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The study utilises unique survey data gathered from 12,427 party members. The dependent variable measures party members’ in-party commitment and is based on willingness to donate money, to contribute effort, the feeling of belonging in the party network and social trust in the party network.

In this article, we study how different extra-parliamentary online and offline activities are associated with in-party commitment amongst political party members from the six largest Finnish parties. We especially delve into the differences between members of the Finnish parties.

We found that extra-parliamentary political activity, including connective action through social media networks and collective action through civic organisations, is highly associated with members’ in-party commitment. Additionally, members of the newer identity parties more effectively utilised social media networks, whilst the traditional interest parties were still more linked to traditional forms of extra-parliamentary political action.

By employing the sociological network theory perspective, the study contributes to ongoing discussions surrounding the impact of social media on political participation amongst party members, both within and beyond the confines of political parties.

This study aims to explore what characteristics contribute to the definition of relevance in business-to-business (B2B) marketing research and how/why different strands of B2B marketing maintain or lose their relevance.

This study is conceptual. It adopts a performative-phenomenal standpoint for B2B marketing research and approaches relevance through the concept of episteme, which is considered pivotal for understanding this phenomenon.

This study proposes four axioms that define the characteristics of relevance in B2B marketing research and discusses their implications for scholars and practitioners. Consequently, an action plan for revitalizing B2B marketing research is developed, comprising learning and temporal dimensions, resulting in nine different relevance types.

The central argument put forward in this study is that different research strands of B2B marketing have deeply rooted epistemic underpinnings that influence their interpretation of relevance. Consequently, fostering dialogue between practitioners and scholars is considered necessary to sustain relevance in B2B marketing research. B2B scholars are urged to think beyond their subspecialized silos and acknowledge how the business environment and the various strands of B2B marketing congruently shape B2B marketing relevance, while also embracing research methods that bring them closer to business practice.

Marketing practitioners and academics continue to drift apart. This study puts forward three recommendations to bring marketing academics and practitioners closer together.

The study contributes to the B2B marketing literature by grappling with the theory-praxis gap and critically exploring what constitutes relevance in B2B marketing research.

This study aims to investigate how configurations of boundary objects (BOs) support innovation teams in developing innovative product concepts. Specifically, it explores the effectiveness of different artefact configurations in facilitating collaboration and bridging knowledge boundaries during the concept development process.

The research is based on data from ten undergraduate innovation teams working with an industry partner in a creative industry. Six categories of BOs are identified, which serve as tools for collaboration. The study applies fsQCA (fuzzy-set qualitative comparative analysis) to analyse the configurations employed by the teams to bridge knowledge boundaries and support the development of innovative product concepts.

The findings of the study reveal two distinct groups of configurations: product envisioning and product design. The configurations within the “product envisioning” group support the activities of visioning and pivoting, enabling teams to innovate the product concept by altering the product vision. On the other hand, the configurations within the “product design” group facilitate experimenting, modelling and prototyping, allowing teams to design the attributes of the innovative product concept while maintaining the product vision.

This research contributes to the field of innovation by providing insights into the role of BOs and their configurations in supporting innovation teams during concept development. The results suggest that configurations of “product envisioning” support bridging semantic knowledge boundaries, while configurations within “product design” bridge pragmatic knowledge boundaries. This understanding contributes to the broader field of knowledge integration and innovation in design contexts.

The build-up of large-scale COVID-19 testing required an unprecedented effort of coordination within decentralized healthcare systems around the world. The aim of the study was to elucidate the challenges of vertical policy coordination between non-political actors at the national and regional levels regarding this policy issue, using Sweden as our case.

Interviews with key actors at the national and regional levels were analyzed using an adapted version of a conceptualization by Adam et al. (2019), depicting barriers to vertical policy coordination.

Our results show that the main issues in the Swedish context were related to parallel sovereignty and a vagueness regarding responsibilities and mandates as well as complex governmental structures and that this was exacerbated by the unfamiliarity and uncertainty of the policy issue. We conclude that understanding the interaction between the comprehensiveness and complexity of the policy issue and the institutional context is crucial to achieving effective vertical policy coordination.

Many studies have focused on countries’ overall pandemic responses, but in order to improve the outcome of future pandemics, it is also important to learn from more specific response measures.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

This study aims to contribute to the field of computer systems for sustainability research. It proposes a framework for sustainability awareness using online social networks (OSNs) by analyzing major research streams of the current state of knowledge and different bibliometric variables, and identifies a future research agenda in the field.

The preferred reporting items for systematic review and meta-analysis (PRISMA) methodology, content analysis and bibliometric tools were employed to identify, select, collect, synthesize, analyze and evaluate all research published on sustainability awareness using OSNs to provide complete insight into this research area.

This study proposed a framework comprising four categories for sustainability awareness using OSNs. These four categories are: the key factors to success, analysis of existing tools, proposal of new methods, approaches and theoretical frameworks, and case examples. In addition, this study synthesized the future research challenges for each category of the proposed framework.

Fostering sustainability awareness and sustainable behavior using OSNs is a growing area of research that seeks cultural change in society to achieve sustainable development. Through OSNs, people can discover and become aware of the consequences of unsustainable practices and habits in society, and learn how to develop sustainable behavior.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR

Infrastructure forms a basis for the operations and sustainability of the modern society. This paper aims to recognize value creation from the infrastructure procurement ecosystem perspective to achieve those goals. The pursuit of enhancing value creation involves an examination of infrastructure procurement challenges, boundaries as well as boundary spanners that facilitate effective knowledge transfer and interaction.

The qualitative study is based on content analysis of 25 thematic interviews. Data was transcribed and coded via Atlas.ti software.

Infrastructure procurement value creation challenges appear complex and related to boundaries that hamper collaboration, coordination and knowledge sharing. Our results show that these boundaries locate within and between different levels of procurement ecosystem. Therefore, value creation in infrastructure procurement requires boundary spanners for leveraging knowledge sharing and interaction. Artifacts, discussion, processes and brokers as identified boundary spanners are strongly nested and interrelated in the industry. Special attention should be given to supporting individuals to act as brokers, since they play the key roles in trust building, culture steering and usage of other boundary spanners.

Promoting value creation in infrastructure procurement helps to achieve socio-economic development goals.

This study offers a unique perspective on value creation in the context of infrastructure by adopting an ecosystem lens and examining boundary crossing mechanisms. The results support future development of collaboration and knowledge sharing practices fostering procurement productivity.

Effective use of data across public health organisations (PHOs) is essential for the provision of health services. While health technology and data use in clinical practice have been investigated, interactions with data in non-clinical practice have been largely neglected. The purpose of this paper is to consider what constitutes data, and how people in non-clinical roles in a PHO interact with data in their practice.

This mixed methods study involved a qualitative exploration of how employees of a large PHO interact with data in their non-clinical work roles. A quantitative survey was administered to complement insights gained through qualitative investigation.

Organisational boundaries emerged as a defining issue in interactions with data. The results explain how data work happens through observing, spanning and shifting of boundaries. The paper identifies five key issues that shape data work in relation to boundaries. Boundary objects and processes are considered, as well as the roles of boundary spanners and shifters.

The study was conducted in a large Australian PHO, which is not completely representative of the unique contexts of similar organisations. The study has implications for research in information and organisational studies, opening fields of inquiry for further investigation.

Effective systems-wide data use can improve health service efficiencies and outcomes. There are also implications for the provision of services by other health and public sectors.

The study contributes to closing a significant research gap in understanding interactions with data in the workplace, particularly in non-clinical roles in health. Research analysis connects concepts of knowledge boundaries, boundary spanning and boundary objects with insights into information behaviours in the health workplace. Boundary processes emerge as an important concept to understand interactions with data. The result is a novel typology of interactions with data in relation to organisational boundaries.

The purpose of this action research study was to design, implement and evaluate interventions that enhanced the induction program for new teachers in a P-12 school district. At the outset, we hoped the study would provide new teacher support resulting in improved teaching practices, increased job satisfaction and/or increased teacher retention among the target population. With this in mind, our research question was: What structures and supports from a school-university partnership facilitate capacity-building among university teacher education faculty, school and district leaders, mentor teachers, and new teachers in the context of an induction program?

This study used an intervention-centered mode of action research methodology that aims to make systems-level change. This type of action research intends to solve real organizational problems with a focus on conducting “research in action” rather than “research about action” (Coghlan and Brannick, 2014, pp. 5–6). This approach necessitates that data collection and analysis are iterative processes, occurring throughout the research process, instead of solely at the end stages of the research process. Our action research process used Coghlan and Brannick’s (2014) action research cycle model. The cyclical four-step process includes constructing (verifying the problem in the local context), planning action, taking action and evaluating action. Facilitated by the interim director of a Professional development schools (PDS) partnership in the Southeastern United States, a team of co-researchers which included three university teacher education faculty and four school district administrators used action research methodology to create systemic change that enhanced the district’s induction program. We collected data through multiple qualitative methods, including surveys, focus groups, observations and interviews during the course of three action research cycles. These data and our theoretical framework (complex adaptive systems theory and social network theory) informed two major interventions that supported new teachers during the challenging first year of the coronavirus disease (COVID-19) pandemic.

The interventions and the research process were mutually beneficial for both institutions and contributed to professional learning and growth at the individual, group and system levels. The three major findings described include: (1) engaging in collaborative action research is mutually beneficial for both schools and universities; (2) induction programs benefit from university resources; (3) learning communities build all educators’ professional capacity.

Our research recommendations are: (1) more research is needed on the benefits of school-university partnerships to induction programs; (2) school-university partnerships should leverage action research to improve systems; (3) within school-university partnerships, the connection between collaborative leadership and sustainability requires further research. One limitation was that this study was conducted in a single school-university partnership context involving a large public university and a mid-sized public school district that had a well-established partnership. More induction-centered research is needed in different types of school-university partnership contexts that have varying levels of longevity and partnership structures.

Our recommendations for practice include (1) school-university partnerships should leverage collaborative learning communities to catalyze individual, group and systems-level learning and change, and (2) school-university partnerships must prioritize induction support to strengthen the teaching profession.

Since Hunt’s (2014) literature review on induction support in PDS partnerships, very few empirical studies have been conducted in this research area. This study, which examined induction support in a PDS partnership over a two-year period, makes a significant contribution to the scholarly literature on induction teacher support in school-university partnership contexts. Facilitated by the interim director of a PDS partnership, a team of co-researchers, which included three university teacher education faculty and four school district administrators, used action research methodology to create systems-level supports that enhanced the district’s induction program.

In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.