BIG data – BIG gains? Understanding the link between big data analytics and innovation

ABSTRACT This paper analyzes the relationship between firms' use of big data analytics and their innovative performance in terms of product innovations. Since big data technologies provide new data information practices, they create novel decision-making possibilities, which are widely believed to support firms' innovation process. Applying German firm-level data within a knowledge production function framework we find suggestive evidence that big data analytics is a relevant determinant for the likelihood of a firm becoming a product innovator as well as for the market success of product innovations. These results hold for the manufacturing as well as for the service sector but are contingent on firms' investment in IT-specific skills. Overall, the results support the view that big data analytics have the potential to enable innovation.

[1]  Tobias Kretschmer,et al.  ICT and productivity: conclusions from the empirical literature , 2013, Inf. Econ. Policy.

[2]  J. Haskel,et al.  Knowledge Spillovers, ICT and Productivity Growth , 2014, SSRN Electronic Journal.

[3]  Ioanna D. Constantiou,et al.  New games, new rules: big data and the changing context of strategy , 2015, J. Inf. Technol..

[4]  K. Arrow.  Economic Welfare and the Allocation of Resources for Invention , 1962 .

[5]  M. Lessnoff.  Capitalism, Socialism and Democracy , 1979 .

[6]  Hanna Hottenrott,et al.  R&D Partnerships and Innovation Performance: Can There Be Too Much of a Good Thing? , 2014 .

[7]  P. Mohnen,et al.  Innovativity: A comparison across seven European countries , 2006 .

[8]  D. Lazer,et al.  The Parable of Google Flu: Traps in Big Data Analysis , 2014, Science.

[9]  A. Salter,et al.  Open for innovation: the role of openness in explaining innovation performance among U.K. manufacturing firms , 2006 .

[10]  Shahriar Akter,et al.  How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study , 2015 .

[11]  Zvi Griliches,et al.  Issues in Assessing the Contribution of Research and Development to Productivity Growth , 1979 .

[12]  Leslie E. Papke,et al.  Econometric Methods for Fractional Response Variables with an Application to 401(K) Plan Participation Rates , 1993 .

[13]  Elena Huergo,et al.  How Does Probability of Innovation Change with Firm Age? , 2004 .

[14]  Erik Brynjolfsson,et al.  Big data: the management revolution. , 2012, Harvard business review.

[15]  Ken Kennedy,et al.  Automotive big data: Applications, workloads and infrastructures , 2015, 2015 IEEE International Conference on Big Data (Big Data).

[16]  Reinhilde Veugelers,et al.  In Search of Complementarity in Innovation Strategy: Internal R&D and External Knowledge Acquisition , 2006, Manag. Sci..

[17]  P. Schmidt,et al.  Limited-Dependent and Qualitative Variables in Econometrics. , 1984 .

[18]  P. Mohnen,et al.  Product, Process and Organizational Innovation: Drivers, Complementarity and Productivity Effects , 2010 .

[19]  Daniel A. Levinthal,et al.  ABSORPTIVE CAPACITY: A NEW PERSPECTIVE ON LEARNING AND INNOVATION , 1990 .

[20]  H. Varian.  Computer Mediated Transactions , 2010 .

[21]  M. Anusha,et al.  Big Data-Survey , 2016 .

[22]  Stefanie A. Haller,et al.  Determinants of ICT adoption: evidence from firm-level data , 2011 .

[23]  Vincenzo Spiezia,et al.  ARE ICT USERS MORE INNOVATIVE? AN ANALYSIS OF ICT-ENABLED INNOVATION IN OECD FIRMS , 2010 .

[24]  Lorin M. Hitt,et al.  Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? , 2011, ICIS 2011.

[25]  Jacques Mairesse,et al.  Accounting for Innovation and Measuring Innovativeness: An Illustrative Framework and an Application , 2002 .

[26]  Irene Bertschek,et al.  Let the User Speak: Is Feedback on Facebook a Source of Firms' Innovation? , 2017, Information Economics and Policy.

[27]  Bronwyn H Hall,et al.  Evidence on the impact of R&D and ICT investments on innovation and productivity in Italian firms , 2013 .

[28]  Pietro Santoleri.  Diversity and intensity of information and communication technologies use and product innovation: evidence from Chilean micro-data , 2015 .

[29]  Helmut Krcmar,et al.  Big Data , 2014, Wirtschaftsinf..

[30]  Michael Marien,et al.  Book Review: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies , 2014 .

[31]  Leo Sveikauskas,et al.  The Contribution of R&D to Productivity Growth. , 1986 .

[32]  Charles Anderson,et al.  The end of theory: The data deluge makes the scientific method obsolete , 2008 .

[33]  Prasanna Tambe.  Big Data Investment, Skills, and Firm Value , 2014, Manag. Sci..

[34]  Irene Bertschek,et al.  The ZEW ICT Survey 2002 to 2015: Measuring the Digital Transformation in German Firms , 2018 .

[35]  J. Haskel,et al.  How does big data affect GDP? Theory and evidence for the UK , 2015 .

[36]  CassimanBruno,et al.  In Search of Complementarity in Innovation Strategy , 2006 .

[37]  Jeffrey M. Woodbridge.  Econometric Analysis of Cross Section and Panel Data , 2002 .

[38]  Sunil Erevelles,et al.  Big Data consumer analytics and the transformation of marketing , 2016 .

[39]  MaryAnne M. Gobble,et al.  Big Data: The Next Big Thing in Innovation , 2013 .

[40]  T. Amemiya.  Tobit models: A survey , 1984 .

[41]  Randy Holden,et al.  Data-driven innovation : big data for growth and well-being , 2015 .

[42]  F. Palm,et al.  Dynamic Models of R&D, Innovation and Productivity: Panel Data Evidence for Dutch and French Manufacturing , 2013, SSRN Electronic Journal.

[43]  Petra Andries,et al.  Small firm innovation performance and employee involvement , 2011 .

[44]  J. Tobin.  Estimation of Relationships for Limited Dependent Variables , 1958 .

[45]  John Van Reenen,et al.  Productivity and ICT: a review of the evidence , 2006 .

[46]  A. Vinding.  Absorptive Capacity and Innovative Performance: A Human Capital Approach , 2006 .

[47]  Veda C. Storey,et al.  Business Intelligence and Analytics: From Big Data to Big Impact , 2012, MIS Q..

[48]  Jeffrey Perkel,et al.  MAKING SENSE OF BIG DATA. , 2016, BioTechniques.

[49]  Thomas Hempell,et al.  NEW TECHNOLOGY, WORK ORGANISATION, AND INNOVATION , 2008 .

[50]  N. Kshetri.  Big data's impact on privacy, security and consumer welfare , 2014 .

[51]  Bettina Peters,et al.  The Influence of International Dispersed vs. Home-Based R&D on Innovation Performance , 2010 .

[52]  Almas Heshmati,et al.  On the relationship between innovation and performance: A sensitivity analysis , 2006 .

[53]  Thomas Niebel,et al.  Are Intangibles More Productive in ICT-Intensive Industries? Evidence from EU Countries , 2014 .

[54]  John Van Reenen,et al.  Americans Do I.T. Better: US Multinationals and the Productivity Miracle , 2007 .

[55]  Benjamin Engelstätter,et al.  It is not all about performance gains – enterprise software and innovations , 2012 .

[56]  Zvi Griliches,et al.  Patents and R&D at the firm level: A first report , 1980 .

[57]  Daniel A. Levinthal,et al.  Innovation and Learning: The Two Faces of R&D , 1989 .

[58]  J. Manyika.  Big data: The next frontier for innovation, competition, and productivity , 2011 .

[59]  Lorin M. Hitt,et al.  How Do Data Skills Affect Firm Productivity: Evidence from Process-driven vs. Innovation-driven Practices , 2016, ICIS.

[60]  Cristiano Antonelli,et al.  Digital knowledge generation and the appropriability trade-off☆ , 2017 .

[61]  E. Brynjolfsson,et al.  The Rapid Adoption of Data-Driven Decision-Making , 2016 .

[62]  Erik Brynjolfsson,et al.  Data in Action: Data-Driven Decision Making in U.S. Manufacturing , 2016 .