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This study empirically examines the impact of climate change and agricultural research and development (R&D) as well as their interaction on agricultural productivity in 12 selected Asian and Pacific countries over the period of 1990–2018.

Various estimation methods for panel data, including Fixed Effects (FE), the Feasible Generalized Least Squares (FGLS) and two-step System Generalized Method of Moments (SGMM) were used.

Results show that both proxies of climate change – temperature and precipitation – have negative impacts on agricultural productivity. Notably, agricultural R&D investments not only increase agricultural productivity but also mitigate the detrimental impact of climate change proxied by temperature on agricultural productivity. Interestingly, climate change proxied by precipitation initially reduces agricultural productivity until a threshold of agricultural R&D beyond which precipitation increases agricultural productivity.

The findings imply useful policies to boost agricultural productivity by using R&D in the context of rising climate change in the vulnerable continent.

This study contributes to the literature in two ways. First, this study examines how climate change affects agricultural productivity in Asian and Pacific countries – those are most vulnerable to climate change. Second, this study assesses the role of R&D in improving agricultural productivity as well as its moderating effect in reducing the harmful impact of climate change on agricultural productivity.

Golestan province in the northern part of Iran has been affected by devastating floods. There has been a significant change in the pattern of rainfall in Golestan province based on an analysis of the seven heaviest rainfall events in recent decades. Climate change appears to be a significant contributing factor to destructive floods. Thus, this paper aims to assess the susceptibility of this area to flash floods in case of heavy downpours.

This paper uses a variety of computational approaches. Following the collection of data, spatial analyses have been conducted and validated. The layers of information are then weighted, and a final risk map is created. Fuzzy analytical hierarchy process, geographic information system and frequency ratio have been used for data analysis. In the final step, a flood risk map is prepared and discussed.

Due to the complex interaction between thermal fluctuations and precipitation, the situation in the area is further complicated by climate change and the variations in its patterns and intensities. According to the study results, coastal areas of the Caspian Sea, the Gorganrood Basin and the southern regions of the province are predicted to experience flash floods in the future. The research criteria are generalizable and can be used for decision-making in areas exposed to flash flood risk.

The unique feature of this paper is that it evaluates flash flood risks and predicts flood-prone areas in the northern part of Iran. Furthermore, some interventions (e.g. remapping land use and urban zoning) are provided based on the socioeconomic characteristics of the region to reduce flood risk. Based on the generated risk map, a practical suggestion would be to install and operate an integrated rapid flood warning system in high-risk zones.

The paper aims to assess the impact of weather-induced shocks on household food consumption in the rural Vietnamese Mekong Delta (VMD) through the case of Long An province and evaluate the effectiveness of widely used coping strategies in mitigating weather-related shock impacts.

The system generalized method of moments (GMM) estimation method is applied to explore information on shock incidence, recovery, and time occurrences. The paper uses a sample of 272 repeated farming households from 5-wave survey data from 2008 to 2016, resulting in 1,360 observations.

The paper confirms the robust negative effect of a natural shock on food consumption. Additionally, using savings proves to be the most potent measure to smooth food consumption. Other favorable coping strategies are “getting assistance from relatives, friends” or “getting assistance from the Government, and non-government organizations (NGOs).” The mitigating effects are also traced in the current analysis.

Using caution when generalizing the results from Long An to the whole VMD is reasonable. The rather limited observations of coping strategies do not allow the authors to analyze any specific strategy.

The proposed approach employs the GMM technique and controls for endogenous coping strategies and thus provides accurate estimates of the effects of weather-related shocks and the mitigation effectiveness in the rural VMD.

This study aims to measure the status of rural household food security across regions using multidimensional indicators. It also aims to identify the determinants of rural household food security in Ethiopia.

The study adopted descriptive and explanatory designs. It used data from the fourth wave of the Ethiopian socioeconomic survey that has 3,115 respondents. The authors constructed household food security index using variables that capture availability, access, utilization and stability dimensions of food security. The authors categorized households into relative food security groups, namely, alarming and moderately food insecure, as well as moderately and highly food secure. Beta regression model, which is widely used to analyze response variables that assume values between 0 and 1, is used to estimate the determinants of food security.

The study finds that 77.7% of rural households are food insecure. Of this, 90% are moderately food insecure. Regional variations in magnitude of food security showed that Harari, Gambella and Benshanguel Gumuz regional states are relatively better-off than other regions in Ethiopia. The study identified sex, education level, marital status, location and wealth status of households as significant determinants of food security.

This study sheds light on regional variations in multidimensional food security in Ethiopia. It thus challenged previous estimates of food security using uni-dimensional indicator. It highlighted the need for region-specific analysis of determinants and a follow up of tailored regional interventions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0139

This paper aims to investigate the role of corporate governance on the bank profitability of Indian banks vis-à-vis South Asian Association for Regional Cooperation (SAARC) nations.

For the Corporate Governance Index, the authors examined board accountability, transparency and disclosure and audit committee, while Tobin’s Q, return on equity and return on assets are used to measure the bank’s profitability. The study used a two-stage analysis based on balanced panel data for robust findings. Sample of this study consists of 60 commercial banks from India and 60 banks from SAARC nations for the period of 2009–2021. This study used panel regression and a generalized method of moment approach using the CAMELS framework on banking industry-specific variables to determine their respective impacts.

The findings of this study suggest that board accountability is positive and significantly affects the profitability of banks as indicated by return on assets, return on equity and Tobin’s Q. In contrast, the audit committee has a positive and insignificant impact on return on assets, return on equity and Tobin’s Q, while transparency and disclosure have a negative and significant impact on these metrics. Furthermore, the country dummy result shows a significant positive impact on all the bank performance parameters, implying that Indian banks have the highest degree of convergence with corporate governance as compared to other SAARC nations.

This study provides insight to the regulators, policymakers and financial institutions to evaluate the role of corporate governance in emerging economies. However, the findings of the study should be interpreted with caution, as the results are sensitive to the disparity between India and other SAARC nations' government policies, climatic circumstances and cultural or religious traditions.

To the best of the authors’ knowledge, this is the first attempt to gauge the performance of Indian banks vis-à-vis SAARC nations using the CAMELS framework approach. Further, findings of this study suggest some novel evidence tying corporate governance quality with the profitability of banks among SAARC nations.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

This paper examines the determinants of concurrent adoption of farm risk management strategies by rice growers in two different ecosystems of Telangana agriculture-irrigated and rainfed ecosystems.

The primary data have been collected from the rice growers in two different ecosystems, and after checking the variance inflation factor (VIF) for controlling multicollinearity, a multinomial logit model has been used to examine the determinants of concurrent adoption of coping strategies by rice growers.

The study finds that adopting one risk management strategy persuades farmers to embrace other strategies, reducing the risk in agriculture between the two ecosystems. Among the determinants, farmers' age, education, contact with extension services, irrigation sources, livestock income, total farm income, crop loss reasons, and crop insurance awareness significantly influence the adoption of various risk management measures. However, considerable heterogeneity is found among the driving forces across the rice ecosystems.

The major policy implications that can be drawn from the analysis are increased access to information through government-funded extension services and the provision of alternative risk management technologies, such as drought-resistant or flood-resistant seeds, farmers' field schools and increased provision of crop insurance, farmer-friendly agriculture extension services, and farm investment support, are critical for assisting farmers managing risks. In addition, however, there should be ecosystem-specific policies to tackle the ecosystem heterogeneity.

This paper is very timely and entails some relevant policy implications for the development of Indian agriculture.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

This paper aims to answer these questions: “Is the public adopting energy-saving and water-saving facilities because they want to save energy and water in their psychological perception?”, “Is it convenient to use energy-saving and water-saving facilities?”, “If the inductive design of energy-saving and water-saving facilities attracts the public’s interest, the public is it more willing to install energy-saving and water-saving facilities in a widespread manner?” and “Can inductive energy-saving and water-saving facilities be introduced into the smart manufacturing system of manufacturing industries that require a lot of water to effectively save water and save costs for the company?”.

This paper aims to investigate the attitudes of employees toward using energy-saving and water-saving facilities by constructing a questionnaire based on the ABC (Affect, Behavior, Cognition) model to survey the attitudes of employees from the Southern and Eastern of Taiwan and establishing a structural equation modeling (SEM) to examine the relationship between affect, behavior and cognition while using energy-saving and water-saving facilities.

There are some findings in this paper that the affective design have a strongly significant positive impact for using energy-saving and water-saving facility in the proposed model. People are willing to use energy-saving and water-saving facilities but are more willing to adopt those energy-saving and water-saving products of smart designs, as those take into account the emotional factors. The critical factor for the public to adopt energy-saving and water-saving facilities is smart design, which incorporates emotional elements.

There are still some limitations of this study that the ABC model can only be used as a psychological discussion, and the development and design of related facilities still needs to be jointly developed with professionals in related technical fields. The introduction of induction water supply facilities needs to be considered while the company introduces the design of the smart manufacturing system. Therefore, professionals related to induction water supply should participate in the planning at the initial stage of the company's concept of introducing the smart manufacturing system.

On the practical side, based on preliminary research conclusions, this study proposes to introduce inductive water supply into smart manufacturing systems for manufacturing companies that require a lot of water in their manufacturing processes. In practice, the company can actually save a lot of water, thereby saving costs and reducing waste water discharge.

The results of this study show that the public has a cognition of energy-saving and water-saving. However, there is a Chinese proverb that “easy to know and hard to do”, when actually using facilities, convenience is an important consideration for public. Smart facilities of energy-saving and water-saving, in addition to the benefits of energy-saving and water-saving, it is easy to use, and interacts with users through inductive water supply, which can more emotionally attract people's willingness to use.

This study found that smart facilities, which can more emotionally attract people's willingness to use. On the academic side, this study proves that using the ABC theory to explore the public’s psychological affective, behavior and cognition response to the use of facilities is a very suitable method. On the practical side, based on preliminary research conclusions, this study proposes to introduce inductive water supply into smart manufacturing systems for manufacturing companies that require a lot of water in their manufacturing processes. In practice, the company can actually save a lot of water, thereby saving costs and reducing waste water discharge.

This study aims to examine the challenges for green retrofitting implementation in existing residential buildings to lower the running cost and achieve a better energy-efficient system.

This study adopted a qualitative approach by interviewing conveniently selected 16 construction professionals, made up of architects, quantity surveyors and engineers. Data received were analysed using the content analysis method.

The findings revealed that the main barriers to incorporating green retrofitting in the existing residential buildings as the nature of the existing structures, limited knowledge, not being a priority and high costs involved in the process. Moreover, other factors influencing property developers’ decision to apply energy-efficient principles in a residential home include cost (initial capital and maintenance), level of knowledge, nature of the climate in the area, local legislation, more independence and increasing the property’s market value and environmental aspect.

This study is limited to South Africa; thus, the literature available was limited.

People’s perceptions, either wrong or correct, affect their ability to make an informed decision to adopt green retrofitting principles, thereby denying them the opportunity to reap the associated benefits. Therefore, there is an urgent need for the construction industry stakeholders and government to increase educational opportunities for property owners on the importance of green retrofitting.

This study provides the occupants with the possible barriers and problem areas with implementing these principles. They will thus make an informed decision when implementing sustainable design methods.