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The present research attempts to delve into the climate-agriculture-migration nexus to ascertain whether the variation in agriculture output due to climatic factors has a significant influence on the emigration flows from the Asian and African continents.

The present study draws upon a rich panel of data from 27 countries (14 African and 13 Asian) between 1995 and 2020. The first stage least square, OLS and 2SLS techniques have been employed to examine the relationships between climatic factors and international migration, climatic factors and agriculture output, and agriculture output and international migration, respectively.

The results exhibit a positive relationship between temperature and international migration. The influence of temperature on agriculture output is negative but insignificant while precipitation promotes agriculture output. In addition, agriculture output negatively influences international migration, and these findings establish a climate-agriculture-migration relationship.

To counteract the climate-agriculture-migration nexus, it is incumbent upon governments to conduct extensive field trials and data collection exercises to assess the influence of climate in separate agro-ecological zones and devise policies accordingly.

The literature concerning the interrelationship between climatic factors, agriculture and migration is scarce and what is available pertains to different contexts. Moreover, no studies are based on Asia and Africa; the continents have a high dependence on agriculture and outmigration rates, and the present research covers this important gap in the literature.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

Climate change negatively affects agriculture and food security, and jeopardizes Myanmar's agriculture, which is vital to ensure food security, rural livelihoods, and the economy. This study explores the asymmetric impacts of climate change on Myanmar's agricultural sector.

We utilize the nonlinear autoregressive distributed lag (NARDL) approach for the years 1991–2020, the Wald test to validate the asymmetric relationship between climate change and agriculture, and the FMOLS and DOLS approaches to confirm the validity of the outcomes.

Our findings reveal that temperature has a positive impact on Myanmar's agriculture, whereas rainfall and CO2 have negative effects over the long and short terms. Evidently, decreasing temperatures more favorably impact agriculture than increasing temperatures, while increasing rainfall more negatively impacts agriculture than decreasing rainfall. Increasing carbon emissions have a more detrimental effect on agriculture than decreasing them.

We gathered data over periods longer than 30 years to provide more robust findings. However, owing to data limitations, such as missing values or unavailability, the study period spans from 1991 to 2020.

This study contributes to the existing literature on the asymmetric effects of climatic and non-climatic factors on agriculture. It is the first study in Myanmar to use the NARDL approach to measuring the effects of climate change on both the agricultural gross production index and value, providing robust findings.

This paper aims to analyze the influences of context and methodological differences in how universities confront, report and manage carbon neutrality in selected Andean universities, contrasted with a university in the USA.

A sequential, mixed-methods design, using quantitative and qualitative approaches was applied. The data analysis is based on a systematic literature review with bibliometric analysis to identify how carbon neutrality in universities is understood and applied. Informed by the quantitative analysis, the qualitative phase compared the assessment methodologies, opportunities and obstacles in three Andean universities – EAFIT in Colombia, EPN in Ecuador and the UC in Chile – contrasted with MIT (USA) for comparative purposes beyond the region.

The bibliometric analysis points to the evolution of carbon management and carbon neutrality in universities and indicates how universities have applied methodologies and defined opportunities and obstacles. In this comparative experience, the contextual issues are brought to the fore. The conclusions highlight the importance of context in carbon neutrality assessment and argue against crude comparative metrics. While carbon assessment protocols provide data on which actions may be taken, the phase of carbon management development and the specifics of context – based on local institutional, geographical, climatic, cultural, socioeconomic and national policy conditions – are far more relevant for identifying actions.

This study only considered four universities, and the findings are not generalizable. The argument highlights the point that contextual factors generate important differences that may complicate simple comparisons based on the university's type or size. It also highlights the differences in the carbon calculation methodologies used by the institutions.

Results build on the recent publications that document the Latin American context. The article contributes to knowledge about Andean university commitments and actions relating to climate change and carbon neutrality. This knowledge can contribute to how universities in the region seek to apply different methodologies, set targets and the timing of actions and consider their contextual opportunities and obstacles.

Comparing university carbon footprints and carbon neutrality plans is an emerging topic, presenting methodological and institutional difficulties. This paper reveals some of these difficulties by comparing parameters, actions and implementation processes against contextual factors. While there is a drive for international and national comparisons and systematization of data on university carbon performance, significant methodological gaps still need to be resolved to account for these contextual factors.

Fresh out of the two-century-old British legacy, Bangladesh, formerly known as East Pakistan from 1947 to 1971, was searching for a post-colonial architectural style. Colonial architecture in the region in general often imposed imported European elements, ignoring the preceding legacies of the Sultanate and the Mughals. The critical challenge was to find a balance between the prevailing high modernism in architecture and the local vernacular and climatic forces. The Pakistani government invited international architects to fill the gap left by a non-existent local architectural industry. Unfortunately, their work has rarely been properly analyzed. With selected case studies, this paper analyzes their work in an attempt to explore their contribution to creating a national architectural identity.

This study uses a case study approach with selected architectural projects from the period. It uses research tools such as systematic analysis of drawings, volumes and photographs and archival research.

The international architects took inspiration from the strong vernacular and climatic forces of the region. The resultant expressions of the two-decade-long search in their combined body of work are some of the finest examples of vernacular and climate-responsive architecture in the region. They transcended the regular international style and became context-specific and unique. The quest for East Pakistan's post-colonial architectural identity was partially met by the newly found identity through vernacular and climate-responsive adaptation in architecture.

This study explores how a unified vernacular and climate-responsive adaptations potentially shaped the post-colonial architectural identity of the region. No prior study exists on this issue for the time period.

The agricultural sector is a critical component of global economic development, and its significance has grown significantly in recent years. The risks associated with agriculture and the behaviors of farmers in handling these risks are becoming increasingly important, given the sector’s increasing dependence worldwide. Various activities related to agriculture are vulnerable to multiple risks, which can have severe consequences for farmers’ livelihoods. The purpose of this systematic review is to present a comprehensive analysis of the sources of risk faced by farmers and their choices in adopting risk management strategies worldwide.

The Preferred Reporting Items for Systematic reviews and Meta-Analyses protocol was utilized to select relevant literature, and a total of 102 studies were analyzed. Through the use of Venn diagrams and graphical methods, the authors provide a transparent overview of the risks faced by farmers and the adoption of risk management strategies in developed and developing countries.

From the analysis, the authors found that, in terms of risk management strategies, diversification, reserve credit and accumulated assets are frequently used in developing countries, while developed countries tend to rely on future/forward contracts, crop insurance and hedging. Diversification is the most widely used risk management strategy across both developed and developing countries. Our study also highlights the different perceptions of weather-related risks among growers in developed and developing countries.

This systematic review provides valuable insights into the risks associated with agriculture and farmers' strategies in managing these risks, which could inform policy decisions and promote sustainable agricultural practices. For instance, understanding the individualistic nature of farmers' risk perception and the varying risk sources and management strategies depending on the locality and provide assistance to the farmers accordingly.

The paper explains how farmers behave during uncertainty in terms of risk perception and their decision to adopt risk management strategies in developed and developing countries.

The purpose of this paper was to study the possibility of using smartphone roughness measurements for developing pavement roughness regression models as a function of pavement age, traffic loading and traffic volume variables. Also, the effects of patching and pavement distresses on pavement roughness were investigated. The work focused on establishing pavement roughness prediction models and applying these models to pavement management systems (PMS) to help decision-makers choose the best maintenance and rehabilitation (M&R) options by using cost-effective methods.

Signal processing techniques including filtering and processing techniques were used to obtain the International Roughness Index (IRI) from raw acceleration data collected from smartphone accelerometer sensors. The obtained IRI values were inputted as a dependent variable in analytical regression models as well as several independent variables with proper transformations.

According to the study results, several regression models were developed with a big variation in the coefficients of determination (R²). However, the best models included pavement age, accumulated traffic volume (∑TV) and construction quality factor (CQF) with R² equal to 0.63. It was also found that the effects of pavement distresses and patching was significant at a-level < 0.05. The patching effect on pavement roughness was found higher than the effect of other pavement distresses.

The presented results and methods in this paper could be used in the future predictions of pavement roughness and help the decision-makers to estimate M&R needs. The work focused on establishing IRI prediction models and applying these models to the PMS to help decision-makers choose the best M & R options.

To develop sound pavement roughness models, it is essential to collect roughness data using automated procedures. However, applying these procedures in developing countries faces several difficulties such as the high price and operation costs of roughness equipment and lack of technical experience. The advantage of using IRI values taken from smartphones is that the roughness evaluation survey may be expanded to cover the full road network at a cheaper cost than with automated instruments. Therefore, if the roughness survey covers more roads, the prediction model’s accuracy will be improved.

The study examines the project success factors for leadership behavioural practices and communication impacting project success, providing empirical evidence to address the challenges in the digitalized environment in the Australian construction sector.

A quantitative approach was employed to collect survey data from 109 project managers and followers (project engineers, supervisors, team members, and senior managers) with diverse project management experience in the construction sector. An exploratory factors analysis/multivariate regression/relative importance index/t-test was used to identify the key project success factors and validate the study's results.

Data analysis identified four key project success factors: (1) Relationship Management, (2) Leading by Example, (3) Self-Management, and (4) Effective Communication, along with seventeen “behavioural practices attributes” impacting project success positively and significantly and emphasizing inclusiveness, relationship building, self-feedback objectivity, sharing information, collaboratively resolving disputes, and controlling emotions that significantly impact project success.

The study's results will address the industry's challenges in the complex digitalized environment and specific issues experienced in the construction industry: delays and inefficiencies, supply chain management, communication barriers with multicultural workforce and safety protocols implementation, regulatory and safety compliance, infrastructure demands, skills shortages, sustainability, and new technology adoption to achieve project success.

The quantification of research findings, employing an innovative approach, underscores the distinctive nature of this study. The key success factors will help formulate innovative practices using stakeholder analysis, communication plans, conflict resolution strategies, promoting collaboration, safety leadership, providing cultural awareness, and enhancing the decision-making process to face challenges in the construction sector.

As climate change disproportionately affects vulnerable populations, ensuring thermal comfort for older adults is magnified in tropical senior living environments. This study explores the lived experiences of older adults' thermal comfort in senior living facilities in a tropical climate and how these experiences impact their overall well-being.

Employing Moustakas' transcendental phenomenology and the Modified Stevick-Colaizzi-Keen method, this study investigated older adults' thermal experiences through semi-structured interviews with 28 participants in six urban senior living facilities in Malaysia.

Four primary themes emerged: fabric and function; atmospheric conditions and living dynamics; thermal dynamics and environmental comfort; temperature tensions of stress, sound, and sensitivity. Our findings underscore the importance of considering the multisensory and multi-faceted nature of thermal comfort for older adults, considering sensory aspects, early life experiences, cultural practices, and personal preferences, particularly in tropical climates.

As one of the first to explore the thermal comfort of older adults in senior-friendly accommodations in a tropical climate, the findings provide a comprehensive understanding of older adults' diverse thermal comfort needs and offer practical recommendations for environments that support healthy aging. By integrating insights from hospitality, gerontology, and environmental studies, this research contributes to the promotion of public health and aligns with global objectives to improve the well-being of the aging population.

This study aims to understand how climatic drivers of change will affect rural communities living in the hot semiarid region of Bhokardan Taluka of Jalna district in the Indian state of Maharashtra. In the context of the economic and social change they are experiencing, the concern is to evolve ways that enable them to cope with, adapt to and benefit from these challenges.

The focus of most of the climate change studies is on the short- to long-term trends of weather parameters such as rainfall, temperature and extreme weather events. The impact of climate variability and changing patterns on the local communities, the local economy, livelihoods and social life in specific geographies is less explored.

As the impacts of climatic and nonclimatic drivers of change are cross-sectoral, diverse, multidimensional, interlinked and dynamic, this study has adopted a transdisciplinary “research-in-use” approach involving multidisciplinary teams covering the aspects such as changes in land use and land cover, surface and groundwater status, edaphic conditions, crops and livestock, climate analysis including projected changes, socioeconomic analysis, people’s experience of climate variability and their current coping strategies and resilience (vulnerability) analysis of communities and various livelihood groups.

The study was based on the peoples’ perspective and recommendation based on the local communities ability to cope up with climate change. However, a statistical analysis perspective is missing in the present study.

Based on these findings, a set of implementation-focused recommendations are made that are aimed at conserving and enhancing the resilience of the foundations that uphold and sustain the social and economic well-being of the rural communities in Bhokardan taluka, namely, land, water, agriculture, livestock, food and nutrition security, livelihoods, market access and social capital.