Abstract
One of the most important challenges faced by governments is to develop tangible public plans in coproduction with society. This is even a more complex task in Science, Technology and Innovation (ST&I) public plans, due to the intangibility and the lack of value perception by society. In this chapter, we present the development and the application of a framework to coproduction of ST&I public plans. The methodology initiates with participants from all innovation sectors. First, they discuss and decide about the status of their regional ST&I system (regarding institutionalization, regional development, market, infrastructure, education, science, technology and innovation). Then, the groups elaborate proposals to foster their regional ST&I systems in terms of Intellectual Capital (human, structural, relational and social capital), governance and dynamic inducers. In the last phase, academic, governmental, industrial and social organizational institutional representatives analyze these demands and offer goals and actions, later organized as a ST&I strategic map. We have applied the framework in Santa Catarina state (Brazil). More than 1000 ST&I players from six regions developed 450 proposals analyzed by 27 academic, governmental, industrial and social organizational institutional representatives. The result was a state strategic map with 34 goals and 65 actions to foster ST&I regional system.
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Notes
- 1.
- 2.
Since there are 8 dimensions and 36 factors to be evaluated, each group should work at 2 (two) dimensions at most. The distribution can repeat some dimensions so more than one group (preferentially the Value-Generating Factors) will evaluate them.
- 3.
All information and documents relevant to the survey should be taken into account (Bardin, 2009).
- 4.
It allows to admit a sample process of the content, as long as it is pertinent to the whole (Bardin, 2009).
- 5.
Although the documents generated for the collection may have specific research criteria, it is important that they present similar collection criteria to avoid distinct processes of analysis (Bardin, 2009).
- 6.
The documents should point to criteria that corroborate the purpose of the analysis (Bardin, 2009).
References
Allison, R. I., & Uhl, K. P. (1964). Influence of beer brand identification on taste perception. Journal of Marketing Research, 1, 36–39.
Anderson, P. (1999). Perspective: Complexity theory and organization science. Organization Science, 10(3), 216–232.
Bardin, L. (2009). Análise de conteúdo (Edição revista e actualizada) (p. 70). Lisboa: Edições.
Bauer, M. W., & Gaskell, G. (Eds.). (2000). Qualitative researching with text, image and sound: A practical handbook for social research. London: Sage.
Bontis, N. (1998). Intellectual capital: An exploratory study that develops measures and models. Management Decision, 36(2), 63–76.
Brudney, J. L. (1984). Local coproduction of services and the analysis of municipal productivity. Urban Affairs Quarterly, 19(4), 465–484.
Bueno, E., Arrien, M., & Rodríguez, O. (2003). Modelo Intellectus: Medición y gestión del capital intelectual. Documentos Intellectus, 5, 1–175.
Csillag, J. M. (1995). Análise do valor: Metodologia do valor: Engenharia do valor, gerenciamento do valor, redução de custos, racionalização administrativa. São Paulo: Atlas.
De Koeijer, T. J., Wossink, G. A. A., Van Ittersum, M. K., Struik, P. C., & Renkema, J. A. (1999). A conceptual model for analysing input–output coefficients in arable farming systems: From diagnosis towards design. Agricultural Systems, 61(1), 33–44.
Ecker, D. W., & Baker, T. L. (1984). Multiple perception analysis: A convergence model for evaluating arts education. Studies in Art Education, 25(4), 245–250.
Edvinsson, L. (1998). Managing intellectual capital at Skandia. In Profiting from intellectual capital: Extracting value from innovation (p. 279). New York: Wiley.
Ferenhof, H. A., Durst, S., Bialecki, M. Z., & Selig, P. M. (2015). Intellectual capital dimensions: State of the art in 2014. Journal of Intellectual Capital, 16(1), 58–100.
Frodeman, R. (2013). Sustainable knowledge: A theory of interdisciplinarity. New York: Springer.
Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M., Simoes, A., & Yildirim, M. A. (2014). The atlas of economic complexity: Mapping paths to prosperity. Cambridge: MIT Press.
Helliwell, J. F., & Putnam, R. D. (1995). Economic growth and social capital in Italy. Eastern Economic Journal, 21(3), 295–307.
Hollanders, H., Es-Sadki, N., & Kanerva, M. (2016). European innovation scoreboard 2016. European Commission.
Hollies, N. R., Custer, A. G., Morin, C. J., & Howard, M. E. (1979). A human perception analysis approach to clothing comfort. Textile Research Journal, 49(10), 557–564.
Innes, J. E., & Booher, D. E. (2000). Indicators for sustainable communities: A strategy building on complexity theory and distributed intelligence. Planning Theory & Practice, 1(2), 173–186.
Instituto Brasileiro de Geografia e Estatística. (2015). Estimativas da população residente no Brasil e unidades da federação com data de referência em 1° de julho de 2015.
Kable, J. C. (1983). Decision perception analysis—Measuring a manager’s preference for managing. Journal of Management Development, 2(3), 3–18.
Lange, W., Pirzer, C., Dünow, L., & Schelchen, A. (2016). Risk perception for participatory ecosystem-based adaptation to climate change in the Mata Atlântica of Rio de Janeiro State, Brazil. In F. G. Renaud, K. Sudmeier-Rieux, M. Estrella, & U. Nehren (Eds.), Ecosystem-based disaster risk reduction and adaptation in practice (pp. 483–506). Cham: Springer.
Levine, C. H., & Fisher, G. (1984). Citizenship and service delivery: The promise of coproduction. Public Administration Review, 44, 178–189.
Leydesdorff, L. (2000). The triple helix: An evolutionary model of innovations. Research Policy, 29(2), 243–255.
Marques, M. A. J., Alves, V. C., dos Santos Pacheco, R. C., & Orsatto, S. D. (2017). Análise de percepção de atores de Ciência, Tecnologia e Inovação em sistemas regionais e ambientes de inovação. Navus-Revista de Gestão e Tecnologia, 7(3), 86–94.
Marschall, M. J. (2004). Citizen participation and the neighborhood context: A new look at the coproduction of local public goods. Political Research Quarterly, 57(2), 231–244.
Mauser, W., Klepper, G., Rice, M., Schmalzbauer, B. S., Hackmann, H., Leemans, R., & Moore, H. (2013). Transdisciplinary global change research: The co-creation of knowledge for sustainability. Current Opinion in Environmental Sustainability, 5(3–4), 420–431.
Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Thousand Oaks, CA: Sage.
Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Knowledge and Social Capital, 23, 119–157.
OECD Publishing. (2014). OECD science, technology and industry outlook 2014. Paris: OECD Publishing.
Ostrom, E. (1996). Crossing the great divide: Coproduction, synergy, and development. World Development, 24(6), 1073–1087.
Pacheco, R. C. S., Selig, P. M., & Zucco, C. (Eds.). (2016). V Conferência Estadual de Ciência, Tecnologia e Inovação de Santa Catarina: Metodologia e resultados para o plano estadual de CTI. Instituto Stela: Florianópolis.
Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45–77.
Rowe, G., & Wright, G. (1999). The Delphi technique as a forecasting tool: Issues and analysis. International Journal of Forecasting, 15(4), 353–375.
Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83–98.
Santos, P. M. D., Schlosser, J. F., Romano, L. N., Rozin, D., Turatti, J. D. C., & Witter, M. (2008). Requirement priorities for the design of tractor workplaces related to ergonomics and safety. Pesquisa Agropecuária Brasileira, 43(7), 869–877.
Schuttenberg, H., & Guth, H. (2015). Seeking our shared wisdom: A framework for understanding knowledge coproduction and coproductive capacities. Ecology and Society, 20(1), 15.
Schwab, K., & Sala-i-Martin, X. (2016). The global competitiveness report 2015–2016, Geneva. The World Economic Forum, 403, 1–92.
Selig, P. M. (1993). Gerência e avaliação do valor agregado empresarial.
Sharp, E. B. (1980). Toward a new understanding of urban services and citizen participation: The coproduction concept. Midwest Review of Public Administration, 14(2), 105–118.
Sveiby, K. E. (1998). Intellectual capital: Thinking ahead. Australian CPA, 68, 18–23.
Takeuchi, H., & Nonaka, I. (2009). Gestão do conhecimento. Porto Alegre: Bookman Editora.
Wiig, K. M. (1997). Integrating intellectual capital and knowledge management. Long Range Planning, 30(3), 399–405.
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do Nascimento, E.R., Selig, P.M., Pacheco, R.C.d.S. (2019). Intellectual Capital as a Driver to Science, Technology and Innovation Strategies. In: Matos, F., Vairinhos, V., Selig, P.M., Edvinsson, L. (eds) Intellectual Capital Management as a Driver of Sustainability. Springer, Cham. https://doi.org/10.1007/978-3-319-79051-0_3
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