Refine
Document Type
- Journal article (280)
- Conference proceeding (137)
- Book chapter (44)
- Book (26)
- Working Paper (11)
- Doctoral Thesis (8)
- Review (5)
- Anthology (3)
- Issue of a journal (2)
- Journal (1)
Language
- English (518) (remove)
Is part of the Bibliography
- yes (518) (remove)
Institute
- ESB Business School (518) (remove)
Publisher
- Elsevier (95)
- Springer (42)
- MDPI (24)
- Association for Information Systems (20)
- Wiley (20)
- IEEE (19)
- MIT Center for Information Systems Research (17)
- Stellenbosch University (12)
- Emerald (11)
- Hochschule Reutlingen (10)
Learning factories present a promising environment for education, training and research, especially in manufacturing related areas which are a main driver for wealth creation in any nation. While numerous learning factories have been built in industry and academia in the last decades, a comprehensive scientific overview of the topic is still missing. This paper intends to close this gap establishing the state of the art of learning factories. The motivations, historic background, and the didactic foundations of learning factories are outlined. Definitions of the term learning factory and the corresponding morphological model are provided. An overview of existing learning factory approaches in industry and academia is provided, showing the broad range of different applications and varying contents. The state of the art of learning factories curricula design and their use to enhance learning and research as well as potentials and limitations are presented. Conclusions and an outlook on further research priorities are offered.
In the last decade, numerous learning factories for education, training, and research have been built up in industry and academia. In recent years learning factory initiatives were elevated from a local to a European and then to a worldwide level. In 2014 the CIRP Collaborative Working Group (CWG) on Learning Factories enables a lively exchange on the topic "Learning Factories for future oriented research and education in manufacturing". In this paper results of discussions inside the CWG are presented. First, what is meant by the term Learning Factory is outlined. Second, based on the definition a description model (morphology) for learning factories is presented. The morphology covers the most relevant characteristics and features of learning factories in seven dimensions. Third, following the morphology the actual variance of learning factory manifestations is shown in six learning factory application scenarios from industrial training over education to research. Finally, future prospects of the learning factory concept are presented.
Venture capital and the innovative power of a state : econometric study including Google data
(2015)
This article focuses on venture capital investments and the innovative power of a state defined by its public infrastructure. The economic implications are evaluated by estimating several panel regression models. The novelty is twofold: on the one hand the research approach and on the other hand the new data set. The data ranges from 1995 to 2014 and consists of 10 European countries plus the US and Canada. For the first time we include Google search data on Venture Capital. The results show a significant increase in Venture Capital is mainly determined by economic conditions such as real GDP growth. The impact of the innovative power of a state is not significant. We find that Google data is positively related and significant in respect to Venture Capital investments too. Consequently, we confirm that private business investments cannot be created by government policy alone rather via solid macroeconomic conditions.
User innovators follow multiple diffusion and adoption pathways for their self-developed innovations. Users may choose to commercialize their self-developed products on the marketplace by becoming entrepreneurs. Few studies exist that focus on understanding personal and interpersonal factors that affect some user innovators’ entrepreneurial decision-making. Hence, this paper focuses on how user innovators make key decisions relating to opportunity recognition and evaluation and when opportunity evaluation leads to subsequent entrepreneurial action in the entrepreneurial process. We conducted an exploratory study using a multi-grounded theory methodology as the user entrepreneurship phenomenon embodies complex social processes. We collected data through the netnography approach that targeted 18 entrepreneurs with potentially relevant differences through crowdfunding platforms. We integrated self-determination, human capital, and social capital theory to address the phenomena under study. This study’s significant findings posit that users’ motives are dissatisfaction with existing goods, interest in innovation, altruism, social recognition, desire for independence, and economic benefits. Besides, use-related experience, product-related knowledge, product diffusion, and iterative feedback positively impact innovative users’ entrepreneurial decision-making.
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.
In times of climate change and growing urbanization, the way food is produced and consumed also changes. Meanwhile, digitization is transforming farming practices, which also applies to the domestic growing of crops. More and more so-called smart home farms (SHF) are finding their way into private households. This paper conceptualizes the unique nature of enabled smart services and their underlying technology. Following an inductive interpretive approach, this study explores the antecedents of smart home farming practices. Our sample consists of eleven actual smart home farmers. We found six constructs to be of salient importance: expected outcomes related to harvesting, positive feelings, and sustainability; a combination of one's affinity for green and novel technologies; and the smartness and visibility of the enabled services. In the outlook, we present some preliminary thoughts for testing our qualitative findings.
Facing ever-looming climate change, studying the drivers for individuals' Information Systems (IS) Use to reduce environmental harm gains momentum. While extant research on the antecedents of sustainable IS Use has focused on specific theories, interventions, contexts, and technologies, a holistic understanding has become increasingly elusive, with a synthesis remaining absent. We employ a systematic literature review methodology to shed light on the driving antecedents for sustainable IS Use among individual consumers. Our results build on findings of 29 empirical studies drawn from 598 articles retrieved from our premier outlets and a forward/backward search. The analysis reveals six salient complementary antecedents: Relief, Empowerment, Default, User-centricity, Salience, and Encouragement. We recommend considering these concepts when developing, deploying, promoting, or regulating digital technologies to mitigate individual consumers' emissions. Along with memorable and implementable concepts, our theoretical framework offers a novel conceptualization and four promising avenues for researchers on sustainable IS Use.
The proliferation of smart technologies transforms the way individual consumers perform tasks. Considerable research alludes that smart technologies are often related to domestic energy consumption. However, it remains unclear how such technologies transform tasks and thereby impact our planet. We explore the role of technological smartness in personal day-to-day tasks that help create a more sustainable future. In the absence of theory, but facing extensive changes in everyday life enabled by smart technologies, we draw on phenomenon-based theorizing (PBT) guidelines. As anchor, we refer to task endogeneity related to task-technology fit theory (TTF). As infusion, we employ theory on public goods. Our model proposes novel relations between the concepts of smart autonomy and -transparency with sustainable task outcomes, mediated by task convenience and task significance. We discuss some implications, limitations, and future research opportunities.
The proper selection of a demand forecasting method is directly linked to the success of supply chain management (SCM). However, today’s manufacturing companies are confronted with uncertain and dynamic markets. Consequently, classical statistical methods are not always appropriate for accurate and reliable forecasting. Algorithms of Artificial intelligence (AI) are currently used to improve statistical methods. Existing literature only gives a very general overview of the AI methods used in combination with demand forecasting. This paper provides an analysis of the AI methods published in the last five years (2017-2021). Furthermore, a classification is presented by clustering the AI methods in order to define the trend of the methods applied. Finally, a classification of the different AI methods according to the dimensionality of data, volume of data, and time horizon of the forecast is presented. The goal is to support the selection of the appropriate AI method to optimize demand forecasting.
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.
We study whether compulsory religious education in schools affects students' religiosity as adults. We exploit the staggered termination of compulsory religious education across German states in models with state and cohort fixed effects. Using three different datasets, we find that abolishing compulsory religious education significantly reduced religiosity of affected students in adulthood. It also reduced the religious actions of personal prayer, church-going, and church membership. Beyond religious attitudes, the reform led to more equalized gender roles, fewer marriages and children, and higher labor-market participation and earnings. The reform did not affect ethical and political values or non-religious school outcomes.
We study whether compulsory religious education in schools affects students' religiosity as adults. We exploit the staggered termination of compulsory religious education across German states in models with state and cohort fixed effects. Using three different datasets, we find that abolishing compulsory religious education significantly reduced religiosity of affected students in adulthood. It also reduced the religious actions of personal prayer, church-going, and church membership. Beyond religious attitudes, the reform led to more equalized gender roles, fewer marriages and children, and higher labor-market participation and earnings. The reform did not affect ethical and political values or non-religious school outcomes.
Being exposed to compulsory religious education in school can have long-run consequences for students’ lives. At different points in time since the 1970s, German states terminated compulsory religious education in public schools and replaced it by a choice between ethics classes and religious education. This article shows that the reform not only led to reduced religiosity in students’ later life, but also eroded traditional attitudes towards gender roles and increased labor-market participation and earnings.
Cyber-Physical Production Systems increasingly use semantic information to meet the grown flexibility requirements. Ontologies are often used to represent and use this semantic information. Existing systems focus on mapping knowledge and less on the exchange with other relevant IT systems (e.g., ERP systems) in which crucial semantic information, often implicit, is contained. This article presents an approach that enables the exchange of semantic information via adapters. The approach is demonstrated by a use case utilizing an MES system and an ERP system.
Digitalization changes the manufacturing dramatically. In regard of employees’ demands, global trends and the technological vision of future factories, automotive manufacturing faces a huge number of diverse challenges. Currently, research focuses on technological aspects of future factories in terms of digitalization. New ways of work and new organizational models for future factories have not been described yet. There are assumptions on how to develop the organization of work in a future factory but up to now, literature shows deficits in scientifically substantiated answers in this research area. Consequently, the objective of this paper is to present an approach on a work organization design for automotive Industry 4.0 manufacturing. Future requirements were analyzed and deducted to criteria that determine future agile organization design. These criteria were then transformed into functional mechanisms, which define the approach for shopfloor organization design
This booklet will give you an overview of the development of CSR from a (brief) historic point of view and will examine the underlying concepts and research. Furthermore, examples of contemporary CSR management will be explored to show how companies Interpret the issue and how they face the challenges of managing the new demands placed upon them. Business, in the end, comes down to figures and numbers which give management, shareholders and stakeholders a chance to measure a company’s success. Therefore, modern methods and approaches for measuring, rating and ranking a company’s CSR management will be presented. Finally, an attempt will be made to evaluate CSR as a tool for increasing global welfare and as a business and management strategy for companies and entrepreneurs.
Changing requirements and qualification profiles of employees, increasingly complex digital systems up to artificial intelligence, missing standards for the seamless embedding of existing resources and unpredictable return on investments are just a few examples of the challenges of an SME in the age of digitalisation. In most cases there is a lack of suitable tools and methods to support companies in the digital transformation process in the value creation processes, but also of training and learning materials. A European research project (BITTMAS - Business Transformation towards Digitalisation and Smart systems, ERASMUS+, 2016-1 DE02-KA202-003437) with international partners from science, associations and industry has addressed this issue and developed various methods and instruments to support SMEs. Within the scope of a literature search, 16 suitable digitalisation concepts for production and logistics were identified. In the following, a learning platform with a literature database with multivariable sorting options according to branches and keywords of digitalisation, a video gallery with basic and advanced knowledge and a glossary were created in order to provide the user with consolidated and structured specialist knowledge. The 16 identifying concepts for transforming value-added processes in the context of digitalisation were transferred to a learning platform using developed learning paths in coaching and training to online course modules including test questions. A maturity model was developed and implemented in a self assessment tool for the analysis to identify the potential of digitalisation in production and logistics in relation to the current technological digitalisation level of the company. As a result, the user receives one or more of the 16 potential digitalisation concepts suggested or the delta for the necessary, not yet available enabler technologies is presented as a spider diagram. For a successful implementation of the identified suitable digitalisation concepts in production and logistics, a further tool was developed to identify supplementary requirements for all company divisions and stakeholders in relation to the "digital transformation" in the form of a self-evaluation. This paper presents the methods and tools developed, the accompanying learning materials and the learning platform.
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.
Machine learning (ML) techniques are rapidly evolving, both in academia and practice. However, enterprises show different maturity levels in successfully implementing ML techniques. Thus, we review the state of adoption of ML in enterprises. We find that ML technologies are being increasingly adopted in enterprises, but that small and medium-size enterprises (SME) are struggling with the introduction in comparison to larger enterprises. In order to identify enablers and success factors we conduct a qualitative empirical study with 18 companies in different industries. The results show that especially SME fail to apply ML technologies due to insufficient ML knowhow. However, partners and appropriate tools can compensate this lack of resources. We discuss approaches to bridge the gap for SME.
The unprecedented acceleration in the dynamics of economic development and its dependence on global interactions makes predicting the future especially difficult. Nevertheless, an examination of long-term trends provides an opportunity to begin a discussion about what reality could await us tomorrow and how we want to deal with it. With this food-for-thought paper, the member institutes of the Fraunhofer Group for Innovation Research wish to present a selection of the trends that are destined to have a significant impact on innovation systems in the period leading up to 2030. Based on these trends, the paper derives theses for innovation in the year 2030 and describes the resulting tasks for business, politics, science and society.
Since its early beginnings in the form of correspondence schools, e-learning has generally sought to provide flexibility and high quality education. While these are indeed noble intentions, the reality of today's connected world demands that such programs focus on a different purpose. As the main purpose of e-learning shifts, so must be the design approaches.
Rethinking e-learning requires open-mindedness on the part of academies, designers, cyber educators, legislators, IT and administrators, but also the learners themselves. All who are involved in or impacted by e-learning programs must speak up and finally share their perspectives, but who will be listening? The key to rethinking e-learning lies in the ability of the stakeholders to listen to each other and make decisions which are in the best interest of the learner.
This chapter will propose a new purpose for e-learning and explore promising possibilities for learner-centered design. The future of e-learning can be shaped by the decisions made today, but before any decisions can be made, one must acknowledge e-learning's successes as well as its shortcomings. The purpose of this chapter is to encourage those who are impacted by e-learning to think about the future.
There is no denying that organizations, whether domestic or global, whether educational, governmental, or business, are undergoing rapid transformation. However, what is causing it? Prompted by the need to remain relevant and competitive, organizations constantly try to reinvent themselves. Those that do not, according to the laws of economics, will simply serve no purpose and will eventually cease to exist. Regardless of sector or industry, an organization's success pivots around its human talent. Hence, it is crucial to manage it and cultivate certain traits, knowledge, and skills. In today's global economy, organizations are more interconnected than ever before and thus the challenges they face require that employees possess not only expert knowledge, problem-solving, cross-cultural, and cross-functional teaming skills, but also good communications skills and agile thinking.
Many researchers have explored the phenomenon of intercultural communication since Edward T. Hall first brought it to light in the late 1950s. Although the literature is quite extensive, the ongoing sociopolitical struggles are evidence that even in the twenty-first century, society has limited intercultural as well as intracultural communication competence. This limited understanding continues to bring about discord in every facet of life, including work.
The modern workforce is expected to possess certain knowledge, skills, and attitudes that are inherently different from those expected from previous generations. Due to globalization, intercultural competence and highly effective communication skills are at the top of the list - a working knowledge of English as the lingua franca of today's business world can be considered as a first step.
Military organizations have special features like following different organizational laws in times of peace and war and their specific embeddedness in society and politics. Especially the latter aspect has made the military an important object of study since the beginnings of modern sociology. In the wake of establishing specific sociological accounts, military sociology has been developed, dedicated to the different facets of the military. This research is based on different theoretical perspectives, but has hardly embraced the frameworks from economics and sociology of conventions (EC/SC) so far. The aim of the chapter is to explore and demonstrate the potentials of this approach. In a first step, the state of the art of military sociology research is outlined, and potential avenues for analyzing military forces based on EC/SC are identified. It is argued that especially the connection to organizational theory (military as organization) and civil-military relations, including leadership and professionalism, offer starting points. After introducing existing studies addressing military-related topics with reference to EC/SC, relevant concepts and approaches of convention theory that prove to be particularly enriching for military research are discussed. An outlook on possible further fields and topics of research is given to concretize how an inclusion of the perspective of EC/SC could look like.
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.
This study analyses the impact of Basel III on the fair pricing of bank guarantee facilities.Guarantees are an important risk mitigation instrument between exporters and importers in international trade and regularly a prerequisite for cross border sales contracts to be closed. Basel III – which shall be introduced from 2013 onwards - is a new regulation stipulating higher capital requirements for banks compared to the predecessor Basel II. It will therefore have an impact on the pricing of guarantee facilities which banks provide to exporting companies, making it also a crucial regulation for the cost of exportation overall. The study compares those contents of Basel III and Basel II which are particularly relevant for guarantees in order to identify and crystallize pricing-relevant changes in the regulations and their respective impact potential. The Basel frameworks are analyzed part by part and reviewed in terms of relevance for guarantees. In case of ambiguity the analysis is verified by complementary expert interviews. References and examples are mainly focusing on the German banking system but the basic conclusions can be generalized for those countries adopting Basel III.1 As the result, a case study expresses the quantitative outcomes of different scenarios and the impact of the different price determining factors on the overall fair pricing of bank guarantee facilities.
This article reviews the literature on Christmas economics. First, we present an overall picture of the debate on the potential welfare loss of gift-giving and we show strategies that reduce the potential welfare loss and might increase the number of presents received. Second, we discuss the effect of Christmas on prices and the business cycle. We provide evidence that at Christmas stock prices and airfares increase, while food prices decrease.
Business process management and IT supported processes are an actual topic. The procedure of finding a business process system that implements your processes the best way is not easy and takes a lot of time. In this article you will find a recommendation for an open source system. Four selected open source workflow management systems are tested and analyzed. Mean criteria for the evaluation are listed in a criteria catalogue and rated by experts by their importance. Finally, the systems are evaluated by the criteria and the best evaluated system can be recommended.
The functionality of existing cyber-physical production systems generally focuses on mapping technologic specifications derived from production requirements. Consequently, such systems base their conception on a structurally mechanistic paradigm. Insofar as these approaches have considered humans, their conception likewise is based on the structurally identical paradigm. Due to the fundamental reorientation towards explicitly human-centered approaches, the fact that essential aspects of the dimension "human" remain unconsidered by the previous paradigm becomes more and more apparent. To overcome such limitations, mapping the "social" dimension requires a structurally different approach. In this paper, an anthropocentric approach is developed based on possible conceptions of the human being, enabling a structural integration of the human being in an extended dimension. Through the model, extending concepts for better integration of the human being in the sense of human-centered approaches, as envisioned in the Industrie 5.0 conception, is possible.
Artificial intelligence is a field of research that is seen as a means of realization regarding digitalization and industry 4.0. It is considered as the critical technology needed to drive the future evolution of manufacturing systems. At the same time, autonomous guided vehicles (AGV) developed as an essential part due to the flexibility they contribute to the whole manufacturing process within manufacturing systems. However, there are still open challenges in the intelligent control of these vehicles on the factory floor. Especially when considering dynamic environments where resources should be controlled in such a way, that they can be adjusted to turbulences efficiently. Therefore, this paper aimed to develop a conceptual framework for addressing a catalog of criteria that considers several machine learning algorithms to find the optimal algorithm for the intelligent control of AGVs. By applying the developed framework, an algorithm is automatically selected that is most suitable for the current operation of the AGV in order to enable efficient control within the factory environment. In future work, this decision-making framework can be transferred to even more scenarios with multiple AGV systems, including internal communication along with AGV fleets. With this study, the automatic selection of the optimal machine learning algorithm for the AGV improves the performance in such a way, that computational power is distributed within a hybrid system linking the AGV and cloud storage in an efficient manner.
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.
The paradigmatic shift of production systems towards Cyber-Physical Production Systems (CPPSs) requires the development of flexible and decentralized approaches. In this way, such systems enable manufacturers to respond quickly and accurately to changing requirements. However, domain-specific applications require the use of suitable conceptualizations. The issue at hand, when using various conceptualizations is the interoperability of different ontologies. To achieve flexibility and adaptability in CPPSs though requires overcoming interoperability issues within CPPSs. This paper presents an approach to increase flexibility and adaptability in CPPSs while addressing the interoperability issue. In this work, OWL ontologies conceptualize domain knowledge. The Intelligent Manufacturing Knowledge Ontology Repository (IMKOR) connects the domain knowledge in different ontologies. Testing if adaptions in one ontology within the IMKOR provide knowledge to the whole IMKOR. The tests showed, positive results and the repository makes the knowledge available to the whole CPPS. Furthermore, an increase in flexibility and adaptability was noticed.
Cyber-Physical Production Systems increasingly use semantic information to meet the grown flexibility requirements. Ontologies are often used to represent and use this semantic information. Existing systems focus on mapping knowledge and less on the exchange with other relevant IT systems (e.g., ERP systems) in which crucial semantic information, often implicit, is contained. This article presents an approach that enables the exchange of semantic information via adapters. The approach is demonstrated by a use case utilizing an MES system and an ERP system.
The imparting of knowledge and skills in STEM education, especially under the influence of the Covid-19 pandemic, is increasingly taking place online and through digital formats. The partially asynchronous instruction eliminates, on the one hand, the social relation in the learning process and, on the other hand, the direct experience with physical objects. Here, the digital learning systems provide learning tools and controls to support the learning process on a general basis. Existing methods for simulating physical objects (digital twins) are also used to a minimal extent. The following approach presents a learning system framework that enables individualized learning, including all dimensions (social, physical). Implementing a concept that uses a personalized assistance system to orchestrate the individual learning steps enables efficient and effective learning. Applying the learning system framework exemplifies the STEM education at Reutlingen University in the logistics learning factory Werk150.
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.
Mystery shopping (MS) is a widely used tool to monitor the quality of service and personal selling. In consultative retail settings, assessments of mystery shoppers are supposed to capture the most relevant aspects of sales people’s service and sales behavior. Given the important conclusions drawn by managers from MS results, the standard assumption seems to be that assessments of mystery shoppers are strongly related to customer satisfaction and sales performance. However, surprisingly scant empirical evidence supports this assumption. We test the relationship between MS assessments and customer evaluations and sales performance with large-scale data from three service retail chains. Surprisingly, we do not find asubstantial correlation. The results show that mystery shoppers are not good proxies for real customers. While MS assessments are not related to sales, our findings confirm the established correlation between customer satisfaction measurements and sales results.
Gender pay gaps are commonly studied in populations with already completed educational careers. We focus on an earlier stage by investigating the gender pay gap among university students working alongside their studies. With data from five cohorts of a large-scale student survey from Germany, we use regression and wage decomposition techniques to describe gender pay gaps and potential explanations. We find that female students earn about 6% less on average than male students, which reduces to 4.1% when accounting for a rich set of explanatory variables. The largest explanatory factor is the type of jobs male and female students pursue.
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.
Compared to the automotive sector, where automation is the rule, in many other less standardized sectors automation is still the exception. This could soon hurt the productivity of industrialized countries, where the unemployment is low and the population is aging. Phenomena like the recent downfall in productivity, due to lockdowns and social distancing for prevention of health hazards during the COVID19 pandemic, only add to the problem. For these reasons, the relevance, motivation and intention for more automation in less standardized sectors has probably never been higher. However, available statistics say that providers and users of technologies struggle to bring more automation into action in automation-unfriendly sectors. In this paper, we present a decision support method for investment in automation that tackles the problem: the STIC analysis. The method takes a holistic and quantitative approach tying together technological, context-related and economic input parameters and synthetizing them in a final economic indicator. Thanks to the modelling of such parameters, it is possible to gain sensibility on the technological and/or process adjustments that would have the highest impact on the efficiency of the automation, thereby delivering value for both technology users and technology providers.
In this paper it is first identified the trade-off among costs, flexibility and performances of autonomous robotic solutions for material handling processes, where adding value with automation is not as trivial as in production processes: hence the requirement for automated solutions to be simple, lean and efficient becomes even stricter. Then a method for modelling and comparing differential performances and costs of manual and autonomous solutions is developed. As a result of the method, a smart man-machine collaborative interface is designed and its impact evaluated on a specific case of study. Results are then generalized and prove the strong conclusions that in unconstrained environments, where full standardization cannot be achieved, the risk of investing in autonomous solutions can only be mitigated by creating a fast and smart man-machine collaborative interface.
Planning of available resources considering ergonomics under deterministic highly variable demand
(2020)
In this paper, a method for hybrid short- to long-term planning of available resources for operations is presented, which is based on a known or deterministically forecasted but highly variable demand. The method considers quantitative measures such as the performance and the availability of resources, ergonomically relevant KPI and ultimately process costs in order to serve as a pragmatic planning tool for operations managers in SMEs. Specifically, the method enables exploiting the ergonomic advantages of available flexible automation technology (e.g. AGVs or picking robots), while assuring that these do not represent a capacity bottleneck. After presenting the method along with the necessary assumptions, mainly concerning the availability of data for the calculations, we report a case study that quantifies the impact of throughput variability on the selection of different process alternatives, where different teams of resources are used.
The paper focuses on a recently introduced paradigm for the logistic process of picking, with respect to the man-to-goods and goods-to-man concept: the robot to-goods. First the task and system architecture of the fast deployable autonomous commissioning system are described, then the economic efficiency of the system is analysed in a real business case scenario using a simplified method, which is explained and discussed. The clearly positive net present value of the investment and the short payback period obtained in the business case prove how the robot-to-goods paradigm for the commissioning process, implemented through the automation of the forklift platform, is economically attractive for small and medium size enterprises.
In standardized sectors such as the automotive, the cost-benefit ratio of automation solutions is high as they contribute to increase capacity, decrease costs and improve product quality. In less standardized application fields, the contribution of automation to improvements in capacity, cost and quality blurs. The automation of complex and unstructured tasks requires sophisticated, expensive and low-performing systems, whose impact on product quality is oftentimes not directly perceived by customers. As a result, the full automation of process chains in the general manufacturing or the logistic sectors is often a sub optimal solution. Taking the distance from the false idea that a process should be either fully automated, or fully manual, this paper presents a novel heuristic method for design of lean human-robot interaction, the Quality Interaction Function Deployment, with the objective of the “right level of automation”. Functions are divided among human and automated agents and several automation scenarios are created and evaluated with respect to their compliance to the requirements of all process´ stakeholders. As a result, synergies among operators (manual tasks) and machines (automated tasks) are improved, thus reducing time-losses and increasing productivity.
Powered by e-commerce and vital in the manufacturing industry, intralogistics became an increasingly important and labour-intensive process. In highly standardized automation-friendly environments, such as the automotive sector, most of efficiently automatable intralogistics tasks have already been automated. Due to aging population in EU and ergonomic regulations, the urge to automate intralogistics tasks became consistent also where product and process standardization is lower. That is the case of the production line or cell material supply process, where an increasing number of product variants and individually customized products combined with the necessary ability of reacting to changes in market conditions led to smaller and more frequent replenishment to the points of use in the production plant and to the chaotic addition of production cells in shop floor layout. This led in turn to inevitable traffic growth with unforeseeable related delays and increased level of safety threats and accidents. In this paper, we use the structured approach of the Quality Interaction Function Deployment to analyse the process of supply of assembly lines, seeking the most efficient combination of automation and manual labour, satisfying all stakeholders´ requirements. Results are presented and discussed.
According to a recent survey the great majority of players in logistics are planning to adopt one or more robotic solutions until 2019. Technical solutions for automation of processes in logistics are often available as a market-ready product, but the lack of standardization and skepticism towards long term investments are often the reasons why these solutions are not implemented on a large scale. This paper is set to bridge the gap between the world of technologies and the one of applications in order to help investors, robot producers and system integrators to decide on which branch of logistics to set their focus. The three main branches Courier Express Parcel (CEP), contract logistics and production logistics are briefly defined and distinguished through their characteristic factors and parameters. Then a method based on the analysis of three parameters (operative costs, required performance and flexibility) in the three branches is set to identify the most convenient branch of logistics for investing in new technologies, namely the one in which the risk of investment is lower, the return is higher and faster. The conclusion of the method shows that higher labor costs, strict regulations and higher standardization make the production logistics the most suitable branch for investments in emerging automation solutions.
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.
The increasing complexity and need for availability of automated guided vehicles (AGVs) pose challenges to companies, leading to a focus on new maintenance strategies. In this paper, a smart maintenance architecture based on a digital twin is presented to optimize the technical and economic effectiveness of AGV maintenance activities. To realize this, a literature review was conducted to identify the necessary requirements for Smart Maintenance and Digital Twins. The identified requirements were combined into modules and then integrated into an architecture. The architecture was evaluated on a real AGV on the battery as one of the critical components.
The implementation of human resource (HR) policies often proves troublesome due to the appearance, and stubborn persistence, of gaps in the process. Human resource management (HRM) scholars problematise these gaps and advocate tight implementation to reduce gaps and to ensure the desired impact of policies on organisational performance. Drawing on organisational institutionalism, we contend that gaps in implementing HR policies can actually be productive, as they secure organisational legitimacy, and thus enable organisations to operate viably within several institutional environments. We suggest that different approaches to implementation are needed, some of them premised on accepting sustained implementation gaps. We introduce minimum and moderate implementation approaches, rooted in the notion of decoupling, to complement approaches aimed at tight implementation. Our aim is to support the further development of research based on a richer interpretation of HRM implementation challenges and choices they present for HR managers.
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.
»Flexible Arbeitspraktiken: Eine Analyse aus pragmatischer Perspektive«. Traditional human resource management (HRM) research can hardly relate to today's developments in the world of work. Organizational boundaries are blurred because of the complexity due to globalization, digitalization, and demographic changes. In practice, new ways of organizing work can be found that depend on the specifics of the work situation. In this paper, we build on the economics of convention (EC) to elaborate on the current challenges HRM scholarship is confronted with and provide a theoretical lens that goes beyond the tension between market and bureaucracy principles in actual employment settings. We apply EC’s situationalist methodology to examples of the challenging coordination of flexibility in the workplace. We explain two hybrid forms of coordination – compromises and local arrangements – and highlight the dynamics of employment practices in organizations related to these forms. Thereby, we show that different modes of coordination in employment are applied in a fluctuating manner that depends on the specific situations. In doing so, we further seek to remind HRM scholars of the fruitfulness of the pragmatist perspective in analyzing work practices, as well as extending its conceptual toolkit for future analysis.
Consistent supply chain management across all levels of value creation is a common approach in the industrial sector. The implementation in agricultural processes requires rethinking in the supply chain concept. The reasons are the heuristic characterized processes, the stochastic environmental conditions, the mobility of the production facilities and the low division of work.
In this paper we deal with how concepts of innovative supply chain management of Industrie 4.0 could not only deliver a way to overcome said problems but also provide the foundation for the development of new forms of work and business models for Farming 4.0.
In order to decouple economic growth from global material consumption it is necessary to implement material efficiency strategies at the level of single enterprises and their supply chains, and to implement circular economy aspects. Manufacturing firms face multiple implementation challenges like cost limitations, competition, innovation and stakeholder pressure, and supplier and customer relationships, among others. Taking as an example a case of a medium-sized manufacturing company, opportunities to realise material efficiency improvements within the company borders - on the supply chain and by using circular economy measures - are assessed. Deterministic calculations and simulations, performed for the supply chain of this company, show that measures to increase material efficiency in the supply chain are important. However, they need to be complemented by efforts to return waste and used products to the economic cycle, which requires rethinking the traditional linear economic system.
In order to decouple economic growth from global material consumption it is necessary to implement material efficiency strategies at the level of single enterprises and their supply chains, and to implement circular economy aspects. Manufacturing firms face multiple implementation challenges like cost limitations, competition, innovation and stakeholder pressure, and supplier and customer relationships, among others
. An extended evaluation of triggers and barriers to improve material efficiency in manufacturing companies, along the supply chain and concerning circular economy considerations is provided. This paper delivers an extended literature review, a critical discussion of the current situation and resulting challenges concerning material efficiency approaches in manufacturing supply chains. Finally, a conclusion and outlook on further research direction is given.
Mature economies which are driven mainly by small and medium sized enterprises (SMEs) are increasingly becoming dependent on material imports. Global material consumption is ever increasing, mainly driven by population increases. Decoupling of material consumption from economic growth is one of the greatest challenges of the 21st century. Within this paper available methods for the assessment of material efficiency on different economic scales are investigated and those detected that are particulary suitable for the use in SMEs. Recommendations for further improvements of the selected tools and an outlook concerning planned research activities in the field of material efficiency in enterprises, supply chains and circular economy aspects are given.
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.
A seamless convergence of the digital and physical factory aiming in personalized Product Emergence Process (PPEP) for smart products within ESB Logistics Learning Factory at Reutlingen University.
A completely new business model with reference to Industrie4.0 and facilitated by 3D experience software in today's networked society in which customers expect immediate responses, delightful experience and simple solutions is one of the mission scenarios in the ESB Logistics Learning Factory at ESB Business School (Reutlingen University).
The business experience platform provides software solutions for every organization in the company respectively in the factory. An interface with dashboards, project management apps, 3D - design and construction apps with high end visualization, manufacturing and simulation apps as well as intelligence and social network apps in a collaborative interactive environment help the user to learn the creation of a value end to end process for a personalized virtual and later real produced product.
Instead of traditional ways of working and a conventional operating factory real workers and robots work semi-intuitive together. Centerpiece in the self-planned interim factory is the smart personalized product, uniquely identifiable and locatable at all times during the production process – a scooter with an individual colored mobile phone – holder for any smart phone produced with a 3D printer in lot size one. Smart products have in the future solutions incorporated internet based services – designed and manufactured - at the costs of mass products. Additionally the scooter is equipped with a retrievable declarative product memory. Monitoring and control is handled by sensor tags and a raspberry positioned on the product. The engineering design and implementation of a changeable production system is guided by a self-execution system that independently find amongst others esplanade workplaces.
The imparted competences to students and professionals are project management method SCRUM, customization of workflows by Industrie4.0 principles, the enhancements of products with new personalized intelligent parts, electrical and electronic selfprogrammed components and the control of access of the product memory information, to plan in a digital engineering environment and set up of the physical factory to produce customer orders. The gained action-orientated experience refers to the chances and requirements for holistic digital and physical systems.
Technologies for mapping the “digital twin“ have been under development for approximately 20 years. Nowadays increasingly intelligent, individualized products encourages companies to respond innovatively to customer requirements and to handle the rising product variations quickly.
An integrated engineering network, spanning across the entire value chain, is operated to intelligently connect various company divisions, and to generate a business ecosystem for products, services and communities. The conditions for the digital twin are thereby determined in which the digital world can be fed into the real, and the real world back into the digital to deal such intelligent products with rising variations.
The term digital twin can be described as a digital copy of a real factory, machine, worker etc., that is created and can be independently expanded, automatically updated as well as being globally available in real time. Every real product and production site is permanently accompanied by a digital twin. First prototypes of such digital twins already exist in the ESB Logistics Learning Factory on a cloud- and app based software that builds on a dynamic, multidimensional data and information model. A standardized language of the robot control systems via software agents and positioning systems has to be integrated. The aspect of the continuity of the real factory in the digital factory as an economical means of ensuring continuous actuality of digital models looks as the basis of changeability.
For the indoor localization sensor combinations that in addition to the hardware already contain the software required for the sensor data fusion should be used. Processing systems, scenario-live-simulations and digital shop floor management results in a mandatory procedural combination. Essential to the digital twin is the ability to consistently provide all subsystems with the latest state of all required information, methods and algorithms.
Few unfocused factories outperform competitors, but Focus is elusive because the environment is constantly evolving and this requires changes to a factory’s key tasks. So how can focus be achieved and sustained? We present insights derived from an historical analysis of the German Hewlett-Packard server plant which went through a series of Focus changes over the years. Using this example, we provide clues for the right timing of Focus changes and discuss critical structural and infrastructural changes required during the Focus transitions, as well as cross-functional coordination and leadership challenges. Our assertion is that production operations constitute a system that can adapt to disruptive Change by using the levers of manufacturing policies to stay focused on a limited but absolutely essential task which creates a strategic advantage.
Theory predicts that market‐timing activities bias Jensen's alpha (JA). However, empirical studies have failed to find consistent evidence of this bias. We tackle this puzzle in a nested model analysis and show that the bias contains an exogenous market component that is unrelated to market‐timing skill. In a comprehensive empirical analysis of US mutual funds, we find that the timing‐induced bias in JA is mainly driven by this market component, which is uncorrelated with measured timing activities. Measures of total performance that allow for timing activities are virtually identical to JA, even if timing activities are present in the evaluated fund. Hence, we conclude that JA is a sufficient measure of total performance.
The Industry 4.0 paradigm requires concepts for integrating intelligent/ smart IoT Solutions into manufacturing. Such intelligent solutions are envisioned to increase flexibility and adaptability in smart factories. Especially autonomous cobots capable of adapting to changing conditions are a key enabler for changeable factory concepts. However, identifying the requirements and solution scenarios incorporating intelligent products challenges the manufacturing industry, especially in the SME sector. In pick and place scenarios, changing coordinate systems of workpiece carriers cause placing process errors. Using the IPIDS framework, this paper describes the development of a tool-center-point positioning method to improve the process stability of a collaborative robot in a changeable assembly workstation. Applying the framework identifies the requirement for an intelligent workpiece carrier as a part of the solution. Implementing and evaluating the solution within a changeable factory validates the IPIDS framework.
Framework for integrating intelligent product structures into a flexible manufacturing system
(2023)
Increasing individualisation of products with a high variety and shorter product lifecycles result in smaller lot sizes, increasing order numbers, and rising data and information processing for manufacturing companies. To cope with these trends, integrated management of the products and manufacturing information is necessary through a “product-driven” manufacturing system. Intelligent products that are integrated as an active element within the controlling and planning of the manufacturing process can represent flexibility advantages for the system. However, there are still challenges regarding system integration and evaluation of product intel-ligence structures. In light of these trends, this paper proposes a conceptual frame-work for defining, analysing, and evaluating intelligent products using the example of an assembly system. This paper begins with a classification of the existing problems in the assembly and a definition of the intelligence level. In contrast to previous approaches, the analysis of products is expanded to five dimensions. Based on this, a structured evaluation method for a use case is presented. The structure of solving the assembly problem is provided by the use case-specific ontology model. Results are presented in terms of an assignment of different application areas, linking the problem with the target intelligence class and, depending on the intelligence class of the product, suggesting requirements for implementation. The conceptual frame-work is evaluated by utilising a case study in a learning factory. Here, the model-mix assembly is controlled actively by the workpiece carrier in terms of transferring the variant-specific work instructions to the operator and the collaborative robot (cobot) at the workstations. The resulting system thus enables better exploitation of the poten-tials through less frequent errors and shorter search times. Such an implementation has demonstrated that the intelligent workpiece carrier represents an additional part for realising a cyber-physical production system (CPPS).
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.
The Covid-19 virus has triggered a worldwide pandemic and therefore many employees were required to work from home which caused numerous challenges. With the Covid-19 pandemic now in its third year, there are already several studies available on the subject of home offices. To investigate the impact of remote work on employee satisfaction and trust, this quantitative study aims to review existing results and formulate hypotheses based on a conceptual model created through a qualitative study and extensive literature review. The research question is as follows: Does home office during Covid-19 affect employee satisfaction and trust? To test the hypotheses, a structural equation model was constructed and analyzed. The culture of trust and flexibility are identified as the biggest influencing factors in this study.
Do Chinese subordinates trust their German supervisors? A model of inter-cultural trust development
(2023)
In this qualitative study based on 95 interviews with Chinese subordinates and their German supervisors, we inductively develop a model which advances theoretical understanding by showing how inter-cultural trust development in hierarchical relationships is the result of six distinct elements: the subordinate trustor’s cultural profile (cosmopolitans, hybrids, culturally bounds), the psychological mechanisms operating within the trustor (role expectations and cultural accommodation), and contextual moderators (e.g., country context, time spent in foreign culture, and third-party influencers), which together influence the trust forms (e.g., presumptive trust, relational trust) and trust dynamics (e.g., trust breakdown and repair) within relationship phases over time (initial contact, trust continuation, trust disillusionment, separation, and acculturation). Our findings challenge the assumption that cultural differences result in low levels of initial trust and highlight the strong role the subordinate’s cultural profile can have on the dynamics and trajectory of trust in hierarchical relationships. Our model highlights that inter-cultural trust development operates as a variform universal, following the combined universalistic-particularistic paradigm in cross-cultural management, with both culturally generalizable etic dynamics, as well as culturally specific etic manifestations.
This introductory chapter starts with a brief discussion about the differences between the long-standing perspective of sports marketing and more modern sports marketing approach. The discussion leads to the ultimate question whether sports marketing can be seen as a new and independent marketing discipline rather than a normal form of marketing. In addition, a coherent definition of sports marketing will be presented which serves as the underlining definition of this edition volumen. Then the most important characteristics of sports of a marketing perspective will be explained using some real-life examples. The structure as well as the individual chapters of this book will be introduced in the following. This first chapter concludes with the introduction of the German Institute for Sports Marketing which has been founded by the editors of this book.
Marketing in sports
(2014)
In this chapter the principals of marketing will be explained an transferred to the contex of sports. Following a brief introduction the principles of marketing will be outlined and explained in further detail. Then the subject of sports marketing will be introduced from different perspectives using various definitions and approaches. Afterwards the focus is on the unique characteristics of sports marketing before a model of sports marketing will be presented. Then it will be shown how professional sporting organisations might market their products an themselves. The chapter concludes with a detailed case study using the example of FC St. Pauli which is one of only few real brands in German sports.
This chapter presents the diverse facets of sports marketing in Western Europe. It showcases the most important types of sports, most significant leagues, bestknown clubs, most popular athletes and the biggest sporting events in Western Europe while elaborating on the relevant aspects of sports marketing. We examine European sportsconsumers, characterise the sports marketing market in Western Europe an explain the current scientific/academic status of sports marketing. Moreover, we illustrate the motives for the internationalisation taking place in sports marketing. In conclusion, this chapter includes an international case study on the entry of the NFL into the European market.
Although sports is generally defined as motor activity, it has always been much more than that. Since management and sports follow the same objective of achieving highest performance, correlation between these two fields nowadays become increasingly interesting in terms of corporate strategy. This chapter aims to point out how organisations as well as individuals can benefit from the general and psychological values and strategies of sports, by first looking at the general framework of professional sports an futher applying approaches from various types of sports directly to certain business functions like general management, human resource management and marketing management. The chapter concludes with an international case study and brief outlook.
This concluding chapter summarises and discusses the different parts and findings of the anthology on hand. The main statements and conclusions of each chapter are presented. Following up, the editors try to look into the future of the sports business and sports management in general and the future of sports marketing in particular and draw a final conclusion.
As long as there have been professional sports, there have been relationships on different levels. For example, sponsorship (or patronage as it was called in the early days) was mostly based on personal relations between the local benefactors and their favourite sports club. Regarding media, clubs always maintained special relationships with selected journalists. The bond between fans and their clubs was always a close and mutually beneficial one. All these relationships existed from the start of the sports business. Therefore, relationship marketing is nothing new in the context of sports. Many sporting organisations always knew to value a deep and good relationship with their stakeholders and practised relationship marketing without being aware of it. Successful sports managers, however, take the old wisdom and turn it into a modern relationship marketing approach by structuring the various relationships in order to make them more effective and profitable for the own sporting organisation and the various stakeholders. This chapter ... illustrates the many facets of relationship marketing and the possibilities it offers in the context of the sports business.
Executive education in IS is under the scrutiny of many institution for the potential to bring in financial revenues. However teaching executives can be a very challenging task because of the previous experiences, variation in their previous education, and multiplicity of motivations for pursuing a continuous education. The panel aims at sharing successful experiences and highlighting challenges of dealing with executive audiences. The panel will present the results of a large survey among executive students and identify the three most significant elements emerged from the survey: the importance of theory that is actionable, the importance of varied pedagogical tools and practices, and the importance of relevance beyond practical tools. Based on a survey that will be distributed to the audience at the beginning of the panel, the audience will be actively engaged in sharing their experiences on the three topics aiming at capitalize and sum up the collective knowledge of the room.
Twitter and citations
(2023)
Social media, especially Twitter, plays an increasingly important role among researchers in showcasing and promoting their research. Does Twitter affect academic citations? Making use of Twitter activity about columns published on VoxEU, a renowned online platform for economists, we develop an instrumental variable strategy to show that Twitter activity about a research paper has a causal effect on the number of citations that this paper will receive. We find that the existence of at least one tweet, as opposed to none, increases citations by 16-25%. Doubling overall Twitter engagement boosts citations by up to 16%.
IOS 2.0 : new aspects on inter-organizational integration through enterprise 2.0 technologies
(2015)
This special theme of „Electronic Markets“ focuses on research concerned with the use of social technologies and "2.0" principles in the interaction between organization (i.e., with "inter-organizational systems (IOS) 2.0"). This theme falls within the larger space of Enterprise 2.0 research, but focuses in particular on inter-organizational use (between enterprises), not intra-organizational use (in a single enterprise). While there is great interest in practice regarding the use of 2.0 technologies to support intra-organizational communication, collaboration and interaction, information systems (IS) research has largely been oblivious to this important use of social technologies.
Development of an IoT-based inventory management solution and training module using smart bins
(2023)
Flexibility, transparency and changeability of warehouse environments are playing an increasingly important role to achieve a cost-efficient production of small batch sizes. This results in increasing requirements for warehouses in terms of flexibility, scalability, reconfigurability and transparency of material and information flows to deal with large number of different components and variable material and information flows due to small batch sizes. Therefore, an IoT-based inventory management solution and training module has been developed, implemented and validated at Werk150 – the Factory on campus of the ESB Business School. Key elements of the developed solution are smart bins using weight mats to track the bin’s content and additional sensors and buttons which are connected to an IoT – Hub to collect data of material consumption and manual handling operations. The use of weight mats for the smart bins offers the possibility to measure the container content independent of the specific component geometry and thus for a variety of components based on the specific component weights. The developed solution enables focusing on key for success elements of the system to provide synchronization of the flow of materials and information resulting an increase of flexibility and significantly higher transparency of the material flow. AIbased algorithms are applied to analyse the gathered data and to initiate process optimizations by providing the logistics decision makers a profound and transparent basis for decision making. In order to provide students and industry visitors of the learning factory with the necessary competences and to support the transfer into practice, a training module on IoT-based inventory management was developed and implemented.
Traditional communication of research on climate change fails to encourage individual, corporate, and political leaders to take appropriate action. We argue that this problem is based on an overly simplistic unidirectional model of science communication. Conversely, theory shows that active learning processes are better suited to initiate and mobilize engagement among all stakeholders. Here, we integrate theoretical insights on active learning with empirical evidence from serious gaming: communication should be understood as an integral design feature that relates active learning on climate change to tangible action.
Customer relationship management (CRM) is one of the most frequently adopted management tools and has received much attention in the literature. From a company-wide perspective, CRM is viewed as a complex process requiring interventions in different company areas. Previous research has already highlighted the pitfalls and failures related to a partial and incomplete view of CRM. This study advances research on CRM by investigating the impact of the relative implementation time according to which interventions are implemented in different areas (customer management, CRM technology, organizational alignment, and CRM strategy) on CRM performance. The results of the empirical study reveal that compared to other critical CRM activities, a later implementation of organizational alignment activities has a negative impact on performance. Further, our results show that CRM implementations do not equally address the areas of customer acquisition, growth, and loyalty, since this clearly depends on company objectives and also on geographical differences.
The paper describes a new stimulus using learning factories and an academic research programme - an M.Sc. in Digital Industrial Management and Engineering (DIME) comprising a double degree - to enhance international collaboration between four partner universities. The programme will be structured in such a way as to maintain or improve the level of innovation at the learning factories of each partner. The partners agreed to use Learning Factory focus areas along with DIME learning modules to stimulate international collaboration. Furthermore, they identified several research areas within the framework of the DIME program to encourage horizontal and vertical collaboration. Vertical collaboration connects faculty expertise across the Learning Factory network to advance knowledge in one of the focus areas, while Horizontal collaboration connects knowledge and expertise across multiple focus areas. Together they offer a platform for students to develop disciplinary and cross-disciplinary applied research skills necessary for addressing the complex challenges faced by industry. Hence, the university partners have the opportunity to develop the learning factory capabilities in alignment with the smart manufacturing concept. The learning factory is thus an important pillar in this venture. While postgraduate students/researchers in the DIME program are the enablers to ensure the success of entire projects, the learning factory provides a learning environment which is entirely conducive to fostering these successful collaborations. Ultimately, the partners are focussed on utilising smart technologies in line with the digitalization of the production process.
Over the last 50 years, neoclassical financial theory has been dominating our perception of what is happening in financial markets. It has spurred numerous valuable theories and concepts all based on the concept of Homo Economicus, the strictly rational economic man. However, humans do not always act in a strictly rational manner. For students and practitioners alike, our book aims at opening the door to another perspective on financial markets: a behavioral perspective based on a Homo Oeconomicus Humanus. This agent acts with limited rationality when making decisions. He/she uses heuristics and shortcuts and is prone to the influence of emotions. This sounds familiar in real life and can be transferred to what happens in financial markets, too.
Indicators of disruption potentials - analysis of the blockchain technology’s potential impact
(2019)
The goal of this paper was to answer the question whether blockchain has the potential to become a disruption according to Clayton Christensen’s disruption theory. Therefore, the theory and the five characteristics that define the process of disruption were outlined in the first part of the paper. That and the following explanation of the blockchain technology served as the basis for the analysis and evaluation in chapters four to seven. For the analysis, three applications of the DLT, namely payment methods, intermediaries, as well as data storage and transfer, were considered. The fulfillment of the five characteristics of disruption was assessed using an example for each of the three applications.
Additionally, the paper might serve as a basis for future research on the topic, once the technology develops further, since it is generally hard to tell whether the fourth and fifth characteristics are fulfilled by blockchain at this point. Therefore, the results of the paper also back criticism of Christensen’s theory regarding its usefulness for predictions.
This paper suggests that, in the financial services industry, too, the impact of blockchain will be significant. However, given the manifoldness of the services that are part of the industry, it cannot generally be concluded whether the DLT will disrupt the industry. For example, in services related to payment methods, blockchain is unlikely to follow disruptive pattern, despite the recent hype surrounding blockchain-based cryptocurrencies. However, regarding data storage and transfer, the technology might as well follow disruptive pattern in the financial services industry just as the application of blockchain solutions has been doing in the healthcare industry.
The intention of this paper is to show that the statistical approach to risk is not enough to explain the behavior of investors. It furthermore proposes ideas and alternative approaches on how to deal with risk. Psychological findings are of particular interest as they might enhance our understanding of risk perception and assessment. The chapter “From the normal distribution to fat tails” starts with the rejection of the normal distribution as a simplifying basis for risk and return. This rejection is supported by several empirical observations like clustering of volatility and fat tails. This leads to a two-step approach for modeling risk and return based on the distinction of conditional and un-conditional changes. Conditional time series models (ARMA, ARCH, GARCH) and alternative distributions are presented (Stable Paretian, Student’s T, EVT) as a way to improve the art of risk and return modeling beyond the normal distribution assumption. The chapter ends with the conclusion that each model is only a statistical approximation and never encompasses the unpredictability of black swans and the nature of human behavior in the financial markets. After having discussed the limitations of the purely statistical approach to risk and return this paper goes beyond the standard theory of finance for two purposes. Firstly, behavioral finance provides some arguments for the limitation of statistics in assessing risk. Secondly, an alternative approach to risk perception is presented. This alternative is called Prospect Theory, a rather psychology-based approach using preferences to explain investors’ actions by human behavior in decision making processes. Starting point is the utility function and the value function followed by a description of the two phases: framing and evaluation. The value function is then clearly distinguished from the utility function by elaborating certain effects like reference points, loss aversion or the weighting function. In this section the paper enters the arena of human risk perception which is far from being monetarily rational in the sense of the homo oeconomicus. With Cumulative Prospect Theory there exists an extension to multiple outcome scenarios where risk does not necessarily have to be known. In such a situation, besides risk, there also exists immeasurable uncertainty. Current research confirms and rejects parts of (Cumulative) Prospect Theory which is not necessarily a bad sign as human behavior is rarely exactly replicable and the complexity does not really allow generalizations. Therefore, even if the theory is not completely correct it still enhances our understanding of risk perception and human decision making which can be a very valuable input for agent-based models. The next chapter analyses in more detail possible distortions from psychological biases in the assessment of risk. In this context the law of small numbers, overconfidence and feelings/experience are discussed. Knowing these biases complicates the idea of developing a risk model even further. However, this is again another step to better understand the underlying processes and motives of decision making in the context of financial markets. The last chapter is an attempt to link the different aspects to get a holistic view on risk behavior. Two possibilities are discussed: Hedonic psychology, with the distinction between blow up and bleeding strategy, and heuristic-based explanations for real observations like clustering of expectations and trust in experts. This leaves space for further research as we do not have a tool that is based on current findings and can actually help us in explaining and predicting behavior in financial markets. One possibility would be to link all these aspects in the approach of computational finance to develop agent-based models in which market observations, psychological findings and the situational context can be integrated.
In a recent publication Novy-Marx (2013) finds evidence that the variable gross profitability has a strong statistical influence on the common variation of stock returns. He also points out that there is common variation in stock returns related to firm profitability that is not captured by the three-factor model of Fama and French (1993). Thus, this thesis augments the three-factor model by the factor gross profitability and examines whether a profitability-based four-factor model is able to better explain monthly portfolio excess returns on the German stock market compared to the three-factor model of Fama and French (1993) and the Capital Asset Pricing Model (CAPM). Based on monthly stock returns of the CDAX over the period July 2008 to June 2014 this thesis documents four main findings. First, a significant positive market risk premium and a significant positive value premium can be identified. No evidence is found for a size or a profitability effect. Second, all included factors have a strong significant effect on monthly portfolio excess returns. Third, the four-factor model clearly outperforms both the three-factor model of Fama and French (1993) and the CAPM in capturing the common variation in monthly portfolio excess returns. The CAPM performs worst. Finally, the results indicate that the three-factor model of Fama and French (1993) is somewhat better in explaining the cross-section of portfolio excess returns than the four-factor model. Again, the CAPM performs worst. Nevertheless, the four-factor model is considered to be an improvement over the three-factor model of Fama and French (1993) and the CAPM in determining stock returns on the German stock market.
In a corporation’s financial life “going public” by means of an IPO is probably the single most important decision. It turns a private company into a public one. Our book will provide an inside view of the IPO process. On the one hand, it draws on the insights of an experienced investment banker, who has gone through numerous IPO transactions. On the other hand, it relates the story of an actual IPO through the eyes of a Chief Executive Officer who has taken two of his companies public. This unique double perspective is our book’s defining feature. We do not discuss initial public offerings in a textbook style fashion. What we would like to bring out is a more comprehensive portrayal of a “once-in-a-lifetime” event for most companies and their management, alike.
Rising consumption due to a growing world population and increasing prosperity, combined with a linear economic system have led to a sharp increase in garbage collection, general pollution of the environment and the threat of resource scarcity. At the same time, the perception of environmental protection becomes more sensitive as the consequences of neglecting sustainable business and eco-efficiency become more visible. The Circular Economy (CE) could reduce waste production and is able to decouple economic growth from resource consumption, but most of the products currently in use are not designed for the reuse-forms of the CE. In addition, the decision-making process of the End of-Usage (EoU) products regarding the following steps has further weaknesses in terms of economic attractiveness for the participants, which leads to low return rates and thus the disposal is often the only alternative.
This paper proposes a model of the decision-making process, which uses machine learning. For this purpose, a Machine Learning (ML) classification is created, by applying the waterfall model. An artificial neural network (ANN) uses information about the model, use phase and the obvious symptoms of the product to predict the condition of individual components. The resulting information can be used in a downstream economic and ecological evaluation to assess the possible next steps. To test this process comprehensive training data is simulated to train the ANN. The decentralized implementation, cost savings and the possibility of an incentive system for the return of an end-of-usage product could lead to increased return rates. Since electronic devices in particular are attractive for the CE, laptops are the reference object of this work. However, the obtained findings are easily applicable to other electronic devices.
Because of a high product and technology complexity, companies involve external partners in their research and development (R&D) processes. Interorganizational projects result, which represent temporary organizations. In these projects heterogenous organizations work closely together. Since project work is always teamwork, these projects face due to their characteristic’s major challenges on an organizational, relational, and content-related collaboration level. Thus, this paper raises the following research question: “How can a project team be supported on an organizational, relational, and content-related level in an interorganizational new product development setting?” To answer this research question, an explorative expert study was set up with two digital workshops using the interactive presentation tool Mentimeter. The results show that a cooperative innovation culture could support project teams on an organizational and relational level in the future in minimizing predominant problems. Moreover, it supports project teams for example in a functional communication. Furthermore, 18 values of a cooperative innovation culture result which are for example openness and transparency, risk and failure tolerance or respect. On a content-related level the results show that an adaptable tool which promotes creativity and collaboration method as well as content-related input support could be beneficial for problem-solving in an interorganizational new product development setting in the future. Because the tool can guide product developers through the process with suitable creativity and collaboration methods, can give content-related input and can enable interactive interchange on a table-top. Future research could mainly focus on the connection of the cooperative innovation culture and the tool since these potentially influence each other.
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.
A closed-loop control for a cooperative innovation culture in interorganizational R&D projects
(2022)
Since project managers only have a limited authority in interorganizational R&D projects a cooperative innovation culture is essential for team cohesion and thus for achieving project scope in time and cost. For its development different factors depending on underlying values are essential. These factors must be learned iteratively by the project members so that they are living the values of a cooperative innovation culture. Hence, this paper raises the following research question: “How to control living the values of a cooperative innovation culture in interorganizational R&D projects?” To answer this question, a closed-loop control for a cooperative innovation culture is developed. The developed closed-loop control system includes several different functional units which show essential roles and several different variables which show what to consider and design in the control system. In addition, the developed closed-loop control system is generalized for other types of projects such as intraorganizational projects.
Project managers still face management problems in interorganizational Research and Development (R&D) projects due to their limited authority. Addressing a project culture which is conducive to cooperation and innovation in interorganizational R&D project management demands commitment of individual project members and thus balances this limited authority. However, the relational collaboration level at which project culture manifests itself is not addressed by current project management approaches, or it is addressed only at a late stage. Consequently, project culture develops within a predefined framework of project organization and organized contents and thus is not actively targeted. Therefore, a focus shift towards project culture becomes necessary. This can be done by a project-culture-aware management. The method CLIPS actively supports interorganizational project members in this kind of management. It should be integrable in the common project management approaches, that with its application all collaboration levels are addressed in interorganizational R&D project management. The goal of this paper is to demonstrate the integrability of the method CLIPS and show how it can be integrated in common project management approaches. This enriches interorganizational R&D project management by a project culture focus.
Since project managers still face problems in managing interorganizational R&D projects, it is a promising approach to manage these projects project-culturally-aware. However, an important prerequisite for a project-culture-aware management is that the involved individual organizations pursue a collaborative strategy. Therefore, our article provides a conceptual approach including a new tool, the Collaborative Iron Triangle, which supports both project sponsors and managers in different phases of the collaboration process to pursue a collaborative strategy in interorganizational R&D projects.
Supply chains have evolved into dynamic, interconnected supply networks, which increases the complexity of achieving end-to-end traceability of object flows and their experienced events. With its capability to ensure a secure, transparent, and immutable environment without relying on a trusted third party, the emerging blockchain technology shows strong potential to enable end-to-end traceability in such complex multitiered supply networks. However, as the dissertation’s systematic literature review reveals, the currently available blockchain-based traceability solutions lack the ability to map object-related supply chain events holistically, which involves mapping objects’ creation and deletion, aggregation and disaggregation, transformation, and transaction. Therefore, this dissertation proposes a novel blockchain-based traceability architecture that integrates governance and token concepts to overcome the limitations of existing architectures. While the governance concept manages the supply chain structure on an application level, the token concept includes all functions to conduct object-related supply chain events. For this to be possible, this dissertation’s token concept introduces token ‘blueprints’, which allow clients to group tokens into different types, where tokens of the same type are non-fungible. Furthermore, blueprints can include minting conditions, which are, for example, necessary when mapping assembly or delivery processes. In addition, the token concept contains logic for reflecting all conducted object-related events in an integrated token history. This ultimately leads to end-to-end traceability of tokens and their physical or abstract representatives on the blockchain. For validation purposes, this dissertation implements the architecture’s components and their update and request relationships in code and proves its applicability based on the Ethereum blockchain. Finally, this dissertation provides a scenario-based evaluation based on two industrial case studies from a manufacturing and logistics perspective to validate the architecture’s capabilities when applied in real-world industrial settings. The proposed blockchain-based traceability architecture thus covers all object-related supply chain events derived from the two industrial case studies and therefore proves its general-purpose end-to-end traceability capabilities of object flows.
The fifth mobile communications generation (5G) can lead to a substantial change in companies enabling the full capability of wireless industrial communication. 5G with its key features of providing Enhanced Mobile Broadband, Ultra-Reliable and Low-Latency Communication, and Massive Machine Type Communication will support the implementation of Industry 4.0 applications. In particular, the possibility to set-up Non-Public Networks provides the opportunity of 5G communication in factories and ensures sole access to the 5G infrastructure offering new opportunities for companies to implement innovative mobile applications. Currently there exist various concepts, ideas, and projects for 5G applications in an industrial environment. However, the global rollout of 5G systems is a continuous process based on various stages defined by the global initiative 3rd Generation Partnership Project that develops and specifies the 5G telecommunication standard. Accordingly, some services are currently still far from their final performance capability or not yet implemented. Additionally, research lacks in clarifying the general suitability of 5G regarding frequently mentioned 5G use cases. This paper aims to identify relevant 5G use cases for intralogistics and evaluates their technical requirements regarding their practical feasibility throughout the upcoming 5G specifications.
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.
Towards a model for holistic mapping of supply chains by means of tracking and tracing technologies
(2022)
The usage of tracking and tracing technologies not only enables transparency and visibility of supply chains but also offers far-reaching advantages for companies, such as ensuring product quality or reducing supplier risks. Increasing the amount of shared information supports both internal and external planning processes as well as the stability and resilience of globally operating value chains. This paper aims to differentiate and define the functionalities of tracking and tracing technologies that are frequently used interchangeably in literature. Furthermore, this paper incorporates influencing factors impacting a sequencing of the connected world in Industry4.0 supply chain networks. This includes legal influences, the embedment of supply chain-related standards, and new possibilities of emerging technologies. Finally, the results are summarized in a model for the holistic mapping of supply chains by means of tracking and tracing technologies. The resulting technological solutions that can be derived from the model enable companies to address missing elements in order to enable the holistic mapping of supply chain events as well as the transparent representation of a digital shadow throughout the entire supply chain.
Recently, blockchain-based tokens have earned an important role in fields such as the art market or online gaming. First approaches exist, which adopt the potentials of blockchain tokens in supply chain management to increase transparency, visibility, automation, and disintermediation of supply chains. In context, the tokenization of assets in supply chains refers to the practice of creating virtual representations of physical assets on the blockchain. Solutions in supply chain management based on the tokenization of assets vary in terms of application objectives, token types, asset characteristics, as well as the complexities of supply chain events to be mapped on the blockchain. Currently, however, no review exists that summarizes the characteristics of blockchain-based tokens and their scope of applications. This paper provides a clear terminological distinction of existing blockchain token types and therefore distinguishes between fungible tokens, non-fungible tokens, smart non-fungible tokens, and dynamic smart non-fungible tokens. Subsequently, the token types are classified regarding their traceability, modifiability, and authorization to evaluate suitability for mapping assets in supply chains. Given the potential of blockchain in supply chain management, the results of the review serve as a foundation for a practical guide supporting the selection process of suitable token types for industrial applications.