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Internationalisation, innovation and productivity in services: evidence from Germany, Ireland and the United Kingdom

Abstract

This paper examines the links between internationalisation, innovation and productivity in service enterprises. For this purpose, we use micro data from the Community Innovation Survey 2008 in Germany, Ireland and the United Kingdom, and estimate an augmented structural model. Our empirical evidence highlights the importance of internationalisation in the context of innovation outputs in all three countries. Our results indicate that innovation in service enterprises is linked to higher productivity. Among the innovation types that we consider, the largest productivity returns were found for marketing innovations.

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Notes

  1. Recent reviews of these studies are Hall (2011), Mohnen and Hall (2013), Ruane and Siedschlag (2013), and Siedschlag and Zhang (2015).

  2. The Community Innovation Survey is a harmonised survey on the innovation activities in enterprises. It is carried out on a voluntary basis, currently every 2 years, by European Union countries and other countries which are members of the European Statistical System (ESS) such as countries members of the European Free Trade Area (EFTA) and EU candidate countries. The concepts and underlying methodology of the core survey questionnaire are based on the Oslo Manual (OECD and European Commission 1997, 2005), an internationally recognised set of guidelines on collecting and interpreting data on innovation published jointly by the OECD and the European Commission.

  3. Masso and Vahter (2012) being an exception who analysed the role of marketing innovation on productivity in Estonia.

  4. Gross value added per person employed in constant (2010) prices taken from the European Commission's Ameco data base available at: http://ec.europa.eu/economy_finance/ameco/user/serie/SelectSerie.cfm.

  5. For example, Mairesse and Mohnen (2010a, b) and Hall (2011) provide a concentrated review of the literature.

  6. In particular, Pakes and Griliches (1980, 1984) introduce a general model and a ‘path analysis diagram’ linking ‘research expenditures’ with increases in ‘knowledge capital’ (this stage being the ‘knowledge production function’), and increases in knowledge capital then with ‘other expected or realized benefits from invention’ (Pakes and Griliches 1984, p. 56).

  7. The Oslo Manual (OECD and European Commission 2005) defines that “a product innovation is the introduction of a good or service that is new or significantly improved with respect to its characteristics or intended uses. This includes significant improvements in technical specifications, components and materials, incorporated software, user friendliness and other functional characteristics.” Product innovations in services can include improvements how they are provided (e.g. speed, efficiency), the addition of new functions or characteristics to existing services, and of course, introduction of fully new services. “A process innovation is the implementation of a new or significantly improved production or delivery method. This includes significant changes in techniques, equipment and/or software.” An organisational innovation is “the implementation of a new organisational method in the firm’s business practices, workplace organisations or external relations (OECD 2005).” A further type of innovation that affects the benefits from product innovation is marketing innovation. According to the Oslo Manual (OECD 2005 and European Commission), “a marketing innovation is the implementation of a new marketing method involving significant changes in product design or packaging, product placement, product promotion or pricing.” The aim of marketing innovation is to increase sales of the firm by improved addressing of customer needs, opening up of new markets and positioning firm’s goods or services on the market.

  8. This international evidence has been reviewed by Mairesse and Mohnen (2010a, b) and Hall (2011).

  9. See Syverson (2011) for a recent review of productivity measurement issues.

  10. Complementarities exist between factors (Xi, Xj) when the mixed-partial derivatives of a payoff function \(\varPi \left( {X_{i} , X_{j} , Z} \right)\) are positive: \(\frac{{\partial^{2} \varPi \left( {X_{i} , X_{j} , Z} \right)}}{{\partial X_{i} \partial X_{j} }} > 0,\) i.e., if an increase in the level of adoption of one variable (Xi) raises the marginal payoff of the other variable(s) (Xj) (Milgrom and Roberts 1990, 1995). Note: Z denotes other exogenous determinants of payoff.

  11. The term enterprise and firm are used interchangeably.

  12. The specific characteristics of the data collected with CIS and related implications for econometric analysis are discussed extensively by Mairesse and Mohnen (2010a, b). Our econometric methodology discussed above deals, as satisfactorily as possible, with the qualitative and censored nature of the data.

  13. A number of service sectors (e.g. retail) that are available in the CIS for Germany and the UK are excluded to facilitate comparison with the CIS data for Ireland.

  14. For comparability purposes, these summary statistics are weighted to correct for the stratification of the CIS sample by size class, industry and region. Weighting factors are provided the statistical offices (IE and UK) and The Centre for European Economic Research (ZEW) which conducts the survey in Germany on behalf of the Federal Ministry of Education and Research. Discrepancies to published statistics may arise because our focus here is on the estimation sample.

  15. The sampling unit in the UK is the establishment rather than the enterprise (though the vast majority of establishments are in fact single establishment enterprises). Exclusion of the top 0.5% of establishments by employee size brings the mean number of employees in the UK service sector establishments much closer to that in Germany and Ireland.

  16. In the original CDM model, this equation was only estimated for the sample of innovative enterprises.

  17. OLS regressions indicate in all three countries large and highly significant correlations between the observed innovation expenditure intensity and the predicted innovation expenditure intensity. These results are available from the authors upon request.

  18. The industry dummies are at a two-digit level NACE Rev. 1 classification to ensure the identification of the determinants of innovation outputs, as we used three-digit industry dummies in the innovation expenditure intensity equation. Wald tests validate the exclusion of three-digit industry dummies.

  19. We thank an anonymous referee for making this point.

  20. The elasticity of productivity with respect to marketing innovation in Ireland is significant at the 11% level.

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Acknowledgements

This paper was partly funded by the European Commission under the RTD 7th Framework (Grant Agreement No. 244522) and Horizon 2020 Programmes. The work was also partly funded under the programme of the Centre for Learning and Life Chances in Knowledge Economies and Societies (LLAKES), an ESRC-funded Research Centre with grant reference ES/J019135/1. Priit Vahter also acknowledges financial support from the Estonian Research Agency project No. IUT20-49. This research uses statistical data from the Central Statistics Office (CSO) of Ireland. The permission for controlled access to confidential micro data was granted in line with the Statistics Act, 1993. The use of these statistical data does not imply the endorsement of the CSO in relation to the analysis or interpretation of the statistical data. Also, this work contains statistical data which is Crown Copyright and which has been made available by the UK Office for National Statistics (ONS) through the Secure Data Service (SDS) and has been used by permission. Neither the ONS nor the SDS bear any responsibility for the analysis or interpretation of the data reported here. This work uses research data-sets which may not exactly reproduce the National Statistics aggregates. The views expressed in this work are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Central Bank of Ireland or the European System of Central Banks. We thank Mattia Di Ubaldo for his generous assistance with Stata coding. We gratefully acknowledge useful comments and suggestions from the Editor, Horst Raff, two anonymous referees, Alan Barrett, Francesco Venturini and participants at research presentations at the Economic and Social Research Institute (ESRI) in Dublin, the Irish Economic Association Conference in Dublin and the Centre for European Economic Research (ZEW) in Mannheim for useful comments and suggestions.

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Peters, B., Riley, R., Siedschlag, I. et al. Internationalisation, innovation and productivity in services: evidence from Germany, Ireland and the United Kingdom. Rev World Econ 154, 585–615 (2018). https://doi.org/10.1007/s10290-018-0313-9

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Keywords

  • Internationalisation of services
  • Innovation
  • Productivity

JEL Classification

  • F61
  • L25
  • O31