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1 – 10 of 883
Article
Publication date: 22 March 2024

João Eduardo Sampaio Brasil, Fabio Antonio Sartori Piran, Daniel Pacheco Lacerda, Maria Isabel Wolf Morandi, Debora Oliveira da Silva and Miguel Afonso Sellitto

The purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.

Abstract

Purpose

The purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.

Design/methodology/approach

The research method is a quantitative modeling. The main research techniques are data envelopment analysis, TOBIT regression and simulation supported by artificial neural networks. The model’s input and output variables consist of the average billet weight, number of billets processed in a batch, gas consumption, thermal efficiency, backlog and production yield within a specific period. The analysis spans 20 months.

Findings

The key findings include an average current efficiency of 81%, identification of influential variables (average billet weight, billet count and gas consumption) and simulated analysis. Among the simulated scenarios, the most promising achieved an average efficiency of 95% through increased equipment availability and billet size.

Practical implications

Additional favorable simulated scenarios entail the utilization of higher pre-reheating temperatures for cold billets, representing a large amount of savings in gas consumption and a reduction in CO2 emissions.

Originality/value

This study’s primary innovation lies in providing steelmaking practitioners with a systematic approach to evaluating and enhancing the efficiency of reheating processes.

Details

Management of Environmental Quality: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1477-7835

Keywords

Open Access
Article
Publication date: 7 November 2023

Cristian Barra and Pasquale Marcello Falcone

The paper aims at addressing the following research questions: does institutional quality improve countries' environmental efficiency? And which pillars of institutional quality…

Abstract

Purpose

The paper aims at addressing the following research questions: does institutional quality improve countries' environmental efficiency? And which pillars of institutional quality improve countries' environmental efficiency?

Design/methodology/approach

By specifying a directional distance function in the context of stochastic frontier method where GHG emissions are considered as the bad output and the GDP is referred as the desirable one, the work computes the environmental efficiency into the appraisal of a production function for the European countries over three decades.

Findings

According to the countries' performance, the findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries. In this environmental context, the role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries.

Originality/value

This article attempts to analyze the role of different dimensions of institutional quality in different European countries' performance – in terms of mitigating GHGs (undesirable output) – while trying to raise their economic performance through their GDP (desirable output).

Highlights

  1. The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

  2. We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

  3. The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

  4. The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

Details

Journal of Economic Studies, vol. 51 no. 9
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 16 November 2023

Santi Gopal Maji and Rupjyoti Saha

This study investigates the effect of intellectual capital (IC) and its components on the technical efficiency of Indian commercial banks after controlling the influence of…

Abstract

Purpose

This study investigates the effect of intellectual capital (IC) and its components on the technical efficiency of Indian commercial banks after controlling the influence of bank-specific and macroeconomic variables.

Design/methodology/approach

The study selects a sample of 37 listed Indian commercial banks from 2005 to 2019 and uses the two-step data envelopment analysis (DEA) approach. Banks' technical efficiency scores are first estimated, while the relationship between IC and technical efficiency is examined in the second stage using the panel data Tobit model.

Findings

This study's findings suggest a fluctuating trend in the technical efficiency of Indian banks. Notably, from 2015 onwards, a declining technical efficiency trend is observed for all banks. However, private-sector banks outperform public-sector banks in terms of technical efficiency. This study's regression analysis indicates a positive relationship between IC and banks' technical efficiency scores. Further, by decomposing IC into its components like human capital, structural capital and capital employed, the study's findings show that human capital and structural capital enhance banks' technical efficiency. Notably, capital employed reduces technical efficiency. Moreover, bank size, diversification, capitalization, net interest margin and the country's growth rate significantly drive Indian banks' efficiency. In contrast, their operating cost ratio and the country's inflation negatively influence the same.

Originality/value

This study makes a novel endeavor to examine the IC and bank's technical efficiency nexus in the Indian context, encompassing a period of landmark banking reforms.

Details

Managerial Finance, vol. 50 no. 4
Type: Research Article
ISSN: 0307-4358

Keywords

Book part
Publication date: 4 April 2024

Ren-Raw Chen and Chu-Hua Kuei

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this…

Abstract

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

Details

Advances in Pacific Basin Business, Economics and Finance
Type: Book
ISBN: 978-1-83753-865-2

Keywords

Book part
Publication date: 5 April 2024

Zhichao Wang and Valentin Zelenyuk

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were…

Abstract

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

Article
Publication date: 12 September 2023

Usama Alqalawi, Ahmad Alwaked and Anas Al Qudah

This paper aims to determine the tax potential of G20 countries and estimate the tax revenue they could generate. The study evaluates the effectiveness of tax revenue collection…

Abstract

Purpose

This paper aims to determine the tax potential of G20 countries and estimate the tax revenue they could generate. The study evaluates the effectiveness of tax revenue collection for G20 nations from 2008 to 2020 and investigates the relationship between tax collection efficiency and tax evasion. The study also examines the link between tax collection efficiency and a proxy for tax evasion through anti-corruption efforts.

Design/methodology/approach

The study assumes that tax collection is a function of gross domestic product (GDP), population, imports and price level. The study uses a stochastic frontier analysis to calculate the efficiency of tax collection. It estimates the loss in total tax collection due to inefficiency by comparing actual and best-practice tax collection.

Findings

The findings indicate that anti-corruption measures and technological advancements positively impact tax collection efficiency. Great Britain is identified as the most efficient country in tax collection, whereas Saudi Arabia is the least efficient. Germany has the highest losses in tax collection due to inefficiency, while Australia experiences the lowest losses in tax collection.

Originality/value

This study suggests several practical implications. For example, legislators and policymakers should pay more attention to anti-corruption policies. Also, tax agenesis should focus on better understanding variations in tax collection efficiency between countries and how they relate to tax evasion.

Details

Journal of Money Laundering Control, vol. 27 no. 3
Type: Research Article
ISSN: 1368-5201

Keywords

Article
Publication date: 22 June 2023

Parvez Mia, James Hazelton and James Guthrie Am

This study aims to evaluate the quality of the energy efficiency disclosures made by Australian cities. As cities are significant energy users, and energy use is a crucial source…

Abstract

Purpose

This study aims to evaluate the quality of the energy efficiency disclosures made by Australian cities. As cities are significant energy users, and energy use is a crucial source of greenhouse gas emissions, energy efficiency initiatives can play an essential role in addressing climate change. Yet, little is understood about the energy efficiency disclosures being made.

Design/methodology/approach

The authors developed an original energy efficiency disclosure index to assess the reporting quality of the eight largest Australian cities. The websites of these cities were analysed for information on energy efficiency measures from December 2018 to June 2019. Annual reports, environmental reports, climate action plans and any other material related to energy plans were downloaded and then coded using the index.

Findings

While all cities provided energy efficiency information, little financial information was provided, limited forward-looking information was disclosed, key challenges were not disclosed, and each city provided energy efficiency disclosures differently. Collectively, these findings demonstrate that public accountability is limited.

Research limitations/implications

An important implication is the need to standardise and improve cities’ energy efficiency reporting, especially concerning financial information. Cities, governments and the Carbon Disclosure Project (formerly the CDP) could achieve this, perhaps as part of the broader update of the CDP city-focused guidelines for greenhouse gas (GHG) reporting.

Originality/value

Although some studies on GHG reporting by cities have already been undertaken, including energy efficiency as part of their disclosure index, no study has focused on energy efficiency disclosures. The authors provide original insights concerning these practices. The study also provides an energy efficiency disclosure index that can be used in further research.

Details

Meditari Accountancy Research, vol. 32 no. 2
Type: Research Article
ISSN: 2049-372X

Keywords

Article
Publication date: 26 January 2023

Fenglian Wang, Qing Su and Zongming Zhang

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of…

Abstract

Purpose

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.

Design/methodology/approach

This study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.

Findings

The results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.

Research limitations/implications

There are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.

Practical implications

This analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.

Originality/value

The study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.

Book part
Publication date: 5 April 2024

Mike G. Tsionas

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency…

Abstract

In this chapter, we consider the possibility that a firm may use costly resources to improve its technical efficiency. Results from static analyses imply that technical efficiency is determined by the configuration of factor prices. A dynamic model of the firm is developed under the assumption that managerial skill contributes to technical efficiency. Dynamic analysis shows that the firm can never be technically efficient if it maximizes profits, the steady state is always inefficient, and it is locally stable. In terms of empirical analysis, we show how likelihood-based methods can be used to uncover, in a semi-non-parametric manner, important features of the inefficiency-management relationship using a flexible functional form accounting for the endogeneity of inputs in a production function. Managerial compensation can also be identified and estimated using the new techniques. The new empirical methodology is applied in a data set previously analyzed by Bloom and van Reenen (2007) on managerial practices of manufacturing firms in the UK, US, France and Germany.

Open Access
Article
Publication date: 15 December 2023

Nicola Castellano, Roberto Del Gobbo and Lorenzo Leto

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on…

Abstract

Purpose

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

Design/methodology/approach

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

Findings

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

Practical implications

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

Originality/value

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 11
Type: Research Article
ISSN: 1741-0401

Keywords

1 – 10 of 883