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The 17 SDGs, as agreed upon by the international community, are designed to be implemented across all levels of human activity. Alongside the level of international politics, this also includes the local levels, national politics, wider society, and the economic sphere. Many channels are called on to further implementation, including the transfer of technology to developing and emerging countries. As the patent holders, this must include the active participation of companies. While the literature examines the important role of technology transfer in North-South business-to-business (B2B) partnerships, studies on the technology transfer between European and African companies are scarce. Therefore, in this study we use original data from 26 interviews conducted with managers engaged in sales partnerships between German manufacturers and their distributors in African markets to examine the existence and forms of technology transfer. We find that training and marketing excellence are the predominant forms of technology transfer and based on that suggest a refinement of established frameworks on B2B technology transfer.
The dawn of the 21st Century has witnessed a tremendous increase in trade pacts among nations, resulting in renewed hopes for sustainable enterprise development in emerging economies worldwide. Ghana and other sub-Saharan African (SSA) countries have signed onto several North-South and South-South free trade agreements with the hope of strengthening their presence in the international trade arena, and to promote economic growth in SSA. For over two decades, however, very little has changed, and many have dashed their high hopes as enterprises continue to struggle in SSA. Not even the African Continental Free Trade Agreement (AfCFTA) could renew the hopes of sceptics. Several studies opined that enterprises in SSA could improve their domestic and international competitiveness by establishing mutually beneficial partnerships with their counterparts from the Global North and South. This study delved into the issues that affect North-South and South-South business collaborations and recommends key success factors that could help promote mutually beneficial cross-border business partnerships. The research includes both literature and empirical information on the key success factors of business partnerships between African enterprises as well as between African enterprises and firms from the Global North. We approached the study qualitatively using a phenomenological research design. Research participants included important stakeholders in Africa and Europe's international trade and sustainable enterprise development ecosystem. The study identified several challenges with the current business collaborations and recommended new ways of making such partnerships more beneficial.
Internet of things innovations and the industrial internet these days become more and more decisive factors of future success for companies. Especially manufacturing oriented SME will face the challenge to develop innovative technology driven business models alongside technology innovations in this field which will be essential for future competitiveness. Failing in developing these technology driven business models in an internationally highly competitive environment will have a serious impact both on companies and on the society. Hence, securing economic stability and success of these technology driven business models is an indispensable task. To identify challenges for innovative industrial internet business models first it is necessary to understand what the industrial internet means to the leading parties and applying companies and start-ups in the field. Second, challenges from general business model development will be outlined. In a third step risks and challenges in business model development will be discussed with regard to the special characteristics of technology driven business models in the context of the industrial internet and the important role of the technological key component of the business model. Especially the capability to deal with an integrated consideration of the indivisible linked dimensions of economic and technological aspects of these business models is questioned. In the fourth place the specific challenges for industrial internet business models are derived. On the basis of these results it is also discussed what might be done to handle these challenges successfully with the goal to turn them into chances. The need for future research on the integration of the risk management perspective into the development of these technology driven business models is derived. This will help established companies and start-ups to realize great technological innovations for the industrial internet in sound and successful innovative business models.
The financial crisis of 2007-2010 was probably one of the greatest, most lustrous black-swan events that people of our generation(s) will experience – and at its heart, it was a dynamic phenomenon. It is stated in the vision of the System Dynamics Society that we aspire to transform society by influencing decision-making. Yet, it seems as if system dynamics did not play any significant role in this crisis: we did not examine the markets, we did not provide insights to banks, and we did not warn governments or the people. In our presentation we describe the dynamics involved in a housing bubble, and describe what made the last one different. With the insights gained from this exercise we conclude that, from a system dynamics perspective, the dimension of the financial crisis of 2007-2009 was eminently foreseeable, which will lead us to pose the following question: where were we as a field while this crisis was unfolding, why were we not active players? We present a range of potential answers to this question, hoping to provoke some reflection… and maybe some (re)action.
Increasing flexibility, greater transparency and faster adaptability play a key role in the development of future intralogistics. Ever-changing environmental conditions require easy extensibility and modifiability of existing bin systems. This research project explores approaches to transfer the Internet of Things (IoT) paradigm to intralogistics. This allows a synchronization of the material and information flow. The bin is enabled by the implementation of adequate hardware and software components to capture, store, process and forward data to selected system subscribers. Monitoring the processes in the intralogistics by means of the smart bin system ensures the implementation of appropriate actions in case of defined deviations. By using explorative expert interviews with representatives from the automotive and pharmaceutical industries, seven practical application scenarios were defined. On this basis, the requirements of smart bin systems were examined. For each individual case of application, a system model was created in order to obtain an overview of the system components and thus reveal similarities and differences. Based on the similarities of the system models, a general requirement profile was derived. After the hardware components of the bin system had been determined, a utility analysis was carried out to find the adequate IoT software. The utility analysis was conducted with a focus on data acquisition and data transfer, data storage, data analysis, data presentation as well as authorization management and data security. The results show that there is great interest in easily expandable and modifiable bin systems, as in all cases, the necessary information flow in the existing bin system has to be improved by means of new IoT hardware and software components.
Reacting to ever-changing business environments, in the last decade complex systems of systems accomplished giant leaps forward leading to great technological flexibility. However, this dimension of flexibility is often limited by the rigidity of super-ordinated planning systems. Especially when hybrid teams of automated and human resources are in place, the dynamic assignment of tasks taking into account ergonomics remains a challenge. After exposing a gap in the state of the art on the topic, this paper presents an approach to include ergonomics in dynamic resource allocation models. Combining and complementing existing approaches, the presented method monitors the actual ergonomic burden of the resources during a shift and it provides a linear optimization model to steer the resource allocation process.
Ambitious goals set by the European Union strategy towards the emission reduction of multimodal logistic chains and new requirements for intermodal terminals set by the evolution of customer needs, contribute to a shift in the driver for the infrastructure development: from economy of scale to economy of density. This paper aims to present an innovative method for designing a process oriented technology chain for intermodal terminals in order to fulfill these new demanding requirements. The results of the case study of the Zero Emission Logistic Terminal Reutlingen are presented, highlighting how this particular context enables the design and development of a modular concept, paving the way for the generalization of the findings towards the transfer to similar contexts of other European cities.
Rapidly growing population and increasing amount of shipments induced by the e-commerce are two of the main reasons for the constantly rising urban freight traffic. Cities are therefore overwhelmed by a growing stream of goods and the available infrastructure, shared between people and goods traffic, often reached its maximum capacity. Phenomena such as traffic congestion, pollution and lack of space are direct consequences of this trend and their impact on the quality of life in the city is not negligible. City administrations are keen to evaluate innovative city logistics concepts and adopt alternative solutions, to overcome the challenges posed by such a dynamic environment, constrained in existing infrastructure. In this paper, a heuristic method based on the utility analysis is presented. Thanks to a modular approach accounting for stakeholders´ requirements, possible different scenarios and available technologies, the development of new city logistic concepts is supported. The proposed method is then applied to a case study concerning the city of Reutlingen (Germany). Results are presented and a brief discussion leads to the conclusion.
The success of an autonomous robotic system is influenced by several interdependent factors not easily identifiable. This paper is set to lay the foundation of a new integrated approach in order to deeply examine all the parameters and understand their contribution to success. After introducing the problem, two cutting edge autonomous systems for the process of unloading of containers will be presented. Then the STIC analysis, a recently developed method for modelling and interpreting all the parameters, will be introduced. The preliminary results of applying such a methodology to a first study case, based on one of the two systems available to the authors, will be shortly presented. Future research is in the end recommended in order to prove that this methodology is the only way to efficiently and effectively mitigate the risk that stops potential users from investing in autonomous systems in the logistics sector.
Latest advancements in new technologies have made it possible to fully automate the in-plant material flow of small load carriers between the warehouse and the production or assembly line. However, none of methods available in literature fully addresses the planning and dimensioning problem of a logistic system based on these new autonomous technologies. This paper is set to present a method to estimate the fleet size of the new logistic system. After an overview on the state of the art, the method based on combinatorics and probability theory will be explained. A short discussion and suggestions for forthcoming research will conclude the paper.
Milk-run systems are becoming more and more popular when it comes to in-plant material supply. Planning and dimensioning such a system poses challenges, which are difficult to overcome, especially in scenarios characterized by a large number of hard constraints and by well-established processes. This paper is set to ease the task of the planner by presenting an innovative flexible method for the planning and dimensioning of in-plant milk-run systems in high constrained scenarios. After an overview on tugger train systems and existing planning methods, an extensive description of the new method will be given. The new method proposed will be critically analyzed and discussed before suggesting forthcoming research.
The EU funded project RobLog recently developed a system able to autonomously unload coffee sacks from a standard container. Being the first of its kind, a further development is needed in order for the system to be competitive against manual labor. Financing this development entails a risk, hence a justified skepticism, which can be overcome by the longsighted view of the existing market potential. This paper presents a method to estimate the market potential of autonomous unloading systems for heavy deformable goods. Starting from the analysis of the coffee trade, first the current coffee traffic is investigated in order to calculate the number of autonomous systems needed to handle the imported sacks; Results are validated and the method is extended for the calculation of the potential of other market segments, where the same unloading technology can be applied.
The seamless fusion of the virtual world of information with the real physical world of things is considered the key for mastering the increasing complexity of production networks in the context of Industry 4.0. This fusion, widely referred to as the Internet of Things (IoT), is primarily enabled through the use of automatic identification (Auto-ID) technologies as an interface between the two worlds. Existing Auto-ID technologies almost exclusively rely on artificial features or identifiers that are attached to an object for the sole purpose of identification. In fact, using artificial features for the purpose of identification causes additional efforts and is not even always applicable. This paper, therefore, follows an approach of using multiple natural object features defined by the technical product information from computer-aided design (CAD) models for direct identification. By extending optical instance-level 3D-Object recognition by means of additional non-optical sensors, a multi-sensor automatic identification system (AIS) is realised, capable of identifying unpackaged piece goods without the need for artificial identifiers. While the implementation of a prototype confirms the feasibility of the approach, first experiments show improved accuracy and distinctiveness in identification compared to optical instance-level 3D-Object recognition. This paper aims to introduce the concept of multisensor identification and to present the prototype multi-sensor AIS.
So-called cloud-based management information systems are a fairly new phenomenon in management accounting in recent years. Quite a few companies (and especially their business managers and management accountants) do not always work via the cloud, but with hybrid solutions or on-premise solutions of ERP software such as SAP or Oracle, but often still with "manual" solutions such as Microsoft Excel.
Early exposure makes the entrepreneur: how economics education in school influences entrepreneurship
(2022)
Many countries that seek to boost their economy share the goal of promoting entrepreneurship. Whereas there is ample research on the predictors of entrepreneurship during adulthood, we know little about how pre-adulthood experience influences entrepreneurship later in life. Using a natural experiment, this paper examines whether introducing economics classes in school enhances entrepreneurial behavior in adulthood. Our difference-in-differences approach exploits curricula reforms across German states that introduced compulsory economics education classes in secondary schools. Using information on school and labor market careers for more than 10,000 individuals from 1984 to 2019, we find that the reform increases students’ entrepreneurial activities by three percentage points. Examining gender differences, we find that economics classes equally benefit female and male students. Our results advance our understanding of how pre-adulthood experiences shape individuals’ entrepreneurial behavior.
In a recently developed study programme at Reutlingen University, which focuses on practical orientations, an innovative product with solid company references is to be defined and realised by student teams. On the basis of this product, all subjects of the business engineering study programme “Sustainable Production and Business” are taught. By focusing on three main paths of future skills that have been developed by NextSkills to analyse upcoming social changes, global challenges and fields of work that are innovation-driven and agile, the new study programme aims to create responsible leaders who will shape global businesses respectfully. Thereby, different TRIZ tools help to support students in developing their own products with a focus on sustainability and pay off on the future skills enhancement. Further, students get to know TRIZ tools in an unbiased way, unburdened by too much theory, and are thus continuously supported in the progressing product development process that accompanies their studies. Hence, students perceive TRIZ on the one hand as a method to develop sustainable products and, on the other hand, to find sustainable solutions for everyday problems. The knowledge and positive experiences gained in this way should then arouse curiosity for the TRIZ class at the end of the study programme. The students can graduate with a TRIZ Level 1 certificate. Thereby, as many students as possible are introduced to the TRIZ methods, and the TRIZ tool is spread widely.
Governments and public institutions increasingly embrace digital opportunities to involve citizens in public issues and decision making. While public participation is generally seen as an important and promising venture, the design of the participation processes and the utilized digital infrastructure poses challenges, especially to the public sector. Instead of limiting conceptual guidance and exchange to one domain, we therefore develop a taxonomy for digital involvement projects that unites the domains of e-participation, citizen science and crowd-X. Embedded in a design science research approach, we follow an iterative design process to elaborate the key characteristics of a digital involvement project based on the participation process, its individuals and digital infrastructure. Through evaluating the artifact in a focus group with domain practitioners, we find support for the usefulness of our taxonomy and its ability to provide guidance and a basis for discussion of digital involvement projects across domains.
Production systems are becoming increasingly complex, which means that the main task of industrial maintenance, ensuring the technical availability of a production system, is also becoming increasingly difficult. The previous focus of maintenance efforts on individual machines must give way to a holistic view encompassing the whole production system. Against this background, the technical availability of a production system must be redefined. The aim of this publication is to present different definition approaches of production systems’ availability and to demonstrate the effects of random machine failures on the key figures considering the complexity of the production system using a discrete event simulation.
It has been recognized that to increase the competetitiveness of international higher education institutions in the global education market, their international graduates' employability must be enhanced. The present paper investigates, from the employers' perspective, the possibilities of international graduates with domestic degrees in Russia and Germany to find jobs in the Russian and German labor market. It uses qualitative open-ended interviews at 12 companies in St. Petersburg, Russia and Germany, which are engaged with International Business activities. The investigation concentrates on the employment opportunities and barriers of international graduates from an individual, organizational and an institutional perspective.
The research highlighted the main differences and similarities in the perception of the HR managers in both countries. In the German labor market, companies have a high demand for international graduates, especially those operating internationally, highly demand international graduates, emphasizing the existence of international trainee programs and the need to reflect the diversity of their business in the diversity of their staff. In contrast, Russian companies showed a positive predisposition for international graduates but no demand. Domestic firms focus their efforts on expatriate programs and/or highly-qualified specialists rather than trainee programs to hire internationals. On the other hand, insitutional barriers exist, as well as a lack of support with regards to regulations and requirements for entering both Russian and German markets. The national language requirement was stressed as the major barrier towards hiring internationals in both countries. The investigation from an organizational point of view revealed that interviewers showed a positive predisposition towards international graduates in both countries, focusing on the graduate's skill set rather than their nationality. This research explores the opportunities and barriers and discusses the implications for students and universities.
In this paper, research projects with 30 meter balanced cabling and data rates up to 25 Gbps over one single pair are described. The project aim is to achieve 100 Gbps via a four pair balanced cabling channel. In the following, spectral characteristics of the used prototype twisted pair are presented. Therefore, the insertion loss of the single cable in comparison to the insertion loss of the cable in combination with an equalizing amplifier, as well as the group delay of the cable and the cable connected to the equalizing amplifier is shown. Furthermore, a carrierless Pulse Amplitude Modulation with 32 different levels (PAM-32) as an approach for a possible line encoding is presented. Finally, research measurements of the data transmission with a data rate up to 25 Gbps via shielded twisted pair is shown.
Manufacturing companies are confronted with external (e.g. short-term change of product configuration by the customer) and internal (e.g. production process deviations) turbulences which are affecting the performance of production. Predefined, centrally controlled logistics processes are limiting the possibilities of production to initiate countermeasures to react in an optimized way to these turbulences. The autonomous control of intralogistics offers a great potential to cope with these turbulences by using the respective flexibility corridors of production systems and applying intelligent logistic objects with decentralized decision and process execution capabilities to maintain a target-optimized production. A method for AI-based storage-location- and material-handling-optimization to achieve performance-optimized intralogistics system through continuous monitoring of performance-relevant parameters and influencing factors by using AI (e.g. for pattern recognition) has been developed. To provide the basis to investigate and demonstrate the potentials of autonomously controlled intralogistics in connection with turbulences of production and in combination with AI, an intelligent warehouse involving an indoor localization system, smart bins, manual, semi-automated/collaborative and autonomous transport systems has been developed and implemented at Werk150, the factory on campus of ESB Business School (Reutlingen University). This scenario, which has been integrated into graduate training modules, allows the analysis and demonstration of different measures of intralogistics to cope with turbulences in production involving amongst others storage and material provision processes. The target fulfilment of the applied intralogistics measures to master arising turbulences is assessed based on the overall performance of production considering lead times and adherence to delivery dates. By applying artificial intelligence (AI) algorithms the intelligent logistical objects (smart bin, transport systems, etc.) as well as the entire logistics system should be enabled to improve their decision and process execution capabilities to master short-term turbulences in the production system autonomously.
The global demand for individualized products leading to decreasing production batch sizes requires innovative approaches how to organize production and logistics systems in a dynamic manner. Current material flow systems mainly rely on predefined system structures and processes, which result in a huge increase of complexity and effort for system and process changes to realize an optimized production and material provision of individualized products. Autonomous production and logistics entities in combination with intelligent products or logistic load carriers following the vision of the “Internet of Things” offer a promising solution for mastering this complexity based on autonomous, decentralized and target size-optimized decision making and structure formation without the need for predefined processes and central decision-making bodies. Customer orders are going to prioritize themselves and communicate directly with the required production and logistics resources. Bins containing the required materials are going to communicate with the conveyors or workers of the respective intralogistics system organizing and controlling the material flow to the autonomously selected workstation. A current research project is the development of a collaborative tugger train combing the potential of automation and human-robot collaboration in intralogistics. This tugger train is going to be integrated into a self organized intralogistics scenario involving individualized customer orders (low to high batch sizes). To classify the application of self-organization within intralogistics systems, a criteria catalogue has been developed. The application of this criteria catalogue will be demonstrated on the example of a self-organization scenario involving the collaborative tugger train and an intelligent bin system.
The planning and control of intralogistics systems in line with versatile production systems of smart factories requires new approaches and methods to cope with changing requirements within future factories. The planning of intralogistics can no longer follow a static, sequential approach as in the past since the planning assumptions are going to change in a high frequency. Reasons for these constant changes are amongst others external turbulences like rapidly changing market conditions, decreasing batch sizes down to customer-specific products with a batch size of one and on the other hand internal turbulences (like production and logistic resource breakdowns) affecting the production system. This paper gives an insight into research approaches and results how capabilities of intelligent logistical objects (intelligent bins, autonomous transport systems etc.) can be used to achieve a self-organized, cost and performance optimized intralogistics system with autonomously controlled process execution within versatile production environments. A first consistent method has been developed which has been validated and implemented within a scenario at the pilot factory Werk150 at the ESB Business School (Reutlingen University). Based on the incoming production orders, the method of the Extended Profitability Appraisal (EPA) covering the work system value to define the most effective work system for order fulfilment is applied. To derive the appropriate intralogistics processes, an autonomous control method involving principles of decentralized and target-oriented decision-making (e.g. intelligent bins are interacting with autonomously controlled transport systems to fulfil material orders of assembly workstations) has been developed and applied to achieve a target-optimized process execution. The results of the first stage research using predefined material sources and sinks described in this paper is going to set the basis for the further development of a self-organized and autonomously controlled method for intralogistics systems considering dynamic source and sink relations. By allowing dynamic shifts of production orders in the sense of dynamic source and sink relations the cost and performance aims of the intralogistics system can be directly aligned with the aims of the entire versatile production system in the sense of self-organized and autonomously controlled systems.
Industrial practice is characterized by random events, also referred to as internal and external turbulences, which disturb the target-oriented planning and execution of production and logistics processes. Methods of probabilistic forecasting, in contrast to single value predictions, allow an estimation of the probability of various future outcomes of a random variable in the form of a probability density function instead of predicting the probability of a specific single outcome. Probabilistic forecasting methods, which are embedded into the analytics process to gain insights for the future based on historical data, therefore offer great potential for incorporating uncertainty into planning and control in industrial environments. In order to familiarize students with these potentials, a training module on the application of probabilistic forecasting methods in production and intralogistics was developed in the learning factory 'Werk150' of the ESB Business School (Reutlingen University). The theoretical introduction to the topic of analytics, probabilistic forecasting methods and the transition to the application domain of intralogistics is done based on examples from other disciplines such as weather forecasting and energy consumption forecasting. In addition, data sets of the learning factory are used to familiarize the students with the steps of the analytics process in a practice-oriented manner. After this, the students are given the task of identifying the influencing factors and required information to capture intralogistics turbulences based on defined turbulence scenarios (e.g. failure of a logistical resource) in the learning factory. Within practical production scenario runs, the students apply probabilistic forecasting using and comparing different probabilistic forecasting methods. The graduate training module allows the students to experience the potentials of using probabilistic forecasting methods to improve production and intralogistics processes in context with turbulences and to build up corresponding professional and methodological competencies.
Production planning and control are characterized by unplanned events or so-called turbulences. Turbulences can be external, originating outside the company (e.g., delayed delivery by a supplier), or internal, originating within the company (e.g., failures of production and intralogistics resources). Turbulences can have far reaching consequences for companies and their customers, such as delivery delays due to process delays. For target-optimized handling of turbulences in production, forecasting methods incorporating process data in combination with the use of existing flexibility corridors of flexible production systems offer great potential. Probabilistic, data-driven forecasting methods allow determining the corresponding probabilities of potential turbulences. However, a parallel application of different forecasting methods is required to identify an appropriate one for the specific application. This requires a large database, which often is unavailable and, therefore, must be created first. A simulation-based approach to generate synthetic data is used and validated to create the necessary database of input parameters for the prediction of internal turbulences. To this end, a minimal system for conducting simulation experiments on turbulence scenarios was developed and implemented. A multi-method simulation of the minimal system synthetically generates the required process data, using agent-based modeling for the autonomously controlled system elements and event-based modeling for the stochastic turbulence events. Based on this generated synthetic data and the variation of the input parameters in the forecast, a comparative study of data-driven probabilistic forecasting methods was conducted using a data analytics tool. Forecasting methods of different types (including regression, Bayesian models, nonlinear models, decision trees, ensemble, deep learning) were analyzed in terms of prediction quality, standard deviation, and computation time. This resulted in the identification ofappropriate forecasting methods, and required input parameters for the considered turbulences.
Circular economy aims to support reuse and extends the product life cycles through repair, remanufacturing, upgrades and retrofits, as well as closing material cycles through recycling. To successfully manage the necessary transformation processes to circular economy, manufacturing enterprises rely on the competency of their employees. The definition of competency requirements for circular economy-oriented production networks will contribute to the operationalization of circular economy. The International Association of Learning Factories (IALF) statesin its mission the development of learning systems addressing these challenges for training of students and further education of industry employees. To identify the required competencies for circular economy, the major changes of the product life cycle phases have been investigated based on the state of the science and compared to the socio-technical infrastructure and thematic fields of the learning factories considered in this paper. To operationalize the circular economy approach in the product design and production phase in learning factories, an approach for a cross learning factory network (so called "Cross Learning Factory Product Production System (CLFPPS)") has been developed. The proposed CLFPPS represents a network on the design dimensions of learning factories. This approach contributes to the promotion of circular economy in learning factories as it makes use of and combines the focus areas of different learning factories. This enables the CLFPPS to offer a holistic view on the product life cycle in production networks.
Product engineering and subsequent phases of product lifecycles are predominantly managed in isolation. Companies therefore do not fully exploit potentials through using data from smart factories and product usage. The novel intelligent and integrated Product Lifecycle Management (i²PLM) describes an approach that uses these data for product engineering. This paper describes the i²PLM, shows the cause-and-effect relationships in this context and presents in detail the validation of the approach. The i²PLM is applied and validated on a smart product in an industrial research environment. Here, the subsequent generation of a smart lunchbox is developed based on production and sensor data. The results of the validation give indications for further improvements of the i²PLM. This paper describes how to integrate the i²PLM into a learning factory.
Electronic word-of-mouth (eWoM) communication plays an increasingly important role in modern business. The underlying concept of word-of-mouth (WoM) communication is well researched and has proved highly significant in respect of its impact on customers purchase behavior. However, due to the advent of digital technologies, decision-making among customers is progressively shifting to the online world. Consequently, eWoM has received a lot of attention from the academic community. As multiple research papers focus on specific facets of eWoM, there is a need to integrate current research results systematically. Thus, this paper presents a scientific literature analysis in order to determine the current state-of-the-art in the field of eWoM. Five main research areas were analyzed, supporting the need for further eWoM studies and providing a structured overview of existing results.
Digitization will require companies to fundamentally reengineer their sales processes. Adapting the concept of value selling to the digital age will enable them to deliver superior value to their customers. Specifically, social selling will provide them with an answer to the ever-increasing complexity of customer journeys. This article, based on a survey among 235 German companies, assesses the status quo and outlines opportunities. Moreover, it introduces a novel approach for developing well-grounded social selling metrics.
Recent digital technologies like the Internet of Things and Augmented Reality have brought IT into companies’ core products. What were previously purely physical products are becoming hybrid or digitized. Despite receiving a lot of recent attention, digitized products have only seen a slow uptake in businesses so far. In this paper, we study the challenges that keep companies from realizing the desired impacts of digitized products and the practices they employ to address these challenges. To do so, we looked at companies from a set of industries that are highly affected by digital transformation, but at the same time hesitant to move to a more digitized world: the creative industries. Based on a literature review and twelve interviews in creative industries, we developed a conceptual model that can serve as a basis for formulating testable hypotheses for further research in this area.
The digital economy poses existential threats to — and game-changing opportunities for — companies that were successful in the pre-digital economy. What will distinguish those companies that successfully transform from those that become historical footnotes? This is the question a group of six researchers and consultants from Boston Consulting Group set out to examine. The team conducted in-depth interviews with senior executives at twenty-seven companies in different industries to explore the strategies and organizational initiatives they relied on to seize the opportunities associated with new, readily accessible digital technologies. This paper summarizes findings from this research and offers recommendations to business leaders responsible for digital business success.
The increase in product variance and shorter product lifecycles result in higher production ramp-up frequencies and promote the usage of mixed-model lines. The ramp-up is considered a critical step in the product life cycle and in the automotive industry phases of the ramp-up are often executed on separated production lines (pilot lines) or factories (pilot plants) to verify processes and to qualify employees without affecting the production of other products in the mixed-model line. The required financial funds for planning and maintaining dedicated pilot lines prevent small and medium-sized enterprises (SMEs) from the application. Hence, SMEs require different tools for piloting and training during the production ramp-up. Learning islands on which employees can be trained through induced and autonomous learning propose a solution. In this work, a concept for the development and application which contains the required organization, activities, and materials is developed through expert interviews. The results of a case study application with a medium-sized automotive manufacturer show that learning islands are a viable tool for employee qualification and process verification during the ramp-up of mixed-model lines.
Job advertisements are important means of communicating role expectations for management accountants to the labor market. They provide information about which roles of management accountants are sought by companies or which roles are expected. However, which roles are communicated in job advertisements is unknown so far. Using a large sample of 889 job ads and a text-mining approach, we show an apparent mix of different role types with a strong focus on a rather classic role: the watchdog role. However, individuals with business partner characteristics are more often sought for leadership positions or in family businesses and small and medium-sized enterprises (SMEs). The results challenge the current role discussion for management accountants as business partners in practice and some academic fields.
Evaluation of human-robot order picking systems considering the evolution of object detection
(2022)
The automation of intralogistic processes is a major trend, but order picking, one of the core and most cost-intensive tasks in this field, remains mostly manual due to the flexibility required during picking. Reacting to its hard physical and ergonomic strain, the automation of this process is however highly relevant. Robotic picking system would enable the automation of this process from a technical point of view, but the necessity for the system to evolve in time, due to dynamics of logistic environments, faces operations with new challenges that are hardly treated in literature. This unknown scares potential investors, hindering the application of technically feasible solutions. In this paper, a model for the evaluation of the additional cost of training of automated systems during operations is presented, that also considers the savings enabled by the system after its evolution. The proposed approach, that considers different parameters such as capacity, ergonomics and cost, is validated with a case study and discussed.
Today's logistics systems are characterized by uncertainty and constantly changing requirements. Rising demand for customized products, short product life cycles and a large number of variants increases the complexity of these systems enormously. In particular, intralogistics material flow systems must be able to adapt to changing conditions at short notice, with little effort and at low cost. To fulfil these requirements, the material flow system needs to be flexible in three important parameters, namely layout, throughput and product. While the scope of the flexibility parameters is described in literature, the respective effects on an intralogistics material flow system and the influencing factors are mostly unknown. This paper describes how flexibility parameters of an intralogistics system can be determined using a multi-method simulation. The study was conducted in the learning factory “Werk150” on the campus of Reutlingen University with its different means of transport and processes and validated in terms of practical experiments.
Shorter product life cycles and emerging technologies are changing the circumstances under which the design of assembly and logistics systems has to be carried out. Engineers are in charge of adapting the production in accordance with the underlying product at a higher pace, oversee a more complex system and find the ideal solution for a functional work system design as well as social interactions between humans and machines in cyber-physical systems. Such collaborative work systems consider the individual capabilities and potentials of humans and machines to combine them in a manner that assists the operator during his daily work routine. To be able to design such work systems, specific competences such as the ability of integrated process and product planning as well as systems and interface competence are required. Learning factories train students as well as professionals to gain such qualifications by providing a close-to-reality learning environment based on a didactical concept which covers all relevant methods for ergonomic work system design and a state-of-the-art infrastructure. Group-based, activity oriented scenarios enable the participants to put the learnings into their everyday work life. Thereby, learning factories have an indirect impact on the transfer of proven best practices to the industry.
The promise of the EVs is twofold. First, rejuvenating a transport sector that still heavily depends on fossil fuels and second, integrating intermittent renewable energies into the power mix. However, it is still not clear how electricity networks will cope with the predicted increase in EVs and their charging demand, especially in combination with conventional energy demand. This paper proposes a methodology which allows to predict the impact of EV charging behavior on the electricity grid. Moreover, this model simulates the driving and charging behavior of heterogeneous EV drivers which differ in their mobility pattern, decision-making heuristics and charging strategies. The simulations show that uncoordinated charging results in charging load clustering. In contrast, decentralized coordination allows to fill the valleys of the conventional load curve and to integrate EVs without the need of a costly expansion of the electricity grid.
Efficiency in supply chain risk management (SCRM) is a major topic in industries with serial production and a complex supply chain due to limited management and financial resources. A high number of possible risk situations and intertwined processes create a more challenging environment for resource allocation. Managers cannot perform SCRM in all possible supply chain areas and hence have to decide where available resources should be utilised for highest possible risk reduction. This makes it important to quickly and systematically evaluate input and output relationships among risk mitigation actions to determine which actions are deployed first for efficient risk level reduction. This paper introduces a new SCRM method based on the failure mode and effects analysis (FMEA) in order to perform an efficiency-oriented risk action prioritisation. By considering the cost-benefit evaluation of identified risk mitigation actions for each assessed risk and by determining the implementation effort for risk mitigation actions, also considered as the cost for realising a specific risk action the method allows finding those risk and risk mitigation actions, which are most efficient for risk reduction and should be implemented first in the process of risk steering.
Because of saturated markets and of the low profit margins in the sales of cars, car manufacturers focus more and more on profitable product related services. This paper deals with the question how to classify product related services in the automotive industry and which characteristic product related services are offered to the end-users (consumers) in a standardized format. Two research studies on the provided product related services in 2010 und 2017 by 15 car manufacturers and 20 exemplary automotive brands in Germany revealed that the application degree by the OEM (original equipment manufacturers) in these years increased considerably. While in 2010, the average range of services only amounted to 33%, the value in the automotive industry increased until 2017 to 57%.
Today 40 Gbps is in development at IEEE 802.3bq over four pair balanced cabling. In this paper, we describe a transmission experiment of 25 Gbps enabling either a single pair transmission of 25 Gbps over a 30 meter balanced cabling channel, or a 100 Gbps transmission via a four-pair balanced channel. A scalable matrix modeling tool is introduced which allows the prediction of transmission characteristics of a channel taking mode conversion into account . We applied this tool to characterize PCB-channels including the magnetics and PCB for a four-pair 100 Gbps transmission. We evaluated prototype cables and connecting hardware for frequencies up to 2 GHz and beyond. Finally we investigated possible line encoding schemes and provide measurement results of a transmission over 30 m with a data rate of 25 Gbps per twisted pair.
Imagine a world in which the search for tomorrow's trends 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.
The use of digital, IT-based components in physical products is becoming increasingly relevant in practice. Surprisingly, the strategic impact of these "digitized products" has not received a lot of attention in IS research so far. Extant papers on the topic rely on ambiguous terminology (e.g., "smart products", "cyber-physical systems", "digital product-service systems") and underlying concepts differ widely. Based on an extensive literature review, this article provides an overview of the different terms and identifies five conceptual elements that form the building blocks of digitized products in research: "hybridity" (i.e., the combination of digital and physical components), connectivity, smartness, digitized product-service bundles (servitization of digitized products), and digitized product ecosystems. The implication for practitioners is that each element comes with different managerial challenges that companies need to address when incorporating the respective element in their products. The research implication is that each conceptual element is supported by different theoretical streams.
Digital technologies are moving into physical products. Smart cars, connected lightbulbs and data-generating tennis rackets are examples of previously “pure” physical products that turned into “digitized products”. Digitizing products offers many use cases for consumers that will hopefully persuade them to buy these products. Yet, as revenues from selling digitized products will remain small in the near future, digitized product manufacturers have to look for other sources of benefits. Producer-side use cases describe how manufacturers can benefit internally from the digitized products they produce. Our article identifies three categories of such use cases: product-, service-, and process-related ones.
According to several surveys and statistics, the great majority of companies previously not accustomed to automation are piloting solutions to automate business processes. Those accustomed to automation also attempt to introduce more of it, focusing on automation-unfriendly processes that remained manual. However, when the decision on what and whether to automate is not trivial for evident reasons, even industry leaders may get stuck on an overwhelming question: where to begin automating? The question remains too often unanswered as state-of-the-art methods fail to consider the whole picture. This paper introduces a holistic approach to the decision-making for investments in automation. The method supports the iterative analysis and evaluation of operative processes, providing tools for a quantitative approach to the decision-making. Thanks to the method, a large pool of processes can be first considered and then filtered out in order to select the one that yields the best value for the automation in the specific context. After introducing the method, a case study is reported for validation before the discussion.
There are indicators we are entering a new era for MTM research, by moving beyond the structural approach that has characterized MTM research to date, to focus on important and under-researched issues, such as the nature of employees’ experiences in an MTM context. Although team research suggests that the experiences of members impact team functioning, these lines of reasoning have not, until recently, made their way to MTM research. To overcome this limitation, this symposium showcases five papers that use a variety of theoretical perspectives, research designs (i.e., qualitative, quantitative), contexts (e.g., healthcare, automotive manufacturer, online panels), methodologies, and analytical methods (i.e., meta-analysis, content/thematic analysis). The symposium focuses on surfacing and advancing unanswered questions that extend theory and can offer fruitful directions for MTM research by examining critical individual and team level outcomes (e.g., individual/team performance, individual counterproductive and organizational citizenship behavior, individual learning, individual turnover intentions, organizational commitment) in the experiences of MTM employees across their teams (e.g., goals, functions, roles). We hope to provide a forum to advance unanswered questions that offer fruitful directions for MTM research.
In its 100+ years of company history, IBM reinvented itself multiple times. In the last 20 years, IBM had shifted from individual products to integrated solutions and moved to become a globally integrated enterprise with standardized processes. In 2014, the expanding adoption of social, mobile, analytics, and cloud (SMAC) technologies generated excitement in the industry. IBM believed these technologies presented a huge growth opportunity. Simultaneously, management viewed SMAC technologies as disruptive forces demanding transformative changes to how IBM worked. And introducing new ways of working to 400,000 employees in 175 countries was a daunting task.
Based on personal interviews with 17 IBM business and IT executives, the case illustrates organizational challenges of introducing current technologies that even providers of these technologies face – in other words, when they “eat their own cooking.” It demonstrates the difficulties large companies face when implementing technologies that students use daily and take for granted.
As "the most international company on earth", DHL Express promised to deliver packages between almost any pair of countries within a defined time-frame. To fulfill this promise, the company had introduced a set of global business and technology standards. While standardization had many advantages (improving service for multinational customers, faster response to changes in import/export regulations, sharing of best practices etc.), it created impediments to local innovation and responsiveness in DHL Express' network of 220 countries/territories. Reconciling standardization-innovation tradeoffs is a critical management issue for global companies in the digital economy.
This case describes one large, successful company's approach to the tradeoff of standardization versus innovation.
Started as a mono-line focused purely on savings, in late 2012 ING Direct Spain was becoming a full-service bank. To this end, the bank had substantially increased its product- and channel-portfolio. ING Direct Spain originally provided "simple", "good value for money" products in an "easy to deal with" way at low cost supported by a direct model. But with the growth in its product portfolio during the previous decade and the ambitious goal of becoming a full-service bank, an increase in complexity seemed inevitable. Like many businesses in the global, digital economy, ING Direct Spain found it needed to decide which complexity created value for its customers and which one not. It also learned that IT can contribute to complexity and/or help manage complexity.
This case offers a close look at challenges of growing a company by increasing product complexity to provide comprehensive yet simple services.
In 2017, Philips' goal was to use innovation to improve the lives of three billion people a year by 2025. To achieve that, the company was shifting from selling medical products in a transactional manner to providing integrated healthcare solutions based on digital health technology. Based on our interviews with 23 executives at Philips, the case examines the two directions of the transformation required by this shift: externally, Philips worked on transforming how healthcare was conducted. Healthcare professionals would have to change the way they worked and reimbursement schemes needed to change to incentivize payers, providers, and patients in vastly different ways. Internally, Philips needed to redesign how its employees worked. The company componentized its business, introduced digital platforms, and co-created integrated solutions with the various stakeholders of the healthcare industry. In other words: Philips was transforming itself in order the reinvent healthcare in the digital age.
By 2019, Germany-based Kärcher, “the world’s leading provider of cleaning technology,” had turned its professional cleaning devices into IoT products. The data generated by these IoT-connected cleaning devices formed a key ingredient in the company’s ongoing strategic shift in its B2B business: Kärcher was transforming from a seller of cleaning devices to a provider of consulting services in order to help professional cleaning companies improve their cleaning processes. Based on interviews with seven IT- and non-IT executives, the case illustrates how the company learned to generate value from IoT products. And it demonstrates how a family-owned company transformed its organization in order to be able to more effectively develop and provide IoT products, while adding roles, developing technology platforms, and changing organizational structures and ways of working.