Scientific and methodological approaches to assessing the impact of innovative digital technologies and services on the transformation of petrochemical enterprises' supply chains
Abstract
This study is devoted to the analysis of scientific and methodological approaches to assessing the impact of innovative digital technologies and services on the transformation of supply chains in petrochemical enterprises. The paper reviews existing methods for evaluating the effectiveness of the practical application of innovative digital technologies and services in supply chain management, outlining their advantages and limitations, and identifies the most effective combinations of assessment methods. Based on a systematic analysis of academic literature, industry reports, and implemented projects, the study proposes an evaluation scale and an integrated assessment criterion, which are used to assess nine key digital technologies and services that exert a significant influence on the transformation of supply chain-related business processes. The key effects resulting from the implementation of each technology are identified. The findings reveal a high degree of interdependence among digital technologies and services, with the most substantial effects achieved through their comprehensive integration into enterprise business processes.
References
Doulabi H., Khamseh A., Torabi T. Evaluation of Key Factors Influencing Technological Innovation Management in the Petrochemical Industry with a Focus on Chemical Companies // Pet. Bus. Rev. - 2022. - Vol. 6, № 3. - С. 1–16.
Shcherbakov V., Silkina G. Supply Chain Management Open Innovation: Virtual Integration in the Network Logistics System // J. Open Innov. Technol. Mark. Complex. - 2021. - Vol. 7, № 1. - С. 54.
Barsegyan N. V., Salimyanova I. G., Kushaeva E. R. Typology of innovation strategies for petrochemical enterprises // J. Phys. Conf. Ser. - 2020. - Vol. 1515, № 4. - С. 042090. DOI: 10.1088/1742-6596/1515/4/042090.
Lagorio A. и др. A systematic literature review of innovative technologies adopted in logistics management // Int. J. Logist. Res. Appl. - 2022. - Vol. 25, № 7. - С. 1043–1066.
Tavasszy L. A. Predicting the effects of logistics innovations on freight systems: Directions for research // Transp. Policy. - 2020. - Vol. 86. - С. A1–A6.
Hahn G. J. Industry 4.0: a supply chain innovation perspective // Int. J. Prod. Res. - 2020. - Vol. 58, № 5. - С. 1425–1441.
Belina B. и др. Setting of criteria in the commercial potential assessment method of innovative technological solutions // Probl. Eksploat. - 2013.
Ismagilova L. A., Sukhova N. A. Assessment of quality of innovative technologies // Int. J. Qual. Res. - 2016. - Vol. 10, № 4.
Alexandrova T. V., Zhukovskaya S. L., Voevodkin N. Y. The development of a multi-criteria approach to assess innovative projects efficiency // Rev. Espac. ISSN. - 2018. - Vol. 798, № 1015. - С. 22.
Бухалкин Д. Д., Костров В. Н., Чеботарев В. С. Роль интернета вещей в цифровой трансформации логистики нефтехимических предприятий // Экономика: вчера, сегодня, завтра. - 2024. - Т. 14, № 9А. - С. 459–471.
The Logistics Trend Map [Электронный ресурс] // MAERSK. - URL: https://www.maersk.com/insights/logistics-trend-map/iot-logistics?exit=ExitIntentPopup+-+logistics+trend+map (дата обращения: 27.05.2025).
Digital twins: The key to unlocking end-to-end supply chain growth [Электронный ресурс] // McKinsey & Company. - URL: https://www.mckinsey.com/capabilities/quantumblack/our-insights/digital-twins-the-key-to-unlocking-end-to-end-supply-chain-growth#/ (дата обращения: 27.05.2025).
Kamath R. Food traceability on blockchain: Walmart’s pork and mango pilots with IBM // The Journal of the British Blockchain Association. - 2018. - Т. 1, № 1. DOI: 10.31585/jbba-1-1-(10)2018.
Boute R. N., Udenio M. AI in Logistics and Supply Chain Management // Global Logistics and Supply Chain Strategies for the 2020s. - Cham: Springer International Publishing, 2023. - С. 49–65.
Trzuskawska-Grzesińska A. Control towers in supply chain management - past and future // J. Econ. Manag. - 2017. - Vol. 27. - С. 114–133.
Шалдыбин И. И., Литовченко В. Б., Додорина И. В. Электронный документооборот в логистике // Наука и образование транспорту. - 2020. - № 1. - С. 219–222. - EDN YQRKEY.
Antov M. Possibilities for application of E-CMR from a customs point of view. - 2020. - С. 128–136.
Дергачева В., Попова А. С. Перспективы развития цифровой логистики в России: умные контейнеры и склады, дроны // Стратегии бизнеса. - 2022. - Т. 10, № 12. - С. 301–305. DOI: https://doi.org/10.17747/2311-7184-2022-12-301-305.
Aljohani A. Predictive Analytics and Machine Learning for Real-Time Supply Chain Risk Mitigation and Agility // Sustainability. - 2023. - Vol. 15, № 20. - С. 15088.
Deiva Ganesh A., Kalpana P. Supply chain risk identification: a real-time data-mining approach // Ind. Manag. Data Syst. - 2022. - Vol. 122, № 5. - С. 1333–1354.
Klingebiel K., Wagenitz A. An Introduction to Logistics as a Service. - 2013. - С. 209–216.
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