Increasing digitization and global interconnectedness provide firms with new opportunities for openness in value creation, generating new sources of competitive advantage. We investigate the competitive advantage of open value creation (OVC) and the influencing role of novelty- and efficiency-oriented business model (BM) designs as unique logics of guiding collaborations to access and utilize external resources for value creation. We further examine the role of trust in such collaborative relationships to navigate the relational uncertainties in boundary-spanning transactions within BMs. Based on a survey study with secondary data triangulation, we investigate how companies gain competitive advantage through OVC by adopting an appropriate BM design and relational governance of trust in partners. Our results prove a positive effect of openness in value creation on competitive advantage while the strength of this positive effect is moderated by the BM design and relational trust. Our paper provides guidance on managing openness in value creation under the divergent designs of BMs and relational trust.

Platforms are on the rise in the Industrial Internet of Things (IIoT) as they transform industrial manufacturing and change how companies create and capture value. More and more companies are starting to develop IIoT platform-based business models (PBMs), but often face difficulties. Since these difficulties have mainly been discussed in business-to-consumer settings, we study those PBMs in an IIoT environment due to their differences from business-to-consumer environments. Using a mixed method, we first develop a taxonomy for IIoT PBMs based on a systematic literature review of 400 articles, 21 interviews, and 45 real-world PBMs and, secondly quantitatively analyze those real-world examples to derive five archetypes. By drawing conclusions about how these difficulties are addressed differently by the archetypes, our study contributes to the emerging research area of platforms in industrial business-to-business settings and guide firms to inform the design of new IIoT PBMs, ensuring they consider strategic factors.

Platform ecosystems have attracted a lot of attention as a new way of value creation and capture. In a longitudinal multi-case study, we compare the transformation efforts of two incumbents in the agricultural equipment industry between 2012 and 2021. We identify a set of interdependent choices incumbents make to adapt their model of value creation and capture toward a platform ecosystem. Based on an in-depth comparison, we show that incumbents' assessment of the potential of their product business may lead to distinct platform positioning – the platform as an extension of the legacy business (i.e., product-centric), or a product-independent platform. While our results indicate that both can initiate viable pathways for incumbents in their transition, we find that product-independent and product-centric positioning lead to distinct choice patterns and outcomes at the different levels of the emerging platform ecosystem.

Digital twins (DTs) are virtual representations of real-world entities like production assets, processes, or products. They are updated at a defined fidelity and frequency along the entire life cycle from development and engineering over the production or implementation of a product or process until its usage stage. Interconnected digital twins (IDTs) are DTs shared and connected across organizations with the objective to create holistic simulation and decision models of an entire physical system. In this paper, we investigate how IDTs shape future digital manufacturing scenarios and impact innovation management. We present the results of a real-time Delphi study, analyzing quantitative and qualitative estimates on a set of 24 projections, forecasting the future of digital manufacturing with a projection horizon towards 2030. Using this data and 22 additional use cases of IDTs in manufacturing companies, we present a baseline scenario where our Delphi panel reached a consensus, representing a likely future of digital manufacturing in 2030. By analyzing projections where our expert panels' evaluations vary widely, we identify key design decisions that may impact innovation management along the dimensions of variation, choice, and control in digital manufacturing. We explain how IDTs will impact external knowledge inflows, the emergence and governance of industrial data spaces, and the potential of data-driven and AI-enabled applications for prediction and regulation to drive better decision-making and continuous innovation.

Companies face both increasing demands for more environmental sustainability in their business decisions and stakeholder expectations for more profits. This trade off can be well examined by looking at location decisions of companies. Our paper addresses the question of the influence of countries' environmental regulations on company’s manufacturing location decisions. We investigate whether production decisions are cost-oriented or made according to ecological considerations. Consistent with the institutional theory we argue that firms select countries with weak environmental regulations for their manufacturing location. In addition, we ask what differences there are between companies. By considering firm heterogeneity, we expect that environmental capabilities and firm visibility weaken the negative effect of environmental regulation on manufacturing location decisions. An analysis of 779 location decisions made by 343 firms from 30 industrialized countries between 2007 and 2019 confirm our hypotheses. Our results provide empirical evidence for the Pollution Haven Hypothesis (PHH) and suggest that manufacturing location decisions are still made based on costs rather than environmental considerations. We contribute to the institutional theory and the PHH literature by focusing our analysis on manufacturing investments and by accounting for firm heterogeneity. Further, our empirical findings provide valuable insights for practice and policy maker.

AbstractThe Internet of Production (IoP), the global and integrated use of production data, will completely reshape how organizations operate and interact with each other. We introduce how these developments will affect the usage phase including value creation and capture in the future manufacturing ecosystem. Our analysis highlights requirements and implications for governance, organization, capabilities, and interfaces. These factors are considered from both a company internal and a company external perspective on usage as well as in terms of their interplay. The internal perspective focuses on the role of humans in interacting with IoP-based technology in future socio-technical production systems. The external perspective describes how value is captured and shared between stakeholders by incorporating data based on platform-based industrial ecosystems. The interplay of the two perspectives is exemplarily discussed using a foresight study on next-generation manufacturing.

The vision of the Internet of Production (loP) is focused on optimizing manufacturing processes, with the help of Industry 4.0 technologies (14Ts). However, considering global megatrends such as climate change and the need to achieve the Sustainable Development Goals (SDGs), it is a growing imperative for the manufacturing industry to become more sustainable. This opens the door to transforming the IoP into an Internet of Sustainable Production (loSP). Accordingly, this paper proposes a novel four-step loSP-framework that establishes an Information System (IS) allowing researchers and practitioners to acknowledge and adapt to the interconnected nature of sustainability. Further, to test its applicability, an inter- and cross-disciplinary perspective is adopted to illustrate case-related challenges, opportunities, and pathways - revealed by the proposed framework - in the example of a digital economy for sustainability data, strategic design of global production networks, human-robot collaboration, digital photonic production, and the textile industry. Together, the framework demonstrates the usefulness of generating holistic information on the interconnected nature of sustainability derived from process-specific and contextualized data, while simultaneously assessing the framework's utilization for sustainability, as well as the sustainability of its use.

AbstractMany companies in the Industry 4.0 (I4.0) environment are still lacking knowledge and experience of how to enter and participate in a platform-based ecosystem to gain long-term competitive advantages. This leads to uncertainty among firms when transforming into platform-based ecosystems. The article presents a structuralist approach to conceptualize the platform-based ecosystem construct, giving an overview of the literature landscape in a model bundled with unified terminology and different perspectives. The holistic process model aggregates the findings of 130 papers regarding platform-based ecosystem literature. It consists of 4 phases and 16 design elements that unify different terminologies from various research disciplines in one framework and provide a structured and process-oriented approach. Besides, use cases for different design elements were developed to make the model apply in an I4.0 context. Use Case I is a methodology that can be used to model and validate usage hypotheses based on usage data to derive optimization potential from identified deviations from real product usage. By collecting and refining data for analyzing different manufacturing applications and machine tool behavior the importance of specific data is shown in Use Case II and it is highlighted which data can be shared from an external perspective. Use Case III deals with strategic modeling of platform-based ecosystems and the research identifies control points that platform players can actively set to adjust their business models within alliance-driven cooperation to create and capture value jointly. Use Case IV investigates the status quo and expectations regarding platform-based ecosystems in the field of laser technology with the help of structured expert interviews. Overall, this chapter presents a framework on industrial platform-based ecosystems that gives researchers and practitioners a tool and specific examples to get started in this emerging topic.

The Delphi method is a structured scientific approach used to organize and structure an expert discussion in order to gain insights about the future. In order to develop scenarios for the future of Next Generation Manufacturing, an innovative real-time Delphi survey was conducted with 35 experts from industry and academia. The survey involved evaluating a set of 24 projections on the future of Next Generation Manufacturing, and the results of the survey were used to develop reliable future scenarios. Our main objective was to create a picture of the elements of Next Generation Manufacturing in 2030, guided by developments in the context of Industry 4.0. By using an innovative real-time Delphi approach in the context of Next Generation Manufacturing, we extend this established tool of strategic technology management from predicting technological developments and their impact on firms and society to providing a strategic guide for decision-makers in times of high uncertainty. Our study thus serves as a template for further applications of forecasting studies in interdisciplinary settings with high degrees of technical uncertainty. [Abstract generated by machine intelligence with GPT-3. No human intelligence applied.]

This study adds to the literature on household sector (HHS) innovation by investigating how user and professional designer teams differ in their ability to translate knowledge diversity into collective creative output. We test our hypotheses on a unique data set of more than 5,000 board game design projects conducted by either teams of professional game designers or by hobbyist (user) designers. Our study lends support for the notion that knowledge diversity is a double-edged sword that has opposing effects on the two dimensions of team creativity, novelty and usefulness. We argue and find that teams composed of self-rewarded users in the household sector are better able than teams of professionals to translate the informational benefits of knowledge diversity into novel concepts and game designs. Finally, we find that user teams are in general more likely to create truly creative (i.e. novel and useful) game designs. This particular result emphasizes the relevance of research on HHS innovation and shows that user designers from the HHS are able to conduct collective development work more effectively than teams of professional designers.

Many incumbents have the ambition to become ecosystem leaders when transitioning an established business model into a platform-based one. Prior research predominately has studied established consumer markets. Our study extends the empirical knowledge on ecosystem dynamics with a focus on platforms providing services based on (shared) industrial data. In a longitudinal study, we investigate factors influencing this transition and study in particular how industrial incumbents balance value creation and capture during ecosystem emergence. In this stage, managing openness is a key strategic decision. While openness is required for value creation, the complexity and physicality of the industrial setting hampers value capture. We identify control points to manage the tension between value creation & capture and derive different transition journeys. Lastly, we propose that in industrial markets, multiple platforms can co-exist in the same ecosystem, complementing the established "winner-takes-all" paradigm. Our research identifies situations where incumbents intentionally forfeit a leadership position in favor of joining an alliance-driven ecosystem

Intermediaries are an inherent part of value creation in open innovation. They connect organisations seeking external solutions for an innovation-related problem (seekers) with potential solution providers (solvers). To bridge between the innovation problem and external knowledge sources, intermediaries deploy different search strategies. This study compares the cost of using two prevalent approaches: direct versus delegated search. Direct search corresponds to the conventional understanding of search by screening a pre-identified set of solution providers that the intermediary has identified as potentially relevant contributors. Delegated search comprises more indirect search such as problem broadcasting or crowdsourcing. Here, the innovation problem is distributed to a large external network of potential solvers, allowing even unobvious outsiders to contribute to its solution. An empirical study of 53 open innovation intermediaries indicates that delegated search outperforms direct search in terms effectiveness. The lower overall effort for intermediation in delegated search mainly arises from decoupling the effort to coordinate the search process by shifting it towards the solution provider.

With the rise of Industry 4.0, manufacturing ecosystems are undergoing a fundamental transformation. Machinery manufacturers attempt to transition from pipeline to platform business models, hoping for new profit opportunities and establishing themselves as the new ecosystem leader. While literature suggests using openness to achieve competitive advantage, we observe firms following tight coupling strategies. This paper analyzes how firms can successfully transition their business model by employing openness. To answer this question, we conduct a longitudinal ecosystem study in the agricultural industry. We explore an incumbent machinery company trying to position itself as the ecosystem leader by establishing a platform business model. Our findings show that openness leads to risks due to interdependencies in the ecosystem. As a result, the focal company’s abilities to create network effects and to capture value from these are affected. We argue that the right configuration of control points can help to reduce or eliminate these risks. Subsequently, we show three transition journeys based on a combination of control points enabling a company to go from a pipeline to a platform business model, thereby positioning itself as the ecosystem leader.

Established organizations need to adapt their current business models (BMs) to match dynamic changes in their environment. Alternatives to the established BM usually incorporate a different logic of how value is created, offered, and captured. When selecting and implementing the best BM alternative, organizations have to make decisions on several highly uncertain questions: What will the future look like, on what basis should we take action, how do we act under risks and limited resources, and how should we behave in light of unexpected events and towards outsiders. Firms can apply the logic of causation or that of effectuation when making these decisions. In this context, we apply a longitudinal single case study of a manufacturing company encountering a digital transformation journey. In this case study, we investigate the shift from a product-based to a smart service model and the underlying process of decision-making in the context of business model innovation (BMI). From our case study, we identify latent conflicts resulting from two different BM logics: the logic of value offering, creation, and capture of the dominant (established) BM versus that of the new one. We show that logic conflicts become especially visible when actors cannot reduce uncertainty about the new BM effectively. These conflicts finally inhibit the change of the dominant BM to the new one. Sensemaking in the company about the latent logic conflicts within the BMI process reveals the need to change its decision-making logic from managerial causation to intrapreneurial effectuation. The findings from our study contribute to entrepreneurship and institutional theory while highlighting the concept of institutional intrapreneurship for BMI. Our results suggest separating the alternative BM from the existing one. This separation can reduce cognitive uncertainty associated with BMI processes through logic pluralism, i.e., building a new decision-making logic in parallel to the old one. We contribute to the BMI literature by adding logic conflicts of BMI and the decision-making logic of an organization to the list of important contingency factors that influence the execution and outcome of a BMI process.