ICT, Co-innovation and Productivity: Evidence fromEastern European Firms.

Aleksandra Skorupinska∗and Joan Torrent-Sellens†

Internet Interdisciplinary Institute (IN3), Open University of Catalonia (UOC)

Abstract

Main motivation behind this study is to evaluate relations between ICT, knowledge, man-agement practices, innovation, human capital, organizational and structural changes in sample ofmanufacturing enterprises from Eastern European countries. The main questions behind this studyare: 1) Does existence of new co-innovation productivity sources (usage of ICT, workplace or-ganization and human capital) affect manufacturing enterprises performance in Eastern Europeancountries? 2)What are the differences between Eastern European manufacturing enterprises?.

Our empirical descriptive and econometric analysis is based on data from Management, Or-ganization and Innovation (MOI) Survey 2009, a joint initiative of the European Bank for Recon-struction and Development (EBRD) and the World Bank Group. The MOI survey was undertakenfor the first time in 2008-2009, covering 1,800 manufacturing establishments with between 50and 5000 employees. For the present study, we have included data from 11 countries: Belarus,Bulgaria, Kazakhstan, Lithuania, Poland, Romania, Russia, Serbia, Ukraine, Uzbekistan and Ger-many as a developed country benchmark. Data from MOI survey was complemented by firmperformance data from Bureau van Dijk’s Orbis database. For the econometric analysis ordinaryleast squares regression is used to explain the role of factors that are affecting productivity.

The results of the investigation will bridge the gap of insufficient academic research aboutEastern European countries and extend existing research on firm-level labour productivity deter-minants. The model shows influence of ICT and complementarities on performance and develop-ment of enterprises and enable to compare the results at the international framework. Our findingscan be useful to suggest new directions in public policy to improve productivity in Eastern Euro-pean countries countries and in companies.

Keywords: Information and Communication Technologies (ICT); Co-innovation; Firm-level Produc-tivity.

∗Electronic address: askorupinska@uoc.edu; Corresponding author†Electronic address: jtorrent@uoc.edu

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1 Introduction

The widespread use of Information and Communication Technologies (ICT) is one of the main dis-tinguishing features of today’s economic activity (Jovanovic and Rousseau, 2005; Jorgenson and Vu,2007). The reason for this is twofold: first, their direct contribution to increased productivity and eco-nomic growth and second, their indirect contribution resulting from the generation of complementaryinnovations that improve economy’s Total Factor Productivity (TFP) (Pilat, 2006; Jorgenson et al.,2011; Ceccobelli et al., 2012). From the perspective of the impact analysis of ICT investment onproductivity and economic growth, empirical evidence shows that: 1) the rates of return on digitalinvestment are relatively much higher than those on investment in other physical components; 2) thereason for this is that digital investment and use often go hand in hand with other endeavours, usuallyhuman capital improvement and organisational and institutional change (Bresnahan et al., 2002; Ar-vanitis, 2005). Indeed, the transformative impact of digital investment and use on the productivity andeconomic growth becomes more evident through co-innovation processes. The transition countries ofEastern Europe (EE) face considerable challenges in adapting their economies to compete effectivelyin regional and global markets. It is a key issue to find a path to increase their productivity, adapt thestructure of their economy to global-knowledge competition, to promote co-innovation and developnew goods and services that respond to changing domestic and international demand. Thus, the im-pact of digital technological change and their co-innovation processes on productivity is an importantaspect for the region’s economic performance.

Main motivation behind this study is to evaluate relations between ICT, knowledge, managementpractices, innovation, human capital, organizational and structural changes in sample of manufactur-ing enterprises from Eastern European countries. The main questions behind this study are: 1) Doesexistence of new co-innovation productivity sources (usage of ICT, workplace organization and hu-man capital) affect manufacturing enterprises performance in Eastern European countries? 2)Whatare the differences between Eastern European manufacturing enterprises?.

2 Literature review: ICT, Co-innovation and Productivity

Much effort was put into research to understand the so called Solow Paradox concerning the limitedevidence of a positive productivity impact of the ICT (Jorgenson and Stiroh, 1999). The importanceof ICT is a much debated question with extensive literature focused on explaining and understand-ing their role in economic growth, productivity and efficiency. Significant progress has been notedsince 1990 in the analysis of ICT and productivity. Most empirical studies have been performed atthe microeconomic firm and industry level examining their relationship with economic growth andproductivity. At macroeconomic level fewer studies have been conducted because of a shortage ofdatasets related especially to ICT investment and usage and other relevant national characteristics.

Firm-level analysis complements the analysis at the macro-level and enables researches to bet-ter understand ICT diffusion effects and especially to more adequately reflect those quality changesbrought about by ICT. Regarding the relation between ICT and productivity at the firm-level there arefindings that ICT alone is not enough affect for productivity. Ignoring other complementaries maybias the analysis and overestimate the effect on ICT on productivity. Significant changes within thefirm structure, such as a shift in the employment structure from low to high skills, the diffusion ofICT, and a redesign of a firms workplace organization, can be observed over the last years and presentnew challenges for companies. Many authors pointed out importance of these interrelated changesas a shift towards a “new firm paradigm”, which they characterized using different labels: from a“mechanistic” to an “organic” firm structure (Burns and Stalker, 1994), from the “mass productionmodel” to the “flexible multiproduct firm” (Milgrom and Roberts, 1990), or from a “tailoristic” to a

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“holistic” organization of work (Lindbeck and Snower, 2000). Potential of ICT will not be realizedwithout business model changes and increase of human capital and ICT skills (Bresnahan et al., 2002;Arvanitis, 2005).

Most of the firm-level studies were focused on highly-developed countries. The empirical studyfor the Unites States (Bresnahan et al., 2002) formulated and confirmed new theory of skill-biasedtechnical change. The authors have shown the evidence of positive correlation of ICT use and in-vestment, workplace organization and skilled labour which have affected productivity. Moreover, itconcluded that with growing spread and access to ICT, the investment in complementarities is cru-cial, particularly in skilled labour. Furthermore taking the Unites States into consideration, there arestudies from Black and Lynch (2001, 2004) of manufacturing establishments showing that productiv-ity growth during 1990s has a source in workplace organization changes and innovations (employeeinvolvement, team work, incentive pay and decision-making autonomy) along with diffusion of com-puters.

Investigations conducted in other countries followed the path of analysis initiated in the UnitesStates. Analysis of panel data from for British and French firms (Caroli and Van Reenen, 2001)revealed that skilled workers adapt more easily to changes in organization. Having the above inmind, the authors presented empirical evidence of relationship between workplace innovation andhuman capital, and its influence on productivity. Another comparative study of Swiss and Greek firms(Arvanitis and Loukis, 2009) shows positive effects of physical capital, ICT, human capital and neworganizational practices on labour productivity. However, Swiss firms are more efficient in combiningand implementing those factors, while in the Greeks firms physical capital still plays crucial role inrelation to labour productivity. Research for the Catalan firms (Torrent-Sellens and Ficapal-Cusí,2010) confirmed role of new co-innovative sources in technology and knowledge-intensive firms.Among the remaining 80% of firms no evidence was found to show any impact of those sources.

In recent work Hall et al. (2012) examine the firm-level relationships between product, process,and organizational innovations, productivity, research and development (R&D) and ICT, using data onmanufacturing enterprises from Italy. They find that R&D and ICT are both strongly associated withinnovation and productivity, with ICT investment being more important for productivity. ICT andR&D contribute to productivity both directly and indirectly through the innovation equation, but theyare neither complements nor substitutes. However, individually both appear to have large impacts onproductivity, suggesting some underinvestment in these activities by Italian firms.

The transition of Eastern European economies is a recent phenomenon. Those countries havemuch less experience in evaluating the effect of ICT. Publications on ICT in transition economies aresparse. Following Roztocki and Weistroffer (2008) there are several explanations of this scarcity ofpublished research. Firstly, lack of funding for this type of research. Much of the published researchdealing with ICT in transition economies has therefore been carried out by researchers employed atinstitutions in developed countries. Secondly, in the communist period research was directed to otherdisciplines than ICT, such as physics and chemistry. Moreover, the effect of many administrativestructures and procedures that were instituted in the past still remain. Furthermore, reforms have beenconcentrated on economic changes rather than academics, with existing structures at many higheruniversities still inhibiting research productivity.

First publications concerning Eastern European countries evaluated the impact of ICT on growthat the aggregate level. Van Ark and Piatkowski (2004) compare productivity performance of 10 Cen-tral and Eastern European countries (CEE) and EU-15 countries during 1990s examining productivityand income convergence hypothesis. Their investigation gives more support to the convergence hy-pothesis. Besides, they show that ICT capital in the CEE countries has contributed as much to labourproductivity growth as in the EU-15 countries and that ICT capital depending on itself has not beenan important source of convergence. They emphasize the importance of consistent progress in eco-

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nomic, institutional and regulatory environment, the creation of modern institutions, implementationof market oriented policy reforms, increase in innovation and improvements in the quality of humancapital.

There are some pioneers of firm-level analysis as Stare et al. (2006) who explored a link betweenICT and the performance of service firms in Slovenia. They confirmed positive impact of ICT useon productivity, however due to absence of data on complementary expenditures for training andorganizational change the results might overestimate the impact of ICT.

Table 1 summarises the main results for a broad set of studies. Most of international empiricalevidence has confirmed the complementarities of new co-innovative firm productivity sources: ICTinvestment and usage, human capital and new forms of work organization, however more empiricalstudies are still needed in this field. Eastern European countries are clearly marked by sacristy ofstudies on ICT and complementarities and productivity.

Table 1: Literature Review Summary

Autors Region Time period Key results

Macroeconomic literatureVan Ark &Piatkowski(2004)

CEE-10 &EU-15

1989-2002 Support of convergence hypothesis. Emphasison complementaries to ICT investment.

Microeconomic (firm-level) literatureCaroli& VanReenen2001

UnitedKingdom& France

1984,1990,1992, 1996

Skilled workers more easily adapt to changesin organization. Evidence of relationship be-tween workplace innovation and human capitaland their influence on productivity.

Bresnahan& Brynjolf-sson & Hitt(2002)

UnitesStates

1987-1994 Positive correlation of ICT, workplace organi-zation and skilled labour which have affectedproductivity.

Black &Lynch(2004)

UnitesStates

1987-1993,1997

ICT together with workplace organization havesignificant and positive impact on productivity.

Stare &Jaklic &Kotnik(2006)

Slovenia 1996-2002 Positive impact of ICT use on productivity.

Arvanitis& Loukis(2009)

Switzerland& Greece

2005 Positive effects for physical capital, ICT, hu-man capital and new organizational practices onlabour productivity.

Torrent& Ficapal(2010)

Spain (Cat-alonia)

2003 No relevant impact of ICT use in 80% of firms.Significant delay in the implementation of theco-innovative productivity sources in Catalonia.

Hall &Lotti &Mairesse(2012)

Italy 1995-2006 R&D and ICT are associated with innovationand productivity. They contribute to productiv-ity both directly and indirectly through the in-novation equation.

Source: Own elaboration.

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3 Data

Our empirical descriptive and econometric analysis is based on data from Management, Organizationand Innovation (MOI) Survey 2009, a joint initiative of the European Bank for Reconstruction and De-velopment (EBRD) and the World Bank Group. The MOI survey was undertaken for the first time in2008-2009, covering 1,800 manufacturing establishments with between 50 and 5000 employees. Forthe present study, we have included data from 11 countries: Belarus, Bulgaria, Kazakhstan, Lithuania,Poland, Romania, Russia, Serbia, Ukraine, Uzbekistan and Germany as a developed country bench-mark. MOI interviews were conducted face-to-face and took place between October 2008 and April2010. The Survey uses a standardized survey instrument and a uniform sampling methodology to min-imize measurement error and generate a sample representative of the manufacturing sectors in eachcountry. Data are comparable across the countries and the sample seize is large enough to conductstatistically robust analysis with levels of precision at minimum 7.5% precision for 90% confidenceintervals (EBRD and World Bank, 2008).

Data from MOI survey was complemented by firm performance data (balance sheets and incomeand loss statement) from Bureau van Dijk’s Orbis database. Given that the output variables fromBureau van Dijk’s Orbis database are not available for all countries and also for all firms in thecountry, we run the risk that results are driven by specific country. Used sample in econometricanalysis is reduced to 779 companies with operating revenue in 2008 data available. Measures ofprobability: the operating revenue and fixed financial assets are winsored at 1 % to limit the impactof outliers on the result1.

4 Co-innovation productivity sources in transition countries

4.1 Productivity comparison

The aggregate productivity patterns in EE countries resemble those of advanced market economiesand are mainly driven by efficiency gains within individual firms. Nowadays, when transition is overthe productivity improvements should be searched in other factors such as research and innovativeeffort, the development of human capital through education and incentives from stronger competition(Alam et al., 2008). Firms face rapid changes of environment caused by globalization, appearanceof new competitors and diversification of demand. Though, the priority is to maintain and improveability of firms to innovate and compete. Firms to remain competitive on the market have a need todevelop new organizational strategies. ICT enable new business processes and new work practices,which lead to cost reductions, improved output and productivity gains. Moreover, ICT give newpossibilities of doing business (B2B) and new ways of producing goods and services. Figure 1ashows how significant is a gap between EE countries and Germany in productivity, measured asa company’s turnover in 2008 divided by the number employees. Considering this indicator on theaverage the firms from the leader from EE countries Poland have more the six times lower productivitythan German’s enterprises.

4.2 ICT

Infrastructure improvement is required to benefit from network effect as one needs to exceed certainpoint in development of the network. Communications and Internet infrastructure are wonders ofthe knowledge-based economy facilitating rapid catch-up with developed countries (Kauffman and

1This means that all the data below the 0.5th percentile are set to 0.5th percentile and all the data above the 99.5thpercentile are set to 99.5th percentile as in Bloom et al. (2012).

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Techatassanasoontorn, 2009). Transition economies made a big step in upgrading their networks.Despite of Uzbekistan where less that 50% (Figure 1b) of manufacturing enterprises have high-speedInternet connection, on the average more than 75% of establishments have Internet access. Polandand Romania are leaders with more than 98% of connected companies.

In addition, one of the main information society indicators: level of computer usage, shows asignificant differences between countries. Figure 1c shows that in Germany’s manufacturing com-panies at average more than 40% of employees regularly uses personal computers for their job. Intwo European Union countries: Bulgaria and Romania this indicator is below 20%. Regarding East-ern European countries, ICT-skill oriented education level is not sufficient. Moreover, firms shouldprovide equipment and training to encourage workers to change their attitudes toward the adoptionof technology. Young workers will adopt technology faster, however similarly to the rest of Europe,society is ageing which can further hinder the progress.

Figure 1: Productivity and ICT

(a) Productivity (b) ICT infrastructure (c) Internet use

Source: Own elaboration. Orbis database and MOI survey.

4.3 Innovation

Nowadays, knowledge is the resource and the commodity of knowledge economy, which explainsthe progress in productivity. The knowledge generation is a dynamic process created on the basisof interactions between individuals, groups, organizations and societies (Castells, 2011). Innovationbegins with firms’ formal and informal R&D effects. R&D activity is generally conceptualized asan input to the innovation process and can have substantial influence on the innovation performanceof firms (Hall et al., 2012). Internal R&D activities are needed for understanding and absorption ofknowledge developed internationality, for improvement of local R&D skills and active participationin international R&D networks. Countries where ease business arrangements and quality of tertiaryeducation are relatively high tend to benefit more from R&D efforts and from international R&Dspillovers. Surprisingly, less than half of companies in the sample invested during year 2008 in anykind of R&D activities, either in-house or contracted with other companies. Innovation abilities arestrongly connected with human capital. Wide range of skills needed for innovation, including techni-cal skills, academic skills, generic skills, creativity, soft skills, and management and entrepreneurialskills.

Profitable application of the newly created knowledge is crucial. Development of new products orservices is a prime source for gaining position in the market. Propensity of firms to perform product

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Figure 2: Innovation

(a) R&D investment (b) Product innovation (c) Patents

Source: Own elaboration. MOI survey.

innovation or in the other words ’occurrence of innovation’ (Figure 2b) happened that more than 75%of Bulgarian, German, Lithuanian and Polish manufacturing enterprises introduced new product orservice. In addition, strong patent protection, which preserve new innovation is associated with higherlevels of total factor productivity. Patents can be used as a measure of the output of innovation (Figure2c). Patents are registered in more than half German companies, fallowed by Ukraine and Poland.Low level of innovation in EE countries is another legacy of the communism. Under the centrallyplanned economic system there were no incentives to innovate. Flow of the knowledge betweenscience and industry is weak and there are difficulties in diffusion of existing results to business use.It is mostly due to the heritage of socialist times when all applications of R&D were controlled bystate and due to insufficient financial support.

4.4 Human Capital

Presently the importance of human capital is much higher in knowledge economy than in industrialeconomy. Better quality human capital can help enterprises to develop their technologies as well asincrease enterprises ability to absorb high technology knowledge from abroad. Firms with greaterhuman capital innovate more. Education acquisition, especially tertiary education, provides higherlevel knowledge and skills which is the key to technology use and support within organizations (firms,governments, schools). Human capital derived from university education, but also from training andaccumulated through learning by action, can increase the efficiency of labour and also enhance TFP(Black and Lynch, 2001; Arvanitis, 2005). Apparently, it is the cumulative knowledge constituted byknowledge possessed by the technical personnel and managers together that seem to be effectual forfirms’ productivity. However, it should be noted here that the employees on the lower level are equallyimportant to the firm performance. In the manufacturing enterprises the highest share of employeeswith university degree is in Russia (Figure 3a) followed by Ukraine, Kazakhstan and Belarus.

4.5 Organization

Crucial aspects are reformulation of the organizational architecture and new forms of work organi-zation. ICT implementation brings innovation to the work place, changes of distribution channelsand production processes. To take advantage from the opportunities offered by ICT it is important

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to change the organization structure and adapt working processes. The other important human factorare actions, which increase workers’ commitment and motivate them to be more efficient and produc-tive, such as decrease in hierarchical structures, increased autonomy and decision making capacity,working time flexibility or innovative remuneration strategies (Caroli and Van Reenen, 2001). One ofthe characteristics of organizational change is greater flow of communication, sharing and exchangeof information between workers. Management and organization practices in Kazakhstan and Uzbek-istan, have on average very poor. In contrast Central European countries such as Poland and Lithuaniaoperate with management practices which are only moderately worse than in Germany (Bloom et al.,2012) 2. Figure 3b presents what percentage of employees report directly to the factory manage-ment, which includes regular interaction, pay setting and the determination of promotion. There isa significant difference between countries, where in Germany more than 30% of workers report di-rectly to managers, in opposite in Bulgaria only 2% of workers. Further, regarding if establishment’smanagement asks any workers for their opinion with regard to the decisions about work conditions(Figure 3c) in European Union countries and in Uzbekistan in more than 50% companies workers areasked about they opinion.

Figure 3: Human capital and organization

(a) Education (b) Reporting (c) Asking for opinion

Source: Own elaboration. MOI survey.

5 Empirical model

5.1 Methodology

Methodology is an extension of well-established traditional growth and productivity accounting ap-proach, based on Solow growth model (Solow, 1957) and its extension by Jorgenson and Griliches(Jorgenson and Griliches, 1967). The new co-innovation productivity sources are incorporated in theefficiency component (Total Factor Productivity). We use ordinary least squares to explain the roleof factors that are affecting productivity. These methods enable to estimate factors and explainingdifferences in productivity between firms.

2For more information on management practices in transition countries consult: Bloom et al. (2012); Schweiger andFriebel (2013).

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5.2 General Model

Production function takes form:

Yi = AiKαi L

βi I

γi (1)

Where, for any given firm i, Y is lever of turn over; A is production efficiency (total factor pro-ductivity); K is input of physical capital; L is input of labour; I is intermediate production costs.Co-innovative productivity sources are incorporated in production efficiency.

Ati = exp(δ0ICT + δ1Innovation + δ2HumanCapital + δ3Organization) (2)

After logarithm transformation of some variables the final model takes form:

lnYi−lnLi = β0+β1(lnKi−lnLi)+β2ICT+β3Innovation+β4HumanCapital+β5Organization

(3)

5.3 Variables

Table 2 presents list of variables included in the model.

Table 2: Variables

Indicator DescriptionProductivity Logarithm of turnover divided by the number of full-time employeesPhysical capital (K) Fixed assets divided by the number of full-time employeesICT Usage Percentage of firm employees that regularly use personal computers in their

jobsInfrastructure 1 when firm has a high-speed Internet connection on its premises; 0 otherwiseProduct innovation 1 when firm has introduced new products or services in the last three years; 0

otherwiseR&D investment 1 when firm has spent on research and development activities, either in-house

or contracted with other companies (outsourced) in fiscal year; 0 otherwisePatents 1 when firm has have any patents registered abroad or at home; 0 otherwiseOrganization Percentage of firm employees that report directly to the factory managerEducation Percentage of firm full-time employees with a university degree

Source: Own elaboration.

5.4 Results

The results obtained by estimation of ordinary least squares for the productivity of manufacturingestablishments in transition countries and Germany are presented in Table 3. We estimated the model

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for all countries and with sample division for 5 Eastern European, 5 European Union countries, 4Central European and Germany. ICT usage is considered to be important determinant of productivityin manufacturing firms considering All countries, EU and CEE sample. Another explanatory variable- Infrastructure - affirmed the fact that access to high-speed Internet is significant in explaining vari-ations in the labour productivity in whole sample and in EE countries. Furthermore, patents appearto be relevant factor in explaining variations in productivity in All countries, EU and Germany. Otherindicators of innovation, R&D investment is not significant and introduction of new product has pos-itive influence only in the whole sample. Human capital represented by percentage of firm full-timeemployees with a university degree is positive and significant for EE countries and negative for EUsample. Our variable Organization, which is a share of workers that report directly to the factorymanager is significant, besides of CEE and Germany.

Table 3: Influence of ICT and complementarities on labour productivity

All countries R,U,B,K,S EU CEE Germany(Intercept) 1.790∗∗∗ 1.802∗∗∗ 2.399∗∗∗ 2.002∗∗∗ 4.177∗∗∗

(0.153) (0.173) (0.288) (0.324) (0.495)log(K) 0.398∗∗∗ 0.286∗∗∗ 0.484∗∗∗ 0.377∗∗∗ 0.465∗∗∗

(0.020) (0.025) (0.035) (0.040) (0.050)ICTUsage 0.010∗∗∗ 0.003 0.013∗∗∗ 0.008∗∗∗ 0.001

(0.002) (0.002) (0.003) (0.003) (0.004)Infrastructure 0.318∗∗ 0.505∗∗∗ −0.419 0.164 −0.090

(0.140) (0.155) (0.267) (0.320) (0.370)RDinvestement 0.091 0.066 0.082 0.125 −0.202

(0.088) (0.111) (0.129) (0.137) (0.206)ProductInnovation 0.222∗∗ 0.159 0.148 0.152 -0.562∗∗

(0.090) (0.113) (0.134) (0.135) (0.279)Patents 0.215∗∗ −0.053 0.418∗∗∗ 0.141 0.553∗∗

(0.084) (0.106) (0.124) (0.134) (0.206)Education −0.002 0.006∗∗∗ -0.008∗∗ 0.004 −0.006

(0.002) (0.002) (0.003) (0.004) (0.009)Organization 0.008∗∗∗ 0.006∗∗∗ 0.009∗∗∗ −0.003 0.003

(0.002) (0.002) (0.002) (0.003) (0.003)R2 0.437 0.282 0.570 0.423 0.573Adj. R2 0.431 0.268 0.560 0.405 0.529Num. obs. 779 425 354 266 88***p < 0.01, **p < 0.05, *p < 0.1 Std. errors are in parenthesisSource: Own elaboration. Orbis database and MOI survey.Note: R,U,B,K,S - Russia, Ukraine, Belarus, Kazakhstan, Serbia; CEE - Poland, Bulgaria, Romania, Lithuania;Uzbekistan was excluded from econometric analysis due to lack of financial data.

Furthermore, we computed regression separately for every country (Table 4). Only physical capi-tal is significant for all countries. Estimated models shows that different variables influence on labourproductivity. In Germany and Ukraine meaningful are patents, in Poland and Romania variable Edu-cation, in Serbia access to Internet and in Bulgaria and Russia ICT usage.

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Table 4: Influence of ICT and complementarities on labour productivity: Cross-country comparison

Germany Poland Lithuania Romania Bulgaria Serbia Ukraine Russia(Intercept) 4.177∗∗∗ 1.786∗∗∗ 3.085∗∗∗ 1.677∗∗ 1.760∗∗ 1.089∗∗ 1.721∗∗∗ 3.081∗∗∗

(0.495) (0.448) (0.560) (0.539) (0.542) (0.379) (0.263) (0.271)log(K) 0.465∗∗∗ 0.546∗∗∗ 0.300∗∗∗ 0.296∗∗∗ 0.270∗∗ 0.428∗∗∗ 0.274∗∗∗ 0.258∗∗∗

(0.050) (0.093) (0.072) (0.063) (0.080) (0.079) (0.056) (0.028)ICTUsage 0.001 0.002 0.003 −0.006 0.012∗∗ 0.012 0.001 0.004∗

(0.004) (0.006) (0.006) (0.007) (0.005) (0.008) (0.003) (0.002)Infrastructure −0.090 −0.034 0.420 0.569 0.782∗∗ 0.222 −0.239

(0.370) (0.505) (0.541) (0.535) (0.301) (0.253) (0.244)RDinvestment −0.202 0.289 −0.150 0.276 −0.041 0.128 −0.110 0.030

(0.206) (0.257) (0.282) (0.213) (0.294) (0.248) (0.197) (0.135)ProductInnovation -0.562∗∗ 0.164 −0.109 0.493∗∗∗ −0.086 0.029 0.114 0.084

(0.279) (0.292) (0.395) (0.181) (0.291) (0.255) (0.187) (0.146)Patents 0.553∗∗∗ 0.031 0.113 0.400 0.259 0.184 0.358∗∗ −0.141

(0.206) (0.235) (0.287) (0.240) (0.244) (0.271) (0.170) (0.131)Education −0.006 0.015∗ 0.013 0.018∗∗∗ −0.001 −0.008 0.003 0.005

(0.009) (0.008) (0.009) (0.006) (0.006) (0.010) (0.004) (0.003)Organization 0.003 0.006 −0.011 -0.017∗∗∗ −0.004 0.006 −0.002 0.004∗

(0.003) (0.004) (0.038) (0.004) (0.010) (0.004) (0.010) (0.002)R2 0.573 0.636 0.478 0.589 0.270 0.379 0.281 0.364Adj. R2 0.529 0.576 0.359 0.541 0.202 0.329 0.226 0.337Num. obs. 88 51 44 77 94 109 113 193***p < 0.01, **p < 0.05, *p < 0.1 Std. errors are in parenthesisSource: Own elaboration. Orbis database and MOI survey.Note: In Poland variable Infrastructure is not relevant, because all companies have Internet connection.Belarus and Kazakhstan were excluded from comparison because of too small data sample available.

6 Conclusion

In the last years variety of international research has demonstrated the existence of co-innovativesources of firm productivity. Precisely, complementarity between ICT usage and investment, innova-tion, human capital and work organization. Using MOI survey (2008) data for representative sampleof manufacturing enterprises from transition economies and Germany, we analysed the determinantsin firm labour productivity. We aim to extend existing literature by new empirical evidence for tran-sition economies.

The Eastern European have enjoyed strong economic growth, that has been spurred by both do-mestic and external factors, and made a huge step to restructure and are steadily striding towardsa knowledge economy. Companies form countries which have joined European Union: Bulgaria,Lithuania, Poland and Romania are ahead other transition economies. The improvement of firms pro-ductivity are affected not only by their own ideas and capabilities, but also by framework in whichthe firms operate. The obtained results have some policy implications. The policy makers should sup-port ICT use, reduce digital divide and avoid inhibiting policies such as taxes or charges. It should bemade an effort to promote jointly ICT usage and investment, with innovation activities, organizationalchanges and human capital improvement.

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The main limitation of this research is relatively small sample of enterprises included in the MOIsurvey database and high number of missing financial data. We have in mind firm heterogeneityacross countries and across industries. It implies that more factors influence labour productivitywhich we could not have taken into consideration. However, such a discussion is out of scope ofcurrent research. Regarding importance of this topic especially for transition economies there is aneed for more data including: more countries, improving indicators, collecting data from serviceenterprises and small and medium enterprises. This study has a preliminary character and suggestfurther research lines for transition economies.

7 Acknowledgements

We thank the European Bank for Reconstruction and Development for having kindly supplied firm-level data for this project, in particular Helena Schweiger.

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