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The proliferation of smart technologies transforms the way individual consumers perform tasks. Considerable research alludes that smart technologies are often related to domestic energy consumption. However, it remains unclear how such technologies transform tasks and thereby impact our planet. We explore the role of technological smartness in personal day-to-day tasks that help create a more sustainable future. In the absence of theory, but facing extensive changes in everyday life enabled by smart technologies, we draw on phenomenon-based theorizing (PBT) guidelines. As anchor, we refer to task endogeneity related to task-technology fit theory (TTF). As infusion, we employ theory on public goods. Our model proposes novel relations between the concepts of smart autonomy and -transparency with sustainable task outcomes, mediated by task convenience and task significance. We discuss some implications, limitations, and future research opportunities.
Facing ever-looming climate change, studying the drivers for individuals' Information Systems (IS) Use to reduce environmental harm gains momentum. While extant research on the antecedents of sustainable IS Use has focused on specific theories, interventions, contexts, and technologies, a holistic understanding has become increasingly elusive, with a synthesis remaining absent. We employ a systematic literature review methodology to shed light on the driving antecedents for sustainable IS Use among individual consumers. Our results build on findings of 29 empirical studies drawn from 598 articles retrieved from our premier outlets and a forward/backward search. The analysis reveals six salient complementary antecedents: Relief, Empowerment, Default, User-centricity, Salience, and Encouragement. We recommend considering these concepts when developing, deploying, promoting, or regulating digital technologies to mitigate individual consumers' emissions. Along with memorable and implementable concepts, our theoretical framework offers a novel conceptualization and four promising avenues for researchers on sustainable IS Use.
Teaching at assembly workstations in production in SMEs (small and medium sized companies) often does not take place at all or only insufficiently. In addition to the lack of technical content, there are also aggravatingly incorrect movement sequences from an ergonomic point of view, which "untrained" people usually automatically acquire. An AI based approach is used to analyze a definite workflow for a specific assembly scope regarding the behavior of several employees. Based on these different behaviors, the AI gives feedback at which points in time, work steps and movement’s particularly dangerous incorrect postures occur. Motion capturing and digital human model simulation in combination with the results of the AI define the optimized workflow. Individual employees can be trained directly due to the fact that AI identifies their most serious incorrect postures and provide them with a direct analogy of their “wrong” posture and “easy on the joints posture”. With the assistance of various test persons, the AI can conduct a study in which the most frequently occurring incorrect postures can be identified. This could be realized in general or tailored to specific groups of people (e.g. "People over 1.90m tall must be particularly careful not to make the following mistake...). The approach will be tested and validated at the Werk150, the factory of the ESB Business School, on the campus of the Reutlingen University. The new gained knowledge will be used subsequently for training in SMEs.
Model-guided Therapy and Surgical Workflow Systems are two interrelated research fields, which have been developed separately in the last years. To make full use of both technologies, it is necessary to integrate them and connect them to Hospital Information Systems. We propose a framework for integration of Model-guided Therapy in Hospital Information Systems based on the Electronic Medical Record, and a taskbased Workflow Management System, which is suitable for clinical end users. Two prototypes - one based on Business Process Modeling Language, one based on the serum-board - are presented. From the experience with these prototypes, we developed a novel personalized visualization system for Surgical Workflows and Model-guided Therapy. Key challenges for further development are automated situation detection and a common communication infrastructure.
Power line communications (PLC) reuse the existing power-grid infrastructure for the transmission of data signals. As power line the communication technology does not require a dedicated network setup, it can be used to connect a multitude of sensors and Internet of Things (IoT) devices. Those IoT devices could be deployed in homes, streets, or industrial environments for sensing and to control related applications. The key challenge faced by future IoT-oriented narrowband PLC networks is to provide a high quality of service (QoS). In fact, the power line channel has been traditionally considered too hostile. Combined with the fact that spectrum is a scarce resource and interference from other users, this requirement calls for means to increase spectral efficiency radically and to improve link reliability. However, the research activities carried out in the last decade have shown that it is a suitable technology for a large number of applications. Motivated by the relevant impact of PLC on IoT, this paper proposed a cooperative spectrum allocation in IoT-oriented narrowband PLC networks using an iterative water-filling algorithm.
The fifth mobile communications generation (5G) can lead to a substantial change in companies enabling the full capability of wireless industrial communication. 5G with its key features of providing Enhanced Mobile Broadband, Ultra-Reliable and Low-Latency Communication, and Massive Machine Type Communication will support the implementation of Industry 4.0 applications. In particular, the possibility to set-up Non-Public Networks provides the opportunity of 5G communication in factories and ensures sole access to the 5G infrastructure offering new opportunities for companies to implement innovative mobile applications. Currently there exist various concepts, ideas, and projects for 5G applications in an industrial environment. However, the global rollout of 5G systems is a continuous process based on various stages defined by the global initiative 3rd Generation Partnership Project that develops and specifies the 5G telecommunication standard. Accordingly, some services are currently still far from their final performance capability or not yet implemented. Additionally, research lacks in clarifying the general suitability of 5G regarding frequently mentioned 5G use cases. This paper aims to identify relevant 5G use cases for intralogistics and evaluates their technical requirements regarding their practical feasibility throughout the upcoming 5G specifications.
The production environment experiences copious challenges, but likewise discovers many new potential opportunities. To meet the new requirements, caused by the developments towards mass-customization, human-robot-cooperation (HRC) was identified as a key piece of technology and is becoming more and more important. HRC combines the strengths of robots, such as reliability, endurance and repeatability, with the strengths of humans, for instance flexibility and decision-making skills. Notwithstanding the high potential of HRC applications, the technology has not achieved a breakthrough in production so far. Studies have shown that one of the biggest obstacles for implementing HRC is the allocation of tasks. Another key technology that offers various opportunities to improve the production environment is Artificial Intelligence (AI). Therefore, this paper describes an AI supported method to improve the work organization in HRC in regards to the task-allocation. The aim of this method is to build a dynamic, semi-autonomous group work environment which keeps not just employee motivation at a high level, but also the product quality due to a decreased failure rate. The AI helps to detect the perfect condition in which the employee delivers the best performance and also supports at identifying the time when the worker leaves this optimal state. As soon as the employee reaches this trigger event, the allocation of the tasks adapts based on the identified stress. This adaptation aims to return the employee to the state of the optimal performance. In order to realize such a dynamic allocation, this method describes the creation of a pool with various interaction scenarios, as well as the AI supported recognition of the defined trigger event.
Die Digitalisierung und Nachhaltigkeit werden die Erwartungen und Anforderungen an die Controller dauerhaft und umfassend verändern. Die Lehre hat für den Rollenwandel eine hohe Relevanz. Eine auf die veränderten Anforderungen abgestimmte Ausbildung bietet den Unternehmen die Möglichkeit, Controller mit diesen veränderte Rollenprofilen für ihre Organisation zu gewinnen. Für die Absolventen mit dem Berufswunsch Controlling sichert das veränderte Rollenprofil ihre langfristige Arbeitsmarktfähigkeit. Für den Rollenwandel selbst kann diese als Treiber verstanden werden.
Trotz der Bedeutung der Lehre für den Rollenwandel gibt es dazu bislang wenige Forschungsergebnisse zur konkreten Abbildung der Rollen in der Lehre. Es stellt sich daher die Frage, wie Hochschulen in ihren Studiengängen die Rollen grundsätzlich abbilden und mit welcher Intensität sowie Kombinationen die Rollen gelehrt werden. Diese Forschungsfrage wird anhand einer Analyse von controllingspezifischen Masterstudiengängen und deren Modulhandbücher evaluiert und diskutiert.
Im Ergebnis stellt sich der Rollenwandel in der Controllinglehre sehr heterogen dar. Es dominiert die Vermittlung der klassische Controllerrolle gefolgt von der Business Partner Rolle. Lehrinhalte bezogen auf die Rollen des digitalen Controllers oder Risikocontrollers sind schwach ausgeprägt. Für die Übernahme einer Controllerrolle im Nachhaltigkeitsmanagement existiert kaum ein Lehrangebot. Diese Ergebnisse sollen zum Diskurs über den Rollenwandel und die Gestaltung der Lehre im Controlling beitragen.
Indoor localization systems are becoming more and more important with the digitalization of the industrial sector. Sensor data such as the current position of machines, transport vehicles, goods or tools represent an essential component of cyber physical production systems (CCPS). However, due to the high costs of these sensors, they are not widespread and are used mainly in special scenarios. However, especially optical indoor positioning systems (OIPS) based on cameras have certain advantages due to their technological specifications. In this paper, the application scenarios and requirements as well as their characteristics are presented and a classification approach of OIPS is introduced.
Quest 3C : an integrative simulation game used to encourage cross-disciplinary thinking and action
(2014)
Interdisciplinary, complex problem-solving and the necessity to communicate effectively in global Teams characterise today’s rapidly changing Business environment. Employers consistently stress the need for business engineering graduates to demonstrate technical expertise, methodological competences and diverse soft skills. The "silo effect" in higher education has partially created a gap between what industry wants and what academia provides. Here we examine how interdisciplinary team teaching and shared ICT might be more effective in bringing higher education teaching in sync with industry and its demands.