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This study aims to assess the knowledge of Amhara Sayint district community in Northeastern Ethiopia towards the health impacts of climate change.

A community-based cross-sectional study was conducted from 20 July to 5 September 2022, involving 605 randomly selected households in Amhara Sayint district, Northeastern Ethiopia. Data were collected through face-to-face interviews using a pilot-tested and content-validated questionnaire administered via Kobo Collect survey tool. The data were then exported to STATA for management and analysis. A proportional odds approach of ordinal logistic regression model was fitted with a 95% confidence level to identify factors associated with the community’s knowledge towards the health impacts of climate change.

Of the total respondents, 3.47% (95% confidence interval [CI]: 2.1, 5.3) and 42.98% (95% CI: 38.9, 47) had inadequate and medium levels of knowledge towards the health impacts of climate change, respectively. Proportional odds model analysis result indicated that gender (female) (adjusted odds ratio [AOR] = 1.49; 95% CI: 1.053, 2.13), wealth status (poorest) (AOR = 1.97; 95% CI: 1.01, 3.83), educational status (unable to read and write) (AOR = 4.13; 95% CI: 1.25, 13.68) and participation status in environmental protection activities (not) (AOR = 1.78; 95% CI: 1.17, 2.71) were factors that significantly associated with inadequate and medium levels of knowledge towards the health impacts of climate change.

The result of this research is not supported by qualitative methods.

Residents of the study area know the climate is changing; however, they lack adequate knowledge towards the health impacts of climate change.

Significant number of people have inadequate level of knowledge about health impacts of climate change so relevant health education is needed.

This research is original in its focus on assessing public knowledge about the health impacts of climate change in the Amhara Sayint district, northeastern Ethiopia, a perspective often overlooked in existing studies. Its findings are crucial for guiding future research and developing targeted public health strategies and educational initiatives.

This paper aims to report on a case in which encouraging climate-smart agriculture in the form of better irrigation techniques in India can contribute to both climate change mitigation and adaptation goals by improving resource-use efficiency. It provides grounded institutional analysis on how these transformations can occur.

The authors based their research on three complementary approaches: institutional, sociological and technical. The institutional approach analyzed actors and interests in the water-energy nexus in India via over 25 semi-structured key informant interviews. The sociological approach surveyed over 50 farmers and equipment suppliers for insight into technology adoption. The technical component analyzed water and energy consumption data to calculate potential benefits from transitioning to more efficient techniques.

Because policymakers have a preference for voluntary policy instruments over coercive reforms, distortions in policy and market arenas can provide opportunities for embedded actors to leverage technology and craft policy bargains which facilitate Pareto superior reforms and, thereby, avoid stalemates in addressing climate change. Enlarging the solution space to include more actors and interests can facilitate such bargains more than traditional bilateral exchanges.

The analysis provides insights into crafting successful climate action policies in an inhospitable institutional terrain.

Studies about climate change politics generally focus on stalemates and portray the private sector as resistant and a barrier to climate action. This paper analyzes a contrary phenomenon, showing how reforms can be packaged in Pareto superior formats to overcome policy stalemates and generate technology-based climate and environmental co-benefits in even unpromising terrain such as technologically laggard and economically constrained populations.

Neurodivergent employees have atypical needs that require distinctive leadership approaches. In this study, the specific nature of a relationship between neurodivergent employees and their neurotypical leaders is explored through the lens of the leader–member exchange (LMX) theory.

This two-phased qualitative study builds on 12 semi-structured interviews with neurodivergent employees and an unstructured focus group with 15 individuals with professional and/or personal interest in neurodiversity. The researcher spent almost 13 h listening to the lived experiences of research participants concerning neurodiversity and leadership.

Leaders who exhibit empathy and understanding were noted to provide greater support. The findings also highlight the complexity of neuro-inclusion in the workplace. Specifically, the delicate balance between accommodation and avoiding stigmatization is emphasized, addressing the concerns raised regarding the legal risks associated with neurodivergent inclusion. Additionally, the findings underscore the necessity for leaders to avoid patronizing behaviors while catering to the diverse needs of neurodivergent employees. This underscores the importance of supporting both neurodivergent employees and leaders navigating such challenges.

The findings help establish inclusive and accommodating employee relations practices that conscientiously address the requirements of neurodivergent employees while providing support for those in leadership roles.

This study constitutes a direct answer to recent calls to develop a more nuanced understanding of workplace neurodiversity, with a specific focus on neuro-inclusive leadership. Acknowledging that we still use inappropriate, old tools in new situations that require novel approaches to leadership helps set the agenda for future research in this area.

The impact of frontline robots (FLRs) on customer orientation perceptions remains unclear. This is remarkable because customers may associate FLRs with standardization and cost-cutting, such that they may not fit firms that aim to be customer oriented.

In four experiments, data are collected from customers interacting with frontline employees (FLEs) and FLRs in different settings.

FLEs are perceived as more customer-oriented than FLRs due to higher competence and warmth evaluations. A relational interaction style attenuates the difference in perceived competence between FLRs and FLEs. These agents are also perceived as more similar in competence and warmth when FLRs participate in the customer journey's information and negotiation stages. Switching from FLE to FLR in the journey harms FLR evaluations.

The authors recommend firms to place FLRs only in the negotiation stage or in both the information and negotiation stages of the customer journey. Still then customers should not transition from employees to robots (vice versa does no harm). Firms should ensure that FLRs utilize a relational style when interacting with customers for optimal effects.

The authors bridge the FLR and sales/marketing literature by drawing on social cognition theory. The authors also identify the product categories for which customers are willing to negotiate with an FLR. Broadly speaking, this study’s findings underline that customers perceive robots as having agency (i.e. the mental capacity for acting with intentionality) and, just as humans, can be customer-oriented.