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This study aims to analyse the outcomes of Indian insolvency proceedings for their ex-post economic efficiency. Ideally, insolvent yet viable companies should witness resolution, whereas insolvent-unviable companies should be liquidated. This study aims to ascertain the key forces that ensure or prevent the application of the first part of this maxim in practice.

The study uses logistic regression on a sample of 320 corporate insolvencies (out of 942 insolvencies) reported under the Insolvency and Bankruptcy Code (IBC), 2016. Two-stage least squares regression is used to check endogeneity issues.

The results claim high levels of rationality from the financial creditors and acceptable levels of viability from the plan proposers for precluding liquidation of insolvent yet viable companies. The findings reveal that an excess of value from resolution over that from liquidation, controls the outcomes of insolvency proceedings. Further examinations indicate that financial creditors’ focus on upfront recovery prevents them from judging the plans on other viability-related factors. Based on the findings, this study recommends that IBC must focus on the importance of both long-term recovery rates and resolution.

To the best of the authors’ knowledge, this is one of the first studies to empirically analyse Type 2 efficiency-related errors prevalent in the Indian insolvency proceedings since the enactment of its new code. The empirical explorations offered in this research can prove to be unique for policy-making.

The purpose of this study was to investigate the state of appraisal with regard to compliance with archives and records management legislations (ARML), the archives and records management policy (ARMP), reappraisal of records, capacity building, archives building and electronic records management (ERM) and to make a recommendation based on the research findings.

This study was based on the qualitative research technique. The research approach was a multiple case study comparing the previously advantaged and disadvantaged universities in South Africa.

The study found that ARML, ARMP, reappraisal of records and capacity building are essential for the appraisal of university records. The lack of appropriate appraisal theory/strategy led to a loss of institutional memory.

This research was limited to the University of the Witwatersrand (WITS) and the University of Venda (UNIVEN). These two institutions are representatives of the state of archiving in South Africa.

This research will serve a benchmark for other South African universities, intending to implement systematic disposal of records in compliance with legislations and policies.

Failure by universities to appraise records will lead to the loss of institutional memory. This implies that history of institution will be lost if necessary measures are not taken.

There is very little, if any, research on the appraisal of South African universities’ records. The outcome of this research will benefit universities that are seeking to develop and implement appraisal strategies.

The objective of this study was to investigate the impacts of personality traits and the ability to detect fake news on information avoidance behavior. It also examined the effect of personality traits on the ability to detect fake news.

The sample population included Shiraz University students who were studying in the second semester of academic year 2021 in different academic levels. It consisted of 242 students of Shiraz University. The Big Five theory was used as the theoretical background of the study. Moreover, the research instrument was an electronic questionnaire consisting of the three questionnaires of the ability to detect fake news (Esmaeili et al., 2019, inspired by IFLA, 2017), the Big Five personality traits (Goldberg, 1999) and information avoidance (Howell and Shepperd, 2016). The statistical methods used to analyze the data were Pearson correlation and stepwise regression, which were performed through SPSS software (version 26).

The results showed that from among the five main personality factors, only neuroticism had a positive and significant effect on information avoidance. In addition, the ability to detect fake news had a significant negative effect on information avoidance behavior. Further analyses also showed positive and significant effects of openness to experience and extraversion on the ability to detect fake news. In fact, the former had more predictive power.

Following the Big Five theory considering COVID-19 information avoidance and the ability to detect COVID-19 fake news, this study shifted the focus from environmental factors to personality factors and personality traits. Furthermore, this study introduced the ability to detect fake news as an influential factor in health information avoidance behaviors, which can be a prelude for new research studies.

The present study applied the five main personality factors theory in the context of information avoidance behavior and the ability to detect fake news, and supported the effect of personality traits on these variables.

The transition period from eating disorder inpatient (IP) care to outpatient care can be difficult for patients and is often characterised by high relapse rates. This study aims to co-develop a novel treatment pathway to support patients during this critical period.

This was a mixed-methods case study using co-production methodology and a nested qualitative component. The authors co-developed an initial proposed pathway structure with clinicians and people with lived experience of an eating disorder, based on a review of the literature. They then conducted interviews with clinicians and patients (n = 8) to refine the pathway; these were analysed using framework analysis.

A four-component pathway structure was developed. Six main themes emerged from this qualitative analysis: autonomy, the need for holistic patient care, difficult experiences, service provision, relationships and feedback on the discharge pathway.

This study highlighted the importance of centring patient autonomy during treatment, as well as ensuring treatments are holistic in nature. This may reduce the high levels of relapse associated with discharge from IP treatment and improve the quality and effectiveness of eating disorder treatment delivered.

Co-production approaches were used to develop the IP discharge pathway with members of a Lived Experience Advisory Panel alongside clinicians. To the best of the authors’ knowledge, this study was also the first intervention development study aimed at providing targeted support for patients dealing with the adverse effects of hospitalisation and difficulties transitioning to outpatient care.

This study aims to assess the recreational value of the National Chambal Sanctuary highlighting the potential benefits of conservation and the need for sustainable practices.

This study uses the Individual Travel Cost Method to evaluate the expenses of individuals visiting the National Chambal Sanctuary.

The study reveals that the National Chambal Sanctuary has a significant recreational value, with an average visitor value of INR 35,335.69 or USD 434 and an annual value of INR 132,473,501.81 or approximately USD 1.62m, indicating substantial economic contribution.

The study's limitations may stem from data collection constraints, visitor reporting biases or other factors affecting estimates' accuracy. Future research could explore socio-economic factors or factors affecting low tourist inflow in India's protected areas (PAs).

This study suggests raising entrance fees for the National Chambal Sanctuary to ensure financial sustainability, based on its high recreational value and average consumer surplus. This has practical implications for policymakers, conservationists and the tourism industry.

The study underscores the significance of protecting PAs like the National Chambal Sanctuary, suggesting that public attitudes towards biodiversity conservation can be influenced by highlighting its economic and recreational value and promoting awareness of its significance.

The study evaluates the recreational value of a wildlife sanctuary in India, offering insights into conservation's economic benefits and sustainable practices and promoting further research.

This study aims to assess barriers in accessing and uptaking climate change adaptation information among smallholder tomato farmers in Tanzania.

This study was conducted in Iringa and Morogoro regions, Tanzania. It adopted cross-sectional research design. Multistage, purposive and random sampling techniques with a sample size of 183 smallholder tomato farmers were used. Questionnaires containing closed- and open-ended questions, interview guide and focus group discussions were used to collect data. To ensure validity and reliability of data collection instruments, pretesting of the questionnaires was conducted by administering them to a small group of smallholder tomato growers. Statistical Product and Service Solutions software was used to analyse quantitative data while NVivo was used for analysing qualitative data.

Lack of clear understanding of climate change information (132, 72.1%), scarcity of libraries and information centres (125, 68.3%), inadequate income (125, 68.3%), lack of trust of sources of information (114, 62.3%), lack of sufficient knowledge about climate change (111, 60%), illiteracy (110, 60.1%), poor distribution of electricity in rural areas (109, 59.6%) and use of jargons (93, 50.8%) in explaining climate change adaptation issues are hindrances for smallholder tomato farmers to access and uptake climate change adaptation information.

This study was conducted in only two districts in Tanzania; thus, the findings cannot be generalized.

The government and relevant agencies are recommended to use appropriate strategies for breaking the barriers that impede easy access and uptake of climate change adaptation information by smallholder tomato farmers as one of the interventions to combat the impacts posed by climate change.

This study has contributed to the ongoing discourses on climate change issues. Such discourses have influenced attention and understanding of the role of access and uptake of climate change adaptation information by smallholder farmers for planning and implementation of adaptation strategies through awareness creation.

This study is in line with goal number 13.3 of Sustainable Development Goals, which vows on taking necessary actions in combating climate change and its impacts. Thus, smallholder tomato farmers’ awareness about climate change through access and uptake of climate change adaptation information is one of the interventions to combat climate change and its impacts.

Employability skills training programmes are an effective means for reducing unemployment rates. Such programmes also have the potential to improve the general well-being (e.g. self-efficacy) of disadvantaged individuals, however, reliable longitudinal evaluations of the psychological benefits of such programmes are limited. The present study evaluated the impact of an employability programme offered to disadvantaged adults in North-West England on self-efficacy. Additionally, the study aimed to identify risk factors for programme disengagement to identify at-risk groups that require further support.

Secondary longitudinal data pertaining to the background characteristics, programme engagement and self-efficacy scores (repeatedly measured on a monthly basis) of 308 programme users were analysed.

Results demonstrated that employability programme engagement significantly increased self-efficacy scores. Additionally, the findings suggested that individuals with mental health and learning difficulties were more likely to disengage from the programme. The findings demonstrate that employability programmes can have a positive impact on the well-being of individuals from disadvantaged backgrounds, however, prolonged engagement is needed for which some individuals require further support with.

The present study analysed longitudinal data from a diverse sample of disadvantaged individuals to reliably evaluate psychological outcomes from employability training programmes.

This study aims to investigate the impact of changes in audit processes during the pandemic on auditors’ deviant behavior, considering auditors’ personal characteristics, including demographic variables, spirituality levels and personality traits.

A survey consisting of five parts was used to gather data from auditors employed at Big Four audit firms in the Middle East. The questionnaire collected data on auditors’ perceptions of changes in audit processes and deviant audit behavior during the pandemic, as well as information about their personal characteristics.

The findings revealed a significant positive association between changes in audit processes and a heightened perception of deviant audit conduct during the pandemic. Males and extravert auditors expressed less favorable attitudes toward such behavior.

The sample size was limited to 107 auditors due to the challenges of soliciting responses from auditors during the pandemic. The sole focus on the Big Four audit firms limited the generalizability of the results. Upcoming research should integrate qualitative methods alongside surveys and collect data from larger, more diverse samples to enhance the understanding of the pandemic’s impact on audit behavior.

The findings provide guidance and recommendations for audit firms to mitigate deviant behavior during crises while considering auditors’ personal factors. Recommended strategies include the organization of trainings to raise awareness of these risks and the integration of artificial intelligence to modernize audit processes and enhance audit firms’ readiness to confront future crises.

This study offers a novel empirical investigation into how pandemic-driven changes in audit procedures relate to auditors' deviant behavior, while exploring the influence of auditors' individual traits, an unexplored area in the literature. It addresses this gap specifically in the context of the understudied Middle East region.

This paper examines open innovation (OI) based on sustainability principles within the agri-food sector. The study aims to understand the interplay between different actors and develop a typology of their roles in fostering sustainability. Three key research questions guided our inquiry: “WHY” sustainability is driving the OI initiatives as presented by companies, “WHO” participates in OI interactions and “HOW” these interactions are structured among diverse agri-food actors.

Through a theoretical prism encompassing OI modes, types, practices, sustainability dimensions and multilevel perspectives, we analyzed 78 agri-food sustainable OI initiatives, as described by the companies, to identify and explain why, who and how they engage in OI to drive sustainability shifts.

The results reveal typical patterns of transaction and cooperation between actors and confirm the collaborative nature of sustainable OI in the agri-food sector when actors must transcend traditional economic boundaries and reshape both the internal performance culture and the broader industrial or community mindset. The paper also conceptualizes the roles of actors in co-creating value in the context of sustainable food transitions.

This study brings the theoretical lenses of OI to conceptualize the collaborative nature of sustainability transitions in the agri-food system. The focus on sustainability transitions is dominantly placed on innovators at the niche level, while incumbents tend to be depicted as protecting the status quo. Thus, the focus on the collaborative interplay among different actors engaged in OI for sustainability contributes to offering a more nuanced view of innovation in sustainability transitions. In turn, the development of a typology of actors, motivations and configurations of OI from sustainability transition perspectives contributes to strengthening the conceptualization of sustainable value co-creation in the OI realm.

This study aims to objectively synthesize the volume of accounting literature on financial statement fraud (FSF) using a systematic literature review research method (SLRRM). This paper analyzes the vast FSF literature based on inclusion and exclusion criteria. These criteria filter articles that are present in the accounting fraud domain and are published in peer-reviewed quality journals based on Australian Business Deans Council (ABDC) journal ranking. Lastly, a reverse search, analyzing the articles' abstracts, further narrows the search to 88 peer-reviewed articles. After examining these 88 articles, the results imply that the current literature is shifting from traditional statistical approaches towards computational methods, specifically machine learning (ML), for predicting and detecting FSF. This evolution of the literature is influenced by the impact of micro and macro variables on FSF and the inadequacy of audit procedures to detect red flags of fraud. The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper chronicles the cluster of narratives surrounding the inadequacy of current accounting and auditing practices in preventing and detecting Financial Statement Fraud. The primary objective of this study is to objectively synthesize the volume of accounting literature on financial statement fraud. More specifically, this study will conduct a systematic literature review (SLR) to examine the evolution of financial statement fraud research and the emergence of new computational techniques to detect fraud in the accounting and finance literature.

The storyline of this study illustrates how the literature has evolved from conventional fraud detection mechanisms to computational techniques such as artificial intelligence (AI) and machine learning (ML). The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper contributes to the literature by providing insights to researchers about why the evolution of accounting fraud literature from traditional statistical methods to machine learning algorithms in fraud detection and prediction.