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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 interview study examines Hungarian journalists' and copywriters' expectations of generative AI’s impact on their professions and factors influencing these views during a period of hype.

While acknowledging the specialized knowledge of journalists and copywriters relative to the general public, the study employs the sociology of expectations framework to interpret their anticipations not as objective forecasts of the future, but rather as phenomena shaped by diverse influences. The research comprises 30 semi-structured interviews conducted in spring 2023 to explore these expectations and their contributing factors.

Results reveal ChatGPT’s media coverage as pivotal, encouraging the professionals interviewed to experiment with AI, reassess their roles, and cause a shift in their job expectations. At the same time, this shift was limited. Skepticism about hyperbolic media formulations, their own experiences with ChatGPT and projecting its constraints into the future, contextual factors, and optimism bias contributed to moderating their expectations. They perceived AI as an enhancer of efficiency and quality, not as a radical disruptor. Copywriters were more open to integrating AI in their work, than journalists.

The results underscore the importance of further research to explore subjective experiences associated with technological change, particularly considering their complex social, psychological, and cultural influences.

The study uniquely contributes to the sociology of expectations by highlighting how a complex interplay of factors can shape professionals' anticipation of the impact of AI on their careers, including optimism bias and media hype.

This paper aims to determine the impact of perceived virtuality on team dynamics and outcomes by adopting the Input-Mediators-Outcome (IMO) framework. Further, it also investigates the mediating role of team processes and emergent states.

The authors collected survey data from 315 individuals working in virtual teams (VTs) in the information technology sector in India using both offline and online questionnaires. They performed the analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM).

The authors investigated two sets of hypotheses – both direct and indirect (or mediation interactions). Results show that psychological empowerment and conflict management are significant in managing VTs. Also, perceived virtuality impacts team outcomes, i.e. perceived team performance, team satisfaction and subjective well-being.

The interplay between the behavioural team process (conflict management) and the emergent state (psychological empowerment) was examined. The study also helps broaden our understanding of the various psychological variables associated with teamwork in the context of VTs.

Findings from this study will aid in assessing the consequences of virtual teamwork at both individual and organisational levels, such as guiding the design and sustainability of VT arrangements, achieving higher productivity in VTs, and designing effective and interactive solutions in the virtual space.

The study examined the interplay between behavioural team processes (such as conflict management) and emergent states (such as psychological empowerment). The study also theorises and empirically tests the relationships between perceived virtuality and team outcomes (i.e. both affective and effectiveness). It may serve as a guide to understanding team dynamics in VTs better.

This exploratory study attempts to enhance the current understanding of the research and practice of VTs within a developing economy.

Energy consumption in existing office buildings has been growing in parallel with the rise in occupant energy demand. As a result, many building owners have given smart retrofits (SRs) a higher priority. However, the utilisation of suitable SRs from a range of SRs has become a challenging task. The purpose of this paper is to develop a decision-making model to select the most suitable SRs for conventional office buildings and form a set of benchmarks for assessing the performance of SRs.

A qualitative approach with six case studies was used. Content analysis was carried out using NVivo to explore the factors considered for the selection of SR techniques. A decision-making model for selecting SRs in Sri Lankan office buildings was proposed. SR performance benchmarks were developed by referring to established standards and studies done in tropical office buildings.

Out of 18 identified SRs from literature, fan cycling, ventilation control and LED luminaires have been recognised as commonly used SRs in Sri Lankan office buildings. Analysis showed that HVAC retrofits saved more energy, while lighting retrofits could be easily implemented in existing buildings. The proposed decision-making model can explore further improvements to enhance the performance of SRs.

The selection of SRs is a comprehensive decision-making process. Metrics were established to benchmark the performance of SRs. The proposed model offers a tool for building owners and facility managers to optimise facility operations.