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The purpose of this paper is to compare technical efficiency and metatechnology ratios (MTR) in three production systems confronted with different technological and resource endowments in Bangladesh to identify the suitable production systems for increasing productivity.

The primary data collected by authors from 180 dairy farmers were sampled and modeled in a stochastic metafrontier framework due to its ability to estimate and compare the efficiency of firms among various groups with possibly different group-specific technologies and heterogeneous production environments.

The empirical results show that farms from intensive system were closer to their production frontier than extensive and traditional system. Regarding productivity differences among systems, the MTR is by far highest for intensive, indicating the technological advantage of this system over others two systems. The estimation of farm-specific inefficiency model revealed that farmers’ access to extension and credit services are assumed to be significant determinants in reducing inefficiency.

This study concludes that the ability of the farmers to increase productivity vary depending on the production systems due to variation in resource endowments and access to various inputs and support services. Thus, improving productivity depends on effective policy design on harmonizing access to resources and delivery of extension and credit services.

The empirical analysis of data representing different production endowments by stochastic metafrontier make it possible to identify the efficiency level as well as technology gap, thus, ways to identify the possible policy options reducing those gaps and improving productivity.

The purpose of this study is threefold: to use an innovative metafrontier‐to‐data‐envelopment analysis (MDEA) model incorporating multiple outputs and inputs – including the item revenue, gross profit, food costs, time‐driven labor costs, and other operating expenses (OOEs) – to distinguish four quadrants based on efficiency and profit to offer different strategies to the restaurateur under study; to compare the proficiency levels of the different meal categories of the à la carte and combo set menus using the metatechnology ratio (MTR) via the MDEA; and to use slack‐based analyses with simulation to improve the financial performance of a teppanyaki‐style restaurant.

Six months of point of sale (POS) data are obtained from a teppanyaki‐style restaurant. The proposed inputs are categorized into total food costs, total labor cost, the number of processes, and OOEs. Two outputs (total revenue and gross profit) are used to assess the efficiency of the menu items. The MTR is used to differentiate the proficiency level of the heterogeneous meal categories and to create four quadrants based on the efficiency index and financial performance.

The MTR is lower for the combo set category than for the à la carte category. Four quadrants are obtained based on the efficiency and financial performance to provide further menu suggestions. The MDEA analysis yields menu suggestions that could enhance the overall efficiency and profitability of the menu items. A simulation using these two models is conducted and shows that the restaurant profitability would be 22 percent greater using the MDEA than using the menu engineering model.

Because there are no publicly listed teppanyaki‐style restaurants in Taiwan and it is difficult to find the same menu in different restaurants, this study consists of only a single restaurant, and the results may not be generalizable to other types of restaurants.

This paper contributes to menu analysis by establishing an efficiency index and using financial performance as criteria for determining which menu items to improve in a teppanyaki‐style restaurant. The MTR of the metafrontier model can differentiate the proficiency level of the heterogeneous categories, such as à la carte and combo set menus. This paper offers empirical results pertaining to the classification of menu items and describes a slack‐based analysis for improving menu items.

This paper aims to investigate the efficiency implications of belonging to a strategic hospital alliance (SHA) and measuring the effects over capacity utilization of such agreements in a Mexican healthcare context.

Data Envelopment Analysis (DEA) is the nonparametric methodology used, which supports both objectives. Technological gaps ratios are calculated by using DEA-metafrontier approach to compare efficiency between SHA members and a hospital’s control group. Also, hospital capacity utilization ratios are used as the maximum rate of output possible from fixed inputs in a frontier setting using directional distance functions. Data were collected from an alliance called Consorcio Mexicano de Hospitales in México, which has 29 general private hospitals and a group of 47 hospitals with same characteristics from a database made by the Instituto Nacional de Estadística y Geografía for year 2014.

The results indicate that efficiency is better at hospitals that belong to an alliance; it also shows an improvement of installed capacity management for hospital alliances in México.

The results can be useful for both private health organization managers and regulators themselves to adopt management practices that may end up having a favorable impact on cost and prices containment. Additionally, there are no previous studies neither in Mexico nor in Latin America that analyze the impact of strategic hospitality alliances on the efficiency and utilization of the capacity of private hospitals.

Este documento tiene como objetivo investigar las implicaciones de pertenecer a una alianza hospitalaria estratégica (AHE) en la eficiencia, así como cuantificar los efectos sobre la utilización de la capacidad de dichos acuerdos en el contexto mexicano de atención médica.

El Análisis Envolvente de Datos (DEA) es la metodología no paramétrica utilizada para lograr ambos objetivos. Las brechas tecnológicas se estiman empleando meta-fronteras calculadas mediante modelos DEA, comparando la eficiencia entre los miembros de la AHE y un grupo de control de hospitales. El nivel de utilización de la capacidad hospitalaria se calcula, utilizando funciones direccionales de distancia, a partir del máximo output alcanzable a partir de la dotación de inputs fijos. Los datos fueron obtenidos de la alianza Consorcio Mexicano de Hospitales en México, integrada por 29 hospitales privados generales, y de un grupo de 47 hospitales con las mismas características obtenidos de una base de datos del Instituto Nacional de Estadística y Geografía para el año 2014.

adosLos resultados indican que los niveles de eficiencia son superiores en los hospitales pertenecientes a la alianza, así como una mejor gestión de la capacidad instalada en la alianza hospitalaria en México.

Los resultados pueden ser útiles tanto para los administradores de las organizaciones de salud privadas como para los reguladores, de forma que puedan adoptar prácticas de gestión con un impacto favorable en la contención de costos y precios. Asimismo, no existen estudios previos ni en México ni en América Latina que analicen el impacto de las alianzas estratégicas hospitalarias en la eficiencia y la utilización de la capacidad de los hospitales privados.

The purpose of this paper is to analyze the efficiency of trade shows and provide insights for trade show exhibitors using data envelopment analysis (DEA). The paper also offers a benchmarking analysis of the business factors for the most efficient trade shows in each sector.

The paper uses the metafrontier DEA methodology and identifies several frontiers according to the sector in which the trade show operates since different sectors could not share homogeneous production technology for exhibitor firms.

The main findings reveal different profiles of individual sectors. The investment sector presents a more homogenous profile than either the consumer goods or the services sector. The consumer goods sector is more heterogeneous but it is also possible to find common characteristics for the most efficient trade shows. The service sector is characterized by a high variability and as such it is more difficult to identify benchmarking elements for the most efficient trade shows.

The main limitation of the study is that the sample only includes audited trade shows. Future studies could extend the period under study in order to obtain a more complete picture on the evolution of trade show efficiency.

This paper extends the DEA results by profiling the most efficient trade shows in each sector so that this information can be used as a benchmarking tool to define exhibitors’ strategic decision making.

The study measures the technology gap and performance of the Norwegian dairy farms accounting for farm heterogeneity.

The analysis was based on a meta-frontier and unbalanced farm-level panel data for 1991–2014 from 417 Norwegian farms specialized in dairy production in five regions of Norway.

The result of the analysis provides empirical evidence of regional differences in technical efficiencies, technological gap ratios (TGRs) and input use. Consequently, the paper provides some insights into policies to increase the efficiency of dairy production in the country across all regions.

The author used a meta-frontier approach for modeling regional differences based on a single-output production function specification. This approach has commonly been used in the economics literature since Battese et al. (2004). To get more informative and useful results, it would be necessary to repeat the analysis within terms of multiple input-output frameworks using, for instance, the input distance function approach. Moreover, the author estimated the meta-frontier using the non-parametric approach, thus it is also a need for further analysis if the values are different by estimating using a parametric approach.

One implication for farmers (and their advisers) is that dairy farms in all regions used available technology in the area sub-optimally. Thus, those lagging the best-performing farms need to look at the way the best-performing farmers are operating. Policymakers might reduce the gap is through training, including sharing information about relevant technologies from one area to another, provided that the technologies being shared fit the working environment of the lagging area. Moreover, some of the dairy technologies they use may not fit other regions, suggesting that agricultural policies that aim to encourage efficient dairy production, such as innovation of improved technology (like breeding, bull selection and improved feed varieties) through research and development, need to account the environmental differences between regions.

For both taxpayers and consumers, one implication is that the contributions they pay that go to subsidize dairy farmers appear to bring some benefits in terms of more efficient milk production that, in turn, increases the supply of some foods so possibly making food prices more affordable.

The paper contributes to the literature in several ways. In contrast to Battese et al. (2004), the author accounts for farm-level performance differences by applying the model devised by Greene (2005), thus may serve as a model for future studies at more local levels or of other industries. Moreover, the author is fortunate to able to use a large level farm-level panel data from 1991 to 2014.

This systematic literature review integrates the findings of existing studies regarding technical efficiency (TE) in dairy farms. The purpose of this paper is to offer a research framework that assembles TE descriptors, a classification of previous literature that provides the basis for the synthesis and research agenda.

This paper systematically reviews 86 survey research studies using rigorous and reproducible procedures. The review is applied to published survey research.

The framework relates context, inputs, outputs and metrics of TE. There is no agreement among the authors on the context and determinants of TE. The main determinants of TE are geographical location, farm size, investments in veterinary care, feeding and milking practice, TE model estimation techniques, public policy, and management-related variables. This paper offers ten propositions for future research on the controversial results on the determinants of TE. The authors also explore the reasons for the discrepant results based on the Debreu-Farrell’s definition of TE, the contingency theory and the resource-based view of the firm, elucidating the literature and serving as a basis for future investigation. Implications for dairy farmers and researchers close the review.

Meta-analysis and meta-regression studies were long at the forefront of reviews in the TE of dairy farms. This paper offers a novel qualitative research synthesis with frameworks and the classification of previous literature and a research agenda, which provides a new and different perspective for analysis, by innovating over the available quantitative procedures to combine statistical results.

The purpose of this paper is to examine the impact of agricultural cooperative membership on potato production and technical efficiency.

A combination of propensity score matching technique and sample selection stochastic frontier framework that addresses potential selection bias due to observable and unobservable attributes is used to estimate the effect of participation between cooperative members and non-members. Using a stochastic meta-frontier approach, the technical efficiency of farmers was estimated and compared.

The empirical results show that the effect of participation in agricultural cooperatives is associated with increased yield and technical efficiency. A comparison of group-specific frontiers indicates that cooperative members perform better than non-members. Cooperative membership decisions is significantly associated with household and farm characteristics (e.g. education, participation in off-farm work, total farmland, distance to market and geographic location).

The findings of this study demonstrate that cooperative organisations can be an important tool to enhance the productivity and efficiency of smallholder farmers. Successful cooperative models together with training programs designed to enlighten farmers on the importance and tangible benefits of collective action should be used to enlarge participation in cooperative organisations. In addition, governments and development agencies should implement targeted investment and capacity building programs related to irrigation management, gender-sensitive awareness and development of the internal institutional mechanisms in cooperatives for the transfer of knowledge and mutual learning so that all members benefit from cooperatives.

Despite the pervasive evidence of the impact of cooperatives on productivity and technical efficiency in the Asian region, this study is probably the first attempt in the crop sector in Mongolia. It provides a rigorous empirical analysis of the impact of agricultural cooperative membership on potato production and technical efficiency through a counterfactual design.

Based on the survey data of 650 kiwi growers from Shaanxi and Sichuan provinces, this paper used multiple endogenous transformation regression models to explore the effect of the joint adoption of green production technology on farmer’s welfare. The purpose of the study is to analyze the influence of green production technology on the yield, household income and socioeconomic characteristics of Kiwi fruit growers.

In the context of the study, multiple endogenous transformation model (MESR) are adopted, but self-actualization tactics were adopted to deal with the instrumental variables. The empirical data has been collected via a combined hierarchical sampling and random sampling, whereas a well-structured Likert scale questionnaire was adopted as well. The empirical data has been processed with the help of STATA 15.1 version.

The study found a positive impact of adopting green production technology. Moreover, the joint adoption of green production technology by kiwi growers has significantly increased the yield, economic values of Kiwi and household income of kiwi farmers. The households with higher asset value, better land quality, weaker credit constraints, more technical training and stronger government promotion and support from local governments are the most likely to adopt pest control technology and soil management technology jointly.

The prime innovation of the paper is to measure the impact of technology combination adoption on farmer’s welfare is evaluated, rather than the impact of single sub technology on farmer’s’ welfare.

The purpose of this paper is to analyse the determinants of technical efficiency (TE) in dairy farms located in the South of Brazil, aiming for a better understanding of the topic for academics, dairy farmers and policymakers to improve the productivity and competitiveness of dairy farms.

This study was developed using a two-stage approach. Data envelopment analysis was used to estimate the TE level and regression models to understand the factors affecting TE in dairy farms. The sample size is 253 dairy farms in the South of Brazil.

The variation in the mean TE indexes reported in the literature can be explained by the attributes of the analysed studies, including the education of the farm operator, farm size (number of cows and milk), feed and labour costs, and use of services. Additionally, the results suggest that dairy farmers in the sample could increase milk output by 50.1 per cent (level of inefficiency) on average if they improve their TE.

This study makes three important contributions: first, it formulates hypotheses from the previous literature’s propositions on the estimation of TE in dairy farms; second, it tests the hypotheses in an empirical study to understand the main factors affecting the TE in dairy farms of the selected municipalities in the South of Brazil; and third, it compares previous findings on the determinants of TE in dairy farms serving different stakeholders, such as researchers, farmers and government representatives, to improve the productivity and competitiveness of dairy farms.

The purpose of this study is to examine the operational efficiency of restaurants in a dynamic context, over the period 2011-2014. The paper also analyzes efficiency with respect to several frontiers and production technologies dependent on restaurant size. Finally, it provides a new perspective by examining financial and non-financial variables that can directly affect the efficiency of restaurant firms.

The study applies metafrontier data envelopment analysis (DEA) methodology to investigate differences in production technologies, dynamic Tobit regression models and bootstrap procedure.

The results reveal that operational efficiency in the restaurant industry is affected by firm size, showing that large restaurants perform better than medium-sized and small restaurants Moreover, the evidence suggests a link between the efficiency index and financial variables, such as credit ratings, probability of default or bankruptcy, leverage and cash flow, as well as a link with non-financial variables, such as type of auditor.

The strength of restaurant firms has practical implications for managers and entrepreneurs, linked to the investment possibilities and growth potential of companies in that industry.

This study provides exploratory insights into operational efficiency as well as restaurant efficiency determinants. Performance and operational efficiency are key factors to restaurant firms’ survival in the economies that have been most severely affected by the financial crisis. Furthermore, this study confirms the relevance of financial and non-financial variables, which are associated with firm efficiency in this industry.