Managing risk in the formative years Evidence from young ...

Managing risk in the formative years: Evidence from youngenterprises in Europe$

YoungJun Kim a, Nicholas S. Vonortas b,n

a Graduate School of Management of Technology, Korea University, Anam-Dong, Seongbuk-Gu, Seoul 136-713, South Koreab Center for International Science and Technology Policy & Department of Economics, George Washington University, 1957 Street, N.W., Suite 403,Washington, DC 20052, USA

a r t i c l e i n f o

Available online 23 May 2014

Keywords:RiskRisk managementSmall firmsSMEs

a b s t r a c t

This paper empirically investigates aspects of risk management in young small enterprises' effort tosurvive and grow. We use a new dataset on several thousands small businesses in their “formative age”(2–8 years old) in 10 European countries and 18 sectors. Firms across all types of sectors use internal riskmitigation strategies to manage technology risk and operational risk. Financial risk is managed bytapping formal and informal networks. Market risk appears less amenable to internal managementaction. Formal network participation (strategic alliances) is a strategy cutting across all kinds of risk withthe exception of operational risk. Firms in knowledge-intensive sectors (high-tech manufacturing andKIBS) engage in risk management activities more extensively. Firms led by more educated entrepreneursand/or operating in demanding volatile markets tend to network more and to use internal riskmitigation strategies more extensively.

& 2014 Elsevier Ltd. All rights reserved.

1. Introduction

This paper empirically analyzes aspects of risk management inyoung small enterprises. We investigate risk mitigation strategies ina population of several thousand newly established, independentsmall businesses that have entered the “formative age”, determinedto be 2–8 years from establishment. The examined firms operatedacross sectors including high- and low-tech manufacturing andknowledge intensive services.

Whereas there is an extensive literature on risk managementcovering all aspects of an enterprise such as project management,research and development (R&D), accounting, finance, and insur-ance, attention to risk management practices of small and mediumsized enterprises (SMEs) is a recent development (Verbano andVenturini, 2011, 2013). This apparent gap is even more visible asregards systematic empirical evidence on the nature, extent andantecedents of risk management in small firms. This seems at odds

with the widespread perception that newer and smaller firms aremuch more vulnerable to various types of risk (Street andCameron, 2007) and have much higher probabilities to exitthan their larger, more established counterparts (OECD, 2001).Young small companies are challenged in terms of access toresources such as human or financial capital, other complemen-tary resources for technological development and commercializa-tion, and access to markets. We know little about the riskmanagement practices of the cohort of companies which havesurvived the first major shake-out – typically in the first 2–3 yearsof a firm's life – and are still small and vulnerable. This cohort isthe focus of the present paper.

Risk can generally be defined as the potential that a certainaction will lead to an undesirable effect, positive or negative(Leitch, 2010). The undesirable consequences of the action mayaffect the achievement of the strategic, operational and financialobjectives of a company (British Bankers' Association, 1999).Risk can be caused by external factors (economic, environmental,social, political) or by internal factors (human resources, processes,technology) (COSO, 2004). Risks vary by sector and by type oforganizational structure. All kinds of organizations – whether for-profit or not-for-profit – face risks, but not always of the same typeor intensity.

Risk management is the “identification, assessment, and prior-itization of risks followed by coordinated and economical applicationof resources to minimize, monitor, and control the probability

Contents lists available at ScienceDirect

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Technovation

http://dx.doi.org/10.1016/j.technovation.2014.05.0040166-4972/& 2014 Elsevier Ltd. All rights reserved.

☆Note: The underlying empirical information was produced in the context of theresearch project “Advancing Knowledge-Intensive Entrepreneurship and Innova-tion for Economic Growth and Social Wellbeing in Europe” (AEGIS), 7th FrameworkProgramme for Research and Technological Development, European Commission.We acknowledge the extremely useful comments of two anonymous referees andthe editors of the journal in improving the paper.

n Corresponding author. Tel.: þ1 202 994 6458.E-mail addresses: [email protected] (Y. Kim),

[email protected] (N.S. Vonortas).

Technovation 34 (2014) 454–465

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and/or impact of unfortunate events or to maximize the realiza-tion of opportunities” (Hubbard, 2009). Managing risk responsiblymeans developing a framework that is not too far on either side ofcautiousness or carelessness (Culp, 2011). It also means that risk isinseparable from discussions of corporate strategy and financingand should be considered to be an integral part of the process fromstart-up to a highly-successful venture. A well thought out riskmanagement plan can be critical to the future of a current orforthcoming venture (Andersen, 2008; Longenecker et al., 2010).The plan must concentrate on risk control – minimizing lossthrough prevention, avoidance and/or reduction – but also onupside gains (exploiting opportunities) (Bekefi et al., 2008).Managing risks holistically – e.g., following the enterprise riskmanagement (ERM) approach (Beasley et al., 2005; Pagach andWarr, 2011) – is argued to provide firms a long-run competitiveadvantage by optimizing the trade-off between risk and return(Nocco and Stulz, 2006). Whereas the International Organizationfor Standardization has published “Risk Management Principlesand Guidelines” (ISO 31000) designed to be the internationalstandard for ERM providing a best practice document (Baker,2011), the actual conceptualization of risk management must bedriven by the values and priorities of the firm. It will reflect theextent of risk tolerance of entrepreneurs and investors (Palich andBagby, 1995).

Companies can manage risk with the help of “external” sources(networking) and “internal” strategies (sensing/seizing/acting onopportunities). Through various types of formal agreements a firmcan obtain the necessary complementary assets/resources andvaluable information that are required to manage risk effectively.Frequently it has been argued that technology start-ups facingadverse market conditions are more inclined than larger firmsto establish collaborative agreements (Colombo et al., 2006;Eisenhardt and Schoonhoven, 1996; Shan, 1990). Faced with highuncertainties and stiff competition, new and small firms inemergent sectors consider alliances to avoid vulnerable positions(due to the “liability of newness”), complete technological devel-opment and commercialize successfully (Shan, 1990). Allianceswith third parties can help small firms overcome a host oftechnological, financial and operational challenges (Baum et al.,2000; Flatten et al., 2011; Nieto and Santamaría, 2010). On thewhole, the literature indicates cooperative agreements and net-work strategy as a critical element in determining survival andprosperity of young and small companies (Brüderl and Preisendor̈fer,1998; Havnes and Senneseth, 2001; Schoonjans et al., 2013). Havingthe chance to cooperate with leading firms allows access to marketsand important resources such as complementary technologies,complementary skills, finance, R&D and research synergies, andmore importantly, reduces various kinds of risks related to technol-ogy, market, finance and organization.

By sensing and seizing technological and market opportu-nities, companies can manage risk through their own internalstrategic actions. Internal risk management actions can includeefforts to stay ahead of the competition by frequently introducingnew products/services and maintaining formal R&D departmentand/or engineering and technical studies departments, recogniz-ing quickly market shifts and responding rapidly both to compe-titor moves and to customer feedback, maintaining formal andinformal networks for easier access to business funds, and finallyfocusing on human resources and implementing systematicpersonnel training and improved communication of practicalexperiences. A quite extensive and diverse literature has exten-sively referred to these issues and offered advice for accessing therequisite capabilities (e.g., Culp, 2011; Ebben, 2005; Keizer et al.,2002; Mu et al., 2009; Nocco and Stulz, 2006; Perez-Luno andCambra, 2013). Extant literature has by and large focused on largeincumbent companies, however leaving much to be desired in

terms of systematic empirical evidence addressing young smallcompanies.

This paper concentrates on risk management in young entre-preneurial companies operating in a set of sectors that includeboth high- and low-tech manufacturing and knowledge-intensivebusiness services. The paper empirically relates four types of risk –

technology, market, finance, and operation risk – to risk-mitigationstrategies. We employ a new important set of information on 3624newly established (2–8 years old) independent small businesses(r49 employees) in 10 European countries to understand theimportant factors in their efforts to mitigate risk.

Our results indicate that firms across all types of sectors useinternal risk mitigation strategies to manage technology risk andoperational risk. Financial risk is managed by tapping formal andinformal networks. Market risk, on the other hand, appears lessamenable to internal management action. Formal network parti-cipation (strategic alliances) emerges as a strategy cutting acrossall kinds of risk, with the exception of operational risk. Firms inknowledge-intensive sectors (high-tech manufacturing and KIBS)appear to engage in all kinds of risk management activities moreextensively.

Several factors characterizing the firm founder(s) and themarket the firm operates in are also important. Firms establishedby better educated entrepreneurs and/or operating in demandingvolatile markets tend to engage more both in strategic alliancesand in various internal strategic actions to manage risk. However,we could not find a statistically significant relationship betweenthe founders' employment just prior to establishing the specificfirm with either networking or with internal risk managementaction. This was somewhat unexpected given that prior experienceis a typical risk mitigation strategy in itself.

The rest of the paper is divided into four sections. Section 2below provides the theoretical background and builds ourresearch hypotheses. Section 3 explains the data and our analy-tical methods. Section 4 summarizes our results. Finally, Section 5concludes.

2. Theoretical background and hypotheses

The sources of risks affecting business firms abound. Whileconsensus in the literature on the types and titles of business risksis still pending, there is significant overlap in terms of character-ization. For example, the Casualty Actuarial Society (2003) classi-fied risk types as hazard risk, financial risk, operational risk, andstrategic risk. Ebben (2005) distinguished between market risk,operational risk, opportunity risk, financial model risk, and finan-cial risk in the mix. Ekanayake and Subramaniam (2012) classifiedbusiness risks as financial risk (the financial aspects of a business),operational risk (business operations and activities), environmen-tal risk (a variety of social, economic, political and physical risks),and reputational risk (an organization's public standing andtrustworthiness). Epstein and Rejc Buhovan (2005) discussedstrategic risk, operations risk, reporting risk, and compliance risk.Within the context of new product development, scholars like Muet al. (2009) and Doering and Parayre (2000) suggested threekinds of risks: technological risk, market risk, and organizationalrisk. And Keizer et al. (2002) identified four risk domains poten-tially affecting product innovation: technology (product designand platform development, manufacturing technology and intel-lectual property); market (consumer/public/trade acceptance andthe potential actions of competitors); finance (commercial viabi-lity); and operations (internal organization, project team, co-development with external parties and supply and distribution).Finally, in their survey of the literature on SME risk management,Verbano and Venturini (2011, 2013) classified applications into

Y. Kim, N.S. Vonortas / Technovation 34 (2014) 454–465 455

nine different streams: strategic risk management, financial riskmanagement, enterprise risk management, insurance risk man-agement, project risk management, engineering risk management,supply chain risk management, disaster risk management, andclinical risk management. Clearly, in our view, there is room foradditional theoretical conceptualization towards greater standar-dization.

In this paper, we adapt the four risk domains of Keizer et al.(2002) to young small companies:

� Technology risk – referring to product design, productiontechnology, and intellectual property. The technology of theyoung entrepreneurial company is frequently unproven and theapplication yet to be demonstrated: development may takelonger than expected, it may not produce the expected result,it may not work, or it may be superseded by competingtechnologies. Technology risk captures the firm's inability tocompletely understand or accurately predict some aspects ofthe technological environment (Milliken, 1987). This riskrelates to technological complexity, reflecting the level ofcomplex knowledge and information required to understandthe environment (Perez-Luno and Cambra, 2013) and thenumber of parts and/or process steps involved (Walsh andLinton, 2011). Technology risk increases in sophisticated andtechnologically complex environments.

� Market risk – referring to product market acceptance, thepotential actions of competitors, and general market conditionsand evolution. Market risk reflects the difficulty in assessingthe market potential for products that may be at a very initialstage or may not yet exist but which have the potential tocreate a new market. It reflects ambiguity about the types andextent of customer needs that can be satisfied by a particulartechnology or new product (Moriarty and Kosnik, 1989).Market risk relates to changes in the competitive marketenvironment: who are the competitors, what products theyoffer, what competitive advantages they might have; potentialfuture competitors and their competitive strategies and tactics(Boyd et al., 1993).

� Financial risk – referring to the tangible value investors lose ifthe business fails and to the financial aspects of a business (e.g.,liquidity risk, foreign exchange risk). While the problems withSME creditworthiness are well known, good credit risk modelsand data to predict failure are still unavailable (Altman andSabato, 2007; Altman et al., 2010). One important reason, ofcourse, is that many of these companies are unlisted andinformation about them is scarce. Young and small firmstypically face difficulties in raising investment funds due tohigh levels of perceived risk by external investors – clearlyindicated, among others, by the AEGIS survey supporting ourempirical investigation where more than 9 in 10 surveyrespondents used their own resources rather extensively inestablishing the company while only 5% of the surveyed firmshad accessed venture capital. Janney and Dess (2006) stressthat the use of conventional measures of risk may be harmingnew entrepreneurs by reinforcing the impression that theentrepreneur takes more risks than others, which can scareoff potential investors. There is a widespread perception thatinvesting in early stage technology-based small firms carrieshigher risks than investing in non-technology ventures (Masonand Harrison, 2004). Ben-Ari and Vonortas (2007) andMacmillan et al. (1985, 1987), for example, point out thatnew knowledge-based entrepreneurial ventures are much lesslikely to attract external funding. If all the proposed value ofyoung and small ventures is contained in the head of itsfounders, potential investors have a hard time projecting thisknowledge into real profits.

� Operational risk – referring to the internal organization andmanagement of own operations team for development, pro-duction, supply and distribution. Operational risk is a broadterm capturing the business dangers challenges arising fromthe people, systems and processes the company utilizes. It canalso include other classes of risk such as fraud risk, legal risk,supply-chain risks, and physical or environmental risks. Amongthese diverse sources, human resource risk is the key (Epsteinand Rejc Buhovan, 2005): one of the greatest difficulties for anyfirm is to find and attract employees with appropriate skills.The problem is exaggerated in small fledgling companies whichmay face acute difficulties in attracting top job candidates.Inadequately trained people create the potential for significantloss when internal systems and processes fail. Operational riskin our paper will be limited to human resource risk.

2.1. Networks

One of the effective ways of managing risk might be collaboratingwith other organizations. The companies can form networks withothers through various types of formal agreements such as strategicalliances, R&D agreements, technical cooperation agreements, licen-sing agreements, subcontracting, marketing/export promotion, and/orresearch contract-out. Through networking, firms can obtain thenecessary complementary assets/resources and valuable informationthat are required to manage risk effectively.

Several special issues on alliances and networks have appearedover the years in an array of journals in management/organization,economics and policy. Examples include the Journal of BusinessVenturing (edited by Alvarez et al., 2006), the Academy ofManagement Journal (edited by Osborn and Hagedoorn, 1997),Organization Science (edited by Koza and Lewin, 1998), Organiza-tion Studies (edited by Grandori, 1998), International Studies ofManagement and Organizations (edited by Ebers and Jarillo, 1998),Strategic Management Journal (edited by Gulati et al., 2000), andthe Journal of Technology Transfer (edited by Arvanitis andVonortas, 2000). On the whole, the literature indicates cooperativeagreements and network strategy as a critical element in deter-mining survival and prosperity of young and small companies(Brüderl and Preisendor̈fer, 1998; Havnes and Senneseth, 2001;Schoonjans et al., 2013). Scholars have thus argued that “… whenthe knowledge base of an industry is both complex and expandingand the sources of expertise are widely dispersed, the locus ofinnovation will be found in networks of learning, rather than inindividual firms” (Powell et al., 1996). Having the chance tocooperate with leading firms allows access to markets and toimportant resources such as complementary technologies, com-plementary skills, finance, R&D and research synergies, and moreimportantly, reduces various kinds of risks related to technology,market, finance and organization.

Knowledge from external sources can be valuable for reducingtechnological risk through improved access to other organizations'knowledge and expertise. It can help firms acquire and apply newtechnologies to product development, thus keeping up with thetechnological trends (Gatignon and Xuereb, 1997). Firms thatassimilate knowledge from various sources will be capable ofaligning their products or services with emerging trends andaccordingly realize greater success in the marketplace. Alliancesmay able to produce a superior technology by combing the bestaspects of partner know-how, which can be a powerful weapon inthe young firm's arsenal of options.

Besides synergies, networks are often quite useful in ensuringproduct compatibility, a source of significant concern for theadopters of the new products and technologies. The introductionof “industry standards” – agreed upon specifications based on a

Y. Kim, N.S. Vonortas / Technovation 34 (2014) 454–465456

common architecture or design principles that ensure technicalcompatibility for products offered by different firms in the market– allows customers to gain compatibility across the variousproduct choices (Mohr et al., 2010). Strategic alliances are knownas an effective channel for setting industry standards. Networkingthat establishes industry standards can help to ensure a widesupply base for the product and technology, can co-opt competi-tors, and can help build positive expectations for market demand(Mohr et al., 2010). Networking with others can thus reduceconfusion in the market place and lower market risk.

Typically it will be harder for young and small firms to obtainexternal funding. Raising funds from alliance partners offers a wayout. Networking with established, reputable organizations can alsoprovide a positive signal to other investors.

Regarding operational risk one can argue that firms can exploittheir external sources to pool knowledge and people as well asgather and screen relevant information (Ahuja, 2000). Linkagesbetween otherwise unconnected firms facilitate the combinationof diverse or non-redundant knowledge that relates to technology,experts, organizational practices, and market trends, thus allowingthem to manage risks better. Firms can also learn best practicesfrom their various alliance partners over time and acquire strategicintelligence about competitors (Mu et al., 2009). Scholars such asAhuja (2000) and Burt (1992) point out that external networkshave been regarded as important factors in enhancing innovationand resources and capabilities. Networks can be a type of valuableresource in themselves, while they independently moderate theeffects of resources on performance (Lee et al., 2001). Nonetheless,expectations about the extent of contribution of alliances tooperational risk mitigation should be moderated by the fact thatthe risk here refers primarily to the internal organization andmanagement of own operations, and addresses business chal-lenges arising from the people, systems and processes the com-pany utilizes.

Hypothesis 1. The higher the perceived overall risk, the higherthe likelihood that young small firms will use networks to managerisk successfully and responsibly.

2.2. Internal risk management

In addition to external networking with other organizations,it is important for companies to sense and seize various opportu-nities by acting strategically and managing risks internally.They can respond to technology risk, for instance, by continuouslyimproving products and by maintaining formal R&D and/orengineering and technical departments. They can respond tomarket risk by responding rapidly to competitor moves, payingclose attention to customer feedback, monitoring market devel-opments, and by quickly recognizing broader market shifts due toregulation, competition, demography, etc. They can respond tofinancial risk better by nurturing and promoting formal andinformal networks of managers in order to have easier access tofunds. Finally, they can respond to operational risk by hiring thebest available employees and training them adequately for the job.In this paper we take a narrower view of operational risk to focuson human resource risk in particular (Epstein and Rejc Buhovan,2005), referring to the difficulty of finding and attracting employ-ees with most appropriate skills.

The large survey which the empirical analysis of this paper isbased on strongly indicated that entrepreneurs perceive the fourtypes of risks differently. Market risk was considered the mostimportant obstacle to company growth: three quarters of therespondents opined that it is at least of moderate importanceand at least two-fifths that it is of great importance. Market risk isfollowed by two other factors, funding difficulties (financial risk)

and difficulties in recruiting high-skill employees (operationalrisk): 60% of respondents thought each of these obstacles as ofmoderate importance for company growth, with 40% consideringthem of high importance. Interestingly, the lack of technologicalknow-how and technology risk/uncertainty were the two factorsat the bottom of the obstacle list: only about 15% or respondentsconsidered them to be of high importance.

2.2.1. Technology riskSMEs are a heterogeneous population of firms whose charac-

teristics vary according to their environment, their size, theirmarket and a series of other parameters. This carries over totechnological activity. A survey conducted in 2006 by the Uni-versity of Cambridge and the MIT distinguished among differentgroups of SMEs on the basis of innovation resources (people andideas), effort (innovation expenditure of various kinds) and inno-vation outcomes (Cosh et al., 2006). The OECD (2001) has alsoused a series of surveys of the European Commission and theIRDAC – former Industrial R&D Advisory Committee of the Eur-opean Commission – to classify SMEs according to technologicalintensity. They identified three groups of SMEs:

� Technology Developers which tended to be younger companies(33% of them less than 5 years old) predominantly in high-techsectors with a significant share of them investing more than20% of their turnover in R&D;

� Leading Technology Users (with or without R&D capacity),whose vast majority was created more than 10 years ago, fromboth manufacturing and services but less often from high-techsectors; and

� Technology Users mostly in low-tech sectors with a longhistory (64% created more than 10 years ago) and investinglittle or nothing of turnover in R&D.

The diversity in the SME population has been captured by anumber of typologies such as the “Arnold Staircase” used todescribe categories of enterprises with varying levels of R&Dcompetence (Fig. 1).

A related taxonomy is the so-called “SME Research Stairway”distinguishing among the following groups (Fig. 2)

� Technology Pioneers which manage to keep in touch with high-level research (carried out either internally or in associatedorganizations);

� Leading Technology Users which usually combine existingtechnologies in new innovative ways (although a little devel-opment may also occur);

Fig. 1. Arnold Staircase – hierarchy of company types and size class.Source: Arnold and Thuriaux (1997).


� Technology Adopting Enterprises which adapt existing tech-nologies in order to connect them with customers andmarket needs;

� Basic SMEs with no or little R&D.

The takeaway from such taxonomies is that the vast majority ofSMEs undertakes no or little R&D. At the other extreme, a smallnumber of them are involved in leading-edge research. In betweenthe two extremes, a group representing something around one-third of the total SME population regularly develops, applies oracquires technology. Obviously, the actual shares will vary acrossindustries. We hypothesize that the perception of technology riskpositively affects firm incentives to try manage it successfully byracking up the requisite internal capabilities.

Hypothesis 2. The higher the perceived technology risk, thehigher the likelihood that young small firms will introduce new/improved products frequently and maintain formal research andengineering/technical activities in-house.

2.2.2. Market riskWhile technology risk largely depends on company circum-

stances and can, to this extent, be considered as diversifiable(unsystematic) and naturally subject to active management, mar-ket risk largely depends on external factors. As a first approxima-tion, then, one would tend to think that market risk is non-diversifiable to some extent and does not easily lend itself tomanagement. This would be a rushed conclusion. At least since thelarge SAPPHO project carried out by the Science Policy ResearchUnit at the University of Sussex in the 1970s, it is well understoodthat the factors most strongly associated with the successfulintroduction of innovative products are related to marketing.Successful attempts to innovation were distinguished frequentlyfrom failure by greater attention to the education of users,publicity, market forecasting, and to understanding of customerrequirements (Freeman and Soete, 1997). In other words, somecompanies were better than others in understanding the impor-tance of actively trying to manage market risk. The SAPPHO resultshave been replicated repeatedly by other studies (Hartley, 2006).The importance of differential competitive strategies by entrepre-neurial companies in new versus established markets has alsobeen shown in experimental environments (Katila et al., 2012).

The sources of market risk are several (Mu et al., 2009):customer perception of product efficacy, changing customer needs,successful prediction of market developments, competition, andprice elasticities. Timely and reliable information about customerpreferences and requirements is among the most important kindof information necessary for successful market introduction.Managers need to formulate a strategic process to answer thefollowing core questions: (a) Who are our target customers?

(b) What value do we offer to them? (c) How can we create anddeliver that value efficiently? (Markides, 1997; Moore, 2002).In answering these questions, managers must consider the presentand the future, think out of the box, and imagine possibledevelopments and potential competition arising from outsidean industry's existing boundaries (Hamel and Prahalad, 1994;Kim and Mauborgne, 2005; Mohr et al., 2010; Bossidy andCharan, 2002).

We hypothesize that, even though only partially diversifiable,firms try to manage market risk by closely engaging with actualand prospective users and by quickly recognizing and respondingto market changes.

Hypothesis 3. The higher the perceived market risk, the higherthe likelihood that young small firms will be sensitive to compe-titor moves, pay close attention to customer feedback, closelymonitor market developments, and try to keep abreast withbroader market shifts due to regulation, competition,demography, etc.

2.2.3. Financial riskFinancial risk pertains to the difficulty in accessing funding

which was placed a close second after market risk on the list ofobstacles to company growth in the large survey supporting ourempirical analysis.

The difficulties of small companies in accessing adequatefinance are not unknown. The main cause frequently amounts tothe information asymmetries between entrepreneurs and inves-tors. Entrepreneurs tend to know their product or service better.They have a better grasp than outsiders of the timeline for acompleted product and its market variability. Investors also tendto have less technical expertise in the field than do the entrepre-neurs. Such information asymmetries result in a “trust gap” whichcreates communication challenges in the relationship betweeninvestors and entrepreneurs. While keeping investors informedabout progress in product development and the timeline forreturn on their investment, entrepreneurs will always be mindfulof disclosing too much information that potentially allows othersto mishandle. Investors may also question the quality of theinformation because entrepreneurs have an interest in pre-serving funding sources and may bias information in a way thatbenefits them. The trust gap makes initial investment decisionsmore difficult: it increases the risk of investing in a project withlow potential for future returns and therefore raises the cost ofcapital for investments in innovative companies across the board(Hall and Lerner, 2009; Vonortas and Aridi, 2012).

Information asymmetries and high failure rates are morepronounced in innovative young firms compared to new busi-nesses in more established fields. This raises the price of externalcapital for innovative companies over what other new companieswould pay. Maintaining strong networks is thus the key for themin order to have easier access to external business funds and haslong been recognized as a basic incentive for engaging in strategicalliances (Hemphill and Vonortas, 2003). We hypothesize thatfirms try to manage financial risk by tapping the personal net-works of managers and formal networks of other organizations.

Hypothesis 4. The higher the perceived financial risk, the higherthe likelihood that young small firms will use formal and informalnetworks to facilitate access to business funds.

2.2.4. Operational riskOperational risk refers to the internal organization and man-

agement of own operations. The sources of operational risk arediverse and capture the business challenges arising from thepeople, systems and processes the company utilizes. A broaderuse of the term can also include other business challenges related

Fig. 2. The “SME Research Stairway”.Source: EURAB (2004).


to the supply-chain, the physical environment, legal liabilities, andso forth. Among these diverse sources of operational risk, humanresource availability is the key (Epstein and Rejc Buhovan, 2005):one of the greatest difficulties for any firm is to attract employeeswith the requisite skills and motivate them appropriately. Theproblem is exaggerated in small fledgling companies which mayface acute difficulties in attracting top job candidates. Inadequatelytrained people create the potential for significant loss wheninternal systems and processes fail.

In this paper we take a narrower view of operational risk tofocus on human resources. The manager's responsibility includesincreasing the level of cross-functional integration between per-sonnel in various departments (De Luca et al., 2007; Mohr et al.,2010), ensuring consistency in all decisions that support theproduct's market position, and ensuring that all personnel arefocused on delivering value to customers (Bruner, 1998). Wehypothesize that firms try to manage operational risk by hiringthe best available employees, training them adequately for the job,and by enhancing the quality of interdepartmental relations.

Hypothesis 5. The higher the perceived operational risk, the higherthe likelihood that young small firms will use systematic personneltraining and try to improve internal communication systems forsharing experiences and working towards common goals.

3. Methods

3.1. Data

The data used in this paper comes from the European AEGISsurvey – produced in the context of the multi-national researchproject “Advancing Knowledge-Intensive Entrepreneurship andInnovation for Economic Growth and Social Wellbeing in Europewith financial support by the 7th Framework Programme of theEuropean Commission. The survey was launched in an attempt toidentify motives, characteristics and patterns in the creation andgrowth of young – but not brand new – firms which are based onthe intensive use of knowledge and operate in both knowledge-intensive and low tech sectors. It was carried out during Fall 2010and Spring 2011. The survey recovered 4004 fully completedquestionnaires (about 300 variables) from an equal number ofindependent enterprises established during the period 2002–2008in 10 European countries (Croatia, Czech Republic, Denmark,France, Germany, Greece, Italy, Portugal, Sweden, and the UnitedKingdom) (Table 1). This sample did not include subsidiaries ofexisting companies, mergers/acquisitions, joint ventures, or newentities resulting from any type of legal transformation of alreadyexisting firms. At the time of the survey, these enterprises were2–8 years old and were distributed as follows: 2-year old, 431 firms;

3-year old, 759 firms; 4-year old, 409 firms; 5-year old, 462 firms;6-year old, 464 firms; 7-year old, 149 firms; 8-year old, 950 firms.Both manufacturing sectors and service sectors were covered.Manufacturing included high tech, medium, and low tech sectors.In addition, four knowledge intensive business service sectors(KIBS) were included (Table 2).

The population of companies to survey in these preselectedsectors was built from the Amadeus business database withadditional criteria of allocation among the 10 countries in roughconcordance to their relative size and income. The startingpopulation of 338,725 firms was allocated among high techmanufacturing (9.3%), low tech manufacturing (23.6%), and KIBS(67.1%). Multiple screenings left a sample of 12,824 newly-established companies that satisfied all criteria and were eligiblefor contacting. All respondents were contacted by telephone andcompleted the questionnaire online in their local language underthe tutelage of expert interviewees. Of those contacted, the overallachieved response rate was 31.3% (4004 companies) which variedacross countries ranging from Sweden at the low end (19.5%) toCroatia at high (63.9%).

Most firms in the resulting sample are small. Micro-firms (o10employees) account for 72.11% of the total, including a 8.51% shareof non-employers (no employees besides the owner). Firms with10–49 employees (small) account for an additional 24.82% of thesample. The next size category (50–249 employees) (medium)accounted for 2.79% of the total. Finally, six firms had 250–499employees and 5 firms had more than 500 employees (large). Thisstructure conforms to earlier findings whereby most firms remain“micro”, a relatively small portion grows to become “small”, a verysmall portion becomes “medium”, and only very few grow to“large” (Landstrom and Johanisson, 2001).

Our analysis excludes the 11 larger companies in the sample. Italso excludes the medium-sized companies, a strategic decision toconcentrate on the micro- and small firms. For convenience, wecall all of them as small firms. Like Street and Cameron (2007) wefeel that small firms require specific attention as they are relatively

Table 1Country distribution of firm sample.

Country Number of firms

Croatia 190Czech Republic 190Denmark 294France 461Germany 508Greece 313Italy 527Portugal 321Sweden 266United Kingdom 554Total 3624

Table 2Sector distribution of firm sample.

Industrya Number offirmsin sector

High-technology manufacturing sectorsAerospace 1Computers and office machinery 20Radio-television and communication equipment 33Manufacture of medical, precision and optical

instruments59

Medium to high technology manufacturing sectorsManufacture of electrical machinery and apparatus 35Manufacture of machinery and equipment 177Chemical industry 49

Medium–low technology manufacturing sectorsBasic metals 30Fabricated metal products 198

Low technology manufacturing sectorsPaper and printing 549Textile and clothing 194Food, beverages and tobacco 270Wood and furniture 211

Knowledge intensive business services (KIBS)Telecommunications 22Computer and related activities 474Research and experimental development 66Selected business services activities 1236

Total 3624

a Notes: OECD classification based on technological intensity.


more disadvantaged in terms of market positioning and access toresources.

3.2. Model specification

We run probit models for networking and internal risk man-agement where the dependent variable is a binary construct.

3.2.1. Networking

Networki ¼ β1þβ2 technology riskiþβ3 market riskiþβ4 f inancial riskiþβ5 operational riskiþβ6 FIRMi

þβ7 BUSINESS ENVIRONMENTiþϵi;for i¼ 1;…;N firms

The error term is assumed to be normally distributed.

3.2.1.1. Dependent variable. Network. The firm is asked to indicate thetypes of formal agreements the company has involved in. Network iscoded as 1 if the firm has often or very often participated in at leastone of the following different types of formal agreements: strategicalliances, R&D agreements, technical cooperation agreements,licensing agreements, subcontracting, marketing/export promotion,and/or research contract-out. Network is coded as 0 otherwise.

3.2.1.2. Independent variables

Technology risk: The level of technology risk perceived bythe firm.Market risk: The level of market risk perceived by the firm.Financial risk: The level of financial risk perceived by the firm.Operational risk: The level of operational risk (human resource)perceived by the firm.

Firms were asked to indicate to what extent each of the four typesof risk – technology, market, financial, operational – has been anobstacle to firm growth and expansion of business activities. A five-point Likert-type scale ranges from 1 (“not at all”) to 5 (“to a greatextent”).

3.2.1.3. Control variables. Entrepreneurial risk taking is influencedby a variety of factors, including the characteristics of the founderentrepreneur such as education and prior industrial tenure(Sharma, 2004; Wang and Poutziouris, 2010; Zahra, 2005), thecharacteristics of the firm and the characteristics of the businessenvironment the firm operates in.

FIRMi is a vector of variables capturing general characteristics ofthe firm and of its founder(s). This set of variables includes thenumber of employees (Firm size), the years of professional experi-ence the founder has had in the same sector before establishingthe company (previous work), and the educational attainment ofthe founder(s)/business owner(s) (founder education). Firm sizecontrols for the fact that, even within our small-size group,relatively larger firms will find it easier to engage in alliances.The lack of reputation by small young firms works negatively forthe transaction costs of alliance formation and leads to adverseselection problems (Teece, 1986). The way the small firm couldcompensate for this is through strong patent position (Stuart, 1998)or a strong portfolio of promising new products (Rothaermel, 2002).Work experience in the same sector is expected to decrease theearly transaction costs of networking (Storey, 1994; Iacobucci andRosa, 2005). The level of education of the business owner canenhance the entrepreneur's motivation and ability to use skills thatare useful in managing enterprises (Storey, 1994). Firms led byentrepreneurs with higher educational attainment and/or prior

work experience in the core field of the company are expected tohave a higher propensity to engage in networking agreements.

Founder education is coded as 1 if the highest educational attain-ment of the founder (or of at least one of the founders) is elementaryeducation; 2 for secondary education; 3 for bachelors degree; 4 forpostgraduate degree except Ph.D.; and 5 for Ph.D. degree.

BUSINESS ENVIRONMENTi captures the general characteristics ofthe business environment of the firm. This set of variables includeswhether the life cycle of products is typically short (life cycle) andwhether customers regularly ask for new products and/or services(new product). Each firm is asked to characterize its businessenvironment using a five-point Likert-type scale where 1 equals“completely disagree” and 5 equals “completely agree”. Shortproduct life cycles and strong pressure for new products oftencharacterize complex business environments. Finally, a set ofdummy variables control for potential country specific effects(country dummy). Country as well as industry effects have beenfound to affect project level risk (Zwikael and Ahn, 2011) and theyare expected to have a marked “cultural” influence on risk taking.

3.2.2. Strategy

STRATEGYji ¼ β1þβ2 RISKjiþβ3 FIRMiþβ4 BUSINESS

ENVIRONMENTiþϵi;for i¼ 1;…;N firms; j¼ 1;…;4 strategies=risk:

where

STRATEGY1i ¼ technology strategy;market strategy;…:;

RISK1i ¼ technology risk;market risk;…:;

The error term is assumed to be normally distributed.

3.2.2.1. Dependent variable. Firms were asked to indicate to whatextent they agree or disagree with the following strategic actionsto sense and seize opportunities.

– Technology strategy is coded as 1 if the firms agree or stronglyagree with at least one of the statements: introducing newproducts/services to the market; having a formal R&D depart-ment in the firm; and having a formal engineering andtechnical studies department in the firm. Technology strategyis coded as 0 otherwise.

– Market strategy is coded as 1 if the firms agree or strongly agreewith at least one of the following statements: respondingrapidly to competitive moves; changing practices based oncustomer feedback; actively and regularly considering theconsequences of changing market demand in terms of newproducts and services; and being quick to recognize shifts inbroad market (e.g. competition, regulation, demography). Mar-ket strategy is coded as 0 otherwise.

– Financial strategy is coded as 1 if the firms agree or stronglyagree with the statement: maintaining formal and informalnetworks in order to have easier access to business funds.Financial strategy is coded as 0 otherwise.

– Operational strategy is coded as 1 if the firms agree or stronglyagree with at least one of the statements: implementingsystematic internal and external personnel training; and havingemployees share practical experiences on a frequent basis.Operational strategy is coded as 0 otherwise.

3.2.2.2. Independent and control variables. We employ the same setof independent variables and control variables as in the setupfor network (Section 3.2.1). Tables 3 and 4 provide descriptivestatistics of the variables and the correlation matrix respectively.


Two sample t-tests in Tables 5 and 6 indicate that the sales ofcompanies that replied positively to networking and to activelytrying to manage risks grew more strongly on the whole than thesales of the rest (statistically significant). This hints that firms thatactively engaged in risk management tended to perform better.

4. Results

4.1. Networking

Table 7 presents the estimation results for the probabilitythat firm i engages extensively in networking activities. Marginal

effects are indicated which measure the estimated change in theprobability of observing networking or strategic action from firm igiven a small change in the value of a variable. We use marginaleffects of estimated variables to discuss the results in this paper ascoefficients of estimation lack a clear interpretation in limited

Table 4Correlation matrix (all sectors).

Variables 1. 2. 3. 4. 5. 6. 7.

1. Network □2. Technology strategy .1139 □3. Market strategy .1074 .1728 □4. Financial strategy .0820 .0780 .0526 □5. Operational strategy .1172 .2492 .3196 .0394 □6. Technology risk .0932 .1276 � .0018 .1270 .0060 □7. Market risk .0851 .0955 .0329 .0902 .0659 .1679 □8. Financial risk .0646 .1372 � .0058 .2867 .0380 .1368 .24359. Operational risk .0360 .0631 .0725 .0524 .0766 .1162 .101410. Firm size .0082 .0447 .0125 .0497 � .0169 .0451 .018711. Founder education .1317 .0823 .0107 .0959 .0497 � .0508 � .034412. Previous work � .0091 .0057 .0007 � .0062 .0111 .0101 � .022513. Life cycle .0092 .0003 .0226 .0431 .0089 .0868 .062414. New product .0799 .1500 .1386 .0781 .0917 .1318 .0767

Variables 8. 9. 10. 11. 12. 13. 14.

1. Network2. Technology strategy3. Market strategy4. Financial strategy5. Operational strategy6. Technology risk7. Market risk8. Financial risk □9. Operational risk .1714 □10. Firm size .0517 .0744 □11. Founder education � .0891 � .0435 � .0071 □12. Previous work � .0424 � .0162 .0081 � .0739 □13. Life cycle .0734 .0443 .0275 � .0711 � .0299 □14. New product .0892 .0787 .0621 � .0228 � .0538 .2199 □

Table 3Descriptive statistics.

Variables Mean (std. dev.)all sectors(N¼3624)

Mean (std. dev.)high-techmanufacturing andKIBS (N¼1929)

Mean (std. dev.)low-techmanufacturing(N¼1695)

Network .5344 (.4988) .6003 (.4899) .4595 (.4985)Technologystrategy

.375 (.4841) .3701 (.4829) .3805 (.4856)

Market strategy .6572 (.4746) .6832 (.4653) .6277 (.4835)Financial strategy .2505 (.4333) .2099 (.4073) .2967 (.4569)Operationalstrategy

.4575 (.4982) .4961 (.5001) .4135 (.4926)

Technology risk 2.2991 (1.1956) 2.2296 (1.1876) 2.3781 (17.2983)Market risk 3.2549 (1.1841) 3.1840 (1.1656) 3.3356 (1.2001)Financial risk 3.0488 (1.5006) 2.8299 (1.5014) 3.2979 (1.4607)Operational risk 3.0482 (1.4005) 2.9891 (1.3880) 3.1156 (1.4119)Firm size 10.3291 (17.9624) 9.0554 (18.4368) 11.7787 (17.2983)Foundereducation

2.9292 (1.0727) 3.2738 (1.0182) 2.5330 (.9944)

Previous work 13.3933 (10.3932) 13.218 (9.7059) 13.5929 (11.1232)Life cycle 2.6302 (1.4998) 2.5365 (1.441) 2.7368 (1.5573)New product 3.1194 (1.3286) 3.0590 (1.3093) 3.1882 (1.3472)

Table 6Two sample t-test comparison of means: average sales growth and internal riskmanagement (all sectors; 2007–2009, end of 2010).

Mean (sales growth,2007–2009)

Mean (sales growth,2010)

Strategy (N¼2813) 36.5756 16.2964No Strategy (N¼502) 21.9552 9.1739Diff. 14.6204 7.1225

t¼1.8146 t¼2.7034P4t¼ .077n P4t¼ .0034nnn

Note: 1. nnnSignificant at 1% significance level; nnSignificant at 5% significance level;nSignificant at 10% significance level. 2. Strategy: firms who have used any of fourtypes of strategies (i.e. technology, market, financial, operational).

Table 5Two sample t-test comparison of means: average sales growth and networking (allsectors; 2007–2009, end of 2010).

Mean (sales growth,2007–2009)

Mean (sales growth,2010)

Networking (N¼1789) 47.7804 19.8106No Networking (N¼1526) 18.63 9.8241Diff. 29.1503 9.9866

t¼2.2597 t¼5.2673P4t¼ .012nn P4t¼ .00001nnn

Note: nSignificant at 10% significance level.nn Significant at 5% significance level.nnn Significant at 1% significance level.


dependent variable models. See Greene (2003). Aggregate resultsacross all sectors are reported in Model 1. Disaggregated results forhigh-tech manufacturing and knowledge-intensive business ser-vices (KIBS) and low-tech manufacturing are reported in Model2 and Model 3 respectively.

Perceived technology risk, market risk, and financial risk posi-tively affect the likelihood of the young firms' extensive engagementin networks. This is especially pronounced in knowledge-intensivesectors. The estimated marginal effects in Model 1, for example,show that the increase in technology risk by one raises the like-lihood of the firm's participating in networks by 2.7%. Increasingmarket risk by one increases the likelihood of networking by 2.2%.Each additional financial risk increases the likelihood of networkingby 1.5%. In contrast, operational risk does not have a statisticallysignificant impact on the firms' propensity to networking acrossboth industry groups.

The implication here is that companies use strategic alliances torespond to increased perceived levels of technology, market, andfinancial risk. Firms in high-tech sectors appear more likely toparticipate extensively in formal networking than firms in low-tech sectors apparently in reflection of the higher expected levelsof all these three sources of volatility there. The lack of statisticalsignificance for operational risk can probably be explained by thenature of the risk itself. This risk refers primarily to the internalorganization and management of own operations, and addresseschallenges arising from the people, systems and processes thecompany utilizes. Strategic alliances may provide knowledgeabout good practices elsewhere and access to people for specifictasks but would not fundamentally contribute to a change of owninternal operations. We acknowledge, however, that our approx-imation of operational risk as human resource risk in this papermay be too narrow.

The positive and statistically significant coefficient on foundereducation demonstrates that firms set up by better educatedentrepreneurs are more likely to participate in alliances. And thatholds strongly across all sectors, knowledge-intensive and others.In addition, the coefficient on new product (introduction) ispositive and significant, indicating that firms operating indemanding business environments where customers regularlyask for new products and services have more incentives to

collaborate. Finally, a statistically significant coefficient for lifecycle points at an association between short product life cyclesand propensity to network in the case of lower technology sectors.We were somewhat surprised that this effect did not carrythrough to knowledge-intensive industries.

4.2. Strategy

Estimation results for the probability that firm i will usetechnology, market, financial, and operational strategy are reportedin Tables 8, 9, 10, and 11 respectively (marginal effects).

Hypotheses 2, 4, and 5 are confirmed: firms are likely toactively try to manage technology risk, financial risk, and opera-tional risk. Strong statistically significant effects carry throughacross both groups of sectors, knowledge-intensive and low-tech.Firms will introduce new products/services to the market and theywill set up formal R&D and engineering and technical studiesdepartments to deal with technology risk. They will try tomaintain networks for easier access to business finance to dealwith financial risk. And they will implement systematic internaland external personnel training while promoting frequentexchanges of practical experiences among employees to deal withoperational (human resource) risk. Interestingly, the coefficient(marginal effect) of each risk – technology, financial, operational –

Table 7Probit estimates of the likelihood of network engagement by firm i (marginaleffects at mean values).

(Model 1) Allsectors

(Model 2) High-techmanufacturing andKIBS

(Model 3) Low-techmanufacturing

Dependentvariable

Network Network Network

Technology risk .0270nnn

(.0079).0320nnn (.0107) .0217n (.0116)

Market risk .0218nnn

(.0079).0263nn (.0108) .0187n (.0116)

Financial risk .0149nn (.0061) .0214nn (.0082) .0156n (.0091)Operational risk .0070 (.0063) .0058 (.0085) .0092 (.0092)Firm size .0005 (.0004) .00002 (.0006) .0007 (.0007)Foundereducation

.0678nnn

(.0082).0457nnn (.0114) .0549nnn (.0130)

Previous work .0003 (.0008) � .0001 (.0012) .0009 (.0011)Life cycle .0092 (.0059) � .0043 (.0083) .0202nn (.0083)New product .0282nnn

(.0067).0224nn (.0093) .0346nnn (.0097)

N 3392 1815 1577Log likelihood �2275.0798 �1188.8028 �1063.2907

Note: Standard errors in parentheses; country dummies omitted.n Significant at 10%.nn Significant at 5%.nnn Significant at 1%.

Table 8Probit estimates of the likelihood of firm i using technology strategy (marginaleffects at mean values).


(Model 2) High-techmanufacturingand KIBS


Dependentvariable

Technologystrategy

Technology strategy Technology strategy

Technology risk .0468nnn (.0070) .0536nnn (.0096) .0383nnn (.0102)Firm size .0008n (.0004) .0003 (.0006) .0012n (.0007)Foundereducation

.0415nnn (.0078) .0436nnn (.0113) .0492nnn (.0125)

Previous work .0008 (.0008) .0002 (.0011) .0013 (.0011)Life cycle .0112n (.0057) .0073 (.0081) .0158n (.0081)New product .0534nnn (.0065) .0578nnn (.0091) .0478nnn (.0094)N 3392 1815 1577Log likelihood �2163.1473 �1144.4177 �1014.9124

Note: nnn, nn, n: Significant at 1, 5 and 10% significance levels; Standard errors inparentheses; Country dummies omitted.

Table 9Probit estimates of the likelihood of firm i using market strategy (marginal effectsat mean values).


(Model 2) High-techmanufacturingand KIBS


Dependentvariable

Marketstrategy

Market strategy Market strategy

Market risk .0104 (.0069) .0117 (.0094) .0113 (.0102)Firm size .0001 (.0004) .0003 (.0006) .0002 (.0007)Foundereducation

.0051 (.0076) .0251nn (.0108) .0186 (.0125)

Previous work .0003 (.0007) .0004 (.0011) .0004 (.0011)Life cycle .0181nnn

(.0056).0161nn (.0078) .0181nn (.0081)

New product .0542nnn

(.0063).0402nnn (.0087) .0709nnn (.0094)

N 3392 1815 1577Log likelihood �2131.1373 �1111.9374 �1006.0409



is generally higher for high-tech manufacturing and KIBS(Model 2) than for low-tech manufacturing (Model 3). That is tosay, firms in knowledge-intensive sectors are more likely to useinternal strategies to manage these risks successfully when per-ceived risk levels are high.

Hypothesis 3 cannot be supported. We could not confirm thatfirms faced with increased levels of market risk are more likelyto employ strategy to actively manage the risk by respondingrapidly to competitor moves, changing practices on the basis ofcustomer feedback, actively following market demand develop-ments, and being quick to recognize shifts in the broader market.A possible explanation is always model misspecification: theutilized variables may not be capturing the right measures ofmarket risk management. Another possible explanation drawson the possibility of their perceiving market risk as largelysystematic (non-diversifiable), depending extensively on exter-nal factors that the company cannot manage consistently. Thismay not be an unreasonable situation to imagine for thecompanies under investigation. Many of these companies arerelatively new (footnote 8), of either micro- or very small size

(Section 3.1), and operate in small national markets (Table 1).The combination can often hide more than average attachmentto a few large clients and a responsive mode of operation whileeschewing a more fully developed market risk strategy. Whatmakes us suspect that this is an important factor here is that theAEGIS survey strongly indicates that these same companiesconsider clients, suppliers and competitors as the major sourcesof knowledge (in that order). They consider the capacity to adapttheir products to client needs as the most important factor forcreating and sustaining comparative advantage. And they con-sider market risk the most important obstacle to companygrowth. In other words, these are not unaware enterprises; theyself-report strong market/client awareness for survival andgrowth.

The coefficients on founder education and new product (intro-duction) are by and large positive and statistically significant,indicating that firms set up by better educated entrepreneursoperating in demanding business environments are more likely tomanage risks actively through internal strategies. Short life-cyclesare strongly related to market risk mitigating strategies and tostrategies for technology risk.

Last but not the least was the unexpected lack of statisticalsignificance of the founder's employment prior to establishing thespecific firm. It is commonly understood that one of the best ways forthe entrepreneur to protect against risk is to set up the new companyin a sector/thematic area in which s/he has had prior exposure.Exposure translates into operational experience, knowledge of thetechnical field and of the market, pre-established networks, and thelike. We do not find a statistically significant relation of this factorwith either risk mitigating strategies (with only one exception ofoperational risk in low-tech sectors) or with networking.

4.3. Summing up

Our results can be summarized as follows:

1. Technology risk and financial risk are positively related both tointernal strategic action for risk mitigation and to networking.

2. Operational (human resource) risk is positively related to inter-nal strategic action for risk mitigation but not to networking.

3. Market risk is positively related to networking but not tointernal strategic action for risk mitigation.

4. Founder education is positively related to networking and tointernal strategic action to mitigate technology risk. It ispositively related to strategic action to mitigate financial andoperational risk in low-tech sectors.

5. New product (introduction) is positively related to both net-working and to internal strategic action to mitigate all types ofrisk across all sectors.

6. Short life-cycles are strongly related to market risk mitigatingstrategies across all sectors. They are related to networking andtechnology risk management in low-tech sectors.

7. Founders' employment just prior to establishing the specificfirm is not significantly related either to networking or tointernal strategic action to mitigate any type of risk.

8. Firms in knowledge-intensive sectors – including high-techmanufacturing and knowledge-intensive business services(KIBS) – are more likely to engage in strategic alliances as wellas use risk mitigation strategies than do firms in low-technologymanufacturing sectors.

5. Concluding remarks

Entrepreneurs enter the market with innovative ideas andproducts designed to fix a problem, make something better, or

Table 10Probit estimates of the likelihood of firm i using financial strategy (marginal effectsat mean values).




Dependentvariable

Financialstrategy

Financial strategy Financial strategy

Financial risk .0825nnn

(.0050).0884nnn (.0062) .0683nnn (.0082)

Firm size .0008nn

(.0003).0002 (.0004) .0015nn (.0006)

Foundereducation

.0297nnn

(.0069)� .0132 (.0089) .0363nnn (.0120)

Previous work � .00001(.0007)

� .0005 (.0009) .0004 (.0010)

Life cycle .0022 (.0050) � .0100 (.0066) .0120 (.0076)New product .0173nnn

(.0057).0110 (.0072) .0231nnn (0088)

N 3392 1815 1577Log likelihood �1756.0403 �822.65214 �917.69482


Table 11Probit estimates of the likelihood of firm i using operational strategy (marginaleffects at mean values).




Dependentvariable

Operationalstrategy

Operational strategy Operational strategy

Operational risk .0267nnn

(.0061).0290nnn (.0085) .0255nnn (.0089)

Firm size � .0007(.0004)

.0002 (.0006) � .0020nn (.0007)

Foundereducation

.0262nnn

(.0080).0040 (.0115) .0294nn (.0127)

Previous work .0010 (.0008) � .0006 (.0012) .0026nn (.0011)Life cycle .0030 (.0058) .0072 (.0084) � .0031 (.0081)New product .0347nnn

(.0066).0291nnn (.0093) .0411nnn (.0095)

N 3392 1815 1577Log likelihood �2309.676 �1245.7529 �1049.8783



offer something completely new. To ignore risk is foolhardy andfor those able to think outside the box, embarrassing. Having asound risk management strategy goes a long way toward thesurvival and long-term success of a venture, especially a new one.The more precise the conceptualization of risk and the moreexplicit the strategy of the firm to mitigate it, the better thechance to attract investors.

This paper has presented an attempt to empirically relate theinfluence of various types of risk on risk mitigation strategies ofyoung small enterprises. The analysis was based on an extensivedatabase of young small enterprises spanning 10 European coun-tries and 18 sectors, including both high-tech and low-techmanufacturing and knowledge-intensive business services. Whensurveyed the enterprises in question were in their “formative age”of 2–8 years old. The paper thus contributes to the literature of riskmanagement by covering a large and diverse set of small firmswhich although still relatively young have survived the first majorshakeout typically happening in the first couple of years followingestablishment. The empirical analysis also links basic character-istics of the company's founder(s) as proxied by education to riskmanagement methods.

To the extent that risks are unsystematic (diversifiable) –

primarily technology risk and operational (human resource) riskin our case – one would expect the firm to use internal riskmitigation strategies to manage them. This is confirmed by ouranalysis across all types of sectors. To the extent that risks aresystematic (non-diversifiable) – primarily market risk and finan-cial risk in our case – they may not be easily amenable to internalstrategic action for management. We find strong evidence thatfirms will try to mitigate financial risk by tapping their formal andinformal networks. In fact, formal network participation (strategicalliances) is a strategy cutting across this division of risk: itappears positively related to both types of systematic risk as wellas to technology risk across all types of sectors. Network participa-tion, on the other hand, does not appear to do much aboutoperational risk besides providing information about good prac-tices and allowing temporary access to external resources.

Firms in knowledge-intensive sectors (high-tech manufactur-ing and KIBS) with relatively higher perceived risk levels would beexpected to try harder. This is exactly what we find here, and itholds for all types of internal risk mitigation strategies as well asfor networking.

Factors characterizing the firm founder(s) and the market thefirm operates in are also important. Founder education is one.Firms led by more educated entrepreneurs tend to engage more instrategic alliances and in various internal strategic actions tomanage risk. Firms operating in demanding volatile markets tendto network more and to use internal strategies to mitigate riskmore extensively.

We were surprised to find the absence of significant statisticalrelationship between the founders' employment just prior toestablishing the specific firm either with networking or withinternal strategic action to mitigate risk. A typical risk manage-ment procedure is the establishment of a new company in an areawhere the entrepreneur has had significant prior experience. Morethan four-fifths of the surveyed entrepreneurs in AEGIS gradedprior work experience in the current activity field as of high orvery high importance, while three quarters graded relevantmarket knowledge similarly, and more than two-thirds gradedtechnical/engineering knowledge and networks built during theirprevious career similarly. This topic will need to be investigatedfurther in the future. Another step would be to differentiatebetween knowledge-intensive services and manufacturing. Profes-sional service firms are presumed to be distinct from other types(Blind et al., 2003; Greenwood et al., 2005): they are heteroge-neous and the knowledge content of the services provided is

diverse. Finally, in light of the strong results on entrepreneureducation, further effort is warranted to empirically investigate ingreater detail the impact of this seemingly very important factoron small company risk mitigating behavior.

In conclusion, we must acknowledge a couple of limitations ofthe paper. The first limitation results from the nature of theavailable data. The underlying survey did not identify specificcases of risk and risk mitigation efforts for the respondingcompanies. Rather, it asked respondents about their perceptionof the existence of the various types of risks and about their ratingon a Likert scale of the importance of various risk mitigation“capabilities” in their day-to-day operation. For example, they maysay “we perceive technology risk as very important in our line ofbusiness” and at the same time they may rate one or more of thefollowing actions as very important: frequently introducing new/products services; maintaining a formal R&D department; andmaintaining a formal engineering and technical studies depart-ment in-house. While these are not specific actions to directlymanage specific occurrences of risk, they are at least actions tomaintain capabilities to respond to such occurrences. The paper isbased on an implicit assumption that the link between the two isvery strong. Future analyses may focus more accurately on specificprocedures of risk identification, risk analysis, risk responseplanning, and risk monitoring. The second limitation is due tothe fact that the paper does not link the risk mitigation behavior ofyoung small companies to market performance. Due to the size ofthe examined company sample, the micro-/small size of theinvestigated companies and their spread across ten heterogeneouscountries it was doubted that reliable data on market performancecould be obtained. Future investigations with more concise com-pany populations should try to link risk management to thecreation of competitive advantage and market performance.

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