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This paper aims to assess the design of national-level flexible work arrangement (FWA) policies, evaluating their potential to serve as an effective resource for employees to work flexibly depending on how they set the stage for flexibility claims that will be subject to industrial and workplace dynamics.

Using a capability approach, the authors conceptualize and operationalize two aspects of FWA policy design, namely accessibility and availability. The authors' analysis allows for an understanding of how the availability and accessibility of national FWA policies explicitly and implicitly restrict or facilitate flexible working in a structural manner. The study focuses on countries with differing working time regimes and gender norms on work and care: the Netherlands, Spain and Slovenia.

The authors' findings highlight how FWA accessibility is broader when national policy is specified and FWA availability is not conditional to care. In Spain and Slovenia, access to FWAs depends on whether employees have care responsibilities, which reduces accessibility and reinforces gender imbalances in care provision. In contrast, the Netherlands provides FWAs universally, resulting in wider availability and accessibility of FWAs for employees regardless of their care responsibilities. Despite this universal provision, gender imbalances remain.

The originality of this paper lies in its conceptualization and operationalization of FWAs at the national level using a capability approach. The study adds to the existing literature on flexible working and provides insights for policymakers to design more effective FWAs.

Many libraries and archives maintain collections of research documents, such as administrative records, with paper-based formats that limit the documents' access to in-person use. Digitization transforms paper-based collections into more accessible and analyzable formats. As collections are digitized, there is an opportunity to incorporate deep learning techniques, such as Document Image Analysis (DIA), into workflows to increase the usability of information extracted from archival documents. This paper describes the authors' approach using digital scanning, optical character recognition (OCR) and deep learning to create a digital archive of administrative records related to the mortgage guarantee program of the Servicemen's Readjustment Act of 1944, also known as the G.I. Bill.

The authors used a collection of 25,744 semi-structured paper-based records from the administration of G.I. Bill Mortgages from 1946 to 1954 to develop a digitization and processing workflow. These records include the name and city of the mortgagor, the amount of the mortgage, the location of the Reconstruction Finance Corporation agent, one or more identification numbers and the name and location of the bank handling the loan. The authors extracted structured information from these scanned historical records in order to create a tabular data file and link them to other authoritative individual-level data sources.

The authors compared the flexible character accuracy of five OCR methods. The authors then compared the character error rate (CER) of three text extraction approaches (regular expressions, DIA and named entity recognition (NER)). The authors were able to obtain the highest quality structured text output using DIA with the Layout Parser toolkit by post-processing with regular expressions. Through this project, the authors demonstrate how DIA can improve the digitization of administrative records to automatically produce a structured data resource for researchers and the public.

The authors' workflow is readily transferable to other archival digitization projects. Through the use of digital scanning, OCR and DIA processes, the authors created the first digital microdata file of administrative records related to the G.I. Bill mortgage guarantee program available to researchers and the general public. These records offer research insights into the lives of veterans who benefited from loans, the impacts on the communities built by the loans and the institutions that implemented them.

Despite the unparalleled importance of value within healthcare, value-based models remain underutilised in the procurement of medical devices. Research is needed to understand what factors incentivise standard, low-priced device purchasing as opposed to value-adding devices with potentially higher overall health outcomes. Framed in agency theory, we examine the conditions under which different actors involved in purchasing decisions select premium-priced, value-adding medical devices over low-priced, standard medical devices.

We conducted 2 × 2 × 2 between-subjects scenario-based vignette experiments on three UK-based online samples of managers (n = 599), medical professionals (n = 279) and purchasing managers (n = 449) with subjects randomly assigned to three treatments: (1) cost-saving incentives, (2) risk-sharing contracts and (3) stronger (versus weaker) clinical evidence.

Our analysis demonstrates the harmful effects of intra-organisational cost-saving incentives on value-based purchasing (VBP) adoption; the positive impact of inter-organisational risk-sharing contracts, especially when medical professionals are involved in decision-making; and the challenge of leveraging clinical evidence to support value claims.

Our results demonstrate the need to align incentives in a context with multiple intra- and inter-organisational agency relationships at play, as well as the difficulty of reducing information asymmetry when information is not easily interpretable to all decision-makers. Overall, the intra-organisational agency factors strongly influenced the choices for the inter-organisational agency relationship.

We contribute to VBP in healthcare by examining the role of intra- and inter-organisational agency relationships and incentives concerning VBP (non-) adoption. We also examine how the impact of such mechanisms differs between medical and purchasing (management) professionals.

This study aims to examine how knowledge sharing contributes to organizations’ ambidexterity, their overall performance and the role of knowledge quality in this relationship. Knowledge sharing is conceptualized based on tacit and explicit dimensions, and ambidexterity is viewed as comprising exploitative and explorative capabilities.

This study uses a cross-sectional survey-based research design and structural equation modeling to test the proposed model of knowledge sharing and knowledge quality in organizational ambidexterity and the related hypotheses.

The results indicate that tacit knowledge sharing has a significant, direct impact on the exploitative and explorative capabilities of the organization and indirectly impacts both dimensions of ambidexterity (i.e. exploitative and explorative) through knowledge quality. In contrast, explicit knowledge sharing does not have a significant impact on knowledge quality and affects only the exploitative extent of ambidexterity. Both exploitative and explorative capabilities significantly impact organizational performance.

To the best of the authors’ knowledge, this study is the first study to empirically examine the role of knowledge quality in the context of knowledge sharing for ambidexterity, especially within the context of organizations in the United Arab Emirates.

This article aims to examine whether specific job tasks measured at the individual level or personality traits are associated with wages and whether the relationship between personality traits and wages differs depending on the job tasks that individuals perform.

This study analyzes the association between job tasks and personality traits, and their interaction, with regard to wages using German employee data from 2017/2018.

Results suggest that nonroutine manual, interactive or analytic tasks are associated with significantly higher wages compared to routine manual tasks, and while extraversion and emotional stability are related to higher wages, agreeableness and openness tend to be associated with lower wages also within occupations. Moreover, the association between personality traits and wages varies depending on the job task requirements at the workplace. A high degree of extraversion in particular is associated with higher wages when the employee performs nonroutine manual, interactive or analytic tasks.

To date, especially the interaction between individual job tasks and personality traits on wages has not been extensively studied because data on both job tasks and personality at the employee level are scarce. This study contributes to the understanding of wage differences among employees.

This essay aims to draw attention to the idea of a new research approach to knowledge management (KM) labelled responsible KM (rKM) as a possible answer to not only address the consequences of the pandemic but also other present and upcoming societal challenges.

This essay has been prepared by a KM researcher who shares their own personal views and opinion regarding past and current societal developments and based on that offers a potentially new KM direction.

Switching the focus to rKM may help address current and upcoming social challenges that can only be addressed jointly by the global community and which would also involve a new consideration of the “knowledge” resource.

The essay proposes a new alternative approach to KM called rKM that is based on ideas that to the author’s knowledge have not been discussed in this way in the contemporary literature on KM.

This paper aims to examine how a social entrepreneurial organisation in Sweden collectively learned to adapt itself to the COVID-19 pandemic.

Using an abductive approach, this study conducted single case fieldwork on a social entrepreneurial organisation called SFE. The following research questions were asked: What are the changes in collective learning conditions that SFE has to face during the pandemic? What are the outcomes of collective learning during the pandemic in SFE?

This study results indicate that collective learning conditions were changed by restructuring the organisation’s design and teamwork during the pandemic, which facilitated sharing of knowledge and experiences. This collective learning helped the organisation develop new virtual projects during the pandemic. Another result of this collective learning was the members’ new shared understanding of the organisation’s vision.

This study hopes to broaden the understanding of the relationship between collective learning in organisations and organisational adaptation in times of crisis.

This study can help leaders of social entrepreneurial organisations understand what changes are necessary to create a team that collectively learns.

The data had the advantage of being gathered as a real-time process, and the researcher witnessed how the organisation achieved adaptation as it happened and not just through its members’ reflection of it as a past phenomenon.

Recognizing novel entrepreneurial opportunities arising from a crisis is of paramount importance for firms. Hence, understanding the pivotal factors that facilitate firms in this endeavor holds significant value. This study delves into such factors within a representative empirical context impacted by a crisis, drawing insights from existing literature on opportunity recognition during such tumultuous periods.

The authors conducted a qualitative inspection of 14 Italian firms during the COVID-19 pandemic crisis. The authors collected a rich body of multi-source qualitative data, including 34 interviews (with senior managers and entrepreneurs) and secondary data (press releases, videos, web interviews, newspapers, reports and academic articles) in two phases (March–August 2020 and September–December 2020).

The results suggest the existence of a process model of opportunity recognition during crises based on five entrepreneurial influencing factors (entrepreneurial knowledge, entrepreneurial alertness, entrepreneurial proclivity, entrepreneurial personality and entrepreneurial purpose).

Various scholars have highlighted that, in times of crises, it is not easy and indeed very challenging for entrepreneurs to identify novel entrepreneurial opportunities. However, recent research has shown that crises can also positively impact entrepreneurs and their capacity to identify new entrepreneurial opportunities. Given these findings, not much research has analyzed the process by which entrepreneurs identify novel entrepreneurial opportunities during crises. This study shows that some entrepreneurial influencing factors are very important to identify new entrepreneurial opportunities during crises.

This article explores the heterogenous social mechanisms that drive responsible environmental behaviours by investigating differences in the mean effect of the psychosocial determinants of the intention to buy organic foods.

Using data for a representative sample of the Spanish population, we estimated the mean effect of the constructs represented in the responsible environmental behaviour (REB) theory that affect sustainable food consumption, and examined the social mechanisms that may explain heterogeneity in the mean effect of those constructs. Confirmatory factor analysis, linear regression, and latent class regression were used in the analysis.

We found that the effect of REB’s psychosocial constructs varied significantly, demonstrating social heterogeneity in the estimated average effect. We identified different social mechanisms that explain variations in organic food purchase intentions: environmental attitudes and social norms shape these intentions among socioeconomically privileged consumers, whereas personal norms shape these intentions among less socially advantaged consumers.

Our research contributes to the literature by highlighting the existence of differing social mechanisms explaining organic food purchase intentions. The uncovering of three social mechanisms explaining differences in the mean effect of factors driving those intentions provides valuable insights with regard to both further developing a holistic framework for responsible environmental behaviours and developing new public policies and marketing strategies aimed at improving sustainable food consumption.

Based on an exploratory case-based approach, the purpose of this paper is to open the KM black box and examine the relationships that link knowledge management (KM) inputs (i.e. knowledge resources and KM practices) via knowledge processes to KM performance. This paper aims to identify the underlying mechanisms and explain how KM performance is enabled.

This in-depth case study conducted at a medium-sized consultancy in the supply chain management industry empirically examines knowledge flows to uncover the relationships between KM inputs, knowledge processes and KM performance. We adopt the viable system model (VSM) as a theoretical lens to identify KM mechanisms.

By identifying six KM mechanisms, we contribute to the theoretical understanding of how KM inputs are interconnected and lead to KM performance via knowledge processes.

Based on the insights gained, we provide propositions that organizations should consider in designing viable KM. Our findings help organizations in understanding their KM with the help of knowledge flow analysis and identifying how critical KM elements are interconnected.