Vol. 29 (2019)
Artículos de investigación

How the Big Data is influencing the Open Innovation. First insights into the IT Sector of Mexico

HTML (Spanish) PDF (Spanish) XML (Spanish)
  • Juan Mejia Trejo
Juan Mejia Trejo Centro Universitario de Ciencias Económico Administrativas (CUCEA) de la Universidad de Guadalajara (UdG)

Bio

Published 2019-04-08

Copyright Notice

How to Cite

How the Big Data is influencing the Open Innovation. First insights into the IT Sector of Mexico. (2019). Acta Universitaria, 29, 1-25. https://doi.org/10.15174/au.2019.1865

Abstract

The purpose is aimed to disclose how the Big Data (BGD) is affecting the practice of Open Innovation (OIN) in the Information Technologies Sector of the Metropolitan Zone of Guadalajara, México (ITSMZG) to achieve an empirical model for the improvement of this sector. The Design was based on literature reviewed to propose conceptual constructs through the factors BGD and OIN. The methodology is descriptive, exploratory, correlational, and cross sectional. The Delphi Panel and Analytic Hierarchy Process (AHP) were used to get the main factors, the variables, and the final questionnaire of the model, applied to 500 ITSMZG specialists, were used. The results were analyzed using a multiple linear regression and a confirmatory factor analysis, applying the structural equation modeling by the EQS 6.2 software. A final model, a questionnaire, and the relationships between factors such as the OIN and the Knowledge Management (KMG), as well as the Open Business Model (OBM) and Innovation Ecosystem (IEC) related with BGD, were obtained.

HTML (Spanish) PDF (Spanish) XML (Spanish)

References

  1. Allarakhia, M. Kilgour, D. M. Fuller, J. D .(2010), “Modelling the incentive to participate in open source biopharmaceutical innovationâ€. R&D Management. Jan, Vol. 40 No.1, pp. 50-66.
  2. Asakawa, K. Nakamura, H. Sawada, N.(2010), “ Firms' open innovation policies, laboratories' external collaborations, and laboratories' R&D performanceâ€. R&D Management. Mar, Vol. 40 No.2, pp.109-123.
  3. Beckman, C. Haunschild, P. Philips, D. (2004). “Friends or Strangers? Firm-Specific Uncertainity, Market Uncertainity and Network Partner Selectionâ€. Organisation Science, Vol.15 No. 1, pp. 259-275.
  4. Cavanillas, J.M., Curry, E., Wahlster,W. (2015) New Horizons for a Data-Driven Economy A Roadmap for Usage and Exploitation of Big Data in Europe. Chapter 1: The Big Data Value Oportunity: 3-11. Madrid, España: Springer Open.
  5. Cohen, W. M. Nagata, A. Nelson, R.R. Wlash, J.P. (2002). “R&D Spillovers, Patents and the Incentives to Innovate in Japanand the USAâ€. Research Policiy, Vol. 31, pp: 1349-1367
  6. Curley, M. & Salmelin, B. (2012) Open Innovation 2.O:A New Paradigm. Retrieved from:https://www.google.com.mx/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF-8#q=open+innovation+2.0+pdf&* (accessed 14-Dec-2016).
  7. Curry, E. (2014) The Big Data Value Chain: Definitions, Concepts, and Theoretical Approaches,in Cavanillas, J.M., Curry, E., Wahlster,W. (2015) New Horizons for a Data-Driven Economy A Roadmap for Usage and Exploitation of Big Data in Europe. Chapter 3: 29-37. Madrid, España: Springer Open.
  8. Chatenier, E. Verstegen, J. Biemans, H. Mulder, M. and Omta, O. (2010) “ Identification of competencies for professionals in open innovation teamsâ€, R&D Management. Jun, Vol. 40 No.3, pp: 271-280.
  9. Chesbrough, H. (2003). Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business School Press. Boston, MA.Chesbrough , H.and Teece, D.J. (2002). “Organizing for innovation: When is Virtual Virtous?â€. Harvard Business review. pp 5-12.
  10. Chesbrough, H. and Kardon –Crowter, A. (2006). Beyond high tech: early adopters of open innovation in other industries. R&D Management. 36(3). 229-236.
  11. Chesbrough, H.W. (2006). Open Business Models: How to Thrive in the New Innovation Landscape. Boston, MA: Harvard Business School Press.
  12. Chesbrough, H.W. (2007). Why Companies should have Open Business Models. MIT Sloan Management Review, 48 (2)
  13. Chesbrough, H. Bogers, M. (2014), “Explicating open innovation: Clarifying an emerging paradigm for understanding innovation†in H.
  14. Chesbrough, W. Vanhaverbeke, & J. West (Eds.), New Frontiers in
  15. Open Innovation: pp.3-28. Oxford University Press.Oxford
  16. Chien-Tzu, T. Wan-Fen, L. (2014). “A Framework for Open Innovation Assessmentâ€. International Journal of Innovation Management. Oct., Vol. 18 No.5,pp: 100-128
  17. Deloitte. (2015). Executing an Open Innovation Model: Cooperation is a Key toCompetition for Biopharmaceutical Companies. Deloitte Development LLC.USA.
  18. Docherty, M. (2006), “ Primer on Open Innovation: Principles and Practiceâ€. PDMA Visions, Vol. 30 No.2. pp: 13-17.
  19. Economista (2014.Feb.18). Jalisco quiere dar valor agregado a su clúster tecnológico. Retrieved from: http://eleconomista.com.mx/estados/2014/02/18/jalisco-quiere-dar-valor-agregado-su-cluster-tecnolAogico (accessed 10-May-2016 )
  20. Enkel, E., Gassman, O. Chesbrough, H. W. (2009). “Open R&D and open innovation: Exploring the phenomenonâ€. R&D Management. Vol. 39 No 4. pp: 311-316.
  21. EIRMA.(2003). Innovation through Spinning In and Out. WG60 Report.
  22. Paris Etzkowitz, H. Leydesdorff, L. (1995). “The Triple Helix: University-Industry-Government
  23. Relations: A Laboratory for Knowledge-Based Economic Developmentâ€, EASST Review. Vol. 14. pp: 14-19.
  24. Ezell, S. & Atkinson, R. (2010). “The Good, the Bad, and the Ugly (and the Self-Destructive) of Innovation Policy: A Policymakers Guide to Crafting Effective Innovation Policyâ€. ITIF, October
  25. Gassman, O. & Enkel, E. (2004). Towards a Theory of Open Innovation: Three Core Process
  26. Archetypes. 2-18. Avalaible at :
  27. https://www.alexandria.unisg.ch/274/1/Gassmann_Enkel.pdf (accessed 12 July,2016)
  28. Gassman , O. (2006). “Opening up the Innovation Process: Towards and Agendaâ€, R&D
  29. Management. Vol. 36 No. 3, pp: 223-228.
  30. Gassmann, O. Enkel, E.Chesbrough, H. (2010). “The Future of Open Innovationâ€, R&D
  31. Management, Jun, Vol. 40 No. 3.pp: 213-221.
  32. Goglio-Primard, K. Crespin –Mazet, F. (2014). “Organizing Open Innovation in Networks –
  33. the role of boundary relationsâ€, Management international, Vo1. 9, pp: 135-147.
  34. Holmes, S. Smart, P. (2009), “Exploring open innovation practice in firm-nonprofit
  35. engagements: a corporate social responsibility perspectiveâ€, R&D Management, Vol. 39 No.4.pp: 394-409
  36. Hopkins, M. Tidd, Joe; Nightingale, P. Miller, R.(2011), “Generative and degenerative
  37. interactions: positive and negative dynamics of open, user-centric innovation in
  38. technology and engineering consultanciesâ€, R&D Management, Jan., Vol.41 No.1, pp: 44-60.
  39. Jackson, D.J. (2010). What is an Innovation Ecosystem? Retrieved from:http://erc-assoc.org/sites/default/files/topics/policy_studies/DJackson_Innovation%20Ecosystem_03-15-11.pdf (accessed 10-December-2016)
  40. Keup, M.M; Gassmann, O.(2009), “Determinants and archetype users of open innovationâ€, R&D Management, Sep, Vol. 39 No.4, pp: 331-341.
  41. Lichtenthaler, U. (2015), “A note on outbound open innovation and firm performanceâ€,R&DManagement, Nov, Vol. 45 No. 5, pp: 606-608.
  42. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C.,
  43. & Byers, A. H. (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute, p. 156.
  44. Mejía-Trejo, J. Sanchez-Gutierrez, J. Ortiz-Barrera, A. (2013), “Leadership and Value Creation on Innovation: The Case of Software Developer Sector in Guadalajara Méxicoâ€, Competition Forum. Vol. 11 No. 1.pp: 24-31.
  45. Miller, K.; Puthusserry, P.; McAdam, R.; Moffett, S.; Alexander, A. (2016), “Knowledge
  46. transfer in university quadruple helix ecosystems: an absorptive capacity perspectiveâ€, R&D Management,Mar. Vol. 46 No.2, pp: 383-399.
  47. Nelson, R.R.(1993), National Innovation Systems: A Comparative Analysis, OxfordUniversity Press., Oxford.
  48. OECD. (2003) Knowledge Management. Measuring Knowledge Management in the Business Sector. First Steps, Organisation for Economic Co-operation and Development Publishing, Canada.
  49. OECD. (2008). Open Innovation in Global Networks. Organisation for Economic Co-operation and Development Publishing.France.
  50. OECD. (2011). Quality Framework and Guidelines for OECD Statistical Activities. Organisation for Economic Co-operation and Development Publishing.France.
  51. Osterwalder, A. Pigneur, T (2010), Business Model Generation, John Wiley & Sons,Inc., Hoboken, New Jersey
  52. Parmented, D. (2010), Key Performance Indicators. Developing, Implementing and Using Winning KPIs.2ed., John Wiley & Sons, New Jersey.
  53. Rayna, T.and Striukova,L. (2014). “Open Innovation 2.0: Is co-creation the ultimate challenge?â€, International Journal of Technology Management, Vol. 69 No.1, pp:100-118
  54. Remneland-Wikhamn, B and Knights, D. (2012), “Transaction Cost Economics and Open Innovation: Implications for Theory and Practiceâ€, Creativity and Innovation Management, Vol. 21 No.3, pp: 277-289
  55. Rohrbeck, R., Hölzle, K., Gemünden, H. G. (2009), “Opening up for competitive advantage: How Deutsche Telekom creates an open innovation ecosystemâ€, R&D Management, Vol. 39 No.4, pp: 420-430.
  56. Saebi, T. Foss, N.J. (2013), “Business models for open innovation: Matching Heterogenous Open Innovation Strategies with Business Model Dimensionsâ€, European Management Journal, Vol. 33 No.3.pp: 201-213.
  57. Schwaag , S. (2006), “China , from Shop Floor to Knowledge Factoryâ€, Swedish Institute for Growth Policy Studies, pp: 227-266.
  58. Sieg, J.H. Wallin, M. W. Von Krogh, G. (2010), “Managerial challenges in open innovation: a study of innovation intermediation in the chemical industryâ€, R&D Management. Jun, Vol. 40 No.3, pp: 281-291.
  59. Tableau (2017). Top Ten Big Data Trends For 2017. Retrieved form
  60. https://www.tableau.com/es-es/resource/top-10-big-data-trends-2017
  61. (Accessed 1-Jnauary.2017)
  62. Tidd, J. (2006). A Review of Innovation Models. Discussion Paper 1. Tanaka Business School, Imperial College, London.
  63. Turton, A.R., Hatting, J., Claassen, M., Roux, D.J., Ashton, J.P. (2007). “Towards a Model for Ecosystem Governance: An Integrated Water Resource Management Example†Water Resources Development and Management Series. Springer-Verlag Berlin Heidelberg.
  64. Van der Borgh, M., Cloodt, M., and Romme, A. G. L. (2012), “Value creation by knowledge-based ecosystems: Evidence from a field studyâ€, R&D Management. Vol. 42 No. 2, pp: 150-169.
  65. Vanhaverbeke, W. & Chesbrough, H.W. 2014. “A Classification of Open Innovation and Open Business Models â€. Retrieved from:
  66. https://www.researchgate.net/publication/266737917_A_Classification_of_Open_Innovation_and_Open_Business_Models (accessed 15-Dec-2016)
  67. Von Hippel, E. (2005). “Democritizing Innovation: The evolving phenomenon of user Innovation. Journal für Betriebswirtschaftâ€. March. 55(19). 63–78. Springer.
  68. West,J. & Bogers, M. (2014). “Leveraging External Sources of Innovation: A Review of Research on Open Innovationâ€, Journal of Product Innovation Management Vol. 31 No.4.pp: 814–831.
  69. Yun-Hwa Ch. Kuang-Peng H.(2010), “Exploring open search strategies and perceived innovation performance from the perspective of inter-organizational knowledge flowsâ€, R&D Management, Jun, Vol. 40 No.3.pp: 292-299.
  70. West, J.& Wood, D. (2008).“Creating and Evolving an Open Innovation Ecosystem: Lessons from Symbian Ltd.â€User and Open Innovation Workshop.
  71. EQS 6 Software References
  72. Anderson , J.C.& Gerbing, D.,W. 1988.Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin. 1 (3): 411-423.
  73. Bagozzi, R.P. &YI, Y.1988. On the evaluation of structural equation models. Journal of the Academy of Marketing Science. 16(1): 74-94.
  74. Byrne, B. M. 2006. Structural Equation Modeling With EQS, basic concepts,applications, and programming. London: LEA Publishers.
  75. Chou, C.P., Bentler, P.M. & Satorra, A. 1991. Scaled test statistics and robust standard errors for nonnormal data in covariance structure analysis. British Journal of Mathematical and Statistical Psychology. 44: 347-357.
  76. Fornell, CL. & Larcker, D. 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. 18 (2): 39-50.
  77. Hair,J.F. Anderson, R.E. Tatham, R.L.& Black, W.C. 2014. Multivariate Data Analysis. 7th USA: Ed. Pearson, Prentice Hall.
  78. Hatcher, L. A. (1994).Step by Step Approach to Using the SAS System for FactorAnalysis and Structural Equation Modeling. USA, Cary, NC: SAS Institute Inc.
  79. Hu, L.T., Bentler, P.M. & Kano, Y. 1992. Can test statistics in covariance structure analysis be trusted?. Psychological Bulletin. 112: 351-362.
  80. Nunnally, J.C. & Bernstein I.H. 1994. Psychometric Theory. NY: McGraw Hill
  81. Satorra, A. & Bentler, P.M. 1988. Scaling corrections for chi square statistics in covariance structure analysis, American Statistics Association 1988 Proceedings of the Business and Economic Sections:208-313.
  82. Segars, A.H. & Grover, V. 1993.Re-examining perceived ease of use and usefulness: a confirmatory factor analysis. MIS Quarterly. 17(4): 517-525.