Organisational capital, firms’ innovation strategies and productivity Rebecca Riley* and Priit Vahter** *National Institute of Economic and Social Research; Centre for Learning and Life Chances in Knowledge Economies **University of Tartu, Estonia Productivity and Firm Growth Workshop NIESR 2 July 2014 Acknowledgements: The financial support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. The work was part of the programme of the Centre for Learning and Life Chances in Knowledge Economies and Societies (LLAKES), an ESRC-funded Research Centre – grant reference ES/J019135/1.

Disclaimer This work contains statistical data which is Crown Copyright; it has been made available by the 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 datasets which may not exactly reproduce National Statistics aggregates.

Substantial performance differentials across firms – Within narrowly defined industries and between observationally similar firms (Syverson, JEL 2011) Organisational capital as a driver of performance differentials – Schumpeterian entrepreneur drives the innovation process – Building absorptive capacity Cohen and Levinthal, 1989 – HRM related aspects of management thought to be important for productivity Ichniowski et al., 1997, 2003; Bandiera et al – Recent studies by Bloom et al. demonstrate a positive association between “best practice” management and firms’ performance – Recent management literature demonstrates positive associations between indicators of management and indicators of innovation Laursen & Foss, 2013 – Complementarities with other inputs, IT in particular Bloom, Sadun & Van Reenen 2012; Bresnahan et al. 2002; Crespi et al – Mirrored in the macroeconomic literature on intangibles, with the concept of economic competencies Corrado et al. 2009; Haskel et al. for the UK Background & Motivation (1)

Moving beyond the basic concept of human capital or quality adjusted labour in the production function – Human capital as an input to the production of other knowledge intensive intangible capital inputs Existing firm-level studies of organisational capital and performance – Typically rely on indicator variables – Capturing very specific aspects of organisational capital – Case study evidence; relative dearth of representative analyses – Usually consider productivity as the outcome variable, innovation linkages ignored – Causality remains a big issue This paper – Studies linkages between organisational capital, innovation and productivity at the level of the firm – Using a relatively generic measure of organisational capital – Within a relatively standard structural model of innovation and productivity Background & Motivation (2)

Measuring firms’ organisational capital (1) Assess labour costs associated with production of organisational investment – Evaluate occupational structure of the firm’s workforce using linked employer-employee data – Assumptions about the share of worker effort that leads to investment Account for related costs of production – Evaluate cost structure of production in Other Business Service industries Capitalisation – PIM – Assumptions about depreciation rates, starting stocks Data developed and detailed in FP7 INNODRIVE. See also Riley and Robinson (2011) Skills and Economic Performance: The Impact of Intangible Assets on UK Productivity Growth, UK Commission for Employment and Skills.

Investment in organisational capital = (cost of workers performing “organisational” tasks) x (share of worker effort leading to investment; 0.2) x (cost of associated physical capital & intermediates; 1.76)

Workers involved in production of organisational assets – Production & operations department managers – Highly skilled business professionals – Sales, marketing, advertising & public relations managers Data sources – Annual Business Inquiry (census of large firms, sample of smaller firms) – Annual Survey of Hours and Earnings (1% sample of employees ) LEED data – Firm linked data yields much smaller sample – Link by NACE3 & 3 size categories – Correlation between measures is 0.50 Measuring firms’ organisational capital (2)

Linked innovation survey data UK CIS4 (period ) & CIS6 (period ) – merged with firm level data on materials purchases, organisational and fixed assets per employee – enterprises with 10+ employees – manufacturing and market services Innovation expenditure – Internal & external R&D; acquisition of external knowledge; acquisition of machinery, equipment and software for innovation Innovation output – Product, process, share of new and modified products in sales Human capital – Share of workers with a degree Other data – Labour productivity, employment, exporting, industry affiliation, innovation co-operation, funding for innovation

Sample characteristics sourcetimingmeansd Innovation expenditure>0 dummy CISperiod end Innovation expenditure per employee (log) CISperiod end Product innovation CIS3-yr period Market novelties CIS3-yr period Firm novelties CIS3-yr period Process innovation CIS3-yr period Innovative turnover share CIS3-yr period Innovative turnover share (new to market) CIS3-yr period Innovative turnover share (new to firm) CIS3-yr period Funding for innovation CIS3-yr period Co-operation on innovation CIS3-yr period Exporter CIS3-yr period Share of skilled employees CISstart/end period Organisational capital per employee (log) ARD/ASHEperiod start Tangible capital per employee (log) ARD/ASHEperiod start Materials per employee (log) ARD/ASHEperiod start Turnover per employee (log) CISperiod end Size employees CISperiod start Size employees CISperiod start Size employees CISperiod start Size employees CISperiod start Observations 5707 Materials/Turnover 45% Fixed capital/Turnover 15% Organisational capital/Turnover 7% Note: Tangible capital estimates provided by Richard Harris. These exclude property capital.

Innovation output Innovation input Innovation decision Propensity to invest in innovation 2nd stage: Innovation production function 3rd stage: Augmented production function 1st stage: Innovation investment Selection equation and innovation investment function Econometric Model (augmented CDM model) Innovation expenditure intensity Innovation output Product innovation Process innovation Productivity Organizational capital (management) Based on the Crépon-Duguet-Mairesse (CDM, 1998) model and extension in Griffith et al. (2006). Sales/employee

Investment in Innovation (stage 1) DPV Propensity to invest in innovation Intensity of innovation expenditure Heckman stage 1Heckman stage 2 Exporter0.072***0.053 (0.016)(0.073) Share of skilled employees0.171***0.892*** (0.038)(0.152) Organisational capital per employee (log)0.023*0.270*** (0.013)(0.070) Tangible capital per employee (log) *** (0.006)(0.029) Materials per employee (log) *** (0.008)(0.036) Funding for innovation0.284***0.736*** (0.018)(0.087) Co-operation in innovation 0.383*** (0.064) Size employees0.067*** (0.021) Size employees0.103*** (0.020) Size employees0.117*** (0.020) Size employees0.105*** (0.027) Industry fixed effects x time effects2-digit3-digit Observations5,7073,331 Log likelihood-9626lambda=0.704 Wald test for H0: rho=033.94rho=0.438 Notes: Marginal effects; robust standard errors; CIS4 ( )andCIS6 ( ); manufacturing and market services (excluding finance).

Innovation Output (stage 2) Innovation Output Equation DPV: Product innovation Market novelties Firm novelties Process innovation Innovative turnover share Estimator:Probit OLS Predicted innovation expenditure0.063***0.029***0.051***0.050***0.020*** (0.013)(0.009)(0.011)(0.010)(0.005) Exporter0.083***0.062***0.065***0.029**0.024*** (0.017)(0.012)(0.015)(0.013)(0.007) Share of skilled employees0.110***0.117*** *** (0.038)(0.026)(0.035)(0.030)(0.018) Organisational capital per employee (log) (0.015)(0.011)(0.013)(0.012)(0.005) Tangible capital per employee (log) * (0.006)(0.005)(0.006)(0.005)(0.003) Materials per employee (log) **-0.005* (0.008)(0.006)(0.007)(0.006)(0.003) Co-operation in innovation0.438***0.250***0.339***0.312***0.138*** (0.017)(0.016)(0.017) (0.009) Size employees (0.024)(0.018)(0.021)(0.019)(0.009) Size employees0.045**0.029* *** (0.022)(0.017)(0.020) (0.008) Size employees0.037* *0.090***0.008 (0.020)(0.014)(0.017) (0.008) Size employees0.120***0.114***0.075***0.135***0.01 (0.029)(0.025)(0.026)(0.027)(0.010) Industry fixed effects (2 digit) x time effectsyes Observations5,7025,6905,7025,6955,707 Pseudo Rsq/Rsq Log likelihood Notes: Marginal effects; robust standard errors; CIS4 ( )andCIS6 ( ); manufacturing and market services (excluding finance).

Productivity (stage 3) Productivity Equation (DPV = Turnover/Employees) Type of innovation output Product innovation Market novelties Firm novelties Process innovation Innovative turnover share Predicted innovation output0.021**0.028**0.026** 0.183** (0.009)(0.012)(0.011) (0.080) Exporter0.061***0.058***0.060***0.062***0.060*** (0.012)(0.013) (0.012) Share of skilled employees0.149***0.144***0.154***0.156***0.139*** (0.027)(0.028)(0.026) (0.028) Organisational capital per employee (log)0.142*** 0.143*** (0.010) Tangible capital per employee (log)0.030*** 0.031***0.030***0.031*** (0.004) Materials per employee (log)0.522*** 0.523*** (0.006) Size employees-0.046***-0.047***-0.046*** *** (0.017) Size employees (0.016) Size employees (0.014) Size employees0.037* * ** (0.020) (0.019)(0.020)(0.019) Industry fixed effects (2 digit) x time effectsyes Observations5,7025,6905,7025,6955,707 Rsq0.857 Notes: Marginal effects; CIS4 ( )andCIS6 ( ); manufacturing and market services (excluding finance); robust regression; std errs in brackets.

Complementarities-in-Use. Innovation Expenditures and Organisational Capital Kernel density of organisational capital per employee for firms with above and below median innovation expenditure (deviation from NACE 2-digit sector and year averages). Data: UK CIS 4 and 6, years , K-S test statistic (p-value= 0.000). Firms with above median innovation expenditures Firms with below median innovation expenditures

Other Results Excluding innovation expenditure in the innovation output equation – Organisational capital becomes positive and significant Additional controls to take into account known complementarities do not change the overall pattern of results – Foreign ownership – IT capital Alternate specifications – Linear employment term to measure firm size/inclusion in all equations does not change the pattern of results – Using OLS to estimate the productivity equation we find that innovation output is not statistically significant – Lagged dependent variable in the productivity equation alters the magnitudes of some of the long run output elasticities – Single innovation indicator – Innovation inputs in the productivity equation

Conclusions Organisational capital contributes to business performance both directly and indirectly via the innovation process. The association between organisational capital and innovation performance occurs mainly via the intensity of innovation investments. – Measurement issues (a sensible distinction between innovation inputs/outputs)? – Organisational capital as an input to strategic decision making; Organisational capital as absorptive capacity And is persistent across broad sectors – Knowledge Intensive Services, Other Services, High Tech Manufacturing, Low (Medium) Tech Manufacturing Firm-specific organisational capital is positively associated with firm’s productivity levels. This correlation is very high, even when controlling for workforce qualifications (and innovation). Identification issues – Identifying causal relationships requires better data

Further Research A narrower definition of organisational capital, focusing exclusively on management (excluding brand and HRM elements). Inclusion of more recent data (recession period). Explore further complementarities between organisational capital and innovation performance in the production function.