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Deployment of knowledge management systems (KMSs) suffers from low adoption in organizational reality that is attributed to a lack of perceivable added value for people in actual work situations. Poor task/technology fit in the process of knowledge retrieval appears to be a major factor influencing this issue. Existing research indicates a lack of re-contextualizing stored information provided by KMSs in a particular situation. Existing research in the area of organizational memory information systems (OMISs) has thoroughly examined and widely discussed the topic of re-contextualization. The purpose of this paper, thus, is to examine how KMS design can benefit from OMIS research on approaches for re-contextualization in knowledge retrieval.

This paper examines OMIS literature and inductively derives a categorization scheme for KMS according to their strategy of re-contextualizing knowledge. The authors have validated the scheme validated in a multiple case study that examines the differentiatory value of the scheme for approaches with various re-contextualization strategies.

The classification scheme allows a step-by-step selection of approaches for re-contextualization of information in KMS design and development derived from OMIS research. The case study has demonstrated the applicability of the developed scheme and shows that the differentiation criteria can be applied unambiguously.

Because of the chosen case study approach for validation, the validation results may lack generalizability.

The scheme enables an informed selection of KMSs appropriate for a particular OMIS use case, as the scheme’s attributes serve as design rationale for a certain architecture or constellation of components. Developers can not only select from various approaches when designing re-contextualizaton but also come up with rationales for each candidate because of structured representation. Hence, stakeholders can be supported in a more informed way and design KMSs more effectively along organizational change processes.

The paper addresses an identified need for systematic characterization of KMS approaches and systems intending to meet the objectives of OMISs. As such, it allows streamlining further research in this field, as approaches can be judged according to their originality and positioned relative to each other.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

This chapter focuses on the micro-contexts of cross-innovation between digital audiovisual media and the health care sector by examining two cases, both start-ups working on virtual reality-assisted rehabilitation solutions. Through a discussion of the two cases, this chapter aims to elucidate the broader dynamics of digital health care as experienced by innovators seeking to contribute to it. It addresses the challenges faced by innovators, including the lengthy and costly nature of medical licensing, the inflexibility and fragmentation of pertinent regulations, and health care institutions’ and insurers’ resistance to change. It also highlights the importance of networking and the emergence of digital health care as a distinct and increasingly visible epistemic community, while touching upon the tensions between the public and the private sectors as a target market for innovators.

To ensure that more people will benefit from integrated care initiatives, scaling-up of successful initiatives is the way forward. However, new challenges present themselves as knowledge on how to achieve successful large-scale implementation is scarce. The EU-funded project SCIROCCO uses a step-based scaling-up strategy to explore what to scale-up, and how to scale-up integrated care initiatives by matching the complementary strengths and weaknesses of five European regions involved in integrated care. The purpose of this paper is to describe a multi-method evaluation protocol designed to understand what factors influence the implementation of the SCIROCCO strategy to support the scaling-up of integrated care.

The first part of the protocol focuses on the assessment of the implementation fidelity of the SCIROCCO step-based strategy. The objective is to gain insight in whether the step-based strategy is implemented as it was designed to explore what works and does not work when implementing the scaling-up strategy. The second part concerns a realist evaluation to examine what it is about the SCIROCCO’s strategy that works for whom, why, how and in which circumstances when scaling-up integrated care.

The intended study will provide valuable information on the implementation of the scaling-up strategy which will help to explain for what specific reasons the implementation succeeds and will facilitate further improvement of project outcomes.

The expected insights could be useful to guide the development, implementation and evaluation of future scaling-up strategies to advance the change towards more sustainable health and care systems.

The purpose of this paper is to analyse how different strategic goals of (micro-, small- and medium-sized firms=SMEs) relate to the business model innovation (BMI) paths that SMEs take when improving their business.

The authors conducted 11 in-depth case studies involving SMEs innovating their business models (BMs).

The authors found evidence that strategic goals of SMEs (start new business, growth and profitability) lead them to alternative innovation path in terms of BM components affected. Growth seekers start from the right-hand side of a BM Canvas, while profitability seekers start from the back end, the left side of a Canvas; and new businesses adopt a cyclical approach considering BM components in turn, while at the same time redesigning and testing the BM. The findings of this study also indicate that all three paths gradually lead to improvement in several BM components.

Findings indicate that a strategic management view in which strategic goals define BMI also applies to SMEs. The distinctive BMI paths that the authors identified provide evidence to suggest that, although the SMEs may not have an explicitly formulated strategy, their strategic goals determine the type of improvements they make to their BM. All three SME groups started their improvements from different BM components and changed several elements in their BMs in a specific order, forming distinctive BMI paths. Finally, to understand the BMI in SMEs better, more research is needed into BMI processes and into the way BMI is managed in SMEs.

The findings of this study help SMEs to anticipate the next steps in their path towards an improved BM. By mirroring their approach to the BMI paths, they can better manage their BM makeover process and focus on their innovation activities. For providers of BMI tools and methods, the study indicates which SME innovation tasks could be supported by tools and how the tools should be aligned with the BMI paths.

BMI is attracting growing attention in both research and practice. However, knowledge concerning BMI in SMEs is limited. The authors contributed to BMI research by focussing on the BMI paths of SMEs, i.e. the often sequential, non-linear and iterative steps taken to improve the business by making changes to specific BM components.