Industry 4.0: Marvels in Profitability in the Transport Sector

Author:

Bugaj Martin1ORCID,Durana Pavol2ORCID,Blazek Roman2,Horak Jakub3ORCID

Affiliation:

1. Air Transport Department, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia

2. Department of Economics, Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia

3. Institute of Technology and Business, School of Expertness and Valuation, Okruzni 517/10, 37001 Ceske Budejovice, Czech Republic

Abstract

Despite the COVID-19 pandemic, the current era offers the ultimate possibility for prosperous corporate life, especially in the transport sector. Industry 4.0 covers artificial intelligence, big data, or industrial IoT, and thus spatial cognition algorithms, traffic flow prediction, autonomous vehicles, and smart sustainable mobility are not far away. The mentioned tools have already been implemented by enterprises in emerging countries. This exploration focused on transportation within the V4 region from 2016–2021. This article aims to confirm the positive sequel of applying Industry 4.0 to chosen indicators of profitability. The positive, negative, or no shift in the development of 534 businesses was based on Pettitt’s test. The Pearson chi-square test disclosed the significant dependency between Industry 4.0 and shifts in profitability ratios. Then, more than 25% of enterprises involved in Industry 4.0 had positive shifts in ROA, ROC, ROS, and ROR. The research proved not only its balanced effect but also its augmented force through the z-test of proportion. This investigation may provide multiple proofs for connected sectors with transportation to adapt the tools of Industry 4.0 and deliver the call for the governments in the V4 region to make this tool more achievable.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep Learning based Advanced Image Recognition in Autonomous Vehicles in Industry 4.0;2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2024-06-05

2. Drivers of decision-making towards for digital transformation;Review of Managerial Science;2024-04-16

3. Integration between green power generation, energy storage and smart grids in the context of e-mobility;E3S Web of Conferences;2024

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