Exposure to foreign information as an influence factor on R&D activity. The case of the Romanian textile industry.

AuthorIvanov, Florentina
PositionReport

Introduction

Globalization offers companies the possibility to bring new products and strategies to foreign markets. By adapting their output and operations to the domestic circumstances of the target market, they create new products and engage thus in an innovation process. Ultimately, they test their own adaptability limits, but also put pressure on the innovation limits of the market. The empirical studies show that this is not a one-way transfer of knowledge and inspiration, but rather a mutual benefit. By entering a new market, the globalized company adapts itself to the new economy. It tests its products and procedures in a new environment, faces new perspectives and challenges. By absorbing knowledge from this experience, it develops innovative ideas and brings them subsequently back home or elsewhere. A study conducted on the interaction of expatriates in multinational corporations with host country nationals shows that there is an active transfer of knowledge both ways, from the expatriates to the companies abroad and vice-versa (Hsu, 2012).

The business sector is not the only means of innovation by pooling together diverse knowledge. International research projects, the inflow and outflow of students engaged in mobility programs and teachers' professional stages abroad are conductors of innovative ideas in the education and public research system. Global access to external data is also a channel for knowledge and transfer of ideas, and thus enables innovation in the private sector, with potential for entrepreneurship. This article analyses some of the effects that the flows of knowledge between the Romanian macroeconomic regions and the external sector have on the national R&D activity, using econometric models.

Methodology

Creating an innovation-friendly environment is one of the top seven priorities to raise growth and employment mentioned in the EU Strategy 2020. However, this strategy lacks sufficient support in Romania. The 2015 RIO Country Report of the European Commission (EC, 2015) illustrates a weak position of Romania when compared to the EU average. Romania has the lowest R&D expenditure in the EU, 0.38% of GDP in 2014. The rate of business R&D investments is negative as well: an -6.8% annual average growth for 2007-2012, reaching a level of 0.16% of GDP in 2014 (EC, 2014). The 2015 innovation report (EC, 2015) defines Romania as the country with the lowest rate of innovations among the EU Member States.

The reasons for this low level of R&D activity are diverse. On one hand, the yearly reports of the European Commission recognize the efforts made by the policy-makers to reform the research system in the country. Nevertheless, these efforts remained poorly implemented. Romania's public R&D expenditure was set at 1% for the period 2007-2013, but the actual annual allocation was around 0.3%. The Government reaffirmed the 1% target (twice lower than the EU average) for the National RDI Strategy 2014-2020. However, just a few months later in 2015, the budgetary allocation was established at a level that was 2.17 times lower than this objective. On the other hand, the business sector is dominated by multinationals that perform a relatively limited R&D activity in Romania. The SME sector carries out predominantly low value-added activities, having the lowest innovation score in EU. In addition to the governmental and business sectors, higher education institutions have also experienced a decreasing trend in R&D expenditures (RIO, 2015). The general image shows that there is much to do for Romania in this area, from securing the proper financing, to attracting the general interest in high value added activities. According to the EC research, the Romanian population continues to be unaware of the value that the R&D sector has for enhancing competitiveness and securing high-quality jobs. This article aims at raising interest in R&D activities by underlining some of the factors influencing it and the risks of ignoring this development strategy.

The research question

In this article, we analyse how the internalization of the Romanian macroeconomic NUTS 2 regions relates to the R&D activities in the country. According to the economic theory, the presence of international companies, the number of students and teachers engaged in mobility programs and the access to global data are all indirect factors of stimulating the R&D activity. The EU country report (RIO, 2015) recognises that there are no estimates of the general relationship between FDI and R&D activity in Romania, as the National Bank does not publish specific data for this component, but there are indications of such a relationship. The 2014 EU Industrial R&D Investment Scoreboard (Hernandez et al. 2014) shows that several of the top 18 'leading innovators in the EU' engaged in FDI projects in Romania. Romania attracted over 6% of such FDIs in manufacturing, and 19% in business services, accounting for almost 10% of their total foreign investments. In order to test the general relationship between the foreign exchange of information in the business and academic sectors and the R&D activity, we formulated the following research question: "Is there a statistically significant relationship between the level of R&D activity and the inflow of knowledge from abroad through FDI, professional mobility and use of internet?"

After studying the general model on the Romanian macroeconomic regions, we analyse the particular case of the textile industry. This is because the textile industry is a good example of a sector in which the foreign presence through FDI does not trigger knowledge transfer. The textile industry in Romania received a high level of foreign investments after 1990s, but most of the economic activities were directed through "Lohn" contracts. These types of supply contracts stipulate that all the innovative activities in the production chain--business model, market research, design, strategy and marketing--are managed abroad, at the headquarters of the investors. The only resource of the country used in this process is the low-skilled labour force in the manufacturing process. This case study allows us to test if subcontracting the knowledge intensive activities is an essential factor in determining whether the FDI can stimulate the regional R&D process. By testing these limits, we can underline the effects of the knowledge component in FDI, apart from other elements, like financing, experience, access to other markets or other effects that FDI can have on the target economy and that do not relate to knowledge transfer.

Research steps

For testing our general research question, we will use an econometric model. The importance of the FDI nature--whether or not it includes knowledge intensive activities--will follow shortly after. Our analysis focuses on the eight macroeconomic regions of Romania. Based on our research question, we defined the dependent variable as an estimator of the level of R&D activity and wrote the general econometric model. After selecting the best estimators for the dependent and independent variables, we decided upon the relevant period and afterwards scaled the estimators in respect to the size of the macroeconomic regions, in order to account for size differences. The next step was data collection, computation and formalisation. For analysing the data, we used Stata, as this program makes it convenient to examine cross-sectional time series models. Based on the Breusch and Pagan Lagrangian multiplier and the Hausman tests, we selected the model and ran the regression analysis. Finally, the results were reported and interpreted.

For the second part of our research question (the importance of knowledge intensive activities), we decided upon the statistical model and implemented the first steps described above. The data collection showed that the dependent variable had the level "zero" during the entire analysed period. This invalidated the choice of an econometric analysis and we made use of economic reasoning and descriptive statistics instead. The results were reported and analysed, linking them to the general research question.

First research question: estimators of the general model

In order to assure the relevance of the results for the policymaking, we considered only data starting one year after the membership in the European Union, 2008 and up to the last available statistical year reported, 2013. Delayed effects of membership are thus accounted for by leaving one year for adaptation.

The R&D activity of the regions is estimated by the percentage...

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