Artificial intelligence, robotics, and logistics employment: The human factor in digital logistics

Abstract

With this editorial, we aim to shed light on the role of the human factor in digital logistics. This has been already established in general (Neumann et al., 2021; Schorsch et al., 2017) as well as regarding specific perspectives like, for example, addressing the important role of human intuition (Carter et al., 2017) or cost developments (Fager et al., 2021). For a detailed and comprehensive analysis, we apply an interdisciplinary perspective drawing on economic and social sciences. Starting from the observation of technological innovations such as AI, robotics, and digital technologies and their implementation into supply chains, it can be expected that this impacts work and employment in the field of logistics. It is also evident that a change in work content and job demands is expected, which also depends on the design of human–computer interaction (HCI). HCI is a broad field that covers any interaction between humans and machines such as operating computers, handheld scanners, and mobile devices (Grudin, 2012). Depending on the interaction with machines, humans will refrain more and more from operational tasks and have to migrate their capabilities and attention toward supervisory tasks. It is likely that this affects individual psychological outcomes such as motivation, work engagement, and job satisfaction and also team and organizational decisions and processes (Cummings & Bruni, 2009; Klumpp et al., 2019; Lee et al., 2015). However, this also impacts the cooperation among colleagues and with supervisors. Considering the different levels of change, we propose a conceptual framework for analyzing the relevance of the human factor for digital logistics work. The core topic of the structure is the question of HCI. For this area, we distinguish between four relevant levels as outlined below (see Figure 1). As the human factor in digital logistics work is of outstanding relevance, we expect that this conceptual framework enables researchers to identify critical gaps and frame their individual research. In this context, it is especially relevant to focus not only on individuals in logistics contexts but to also consider that individuals and organizations operate in dynamic and complex interdependent systems and that thus (social) interactions matter for the implementation and success of digital transformation in business practice (D'Aleo & Sergio, 2017). Social interaction is an exchange between two or more individuals, which further influences the perspectives, positions, and actions of the interacting individuals. Through interactions, people design rules, institutions, and systems, which give further orientation and form perceptions (Weber, 1978). Besides the examples to be seen in the papers included within this special topic forum, we can outline the importance of a differentiated analysis of such interactions for the implementation and success in digital logistics (Cerulo, 2009). This can be exemplified regarding different professional groups, from driving professions to intralogistics personnel. Besides blue-collar workers, also white-collar logistics professions such as dispatchers or team leaders are susceptible to the mechanisms of social interaction with the four levels of HFI. This is even more relevant in the context of digitalization as transparency, communication, and interconnectedness are enabling closer connections and increased possibilities for social interaction. Regarding the relevance of the human factor in digital logistics work, the call for a special topic forum attracted four profound and future-oriented contributions. They allow for a broad overview regarding the topic of “Artificial Intelligence, Robotics and Logistics Employment” based on a range of disciplines and applying various research methods. Moreover, and considering the wide range of logistics settings, the contributions address different functional sectors like ports, intralogistics, and internal marketing in supply chains. To provide