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The aim of this chapter is to provide an overview of the student mental health crisis in Higher Education (HE), and how resilience and grit, two important positive psychological constructs, can be beneficial for university students’ success and wellbeing. As part of a discussion around some of the current approaches to intervening in wellbeing in universities, the chapter provides evidence for the use of PPIs for wellbeing in university students, alongside some of the challenges of implementing these in HE. It also provides an overview of the Thriving Students Framework and presents a case for a multicomponent approach to monitoring and improving educational success. In particular, a wellbeing framework that, alongside resilience, also recognises the importance of strengths, persistence in the face of difficulty, a growth mindset, self-control and mental wellbeing; Academic Tenacity. The implications of utilising this framework for educational attainment in university students are discussed. The Bolton Uni-Stride Scale (BUSS), a single short measure of academic tenacity that combines the attributes enabling measurement and intervention to support university students to thrive, is also presented for educators to use.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

Competitiveness is an important personality trait that has been studied in various disciplines and has been shown to predict critical work outcomes at the individual level. Despite this, the role of competitiveness in groups and teams has received scant attention amongst organizational researchers. Aiming to promote future research on the role of competitiveness as both an adaptive and maladaptive trait – particularly in the context of work – the authors review competitiveness and its effects on individual and team stress and Well-Being, giving special attention to the processes of cohesion and conflict and situational moderators. The authors illustrate a dynamic multilevel model of individual and team difference factors, competitive processes, and individual and team outcomes to highlight competitiveness as a consequential occupational stressor. Furthermore, the authors discuss the feedback loops that inform the different factors, highlight important avenues for future research, and offer practical solutions for managers to reduce unhealthy competition.

The chapter identifies the COVID-19 pandemic as not just a public health crisis but also an information crisis. The authors argue that a deeper understanding of the role of culture in information practices is critical for the future of research and theoretical development around humanity’s relationship to information (i.e., why information is or is not created, represented, avoided, sought, retrieved, used, shared, or hidden). This chapter highlights the Black Feminist Information Community (BFIC) framework, especially the voice and information aspect of the model in the context of community justice.

At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.

This paper considers how knowledge has been organized about museum objects and belongings at the Museum of Anthropology, in what is now known as British Columbia, and proposes the concept of historical or provenance warrant to understand how cataloguing decisions were made and are limited by current museum systems.

Through interviews and archival research, we trace how cataloguing was done at the museum through time and some of the challenges imposed by historical documentation systems.

Reading from the first attempts at standardizing object nomenclatures in the journals of private collectors to the contemporary practices associated with object documentation in the digital age, we posit that historic or provenance warrant is crafted through donor attribution or association, object naming, the concept of geo-cultural location and the imposition of unique identifiers, numbers and direct labels that physically mark belongings.

The ultimate goal and contribution of this research is to understand and describe the systems that structure and organize knowledge, in an effort to repair the history and terminologies moving forward.

Job performance literature has evolved to address the aspects of performance thinking where knowledge sharing (KS) and emotions on the job are considered important. This study evaluates the influence of emotional intelligence (EI), mediated through KS, on job outcomes measured as job performance (JP) and job satisfaction (JS).

Structural equation modeling methods are used to investigate the degree of influence of EI on job outcomes through KS. The data for analysis has been collected from 227 project managers at Information Technology-Information Technology Enabled Services (IT-ITeS) firms.

The findings suggest that the EI has a positive and significant effect on KS. This implies that employees with high EI scores are more involved in the KS behavior. Furthermore, the findings suggest that KS partially mediates the relationship between EI and JP, and it fully mediates the relationship between EI and JS.

For KS, the answer lies in the recruitment and retention of emotionally intelligent persons rather than investing only in information technology. The study enhances the literature on knowledge management, sharing and EI.

The proposed research model suggests a successful infusion of KS within IT-ITeS firms. Knowing the EI of employees and, accordingly, changing their behavior towards sharing knowledge is probably a distinctive, most efficacious and essential strategy for augmenting job outcomes.

The study establishes the role of KS in translating the impact of EI on JP and JS. Furthermore, it contributes a novel framework of KS behavior.

Synthetic biology begins with the underlying assumption that life and life forms can be divided into parts and reassembled or redesigned according to the whims of their creators. Therefore, synthetic biology needs to be at the centre of ethical thinking since it engages the very concept of life and radically changes it. In this paper, we will investigate the phenomenon of synthetic biology through an ethical analysis of the unfulfilled promises and potential perils surrounding this technology. The paper consists of four parts. In the first part, we will deal with the problem of defining synthetic biology since it is a field in which many scientific disciplines meet and intertwine. The second part will present a brief history of systemic biology and the groundbreaking creation of Synthia, the first synthetic organism. The third part focuses on synthetic biology's potential benefits and some prominent ethical issues. In the fourth part, we will point out the problem of synthetic biology regulation. In conclusion, we will highlight the essential ethical remarks on synthetic biology and provide the impetus for further ethical debate.

The globalisation of markets, emerging concepts of sustainable development, and circular economy have defined the boundaries within which organisations must compete and address the needs of key stakeholders. As circumstances change, boundaries are often replaced by the relationships between companies and the communities they serve. Consequently, strategy has become a central aspect of sustainable leadership and the foundation for implementing strategic management in a dynamic system of relationships. Every company is born and grows within social and economic ecosystems. Drawing on the metaphor of biology, ecosystems are described as dynamic interconnections among various elements that influence and foster entrepreneurship. Interconnections between players (such as marketplaces, organisations, governments, and universities) create a flow of expertise, abilities, knowledge, experience, and tangible resources. Economic and social ecosystems involve various actors and components that continuously coexist and interact, leading to the creation of numerous mutual relationships. Consequently, it is crucial for managers to gain a comprehensive understanding of the internal and external environments. Various decision-making tools and strategies can be used to achieve this goal. These tools were developed to assist managers, researchers, and consultants in making informed decisions under complex scenarios. This chapter presents several decision-making strategies and tools, including the Boston Consulting Group (BCG) matrix, General Electric (GE) matrix, Balanced Scorecard (BSC), PEST, PESTEL analysis, and SWOT analysis.