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01-12-2016 | Original Paper

Entrepreneurial traits and firm innovation

Author: Jocelyn Olivari

Published in: Eurasian Business Review | Issue 3/2016

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Abstract

Entrepreneurial behavior is widely considered to be influenced by the interaction between skills and motivation. And because entrepreneurial behavior is viewed as a causal determinant of firm performance, given the context in which the venture is embedded, factors determining entrepreneurial behavior are expected to influence firm performance. The research questions explored in this paper are: Do entrepreneurial traits have a direct effect on firm innovation? and if so, Is there a specific entrepreneurial profile that makes firms more innovative? I use a representative survey of firms from Chile to examine whether owners’ skills and motivations affect firm innovation. The survey collects information on both firm and owner characteristics, which allows us to put the entrepreneur back into the analysis of the determinants of firm innovation, a dimension that the related literature does not generally focus on. The survey also allows us to analyze the incidence of innovation in micro and small firms, which have been traditionally overlooked in the study of innovation, despite the fact that they represent the majority of firms in developing countries. The results from a probit model suggest that entrepreneurial traits are important in explaining firm innovation propensity, so any attempt to understand firm innovation should also take the characteristics of the entrepreneur into consideration. Furthermore, different entrepreneurial profiles are related to different firm innovation propensities, providing new evidence on the sources of firm heterogeneity. These results confirm the idea that not all entrepreneurs are the same and that some have particular traits that greatly affect the innovating performance of their ventures.

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Footnotes
1
See Schumpeter (1934) page 66 in Chapter 2 for a list of cases of innovations or new combinations.
 
2
Personality traits also affect entrepreneurial behavior but in an indirect way as they are assumed to be mediated by motivation (Herron and Robinson 1993).
 
3
In his book Wasserman (2012) analyzes the different dilemmas that entrepreneurs behind technology- and science-based startups face and the critical decisions they have to make, from the decision to found or not in the first place to the decision to exit the company. Each decision involves assessing different options and weighing trade-offs. And although there is no ‘right decision’, any early decision will surely influence the development of the startup in the future, in a very path-dependent fashion.
 
4
The relationship between skill endowment and innovation has been analyzed in the literature suggesting complementarities between skill endowment and innovation (Leiponen 2005). The literature has focused typically on one direction of causality: the ‘skill-biased’ impact of innovation, where a larger availability of skilled workers induces investment in that technology that is more intensive in the use of that production factor that has become relatively more abundant (Acemoglu 1998). Therefore, the direction of technical change closely relates to the availability of technical skills. The complementarity between skills and technological innovation has also been empirically tested by Piva and Vivarelli (2009), who supply evidence for the role of skill endowment in increasing a firm’s R&D investments. Their results suggest that there is a co-evolution of skills and technological innovation, but it should not be solely attributed to the skill-biased technological change discussed before. The link goes also in the opposite direction: an adequate ex-ante endowment of skills may accelerate R&D investment and so drive innovation ex-post. Their results have important implications from a policy point of view in the sense that successful education and training policies that increase the skill ratio may also act as indirect incentives to R&D investments.
 
5
For a review on econometric evidence using Innovation Surveys, see Mairesse and Mohnen (2010).
 
6
The Unidad de Fomento (UF) is an accounting unit that is adjusted periodically by the inflation rate. The average value of the UF in December of 2009 was $20,989.80 Chilean pesos according to the Tax Office website, or €29. Meaning that the sample included firms whose sales were higher than €23k approximately.
 
7
Large firms were censed, meaning a total of 326 firms compulsory included in the sample.
 
8
In Chile firm size is measured through yearly sales. The different size categories and their sales levels measured in euros of 2009 are the following: Micro 1: <23k; Micro 2: €23k–€69k; Small 1: €69k–€158k; Small 2: €158k–€792k; Medium: €792k–€3167k; Large: >€3167k.
 
9
Large firms are compulsorily included in the sample of both waves.
 
10
Alvarez and Robertson (2004) study the effect of the exposure to foreign markets over plant-level innovation in Chile and Mexico, distinguishing three mechanisms: exports, foreign investment, and trade in intermediate inputs. Taking into consideration the potential problem of bicausality between foreign exposure and innovation by measuring all control variables at the beginning of the period, their results for Chile show a positive relationship between exports and technological innovation. However, they find that the effect of exports is not linear, since the squared export term is negative and significant. This indicates that a higher ratio of exports to output increases the propensity to innovate, but at some level it decreases.This evidence may be consistent with the idea that plants more consolidated in the international markets require lower efforts in innovation to remain competitive than plants that are in the first steps of the exporter process (Alvarez and Robertson 2004). Furthermore, in a later paper, Alvarez and Garcia (2008) study whether innovation promotes exporting activities in Chilean manufacturing firms. They do not find evidence that product and process innovations affect the probability of exporting.
 
11
It is important to remark that a firm may share its ownership between several partners. Therefore, when talking about owners I refer to both sole owners and partners. I also refer to them summarily as entrepreneurs.
 
12
Large firms are not included in the analysis, as explained in Sect. 4.1.
 
13
Not reported here. Results of the error correlation can be provided upon request.
 
14
See a review of personality traits of entrepreneurs in Rauch and Frese (2007) and Zhao et al. (2010).
 
15
The exercise was done as follows: First, the estimated coefficients \(\hat{\beta }_{j}\) (not reported here) were retrieved after the probit estimation; second, the \(\sum _{i}\hat{\beta }_{j}x_{ij}\) was calculated for each observation i after fixing the values of the motivation and education variables and letting the rest of the variables in Table 2 take the observed value; third, the nonlinear probability of innovating \(p_{i}=Pr(y_{i}=1)=\mathbf {\Phi }\sum _{i}\hat{\beta }_{j}x_{ij}\) was calculated for each observation i; and fourth, the kernel density function was estimated for the predicted probabilities obtained in the previous step, using an Epanechnikov density function and the default bandwidth.
 
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Metadata
Title
Entrepreneurial traits and firm innovation
Author
Jocelyn Olivari
Publication date
01-12-2016
Publisher
Springer International Publishing
Published in
Eurasian Business Review / Issue 3/2016
Print ISSN: 1309-4297
Electronic ISSN: 2147-4281
DOI
https://doi.org/10.1007/s40821-016-0060-6

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