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This study aims to explore the interrelationships among quality and safety metrics within the Global Food Security Index (GFSI). Its primary objective is to identify key indicators and their respective influences on food security outcomes, thereby enriching comprehension of the intricate dynamics within global food security.

The analysis encompasses data from 113 countries for the year 2022, utilizing Bayesian Belief Network (BBN) models to identify significant drivers of both the GFSI and quality and safety dimensions. This methodological approach enables the examination of probabilistic connections among different indicators, providing a structured framework for investigating the complex dynamics of food security.

The study highlights the critical role of regulatory frameworks, access to clean drinking water, and food safety mechanisms in fostering food security. Key findings reveal that “nutrition monitoring and surveillance” has the highest probability (75%) of achieving a high-performance state, whereas “national dietary guidelines” have the highest probability (41%) of achieving a low-performance state. High GFSI performance is associated with excelling in indicators such as “access to drinking water” and “food safety mechanisms”, while low performance is linked to underperformance in “national dietary guidelines” and “nutrition labeling”. “Protein quality” and “dietary diversity” are identified as the most critical indicators affecting both the GFSI and quality and safety dimensions.

This research operationalizes a probabilistic technique to analyze the interdependencies among quality and safety indicators within the GFSI. By uncovering the probabilistic connections between these indicators, the study enhances understanding of the underlying dynamics that influence food security outcomes. The findings highlight the critical roles of regulatory frameworks, access to clean drinking water, and food safety mechanisms, offering actionable insights that empower policymakers to make evidence-based decisions and allocate resources effectively. Ultimately, this research significantly contributes to the advancement of food security interventions and the achievement of sustainable development goals related to food quality and safety.

This paper aims to identify the factors that influence students' mental health, particularly in the context of MBA students passing through an emotional phase of the placement season.

A conceptual model through literature has been proposed. To test the proposed model of this study, a survey was conducted among the students of three MBA institutes of national reputation in India. The study's hypotheses were investigated using partial least squares-structural equations modeling and analysis of variance. To corroborate the findings of the survey data, a qualitative study in the form of open-ended interviews with five students was conducted.

The study revealed that female students, non-engineering graduates and students from non-family business backgrounds undergo stress, anxiety and depression higher than their classmates. Cumulative grade point average and bank loans do not significantly affect students' stress, anxiety and depression during the placement season. It was found that the increase in the levels of mindfulness scores led to a significant negative impact on stress, anxiety and depression among the students.

There is a gap in the literature that addresses the mental health of MBA students during campus job placements and the role of mindfulness in mitigating stress, anxiety and depression in these students. This research attempts to fill these research gaps.

The purpose of this paper is to explore the different contextual and psychological determinants of organisational resilience (OR) in the context of global mobility in multinational enterprises (MNEs). Banking upon the conservation of resources theory, this paper studies how and when reattachment to work (RTW), work engagement (WE) and two types of presenteeism lead to OR. Further, in the backdrop of the post-pandemic world of work, this paper also conceptualises the conditional effects of trait resilience (TR), organisational support (OS) and expatriation type (ET) on the aforementioned linkages.

This paper develops a conceptual framework that depicts various antecedents of OR in MNEs. Several testable propositions are also offered alongside the model’s moderated mediation and moderated moderation relationships.

The conceptual framework depicts the causal relationships between RTW and OR, such that Flexible RTW increases OR through higher WE and functional presenteeism under the conditional influences of TR, OS and ET, whereas rigid RTW decreases OR through lower WE and dysfunctional presenteeism under the conditional effects of TR, OS and ET.

To the best of the authors’ knowledge, this paper is the first of its kind that explores the psychological and contextual antecedents of the OR of MNEs and offers numerous testable propositions. The nexus of unique relationships presented in the conceptual framework bridges a crucial gap in the literature that explores the complexities of the post-pandemic workplace in the context of global mobility.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

Since the past two years, workplace dynamics has changed, as employees have witnessed uncertainty and a constantly fluctuating business environment due to COVID-19. The outbreak is nearly over, but it has led to new work settings in most parts of the world. This requires a suitable leadership approach to derive strategic decisions and cultivate proficiency amongst employees in the new work setting. The purpose of the article is to explore the effects of ambidextrous leadership (AL) in boosting social capital (SC) which further lead to employee creative work behavior. Further, the study also examined the moderating role of well-being in enriching creative work behavior.

In this study, 281 knowledge workers working in Mumbai were selected as subjects for the study. Structural equation modelling using analysis of moment structure was used to test the mediation. Later, moderated regression analysis confirmed the moderating role of well-being in employee creative behaviour.

The results confirmed the role of AL comprising closed and open leadership behaviours in enhancing the SC, which is an important element to cultivate creative behaviour amongst employees. In addition, the role of well-being is found to be critical for enhancing creative work behaviour.

The study will help organizations to understand the role of AL, SC and well-being in enhancing creative behaviour amongst knowledge workers.

This study contributes to leadership literature by attempting to integrate the concepts of leadership with SC, well-being and creative work behaviour, which has rarely been done in the Indian context.