4.1. Logistics 4.0 Applications
Decision-support and decision-making tools are crucial for all logistics operations, and their implementation is not limited to a specific activity. In this group, the 4.0 technologies mainly used are BDA, AI, augmented and virtual reality, and simulation. BDA provides a clear understanding of a situation through descriptive and prescriptive data analysis [
50]. Within an organization, BDA enables the integration of different processes, such as the evaluation of equipment and vehicles for preventive maintenance tasks [
51]. BDA can be used to reach sustainability goals by studying trends, patterns, limits, and potential risks related to the market, the material flow inside and outside the industry, and the information flow [
11,
12]. From an economic point of view, it leads to a reduction in logistics costs, improved space utilization, increased customer satisfaction, and increased efficiency in logistics activities [
9]. Big data analysis also improves transportation reliability, fleet routes for freight transport, and material handling strategies [
14]. At the same time, environmental and social sustainability are also achieved. Companies can significantly reduce greenhouse gas emissions, fuel consumption, waste, and noise through better vehicle routing, traffic condition analysis, and delivery planning [
9]. Additionally, operators benefit from an efficient work environment where their tasks are enhanced thanks to data-based decisions [
9]. Together with BDA, AI plays a vital role in the optimization software used to improve logistics activities. AI technologies in logistics operations are used with systems capable of making decisions and taking actions autonomously or semi-autonomously according to the current state of a process [
3]. In this sense, an industrial plant that takes advantage of this solution can replace human resources with 4.0 technology to efficiently and quickly solve high-complexity logistical problems [
2]. Implementing AI leads to cost reduction, improved resource utilization, greater efficiency, and decreased environmental impact [
9]. At the same time, AI can replace or substantially assist workers in repetitive tasks, improving employees’ welfare and thus reaching social sustainability [
1]. Other relevant 4.0 technologies are augmented and virtual reality, which can assist and optimize logistics activities in decision-making processes [
52]. Concerning augmented reality, pick-by-vision technologies are an application in which workers are guided in specific tasks with real-time information. These 4.0 technologies are mainly used in storage location for picking activities, where storage location is typically a time-consuming and labor-intensive logistics operation. Indeed, the working conditions of the operators have improved in terms of safety and knowledge of the information needed at the right time [
53]. Moreover, fewer accidental mistakes are made by workers, improving productivity and efficiency, reducing costs, and increasing warehouse flexibility [
14]. Virtual reality also enables the simulation of complex processes, such as materials handling and dangerous operations [
54]. The use of simulation reduces the time, cost, and effort required to design new logistics strategies, such as green strategies that improve economic and environmental sustainability [
1]. Additionally, virtual reality provides low-risk training opportunities for workers.
The identification and interconnectivity of industrial systems are made possible by industrial IoT technologies and CPSs through smart sensors such as automated identification technologies, real-time locating systems (RTLSs), and global positioning systems (GPSs). The use of these solutions allows for the definition of integrated networks that guarantee knowledge and control of the product flow through communication and cooperation between entities [
3,
5]. More specifically, radiofrequency identification (RFID) is a type of automated identification technology that acquires certain data about an entity through radio-frequency communication [
50]. RFID technology makes it possible to collect a significant amount of real-time traceability data quickly and easily on material flows [
9,
10]. Decision makers, whether human or automated, can use the information obtained by RFIDs to make decisions about that specific item [
55]. Such 4.0 technologies are employed, for instance, in picking, storage, and material handling processes [
10]. Implementing RFIDs has been shown to increase revenue, reduce inventory costs, and increase service levels [
9]. RTLSs allow for real-time tracking of the location of items and/or people, typically within a building or other contained area [
50]. On the other hand, GPSs are used for tracking purposes outside a confined environment, mainly for the near-real-time location of products. This enables taking adequate steps to solve potential issues that can arise during outbound logistics [
7]. The auto-identification and interconnectivity allowed by these 4.0 technologies lead to the concept of industrial IoT. IoT enables just-in-time deliveries, fleet tracking, supply chain visibility and monitoring, internal processes, efficient inventory, effective warehouse management, and safe product delivery [
14]. IoT is considered one of the core elements of Logistics 4.0, and it meets the three main objectives of sustainability [
12]. By improving traceability, also thanks to cloud technologies, delays in decision-making, accidental damages, service times, and operational errors in warehousing activities can be critically reduced [
11,
12]. At the same time, IoT leads to the optimization of internal processes, greater supply chain control, and improved reliability and accuracy of logistics operations [
14]. All of this leads to a reduction in costs, greater efficiency, and greater profits [
12]. Furthermore, IoT technology is considered to improve customer service, resulting in better business visibility and brand recognition for the company [
9]. Real-time tracking is another key characteristic of IoT that economically favors the industries that implement these 4.0 technologies, as it enables transparency in the supply chain [
9]. For social sustainability, IoT is useful in limiting social issues such as product theft, fraud, and counterfeiting, while also improving the safety conditions of employees [
12]. For example, the deployment of IoT in a warehouse can detect instances of inadequate use of safety equipment by workers [
9]. Additionally, IoT and digitalization in general enable a reduction in resource waste and energy consumption by monitoring key operational factors, measuring fuel consumption in industrial equipment, and identifying strategies that contribute to reducing the environmental impact of logistics activities [
4].
In logistics operations, the flow of information is considered as important as the flow of materials. Together with the 4.0 technologies described in the previous paragraph, cloud computing, blockchain, and cybersecurity are the enablers of both horizontal and vertical integration of information technology systems, which contribute to the creation of a seamless and secure flow of information. Blockchain enables effective integration of information and material flow; in this sense, it allows companies to obtain, manage, and use critical and secure data throughout the entire supply chain, which leads to better performance, reliability, traceability, and transparency [
11,
12]. This leads to higher profitability because it reduces the risks of product alteration, delivery rejections, and economic losses [
12]. Blockchain technologies can also be used to track and measure carbon emissions related to a company’s logistics activities so that, on the one hand, they can study and take the appropriate improvement actions and, on the other, they can feel the social responsibility to address the inefficiencies. Moreover, always from an environmental perspective, blockchain can help limit resource wastage by allowing data-driven decision making [
11]. Other applications of blockchain technologies that positively impact the three dimensions of sustainability are delivery monitoring, statistics updating in real-time, and fleet monitoring [
14]. Blockchain together with cloud computing and cybersecurity enable access to software programs and data storage without requiring a substantial infrastructure expenditure [
10]. Such software applications are, among others, warehouse management systems, inventory management systems, and order management systems [
3]. These types of software are vital for basically all internal logistics activities, from picking and storage to material handling, packing, and data storage [
16]. These systems are also important for having a balanced inventory [
11]. For what concerns the human-technology relationship, these types of software represent a total replacement for previously performed tasks [
10]. The sustainability impact of these 4.0 technologies is again very relevant. Real-time data sharing through cloud services enhances efficiency and effectiveness in different logistics activities by enabling better communication, coordination, more accurate predictions of crucial operations, and increased supply-chain visibility [
9,
12]. For example, better predictions enable more cost-efficient maintenance and reduced equipment downtime [
11]. Additionally, GHG emissions, resource usage, wastage, handling costs, and working hours of transport vehicle drivers can be reduced by mastering a just-in-sequence delivery system [
12]. From a social perspective, implementing information technologies requires highly skilled technicians, so workers, given the nature of their jobs, operate in overall better conditions compared to other manual-skilled tasks [
11].
Finally, robots and new production technologies are key enablers of Logistics 4.0 in smart factories, particularly for internal logistics activities. Advanced robotics are 4.0 technologies that can partially reduce the presence of human workers inside a plant, depending on their level of mobility, autonomy, and intelligence [
11]. These 4.0 technologies help alleviate the burden that workers have to sustain in order to complete their tasks, resulting in greater efficiency, productivity, flexibility, reduced accidental errors, and overall better working conditions [
53], which consequently leads to the achievement of social and economic sustainability goals. Examples of these 4.0 technologies include autonomous and collaborative robots, exoskeletons, drones, and automated guided vehicles (AGVs). Autonomous robots can independently assess the working conditions and external environment, thus operating their tasks accordingly by making decisions without the need for human interaction [
11]. On the other hand, collaborative robots are specifically designed for human-robot interaction within a shared space to support the worker in repetitive and heavy-duty tasks [
3,
10]. Exoskeletons are also a powerful way in which robots assist humans in injury-prone operations. They are wearable structures that support the worker’s musculoskeletal system during physically demanding activities [
3]. Thus, this type of 4.0 technology helps drastically improve the working conditions of operators, creating a socially sustainable work environment. While more conventional robots have bi-dimensional flexibility, drones allow logistics activities to occur in a three-dimensional space [
53]. Drones are also referred to as unmanned aerial vehicles as they do not require a human pilot onboard [
11]. Some of the main applications of drones include last-mile deliveries of relatively low-weight goods, order-picking in automated warehouses, and semi-automated physical inventory [
14]. AGVs are autonomous and remotely operated vehicles that are used for moving loading units or products from one point to another in a predetermined and consistent amount of time [
56]. AGVs have magnetic or embedded optical guided sensors that ensure the predetermined path is followed [
57]. The path is designed considering various factors, including battery management, traffic, location, and the number of load/unload points and idle spots where AGVs can pause without getting in the way of other operations [
58]. AGVs are used inside warehouses or confined spaces to deliver goods within the facility [
57]. Exoskeletons, AGVs, drones, and collaborative robots can be used in several internal logistics activities regarding material flow, particularly during picking, storage, and material handling. Collaborative robots are also used in packing [
3,
10]. AGVs are used to transport heavy materials and for parts and line feeding [
5]. With regards to the human-technology relationship, these 4.0 technologies only support workers and do not replace them [
10]. Autonomous robots and automated guided vehicles can be used for various applications in logistics operations. For example, there can be automated storage and retrieval systems, loading, unloading, picking robots, and sorting conveyor systems [
58]. Smart robots that replace or assist with manual operations offer multiple benefits regarding the three dimensions of sustainability. Firstly, activities carried out partially or fully autonomously by robots minimize accidental errors, costs, and product damage, while improving the efficiency and effectiveness of operations, thus drastically increasing the profitability of a business [
11,
14]. In addition, they also guarantee greater safety for workers on the floor, as they can detect potential risks and automatically stop incriminated operations and machines [
9]. They can also be used for potentially dangerous operations, such as handling hazardous materials and improving the safety of the working environment [
11]. Collaborative robots help ease pressure on workers when dealing with heavy tasks, once again contributing to the dimension of social sustainability [
12]. There is contradictory literature regarding the environmental sustainability of smart robots. Although it is generally true that more efficient, effective, and faster operations result in fewer emissions and less fuel consumption (thereby decreasing the environmental footprint), some authors argue that there can be a substantial increase in energy consumption needed to run these 4.0 technologies, which, without adequate optimizations, makes the environmental friendliness of robots doubtful [
14,
58]. In addition, another major problem attributable to robotic systems concerns the upstream and downstream phases of their use in life cycle assessment. Such systems are powered by lithium-ion batteries. The procurement of materials for the production of batteries (e.g., copper, zinc, and nickel) and their disposal are highly impactful activities from an environmental point of view compared to other less digitized solutions [
56]. Finally, new 4.0 production technologies can also be used favorably for smarter logistics operations. For instance, additive manufacturing is beneficial for more intelligent warehouse management and inventory since it can be seen as a way of digitally storing an array of lowly or irregularly demanded products without requiring an actual physical space [
11]. This strongly simplifies manufacturing logistics, while, at the same time, enabling a high degree of product customization. In this sense, 3D printing meets economic and environmental sustainability demands [
59].
Table 3 summarizes the results of the literature review on the applications of Logistics 4.0 technologies.
4.2. Logistics 4.0 Sustainable Impact and Criteria
As mentioned above, Logistics 4.0 technologies are typically considered to provide economic advantages. However, a crucial limitation is the high initial financial costs associated with transitioning to a smart logistic system that implements sustainable practices [
9,
20]. Furthermore, most of the 4.0 technologies require state-of-the-art and powerful internet-based networks and digital infrastructure that are not always available in industries, depending on their geographical location [
20]. A great technological concern shared by several authors is about cybersecurity and how to guarantee information security [
9,
11,
17,
20,
61]. In fact, two of the critical characteristics of Logistics 4.0 are digitalization and the aim of horizontal and vertical integration. As a result, data becomes one of the company’s most valuable assets, making it a target for cyberattacks. Some studies argue that, given the critical nature of information, research and applications in this field are still not particularly mature and that more work needs to be conducted to prevent and respond to cyberattacks [
62]. In this sense, data security represents a significant challenge for companies and supply chain stakeholders. Another data-related technological issue is data quality [
11,
17]. First, big data analytics can be difficult without high data quality and without achieving the desired objectives [
20]. Furthermore, given the data sharing that occurs between different facilities and companies in a logistic system, the different levels of maturity and quality of data processing techniques can influence the analysis outcome; in this sense, stakeholders in a logistic network should cooperate to achieve a homogeneous degree [
11].
From an environmental perspective, 4.0 technologies typically enable improved resource utilization, better efficiency, and reduced waste generation. However, researchers [
11] argue that, given the large number of smart devices being used (robots, smart machines, sensors, etc.), there is an increased consumption of electricity, which, depending on the sources used to generate that electricity, could result in a negative environmental impact [
63]. Furthermore, other authors [
9] show inconclusive results on how 4.0 technologies affect the disposal of solid and energy waste and fuel consumption [
64].
Even if 4.0 logistic technologies should meet all three objectives of TBL (environmental, economic, and social sustainability), social sustainability is often neglected. Indeed, several authors agree that the social impact of smart technologies is under-considered with respect to the economic benefits associated with them. For example, autonomous and semi-autonomous robots replace human workers in physical tasks, guaranteeing a safer working environment. At the same time, however, this will inevitably also cause job losses [
3], negatively affecting the social dimension of the TBL. According to some authors, it is not just about layoffs. Bai et al. in [
64] argue that also the feeling of job insecurity experienced by workers and anxiety about the progression of their careers should be considered as negatively impacting this sustainability dimension. Nantee et al. in [
9] also add that this will also affect the economic dimension, as employees who feel this way will work less productively. However, although Logistics 4.0 eliminates many manual-skilled jobs, the authors also admit that smart transformation creates opportunities for information technology-related jobs. Another consequence of 4.0 technologies is that the skills required for workers have drastically changed. For this reason, training is implemented for the workforce, and employees must forcibly adapt to these technological transformations, acquiring new technical skills in order to handle new equipment and keep their jobs [
11]. This can lead to reluctant behavior toward these changes, not only from first-line workers but also from managers, who suddenly find themselves operating in new and unfamiliar settings [
20]. Moreover, this aspect disproportionally impacts the workforce: older workers face more challenges than younger ones because they are less willing to adapt to new procedures. Overall, since the fourth industrial revolution can have some stress-inducing consequences, worsening the well-being of employees, the impacts of 4.0 technologies on social sustainability should not be overlooked by the literature [
9].
Based on the applications of Logistics 4.0 technologies and their critical implementation issues, it is possible to identify the most important sustainability indicators. The sustainability indicators represent the critical factors to be assessed for the dimensions of economic, environmental, and social sustainability. Within the economic dimension, indicators are cost reductions (Ec.1) and improvements in efficiency and effectiveness (Ec.2), while in the environmental dimension, are reductions in energy and fuel consumption (En.1) and improvements in resource and waste management (En.2). Finally, social sustainability indicators deal with the improvement of working conditions (So.1) and worker safety (So.2).
Table 4 summarizes the impacts achieved on the aforementioned sustainability indicators when introducing different 4.0 technologies in a company. In
Table 3, each 4.0 technology can produce a positive (+), negative (−), or irrelevant (±) impact on each sustainability indicator, thus impacting the company’s performance. Therefore, the most convenient 4.0 technology to adopt must be selected by considering the corporate objectives and their positioning with respect to the three sustainability dimensions of the TBL framework.