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In India, the operational performance of the refinery is influenced by many factors. It is important to identify those key drivers which can assist the refineries to uphold and succeed in day-to-day production activities. Therefore, the purpose of this study is to evaluate the operational efficiency of seven Indian oil refineries during the period 2010 to 2018.

In this work, a two-stage empirical analysis is proposed. In the first stage, the data envelopment analysis (DEA) – variable return to scale model is used to evaluate the operational efficiency of the Indian oil refineries. The ordinary least square (OLS), random effect generalized least square (GLS) and Tobit model are used in the second stage to identify the key determinants of efficiency and to explain the variation in refinery efficiency.

The first-stage DEA results showed that the Numaligarh Refinery Limited and Chennai Petroleum Corporation Limited are found to be more efficient than the rest of the sampled refineries and attained their efficiency scores of 0.993 and 0.981, respectively, during the study period. The second-stage regression analysis suggested three explanatory variables: refinery structure, utilization rate and distillate yield, which are found to be significant in explaining variations in refinery efficiency.

This study provides valuable information that would help policymakers to formulate policies toward improving the efficiency of underperforming Indian refineries, which reduces the excessive use of resources and gives a competitive advantage.

This study proposes the first-ever application of the profit frontier DEA model for assessing the operational efficiency of oil refineries and explains the variation in refinery’s efficiency using OLS, GLS as well as the Tobit model.

This study aims at evaluating the technical efficiency (TE) of healthcare systems in the Arab region and exploring the key factors that affect the efficiency performance.

The study applies a two-stage Data Envelopment Analysis (DEA) approach to a sample of 20 Arab countries. In the first stage, a DEA model is used to calculate the TE scores of the examined healthcare systems in 2019 and 2010, following both the output and input orientations of efficiency. In the second stage, a censored Tobit model is estimated to investigate the determinants of healthcare efficiency.

DEA results of 2019 indicate that achievable efficiency gains of the Arab countries range from 0.4% to 16% under the output and input orientations, respectively. Six countries are efficient under both orientations. Although the average efficiency scores of the Arab countries have deteriorated between 2010 and 2019, Djibouti and Sudan had the greatest efficiency improvements between the two years. Bahrain, Mauritania, Morocco and Qatar proved to be efficient in 2010 and 2019 under the two orientations of efficiency and according to the two DEA specifications followed. The Tobit model reveals that corruption and government health expenditure tend to have an adverse impact on healthcare efficiency.

The author evaluates healthcare efficiency and healthcare's efficiency determinants in the Arab countries. Regardless Arab countries' diversity, these countries are facing common health challenges, including diminishing role of governments in healthcare financing; increased out-of-pocket healthcare spending; poor healthcare outputs and prevalence of health inequities resulting from weak governance institutions. Comparing the efficiency of healthcare systems between 2010 and 2019 gives insights on the potential impact of the Arab spring uprisings on healthcare efficiency. Moreover, examining the determinants of healthcare efficiency allows for better understanding of how to improve the efficiency of healthcare systems in the region.

The authors investigated cocoa farmers' access to subsidized fertilizer in Ghana and implications on productivity.

Primary data were sourced from 435 cocoa farmers. Cragg hurdle and two-step Tobit model with continuous endogenous regressors/covariates were applied for the drivers of cocoa farmers' participation in fertilizer subsidy programme and productivity. Propensity score matching (PSM), inverse-probability weights (IPW) and augmented inverse-probability weights (AIPW) were applied for productivity impact assessment of fertilizer subsidy.

All the farmers were aware of fertilizer subsidy for cocoa production in Ghana. Farmers became aware of fertilizer subsidy through extension officers, media and other farmers. Half of cocoa farmers benefitted from fertilizer subsidy. Averagely, cocoa farmers purchased 292 kg of subsidized fertilizer. Many socio-economic, farm-level characteristics and institutional factors determine cocoa farmers' participation in fertilizer subsidy programme, quantity of subsidized fertilizer obtained and productivity. Beneficiaries of fertilizer subsidy recorded higher cocoa productivity than non-beneficiaries. Hence, fertilizer subsidy for cocoa production in Ghana leads to a gain in productivity.

There should be more investments in fertilizer subsidy so that all cocoa farmers benefit and obtain the required quantities.

The authors provide new evidence on cocoa productivity gain or loss emanating from fertilizer subsidy by combining different impact assessment techniques for deeper analysis: PSM, IPW and AIPW.

The purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.

The research method is a quantitative modeling. The main research techniques are data envelopment analysis, TOBIT regression and simulation supported by artificial neural networks. The model’s input and output variables consist of the average billet weight, number of billets processed in a batch, gas consumption, thermal efficiency, backlog and production yield within a specific period. The analysis spans 20 months.

The key findings include an average current efficiency of 81%, identification of influential variables (average billet weight, billet count and gas consumption) and simulated analysis. Among the simulated scenarios, the most promising achieved an average efficiency of 95% through increased equipment availability and billet size.

Additional favorable simulated scenarios entail the utilization of higher pre-reheating temperatures for cold billets, representing a large amount of savings in gas consumption and a reduction in CO2 emissions.

This study’s primary innovation lies in providing steelmaking practitioners with a systematic approach to evaluating and enhancing the efficiency of reheating processes.

This paper aims to investigate the performance of OECD countries' long-term productivity during the period of 1975–2018.

This study employed different approaches to evaluate how efficiency scores vary with changes in inputs and outputs: Data Envelopment Analysis (CRS, VRS and FDH), TOPSIS and TOPSIS of these scores.

The findings suggest that, during the period of this study, countries with higher freedom of religion and with Presidential democracy regimes are positively associated with higher productivity.

To the best of the authors’ knowledge, this is the first study that uses efficiency models to assess the productivity levels of OECD countries based on several contextual variables that can potentially affect it.

In view of the increasing trend in food policies targeting the promotion of consumer interest in locally produced foods and growing developments in willingness-to-pay (WTP) methodologies, the authors investigate consumer preference for packaged traditional drink asaana.

The study used a simple random sample of 336 consumers to draw on perception index and contingent valuation methods to evaluate consumers' perceptions of the attributes of packaged asaana – a traditional maize-based beverage produced in Ghana (also known as Ghana Coca-Cola). A tobit regression model was employed to analyze consumers’ WTP for the product.

Analyzing the factors that influence consumers' WTP for packaged asaana using the tobit regression model, the study established the existence of positive health and nutrition, economic benefits and purchasing decision-making perceptions for asaana. While the results further showed that consumers are willing to pay a premium for well-packaged asaana, demographics such as age, income level, labeling, price of the product and savings were found to exert significant influence on consumers’ WTP for packaged asaana. Salient recommendations for food processors and relevant government agencies and food policy implications are identified.

Comprehending WTP provides valuable understanding regarding consumer qualms, actions and WTP for more secure traditional drinks and an examination of how the different factors that influence WTP for local beverages help boost local beverage production and guarantee employment.

Analyzing WTP data for traditional drinks reveals important implications for production, marketing and public health policies. Certification systems for traditional beverages may be beneficial, and the findings can be used to create public awareness campaigns about the safety of local drinks.

Assessing the WTP among Ghanaian consumers for traditional drinks, specifically asaana, is a ground-breaking study. The contingent evaluation (CE) and tobit regression approaches utilized in this research are strong, and the results obtained can guide decisions related to traditional drink production, marketing and the development of public health policies.

Outgrower scheme as a contractual agreement between farmers and some funding entities has in recent times found proliferation among resource poor farmers in Ghana, especially in northern Ghana. This contractual arrangement, which involves the provision of farm inputs, and in some cases, technical support by the implementing company and the repayment by farmers with portions of their harvest, is often regarded as an effective way to mutually improve the outcomes of both smallholder farmers and outgrower companies. The study aims to analyse. the level of awareness, nature of input package, determinants of participation and intensity of participation in input credit scheme by smallholder rice farmers in the Mamprugu Moagduri District of Ghana’s North East Region, using the Integrated Water Management and Agriculture Development (IWAD) scheme as a case.

Using a quantitative analytical approach, the study gathers information from 233 randomly selected smallholder rice farmers consisting of 150 participants and 83 non-participants using a structured questionnaire. Descriptive statistics, as well as the Tobit model, are the methods used in the analysis.

The results show that while factors such as age, marital status, number of dependents and farming experience only influenced participation in the scheme, religion, age, sex, number of dependents and farming experience influenced intensity of participation.

This study calls for the adoption of sustainable approaches by input credit companies in their credit support to smallholder farmers rather than the current ad hoc support during each cropping season.

This study investigates the effect of intellectual capital (IC) and its components on the technical efficiency of Indian commercial banks after controlling the influence of bank-specific and macroeconomic variables.

The study selects a sample of 37 listed Indian commercial banks from 2005 to 2019 and uses the two-step data envelopment analysis (DEA) approach. Banks' technical efficiency scores are first estimated, while the relationship between IC and technical efficiency is examined in the second stage using the panel data Tobit model.

This study's findings suggest a fluctuating trend in the technical efficiency of Indian banks. Notably, from 2015 onwards, a declining technical efficiency trend is observed for all banks. However, private-sector banks outperform public-sector banks in terms of technical efficiency. This study's regression analysis indicates a positive relationship between IC and banks' technical efficiency scores. Further, by decomposing IC into its components like human capital, structural capital and capital employed, the study's findings show that human capital and structural capital enhance banks' technical efficiency. Notably, capital employed reduces technical efficiency. Moreover, bank size, diversification, capitalization, net interest margin and the country's growth rate significantly drive Indian banks' efficiency. In contrast, their operating cost ratio and the country's inflation negatively influence the same.

This study makes a novel endeavor to examine the IC and bank's technical efficiency nexus in the Indian context, encompassing a period of landmark banking reforms.

With the rapid development of the economy in China, the wealth of residents has continued to increase, and most families have gradually been aware of the importance of commercial insurance. The family purchase of insurance in China was still not optimistic. Many scholars focus on wealth allocation, but the attention to the commercial insurance market was still less. Based on previous research studies, this study aims to investigate the impact of education and financial literacy on the commercial insurance purchase in China.

China Household Finance Survey data was used to investigate the purchase of commercial insurance in Mainland Chinese families. Factor analysis was used to construct financial literacy, and the education data were combined to analyze the commercial insurance purchase using the Probit model and the Tobit model. Finally, the contributions of education and financial literacy to commercial insurance purchases were analyzed.

Both education and financial literacy exerted a positive impact on the purchase of commercial insurance in China. Individual characteristics such as gender, age, marital status, risk attitude, purchase of social insurance and consultation with a financial advisor possessed significant effects; household factors like household size and assets, macro factors such as the density of financial institutions and the density of financial industry staff, and regional factors as local unemployment rate excreted influences on the commercial insurance purchase.

Based on the current economic development in China, this study investigated and expressed opinions on the public and insurance companies regarding commercial insurance purchases. It accentuated financial literacy and education as factors that facilitated commercial insurance development.

The Indian Companies Act (2013) mandates the appointment of at least one woman director for large publicly listed companies in India in order to increase gender diversity on corporate boards. The study analyzes the relationship between corporate governance mechanisms, board gender diversity, and ownership structure on dividend payout decisions in an emerging economy like India. The study uses data collected for nonfinancial firms listed on NSE (National Stock Exchange) 500 in India from the period 2008 to 2020. Contrary to the evidence from developed economies, the study finds that increased female representation and greater proportion of female independent directors on the board are associated with lower dividend payout decisions in the Indian context. As it stands, the female representation on corporate boards in India is woefully low and appears to be mere tokenism. The study explores the role of regulation in increasing gender diversity on corporate boards and offers insights from an emerging economy where such a regulation is in place.