Search results

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 purpose of this paper is to conduct a benchmark analysis of European cities based on the estimation of a composite index of efficiency from the dimensions of the Cultural and Creative Cities Monitor 2017 (CCCM). The study helps to initiate a new exploration path based on this information, using a segmentation criterion of countries according to their economic and demographic characteristics, in search of greater comparative homogeneity.

In this paper, the metafrontier methodological proposal with data envelopment analysis (DEA) has been used to compare the groups of cities individually with their joint reference.

The results obtained indicate, from a greater control of heterogeneity, through the segmentation of the sample of cities and the metafrontier methodology, that the composite index (IEC3) through the enveloping data analysis methodology (DEA) is more robust than that obtained with the arbitrary assignment of CCCM weights. The analyses carried out make it possible to study and conduct more real and rigorous comparisons of the cities that experience the best practices, unlike other more distant ones. Reference to cities such as Paris, Louvain and Cork could serve as a basis for possible improvements.

It is important to bear in mind that the possible urban policies of a city and the creative strategies and their derived impact are different, because of the diversity in each city. These new comparability possibilities could serve as a tool for economic policy makers, companies and local managers to carry out learning and simulation processes in the improvement of creative cities.

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.

The fiscal outlay efficiency matters when the performance-based allocation of funds is made to state governments by the central government in a federal structure of an economy like India. Also the efficiency cannon of public expenditure is a key aspect in the field of public economics. Thus, a study to evaluate the efficiency in fiscal outlay of Indian states has been conducted.

The paper offers a three divisions–based paradigm under Network Data Envelopment Analysis framework to compare the performance of fiscal entities (say Indian state governments) in converting available fiscal resources into desired short-run and long-run growth and development objectives. The network efficiency score has been taken as a measure of the quality of fiscal outlay management that is trifurcated into divisional efficiencies representing budgeting process, fiscal outlay efficiency process and fiscal outlay effectiveness process.

It has been noticed that the states are under performing in achieving short-run growth targets and so the efficiency process division has been identified a major source of fiscal under performance. Suboptimum allocation of fiscal expenditure under various heads within the fiscal resources, as explained under budgeting process, is another major cause of fiscal under performance.

The study purposes a three divisions–based paradigm that takes into account efficiency of a state in (1) planning budget, (2) achieving short-run growth targets and (3) achieving long-run development targets. These three stages are named as budgeting process efficiency, fiscal outlay efficiency and fiscal outlay effectiveness, respectively. Therefore, a new paradigm called BEE paradigm is proposed to evaluate performance of fiscal entities in terms of fiscal outlay efficiency.

In existing literature on measuring efficiency of public expenditure, the public sector outputs have been made as function of fiscal expenditure as input treating the said outlay as an exogenous variable. In present context, the fiscal expenditure has been treated endogenous to the budgeting process. A high inefficiency on account of budgeting process supports this treatment too.

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.

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 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.

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.

This paper aims to examine the efficiency of Islamic vs conventional banks in Malaysia by unveiling the traditional efficiency concept – black box – with a three-stage network structure of bank operations.

This paper applies data envelopment analysis (DEA) for examining bank efficiency. An adaptive three-step network DEA (NDEA) model is demonstrated for redefining the traditional black box of banking operations. Slack-based variable returns to scale approach is used. Data from all 43 commercial banks in Malaysia are examined over a six-year study period (2010-2015). Inputs and outputs of the model are selected based on CAMELS rating. Undesired output is also considered in time of examining bank efficiency in Malaysia.

The empirical results of this study signify that only a few banks in Malaysia have been performing well in converting deposits and equities into profit as well as minimizing loan loss provisions. Islamic banks in Malaysia have performed better both in production (converting deposits and equities into earning assets) and profitability (converting loans into net income). Conventional banks, however, have over scored in intermediation (converting earning assets into loans).

An adaptive NDEA approach proposed in this paper defines the core banking process instead of traditional approaches in examining bank efficiency based on individual functions (nodes in the network model). This approach has proven to provide better benchmark capacity.

This paper aims to assess the efficiency levels of World Cup teams via the slack-based data envelopment analysis (DEA) approach, which contributes to filling an important gap for performance measurement in football.

This study focuses on a comparative analysis of the past two World Cups. The authors initially estimate the efficiency of the World Cup teams via the slack-based DEA approach, which is a novel approach for sports performance measurement. The authors also present the conventional DEA results to compare results. The authors also include improvement ratios, which provide significant details for inefficient countries to enhance their efficiency. Besides, the authors include effectiveness ratings to present a complete performance overview of the World Cup teams.

According to the analysis results of the slack-based DEA approach, titleholder Germany and France are found as efficient teams in the 2014 and 2018 World Cup, respectively. Besides, Belgium and Russia recorded the highest efficiency improvement in the 2018 World Cup. The novel approach for sports performance measurement, the slack-based DEA approach, significantly overlaps with the actual performance of teams.

This study presents novelty in football performance by adopting the slack-based DEA with an undesirable output model for the performance measurement of the World Cup teams. This empirical analysis would be a pioneer study measuring the performance of football teams via the slack-based DEA approach.