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This paper presents an illustrated model to explain digitalisation in industry in a holistic, non-technological way. It reflects the dimensions of the product lifecycle and the supply chain. More specifically, it discusses the interaction between customer, product, production, and suppliers along a product’s life and how digitalisation supports these interactions. Particular attention is given to the transition from type to its product instances. Especially in the case of complex products, mastering this transition plays a key role in understanding digitalisation requirements. Reclining the concept of type and instance, different element of the digital twin, as digital master and the different shadows, are classified. Developed initially to structure a course in an engineering master’s program, the model has evolved to be used in different courses and currently supports consulting and applied research projects to orchestrate digitalisation initiatives in the industry.

Scheduling is classically centered around jobs with constant processing times. This allows for universal methods of a simple structure, like Smith’s rule, proven by job interchange arguments. Certain applications, however, entail variable processing times, depending on the job’s start time. Then, interchanging jobs implies changing start times for successive jobs, which escalates the computational complexity. To plan car assembly on a moving conveyor line, we are concerned with time-dependent processing time functions that are V-shaped and piecewise-linear. We present complexity results and draw relations to classic scheduling problems.

Recent occurrences such as the Covid-19 outbreak, the Russo-Ukrainian war, and others have disrupted global supply chains in an unprecedented manner. Consequently, a worldwide supply chain crisis originated, which affected businesses and consumers alike. While end-users were not able to acquire the desired products, companies incurred massive financial losses due to the supply disruptions. Based on this complication, this bachelor’s thesis analyzes and assesses the driving academic theories about supply chain resilience together with first-hand results obtained from semi-structured interviews with supply chain specialists. In particular, this paper sheds light on the factors that necessitate supply chain resilience. Moreover, insights about the most recent resilience-enhancing antecedents are provided, and a possible connection between supply chain resilience and the customer value proposition is examined. The literature review reveals five essential supply chain resilience antecedents, namely, flexibility, redundancy, agility, collaboration, and culture. Furthermore, the secondary research demonstrates that there is a literature gap in identifying the circumstances that demand resilience and a possible incorporation of resilience in the customer value proposition. Thus, while companies had to adapt quickly to the new status quo, research is still lagging behind the current disruptive events. Methods of analysis include comparing the results of extensive semi-structured interviews with the guiding theories of the respective concepts. The collected information demonstrates that theory and practice are mostly consistent, hence validating both. The thesis illustrates that the awareness of vulnerable supply chains increased drastically in the aftermath of the pandemic. Thus, the pandemic prompted a widespread effort to develop a balanced supply chain resilience securing strategically essential items and efficiently sourcing minor products. The findings also reveal that, in accordance with the guiding literature, every business faces its unique set of capabilities and vulnerabilities. The five above-mentioned theoretical supply chain resilience-enhancing components are widely used in practice. However, the supply chain managers interviewed stressed the importance of technology, a component that has received scant attention in the literature. The study concludes that supply chain resilience cannot be used as a customer value proposition. This is due to the theoretical antecedents of a customer value proposition not being enhanced by supply chain resilience and the practice’s opinion that customers expect product availability. Instead, supply chain resilience may be leveraged as an added value to the customer.

In the contention of the current industrial landscape, an increasing number of manufacturing firms are experimenting with the transition from product-centric offerings to service-based value concepts and product-service bundles as high-value integrated customer solutions to increase their revenues and build sustainable competitive advantages; a phenomenon known as the “servitization” of manufacturing. Nowadays, consistently with the Industry 4.0 paradigm, these companies have therefore started a process of integrating their traditional value offerings with digital services. This recent strategy is known as “Digital Servitization” and consists of developing new services and/or improving existing ones through digital technologies. However, this transformation is challenging, and companies often struggle to achieve their expectations. Thus, this study aims to shed light on the current state of Digital Servitization strategies in the manufacturing sector based on a survey addressed to the top and middle management. The results obtained by the analysis of the data collected from the survey show an increasing trend towards the adoption of digital technologies for enabling innovation and differentiation in service delivery processes.

The paper was awarded the best paper award, Data-driven value creation is a key topic in industrial services. However, designing such services in an optimal way represents a multidimensional and complex task. In this paper, we present a design methodology based on a simultaneous maxi-mization of value creation for both the provider and the customer, allowing the identification of optimal service configurations. We apply this methodology to a use case of a manufacturer delivering services for its machines in the context of a pay-per-use business model. The approach is based on modeling the value creation separately for both provider and customer, as a function of data-driven services which may be offered in different phases of the lifecycle. The model allows finding Pareto-optimal service configurations which provide value creation optimized simultaneously for both the provider and the customer. These optimal configurations are not easy to find with simpler methods because of non-linear effects in value creation along the lifecycle.

Kaizen, pioneered by Japanese automaker Toyota after World War II, is more than a method for increasing efficiency and reducing costs. It is a management philosophy that aims to advance a company through continuous improvements by all employees. Especially in Switzerland, small and medium-sized enterprises expand into the European Union comparatively early in their life cycle due to the limited domestic market. Efficiency increases and innovations are crucial to keep up with the competitive prices of the European competitors. In addition, companies with solid growth often experience a proliferation of processes and lose agility, making the introduction of kaizen beneficial. As a result, this thesis aims to determine the success factors and prerequisites for implementing Toyota-based kaizen in small and medium-sized companies. First, a systematic literature review was conducted to identify the barriers and success factors for the kaizen implementation. The research is based on peer-reviewed databases and reports from renowned consulting firms. Subsequently, the New St. Gallen Management Model was applied to examine the prerequisites systematically. The success factors were discussed in five semi-structured interviews with a professor, a consultant, and managers from different positions in Swiss kaizen companies to obtain additional insights and best practice examples. From the results, the author has designed a model to guide Swiss managers in implementing Toyota-based kaizen in small and medium-sized enterprises. According to the literature, many Western companies fail to implement kaizen in their organization. While Japanese companies realized 30 to 40 percent cost reductions, many foreign companies managed only 10 to 15 percent. Although it is a great challenge, many authors agree that kaizen can be transferred internationally. However, organizations must adapt kaizen to the national characteristics while insisting on the basic principles. At its core, a kaizen company must empower its employees to participate and create a long-term competitive advantage for the company through continuous improvements and striving for perfection. For an organization to achieve this, the paper identifies three core requirements: top management commitment, human capital management strategy, and basic kaizen tools. Additionally, these prerequisites are influenced by three structuring forces that should be aligned with kaizen: a team-based culture, a process-oriented structure, and a customer-focused strategy. These six factors create an atmosphere in which kaizen can thrive. Nevertheless, the whole organization is in an environment of continuous change due to internal and external influences. Therefore, constant reflection and improvement of the management philosophy according to the plan-do-check-adjust cycle is mandatory. Kaizen is never finished, and each company interprets it slightly differently based on its underlying values.

The goal of this paper is to further elaborate a new concept for value creation by decision support services in industrial service ecosystems using digital twins and to apply it to an extended case study. The aim of the original model was to design and integrate an architecture of digital twins derived from business needs that leveraged the potential of the synergies in the ecosystem. The conceptual framework presented in this paper extends the semantic ontology model for integrating the digital twins. For the original model, technical modeling approaches were developed and integrated into an ecosystem perspective based on a modeling of the ecosystem and the actors' decision jobs. In a service ecosystem comprising several enterprises and a multitude of actors, decision making is based on the interlinkage of the digital twins of the equipment and the processes, which is achieved by the semantic ontology model further elaborated in this paper. The implementation of the digital twin architecture is shown in the example of a manufacturing SME (small and medium-sized enterprise) case that was introduced in. The mixed semantic modeling and model-based systems engineering for this implementation is discussed in further detail in this paper. The findings of this detailed study provide a theoretical concept for implementing digital twins on the level of service ecosystems and integrating digital twins based on a unified ontology. This provides a practical blueprint to companies for developing digital twin based services in their own operations and beyond in their ecosystem.

Process automation systems are used to control a process such as chemical, steel, oil refineries, petrochemical, paper, or pulp factories. Such systems consist of many individual stations, producing traffic of varying priorities and are spread over a large geographical area. In the presence of so many traffic sources, congestion is inevitable. IEEE Std 802.3cg defines 10BASE-T1L to directly address the distances involved in process automation systems while preemption provides a means to address congestion by giving high priority traffic.

The paper at hand takes the widely used Lotka-Volterra model from biology and transfers it to the supply chain context. The model is used to analyse whether supply chain partners can benefit from symbiotic mutualism. Results show that in certain situations, both mutualism partners disappear from the marketplace, while in other situations, one of the partners survives while the other dies. The model furthermore shows that symbiotic mutualism exists in which both supply chain partners can benefit from the collaboration and a stable coexistence can be reached.

Supply chain network disruptions have become an increasingly relevant topic in literature and industry. Just recently the COVID-19 pandemic demonstrated the need for greater resilience in global supply chain networks. We present a quantitative social network analysis (SNA) approach to selectively fortify nodes in complex supply chain networks targeting ripple-effect mitigation and enhancing supply chain network resilience (SCNR). Our model can be used to analyze supply chain resilience and derive strategies to mitigate disruptions, specifically using betweenness centrality for fortification. The model can be applied by supply chain managers to existing supply chain networks regardless of the underlying network type.

IISE Transactions (Journal) Best Paper : Scheduling and Logistics Placing material containers at moving assembly lines is an intriguing problem because each container position influences worker paths. This optimization is relevant in practice as worker walking time accounts for about 10–15% of total work time. Nonetheless, we find few computational approaches in the literature. We address this gap and model walking time to containers, then optimize their placement. Our findings suggest this reduces walking time of intuitive solutions by an average of 20%, with considerable estimated savings. To investigate the subject, we formulate a quintessential optimization model for basic sequential container placement along the line side. However, even this core problem turns out as strongly NP-complete. Nonetheless, it possesses several polynomial cases that allow to construct a lower bound on the walking time. Moreover, we discover exact and heuristic dominance conditions between partial placements. This facilitates an exact and a truncated branch-and-bound solution algorithm. In extensive tests, they consistently deliver superior performance compared to several mixed integer programming and metaheuristic approaches. To aid practitioners in quickly recognizing instances with high optimization potential even before performing a full optimization, we provide a criterion to estimate it with just few measurements.

Purpose: The goal of this paper is to elaborate a new concept for value creation by decision support services in industrial service ecosystems using a digital twin. The aim is to design and integrate an architecture of digital twins that is derived from the actors’ needs and that leverages the potential of the synergies in the ecosystem. Design/Methodology/Approach: The conceptual framework presented in this paper is elaborated based on a multiple case study with ten cases (West et al., 2020). Based on a modelling of the ecosystem and the actors’ decision jobs, technical modelling approaches are developed and integrated to an ecosystem perspective. Findings: In a service ecosystem comprising several enterprises and a multitude of actors, decision making is based on the interlinkage of the digital twins of the equipment and the processes. In order to foster the full potential of the digital twins in an ecosystem, they are integrated in a hierarchical concept using ontology approaches. Originality/Value: The findings of this study integrate the modelling approaches for digital twins and extends these to a new modelling approach on the level of service ecosystems. This provides a practical blueprint to companies for developing digital twin based services in their own operations and beyond in their ecosystem.

The application of digital twins provides value creation within the fields of operations and service management, existing research around decision-making and value co-creation is limited at this point. Prior studies have provided insights into the benefits of digital twins that combined both data and simulation approaches, however, there remains a managerial gap. The purpose of this paper is to explore this research gap using input from a multiple case study research design from both manufacturing environments and non-manufacturing environments. The authors use ten cases to explore how digital twins support value co-creation through decision-making. The authors were all involved in the development of the ten cases. Individual biases were removed by using the literature to provide the assessment dimensions and allowing a convergence of the results. Drawing on the lessons from the ten cases, this study empirically identified eight managerial issues that need to be considered when developing digital twins to support multi-stakeholder decision-making that leads to value co-creation. The application of digital twins in value co-creation and decision-making is a topic that has developed from practice and is an area where a research gap exists between theory and practice. A cross-case analysis was developed based on the literature and the ten cases (eight industrial and two pilot-scale cases) providing the empirical findings. The findings describe how firms can design, develop, and commercialize digital-twin-enabled value propositions and will initiate future research.

The increasing demand for temperature-controlled products (pharmaceuticals / food) leads to increased energy demand in the logistics sector and to increasing greenhouse gas emissions. Even though there exist efforts to increase energy efficiency in logistics, they are mostly isolated solutions emphasising drive technologies or technological possibilities in building infrastructure. These isolated solutions will not be enough to achieve the climate targets. The paper provides insights into the development of a simulation and design model for a logistics system, which serves as a planning tool and as basis for decision-making for design options for energy autonomy. Different options for transport, cooling of the products during transport, storage and distribution with regards to CO2-equivalent emissions and costs are incorporated. In this way, different scenarios are modelled as basis for qualified decisions for the design of an energy autonomous logistics system.

The megatrends of digitalization and globalization have shaped the retail industry during the last decades significantly. However, the outbreak of the Covid-19 pandemic in 2019 has severely affected the global economy as interconnected value chains have been disrupted, and digitalization has become a sudden necessity due to lockdowns and travel bans. The aim of this master’s thesis was to identify the impact of the Covid-19 pandemic on global upstream value chains as well digitization efforts in the European non-food retail industry. In addition, this thesis examined the potential future development of the retail value chains along the dimensions of globalization and digitalization within 10 years. The novelty of the pandemic made it a largely unresearched phenomenon. A comprehensive literature review has been conducted to provide a broad understanding of the subject. This review encompassed the retail industry, the Covid-19 pandemic, and the megatrends of digitalization and globalization. In addition, the digital business transformation matrix, Porter’s value chain, and a digital maturity model were introduced as frameworks for subsequent primary data collection. Subsequently, empirical research has been conducted through nine qualitative interviews with decision-makers from the European retail industry to answer the research questions. The thesis identified a fluctuation in demand, promotion of sustainability, disturbance of information flow in procurement, supply shortage, interruption of logistics flows, and saturation of distribution as impacts of the Covid-19 pandemic on upstream value chain activities. Moreover, globalization depends largely on product category level criteria, and Covid-19 has led to further globalization of value chains. The pandemic’s impact on digitalization encompassed an acceleration of digitalization, shift of customer expectations towards digitalization, improved digital connectivity, moderate investments in digital infrastructure, high investments in digital competence, and strategic optimization. Moreover, a sustainable digital acceleration has been identified, and retail organization’s decision-making was considerably sped up. Lastly, all retail organizations greatly gravitate towards increasingly digitalized operating models. Overall, it was concluded that the Covid-19 pandemic has critically affected the retail industry, but the sector will eventually emerge strengthened from the crisis. Digitalization enables further globalization, and location advantages make specialized clusters inevitable sourcing partners. Globalization has not come to a halt due to Covid-19 but will increasingly be enabled by digital means. Retailers are recommended to embrace digital business models to remain competitive and to use the advantages of globalization. The results of this thesis are generally valid for the European retail industry, and further research is recommended to draw an analogy to the findings in 10 years.

​© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works., Service customization is a central issue in socio- technical service ecosystems, enabled and fueled by new data- driven approaches, and with the goal of increasing value creation for the customer, and value capture for the provider. In this paper, we address the question of how to design service customization within the provider-customer interaction. We propose a novel quantitative approach for modeling the relation between cus- tomization level at the various steps of the customer journey on the one hand, and its effect on the value created for customer and provider on the other hand. Combining this model with approaches from multi-objective optimization, optimum levels of customization from both the customer and the provider perspective can be determined. Thus, the proposed model allows the identification of service designs which are optimized in terms of their value creation and value capture.

The nascent technology of smart dust—miniaturized sensor networks—promises high value to advance industrial product-service-systems. While previous studies have identified smart dust as source for product and service innovation, the pathways from an initial offering to smart dust-enhanced product-service-systems have received scant attention. The present work in the scope of a Swiss National Science Foundation project on the economic potentials of this technology aims to conceptualize and apply strategies for smart dust-enhanced product-service-systems. This conceptual research resulted in the three pathways (1) product-driven strategy, (2) service-driven strategy and (3) holistic strategy which could be successfully mapped to the use case “Monitoring of structures“. In closing, this emerging technology helps to make industrial product-service-systems more customer- and user-oriented as called by recent voices. To science, we introduce smart dust in the field of product-service-systems and offer a first systemization of pathways, thus contribute to the product-service-systems engineering knowledge base. To practice, we provide useful approaches to be applied at a strategy level to push the servitization in manufacturing forward.

The paper at hand takes the widely used Lotka-Volterra model from biology and transfers it to the supply chain context. The model is used to analyse whether supply chain partners can benefit from symbiotic mutualism. Results show that in certain situations, both mutualism partners disappear from the marketplace, while in other situations, one of the partners survives while the other dies. The model furthermore shows that symbiotic mutualism exists in which both supply chain partners can benefit from the collaboration and a stable coexistence can be reached.

PurposeThe purpose of this study is to explain how the application of fuzzy-set qualitative comparative analysis (fsQCA) and experiments can advance theory development in the field of servitization by generating better causal explanations.Design/methodology/approachFsQCA and experiments are established research methods that are suited for developing causal explanations but are rarely utilized by servitization scholars. To support their application, we explain how fsQCA and experiments represent distinct ways of developing causal explanations, provide guidelines for their practical application and highlight potential application areas for a future research agenda in the servitization domain.FindingsFsQCA enables specification of cause–effects relationships that result in equifinal paths to an intended outcome. Experiments have the highest explanatory power and enable the drawing of direct causal conclusions through reliance on an interventionist logic. Together, these methods provide complementary ways of developing and testing theory when the research objective is to understand the causal pathways that lead to observed outcomes.Practical implicationsApplications of fsQCA help to explain to managers why there are numerous causal routes to attaining an intended outcome from servitization. Experiments support managerial decision-making by providing definitive “yes/no” answers to key managerial questions that address clearly specified cause–effect relationships.Originality/valueThe main contribution of this study is to help advance theory development in servitization by encouraging greater methodological plurality in a field that relies primarily on the qualitative case study methodology.

Improving current supply chains by using distributed ledger technology (DLT) has been a highly researched topic during the last years. Currently, there are numerous articles elaborating on how such technologies can theoretically improve supply chains. However, case studies of such concepts and their economic value are scarce. In order to bridge this gap, we collaborated with a regional label company to clarify how a distributed ledger technology would benefit their ecosystem. This work answers the question of how such a prototype would look and whether it adds value. By following design science research practices, we design two artifacts based on requirements gathered in 14 interviews and discuss the artifacts&rsquo, elements within an evaluation panel. Our findings show that a distributed ledger application for the regional label ecosystem should have an open and decentralized architecture giving all participants full access to the shared data while still providing security and privacy for sensitive data. Additionally, data capturing should be simple. However, such an application does not add sufficient economic value and is currently of no practical interest in the regional label ecosystem as the expenditure likely exceeds the benefit.

Purpose: The motivation of this paper is to investigate how digital twins can enable the design of new value propositions in digitally enabled servitization. This is important, as the application of this technology is an opportunity to deliver new value propositions for customers, and for the supplier to gain deeper understanding of the actual performance of the equipment (Kowalkowski and Ulaga, 2017). This builds upon the assessment of service value co-creation supported by digital twin technologies (Meierhofer & West, 2019). Design/Methodology/Approach: Ten cases have been assessed in this paper using different dimensions, and a cross-case analysis to consider value co-creation, value measures, support to the value proposition, and the servitization context. All of the cases are from an Innosuisse-supported project in Switzerland and were selected for their diversity. Findings: Classifying the digital twins by service proved useful to understand each one and its position within the business system. Knowing which business functions the twin supports helps to identify and confirm value co-creation opportunities as well as the possible areas impacted. It also provides different servitization perspectives that can support new and disruptive models, which is helpful for firms looking for new services to support their customers. The lifecycle perspective confirms the links between different phases and can provide new insight for the development of digital twins. The cross case analysis confirmed that a digital twin could support the development of new value positions within the context of servitization, as well as allow others (e.g., installers or asset owners) to develop and sell their own value solutions.

Whether or not blockchain technology adds value to supply chains is a highly controversial topic. It has been lauded as the technology that brings transparency and efficiency to supply chains. However, others find this view overly optimistic. In this paper, we aim to add more insight into the issue by applying an action design research approach. We develop and evaluate two artifacts in collaboration with companies and use the results to conclude how blockchain technology can help overcome issues in the current supply chain information flow. It shows that blockchains can provide a shared trust base and a common standard that allows for increased information exchange between supply chain partners. Based on our findings, we propose a research agenda for studying blockchain technology with a stronger focus on governance mechanism and transparency issues.

Dissertation, Universität Ulm, Germany, 2019 Moving assembly lines are the stepping stone for mass production of automobiles. Here, every second counts, which necessitates planners to meticulously optimize them. A crucial factor is each worker’s nonproductive walking time between the moving workpiece and line-side material containers for picking up required material. Minimizing the walking time is difficult because the workpiece moves steadily. Helmut A. Sedding devises algorithms to optimize the sequence of work operations, and the placement of material containers. Thereby, he introduces a novel category of time-dependent scheduling problems, and lays the basis for the algorithmic optimization of time-dependent paths at the moving assembly line.

It is challenging for small and medium-sized enterprises (SMEs) to successfully adopt the concepts of servitization of manufacturing. This is because many of the concepts and approaches of servitization have been designed for larger companies (Hewitt-Dundas, 2006). It is considerably more demanding for SMEs to develop the necessary resources (Neely, 2008) in the area of data capabilities for services (Meierhofer et al., 2019). The lack of consideration of servitization research in the SME area is discussed in (Kowalkowski et al., 2015). This paper discusses the hurdles that SMEs face in data-driven servitization by means of a multiple case study. For the creation of the cases, data-driven servitization approaches for different types of manufacturing SMEs were developed based on the key question: How can SMEs undertake first steps in the development of data-driven services against the background of their limited resources and capabilities?

In application of business process management (BPM) tools in European commercial sectors, this paper examines current maturity of customer centricity construct (CC). CC is observed as an emerging dimension of competition and as a potential strategic management direction for the future of business. Processes are one of the key components of transformation in the CC roadmap. Particular departments are more customer orientated than others, and processes, customer-centric expertise, and approach can be built and utilized starting from them. Positive items within a current business process that only involve minor modification could be the basis for that. 18 case studies are used to assess the mapping of an operational definition of CC with value aims of BPM. The evidence of movement on the customer-centric roadmap is found. BPM in European telecommunications, banking, utility and retail sector supports roadmap towards customer-centricity in process view, process alignment and process optimization. However, the movement is partial and not flawless, as BPM hasn’t been inquired for supporting many of customer-centric dimensions.

Rooted on the principle “from cradle to grave”, the lifecycle-driven approach to managing products like automobiles and related services has been recognised as a pivotal approach in research and practice [5, 15]. Digital technologies have continuously fostered the further development of product lifecycle management (PLM) in recent decades [17]. Nowadays, novel disruptive technologies offer even more important advances for providers and users of such solutions alike [14]. For the case of the automotive industry, intelligent products have created seamless visibility over the vehicle operations [9], big data techniques allow for the creation of sound insights [10], and blockchain technology holds the potential for trustworthy vehicle data management [2, 7]. The economic potential of preventing fraud and providing correct data is vast. Solely for the case of mileage manipulation, financial damage of around 9 billion Euro is estimated for the European Union [3]. Accurate data establishing the basis for digital services potentially delivers a global revenue in the 100 billion Euro range [11]. While these benefits of decentralised and encrypted data management are clear in theory [6, 18], less knowledge is available about the practical implementation of such blockchain-based solutions [2, 7]. The purpose of this case study [19] is to reflect experiences from a project in the setting of a leading automotive player which targets development and roll out of a trustworthy product lifecycle management using blockchain technology. Specifically, the study at hand mirrors insights from the automotive ecosystem focusing on the business-to-business context, involving fleets, OEMs, and repair shops. Such a case study seems valuable as research and practice call for real-world insights on blockchain applications especially outside the financial industry [1]. After this abstract, the second part of the case study provides a sketch of product lifecycle management and blockchain technology itself. In the third part, further details on the case of vehicle operations in the automotive ecosystem are given. The fourth part illustrates findings in terms of experience from the realisation of trustworthy product lifecycle management. In the fifth part, a discussion on the diverse and relevant hurdles to overcome is followed by a description of limitations and a view towards the future.

The paper at hand analyses if plants follow a development path in knowledge transfer from a knowledge receiver role to a knowledge sender role. In this, the plant’s age and the content of knowledge that is transferred are analysed. The study includes thirteen case studies in four different European countries (i.e., Switzerland, Romania, Albania, and Macedonia) and shows that the content of the transferred knowledge changes in relation to the plant’s development stage and its role that the plant takes at the end of the undergone development stage. The lower the development stage, the more basic knowledge related to innovation and product/process improvement is transferred. As the development stage gets higher, more specific task related knowledge is transferred. Furthermore, results indicate that the plant’s age cannot fully be linked to the development stage of the plant under investigation.

Purpose: This paper discusses approaches that are specific for manufacturing SMEs (small and medium-sized enterprises) to leverage data in the servitization process. Advanced services are based on output performance guarantees with complex risk and revenue sharing mechanisms. For this type of services, the ability to manage, process, and analyse data of the installed base is considered essential. Therefore, with the increasing degree of servitization of manufacturing, leveraging data for the development and the provision of services becomes a key asset and represents a key challenge. Design/Methodology/Approach: An SME-specific analysis of these challenges and approaches for developing data-driven services is presented based on a combination of theoretical insights and a case study with several SMEs. The concepts derived from the literature are validated and enhanced with the insights gained from the SMEs in practice. Findings: First, the drivers pushing the SME towards providing output-oriented advanced services are discussed. These drivers are related to the customer needs and the market position of the manufacturer. Second, the data-specific challenges of SMEs in the servitization process are elaborated, which are related to the SME’s position in the value chain as well as to its access to the required skills and resources. Third, approaches for the SMEs to tackle these challenges are presented in order to enable the data-driven servitization process. Originality/Value: This paper provides a new perspective on servitization of manufacturing by a focus on leveraging data and analytics for servitization. The research is relevant in order to address the challenges and solution approaches which are specific for manufacturing SMEs.

IIoT may influence supplier, internal and customer integration. However, the influence may not be described with the usual items of SCI but instead needs to be adapted. The analysis is based on 11 IIoT initiatives and reveals that the overarching changes related to people, data and technologies can be summarized into measures concerning condition monitoring and predictive maintenance. Thus, the respective factors seem to be relevant in order to analyse the influence of IIoT initiatives on SCI. Despite the decision where to start (internal or external), the IIoT initiatives seem to lead to a higher level in both dimensions.

The pervasive infiltration of digital technology into physical products brings both tremendous challenges and opportunities to original equipment manufacturers. With the goal to support the initial stages of the product lifecycle, this article introduces a method compendium for the development of digitised products. More precisely, the compendium suggests: 1) customer- and user-centric innovation methods; 2) agile and prototyping methods; 3) system and architecture modelling methods; 4) feedback- and data-driven methods; 5) service and business modelling methods. Methodically, we draw on secondary data from a longitudinal single-case study scrutinising the development of digitised trucks at a leading materials handling and intralogistics organisation. Bounded to the business-to-business context of industrial equipment manufacturing, we enrich product lifecycle management with methodological contributions valuable for academia and practice alike.

Introduction: The aim of a circular economy is to transform waste into resources. There is a plethora of waste and by-products that remain unused in the traditional linear industrial system. However, transformation from a linear to a circular system is challenging, limited by several constraints such as the availability of information on the specific composition of the waste, the availability in time and space, the quantity of waste, as well as limited knowledge of the usability of such waste products. These challenges are exacerbated by the initial effort needed for implementation before an economy benefits from economic, ecological or societal improvements. Nevertheless, a circular economy generates less waste and consumes fewer resources, which in return makes it more profitable due to cost savings enabled by efficient resource use. The goal of the SHAREBOX project is the development of a platform for the facilitation of synergies within the industry to enable a more circular flow of resources within the European process industries. The project consortium has 15 partners including research organisations, SMEs and industrial partners as well as market actors and is part of the EU framework program Horizon 2020. Materials and Methods: The SHAREBOX platform is a database of available waste and resources required by companies, enabling the transformation of waste to resources by matching of two demands. The platform also serves as the first point of contact between different partners in a circular system. Furthermore, the platform enables the identification of new synergies overarching the different subsectors of the industries as well as optimal matching from the perspective of a circular economy. The key objectives are the facilitation of circular synergies through information and communications technology, the provision of information required to realise circular synergies within European industries and the identification of new circular synergies. Results and Discussion: The results of circular industry systems facilitated by the National Industrial Symbiosis Program (NISP) in the United Kingdom show a substantial reduction in the consumption of resources and generation of emissions compared to linear systems. Nevertheless, if there is a plethora of different types of waste, there is also a plethora of different synergies. This leads to different results for each type of waste that is transformed to a resource. Furthermore, the life cycle stage of transformation also has to be included. A transformation such as the reuse of polyethylene terephthalate (PET) can lead to emissions or require additional auxiliary materials as well as transportation. Therefore, the potential benefit will never be equal to the total impact of the primary input because of the transformation stage and the associated environmental impacts of collection and beneficiation. We analysed the implications of the transformation of different waste types to resources when industries are located in different geographic locations under consideration of the life cycle stage of transformation. Figure 2 shows the most significant results of the net benefit within the set of analysed waste types: the transformation of PET and concrete waste. Waste PET can be transported up to 10 000 km by lorry and still provide a net benefit regarding greenhouse gas emissions due to circular use. However, in case of concrete, the results are very different. A net benefit only occurs if the additional transport distance compared to primary concrete is less than 5 km. As a reference, the median of the transported distance of completed transformations within the NISP in the United Kingdom according to Jensen et al. is indicated with a black cross. About half of the 979 transformations within NISP were realised within a radius of 33 km and only one quarter of the synergies involved distances greater than 64 km. Conclusions: Transformation from linear to circular systems can substantially reduce total resource consumption as well as emissions of the whole value chain and therefore contribute to a greener economy. However, matching industries for transformations leading to the substitution of primary materials is still a major challenge. In addition, the environmental benefits of the reuse of resources is limited by the life cycle stage of the transformation as well as by additional transportation that may be required. The analysed set of types of waste shows a broad range of potential benefits. For some types of waste, the net benefits are still considerable after the subtraction of the additional impacts due to the life cycle stage of transformation as well as additional transport requirements. However, for selected types of waste, the net benefit tends to be negligible. The completeness of the scope will be crucial for the assessment and generalisations overarching different types of waste remain challenging.

In the digital age, manufacturing industries are in constant motion. Driven by tremendous advances of information technology and as response to a variety of challenges in highly competitive market places, a set of product-related processes, methodologies, and information and communication technologies emerged over the last decades. In brief, product lifecycle management is a business strategy that aims at navigating industrial products from early design and manufacturing to actual usage and support to ultimate deposition. Relevant and timely in research and practice, product lifecycle management manifests as (1) challenging in practice, (2) influenced by emerging digital technologies, and (3) novel to information systems. In this sense, the cumulative dissertation at hand represents a continuation and extension of existing research on product lifecycle management. In detail, the objective of the dissertation is to understand (1) challenges, (2) developments, and (3) transformation processes of product lifecycle management in manufacturing industries occupying an information systems point of view. The first article explores challenges in product lifecycle management by taking the example of the automotive industry. Subsequent articles two, three, and four represent the main part of the dissertation. They address pivotal developments in product lifecycle management adopting lifecycle, stakeholder, and discipline perspectives. The fifth article thematizes a transformation project as longitudinal case study. Conclusively, the sixth article charts the research field employing bibliometric methods. Considering limitations by the ample scholarly field, heterogeneous contextual settings and scientific communities, and the mainly qualitative research strategy, the dissertation contributes as follows: For research, the work at hand extends the body of knowledge in information systems and product lifecycle management. Thereby, the application of information systems foundations and methodologies supports advanced insights into the socio-technical dimensions of product lifecycle management. For practice, the work at hand offers business- and technology-oriented executives in strategic research & development and IT engineering departments valuable knowledge for the design, implementation, and advancement of product lifecycle management in manufacturing industries.

Computer games and gaming consoles have used gesture and speech recognition for many years, making the gaming experience more exciting by increasing the level of immersion. Like games, business process models and their creation require extensive human computer interaction but fail to appeal to people in the same way, i.e., through a comparable (exciting or fascinating) experience. Because involvement and motivation of knowledge workers is essential for the success of process modeling, the adaptation of interaction concepts used successfully in computer games to process modeling might be a promising approach. In this paper, we present our findings from implementing prototypes for modeling business processes with gesture and speech recognition and analyze strengths and weaknesses of these interfaces. In addition, we present our results from an evaluation of our prototypes on efficiency, collaboration, and immersion and compare these results with tools using mouse and keyboard as input devices.

This overview article broadly summarizes the current state of knowledge and key future challenges for marketing logistics services. The best companies now market “with”, rather than “to” customers and have become masters of digital marketing. Two new customer categories that will expand logistics marketing beyond what is imaginable today are just around the corner.

Purpose The purpose of this paper is to analyse the prerequisites for lateral knowledge transfer in manufacturing networks. Design/methodology/approach Data stem from a single case study involving 26 interviews at the management level of a manufacturing network and a survey of 17 manufacturing plants in the network. Findings The requirements for lateral knowledge transfer between knowledge-sending and knowledge-receiving plants are similar strategic orientation, product portfolio similarity and process similarity. If the knowledge-sending and knowledge-receiving plants meet at least one of these requirements, then knowledge transfer is facilitated. Plant age, functional ties and geographical proximity do not seem to be important in lateral knowledge transfer. Research limitations/implications The results come from a single case study, limiting their generalisability. Further research should consider the influence of the network’s coordination mechanism on lateral knowledge transfer. Originality/value The paper investigates prerequisites for lateral knowledge transfer in manufacturing networks, shedding light on the fundamental factors that must be in place at the knowledge-sending and knowledge-receiving plants.

In the light of pervasive digitalization, traditional physical products get augmented with digital components that create the potential of making the whole product lifecycle visible for product developers. As numerous opportunities sketch out how feedback such as sensor data might be leveraged for future products, a comprehensive model to describe, particularly a classification model to organize and structure these opportunities seems analytically useful. Hence, this paper pursues a scenario-based approach and proposes a taxonomy for feedback-driven product development scenarios in manufacturing industries. Grounded on (1) empirical data from case studies and focus groups and (2) a systematic literature review, we follow an established taxonomy development method employing the general systems theory as meta-characteristic. With the limitation of a (1) qualitative, interpretive empirical research design and a (2) representative literature review, we contribute to the body of knowledge by shedding light on feedback-driven product development from a classification perspective which may act as structuring and creativity fostering tool.

Purpose: This paper aims at describing a design approach for the transformation from products to services in small manufacturing firms. We discuss the design of value propositions for customers which takes the customer life-cycle into account. Additionally, we present a scheme for designing the customer interactions that enables the optimisation of the cost and value contributions. Design/Methodology/Approach: We interpret the methodologies of service design for the industrial context. The concept of the customer journey design is transferred to the business-to-business constellation. Moreover, an established scheme for the value-based design of customer interactions is adapted to the case of services in manufacturing. Findings: Methodologies for customer-centric service design can be transferred and applied to industrial services. The concepts of customer insight research and value proposition design can be interpreted for the business-to-business context. Special attention has to be paid to the design of the customer journey for manufacturing companies. Additionally, a dedicated scheme can be used to map the service interactions to a value matrix depending on their value contribution to the customer and the provider, respectively. Originality/Value: This paper provides a new approach to servitization of manufacturing by adapting approaches from service and interaction design to the product-service transformation of manufacturing firms. The research is relevant in order to address the lack of methodologies for design-centred servitization approaches in small manufacturing firms.

Die Leistungsfähigkeit eines Produktionssystems wird wesentlich durch die Logik der Produktionsplanung und -steuerung (PPS) bestimmt, wobei die physische Produktionsinfrastruktur die Rahmenbedingungen dazu liefert. Industrie 4.0 schlägt sowohl auf physischer als auch auf logischer Ebene neue Ansätze vor. Auf physischer Ebene werden Möglichkeiten der digitalen Infrastrukturvernetzung betrachtet, welche eine detaillierte, zeitnahe Erfassung dynamischer Betriebsdaten erlauben. Auf logischer Ebene werden dezentrale Steuerungskonzepte basierend auf autonomen Systemkomponenten diskutiert. Für den PPS-Praktiker ergeben sich zahlreiche betriebsrelevante Fragen: Wie sollen die detailliert verfügbaren Betriebsdaten neu in die PPS-Logik einfliessen? Welcher Nutzen kann daraus gezogen werden? Welche PPS-Planungsebenen (langfristige Programmplanung, mittelfristige Materialbedarfs- und Terminplanung, kurzfristige Ablaufplanung) sollen wie angepasst werden? Wann und in welchem Bereich könnten dezentrale Steuerungskonzepte vorteilhaft sein? Worin unterscheiden sich die neuen Steuerungsansätze von den bekannten, dezentralen Konzepten des JIT und Lean Manufacturing? Welcher Optimierungsansatz ist in welcher Situation adäquat? Das Institut für Datenanalyse und Prozessdesign (IDP) der ZHAW beschäftigt sich in der Fachgruppe "Business Engineering and Operations Management" intensiv mit solchen Fragen und unterstützt zahlreiche Industrie- und Wirtschaftspartner im Rahmen von F&E-Projekten, Beratungsaufträgen und Studentenarbeiten. Zu den Kernkomptenzen des IDP gehören insbesondere die wissenschaftliche Analyse und Umsetzung anspruchsvoller Planungsmethoden sowie die quantitative Modellierung und softwarebasierte Optimierung komplexer Geschäftsprozesse.

Starting next year, what can be labelled as ‘Swiss Made’ in Advertising will be governed by a new set of laws. These laws will also affect services; and, as 2017 is right around the corner, it is time to consider their implications for the Swiss service industry, including logistics.

Your suppliers’ wrongdoings can be reflected in the service you offer to your customers. This creates the need for Suppliers Codes of Conducts (SSC), which transfer buyer expectations into supplier behavior and have become an essential tool in global supply chain management. Looking at the SSC of Roche, of SWISS, and initiatives in supplier collaboration, we argue that SSC are important to create mutual understanding on what matters in the supply chain beyond product and service specifications.

Purpose The purpose of this paper is to provide guidance in setting the level of autonomy (i.e. parental control) of plants in a network to enhance operational performance. In particular, the effect of autonomy on performance is analysed directly and indirectly through internal manufacturing network integration (MNI) and external supply chain integration (SCI) as two dimensions of manufacturing network embeddedness. Design/methodology/approach The analysis is based on data from 441 manufacturing plants in 17 countries. Data were gathered during the Sixth International Manufacturing Strategy Survey. Five main constructs were obtained after carrying out a confirmatory factor analysis: plant autonomy, internal MNI, external SCI, efficiency and effectiveness. Direct and indirect relationships among the constructs are tested through a structural equation model. Findings Higher levels of autonomy correlate with higher effectiveness and similar efficiency. However, lower autonomy leads to higher levels of manufacturing network and SCI, which enhance performance. Although not statistically significant, the analysis of the total effects reveals a mildly positive effect of autonomy on effectiveness and negative effect on efficiency, which requires further investigation. Research limitations/implications Further research could include headquarters’ perspectives or additional determinants (e.g. business strategy objectives). Practical implications Managers should set autonomy levels strategically: higher for effectiveness and lower for efficiency. However, lower autonomy can also strengthen internal MNI and external SCI, thus improving operational performance. Originality/value The concept of manufacturing network embeddedness highlights the importance of considering external supply chain and internal MNI in the same framework, as both dimensions can affect operational performance.

The economics of production systems depends on how expenses in terms of lifecycle costs for machines are balanced by revenues. Most classical models for optimizing lifecycle decisions are based on a profit maximization paradigm. However, the solutions are strongly dependent on how the technical performance of the machine is translated into monetary units. This is a critical issue because often it is not easy to monetarize non-ideal behavior of machines (e.g. How to monetarize the image damage of the company resulting from a major production outage?). In the present paper, we present a new perspective on the economics of production systems which is not based on a monetary (profit maximization) paradigm. Instead, we model a production system as an object that (a) needs investment, and (b) generates a value for the company, but this value can be expressed in arbitrary units. This is consistent with the approach of the new ISO standard 55’000. In such a framework, it is no more possible to base decision making on maximization of a single objective such as profit, as costs and value are measured in different units and cannot be added. However, many lifecycle decision problems can still be solved. In particular, we discuss typical lifecycle problems such as determining optimal lifetime or optimum maintenance levels. We show that, given a portfolio of machines, the optimum decisions for the single machines can be determined, with exception of a single global parameter that holds for the portfolio as a whole. For our approach, we combine approaches from economic utility theory and multidimensional optimization with lifecycle models of technical assets.