Adapting DIGCOMP 2.1 for Logistics 4.0: A Competence-Based Framework for Hungarian Companies' Digital Transformation
DOI:
https://doi.org/10.14513/sbe.00637Keywords:
digital competencies, DIGCOMP 2.1, Industry 4.0, logistics sector, triangulation methodologyAbstract
This research investigates the applicability of the European Digital Competence Framework to the digitalization processes of Hungarian logistics companies. Using a triangulation methodology, the study combines structured interviews with three major logistics service providers and a quantitative analysis of the resulting text using Python-based tools.
Our key findings demonstrate that four of the five DIGCOMP 2.1 competency areas are highly relevant and applicable to the Hungarian logistics sector, providing an 80% framework coverage. Evidence suggests a clear dominance of "Information and data management" (58.5%) and "Problem-solving" (28.0%). A critical competency gap was identified in "Digital content creation," which was entirely absent from the discourse, suggesting that the sector currently acts as a "digital consumer" rather than a "digital creator." The triangulation analysis further confirms a medium-to-weak validation strength across competencies, highlighting a heterogeneous and nascent stage of digital maturity within the sector. To address this gap, we recommend developing conscious training programs and fostering corporate collaborations to enhance digital content creation competencies. The results highlight the need for educational institutions to launch project-based, practice-oriented programs aimed at developing these critical digital skills in logistics. This study concludes that the European framework provides a scientifically sound foundation for digital competency assessment in logistics, though it requires sector-specific adaptation. Our research offers insights for strategic planning, curriculum design, and targeted policy formulation to help the sector navigate the challenges of Industry 4.0.
References
Adams, W. C. (2015). Conducting semi-structured interviews. In R. C. Bainbridge (Ed.), Handbook of practical program evaluation (4th ed., pp. 492–505). John Wiley & Sons.
Alkhlaifat, O. K., & Koloszár, L. (2023). The effectiveness of lean management applying process: Case study on Jordan Electricity Distribution Company. International Journal of Productivity and Quality Management, 38(4), 464. https://doi.org/10.1504/IJPQM.2023.130185
Avnet. (2020, April 7). How AI and IoT are transforming logistics. Avnet Resources. https://www.avnet.com/americas/resources/article/how-ai-and-iot-are-transforming-logistics/
Barreto, L., Amaral, A., & Pereira, T. (2017). Industry 4.0 implications in logistics: An overview. Procedia Manufacturing, 13, 1245–1252. https://doi.org/10.1016/j.promfg.2017.09.045
Bloem, J., van Doorn, M., Duivestein, S., Excoffier, D., Maas, R., & van Ommeren, E. (2014). The fourth industrial revolution: Things to tighten the link between IT and OT. Sogeti VINT.
Carretero, S., Vuorikari, R., & Punie, Y. (2017). DigComp 2.1: The digital competence framework for citizens with eight proficiency levels and examples of use (EUR 28558 EN). Publications Office of the European Union. https://doi.org/10.2760/38842
Carter, N., Bryant-Lukosius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2014). The use of triangulation in qualitative research. Oncology Nursing Forum, 41(5), 545–547. https://doi.org/10.1188/14.ONF.545-547
Céginformáció.hu. (2024). Céginformációs adatbázis. https://www.ceginformacio.hu/
Christopher, M. (2016). Logistics & supply chain management (5th ed.). Pearson Education.
Denzin, N. K. (1978). The research act: A theoretical introduction to sociological methods. McGraw-Hill.
Dexory. (2024). AI and IoT in logistics: How do the Internet of Things and AI work together? Dexory Insights. https://www.dexory.com/insights/ai-and-iot-in-logistics-how-do-the-internet-of-things-and-ai-work-together
Eapen, B. R., Archer, N., & Sartipi, K. (2020). QRMine: A python package for triangulation in grounded theory. arXiv. https://arxiv.org/abs/2003.13519
Fragapane, G., Ivanov, D., Peron, M., Sgarbossa, F., & Strandhagen, J. O. (2020). Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics. Annals of Operations Research, 308(1), 125–143. https://doi.org/10.1007/s10479-020-03603-y
Kagermann, H., Helbig, J., Hellinger, A., & Wahlster, W. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry. Federal Ministry of Education and Research.
Koloszár, L. (2013). Vállalati információs rendszerek. Nyugat-magyarországi Egyetem Kiadó.
Koloszár, L., Bednárik, É., Erdős, F., Thinakaran, R., & Takáts, A. (2024). User experience testing methods: Conclusions from the literature. Edelweiss Applied Science and Technology, 8(5), Article 5. https://doi.org/10.55214/25768484.v8i5.1843
Kvale, S., & Brinkmann, S. (2009). InterViews: Learning the craft of qualitative research interviewing (2nd ed.). Sage.
Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial Marketing Management, 29(1), 65–83. https://doi.org/10.1016/S0019-8501(99)00113-3
94
Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business Logistics, 22(2), 1–25. https://doi.org/10.1002/j.2158-1592.2001.tb00001.x
Nagyné Halász, Zs., Gubán, M., & Koloszár, L. (2018). Az informatikusképzés a felsőoktatásban [IT education in higher education]. GIKOF Journal, 2018(11), 40–50. http://publicatio.uni-sopron.hu/3362/1/GIKOF-Journal-2018-11-40-50.pdf
Porter, M. E. (1985). Competitive advantage: Creating and sustaining superior performance. Free Press.
Schwab, K. (2017). The fourth industrial revolution. Crown Business.
Strandhagen, J. O., Vallandingham, L. R., Fragapane, G., Strandhagen, J. W., Stangeland, A. B. H., & Sharma, N. (2017). Logistics 4.0 and emerging sustainable business models. Advances in Manufacturing, 5(4), 359–369. https://doi.org/10.1007/s40436-017-0198-1
Tonelli, F., Demartini, M., Loleo, A., & Testa, C. (2021). A novel methodology for manufacturing firms value modeling and mapping to improve operational performance in the Industry 4.0 era. Procedia CIRP, 99, 768–773. https://doi.org/10.1016/j.procir.2021.03.106
Wang, S., Wan, J., Zhang, D., Li, D., & Zhang, C. (2016). Towards smart factory for Industry 4.0: A self-organized multi-agent system with big data-based feedback and coordination. Computer Networks, 101, 158–168. https://doi.org/10.1016/j.comnet.2015.12.017
World Economic Forum. (2024). Digital transformation for SMEs: A strategic framework. https://www3.weforum.org/docs/WEF_DigitalTransformationforSMEs2024.pdf
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