Smart Services Summit

Digital servitization describes the change of business models towards smart service offerings enabled by digitization. One challenge of digital servitization for manufacturers is to gain a better understanding how smart services generate value-in-use. To examine individual value-in-use concepts regarding smart services, we conducted and analyzed 22 in-depth interviews with the repertory grid technique. Our findings show that the respondents have a fairly uniform understanding of what constitutes an ideal service. Their perception of the service of tomorrow, smart service, and remote service offerings is closer to a future ideal than the service of today. Further we were able to group individual value perceptions into four groups and to discuss differences of an external and internal view on smart service. Interestingly sustainability was not mentioned as a value dimension in our study, which should be investigated further.

Digital Transformation provides both value creation and co-creation opportunities within manufacturing firms, enabling these to develop new and more efficient ‘digitally-enabled’ value propositions. However, there remain notable gaps in communicating these digital opportunities (value) throughout a firm, creating barriers to justifying (digital) transformations, and limiting their adoption. This paper aims to explore this gap using input from industrial case studies and to create a framework that recognises relevant metrics to identify and communicate digital value. The findings highlight the importance of translating metrics between the different levels of a firm and communicating visually these to better appreciate the new digitally-enabled value (co-)creation process(es).

This paper investigates the creation of economic and ecological value in manufacturing ecosystems. The focus is put on the B2B relationship during a lifecycle between a provider of production machines and a customer applying this machine in its own production processes. Smart services for manufacturing environments have been proven to create economic value for the actors in an ecosystem and there are several quantitative approaches to assess this value. Additionally, smart services have the potential to create ecological value by manifold levers such as, for example, higher equipment efficiency, extended lifetime, or more efficient maintenance processes. This paper extends the existing quantitative models for economic value creation by incorporating a quantitative model for ecological benefits and costs.

This paper takes a design research approach to explore the challenge of user attrition in the consumer wearables sector and its impact on eWaste which is a growing concern for many countries. Previous research demonstrated the lack of value-in-use realised by users as the key driver of user attrition. The abandoned smart service products then become the source of mounting eWaste which creates environmental pollution and puts human health at risk. This study hypothesises that a sustainable interaction between user and consumer wearables will reduce the user attrition rate, which will, as a result, decrease the amount of eWaste. This hypothesis is examined through three case studies that showcase the past, the present, and the future of the consumer wearables sector. The study contributions are as follows. First, it takes a zoom-in and a zoom-out approach to understand how the challenge of user attrition at the micro-level leads to the challenge of environmental sustainability at the macro-level. Secondly, this study introduces how the design research community uses case studies as a method in design research to the non-design research community. Lastly, three propositions introduced in this research could inform the foundation of a sustainable human-smart service product interaction framework.

Improving sustainability concerns many stakeholders: customers, shareholders, employees, and regulators. The manufacturing industry is a significant factor as production continually depletes finite resources. Without a shift to more sustainable business models (i.e. those based on the triple bottom line), there is a risk of continued depletion of resources. A common finding from prior work is the need to act within an ecosystem approach to support the development of a circular economy that considers the multiple interactions and dynamic recombination of resources that lead to value co-creation. This paper investigates the interplay of ecosystem actors and builds conceptual habitats to improve sustainability. It considers the strategic meso and macro levels of the ecosystem to provide detailed insights into the behaviors and motivations of different actors. Critical bilateral and multilateral interdependences among the ecosystem actors are highlighted. The presence of digitalization provides the necessary institutional arrangements for interactions between diverse actors. This builds upon the work of West et al. (Practices and tools for servitization. Springer, pp. 363–385, 2018), by creating multiple conceptual future state ecosystems, identifying gaps within the ecosystems, and providing a description of the actors. The study suggests that an extended model is considered for developing and operationalizing sustainability-based business models for capital equipment. The limitations of this study reveal the requirement to validate and cross-check the suggestions in a real case example with a broader scope for comprehensive qualitative and quantitative data collection.

35% of Green house Gases (GhG) savings to meet the Paris climate targets can be achieved through energy efficiency. Unfortunately, strong demand market barriers slow down market adaptation of energy efficient solutions. Servitisation, or the business model of paying for a service received instead of purchasing the asset, represents a strong solution to accelerate the implementation of higher energy efficient solutions, while also fostering a circular economy mindset and therefore reducing the economy’s dependence and consumption of raw materials. Several companies across the globe have started implementing the model, and results are promising. Customers benefit from instantaneous energy consumption reductions while providers gain control to accelerate the implementation of innovative climate resilient technologies on the markets. Nonetheless, implementing servitisation in business operations is complex; it requires a shift in company revenue models, a much more active on the ground presence, digital solutions, reliable measurements, state of the art maintenance and repairs, and optimised supply chains, while also requiring for solution providers to develop the right financing mechanism to fund the implementation of the solutions and their operations. Implementing servitisation differs considerably from the classic sales business models. However, beyond these challenges, removing the upfront investment requirement and all perceived risks of operations from the customer’s table is a highly competitive selling argument to convince clients to engage with climate resilient solutions.

Following the Paris Climate Agreement, the maritime industry has committed to reducing its GHG emissions by 50% by 2050 (compared to 2008). In this sense, the present work pursues this goal by focusing on an improved route optimization method using Reinforcement Learning (RL). A detailed comparison between RL and the conventional approach is carried out in this study. Besides RL, Dynamic Programming (DP) is also used to establish the benchmark. The influence of different grid resolutions and dynamic weather on effective CO₂ reduction is analyzed. It is observed that these two aspects can play a significant role in the route optimization results. Furthermore, the results show that RL as a model-free approach offers a great advantage for these considerations.

Three marketplace archetypes of increasing complexity are conceptualised with business models for services that support the implementation of demand response programs.

As one of the most important branches of the industry in Germany and the European Union, the mechanical and plant engineering sector is confronted with fundamental changes due to ever shorter innovation cycles and increased competitive pressure. This makes it even more important to increase the level of service components in business models with a low service level, which are still frequently found in SMEs. This paper is dedicated to the changes that the individual components of a business model have experienced and will experience. Special attention is paid to economic sustainability, since service business models can also positively influence the long-term nature of a business. Seven interviews conducted with relevant companies serve as the empirical basis of this paper. The analysed effects of smart services and active customer integration are structured and summarized within the three pillars of every business model (value proposition, the value creation architecture and the revenue mechanic).

The role of entrepreneurs and intrapreneurs in the current zeitgeist is to drive innovation, re-shape rigid, established processes in business as well as for consumers. They use new viewpoints to pioneer new (business) models which focus on ‘smartness’ rather than the purely monetary and short-sighted models of yesteryear. Fostering and supporting the culture of this current zeitgeist is a mayor challenge for entre- and intrapreneurial support infrastructures, namely startup centres and innovation hubs of universities and other public institutions as well as innovation centres of private companies. Hereby, support may range from access to funding over provision of resources such as offices or computing hardware to coaching in the development of business ideas and strategic roadmaps for product and service deployment. In this paper, we focus on describing the status-quo of aforementioned support infrastructures in Vorarlberg and the Lake Constance region, then extend the scope to existing (international) approaches for aiding founders and innovators in the development of smart services. An analysis of success stories of the Vorarlberg startup centre ‘startupstube’ and other initiatives including their comparison to international counterparts builds the basis for a methodological framework for (service science) coaching in entre- and intrapreneurial support infrastructures. The paper is concluded by the description of a framework for choosing the right methods and tools to create service value in entre-/intrapreneurship based upon tested, proven know-how and for defining support infrastructure needs based upon pre-defined stakeholder and target groups as well as the (industry) sectors of the innovators.

This paper explores radical innovation in industrial firms in the DACH region to help identify success factors via an exploratory study. The underpinning assumption is that for real sustainability, firms must innovate for the long-term and deliver ongoing incremental innovation. The challenge is that different approaches are needed to be successful in both forms. In our study, we interview over 100 senior managers through a Delphi process to gain insights. We identify seven barriers and the cause of the obstacles, and we also recognise seven lessons that improve the sustainability of radical innovation. The synthesis of the work is that firms must become learning organisations and that they need to consider the behavioural aspects of management, the necessary adaptability of the process, and the long-term funding aspect of radical innovation.

As software services become more and more indispensable in our daily lives, low-code and no-code platforms are gaining significance, especially for non-technical users. We present a novel domain-specific modeling language for the definition of smart service systems in the context of smart cities, which we call Smart Service Definition Language (SSDL). The main goal of this formal language is to provide a basis for a low-coding software engineering approach for the design and deployment of smart services. SSDL is based on the Smart City Ontology (SCO) to provide syntactic and semantic elements related to the smart city environment and aims at defining a syntax as near as possible to human language to overcome acceptance problems for non-technical users. The proposed language can be used by smart system designers and other stakeholders to define the components, actors, data and relationships between the different elements that compose smart service systems in a formal and reproducible way, paving the way for an automatic or semi-automatic generation of ready-to-deploy smart services as independent applications, which may take the form of web services to be integrated in service-oriented architectures. In this paper, we present the syntax of SSDL and provide an example use-case for its application to the problem of designing a smart service for parking lot management.

This paper aims to apply the basics of the Service-Dominant Logic, especially the concept of creating benefits through serving, to the stationary retail industry. In the industrial context, the shift from a product-driven point of view to a service-driven perspective has been discussed widely. However, there are only few connections to how this can be applied to the retail sector on a B2C-level and how retailers can use smart services in order to enable customer engagement, loyalty and retention. The expectations of customers towards future stationary retail develop significantly as consumers got used to the comfort of online shopping. Especially the younger generation—the Generation Z—seems to have changed their priorities from the bare purchase of products to an experience- and service-driven approach when shopping over-the-counter. To stay successful long-term, companies from this sector need to adapt to the expectations of their future main customer group. Therefore, this paper will analyse the specific needs of Generation Z, explain how smart services contribute to creating benefit for this customer group and how this affects the economic sustainability of these firms.

Climate change and environmental pressures are pushing companies to adopt Circular Economy (CE) business models based on remanufacturing and on the provision of Product-Service Systems (PSS). However, specific guidelines on how to implement these business models are lacking. Thus, this paper aims to analyze CE business models based on remanufacturing and PSS, to define a full list of key recurrent and common elements that are needed to setup these specific business models. A multiple case study analysis is carried out, and a full list of configuration options for both remanufacturing and PSS business models is drafted. Results can help manufacturing companies in reshaping their value proposition, value delivery, value creation and value capture towards a CE based on remanufacturing and PSS.

Through mandatory ESG (environmental, social, governance) reporting large companies must disclose their ESG activities showing how sustainability risks are incorporated in their decision-making and production processes. This disclosure obligation, however, does not apply to small and medium-sized enterprises (SME), creating a gap in the ESG dataset. Banks are therefore required to collect sustainability data of their SME customers independently to ensure complete ESG integration in the risk analysis process for loans. In this paper, we examine ESG risk analysis through a smart science approach laying the focus on possible value outcomes of sustainable smart services for banks as well as for their (SME) customers. The paper describes ESG factors, how services can be derived from them, targeted metrics of ESG and an ESG Service Creation Framework (business ecosystem building, process model, and value creation). The description of an exemplary use case highlighting the necessary ecosystem for service creation as well as the created value concludes the paper.

More and more companies in the manufacturing industry are striving to transform from a transactional to a service-driven so-called “Subscription” business model to benefit monetarily from the opportunities offered by Industry 4.0. One hurdle in this transformation is the formulation of the appropriate service offering. While customers’ demands for value provided with the service offering are becoming ever more extensive, the complexity of a combined service offering consisting of product, service, and software (product-service system) is also increasing. In practice as well as in the literature, recurring patterns of specific user types can be identified, which in turn help to standardize the service offering. However, this concrete user and value consideration has not yet been applied to business models in the subscription economy. The two central research methods that are used here are a detailed literature analysis and interviews with experts from the industry. The aim of this work is the identification of concrete customer types and their characterization based on specific features and attributes. With the help of specific customer types, companies in the manufacturing industry should be able to align their range of services in a targeted and user-oriented manner. In addition, the concrete addressing of identified customer types helps to better meet customer requirements and consequently to increase business success.

As a digital technology, predictive maintenance (PdM) can contribute substantially to the necessary sustainable transformation of the manufacturing industry by maintaining assets more efficiently, increasing material and energy efficiency, and reducing associated waste. But as manufacturing companies struggle to implement sustainability, sustainable business models (SBM) for PdM might be a viable approach to systematically integrate sustainability. Hence the current PdM business models of manufacturing companies were analyzed by means of an exploratory case study. In a second step, elements of SBM that are already supported by today’s PdM business models, as well as respective gaps to be addressed in the future, were identified. This study concludes that many elements of SBMs are already supported today, but the main emphasis lies purely on the economic benefits, and ecological and social benefits are currently disregarded. To develop SBMs for PdM, ecological and social aspects need to be systematically evaluated and integrated.

A successful business is increasingly concerned with comprehending the challenges and opportunities associated with society’s shift towards sustainability. However, current business model innovation fails to embrace the sustainability dimensions sufficiently. Many organizations lack a process that allows them generate entirely new and viable alternatives for business models. Sustainable development and its three-dimensional framework significantly impact most businesses’ re-organization. The complexity of balancing the economic, environmental, and social dimensions of sustainable development signals the need for a new business model. In this conceptual paper, the authors discuss possible transitioning from the business model to the contribution model, where the value ecosystem and value exchange plays a defining role.

In shipping, the choice of the right routing and speed offers the opportunity to act more sustainably from both an economic and an ecological point of view. Reinforcement Learning (RL) agents could be suitable for this task. However, as a learning environment the agents require the most detailed, accurate, and fast representation of reality possible. This paper describes approaches to build such an environment using neural networks (NN) trained with both simulation and real-world data. It is shown that simple feed-forward networks can reproduce data created by 1D flow simulation sufficiently accurate. By examining the differences between simulation and measured data, the simulation could be improved. Since NNs trained with vessel data only are limited in their generality, approximating nets trained with simulation data to vessel data using Transfer Learning (TL) was investigated. Initial results for this approach show good quantitative results, but only in the data region where vessel and simulation data overlap. The paper provides an overview of the necessary steps towards Digital Twins for ship propulsion systems.

Asset management strategies for industrial process plants and utilities are based on inspection and test programs to periodically evaluate the progression of life consumption. A common shortcoming of such plans is that they are static and offer little flexibility for adaptation based on the actual operating experience. Data to improve these asset management plans is available from a variety of sources. Consolidating the data from these different sources is challenging but represents an opportunity for smart service providers to improve their offering and for operators to increase their production in a safe and reliable manner. Over the years, General Electric (GE) has been applying a variety of asset management technologies to improve power plant life and performance for their customers. These methods consider various inputs including equipment design knowledge, asset condition assessed from real-time monitoring and inspection data, and lessons learned from repairing, operating and maintaining thousands of assets globally. Risk-based inspection (RBI) represents a next generation of inspection and life management approaches. RBI is a consistent decision-making technique, which uses risk as a proxy for “asset condition,” to manage the scope and frequency for the different activities in an asset life plan. This paper shows how GE has used RBI to perform risk-based health and life assessments for steam turbines and generators in power plants. The method has been used on several steam power plants around the world, to help operators of ageing steam plants make the right decisions to successfully navigate the global energy transition.

Last mile delivery of perishables is challenging in situations where necessary infrastructure to accomplish this task is lacking. However, the need for perishables, such as fresh blood for transfusion, does not disappear simply because of transportation-related issues. While last mile delivery has traditionally been done through ground-based modes, recent advances in drone-based technology calls for serious consideration of air-based delivery mode. In response to this call, current last mile delivery includes a mix of ground- and drone-based modes. In addition to the rest of the supply chain, the need to consider the last mile delivery aspect invariably renders the system more complex and requires the consideration of effective methods. Machine learning has been successfully used in complex systems. We therefore consider machine learning in various facets of last mile delivery scenarios with specific focus on classification, clustering, and optimization. We discuss possible applications of machine learning across these facets in drone-based last mile delivery of perishables.

Field service providers can reduce customer trips with evermore improving technologies in machine learning and digital twins. However, there is more than one aspect that needs to be considered. First, the customer’s intimacy with the provider may shrink with reduced customer service journeys. Furthermore, the reduction of service trips may have a positive influence on ecological sustainability as CO\(_2\) emissions are reduced. This paper presents an early-stage model to calculate three main KPIs in the service field: Ecological sustainability, Economic sustainability, and Customer intimacy. The model is built on an agent-based and discrete event core that simulates a service provider’s service ecosystem. It is then tested on data from a real-life use case. The results are promising and show interrelationships that need to be further investigated in the future. A particular focus in further research has to lie in understanding the economic splitting of cost and benefit between the customer and the provider.

In the context of digitalization, companies today are faced with the challenge of rethinking their process management, especially if they aim to provide smart services. Digitizing processes is not a direct route, as they are neither merely transferable nor do the processes will remain unchanged. The development and implementation of smart services as a dynamic form of digitalization also includes the consideration and analysis of existing workflows and practices. In particular, the embedded knowledge of interconnected and complex processes is underestimated, and digitization initiatives tend to move towards a closed end. In addition, the skills and embodied knowledge situated in employees is difficult to be used as core source for co-creative teamwork in front of transformation. Policy making and manual development used to support knowledge extraction and analysis of process management is a co-creative and highly effective support in this context. This paper sheds light on how the visual practice of guideline development from an industrial case can inform the creation of smart services in its primary state as proto service. This helps digital transformation project management become commercially attractive by reducing rework or project re-planning, and it enables employee integrity during the transformation. In addition, the developed approach can be used in such projects to support service training of employees in various roles from operations, development to management.