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The purpose of this paper is to determine the most efficient hotels in the Indian hotel industry, the competitive positioning of these hotels, and the factors that affect their efficiency change.

This study conducts a two-stage analysis and uses data envelopment analysis (DEA) and Global Malmquist productivity index (MPI) approach in the first stage to calculate the managerial performance of a panel of 63 Indian hotels in 2019–2020 and their efficiency change from 2009–2010 to 2019–2020. Bootstrapped generalized least square (GLS) approach is applied in the second stage to evaluate the impact of contextual variables on efficiency change.

Using the results of the first stage analysis, the authors categorized the 63 Indian hotels into 7 distinct clusters. These clusters represent different levels of competitiveness and pace of growth. The GLS regression reveals a U-shaped relationship between hotel size and efficiency change and a negative relationship between pro social investments and efficiency.

This is the first study in the hotel industry that has used global MPI as a measure of efficiency change in the first stage and GLS in the second stage. In the Indian context, to the best of authors’ knowledge, no such study exists.

The purpose of this study is to benchmark the performance of state-owned coal-fired power plants (CFPPs) and test whether plant-specific knowledge in terms of quality of coal, size, age and make of plant contribute to an improvement in plant efficiency.

The methodology that is utilized in the study follows a nonparametric approach of data envelopment analysis (DEA) with sensitivity analysis and Tobit regression model. The input-oriented DEA models are applied to evaluate the overall, pure technical and scale efficiencies of the CFPPs. Further, slack analysis is conducted to identify modes to improve the efficiency of the inefficient plants. Sensitivity analysis based on peer count and the removal of variables is carried out to identify the benchmark power plant. Through Tobit and bootstrap-truncated regression model, the paper investigates whether a plant's specific knowledge influences its efficiency.

The DEA analysis demonstrates that nine plants are technically purely efficient.The slack analysis reveals that reducing the consumption of oil is the most effective way to improve the efficiency of inefficient plants. Mattur plant is the benchmark for most of the inefficient plants. Regression result suggests that quality of coal and size of plant significantly affect the inefficiency of the sample plants. Bharat Heavy Electrical Limited MAKE plant achieved higher efficiency in comparison to mixed MAKE.

This study is one of the few published studies that benchmark the performance of state-owned CFPPs. This research carried out taking some new uncontrollable parameters of power plant utilities of India. Research work also identifies the possible causes of inefficiency and provides measures to improve the efficiency of the inefficient power plant.

The purpose of this paper is to estimate advertising efficiency in the Spanish beer industry and to analyse the effects of several environmental variables and brand portfolio scope on advertising efficiency scores.

A two-stage double bootstrap procedure is used. In the first stage, advertising efficiency is estimated using a bootstrapped data envelopment analysis on a multiple input-output model of advertising. In the second stage, a bootstrapped truncated regression model is estimated to identify the determinants of advertising efficiency. Both stages are estimated simultaneously. The empirical application is carried out on a sample of Spanish brewers between 2007 and 2014.

Results show low advertising efficiency scores and highlight the effects that environment and brand portfolio scope have on these estimates.

For the first time, this paper analyses the effect of environmental variables and the brand portfolio scope on advertising efficiency in the beer industry.

The purpose of this study is to measure the technical efficiency of Japanese national universities over the period 2010–2016. In addition, the authors also sought to identify the determinants of efficiency, especially those amenable to public policy intervention.

First, the authors ran a global intertemporal data envelopment analysis to understand the trends in efficiency for national universities over the relevant period. Following this, the authors conducted a second-stage regression using a double-bootstrapped truncated regression model to identify the possible determinants of efficiency.

The authors found no evidence to suggest that technical efficiency of national universities systematically decreased or increased in response to either structural reform or a reduction to government grants. Moreover, the share of government grants, the size of universities and disciplines of study offered by the universities were statistically significant determinants of efficiency.

The study results suggest that efficacious public policy remedies might include inter alia measures to reduce the reliance on public funding, efforts to attract more foreign students, the execution of mergers among small universities and consolidation of inefficient departments.

This research fills an important gap in the scholarly literature with respect to Japanese national universities and identifies possible determinants to efficiency, which are amenable to remedial public policy interventions.

The purpose of this paper is to estimate production and scale efficiency of maize producing farms in South-Western Nigeria.

This study is based on a semi-parametric approach and uses a combination of econometrics and linear programming to build two stage Data Envelopment Analysis (DEA) model.

Model findings shows existence of production and scale inefficiencies in maize production. The study concludes that there is still room for efficiency improvements in the existence of the current maize production technology. It also finds several socio-economic variables such as, off-farm work, education, extension services and credit, which positively impact on technical efficiency of farm households.

Efficiency indicators could be used to monitor resource use efficiency in crop production by local government.

Efficiency improvements will increase maize production in the country which in turn reduce social unrest and food insecurity.

This study is one of the first which has employed DEA approach to analyze maize productivity and pioneer in using non-traditional bootstrapping approach to obtain robust efficiency scores in the case of Nigeria.

The purpose of this paper was to measure the efficiency of resource utilization across OECD countries aiming to verify that higher levels of competitiveness enhance the production capacity – the maximum possible output of an economy in a given period with the available resources.

The author used a two-stage procedure to first estimate the cross-sectional efficiency scores of 18 OECD economies by data envelopment analysis, and then to assess the impact of contextual variables on efficiency running regressions in the second-stage analysis. In particular, in the second stage, the author examined the effects of competitiveness on the production efficiency of the countries, while controlling for other independent variables.

The results confirmed that the higher the level of competitiveness, innovation and sophistication factors predominantly, the higher the level of productive efficiency of the countries analyzed.

The paper is novel because it opens the black box of the aggregate process of production of the conversion of resources into a national product. From the social point of view, it is relevant to know if a country could produce more output with the same resources, such as labor and capital and, therefore, could increase per capita income and social welfare.

The purpose of this paper is to measure profitability and marketability efficiencies as well as examine the efficiencies’ determinants of listed manufacturing firms in Vietnam.

This study employs a bootstrap two-stage data envelopment analysis (DEA) approach to investigate the profitability and marketability efficiencies of 102 listed manufacturing firms on Vietnam stock market from 2007 to 2018. The study also applies fractional regression models (FRM) to identify the determinants of Vietnam manufacturing firms’ efficiencies.

The results reveal that Vietnam manufacturing firms obtain higher average profitability efficiency scores (0.888) than marketability efficiency scores (0.527) from 2007 to 2018. The high-tech firms achieve better profitability and marketability efficiencies than the traditional (resource-intensive and labour-intensive) Vietnam manufacturing firms in recent years (2016–2018). Further, the financial and non-financial factors have heterogeneous impacts on Vietnam manufacturing enterprises’ profit and market valuation efficiencies.

Due to the nature of DEA technique that requires every decision-making unit to have available data of all inputs and outputs, the listed Vietnam manufacturing firms that have incomplete data or go public after 2007 are not included in the data set.

This study provides a reference for Vietnam manufacturing managers to position their firms competitively in the market as well as make wise operating, financing and management decisions.

This is the first study that attempts to combine bootstrap two-stage DEA and FRM, which are considered advantageous methods for DEA scores’ measurements and determinant evaluations in the current literature.

This paper aims to identify the scale efficiency of dry ports in Brazil and its main technological drivers.

This paper uses the Data Envelopment Analysis (DEA) model in two stages. The first stage of the DEA was used to measure the efficiency of the dry ports. In the second stage, the Bootstrap Truncated Regression (BTR) was applied to explore the relationship between efficiency and the factors analyzed. The inputs, outputs and contextual variables for this analysis were extracted from the secondary database provided by Revista Tecnologística.

In the first analysis stage, a high level of idleness was verified in the operations. The contextual variables in the second stage were significant: Certification, Warehouse Management System (WMS), barcode and Radio Frequency Identification (RFID). Results corroborate the positive impact of Information Technology (IT) coordination processes on logistics performance.

Results show that dry ports operate below their technical and operational capacity and that the sector's lack of regulation in Brazil can facilitate and encourage the use of ports and marine terminals by importers and exporters.

Application of two-stage DEA measures efficiency as a sectoral benchmarking tool.

The purpose of this paper is to investigate the relation between industrial concentration and technical inefficiency in the Indonesian food and beverages industry using a dynamic performance measure (dynamic technical inefficiency) that accounts for the presence of adjustment costs.

This research uses panel data of 44 subsectors in the Indonesian food and beverages industry for the period 1980-2014. The dynamic input directional distance function is applied to estimate the dynamic technical inefficiency. Further, the Granger causality between industrial concentration and dynamic technical inefficiency is tested using a dynamic panel data model. A bootstrap truncated regression model is finally applied to estimate the relation between industrial concentration and dynamic technical inefficiency based on the results from the Granger causality test.

The results show that the Indonesian food and beverages industry has a high dynamic technical inefficiency. Investigation of the causality of the relation shows that industrial concentration has a positive effect on dynamic technical inefficiency at the subsector level, with no reversed causality. The results suggest that the quiet life hypothesis applies to the Indonesian food and beverages industry.

The literature investigating the relation between industrial concentration and performance relies on static measures of performance, such as technical efficiency. Static measures provide an incorrect metric of the firms’ performance in the presence of adjustment costs associated with investment. Therefore, this research has a contribution in measuring dynamic technical inefficiency that accounts for the presence of the adjustment cost as well as its relation with industrial concentration in the Indonesian food and beverages industry.

The purpose of this paper to study the hotel performance determinants by examining the impact of the internal and the external environment of the hotel on its performance.

A bootstrapped truncated regression model is used following the evaluation of efficiency score for hotels using data envelopment analysis (DEA). The effects of the cited variables are discussed to determine the best development strategy for increasing hotel performance.

This paper has four major contributions. First, the test results confirm that macro-contextual factors, such as international attraction and market competition, have a direct influence on hotel efficiency. Second, hotel efficiency depends on hotel characteristics, such as hotel age, hotel type, management type and the location of the hotel. Third, the tenure of the general manager, education level of the board staff and number of managers influence hotel efficiency. Finally, general tourism wages increase the efficiency score of the corporate hotel performance.

Tourism employment studies require further improvement, and their challenges should be highlighted when countries develop tourism strategies. Moreover, hiring employees with a better educational background appears to be an effective human resource strategy to reduce inefficiency in the hotel sector. Tourism performance and development need a thorough investigation into tourism wages to attract the best students and the best graduates to the tourism sector to bring out the needed number and skills of employees.

The conclusions of this paper are consistent with the literature results. However, it is important to separate market concentration from market competition for whose literature concluded an opposite influence on the hotel performance. The authors explain this contrast by the measure choice.

The performance of the hotel depends not only on the physical resources and on the destination characteristics but also on the management characteristics.

This paper is the first to test empirically the influence of destination attractiveness, competition level, hotel size, hotel age, management contract, hotel type, location, advertising, manager’s tenure, tourism education and wages on the hotel performance in Tunisia.