The business plan as a project: an evaluation of its predictive capability for business success
The business plan as a project: an
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The business plan as a project: an
evaluation of its predictive capability for business success Rafael Fernández-Guerrero a , Lorenzo Revuelto-Taboada a & Virginia Simón-Moya a a Business Management, University of Valencia, Av. Los Naranjos, Valencia, 46022, Spain Version of record first published: 30 Apr 2012. To cite this article: Rafael Fernández-Guerrero, Lorenzo Revuelto-Taboada & Virginia Simón- Moya (2012): The business plan as a project: an evaluation of its predictive capability for business success, The Service Industries Journal, 32:15, 2399-2420 To link to this article: http://dx.doi.org/10.1080/02642069.2012.677830 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.tandfonline.com/page/terms-and- conditions This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. The business plan as a project: an evaluation of its predictive capability for business success Rafael Ferna´ndez-Guerrero, Lorenzo Revuelto-Taboada and Virginia Simo´n-Moya ∗ Business Management, University of Valencia, Av. Los Naranjos, Valencia 46022, Spain (Received 21 January 2012; final version received 24 January 2012) Although there is extensive research aimed at identifying the main success factors for new ventures, efforts directed at evaluating the real effect of the existence and quality of a business plan on a firm’s survival chances have been limited. This study attempts to fill this gap by analyzing to what extent the quality of a business plan, measured according to its economic, financial and organizational viability, constitutes a good predictor of business survival; and how other variables related to the characteristics of the entrepreneur and the business can affect the predictive capability of the model under consideration. Hypotheses are tested using data collected from 2142 service firms. The results show that none of the three variables that evaluate business plan quality (economic, financial and organizational viability) seems to have a determining influence on survival chances. Adding essential characteristics related to the entrepreneur and the business (education and training, experience, kind of motivation, number of employees and start-up capital) does little to increase the model’s predictive capabilities. Keywords: business plan; entrepreneurship; new ventures; survival Introduction Ample evidence supports the suggestion that start-ups play a crucial role in job creation, economic growth, innovation and competitiveness (Acs, Arenius, Hay, & Minniti, 2005; Armington & Acs, 2002; Audretsch & Thurik, 2001; Carree, Van Stel, Thurik, & Wene- kers, 2002; Davidsson & Wiklund, 2001; Johnson, 2004; Minniti, Bygrave, & Autio, 2006; Storey, 1994). This circumstance has made the promotion of entrepreneurship a funda- mental part of any modern economy. Consequently, since the 1980s, a growing number of either public institutions or institutions with significant public participation have shown an increasing interest in promoting and encouraging the creation of new business. This has resulted in a considerable increase in the number and variety of the measures aimed at promoting and supporting the start-up of new ventures, as well as in the economic resources invested. In general, while both large private and public companies, that operate at either a national or a multinational scale, represent a basic element of the production structure, small and medium-sized enterprises (SMEs) constitute the immense majority of the business sector and represent a fundamental element in the employment structure. In Spain, authors, such as Ruano (2001) and Garcı´a et al. (2002), emphasize their importance in job creation, compared to that of large companies. More specifically, Ruano’s work suggests that the rate of job creation is inversely proportional to the size of the firm. ISSN 0264-2069 print/ISSN 1743-9507 online # 2012 Taylor & Francis http://dx.doi.org/10.1080/02642069.2012.677830 http://www.tandfonline.com ∗ Corresponding author. Email: virsimo@alumni.uv.es The Service Industries Journal Vol. 32, No. 15, November 2012, 2399 – 2420 Downloaded by [University of Valencia] at 09:48 23 September 2012 At the international level, the job creation role played by SMEs has been discussed in a number of papers such as those of Davis, Haltwanger, and Schuh (1994, 1996), Kongolo (2010), Schreyer (1996) and Storey (1994), among others. These small businesses are the main recipients of those public initiatives aimed at stimulating the establishment of new businesses, since their main objective is to generate opportunities for sustainable employment through self-employment and employment at already existing microfirms and SMEs. Leaving aside infrastructure development programs and economic policy in general, business start-up support programs may translate into various types of activities directed toward training, access to relevant information, appreciation of the role played by entrepreneurs in society, advice prior to setting up a firm, monitoring and counseling subsequent to setting up a business, help in carrying out applicable legal procedures, setting up business incubators, financial support, establishing entrepreneurial networks, etc. (Toledano & Urbano, 2007). Some of these initiatives are designed for the adult population in general, while others are aimed at certain demographic segments with specific employability issues (young people, women and residents in rural areas) or simply at unemployed individuals. With growing stimulus from entrepreneurship programs on the part of public admin- istrations, universities and other promoting bodies, business plans have achieved consider- able relevance in the business management field. For those companies that turn to public institutions looking for help in setting up their business, the business plan plays a crucial role. In some cases, the business plan itself is the end result of free counseling, and in the case of financial support measures, in general, the business plan represents a key element for cheap or cost-free financing eligibility. If we focus on the issue of financial support, it is often the case that the instance of making the decisions will establish a scale to evaluate the different applications, a scale that will consider business plan quality to be of utmost importance, assuming that a good business plan is a guarantee for start-up viability and, therefore, that public funding is being put to good use. But is this really true? Is a good business plan such a decisive factor? What other conditions must be met to ensure that the public funds invested in a private project will pay off? These are the issues that we tackle in the following sec- tions, and for this, we analyze the business plan as a project aimed at managing, as its overriding goal, to successfully survive the first stages of the business life cycle that, as we go on to see, are those that entail the highest risk of failure. This paper aims to analyze to what extent the quality of a business plan, measured according to its economic, financial and organizational viability, constitutes a reliable predictor of business survival and how other variables related to the characteristics of the entrepreneur and the business can affect the predictive capability of the model under consideration. The following section offers some relevant data about the survival probabilities of new ventures and briefly reviews the different success factors that have been analyzed in the specialized literature. The next section analyzes the business plan from the perspective of project management, followed by hypotheses on the quality of the business plan as a predictor of future venture survival. The next two sections are devoted to explaining the methodology of the research and the results obtained from a sample of 2401 service companies, created between 2000 and 2004, by young entrepreneurs in the Valencia Autonomous Region in Spain. The final discussion section presents the main conclusions derived from the results and states the limitations of the study, as well as providing some future research proposals. 2400 R. Ferna´ndez-Guerrero et al. Downloaded by [University of Valencia] at 09:48 23 September 2012 Survival and success factors for start-ups Recent decades have witnessed a great deal of discussion on the factors considered to be critical for start-up survival and success. The literature typically takes into account three groups of explanatory variables: those relating to the characteristics of the entrepreneur, those relating to the characteristics of the newly founded firm, and those external factors embracing the geographical and industrial environment in which entrepreneurial phenomena occur (Franco & Haase, 2010; Schutjens & Wever, 2000). What is beyond any doubt today is that young companies show higher closure rates in their first few years of existence. Many studies that have examined the behavior of young firms have provided evidence of the frailty of newly created businesses. For example, Phillips and Kirchhoff (1989), using Dun & Bradstreet data, found that 76% of new firms were still open after 2 years, 47% after 4 years and 38% after 6 years. Headd (2003), using the BITS database, found that 66% of new firms were still in existence after 2 years, 49.6% after 4 years, and 39.5% after 6 years. In France, official data report firm mortality at about 50% in the first 5 years of existence (Letowski, 2004). American authorities indicate that about 56% of firms’ have closed after 4 years (Knaup, 2005). The OECD declares that only between 40% and 50% of new firms survive after 7 years of existence (Cotis, 2007). Finally, in Spain, firm survival after 4 years is around 53% (Caneda & Garcı´a, 2008). As we can see, all these studies show reasonably similar results in terms of survival rates of business entrepreneurship. Stinchcombe (1965) argued that young organizations had a higher propensity to die than older ones. To name this phenomenon, he coined the term ‘liability of newness’. This hypothesis became a main issue in organization theory during the 1980s, in accord- ance with the thesis of the new population ecology approach (Hannan & Freeman; 1977, 1989). There are four main reasons that explain the greater risk of failure that young firms face. Firstly, they depend on new roles and tasks that have to be learned at certain costs. Secondly, sometimes roles have to be developed, and this may be in conflict with constraints on resources or creativity. Thirdly, social interactions in a new organization resemble those between strangers, and a common normative basis or informal information structure may be lacking. Finally, stable links to clients, supporters or customers are not yet established when an organization begins its activity (Bru¨derl & Schussler, 1990; Singh, Tucker, & House, 1986). Organizational members take time to learn to trust and cooperate with one another (Stinchcombe, 1965), and learn organizational specific skills and routines (Nelson & Winter, 1982). External legitimacy is also a critical problem for young organizations. In short, new firms depend on the cooperation of strangers having low levels of legitimacy and less capacity to compete effectively against established organizations (Freeman, Carroll, & Hannan, 1983). Although the findings of many studies indicate that a genuine inverse relation exists between age and death rates (Carroll & Delacroix, 1982; Halliday, Powell, & Granfors, 1987; Hannan & Freeman, 1989), as was predicted by Stinchcombe (1965), others cast doubts on the validity of this assumption (Aldrich, Staber, Zimmer, & Beggs, 1989; Carroll & Huo, 1988; Fichman & Levinthal, 1991). Taking into account this contradiction, Bru¨derl and Schu¨ssler (1990) developed what is known as the ‘liability of adolescence’. Contrary to Stinchcombe (1965), Bru¨derl and Schu¨ssler (1990) point out that the failure rates are minor at the beginning of the business, but later, mortality rates begin to grow and later climax. This final decline of the risk of failure is assumed to be due to the The Service Industries Journal 2401 Downloaded by [University of Valencia] at 09:48 23 September 2012 same reasons that led to the liability of newness hypothesis. The initial period of rising risk is a result of the influences of initial resources stocks and the rational behavior of entre- preneurs. In the first stage, referred to as adolescence, the risk of failure is low, essentially for two reasons: firstly, because decision makers are monitoring performance, postponing judgment about success or failures; secondly, because in this first period, organizations have a certain amount of initial resources, which help them to survive for some time in order to give them a chance to establish themselves and to help founders and other relevant stakeholders to gain a basis for judging performance (Bru¨derl & Schu¨ssler, 1990). Although these authors do not agree on a specific period of higher risk, it is patently clear that the first stages in a firm’s life cycle entail higher risk of failure. Apart from the firm’s own longevity, when analyzing the explanatory factors of business success or failure, the doctrine has emphasized, first and foremost, the entrepreneur himself, which has led researchers to carefully consider variables such as age (Doutriaux, 1992; Sapienza & Grimm, 1997; Van Praag, 1996), race and gender (Bates, 1997; Robb & Fairlie, 2009), education level (Astebro & Bernhardt, 2003; Bates, 1997; Headd, 2003; Schiller & Crewson 1997; Van de Ven, Hudson, & Schroeder, 1984), previous experience, in managerial positions, as an entre- preneur and/or in the industry (Doutriaux, 1992; Dyke, Fisher, & Reuber, 1992; Luk, 1996; Pen˜a, 2002; Reuber & Fisher, 1999), having a self-employed family member (Robb & Fairlie, 2009), motivation to create a business (Alstete, 2008; Kautonen & Palmroos, 2010; Van Praag, 2003; Van Praag & Cramer, 2001) and the psychological profile of the entrepreneur (Alstete, 2008; Brockhaus, 1982; Brockhaus & Horwitz, 1986; Herron & Robinson, 1993). Although partially contradictory results have been occasionally found, in general, results show the existence of significant differences in the chances of survival of these variables. Of particular relevance is the importance endowed to those variables related to human capital (Becker, 1975; Hormiga, Batista-Canino, & Sa´nchez-Medina, 2011; Wakkee, Elfring, & Monaghan, 2010). Variables which show more questionable results are those related to the entrepreneur’s psychological profile, which makes it impossible to establish a link with the new venture’s success. A second set of widely used explanatory variables relates to the characteristics of the business or organization. The most widely used, besides the previously discussed organiz- ation’s age or longevity, have been those related to the size of the organization, number of employees (Argawal & Audretsch, 2001; Dunne & Hughes, 1994; Lo´pez-Garcı´a & Puente, 2006) and financial start-up capital (Bru¨derl, Preisendo¨rfer, & Ziegler, 1992; Cooper, Gimeno-Gaston, & Woo, 1994; Headd, 2003; Krasniqi, 2010; Schutjens & Wever, 2000; Smolarski & Kut, 2011). Several authors, who usually employ these variables as proxies for the firm’s initial resources endowment, pose the ‘liability of size’ or ‘liability of smallness’ hypothesis, which has been, in general, empirically validated (Bru¨derl & Schussler, 1990; Singh et al., 1986). Other variables taken into consideration are legal form, the presence or not of entrepreneurial teams and organizational strategy (Keeley & Roure, 1990; McDougall, Covin, Robinson, & Herron, 1994; McDougall, Robinson, & DeNisi, 1992; Pen˜a, 2002; Robb & Fairlie, 2009; Schutjens & Wever, 2000), and innovation (Ca´ceres, Guzma´n, & Rekowski, 2011; Cavalcante, Kesting, & Ulhøi, 2011; Goktan & Miles, 2011; Hotho & Champion, 2011; Huang, Chou, & Lee, 2010; Huarng & Yu, 2011; Naranjo-Valencia, Jime´nez-Jime´nez, & Sanz-Valle, 2011; Zhang & Duan, 2010). Certain environmental factors have been considered as explanatory variables for entre- preneurial success such as type of industry and/or its characteristics (Audretsch, 1991; Carter, Stearns, Reynolds, & Miller, 1994; Keeley & Roure, 1990; McDougall et al., 1992, 1994; Schutjens & Wever, 2000); regional characteristics such as entrepreneurial climate, location specific advantages, public policies, economic growth and unemployment 2402 R. Ferna´ndez-Guerrero et al. Downloaded by [University of Valencia] at 09:48 23 September 2012 levels, the role of universities and the existence of business incubators and business networks (Acs, Armington, & Zhang, 2007; Alpkan, Bulut, Gunday, Ulusoy, & Kilic, 2010; Keasy & Watson, 1991; Pen˜a, 2002; Reynolds, Storey, & Westhead, 1994; Robb & Fairlie, 2009; Schutjens & Wever, 2000; Sorenson & Audia, 2000; Storey, 1994; Tama´sy, 2006). It is worth mentioning that recent studies have contemplated a wide range of explanatory factors included in the three aforementioned groups (Cassia & Colombelli, 2010; Lussier & Halabi, 2010; Pen˜a, 2002; Robb & Fairlie, 2009; Tama´sy, 2011). However, when considered separately, the explanatory capability of each factor is usually low, but when considered jointly the explanatory potential of the models becomes significantly enhanced, and it is possible to develop a better conceptualization of the entrepreneurial phenomenon. Neverthe- less, in spite of (a) the transcendental importance endowed to the business plan in the scientific literature; (b) the number of public and semi-public programs aimed at helping future entrepreneurs make good business plans and (c) the fact that the assessment of quality has been commonly used as a key criterion for granting economic support measures, it is very difficult to find research that has empirically analyzed whether, in reality, a business plan may become a determinant factor in the survival and success of new ventures. Studies by Busstra and Verhoef (1993), Henninger et al. (1993) and Bru¨derl et al. (1996) 1 are exceptions, along with research based on the Lussier (1995) model. It is worth mentioning that their findings are contradictory, occasionally showing evidence for or against planning having a positive effect on survival. Along these lines, this paper deals with the question of how to analyze the impact a business plan might have on the chances of business survival, considering business plan quality, not merely its existence or degree of specificity, as in the studies previously mentioned. This study also analyzes how other variables related to the characteristics of the entrepreneur, the business and the sector can affect the predictive capability of the model under consideration. Business plans and project management Setting up a firm is a process subject to restrictions of a technical, administrative, legal, financial and economic nature (Anderse´n, 2011; Van Stel, Storey, & Thurik, 2007), which will influence its development and, therefore, will determine the nature of the business plan, as well as its contents and structure. This business plan is a written docu- ment that systematically, and in an orderly fashion, details a firm’s strategic and operative aspects, and should therefore allow for the assessment of a business project’s economic, financial, commercial and legal administrative viability. As a map guides a traveler, a business plan must make it possible to determine in advance where we want to go to, where we are now and the necessary guidelines for achieving the stated goal. The plan represents a communication tool that allows management, workforce, suppliers, financial institutions and other stakeholders to become familiar with the firm’s project and its goals and objectives (Bourne, 2011; Comeche & Loras, 2010; Ga´mez-Gonza´lez, Rondan- Catalun˜a, Diez-de Castro, & Navarro-Garcia, 2010; Lin, Lin, & Lin, 2010; Mainardes, Alves, & Raposo, 2011; Sebora & Theerapatvong, 2010). As Varela (2001) points out, the business plan is a mechanism used to project the firm into the future, to foresee difficulties and to identify possible solutions for the different situations that may arise, and makes it possible to reduce the project’s risks by making decisions with more and better quality information, as well as enabling the firm to connect with its environment (Arendt & Brettel, 2010; Ca´ceres-Carrasco & Guzma´n- Cuevas, 2010; Liu & Hsu, 2011; Park, Lee, & Hong, 2011; Salavou, 2010, Sonmez & Moorhouse, 2010; Ullah, Abbas, & Akbar, 2010; Visscher & Visscher-Voerman, 2010). The Service Industries Journal 2403 Downloaded by [University of Valencia] at 09:48 23 September 2012 The plan must develop the procedures and strategies needed to turn a business opportunity into a reality (Mele´ndez, 2005). Furthermore, it must become a reference point to measure the firm’s performance during its implementation, by incorporating financial, manage- ment, social and legal projections (Sapag & Sapag, 2003). The Guide to the Project Management Body of Knowledge (PMIw, 1996, p. 4) defines a project as ‘a temporary endeavour undertaken to create a unique product or service. . ..’ and project management as ‘the application of knowledge, skills, tools and techniques to project activities in order to meet or exceed stakeholder needs and expectations from a project’ (PMIw, 1996, p. 6). Taking into account these definitions, there is no doubt that a business plan can be conceived as a project, the first and most important project a start-up must face, to turn a business opportunity into a reality. As Sense and Fernando (2011) state, other authors, such as Gido and Clements (2003), Gray and Larson (2002) or Turner and Mu¨ller (2003), among others, ‘support those defi- nitions, but in addition, highlight that projects are non-routine processes that involve the novel coordination of interrelated activities and resources to achieve beneficial change’. Such attributes clearly emphasize the complex, emergent and negotiated nature of project activity as achieved through the collective interactions of project participants and other inter- ested stakeholders. If we take into account this more complete definition, we still can state without any doubt that a business plan can be conceived and analyzed as a project, because it possesses all these relevant features (Cegarra-Navarro, Sa´nchez-Vidal, & Cegarra-Leiva, 2011; Lindblom & Tikkanen, 2010). This approach is consistent with a broad sense of the concept of project management that may allow for relevant contributions to this disci- pline in the field of management. Kwak and Anbari (2009), in their paper, consider strategic discipline as one of the associated disciplines of project management, which promotes the analysis of issues relating to the organization and management of resources to maximize profit, minimize costs and support the overall strategy of the organization, taking into con- sideration contributions made from the field of project management studies. The quality of the business plan as a predictor of future venture survival The few studies that have analyzed the impact of an existing business plan on chances of firm success show contradictory evidence. On the one hand, papers by Busstra and Verhoef (1993) and Henninger et al. (1993) conclude that having a business plan is not a guarantee for success. On the other hand, Bru¨derl et al. (1996) demonstrated on the basis of an extensive retrospective study that creating a business plan could have a positive influence on the chances of success. In the papers by Lussier (1995), Lussier and Pfeifer (2001) and Lussier and Halabi (2010), apart from other variables related to the entrepre- neur and characteristics of the business, using a scale from 1 to 7, they evaluate the extent to which firms develop specific business plans and propose the hypothesis that firms that do not develop such plans are more likely to fail. Their findings identify a positive effect from the existence of these specific plans on the chances of firm survival. If we assume that the business plan constitutes a non-routine process that involves the novel coordination of interrelated activities and resources to achieve survival after the first and riskiest phase of the life cycle of a venture; a complex and dynamic project, whose objectives have to be achieved through the collective interactions of project participants and other interested stakeholders, it would be somewhat naive to believe that the mere existence of a plan might have a positive impact on the probabilities of success. One cannot disregard the fact that, as Papke-Shields, Beise, and Quan (2010, p. 650) state, ‘although some improvements have been seen in terms of project success, a relatively 2404 R. Ferna´ndez-Guerrero et al. Downloaded by [University of Valencia] at 09:48 23 September 2012 high frequency of project failures has been reported elsewhere as well’, and that in this case, the project’s failure brings about the closure of the firm. In the literature on project management, there is an abundance of studies that have attempted to identify the critical factors in any project’s success. Based on these studies, different standards have been developed that seek to codify good practices in project management disseminated by institutions such as the Project Management Institute (PMI w, 1996), the Association for Project Management (2006), the International Project Management Association (2009) and so on. Nevertheless, there is still a lack of consensus among researchers on the factors that influence the success of most projects. The most commonly cited include leadership; support from senior managers; clear and realistic objectives, aligned with the business strategy; a detailed plan kept up to date; good com- munication and feedback; the use of specific project management practices, tools and techniques; a highly project-oriented resource allocation system; specific training; stake- holder analysis; and continuous assessment (Papke-Shields et al., 2010; Shy, 2011). In addition, it must be said that in the case of projects conducted in uncertain environ- ments, which is the case of business plans, project management presents the following challenges: (a) planning for uncertain outcomes; (b) balancing flexibility with reliability and accountability; (c) balancing decision quality against decision speed and (d) timing scope freeze during rapid change (Collyer & Warren, 2009). Consequently, as Pich, Loch, and De Meyer (2002) state, a ‘learning strategy’, which involves scanning, problem-solving and flexibility, is needed to succeed in project management, in our case in the consolidation of a new venture. In conclusion, the formulation of a business plan alone cannot be considered as a guar- antee of success or, more specifically, in the case considered here, of new ventures. Such a plan must be correctly implemented, using adequate resources and methodologies, and its contents should be constantly adapted, depending on the evolution of the relevant variables in its environment (Aspara, Lamberg, Laukia, & Tikkanen, 2011; Yang & Li, 2011). All this connects, therefore, with the body of literature on strategy that pushes for a rational and at the same time emergent strategy formation process that combines both the need to adopt planned and rational processes and the need for flexibility and participation when organizations have to formulate and implement strategies in order to become competitive in today’s environments (Andersen, 2004; Brews & Hunt, 1999; Grant, 2003; Hart & Banbury, 1994; Mintzberg & Lampel, 1999; Whittington, 2006; Wilson & Jarzabkowski, 2004; among others). Without it, the chances of overcoming the challenges posed in the first stages of a firm’s life cycle are substantially reduced. It must also be stated that, although creating and evaluating a formal business plan con- stitute basic elements in most self-employment promoting public initiatives and start-up support programs, there is not, in general, a monitoring of the entrepreneurial initiatives that have benefited from financial or non-financial support measures. The situation may arise where business plans are formally created and adjusted to the requirements of each support program, specifically designed by the promoters or specialized advisors (who in some cases make a line of business out of presenting this kind of application) to obtain subsidies, without really having the capability to implement the plans or the will to do so. In this instance, the business plan is a mere artifice aimed at achieving a short-term goal, that is, securing public aid. In light of these observations, we propose the following hypothesis: H1: There is no positive and relevant correlation between the quality of a firm’s business plan and its chances of survival. The Service Industries Journal 2405 Downloaded by [University of Valencia] at 09:48 23 September 2012 Although it is highly likely that the mere existence of a business plan, even when it is well articulated and consistent, may by itself substantially enhance the chances of success of new ventures, it can be expected that when entrepreneurs and businesses also fulfill the right conditions, the joint effect of these variables may well translate into greater survival probabilities. As the specialized literature indicates, much of the success of a new firm is determined by the founder’s characteristics (Korunka, Kessler, Frank, & Lueger, 2010). Specifically, three of the most important characteristics of an entrepreneur which can have a positive effect on the success probabilities of a firm are education (Astebro & Bern- hardt, 2003; Bates, 1997; Gimeno, Folta, Cooper, & Woo, 1997; Headd, 2003; Schiller & Crewson, 1997; Van de Ven et al., 1984), previous experience (Doutriaux, 1992; Dyke et al., 1992; Luk, 1996; Pen˜a, 2002; Reuber & Fisher, 1999) and motivation to start a new venture (Alstete, 2008; Headd, 2003; Van Praag, 2003; Van Praag & Cramer, 2001). An entrepreneur’s training and experience may have a substantial influence on the business plan’s adequate formulation and the ability to adapt to changes in its environment and implementation substantially increases the chances of success (Castro- giovanni, 1996; Haber & Reichel, 2005; West & Noel, 2009). On the other hand, when entrepreneurs’ motivation derives from a business opportunity, that is, when entrepreneurs are driven by the search for independence, autonomy and the will to set up their own business, not only the need to work, rigor and accuracy in planning, but also an increased disposition to make all necessary efforts to ensure that the business plan becomes a sustainable reality can be expected (Headd, 2003; Ho & Wong, 2007). In terms of business characteristics, two of the most analyzed factors that have consist- ently shown a positive and relevant relation with success of new ventures are the number of employees (Argawal & Audretsch, 2001; Dunne & Hughes, 1994; Lo´pez-Garcı´a & Puente, 2006) and financial start-up capital (Bru¨derl et al., 1992; Cooper et al., 1994; Headd, 2003; Schutjens & Wever, 2000). Therefore, the larger the number of employees and the initial financing the new venture has at its disposal to launch its business activities, the better its chances of survival. This is consistent with the ‘liability of adolescence’, hypothesis proposed by Bru¨derl and Schu¨ssler (1990). According to this theory, the larger the resources companies have at their disposal, the better their survival chances during their initial stage of existence. This might help them to keep functioning long enough to identify adequate organizational routines, learn to cooperate with the various internal and external stakeholders, obtain legitimacy and develop the knowledge and skills needed for an adequate implementation of the business plan, as well as to adapt its contents, plans and processes depending on the evolution of the relevant variables in the environment. Considering these variables on the characteristics of the entrepreneur and the business leads us to propose the following hypothesis: H2: The combination of a good plan and an adequate entrepreneurial profile (with training and experience both significant and relevant to the line of business, and driven by opportunity), and the business (businesses with a minimum size in terms of human and financial resources) could become a reliable indicator of new venture survival chances. Methodology Sample characteristics Collaboration with the Program Management and Planning Service from the Valencia Institute of Youth (IVAJ) provided data from 2401 service companies, created between 2000 and 2004, by young entrepreneurs aged under 30 years, or under 30 years but partnered 2406 R. Ferna´ndez-Guerrero et al. Downloaded by [University of Valencia] at 09:48 23 September 2012 with co-workers aged over 30 years; 2142 were pure business ventures and 259 fostered activities of social interest. 2 Collaboration with IVAJ focused on the evaluation of projects presented by entrepreneurs from enterprises of less than a year old which applied for a grant. The information used was obtained from the project portfolio presented to obtain the grant, from the annual report of the aid program to enterprises created by young entrepreneurs, and from monitoring firms created using the databases of the Chambers of Commerce of Alicante, Castello´n and Valencia. This study is based solely on the companies evaluated in service sectors, as information on the rejected ones is extremely limited. Variables used in the study Dependent variables Survival by 31 December at the third- and sixth-year mark from the date of institution of the firm were taken as dependent variables. These two variables are dichotomous and indicate whether the firm survived or not at the moments t + 3 and t + 6. Independent variables The first group of variables includes the three dimensions of business plan quality taken into account by the IVAJ and assessed by a group of five experts 3 : . Economic viability: assesses competitor analysis, level of internal skills, stated objectives and the kind of competitive advantages it will attempt to exploit, basically from the logic of consistency. . Financial viability: assesses the financing schemes put to use, debt levels, funding generating capabilities and, in general, economic status and future projections. . Organizational viability (OV): assesses past and future practices connected with various firm functions, procurement, operations, finance, marketing and human resources. The second group of variables includes entrepreneur characteristics related to edu- cation, experience and motivation to start a business: . Education level: a categorical variable that includes four levels of education: primary school; high school + vocational training I; vocational training II + bacca- laureate; and university studies. . Related education: a dichotomous variable that indicates whether the entrepreneur has some type of specific education related to the business. . Related experience: a dichotomous variable that indicates whether the entrepreneur has at least a year of work experience related to the business. . Motivation to undertake a business: a dichotomous variable that indicates whether a business started out based on opportunity or necessity. A third set of variables representing the amount of resources at the start-up’s disposal when launching its activities are the following: . Workforce: the total number of stable employees, including entrepreneurs. . Initial capital: proxy of initial capital, subsidized capital according to the criteria of Program Management and Planning Service from IVAJ. One last set of variables is included in order to control the effect of the firm belonging to different subsectors and the effect of its condition as purely business-driven concern, a socially oriented business or a mixture of the two on its chances of survival. The Service Industries Journal 2407 Downloaded by [University of Valencia] at 09:48 23 September 2012 . Sector: a categorical variable based on two digits pertaining to the CNAE-93 classi- fication. This variable has seven categories that group different but related sectors. . Kind of venture: a dichotomous variable that indicates whether the firm is a pure business venture or is a social or mixed venture. It is important to establish that the values assigned to economic, financial and organ- izational viability, related education, related experience and type of activity were set by the expert evaluators of the IVAJ program, taking into account the information included in the project portfolios. In order to avoid possible risks and to improve the reliability of the evaluations, each year a select sample of firms was chosen which was successively evaluated by different experts. Any discrepancies found were analyzed to resolve such issues and to unify the criteria used in the evaluation. The remaining variables are objec- tive ones obtained from entrepreneurs and the Chambers of Commerce. Methodology of statistical analysis Due to the nature of the dependent variables (survival in t + 3 and t + 6), we opted to use the Mann – Whitney test for two independent samples, and a multivariate logistic model or logit model. The level of significance used in all of the analyses was 5% (a ¼ 0.05). The bivariate analysis techniques allow identification of the variables that individually have explanatory capacity in relation to the survival of the companies. The Mann – Whitney test for two independent samples was employed in order to contrast whether the distri- bution of a parameter, at least in an ordinal sense, is the same in two independent samples. For example, it has been used to test if there is a relationship between firm survival chances and the quality of their business plan, assessed in terms of its economic, financial and organizational viability. In order to complete the previous bivariate analysis, a logistic regression model, pre- viously used by authors such as Headd (2003), Lussier (1995), Lussier and Halabi (2010) and Lussier and Pfeifer (2001), among others, which estimates the relationship or associ- ation between two variables taking into account the fact that other factors may exist which can modify this relationship, was estimated. This logit model expresses the probability of not surviving as a function of a number of independent variables. The logistic model expresses the odds 4 as an exponential function of two independent variables: p 1 − p = e b 0 +bX 1 +bX 2 , where p is the probability of not surviving and X i (i ¼ 1, 2, . . ., n) are the independent variables (education, experience, etc.). The b i are the regression coefficients used for estimation in the analysis. An equivalent way of writing this equation is p 1 − p = e b 0 e b 1 X 1 e b 2 X 2 . One can see that the unit increase of a factor X i multiplies the odds by the value e b i , and thus, the significant influence of a factor is going to be measured in terms of variation produced in the odds of non-survival. The entry model of variables is conditioned on a step-by-step basis, with an entry p- value of 0.05 and an exit p-value of 0.1 for the variables. Different measures of goodness of fit are applied: the statistical minus twice the Napierian logarithm of the verisimilitude 2408 R. Ferna´ndez-Guerrero et al. Downloaded by [University of Valencia] at 09:48 23 September 2012 (22LL), 5 and the R 2 coefficient of Nagelkerke. 6 In the same way, the Hosmer and Lemeshow test was used to contrast the calibration of the model, that is, the degree to which the prognosticated probability conforms to reality. It must be noted, finally, that the researchers have had access to a large amount of information, both of a qualitative and of a quantitative nature, included in the projects’ briefings, IVAJ annual reports, experts’ reports, as well as data obtained through inter- views with the directive and technical staff at the Program Management and Planning Service. All this information has been of great help for the planning of the research, as well as for the interpretation of its findings. Results Sample characterization The sample is made up of 2401 service firms founded between 2000 and 2004 by young entrepreneurs aged under 30 years, or under 30 years but partnered with co-workers aged over 30 years. The enterprises created in the year 2000 were 12.7% ; in 2001 were 15.2%; in 2002 were 21.7%; in 2003 were 24.1% and in 2004 were 26.3%. Only 259 of these firms have some degree of social interest. The test sample is made up of small enterprises, with a workforce which ranges from 1 to 34 employees (entrepreneurs included), with an average of 1.83 employees. Eligible capital (proxy to invested capital) ranges between 1000 and 494,052 euros, with an average of 30,345.81 euros. By sector, 32% are commerce/retail related; 16% ascribe to other business activities (legal services, accounting and financial advisory, and architectural and technical engineering services); 14% correspond to different professional services (dry cleaners and hairdressers); 12% hotel and restaurant industry; 8% health care, veterinary medicine and social services; 3% transportation and telecommunications; and the remaining 15% belong to other economic sectors with scant representation. Significantly, 72% of the surveyed companies survive up to 3 years, whereas by the sixth year this percentage drops to 54%. With regard to the entrepreneurs, 59% start a business out of necessity and the remaining 41% through opportunity. As for their level of education, 13.1% have primary education, 15.4% attended secondary school or vocational training I, 25.3% high school or vocational training II, and 46.2% have a university degree; 64.1% have training related or specific to the venture and 66.4% have experience which is relevant or specific to the business. Survival and quality of the business plan In order to establish whether there is any kind of relation between business plan quality and chances of the firm’s survival, the non-parametric Mann – Whitney test was used, since the distributions of the economic, financial and organizational viability variables did not meet the parametric assumption of normality. The results in Table 1 show relevant differences for the first 3-year period only in the organizational viability variable (p ¼ 0.05) between companies that survive and those that do not. By the sixth year, these relevant differences in organizational viability are maintained, and one can also detect relevant differences in economic viability. In both cases, the values of these variables are higher for the companies that survive. For the assessment of a relation’s robustness between viability plan quality and the chances of survival, two logistic regressions were carried out: one for the 3-year survival period and the other for the 6-year survival period. Such an analysis makes it possible to The Service Industries Journal 2409 Downloaded by [University of Valencia] at 09:48 23 September 2012 detect whether the three variables under consideration increase or decrease the chances of not surviving the 3- and 6-year periods. Table 2 summarizes the results for the 3-year survival period iterations. As we can ascertain, only the financial and organizational viability variables fit the model and are, therefore, relevant, and their beta coefficients show that both reduce the chances of not surviving. The value for 22LL is 2875.679 for the first step and 2871.376 for the second, and the significativity for the Hosmer – Lemeshow contrast is 0.656, which means the null hypothesis that the model is correct can be accepted. Nevertheless, the Nagelkerke’s R 2 is 0.007, so the model explains almost nothing about the variance – only 0.7% – which indicates that at the 3-year mark, viability plan quality is not a determinant factor in the firm survival. Furthermore, greater planned financial viability would slightly reduce the chances of survival (Exp(b) ¼ 1.020). Regarding the 6-year survival period (Table 3), the model’s results show that only organizational viability is relevant (Sig. ¼ 0.000), a variable that yields a negative beta value (20.044), which is consistent with a positive impact on survival. Nevertheless, the significativity for the Hosmer – Lemeshow contrast (0.016) indicates that the model does not correctly fit to the data, since the null hypothesis that the model is adequate cannot be accepted. Thus, the quality of the viability plan is not a determinant for the sur- vival of businesses after a 6-year period. Therefore, the results seem consistent with H1. Even though the previous results show that the quality in the viability plan does not seem to have, on its own, the potential to influence the survival of these service sector firms, it may do so when combined with other factors related to the entrepreneur and the business. A good business plan implemented by an entrepreneur with adequate train- ing, experience and motivation, with access to an initial stock of appropriate financial and human resources to compete in the chosen sector of activity, could very well have a much greater impact on the firm’s chances of survival. Table 1. The Mann – Whitney (M – W) test results. Results Survival at 3 years p-value (test) Survival at 6 years p-value (test) Economic viability 0.900 (M – W) 0.027 (M – W) Financial viability 0.496 (M – W) 0.252 (M – W) Organizational viability 0.009 (M – W) 0.000 (M – W) Table 2. Results of logit model in t + 3 with economic, financial and organizational viability. b S.E. Wald df Sig. Exp(b) C.I. 95.0% for Exp(b) Inferior Superior Step 1(1) VORG100R 20.025 0.009 8.008 1 0.005 0.976 0.959 0.992 Constant 20.751 0.069 117.280 1 0.000 0.472 Step 2(2) VFIN100R 0.019 0.009 4.316 1 0.038 1.020 1.001 1.038 VORG100R 20.032 0.010 11.564 1 0.001 0.968 0.950 0.986 Constant 20.834 0.080 107.805 1 0.000 0.434 Notes: E.T., standard error (S.E.); gl, degrees of freedom (df) and I.C., confidence interval (C.I.). 2410 R. Ferna´ndez-Guerrero et al. Downloaded by [University of Valencia] at 09:48 23 September 2012 Therefore, in a second stage, the variables related to the entrepreneur’s training, experi- ence and motivation for setting up a business, and the two variables concerned with the initial amount of human and financial resources at the venture’s disposal (starting capital and staff), were introduced into the model as explanatory variables as well as the three variables relating to project quality. Activity subsector and the type of firm according to its business-only, social or mixed nature were introduced as control variables. The final results, after six iterations of the logit model for 3-year survival period, are shown in Table 4. The value for 22LL has decreased between the first step and the sixth step from 2305.957 to 2253.955 and the significativity for the Hosmer – Lemeshow contrast is 0.423 (.0.05), that is, the null hypothesis that the model is adequate can be accepted, since the model correctly fits the data. Nagelkerke’s R 2 is 0.089, so the coefficient of determination is 8.9%. Therefore, the model is adequate, but with a limited explanatory capacity, which indicates that there are other determinant factors of survival chances after a 3-year period which are not included in the model. The model includes training levels, related experience, motivation to launch a new venture, capital, human resources and financial viability. Conversely, economic and organizational viability, related training, the control variables (activity sector and type of venture) are not included in the model. If we focus on the variables’ Exp(b) values, it becomes clear that the probabilities of not surviving decrease between 41.8% and Table 3. Results of logit model in t + 6 with economic, financial and organizational viability. b S.E. Wald df Sig. Exp(b) C.I. 95.0% for Exp(b) Inferior Superior Step 1(1) Organizational viability 20.045 0.008 31.762 1 0.000 0.956 0.942 0.971 Constant 0.143 0.064 4.942 1 0.026 1.153 Notes: E.T., standard error (S.E.); gl, degrees of freedom (df) and I.C., confidence interval (C.I.). Table 4. Last step results of logit model in t + 3 with all the variables. b S.E. Wald df Sig. Exp(b) C.I. 95.0% for Exp(b) Inferior Superior Step 6(6) Training 17.865 3 0.000 Training 1 20.667 0.184 13.122 1 0.000 0.513 0.358 0.736 Training 2 20.541 0.166 10.633 1 0.001 0.582 0.421 0.806 Training 3 20.582 0.152 14.770 1 0.000 0.559 0.415 0.752 Related experience 20.335 0.110 9.238 1 0.002 0.716 0.577 0.888 Entrepreneur motivation 0.261 0.114 5.206 1 0.023 1.298 1.037 1.624 Staff 20.341 0.060 31.934 1 0.000 0.711 0.632 0.800 Capital 20.005 0.002 9.583 1 0.002 0.995 0.991 0.998 Financial viability 0.024 0.010 6.168 1 0.013 1.025 1.005 1.045 Constant 0.202 0.204 0.979 1 0.322 1.224 Notes: E.T., standard error (S.E.); gl, degrees of freedom (df) and I.C., confidence interval (C.I.). Variable(s) introduced in step 1, staff; step 2, training levels; step 3, related experience; step 4, starting capital; step 5, financial viability; and step 6, start-up motivation. The Service Industries Journal 2411 Downloaded by [University of Valencia] at 09:48 23 September 2012 48.7%, if entrepreneurs enjoy a higher education level than the reference category (primary studies). Having related experience diminishes the risk of not surviving by 28.4%. This non-survival risk decreases a further 0.5% for each 1000 euros capital increase, and a 28.9% for each increment of one employee in the firm’s staff. On the other hand, the risk of not surviving increases by 29.8% when the venture is motivated by necessity. With regard to these variables, results conform to expectations derived from existing theory. In terms of project quality, not only economic and organizational viability were inte- grated into the model, but also the beta coefficient and the Exp(b) value of the financial viability show that increased financial viability in the plan slightly increases the chances of not surviving (2.5% for every 5% increase). This might seem contrary to logic, but could be explained by the ad hoc nature of many of the proposed business plans, which constitute, in many cases, a mere artifice aimed at obtaining subsidies, rather than a plan based on a rigorous strategic analysis, to be used by the entrepreneur as a fundamental tool for guiding the venture’s activity while guaranteeing its survival. This state of affairs has been duly noted on several occasions by different evaluations, as well as by program managers in many reports surveyed by researchers. With regard to the results of the logistic regression analysis in t + 6 with all the variables (cf. Table 5), in terms of goodness of fit, the value for 22LL in the first step is 2625.390 and in the sixth step is 2531.386. Significativity for the Hosmer –Lemeshow contrast is 0.208 (.0.05), that is, the null hypothesis that the model is correct can be accepted, since the model correctly fits the data. Furthermore, Nagelkerke’s R 2 is 0.129; therefore, the coeffi- cient of determination is 12.9%. Thus, the model is adequate, but in this case, it also shows a diminished explanatory capability, which indicates that there are other determinant factors in the chances of surviving the 6-year period which are not included in the model. The model includes related training, related experience, motivation to launch a new venture, capital, human resources and the hotel and restaurant sector. Economic, financial and organizational viability, level of education and type of venture are not included in the model. If we focus on the variable Exp(b) values, it becomes clear that the probabilities of not surviving decrease between 39.9% and 48.7%, if entrepreneurs have related education. Also, having related experience diminishes the risk of not surviving by 28.1%. This Table 5. Last step results of logit model in t + 6 with all the variables. b S.E. Wald df Sig. Exp(b) C.I. 95.0% for Exp(b) Inferior Superior Step 6(6) Related education 20.509 0.110 21.475 1 0.000 0.601 0.485 0.746 Related experience 20.330 0.107 9.447 1 0.002 0.719 0.583 0.887 Hotel – restaurant sector 0.336 0.163 4.240 1 0.039 1.400 1.016 1.929 Entrepreneur’s motivation 0.399 0.103 15.042 1 0.000 1.490 1.218 1.823 Staff 20.327 0.050 43.398 1 0.000 0.721 0.654 0.795 Capital 20.005 0.001 12.084 1 0.001 0.995 0.992 0.998 Constant 0.828 0.157 27.784 1 0.000 2.289 Notes: E.T., standard error (S.E.); gl, degrees of freedom (df) and I.C., confidence interval (C.I.). Variable(s) introduced in step 1, staff; step 2, related education; step 3, start-up motivation; step 4, starting capital; step 5, related experience; and step 6, hotel – restaurant sector. 2412 R. Ferna´ndez-Guerrero et al. Downloaded by [University of Valencia] at 09:48 23 September 2012 non-survival risk decreases a further 0.5% for each 1000 euro increase in capital, and 27.9% for each increment of one employee in the firm’s staff. On the other hand, the risk of not surviving increases 49% when the venture is motivated by necessity, and 40% among the hotel and restaurant business sector in comparison with the other subsectors. A significant aspect of these results is the fact that none of the three variables used to evaluate business plan quality (economic, financial and organizational viability) seems to have a determining effect on the chances of survival. Furthermore, the results also show that a higher score in financial viability seems to work slightly against survival. By com- bining the aforementioned variables with the other explanatory variables, the coefficient of determination undergoes a marked increase, but the influence of business plan quality becomes virtually non-existent, even considering whether entrepreneurs are educated and experienced, motivated by opportunity and have human and financial resources at their disposal. In conclusion, it is not possible to identify an entrepreneurial and business profile that, when provided with a highly valued business plan, shows distinctly higher survival levels. These results are contradictory to H2, which must thus be rejected. Conclusions Start-ups undeniably play a fundamental role in job creation, economic growth, competi- tiveness and innovation. It is therefore perfectly understandable that, over the last few decades, public institutions have implemented an increasing number of initiatives aimed at promoting entrepreneurial activity and supporting the creation of new ventures. This growing stimulus directed at entrepreneurship programs, together with the relevance that experts and academia have bestowed upon them, has caused business plans to take on substantial relevance in the business management field. More specifically, business plans play a fundamental role for those companies that turn to public institutions looking for help in launching a new venture. Generally, in the case of financial support programs, the business plan stands as a key element in order to be eligible for cheap or free financing, under the premise that a good business plan is a guarantee for the survival of start-ups and that, therefore, public funds are put to good use. Nevertheless, although there is extensive research aimed at identifying the principal success factors for new ventures, efforts directed at evaluating the effect that the existence and quality of business plans really have on the firm survival chances have been limited. It should be added that a review of the scant literature available on this issue provides patently contradictory results. Our results show how business plan quality, evaluated according to economic, financial and commercial viability, does not constitute a good predictor for the survival chances of new ventures. The model’s predictive capabilities do not increase significantly even when taking into account certain essential entrepreneurial characteristics, such as education and training, experience and the nature of the motivation to launch a new venture or character- istics of the business itself, such as the number of employees and start-up capital. Resources used for evaluating business plans do not appear to be offset by the choice of better projects in terms of survival. In light of these results, it is worth questioning whether public institutions should not give more relevance to variables that are more objective and easier to evaluate when establishing the eligibility criteria for access to public support programs. Some of the variables considered in this paper, such as entrepreneurial education and training and experience, the motivation to set up a business, as well as the new venture’s size in terms of number of employees and start-up capital, constitute examples of better predictors of survival probabilities and are also easier to evaluate. The Service Industries Journal 2413 Downloaded by [University of Valencia] at 09:48 23 September 2012 Another kind of start-up promotion program, based on preliminary counseling and monitoring subsequent to setting up the firm, could make a substantial contribution to entrepreneurship and to society, incorporating the business plan as its mainstay. These programs, that may or may not be connected to obtaining public financial support, may be very useful in increasing the chances of success by improving the formulation of business plans and execution processes. In this respect, the new venture’s program set up by the IVAJ itself in 1990, together with other complementary initiatives that have focused on training, identifying business initiatives, the selection of viable projects, drawing up viability studies, their execution and follow-up and subsequent counseling, has achieved more than promising results, enabling the launch of a considerable amount of sustainable companies. With regard to the limitations of this paper, the study has been carried out within the area of the Valencia Autonomous Region, on a sample made up of entrepreneurs aged under 30 years or aged under 30 years with older co-entrepreneurs, all of whom are appli- cants for financial support initiatives managed by the IVAJ. All this poses some limitations on the possibilities of generalizing the findings. It is therefore advisable for subsequent research to replicate the study in a different geographical area. It would also be appropriate to employ a sample comprising entrepreneurs of any age, which would probably make pre- vious experience play a more determinant role when explaining the survival chances of firms. Likewise, it would be advisable to examine the role played by the business plan in those firms that do not intend to use it as a means of obtaining public support. Acknowledgements We are very grateful to the staff of the Program Management and Planning Service of Valencia Youth Institute, and especially to Mrs Silvia Albert Guardiola. Notes 1. All three papers have been quoted by Schutjens and Wever (2000). 2. According to the criteria of the IVAJ, a social venture is a firm dedicated to activities that promote equal opportunities (integration), environmental improvement, technological innovation, organ- izational innovation, education and training for the integration or entrepreneurial cooperation. 3. When evaluating a financial subsidy application, the IVAJ takes into consideration, besides these three factors, an appraisal of the conditions and requirements of the entrepreneur or entrepreneurs and the social interest of the firm. The scoring on these two last items has not been considered because it does not evaluate business plan’s quality, but the entrepreneur’s profile, the type of investment made, the amount of employment generated, etc. They are basically used to boost those projects that adhere more closely to the ideal profiles of entrepreneur and firm the IVAJ aims to encourage. 4. 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