Abstract
The aim of this paper is to assess the influence of innovation barriers for technological innovation on the innovation performance as well as sales market orientation of Polish firms. The analysis is conducted on the sample of 7783 manufacturing enterprises participating in the survey GUS PNT–02/CIS for the years 2008–2010. The results show statistically significant relations between innovation barriers and both innovation performance and international market orientation of surveyed firms. Various advanced statistical methods were used in order to verify research hypotheses. The results of the study reveal complexity of interactions between analysed variables leading to the conclusion that innovation process cannot be reduced to linear relationships only.
Highlights
Recent literature as well as business practices provide evidence that innovation is regarded as an essential tool for stimulating the growth of enterprises and economies
The aim of the paper is to examine the importance of innovation obstacles and their impact on innovation performance as well as on international market orientation of Polish manufacturing enterprises
The probability of being in a group of Polish irms selling on EU markets and “other markets” increases by a bit less than 150 percent (Exp(B)=1.357) (Exp(B)=1.318) with each additional indication for the process innovation
Summary
Recent literature as well as business practices provide evidence that innovation is regarded as an essential tool for stimulating the growth of enterprises and economies. High risk and uncertainty are the features that distinguish innovation from activities connected with the routine management of the company. In this context, the aim of the paper is to examine the importance of innovation obstacles and their impact on innovation performance as well as on international market orientation of Polish manufacturing enterprises. The irst part of the paper provides an overview of the literature and research hypotheses. The second part contains the sample description, methods applied and the operationalization of variables. Note: Each letter (a, b) denotes a subset of categories whose column proportions (Bonferroni method) differ signiicantly from each other at the 0.05 level
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