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Opportunity Recognition among Intentional and Nascent Entrepreneurs1

Heiko Bergmann University of St. Gallen Swiss Research Institute of Small Business and Entrepreneurship Switzerland and: University of Hohenheim Chair of Entrepreneurship (570 C) Germany [email protected]

Paper presented at the 56th Annual ICSB World Conference, Stockholm, 15-18 June 2011

Abstract This contribution applies and tests an extended version of a measure of opportunity recognition recently proposed by Gregoire, Shepherd, and Schurer Lambert (2010) in a large-scale survey among intentional and nascent entrepreneurs. Statistical analyses confirm the reliability and partly the unidimensionality of the opportunity recognition measure. This paper also investigates determinants of the extent of opportunity recognition. As expected, entrepreneurial education has a positive effect on opportunity recognition only for people with professional experience. Progress in the entrepreneurial process is positively related to opportunity recognition. The analysis is based on data from the 2011 Global University Entrepreneurial Spirit Students' Survey (GUESSS) in Germany.  

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I thank Philipp Sieger for the global coordination of the GUESSS project and Matthias Baum for his reliable and efficient support of the data collection in Germany. The participation of Germany in the GUESSS project has been supported financially by the University of Hohenheim.

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Opportunity Recognition among Intentional and Nascent Entrepreneurs

1.

Introduction

The notion of opportunity recognition is a central concept in entrepreneurship research. However, research on opportunity recognition has been hampered by a conceptual ambiguity and until recently - the lack of a reliable and valid measure of this concept. On the conceptual side, there is still an ongoing debate whether entrepreneurial opportunities are objective or subjective, i.e. whether they exist in some form in the market and have to be recognized by an individual with the necessary skills and information (Kirzner, 1979; Shane, 2000) or, in contrast, whether they do not exist per se but have to be enacted and created by purposeful actions of individuals (Gartner, Carter, Nancy, & Hills, 2003; Schumpeter, 1934). The measurement of opportunity recognition proves to be a challenge (Frank & Mitterer, 2009). Only very recently has a reliable and valid measure of opportunity recognition been proposed: Gregoire, Shepherd, & Schurer Lambert (2010) develop, illustrate, and validate an experimental approach to study opportunity recognition, including a scale for opportunity recognition. Although they stress the use of hypothetical exercises and behavioral experiments, they argue that their measure can also be used for other kinds of data collection methods as e.g. surveys. I follow their suggestion and analyze opportunity recognition in the early stage of the entrepreneurial process in a large-scale survey of student entrepreneurs. I develop an extended version of their measure because one dimension of opportunity recognition is not covered in their proposed scale. I apply different methods for scale development because I conduct this study in another language as the original scale, for another population of interest (student entrepreneurs) and because I added new items. In a second step, this contribution investigates determinants of opportunity recognition among student entrepreneurs. I am aware that “entrepreneurial research on student subjects does not

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generalize to real world entrepreneurs” (Robinson, Huefner, & Hunt, 1991). However, the focus in this study is on intentional and nascent student entrepreneurs only, i.e. people who are studying and trying to start their business at the same time. Entrepreneurial activities of students are important because many groundbreaking business concepts originate from universities. Most concepts of the innovation economy stress the importance of universities. Clearly, as demonstrated by a company like facebook, it is not only the small number of university spin-offs exploiting a piece of intellectual property (Shane, 2004) that contribute to wealth creation but all innovative start-ups from current or former students as well. Still, we know relatively little of how opportunity recognition takes place and whether the attendance of entrepreneurship courses, subject of study, and previous employment activities play a role. Against this background, the aims of this paper are twofold: First, I want to apply and test an extended version of the measure of opportunity recognition proposed by Gregoire, Shepherd, & Schurer Lambert (2010) in a large scale survey of intentional and nascent entrepreneurs. Second, I aim to determine factors contributing to the recognition of an entrepreneurial opportunity and analyze its relationship towards progress in the entrepreneurial process. Here I focus on factors relevant to idea and business development in the context of early-stage student entrepreneurs.

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Opportunity Recognition and its Measurement

Although opportunity recognition is central a central concept in many entrepreneurship theories, the measurement of this concept remains heterogeneous, inconsistent and partly problematic (Frank & Mitterer, 2009). Some former studies equate opportunity recognition with new venture creation (Dyer, Gregersen, & Christensen, 2008), or patenting activities (D'Este, Mahdi, & Neely, 2010) which appear as imprecise approaches. Arenius & De Clercq (2005) use a single binary item to measure opportunity recognition. Other studies asked (potential)

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entrepreneurs how many entrepreneurial opportunities they have identified in a given period in the past (Ucbasaran, Westhead, & Wright, 2009). However, opportunity recognition is prospective in nature because the opportunities still have to be fully discovered and exploited. Thus, retrospective measures of opportunity recognition have clear weaknesses (Ozgen & Baron, 2007). An opportunity should also be distinguished from a business idea because the latter does not say anything about the economic value or attractiveness of a proposed new venture. Opportunities first begin as venture ideas that can change and become more elaborate over time (Davidsson, 2003: 339f). Recently, Gregoire, Shepherd, & Schurer Lambert (2010) developed, illustrated, and validated an experimental approach to study opportunity recognition, including a scale for opportunity recognition. This scale forms the basis for our empirical study. The first step when developing a new measure is to define clearly what it is supposed to capture. The ambiguities concerning the measurement of opportunity recognition are partly the result of a vagueness on the conceptual side as authors frequently do not clearly distinguish between business ideas, entrepreneurial alertness, business opportunities, and entrepreneurial activity. Also, there are conflicting viewpoints of opportunities as either being objective artifacts that exist “out there” or as being the result of subjective interpretations and perceptions. To overcome these conflicting viewpoints and to help transcend the conceptual debates, Gregoire, Shepherd, & Schurer Lambert (2010: 117ff) make four assumptions concerning opportunity recognition. First, they accept the common view that opportunities are related to market failures. However, these two notions are not identical; opportunities arise from market failures and offer the possibility to act in the hope of individual, firm, and social betterment. Second, they stress that opportunities are uncertain ex-ante and therefore do not exist per se as objective arte. However, the recognition of an opportunity recognition rests on the subjective perception and interpretation of

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these objective realities. Thus, opportunity recognition has elements of both, objectivity and subjectivity. Third, they follow Mcmullen & Shepherd (2006: 133) by distinguishing between two phases of entrepreneurial action: Initially, a person forms a subjective believe that an opportunity exists for somebody with the relevant qualities and means (third-person opportunity). Once a person perceives a third-person opportunity he or she forms beliefs regarding this opportunity and whether to exploit it or not, i.e. whether this is an opportunity for the actor (first-person opportunity) and should be acted upon (Mcmullen & Shepherd, 2006: 141). Fourth, they model variations in opportunity beliefs of a person in terms of his or her certainty that a venture idea represents an opportunity. Given these assumptions, Gregoire, Shepherd, & Schurer Lambert (2010: 117) define entrepreneurial opportunities as “projected courses of action to introduce (and profit from) new and/or improved supply-demand combinations that seek to address market failure problems”. I also follow this definition in this contribution. Building on the conceptual assumptions stated above, they propose that opportunity-recognition beliefs will be reflected in indicators pertaining to three perceptual dimensions: (a) the degree of alignment between an opportunity’s specific means of supply and a target market, (b) the general feasibility of introducing this new/improved supply-demand combination, and (c) the general desirability of doing so. These dimensions are then also covered in their empirical anaylsis. In the end, Gregoire, Shepherd, & Schurer Lambert (2010) are able to provide evidence that opportunityrecognition beliefs are captured by dimensions (a) and (b) which are related, yet distinct. Contrary to their theoretical developments, their results do not allow to establish the role of (c) as a relevant dimension of opportunity-recognition beliefs. Yet, they encourage future research to develop and test new items concerning this dimension.

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3.

Determinants of Opportunity Recognition

As this study deals with student entrepreneurs in the early stage of venture development I specifically consider factors that can be expected to influence opportunity recognition in this context: progress in the entrepreneurial process, entrepreneurial education and the breath of the sources of the business idea, i.e. the extent of boundary spanning.

3.1. Progress in the Entrepreneurial Process The entrepreneurial discovery process starts with the conception of a venture idea that can change and become more and more elaborate over time (Davidsson, 2003: 340). Opportunity recognition and the decision to exploit an opportunity are distinct phases in the entrepreneurial process. People may notice an opportunity, but only people who have the necessary knowledge and motivation will pursue this opportunity further (McMullen & Shepherd, 2006). The process of opportunity identification and development is hardly linear, predictable, or inevitable (Dimov, 2011). Although there is no clear pattern of activities in the early stage of venture development, it can still be assumed that an entrepreneur’s certainty that a venture idea represents an opportunity increases with growing involvement in the entrepreneurial process and the completion of gestation activities. Overall, it can be expected that students with relatively vague entrepreneurial intentions have not recognized a concrete business opportunity yet. The more thoroughly students consider to start a new business and the more activities they have already completed towards establishing a business the more likely it will be that they recognize a valuable opportunity. As many entrepreneurs are overly optimistic (Cassar, 2010) one could also argue for an opposite influence. People might start with high expectations concerning the economic value of their business idea which they have to revise once they start implementing it. However, this is not likely to affect such an early stage of company development as investigated in this contri-

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bution. Also, a suitable measure of opportunity recognition should capture the perceived value of a proposed business solution rather than just of a business idea (Gregoire, Shepherd, & Schurer Lambert, 2010). Hypothesis 1: There is a positive relationship between progress in the entrepreneurial process and opportunity recognition.

3.2. Entrepreneurial Education and Professional Experience By and large, the existing empirical evidence suggests that entrepreneurial education enhances students’ propensity or intentionality for entrepreneurship. However, there is less clear cut evidence whether this propensity is turned into entrepreneurial behavior (Pittaway & Cope, 2007). Also, there is only scant evidence on the influence of entrepreneurial education on opportunity recognition. Souitaris, Zerbinati, and Allaham (2007) suggest that specific knowledge about entrepreneurship learned during a program improves the participants' opportunity-identification ability. However, a frequent challenge of entrepreneurial education is the lack of professional experience and knowledge about target markets. Changes in technology, markets or framework conditions do not generate obvious entrepreneurial opportunities. Without a certain degree of domain-specific knowledge, one may not recognize the possibility for action (McMullen & Shepherd, 2006; Shane, 2000). Thus, entrepreneurial education is likely to be of limited effect on opportunity recognition without any knowledge of the target market of the business idea. Shane (2000) shows that individuals with a direct experience in manufacturing, in addition to having a strong scientific research profile, were particularly capable of identifying business opportunities and acting upon them. Overall, one can assume that individuals who are knowledgeable about the target market and who have also gained some understanding of entrepreneurship are most likely to recognize an opportu-

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nity. Thus, I assume a moderating effect of previous professional experience on the impact of entrepreneurial education. Hypothesis 2: Entrepreneurial education has a positive effect on opportunity recognition for people with previous professional experience. The more professional experience people have, the stronger is the impact of entrepreneurial education.

3.3. Boundary Spanning Abilities Boundary spanning activities are important for information transfer (Tushman & Scanlan, 1981) and also for the identification of entrepreneurial opportunities (Vaghely & Julien, 2010). Baron (2006) argues that entrepreneurs use cognitive frameworks they have acquired through experience to perceive connections between seemingly unrelated events or trends in the external world, i.e. they are able to “connect the dots” between changes in technology, demographics, markets, government policies, and other factors. Often entrepreneurs draw on know-how from a range of contexts when identifying and developing ideas for new products or services (Cooper & Park, 2008). Previous research has demonstrated that academics with boundary spanning attributes are more likely to take steps towards exploiting an invention (Bercovitz & Feldman, 2008). I also expect to find such an influence on opportunity recognition. Hypothesis 3: People with boundary spanning abilities are more likely to perceive an opportunity.

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4. Methods 4.1. Study 1 The measure of opportunity recognition has been developed on the basis of the measure of Gregoire, D. A. Shepherd, & Schurer Lambert (2010). They provide a set of five items concerning the 'degree of alignment between an opportunity’s specific means of supply and a target market' and the 'general feasibility of introducing this new/improved supply-demand combination'. They recommend "that future research develops and tests new sets of items to assess whether perceptions of general desirability effectively reflect a relevant and distinct dimension of opportunity-recognition beliefs". I took the five items of their final scale and, as proposed, added four new items for the ‘general desirability of the opportunity’. One new item was inspired by the measure of opportunity attractiveness of Haynie, Shepherd, & McMullen (2009). All nine items are listed in table 1. ******************************************************* Include Table 1 about here ******************************************************* Although the measurement is partly based on a reliable and valid measure, I still follow Hinkin's (1998) guidelines for the development of measures for survey questionnaires because I conduct this study in another language, for another population of interest (student entrepreneurs) and because I added new items. In a first step, this questionnaire was tested in a paper-and-pencil test at a mid-size university in Germany. After a screening of more than 400 students we identified a sample of 99 intentional and nascent entrepreneurs from different subjects of which 79 filled in the whole set of

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items2. We conducted an exploratory factor analysis to evaluate construct validity. The dataset seems suitable to conduct a factor analysis: Kaiser-Meyer-Olkin measure of sampling adequacy is 0.811, thus, highly suitable for a factor analysis. The measures of sampling adequacy are for most items above 0.80 and for all above 0.65, again showing the suitability to include them in a factor analysis. The factor analysis delivers a two factor solution with all five items taken from Gregoire, Shepherd, & Schurer Lambert (2010) loading high on one factors and all four new items as loading high on the other factor. The first factor can be interpreted as "general feasibility and fit with market needs" and the second factor as "general desirability" of the opportunity. Cronbach's Alpha for the first five items is 0.852; for the items of the second factor, it is 0.731. Furthermore, it also became clear in study 1 that the measure of opportunity recognition can only be applied to people with a serious intention to start a new business and not to people with a general interest in an entrepreneurial career. Respondents who just stated that they have been thinking “repeatedly” about founding an own company frequently did not answer all questions of the scale or scored rather low on the overall scale. Thus, people with such a vague interest in starting a business were not included in the following study any more.

4.2. Study 2 The list of items was then included in the German version of the 2011 Global University Entrepreneurial Spirit Students' Survey (GUESSS). GUESSS is an international research project that investigates and compares entrepreneurial intentions and activities of students in more than twenty countries in the world.3 In Germany, this online survey has been conducted at more than fourty universities in March and April 2011. The questionnaire also includes meas                                                            2

For all items I used a rating scale that ranges from –3 (no, certainly not) to +3 (yes, certainly) with the midpoint of 0 (uncertain). However, data were coded from 0 to 6. 3 More information about the project can be found at: http://www.guesssurvey.org/

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ures of entrepreneurial intentions and their determinants (C. Chen, Greene, & Crick, 1998; Levenson, 1973; Liñán & Y.-W. Chen, 2009) , career choice motives (Carter, Gartner, Shaver, & Gatewood, 2003), university context, and family background. Previous research based on GUESSS-data has e.g. looked at career choice intentions of students with family business background (Zellweger, Sieger, & Halter, 2010). Up to mid-April 2011, 6931 students (from Bachelor to PhD-level) completed the GUESSS questionnaire in Germany. The response rate to this online survey is about 7%, which is comparable to other online-surveys among students (Porter & Whitcomb, 2003). 908 of the 6931 students can be considered as intentional or nascent entrepreneurs; i.e. they stated that they have been thinking “relatively concrete” about founding an business or “have made an explicit decision to found a company” or “have a concrete time plan when to do the different steps for founding” or “have already started with the realization”. We do not include all the people who state that they have not thought about starting a business, have only thought sketchily or repeatedly about starting a business or who are already self-employed. Of all intentional and nascent entrepreneurs, 859 answered all items concerning opportunity recognition which form the basis of the analysis in this paper. Because of the relatively low share of missing cases I do not apply a technique for the imputation of missing values. Again, I conducted an exploratory factor analysis to evaluate construct validity. KaiserMeyer-Olkin measure of sampling adequacy is 0.916, thus, highly suitable for a factor analysis. The measures of sampling adequacy are above 0.89 for all items, again showing the suitability to include them in a factor analysis. In contrast to study 1, the factor analysis delivers a one-factor solution for all nine items, suggesting unidimensionality of the opportunity recognition scale. Cronbach's Alpha for this scale is 0.902 which is an excellent value for a scale of nine items and shows a high degree of reliability.

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However, whether a scale is unidimensional or not requires further analysis. Confirmatory factor analysis allows a stricter interpretation of unidimensionality than can be provided by Cronbach's Alpha, item-total correlations and exploratory factor analysis (Gerbing & Anderson, 1988; Hinkin, 1998). I conducted exploratory factor analyses with two competing models: In the first model a unidimensional structure is assumed for all nine items. In the second model I assume a three-dimensional structure with 'degree of alignment between focal means of supply and target markt' (3 items), 'general feasibility of the opportunity' (2 items) and 'general desirability of the opportunity' (4 items) as separate constructs. The first, unidimensional model has a reasonable model fit (CFI: 0.932, RMSEA: 0.123, Chi-square: 398.8, df=27). However, the three factor model exhibits a better fit than the single factor solution with CFI: 0.969, RMSEA: 0.083, Chi-square: 173,8, df=24). This result is similar to the one of Gregoire, Shepherd, & Schurer Lambert (2010) although the wording of the items concerning the general desirability of an opportunity has been changed. To sum up, although exploratory factor analysis and Cronbach's Alpha support a unidimensional structure of the scale, confirmatory factor analysis suggests a three-dimensional structure with all three elements of opportunity recognition as related but somehow distinct constructs. Further research needs to be done to analyze the structure and dimensionality of this opportunity-recognition scale. Still, as a tentative measure of opportunity recognition I calculate the sum index of all nine items and use this as a dependent variable in the subsequent analysis.

4.3. Analysis of Determinants of Opportunity Recognition The extent of opportunity recognition acts as dependent variable in the following analysis. Using hierarchical linear regression models I analyze the determinants of opportunity recognition among intentional and nascent entrepreneurs.

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I use the following measures for the independent variables: Progress in the entrepreneurial process is measured in two ways: First, I consider the answer to the question of how serious people are thinking about starting a new business, i.e. in what stage of the entrepreneurial process they consider themselves. As explained above, only intentional and nascent entrepreneurs are included in the analysis. However, people who “have made an explicit decision to found a company” can be regarded as more advanced in the entrepreneurial process than people who have only been thinking "relatively concrete" about this. People with “a concrete time plan when to do the different steps for founding” can be considered even more advanced. Finally, nascent entrepreneurs who “have already started with the realization” are most advanced in the entrepreneurial process in my sample. Second, following Samuelsson & Davidsson (2009) and other previous studies I measure progress in the entrepreneurial process by the number of conducted gestation activities. In the GUESSS study, respondents had to answer a number of items which steps they have already undertaken to found their company. As suggested by Bird & Schjoedt (2009) I focus on concrete activities rather than less specified behaviors (Formulated a business plan; Looked for potential partners (e.g., fellow students); Purchased equipment; Worked on product development; Discussed with potential customers; Asked financial institutions for funding) and calculate the sum index of these six binary items. I measure boundary spanning ability by the number of different sources where the idea for the intended business came from. Respondents had the choice between seven different answers (current or former work activity, hobby or recreational pastime, university studies, academic, scientific or applied research, idea from self or fellow student, idea from friends outside the university, idea from family member). Multiple responses were possible. I measure the extent of entrepreneurial education by the number of attended entrepreneurship courses. The extent

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of previous experience is measured by the number of years people have already made professional work experiences that are relevant for the intended business. A number of control variables are also included in the analysis: age (in years), age (squared) (to control for non-linear relationships), gender, graduate student, PhD-student, former selfemployment, subject: management or related and subject: technical, mathematical, computer sciences. The descriptives of all variables are given in table 2. ******************************************************* Include Table 2 about here *******************************************************

5. Results The results of different OLS regression models are presented in table 3. Model 1 only includes the control variables. This model has a low explanatory power. Model 2 includes control variables and the three dummy variables concerning the progress in the entrepreneurial process. As expected, there is a positive and highly significant influence for all three variables on opportunity recognition. This significant influence can also be found in models 3 and 4. Model 3 includes all variables from model 2 plus the measure of boundary spanning ability, number of visited entrepreneurship courses and the interaction term of this variable and years of professional experience in the relevant market. Model 4 is the full model; in addition to all previously mentioned variables it also includes the number of completed gestation activities. The number of completed gestation activities has a positive and highly significant influence on opportunity recognition. Together with the significant influence of the three dummy variables about the stage in the entrepreneurial process, explained above, I am able to support

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hypothesis 1; there is clearly a positive relationship between progress in the entrepreneurial process and opportunity recognition. While entrepreneurial education has a significant negative influence on opportunity recognition, the coefficient for the interaction term of entrepreneurial education and professional experience is positive and highly significant. Thus, I am able to support hypotheses 2: Entrepreneurial education has a positive effect on opportunity recognition only for people with previous professional experience. The number of sources of the business idea acts as measure of boundary spanning ability. This variable has a significant positive effect on opportunity recognition in model 3. However, this effect disappears in model 4 when the number of gestation activities is included. Thus, there is only partial support for hypotheses 3. ******************************************************* Include Table 3 about here ******************************************************* Interestingly, the only control variable that has a significant impact on opportunity recognition is age (in simple and in squared form) in models 1 and 2. The signs and size of the coefficients of age (in years) and age (squared) reveal an inverse u-shaped influence of age on opportunity recognition with a maximum around the age of 40 years. In models 3 and 4 the significance of the direct effect of age disappears, probably because of the inclusion of other variables into the models.

6.

Discussion

This analysis applies an extended measure of opportunity recognition of Gregoire et al. (2010) in a large-scale survey of intentional and nascent entrepreneurs and largely confirms their

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results. The results suggest that opportunity recognition might not be an unidimensional concept but consists of related but somehow distinct constructs. Further research will have to determine whether the three related constructs should be investigated separately or together in the form of a formative index (Diamantopoulos, Riefler, & Roth, 2008). Still, the tentative measure of opportunity recognition has a very high reliability and delivers consistent and sound results when being used as dependent variable. The study of opportunity recognition among early-stage student entrepreneurs delivers interesting and important results: I am able to support hypotheses 1 and 2. Opportunity recognition is dependent on how serious intentional and nascent entrepreneurs intend to start a new business and how active they have already been towards achieving this goal. Interestingly, entrepreneurial education has a positive effect on opportunity recognition only for people with some professional experience. Shane (2000) has called for studies of how prior knowledge influences opportunity recognition outside the context of high technology. This contribution shows that prior knowledge is essential for the formation of opportunity recognition beliefs. Entrepreneurial education may have a positive influence on intentions (Pittaway & Cope, 2007), but these remain fruitless without knowledge about specific markets and the needs of customers. This study finds only partial support for the influence of boundary spanning abilities on opportunity recognition (hypothesis 3). It might be that the applied measure of boundary spanning is mainly relevant for the generation of a business idea rather than having a profound effect on the perceived economic value of a proposed business solution. We know from previous studies that entrepreneurial intentions differ between student groups (Zellweger et al., 2010). However, the insignificance of most of the control variables suggests that subject of study, gender, and level of study do not have an effect on opportunity recognition once people have entered the entrepreneurial discovery process. This is an important re-

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sult because it indicates that promising business ideas can be found in all faculties and are only loosely related to the number of students with entrepreneurial intentions.

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Contribution to the Literature

To my knowledge, this is the first large scale study of opportunity recognition among intentional and nascent entrepreneurs based on an extended version of the recent measure proposed by Gregoire et al. (2010). This study has two main contributions. First, I partly replicate the study of Gregoire et al. (2010) for a new target group and in a new cultural setting and largely confirm their measure of opportunity recognition. I thus add to our understanding of the measurement of opportunity recognition. Second, by applying this measure as a dependent variable I am able to contribute to our understanding of the determinants of opportunity recognition and its relationship to entrepreneurial intentions and actions. This research contributes to our understanding of the formation of opportunity recognition beliefs among students and is, thus, important for the study of university spin-offs as well as for teaching entrepreneurship.

8.

Limitations and Future Research

This study still has some limitations. The results of the confirmatory factor analysis are somewhat ambiguous concerning the dimensionality of opportunity recognition. Thus, further analyses will have to be conducted to investigate this issue further. The causality between progress in the entrepreneurial process and the extent of opportunity recognition is bidirectional. While it is reasonable to assume that by completing different activities to get their business up and running people will develop a greater certainty that their venture idea represents an opportunity, the opposite relationship is possible as well. People

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might foster the development of their business when they are to a large extent certain that their business idea represents a viable opportunity. This contribution is the first analysis of data collected within the Global University Entrepreneurial Spirit Students' Survey (GUESSS) 2011. As researchers in more than twenty countries are involved in this international project, it can be expected that in the coming months and years more publications based on this large-scale survey of entrepreneurial activities and intentions of students will follow and help to increase our knowledge of this important area.  

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9.

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TABLE 1 Items of the opportunity-recognition measure and their source and item-total correlations Item

Source

Corrected Item-Total Correlation (study 2)

General feasibility of the opportunity The proposed business solution is sufficiently developed to be applied with individuals/firms in the targeted markets.

Grégoire et al. (2010), item 2a

.553

Applying the proposed business solution with individuals/firms in the targeted market does constitute a feasible opportunity.

Grégoire et al. (2010), item 2b

.808

The proposed business solution has the capabilities to answer the needs of the market described.

Grégoire et al. (2010), item 1b

.810

There is a ‘‘match’’ between what the proposed business solution does, and what the targeted market demands.

Grégoire et al. (2010), item 1c

.786

The proposed business solution can be used to solve the problems of the targeted market.

Grégoire et al. (2010), item 1a

.667

Irrespective of my person, the business solution has the potential to be applied successfully in the targeted market.

(new)

.675

The targeted market is large enough to support the profitable application of the proposed business solution.

(new)

.726

Applying the business solution will provide the entrepreneur with an attractive opportunity to earn money.

(new)

.749

Applying the business solution will give the new venture a sustainable competitive advantage in the marketplace.

inspired by Haynie et al. (2009)

.587

Degree of alignment between focal means of supply and target market

General desirability of the opportunity

23

TABLE 2 Descriptives of independent and dependent variables N

Min.

Max.

Mean

Std. Deviation

age (in years)

908

19

67

25.60

4.707

gender (female)

908

0

1

.44

.496

graduate student

908

0

1

.25

.434

PhD-student

908

0

1

.07

.249

former selfemployment

908

0

1

.08

.277

subject: management or related

908

0

1

.26

.439

subject: technical, math., comp. sciences

908

0

1

.33

.471

stage: explicit decision to start a business

908

0

1

.37

.483

stage: concrete time plan for founding

908

0

1

.05

.224

stage: nascent entrepreneur

908

0

1

.08

.265

number of sources of business idea (boundary spanning)

908

0

7

2.08

1.183

number of visited entrepreneurship courses

908

0

8

1.15

1.652

(prof. experience) x (nr. eship courses)

908

0

8

.67

1.354

number of gestation activities

908

0

6

1.06

1.204

opportunity recognition (index)

859

0

54

37.65

9.850

Valid N (listwise)

859

24

TABLE 3 Determinants of opportunity recognition (results of OLS-regressions) Model 1 (Constant) age (in years) age (squared) gender (female) graduate student PhD-student former selfemployment subject: management or related subject: technical, math., comp. sciences stage: explicit decision to start a business stage: concrete time plan for founding stage: nascent entrepreneur number of sources of business idea (boundary spanning) number of visited entrepreneurship courses (prof. experience) x (nr. eship courses) number of gestation activities R square adj. R square Sign. N

B 22.398 .903 -.011 -.696 .694 -.115 .466 -.269 -.157

Model 2 p .000 .011 .033 .336 .398 .936 .708 .758 .852

0.018 0.009 0.050 859

B 21.708 .803 -.010 -.296 1.027 .227 .760 -.058 -.034 3.585 5.566 8.029

Model 3 p .000 .020 .043 .674 .198 .871 .530 .945 .967 .000 .000 .000

0.082 0.070 0.000 859

Model 4

B 22.922 .653 -.008 -.098 .771 .137 .439 .022 .017 3.376 5.282 7.524

p .000 .058 .098 .888 .335 .921 .715 .980 .983 .000 .000 .000

B 25.018 .482 -.006 .375 .697 -.209 .357 .260 -.143 3.053 4.598 4.615

p .000 .156 .206 .589 .375 .879 .762 .763 .858 .000 .002 .001

.545

.048

.313

.252

-.549 1.298

.046 .000

-.723 1.217 1.680

.008 .000 .000 0.136 0.120 0.000 859

0.104 0.089 0.000 859