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The purpose of this study is to examine learning and employee-driven innovation (EDI) in the public sector, with a particular focus on the interplay between employee engagement and organisational conditions.

The material consists of qualitative interviews with 23 participants from three municipal sites of innovation support that participated in a national programme aiming to strengthen municipalities’ innovation work.

The study found numerous constraining organisational conditions resulting in consequential loss of employee engagement for EDI. The conclusion drawn is that employee engagement and enabling organisational conditions are central to EDI in public sector workplaces, and that incorporating EDI into municipal daily operations requires paying attention to the interplay between organisational conditions and employee engagement.

This paper provides important guidance for supporting EDI in the public sector. Implementing EDI into operations requires employee engagement to be successful. However, employees’ engagement should not be overlooked or taken for granted. A practical implication of this study is that EDI in the workplace must be encouraged by creating a learning environment that supports innovative learning in the workplace. In practice, measures should be taken to support employee engagement by creating organisational conditions that provide a more expansive learning environment to ensure the continuity and perpetuation of EDI in public sector organisations.

Technological innovation and the flexibilisation of labour markets have expanded the pool of workers engaged in globally distributed work. This paper aims to propose an analytical framework to understand and support the productive professional learning of those engaged in global work. Drawing on the theory of expansive learning in the cultural-historical activity theory tradition the study aims to stimulate and enrich the conceptual notion of work as a learning space in the discussion of workplace learning particularly in global work.

Iteration between theory and data is applied to identify the dimensions of expansion for the configuration of learning spaces in global work. Data are drawn from the experiences of 10 professionals selected by purposive sampling in Austria, Italy, the Netherlands and Singapore.

Six dimensions of expansion are identified as challenging and potentially empowering for professionals’ configuration of learning spaces in global work: social-spatial, material-instrumental, moral-ethical, political-economic, personal-professional and temporal-developmental.

The conceptual framework for the dimensions of expansion of learning spaces provides the broad strokes for reflexive curricula that democratise the learning and development of professionals in global work, who are currently underserved given the national orientation of vocational education and training and professional development ecosystems.

Local Safeguarding Adults Board (SAB) policies, procedures, guidance and related documents on self-neglect were gathered and analysed, to map what approaches are being taken across England. This paper aims to identify areas of divergence to highlight innovations or challenges faced by SABs.

Self-neglect documents were identified by searching SAB websites. Data were extracted into a framework enabling synthesis and comparison between documents.

This paper reports on how English SAB documentation defines self-neglect, treats executive capacity, lays out pathways for self-neglect cases, advises on refusal of service input and multi-agency coordination and draws on theories or tools. Greater coherence in understanding self-neglect has developed since it was brought within safeguarding in 2014; however, variation remains regarding scope, referral pathways and threshold criteria.

This review was limited to published SAB documentation at one point in time and could not consider either the wider context of safeguarding guidance and training or implementation in practice.

This review provides an overview of how SABs are interpreting national guidance and guiding practitioners. The trends and areas of uncertainty identified offer a resource for informed research and policy-making.

To the best of the author’s knowledge, this is the first systematic survey of SAB self-neglect policies, procedures and guidance since self-neglect was included under safeguarding.

The academic library’s physical capacity and its service obligations to local users structured the traditional print collection. Largely freed of these constraints, the digital collection manager enjoys unprecedented freedoms but now contends with a collection susceptible to resource sprawl and scope ambiguity. This exploratory study aims to consider the possibility that intra-field social processes help to structure and routinize digital collection practice.

Lacking the constraints to which print collections are subject, electronic resource and digital library collections are more likely to reflect idiosyncratic institutional interests and therefore, to demonstrate significant variation. Evidence of homogeneity may suggest the influence of heretofore underexplored social structures. To determine the extent of such homogeneity, the author performed exploratory/descriptive content analyses on ten electronic resource collection development policies and six digital library collection development policies.

The data reveal among both the electronic resource and digital library collection policies significant uniformity. Content analyses demonstrate consistent themes (e.g. media, audience, selection priorities, etc.) and rhetoric. These findings lend support to the study’s central hypothesis regarding latent social structures. Analyses also reveal a set of unanticipated constraints unique to digital collection management.

Despite the breadth and maturity of literature addressing the Digital Turn in academic librarianship, relatively little attention has been paid to the social dimensions of collection management. This work represents an important corrective and suggests new theoretical approaches to the study of digital collection practice.

Organisations have over time adopted conservative, structured and controlled processes to manage and achieve goals set with their stakeholders. Contrary to that, an environment of disruption has emerged, that being a faster, less predictable and less certain environment than the previous fifty or more years. This environmental difference has emerged due to the interconnectivity of trade formed out of globalisation, technology, internet and social media. The historical organisational decision models and structures are perhaps too slow and conservative for a faster less certain new age. Whilst pandemic was considered but one disruption to consider for the new age, more guidance is required for those leading and managing organisations through the current specific Covid-19 pandemic, into the pending recovery and beyond.

Whilst wide-scale jobs may be lost in this new future, new opportunities for entrepreneurs, creativity and skills will likely emerge. This article will research how disruption, pandemic in particular, is changing leadership and management practices. Additionally, this article recognises that many of the organisational structures and processes of today were originally designed over thirty to forty years ago, so may no longer be appropriate. The design aspects or organisations, decision models and dealing with stakeholders will likely need to change in a pandemic, so this paper will recommend new and modified ways for organisations to operate. This research will offer a theoretical solution to assist management and leaders adjust their business and decision models in a pandemic. The past operating organisational models may lack the creativity and flexibility necessary for a world that has locked down, works from home or have closed without notice at once. Leading and managing is so different in a pandemic, especially when so much has changed so quickly, so this article will contribute by recommending new organisational principles to work to.

Health risks associated with coronavirus disease 2019 (COVID-19) have severely affected the financial stability of airline companies globally. Recapturing financial stability following this crisis depends heavily on these companies’ ability to attain efficient and productive operations. This study uses several empirical approaches to examine key factors contributing to carriers sustaining high productivity prior to, during and after a major recession. Findings suggest, regardless of economic conditions, that social distancing which requires airline companies in the Asia Pacific region to fly with a significant percentage of unfilled seats weakens the performance of those companies. Furthermore, efficient operations do not guarantee the avoidance of productivity declines, especially during a recession.

There is abundant literature analyzing the determinants of banks’ profitability through its main component: the net interest margin. Some of these determinants are suggested by seminal theoretical models and subsequent expansions. Others are ad-hoc selections. Up to now, there are no studies assessing these models from a Bayesian model uncertainty perspective. This paper aims to analyze this issue for the EU-15 countries for the period 2008-2014, which mainly corresponds to the Great Recession years.

It follows a Bayesian variable selection approach to analyze, in a first step, which variables of those suggested by the literature are actually good predictors of banks’ net interest margin. In a second step, using a model selection approach, the authors select the model with the best fit. Finally, the paper provides inference and quantifies the economic impact of the variables selected as good candidates.

The results widely support the validity of the determinants proposed by the seminal models, with only minor discrepancies, reinforcing their capacity to explain net interest margin disparities also during the recent period of restructuring of the banking industry.

The paper is, to the best of the knowledge, the first one following a Bayesian variable selection approach in this field of the literature.

The purpose of this paper is to summarise and reflect upon key issues at the interface of prices, information and regulation with a focus upon the stock market in context. Reflecting upon academic research in the area of efficient markets, and regulatory policy, the concern is to discern issues in terms of policy and support for policy. What does the research imply for policy? Is it possible that the research, perhaps given its rhetoric, can be misinterpreted in relation to policy? The study is also concerned to develop avenues for future research based on these considerations.

The paper is an analytical and critical review and writing.

The reading of the research suggests a pragmatic regulatory policy that should be concerned to improve stock market functioning, including with respect to information, as well as the context of which this is part. At the same time, the literature may be read as promoting anti-regulatory policy.

On the one hand, these are consistent with the pragmatic policy referred to above. On the other hand, further research is suggested to explore substantively the rhetoric of the research and its interpretation and to explore understandings of the research and its implications amongst key constituencies in practice.

The concern is to bring key insights from the academic literature together with a view to promoting a pragmatic policy orientation, while cautioning in a critical perspective about how this academic literature and research might be interpreted from a policy perspective.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.