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This paper aims to build on Part 1 which generated a theory representing the experiences of charity peer leaders facilitating well-being interventions (Burns, 2024). This study (Part 2) examines the process of peers [1] becoming peer leaders using the generated theory.

Following the Medical Research Council Process Evaluation Framework (Moore et al, 2015), the methods for this study were as follows: discussion and informal questions with all project staff (skilled group facilitators and peer leaders) at the start of the Refugee projectx; in-depth, self-report questionnaire with the skilled group facilitators; researcher observations of the peer leaders learning to lead and leading the groups; and group interview with peer leaders.

When analysed in line with the theory, the data showed the following: being empathic and validating someone’s story helps the person feel like their journey counts and is of worth; the “dance” of rapport and relationship is a vital ingredient for a successful group; the process of sharing stories and giving hope bring rewards; hope can be gained, given and given again without diminishing hope within the giver.

The theory that emerged in this study is unique to Part 1 and therefore Part 2 is also original, to the best of the author’s knowledge. The demonstration of the use of the theory in practise could support mental health peer work in offsetting statutory health-care costs.

Drawing on the time compression diseconomies perspective and business network theory, this study examines how the international expansion of a business group’s pace, scope and rhythm affects its performance.

Panel data (1999–2013) from the top 100 Taiwanese business groups investing in globalization were collected.

The results show that international pace and rhythm have an inverse U-shaped relationship with business group performance, while the relationship between international scope and business group performance is U-shaped. This study highlights that international expansion is multidimensional and nonlinear and that the factors that shape nonlinear relationships between international processes and performance are different. Furthermore, family group involvement positively moderates the link between international scope and performance and negatively affects the relationship between international pace and performance. However, no significant effect is observed between rhythm and performance. High family business group involvement mitigates the impact of outsiders’ liability and managerial costs; moreover, it enhances the positive effects of location-specific advantages and business network resources.

This study combined the time compression diseconomies perspective and business network theory to explain why and how internationalization may not always lead to good performance by examining the effects of different international expansion processes and the interactive effect of family group involvement.

The authors are developing a model for rural science teacher professional development, building teacher expertise and collaboration and creating high-quality science lessons: technology-mediated lesson study (TMLS).

TMLS provided the means for geographically distributed teachers to collaborate, develop, implement and improve lessons. TMLS uses technology to capture lesson implementation and collaborate on lesson iterations.

This paper describes the seven steps of the TMLS process with examples, showing how teachers develop their content and pedagogical knowledge while building relationships.

The TMLS approach provides an innovative option for teachers to collaborate across distances and form strong, lasting relationships with others.

Mentalization-based treatment (MBT) is a psychotherapeutic approach that aims to increase mentalizing capacity. The purpose of this meta-ethnography was to synthesize the available qualitative literature on MBT to allow for a more thorough understanding of the lived experience of those who have undergone this therapy.

A systematic search of seven databases was carried out. The Critical Appraisal Skills Programme was used to appraise the papers suitable for inclusion. The data were synthesized using a meta-ethnographic approach in which the second-order constructs from each paper were translated and reinterpreted creating a line of argument synthesis.

A total of 11 studies were included in the meta-ethnography. Three overarching themes were identified within the included papers which outlined that participant experience of MBT consisted of three different developmental stages. Navigating the therapeutic process describes the participant’s experience of the therapeutic process of MBT. The processes of change in MBT outlined participant reports of mechanisms of change experienced in MBT. Mentalizing self and others described the experience of generalizing new knowledge and skills to the world outside of therapy and unveiled the impact that engaging in MBT had on participants.

This meta-ethnography offers new insights into how clients experience MBT as a therapeutic process and offers suggestions for implementation in clinical practice as well as areas of focus for research of this therapeutic approach.

This paper primarily aims to identify the multilevel learning processes emerging from abrupt telework implementation in a public knowledge-intensive organization (KIO) amid the COVID-19 crisis.

This single-case process research was guided by interpretivist epistemology. Empirical data from documentary research and 41 interviewed managers were processed by inductive qualitative analysis using the multilevel learning theoretical model.

Eight types and three modes of learning processes during the COVID-19 pandemic were identified in a public KIO, iteratively emerging in multilevel learning dynamics during the compulsory adoption of telework and replacing the face-to-face work mode conducted since its foundation.

As insider researchers, while daily and privileged access to the field was obtained, it also demanded their continuous effort to maintain transparency and scientific distancing; conceptual results are restricted to process theorisation studies, specifically the 4Is theoretical model in the scope of crisis learning process studies concerning KIOs.

This study provides evidence for managers to adopt interactive dynamics among eight multilevel types and three learning modes of emergent learning, developed during the COVID-19 pandemic, and support learning practices’ implementation and routinisation across three organizational levels in crisis situations. In addition, evidencing emergent types of learning enables organizational learning (OL) researchers to examine how organizational structures and work practices either promote or inhibit different learning types and impact multilevel learning when adopting teleworking during a crisis.

This research has theoretical value in two ways: (i) Providing empirically supported knowledge: This involves understanding multilevel learning processes resulting from emergent learning in a public KIO that abruptly adopted teleworking during a crisis context; (ii) deepening process theorization studies on OL: To achieve this, we enhance the 4I model by incorporating eight types and two modes of learning processes. These processes iteratively emerge from the individual and group levels towards the institutional level in a public KIO.

The purpose of this paper is to demonstrate the efficacy of machine learning (ML) in managing natural language processing tasks, specifically by developing two ML models to systematically classify a substantial number of food waste interventions.

A literature review was undertaken to gather global food waste interventions. Subsequently, two ML models were designed and trained to classify these interventions into predefined supply chain-related groups and intervention types. To demonstrate the use of the models, a meta-analysis was performed to uncover patterns amongst the interventions.

The performance of the two classification models underscores the capabilities of ML in natural language processing, significantly enhancing the efficiency of text classification. This facilitated the rapid and effective classification of a large dataset consisting of 2,469 food waste interventions into six distinct types and assigning them to seven involved supply chain stakeholder groups. The meta-analysis reveals the most dominant intervention types and the strategies most widely adopted: 672 interventions are related to “Process and Operations Optimisation”, 457 to “Awareness and Behaviour Interventions” and 403 to “Technological and Engineering Solutions”. Prominent stakeholder groups, including “Processing and Manufacturing”, “Retail” “Government and Local Authorities” and “NGOs, Charitable Organisations and Research and Advocacy Groups”, are actively involved in over a thousand interventions each.

This study bridges a notable gap in food waste intervention research, a domain previously characterised by fragmentation and incomprehensive classification of the full range of interventions along the whole food supply chain. To the best of the authors’ knowledge, this is the first study to systematically classify a broad spectrum of food waste interventions while demonstrating ML capabilities. The study provides a clear, systematic framework for interventions to reduce food waste, offering valuable insight for practitioners in the food system, policymakers and consumers. Additionally, it lays the foundation for future in-depth research in the food waste reduction domain.

While corporate social responsibility (CSR) has been gaining support for the role it plays in employee outcomes, such as organizational identification (OID), the view of CSR from a social identity perspective is underdeveloped. This conceptual chapter explores the role of social identity processes grounded in organizational justice to develop a model of CSR attributions and the moderating role these attributions play in organizational member outcomes. CSR is understood as the relational processes happening with stakeholders, and these relationships engage specific organizational identity orientations. The social identity process flows from there, resulting in CSR attributions including strategic, relational, and virtuous. Using social identity, organizational identity, and organizational justice, this chapter makes two specific contributions: a CSR attribution typology grounded in organizational justice and the moderating impact of these attributions between activated justice dimensions and resulting organizational member outcomes.

This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the D_Div index, for this purpose.

The D_Div index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis.

The sensitivity analysis demonstrated the D_Div index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the D_Div index reached the highest prediction accuracy of 0.8. Furthermore, the D_Div index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation.

This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.

Experts may adjust their assessments through communication and mutual influence, and this dynamic evolution relies on the spread of internal trust relationships. Due to differences in educational backgrounds and knowledge experiences, trust relationships among experts are often incomplete. To address such issues and reduce decision biases, this paper proposes a probabilistic linguistic multi-attribute group decision consensus model based on an incomplete social trust network (InSTN).

In this paper, we first define the new trust propagation operators based on the operations of Probability Language Term Set (PLTS) with algebraic t-conorm and t-norm, which are combined with trust aggregation operators to estimate InSTN. The adjustment coefficients are then determined through trust relations to quantify their impact on expert evaluation. Finally, the particle swarm algorithm (PSO) is used to optimize the expert evaluation to meet the consensus threshold.

This study demonstrates the feasibility of the method through the selection of treatment plans for complex cases. The proposed consensus model exhibits greater robustness and effectiveness compared to traditional methods, mainly due to the effective regulation of trust relations in the decision-making process, which reduces decision bias and inconsistencies.

This paper introduces a novel probabilistic linguistic multi-attribute swarm decision consensus model based on an InSTN. It proposes a redefined trust propagation and aggregation approach to estimate the InSTN. Moreover, the computational efficiency and decision consensus accuracy of the proposed model are enhanced by using PSO optimization.

Even though the idea of citizen participation in tourism planning and policy-making is anything but new (Keogh, 1990; Murphy, 1985) its implementation becomes increasingly important as citizens play a key role for a socially sustainable tourism development (Bramwell & Lane, 2011; Moscardo, 2011; Papachristou & Rosas-Casals, 2019; Spil et al., 2017). Nonetheless, despite the consensus on the importance and urgency, the plethora of collaborative concepts has hardly been translated into reality. In this chapter, it will be questioned why citizen involvement in tourism policy is such a wicked problem. Further, the issue will be framed with the 10 characteristics of wicked problems by Rittel and Webber (1973) as well as Head’s (2022) governmental responses to wicked problems. Based on empirical data of two urban case studies, namely Munich (Germany) and Copenhagen (Denmark), citizens’ perspectives on their role in tourism have been disclosed to expand the past debate. Contrasting empirical findings and the outlined theoretical frame, various solution approaches could be identified from the so far neglected perspective of those at the heart of the wicked problem – the destination citizens.