Cotton production makes an important contribution to the income of rural residents and the economy in Xinjiang province, which leads other provinces in terms of planted area, total production, and average yield of cotton in China. This study analyzed the competitiveness of cotton production in the study area using the efficiency advantage index (EAI), scale advantage index (SAI), and aggregated advantage index (AAI). Moreover, the factors influencing the productivity of cotton have been investigated by the use of ridge regression and correlation matrix using a dataset for the period 2005 to 2018. The results showed that cotton production had a large comparative advantage in Xinjiang from 2005 to 2018. The average of efficiency advantage index (EAI), scale advantage index (SAI), and aggregated advantage index (AAI) are 1.50, 12.96, and 4.35, respectively. Overall, Xinjiang cotton production has a higher planting scale advantage and productivity. By using ridge regression to calculate the impact of cotton production on agricultural output value in Xinjiang, the results showed that total cotton production, fiscal expenditure on agricultural support, total agricultural machinery power, and fertilizer use had significant positive effects, whereas cotton sown area, average cotton yield, and the proportion of affected area by insects and diseases had negative impact agricultural output value. The study implies the need for a implementing a well-thought and empirically backed plan to support cotton production based on comparative advantage for a specific area, building a cotton production standard system, reducing the cost of cotton production, and building a cotton risk-protection system to protect the interests of cotton farmers and promote the sustainable development of the cotton industry.

Tomato production under tunnel structures has shown promising returns in recent years in Pakistan. However, the energy use and GHGs dynamics remain largely unknown for tomato production under controlled conditions. This study estimates the energy budgeting and GHG emission in off-season (tunnel-farming) tomato production. Study data were gathered from 70 tunnel tomato growers through a simple random sampling technique. Energy use efficiency, energy productivity, and net energy along with covariates of energy output were estimated through Cob–Douglas regression. The results indicate that the total input energy consumption and production were 91,376.38 MJ ha⁻¹ and 56,764.64 MJ ha⁻¹, on average, respectively. The contribution of fertilizers (60.78%) was higher in total input energy followed by diesel and chemicals. The value of energy use efficiency was 0.652, which was higher for small farms (0.678) and lower (0.604) for large farms. Energy productivity (0.815 kg MJ⁻¹), specific energy (1.355 MJ Kg⁻¹), and net energy (−34,611.743 MJ ha⁻¹) were also estimated. The total greenhouse gas emission was 3426.66 kg CO₂ eq. ha⁻¹, which is low for large farms (3197.57 kg CO₂ eq. ha⁻¹). The contribution of farmyard manure to total GHG emissions was high. The results show the inefficient use of inputs, responsible for GHG emissions. Fertilizers were a major contributor both in total input energy and GHG emission. The efficient utilization of agricultural inputs is a solution to reduce GHGs emissions in crop production. Therefore, the agriculture department should play its role to ensure the optimal or efficient use of agricultural inputs. The Department of Extension is working to guide farmers about crop production at each stage. Thus, regular visits from extension staff are recommended to guide vegetable producers about efficient input use.

Governments around the globe are trying to find sustainable solutions for lessening pressure on natural resources and reducing carbon emissions. Daily household consumption of food, energy, and water has an impact on stocks of natural resources, environmental quality, and climate change. Households have significant potential for increasing conservation actions for efficient use of natural resources and greenhouse gas emissions. Households could contribute to a clean and healthy environment by adopting sustainable household practices through lower per capita consumption and carbon emissions. This study explored the role of different sustainable household consumption practices in promoting a clean environment as well as the factors affecting the adoption of these practices in Pakistan. Factor analysis and an ordered probit model were used to analyze the data from 1424 participants chosen through a multistage random sampling technique. The factor analysis identified 35 sustainable household practices for sustainable consumption. These 35 practices were grouped into the underlying factors of “Food” (14 items), “Energy” (12 items), and “Water” (9 items). The results from the econometric model showed a significant relationship between gender, education, residential area, family size, and income and the adoption of sustainable household consumption practices. Statistically, higher levels of reported sustainable consumption practices were apparent among females, households living in urban areas, more educated people, individuals of large family sizes, and more affluent households. Therefore, public policies for taking care of the environment need to put households at the center while at the same time promoting mass uptake of sustainable consumption practices related to food, energy, and water. In addition, the sector-specific policies also need to be augmented through focus on household-level consumption and production dynamics for achieving the UN’s SDGs.

This paper is aimed at evaluating the factors affecting the concurrent adoption of two risk coping strategies among hybrid maize farmers, namely income diversification supplemented with off-farm work and contract farming in the wake of changing climatic conditions. Climatic changes and food insecurity at the national level have emerged as key risk elements for hybrid maize production due to varying economic conditions. The present paper addresses these risks by examining various sources of risks faced by hybrid maize farmers and develops ideas to tackle these risks. Bivariate and multinomial probit models were employed to analyze numerous factors that influence farmers’ choice of the simultaneous adoption of income diversification (both on and off the farm) and contract farming at the farm level. The results reveal that hybrid maize farmers’ socioeconomic attributes significantly affect their adoption of risk coping tools. Similarly, the climatic, economic (price-related), biological, and financial risk perceptions and risk preference significantly influence the utilization of risk coping strategies in maize production. These outcomes extend our understanding of farmers’ risk preferences and provide parameters for policymakers to forestall diverse risk sources associated with hybrid maize production.

This research aims to examine the impact of macroeconomic and sustainability practices on carbon emission performance. Furthermore, it attempts to evaluate the moderating effect of Environmental, Social, and Governance (ESG) on the association between macroeconomic factors and sustainability and carbon emission performance. The final sample consists of 237 firms from the Middle East region. Results reveal that the resource use score, product responsibility score, inflation, and ESG have a positive and significant impact on carbon emission performance. Furthermore, it is revealed that ESG has a negative and significant moderating effect on the association between the environmental innovation score and carbon emission performance. On the other hand, ESG positively and significantly moderates the association between GDP growth, inflation, and the emission score. By addressing these aspects, this study enhances and broadens the existing literature, providing deeper insights into how macroeconomic determinants, environmental factors, and ESG jointly influence carbon emissions in the Middle East region. Furthermore, the study provides practical implications for policymakers, regulators, and corporate leaders by highlighting the importance of macroeconomic and environmental determinants in achieving superior carbon emission reductions in an increasingly competitive and sustainable global business environment.