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Corporate social responsibility (CSR) has gained tremendous importance after several corporate scandals, financial crises and the rise of the hyper-competitive world. Firms must address multiple stakeholders’ interests to increase firm value. This study aims to investigate the effect of CSR on firm value. This study also examines the mediating role of enterprise risk management (ERM) and the moderating influence of corporate governance (CG) in this CSR-firm value relationship.

The sample of the study comprises 119 Pakistan Stock Exchange (PSX) listed firms and the study covers the period from 2010 to 2021. The corporate social responsibility performance has been quantified across five dimensions. These aspects are product, environment, employee relations, diversity and community. Four proxies i.e. strategy, operation, reporting and compliance, have been used to measure ERM. The governance quality of the sample companies was evaluated using the governance index, which included 29 governance provisions. The authors used the dynamic panel data technique (system-GMM) is used to achieve the objectives of the study. Furthermore, a firm’s engagement in CSR activities can also be measured through a multinational financial approach to check the robustness of the result.

Based on the regression analysis, the authors discovered that CSR was positively connected with firm value, validating the stakeholder view of CSR. Furthermore, following Baron and Kenny’s (1986) mediation technique, the findings confirm that ERM mediates this association. These results are robust by using the bootstrapping tests by Preacher and Hayes (2004). Furthermore, the result shows that corporate governance (CG) is positively connected with firm performance, and this relationship is strengthened in the presence of an effective governance system in the organization.

This study provides useful insights to regulators, investors and policymakers to consider CSR as a value-enhancing factor and encourage the development of enterprise risk management and compliance with CG mechanisms to improve firm value.

The presented analysis strengthens the existing CSR–firm value relationship by analyzing the mediating and moderating roles of ERM and CG, which have not yet been tested, particularly in the context of Pakistan.

The study aims to investigate the current electronic records management practices in government departments of South Africa to establish the extent to which they foster service delivery in public service reform programmes.

This study applied a systematic literature review approach to critically appraise the published literature on the status of records management in South Africa, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The findings indicate that the South African public sector encounters challenges such as a lack of skills in managing electronic records, management support, resources and legislative frameworks and policies. The study’s findings revealed that although electronic records are essential for service delivery in South Africa, the existing records management programme is not efficient and effective and does not sufficiently comply with legislative and statutory requirements.

This study was limited to the public sector of South Africa.

This study recommends the development of policy frameworks and strategies aligned with the organisational goals and facilitation of professional training for all staff, including attendance of seminars, workshops and workplace training.

The research demonstrates the need for a comprehensive legislative and policy framework, robust integration of electronic records practices in government e-government efforts, and adequate technological infrastructure support.

This study offers informed recommendations to address the challenges of managing electronic records in South African public sector organisations that continue to be a cause for concern.

Traditional risk prioritization methods in Enterprise Risk Management (ERM) rely on precise data, which is often not available in real-world contexts. This study addresses the need for a robust model that can handle uncertain and imprecise information for more accurate risk assessment.

We propose a group decision-making approach using fuzzy numbers to represent risk attributes and preferences. These are converted into fuzzy risk scores through defuzzification, providing a reliable method for risk ranking.

The proposed fuzzy risk prioritization framework improves decision-making and risk awareness in businesses. It offers a more accurate and robust ranking of enterprise risks, enhancing control and performance in supply chain operations by effectively representing uncertainty and accommodating multiple decision-makers.

The adoption of this fuzzy risk prioritization framework can lead to significant improvements in enterprise risk management across various industries. By accommodating uncertainty and multiple decision-makers, organizations can achieve more reliable risk assessments, ultimately enhancing operational efficiency and strategic decision-making. This model serves as a guide for firms seeking to refine their risk management processes under conditions of imprecise information.

This study introduces a novel weighted fuzzy Risk Priority Number method validated in the risk management process of an integrated steel plant. It is the first to apply this fuzzy approach in the steel industry, demonstrating its practical effectiveness under imprecise information. The results contribute significantly to risk assessment literature and provide a benchmarking tool for improving ERM practices.

This article explores women entrepreneurs' lived experiences in their interactions with government enterprise support agencies. It investigates the relationship between gendering and Entrepreneurial Orientation (EO), as a normative orientation adopted at the institutional level and justified by an economic rationale. It also explores how women entrepreneurs articulate their experiences through embodied metaphors and image schemas, shedding light on how they navigate the institutional entrepreneurial space.

This study is framed within the concept of Phenomenological Orientation as conceptualised in feminist phenomenology. It applies Interpretative Phenomenological Analysis, a qualitative methodology focused on interpreting accounts of first-person lived experiences of a phenomenon. It combines IPA with Conceptual Metaphor Theory to understand women's articulation of their embodied relationship within the entrepreneurial space.

Findings reveal that the entrepreneurial orientation functions as a gendering process within entrepreneurial institutions, reinforcing masculine hegemonic ideals and marginalising women entrepreneurs. Women's phenomenological orientations often diverge from the normative entrepreneurial orientation, highlighting the need for a more inclusive framework in institutional entrepreneurial spaces.

This article contributes to women's entrepreneurship literature by underlining the temporal dimension of entrepreneurship and the tension that underpins their interactions with government support bodies. It calls for inclusive policies and procedures to match the heterogeneity of orientations. While highlighting its limitations, it also suggests future research directions to deepen the understanding of entrepreneurship and inform more suitable support structures for all entrepreneurs.

This study contributes to the literature by shedding light on the nuanced interplay between gendering, entrepreneurial orientation, and women entrepreneurs' lived experiences. It extends previous research by framing “orientation” within a temporality framework, offering a novel perspective on the gendering of entrepreneurial spaces.

In this paper, the impact of the 2004 European Union accession on income inequalities within New Member States is analyzed.

An empirical analysis is conducted with nine New Member States over the period 1991–2015, with 55 economies serving as a control group. The newly introduced (by de Chaisemartin and D’Haultfœuille, 2023) method belonging to the family of difference-in-differences (DID) estimators is applied to allow for multiple non-binary treatments.

While accession to the European Union had a positive and significant impact on the market and net Gini coefficients in the treated countries, no evidence of the impact of accession on redistribution was found. Single-unit estimates signal that income inequalities rose due to EU membership in some member countries; the most convincing evidence shows that income distribution in Latvia was especially affected.

The author applied the method which addresses the presence of multiple non-binary treatments. Full-fledged membership was preceded by association status, and accession to the EU was accompanied or followed by engagement in other layers of integration (European Monetary Union and Schengen Area). Controlling for these features, the author was able to assess whether the pure EU effect contributed to increases in income inequalities.

The paper aims to gain understanding of perceived benefits and barriers to GAS-light as an occupational therapy outcome measure in community adult mental health. The study explored occupational therapists’ views on the client-centred nature of GAS-light and whether it is an applicable outcome measure for group intervention. It also aimed to understand how occupational therapists use of GAS-light informed their practice and the wider multidisciplinary team perspective.

The study used a phenomenological design. This comprising of a focus group of occupational therapists experienced in using the tool, followed by framework analysis. Focus group questions were derived from literature.

Three main themes were identified to reflect experiences relating to the GAS-light tool as an outcome measure; value in process, occupational narrative and language and expertise.

The paper is indicative of practical implications regarding the use of the GAS-light tool with community mental health clients and therapists, including the perceived value in the process, the language used by the therapist and level of expertise.

This paper fulfils an identified need to contribute towards an evidence base for occupational therapy and mental health.

The purpose of the study is to investigate female prisoners’ perspectives on why they gain weight while in prison.

A qualitative design was used with semi-structured interviews with six females currently residing in a prison in the south of England.

Analysis of the data generated three themes relating to the reasons why women gain weight in prison. These were labelled as “The only thing you haven’t got to ask permission for is your food, it’s just handed to you”, “If you’ve been stripped of the things that make you happy, or that you are addicted to, eating can soothe you” and “prison can make you take better care of your health”.

The results identify perceived reasons why women gain weight in prison uniquely from the female prisoner perspective. The implications of the research identify the need for systemic change throughout different prison departments to enable women to maintain a healthy weight during their custodial sentence.

Predicting a user’s click-through rate on an advertisement or item often uses deep learning methods to mine hidden information in data features, which can provide users with more accurate personalized recommendations. However, existing works usually ignore the problem that the drift of user interests may lead to the generation of new features when they compute feature interactions. Based on this, this paper aims to design a model to address this issue.

First, the authors use graph neural networks to model users’ interest relationships, using the existing user features as the node features of the graph neural networks. Second, through the squeeze-and-excitation network mechanism, the user features and item features are subjected to squeeze operation and excitation operation, respectively, and the importance of the features is adaptively adjusted by learning the channel weights of the features. Finally, the feature space is divided into multiple subspaces to allocate features to different models, which can improve the performance of the model.

The authors conduct experiments on two real-world data sets, and the results show that the model can effectively improve the prediction accuracy of advertisement or item click events.

In the study, the authors propose graph network and feature squeeze-and-excitation model for click-through rate prediction, which is used to dynamically learn the importance of features. The results indicate the effectiveness of the model.

Despite India achieving many milestones under MGNREGA, the external and internal shocks result in below potential outcomes in employment demand and generation. This study examines how these shocks matter and how the migration-prone regions perform.

This study, employing district-level data from 2018 to 2021, investigates how climate change and COVID-19 have affected the employment demand and supply. We applied RE-GLS and IV-2SLS regressions to examine the effects of shocks on employment demand and generation, respectively. The difference in difference panel model is employed to test the spatial effects of the pandemic. Further, we used RE-GLS and extended regression model to examine how external shocks interacting with migration affect unemployment rates.

It was found that the pandemic increased employment demand and generation. This reflects the adverse effects of the pandemic and the swift action by the government. However, the responses were possibly different during climate shocks. The wage differential increased employment demand. However, demand decreased due to poor support from the support staff. The employment generation was higher in migration-prone districts, indicating that seasonal migration, being a lean-season phenomenon, continues to occur despite employment generation.

This study contributes to the literature in several ways. It captures spatial variations while examining the impact of climate change and COVID-19. It investigates the performance of MGNREGA in migration-prone areas. In effect, the findings provide policymakers with greater insight into the issues.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2024-0132.

This study investigates the impact of internal expectations, such as fantasy of success and fear of failure and external factors, such as social environment and past experiences, on entrepreneurial choice.

Based on achievement motivation and social cognitive theories, the authors construct hypotheses and use secondary data from the Global Entrepreneurship Monitor (GEM) database and Economic Freedom Index report to empirically test the hypotheses. The authors also use propensity score matching to solve the endogeneity issue and test the robustness.

Internal expectations (fantasy of success and fear of failure) on business outcomes inversely affect entrepreneurial choices, with a vibrant business environment amplifying and past failure experience mitigating these effects.

Due to the economic recession, governments encourage small businesses. Thus, the complexity of individual entrepreneurial motivations and influencing factors necessitate deeper exploration. This study is one of the first research offering insights into entrepreneurial motivations from combined dimensions and providing theoretical support for strategies promoting public entrepreneurship.