Extensive research on pro-environmental behaviour (PEB) reveals a significant knowledge gap in understanding the influence of social class, perceived status and the middling tendency on pro-environmental behaviour. Using the International Social Survey Programme Environment dataset, and conducting multilevel mixed-effects linear regressions, we find that the middling tendency and biased status perceptions significantly influences pro-environmental behaviour. Those who deflate their social position have higher pro-environmental behavior and this reinforces the idea that pro-environmental behaviour is driven by a post-materialist effect rather than a status enhancement effect. Moreover, the objective middle class is still a stronger contributor to higher PEB levels compared to subjective middle class. We also find the relation between class, status and PEB vary by country. These findings provide vital insights into the intricate and heterogenous dynamics between class, status and pro-environmental behaviour among different countries and shed light on class and status as driving forces behind pro-environmental behaviour.

Smallholder paprika farmers in Zimbabwe contribute to local economies and food security but face supply chain challenges like limited market access and poor infrastructure which lead to post harvest losses and unpredictable prices. To survive, these farmers must adopt sustainable value networks to reduce operational costs and improve performance. This study sought to establish the effect of sustainable value networks on the operational performance of smallholder paprika farming in Zimbabwe. This study, using a positivist research philosophy and a quantitative approach, surveyed 288 smallholder paprika farmers in Zimbabwe. Exploratory factor analysis and partial least squares structural equation modelling were used to validate the constructs and test the hypothesised relationships. Results demonstrate a moderate level of implementation of value networks in smallholder paprika farming characterised by successes and challenges. The findings illustrated resource sharing among smallholder farmers, facilitated by initiatives, such as recycled seed exchanges and financial support through village savings and loan associations. However, results show that challenges persist, particularly with market access and financial support. Results indicate that there is a significant awareness and implementation of green supply chain management practices among smallholder paprika farmers even though they do not have access to resources and live in rural areas. The findings demonstrate that value networks significantly influence the adoption of green supply chain management practices, which in turn positively impact operational performance, environmental performance, and social performance. Green supply chain management practices were found to mediate the relationship between value networks and environmental performance, social performance, and operational performance, underlining the critical role of sustainable practices in enhancing performance outcomes. While environmental performance showed a positive effect on operational performance, the direct influence of social performance on operational performance was found to be statistically insignificant, suggesting the need for further exploration of the factors linking social benefits to operational efficiency. The research contributes to both theory and practice by presenting a sustainable value network model for smallholder paprika farmers, integrating value network, green supply chain management practices and environmental performance to enhance operational performance. Practical implications include policy recommendations to strengthen collaboration between smallholder farmers and other stakeholdersand address power imbalances with intermediaries. Future research should extend the study to other agricultural sectors and incorporate more diverse stakeholder perspectives to validate and generalise the proposed sustainable value network model.

The main purpose of this paper was to examine the impact of generative artificial intelligence (AI) on employee well-being and work dynamics. Using qualitative methodology, three semi-structured interviews were conducted to investigate the implications of generative AI on employee outcomes such as efficiency, job satisfaction, ethical considerations, and work-life balance. The findings highlighted the potential benefits and risks associated with generative AI implementation in the workplace. The study contributed to the literature by adopting a qualitative approach, allowing in-depth exploration of individual experiences with generative AI in the workplace. The study discussed the implications for employers, employees, and society.