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Article
Publication date: 13 September 2022

Yongfeng Zhu, Zilong Wang and Jie Yang

The existing three-stage network Data Envelopment Analysis (DEA) models with shared input are self-assessment model that are prone to extreme efficiency scores in pursuit…

Abstract

Purpose

The existing three-stage network Data Envelopment Analysis (DEA) models with shared input are self-assessment model that are prone to extreme efficiency scores in pursuit of decision-making units (DMUs) efficiency maximization. This study aims to solve the sorting failure problem of the three-stage network DEA model with shared input and applies the proposed model to evaluate innovation resource allocation efficiency of Chinese industrial enterprises.

Design/methodology/approach

A three-stage network cross-DEA model considering shared input is proposed by incorporating the cross-efficiency model into the three-stage network DEA model. An application of the proposed model in the innovation resource allocation of industrial enterprise is implemented in 30 provinces of China during 2015–2019.

Findings

The efficiency of DMU would be overestimated if the decision-maker preference is overlooked. Moreover, the innovation resource allocation performance of Chinese industrial enterprises had a different spatial distribution, with high in eastern and central China and low in western China. Eastern China was good at knowledge production and technology development but not good at commercial transformation. Northeast China performed well in technology development and commercial conversion but not in knowledge production. The central China did not perform well in terms of technology development.

Originality/value

A three-stage network DEA model with shared input is proposed for the first time, which makes up for the problem of sorting failure of the general three-stage network model.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 9 September 2022

Li-Huan Liao, Lei Chen and Yu Chang

Safety efficiency is the key to balance safety and production in construction industry; but the existing safety efficiency evaluation methods have the limitations of…

12

Abstract

Purpose

Safety efficiency is the key to balance safety and production in construction industry; but the existing safety efficiency evaluation methods have the limitations of overestimating efficiency and ignoring undesirable outputs; therefore, according to the characteristics of safety production in construction industry, this paper innovatively develops a new cross-efficiency data envelopment analysis method to analyze safety efficiency, which can solve the limitations of traditional methods; and then the safety efficiency and its influencing factors of China's construction industry are analyzed, and some useful conclusions are obtained to improve its safety efficiency.

Design/methodology/approach

A new cross-efficiency data envelopment analysis method with undesirable outputs is proposed; and the two-stage efficiency analysis framework is designed.

Findings

First, the construction industries in different areas have different reasons for affecting their safety efficiency; second, the evaluation results of global safety priority tend to be more acceptable; third, frequent safety accidents and low resource utilization lead to a slow downward trend of the safety efficiency of China's construction industry in the long run; fourth, construction engineering supervision, construction industrial scale, and construction industrial structure have the significant impact on safety efficiency.

Originality/value

Theoretically, a new cross-efficiency data envelopment analysis method with undesirable outputs is proposed for evaluating safety efficiency; practically, the safety efficiency and its influencing factors of China's construction industry are analyzed.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 26 September 2022

Qiang Wang, Chen Zhang and Rongrong Li

This study is aimed to measure the intertemporal financial efficiency of 16 emerging economy countries (BRICS and N-11) and further to investigate the mechanisms of…

Abstract

Purpose

This study is aimed to measure the intertemporal financial efficiency of 16 emerging economy countries (BRICS and N-11) and further to investigate the mechanisms of financial development on energy efficiency covering the period 2008–2020.

Design/methodology/approach

The dynamic data envelopment analysis model is used to measure financial efficiency dynamically. The generalized method of moments is used to investigate the effects of financial efficiency on energy efficiency. In the proposed approach, energy efficiency is the dependent variable, whereas financial efficiency, GDP per capita, industrial structure upgrade index, urbanization level and export trade structure are the regressors. Generalized moment estimation is performed.

Findings

There is heterogeneity in the level of financial development at different stages of economic development. The impact of financial efficiency on energy efficiency is related to the type of industries to which financial institutions are allocated. With the financial development of emerging economies, enterprises in technology-intensive industries are becoming the main contributors to higher profits for financial institutions, the products and results of these enterprises reduce energy consumption and increase energy efficiency. In addition, residents with rising levels of wealth holdings prefer low-carbon and environmentally friendly products, which indirectly improves energy efficiency. Per capita GDP and urbanization have no significant impact on the energy efficiency of emerging economies. The optimization and upgrading of the industrial structure of emerging economies has played a role in promoting energy efficiency. The export trade structure has a restraining effect on energy efficiency.

Originality/value

The findings contribute value by supporting a positive link between Financial Development and Energy Efficiency in the emerging economies. Enterprises in technology-intensive industries have gradually become the main force that brings higher profits to financial institutions. The products and achievements of these enterprises will reduce energy consumption and improve energy efficiency. The findings of this study provide emerging economies with an objective view of their financial development and energy efficiency, while also providing governments and policymakers with ways to improve energy efficiency and achieve sustainable development.

Details

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

Keywords

Article
Publication date: 20 September 2022

Hongyan Dai, Yan Wen, Weihua Zhou, Tingting Tong and Xun Xu

The overuse and scarcity of resources emphasize the importance of the circular economy. The technology facilitated by Industry 4.0 stimulates the implementation of the…

Abstract

Purpose

The overuse and scarcity of resources emphasize the importance of the circular economy. The technology facilitated by Industry 4.0 stimulates the implementation of the circular economy that aims to reduce resource use and enhance operational efficiency. This study focuses on enhancing delivery efficiency in an online-to-offline (O2O) context from an Industry 4.0 technology-facilitated personal configuration perspective, that is, comparing in-house and crowdsourced delivery efficiency in China's O2O on-demand food delivery context.

Design/methodology/approach

The authors collect 128,152 orders from 38 restaurants of an online restaurant chain in China. The authors adopt multiple regression analysis to examine the delivery efficiency gap between in-house and crowdsourced deliverymen and the determinants of this efficiency gap.

Findings

The findings of this study reveal that crowdsourced deliverymen exhibit higher delivery efficiency, in terms of a shorter delivery time, than in-house deliverymen. In addition, the authors find that platforms providing monetary incentives or implementing late delivery penalties enlarge this efficiency gap. Furthermore, the authors show that external factors, such as working on weekends and bad weather conditions, contribute to the narrowing of this performance efficiency.

Practical implications

The study's findings suggest that platforms should use advanced technologies facilitated by Industry 4.0 to optimize their personnel configuration to enhance their delivery efficiency and reduce carbon emissions. The effective approaches include using financial incentives and improving working schedules.

Originality/value

The authors' findings contribute to the online fulfillment literature by focusing on delivery efficiency in the O2O context from the Industry 4.0 technology-facilitated personnel configuration perspective. The authors examine how internal and external factors moderate the performance efficiency between these two types of deliverymen.

Details

Industrial Management & Data Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 16 August 2022

Abebayehu Girma Geffersa

The purpose of this paper is to measure technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from actual…

Abstract

Purpose

The purpose of this paper is to measure technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from actual inefficiency using comprehensive household-level panel data.

Design/methodology/approach

This paper estimates technical efficiency based on the true random-effects stochastic production frontier estimator with a Mundlak adjustment. By utilising comprehensive panel data with 4,694 observations from 39 districts of four major maize-producing regions in Ethiopia, the author measures technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from technical inefficiency. By using competing stochastic production frontier estimators, the author provides insights into the influence of farm heterogeneity on measuring farm efficiency and the subsequent impact on the ranking of farmers based on their efficiency scores.

Findings

The study results indicate that ignoring unobservable farmer heterogeneity leads to a downwards bias of technical efficiency estimates with a consequent effect on the ranking of farmers based on their efficiency scores. The mean technical efficiency score implied that about a 34% increase in maize productivity can be achieved with the current input use and technology in Ethiopia. The key determinants of the technical inefficiency of maize farmers are the age, gender and formal education level of the household head, household size, income, livestock ownership, and participation in off-farm activities.

Research limitations/implications

While the findings of this study are critical for informing policy on improving agricultural production and productivity, a few important things are worth considering in terms of the generalisability of the findings. First, the study relied on secondary data, so only a snapshot of environmental factors was accounted for in the empirical estimations. Second, there could be other sources of unmeasured potential sources of heterogeneity caused by persistent technical inefficiency and endogeneity of inputs. Third, the study is limited to one country. Therefore, future research should extend the analysis to ensure the generalisability of the empirical findings regarding the extent to which unmeasured potential sources of heterogeneity caused by persistent technical inefficiency, endogeneity of inputs and other unobservable country-specific features – such as geographical differences.

Originality/value

This paper contributes to the literature on agricultural productivity and efficiency by providing new evidence on the influence of unobservable heterogeneity in a farm efficiency analysis. While agricultural production is characterised by heterogeneous production conditions, the influence of unobservable farm heterogeneity has generally been ignored in technical efficiency estimations, particularly in the context of smallholder farming. The value of this paper comes from disentailing producer-specific random heterogeneity from the actual inefficiency.

Details

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

Keywords

Open Access
Article
Publication date: 1 September 2022

Yu Chen, Di Jin and Changyi Zhao

Global climate change is a serious threat to the survival and development of mankind. Reducing carbon emissions and achieving carbon neutrality are the keys to reducing…

Abstract

Purpose

Global climate change is a serious threat to the survival and development of mankind. Reducing carbon emissions and achieving carbon neutrality are the keys to reducing greenhouse gas emissions and promoting sustainable human development. For many countries, taking China as an example, the electric power sector is the main contributor to the country’s carbon emissions, as well as a key sector for reducing carbon emissions and achieving carbon neutrality. The low-carbon transition of the power sector is of great significance to the long-term low-carbon development of the economy. Therefore, on the one hand, it is necessary to improve the energy supply structure on the supply side and increase the proportion of new energy in the total power supply. On the other hand, it is necessary to improve energy utilization efficiency on the demand side and control the total primary energy consumption by improving energy efficiency, which is the most direct and effective way to reduce emissions. Improving the utilization efficiency of electric energy and realizing the low-carbon transition of the electric power industry requires synergies between the government and the market. The purpose of this study is to investigate the individual and synergistic effects of China’s low-carbon policy and the opening of urban high-speed railways (HSRs) on the urban electricity consumption efficiency, measured as electricity consumption per unit of gross domestic product (GDP).

Design/methodology/approach

This study uses a panel of 289 Chinese prefecture-level cities from the years 1999–2019 as the sample and uses the time-varying difference-in-difference method to test the relationship between HSR, low-carbon pilot cities and urban electricity consumption efficiency. In addition, the instrumental variable method is adopted to make a robustness check.

Findings

Empirical results show that the low-carbon pilot policy and the HSR operation in cities would reduce the energy consumption per unit of GDP, and synergies occur in both HSR operated and low-carbon pilot cities.

Research limitations/implications

This study has limitations that would provide possible starting points for future studies. The first limitation is the choice of the proxy variable of government and market factors. The second limitation is that the existing data is only about whether the high-speed rail is opened or not and whether it is a low-carbon pilot city, and there is no more informative data to combine the two aspects.

Practical implications

The findings of this study can inform policymakers and regulators about the effects of low-carbon pilot city policies. In addition, the government should consider market-level factors in addition to policy factors. Only by combining various influencing factors can the efficient use of energy be more effectively achieved so as to achieve the goal of carbon neutrality.

Social implications

From the social perspective, the findings indicate that improving energy utilization is dependent on the joint efforts of the government and market.

Originality/value

The study provides quantitative evidence to assess the synergic effect between government and the market in the low-carbon transition of the electric power industry. Particularly, to the best of the authors’ knowledge, it is the first to comprehend the role of the city low-carbon pilot policy and the construction of HSR in improving electricity efficiency.

Details

International Journal of Climate Change Strategies and Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-8692

Keywords

Article
Publication date: 23 August 2022

Qingqiu Gan

This study aims to investigate the influence of the financial system (financial development and financial structure) on firms' innovation efficiency in China.

Abstract

Purpose

This study aims to investigate the influence of the financial system (financial development and financial structure) on firms' innovation efficiency in China.

Design/methodology/approach

This study employs country level data of capital markets and financial institutions along with innovation data from 18 high-tech industries in China spanning the 2009–2016 period, and the stochastic frontier analysis (SFA) is applied to explore how financial development and financial structure affect the innovation efficiency of these industries.

Findings

Results show that financial development influences firms' innovation efficiency positively and the capital-market-based financial structure has a positive impact on innovation efficiency of high-tech industries. Furthermore, when the high-tech industries are grouped into five sub-industries, the results show that financial structure had different effects on the innovation efficiency in each sub-industry.

Originality/value

This work contributes to the empirical research on considering the influential factors of innovation efficiency from the perspective of financial system. This paper also extends the existing literature by the different influences of financial system on innovation efficiency in each sub-industry of Chinese high-tech industries.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 18 August 2022

Joanna Oczkowicz and Jan M. Myszewski

The purpose of this study is to investigate the system of factors influencing the efficiency of internal evaluation in Polish secondary schools.

Abstract

Purpose

The purpose of this study is to investigate the system of factors influencing the efficiency of internal evaluation in Polish secondary schools.

Design/methodology/approach

Data collected in interviews with evaluation experts and teachers on the barriers to the efficiency of internal evaluation and their causes were subjected to a qualitative cause-and-effect analysis.

Findings

Five barriers to the evaluation efficiency (6B model) and five actions of the school head stopping their impact (6A model) were identified. The latter include selecting the key evaluation function (3KEF model) and ensuring the conditions for efficiency in the improvement loop.

Research limitations/implications

Although the research was carried out in Polish schools, the conclusions indicate regularities affecting organizations throughout the world.

Practical implications

Students’ educational needs may exceed the schools’ ability to meet them at class time mostly due to resource constraints. The implementation of the principle of equal opportunities in education requires continuous improvement of the efficiency of schools’ processes. Evaluation can help qualify tasks for improvement.

Social implications

The level of engagement (reactive/active) of the school principal and teachers in evaluation and improvement is a crucial factor in overcoming the barriers to the efficiency of the school processes.

Originality/value

The ability to respond to the efficiency gaps of the school processes depends on the choice and efficiency of the KEF. The rationale for selecting the function and the schemes for its implementation have paradigmatic grounds.

Details

Quality Assurance in Education, vol. 30 no. 4
Type: Research Article
ISSN: 0968-4883

Keywords

Article
Publication date: 15 August 2022

Jie Wu, Qingsong Liu and Zhixiang Zhou

The purpose of this study is to evaluate the profit efficiency of decision-making units (DMUs) based on predicted future information to solve the lag problem of…

Abstract

Purpose

The purpose of this study is to evaluate the profit efficiency of decision-making units (DMUs) based on predicted future information to solve the lag problem of improvement benchmarks given by the traditional profit efficiency model.

Design/methodology/approach

This paper proposes a two-step profit efficiency evaluation method. The first step predicts the future input and output information of DMUs through the past time-series data, obtaining a likely production possibility set (PPS) and profit frontier for the next period. The second step calculates DMUs' profit efficiency based on the predictions obtained in the first step and provides predictive benchmarking for DMUs.

Findings

The empirical results show that the proposed method yields good solutions for the lag problem of benchmarks given in ex-post evaluation, enabling bank managers to use predicted future information to achieve better improvement. Besides, compared with the technical efficiency measure, profit efficiency can better reflect the financial situation of DMUs and give the specific gap between the evaluated and optimal DMU.

Practical implications

For bank managers, the authors' new technique is advantageous for grasping the initiative of development because this technique accounts for the future development of the whole industry and sets forward-looking targets. These advantages can help banks improve in a more favorable direction and improve the asset management ability of banks.

Originality/value

This paper combines the data envelopment analysis (DEA) profit efficiency model with performance prediction and proposes a new two-step profit efficiency model, filling a gap in previous studies.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Open Access
Article
Publication date: 4 August 2022

Shiqian Hu, Dan Li and Xiaodan Wang

To cope with climate change and achieve the dual carbon goal, China has actively promoted the implementation of carbon trading pilot policy, among which the power industry…

Abstract

Purpose

To cope with climate change and achieve the dual carbon goal, China has actively promoted the implementation of carbon trading pilot policy, among which the power industry plays an important role in China’s carbon emission reduction work. The purpose of this paper is to study the influence of carbon trading policy on the energy efficiency of power industry and achieve the comprehensive goal of carbon emission reduction, carbon peak and carbon neutralization.

Design/methodology/approach

This paper constructs the difference-in-differences model based on 2012–2019 provincial data to study the impact of carbon trading policy on energy efficiency in the power industry and its effect path. Heterogeneity analysis was conducted to compare the effects of carbon trading policy in eastern, central and western regions as well as at different levels of power structures.

Findings

Carbon trading policy can significantly improve the energy efficiency of the power industry, and the policy effect is more significant in eastern and western regions and areas with high power structure. Mechanism analysis shows that carbon trading policy mainly influences the energy efficiency of power industry by environmental protection investment, power consumption demand and industrial structure.

Originality/value

This paper uses provincial panel data to deeply study the influence of carbon trading policy on energy efficiency of the power industry and its effect path. By constructing the difference-in-differences model, this paper empirically analyzes the governance effect of carbon trading policy. Meanwhile, it controls individual and time effects to solve the endogeneity problem prevalent in previous literature.

Details

International Journal of Climate Change Strategies and Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-8692

Keywords

1 – 10 of over 131000