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Crisis services personnel are frequently deployed around the globe under highly demanding conditions. This raises the need to better understand the deployment process and more especially, sustainable reintegration after deployment. Despite recent research efforts, the study of the post-deployment stage, more specifically the reintegration process, remains fragmented and limited. To address these limitations, this review aims at (1) describing how reintegration is conceptualised and measured in the existing literature, (2) identifying what dimensions are associated with the reintegration process and (3) identifying what we know about the process of reintegration in terms of timing and phases.

Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol, the authors identified 5,859 documents across several scientific databases published between 1995 and 2021. Based on predefined eligibility criteria, 104 documents were yielded.

Research has primarily focused on descriptive studies of negative individual and interpersonal outcomes after deployment. However, this review indicates that reintegration is dynamic, multi-sector, multidimensional and dual. Each of its phases and dimensions is associated with distinct challenges.

To the authors’ knowledge, this is the first research that investigates reintegration among different crisis services and provides an integrative social-ecological framework that identifies the different dimensions and challenges of this process.

The majority of business-to-business companies are working on their digital transformation in sales. Despite enormous transformation efforts, the expected productivity gains are often missing in most companies. Based on empirical research, this paper aims to develop a new market-oriented transformation model. Management implications as well as future research directions are derived for a more focused digital transformation process in sales.

Within the exploratory research study, 90 key informants were interviewed to provide better insights in the context of digital transformation in sales. The accuracy of the research results was safeguarded by triangulation.

As this research paper will show, the reasons for the missing productivity gains caused by a limited knowledge about the main success factors of digital transformation as well as a lack of understanding of digital transformation as an evolving process.

Based on the empirical research, a new market-oriented transformation model is developed and management implications as well as future research directions are derived for a more focused digital transformation process in sales.

This paper aims to provide readers with a comprehensive overview of the current state of the millennial literature, highlighting the significance and challenges of millennial professionals, their reported high turnover and the various recommendations designed to engage and retain them.

An integrated review approach was applied to synthesise contemporary peer-reviewed articles, supplemented by legacy and grey literature and relevant book chapters, to comprehensively explore and construct a cohesive overview of the current research on the millennial workforce.

Within the wealth of available information, examining the various studies on millennial turnover reveals diverse theories, evidence and opportunities for advancement, underscoring the necessity for more robust empirical studies. The investigation identified three overarching retention strategy themes: (1) intergenerational conflict management, (2) workplace adaptations and (3) solutions rooted in a protean career orientation. In alignment with protean career concepts, coaching shows promise as an underexplored option.

This article holds practical significance by offering researchers a comprehensive and cohesive overview of the millennial literature. Additionally, it gives organisations a novel perspective on the crucial role coaching can play in engaging and retaining millennial employees.

The increased focus on retaining millennial workers in recent decades has spurred a proliferation of articles and books on this subject. However, this body of research remains fragmented, lacking an overview that provides a clear picture of its current state. This review aims to bridge this gap.

Within the growing study of transnational entrepreneurial practice, existing conceptualisation of diaspora entrepreneurship has often lacked engagement with the particularities of the diaspora condition. This paper seeks to advance theoretical understanding and empirical study of diaspora entrepreneurship through identifying the processes that generate diaspora entrepreneurship across economic, social and political spheres.

To analyse the relationship between the development of venture activity and diaspora (re)production, in depth, qualitative biographical analysis was undertaken with UK-based diaspora entrepreneurs embedded within the particular contexts of the Sri Lankan Tamil and Kurdish diasporas. Skilled and active diaspora entrepreneurs were purposively selected from these extreme case contexts to explore their entrepreneurial agency within and across the business, social and political realms.

Results identified key dimensions shaping the development of diaspora entrepreneurship. These comprised the role of diaspora context in shaping opportunity frameworks and the mobilisation of available resources, and how venture activity served to sustain collective diaspora identity and address diaspora interests. These findings are used to produce an analytical model of the generation of diaspora entrepreneurship to serve as a basis for discussing how heterogeneous and hybrid entrepreneurial strategies emerge from and shape the evolving diaspora context.

By placing the reproduction of social collectivity centre-stage, this paper identifies the particularities of diaspora entrepreneurship as a form of transnational entrepreneurship. This recognizes the significance of a contextualised understanding of entrepreneurial diversity within wider processes of diaspora development, which has important implications for policy and practice development in homeland and settlement areas.

Background: Evidence from a range of major public health incidents shows that neighbour-based action can have a critical role in emergency response, assistance and recovery. However, there is little research to date on neighbour-based action during the 2020 coronavirus pandemic. This article reports on a survey of people engaged in supporting their neighbours in weeks three and four of the UK COVID-19 lockdown.

Methods: Members of area-based and community of interest COVID-19 support groups in the Bristol conurbation were invited to complete an online survey. Of 1,255 people who clicked on the survey link, 862 responded; of these, 539 responses were eligible for analysis.

Results: Respondents reported providing a wide range of support that went beyond health information, food and medical prescription assistance, to include raising morale through humour, creativity and acts of kindness and solidarity. A substantial proportion felt that they had become more involved in neighbourhood life following the lockdown and had an interest in becoming more involved in future. Neighbour support spanned all adult age groups, including older people categorised as being at-risk to the virus. With respect to most measures, there were no differences in the characteristics of support between respondents in areas of higher and lower deprivation. However, respondents from more deprived areas were more likely to state that they were involved in supporting certain vulnerable groups.

Conclusions: As with previous research on major social upheavals, our findings suggest that responses to the viral pandemic and associated social restrictions may increase existing social and health inequalities, and further research should explore this issue in more depth.

The purpose of this study is to better understand technology adoption and working from home (WFH) behaviour of micro and small enterprises (MSE) with 4 to 49 employees during the first (2020) and second (2021) COVID-19 lockdowns in Switzerland.

This study uses two data sets gathered using computer-assisted telephone interviewing surveys conducted with 503 managing directors of Swiss MSEs after the first and 506 MDs after the second COVID-19 lockdown period.

The study revealed that during the COVID-19 pandemic, WFH arrangements are related to the adoption of technology by Swiss industry groups. Furthermore, industry characteristics and technology adoption strategies are also associated with the long-term prospect of WFH. The overall result confirms the predominant role of technology pioneers.

The study focuses on MSEs in Switzerland during a specific period. The data set includes mainly quantitative data. Future studies could investigate larger enterprises in international contexts, integrating employees’ viewpoints founded on long-term gathered qualitative data. The implications of this study include predictions about future WFH behaviour in Swiss MSEs.

To the best of the authors’ knowledge, this is the first study collecting data in Swiss MSEs after the two COVID-19 lockdowns in 2020 and 2021. As a result, this study offers a unique perspective on a specific business segment, which accounts for around 70% of global employment.

With the advancement of novel forms of text mining techniques, new possibilities have opened up to conduct large-scale content analysis of educational research from an international and comparative perspective. Since educational research tends to convey great variation based on country-specific circumstances it constitutes a good testbed for context-rich depictions of the knowledge formation within a given research field.

In this article, the authors compare the educational research that has been produced by scholars in Singapore and Sweden. The article begins by providing a rich overview of what has characterised the formation and institutionalization of educational research in public policy. After this background they map the knowledge formation of education by means of a comparative bibliometric approach using words from abstracts, titles and keywords published in 9017 peer-reviewed articles between 2000 and 2020. First, the authors describe the dominant topics in each country using topic modelling techniques. Secondly, the authors identify the most distinguishing discourses when comparing the two countries.

The findings illustrate two ideal-types for conducting educational research: Singapore being more centralised, practically-oriented, quantitative and uncritical, whereas Sweden is decentralised, pluralistic, qualitative and critical in orientation. After having mapped out the prevailing topics among researchers working in these locations, the authors connect these findings to larger debates on rivalling knowledge traditions in educational scholarship, the role of the state and the degree of autonomy within higher education.

Through large scale text mining techniques, researchers have begun to explore the semantic composition of various research fields such as higher education research, research on lifelong learning, or social science studies. However, the bibliometric method has also been criticised for creating “mega-national comparisons” that suffer from a lack of understanding of the national ramifications of various research pursuits. The authors’ study addresses these shortcomings and provides a rich depiction of educational research in Singapore and Sweden. It zooms in on the relationship between each country's institutional histories, research priorities and semantic output.

This paper aims to improve the delimitation of plant growth stages in the context of weather index insurance design. We propose a data-driven phase division that minimizes estimation errors in the weather-yield relationship and investigate whether it can substitute an expert-based determination of plant growth phases. We combine this procedure with various statistical and machine learning estimation methods and compare their performance.

Using the example of winter barley, we divide the complete growth cycle into four sub-phases based on phenology reports and expert instructions and evaluate all combinations of start and end points of the various growth stages by their estimation errors of the respective yield models. Some of the most commonly used statistical and machine learning methods are employed to model the weather-yield relationship with each selected method we applied.

Our results confirm that the fit of crop-yield models can be improved by disaggregation of the vegetation period. Moreover, we find that the data-driven approach leads to similar division points as the expert-based approach. Regarding the statistical model, in terms of yield model prediction accuracy, Support Vector Machine ranks first and Polynomial Regression last; however, the performance across different methods exhibits only minor differences.

This research addresses the challenge of separating plant growth stages when phenology information is unavailable. Moreover, it evaluates the performance of statistical and machine learning methods in the context of crop yield prediction. The suggested phase-division in conjunction with advanced statistical methods offers promising avenues for improving weather index insurance design.