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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.
Today 40 Gbps is in development at IEEE 802.3bq over four pair balanced cabling. In this paper, we describe a transmission experiment of 25 Gbps enabling either a single pair transmission of 25 Gbps over a 30 meter balanced cabling channel, or a 100 Gbps transmission via a four-pair balanced channel. A scalable matrix modeling tool is introduced which allows the prediction of transmission characteristics of a channel taking mode conversion into account . We applied this tool to characterize PCB-channels including the magnetics and PCB for a four-pair 100 Gbps transmission. We evaluated prototype cables and connecting hardware for frequencies up to 2 GHz and beyond. Finally we investigated possible line encoding schemes and provide measurement results of a transmission over 30 m with a data rate of 25 Gbps per twisted pair.
The 21st century: an era where emojis and hashtags find their way into every sentence, where taking selfies, live tweeting and mining bitcoin are the norm, and where Insta-culture dictates what we say and do. This is the era into which the digital native was born. With so many changes in every aspect of our lives, how is it that one of the most influential aspects, our education, has remained unchanged? Our education system not only fails to appeal to today’s students, but more importantly, it fails to equip them with the skills required in the 21st Century. It is thus of no surprise that industries feel graduates entering the workplace lack skills in critical thinking, problem solving and self-directed learning. AI, machine learning and big data: Tools and mechanisms we so eagerly incorporate to create smart factories yet are hesitant to use elsewhere. Gamification and games have shown great results in education and training; with most research suggesting a stronger focus on personalization and adaptation. When combined with analytics and machine learning, the potential of games is yet to be realized. A real-time adaptive game would not only always present an appropriate degree of challenge for the individual but would allow for a shift in focus from the recitation of facts, to the application of information filtered to solve the particular problem at hand. South Africa, a country faced with a severe skills gap, could benefit greatly from games. If used correctly, they may just offer a desperately needed contribution toward equipping both current and future employees with the skills needed to survive in the 21st century. This paper explores the feasibility of using such games for enhanced knowledge dissemination and the upskilling of the workforce.
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.
The members of the European TRIZ Campus (ETC) have been learning from and working together with many honorable members of MATRIZ Official for many years and feel very connected to the official International TRIZ Association.
To further spread the TRIZ methodology and TRIZ teaching in the European area in the past 12 months the ETC has put a lot of thought in how making TRIZ accessible to a broader audi-ence and getting more professionals in touch with the methodology was one of the focal points.
To this end, we have developed new formats such as the "Trainer Day" to support trainers on their way into practice. We have drawn up detailed quality guidelines for the teaching of the TRIZ methodology, which are intended to provide orientation for the design of training classes and docu-mentation. We strive for exchange with representatives of "neighbouring" methods such as Six sigma, Lean, DFMA and Design Thinking to indicate synergies and added value among methods and approaches of different kinds. We are testing formats for community building, in order to connect users of all places more strongly with the TRIZ methodology through communication and information of-fers. If TRIZ users feel alone in their organizations, the exchange outside their organi-zation helps them to keep up with the TRIZ methodology. Moreover, the ETC strives to increase the ability to communicate the benefits of TRIZ-usage inside organizations. We discuss, how to reach teachers and students of all age, to make them the unique way of inventive thinking accessible.
In our paper we want to give other MATRIZ Official members insights and share our experi-ences and best practices with our fellow MO members.
The high system flexibility necessary for the full automation of complex and unstructured tasks leads to increased complexity, thus higher costs. On the other hand, the effectiveness and performance of such systems decrease, explaining the unfulfilled potential of robotcs in sectors such as intralogistics, where the benefits of a robotic solution rarely justify its costs. Taking the distance from the false idea that a task should be either fully automated, or fully manual, this aper presents a method for design of a lean human-robot interaction (HRI) withe the objective of the "right level of automation", where functions are divided among human and automated agends, so that the overall process gains in performances and/or costs. ... The 10 progressive steps of the method are presented and discussed with reference to their graphical tool: the House of Quality Interaction.
The financial crisis of 2007-2010 was probably one of the greatest, most lustrous black-swan events that people of our generation(s) will experience – and at its heart, it was a dynamic phenomenon. It is stated in the vision of the System Dynamics Society that we aspire to transform society by influencing decision-making. Yet, it seems as if system dynamics did not play any significant role in this crisis: we did not examine the markets, we did not provide insights to banks, and we did not warn governments or the people. In our presentation we describe the dynamics involved in a housing bubble, and describe what made the last one different. With the insights gained from this exercise we conclude that, from a system dynamics perspective, the dimension of the financial crisis of 2007-2009 was eminently foreseeable, which will lead us to pose the following question: where were we as a field while this crisis was unfolding, why were we not active players? We present a range of potential answers to this question, hoping to provoke some reflection… and maybe some (re)action.
Blockchain is a technology for the secure processing and verification of data transactions based on a distributed peer-to-peer network that uses cryptographic processes, consensus algorithms, and backward-linked blocks to make transactions virtually immutable. Within supply chain management, blockchain technology offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. However, its complexity requires future employees to have comprehensive knowledge regarding the functionality of blockchain-based applications in order to be able to apply their benefits to scenarios in supply chain and production. Learning factories represent a suitable environment allowing learners to experience new technologies and to apply them to virtual and physical processes throughout value chains. This paper presents a concept to practically transfer knowledge about the technical functionality of blockchain technology to future engineers and software developers working within supply chains and production operations to sensitize them regarding the advantages of decentralized applications. First, the concept proposes methods to playfully convey immutable backward-linked blocks and the embedment of blockchain smart contracts. Subsequently, the students use this knowledge to develop blockchain-based application scenarios by means of an exemplary product in a learning factory environment. Finally, the developed solutions are implemented with the help of a prototypical decentralized application, which enables a holistic mapping of supply chain events.
Lean Management hat in viele Unternehmen Einzug gehalten. Lean Konzepte stellen neue Anforderungen an die Art und Struktur der benötigten Kosteninformation, welche von traditionallen Kostenrechnungssystemen nicht unmittelbar erfüllt werden. Vertreter eines „Lean Accounting“ schlagen deshalb teils radikale Änderungen und eine Vereinfachung der Kostenrechnung vor. Der Beitrag diskutiert die Beschränkungen der traditionellen Kostenrechnung bei der Umsetzung von Lean Management und stellt ausgewählte Ansätze eines „Accounting for Lean“ vor. Die Analyse zeigt, dass Ansätze des Lean Accounting zu eng fokussiert sind und die in der Praxis vorhandene Pluralität der Kostenrechnungsfunktionen nicht adäquat abbilden können. Eine radikale Neugestaltung bestehender Kostenrechnungssysteme wird deshalb als unrealistisch und unbegründet verworfen. Der Beitrag entwickelt alternative Vorschläge, wie Konzepte des Lean Managements und die dafür benötigte Kosteninformation in traditionellen Kostenrechnungssystemen integriert werden können.
Im Fokus der AG stand in erster Linie die Auseinandersetzung mit Konzepten und Praxismodellen aus den Lehrangeboten der Sprachzentren ... Es ging ... um Themen und Aspekte, die noch nicht in den GER aufgenommen und beschrieben sind, um die Grenzen und Lücken des GER; die das Thema des 6. Bremer Symposiums waren : interkulturelle, soziale, strategische und mediatorische Kompetenzen.
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.
The supply of customer-specific products is leading to the increasing technical complexity of machines and plants in the manufacturing process. In order to ensure the availability of the machines and plants, maintenance is considered as an essential key. The application of cyber-physical systems enables the complexity to be mastered by improving the availability of information, implementing predictive maintenance strategies and the provision of all relevant information in real-time. The present research project deals with the development of a cost-effective and retrofittable smart maintenance system for the application of ultraviolet (UV) lamps. UV lamps are used in a variety of applications such as curing of materials and water disinfection, where UV lamps are still used instead of UV LED due to their higher effectiveness. The smart maintenance system enables continuous condition monitoring of the UV lamp through the integration of sensors. The data obtained are compared with data from existing lifetime models of UV lamps to provide information about the remaining useful lifetime of the UV lamp. This ensures needs-based maintenance measures and more efficient use of UV lamps. Furthermore, it is important to have accurate information on the remaining useful lifetime of a UV lamp, as the unplanned breakdown of a UV lamp can have far-reaching consequences. The key element is the functional model of the envisioned cyber-physical system, describing the dependencies between the sensors and actuator, the condition monitoring system as well as the IoT platform. Based on the requirements developed and the functional model, the necessary hardware and software are selected. Finally, the system is developed and retrofitted to a simulated curing process of a 3D printer to validate its functional capability. The developed system leads to improved information availability of the condition of UV lamps, predictive maintenance measures and context-related provision of information.
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.
Im Rahmen der wissenschaftlichen Vertiefung an der Hochschule Reutlingen befasst sich diese Arbeit mit der Untersuchung der Anforderungen und der Machbarkeit zur computergestützten Erkennung der Deutschen Gebärdensprache (DGS) und des deutschen Fingeralphabets. Die Erkenntnisse aus dieser Arbeit dienen als Grundlage zur Entwicklung eines Systems zur Übersetzung von Gebärden der DGS oder des Fingeralphabets in die deutsche Schriftsprache. Zunächst werden grundlegende Informationen zu Geschichte, Aufbau und Grammatik der DGS und des Fingeralphabets aufgeführt. Die Erkennung der Gebärden soll durch optische Bewegungssensoren erfolgen. Hierfür werden unterschieliche Sensortypen betrachtet und verglichen. Im weiteren Verlauf erfolgt die Analyse der benutzerspezifischen und technischen Anforderungen. Erstere basieren auf der Befragung einer Fokusgruppe aus gehörlosen und hörenden Menschen aus dem Bereich der Gehörlosen-, Schwerhörigen- und Sprachbehindertenpädagogik. Abgeleitet aus den Informationen der Anforderungsanalyse ergibt sich, bis zu einem gewissen Grad, die Machbarkeit aus technischer und benutzerspezifischer Sicht. Abschließend erfolgen die Zusammenfassung der Anforderungen, welche an das zu entwickelnde System gestllt werden, sowie eine Handlungsempfehlung für die Entwicklung eines Prototyps.
The aim of this paper is to show to what extent Artificial Intelligence can be used to optimize forecasting capability in procurement as well as to compare AI with traditional statistic methods. At the same time this article presents the status quo of the research project ANIMATE. The project applies Artificial Intelligence to forecast customer orders in medium-sized companies.
Precise forecasts are essential for companies. For planning, decision making and controlling. Forecasts are applied, e.g. in the areas of supply chain, production or purchasing. Medium-sized companies have major challenges in using suitable methods to improve their forecasting ability.
Companies often use proven methods such as classical statistics as the ARIMA algorithm. However, simple statistics often fail while applied for complex non-linear predictions.
Initial results show that even a simple MLP ANN produces better results than traditional statistic methods. Furthermore, a baseline (Implicit Sales Expectation) of the company was used to compare the performance. This comparison also shows that the proposed AI method is superior.
Until the developed method becomes part of corporate practice, it must be further optimized. The model has difficulties with strong declines, for example due to holidays. The authors are certain that the model can be further improved. For example, through more advanced methods, such as a FilterNet, but also through more data, such as external data on holiday periods.
Due to Industry 4.0, the full value creation has the chance to undergo a fundamental technological transformation, the realisation of which, however, requires the commitment of every company for its own benefit. The new approaches of Industry 4.0 are often hardly evaluated, let alone proven, so that SMEs in particular often cannot properly estimate the potentials and risks, and often waiting too long with the migration towards Industry 4.0. In addition, they often do not pursue an integrated concept in order to identify possible potentials through changes in their business models. . As part of the research project "GEN-I 4.0 – Geschäftsmodell-Entwicklung für die Industrie 4.0” ", the ESB Business School at Reutlingen University of Applied Sciences and the Fraunhofer Institute for Industrial Engineering and Organization FHG IAO were engaged by the Baden-Württemberg Foundation from 2016 to 2018 to develop tools and an approach how the local economy can develop digital business models for itself in a methodical, beneficial and targeted manner. Through international analyses and interviews GEN-I 4.0 gained and concretized the knowledge required for the evaluation and selection of solutions and approaches for the transfer to develop digital business models. Together with the know-how of the project partners on Industry 4.0 and business model development, the findings were incorporated into the development of two software tools with which SMEs are shown the potentials of Industry 4.0 for their individual business model, online and in selfassessment, and given a comprehensive structured, concrete approach to development, as well as their individual risk. Users of the tools are supported by the selected platform for the networking of different players to implement innovative business models accompanied by coaching concepts for the companies in the follow-up and implementation of the assessment results.
The early involvement of experiences gained through intelligence and data analysis is becoming increasingly important in order to develop new products, leading to a completely different conception of product creation, development and engineering processes using the advantages that the dedication of the digital twin entails. Introducing a novel stage gate process in order to be holistically anchored in learning factories adopting idea generation and idea screening in an early stage, beta testing of first prototypes, technical implementation in real production scenarios, business analysis, market evaluation, pricing, service models as well as innovative social media portals. Corresponding product modelling in the sense of sustainability, circular economy, and data analytics forecasts the product on the market both before and after market launch with the interlinking of data interpretation nearby in real-time. The digital twin represents the link between the digital model and the digital shadow. Additionally, the connection of the digital twin with the product provides constantly updated operating status and process data as well as mapping of technical properties and real-world behaviours. A future-networking product, by embedded information technology with the ability to initiate and carry out one's own further development, is able to interact with people and environments and thus is relevant to the way of life of future generations. In today's development work for this new product creation approach, on one hand, "Werk150" is the object of the development itself and on the other hand the validation environment. In the next step, new learning modules and scenarios for trainings at master level will be derived from these findings.
Artificial Intelligence (AI) in der Markenführung: Künstliche Neuronale Netze zur Markenimagemessung
(2023)
Da Künstliche Neuronale Netze die Modellierung nichtlinearer und vielschichtiger Beziehungen ermöglichen, befasst sich dieser Beitrag mit deren Einsatzmöglichkeiten für die methodisch anspruchsvolle Analyse und Messung des Markenimages. Zur Veranschaulichung des konzeptionellen Ansatzes wird am empirischen Beispiel des Sportartikelherstellers adidas ein mehrschichtiges Künstliches Neuronales Netz zwischen den Bewertungen spezifischer Markenattribute und der Gesamtbewertung der Marke erzeugt. Auf der Grundlage einer Analyse der Verbindungsgewichte des Künstliches Neuronales Netzes wird die Bedeutung verschiedener Markenattribute für die Markenbewertung gemessen, wodurch sich konkrete Implikationen für die Praxis der Markenführung ableiten lassen.
Demand forecasting intermittent time series is a challenging business problem. Companies have difficulties in forecasting this particular form of demand pattern. On the one hand, it is characterized by many non-demand periods and therefore classical statistical forecasting algorithms, such as ARIMA, only work to a limited extent. On the other hand, companies often cannot meet the requirements for good forecasting models, such as providing sufficient training data. The recent major advances of artificial intelligence in applications are largely based on transfer learning. In this paper, we investigate whether this method, originating from computer vision, can improve the forecasting quality of intermittent demand time series using deep learning models. Our empirical results show that, in total, transfer learning can reduce the mean square error by 65 percent. We also show that especially short (65 percent reduction) and medium long (91 percent reduction) time series benefit from this approach.
The promise of the EVs is twofold. First, rejuvenating a transport sector that still heavily depends on fossil fuels and second, integrating intermittent renewable energies into the power mix. However, it is still not clear how electricity networks will cope with the predicted increase in EVs and their charging demand, especially in combination with conventional energy demand. This paper proposes a methodology which allows to predict the impact of EV charging behavior on the electricity grid. Moreover, this model simulates the driving and charging behavior of heterogeneous EV drivers which differ in their mobility pattern, decision-making heuristics and charging strategies. The simulations show that uncoordinated charging results in charging load clustering. In contrast, decentralized coordination allows to fill the valleys of the conventional load curve and to integrate EVs without the need of a costly expansion of the electricity grid.
Business Process Management (BPM) ist aufgrund seiner Bedeutung für prozessorientierte Unternehmen und den daraus resultierenden Anforderungen hinsichtlich interner Betriebsorganisation und Audits, ein zentraler Bestandteil. Die Einführung und Aufrechterhaltung von BPM stellt jedoch einen erheblichen Aufwand dar, da Prozesse aufgenommen, modelliert und aktuell gehalten werden müssen. Empirische Belege zeigen, dass erfolgreiche Prozessmodellierung dabei eine besondere Herausforderung darstellt, welche häufig nicht zufriedenstellend nachhaltig gelingt. Ein wesentlicher Erfolgsfaktor für die nachhaltige Prozessorientierung in Unternehmen ist somit die konsistente und aktuelle Prozessmodellierung, sowie deren Adaption an externe und interne Veränderungen. Mittels einer Literaturrecherche werden die relevanten Dimensionen zur nachhaltigen Prozessorientierung auf Grundlage der Prozessmodellierung ermittelt. Auf deren Basis wird ein adaptives handlungsorientiertes Framework für die praktische Anwendung in Unternehmen abgeleitet.
The high system flexibility necessary for the full automation of complex and unstructured tasks leads to increased technological complexity, thus to higher costs and lower performance. In this paper, after an introduction to the different dimensions of flexibility, a method for flexible modular configuration and evaluation of systems of systems is introduced. The method starts from process requirements and, considering factors such as feasibility, development costs, market potential and effective impact on the current processes, enables the evaluation of a flexible systems of systems equipped with the needed functionalities before its actual development. This allows setting the focus on those aspects of flexibility that add market value to the system, thus promoting the efficient development of systems addressed to interested customers in intralogistics. An example of application of the method is given and discussed.
According to several surveys and statistics, the great majority of companies previously not accustomed to automation are piloting solutions to automate business processes. Those accustomed to automation also attempt to introduce more of it, focusing on automation-unfriendly processes that remained manual. However, when the decision on what and whether to automate is not trivial for evident reasons, even industry leaders may get stuck on an overwhelming question: where to begin automating? The question remains too often unanswered as state-of-the-art methods fail to consider the whole picture. This paper introduces a holistic approach to the decision-making for investments in automation. The method supports the iterative analysis and evaluation of operative processes, providing tools for a quantitative approach to the decision-making. Thanks to the method, a large pool of processes can be first considered and then filtered out in order to select the one that yields the best value for the automation in the specific context. After introducing the method, a case study is reported for validation before the discussion.
The EU funded project RobLog recently developed a system able to autonomously unload coffee sacks from a standard container. Being the first of its kind, a further development is needed in order for the system to be competitive against manual labor. Financing this development entails a risk, hence a justified skepticism, which can be overcome by the longsighted view of the existing market potential. This paper presents a method to estimate the market potential of autonomous unloading systems for heavy deformable goods. Starting from the analysis of the coffee trade, first the current coffee traffic is investigated in order to calculate the number of autonomous systems needed to handle the imported sacks; Results are validated and the method is extended for the calculation of the potential of other market segments, where the same unloading technology can be applied.
Prior studies ascribed people’s poor performance in dealing with basic systems concepts to different causes. While results indicate that, among other things, domain specific experience and familiarity with the problem context play a role in this stock-flow-(SF-)performance, this has not yet been fully clarified. In this article, we present an experiment that examines the role of educational background in SF-performance. We hypothesize that SF-performance increases when the problem context is embedded in the problem solver’s knowledge domain, indicated by educational background. Using the square wave pattern and the sawtooth pattern tasks from the initial study by Booth Sweeney and Sterman (2000), we design two additional cover stories for the former, the Vehicle story from the engineering domain and the Application story from the business domain, next to the original Bathtub story. We then test the three sets of questions on business students. Results mainly support our hypothesis. Interestingly, participants even do better on a more complex behavioral pattern from their knowledge domain than on a simpler pattern from more distant domains. Although these findings have to be confirmed by further studies, they contribute both to the methodology of future surveys and the context familiarity discussion.
SF-failure, the inability of people to correctly determine the behavior of simple stock and flow structures is subject of a long research stream. Reasons for SF-failure can be attributed to different reasons, one of them being lacking domain specific experience, thus familiarity with the problem context. In this article we present a continuation of an experiment to examine the role of educational background in SF-performance. We base the question set on the Bathtub Dynamics tasks introduced by Booth Sweeney and Sterman (2000) and vary the cover stories. In this paper we describe how we developed and tested a new cover story for the engineering domain and implemented the recommendations from a prior study. We test three sets of questions with engineering students which enables us to compare the results to a previous study in which we tested the questions with business students. Results mainly support our hypothesis that context familiarity increases SF-performance. With our findings we further develop the methodology of the research on SF-failure.
It is assumed that more education leads to better understanding of complex systems. Some researchers claim, however, find indications that simple mechanisms like stocks and flows are not well understood even by people who have passed higher education. In this paper, we test people’s understanding of complex systems with the widely studied stock-and-flow (SF) tasks (Booth Sweeney and Sterman 2000). SF tasks assess people’s understanding of the interplay between stocks and flows. We investigate SF failure of domain experts and novices in different knowledge domains. In particular, we compare performance on the original study’s Bathtub task with the square wave pattern (Booth Sweeney and Sterman 2000) with two alternative cover stories from the engineering and business domains on different groups of business and engineering students from different semesters. Further, we show that, while engineering students perform better than business students, with progressing in higher education, students seem to lose the capability of dealing with simple SF tasks from domains other than their field. We thus find hints on déformation professionelle in higher education.
Fundamentale Veränderungen der heutigen Arbeitswelt stellen Menschen, Systeme, Prozesse und ganze Organisationen vor erhebliche Herausforderungen. Der Faktor Mensch leistet in allen Bereichen dieses Wirkgefüges einen essentiellen Beitrag zum Wettbewerbsvorteil vieler produzierender Unternehmen am Standort Deutschland. Der Wandel von Automatisierung zu selbststeuernden Unternehmen geht dabei nicht spurlos an dem wandlungsfähigsten Glied dieses Gefüges, dem Menschen, vorüber. Belastungsarten verändern sich, singuläre Bewältigungsstrategien genügen nicht mehr, um einen optimalen Beanspruchungszustand jedes einzelnen Individuums zu erreichen und gleichzeitig das höchstmögliche Potenzial zu schöpfen. Das Belastungs- und Beanspruchungscockpit bildet einen Lösungsansatz zur systematischen und durchgängigen Bewertung von Belastungszuständen und der individuellen Beanspruchung von Beschäftigten an Montagearbeitsplätzen. Es liefert in Echtzeit Informationen zum Belastungs- und Beanspruchungszustand des Mitarbeiters und kann mit Ergonomiebewertungsverfahren verknüpft werden. Der Aspekt der Multidimensionalität umfasst die Bewertung verschiedener Indikatoren unter Betrachtung ihrer Wirkzusammenhänge.
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.
As "the most international company on earth", DHL Express promised to deliver packages between almost any pair of countries within a defined time-frame. To fulfill this promise, the company had introduced a set of global business and technology standards. While standardization had many advantages (improving service for multinational customers, faster response to changes in import/export regulations, sharing of best practices etc.), it created impediments to local innovation and responsiveness in DHL Express' network of 220 countries/territories. Reconciling standardization-innovation tradeoffs is a critical management issue for global companies in the digital economy.
This case describes one large, successful company's approach to the tradeoff of standardization versus innovation.
In 2013, Royal Philips was two years into a daunting transformation. Following declining financial performance, CEO Frans van Houten aimed to turn the Dutch icon into a "high-performing Company" by 2017. This case study examines the challenges of the business-driven IT transformation at Royal Philips, a diversified technology company. The case discusses three crucial issues. First, the case reflects on Philips’ aim at creating value from combining locally relevant products and services while also leveraging its global scale and scope. Rewarded and unrewarded business complexity is analyzed. Second, the case identifies the need to design and align multiple elements of an enterprise (organizational, cultural, technical) to balance local responsiveness with global scale. Third, the case explains the role of IT (as an asset instead of a liability) in Philips’ transformation and discusses the new IT landscape with its digital platforms, and the new practices to create effective business-IT partnerships.
Because of saturated markets and of the low profit margins in the sales of cars, car manufacturers focus more and more on profitable product related services. This paper deals with the question how to classify product related services in the automotive industry and which characteristic product related services are offered to the end-users (consumers) in a standardized format. Two research studies on the provided product related services in 2010 und 2017 by 15 car manufacturers and 20 exemplary automotive brands in Germany revealed that the application degree by the OEM (original equipment manufacturers) in these years increased considerably. While in 2010, the average range of services only amounted to 33%, the value in the automotive industry increased until 2017 to 57%.
Classification model of supply chain events regarding their transferability to blockchain technology
(2021)
The blockchain technology represents a decentralized database that stores information securely in immutable data blocks. Regarding supply chain management, these characteristics offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. In this context, first token-based mapping approaches exist to transfer certain supply chain events to the blockchain, such as the creation or assembly of parts as well as their transfer of ownership. However, the decentralized and immutable structure of blockchain technology also creates challenges. In particular, the scalability, storage capacity, and the special requirements for storage formats make it currently impossible to map all supply chain events unrestrictedly on the blockchain. As a first step, this paper identifies important supply chain events for different use cases combining blockchain technology and supply chain management. Secondly, the supply chain events are classified in terms of their expected technical properties and their relevance for the respective use case. Finally, the identified supply chain events are evaluated regarding their transferability to blockchain technology and a classification model is introduced.
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.
So-called cloud-based management information systems are a fairly new phenomenon in management accounting in recent years. Quite a few companies (and especially their business managers and management accountants) do not always work via the cloud, but with hybrid solutions or on-premise solutions of ERP software such as SAP or Oracle, but often still with "manual" solutions such as Microsoft Excel.
Shorter product life cycles and emerging technologies are changing the circumstances under which the design of assembly and logistics systems has to be carried out. Engineers are in charge of adapting the production in accordance with the underlying product at a higher pace, oversee a more complex system and find the ideal solution for a functional work system design as well as social interactions between humans and machines in cyber-physical systems. Such collaborative work systems consider the individual capabilities and potentials of humans and machines to combine them in a manner that assists the operator during his daily work routine. To be able to design such work systems, specific competences such as the ability of integrated process and product planning as well as systems and interface competence are required. Learning factories train students as well as professionals to gain such qualifications by providing a close-to-reality learning environment based on a didactical concept which covers all relevant methods for ergonomic work system design and a state-of-the-art infrastructure. Group-based, activity oriented scenarios enable the participants to put the learnings into their everyday work life. Thereby, learning factories have an indirect impact on the transfer of proven best practices to the industry.
Competing logics in evaluating employee performance : building compromises through conventions
(2015)
Current research argues that competing institutional logistics1 can co-exist enduringly and investigates how organizations cope with such institutional complexity (Greenwood et al. 2011). Thereby, the role of practices for handling competing logics has been overlooked and it is currently only to limited extent understood how organizations establish compromises between competing logics. Therefore, we investigated the recent performance appraisal reform of a German public sector organization that occurred in 2008 (see also Kozica, Brandl 2015). BAND (the pseudonym for our organization) has been using performance appraisals for several decades, and performance appraisals have already become entrenched instruments (Zeitz, Mittal, McAulay 1999) for handling staff promotion decisions. While BAND accepted the accountability logic of the performance appraisal, the professional logic (which is based on trust and comradeship as a high value of being professional in our organization) is accepted too and BAND has established a fine-grained compromise between the different logics. During the recent reform of the performance appraisal system, however, this compromise has broken up and challenged organizational members to (re-)arrange a compromise. By using French convention school of thinking (Boltanski, Thévenot 2006) we address how BAND copes with conflicting logics by forming compromises in organizational practices. Thereby, we show that the concept of convention is particularly promising for understanding of how organizations deal with institutional complexity. More broadly, our argument contributes to the elaboration of an organizational theory for the institutional logics discussion that explains how organizational and individual actions are interlinked.
Public transport causes in rural areas high costs per passenger and kilometer as the frequency of scheduled busses is low and therefore, many people avoid using public transport. With the trend of moving from urban regions to countryside individual traffic will further increase. To tackle issues of emissions, mobility for young and elderly people and provide economically meaningful public transport a new concept was elaborated in Germany. This consists of (partly) autonomous shuttle busses which are remote controlled. For implementation rural districts of Germany have worked together and set up a three-phase plan consisting of a project with public funding, a highly frequent used pilot region and industrial partners with the commitment and possibilities for necessary investments. The concept promises economical value with respect to installation, service and maintaining costs, it leads to lower barriers for public transport of young and elderly people and ultimately reduces emissions and congestions.
The blockchain technology represents a decentralized database that stores information securely in immutable data blocks. Regarding supply chain management, these characteristics offer potentials in increasing supply chain transparency, visibility, automation, and efficiency. In this context, first token-based mapping approaches exist to transfer certain manufacturing processes to the blockchain, such as the creation or assembly of parts as well as their transfer of ownership. However, the decentralized and immutable structure of blockchain technology also creates challenges when applying these token-based approaches to dynamic manufacturing processes. As a first step, this paper investigates existing mapping approaches and exemplifies weaknesses regarding their suitability for products with changeable configurations. Secondly, a concept is proposed to overcome these weaknesses by introducing logically coupled tokens embedded into a flexible smart contract structure. Finally, a concept for a token-based architecture is introduced to map manufacturing processes of products with changeable configurations.
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.
The automotive industry faces three major challenges – shortage of fossil fuels, politics of global warming and rising competition from new markets. In order to remain competitive companies have to develop more efficient and alternative fuel vehicles that meet the individual requirements of the customers. Functional Integration combined with new Technologies and materials are the key to stable success in this industry. The sustaining upward trend to system innovations within the last ten years confirms this. The development of complex products like automobiles claim skills of various disciplines e.g. engineering, chemistry. Furthermore, these skills are spread all over the supply chain. Hence the only way to stay successful in the automotive industry is cooperation and collaborative innovation. Interdisciplinary and interorganizational development has high demands on cooperation models especially in the automotive industry. In this case study cooperation models are analyzed and evaluated according to their applicability to interdisciplinary, interorganizational development projects in the automotive industry. Following, the research campus ARENA2036 is analyzed. ARENA2036 is an interdisciplinary, interorganizational development project housing automobile manufacturers, suppliers, research establishments and university institutes. Finally, based on interviews with the partners and the precede analyses of cooperation models, suggestions for implementation are given to ARENA2036.
At Reutlingen University in Germany students from different countries and disciplines can learn business English within the framework of a theatre production. In the "Business English Theatre" they work in an international project team staging a play with a business focus and thus improve both their language, social and professional skills.
Die Automobilindustrie steht insbesondere im Forschungs- und Entwicklungsbereich vor großen Herausforderungen. Es zeichnet sich eine deutliche Entwicklung hin zu Systeminnovationen ab, um den gestiegenen Anforderungen des Marktes gerecht zu werden. Voraussetzung hierfür ist die Kooperation von Unternehmen innerhalb der Wertschöpfungskette. In dieser Arbeit werden zunächst auf theoretischer Basis geeignete Kooperationsmodelle ausgewählt, die in einem zweiten Schritt anhand einer Nutzwertanalyse bewertet werden. Die Basis für die Bewertung bilden theoretische Überlegungen, die anhand von Experteninterviews validiert werden. Die Analyse zeigt, dass der Forschungscampus als auch das Branchencluster die beste Eignung aufweist. Abschließend werden die Erkenntnisse an einem Praxisobjekt angewandt.
Production planning and control are characterized by unplanned events or so-called turbulences. Turbulences can be external, originating outside the company (e.g., delayed delivery by a supplier), or internal, originating within the company (e.g., failures of production and intralogistics resources). Turbulences can have far reaching consequences for companies and their customers, such as delivery delays due to process delays. For target-optimized handling of turbulences in production, forecasting methods incorporating process data in combination with the use of existing flexibility corridors of flexible production systems offer great potential. Probabilistic, data-driven forecasting methods allow determining the corresponding probabilities of potential turbulences. However, a parallel application of different forecasting methods is required to identify an appropriate one for the specific application. This requires a large database, which often is unavailable and, therefore, must be created first. A simulation-based approach to generate synthetic data is used and validated to create the necessary database of input parameters for the prediction of internal turbulences. To this end, a minimal system for conducting simulation experiments on turbulence scenarios was developed and implemented. A multi-method simulation of the minimal system synthetically generates the required process data, using agent-based modeling for the autonomously controlled system elements and event-based modeling for the stochastic turbulence events. Based on this generated synthetic data and the variation of the input parameters in the forecast, a comparative study of data-driven probabilistic forecasting methods was conducted using a data analytics tool. Forecasting methods of different types (including regression, Bayesian models, nonlinear models, decision trees, ensemble, deep learning) were analyzed in terms of prediction quality, standard deviation, and computation time. This resulted in the identification ofappropriate forecasting methods, and required input parameters for the considered turbulences.
Production systems are becoming increasingly complex, which means that the main task of industrial maintenance, ensuring the technical availability of a production system, is also becoming increasingly difficult. The previous focus of maintenance efforts on individual machines must give way to a holistic view encompassing the whole production system. Against this background, the technical availability of a production system must be redefined. The aim of this publication is to present different definition approaches of production systems’ availability and to demonstrate the effects of random machine failures on the key figures considering the complexity of the production system using a discrete event simulation.
Forecasting intermittent and lumpy demand is challenging. Demand occurs only sporadically and, when it does, it can vary considerably. Forecast errors are costly, resulting in obsolescent stock or unmet demand. Methods from statistics, machine learning and deep learning have been used to predict such demand patterns. Traditional accuracy metrics are often employed to evaluate the forecasts, however these come with major drawbacks such as not taking horizontal and vertical shifts over the forecasting horizon into account, or indeed stock-keeping or opportunity costs. This results in a disadvantageous selection of methods in the context of intermittent and lumpy demand forecasts. In our study, we compare methods from statistics, machine learning and deep learning by applying a novel metric called Stock-keeping-oriented Prediction Error Costs (SPEC), which overcomes the drawbacks associated with traditional metrics. Taking the SPEC metric into account, the Croston algorithm achieves the best result, just ahead of a Long Short-Term Memory Neural Network.
Der relative Vorteil von Heim- gegenüber Auswärtsteams im Sport - der sogenannte Heimvorteil - ist in mehreren Studien belegt (z.B. Nevill et al., 2002; Jamieson, 2010). Als theoretisch dem Heimvorteil zugrundeliegende Faktoren gelten u.a. folgende: die Zuschauer (durch ihre motivierende Wirkung auf Spieler oder beeinflussende Wirkung auf Schiedsrichter), Reisefaktoren (z.B. die Entfernung bzw. Dauer der Reise und die damit einhergehende Erschöpfung der Spieler) und die Vertrautheit der Heimmannschaft mit der Umgebung (z.B. die Vertrautheit mit dem Stadion und dem Spieluntergrund) (Courneya & Carron, 1992; Nevill et al., 2002). Durch die während der COVID-19-Pandemie stattfindenden Spiele ohne Zuschauer (Geisterspiele) lässt sich erstmals durch ein natürliches Experiment der Einfluss von Zuschauern auf den Heimvorteil betrachten. Ein Überblick über die Studien, die den Heimvorteil in verschiedenen Fußballligen während der pandemiebedingten Geisterspiele untersuchen, findet sich in Leitner et al. (2022).
The world is becoming increasingly digital. People have become used to learning and interacting with the world around them through technology, accelerated even further by the Covid-19 pandemic. This is especially relevant to the generation currently entering education systems and the workforce. Considering digital aids and methods of learning are important for future learning. The increasing online learning needs open the case for integrating digital learning aspects such as serious gaming within education and training systems. Learning factories fall amongst the education and training systems that can benefit from integration with digital learning extensions. Digital capabilities such as digital twins and models further enable the exploration of integrating digital serious games as an extension of learning factories. Since learning factories are meant for a range of different learning, training, and research purposes, such serious games need to be adaptable across stakeholder perspectives to maximize the value gained from the time and cost invested into such design and development. Research into the development of adaptive serious games for multiple stakeholder perspectives must first determine whether such development can be developed that reaches the objectives set for different included stakeholder perspectives. The purpose of this research is to investigate this at the hand of the practical development of a digital adaptive serious game for stakeholder perspectives.
The digital economy poses existential threats to — and game-changing opportunities for — companies that were successful in the pre-digital economy. What will distinguish those companies that successfully transform from those that become historical footnotes? This is the question a group of six researchers and consultants from Boston Consulting Group set out to examine. The team conducted in-depth interviews with senior executives at twenty-seven companies in different industries to explore the strategies and organizational initiatives they relied on to seize the opportunities associated with new, readily accessible digital technologies. This paper summarizes findings from this research and offers recommendations to business leaders responsible for digital business success.