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While there has been increased digitization of private homes, only little has been done to understand these specific home technologies, how they serve consumers, among other issues. “Smart home technology” (SHT) refer to a wide range of artifacts from cleaning aids to energy advisors. Given this breadth, clarity surrounding the key characteristics and the multi-faceted impact of SHT is needed to conduct more directed research on SHT. We propose a taxonomy to help outline the salient intended outcomes of SHT. Through a process involving five iterations, we analyzed and classified 79 technologies (gathered from literature and industry reports). This uncovered seven dimensions encompassing 20 salient characteristics. We believe these dimensions/characteristics will help researchers and organizations better design and study the impacts of these technologies. Our long-term agenda is to use the proposed taxonomy for an exploratory inquiry to understand tensions occurring when personal and sustainability-related outcomes compete.
Sichtprüfungen von Produktoberflächen werden überwiegend von Mitarbeitern ausgeführt, wobei Automatisierungsansätze mit Kamera- und Bildverarbeitungssystemen großes Potenzial zeigen. Auch Cobots werden in Qualitätssicherungsprozesse einbezogen.Im Folgenden werden die Integrationsmöglichkeiten von Cobots in die Sichtprüfung diskutiert und ein Entscheidungsmodell dargestellt, mit dem Sichtprüfungsprozesse auf ihre Cobot-Tauglichkeit überprüft werden können. Das Entscheidungsmodell ist für die direkte Integration in bereits existierende Cobot-Eignungsuntersuchungsverfahren konzipiert und dient als erste strategische Entscheidungshilfe.
Für die digitale 3D-VR-Fabrikplanung sind unterschiedliche Soft- und Hardwaresysteme am Markt verfügbar, die teilweise erhebliche Kompatibilitätsprobleme aufweisen. Für die Bewertung der Hardwareeignung für die 3D-VR-Fabrikplanung wird ein Bewertungssystem vorgestellt, das anhand konkreter Softwareapplikationen und einem passiven 3D-Stereo-Monitor mit Head-Tracking erläutert wird. Es wird dazu auch die Notwendigkeit des Einsatzes von Software-Middleware zur Nutzungssteigerung diskutiert.
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand may be constant and regular for one product, it may be sporadic for another, as well as when demand occurs, it may fluctuate significantly. Forecasting errors are costly and result in obsolete inventory or unsatisfied demand. Methods from statistics, machine learning, and deep learning have been used to predict such demand patterns. Nevertheless, it is not clear for what demand pattern, which algorithm would achieve the best forecast. Therefore, even today a large number of models are used to forecast on a test period. The model with the best result on the test period is used for the actual forecast. This approach is computationally and time intensive and, in most cases, uneconomical. In our paper we show the possibility to use a machine learning classification algorithm, which predicts the best possible model based on the characteristics of a time series. The approach was developed and evaluated on a dataset from a B2B-technical-retailer. The machine learning classification algorithm achieves a mean ROC-AUC of 89%, which emphasizes the skill of the model.
Maintenance is an increasingly complex and knowledge-intensive field. In order to address these challenges, assistance systems based on augmented, mixed, or virtual reality can be applied. Therefore, the objective of this paper is to present a framework that can be used to identify, select, and implement an assistance system based on reality technology in the maintenance environment. The development of the framework is based on a systematic literature review and subject matter expert interviews. The framework provides the best technological and economic solution in several steps. The validation of the framework is carried out through a case study.
This article studies the effects of reverse factoring in a supply chain when the buyer company facilitates its lower short-term borrowing rates to the supplier corporation in return for extended payment terms. We explore the role of interest rate changes, rating changes, and the business cycle position on the cost and benefit trade-off from a supplier perspective. We utilize a combined empirical approach consisting of an event study in Step 1 and a simulation model in Step 2. The event study identifies the quantitative magnitude of central bank decisions and rating changes on the interest rate differential. The simulation computes with a rolling-window methodology the daily cost and benefits of reverse factoring from 2010 to 2018 under the assumption of the efficient market hypothesis. Our major finding is that changes of crucial financial variables such as interest rates, ratings, or news alerts will turn former win-win into win-lose situations for the supplier contingent to the business cycle. Overall, our results exhibit sophisticated trade-offs under reverse factoring and consequently require a careful evaluation in managerial decisions.
Conventional production systems are evolving through cyber-physical systems and application-oriented approaches of AI, more and more into "smart" production systems, which are characterized among other things by a high level of communication and integration of the individual components. The exchange of information between the systems is usually only oriented towards the data content, where semantics is usually only implicitly considered. The adaptability required by external and internal influences requires the integration of new or the redesign of existing components. Through an open application-oriented ontology the information and communication exchange are extended by explicit semantic information. This enables a better integration of new and an easier reconfiguration of existing components. The developed ontology, the derived application and use of the semantic information will be evaluated by means of a practical use case.
Learning factories on demand
(2021)
Learning Factories are research and learning environments that demonstrate new concepts and technologies for the industry in a practical environment. The interaction between physical and virtual components is a central aspect. The mediation and presentation usually occur directly in the learning factory and are thus limited in time and concerning the user group. A learning factory- on-demand- can be provided by dividing and virtualizing the individual components via containers and microservices. This enables both local operation and operation hybrid cloud or cloud systems. Physical components can be mapped either through standardized interfaces or suitable emulators. Using the example of the Learning Factory at Reutlingen University (Werk150), it will be shown how different use cases can be made available utilizing software-based orchestration, thus promoting broader and more independent teaching.
In a networked world, companies depend on fast and smart decisions, especially when it comes to reacting to external change. With the wealth of data available today, smart decisions can increasingly be based on data analysis and be supported by IT systems that leverage AI. A global pandemic brings external change to an unprecedented level of unpredictability and severity of impact. Resilience therefore becomes an essential factor in most decisions when aiming at making and keeping them smart. In this chapter, we study the characteristics of resilient systems and test them with four use cases in a wide-ranging set of application areas. In all use cases, we highlight how AI can be used for data analysis to make smart decisions and contribute to the resilience of systems.
Prior to the introduction of AI-based forecast models in the procurement department of an industrial retail company, we assessed the digital skills of the procurement employees and surveyed their attitudes toward a new digital technology. The aim of the survey was to ascertain important contextual factors which are likely to influence the acceptance and the successful use of the new forecast tool. What we find is that the digital skills of the employees show an intermediate level and that their attitudes toward key aspects of new digital technologies are largely positive. Thus, the conditions for high acceptance and the successful use of the models are good, as evidenced by the high intention of the procurement staff to use the models. In line with previous research, we find that the perceived usefulness of a new technology and the perceived ease of use are significant drivers of the willingness to use the new forecast tool.
Autonomisierung von Shopfloor Management : Der Weg vom analogen zum autonomen Shopfloor Management
(2021)
Neue Technologien der Digitalisierung, Vernetzung und künstlichen Intelligenz werden zunehmend auch im Shopfloor Management (SFM) Einzug halten. Dieser Beitrag beschreibt in vier Stufen, wie sich das klassische SFM über das digitale SFM hin zu einem smarten und autonomen SFM entwickeln könnte. Darauf aufbauend wird diskutiert, welche Auswirkungen der Einsatz dieser neuen Technologien auf die operative Gestaltung der Durchführung eines SFM hätte und welche Konsequenzen somit auf Mitarbeiter und Führungskräfte zukommen würden.*)
Imagine a world in which the search for tomorrow's trends of (software) products is not subject to a long and laborious data search but is possible with a single mouse click. Through the use of artificial intelligence (AI), this reality is made possible and is to be further advanced through research. The study therefore aims to provide an initial overview of the young research field. Based on research, expert interviews, company and student surveys, current application possibilities of AI in the innovation process (defined as Smart Innovation), existing challenges that slow down the further development are discussed in more detail and future application possibilities are presented. Finally, a recommendation for action is made for business, politics and science to help overcome the current obstacles together and thus drive the future of Smart Innovation.
Adaptation of the business model canvas template to develop business models for the circular economy
(2021)
The Business Model Canvas as a template for strategic management serves the development of new or the documentation of existing linear business models. However, the change towards a Circular Economy requires new value creation structures and thus changed business models. To develop business models for circular economies, it is necessary to adapt the existing template, since the actors involved along the value chain take on changed roles. In the context of this paper, a template is presented, based on the existing Business Model Canvas, which allows to develop and document business models for a Circular Economy.
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.
Effektives Risiko-Management sollte neben quantifizierbaren, bekannten Risiken auch Ereignisse berücksichtigen, die entweder in ähnlicher Art bereits eingetreten oder grundsätzlich vorstellbar sind. Für eine Identifikation dieser "Grauen Schwäne" müssen institutionell-organisatorische Voraussetzungen geschaffen und analytisch-konzeptionelle Instrumente bereitgestellt werden.
Trotz Niedrigzinsphase bleibt das Working Capital Management ein wichtiger Treiber für Wertgrößen in Unternehmen und wichtiges Managementinstrument. Unsere Ergebnisse über 115 Unternehmen aus den wichtigsten deutschen Indizes in den Jahren 2011 bis 2017 zeigen, dass effektives Working Capital Management einen positiven Einfluss auf die Rentabilität und den Unternehmenswert haben kann. Gleichzeitig zeigen unsere Ergebnisse aber auch, dass dem Working Capital Management jüngst weniger Aufmerksamkeit zuteilgeworden ist und digitale Innovationen vermutlich noch nicht in dem Umfang zur Effizienzsteigerung eingesetzt werden, wie dies möglich erscheint. Selbst vor dem Hintergrund andauernd niedriger Kapitalmarktzinsen ist dies kritisch zu sehen.
Die zunehmende Technologie- und Produktkomplexität führen dazu, dass sich immer mehr Unternehmen für ihre F&E mit externen Organisationen vernetzen. So entstehen interorganisationale F&E-Projekte, welche temporäre Organisationen darstellen. Forschungsfragen zu diesen Projekten sind u.a. hinsichtlich der Praktiken und Verhaltensregeln offen. Über ein kulturbewusstes Projektmanagement können kooperations- und innovationsförderliche Praktiken und Verhaltensregeln aufgebaut werden, die für diese F&E-Projekte essenziell sind. So ist die Forschungsfrage dieses Beitrags, wie ein projektkulturbewusstes Management interorganisationaler F&E-Projekte erfolgen kann. Dafür wird auf Basis der theoretischen Grundlagen zum F&E-Projektmanagement, zu menschlichen Handlungssystemen und Ebenen der Zusammenarbeit, zu Kultur und Verhalten ein projektkulturbewusstes Management-Modell entwickelt. Das Modell umfasst zwei Teile. Im ersten Teil wird der Bereich aufgezeigt, in welchem sich die Projektkultur entwickelt. Im zweiten Teil wird aufgezeigt, wie die Faktoren für ein wahrscheinlich kooperatives und innovatives Verhalten innerhalb dieses Bereiches gestaltet werden sollten.
This paper takes a holistic view on an IP-traceability process in interorganizational R&D projects, as a particular Open innovation mode, aiming at showing different technologies which can be used in the front and backend of a traceability process and discussing these technologies in terms of their suitability for data from creativity processes in these projects. To achieve this goal a two-stage literature review on different technologies in the context of traceability was conducted. Then, criteria were derived from the characteristics of data from creativity processes and of interorganizational R&D projects, with which the resulting technologies were discussed. At the end, recommendations regarding suitable technologies for tracing individual creativity artifacts in interorganizational R&D projects were given.
Supply chains have become increasingly complex, making it difficult to ensure transparency throughout the whole supply chain. In this context, first approaches came up, adopting the immutable, decentralised, and secure characteristics of the blockchain technology to increase the transparency, security, authenticity, and auditability of assets in supply chains. This paper investigates recent publications combining the blockchain technology and supply chain management and classifies them regarding the complexity to be mapped on the blockchain. As a result, the increase of supply chain transparency is identified as the main objective of recent blockchain projects in supply chain management. Thereby, most of the recent publications deal with simple supply chains and products. The few approaches dealing with complex parts only map sub-areas of supply chains. Currently no example exists which has the aim of increasing the transparency of complex manufacturing supply chains, and which enables the mapping of complex assembly processes, an efficient auditability of all assets, and an implementation of dynamic adjustments.
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.
Distributed ledger technologies such as the blockchain technology offer an innovative solution to increase visibility and security to reduce supply chain risks. This paper proposes a solution to increase the transparency and auditability of manufactured products in collaborative networks by adopting smart contract-based virtual identities. Compared with existing approaches, this extended smart contract-based solution offers manufacturing networks the possibility of involving privacy, content updating, and portability approaches to smart contracts. As a result, the solution is suitable for the dynamic administration of complex supply chains.
This paper studies the power of online search intensity metrics, measured by Google, for examining and forecasting exchange rates. We use panel data consisting of quarterly time series from 2004 to 2018 and ten international countries with the highest currency trading volume. Newly, we include various Google search intensity metrics to our panel data. We find that online search improves the overall econometric models and fits. First, four out of ten search variables are robustly significant at one percent and enhance the macroeconomic exchange rate models. Second, country regressions corroborate the panel results, yet the predictive power of search intensity with regard to exchange rates vary by country. Third, we find higher prediction performance for our exchange rate models with search intensity, particularly in regard to the direction of the exchange rate. Overall, our approach reveals a value-added of search intensity in exchange rate models.
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.
Forschungsfrage: Was sind Motivationen, Bedenken und Karriereerwartungen von Hochschulabsolventen, die sich für eine selbstinitiierte Auslandsentsendung direkt nach dem Studienabschluss entscheiden?
Methodik: Quantitative Befragung unter Absolventen deutscher Hochschulen
Praktische Implikationen: Aus den Ergebnissen lassen sich Maßnahmen zur Gewinnung und Bindung von Hochschulabsolventen als selbstinitiierte Entsandte und damit zur Nutzung des Potenzials der selbstinitiierten Entsendung ableiten.
Problem: Die Covid-19 Pandemie verschärft nicht nur die wirtschaftlichen, sondern auch die öko-sozialen Rahmenbedingungen vieler Unternehmen. Nachhaltiges Handeln ist daher wichtiger denn je. Unternehmen wählen unterschiedliche Wege, um Nachhaltigkeit in das Managementsystem der oberen Führungsebene zu integrieren. Dadurch besteht die Chance, Nachhaltigkeit nicht nur in Form von Einzelmaßnahmen zu sehen, sondern als Element der Strategie- und Organisationsentwicklung zu verstehen. Für die gesamthafte Betrachtung kommen u. a. die Gemeinwohlbilanz (GWB) und die Nachhaltigkeits-Balanced Scorecard (N-BSC) in Betracht, wie die Beispiele von Vaude und der Sparda Bank München, die die GWB nutzen (siehe https://web.ecogood.org/de/die-bewegung/pionier-unternehmen/), sowie Alpha und Axel Springer, die Nachhaltigkeit in ihre BSC integrieren (Hansen/Schaltegger, 2016, S. 207), zeigen.
Ziel: Diskussion der GWB und der N-BSC als Möglichkeiten zur Integration öko-sozialer Aspekte in das Managementsystem.
Methode: Aufzeigen wesentlicher Grundzüge der GWB und N-BSC
F&E-Bereiche nur kostenorientiert zu steuern, wird der immensen Bedeutung von Innovationserfolgen für die Zukunft von Unternehmen nicht gerecht. Ein agiles Innovationsmanagement benötigt ein solides F&E-Performance-Managementsystem als Basis. Entscheidend ist neben der Wahl "richtiger" Methoden und Kennzahlen die Wahrnehmung der Business-Partnerrolle durch die Controller. In diesem Beitrag wird das Innovation Performance Management beispielhaft für WMF konkretisiert.
Purpose – This paper aims to determine the affecting factors of the brand authenticity of startups in social media.
Design/methodology/approach – Using a qualitative method based on a grounded theory approach, this research specifies and classifies the affecting factors of brand authenticity of startups in social media through in-depth semi-structured interviews.
Findings – Multiple factors affecting the brand authenticity of startups in social media are determined and categorized as indexical, iconic and existential cues through this research. Connection to heritage and having credible support are determined as indexical cues. Founder intellectuality, brand intellectuality, commitment toward customers and proactive clear and interesting communications are identified as iconic cues. Having self-confidence and self-satisfaction, having intimacy with the brand and a joyful feeling for interactions with the community around the brand are determined as existential cues in this research. This research furthers previous arguments on a multiplicity of brand authenticity by shedding light on the relationship between the different aspects of authenticity and the form that different affecting factors can be organized together. Consumers eventually evaluate a strengthened perception of brand authenticity through existential cues that reflect the cues of other aspects (iconic and indexical) which passed through the goal-based assessment and self-authentication filter.
Research limitations/implications – The research sampling population can be more diversified in terms of sociodemographic attributes. Due to the qualitative methodology of this research, assessment of the findings through quantitative methods can be considered in future research. Practical implications – Using the findings of this research, startup managers can properly build a perception of authenticity in their consumers’ minds by using alternate factors while lacking major indexical cues such as heritage. This research helps startup businesses to design their brand communications better to convey their authenticity to their audiences.
Originality/value – This research determines the factors affecting the authenticity of startup brands in social media. It also defines the process of authenticity perception through different aspects of brand authenticity.
Interkulturelles Management
(2021)
Kultur lässt sich beschreiben als „kollektive Programmierung des Geistes, die die Mitglieder einer Gruppe oder Kategorie von Menschen von anderen unterscheidet“ (Hofstede/Hofstede/Minkov, S.6). Die Muster des Glaubens, Denkens, Fühlens und Handelns, die diese mentalen Programme oder kulturellen Denkweisen ausmachen, werden von den Gruppenmitgliedern im Rahmen ihres Sozialisierungsprozesses erlernt. Sie sind die gemeinsamen „ungeschriebenen Regeln“, wie Dinge in diesem sozialen Umfeld gehandhabt werden (vgl. Hofstede/Hofstede/Minkov, S.6). Die Art und Weise, wie sich Menschen in einer bestimmten Kultur verhalten, ihre Praktiken und Normen, ist daher nicht willkürlich, sondern wird in hohem Maße von diesen erlernten Prinzipien und Werten beeinflusst. Das Wissen über eine Kultur ermöglicht es, Reaktionen ihrer Mitglieder zu erklären und vorherzusagen (vgl. Lewis, S. XII).
COVID-19 and educational inequality: How school closures affect low- and high-achieving students
(2021)
In spring 2020, governments around the globe shut down schools to mitigate the spread of the novel coronavirus. We argue that low-achieving students may be particularly affected by the lack of educator support during school closures. We collect detailed time-use information on students before and during the school closures in a survey of 1099 parents in Germany. We find that while students on average reduced their daily learning time of 7.4 h by about half, the reduction was significantly larger for low-achievers (4.1 h) than for high-achievers (3.7 h). Low-achievers disproportionately replaced learning time with detrimental activities such as TV or computer games rather than with activities more conducive to child development. The learning gap was not compensated by parents or schools who provided less support for low-achieving students.
Intralogistics operations in automotive OEMs increasingly confront problems of overcomplexity caused by a customer-centred production that requires customisation and, thus, high product variability, short-notice changes in orders and the handling of an overwhelming number of parts. To alleviate the pressure on intralogistics without sacrificing performance objectives, the speed and flexibility of logistical operations have to be increased. One approach to this is to utilise three-dimensional space through drone technology. This doctoral thesis aims at establishing a framework for implementing aerial drones in automotive OEM logistic operations.
As of yet, there is no research on implementing drones in automotive OEM logistic operations. To contribute to filling this gap, this thesis develops a framework for Drone Implementation in Automotive Logistics Operations (DIALOOP) that allows for a close interaction between the strategic and the operative level and can lead automotive companies through a decision and selection process regarding drone technology.
A preliminary version of the framework was developed on a theoretical basis and was then revised using qualitative-empirical data from semi-structured interviews with two groups of experts, i.e. drone experts and automotive experts. The drone expert interviews contributed a current overview of drone capabilities. The automotive experts interview were used to identify intralogistics operations in which drones can be implemented along with the performance measures that can be improved by drone usage.
Furthermore, all interviews explored developments and changes with a foreseeable influence on drone implementation.
The revised framework was then validated using participant validation interviews with automotive experts.
The finalised framework defines a step-by-step process leading from strategic decisions and considerations over the identification of logistics processes suitable for drone implementation and the relevant performance measures to the choice of appropriate drone types based on a drone classification specifically developed in this thesis for an automotive context.
Die Corona-Pandemie hat zu einer Einschränkung des Alltags der medizinischen Versorgung geführt. Das zeigt sich u.a. in zum Teil erheblichen Zugangsbeschränkungen zu Krankenhäusern und Praxen mit stark reduzierter Einbestellung von Patienten, der Einhaltung von gesteigerten Hygienemaßnahmen mit entsprechend längeren Wartezeiten, dem Zugangsverbot für Begleitpersonen und nicht zuletzt der Angst vieler Patienten vor einer Ansteckung bei einem Aufenthalt in medizinischen Bereichen. Folge dessen war und ist, dass ein deutlich wahrnehmbarer Rückgang der Patientenzahlen in den Krankenhausambulanzen und Praxen zu verzeichnen war. Davon war die Augenheilkunde als Fachdisziplin mit einem hohen Anteil an ambulanten und geplanten, chirurgischen Eingriffen in besonderem Maße betroffen.
This article studies the hidden blemishes of two benchmark rulings of the European Court of Justice (ECJ). In 2015 and 2018, the ECJ approved two unconventional monetary instruments, among others ‘Outright Monetary Transactions’ and the ‘Public Sector Purchase Program’. Yet, there is a vigorous debate about both monetary operations in law and economics. In this interdisciplinary article, we address law and economic arguments in order to elucidate insights to the legal community. In particular, we elaborate on the legal implications of a variety of concerning issues such as public policy interference, effect on wealth redistribution, erosion of democratic legitimacy and lack of effectiveness of monetary policy. These topics remain disregarded in the ECJ rulings. Consequently, the verdicts do not identify the economic boundaries of the European Central Bank’s mandate appropriately.
Das Weltwirtschaftswachstum der vergangenen Jahrzehnte war durch die Dynamik der Digitalisierung und Globalisierung in den Lieferketten geprägt. Die Corona-Pandemie hat die Abhängigkeit und Verletzlichkeit der Lieferketten offengelegt. Trotz einer Vielzahl verbindlicher Standards haben Unternehmen die Digitalisierung und Arbeitsteilung auch für regulatorische Arbitrage genutzt. Einerseits erhöht das die Effizienz der Wirtschaft - was mithin ökologische Ressourcen schont - andererseits werden damit internationale Standards konterkariert. Globalisierung und Digitalisierung sind Segen und Fluch zugleich.
In this paper, we examine the political gridlock in reforming the Economic and Monetary Union. We utilize a two–stage game with imperfect information in order to study the optimal sequencing. The main results are: first, optimal sequencing requires for incompliant Member States a default option in stage–two, which in principle is related to the today's fiscal architecture (EMU-I). Second, we show that compliant countries prefer a reform equilibrium today if and only if they have a free choice about the preferred fiscal architecture at the end — either EMU-II with binding European coordination or EMU-I related to Maastricht. Noteworthy, our sequencing approach works for any design of the EMU-II architecture.
This article studies the renewed interest surrounding sustainable public finance and the topic of tax evasion as well as the new theory of information inattention. Extending a model of tax evasion with the notion of inattention reveals novel findings about policy instruments that can be used to mitigate tax evasion. We show that the attention parameters regarding tax rates, financial penalty schemes and income levels are as important as the level of the detection probability and the financial penalty incurred. Thus, our theory recommends the enhancement of sustainability in public policy, particularly in tax policy. Consequently, the paper contributes both to the academic and public policy debate.
Das Projekt DigiTraIn 4.0 hat ein Beratungskonzept entwickelt und erprobt, das Unternehmen bei der erfolgreichen Digitalisierung ihrer Arbeitswelt unterstützt. Das Beratungskonzept basiert auf vier anwendungsorientierten Instrumenten: Der Digitalisierungsatlas bildet die Digitalisierung der Arbeitswelt in all ihren Dimensionen ab und ermöglicht es, die Notwendigkeit sowie Chancen und Risiken der Veränderungen zu verstehen. Hierauf aufbauend können Unternehmen mit dem Digitalisierungsindex ihren aktuellen Ist-Digitalisierungsgrad der Arbeitswelt individuell bestimmen. Der individuelle Digitalisierungsgrad dient als Ausgangspunkt für den Digitalisierungskompass, der es dem Unternehmen ermöglicht, die Soll-Vorstellung der digitalen Arbeitswelt zu illustrieren und eine unternehmensspezifische Transformationsagenda abzuleiten. Der Beratungsprozess und die Entwicklung der zentralen Instrumente werden in diesem Beitrag dargestellt.
Kopainsky et al., (2020) examines intended and unintended transition effects of the Swiss food system on the system's structure and the environment. Kopainsky et al.'s research refers to studies on and is embedded in research streams in global health (Jamison et al., 2013) and sustainable food systems (Willett et al., 2019). It also addresses many of Steffen et al.'s (2015) planetary boundaries, the United Nations' (2015) sustainability goals (SDGs), and potentially could address how they are interrelated, following Randers et al. (2019). It is furthermore embedded in research on natural and human systems, particularly in the intertwined business, supply and demand, governance, ecological and health feedback loops (Swinburn et al., 2019). This feedback view enhances understanding and assessment of drivers towards improving human and ecological health and mitigating climate change.
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.
Today, many industrial tasks are not automated and still require human intervention. One of these tasks is the unloading of oversea containers. After the end of transportation to the sorting center, the containers must be unloaded manually for further sending the parcels to the recipients. A robot-based automatic unloading of containers was therefore researched. However, the promising results of the system developed in these projects could not be commercialized due to problems with its reliability. Mechanical, algorithmic or other limitations are possible causes of the observed errors. To analyze errors, it is necessary to evaluate the results of the robot’s work without complicating the existing system by adding new sensors to it. This paper presents a reference system based on machine learning to evaluate the robotics grasps of parcels. It analyzes two states of the container: before and after picking up one box. The states are represented as a point cloud received from a laser scanner. The proposed system evaluates the success of transferring a box from an overseas container to the sorting line by supervised learning using convolutional neural networks (CNN) and manual labeling of the data. The process of obtaining a working model using a hyperband model search with a maximum classification error of 3.9 % is also described.
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand may be constant and regular for one product, it may be sporadic for another, as well as when demand occurs, it may fluctuate significantly. Forecasting errors are costly and result in obsolete inventory or unsatisfied demand. Methods from statistics, machine learning, and deep learning have been used to predict such demand patterns. Nevertheless, it is not clear for what demand pattern, which algorithm would achieve the best forecast. Therefore, even today a large number of models are used to forecast on a test period. The model with the best result on the test period is used for the actual forecast. This approach is computationally and time intensive and, in most cases, uneconomical. In our paper we show the possibility to use a machine learning classification algorithm, which predicts the best possible model based on the characteristics of a time series. The approach was developed and evaluated on a dataset from a B2B-technical-retailer. The machine learning classification algorithm achieves a mean ROC-AUC of 89%, which emphasizes the skill of the model.
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.
Digitalization increases the pressure for companies to innovate. While current research on digital transformation mostly focuses on technological and management aspects, less attention has been paid to organizational culture and its influence on digital innovations. The purpose of this paper is to identify the characteristics of organizational culture that foster digital innovations. Based on a systematic literature review on three scholarly databases, we initially found 778 articles that were then narrowed down to a total number of 23 relevant articles through a methodical approach. After analyzing these articles, we determine nine characteristics of organizational culture that foster digital innovations: corporate entrepreneurship, digital awareness and necessity of innovations, digital skills and resources, ecosystem orientation, employee participation, agility and organizational structures, error culture and risk-taking, internal knowledge sharing and collaboration, customer and market orientation as well as open-mindedness and willingness to learn.
This study determines the correlation between industry-specific success patterns of Germany’s engineering industry and the business models applied within. In order to identify this correlation, the following objectives are addressed within the framework of this paper: (1) identification and description of business models used by Germany’s engineering industry; (2) analysis of industry-specific success patterns of Germany’s engineering industry by the usage of Key-Performance-Indicators (KPIs); and (3) determination of correlation between the KPIs and Germany’s engineering industry’s business models’ effectiveness. These objectives are mainly achieved by literature research and expert surveys. The findings highlight the KPIs (overall 41) that are relevant for the respective business models. This enables a better understanding of the interrelationships of the business model, in order to derive relevant conclusions. The paper contributes to the literature as it advances this field of research in Germany, and it is one of the first studies to examine the relationship between business models and industry-specific success patterns with relevant KPIs.
Kontrolle bei New Collaboration Work: Über die Fantasien von Purpose, Wachstum und Zugehörigkeit
(2021)
Derzeit geht es in vielen Unternehmen darum, Zusammenarbeit zukunftsfähig zu gestalten: Hierarchien werden flacher, Teams stärker selbstorganisiert, und Prozesse wie agile Frameworks regeln die Abläufe.
Was aber passiert in solchen kollaborativen Arbeitskontexten, wenn es um Kontrolle geht? In hierarchischen Organisationen ist das Thema vergleichsweise einfach zu greifen: Führungskräfte kontrollieren Arbeitsprozesse über Arbeitsteilung und -zuweisung, über disziplinarische Hoheit und motivierendes Führungsverhalten (Mitarbeitergespräche, Kritik, Lob).
Organisationale Identität in digitalisierten Arbeitswelten: Grundlagen für gelingende Kooperation
(2021)
Organisationen bilden Identitäten aus und beantworten dabei die Fragen „Wer sind wir? Und wer sind wir nicht?“. Vorstellungen zur organisationalen Identität gehen zunächst von traditionellen Organisationen aus. Durch die Digitalisierung können bisher integrierte Aufgaben stärker modularisiert werden, sodass die Koordination der organisatorischen Gesamtaufgabe stärker sach- und weniger personenorientiert erfolgt. Zudem lassen sich organisationale Aufgaben zunehmend projektorientiert und virtuell abbilden, sodass externe Aufgabenträger leichter integriert werden können. Unsere Vorstellungen zu Organisationsgrenzen und -mitgliedschaften verändern sich dadurch. Dies wirft die Frage auf, inwiefern sich in solchen sach- und projektorientierten, grenzaufgelösten Organisationen eine gemeinsame organisationale Identität ausbildet. Im Beitrag wird argumentiert, dass sich die Wege der Identitätsentwicklung verändern, die Funktionen der organisationalen Identität für gelingende Kooperation aber erhalten bleiben.
Arbeitswelten strategisch entwicklen: mit den DigiTraIn-Instrumenten zur digitalen Transformation
(2021)
Der Weg in die digitale Arbeitswelt ist für viele Unternehmen eine herausfordernde und komplexe Transformation. Um diesen Weg erfolgreich zu beschreiten, benötigen Unternehmen funktionierende Managementinstrumente. Im Projekt DigiTraIn 4.0 wurden vier Instrumente für eine gelingende Transformation in das digitale Arbeiten entwickelt und in der Unternehmenspraxis erprobt. Diese Instrumente werden im vorliegenden Beitrag, ausgehend von der Zielsetzung des Projekts, einführend dargestellt. Zudem wird ein Überblick über die weiteren Beiträge in diesem Buch gegeben, in denen die Instrumente im Detail erläutert werden und spezifische Aspekte des Wandels in die digitale Arbeitswelt im Fokus stehen.
Die digitale Transformation und gesellschaftliche Entwicklungen verändern die Arbeitswelt nicht erst seit der Corona-Pandemie. Kommunikation, Kreativität und agile Vorgehensweisen in der Arbeitsorganisation rücken in den Vordergrund und werden gerade in Krisenzeiten zu wichtigen Stärken von Unternehmen. Der Grad der Selbstorganisation von Teams steigt und erfordert mehr individuelle Selbstorganisation der Beschäftigten. Dies birgt neben vielen Chancen auch Gesundheitsrisiken.
Der Report beleuchtet die agile Organisation und weitere moderne Organisationsmodelle wie die Soziokratie, die Holokratie und die evolutionäre Organisation unter dem Gesundheitsaspekt. All diese Organisationsmodelle sind gekennzeichnet durch die Abflachung von Hierarchien, eine stärkere Sinnorientierung, mehr Flexibilität sowie die Integration von Leistungspotentialen der Beschäftigten. Die Gemeinsamkeiten, aber auch Unterschiede und Konfliktpotenziale werden ausführlich erklärt.
Mit diesem Hintergrundwissen können Beratende Gesundheitsthemen besser in Phasen gesundheitlicher Belastungen einbringen und richtig adressieren. Der iga.Report 44 gibt einen Überblick zum noch jungen Stand der Forschung und liefert zahlreiche Ansatzpunkte für die Präventionsarbeit und die Betriebliche Gesundheitsförderung in einer neuen Arbeitswelt.
Experimentelle Organisationsentwicklung : Perspektiven eines zukunftsfähigen Veränderungsansatzes
(2021)
Die Organisationsentwicklung selbst verändert sich und wird “zukunftsoffener”. In diesem Beitrag argumentieren die Autoren, dass die Idee des Experimentierens als zukunftsfähige Veränderungsmethode angewandt werden kann. Sie stellen zentrale Prämissen einer "experimentellen Organisationsentwicklung" und zeigen die Eckpunkte eines spezifischen Interventionsdesigns auf.
The technologies of digital transformation, such as the Internet-of-Things (IoT), artificial intelligence or predictive maintenance enable significant efficiency gains in industry and are becoming increasingly important as a competitive factor. However, their successful implementation and creative, future application requires the broad acceptance and knowledge of non-IT-related groups, such as production management students, engineers or skilled workers, which is still lacking today. This paper presents a low-threshold training concept bringing IoT-technologies and applications into manufacturing related higher education and employee training. The concept addresses the relevant topics starting from IoT-basics to predictive maintenance using mobile low-cost hardware and infrastructure.
In the current age of innovative business financing opportunities available from fintech apps, social media crowdfunding sites such as Kickstarter, Indiegogo, and RocketHub, et.al., and friends and family private equity investors, start-up firms can strategically source their venture capital funds from many globally disperse organizations and individuals. As the firm in this case learned, the benefit of alternative investing sources comes with a critical hidden risk for corporate governance. After a financial restructuring, a typical Silicon Valley software start-up found itself with close to 300 external individual shareholders, some of whom had not been documented as accredited investors. The regulatory agency could decide that the prior actions of the founders and the decisions of the board had been prejudicial to the interests of the minority investors. The management of this small private company faced an atypical investor relations dilemma, before its initial public offering (IPO).