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Top1. Introduction
Nowadays, the world is governed, shaped, and controlled by both technologies and digitization. Industry 4.0 causes a disruption to all industries, forcing all governments to consider making use of such technologies in order to keep a competitive stand in the world market. That being said, the process of transitioning to Industry 4.0 is sensitive to numerous factors, e.g., type of industry, government regulations and workforce. This study focuses on the logistics industry and how it can be optimized to reach Industry 4.0 standards (Gumzej, 2022). Moreover, this study aims at introducing a theoretical framework that enables a constructive transition of the logistics industry to Industry 4.0 standards (Logistics 4.0) through human capital development (HCD).
Industry 4.0 is the presence of automation and decentralization along with interdependence control (Qin et al., 2016). Consequently, its implementation and growth require less old-fashioned manufacturing workforce and more modernized one. The biggest drivers of Industry 4.0 are technology developers as they provide the biggest two main elements of Industry 4.0 and they are; Internet of things and Big data (Umachandran et al., 2019). But Industry 4.0 is an exceptionally large concept and involves many practices that are evolving rapidly, hence the need to summarize it. The amalgamation of four elements were found to give a brief and general representation of the Industry 4.0 concept, and these elements are; Internet of thing (IoT), Big data, Cyber-physical systems (CPS) and smart factory (Hofmann & Rüsch, 2017). IoT utilizes artificial intelligence, big data and the cloud to achieve a continuous connectivity between all elements of the industrial practices and enables immediate responses when needed. Big data is the key for autonomy as everything in Industry 4.0 operates on or generates data. This data is exceptionally large, comes in a vast variety of forms, grows and shifts very fast. Big data can come structured, i.e., easy to draw value from, semi-structure, i.e., not defined enough to draw value from it, and unstructured, i.e., raw and large data that give no value unless it is processed. CPS is defined as providing control over the physicality of the industrial operations by integrating computational and network solutions, e.g., IoT and Big data. With special elements such as; actuating and sensing devices, control processing solutions and communicative machines and devices. Smart factory is the incorporation of all previously mentioned technologies in order to optimize the efficiency of the industrial and reduce traditional labor to the minimum (Barreto et al., 2017; Hozdić, 2015; Shafiq et al., 2019).
The logistics industry represents the perfect environment for the employment of Industry 4.0 practices (Wang, et al., 2020). Especially since logistics is embedded in almost all industrial, health and food sectors and practices. A vast number of technological solutions that has the potential to revolutionize the logistics sector and bring the Logistics 4.0 era are present today. These technologies can disrupt all parts of the supply chain industry including its economical contribution (Wang, et al., 2021). The fact that the logistics industry is a form of international connectivity between different countries represents an opportunity to encourage the spread of Industry 4.0 and Logistics 4.0 rudiments world widely (Gumzej, 2022). Some of the technological solutions that enable logistics 4.0 practices and are employed today such as; Automation, Robotics, Blockchain, IoT, Big data, Cloud computing, 3D printing, Artificial intelligence (AI) and Augmented reality (AR) (Barleta et al., 2019; Bhattacharyya & Mandke, 2021).