides an exit alternative for the risk-averse entrepreneur to lower the likelihood of failure. Similarly, such results revealed howentrepreneurs are overconfident of the founder’s own abilities. Such results are consistent withJanney and Dess (2006) and Grichnik (2008) in how overconfidence influences risk perception. Not only are entrepreneurs overconfident about self-abilities and pursuit of opportunities,but firm founders overlook the effect of waiting to detect threats from risks the founder fails toenvisage. Although a high-level of commitment characterizes entrepreneurs, neglecting the
  • 54. 42presence of risk and staring in the face of uncertain conditions makes founders unprepared toseek necessary financing. Thus venture capitalists (VC) see many entrepreneurs as not “investorready” because of a lack of planning for risk (Proimos & Murray, 2006). In the study, Proimosand Murray used two surveys of 21 entrepreneurs and 53 venture capitalists finding a divergencein seeing the entrepreneurs’ readiness for financing between the groups. The research provided acomparison between the two groups by technology readiness, market readiness, managementteam, and gut feel. The VC group rated management readiness, technology readiness, and gutreaction much higher than the entrepreneurial group (Proimos & Murray, 2006). Such results arealso consistent with Grichnik’s (2008) conclusion that overconfidence tempers risk perception.Read, Dew, Sarasvathy, Song, and Wiltbank (2008) reasoned, as noted later that entrepreneursaddress uncertain conditions through effectuation without any difference in the dislike of riskthan any other actor. Decreasing the diverging opinions between VCs and entrepreneurs likelyimproves opportunities for funding and the eventual success of an entrepreneur.Defining and Extracting Risk from Uncertainty In Wiltbank et al.’s (2009) research about the influence of prediction and control oninvestors’ risk taking, separating risk identification and management from uncertainty offered anexplanation for using these techniques. Wiltbank et al. assessed the success of angel investmentsin which investors exercised some control over investments. The results supported the view thatby becoming aware of risk and conducting planning the investee improved the likelihood ofsuccess. The study encompassed 1,038 investments by 121 investors with 76 experiencing exitsfrom investments with 414 total exits amassing to the time the study completed. The authorsnoted the study only addressed angel investors in the United Kingdom for investees belonging toan online investment group and relied on the self-reporting of internal rate of return (IRR) as a
  • 55. 43measure of success or failure. The study did not consider any other possible measures. Althoughthe investments evaluated spanned more than 10 years, Wiltbank et al. arbitrarily decided whatIRRs result in success and failure. Wiltbank et al. also had a limited time horizon of only the twoyears in which to engage in this study. Accurate evaluation of IRR should span the entire term ofeach investment or arbitrary cash flows can result in misreporting of IRRs. Wiltbank et al. alsonoted a low response rate of just 23% from the angel investors surveyed in this study. In line with the study about separating risk and uncertainty, McKelvie, Haynie, andGustavsson (2009) examined the affects of uncertainty on risk reluctance. McKelvie et al. foundthe greater the uncertainty, the lower the willingness of an entrepreneur to exploit an opportunity.Milliken (1987) defined uncertainty, ”… as an individual’s inability to predict somethingaccurately” (p. 136). This definition implies if an outcome is predictable, the firm has theopportunity to manage the condition. On the other hand, if an outcome is unpredictable, the firmwill find mitigation not possible contributing to augmented risk reluctance. Thus risk emergesfrom what is predictable and manageable. Milliken further distinguished between state, effect,and response uncertainty. State uncertainty stems from the inability to predict environmentalchanges. Effect uncertainty originates from powerlessness to predict the effect changes made tothe environment. Response uncertainty reflects a lack of competence to predict the effect of aresponse to the state of the environment (McKelvie, et al., 2009; Milliken, 1987). In conformity with McKelvie et al.’s (2009) notion that uncertain conditions affectentrepreneurial decision-making, Gans, Hsu, and Stern (2008) provided evidence that declininguncertain conditions led to pursuit of protection of intellectual property rights. Similarly, Wu andKnott (2006) explained how uncertain conditions limited market entry decisions. Wiltbank et al.(2009) noted the more an investor believed an opportunity existed to control an environment, the
  • 56. 44less apt that investor is to exit the market. The literature does clearly define a precise line ofdemarcation between risk and uncertain conditions. The literature remains unclear about at whatpoint risk emerges from uncertain conditions. The gap in clearly defining this point providesjustification for further research. Although the precise line of demarcation remains unclear between risk and uncertainty,McKelvie et al. (2009) showed uncertain conditions have an influence on decision-making.Defining and distinguishing between risk and uncertain conditions leads to a betterunderstanding of uncertainty’s influence. On the other hand, gravitating from unknown to theknown moderates the negative influence of uncertainty in exploiting opportunities and probablyis a matter of degree (Ugur, 2005). In other words, the more certain conditions become, the morecomfortable the entrepreneur becomes in exploiting opportunities. The proposed theory here isthe sooner the entrepreneur becomes aware of uncertainty and risk and deals with suchconditions, the better the likelihood of success. Thus addressing risk and uncertain conditions isnot only a matter of degree, but a question of timing. As Parhankangas and Hellstrom (2007)noticed, “interrelations between antecedents of risk-taking, investment decisions and riskreduction strategies still remain largely unexplored territory” (p. 184). In arriving at the conclusion that uncertain conditions have important implications forentrepreneurial decision-making, McKelvie et al. (2009) revealed some significant results. Thestudy focused on entrepreneurial decision-makers from the Swedish software industry. Althoughthe sample included 603 decision makers only 90 responded (15%). Most decision makers hadfewer than 50 employees and 77% reported serving as the primary decision maker with anaverage experience of 13.8 years. The study employed conjoint analysis to break up the decision-making methods. One of the most significant results revealed as expected that not all uncertain
  • 57. 45conditions are the same as determined by Milliken’s (1987) classification of state, effect, andresponse uncertainty (McKelvie, et al., 2009). Thus how entrepreneurs see uncertain conditionshas an important influence on the ability to control such conditions. Entrepreneurial scholarsknow this theory as effectuation in which uncertain conditions cause the entrepreneur to act toexploit an opportunity rather than try to predict an outcome. When conditions are unknown, anentrepreneur takes small steps to work toward exploiting the opportunity instead of letting thoseconditions impede action. Entrepreneurial experience grows in importance to know how tocontinue within available means (Read, Dew, Sarasvathy, Song, & Wiltbank, 2009). The studyalso revealed that no connection exists between external environment characteristics and whatthe entrepreneur sees as unknown. Such characteristics are incapable of measurement byprobabilistic prediction (McKelvie, et al., 2009). Similar to such a revelation, the implication here is that premarket entry risk falls outsideuncertain conditions and into measurable and predictable risks. Due diligence discovery mayfind risks previously determined as uncertain subject to probabilistic measurement and movethem into the category risks Parhankangas and Hellstrom (2007) referred to as antecedent risks.For example, Heukamp, Liechenstein, and Wakeling (2007) proposed that angel investors whocontribute time and experience to a new venture should improve the view of risk by co-investingwith venture capitalists. To test the theory that co-investment improves the view of risk, a sample of 173 VCsfrom German-speaking countries yielded 129 (75%) respondents to a mailed questionnaire andfollow-up phone calls (47 of the 129). Of the 129 respondents 59 completed the questionnaire fora participation rate of 34%. The results found that co-investment with business angels (BA) didnot reduce the sensed risk of co-investing with BAs despite the finding that VC goals align
  • 58. 46increasingly with BA goals. The final finding revealed that co-investments do not necessarilyresult in higher returns than when a VC invests on its own. In such case, antecedentpreinvestment by BAs proved not to improve risk perception of VC investors or result in anygreater returns (Heukamp, et al., 2007). Such a surprising finding goes against the notion thatsharing risk reduces the risk of loss. For example, investment bankers form investmentsyndicates to avoid concentrating risk. Although this finding applies to risk rather thanuncertainty, the result is consistent with McKelvie et al.’s (2009) finding which applies touncertainty showing experience tends not to moderate losses. Further, this finding supports Readet al. (2008) who noted that successful entrepreneurs rely on effectuation to deal with uncertainconditions by taking smaller, more deliberate steps within the founder’s means. Read et al.suggested that when uncertain conditions are present, effectuation may work in tandem with riskcutting strategy. Read et al. further noted the skill displayed by successful entrepreneurs in usingeffectuation is consistent with Knight’s (1971) characterization of the entrepreneur in the abilityto deal with uncertainty. In other words, as Read et al. described effectuation, “Entrepreneurialexpertise… equals expertise in uncertainty” (2008, p. 10). Although the Heukamp et al. (2007) did not find any benefit to early detection andplanning for risk, Zsidisin, Ellram, Carter, and Cavinato (2004) asserted that addressing riskearly in a supply chain reduces the likelihood of supplier disruptions. Zsidisin et al. (2004)conducted a case study analysis of different groups of companies and the policies used to detectsupply risk. The companies included two aerospace industry manufacturers, two semi-conductormanufacturers, and a cellular phone manufacturer. Zsidisin et al. inferred that risk identifyingmeasures can reduce the likelihood of supply chain disruptions by creating an earlier awarenessof risks so the firm can avert addressing them reactively or after a problem happens.
  • 59. 47 Because the conflicting results, Heukamp et al. (2007) may have had other motivationthan the five manufacturers studied by Zsidisin et al. (2004) as a venture capitalist likely did notwant to share participation in an investment with a business angel, but each of the firms studiedin the supply chain environment benefited from the early attention to risk management. Further,the venture capitalists may have believed the added concentration of risk on an investmentwarranted a greater eventual return because business angel participation would dilute the venturecapitalists’ return. Because of Parhankagas and Hellstrom’s (2007) results that venture capitalistsare more risk seeking than other types of investors, such an observation is not unreasonable.Such an observation is also consistent with Wiltbank et al.’s (2009) results that investors seekinglarger returns invest larger amounts, but rely on prediction to achieve higher returns rather thanusing control techniques. Investors with an appetite for more risk would benefit from predictingpremarket entry risk to evaluate investing larger sums. Not only should one take the view of the investor into consideration in detecting theinfluence of risk reluctance on early stage decision-making, but the entrepreneurial risk-takershould also garner attention. Leaptrott (2007) performed a study involving a hierarchalregression of a sample of 648 entrepreneurs in the childcare industry with a response rate of29%. Leaptrott noted that successful venture creation relies on founders who not only launch theorganization, but manage the organization. Leaptrott found that entrepreneurs characterized by ahigh need for knowledge and reasoned decision-making proved more successful in launching astart-up. Such individuals spent more time in planning and evaluating information than inmaking quick emotional decisions, especially in the early stages of a firm’s organization. Suchresults are consistent with Wiltbank et al. (2009) who stressed the use of control for more riskaverse investors. Because owners manage more than 85% of most small businesses (Dimarob,
  • 60. 482005), and only 23% have a business degree, the influence of knowledge takes on majorimportance as a predictor of success (Leaptrott, 2007; Schweitzer, 2007). In line with the notion that improved knowledge results in greater incidence of success,the Leaptrott (2007) study also revealed that a correlation existed between sales growth andentrepreneurial knowledge. The study also confirmed previous results that improved capitalcontributions led to higher success rates (Cooper, Folta, & Woo, 1995; Leaptrott, 2007). Thusthe typical entrepreneur without the need for knowledge may not seek expert help when needed,but may just decide based on gut instinct (Biais & Perotti, 2008). Biais and Perotti suggested thatseeking expert advice helps the decision-making, but involves the risk of someone stealing anidea. In comparison with Leaptrott’s (2007) focus on knowledge, Read et al., (2009) assertedthat entrepreneurial experience characterized the successful entrepreneur in dealing with theuncertain conditions described by Knight (1971). Using a helix process, the researchersdeveloped schemes and coded responses from one group of experienced entrepreneurs(composed of 27 expert entrepreneurs with significant prior entrepreneurial experience).Similarly, the researchers used two groups of managers undertaking a venture for the first time.One group consisted of 37 executive managers with little experience in the entrepreneurial realmand another group of 34 senior executives with major firms without any start-up experience. Theresearchers performed further analysis using ANOVA and chi-square tests of the codedresponses. Compelling results of this analysis revealed the experienced entrepreneurial groupquestioned market data more than the two inexperienced groups and relied more on experiencethan on raw data in dealing with uncertain market conditions. Experienced entrepreneurs stressed
  • 61. 49more analysis before committing to a decision. Further evidence showed the experienced groupput more emphasis on keeping cost in line with available sources of supply. The experiencedgroup also displayed a keener focus in framing a decision (Read, et al., 2008). Although Read et al. (2008) concentrated on uncertain conditions rather than risk, theefforts of expert entrepreneurs focus on minimizing unknown circumstance by carefullyanalyzing the circumstances and deciding based on educated reasoning. Such a revelation is incontrast to Schumpeter (1975) and Baumol (1990), who proposed the sole role of theentrepreneur rests on exploiting rent-seeking opportunities and pure profits. Because both riskand uncertain conditions have a role in entrepreneurial success, the study here proposes that bothrisk and uncertainty are important in defining entrepreneurial success. Uncovering uncertainconditions through analysis can lead to a higher concentration of risk subject to management andcontrol. In this study, one of the independent variables deals with market uncertainty otherwiseknown as “market risk.”Dependent Variable: Determinants of Success According to Creswell (2005), a dependent variable represents the variable a researcheraims to explain. The objective of this study is to explain entrepreneurial success. In conductingthe study, the research procedure considers measures that trigger entrepreneurial success. Suchmeasures serve as a proxy for the more unclear entrepreneurial success rate. The researchprocedure considers several metrics to serve in such a capacity. Because risk management is part of “going public,” the procedure provides the basis forcomparison with antecedent risk management of entrepreneurs. The “going public” applicationprocedure compels the applicant to use the ratio of earnings to fixed charges defined by SEC§229.503 of Regulation C to serve as a measure to assess success. The rules define fixed charges
  • 62. 50as the following: (a) both interest charged to expense and interest capitalized on the balancesheet, and (b) amortized premiums and discounts reflected as an adjustment of debt on thebalance sheet. Fixed charges also include (c) an estimate of the interest reflected within rentexpense charged to the income statement, and (d) any dividend preference obligations ofconsolidated subsidiaries ("Electronic Code of Federal Regulations," 2009). Similarly, the lawdefines earnings by adding the following: (a) pretax income from continuing before adjustment for income or loss from equity investees; (b) fixed charges; (c) amortization of capitalized interest; (d) distributed income of equity investees; and (e) your share of pre-tax losses of equity investees for which charges arising from guarantees are included in fixed charges ("Electronic Code of Federal Regulations," 2009).Once added, take away the following: (a) capitalized interest, (b) dividends assigned topreference securities of consolidated subsidiaries, and (c) the pretax income of thenoncontrolling interest in subsidiaries not incurring fixed charges ("Electronic Code of FederalRegulations," 2009). With SEC’s ratio of earnings to fixed charges, this study relies on some alternativemeasures. Altman (1968) used ratio analysis with “discriminant analysis” to detect successfulfrom unsuccessful ventures. Altman’s study adopted five ratios to identify firms that lurked onthe brink of bankruptcy. The five ratios included (a) working capital to total assets, and (b)retained earnings to total assets. Similarly, the ratios include (c) earnings before interest andtaxes (EBIT) to total assets, (d) market value of equity to book value of debt, and (e) sales tototal assets. With the SEC’s ratio of earnings to fixed charges such ratios also serve as support todiscriminate between groups.
  • 63. 51 Related to these measures, Wiltbank et al. (2009) used internal rate of return (IRR) as ameasure to decide the success of a venture. IRR depends on the ability to predict accurate cashflows over the life of a venture. Wiltbank’s study only considered self-reported cash flowsprojected within the two years in which the researchers conducted the study. Although the studyalso relies on self-reported data, the SEC metric and Altman’s (1968) ratios provide alternativemeasures to further confirm the results. By employing alternative measures, the study providesan opportunity to make a comparison with Altman’s measures and help decide whether suchmeasures are reliable.Independent Risk Variables: Determined from Form S-1 Filings In line with defining the success of an organization as decided by the dependentvariables, Creswell (2005) described independent variables as reasons influencing the outcome,which in this case is entrepreneurial success. In the study here the proposal is the sooner anentrepreneur becomes aware of risk and begins to manage such dangers, the more likely successresults. This study employs independent risk variables determined from SEC Form S-1 filings forthe calendar year ended December 31, 2889 of firms engaged in the alternative energy industry.The instructions for SEC Form S-1 according to SEC §229.503 of Regulation C call for aminimum of the following risk variables: (a) a lack of an operating history, and (b) a lack ofrecent profitable operations. Similarly, the instructions call for (c) the financial position of thefirm, (d) risks about the specific business or proposed business, and (e) a lack of a market for thefirm’s securities ("Electronic Code of Federal Regulations," 2009). Within the individual filingsof firms in the alternative energy industry, filers have expanded on such basic risk variables. Inparticular, filers of Form S-1 have provided significant detail on the specific risks about eachunique business.
  • 64. 52 As a sample of some of the unique business specific risks, filers have included manydivergent causes. For example, some of the causes listed include the inability to gain properlicenses, lack of capital to deal with environmental laws, delays in harvesting suitabletechnology, and the means to deal with obsolescence. Similarly, other causes listed include theability to carry maintenance agreements, intense competition from well-financed competitors, theability to market products successfully, the capacity to achieve acceptance of products, and thepower to preserve intellectual property rights. Other listings include the ability to preserveeffective internal controls, the aptitude to manage future growth, and unforeseen safety issues.Last, other listings include overdependence on key suppliers, the skill to manage product liabilityclaims, the ability to earn needed regulatory approvals, and the ability to manage technologicalchanges. Although the list is not exhaustive, the list gives a good idea of the breadth of divergentrisks that are possible. In consideration of the breadth of risks involved, the study undertakes a factor analysis tofind causes of specific risk with the greatest impact in influencing the ability to predict success inthe alternative energy industry. Thurstone (1931) developed the multiple factor analysis as asupplement to Spearman’s two factor analysis to limit variables with a common features andprovide more substance in the relationships between variables. Thus factor analysis groupsvariables with a significant correlation to form one factor ("Principal components and factoranalysis," 1984-2008). Once the study completes such an analysis and discovers the main groupsof risk variables, such risk variables serve as the independent variables for discriminant analysis.Entrepreneurial Entry and Success in Green Energy Industry Entry into the green energy industry provides a ripe new industry in which to examine theinfluence of premarket entry risks and their effects on entrepreneurial success. In the face of
  • 65. 53spiraling oil prices and environmental anxiety, alternative energy has aroused the appetite ofenergy consumers. Because the United States (U.S.) depends heavily on foreign oil, energy usersface unsteady conditions, soaring prices, and continue to seek alternative energy sources totransform into electric power. Electric power affords the common denominator in energytransmission and alternative energy sources remain largely ineffectual without the ability totransfer the power to the user. Although large companies overshadow the industry because of their capital-intensivemakeup, smaller companies can effectively exploit the “green” part of the trade. Under currentconditions, the 50 largest firms of the 2,200 firms in the electric power generation industrycontrol 50% of the market. The move to deregulate the industry has fueled competition bydetaching the transfer and delivery part of the industry from the power generation part. Becauseof deregulation, divestiture of power producing plants allows the new firms entry to take part inthe market ("Industry profile: Electric power generation," 2009). Because of a changing market, the United States (U.S.) produces about 85% of thecountry’s energy from fossil fuel or nonrenewable energy sources such as gas, natural oil, andcoal. The problem with fossil fuels stems from carbon dioxide emissions that pollute theatmosphere ("The hidden cost of fossil fuels," 2008). Renewable energy sources will resolvemany of the troubles associated with consuming fossil fuels and electrical power generation byossifying fuel prices, moderating supply shortages and separation, attenuating pollution, andremoving dependence on foreign oil. The government created the renewable energy standard(RES) to provide a market-based answer to electric power generation ("Real energy solutions,"2005)
  • 66. 54 Associated with a market-based solution to resolve these issues, discovering an accurateforecast of demand will merit special attention to improve efficiency. Sanders and Ritzman(2004) claimed that a firm should balance soft demand forecasts provided by marketing with themore quantitative and hard data supplied by operations to learn possible outcomes. Marketinguses judgmental forecasting techniques such as panel consensus, opinions of management, andmarket surveys, while operations relies more on quantitative methods such as time seriesanalysis, regression, and simulations. Convergence of this information helps build more reliableforecasts (Sanders & Ritzman, 2004). Consistent with accurate demand analysis, Giancarlo (2005) viewed that studies(Barbiroli, 1996) using matrices of economic and technical data to introduce processimprovements. Such studies have shown that transformation of energy and environmentalpractices present an opportunity to gain a competitive advantage by tendering a rapid return oninvestment. Giancarlo (2005) showed that these lessons also provided improvements inproductivity and plant use rates. Such practices allow management to adopt life cyclemanagement (LCM), which offers the other benefits. For example, LCM presents theopportunity to improve product design and increase value. Similarly, LCM offers the chance torealize cost savings from process variations, and the capacity to frame improved strategicdecisions by focusing on inputs and outputs. LCM allows strengthening risk management bycutting down on environmental, health, and safety issues. LCM also presents the opportunity todiscover new product lines and services. Last, LCM provides the power to improvecommunications and public relations (Giancarlo, 2005). In line with demand analysis and the idea of LCM, Steen (2005) found the life cycleassessment (LCA) and life cycle costing (LCC) techniques occurred from the energy crisis of the
  • 67. 55mid-1970s to estimate successfully costs and their related benefits. LCC arose from the study ofcost from “cradle to grave” of a project and originated from the “polluter pays principle” (PPP).Firms less often draw on LCA to earn certification and integrate products. This techniqueconverges on uncovering impending external costs connected with products to avoid the duty topay for such costs (Steen, 2005). Just as an analysis of cost helps improve efficiency in an organization committed to“green” energy, information technology (IT) is critical to the industry. Sharpe (2009) in aninterview with General Electric’s Carlos Haertel resolved that upgrading most new projectsinvolves upgrading technology. Although massive organization’s reminiscent of General Electricrecognize keeping IT up-to-date is important, even smaller alternative energy firms realizeinnovative technology is important to detecting safety issues ("EPA awards small businesses todevelop green technologies," 2009). Updegrove (2009) noted how Congress recognized the needto update the outdated energy power grid by helping explore alternative energy production,confronting the growing dependence of foreign oil, decreasing emissions of greenhouse gases,and leveling temporary energy spike disruption. Updegrove communicated how a new “SmartGrid” will benefit users looking to transfer electric energy produced from alternative energysources. Congress provided funding for the Smart Grid in the 2009 economic stimulus package(Updegrove, 2009). Consistent with the means to transform alternative energy sources into electrical power,transmission of the converted energy depends on decentralizing information communicationtechnology (ICT). Walter (2009) recognized that alternative power generation will need a moreshared and decentralized approach to communication for these sources to integrate with oneanother. Smart meters can detect unused energy and send it back into the power grid for others to
  • 68. 56use. Jeremy Riftkin, president of the Foundation of Economic Trends, reported at the ResearchConnection 2009 conference in Prague that minipower plants calls for something similar to peer-to-peer information sharing (Walter, 2009). Although the Obama administration envisages mainly centralizing ICT (Walter, 2009),Azarbaiejani and Fahimifard (2009) pictured the communication problem as a scattered problem.Azarbaiejani and Fahimifard recommended several benefits using decentralization to collectaccurate and genuine data, promote partnering, view economic trends, and promote technologicaldiffusion and distribution. Similarly, Azarbaiejani and Fahimifard suggested a decentralizedapproach would create opportunities for market expansion, aid in pooling resources, realizeeconomies of scale in production use, and promote more efficient sharing of energy. In fact,Leong (2009) commented that Yahoo has already created a “green” IT initiative and has workedon developing a secure Web-enhanced data information center for energy in its East Asia office. Despite Yahoo’s involvement, the United States continues to take a buyer beware attitudebecause of improprieties by China aimed to control the Internet (Cannici, 2009). Yahoo, a majorsupplier of such technology, lingers under watchful legal scrutiny for aiding the Chinese incensoring the Internet. The future of “green” ICT, although it may remain on the Internet,remains suspended because of these suspicions (Bodard, 2003). On the other hand, otherdevelopers are eager to cultivate Web-enhanced energy technology. Shahrokhi (2008) explainedthe emergent trend to use e-finance. Ranjan (2008) revealed the growing trend in using sharedtechnology for business intelligence including customer relationship management. Energy firmsaspiring to enter global markets should consider using such technology to achieve a prolongedexistence and to seek comparative advantage.
  • 69. 57 Apart from the uncertain conditions confronting entrepreneurs aspiring to enter thealternative energy domain, the industry provides enough opportunities to develop a venture fromthe ground floor. The industry offers a solution to the current dependence on foreign oil and tomoderate the volatility of energy prices. Both an opportunity and the attendant risks offer anenvironment suited to examine the connection between premarket entry risks and entrepreneurialsuccess rates. Entrants to the industry seek to convert uncertain conditions into manageable risksby identifying problems and designing potential solutions to mitigate such risks. How well thosefirms perform these roles serves as the underpinning for this study. Conclusions As risk management strategies have changed, entrepreneurial students have proposedvarious theories about the high failure rates of entrepreneurs. Notable risk managementinnovations originated from Hindu-Arabic numbering. These innovations included developingprobability analysis, forecasting models, regression analysis, and other more recent innovations(Bell, 1998; Bellhouse, 2008; Bernstein, 1996; Bulmer, 1998; Ciecka, 2008; Danesi, 2005; Hon,2008; Kreager, 1988; Magnello, 1998; ORourke, 2008; Sandall, 2008). The literature hasadvanced various theories about the role of the entrepreneur in these practices (Bassiry & Jones,1993; Baumol, 1993; Kirzner, 1999; Klein, Collingsworth, Mitchell, & Lutz, 2005; Knight,1971; Mises, 1944; Montanye, 2006; Murphy, et al., 2006; Renesch, 2008; Schumpeter, 1975;Smith, 1904; Sobel, 2008; Weber, 2001; Wren, 2005). Current results linking risk-taking to theentrepreneur have explored many explanations, but few have brought together the early stagerisk awareness and management with entrepreneurial success. The intent of this study is to linkthese dimensions to discover the effects on entrepreneurial success rates. In this vein, this
  • 70. 58researcher has selected the alternative energy as an active industry in which currententrepreneurial endeavors must consider this linkage. Summary In summary, the underlying theme for this study arises from the inference the sooner theentrepreneur becomes aware of antecedent risks and begins to plan for such risks, the greater thelikelihood of an improvement in entrepreneurial success rates. Ottesen and Gronhaug (2006)noted that exploiting opportunities with an uncertain future remains a difficult task. Surprisinglylittle literature exists on why some firms succeed in the search to exploit opportunities, while themajority fail. The insights gained by exploring the problem can lead to improved success rates(Ottesen & Gronhaug, 2006). Baumol (1990) explained high failure rates result from unfavorablerules of the game leading to unproductive entrepreneurship. Leaptrott (2007) rationalized thatentrepreneurs with a lack of knowledge accounted for high failure rates. Cooper et al. (1995)offered inadequate capital contributions as justification for high failure rates. Others offered anexplanation for high entrepreneurial failure coming from overconfidence and enthusiasm thattempers sensing risk (Grichnik, 2008; Janney & Dess, 2006; Ottesen & Gronhaug, 2006;Proimos & Murray, 2006). Parhankangas and Hellstrom (2007) noticed, “interrelations betweenantecedents of risk-taking, investment decisions and risk reduction strategies still remain largelyunexplored territory” (p. 184). The intent of the study emanates from an ambition to beginexploring this void in the literature about these interrelationships. In the next chapter, theobjective is to discuss design and methods used to test theories proposed in this research study.
  • 71. 59 CHAPTER 3: METHOD Although self-employment rates have fallen in the United States from 8.2% in 1997 to7.2% in 2007, entrepreneurs represent about 30% of the top decile of wealth (De Nardi, et al.,2007; OECD in Figures 2009," 2009). Meanwhile, Finkle (2007) asserted that both primary andtertiary faculty positions for scholars in entrepreneurism have risen from 5% to 95% ofadvertised positions from 1989 through 2005. Clearly, a demand exists to help educateentrepreneurs who want to enter the market, but lack skills to ensure success. Honig and Dana(2008) explained what happens when leadership of a community allows "peripheralization"because of geographic economic constraints and failure to promote and nurture satisfactorydiversification of a community through new business creation (p. 5). Honig and Dana showedhow these conditions lead to communities of “disentrepreneurship” and dismal economicperformance (p. 5). In this chapter, the objective is to discuss the rationale for selecting aquantitative method, show why the selected method is suitable for this study, and discuss theappropriateness of the research design. Related to this objective the goal is to describe thepopulation under study, the sampling procedure and selection of a sampling frame, how the studycaptured data for testing, and the rationale for the procedure. The chapter includes discussionabout reaching both internal and external validity, the statistical method for analyzing the data,and measures taken to ensure the results are reliable. The purpose of this quantitative study is to use discriminant analysis to learn if awarenessof antecedent risks (IV) can improve success rates of entrepreneurs (DV) by early developmentof risk management strategies. Prior research on successful entrepreneurial risk-taking hasfocused on risk perception (Janney & Dess, 2006; Ottesen & Gronhaug, 2006; Parhankangas &Hellstrom, 2007), risk-taking propensity (Brockhaus, 1980; Gilmore, et al., 2004; Grichnik,
  • 72. 602008). Such research focused on prediction and control (Alstete, 2008; Delmar & Shane, 2004;Wiltbank, et al., 2009), and distinguishing between risk and uncertainty (Knight, 1971;McKelvie, et al., 2009; Milliken, 1987; Wu & Knott, 2006). This study extends prior research toinclude how the timing of risk awareness and planning influence the success or failure of anentrepreneurial venture. Firms “going public” take risk more seriously at an earlier stage andforce the firm to engage in risk management (Corwin & Schultz, 2005; Hebb & MacKinnon,2004; Singh, et al., 2007). Thus the position taken in this study hypothesizes that taking similarsteps for the nascent entrepreneur would lead to improved success rates. Such research isimportant because of the high failure rate experienced by nascent entrepreneurs. Entrepreneursplay a critical role in creating economic growth, producing employment opportunities, andmaking new innovative products and services (Banerjee & Duflo, 2008). In this chapter, the goalis to describe the research procedure and explain the protocol for the testing the researchtheories. Research Method and Design Appropriateness Noting the research in the study endeavors to test an idea, this quantitative study helpsfulfill that goal by analyzing associations between variables. In the study, the goal is to settle ifearly risk awareness and management improves the success rate of entrepreneurs. In a qualitativestudy the goal is to explore a broader central phenomenon. Unlike a qualitative study, thequantitative study uses hypotheses developed from the research variables to confirm ordisconfirm such theories through the deductive process (Creswell, 2005). In a qualitative study,variables may emerge from the review of the literature instead of identifying them beforeconducting the study. In this study, the research variables are entrepreneurial risk sources(independent variables) and success rates (dependent variable) in general terms. For example,
  • 73. 61Table D1 in Appendix D shows the dependent variable is entrepreneurial success using ratioanalysis as a proxy for success rates. In accord with the need to decide successful and unsuccessful entrepreneurs, the methodused in this study is discriminant analysis. According to Salkind (2003), multivariate analysis ofvariance (MANOVA) is an advanced statistical technique used to distinguish between twodependent variables. In this study, the objective is to distinguish between successful andunsuccessful groups of entrepreneurs by using multiple risks representing the independentvariables. Weiers (2005) defined discriminant analysis as a technique that isolates variables thatbest divides members into two or more groups. The technique predicts membership in the groupsbased on viewed or measured variables. Discriminant analysis is statistical method used todecide if groups differ from the mean of a variable so the variable can help in predicting groupmembership. This technique employs the analysis of a discriminant function that serves as arestatement of an analysis of variance (ANOVA) problem. When more than one group exists, theprocedure is identical with MANOVA (StatSoft, 2007b). As a forerunner to using discriminant analysis in this study, Altman (1968) decided fiveratios most notably contributed to distinguishing between groups of bankrupt and nonbankruptfirms in a study using discriminant analysis. Originally, Altman started with 22 ratios, but afterseveral iterations narrowed these to five ratios. The ratios used included the ratio of workingcapital to total assets (X1), the ratio of retained earnings to total assets (X2), and the ratio ofearnings before interest and taxes (EBIT) to total assets (X3). Similarly, the ratios includedmarket value of equity to the book value of total debt (X4), and the ratio of sales to total assets(X5) to define the discriminant function in which Z equals the index. Using an iterative process
  • 74. 62to discover the most significant variables, Altman arrived at the following discriminant function: Z = 0.012X1 + 0.014X2 + 0.033X3 + 0.006X4 + 0.999X5 Apart from Altman’s (1968) use of discriminate analysis, other experts have used logisticregression as an alternative for solving the same problem. For example, Mine and Hakan (2006)used a logistic model to predict corporate distress. Mine and Hakan argued logistic regressionachieved a “higher predictive accuracy” than discriminant analysis. In using logistic regression,Mine and Hakan confirmed the use of many of the same ratios used in Altman’s discriminantanalysis study. Although Mine and Hakan noted achieving a higher predictive ability by using logisticregression, a comparison of the models reveals achieving almost identical results usingdiscriminant analysis. For example, McFadden (1976) compared the two methods inferring themethods are interchangeable and the discriminant model aligns better with finding causality.Mapp (2007) credited the problem with the predictive ability of discriminant analysis to“multicollinearity” or the correlation between the independent variables. Despite this problem, discriminant analysis experts continue to use discriminant analysiswith good results. For example, Büyüköztürk and Çokluk-Bökeoglu (2008) commented thatdiscriminant analysis is a powerful multivariate statistical method finding the method accuratelyclassifies predictive variables into predetermined groups. Büyüköztürk and Çokluk-Bökeogluencouraged increased use of this method. Beside the ratios used by Altman, a few extra ratios are part of the plan in this study forother important reasons. First, the ratio of earnings to fixed charges is a ratio the SEC uses toevaluate firms applying to “go public.” Adding this ratio provides consistency with the SECmethod. Second, internal rate of return (IRR) offers one of the most widely accepted ratios used
  • 75. 63to evaluate long-term projects. Similarly, adding this ratio helps decide success or lack of successconsistent with industry practice. Using IRR, each project typically has a different life. Thisstudy arbitrarily limits life to 10 years because after this time the present value becomesinsignificant and for data collection purposes gathering more than 10 years is impractical.Similarly, a project is subject to reduced accuracy in projecting values of cash flows. As shownin Table D1 this study ignores possibly significant cash flows after 10 years. Projecting cashflows further into the future become increasingly difficult to estimate and most firms need apayback sooner making it less likely for firms to consider long-term paybacks. Similarly, various types of risks make up the independent variables, the most significantof which the discriminant analysis helped isolate in developing this study. This study consideredrisk from SEC Form S-1 for alternative energy firms filing to “go public” during the calendaryear 2009. For example, some of the different types risks uncovered in this review included: 1. The dependency on few suppliers of critical services or products may present a problem. 2. Environmental risks and rules may have an unfavorable effect on business. 3. Strong competition from competitors may create difficulty gaining enough of a share of the market. 4. Local, legal, and political risk may hinder the firm’s ability to market products. 5. Limited financing may hamper the firm’s ability to preserve the expense to uphold regulatory needs. 6. The power may not exist for the company to achieve market acceptance for products. 7. Difficulty attracting key management and board members may hinder the ability to carry out business plans and manage growth. 8. Technological changes could make products and services obsolete.
  • 76. 64 9. Safety and product liability could result in unforeseen damages. 10. The company may find gaining necessary licenses for products difficult. Related to this procedure, Altman (1968) also noted that one of the most importantadvantages of using discriminant analysis stems from the ability to reformulate a researchproblem in which many independent variables exists. Because deciding success may considerdifferent risks (independent variables), discriminant analysis allows reframing the problem withthe most significant risks. Those risks contributing to failure can also help reframe the researchproblem. Because the focus of the study looks at effects of antecedent risk on entrepreneurialsuccess rates, the method selected tests such associations between the independent variables(risks) and the dependent variables (successful and unsuccessful entrepreneurs) by relying oncorrelation analysis. Correlation analysis helps discover if any relationships exist. Classifying thedependent variable into the two groups (successful and unsuccessful) is also an integral part ofthe procedure. Discriminant analysis by using a covariate offers the most fitting method todiscover which entrepreneurs who fall into each group. Leech, Barrett, and Morgan (2007) notedthat ANCOVA and MANOVA, similar to discriminant analysis, introduces a measure (acovariate) typically to control the differences between groups. The idea is to improve thestatistical significance by controlling a variable (StatSoft, 2007b). Creswell (2005) explainedcovariates as variables “…relating to the dependent variable, but not the independent variable”(p. 285). According to Creswell, the use of a covariate allows for drawing a conclusion that anindependent variable caused or probably caused the dependent variable, which is stronger thansaying a relationship exists as in a correlation study.
  • 77. 65 Because the discriminant analysis technique introduces a covariate, the outcome of theresearch provides a stronger cause and effect statement. A stronger statement is desirablebecause once timing of risk awareness becomes obvious planning for risk management shouldfollow. Unlike qualitative methods that focus on a broad central phenomenon, an experimentalapproach undertakes to explain those variables that most closely influence success. Arguably, thevariables determined most influential help decide the risk management planning effort anentrepreneur should follow. Such a procedure aids in deciding which risk management efforts afirm should follow. Without such an evaluation, the planning endeavor may neglect the moreinfluential types of risks and deal with those that have little influence on improvement.Discriminant analysis contributes to the evaluation by building “stepwise analysis” both of thefactors contributing most to success and such factors contributing least to success (StatSoft,2007b). Another way of looking at discriminant analysis is as Altman (1968) suggested. Themethod classifies or predicts dependent variables usually considered qualitative. For example,the technique provides a mechanism to classify firms as bankrupt versus not bankrupt as inAltman’s case. In this study, this technique provides a means to distinguish between successfulversus unsuccessful firms. With an understanding of such risks contributing most to the success or failure of aventure, an entrepreneur can engage in risk management sooner to minimize the risk of failure.Such an understanding helps view those risks outside the more common opportunistic lens inwhich exploiting new opportunities traditionally has trumped risk management. Such a view putrisks in a more sensible light by focusing on risks determined most critical to achieving success.The more realistic view seeks to improve entrepreneurial success rates by achieving morebalanced decision-making in the early stages of a venture. Another goal is to transfer as much
  • 78. 66risk from the unknown (uncertain conditions) to the known (risk) to enable risk management totake place at an earlier stage, preferably before market entry. Concurrent with the planning effort, the early awareness and planning of risk helpsentrepreneurial endeavors to seek financing. Venture capitalists, business analysts, and otherfinancial institutions all benefit from gaining “investor ready” projects with risk planning andmanagement efforts already identified (Proimos & Murray, 2006, p. 23). Displaying a morecoordinated effort puts the entrepreneur in a better position to achieve financing to carry a newventure from the beginning through the venture’s maturity. In contrast to Altman’s (1968) study in which the ratios represented independentvariables, ratios serve as the dependent variable in this study as a proxy for success. Altman saida benefit of discriminant analysis arises from the ability to consider an entire profile ofcharacteristics to classify a variable into groups rather than looking at each characteristic one at atime. Altman used of ratio analysis to group firms prone to bankruptcy and firms more likely tosurvive. The objective of the study is to classify firms into groups based on characteristics aboutrisk awareness and planning by deciding what characteristics support firms that succeed andfirms less likely to succeed. Similarly, the risk factors identified in the SEC Form S-1 showmany independent variables exist. A seven-point Likert scale provides a mechanism to identifythe time at which respondents became aware of the risk factors and first started to plan for riskmanagement. Apart from the notion that ratios can serve as a proxy for success, one may question whya proxy is necessary to estimate success rates in this study. Recorded successes and failures arenecessary to decide success rates over some time. Capturing an accurate rate would call for alongitudinal study over several years. On the other hand, experts have embraced Altman’s (1968)
  • 79. 67results using certain ratios as predictors of bankruptcy. Because experts have recognized thisapproach, these ratios provide a good proxy to decide success or lack of success by entrepreneursin launching new ventures. The literature would benefit from a follow-up longitudinal study toconfirm Altman’s results in looking at these results over a time. As noted by Altman, theproblem with this approach emanates from finding entrepreneurs who have failed to discusscandidly what led to the entrepreneurial failure. Research Questions and Hypotheses An obvious disparity exists between entrepreneurs and firms that “go public” about thetiming of awareness and planning for risks that affects if a firm achieves success or failure. Suchobservations lead to the following question:Q. How does the timing of gaining awareness risk affect entrepreneurial success rates in thealternative energy industry?Such a question infers a cause and effect relationship exists between the timing of risk awarenessand management with entrepreneurial success rates (Creswell, 2005). Appendix A shows thesurvey used to evaluate each of the variables on a 7-point Likert scale by when entrepreneursfirst became aware and started to mitigate risk. The central question of the study implies thatsuccessful entrepreneurs have higher Z-scores than unsuccessful entrepreneurs. Based on theresponses from the survey, the research question infers the theories reflected in Chapter 1 andlisted in Table D2. The research procedure sought to compare the z-scores for each of the risks for membersof both the successful group and unsuccessful group to discover if any differences exist. Theexpected result is the successful group has a mean closer to earlier awareness as posed on thesurvey versus the unsuccessful group that gravitates toward the never-planned end of the scale.
  • 80. 68 Population, Sampling, and Data Collection ProceduresPopulation Identifying the entire population of entrepreneurs including both those who havesucceeded and failed is a dubious task because those who failed likely do not respond or supplycandid responses to a survey instrument. The research protocol called for contacting universityincubator programs. These programs have lists of entrepreneurs who failed, but these programsdid not wish to share this information because of confidentiality concerns. The entire populationis therefore unknown, but the expectation is the entire population is large. The entire populationwould not only include entrepreneurs in the United States, but all over the world where manyeconomic models exist. Because a large part of the population is unknown, the objective of the research plan is tofind a representative part of the population on which to generalize the results to the entirepopulation. Another reason to narrow the population to a particular piece rests in the limited timeavailable for testing and keeping the cost of managing tests or surveys in line with availableresources (Neuman, 2003). Creswell (2005) asserted that to have less error variance and preserverepresentativeness, a sample size of at least 30 is necessary.Sampling Frame Recognizing the entire population of nascent entrepreneurial ventures is too large to test,the plan entailed framing the population by nascent entrepreneurs in the “green” alternativeenergy industry in the United States. Nascent entrepreneurs included founders launching a firmor seeking financing within the first five years from the start of the firm. For purposes of thisstudy, defining the start of the firm spans a period from six months before start-up to six monthsafter start-up.
  • 81. 69 The firms in this part of the population sought to include firms listed on the U.S.Department of Energy website under the green power network. This website lists firms active ingreen power markets plus firms with renewable energy requests for proposals ("U. S.Department of Energy," 2008). The combined list of 132 firms should take in all existingparticipants (122) and firms seeking renewable energy certificates (10). The study excludes firmsin existence for more than five years or with more than $100 million in annual revenues or morethan 200 employees. The list also excludes the 20 entities listed as consumer protection agencies(20). Thus the targeted respondents include both recent start-ups and respondents preparing forstart-up. The target population includes 132 firms minus any firms found to exceed requirements.Although the precise number is undeterminable until the respondents return the survey, thesample mirrors the target population and need roughly a 70% response rate or roughly 92 of the132 firms. Because the sample targets the entire defined population, selecting participantsmirrors the target population because the random response of participants decides what firmsmake up the sample. Informed consent, confidentiality, and survey instrument. From the list, the procedureinvolved mailing a request for informed consent (Appendix B) to targeted respondents with afollow-up by phone to improve the likelihood of an acceptable response rate. According toCooper and Schindler (2002), a median response rate should approach 74% and range between50% to 94%. The plan called for targeting receipt of at least 61 respondents from the originalsampling frame of 132 firms. Altman (1968) used a sample of 60 cases in his study. The cover letter ensured respondents protection of their information by not identifyingthe firm or the source of the information individually. Respondents include “green” alternativeenergy firms found in the United States either not yet doing business or in business for fewer
  • 82. 70than five years. The procedure includes asking respondents to complete the survey instrumentincluded in Appendix A. Once the respondent completes the informed consent agreement, the survey instrumentneeds completion of a seven-point Likert scale related to the risks and requests the respondentprovide the information needed to calculate ratios. The objective of the Likert scale seeks tomeasure when the respondent first became aware of risk and started planning risk management.The danger in using a Likert scale stems from respondents expecting a response believed suitablerather than answering candidly. Neuman (2003) asserted that a Likert scale transformsqualitative information such as a person’s opinion into data usable for quantitative analysis. TheLikert scale assigns a weighting factor to show a quantitative ranking. By asking for theinformation to calculate the ratios rather than asking for the ratio itself, the intent of thisprocedure is to ensure consistent calculation and prevent misinterpretation in calculating eachratio. Despite searching for existing surveys to fulfill these goals, the search did not reveal anycompatible with the goals of the study. Thus the procedure called for designing the surveyincluded in Appendix A to meet the specific goals of the study. The design of the survey capturesboth the respondents’ recollection of when they became aware of risks and began to plan forthem and the information needed to calculate the ratios as a proxy for the dependent variable.The survey is easy to understand and does not ask for overwhelming information, which mightserve as a deterrent from completing the survey. Pilot test. To confirm this survey, the plan entails performing a pilot test with a group ofnascent entrepreneurs from Kairos Society. This organization is a national body of college
  • 83. 71students engaged in entrepreneurial projects. The intent of the pilot is to ensure the surveyachieves the reliability of the primary sample frame. Consistent with this goal, Kairos Society has supplied a listing of recent projects bymembers of the group. The next step entails asking permission to contact the members. Onreceiving such permission, the next step entailed mailing informed consent agreements and thesurvey to the pilot study respondents. The procedure called for a sample of 20 participants totake part in the pilot. These respondents are ineligible to take part in the primary study once theyagree to partake in the pilot. The primary study did not use any data collected from participantsin the pilot or influence the results in any way. Validity and ReliabilityInternal Validity According to Cooper and Schindler (2002), internal validity refers mainly to the validityof the research instrument, but history, maturation, testing, selection, mortality, and statisticalregression are also influences. History applies to events external to the experiment that couldpose a threat to validity. Maturation refers to the emotional state of the respondents changingover a time that could influence the respondent’s selections. Testing refers to more than onetreatment affecting the dependent variable. The testing affect risks the capacity to say thetreatment in the experiment caused the outcome as another treatment may have contributed to theoutcome. Mortality results from respondents dropping from participation in the study. Thus adifferent outcome may result than if that respondent had not dropped. Asking for a reason thatrespondents drop is therefore important. Statistical regression also poses a threat when extremerandom errors result from a certain condition (Salkind, 2003). An awareness of such conditionsis important for the study because the procedure cannot anticipate such conditions.
  • 84. 72 Instrumentation validity stems from whether the research instrument does what it claimsto do (Cooper & Schindler, 2002). Salkind (2003) explained internal validity as “the ability toeliminate alternative explanations of the dependent variable” (p. 251). Several types of internalvalidity exist to assess the validity of the research instrument including content, criterion-relatedvalidity, concurrent, predictive, and construct reliability (Cooper & Schindler, 2002). Content validity. Content validity shows how well the research instrument represents theuniverse of relevant items under study. A judgmental determination is necessary to evaluate thisvalidity (Cooper & Schindler, 2002). In this study, the research instrument takes risks from SECForm S-1 for firms seeking to “go public” in the alternative energy industry. The design of theresearch instrument relies on a judgment made these risks show risks normally confronted in theindustry and recognized by the SEC. Criterion-related validity. Criterion-related validity shows how well the measures used aspredictors estimate the outcome. An application of criterion-related validity arises fromcorrelation analysis. The measure used should not have a bias, preserve reliability, displayrelevance, and show availability. Concurrent and predictive validity represent two different typesof criterion-related validity as follows (Cooper & Schindler, 2002): Concurrent validity. Concurrent validity refers to the capacity of the predictors todescribe the present while measuring how well the predictors measure the outcome (Cooper &Schindler, 2002). In this study, the predictors used are risks from the SEC Form S-1, but thefirms making application self-report such risks based on the firm’s own experience. Thus suchrisks are relevant to the firms, available to the public, and unbiased. Predictive validity. Predictive validity shows the ability to predict an outcome over thepassage of time (Cooper & Schindler, 2002). Because this study is not a longitudinal study,
  • 85. 73predictive validity is irrelevant. As noted previously however, a longitudinal study would helpconfirm the results over a time. Construct validity. Construct validity tries to answer whether the association accuratelyportrays the underlying construct (Cone & Foster, 2006; Cooper & Schindler, 2002). In thisstudy, the discriminant analysis serves to test the construct validity by using the predictors toclassify respondents into groups of successful and unsuccessful entrepreneurs. Construct validityrelies on attitude scales such as the Likert scale used to evaluate the risks in this study. In thisstudy, the Likert scale reflects the timing applied to each of the risks. The distributions of theintervals are equal and conform to the expected launch period.External Validity In contrast to internal validity, external validity results from the capacity to generalizeoutcomes across time, settings, and people (Cooper & Schindler, 2002). Salkind (2003)described external validity as the power to generalize results of an experiment in terms externalto the research experiment. External validity deals with realism in two different forms. First,experiment realism explains the ability to generalize the results by how sensible a treatment is.For the experiment in this study, the treatment emanates from the timing of the risk awarenessand planning. Thus such validity assesses whether the time dimensions are sensible for gainingan awareness of the risks and planning to mitigate such risks. Second, mundane realism decideswhether the treatment resembles conditions in the real world (Salkind, 2003). Based on the analysis of risk perception and the inability of entrepreneurs to prepareadequately for investors, the assumption in this study is that sensible conditions are present tojustify the use of such time dimensions. Launching a new venture usually takes three to fiveyears. The time dimensions used in this study conforms to the time an entrepreneur takes to
  • 86. 74launch a new venture. The intervals used in the study range from startup in 12-month incrementsto five and a half months with anything beyond this time frame suggesting that no early planningfor risk took place during the launch period. Although the interval appears realistic, the Hawthorne affect poses a bigger threat tovalidity. The Hawthorne affect emanates from respondents anticipating that a certain answer isbest. Certain respondents may not provide candid responses, which would threaten the validity ofthe results. Similarly, demand characteristics may threaten the validity of the results ifrespondents react to the survey based on how the respondents see the outcome. For example, if arespondent is sympathetic of the research theories, that person would answer the survey in a wayto support the outcome of the study. One other possible threat stems from a placebo affect wherea respondent reacts with an outcome expected because of applying the treatment (Salkind, 2003).Reliability Newman (2003) described reliability as the capacity to achieve consistency under similarcircumstances. A small pilot study helps ensure attainment of this goal. Such a pilot study is partof the plan for this study. Stability reliability. In harmony with the goal of achieving reliability, Neuman (2003)explained three kinds of reliability. The first of which is the capacity to achieve stability over atime. In other words, the survey and testing should achieve similar results over the course ofdifferent periods. The pilot survey seeks to show such reliability before sampling the primarysampling frame (Neuman, 2003). Representative reliability. Representative reliability aims to achieve consistent resultsamong alternative subpopulations. The sample from Kairos Society is different enough from theprimary population from the U.S. Department of Energy listing (Neuman, 2003).
  • 87. 75 Equivalence reliability. Equivalence reliability measures consistency when the samemeasures yield similar results across different groups (Neuman, 2003). Because the survey usesmeasures widely accepted across different industries, the design of the study is such the expectedcomparison of the pilot group with the primary group should gain a high degree of equivalence.For example, ratios gathered from audited financial statements prepared using generally acceptedaccounting principles and risks taken from SEC form S-1 provide measures widely used. Suchmeasures help ensure equivalency both within the “green” energy industry and across otherindustries. Most important, the design of this study takes advantage of all the ways Neumansuggested for improving reliability. Such techniques include having clear ideas, using precisemeasures, offering multiple indicators, and engaging in pilot tests (Neuman, 2003). Carefullychecking this procedure with an awareness of threats to reliability is important for a successfulresearch study. Data Analysis With these concerns in mind, the procedure includes gathering the data collected from thesurvey of the sample population and tabulating it on spreadsheet to import into SPSS foranalysis. Entering the data first into a spreadsheet serves the purpose of making it easy tocalculate consistently the ratios needed for the analysis of the dependent variable. Because theinformation collected is not the ratio itself but self-reported data from the most recent audit orannual financial statement, using Excel helped simplify calculating the ratios consistently. Thisprocedure also simplified scanning for false data. For example, if a respondent uses the samenumber for earnings as for gross revenues, the procedure would raise a red flag that someoneconfused the terms. If an error occurs, the procedure mandated either asking for corrected
  • 88. 76information or removing the respondent from the sample. Similarly, missing data called for thesame procedure to ensure consistency. If abnormalities such as extreme values or outliers exist,the sample excluded the information for that respondent. The data collection procedure included assigning a company number to each respondentto preserve confidentiality of the respondents. An individual respondent only is identifiable onlyby cross-reference to the original response. Thus this routine protected respondents by notrevealing any association with the study. Besides the ratio information, the procedure called for tabulation of the risk responses. Assuggested, the procedure used a seven-point Likert scale capturing responses for each risk withcategories ranging from “planned during inception” to “never planned” to gain an awareness ofthe timing for each specific risk category. On completing the tabulation the procedure called forimporting the data to SPSS and running descriptive statistics and a correlation analysis. After running the basic statistics, the research procedure relied on factor analysis todecide on a manageable number of variables and to help assess the makeup of the variablesnecessary to classify such variables into groups. Two types of factor analysis exist. Confirmatoryfactor analysis allows testing theories about the factor composition for a group of variables. Thistechnique allows for a comparison of samples across samples. Correspondence analysis is adescriptive technique used in exploratory applications to analyze the association betweencolumns and rows to analyze two-way and multiple-way tables with some measure ofcorrespondence. In this study, the idea is to combine variables into one variable by assessing thecorrelation between two variables and plotting a line of best fit to portray the “essence” of thetwo variables together. The procedure used Eigenvalues to decide the percentage of variancecaused by each variable. This technique aided the subjective determination of how many
  • 89. 77variables to keep when little variability existed from the remaining random variables (StatSoft,2007c). After settling on a suitable number of variables, the next step in the plan called forrunning discriminant analysis. As noted earlier, discriminant analysis is similar to MANOVA,which relies in a two-group case on a linear equation in the following form: Group = a + b1*x1 + b2*x2… bm*xmwhere a is a constant, x1 through xm represents factors, and b1 through bm represent regressioncoefficients (StatSoft, 2007b). Altman’s (1968) discriminant function mirrored this equation asnoted previously. With an understanding of this multivariate linear equation, two key assumptions underliecomputing discriminant analysis. First, the data represented in a sample take on a normalmultivariate distribution. Second, the variance and covariance matrices of variables preservehomogeneity across groups (StatSoft, 2007b). These assumptions underpin the predictive powerof assigning cases to groups, which is the purpose of discriminant analysis. To test the null hypothesis, the analysis intended to use z-scores. The procedure called forcalculateing a z-score by subtracting the mean of the scores from a raw score and dividing by thestandard deviation. Because z-scores have a mean of zero and between three standard deviationsabove and below the mean represents 99.74%t of all members of a group, amounts above orbelow three standard deviations do not conform to the characteristics of the group and can rejectthe null hypothesis (Isaac & Michael, 1995). By comparing the hypothesis and the raw score foreach variable to its z-score this procedure intended to serve as the basis to accept or reject thenull hypothesis.
  • 90. 78 Summary In summary, this chapter described discriminant analysis as the research method mostsuitable to perform a quantitative evaluation of research variables to allow for the classificationinto groups (Altman, 1968; StatSoft, 2007b). The plan provided for a sample of entrepreneursfrom the emerging “green” alternative energy industry and designed techniques to preservereliability and validity for running a survey. The plan relied on three kinds of reliability includingstability, representative, and equivalence (Neuman, 2003) In this study, the goal sought to decideon predictors of successful and unsuccessful groups of entrepreneurs. Discriminant analysiscarried out this goal by classifying cases into groups to resolve how an awareness of risk and riskplanning may act as predictors by using a time dimension. The research plan also called fordescribing how test procedures such as Wilks’ lambda and Box M helped ensure the studypreserves a suitable significance (Bartlett, Simonite, Westcott, & Taylor, 2000; StatSoft, 2007b).Finally, the plan for this study provided a basis for analyzing data to achieve reliable results. Thenext chapter detailed the procedures for analyzing the results from the data gathered in thecollection procedure and summarized in SPSS.
  • 91. 79 CHAPTER 4: COLLECTION AND ANALYSIS OF DATA The purpose of the research is to settle how the timing of risk management influencesdispelling antecedent risks in the success of a venture. Chapter 3 aimed to describe the procedureto classify companies into successful and unsuccessful groups using discriminate analysis. Theprocedure called for looking at the influence of timing risk management in dealing with differenttypes of risk. The information gathered from survey participants provided data on the when thesecompanies started to deal with these risks. Archived data from companies’ annual reportsprovided information to calculate financial ratios used to classify the companies into successfuland unsuccessful groups. In this chapter, the goal is to explain gathering and analyzing the data. To carry out thisobjective, the study called for collecting suitable data and analyzing it using discriminantanalysis. Data collection starts with testing the data collected from the completed surveys. Theprotocol calls for testing the survey design to decide if it effectively captures the neededinformation and reports reliable information for use in data analysis. The procedure for datacollection involves resolving any inherent limitations uncovered in pilot testing and decidinghow to deal with these problems. After resolving these issues, the procedure calls for examiningthe data to make sure of its adequacy for use. Clean data precedes statistical analysis to ensureaccuracy (Neuman, 2003). The procedure calls for testing the research hypothesis and decidingon the validity and significance of the test measures. Because of the absence of an existing survey instrument, the survey instrument used inthis study needed some testing. Although the procedure for testing the survey instrumentrightfully belongs in Chapter 3, discovery of the need for testing did not take place until datacollection began. Discussion of these procedures follows in the Pilot Study section.
  • 92. 80 Pilot Study Before collecting data, a pilot study plan called for testing the survey instrument todiscover its reliability. This step provided an opportunity to fine-tune the instrument sorespondents could understand it and report accurate data. Originally, the plan had expected to useKairos Society to draw participants from this group for the pilot study, but this group declined totake part in the study. Kairos Society is a national student entrepreneur group. As an alternative,an alternative approach looked to test the survey instrument included giving the two-page surveyto nascent firms in the energy industry that did not have their own renewable energy certificates(RECs). The respondents came from members of the American Wind Energy Association(AWEA) website or from the Securities and Exchange Commission (SEC) website by searchingrecently filed Form S-1s for energy companies. The procedure entailed checking The Department of Energy website planned for use inthe main study to make sure pilot study companies did not appear on the list of companiesholding RECs. Calls made to 81 companies resulted in just five companies willing to take part inthe survey. Many of the companies expressed an unwillingness to supply financial information.A one-page survey deleting the financial information from the original survey became necessarybecause of the unwillingness to supply this information. The Department of Energy website usedfor the primary study listed companies that both had already gone public and had financialstatement information as part of their 10-K filing. For these companies, the requested financialinformation did not make a difference because the SEC website made the information readilyavailable. The Department of Energy website also listed nonprofit companies, privateassociations, and private cooperatives with RECs. These organizations made RECs available tomembers, but this study excluded them because of their nonprofit status.
  • 93. 81 The presence of RECs showed companies had existing revenue streams compared withthose companies without RECs. A survivor’s bias may exist because the study excludes smallercompanies without RECs less likely to survive. Many of these companies expressed anunwillingness to engage in the survey citing a lack of financial information. To some extent thisbias is offset by larger companies using RECs from one of these excluded organizations. Despite these limitations, the pilot procedure tested reliability using Cronbach’s Alpha.This test measures internal reliability and is common when using a survey that gathers severalLikert-type items to report a composite score. The results show a Cronbach’s Alpha score of0.825 after removing the strong competition risk factor that had a zero variance. A Cronbach’scoefficient score above 0.7 provides a reasonable sign that internal consistency exists in the scalemaking it reliable. Above a score of 0.8 suggests the scale is substantially reliable (Forza, 2002;Leech, et al., 2007; Neuman, 2003). Besides using Cronbach’s Alpha, the study called for asking AWEA respondents aboutthe survey questions to resolve the clarity of both the instructions and the questions. The protocolalso queried respondents about any problem involved in misunderstanding how to answer and iftaking the survey in the form given posed any problems. The responses revealed no problems inany of these areas. Forza (2002) recommended this procedure as a way to pretest a self-administered survey instrument. Limitations The pilot study revealed several limitations. First, the size of the original sampling framedid not include enough entrepreneurial firms to achieve the needed results. Second, only thelarger public firms could take part in the study because smaller firms did not want to sharefinancial data. Third, the survey instrument would improve by excluding financial information
  • 94. 82because the data is readily available for public firms. Another limitation found during the datacollection revealed difficulty in reaching enough respondents willing to complete the surveys.More exploration of willing participants for the study should have taken place before conductingthe pilot survey. Additional exploration might have brought the difficulty in achieving a suitableresponse rate to light earlier. This step would have provided an opportunity to look for otheralternative groups to survey. The original sample of 132 organizations included nonprofit organizations and privateassociations that did not fit the profile of a for-profit entrepreneur. The sample also includedprivate companies unwilling to share financial information. Because of this problem, broadeningthe sampling frame became necessary. The new sample included all industries and not justalternative energy. This population consisted only of public companies headquartered in theUnited States that filed to go public within the last 10 years and excluded subsidiary companies("Build A List," 2010). Although the original sample focused on alternative energy companies, the pilot studyfound few of these companies willing to engage in the study and supply suitable data. In bothcases, the procedure called for using a stratified sample because of drawing the sample from alarge population based on certain variants. Stratified sampling is a subpopulation based ondefined yardsticks that helps define a more representative population with a smaller samplingerror (Neuman, 2003). Within this new subpopulation the plan called for using the entire 443companies. Israel (2009) asserted that using the entire census of a subpopulation removessampling error, but calls for sampling the entire population to gain an acceptable precision level. The new procedure called for mailing an invitation to participate to all 443 companies. Aseries of four mailings included the chief executive officer, chief financial officer, chief
  • 95. 83operating officer, or another company official such as an investor relations representative. Thenew procedure called for a follow-up e-mail and phone call to each company. Once the mailingswent out to the 443 companies only 30 companies replied with usable data resulting in aresponse rate of 6.8%. Neuman (2003) asserted the response rate is the product of the locationrate, contact rate, eligibility rate, cooperation rate, and completion rate. The procedure realized a100% location rate, contact rate, and eligibility rate. However, only 6.8% of the respondentscooperated by completing the survey. Alexander and Wynia (2008) asserted that nonprobabilitytype surveys are neither inferior nor superior to more probabilistic surveys. Each type hasinherent limitations and strengths. The low response rate weakens the ability to generalize theresults to the entire population of entrepreneurs. A survivor bias also hinders the results because the procedure found only publiccompanies willing to engage in the study. This study made no other try to distinguish success orfailure based on organizational size. Future studies examining the differences between publicand nonpublic companies could help gain an understanding of size and organizationaldifferences. Factor Analysis Because the original plan called for using two extra variables to separate cases intosuccessful and unsuccessful groups, factor analysis offered a way to test a new discriminantfunction. Factor analysis looks at variables to discover which ones hang together to reduce thenumber of variables (Leech, et al., 2007; Principal components and factor analysis," 1984-2008).During the pilot study the plan dropped the internal rate of return variable from considerationbecause of the inability to collect the needed financial information from respondents. The
  • 96. 84remaining variables included only the ratio of earnings to fixed charges as an extra variable fromthose used in Altman’s (1968) study. Although at this point the reduced number of variables did not need factor analysis, theprotocol called for running this procedure. Factor analysis confirmed Altman’s conclusion usingthe original five variables to classify the firms into the successful and unsuccessful groups. Thefactors Altman (1968) used for classification included (a) working capital to total assets (b)retained earnings to total assets, and (c) earnings before interest and taxes to total assets. Altmanalso included (d) market value of equity to book value of debt, and (e) sales to total assets. Afterremoving internal rate of return (IRR) the only other variable the study called for is the ratio ofearnings to fixed charges. Because Altman (1968) used these variables, this study used exploratory factor analysismethod to confirm these variables are still relevant. Some investigators use the principalcomponents method of factor analysis to reduce many variables to a more manageable number ina frugal way (Leech, et al., 2007). Although principal components analysis revealed thepossibility of reducing the factors in this study down to three, Altman’s original five variablesstill results a manageable number of components. Although the principal components method narrowed components to three variables,exploratory factor analysis confirmed Altman’s (1968) five ratios as valid to predict companies’membership in successful and unsuccessful groups. An eigenvalue is a measure used to explainhow much variance a variable explains. According to the Kaiser criterion, only variables with avalue greater than 1.0 are useful in explaining variance. A value under 1.0 means the variableexplains less than one variable should explain. Such a variable is not useful. Table D3 shows outof 16 variables only five with early Eigenvalues that exceed 1.0 (Leech, et al., 2007; StatSoft,
  • 97. 852007c). These variables are the same as determined by Altman. The results confirm Altman’sratios are still valid in discriminating between successful and unsuccessful companies. Another way to look at the results is to plot the Eigenvalues for each variable on a ScreePlot. The Scree Plot in Figure 1 shows after the first five variables the Eigenvalues start to flattenout and contribute less to explain the variance because their values are less than one. As noted inTable D3 in Appendix D, the first five variables explain 73% of the variance for all 16 factors.However, the Kaiser-Meyer-Olkin test of adequacy rests on the borderline at 0.471. This testconsiders measures under 0.5 inadequate. Bartlett’s Test of Sphericity is another test used to testthe reasonableness of factor analysis. A value less than 0.05 points to a high correlation amongthe variables and gives a reasonable hint the factor analysis is valid. The Bartlett score resulted ina significance of 0.000 showing a high correlation among the variables and enough to provide areasonable basis for factor analysis (Leech, et al., 2007; StatSoft, 2007c).Figure 1. Scree Plot of Eigenvalues
  • 98. 86 Because correlation is important to serve as a basis for factor analysis, Table D4 inAppendix D shows the correlation between the variables. The table shows all 16 components.The analysis considers a high correlation to exist for amounts plus or minus 0.60 or greater. Lowcorrelations exist the closer the number is to zero (Leech, et al., 2007). Despite confirming the original factors’ predictive ability, the analysis consisted of a mixof ordinal and scale variables. Z-scores only apply to the parametric scale variables because z-scores rely on uninterrupted scale variables falling into a normal distribution. Nonparametricdata may not result in a normal distribution and call for using other types of tests to comparedata. The central tendency theorem relies on a normal distribution (Weiers, 2005). Z-scores areuseful only for the ratio data for classifying companies into groups but not the nonparametricdata. Thus this study does not consider nonparametric Likert-type data for classifying thecompanies into groups. Discriminant Analysis Although the nonparametric data is useless for discriminant analysis, the parametric datafrom the ratio analysis is useful and serves to test the classification into successful andunsuccessful groups. The discriminant procedure initially called for classification of cases intosuccessful and unsuccessful groups using z-scores. This procedure called for calculating a z-score for each case based on Altman’s (1968) discriminant function. Altman’s discriminantfunction considers z-scores of 3.0 and above safe, and those scores in the “zone of ignorance”between 1.81 and 2.99 as questionable and where misclassification is likely to occur (p. 606). Z-scores below 1.81 clearly are unsuccessful firms. This study considers the ignorance zone firmsunsuccessful to make the first try at classification. The zone of ignorance included only one ofthe 30 cases with a z-score of 1.95.
  • 99. 87 Table D5 in Appendix D shows the z-scores for the 30 cases responding to the surveyedcompanies classified as successful and unsuccessful. The z-scores classified 10 of the 30 casesas successful and 20 unsuccessful. The procedure called for calculating each ratio from the mostrecently available 10-K report either on the company or SEC website. The discriminant analysis procedure using SPSS provided descriptive statistics for eachgroup and in total for all cases. SPSS calculated the mean and standard deviation. The mean orarithmetic average provides a measure of central tendency. A mean usually associates with aconfidence interval or p-value, which depends on the sample size and variability of the data. Thestandard deviation is a common measure of variability (StatSoft, 2007a). Table D6 shows thesestatistics for each predictor variable used to classify cases into successful and unsuccessfulgroups. The four predictor variables are working capital to total assets, retained earnings to totalassets, EBIT, market value of equity to book value of debt, and sales to total assets. In Figure 2 scatterplot matrices shows the likeness in the variability of each variablebetween the two groups. This condition suggests the matrices meet the homogeneity of variance-covariance assumption.Figure 2. Scatterplot Covariance Matrices for Each Group
  • 100. 88 In running the discriminant analysis procedure with SPSS, others tests such as Box Mand Wilk’s Lamda tested homogeneity of covariance. Box’s M shows a significance of 0.000suggesting not meeting the homogeneity of covariance assumption and the presence ofnonnormality. Although this test suggested nonnormality, Wilks’ Lambda shows a significanceof 0.013 signaling the predictor variables discriminate enough between the groups. A structurematrix shows the correlations of the independent variable with standardized canonicaldiscriminant functions in order of size in Table 1 (Leech, et al., 2007).Table 1Structure MatrixSales to total assets 0.413Working capital to total assets 0.308Earnings before interest and taxes to total assets 0.244Retained earnings to total assets 0.213Market value of equity to book value of debt 0.061 Each variable has a weighting factor showing how heavily the discriminant functionweighs each variable. Table 2 shows the standardized canonical discriminant functioncoefficients reflecting this weighting. In this analysis, working capital to total assets, earningsbefore interest and taxes, and retained earnings to total assets are the variables with the greatestweightings.Table 2Standardized Canonical Discriminant Function CoefficientsWorking capital to total assets 1.337Retained earnings to total assets 0.815Earnings before interest and taxes to total assets 1.032Market value of equity to book value of debt 0.418Sales to total assets 0.455
  • 101. 89 The test of equality of group means show that none of the independent variables aresignificant predictors by themselves. Table 3 shows the results of this test. The test of equality ofgroup means shows the variables with the most significance by themselves as predictors. Forexample, the ratio of sales to total assets has a significance of 0.067. Although this significancelevel is above p = 0.05 its significance level is close to 0.05. The market value of equity to thebook value of debt has the least significance as a predictor of these variables.Table 3Tests of Equality of Group Means Wilks Lambda F df1 df2 Sig.Working capital to total assets 0.933 2.017 1.000 28.000 0.167Retained earnings to total assets 0.967 0.966 1.000 28.000 0.334Earnings before interest and taxes to total assets 0.957 1.260 1.000 28.000 0.271Market value of equity to book value of debt 0.997 0.078 1.000 28.000 0.782Sales to total assets 0.885 3.624 1.000 28.000 0.067 Discriminant analysis shows two types of effect sizes. First, Wilks’ Lambda describes thevariance for the entire analysis using the formula η2 = 1.0 – λ1/3 = 1.0 - 0.5691/3 = 1.0 - 0.87 =0.13. According to Leech et al.(2007), this effect size is small for the entire analysis. Second, tofind the effect size for the variance related to each discriminant function calls for squaring theCanonical correlation value found in the Eigenvalues table provided by SPSS. In this case, thereported value is 0.657 and 0.6572 = 0.431. Table 4 shows the classification results. This analysis shows the model predicts only 10of the 30 companies surveyed will achieve success. The analysis predicts the remaining 20companies are not going to reach success. Further, the analysis shows the original classification
  • 102. 90of the cases into groups is 80% correctly classified. The discriminant model predicts two morecompanies from the original 20 classified as unsuccessful will fall into this classification.Table 4Classification Results Predicted Group Membership Group Successful Unsuccessful TotalOriginal: Successful 6 4 10 Unsuccessful 2 18 20 Total predicted 8 22 30 % Successful 60.00% 40.00% 100.00% % Unsuccessful 10.00% 90.00% 100.00% Discriminant analysis assessed if the five predictor variables could distinguish successfulcompanies from unsuccessful companies. This analysis relies on the assumptions that linearrelationships exist between all pairs of predictors, multivariate normality exists within groups,and population covariance matrices for the predictor variables exist across groups. For example,Wilks’ Lambda showed a significant result in which λ = .569, x2 = 14.387, p < .05, partial η2 =.13. The results show the five predictor variables significantly discriminate between the twogroups. Table 2 showed the standardized function coefficients suggesting working capital to totalassets, earnings before interest and taxes, and retained earnings to total assets contribute most todistinguishing between the successful and unsuccessful groups. Table 4 showed the modelcorrectly predicted 80% of the cases. The correlation coefficients show the extent to which eachpredictor variable correlates with the discriminant function (Leech, et al., 2007).
  • 103. 91 Kruskal Wallis H Test Although the original plan called for using z-scores to decide if a difference existed in thetiming of planning for risk between the successful and unsuccessful groups, the plan called for achange. Because the survey instrument collected nonparametric ordinal data using a Likert-typescale, the alternative procedure used nonparametric tests to perform this part of the testing. TheKruskal-Wallis H Test models one-way analysis of variance (ANOVA) when testingnonparametric ordinal data. When ordinal data is present or when a violation of homogeneity ofvariance exists, the Kruskal-Wallis H Test offers a superior solution. The test is proper when anordinal dependent variable exists or when a marked violation of independent samples t testsexists (Leech, et al., 2007). Table D7 in Appendix D shows the Kruskal-Wallis H Test results. The results comparethe mean ranks for each ordinal variable. The higher the mean ranks the later a firm plans for thatrisk. Conversely, the lower the mean rank, the sooner a firm plans for that risk. The datasuggested that successful firms plan earlier to deal with strong competition, comply with laws, togain market acceptance, and gain necessary licenses. This data also suggested successful firmswait longer to plan for reliance on few suppliers, environment risks, political risks, attracting keymanagement, technological changes, and liability concerns about product safety. Summary of Results of Hypotheses Testing and ResultsResearch Question and Hypotheses Tests Although the results suggest firms plan for certain types of risk sooner than others, theresults could not answer the research question. The research question asked the following:Q. How does the timing of gaining awareness of risk affect entrepreneurial success rates?
  • 104. 92Because none of the results meet the hypotheses tests at the p < .05 significance level as shownin Table D8 in Appendix D, this study did not decisively answer the question. The results showneither meeting the null nor the alternative hypotheses because of not achieving the neededsignificance level. These results are surprising because these risks are common to most firms.Because most firms report these risks on SEC Form S-1, a reasonable expectation for a newventure is to learn from the experience of predecessor firms. The results suggest that firms do notconsistently deal with risks at a certain time. This inconsistency may arise from industry orcompany disparities about when various risks become relevant. One other possible explanation isthat different founders and managers have disparate views, priorities, and approaches for dealingwith risks. Despite these differences, dealing first with complying with laws, gaining licenses,countering strong competition, and gaining market acceptance have a high priority for the launchof a new firm. The other six risks, although important, do not appear as pressing to the firm rightfrom the start. The firm might set aside these risks to deal with as they become more relevant.Except for gaining market acceptance the other three higher priority risks show a greatersignificance level to support this idea. Besides these risks, discriminant analysis revealed firms even after “going public” stillkeep a high risk of failure. “Going public” does not appear to make a significant difference inallaying risks. The discriminant analysis results predicted 22 of 30 firms in jeopardy ofbankruptcy. The results showed only one firm in the “zone of ignorance” or on the borderline(Altman, 1968). Again these results are surprising because one would expect a greater view ofsuccess by investors buying the securities when “going public.”
  • 105. 93Limitations Because the 443 companies targeted in the sampling frame yielded only 30 participants,the study faced a severe limitation hampering the results’ significance. The reasons given byfirms for nonparticipation included not wanting to reveal insider information, a lack of time torespond to the survey, and that risk is too sensitive an issue. The ability to achieve a largersample with an improved response rate would help decide if the results are fair withinsatisfactory significance levels. Without these improvements, a generalization to the entirepopulation is not possible, and the results are inconclusive. Although the results could not answer the research question, the study revealed someinteresting information. The results showed public firms had a 73.3% failure rate. The ability tocalculate a failure rate for private firms faced a significant limitation because of the absence offinancial ratio information. Because of this limitation the study could not draw a comparisonwith private firms. The public firms having such a high failure rate is surprising considering theunderwriting process makes the firms aware of these risks. Summary In this chapter, the goal is to explain the data collection and analysis procedure. The datacollection procedure started with a pilot study to check the data collection procedure anddiscover the reliability of the survey instrument. The pilot study called for assessing if the datacollected meets the needs of the statistical analysis protocol. The pilot study revealed severallimitations related to the sampling frame causing selection of a broader sample from analternative population. Even after quadrupling the size of the sampling frame, the response rateposed a significant problem because of the sensitivity of the information requested. The dataanalysis procedure used confirmatory factor analysis to test the predictive power of the variables
  • 106. 94used to classify cases into successful and unsuccessful groups. Once confirmed, the procedurecalled for using z-scores to classify cases into successful and unsuccessful groups. Thisprocedure allowed discriminant analysis to assess the correct classification of the cases. Becauserespondents reported nonparametric information on the survey instrument parametric theprocedure could not use parametric data to perform hypotheses testing. The procedure used theKruskal Wallis H Test instead of z-scores to perform hypotheses testing. Kruskal-Wallis workssimilar to one-way Analysis of Variance (ANOVA) and chi-square and is the propernonparametric test with which to do hypotheses testing. The hypotheses testing revealedsurprising results, and showed not meeting any of the hypotheses tests at the p < .05 confidencelevel. Because a poor response by the targeted population hindered the results, the study couldnot decisively answer the research question at the p < .05 confidence level. The study discussedthe implications drawn from these results. The objective of Chapter 5 is to review the results, discuss the results’ implications, andoffer recommendations for future study. Chapter 5 also includes a discussion of how the study’sresults clarify some of the main strands of literature about managing antecedent risks.
  • 107. 95 CHAPTER 5: SUMMARY AND CONCLUSIONS In this chapter, the goal is to provide a review of the results, discuss the implications, andoffer recommendations for future research on the topic. This study sought to test the hypothesesthat early management of certain risks improves entrepreneurial success rates. Improving successrates is good for society because entrepreneurs create jobs and contribute to economic growth(Gelderen, et al., 2006; Proimos & Murray, 2006; Sternberg & Wennekers, 2005). Uncertainty looms in all businesses as the unexpected brings about new risk-bearingconcerns. Entrepreneurs are most susceptible. As risk emerges from uncertainty an entrepreneurcan begin to engage in risk management, but risk is not always obvious to the entrepreneur(McKelvie, et al., 2009; Proimos & Murray, 2006). Entrepreneurs deal with risk as it emergesand rely less on planning and more on need. As risks threaten the entrepreneur, the individualdeals with it by trying out small trial measures to dispel the risks (Read, et al., 2009). Overview of the ResultsPilot Study The pilot study revealed difficulty faced in gathering needed data from prospectiveparticipants in the survey. The original group selected as a pilot study population declined to takethe survey because it believed members could not provide financial ratios. This belief originatedfrom the nascent stage of development of most of members. Although the plan called for sharingthe results of the study with Kairos Society, the group did not have an interest in the results.Consistent with Wu and Knott (2006), this organization’s interest came more from launchingnew businesses to take advantage of opportunities than to deal with risk. Contrary to Proimosand Murray (2006), the group’s members did not see how early risk management could helpmake them “investor ready.”
  • 108. 96 Similar to Kairos Society, members of the American Wind Energy Association (AWEA)had difficulty providing the financial data needed for ratio analysis. Although the members ofthis group had some experience, their nascent business stage made it difficult to see the benefitof achieving risk readiness so early. The concern for many of these firms resulted from the needto keep sensitive financial information private. Talking with people at these firms made clear thatfirms liked to make positive information known, but keep negative information confidential. Theresults support the idea that entrepreneurs are sensitive to negative information and only revealneeded information because entrepreneurs deal with risk as needed and when considerednecessary for a good reason. Consistent with Knight (1921), the results show entrepreneursignore risks because of not having a knowledge about how to deal with uncertain conditions.The AWEA firms showed that many firms fail to see a good reason for dealing with risk withwhich they are unfamiliar. This unfamiliarity with different risks can come from lack ofexperience or distinctive characteristics about the firm or industry. Further study in this area willhelp bring out risk from unclear and indefinite conditions.Limitations Because the original sampling frame included organizations other than for-profits and thesize of the sample could not produce enough responses, a broadened sampling frame becamenecessary. The new sampling frame just included public companies because of the unwillingnessof private companies to reveal the needed ratio information. Thus the sample lacksrepresentativeness coming from the private companies. The broadened sampling frame alsoextends beyond alternative energy as originally planned. The new procedure called for includingall industries to produce enough responses to complete the study. Surprisingly, however, theresults show a 73% failure rate for public firms. The study expected higher failure rates for
  • 109. 97private companies, but this failure rate suggests a big difference between public and privatecompanies may not exist. A survivor bias still exists because the study fails to include any firmsthat already have failed. Looking at how failed companies responded to managing antecedentrisk would also contribute to the literature and make an interesting area of future study. Another limitation of this study emerged from the inability to achieve an acceptableresponse rate. Higher response rates would improve the results’ significance. Similar to the pilotstudy, the respondents did not show an interest in releasing information about risk managementeven after follow-up by phone and e-mail. The low response rate shows public firms are sensitiveabout releasing information they are not certain about similar to the private companies in thepilot study. The public firms are just as careful about not releasing information that might reflectnegatively on them. Because public firms expose themselves to the underwriting process, the study’s centralquestion foresaw public firms having superior risk handling procedures over private firms. Theresults did not show any major benefit resulting from a public firm going through underwritingto deal with risk. The literature would benefit from studies examining more comparisonsbetween private and public firms in how they handle risk.Factor Analysis Factor analysis confirmed the factors used in the discriminant function still are valid andeffective in predicting bankruptcy or a firm’s lack of success. Although the study called foradding some more variables, the factor analysis determined the original variables are best inpredicting classification into successful and unsuccessful groups. Because only one of the 30cases fell in the “zone of ignorance” the factor analysis provided a clear line of demarcationbetween successful and unsuccessful cases (Altman, 1968, p. 606).
  • 110. 98 Although the study shows factor analysis effective, the study shows other nonparametricvariables are not effective. Because of the ineffectiveness of nonparametric variables inpredicting success or lack of success, the protocol called for removing the nonparametricvariables. A lack of a normal distribution is the main reason for the lack of effectiveness.Despite the nonparametric variables, the study had enough parametric variables to make anaccurate prediction.Discriminant Analysis Using Altman’s (1968) discriminant function, the study classified cases into successfuland unsuccessful groups. The study made the first classification by using Altman’s z-scores.Exploratory discriminant analysis performed using SPSS showed the classification using z-scores accurate. As shown in Table 4 the results of this testing showed 80% of the total casesclassified correctly. The results show four of the successful cases and two of the unsuccessfulcases wrongly classified leaving 24 correctly classified out of the 30 cases. Of the 10 casesoriginally classified as successful, the results predicted only six successful cases. Of the 20 casesoriginally classified as unsuccessful the testing predicted 18 cases as unsuccessful. The final tallyshowed eight successful companies and 22 unsuccessful companies yielding a 73.3% failure rate. Because the survey information collected consisted of nonparametric data, the testingcould not use z-scores as originally planned to test for a difference between the groups about thetiming of planning for risk. To use discriminant analysis calls for the ability to calculate z-scores.Instead the study used a nonparametric test of the group means. Kruskal-Wallis H Test is theproper test used in testing nonparametric data (Leech, et al., 2007).
  • 111. 99Kruskal-Wallis H Test When a survey uses a Likert-type scale, the data collected is ordinal because no in-between values exist. For example, financial ratio data is continuous or scale data because thedata did not consist of discrete values like one to seven on a Likert-type scale. Recall the studyused financial ratios for discriminant analysis, but removed ordinal survey data about when afirm started to plan for a particular risk. The study used nonparametric testing to isolate meanranks for successful and unsuccessful groups for each of the 10 ordinal variables. Lower groupmean ranks suggest planning started sooner, while higher group mean rates signaled planning didnot start until later. Comparing the group mean ranks, Table D7 in Appendix D shows successful firms plansooner for dealing with strong competition, complying with laws, gaining market acceptance,and gaining necessary licenses. Successful firms wait longer than unsuccessful firms to deal withthe reliance on a few suppliers, environmental risks, and political risks. Successful firms alsowait longer to attract key management, deal with technological changes, and protect againstproduct safety liability.Hypothesis Testing and Results The research question the study sought to answer is as follows:Q1. How does the timing of gaining awareness of risk affect entrepreneurial success rates?The study tested both the null and alternative hypotheses for each risk. The study reportedneither the null nor the alternative hypotheses met an acceptable confidence level. The testprocedure called for rejecting both hypotheses for each risk. A weakened significance levelresulted because the survey procedure could not capture a large enough sample.
  • 112. 100 Dependency on a few suppliers. The results did not meet the null hypothesis for Ho-1 orthe alternative hypothesis for Ha-1. This result implies varied results are possible in drawing adifferent sample of the same size. A higher mean rank for the successful group compared withthe unsuccessful group showed this group waited longer to deal with this risk than theunsuccessful group. These results suggest a firm may wait until it develops regular suppliersbefore starting to look for alternative suppliers or outsourcing as backup plans. At least initially,entrepreneurial firms do not see a threat from their reliance on a few suppliers. Environmental laws and risks. The results did not meet the null hypothesis for Ho-2 orthe alternative hypothesis for Ha-2. This result implies varied results are possible in drawing adifferent sample of the same size. A much higher mean rank for the successful group comparedwith the unsuccessful group revealed the successful group may consider dealing with such risks alower priority than the unsuccessful group. These results suggest if an entrepreneurial firm hasnot faced a problem with environmental laws and risks it puts off dealing with the issue until thefirm finds conditions more pressing. Strong competition. The results did not meet the null hypothesis for Ho-3 or thealternative hypothesis for Ha-3. This result implies varied results are possible in drawing anothersample of the same size. A much lower mean rank for the successful group compared with theunsuccessful group suggests that entrepreneurial firms place a high priority on planning forstrong competition because they start to plan sooner. Not planning for strong competition canimpede a firm’s growth. These results suggest entrepreneurs concern themselves with finding aniche in the market to exploit. Local, legal, and political risks. The results did not meet the null hypothesis for Ho-4 orthe alternative hypothesis for Ha-4. This result implies varied results are possible in drawing
  • 113. 101another sample of the same size. A much higher mean rank for the successful group comparedwith the unsuccessful group suggests successful firms do not excessively concern themselveswith legal issues and political risks. These results suggest successful entrepreneurial firms mayhold off dealing with laws and political issues until they come more clearly into focus. Regulatory compliance. The results did not meet the null hypothesis for Ho-5 or thealternative hypothesis for Ha-5. This result implies varied results are possible in drawing anothersample of the same size. A much lower mean rank for the successful group compared with theunsuccessful group suggests successful entrepreneurial firms try to deal with compliance withlaws early. These results suggest successful firms believe noncompliance can stymie theirgrowth. Complying early with laws suggest successful entrepreneurial firms sense a threat thatnoncompliance will not allow them to move forward. Because the results for local, legal, and political risks run in the opposite direction, thisoutcome makes these results surprising. One possible explanation for this result may stem fromthe need to only comply with the law and not look any farther for potential trouble. Anotherexplanation stems from the variability in the sample data collected hindering significance. Gaining market acceptance. The results did not meet the null hypothesis for Ho-6 or thealternative hypothesis for Ha-6. This result implies varied results are possible in drawing anothersample of the same size. A higher mean rank for the successful group compared with theunsuccessful group suggests successful entrepreneurial firms start to plan sooner thanunsuccessful firms in preparing for gaining market acceptance. These results suggest gainingmarket acceptable is critical to a firm for survival. Attracting key management. The results did not meet the null hypothesis for Ho-7 or thealternative hypothesis for Ha-7. This result implies varied results are possible in drawing another
  • 114. 102sample of the same size. A higher mean rank for the successful group compared with theunsuccessful group suggests that successful entrepreneurial firms delay hiring key managementuntil a firm achieves a certain sustainable level. Technological changes. The results did not meet the null hypothesis for Ho-8 or thealternative hypothesis for Ha-8. This result implies varied results are possible in drawing anothersample of the same size. A higher mean rank for the successful compared with the unsuccessfulgroup suggests successful entrepreneurial firms hold off planning for technological changes untilthe firm reaches more sustainable levels. Technology is a large investment to make without somecertainty of success. A successful firm may find it favorable to use the services of others fortechnological needs. Safety and product liability. The results did not meet the null hypothesis for Ho-9 or thealternative hypothesis for Ha-9. This result implies varied results are possible in drawing anothersample of the same size. A higher mean rank for the successful group compared with theunsuccessful group suggests that a successful entrepreneurial firm does not expect product safetyand liability issues until such issues start to happen. These results suggest when the firm doesstart to face product safety and liability issues it will begin planning for such issues. Gaining necessary licenses. The results did not meet the null hypothesis for Ho-10 or thealternative hypothesis for Ha-10. This result implies varied results are possible in drawinganother sample of the same size. A higher mean rank for the successful group compared with theunsuccessful group suggests successful entrepreneurial firms plan early to gain the necessarylicenses.
  • 115. 103 Implications of the Results Although inconclusive, the results of this study supported and clarified many ideasexisting in the literature. These ideas related to other key success factor besides risk. The resultsof this study offer entrepreneurs broad general guidelines for prioritizing and dealing withdifferent kinds of risks. For example, Table D9 in Appendix D lists the risk factors by mean rankoffering a general guideline for dealing with the types of risk looked at in this study. The tableshows successful firms deal with regulatory risk, strong competition, gaining necessary licenses,and market acceptance first. Successful firms deal with safety and product liability followed bydependency on a few suppliers, technological changes, attracting key management, anddependency on a few suppliers. These firms deal with local, legal, and political risks last. Thisranking assumes no other risks exist and drawing other samples from the population would yieldthe same results. This ranking does not consider unique differences between companies andindustries in risk handling procedures. Besides offering a guideline for prioritizing an order for dealing with risks, Table D9shows the differences between how successful and unsuccessful entrepreneurs prioritized risks.For example, unsuccessful entrepreneurs waited longer than successful entrepreneurs to dealwith regulatory compliance, acquisition of necessary licenses, strong competition, and gainingmarket acceptance. Unsuccessful firms started sooner than successful firms to deal withtechnological changes, attracting key management, political risks, and environmental risks.Entrepreneurs should find this information valuable in planning to launch new ventures tounderstand the risks in which successful firms place priority. Another benefit of the study’s results is to gain an idea about what steps might help anentrepreneur become more “investor ready” (Proimos & Murray, 2006, p. 23). If an entrepreneur
  • 116. 104knows how to assign priorities to different risks, this knowledge may benefit the entrepreneur inthe search to achieve funding. Focusing on the proper risks helps entrepreneurs see risk in thesame light as venture capitalists. With improved attention to the proper risks, the entrepreneurmay have a better chance to secure funding. Although the results of this study are inconclusive, the results support that entrepreneursdeal with risk as it emerges as needed. The timing of dealing with risk does not influence thesuccess or lack of success. Entrepreneurs with experience dispelling risk do so by trial and errorand taking small steps to reduce risk (Read, et al., 2009). Kim, Clelland, and Bach (2010) founddifferences between how experienced and more nascent entrepreneurs translate risk using theparallel processors of promotive and preventive thinking. Less experienced entrepreneurs mayoveruse promotive and underuse preventive thinking causing differences in when they sense risk.Trevelyan (2011) found a promotion orientation supports exploration, while preventiveorientations motivate more exploitive tasks and reduces entrepreneurs’ efforts in judgmentaldecision making. Entrepreneurial experience self-regulates the balance between theseorientations to find a successful mix. Experience helps the entrepreneur decide on the mixneeded to deal with a particular risk. Besides balancing judgmental orientations, the entrepreneur considers other issues criticalto success such as environmental influences. Levesque, Minniti, and Shepard (2009) showedentrepreneurs should consider the hostility in the learning environment in deciding on an idealtime to enter the market. Levesque et al. showed that learning environment hostility influencesprofit potential, and mortality risk. When an unfavorable learning environment exists theentrepreneur may find it desirable to delay entry. A more favorable learning environmentimproves performance in dealing with risk. Because market entry timing relies on environmental
  • 117. 105conditions entrepreneurs timing of risk management may vary because of company and industrydifferences. In another study, Anderson and Mellor (2009) found that risk preferences are not stable.Anderson and Mellor noted that entrepreneurial learning plays an important role in timingentrepreneurial decisions. Behavioral and cognitive differences shape opportunity recognition.Timing market entry is critical to the ability to deal with risks. This reasoning suggests that riskmanagement follows from individual differences affecting entrepreneurs at time of entry.Entrepreneurs learn to deal with risks from the conditions existing at market entry. Another theory offering an explanation for timing differences comes from expectancytheory. Holland (2011) found expectancy theory and valence helps explain entrepreneurialpersistence. The theory helps entrepreneurs decide whether to persist in the face of distress ornot. Holland argued persistence is a critical success factor to entrepreneurial success but comeswith both emotional and financial costs if the entrepreneur finds the assets used to persist havebetter uses elsewhere. An entrepreneur’s decision to persist must weigh the decision against theopportunity of using assets elsewhere. Entrepreneurs have different experiences and thejudgment about whether to persist or not vary causing timing differences. Besides differences in understanding risks, the time at which an entrepreneur progressesto the ranks of a larger corporate interest by using more elaborate planning remains unclear. Justbecause a firm “goes public” does not immediately make a company embrace planning.Although the SEC requires reporting on risks, companies do not make use of the reportedinformation. A central question of this study came from the idea that identifying risk in theunderwriting process would improve the chance of success (Corwin & Schultz, 2005; Hebb &MacKinnon, 2004). The analysis of z-scores surprisingly showed most companies still are
  • 118. 106susceptible to failure even after “going public.” A recent study of companies in Australiasupported this observation because of the discovery that “going public” increases the chance ofbankruptcy for larger public companies. Smaller more growth-oriented firms are moresusceptible to takeover. Larger firms target smaller firms because of their agility and ability toinnovate (He, Chong, Li, & Zhang, 2010; Izan, 1984). A comparison of failure rates in privateand public companies in the United States would make an interesting area of future research. Another study compared private and public entrepreneurs by redefining entrepreneurshipas driven by self-satisfaction, manipulation avoidance, uncertain environment exposure, and theneed for power decentralization. Entrepreneurship offers the benefit of innovation, risk taking,and proactive actions (Kearney, Hisrich, & Roche, 2009). Bourantas and Papalexandris (1993)reported the culture gap increases because of different commitment levels when a firm movesfrom a private to public outlook. Bourantas et al. found private firms less power-oriented, moreindividualistic, and more task-oriented, but less role-oriented than public firms. As a firm movesfrom a private orientation toward a public orientation the differences begin to moderate. Anentrepreneur launching a new venture should consider how cultural orientation influences workerinnovation, risk taking, and proactive decision making. These characteristics suggest wealthcreation is the main motivation of private firms, while wealth preservation motivates publicfirms. Because of the lack of power in firms with a private orientation, Feng and Wang (2010)found that private firms in China gain organizational legitimacy through connecting withgovernment officers. A person embarking on an entrepreneurial venture should considercompeting firms with a public orientation that amass the power to influence government officialsin its favor. Private firms need to reflect on how to gain an equivalent government outlet to gain
  • 119. 107legitimacy. Entrepreneurs may find a need for access to greater political power to moderate risks,promote innovation, and take proactive measures. Feng and Weng showed the Chinesegovernment celebrated private enterprises as largely responsible for China’s growth. In theUnited States economic growth has fallen because of government’s obvious favor for largepublic firms. Baumol et al. (2007) explained government’s attraction to large monopolies and thenegative impact on economic growth. A similar study in the United States confirmed the benefits in performance by privatefirms compared with public companies. Davis (2009) recognized private firms have theadvantage of a governance more willing to take risk risks, a long-term orientation, and the abilityto draw superior management talent. Private firms also have a greater sense of urgency, employleverage more effectively, avoid the Sarbanes-Oxley law, and sidestep shareholder suits. Davisfavored relaxing the rules on directors of public firms to avoid liability, but that approach wouldfavor large public firms and discourage entrepreneurship. Weir, Wright, and Scholes (2008)found that private equity firms concern themselves less with financial distress costs and morewith projected growth. A growth orientation contributes to the entrepreneur’s ability to deal withearly stage risks. In another study, Jin, Huixin, and Ruizhan (2010) found entrepreneurial human capital inboth high-tech and traditional settings significantly influences innovation and enterprise growth.A nation needs legitimacy of private enterprises to build economic growth and contribute toinnovative abilities, but political favor for monopolies works against smaller firms becausemonopolies by definition do not like competition. Cooke (2008) supported private firms’importance in China and identified key success factors. These success factors included emphasison product innovations, quality improvements, strategic marketing, branding initiatives, and
  • 120. 108entrepreneurial ownership. Cooke found high performing private firms used a model stressingcommitment to employee welfare and organizational culture development. This initiativesuggests firms need to motivate employees to take risks essential to growth. In harmony with private firm’s emphasis on cultural development, Altinay (2008) founda strong relationship between the religion of the entrepreneur and the people the firm seeks. Thisresult suggests culture is important to an entrepreneur. Fredette (2011) used the Muslimpopulation in France as an example in which the elite in some nations prefer to homogenizeethnic differences to larger society with a more top-down hierarchy than a more individualisticapproach. Individualism nevertheless is a factor contributing to entrepreneurial success. Hui,Csete, and Raftery (2006) studied six construction and property entrepreneurs in Hong Kong andfound support for cultural orientation as an entrepreneurial success factor. Padma and Nair(2009) found evidence that private culture firms have more committed employees than firmswith a public orientation. The studies’ results show developing a suitable culture is conducive torisk taking. Despite the evidence supporting private firm entrepreneurship, the political favor forpublic monopolies discourages entrepreneurs from taking risk without gaining needed legitimacyfrom government. Politicians in today’s economy have adopted the Kirznerian view based onlimited government and exploitation for pure profit and a limited role for entrepreneurs (Kirzner,1999). Baumol (1990) looked at entrepreneurship using a historical perspective finding historicalevidence supporting productive entrepreneurship. This view suggests an interesting area forfuture study could come from a comparison of entrepreneurial success rates during periods ofeconomic growth with rates during periods of decline. Such a study would settle if governmentempathy for entrepreneurship improves during economic growth.
  • 121. 109 Consistent with the need for government empathy for entrepreneurship, Zhang and Jia(2010) found increasing both formal and informal contacts makes for improved proceduraljustice and cooperation by the parties. Public-private partnerships can aid a government inimproving outcomes by using equity theory to improve relations through formal and informalcontracts. Bozeman and Kingsley (1998) found organizations more involved with politicians,more bureaucracy, and less interplay between promotion efforts and performance more apt tohave a less risky culture. Large public companies are more averse to risky conditions, but thepresence of public-private partnerships would benefit both public and private companies.Therefore, cooperative relations help resolve conflicts between private and public companies bypromoting risk taking needed for growth creation. Although cooperative relations are helpful, the problem runs deeper. Savino (2009)analogized the problem with how Louis D. Brandeis, one of the most prominent Chief Justices inUnited States history, championed efforts to counter corporate bigness and political corruption.Brandeis vigorously defended individualism and Taylor’s scientific management. Ironically, in1914 Brandeis criticized major banks for anticompetitive practices such as interlockingdirectorates inhibiting creative solutions. Brandeis opposed corporate mergers and consolidationsthat limited market efficiency. History shows government support for entrepreneurial risk-takingimproves during periods in which entrepreneurs can gain political legitimacy. Another area highlighted from the ratio analysis is whether investment bankers oversellinitial public offerings. The study showed that large ratios of market value of equity to bookvalue of debt go with companies’ inability to succeed. He, et al. (2010) identified studies thatconfirmed this ratio correlates negatively with a firm’s chances of bankruptcy. Platt and Platt(1990) showed that as leverage and capital intensity increase the likelihood of bankruptcy
  • 122. 110increases, while as liquidity and growth levels increase failure rates decrease. This discoverysupports the notion that a private growth-oriented firm should have a lower bankruptcy rate andthe market undervalues private firms. This undervaluation makes private firms ripe for takeover(He, et al., 2010). This reasoning suggests investment bankers drive up values in theunderwriting process worsening the riskiness to investors. Besides undervaluing private firms, He et al. (2010) noted that private firms because ofconcentrating ownership have less agency problems than public firms. Because fewer conflictsarise between ownership and management, private firms incur less agency costs. Thisconcentration of power allows the private firm more ability for flexibility and nimbleness inresponding to opportunities that involve risk taking. The literature confirms that other success factors influence when an entrepreneur sees aneed to manage a particular risk and the entrepreneur likely has little or no control over thetiming of these other factors. The entrepreneur benefits from dealing with the other successfactors first. Risk management relies on entrepreneurial insight and sensitivity to which successfactors have the most influence on the success of the firm at a particular time. The importanceattached to these other success factors can differ by person, company, and industry. Much like critical success factors, a private orientation benefits the entrepreneur byproviding a focus on growth, a culture conducive to risk-taking, and a more flexible arrangementthat avoids agency costs. Entrepreneurs work better in a culture free of bureaucracy thatencourages individualism and in which the firm spreads the power to innovate and grow. Firms are sensitive to outsiders looking at the risk they face. Although firms are sensitiveto exposing information about risks, they do not display any consistent pattern of dealing with
  • 123. 111them. The implication is that firms deal with risk as needed as they come up. Each firm may dealwith risks differently based on experience and personal views. Besides dealing with risk differently, a firm may not experience better performance bygoing through the underwriting process when “going public.” New public issues are highly riskyand investors should exercise care in buying new securities. A new public firm may not plan anymore efficiently for risk than a private firm. Another implication of the results supports the notion that entrepreneurs achieve successmore from the quality of opportunities than the ability to deal with risks. Some companies maysucceed despite poor risk management, while others do not have a chance without it. If bothsuccessful and unsuccessful entrepreneurs show no patterns in dealing with risk in such a way tohelp explain it, success is more likely explained by other reasons. For example, Elenurm andAlas (2009) found that other factors leading to entrepreneurial success include the boldness toface risk, ingenious use of information, willingness to try new approaches, creativeness, andresolve. Recommendations for Future Study Because the timing of managing antecedent risks does not influence entrepreneurialsuccess, studies on other critical success factors could help explain improvements anentrepreneur can make to improve the chances of success. Government empathy for smallbusiness is one area that deserves more attention. A study looking at the relationship betweengovernment empathy for small business and entrepreneurial success would help explaineconomic growth and contribute to the literature. Another area warranting future study is to find critical factors in transcending uncertainconditions out from the unknown and turning them into manageable risks. The sooner an
  • 124. 112uncertainty turns into a risk, the earlier an entrepreneur can decide if it warrants risk managementmeasures. Indentifying critical factors that turns unknown conditions into manageable risks mayimprove entrepreneurs’ ability to succeed. Comparing the failure rates of public and private companies would also make aninteresting future study. Such a study would help confirm the benefits and disadvantages of eachform of ownership. Each form of ownership could benefit with an understanding of strengths andweaknesses that contribute to success or failure. Large firms help preserve a firm’s longevity, butsmall firms contribute more to creativity, risk taking, and a growth-oriented environment. Another more obvious idea for a future study is to repeat this study using a differentsubset of the population in which the survey results could achieve a higher response rate. Forexample, a person engaging in future research could use tax records available under the Freedomof Information Act to gather financial information for private companies. This informationwould eliminate the survivor bias present in this study. The response rate might also improve ifsuch a person belonged to a trade group more willing to cooperate. By achieving a higherresponse rate, results’ significance would improve. An improved response rate would make theresults more valuable to an entrepreneur and serve as a guide for handling different kinds of risk.The guide may benefit nascent entrepreneurs by teaching them how to handle risk in the sameway successful entrepreneurs do. Summary In this chapter, the aim of the conversation sought to review the results, discuss theirimplications, and recommend ideas for future study. The discussion showed how the results ofthe study clarified certain ideas found in the literature about how entrepreneurs deal with timingrisk management. Rational thinking, the learning environment, risk preferences, and cultural
  • 125. 113orientation influence timing risk management. Risk sensitivity and achieving political legitimacyalso contribute to timing risk management actions. The results revealed that timing riskmanagement is not as important as other critical success factors and that timing depends on whena risk needs an intervention. Another implication of the results revealed that a firm should stayprivate as long as possible to avoid inhibiting creativity and growth. Areas for future studyinclude looking at the role of political empathy for entrepreneurship to improve entrepreneurialsuccess rates and economic growth. Another area deserving further inquiry is to find othersuccess factors that help turn uncertain conditions into manageable risks. A study to compare thefailure rates of private and public companies would further define strengths and weaknessesinfluencing entrepreneurial success. Last, repeating this study for a subpopulation yielding animproved response rate would benefit entrepreneurs in serving as a guide to help prioritize riskmanagement for different risks.
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  • 151. 139 APPENDIX A: SURVEY INSTRUMENT Survey Instrument: Entrepreneurial Risk Factors Research question: When does the new venture begin to plan for risk? INSTRUCTIONS: Thank you for taking the time to complete this survey. Your responses are important to help decide what risk factors your firm identified before, during, or after its initial founding (up to six months following start-up). Please mark (√) the answer that best matches your circumstances. Planned During Planned Planned Planned Planned Inception Planned from 19 from 31 from 43 from 55 Never (6 months from 7 to to 30 to 42 to 54 to 66 Planned before start- 18 months months months months or months or or after up to 6 after after after after after 66 months after) inception inception inception inception inception months Risk Factor (1) (2) (3) (4) (5) (6) (7)1. The dependency on few suppliers of critical services or products may present a problem.2. Environmental risks and rules may have an unfavorable effect on business.3. Strong competition from competitors may create difficulty gaining enough of a share of the market.4. Local, legal, and political risk may hinder the firm’s ability to market products.5. Limited financing may hamper the firm’s ability to preserve the expense to uphold regulatory needs.6. The power may not exist for the company to achieve market acceptance for products.7. Difficulty attracting key management and board members may hinder the ability to carry out business plans and manage growth.8. Technological changes could make products and services obsolete.9. Safety and product liability could result in unforeseen damages.10. The company may find gaining necessary licenses for products difficult. Indicate when public financing sought in terms of months from inception___________months. Under 101- 151- 201 and Employee Demographics 50 51-100 150 200 over Number of employees
  • 152. 140 Less $51- $100 than $1 $1-50 100 million Company Demographics million million million or moreAnnual revenueFrom your most recent annual audited financial statement please report the following information: Dollar Amount Item (000’s)Fixed charges: Defined as the sum of the following: (a) both interest charged to expense and interestcapitalized on the balance sheet, (b) amortized premiums and discounts reflected as an adjustment ofdebt on the balance sheet, (c) an estimate of the interest reflected within rent expense charged to theincome statement, and (d) any dividend preference requirements of consolidated subsidiaries.Earnings: Defined by adding the following: (a) pre-tax income from continuing operations beforeadjustment for income or loss from equity investees; (b) fixed charges; (c) amortization of capitalizedinterest; (d) distributed income of equity investees; and (e) your share of pre-tax losses of equityinvestees for which charges arising from guarantees are included in fixed charges.Working Capital: Defined as the difference between current assets and current liabilities (per accrualbasis financial statements).Total Assets: Defined as the total of all assets listed on the balance sheet or the sum of total liabilitiesplus total shareholder’s/owner’s equity.Total Retained Earnings: Defined as the accumulated earnings or deficit since the inception of thefirm.Stock Price at Balance Sheet Date: Reported stock price at the balance sheet date as determined on anorganized exchange for a public company or the most recent stock price paid for a share of companystock for a private company. Show number of shares outstanding here: Common__________________.Preferred __ %_____________. ________Book Value of Total Debt: Total amount of debt reported on the financial statements.Gross Revenues: Defined as the total of all operating revenues (not net of operating expenses)reported on the financial statements.Total Shareholder’s Equity: Defined as the total of all equity reported on the financial statements.This amount should be the difference between total assets and the book value of total debt reportedabove.Projected net operating cash flow for next 10 years (in 000’s): Defined as your best estimate of net operatingcash flows based on projected demand for service over the next 10 years. The estimated amounts should reflect theamounts expected on the Statement of Cash Flows per the audited financial statements. List below. Next Year Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Year 8 Year 9 Year 10Explain any discrepancies below:Has the firm sought or planned to seek public financing? Yes No (circle one)Date of actual or planned application____________.
  • 153. 141 APPENDIX B: INFORMED CONSENT FORM UNIVERSITY OF PHOENIX Informed Consent: Participants 18 years of age and olderDear ,My name is Phil Harris and I am a student at the University of Phoenix working on a DBA degree. I am conductinga research study entitled Entrepreneurial Success as Determined by an Evaluation of PreMarket Entry Risks. Thepurpose of the research study is to determine if awareness of antecedent risks can improve success rates ofentrepreneurs by early development of risk management strategies. .Your participation will involve disclosing when your firm first became aware of certain risks and when you startedrisk management activities. You will also be asked to disclose certain financial information from your most recentannual audit. Your participation in this study is voluntary. If you choose not to participate or to withdraw from thestudy at any time, you can do so without penalty or loss of benefit to yourself. The results of the research study maybe published but your identity will remain confidential and your name will not be disclosed to any outside party.In this research, there are no foreseeable risks to you except none.Although there may be no direct benefit to you, a possible benefit of your participation is that I will share the resultswith you at your request.If you have any questions concerning the research study, please call me at 712-722-4810 or contact me via email As a participant in this study, you should understand the following: 1. You may decline to participate or withdraw from participation at any time without consequences. 2. Your identity will be kept confidential. 3. Phil Harris, the researcher, has thoroughly explained the parameters of the research study and all of your questions and concerns have been addressed. 4. If the interviews are recorded, you must grant permission for the researcher Phil Harris to digitally record the interview. You understand that the information from the recorded interviews may be transcribed. The researcher will structure a coding process to assure that anonymity of your name is protected. 5. Data will be stored in a secure and locked area. The data will be held for a period of three years, and then destroyed. 6. The research results will be used for publication. “By signing this form you acknowledge that you understand the nature of the study, the potential risks toyou as a participant, and the means by which your identity will be kept confidential. Your signature on this formalso indicates that you are 18 years old or older and that you give your permission to voluntarily serve as aparticipant in the study described.” Signature of the interviewee _____________________________ Date _____________ Signature of the researcher ______________________________ Date _____________
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  • 161. 149 APPENDIX D: TABLESTable D1Calculation of ratios Ratio Calculation JustificationRatio of earnings to fixed Earnings/Fixed charges Used by SEC on Form S-1 chargesRatio of working capital to Working capital/Total Altman (1968) total assets assetsRatio of retained earnings to Retained Earnings/Total Altman (1968) total assets AssetsRatio of earnings before EBIT/Total assets Altman (1968) interest and taxes (EBIT)Ratio of market value of Market value of Altman (1968) equity to the book value equity/Book value of of total debt debtRatio of sales to total assets Sales/Total assets Altman (1968)Internal rate of return (IRR) Present value of annual Industry practice cash flows*/Original investment*Limited to first 10 years for practical purposes.
  • 162. 150Table D2Risk Factors and Hypotheses Tests Using Z Test Hypothesis Null Alternative Reference Risk Factor (Ho) (Ha) Ho-1 The dependency on few suppliers of critical µ1 = µ2 µ1 ≠ µ2 Ha-1 services or products may present a problem. Ho-2 Environmental risks and laws may have an µ1 = µ2 µ1 ≠ µ2 Ha-2 adverse affect on business. Ho-3 Intense competition from competitors may µ1 = µ2 µ1 ≠ µ2 Ha-3 make it difficult to gain enough market share. Ho-4 Local, legal, and pol itical risk may hinder the µ1 = µ2 µ1 ≠ µ2 Ha-4 firm’s ability to market produ cts. Ho-5 Limited financing may hamper the firm’s ability µ1 = µ2 µ1 ≠ µ2 Ha-5 to pr eserve the expense to uphold regulatory needs. Ho-6 The capability may not exist for the company µ1 = µ2 µ1 ≠ µ2 Ha-6 to achieve market acceptance for products. Ho-7 Difficulty attracting key management and µ1 = µ2 µ1 ≠ µ2 Ha-7 board members may hinder the ability to carry out business plans and manage growth. Ho-8 Technological changes could render products µ1 = µ2 µ1 ≠ µ2 Ha-8 and services obsolete. Ho-9 Safety and pr odu ct liability could result in µ1 = µ2 µ1 ≠ µ2 Ha-9 unforeseen damages. Ho-10 The company may find obt aining necessaryµ1 = µ2 µ1 ≠ µ2 Ha-10 licenses for produ cts difficult.Where µ1 = mean of successful group and µ2 = mean of unsuccessful group
  • 163. 151Table D3Eigenvalues Initial Eigenvalues Component Total %Variance Cumulatative %Working capital to total assets 4.382 27.263 27.263Retained earnings to total assets 2.688 16.801 44.065Earnings before interest and taxes to total assets 1.956 12.223 56.288Market value of equity to book value of debt 1.431 8.946 65.234Sales to total assets 1.250 7.811 73.046Earnings to fixed charges 0.857 5.358 78.404Dependency on a few suppliers 0.814 5.090 83.494Environmental rules and risks 0.778 4.863 88.357Strong competition 0.558 3.489 91.846Local, legal, and pol itical risks 0.410 2.564 94.410Regulatory compliance 0.328 2.052 96.462Market acceptance 0.196 1.228 97.690Attracting key management 0.173 1.082 98.771Technological changes 0.091 0.566 99.337Safety and pr odu ct liability 0.056 0.351 99.688Acquistion of necessary licenses 0.050 0.312 100.000
  • 164. 152Table D4Correlation Matrix Component WC/TA RE/TA EBIT/TAMVE/BVD S/TA E/FC SPL ERWC/TA 1.000 -0.671 -0.558 0.415 0.227 -0.095 -0.003 0.142RE/TA -0.671 1.000 0.584 -0.342 -0.008 0.240 0.109 -0.074EBIT/TA -0.558 0.584 1.000 0.743 -0.074 0.316 0.168 0.243MVE/BVD 0.415 -0.342 -0.743 1.000 -0.069 0.060 -0.170 -0.190S/TA 0.227 -0.008 -0.074 -0.069 1.000 0.050 0.378 0.294E/FC -0.095 0.240 0.316 0.060 0.050 1.000 -0.106 0.026SPL -0.003 0.109 0.168 -0.170 0.378 -0.106 1.000 0.727ER 0.142 -0.074 0.243 -0.190 0.294 0.026 0.727 1.000Note: WC/TA = working capital to total assets, RE/TA = retained earnings to totalassets, EBIT/TA = earnings before interest and taxes to total assets, MVE/BVD =market value of equity to book value of debt, S/TA = sales to total assets, E/FC =earnings to fixed charges, SPL = dependent on a few suppliers, ER = environmental Component SCOMP POL REG MKTAC KMGT TECH SAFE LICSCOMP 1.000 0.284 0.249 -0.098 -0.172 0.248 0.227 0.187POL 0.284 1.000 0.469 0.181 -0.150 0.607 0.407 0.437REG 0.249 0.469 1.000 0.383 -0.024 0.571 0.433 0.891MKRAC -0.098 0.181 0.383 1.000 0.231 0.150 0.375 0.327KMGT -0.172 -0.150 -0.024 0.231 1.000 -0.320 0.034 -0.059TECH 0.148 0.607 0.571 0.150 -0.320 1.000 0.174 0.513SAFE 0.227 0.407 0.433 0.375 0.034 0.174 1.000 0.533LIC 0.187 0.437 0.891 0.327 -0.059 0.513 0.533 1.000Note: SCOMP = strong competition, POL = legal and political risk, REG = regulationand compliance, MKTAC = market acceptance, KMGT = attracting key management,TECH = technological changes, SAFE = safety and product liability, LIC = acquisitionof necessary licenses
  • 165. 153Table D5Altman z-scores 3.0 and 2.99 and 3.0 and 2.99 and 3.0 and 2.99 and Case above under Case above under Case above under 1 8428.93 11 -8.27 21 3.65 2 8.91 12 -2.70 22 1.42 3 -0.02 13 1.95 23 1.75 4 3.96 14 3.19 24 0.89 5 -4.47 15 0.03 25 5.89 6 53.61 16 1.57 26 0.23 7 -9.43 17 0.02 27 1.03 8 18.60 18 0.92 28 1.20 9 -158.08 19 1.25 29 4.80 10 11.46 20 0.16 30 -3.81 n 6 4 1 9 3 7Note: To protect the identity of the company the case numbers do not coincide withthe key code number on the survey instrument.
  • 166. 154Table D6Group Descriptive Statistics Successful Unsuccessful TotalMean: Working capital to total assets 0.4619 0.2887 0.3464 Retained earnings to total assets -0.5629 -1.4707 -1.1681 Earnings before interest and taxes to total assets -0.0050 -0.1521 -0.1031 Market value of equity to book value of debt 1417.8864 2399.5064 2072.2997 Sales to total assets 3.3362 0.3824 1.3670Standard deviation: Working capital to total assets 0.3047 0.3196 0.3204 Retained earnings to total assets 0.8645 2.8329 2.3832 Earnings before interest and taxes to total assets 0.3420 0.3364 0.3397 Market value of equity to book value of debt 4437.3709 10564.0141 8913.3872 Sales to total assets 7.0407 0.4089 4.1833N 10 20 30
  • 167. 155Table D7Kruskal-Wallis H Test Mean Ranks Test Statistics Chi-Square Asymp. 2 Successful Unsuccessful (x ) df Sig.Mean Rank: Dependency on a few suppliers 16.35 15.08 0.168 1 0.682 Environmental rules and risks 18.40 14.05 1.923 1 0.166 Strong competition 13.55 16.48 1.342 1 0.247 Local, legal, and pol itical risks 18.40 14.05 1.920 1 0.166 Regulatory compliance 12.25 17.12 2.494 1 0.114 Market acceptance 14.15 16.18 0.418 1 0.518 Attracting key management 17.65 14.42 0.990 1 0.320 Technological changes 17.40 14.55 0.810 1 0.368 Safety and pr odu ct liability 16.35 15.08 0.161 1 0.688 Acquistion of necessary licenses 13.25 16.62 1.208 1 0.272N 10 20
  • 168. 156Table D8Hypothesis TestingHypothesis Result at Reference Risk Factor Hypothesis p < .05Ho-1 The dependency on few suppliers of critical µ1 = µ2 Not met services or products may present a problem.Ha-1 µ1 ≠ µ2 Not metHo-2 Environmental risks and laws may have an µ1 = µ2 Not met adverse affect on business.Ha-2 µ1 ≠ µ2 Not metHo-3 Intense competition from competitors may µ1 = µ2 Not met make it difficult to gain enough market share.Ha-3Ho-4 Local, legal, and pol itical risk may hinder the µ1 = µ2 Not met firm’s ability to market produ cts.Ha-4 µ1 ≠ µ2 Not metHo-5 Limited financing may hamper the firm’s ability µ1 = µ2 Not met to pr eserve the expense to uphold regulatory needs.Ha-5 µ1 ≠ µ2 Not metHo-6 The capability may not exist for the company µ1 = µ2 Not met to achieve market acceptance for products.Ha-6 µ1 ≠ µ2 Not metHo-7 Difficulty attracting key management and µ1 = µ2 Not met board members may hinder the ability to carry out business plans and manage growth.Ha-7 µ1 ≠ µ2 Not metHo-8 Technological changes could render products µ1 = µ2 Not met and services obsolete.Ha-8 µ1 ≠ µ2 Not metHo-9 Safety and pr odu ct liability could result in µ1 = µ2 Not met unforeseen damages.Ha-9 µ1 ≠ µ2 Not metHo-10 The company may find obt aining necessary µ1 = µ2 Not met licenses for produ cts difficult.Ha-10 µ1 ≠ µ2 Not met
  • 169. 157Table D9Risk Priorities Based on Mean Rank Mean Ranks Risk Factor Successful UnsuccessfulRegulatory compliance 12.25 17.12Acquistion of necessary licenses 13.25 16.62Strong competition 13.55 16.48Market acceptance 14.15 16.18Safety and pr odu ct liability 16.35 15.08Dependency on a few suppliers 16.35 15.08Technological changes 17.40 14.55Attracting key management 17.65 14.42Local, legal, and pol itical risks 18.40 14.05Environmental rules and risks 18.40 14.05Note: The lower the mean rank, the sooner the firm plans for risk.