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LOGISTIC REGRESSION MODELS: REASSESSING THE DETERMINANTS OF PRODUCT INNOVATION USING ROMANIAN SURVEY DATA

Elena Druica and Roxana Adam
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Roxana Adam: The Association for Strategic Decision Analysis

Journal of Social and Economic Statistics, 2015, vol. 4, issue 2, 1-18

Abstract: The aim of the paper is to examine the factors that increase the firm’s propensity towards product innovation, with the goal of identifying the profile of Romanian product-innovative firms. The focus of our analysis is on the obstacles and hampering factors in achieving innovation in enterprises. The methodology makes use of a logistic regression model analysing the relationship between innovation on the one hand and hampering and obstacles on the other hand. We used the Community Innovation Survey (CIS) data, to ensure the representativeness of the study at the national level. The results of the two logistic regressions conducted based on CIS 2012 and CIS 2010 micro data suggest significant relationship between product innovation and: firm size; the strong competition on product quality, reputation or brand; lack of finance; innovation costs and no demand for innovations. Both models have a good prediction power.

Keywords: product innovative enterprises; logistic regression; obstacle factors; hampering factors; Community Innovation Survey (CIS). (search for similar items in EconPapers)
JEL-codes: C01 C50 C51 O00 O30 (search for similar items in EconPapers)
Date: 2015
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