Abstract: Prolonged drought is considered as a creeping natural hazard, which has created a financial burden and unsustainable environment in Iran. Moreover, the effect of drought phenomenon in rural areas is more extensive, causing significant challenges to the rural economy in general and agricultural production in particular. A common strategy to manage drought is based on crisis management (ex-ante). However, for effective drought management, risk management seems to be more in line with drought early warning systems. This quantitative study used risk assessment, which is the function of two elements such as hazard (SPI and SDI indices) and vulnerability (exposure, sensitivity, and adaptive capacity). This study aims to build the foundations for drought early warning systems in limited resource areas such as Kermanshah Township in the northwestern part of Iran. The population of this study comprised of wheat farmers in which 293 farmers were selected using multistage cluster sampling method. In the next step, the drought risk map for Kermanshah Township was developed, which revealed that the majority of villages are at intense environmental risk. The result of this study has implications for drought management practitioners. For example, the results can aid policymakers in the design of an early warning system in order to reduce risk and thus empower farmers toward resilient farming.

Abstract: Purpose This paper aimed to investigate the determinants of loans and advances from commercial banks in the case of Ethiopian private commercial banks. Design/methodology/approach The study randomly selected seven commercial banks to represent the population stratified on their asset, deposit and paid-up capital amounts. The study utilized an unbalanced panel data model as each bank started operation at a different period of time and considered the period 1995-2016 for secondary details. Findings The findings showed that the deposit size, credit risk, portfolio investment, average lending rate, real gross domestic product (GDP) and inflation rate had significant and optimistic effects on the lending and advancement of private commercial banks. On the contrary, liquidity ratio had significant and negative effects on private commercial bank loans and advances. Finally, the study forwarded a feasible recommendation for concerned organs to focus on deposit size, credit risk, portfolio investment, average lending rate, real GDP, inflation rate and liquidity ratio. The results of this study will help banking industry policymakers and planners understand how to minimize inflation and unemployment by improving development and sustainable economic growth. Originality/value The findings of this study can also affect the general attitudes of a society by increasing knowledge and improve the quality of life for the general public.

Abstract: The aim of this study is determination of exergoenvironmental efficiency for using solar technologies in sunflower oil production in Iran. Accordingly, the applications of photovoltaic and photovoltaic/thermal systems were evaluated for both agricultural and industrial phases of sunflower oil production. Energy results reveal that 1 ton of sunflower oil consumes and produces about 180,354 and 39,400 MJ energy, respectively. About 86% of total energy consumption belongs to agricultural phase and electricity with 32%, has the highest share of total energy consumption. IMPACT 2002+ method and cumulative energy demand of life cycle assessment are applied to 3 defined scenarios including Present, photovoltaic and photovoltaic/thermal. Results indicate that total amounts of climate change in Present scenarios is 24537.53 kg CO2 eq.. The highest share of human health (90%), ecosystem quality (90%) and climate change (50%) in all scenarios belongs to direct emissions. Results also illustrates that total cumulative energy demand of Present, photovoltaic and photovoltaic/thermal scenarios are about 177,538, 99,054 and 132,158 MJ 1TSO(-1), respectively. Furthermore, the most contribution of non-renewable resources and fossil fuels belongs to electricity (37%), nitrogen (52%) and photovoltaic/thermal panels (39%) in Present, photovoltaic and photovoltaic/thermal scenarios, respectively. Finally the photovoltaic scenario is the best environmental-friendly scenario. (c) 2021 Elsevier Ltd. All rights reserved.

Abstract: Climate-Smart Agriculture (CSA) is seeking to overcome the food security problem and develop rural livelihoods while minimizing negative impacts on the environment. However, when such synergies exist, the situation of small-scale farmers is often overlooked, and they are unable to implement new practices and technologies. Therefore, the main aim of this study is to improve CSA by adding the neglected but very important element “small-scale farmer”, and introduce Vulnerable-Smart Agriculture (VSA) as a complete version of CSA. VSA indicates, based on the results of this study, that none of the decisions made by policymakers can be realistic and functional as long as the voice of the farmers influenced by their decisions is not heard. Therefore, to identify different levels for possible interventions and develop VSA monitoring indicators, a new conceptual framework needs to be developed. This study proposed such a framework consisting of five elements: prediction of critical incidents by farmers, measuring the consequences of incidents, identifying farmers' coping strategies, assessing farmers' livelihood capital when facing an incident, and adapting to climate incidents. The primary focus of this study is on farmers' learning and operational preparation to deal with tension and disasters at farm level. Understanding the implications of threats from climate change and the recognizing of coping mechanisms will contribute to an increase in understanding sustainable management.

Abstract: Cotton is one of the important crops that play an important role in creating a livelihood for rural people in many parts of Iran. Cotton production necessitates a large amount of resources (e.g., fossil energy and agrochemicals, all of which have the potential to damage the environment in various ways). The purpose of the current study was to evaluate the environmental effects of cotton production in the South Khorasan Province of Iran. For this purpose, life cycle assessment (LCA) and data envelopment analysis (DEA) techniques have been applied to investigate the environmental impacts of cotton production. LCA is a practical method to evaluate the environment on the product flow, in which all aspects of the product life cycle are examined by a comprehensive approach. Furthermore, combining the LCA method with other managerial strategies such as DEA could allow researchers to provide decision-makers with more practical and interpretable data. The findings of the efficiency test showed that the average technical efficiency, pure technical efficiency, and scale efficiency were 0.81, 0.92, and 0.87, respectively. Respiratory inorganics (i.e., respiratory effects resulting from winter smog caused by emissions of dust, sulfur, and nitrogen oxides to air) posed the greatest environmental burden in cotton production, followed by non-renewable energy, carcinogens, and global warming. In addition, the highest effects were on human health, and then, on resources and climate change. Energy, on-system pollution, and waste played a crucial role in the environmental impacts of cotton processing. This study suggests improving farmers' knowledge toward the optimum application of chemical fertilizers, or their substitution with green fertilizers, which reduces the environmental effect of growing cotton in the area.

Abstract: Land-tenure security is integral to local communities' socioeconomic development. It has been a center of debate in academia and for legislators and advocates to implement reforms to enhance efficient and sustainable development in land management. Yet, knowledge gaps remain in how various contract-farming regimes contribute to land-improvement investment and technical efficiency. This study used a data set of 650 farm households collected through a two-stage stratified sampling to investigate the influence of three contract-farming regimes: long-term, medium-term, and short-term contracts, on the land-improvement investment, productivity, and technical efficiency of contract farmers in Punjab, Pakistan. The study used multivariate probit and ordinary least square regression models to examine the posit relationships. The findings highlight that farmers with long-term land contracts have higher per hectare yield, income and profit than those with medium-term and short-term contracts. The results confirm that farmers with medium- and long-term contracts tend to invest more in land-improvement measures, i.e., organic and green manure. Further, the study findings demonstrate that long-term land tenures are more effective when farmers make decisions regarding the on-farm infrastructure, like tube-well installation, tractor ownership, and holding farm logistics. Last, the study results confirm that long-term contracts are more robust regarding technical efficiency. Moreover, the findings support the Marshallian inefficiency hypothesis and extend the literature on contract farming, land-improvement investment, and land use policy, and offer coherent policy actions for stakeholders to improve farmers' productivity, technical efficiency, and income.