Journal of Finance and Economics
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Journal of Finance and Economics. 2015, 3(6), 122-131
DOI: 10.12691/jfe-3-6-3
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Investment, Innovation and Firm Performance: Empirical Evidence from Small Manufacturing Industries

Rytis Krusinskas1, Rasa Norvaisiene1, Ausrine Lakstutiene1, and Sigitas Vaitkevicius2

1Department of Finance, Kaunas University of Technology, Kaunas, Lithuania

2Department of Management, Kaunas University of Technology, Kaunas, Lithuania

Pub. Date: November 24, 2015

Cite this paper:
Rytis Krusinskas, Rasa Norvaisiene, Ausrine Lakstutiene and Sigitas Vaitkevicius. Investment, Innovation and Firm Performance: Empirical Evidence from Small Manufacturing Industries. Journal of Finance and Economics. 2015; 3(6):122-131. doi: 10.12691/jfe-3-6-3


The research paper contains the analysis of the intensity of R&D investments and innovations from 2005 to 2012 in Lithuanian industrial sectors of different technological levels and evaluation of operational efficiency of the aforementioned sectors. The obtained results of the study showed that until 2010 the leaders of investments in the field of tangible assets were medium-low-tech enterprises, while from 2010, high-tech sector was significantly ahead of other Lithuanian industrial sectors by level of its investments. This sector was significantly getting ahead of other industrial sectors by innovative activity. The study found that high and medium-high-tech enterprises are superior in terms of productivity, volumes of export and indicators of return on assets, comparing to medium-low and low-tech enterprises. However, it should be noted that, although, medium-high-tech industries got behind high-tech industries by their innovative activities, their operational efficiency was higher than high-tech enterprises for almost the entire period of study. To extend the research and represent countries general macro-economical tendencies and technological development of the industry, 5 financial indicators (investment to tangible assets, proportion of tangible investments to sales revenue, additional value created, return on assets (ROA), export share in total revenue) were selected to perform cluster analysis between different technological level industries and country’s GDP using Ward’s method with squared Euclidean distance interval.

innovation R&D investment manufacturing companies technological level company‘s performance

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