Benchmarking hotel industry in a multi‐period context with DEA approaches: a case study

Benchmarking the operational efficiency of Mexican hospitals – a longitudinal study

Purpose

This study aims to benchmark the operational efficiency of fifty-eight public hospitals across Mexico between 2015 and 2018 and identifies the most critical inputs affecting their efficiency. In doing so, the study analyzes the impact of policy changes in the Mexican healthcare system introduced in recent years.

Design/methodology/approach

To measure the operational efficiency of Mexican public hospitals, data envelopment analysis (DEA) window analysis variable returns to scale (VRS) methodology using longitudinal data collected from the National Institute for Transparency and Access to Information (IFAI). Hospital groups are developed and compared using a categorization approach according to their average and most recent efficiency.

Findings

Results show that most of the hospitals in the study fall in the moving ahead category. The hospitals in the losing momentum or falling behind categories are mostly large units. Hospitals with initially low efficiency scores have either increased their efficiency or at least maintained a steady improvement. Finally, the findings indicate that most hospitals classified as moving ahead focused on a single care area (cancer, orthopedic care, child care and trauma).

Research limitations/implications

This study examined the technical efficiency of the Mexican healthcare system over a four-year period. Contrary to conventional belief, results indicate that most public Mexican hospitals are managed efficiently. However, recent changes in public and economic policies that came into effect in the current administration (2018) will likely have long-lasting effects on the hospitals' operational efficiency, which could impact the results of this study.

Originality/value

To the best of authors’ knowledge, this is the first study that examines the efficiency of the complex Mexican healthcare system using longitudinal data.

The metaefficiency of trade shows: a benchmarking analysis by sector

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Originality/value

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.

Strategic benchmarking of service pricing based on the value added

Purpose

– The purpose of this paper is to investigate opportunities to move benchmarking studies toward a strategic level. The authors benchmarked how service prices are defined based on the value added for the customer.

Design/methodology/approach

– A multi-case research investigated how manufacturers can increase their service revenues; how corporate reputation can be analyzed to enhance financial and market performance; how customer satisfaction and price acceptance are related; and how benchmark studies can move to a more strategic level based on a conjoint analysis of value and price.

Findings

– Price’s benchmarking studies must combine the customers’ value demands; the customer expectations associated to each value demand; the competitor prices; and the revenue alternatives that a supplier can explore (e.g. sale of new goods, services for new goods, services for non-new goods, and repair parts). The combination of these elements reveals several opportunities for revenue generation. This combination may also help to explain the existence of different prices for similar goods and services. The authors referred to this as a flexible pricing policy. Flexible pricing may help manufacturers maximize revenues, and win and maintain customers.

Research limitations/implications

– The following research questions are suggested for future studies: What other elements should be considered in strategic benchmarking studies? What other elements can influence a flexible pricing policy for goods, spare parts, and services? In what contexts can a flexible pricing policy be applied? How should flexible pricing practices be benchmarked?

Practical implications

– A strategic benchmarking study must first identify the customers’ value demands. It is then necessary to analyze customer expectations associated to each value demand. As shown, customers may have different expectations for the same product or service. Similar expectations must be grouped together in order to allow a well-structured benchmark.

Originality/value

– The authors’ findings suggest interesting points to be observed by the manufacturers who supply integrated solutions with a long life cycle.

Efficiency ranking method using DEA and TOPSIS (ERM-DT): case of an Indian bank

Purpose

– The purpose of this paper is to present a tie-breaking procedure for computing performance efficiencies to improve benchmarking and performance evaluation process in a business situation.

Design/methodology/approach

– The authors propose a unified approach based on data envelopment analysis (DEA) and technique for order of preference by similarity to ideal solution (TOPSIS), to overcome the difficulty of unique ranking in the prevalent benchmarking and performance evaluation processes such as DEA, Super efficiency DEA model, etc., under constant return to scale (CRS) assumption. This model is called as efficiency ranking method using DEA and TOPSIS (ERM-DT). In order to check the consistency of the approach, various input-output combinations (to calculate the efficiencies) have been illustrated. Further, the authors present a case of an Indian Bank to illustrate an application of the proposed approach.

Findings

– The proposed approach, ERM-DT enables assign a unique rank to decision making units and provides a tie breaking procedure. Results obtained using the proposed approach are statistically compared with those obtained from the CRS DEA approach and super efficiency DEA approach using Friedman’s test.

Practical implications

– The proposed model provides an efficiency ranking method based on a score obtained by considering the minimum distance from the best value and maximum distance from the worst value. The proposed methodology is capable of handling negative data and undesirable output variables. This approach is unit invariant and makes the calculations simple. The authors present an application to compute the efficiency of various branches of an Indian bank. The authors hope the proposed method can enhance the decision-making ability of the management in complex situations.

Originality/value

– The authors propose an integrated DEA and TOPSIS framework for better benchmarking and performance evaluation. This approach provides a tie-breaking procedure for the efficiencies computed using CRS DEA approach. Ranks are assigned based on score obtained by considering the distance from the worst and the best solution. The proposed approach can be used with non-positive data points and undesirable output variables.

An exploratory evaluation of state road provision to commuters and shippers

Purpose

– Due to mounting fiscal pressures, the federal government as well as many state and municipal governments in the USA have had to re-examine their transportation policies. Tax increases and/or spending cuts which aim to trim budget deficits are preoccupations of most policy makers and legislative bodies nowadays. With regard to the task of building new or rehabilitating old bridges, highways, and toll gates, cost-benefit analysis and economic impact studies are often undertaken by various government entities to rank and prioritize spending in the hopes of maximizing fiscal efficiency and road usage benefits. Since most highway construction and maintenance expenditures are absorbed by state governments, it is mostly up to state policy makers to decide transportation priorities. Not much research to date has been conducted to evaluate the comparative efficiency of state road provision to commuters and shippers. Such research would be useful to a state government’s budgetary allocation, road planning, and spending plans. The paper aims to discuss these issues.

Design/methodology/approach

– This paper uses data envelopment analysis under both constant and variable returns-to-scale and then to explain variations in efficiency ratings by using Tobit regression analysis.

Findings

– The authors discovered that the greater the level of state resident income and/or the warmer the weather, the higher the road or mass transit provision efficiency on average. The authors also found that greater urbanization in a state had little to do with efficiencies with respect to road provision.

Originality/value

– This paper is one of the first to assess and evaluate the comparative efficiency of road provision across 50 states in the USA and then set a benchmark for utilizing state financial resources to improve road infrastructure. More importantly, this paper helps transportation planners and public policy makers better allocate their limited financial resources to public goods in time of budget cutbacks and shortfalls.