IMPLEMENTING NEW SUPPLY CHAIN MANAGEMENT PRACTICES TO IMPROVE INDUSTRIAL PRODUCTIVITY AMID THE COVID-19 PANDEMIC


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Shametova A., Tazhibekova K., Biryukov V., Mazanova O.

Business: Theory and Practice, vol.24, no.2, pp.349-359, 2023 (Scopus) identifier

  • Nəşrin Növü: Article / Article
  • Cild: 24 Say: 2
  • Nəşr tarixi: 2023
  • Doi nömrəsi: 10.3846/btp.2023.16827
  • jurnalın adı: Business: Theory and Practice
  • Jurnalın baxıldığı indekslər: Scopus, ABI/INFORM, Business Source Elite, Business Source Premier, Central & Eastern European Academic Source (CEEAS), ICONDA Bibliographic, Directory of Open Access Journals
  • Səhifə sayı: pp.349-359
  • Açar sözlər: COVID-19 pandemic, environmental friendliness, optimization, supply chain management, supply chain reliability, supply chain resilience
  • Adres: Bəli

Qısa məlumat

This study aimed to develop a methodological approach to assessing the major directions for introducing new supply chain management (SCM) methods to improve the industrial enterprises’ productivity during the COVID-19 pandemic and test the developed approach at enterprises in the real economy related to Russia, Kazakhstan, and Azerbaijan. To this end, a comprehensive research project needed to be implemented to assess the main prospects for implementing new SCM practices. The objective was to boost the productivity of the enterprises in the context of the pandemic and identify the main problems hindering the sustainable development of such chains. The testing identified the principal characteristics of supply chains amidst the pandemic, namely reliability (30 experts spoke in favor), resilience (22), and economy (19). At the same time, a sharp decrease was observed concerning the interest in the enterprises’ supply chains optimization (7 experts), flexibility (6), efficiency (2), and environmental friendliness (4). The most promising technologies for the development of supply chains, according to the results of the study, should be considered the Internet of things (µ = 3.8), additive manufacturing (3D printing) (µ = 3.77), big data analytics (µ = 3.73), and blockchain and virtual reality (µ = 3.6 each).