Methodology for Assessing Industrial Ecosystem Maturity in the Framework of Digital Technology Implementation

The essence of the transformation processes currently taking place in all sectors of the economy, including industry, is increasingly described by the ecosystem approach. Industrial ecosystems have proven to be the models with the highest production efficiency. The effective management of industrial ecosystems is possible only if the mechanisms underlying their dynamics are understood. Achieving a high level of maturity for industrial ecosystems in the framework of digital technology implementation is of particular relevance, and this research aims to develop and test a methodology for assessing the maturity level of such industrial ecosystems by relying on principal component analysis and hierarchical agglomerative clustering. A mature industrial ecosystem gets rapidly integrated into the new technological paradigm and global value chains, is able to compete in global markets in the long term, and has increased potential for industrialization and digital transformation. The proposed methodology is based on the environmental, social, and corporate governance (ESG) methodology for determining the levels of interests in the area of sustainable development of an industrial ecosystem. The proposed approach singles out a fourth assessment projection in addition to ESG, namely the digital maturity. All four maturity assessment projections are proven to be positively and significantly correlated. An industrial ecosystem maturity assessment scale has been developed, including six levels (very high; advanced; basic; elementary; zero; and minus one). The methodology has been tested on the national industrial ecosystem and the metallurgy and mining industrial ecosystem of Russia. The results show that the maturity level of the Russian industrial ecosystem as of mid-2021 is "basic" with the prospect of transition to "advanced." The Russian metallurgy and mining industrial ecosystem maturity level is “advanced.” The key directions for increasing the maturity levels of Russian industrial ecosystems based on innovations in various industrial aspects are proposed.

Digital maturity; Digital transformation; Ecosystem; Industrial ecosystem; Maturity assessment methodology

    Global transformations affecting all industries and activities are now becoming evident, manifesting themselves in the intensification of complex and volatile processes. This state of external and internal environments is characterized by a whole set of economic, production, social, technological, digital, ecological, and other transformations (Held and McGrew, 2000; Berawi, 2020; Rudskaya et al., 2020; Kusrini et al., 2020). The observed global transformations are largely due to the intensive implementation of digital technologies, fundamentally changing both the quality of life and the system of socioeconomic relations (Fukuda, 2020; Shkarupeta et al., 2020; Shkarupeta et al., 2021). In the near future, Russia is expected to see more active use of the "digital twin" technology and explosive growth in the metallurgy and mining industry (PwC, 2020). 

    The object of this research is an industrial ecosystem as a complex system of economic agents acting on the basis of autonomy and interconnectedness that are distinguished by their activities and features of functioning, whose goal is the creation of industrial products and/or services that are based on the principle of emergence. The research objectives are as follows: to systematize the existing research on assessing the maturity level of industrial ecosystems; to develop and test a methodology for assessing the maturity level of an industrial ecosystem; to identify the main directions of increasing the maturity level of an industrial ecosystem in the framework of the implementation of digital technologies.

    Upon identifying the problem of achieving maturity by Russian industrial ecosystems, a methodology for assessing their maturity has been developed as a continuation of the existing research in this area. The proposed methodology is distinguished by considering the implementation of digital technologies. The methodology has been tested on the Russian industrial ecosystem as well as on the Russian metallurgy and mining industrial ecosystem. The results showed that the national industrial ecosystem is at a basic level, whereas the metallurgy and mining industrial ecosystem is at an advanced level of maturity. The main directions for increasing the maturity level of industrial ecosystems have been systematized. Further research should focus on updating the maturity assessment of the industrial ecosystem for other subindustries and on developing an optimization model, including the one based on machine learning algorithms.

    The research was carried out within the framework of the project No. 20-010-00942A of the Russian Foundation for Basic Research.

Angreani, L.S., Vijaya, A., Wicaksono, H., 2020. Systematic Literature Review of Industry 4.0 Maturity Model for Manufacturing and Logistics Sectors. Procedia manufacturing, Volume 52, pp. 337–343

Babkin, A., Alekseeva, N., Makhmudova, G., Yung, A., 2020. Research and Assessment of Innovatively-Active Industrial Cluster Development. In: Proceedings of the 2^nd International Scientific Conference on Innovations in Digital Economy: SPBPU IDE-2020, pp. 1–6

Babkin, A., Tashenova, L., Eliseev, E., 2021. Digital Potential of a Systemically Important Innovation-Active Industrial Cluster: Concept, Essence, Assessment. Economics and Management. Volume 26, pp. 1324–1334

Berawi, M.A., 2020. Managing Nature 5.0: The Role of Digital Technologies in the Circular Economy. International Journal of Technology, Volume 11(4), pp. 652–655

Berger, S., Bitzer, M., Häckel, B., Voit, C., 2020. Approaching Digital Transformation-Development of a Multi-Dimensional Maturity Model. In: European Conference on Information SystemsAt: Virtual

Bertolini, M., Esposito, G., Neroni, M., Romagnoli, G., 2019. Maturity Models in Industrial Internet: A Review. Procedia Manufacturing, Volume 39, pp. 1854–1863

Burström, T., Parida, V., Lahti, T., Wincent, J., 2021. AI-Enabled Business-Model Innovation and Transformation in Industrial Ecosystems: A Framework, Model and Outline for Further Research. Journal of Business Research, Volume 127, pp. 85–95

Caiado, R.G.G., Scavarda, L.F., Gavião, L.O., Ivson, P., de Mattos Nascimento, D.L., 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, Volume 231, https://doi.org/10.1016/j.ijpe.2020.107883

Diez, L., Marangé, P., Levrat, É., 2017. Regeneration Management Tool for Industrial Ecosystem. IFAC-PapersOnLine, Volume 50(1), pp. 12950–12955

Dudareva, O.V., Dudarev, D.N., Goncharov, A.Y., 2021. Model for Assessing the Dynamics of Maturity of Industrial Ecosystems. Science of Krasnoyarsk, Volume 10(1), pp. 38–54

Fan, J., Hu, S., Chen, D., Zhou, Y., 2017. Study on the Construction and Optimization of a Resource-Based Industrial Ecosystem. Resources, Conservation and Recycling, Volume 119, pp. 97–108

Fukuda, K., 2020. Science, Technology and Innovation Ecosystem Transformation Toward Society 5.0. International Journal of Production Economics, Volume 220(C), https://doi.org/10.1016/j.ijpe.2019.07.033

Glukhov, V., Babkin, A., Alekseeva, N., 2021. Stages and Algorithm for Assessing the Intellectual Capital of an Innovative Industrial Cluster. Economics and Management, Volume 26, pp. 1217–1226

Hackos, J.T., 1997. From Theory to Practice: Using the Information Process-Maturity Model as a Tool for Strategic Planning. Technical communication, Volume 44(4), pp. 369–380

Held, D., McGrew, A., 2000. The Global Transformations Reader (Vol. 13). Cambridge: Polity Press

Human Development Report, 2020. The Next Frontier. Human development and the Anthropocene. United Nations Development Group

Industrial Development Report, 2020. Industrialization in the Digital Age. Review. 2020. UNIDO. United Nations Industrial Development Organization

Kusrini, E., Kartohardjono, S., Putra, N.S.D., Budiyanto, M.A., Wulanza, Y., Berawi, M.A., Suwartha, N., Maknun, I.J., Asvial, M., Setiawan, E.A., Suryanegara, M., Harwahyu, R., Yatmo, Y.A., Atmodiwiryo, P., 2020. Science, Engineering and Technology for Better Future. International Journal of Technology, Volume 11(7), pp. 1286–1291

Lin, T.C., Wang, K.J., Sheng, M.L., 2020. To Assess Smart Manufacturing Readiness by Maturity Model: A Case Study on Taiwan Enterprises. International Journal of Computer Integrated Manufacturing, Volume 33(1), pp. 102–115

Modrák, V., Šoltysová, Z., 2020. Development of an Organizational Maturity Model in Terms of Mass Customization. In: Industry 4.0 for SMEs (pp. 215–250). Palgrave Macmillan, Cham

Mrugalska, B., Stasiuk-Piekarska, A., 2020. Readiness and Maturity of Manufacturing Enterprises for Industry 4.0. In: International Conference on Applied Human Factors and Ergonomics (pp. 263–270). Springer, Cham

Nick, G., Kovács, T., K?, A., Kádár, B., 2021. Industry 4.0 Readiness in Manufacturing: Company Compass 2.0, a Renewed Framework and Solution for Industry 4.0 Maturity Assessment. Procedia Manufacturing, Volume 54, pp. 39–44

Parida, V., Burström, T., Visnjic, I., Wincent, J., 2019. Orchestrating Industrial Ecosystem in Circular Economy: A Two-Stage Transformation Model for Large Manufacturing Companies. Journal of Business Research, Volume 101, pp. 715–725

PwC, 2020. Digital IQ 2020. Available Online at https://www.pwc.com/us/en/tech-effect/cloud/digital-iq.html

Rafael, L.D., Jaione, G.E., Cristina, L., Ibon, S.L., 2020. An Industry 4.0 Maturity Model for Machine Tool Companies. Technological Forecasting and Social Change, Volume 159, https://doi.org/10.1016/j.techfore.2020.120203

Rodionov, D.G., Konnikov, E.A., Konnikova, O.A., 2018. Approaches to Ensuring the Sustainability of Industrial Enterprises of Different Technological Levels. The Journal of Social Sciences Research, Volume S3, pp. 277–282

Rodionov, D., Perepechko, O., Nadezhina, O., 2020. Determining Economic Security of a Business based on Valuation of Intangible Assets according to the International Valuation Standards (IVS). Risks, Volume 8(4), pp. 1–14

Rudskaya, I., Ozhgikhin, I., Kryzhko, D., 2020. Developing and Testing an Algorithm to Identify Future Innovative Research Areas in Digitalization Conditions (using a Medical-sector example). International Journal of Technology, Volume 11(6), pp. 1213–1222

RAEX, 2021. ESG Ranking of Russian Companies. 2021. Available Online at https://www.raexpert.eu/esg_corporate_ranking/, Accessed on July 17, 2021

RAEX, 2019. The methodology of ESG estimation. Rating Agentur Expert Ra Europe. Available Online at https://www.raexpert.eu/files/Methodology_ESG_Corporates_V3.pdf, accessed on July 17, 2021

SAP, Deloitte and iR&D Club, 2021. Digital Maturity of Russian Companies based on the Results of a Survey of Leading Russian Companies from Key Industries. Available Online at https://sapmybiz.ru/digital-maturity/, Accessed on July 17, 2021

Shi, X., Li, X., 2019. A Symbiosis-Based Life Cycle Management Approach for Sustainable Resource Flows of Industrial Ecosystem. Journal of Cleaner Production, Volume 226, pp. 324–335

Shkarupeta, E.V., Savon, D.Y., Safronov, A.E., Avlasenko, L.M., Kruzhkova, G.V., 2020. Digital Ecosystem Development Based on Open Innovation Model. In: Russian Conference on Digital Economy and Knowledge Management (RuDEcK 2020), pp. 601–605

Shkarupeta, E., Safronov, A., Savon, D., Borisova, D., 2021. Technological Development of Innovation Ecosystems in Conditions of Digital and Human-Centric Economy. In: 3^rd International Conference Spatial Development of Territories (SDT 2020), pp. 298–302

Sun, X., Jia, X., Rong, Y., 2018. Maturity Evaluation in China’s Low Carbon Energy Industry. Energy Procedia, Volume 152, pp. 709–714

Susur, E., Hidalgo, A., Chiaroni, D., 2019. The Emergence of Regional Industrial Ecosystem Niches: A Conceptual Framework and a Case Study. Journal of Cleaner Production, Volume 208, pp. 1642–1657

Tashenova, L., Babkin, A., Mamrayeva, D., Babkin, I., 2020. Method for Evaluating the Digital Potential of a Backbone Innovative Active Industrial Cluster. International Journal of Technology, Volume 11(8), pp. 1499–1508

Tolstykh, T., Shmeleva, N., Vertakova, Y., Plotnikov, V., 2020. The Entropy Model for Sustainability Assessment in Industrial Ecosystems. Inventions, Volume 5(4), pp. 1–16

Wagire, A.A., Joshi, R., Rathore, A.P.S., Jain, R., 2021. Development of Maturity Model for Assessing the Implementation of Industry 4.0: Learning from Theory and Practice. Production Planning & Control, Volume 32(8), pp. 603–622

Wang, D., Zheng, J., Song, X., Ma, G., Liu, Y., 2017. Assessing Industrial Ecosystem Vulnerability in the Coal Mining Area Under Economic Fluctuations. Journal of Cleaner Production, Volume 142, pp. 4019–4031

World Bank Group, 2020. World Development Report 2020: Trade as a Development Tool in the Era of Global Value Chains. Review 2020

Zoubek, M., Poor, P., Broum, T., Basl, J., Simon, M., 2021. Industry 4.0 Maturity Model Assessing Environmental Attributes of Manufacturing Company. Applied Sciences, Volume 11(11), pp. 1–24