Industrial process innovation maturity assessment
DOI:
https://doi.org/10.12712/rpca.v19i1.63712Abstract
This article presents a model for assessing maturity in process innovation in small and medium-sized industrial companies is presented. To this end, it includes defining key criteria and indicators such as organizational culture, process management, skills and strategies, tools and technologies, governance, and customers and markets. The tool also incorporates multi-criteria decision-making method (ELECTRE TRI) pessimistic and optimistic categorization procedures to offer a more robust and comprehensive analysis, which showed an accurate classification of alternatives into different innovation categories, facilitating strategic action. prioritization.
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Almeida, A. T., Cavalcante, C. A. V., Alencar, M. H., Ferreira, R. J. P., & Ferreira, L. (2015). Multicriteria and multiobjective models for risk, reliability and maintenance decision analysis. Springer International Publishing.
Ahmed, P., & Shepherd, C. D. (2010). Innovation management: Context, strategies, systems and processes. Pearson.
Akdil, K.Y., Ustundag, A., Cevikcan, E. (2018). Maturity and Readiness Model for Industry 4.0 Strategy. In: Industry 4.0: Managing The Digital Transformation. Springer Series in Advanced Manufacturing. Springer, Cham.
Asdecker, B., & Felch, V. (2018). Development of an Industry 4.0 maturity model for the delivery process in supply chains. Journal of Modelling in Management, 13(4), 840–883 .
Caiado, R. G. G., Scavarda, L. F., Gavião, L. O., Ivson, P., Nascimento, D. L. de M., & Garza-Reyes, J. A. (2021). A fuzzy rule-based Industry 4.0 maturity model for operations and supply chain management. International Journal of Production Economics, 231, 107883.
De Carolis, A., Macchi, M., Kulvatunyou, B., Brundage, M. P., & Terzi, S. (2017). Maturity models and tools for enabling smart manufacturing systems: Comparison and reflections for future developments. In J. Ríos, A. Bernard, A. Bouras, & S. Foufou (Eds.), Product lifecycle management and the industry of the future (Vol. 517, pp. 273–284). Springer.
Certa, A., Enea, M., Galante, G., & Mauri, M. (2017). ELECTRE TRI-based approach to the failure modes classification on the basis of risk parameters: An alternative to the risk priority number. Computers & Industrial Engineering, 108, 100-110.
Dalenogare, L. S., Benitez, G. B., Ayala, N. F., & Frank, A. G. (2018). The expected contribution of Industry 4.0 technologies for industrial performance. International Journal of Production Economics, 204, 383–394.
De Giovanni, P. (2019). Digital Supply Chain through Dynamic Inventory and Smart Contracts. Mathematics, 7(12), 1235.
Denardin, É. S., Murini, L. T., Duarte, T. L., Medeiros, F. S. B., Dill, L. M. S., & Denardin, E. F. (2012). Os tipos de inovações implementadas nos empreendimentos de economia solidária do projeto Esperança/Cooesperança de Santa Maria-RS. Revista de Administração da Universidade Federal de Santa Maria, 5, 651–666.
Dias, L. C., & Mousseau, V. (2006). Inferring Electre’s veto-related parameters from outranking examples. European Journal of Operational Research, 170(1), 172–191.
Dyer, J. S., Fishburn, P. C., Steuer, R. E., Wallenius, J., & Zionts, S. (1992). Multiple Criteria Decision Making, Multiattribute Utility Theory: The Next Ten Years. Management Science, 38(5), 645–654.
Greco, S., Ehrgott, M., & Figueira, J. R. (Eds.). (2016). Multiple criteria decision analysis: State of the art surveys (International Series in Operations Research & Management Science). Springer New York, NY.
Figueira, J., & Roy, B. (2002). Determining the weights of criteria in the ELECTRE type methods with a revised Simos' procedure. European Journal of Operational Research, 139(2), 317–326.
Fontana, M. E., & Nepomuceno, V. S. (2017). Multi-criteria approach for products classification and their storage location assignment. International Journal of Advanced Manufacturing Technology, 88, 3205–3216.
Frank, A. G., Dalenogare, L. S., & Ayala, N. F. (2019). Industry 4.0 technologies: Implementation patterns in manufacturing companies. International Journal of Production Economics, 210, 15–26.
Fraser, P., Moultrie, J., & Gregory, M. (2002). The use of maturity models/grids as a tool in assessing product development capability. In IEEE International Engineering Management Conference (Vol. 1, pp. 244–249). IEEE.
Galo, N. R. (2018). Proposta de método de decisão para avaliação de fornecedores baseado no ELECTRE TRI para categorização e na teoria dos conjuntos fuzzy para a modelagem da incerteza e hesitação de múltiplos tomadores de decisão (Tese de doutorado). Universidade de São Paulo, São Paulo.
Ganzarain, J., & Errasti, N. (2016). Método de maturidade em três estágios em PMEs rumo à indústria 4.0. Revista de Engenharia e Gestão Industrial (JIEM), 9.
Gonçalves, A. T. P., Araújo, M. V. P. de, Mól, A. L. R., & Rocha, F. A. F. da. (2021). Application of the ELECTRE TRI method for supplier classification in supply chains. Pesquisa Operacional, 41, e229708.
Gökalp, E., Şener, U., & Eren, P. E. (2017). Development of an assessment model for Industry 4.0: Industry 4.0-MM. In A. Mas, A. Mesquida, R. O'Connor, T. Rout, & A. Dorling (Eds.), Software process improvement and capability determination: SPICE 2017 (Vol. 770, pp. 103–111). Springer.
Korhonen, P., Moskowitz, H., & Wallenius, J. (1992). Multiple criteria decision support – A review. European Journal of Operational Research, 63(3), 361–375.
LICHTBLAU, K. et al. IMPULS, Industry 4.0 readiness. Impuls-Stiftung des VDMA, Aachen-Kölb, 2015.
McNally, R. C., & Schmidt, J. B. (2011). From the special issue editors: An introduction to the special issue on decision making in new product development and innovation. Journal of Product Innovation Management, 28, 619–622.
Melendez, K. A., Dávila, A., & Melgar, A. (2019). Literature Review of the Measurement in the Innovation Management. Journal of Technology Management & Innovation, 14(2), 81–87.
Mittal, S., Khan, M. A., Romero, D., & Wuest, T. (2018). A critical review of smart manufacturing & Industry 4.0 maturity models: Implications for small and medium-sized enterprises (SMEs). Journal of Manufacturing Systems, 49, 194–214.
Moreira, M. J. B. M. (2010). Contribuições aos métodos de maturidade em gestão por processos e de excelência na gestão utilizando o PEMM e o MEG (Dissertação de Mestrado). Programa de Pós-graduação em Sistemas de Gestão, Universidade Federal Fluminense.
Mousseau, V., Figueira, J., & Naux, J.-P. (2001). Using assignment examples to infer weights for ELECTRE TRI method: Some experimental results. European Journal of Operational Research, 130(2), 263–275.
Mousseau, V., Slowinski, R., & Zielniewicz, P. (2000). A user-oriented implementation of the ELECTRE-TRI method integrating preference elicitation support. Computers & Operations Research, 27(7–8), 757–777.
Naeini, A. B., Zamani, M., Daim, T. U., Sharma, M., & Yalcin, H. (2022). Conceptual structure and perspectives on “innovation management”: A bibliometric review. Technological Forecasting and Social Change, 185, 122052.
Niewöhner, N., Asmar, L., Röltgen, D., Kühn, A., & Dumitrescu, R. (2020). The impact of the 4th industrial revolution on the design fields of innovation management. Procedia CIRP, 91, 43–48
OCDE. (1997). OECD proposed guideline for collecting and interpreting technological innovation data (3rd ed.). Paris: OECD.
Pessl, E., Sorko, S. R., & Mayer, B. (2017). Roadmap Industry 4.0 – Implementation guideline for enterprises. International Journal of Science, Technology and Society, 5(6), 193-202.
Pietronudo, M. C., Croidieu, G., & Schiavone, F. (2022). A solution looking for problems? A systematic literature review of the rationalizing influence of artificial intelligence on decision-making in innovation management. Technological Forecasting and Social Change, 182, 121828.
Röglinger, M., Pöppelbuß, J., & Becker, J. (2012). Maturity models in business process management. Business Process Management Journal, 18(2), 328–346.
Roy, B. (1990). Decision-aid and decision-making. European Journal of Operational Research, 45(2–3), 324–331
Roy, B., & Słowiński, R. (2013). Questions guiding the choice of a multicriteria decision aiding method. EURO Journal on Decision Processes, 1(1–2), 69–97.
Saaty, T. L. (2000). Fundamentals of decision making and priority theory (Analytic Hierarchy Process Series, Vol. 6). RWS Publications.
Santos Bento, G. dos, & Tontini, G. (2018). Developing an instrument to measure lean manufacturing maturity and its relationship with operational performance. Total Quality Management & Business Excellence, 29(9–10), 977–995.
Santos, M. A. P. C. (2009). Maturidade de processos organizacionais: Um estudo em uma indústria multinacional do setor de soldagem (Dissertação de Mestrado). Universidade Fumec.
Tangpong, C. (2011). Content analytic approach to measuring constructs in operations and supply chain management. Journal of Operations Management, 29(6), 627–638.
Tidd, J., & Bessant, J. R. (2020). Managing innovation: Integrating technological, market and organizational change. John Wiley & Sons.
Zhang, H. (2022). Does combining different types of innovation always improve SME performance? An analysis of innovation complementarity. Journal of Innovation & Knowledge, 7(3), 100192.
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