Technical efficiency and its determinants of cane and bamboo handicraft enterprise in Assam: a stochastic frontier analysis approach

The dairy industry is very important to the economy, but it has big problems with sustainability since it doesn't use resources well and doesn't handle waste well. Eco-Efficiency (13.1%) and Technical Efficiency (58.7%) are still very low in Serbia because of ongoing structural inefficiencies. In Indonesia, where 90% of dairy farms are operated by smallholders, an estimated 84% of manure is discharged untreated, contributing to greenhouse gas emissions and eutrophication. To solve these problems, we need to use Circular Economy ideas, such as closed-loop nutrient, energy, and water flows and integrated resource recovery. This review evaluates opportunities, sustainability gains, and barriers to implementing closed-loop systems across the dairy supply chain. The objectives include assessing farm-level efficiency, quantifying environmental and economic benefits of manure-derived resource recovery, evaluating circular feed substitution, and analysing biogas adoption barriers among smallholders. The research integrates findings from Stochastic Frontier Analysis, Life Cycle Assessment and Costing, Multi-regional Input–Output analysis, membrane-based water reuse models, and system dynamics, complemented by qualitative surveys of Indonesian farmers. Integrated recovery systems yielded carbon-negative results (up to –1790 kg CO₂ eq/year) and significant economic advantages ($825–$1,056/year). Biogas cut down on the consumption of LPG by about 45%. Circular feeds made more milk and had less of an effect, while treating whey membranes slashed the need for fresh water by 67–90%. Closed-loop solutions make dairy farming much more sustainable, but they need help from policymakers to be able to grow because of high investment costs and ongoing structural inefficiencies.

Abstract Climate-smart agriculture is heralded for enhancing productivity and combating climate change. It has been purported that the adoption of climate-smart agricultural practices and technologies (CSAPT) remains limited, with various reasons. A key challenge in the existing literature is conflating traditional CSAPT, such as intercropping, with innovative CSAPT, like improved seeds, obscuring critical distinctions. Recognizing that CSAPT adoption is highly context-specific, especially in regions like Northern Togo with unique agro-ecological and socio-economic challenges, this study analyzed farm production efficiency under traditional and innovative CSAPT. Using data from over 500 households in Togo’s Kozah prefecture, farmers were categorized into those who adopted only traditional CSAPT and those combining traditional and innovative CSAPT. A binary probit model identified adoption determinants, while stochastic frontier analysis evaluated farmers’ technical efficiency. The findings indicate that most farmers continue to rely only on traditional CSAPT. Probit analysis indicates that factors like gender, land tenure, farm size, organization membership, and dry spell exposure influence the likelihood of adopting traditional and innovative CSAPT. Farmers combining traditional and innovative CSAPT had higher efficiency than those using only traditional methods. These findings have important policy implications. They emphasize the need for agricultural policies that reduce barriers to adopting innovative CSAPT. Policies should ensure land access for women, empower farmer organizations to spread technology, and develop localized climate-resilience strategies. These initiatives can increase the adoption of efficiency practices, boosting agricultural productivity and food security amid climate change.

Optimizing sugarcane production in Rwanda: a stochastic frontier analysis of smallholder farmers

Accounting for Heterogeneity in the Water-Energy-Carbon Nexus: Evidence from English and Welsh Water Utilities.

Tourism is a key driver of regional economies, but concerns are often raised about the effectiveness with which public resources are managed and translated into tangible outcomes. Despite its importance, research on the efficiency of public spending on tourism remains scarce and mostly confined to national scales. Therefore, this study examines how Apulian municipalities (Italy) convert public tourism expenditure into measurable tourism results, providing new evidence on the efficiency of local governance in this sector. The analysis applies a two-step econometric framework combining Stochastic Frontier Analysis (SFA) and Multiple Linear Regression to data from 247 municipalities over the period from 2020 to 2023. The results reveal generally low average efficiency levels, with only a few coastal destinations achieving high performance. The regression analysis identified key structural and territorial drivers of efficiency, including accommodation capacity, cultural production, coastal and environmental quality, and the presence of agritourism and campsites. The findings suggest that efficiency depends more on the ability of local administrations to coordinate tourism, cultural, and environmental policies than on the amount of spending. Overall, the study provides empirical evidence that an efficient allocation of tourism funds is crucial for achieving long-term sustainability goals, offering practical insights for designing more effective tourism policies.

This study examines how eco-friendly farming practices affect the technical efficiency of grafted tomato production in Moulvibazar District, Bangladesh. Primary data was collected from 210 tomato producers using the multistage sampling technique. The collected data was analyzed to estimate technical efficiency and its determinants by employing stochastic frontier analysis (SFA). Results found that tomato farmers were about 71% efficient, which implies that tomato production could be increased by nearly 29% if resources and technology were used optimally. The study discovered that while higher input costs lowered productivity, using more land, labor, and tractors helped enhance tomato output. Education, household size, access to training, access to extension services, and experience with grafting improved efficiency, whereas leasing land and earning income from non-farming activities caused a lowering of efficiency. Eco-friendly practices like mixed cropping, using vermicompost, yellow sticky traps, pheromone traps, and mulching films significantly improved efficiency, making farmers 2% to 98% more efficient than those who didn’t adopt these methods. These practices helped better manage inputs, control pests, and maintain healthy soil, boosting both productivity and environmental sustainability. Therefore, promoting eco-friendly tomato production practices through national programs, better extension services, improved credit access, and secure land rights can promote sustainable farming adoption and raise tomato production efficiency.

Agricultural production in the Yellow River Basin (YRB) faces challenges including inadequate extension services, outdated technologies, environmental degradation from excessive use of fertilizers and pesticides, and poor waste management. This study employs stochastic frontier analysis to investigate the effects of environmental regulation on technical efficiency, offering new empirical evidence on how environmental regulations influence agricultural production choices and farm-level performance. Stochastic production frontier analysis is used to estimate technical efficiency and inefficiency while evaluating the trade-offs associated with regulatory policy interventions. Data was collected from a stratified random sample of 957 farmers in Gansu, Shaanxi, and Shanxi provinces at the county level through in-person interviews conducted in August 2022 using a questionnaire tool. Regulatory policy interventions, like penalties on crop residue burning, improve efficiency, while excessive use of hazardous chemicals negatively impacts efficiency at the 1% significance level. This study highlights the need for farmer training, with even a 0.10% efficiency gain from demonstration or theory classes. Sustainable farming practices and fertilizers ensure ecological sustainability and long-term agricultural productivity. In conclusion, urgent and robust regulatory oversight is essential to prevent the overuse of chemicals and residue burning, promoting environmental and sustainable agriculture.

The establishment of a tourist village with grapes as a tourist attraction in a suboptimal area is strongly influenced by the level of efficiency, both technically and economically. Suboptimal land in Pangandaran Regency is characterized by dryness, so inefficiency in input use can lead to low production and productivity levels in grape cultivation. Furthermore, the presence of a tourist village has an impact on the social life of the local community. The purpose of this study was to determine the factors that influence grape cultivation as an agritourism activity. In addition, to measure the technical and economic efficiency of grape cultivation at the household scale. The method used in this study was parametric statistics with the Stochastic Frontier Analysis approach. The sample was selected through purposive sampling, comprising 60 respondents who cultivate plants. The research respondents were selected with the criteria of farmers who have grown grapes for more than 2 years. The results showed that the level of efficiency of grape cultivation in the yard has a technical efficiency value of 0.856. Factors that influence the level of technical efficiency are the number of trees, the amount of manure, the amount of growth fertilizer, and labor. Meanwhile, the socioeconomic factor that influences the level of technical inefficiency is the age of the farmer. The age of the farmer has a significant impact on the level of inefficiency in grape cultivation activities. The recommendation from this research is that input subsidy programs, such as compost fertilizer, should continue to be provided to grape farmers. Comparative studies with other tourist villages should be conducted to obtain market information. Additionally, training programs for the young generation in grape cultivation should be implemented to maintain agrotourism.

The commitment to peak carbon emissions before 2030 and the goal of achieving carbon neutrality by 2060 have placed carbon emission efficiency (CEE) at the center of China’s low-carbon development strategy. Although national policies have promoted energy conservation and technological upgrading, substantial heterogeneity in CEE persists across cities of different administrative and economic tiers. To examine this heterogeneity, we construct a city-level CEE index based on a stochastic frontier analysis (SFA) framework that explicitly treats CO2 emissions as an undesirable output. Based on a panel dataset covering 274 prefecture-level cities grouped into five categories from 2006 to 2022, we find that first-tier cities such as Shanghai and Beijing, with advanced technological capacity and strong support by the emission trading scheme (ETS), have shown an upward trend in improving their CEE, while middle-range cities remain locked in carbon-intensive trajectories. In particular, the lowest-level fifth-tier cities show a decreasing trend, implying a bipolarization of urbanization among cities. To address this bipolarization by urbanization, we examine the governance mechanisms of CEE using a second-stage Tobit model and find that governance factors related to urbanization—such as high labor quality and intensive land development in larger cities—have contributed to the widening gap in CEE. This implies that mitigating the negative consequences of urbanization is essential for achieving a carbon-neutral economy.

Background: Yak herding is a traditional livelihood practiced in the high-altitude regions of Arunachal Pradesh, India, where yak milk serves as a vital source of nutrition and income for pastoral communities. Given the challenging terrain, limited resources and changing climatic and market conditions, assessing the technical efficiency of yak milk production is essential to enhance productivity and improve livelihoods. Methods: This study employs a Cobb-Douglas stochastic frontier production function to estimate the technical efficiency of 233 yak herders from Tawang and West Kameng districts. Primary data were collected through structured interviews and key input variables included herd size, green and dry fodder, mineral mix and labour hours. Result: The results revealed that inputs such as herd size, green fodder, dry fodder and concentrates significantly influenced milk yield, while labour input had an insignificant effect. The mean technical efficiency of the sample was estimated at 87.52%, with room for improvement of 12.48% through better input management. Efficiency levels varied across farm sizes and geographic circles, with large herders and those in the Thingbu circle achieving the highest efficiency scores. These findings suggest the need for targeted interventions to enhance productivity and support sustainable yak herding systems in the Eastern Himalayas.

This study explores the intellectual landscape and methodological evolution of Data Envelopment Analysis (DEA) in the context of renewable energy and carbon emission efficiency. Using bibliometric techniques and data extracted from the Web of Science Core Collection (2389 publications from 2000 to 2024), the research identifies influential authors, institutions, and thematic clusters shaping the field. The results reveal that DEA has evolved from a traditional efficiency assessment tool into a comprehensive analytical framework supporting sustainable energy transition and carbon mitigation policies. Six major research clusters were identified, encompassing carbon emission measurement, efficiency benchmarking, methodological innovations, industrial applications, circular economy perspectives, and international productivity comparisons. Notably, Asian scholars, particularly from China and Taiwan, dominate the research landscape, reflecting strong regional leadership in empirical and methodological advancements. The findings demonstrate that recent studies increasingly adopt advanced models such as network DEA, dynamic DEA, DEA–Malmquist, and hybrid DEA–machine learning approaches to address complex energy systems. Comparative insights highlight DEA’s advantages over Stochastic Frontier Analysis (SFA) in handling multi-dimensional, non-parametric data, while emphasizing the need for hybrid frameworks to improve robustness. This study contributes to the ongoing discourse on energy sustainability by mapping knowledge structures, revealing methodological trajectories, and providing guidance for future research on efficiency and carbon reduction strategies.

ABSTRACT The use of digital tools in farm management is increasing in developing countries, yet their effects on production, technology, and managerial performance remain underexplored. This study evaluates the impacts of RiceAdvice, a decision‐support mobile app that provides personalized recommendations to rice farmers. Using a four‐period experimental panel dataset from northern Nigeria, we estimate impacts on technology, technical efficiency, and frontier yields across a control group, a group receiving recommendations only, and a group receiving recommendations plus fertilizer. Results from panel stochastic production frontier models and analysis of covariance estimations show that RiceAdvice improves productivity by enhancing both access to improved practices and managerial performance. Gains are especially large and consistently significant when advisory services are bundled with fertilizer, while effects of the recommendation‐only intervention are more fragile under attrition, as revealed by Lee bounds analysis. Productivity gains peaked in the second year before tapering off, highlighting potential sustainability challenges without continued support. Overall, the findings suggest that sustained access to RiceAdvice, especially when complemented with fertilizer, can strengthen managerial performance and raise productivity among smallholder rice farmers.

Purpose This study investigates performance differences among various types of investment entities in Japan’s asset management industry – specifically domestic financial institutions, foreign financial institutions and independent firms – focusing on the operational realities that remain largely underexplored in academic research. Design/methodology/approach The study employs a stochastic frontier analysis based on input distance functions to assess efficiency and economies of scale across different types of asset management companies. Findings Small, independent asset management firms not affiliated with financial institutions tend to exhibit higher efficiency and stronger economies of scale, whereas firms established by foreign financial institutions demonstrate relatively lower performance. Practical implications The findings challenge the dominance of subsidiaries of major domestic financial institutions in Japan's asset management industry by highlighting the competitive advantages of smaller, independent firms. They suggest a need for policy and strategic shifts to foster a more diverse and efficient asset management ecosystem. Originality/value By examining efficiency across different ownership structures, this study challenges the prevailing dominance of subsidiaries affiliated with major domestic financial groups in Japan. The results contribute to the literature on organizational efficiency in financial services and provide insights for aligning performance management practices with ownership structures, offering implications for both theory and managerial practice.

Sustainability initiatives have gained significant attention; however, limited research has examined whether ESG factors facilitate or hinder financial sector efficiency. This research investigates the differences between the traditional stochastic frontier analysis (SFA) and the ESG-integrated SFA model in explaining inefficiency. In addition, it examines how ESG factors influence inefficiencies in a truncated regression. The sample includes 9 banks (4 Islamic and 5 commercial) and 11 financial firms—all the ESG adopters in Kuwait financial sector. Quarterly data were employed from 2018 to 2023. The findings revealed that the ESG-integrated model improves the explanatory power of the cost function, partially reducing stochastic noise in financial operations. Moreover, ESG facilitates lending consistently and reduces the marginal cost of non-interest activities. Nonetheless, capital reliance in both models is associated with higher inefficiencies. Additionally, we found that financial institutions on average operate at 33% below the best-practice technology frontier, indicating moderate gaps across the sector. Overall, strong ESG alignment is associated with improved cost-efficiency when supported by strong institutional quality.

The sudden expansion in financial technology (FinTech) has altered conventional banking immensely by transforming operations, customer services, and risk management systems. This research therefore employs a systematic literature review (SLR) approach that adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards to assess the influence of FinTech on three bank performance indicators: operating efficiency, risk management, and customer service. A total of 41 peer-reviewed articles, published between 2018 and 2024, were shortlisted from Scopus and Web of Science (WoS). Out of these, 19 utilized frontier efficiency techniques like stochastic frontier analysis (SFA) and data envelopment analysis (DEA). The results indicate that FinTech improves operating efficiency when integrated optimally, as noted by Allen et al. (2022). Yet, outcomes differ by region and type of bank, as some Chinese banks have seen a decline in efficiency (Lee et al., 2023). In risk management, FinTech technologies such as artificial intelligence (AI) have been shown to decrease operational risk (Cheng & Qu, 2023). Customer satisfaction is enhanced further with digital services and personalization (Barbu et al., 2021). Although adoption poses additional risks, the research concludes that FinTech implementation, if managed strategically, will increase bank performance. This review thus offers actionable advice for policymakers and financial institutions to navigate digital transformation.

South Asia and Southeast Asia (SASEA) have exhibited overwhelmingly low intra-regional trade compared with other major regional groups such as the EU, NAFTA and Asia-Pacific Economic Cooperation (APEC). The present article attempts to understand the extent of trade potential between the economies of the SASEA, and it measures the loss of trade potential due to behind-the-border inefficiencies. The potential to trade is analysed with the help of the stochastic frontier gravity model (SFGM). The analysis indicates that there are substantial inefficiencies in bilateral trade among the economies of the SASEA. Following the method of Battese and Coelli, the technical efficiencies of bilateral trade have also been calculated. The comparison results indicate that the bilateral technical efficiencies within the region have been falling over the last 30 years. The article further estimates the SFGM for relatively important factors determining the bilateral trade. Noteworthy findings indicate that population has a negative effect on bilateral trade. At the same time, common religion registers as one of the essential variables for higher trade performance, along with common culture and language. The trends in trade creation or diversion are studied by extending the analysis over the three decades. The gravity analysis indicates that the region registered patterns of trade creation in the 1990s and 2000s. However, during 2010s, a significant trend of trade diversion was identified. This article attempts to make a case for increasing commitment to multilateral reduction in trade barriers among the SASEA countries and the eventual creation of a highly integrated trading bloc. JEL Codes: F02, F14, F15

This paper suggests a theoretical model (a production function) and an empirical model (Stochastic Frontier Analysis) to empirically evaluate the main impacts of socio-cultural contexts on the effectiveness of some sport policies and to address some main methodological problems of sport sociology. As for methods, I identified 2 governmental ethics to and through sport (national pride NP, social cohesion SC), by measuring achievements in terms of alternative indexes based on Olympic medals (gold, total) from 1994 to 2024. I applied panel-data, by focusing on 4 alternative estimations (individual and collective variables for both NP and SC). I introduced 2 sport policies (a quantitative policy aimed at SC, a qualitative policy aimed at NP), by distinguishing cultural approaches to body in terms of 5 different secular ethics (Aristotle, Husserl, Deleuze, Heidegger, Descartes) and 5 different religious ethics (Buddhism, Christianism, Hinduism, Islam, Judaism). I referred to income level and income inequality (i.e., GDP and Gini index), to depict alternative social contexts. I applied country dummies, to represent alternative historical and institutional contexts. As for results, if governments pursue SC, there is significant consonance with more communitarian religions and dissonance with more individualistic religions (to a greater extent at a collective level), whereas religions do not affect the effectiveness of sport policies if governments pursue NP. If governments pursue NP, there is significant consonance with secular body approaches deemphasising mind over body (at an individual level only), whereas if governments pursue SC, there is significant consonance with Deleuze, Heidegger and Descartes and dissonance with Husserl (to a smaller extent at a collective level). In summary, this paper empirically highlights the social and cultural contexts affecting some sport policies, by providing a quantitative methodology to identify groups of countries with institutional or historical peculiarities, to be studied by sport sociology with complementary qualitative methodologies.

Firm-level productivity analysis serves as a cornerstone for understanding the micro-foundations of economic growth, industrial competitiveness, and efficient resource allocation. This comprehensive review synthesizes and critically evaluates the primary statistical and econometric methodologies employed in the measurement and analysis of productivity at the firm level. We systematically delineate the evolution from traditional parametric techniques, such as production function estimation and Stochastic Frontier Analysis (SFA), to non-parametric approaches, including Data Envelopment Analysis (DEA) and the Malmquist Productivity Index. A significant focus is placed on addressing pervasive micro-level challenges, notably firm heterogeneity, measurement error, and endogeneity biases, which are endemic to firm-level data. The paper further explores recent methodological innovations, highlighting the integration of machine learning, quantile regression, and network analysis into the productivity research arsenal. By providing a structured guide for selecting and applying appropriate statistical tools, this review aims to equip researchers with the knowledge to conduct robust micro-level productivity analyses. Finally, we outline promising future research trajectories, emphasizing the potential of novel data sources and computational methods to deepen our understanding of productivity determinants.

This paper analyses the dynamics of performance of Russian banks from 2012 to 2021. To assess the efficiency of financial institutions, the authors used parametric Stochastic Frontier Analysis (SFA) method. The study examines various aspects of bank operations, including lending, deposit-taking, and cost management. For an in-depth analysis and to obtain estimates from more homogeneous samples, all banks were divided into five groups based on asset size. The efficiency models were estimated separately for each group and for each year, enabling the tracking of changes both across groups and over time. The study’s key conclusion is that an overall decline in banking efficiency was observed over the period under review. This fact may be linked to the dynamics of the key interest rate, specifically to the periods of monetary policy easing (during times of higher interest rates, banks are forced to operate with greater efficiency). Only the group of the five largest banks managed to maintain their deposit-taking efficiency, which is likely due to their high level of customer trust and these institutions’ relatively easier access to retail funds. Cost management efficiency was generally found to be higher, with the largest banks demonstrating the most successful performance. The findings of the study and the resulting estimates can be valuable for both government bodies providing banking supervision and regulation, and for the banks themselves and their counterparties.