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The purpose of this paper is to investigate the relationship between total quality management (TQM) practices and banks’ technical efficiency.

A survey questionnaire was constructed to measure TQM practices and quantitative data were collected to measure banks’ technical efficiency. The respondents were required to indicate their degree of implementation of quality management practices in the survey instrument. Organizational performance was indicated by quantitatively measuring banks’ technical efficiency using data envelopment methodology.

The study found that there is a relationship between TQM practices and organizational performance, as measured by banks’ technical efficiency. Furthermore, the TQM practices of human resources management and technical systems would appear to be important practices in impacting banks’ technical efficiency.

This study only considered commercial banks registered in the first market of Amman Stock Exchange due to quantitative data availability. Also, due to data envelopment analysis methodology of homogeneous, Islamic banks were excluded from the study. It can be argued, however, that the surrogating of different organizational performance in one measurement such as technical efficiency and which TQM practices have the strongest impact on such a measure can offer possibly different facets of a single phenomena such as TQM.

Although research on the relationship was investigated by relating TQM practices and a single organizational performance, but no research have surrogated many organizational performance in one measurement such as technical efficiency.

The purpose of this paper is to examine the impact of agricultural credit on technical efficiency of Ghanaian maize farmers using a unique dataset drawn from the database of Sub-Saharan Africa’s intensification of food crops agriculture (Afrint II) in 2008 period.

In this study, a two-stage estimation procedure is employed to determine impact of agricultural credit on technical efficiency of Ghanaian maize farmers. The first stage utilized probit model while the second stage utilized stochastic frontier approach to estimate impact of credit on technical efficiency of Ghanaian maize farmers.

The study found that farmers are producing below the frontier with average technical efficiency of 47 percent. Policy variables such as credit access; education, extension access and farm size played a stronger role in technical efficiency. Agricultural credit in particular increased technical efficiency by 3.8 percent.

The results should not be extended to the impact of agricultural credit on economic efficiency since the allocative efficiency component is not considered in this study. Also, caution should be taken in the interpretation of these results because the data could not permit the incorporation of all variables that might affect technical efficiency.

The originality of the paper and its contribution to existing literature largely lies from the use of a unique dataset to find evidence of the impact of credit on efficiency in Ghana.

The purpose of this paper is to examine the technical efficiency of wheat and paddy rice processing in China. Understanding the level of technical efficiency of food processing helps to decide whether efforts are warranted to improve this efficiency. Studies on China's technical efficiency of flour and rice processing are scarce. This paper fills this gap.

With a unique set of firm‐level survey data collected by China's State Statistical Bureau, this study adopts a stochastic frontier model to investigate the technical efficiency of flour and rice processing.

The technical efficiency for both flour and rice processing is low in China, being only about 50 per cent. On average, rice processing firms have slightly higher technical efficiency than flour processing firms. It is also found that a significant proportion of firms experienced negative growth of technical efficiency during the time period of investigation.

Each year, some 300 million tonnes of wheat and paddy rice are processed in China. Any small improvement in technical efficiency is translated into huge economic gains. Further, a tiny improvement in flour or rice output rate is equivalent to an enormous increase in food supply, contributing to China's food security. The paper confirms the need and potential to raise technical efficiency in China for wheat and paddy rice processing.

The purpose of this paper is to estimate the degree of technical efficiency, determinants of technical inefficiencies and driving forces behind the production growth for a panel data set collected during the 1998/1999 and 2004/2006 Kharif cropping season, from 452 small-scale rice farming households in the Giridih and Purulia districts of Eastern India.

The estimations of technical efficiency utilize stochastic frontier production function with a sub-model of inefficiency effects at both aggregated farm level and disaggregated plot level where traditional varieties (TVs) and high-yielding varieties (HYVs) are differentiated. The output growth decomposition analysis identifies the main contributor to the total rice production growth.

The results indicate that the sampled farms are operated at moderate levels of technical efficiency. The production of HYV rice is associated with higher technical efficiency compared to TV rice. Farming experience, education attainment, landholding size, the share of non-agricultural income and the share of land in the lower terraces account for the differences in technical inefficiencies across the sampled farms. The decomposition analysis suggests that as technical efficiency decreased, technical change is the main source of production growth during the survey period.

The small sample size applied in the analysis will result in an insufficient representativeness of the study area.

This paper fills the literature gap as estimations of technical efficiency that account for subtle differences in adopted rice varieties are still rare in India.

The purpose of this paper is to evaluate the effects of access to formal credit on rural household technical efficiency in China.

Based on the rural household survey data in Weifang city, Shandong province in northern China, the authors apply recent developed bootstrapped DEA approach to investigate rural technical efficiency at the household level under the consideration of off-farm activities. Rural households are then identified as credit constrained and classified as supply-side and demand-side credit constraints by applying direct elicitation method. Finally, the authors apply a tobit regression to examine the effects of credit constraints on household technical efficiency.

Rural households in China not only suffer supply-side credit constraints, but also demand-side credit constraints resulted from the transaction costs and risk rationing. The tobit regression discloses that demand-side credit constraints impose significant negative impacts on household technical efficiency.

The authors clarify the definition of credit constraints and classify the credit constraints into supply-side and demand-side credit constraints. The results of this paper have significant policy implications for rural finance policies in China.

The development of green manufacturing has become essential to achieve sustainable development and modernize the nation’s manufacturing and production capacity without increasing nonrenewable resource consumption and pollution. This study investigates the effect of green industrial practices on technical efficiency for Thai manufacturers.

The study uses stochastic frontier analysis (SFA) to estimate the stochastic frontier production function (SFPF) and inefficiency effects model, as pioneered by Battese and Coelli (1995).

This study shows that, on average, Thai manufacturing firms have experienced declining returns-to-scale production and relatively low technical efficiency. However, it is estimated that Thai manufacturing firms with a green commitment obtained the highest technical efficiency, followed by those with green activity, green systems and green culture levels, compared to those without any commitment to green manufacturing practices. Finally, internationalization and skill development can significantly improve technical efficiency.

Green industry policy mixes will be vital for driving structural reforms toward a more environmentally friendly and sustainable economic system. Furthermore, circular economy processes can promote firms' production efficiency and resource use.

To the best of the authors' knowledge, this study is the first to investigate the effect of green industry practices on the technical efficiency of Thai manufacturing enterprises. This study also encompasses analyses of the roles of internationalization, innovation and skill development.

This study examines the performance of India's food processing sector by estimating its output growth, technical efficiency (TE) and input-driven growth (IDG)

This study used panel data from six food processing manufacturing industries for the period 2000–01 to 2017–18. Technical efficiency and input-driven growth was measured using the parametric half-normal stochastic frontier production function.

The findings of this study showed that the estimated average technical efficiency is 86.6%, which specifies that the Indian food processing sector is technically inefficient. In addition, the output growth rate is 5.5%, driven by high doses of inputs (5.7%), whereas there is no indication of constant returns to scale. However, the food processing sector has experienced more input-driven expansion than either technological or efficiency changes.

This study is limited to India's organized manufacturing food processing sector; the aggregate macro data at a three-digit level based on the national industrial classification (NIC) was used. This study provides robust estimates for industrialists and processors, as well as concrete policy formulations on how overdoses of inputs may lead to high exploitation of resources, whereas outputs can be augmented by implementing upgraded and new technologies.

Previous research has estimated the total factor productivity and technical efficiency only in order to analyze the food sector's performance, but none of the studies have evaluated the share of inputs in growth performance and efficiency. Therefore, this study contributes by measuring growth performance and the share of inputs in the growth performance of India's food processing sector.

The purpose of this paper is to develop a decision-making protocol to meet the new requirements in an atypical panorama, such as the economic instability, in the textile industry.

The methodology consists of analyzing technical criteria, costing parameters and efficiency scores of knitted fabrics using the data envelopment analysis (DEA) and classification and regression (C&R) trees models, together with statistical techniques. From these tools, it is possible to guide the portfolio management of these products in a textile company, identifying those that are inefficient and require immediate management measures. The results are expected to be replicated in other companies because the DEA and C&R trees analytical procedures are applicable to different portfolios, whether in the same industry or not.

The results allowed identifying inefficient textile products regarding the input-output relationship and the main technical reasons related to the most significant inefficiencies, such as fiber composition and knitted fabrics rapports used in manufacturing.

DEA and C&R trees, in combination with the study of textile technical parameters, can be fundamental to investigating the efficiency and profitability of industries in periods of economic instability or other adverse situations. In addition, it is noteworthy that there are practically no studies in the literature on DEA applied in the textile industry, indicating excellent development potential.

This paper aims to reflect on the sources of the technical inefficiency of health care foodservice operations, using a sample of Australian and American hospitals.

The paper applies the stochastic frontier model to reflect on the technical inefficiency and its sources. The advantage of the model is that it allows the simultaneous parameters estimation of technical efficiency as well as the factors that explain variations in technical efficiency. A set of hypotheses are tested to ensure the applicability and suitability of the suggested model. Then the model parameters are estimated, discussed and checked against the theoretical requirements and the literature.

Results show that all the variable coefficients are correctly signed and that the average technical efficiency is around 83 percent for Australia and 80 percent for the USA.

The technical efficiency results, according to the introduced model, suggest that health care foodservice operations in both countries are not operating at a full efficient level. The results also reveal that factors such as manager's education, manager's experience, and size have a direct impact on reducing the level of technical inefficiency of these operations.

This paper overcomes the limitations of the existing efficiency techniques in the area of health care foodservice and also provides policy implications by emphasizing on the sources of technical inefficiency of health care foodservice operations for Australia and USA.

Does MFIs agricultural credit influence the determinants of the efficiency of SFF which are socio-economic factors of the farmers but also agricultural endowments of family farms? This paper aims to study the contribution of MFI services on improving the technical efficiency of SFFs in Cameroon.

The stochastic frontier analysis (SFA) model permits the estimation of the technical efficiency indicators for beneficiaries and nonbeneficiaries of agricultural credits on a sample of 130 cocoa farming households and four MFIs of the same area between 2008 and 2011. The censored tobit model is used to assess the determinants of technical efficiency.

The results show that the SFF beneficiaries of agricultural credit have an average technical efficiency of 0.68 inferior to that of nonbeneficiaries (0.72) as expected. They are, respectively, at 0.32 and 0.28 of their full productive capacities. The results of the censored Tobit model show that socioeconomic characteristics of the producer such as age and gender explain negatively, while experience explains positively the technical efficiency of SFFs.

Although without any selectivity bias, this study indicates the essential character of the socioeconomic factors in the amplification of the role of the MFIs credit on the efficiency of SFFs.

Strategies to improve the efficiency of SFFs require an increase in MFI credits, primarily targeting young, experienced and female farmers.

This study examines the efficiency of SFFs by highlighting the interaction between the socio-economic factors of farmers and the credit of MFIs. It also points to the problem of monitoring the implementation of agricultural financing.