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The major aim of this paper is to model, estimate and compare the technical efficiency and technology gap ratios of health care foodservice operations that operate in different Australian regions.

This paper uses a metafrontier model to analyse the difference in health care food efficiency across the various Australian regions. The interesting feature of this model is that it allows for the estimation of firms' efficiency in of various groups that might differ in technology and other production environments. In testing the model, cross‐sectional input/output data were used reflecting on the operational characteristics of health care foodservice operations.

The estimation process was initially supported by a hypothesis test which confirmed the validity of the metafrontier model in comparing the efficiency of the different outlined groups. Results showed that operations in the states of NSW and Victoria are producing on average 85.6 per cent of their potential output with respect to the metafrontier technology. The ratio is lower in other states with an average of 73.4 per cent. The average technical efficiency for operations in NSW and Victoria is also higher both in terms of local (87.8 per cent) and metafrontier technologies (66.6 per cent).

The paper is the first to introduce the metafrontier model to the health care foodservice area, especially for Australian regions.

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.

Importance of small-scale tea producers in Kenya is not in doubt. They account for 60% of all tea produced in the country, serve about 560,000 tea farmers and employ about 10,000 people directly. However, the subsector faces a myriad of challenges ranging from declining yields and rising costs of production to fluctuating world prices. Thus, it is imperative that the producers entrench efficiency as a critical success factor. This makes it important for the producers to understand their relative performances to inform decisions on improving input use. Congruent with this motivation, this study sought to analyze the technical efficiency (TE) of the country's small-scale tea processors within and across the regions under the management of Kenya Tea Development Authority.

To allow comparison across regions, this study adopted a stochastic metafrontier approach and to be able to decompose inefficiency into persistent and time-varying components, the study adopted regression analysis.

Results showed that the small-scale tea processors operated at a mean TE level of 76% with a technology gap ratio (TGR) of 97%. This implies that the prevailing level of output could be maintained even if inputs were reduced by 24%. Persistent inefficiency could be reduced possibly through rationalization of structural and managerial components of the firms.

While it is important to adopt yield-enhancing technologies and innovation, small-scale tea processors have the latitude to improve their earnings through enhanced TE. They can save up to 24% of their input and be able to pay farmers better even with the fluctuating global tea prices. Enhancing TE should be given priority because it is within the control of the individual firms.

This is a pioneering study in panel data analysis of TE of small-scale tea processors within and across regions in Kenya.

The aims of the paper are to evaluate the relevance of environmental factors (seasonality, size and quality) on hotels’ performance and benchmarks; to measure the bias in efficiency resulting from a failure to control for these sources of heterogeneity; and to propose some managerial policies to handle for environmental heterogeneity.

The sample is constituted by 2,705 hotels operating in Emilia-Romagna (Italy). The metafrontier approach is used to identify the different production processes and measure technical efficiency scores.

Different production processes exist among accommodation firms due to environmental features; not considering heterogeneity in technological sets produces high levels of bias in the efficiency measurement, albeit the ranking of hotels tends to be fairly consistent; the star rating is the primary source of efficiency bias followed by seasonality, while size has a minor impact.

Future research could be directed to analyse the relevance of environmental heterogeneity in other areas; study the dynamics; investigate agglomeration effects; and use other methodological tools.

The analysis proposes new managerial interventions: targeted strategies to different groups; creation of networks of enterprises, clustered mainly in respect to size for highly rated enterprises and seasonality for low-rated enterprises; and incentives to annual hotels and raise in the product quality.

This paper simultaneously considers several environmental factors affecting heterogeneity in hotel production processes; investigates the effect of heterogeneity on either the efficiency scores or the ranking of hotels; and focuses on micro, low-quality or seasonal hotels.

The purpose of this study is to examine efficiency differences among petroleum firms based on their ownership status, with the aim of helping these firms understand how specific levels of state-ownership affects efficiency and to bring new perspective to the ownership-performance literature.

The study uses ten-year data (2001-2010) of 32 global petroleum firms categorized into four groups based on ownership types. The metafrontier analysis is used with the dynamic slack-based measure to estimate dynamic efficiency differences among the groups while respectively, accounting for carryover variables such as oil and gas reserves.

Fully state-owned firms outperformed private, majority and minority state-owned firms, indicating that not all types of state-owned petroleum firms are outperformed by private firms. Additionally, firms with shared ownership between state and private are seen to have a lesser comparative advantage in the industry than those with full private or state ownership.

Jointly owned petroleum firms should consider converting ownership to either full private or full state control. Conflict management measures should be used to handle possible conflicts between different shareholding groups.

This is among the first studies to sub-group state ownership into various levels to comprehensively examine specific levels of state ownership that is detrimental to the performance of petroleum firms. It is also the premier oil efficiency study to use the metafrontier framework to cater for group heterogeneity. The study treats oil and gas reserves as interconnecting variables that are not consumed only in the period for which they are discovered to ensure fair assessment.

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.

In this study, the impact of owner-operator and non-owner operator rice mills on productive efficiency is investigated.

Primary data collected from a survey of 111 rice mills in the Mwea region of Kenya are used. A metafrontier approach is employed to measure overall technical efficiency which is decomposed into managerial and organisational efficiency.

The results reveal no significant difference in overall technical and managerial efficiency between owner and non-owner operated mills. However, a significant difference exists in organisational efficiency of mills: non-owner operated mills were found to be performing significantly better than owner-operated.

The authors provide supporting evidence to the study and discuss some of the significant policy implications stemming from the study.

It is recognised that for owners to take the risk of divesting control to a hired manager rather than manage the firm themselves can have major strategic, financial and often emotional consequences. However, there is little empirical evidence on how production efficiency will develop as a result of hiring a manager with the underlying economic theory providing ambiguous guidance. Standard economic theory assumes that firms behave as profit maximisers, which can be achieved by operating efficiently. However, this may not always be the case and as the literature indicates, this may especially be so for small businesses in low- and middle-income countries.

This paper aims to assess the efficiency of public investment in West African Economic and Monetary Union (WAEMU) countries at both the global and sectoral level over the 2005–2015 period.

This paper estimates efficiency scores using stochastic frontier analysis (SFA) models. Efficiency is divided into managerial efficiency (related to inputs management) and technological efficiency (related to production technology). A Tobit model is then used to investigate the determinants of public investment efficiency.

The findings suggest that, at the global level, WAEMU countries are less efficient than sub-Saharan African and Asian reference countries. However, the breakdown of global efficiency into managerial and technological reveals that WAEMU countries are more efficient than sub-Saharan African countries in terms of technological efficiency. Moreover, these findings are robust to nonparametric estimation. The assessment of financing sources indicates that external debt has a more positive and significant effect on public investment efficiency than internal debt does.

This paper is unique in that it disentangles managerial efficiency from the technological efficiency of public investment in WEAMU countries and highlights how financing sources of investment affect its efficiency. In terms of policy implications, the underlying message of the results is that the rules and conditions of domestic or regional debt in the WAEMU countries must be strengthened to ensure better monitoring and then better efficiency of these resources.

The purpose of this study is to compare the production efficiencies and frontiers differences of oil-producing countries (OPCs) in four inter-governmental organizations (IGOs) in the international petroleum industry with the aim of providing such countries understanding of group characteristics that help maximize their supply interests.

The empirical analysis is based on 14 years of panel data covering the period from 2000 to 2013. In all 46 unique countries who are members of four IGOs relevant to the international petroleum industry are examined on individual and group bases. The authors use both metafrontier analysis and global frontier difference in examining the group average and group frontiers, respectively.

Groups with high inter and intra-group collaborations which ensure exchange of information, organizational learning and innovation tend to do better than groups with even higher hydro-carbon endowment. Additionally, hydro-carbon resource endowment may not be the solution to group inefficiency without higher endowment in human capital, economic stability, technology and infrastructure.

Choice of inter-governmental organizational membership should be based on the level of inter- and intra-group collaborations, human capital endowment among others and not mere historic links or even resource endowment.

This is among the few studies to compare and rank IGOs. Specifically, it is among the first studies to analyze the petroleum production efficiencies of IGOs involved in the international petroleum industry. This study assesses the performance differences among OPCs with the aim of identifying for OPCs the characteristics of inter-governmental groups that are beneficial to efficiency in upstream petroleum activities.

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.