Examining the age‐performance relationship for entrepreneurs: Does the innovativeness of a venture make a difference? (original) (raw)

Age and High-Growth Entrepreneurship

2018

Many observers, and many investors, believe that young people are especially likely to produce the most successful new firms. Integrating administrative data on firms, workers, and owners, we study startups systematically in the U.S. and find that successful entrepreneurs are middle-aged, not young. The mean age at founding for the 1-in-1,000 fastest growing new ventures is 45.0. The findings are similar when considering hightechnology sectors, entrepreneurial hubs, and successful firm exits. Prior experience in the specific industry predicts much greater rates of entrepreneurial success. These findings strongly reject common hypotheses that emphasize youth as a key trait of successful entrepreneurs.

The effect of aging on entrepreneurial behavior

Journal of Business Venturing, 2006

Empirical evidence shows that younger individuals are more likely to start a new firm than older ones. As a result, the age distribution of a population may be important for the rate of new firm creation. Building upon Becker's theory of time allocation, we present a model in which individuals select a career path according to the dynamic interplay of age, wealth and risk aversion. Our analysis complements existing literature on the motivations of entrepreneurial behavior and discusses the potential implications of age for individuals' employment status choices.

Dominant determinant characteristics of innovative behavior of new entrepreneur candidates

Management Science Letters, 2021

In the global competition era and in Covid 19 pandemic period, the innovative competence of emerging entrepreneurs relies on the positive characters they should have. The present study was aimed to formulate a reinforcement model of innovative behavior through the identification of dominant determinant factors. The study employed survey methods and involved variables of innovative behavior (Y), creativity (X1), technology literacy (X2), and risk-taking behavior (X3). The respondents were 86 final year students of Faculty of Business Economics (emerging entrepreneur candidates) as the samples, and the data were further analyzed by multiple regression. The creativity (X1), technology literacy (X2), and risk-taking behavior (X3) contribute simultaneously at 45.70 percent to the development of innovative behavior (Y); b) the applicable prediction model of innovative behavior is Y=1.171+0.622X1+0.170X2 -0.080X3; meanwhile, the creativity yielded the most significant sensitivity in develo...

Management Science Letters 11 (2021) ***-*** Management Science Letters Dominant determinant characteristics of innovative behavior of new entrepreneur candidates

In the global competition era and in Covid 19 pandemic period, the innovative competence of emerging entrepreneurs relies on the positive characters they should have. The present study was aimed to formulate a reinforcement model of innovative behavior through the identification of dominant determinant factors. The study employed survey methods and involved variables of innovative behavior (Y), creativity (X1), technology literacy (X2), and risk-taking behavior (X3). The respondents were 86 final year students of Faculty of Business Economics (emerging entrepreneur candidates) as the samples, and the data were further analyzed by multiple regression. The creativity (X1), technology literacy (X2), and risk-taking behavior (X3) contribute simultaneously at 45.70 percent to the development of innovative behavior (Y); b) the applicable prediction model of innovative behavior is Y=1.171+0.622X1+0.170X2-0.080X3; meanwhile, the creativity yielded the most significant sensitivity in developing the innovative behavior variable compared to the technology literacy and risk-taking behavior variables; c) it is worth noting that risk-taking behavior is not among the contributing factors; in fact, this variable constrains an individual to be innovative (if it is too high); e) the variable of creativity is in line with innovation.

Focus on opportunities as a mediator of the relationship between business owners' age and venture growth

Journal of Business Venturing, 2012

Combining upper echelons and lifespan theories, we investigated the mediating effect of focus on opportunities on the negative relationship between business owners' age and venture growth. We also expected that mental health moderates the negative relationship between business owners' age and focus on opportunities. Path analytic findings based on data from 84 business owners (mean age = 44, range 24-74) supported these hypotheses. Findings suggest that focus on opportunities is a psychological mechanism that links business owners' age with venture growth. Our findings also indicate that mental health helps maintain a high level of focus on opportunities with increasing age.

Creativity and Entrepreneurial Intention in Young People

The international journal of entrepreneurship and innovation, 2011

The authors examine the link between creativity and entrepreneurial intention in young people and the roles that family and education may play in encouraging this link. The results from a survey of 180 undergraduate business school students show that the more creative young people consider themselves to be, the higher are their entrepreneurial intentions. Students' creativity also fully mediates the effect of family support for creativity on their entrepreneurial intention. Support for creativity in the university is found to have no effect on their creativity or on their entrepreneurial intention. Entrepreneurship course attendance moderates the effect of individual creativity on entrepreneurial intention.