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Key Barriers of Digital Transformation of the High-Technology Manufacturing: An Evaluation Method

Author

Listed:
  • Alexey Borovkov

    (The World-Class Research Center “Advanced Digital Technologies”, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia)

  • Oleg Rozhdestvenskiy

    (The World-Class Research Center “Advanced Digital Technologies”, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia)

  • Elizaveta Pavlova

    (The World-Class Research Center “Advanced Digital Technologies”, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia)

  • Alexey Glazunov

    (Research and Production Association “Centrotech”, 624130 Novouralsk, Russia)

  • Konstantin Savichev

    (Joint Stock Company “Power Machines–ZTL, LMZ, Electrosila, Energomachexport” (JSC “Power Machines”), 195009 Saint Petersburg, Russia)

Abstract

It is acknowledged that quality of life is related to economic development in a country or region. The impact of the ongoing transfer to the digital economy on economic growth, sustainable development, and quality of life has been a recent academic focus, finding that the development of digitalisation of the economy and society is happening at a comparable pace. Yet, despite the availability of governmental support and overall strategic orientation of top managers, there is evidence of low digital/advanced manufacturing technologies adoption readiness across economic sectors. Therefore, the object of the research is the digital/advanced manufacturing technologies adoption readiness, which can be assessed on both industrial and organisational levels. The authors carried out an expert poll that has shown low digital/advanced manufacturing technologies adoption readiness on the industrial level (average readiness of 2.18 across estimated industries). For this reason, the focus subject of the research is the evaluation method for determining barriers of digital transformation on organisational level. The review of the academic literature and available digital maturity assessment models has shown the lack of metrics for barrier evaluation. The objective of the research is to develop a method for digital-transformation barrier evaluation. An analytical research method is used to develop a ready-to-use method in a form of a questionnaire that can be applied to measure an overall digital-transformation barrier level and identify problem areas for a manufacturing enterprise. The developed method is approbated in two large industrial companies. The overall barrier equals 39.3% for a power engineering company, which is a deterrent barrier. The overall barrier equals 75.0% for a machine-building company, which is a limiting barrier. The results of approbation correspond with results of the expert poll: the power engineering company has a lower barrier level, which is in line with the engine building and turbine engineering industry showing higher levels of readiness to adopt digital technologies. This finding supports the hypothesis about the rationality of the author’s method.

Suggested Citation

  • Alexey Borovkov & Oleg Rozhdestvenskiy & Elizaveta Pavlova & Alexey Glazunov & Konstantin Savichev, 2021. "Key Barriers of Digital Transformation of the High-Technology Manufacturing: An Evaluation Method," Sustainability, MDPI, vol. 13(20), pages 1-13, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11153-:d:652751
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    References listed on IDEAS

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    1. Titov Sergei & Trachuk Arkady & Linder Natalya & RD Pathak & Danny Samson & Zafar Husain & S Sushil, 2023. "Digital transformation enablers in high-tech and low-tech companies: A comparative analysis," Australian Journal of Management, Australian School of Business, vol. 48(4), pages 801-843, November.
    2. Rafael Martínez-Peláez & Marco A. Escobar & Vanessa G. Félix & Rodolfo Ostos & Jorge Parra-Michel & Vicente García & Alberto Ochoa-Brust & Pablo Velarde-Alvarado & Ramón A. Félix & Sandra Olivares-Bau, 2024. "Sustainable Digital Transformation for SMEs: A Comprehensive Framework for Informed Decision-Making," Sustainability, MDPI, vol. 16(11), pages 1-25, May.

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