The rapid transformation of the industrial sector requires strategies to integrate digitalization and monitoring. While these advancements promote data-driven optimization of manufacturing processes, they raise concerns regarding employee data privacy. This study shifts the focus from the prevalent technological perspective to the perspectives of employees, critically examining the factors influencing their willingness to share data. Employing a Choice-Based Conjoint Analysis with n = 132 participants, our research suggests a strong preference for exclusive control over access to personal data, particularly health-related information, indicating that privacy concerns typically eclipse the advantages offered by data sharing in the workplace. Using latent class analysis, we distinguish between two employee groups characterized by distinct privacy attitudes: “Data Protectors” and “Team Players.” These findings underline the need to further investigate the influence of employee diversity, including demographics, attitudes, and job functions, to effectively optimize communication strategies and address diverse privacy expectations.

Many initiatives aim at answering the challenges of the fourth industrial revolution (Industry 4.0). A key aspect of these initiatives is the connectivity of the different industrial entities. Communication and information exchange between entities usually flows in two dimensions; a vertical one, that spans the different levels of abstraction within the company, and a horizontal one connecting the different entities in the supply chain. In contrast, the Internet of Production (IoP) presents the World Wide Lab (WWL) allowing an extra dimension of communication, which we call the cross-company dimension. Hence, the WWL integrates the different entities within and across potentially competing labs and companies. The WWL leverages and aggregates accessible production data fostering an exchange of information, that prevents redundant experimentation and increases quality of data-driven models by including data from diverse manufacturing settings. This paper discusses work done towards this vision and technical, economic, social, legal, and ethical challenges the WWL faces and provides a roadmap towards infrastructuring the WWL.

The vision of the Internet of Production (loP) is focused on optimizing manufacturing processes, with the help of Industry 4.0 technologies (14Ts). However, considering global megatrends such as climate change and the need to achieve the Sustainable Development Goals (SDGs), it is a growing imperative for the manufacturing industry to become more sustainable. This opens the door to transforming the IoP into an Internet of Sustainable Production (loSP). Accordingly, this paper proposes a novel four-step loSP-framework that establishes an Information System (IS) allowing researchers and practitioners to acknowledge and adapt to the interconnected nature of sustainability. Further, to test its applicability, an inter- and cross-disciplinary perspective is adopted to illustrate case-related challenges, opportunities, and pathways - revealed by the proposed framework - in the example of a digital economy for sustainability data, strategic design of global production networks, human-robot collaboration, digital photonic production, and the textile industry. Together, the framework demonstrates the usefulness of generating holistic information on the interconnected nature of sustainability derived from process-specific and contextualized data, while simultaneously assessing the framework's utilization for sustainability, as well as the sustainability of its use.

Digital shadows play a central role for the next generation industrial internet, also known as Internet of Production (IoP). However, prior research has not considered systematically how human actors interact with digital shadows, shaping their potential for success. To address this research gap, we assembled an interdisciplinary team of authors from diverse areas of human-centered research to propose and discuss design and research recommendations for the implementation of industrial user interfaces for digital shadows, as they are currently conceptualized for the IoP. Based on the four use cases of decision support systems, knowledge sharing in global production networks, human-robot collaboration, and monitoring employee workload, we derive recommendations for interface design and enhancing workers’ capabilities. This analysis is extended by introducing requirements from the higher-level perspectives of governance and organization.

The Industrial Internet-of-Things (IIoT) promises significant improvements for the manufacturing industry by facilitating the integration of manufacturing systems by Digital Twins. However, ecological and economic demands also require a cross-domain linkage of multiple scientific perspectives from material sciences, engineering, operations, business, and ergonomics, as optimization opportunities can be derived from any of these perspectives. To extend the IIoT to a trueInternet of Production, two concepts are required: first, a complex, interrelated network of Digital Shadows which combine domain-specific models with data-driven AI methods; and second, the integration of a large number of research labs, engineering, and production sites as a World Wide Lab which offers controlled exchange of selected, innovation-relevant data even across company boundaries. In this article, we define the underlying Computer Science challenges implied by these novel concepts in four layers:Smart human interfacesprovide access to information that has been generated bymodel-integrated AI. Given the large variety of manufacturing data, newdata modelingtechniques should enable efficient management of Digital Shadows, which is supported by aninterconnected infrastructure. Based on a detailed analysis of these challenges, we derive a systematized research roadmap to make the vision of the Internet of Production a reality.

Digital Shadows as the aggregation, linkage and abstraction of data relating to physical objects are a central vision for the future of production. However, the majority of current research takes a technocentric approach, in which the human actors in production play a minor role. Here, the authors present an alternative anthropocentric perspective that highlights the potential and main challenges of extending the concept of Digital Shadows to humans. Following future research methodology, three prospections that illustrate use cases for Human Digital Shadows across organizational and hierarchical levels are developed: human-robot collaboration for manual work, decision support and work organization, as well as human resource management. Potentials and challenges are identified using separate SWOT analyses for the three prospections and common themes are emphasized in a concluding discussion.

Lifelogging technologies have the potential to facilitate and enrich the everyday life of younger as well as older people. On the one hand, tracking and logging of data about activities and behavior support an active lifestyle. On the other hand, tracking medical data and movements support increasing safety by detecting, e.g., emer-gencies or falls. From a technical perspective, a variety of technologies enable lifelogging and are already available on the market. Instead, there is very little knowledge about the perception and acceptance of lifelog-ging technologies from users’ socio-ethical perspective. Hence, this paper presents research results from four online survey studies (n = 1107) aiming at covering a broad range of lifelogging applications and reaching di-verse target groups. Being based on insights gathered from the quantitative data collection, this paper derives guidelines for integrating ethical and social perspectives in lifelogging technology development and emphasiz-es gaps within the research landscape regarding its perception and acceptance.

Shifts in demographic developments have led to changed needs and requirements in healthcare.Rising life expectancy and improved medical healthcare enable a more independent and healthier lifestyle of (older) persons, but also changes expectations and perceptions of aging, and health-supporting technologies.Knowledge about attitudes towards aging, medical assistive technologies, and impacting user factors (especially age and health status) is limited with regard to a broad sample of participants.In the present study (N=585), we therefore examined in an online-survey current attitudes towards aging and quality of life in older age, as well as perceptions and acceptance of health-supporting technologies, taking age and health status as user factors into account.Results revealed significant effects of age and health condition on the perception of life quality in older age.In addition, positive perceptions of aging, technology acceptance, as well as benefits and barriers were significantly influenced by the respondents' age.In contrast, health status significantly affected the negative perceptions of aging.Under impacts of age and health condition as user factors, results of the study allow a deeper understanding of changing patterns of perceived aging and prevailing opinions regarding acceptance of medical technology.

Industry 4.0 and the Internet of Production can increase efficiency and effectiveness of workflows in manufacturing companies and production networks. Despite ubiquitous automation, people are essential in socio-technical cyber-physical production systems due to unique cognitive capabilities, as final arbitrators, or for ethical and legal reasons. However, the design of interfaces between the human-in-the-loop and production systems poses challenges not yet been sufficiently elaborated in research and practice. We present two behavioural studies in the context of inter-company collaboration that show why considering the human-in-the-loop is crucial: The first study shows that information complexity and individual differences shape the overall decision quality. With increasing information complexity, the decision speed decreases and the decision accuracy descends. Consequently, a fine balance between necessary, abundant, and superfluous information must be found. The second experiment studies human decision making in complex environments using a business simulation. We found that correct decision aids can augment the human-in-the-loop's decision making and that these can increase usability, trust, and proft. Yet, incorrect decision support has the opposite effect. Guidelines for designing socio-technical cyber-physical production systems and a research agenda conclude this article.

With the advent of artificial intelligence (AI) methods, smart decision support systems (DSSs) are becoming ubiquitous. Such systems help reduce complexity for operators by automating data integration tasks and recommending actions. However, these systems are sometimes flawed. It is not sufficiently understood whether, when and why operators comply with such systems in erroneous or correct cases. We empirically investigate compliance with correct and defective DSSs, the influence of correct and erroneous DSS's on performance and subjective factors related to compliance. In the study, a business game was used as an experimental setting in which 40 users took part. The impact of system correctness on user acceptance, trust, compliance and overall performance was investigated. The results show that the defective system reduces trust in automation (−47%), reduces usefulness (−58%), reduces acceptance (−62%) and reduces overall performance (−32%). Overall, the defective system was less user-friendly (−27%). Nevertheless, users who rated the system's usability higher, outperformed users who rated it lower. Usability is therefore an intermediary that compensates for the negative influence of erroneous DSSs.

Ubiquitous computing strives to reach the calm computing state where sensors and actuators disappear from the foreground of our surroundings into the fabric of everyday objects. Despite the great progress in embedded technology, artificial interfaces, such as remote controls and touch screens, remain the dominant media for interacting with smart everyday objects. Motivated by recent advancements in smart textile technologies, we investigate the usability and acceptance of fabric-based controllers in the smart home environment. In this article we describe the development and evaluation of three textile interfaces for controlling a motorized recliner armchair in a living room setting. The core of this contribution is the empirical study with twenty participants that contrasted the user experience of three textile-based interaction techniques to a standard remote control. Despite the slightly lower reliability of the textile interfaces, their overall acceptance was higher. The study shows that the hedonic quality and attractiveness of textile interfaces have higher impact on user acceptance compared to pragmatic qualities, such as efficiency, fluidity of interaction, and reliability. Attractiveness profits from the direct and nearly invisible integration of the interaction device into textile objects such as furniture.