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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.
There are indicators we are entering a new era for MTM research, by moving beyond the structural approach that has characterized MTM research to date, to focus on important and under-researched issues, such as the nature of employees’ experiences in an MTM context. Although team research suggests that the experiences of members impact team functioning, these lines of reasoning have not, until recently, made their way to MTM research. To overcome this limitation, this symposium showcases five papers that use a variety of theoretical perspectives, research designs (i.e., qualitative, quantitative), contexts (e.g., healthcare, automotive manufacturer, online panels), methodologies, and analytical methods (i.e., meta-analysis, content/thematic analysis). The symposium focuses on surfacing and advancing unanswered questions that extend theory and can offer fruitful directions for MTM research by examining critical individual and team level outcomes (e.g., individual/team performance, individual counterproductive and organizational citizenship behavior, individual learning, individual turnover intentions, organizational commitment) in the experiences of MTM employees across their teams (e.g., goals, functions, roles). We hope to provide a forum to advance unanswered questions that offer fruitful directions for MTM research.
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.
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.
Job advertisements are important means of communicating role expectations for management accountants to the labor market. They provide information about which roles of management accountants are sought by companies or which roles are expected. However, which roles are communicated in job advertisements is unknown so far. Using a large sample of 889 job ads and a text-mining approach, we show an apparent mix of different role types with a strong focus on a rather classic role: the watchdog role. However, individuals with business partner characteristics are more often sought for leadership positions or in family businesses and small and medium-sized enterprises (SMEs). The results challenge the current role discussion for management accountants as business partners in practice and some academic fields.
Early exposure makes the entrepreneur: how economics education in school influences entrepreneurship
(2022)
Many countries that seek to boost their economy share the goal of promoting entrepreneurship. Whereas there is ample research on the predictors of entrepreneurship during adulthood, we know little about how pre-adulthood experience influences entrepreneurship later in life. Using a natural experiment, this paper examines whether introducing economics classes in school enhances entrepreneurial behavior in adulthood. Our difference-in-differences approach exploits curricula reforms across German states that introduced compulsory economics education classes in secondary schools. Using information on school and labor market careers for more than 10,000 individuals from 1984 to 2019, we find that the reform increases students’ entrepreneurial activities by three percentage points. Examining gender differences, we find that economics classes equally benefit female and male students. Our results advance our understanding of how pre-adulthood experiences shape individuals’ entrepreneurial behavior.
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.
Manufacturing companies are confronted with external (e.g. short-term change of product configuration by the customer) and internal (e.g. production process deviations) turbulences which are affecting the performance of production. Predefined, centrally controlled logistics processes are limiting the possibilities of production to initiate countermeasures to react in an optimized way to these turbulences. The autonomous control of intralogistics offers a great potential to cope with these turbulences by using the respective flexibility corridors of production systems and applying intelligent logistic objects with decentralized decision and process execution capabilities to maintain a target-optimized production. A method for AI-based storage-location- and material-handling-optimization to achieve performance-optimized intralogistics system through continuous monitoring of performance-relevant parameters and influencing factors by using AI (e.g. for pattern recognition) has been developed. To provide the basis to investigate and demonstrate the potentials of autonomously controlled intralogistics in connection with turbulences of production and in combination with AI, an intelligent warehouse involving an indoor localization system, smart bins, manual, semi-automated/collaborative and autonomous transport systems has been developed and implemented at Werk150, the factory on campus of ESB Business School (Reutlingen University). This scenario, which has been integrated into graduate training modules, allows the analysis and demonstration of different measures of intralogistics to cope with turbulences in production involving amongst others storage and material provision processes. The target fulfilment of the applied intralogistics measures to master arising turbulences is assessed based on the overall performance of production considering lead times and adherence to delivery dates. By applying artificial intelligence (AI) algorithms the intelligent logistical objects (smart bin, transport systems, etc.) as well as the entire logistics system should be enabled to improve their decision and process execution capabilities to master short-term turbulences in the production system autonomously.
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.
Today's logistics systems are characterized by uncertainty and constantly changing requirements. Rising demand for customized products, short product life cycles and a large number of variants increases the complexity of these systems enormously. In particular, intralogistics material flow systems must be able to adapt to changing conditions at short notice, with little effort and at low cost. To fulfil these requirements, the material flow system needs to be flexible in three important parameters, namely layout, throughput and product. While the scope of the flexibility parameters is described in literature, the respective effects on an intralogistics material flow system and the influencing factors are mostly unknown. This paper describes how flexibility parameters of an intralogistics system can be determined using a multi-method simulation. The study was conducted in the learning factory “Werk150” on the campus of Reutlingen University with its different means of transport and processes and validated in terms of practical experiments.
Coopetitive endeavors offer valuable strategic options for firms. Yet, many of them are failure-prone as partners must balance collective and private interest. While interpartner trust is considered central for alliance success, paradoxically, the role and dynamics of trust is still not understood. We synthesize a computational model, capturing relational dynamics of an alliance, encompassing coevolution of trust, partner contributions, and (relative) alliance interactions. Analyzing alliance dynamics using simulation we find and explore a tipping boundary, separating a regime of alliance failure and success. We identify implications for collaborative (aspirations) and private strategies (openness). Our analyses reveal that strategies informed by a static mental model of partner trust, contributions, and openness tend to yield subpar alliance results and hidden failure-risk. We discuss implications for management theory.
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.
Stellenausschreibungen sind ein wichtiges Mittel, um Rollen von Controllern auf dem Arbeitsmarkt zu kommunizieren. Stellenanzeigen öffnen ein Fenster zu dem, was Firmen als Rollen für ihre Controller wahrnehmen. Welche Rollen Stellenanzeigen kommunizieren, ist bisher nicht bekannt. Unter Verwendung einer großen Stichprobe von 889 Stellenanzeigen und eines Text-Mining-Ansatzes zeigen wir, dass es offenbar eine Mischung verschiedener Rollentypen mit einem starken Fokus auf einen eher klassischen Rollentyp gibt, die Watchdog-Rolle. Personen mit Business-Partner-Eigenschaften werden dagegen häufiger für Führungspositionen oder in Familienunternehmen und kleinen und mittleren Unternehmen (KMU) gesucht. Die Ergebnisse stellen die derzeitige Rollen-diskussion für Controller als Business Partner in der Praxis und in einigen Bereichen der Wissenschaft in Frage.
Veränderungen der Rolle von Controllern in Großkonzernen - Ergebnisse einer empirischen Erhebung
(2021)
Die anhaltende Diskussion über die Rolle von Management Accountants (MA) führt häufig dazu, dass die Rolle des Business Partners (BP) als die Rolle der Wahl angesehen wird. Dennoch scheinen viele Wissenschaftler und Praktiker davon auszugehen, dass diese Rolle den Managern und MA klar ist, dass sie für sie sinnvoll ist und alle Manager und MA ihr zustimmen und sie umsetzen. Unstimmigkeiten zwischen der tatsächlichen Rolle, der wahrgenommenen und der erwarteten Rolle könnten zu Identitäts- und Rollenkonflikten führen. Dieser Beitrag basiert auf einer quantitativen empirischen Studie in einem großen deutschen High-Tech-Unternehmen im Jahr 2019, dessen Top-Management sich für die Einführung der BP-Rolle entschied.
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.
Rapidly growing population and increasing amount of shipments induced by the e-commerce are two of the main reasons for the constantly rising urban freight traffic. Cities are therefore overwhelmed by a growing stream of goods and the available infrastructure, shared between people and goods traffic, often reached its maximum capacity. Phenomena such as traffic congestion, pollution and lack of space are direct consequences of this trend and their impact on the quality of life in the city is not negligible. City administrations are keen to evaluate innovative city logistics concepts and adopt alternative solutions, to overcome the challenges posed by such a dynamic environment, constrained in existing infrastructure. In this paper, a heuristic method based on the utility analysis is presented. Thanks to a modular approach accounting for stakeholders´ requirements, possible different scenarios and available technologies, the development of new city logistic concepts is supported. The proposed method is then applied to a case study concerning the city of Reutlingen (Germany). Results are presented and a brief discussion leads to the conclusion.
Milk-run systems are becoming more and more popular when it comes to in-plant material supply. Planning and dimensioning such a system poses challenges, which are difficult to overcome, especially in scenarios characterized by a large number of hard constraints and by well-established processes. This paper is set to ease the task of the planner by presenting an innovative flexible method for the planning and dimensioning of in-plant milk-run systems in high constrained scenarios. After an overview on tugger train systems and existing planning methods, an extensive description of the new method will be given. The new method proposed will be critically analyzed and discussed before suggesting forthcoming research.
Real estate markets are known to fluctuate. The real estate market in Stuttgart, Germany, has been booming for more than a decade: square-meter price hit top levels and real estate agents claim that market prices will continue to increase. In this paper, we test this market understanding by developing and analyzing a system dynamics model that depicts the Stuttgart real estate market. Simulating the model explains oscillating behavior arising from significant time delays and endogenous feedback structures – and not necessarily oscillating interest rates, as market experts assume. Scenarios provide insights into the system's behavior reacting to changes exogenous to the model. The first scenario tests the market development under increasing interest rates. The other scenario deals with possible effects on the real estate market if the regional automotive economy suffers from intense competition with new market players entering with alternative fuel vehicles and new technologies. With a policy run we test market structure changes to eliminate cyclical effects. The paper confirms that the business cycle in the Stuttgart real estate market arises from within the system's underlying structure, thus emphasizing the importance of understanding feedback structures.
In 2016, German car manufacturer the Audi Group (AUDI AG) was working on an expanding array of digital innovations. The goals of these innovations varied, and included strengthening customer- and employee-facing processes, digitally enhancing existing products, and developing new, potentially disruptive business models. Audi’s IT unit was critical to each of these efforts. Based on personal interviews with 11 IT- and non-IT executives at Audi, this case examines the different ways in which digitization can help to enhance and transform an organization’s processes, products, and business models. The case also highlights the challenges that arise as large companies “digitize.”