Improvement In Technical Efficiency Research Articles

ANALYSIS OF EFFICIENCY EVALUATION AND INFLUENCING FACTORS OF FISCAL INVESTMENT IN CHINESE HIGHER EDUCATION

This study employs the Malmquist index and Tobit regression models to evaluate the dynamics and regional disparities in higher education fiscal investment efficiency, based on comprehensive analyses of panel data from 31 provincial administrative units in China from 2002 to 2021. Research findings reveal that improvements in technical efficiency are crucial for the Chinese government to enhance investment efficiency, with significant regional variations. The Eastern region excels in technical efficiency and technological progress, while the Central and Western regions lag. Tobit regression analysis indicates that the educational level of faculty, student-faculty ratio, and research investment intensity significantly positively influence efficiency. In contrast, the negative impacts of government fiscal capacity, per-student educational expenditure index, and faculty title structure highlight structural issues in higher education investment. Based on these findings, we propose some recommendations for government policy amendments that aim to strengthen technological innovation and optimal resource allocation, enhance teacher quality and scientific research investment, encourage the integration of educational resources with urban development, and establish a scientific evaluation and monitoring mechanism to boost the efficiency of fiscal investment in higher education and foster balanced regional development.

Environmental certification and the financial performance of passenger airlines. The mediating effect of image perception, asset management and employee behaviour

Passenger airlines is an important sector throughout the world. However, it has faced criticism and pressure due to its harmful effects on the planet, leading airlines to adopt measures to protect the environment. As environmental responsibility can be a source of competitive advantages resulting from an improvement in image and internal technical and operational efficiency, it could increase their financial performance. Therefore, the aim of this study is to analyse whether their financial performance increases as a result of the competitive advantages gained from the effect of their environmental attitude on the environmental image of passengers, sustainable asset management, and employee ecological behaviour. Using the panel data technique for the 2010–2019 period, a comparison is made of certified and non-certified passenger airlines, differentiated according to ownership, routes they operate, fares, belonging to an alliance and the airline's world region. On the whole, the evidence obtained shows that while the effect of certification on the environmental image of passengers and on sustainable asset management does not increase the financial performance of certified airlines, it does so partially with respect to employee ecological performance. It could be affirmed that the funds and efforts allocated to being more respectful towards the environment do not lead to competitive advantages that could have a greater impact on financial performance.

Productivity and growth decomposition: a novel single-index smooth-coefficient stochastic frontier approach

Abstract Our paper investigates productivity, output growth and total factor productivity (TFP) growth using a novel single-index smooth-coefficient stochastic frontier approach and two firm-level datasets respectively from the high technology (high-tech) manufacturing and Knowledge Intensive Business Services (KIBS) sectors in Norway. The approach considers input productivity and technical inefficiency to be flexible functions of production environmental variables indexed with unknown parameters for more precise estimation of marginal effects of these variables on the frontier and inefficiency. Output growth is decomposed into technical change (TC), input-driven component (IDC) and efficiency change (EC), while TFP growth is decomposed into TC, scale component and EC. The primary objective is to (i) maximise output through the frontier and efficiency channels and (ii) enhance productivity growth through such channels as technical progress and efficiency improvement, specifically tailored for the manufacturing and services industries. The empirical results reveal substantial heterogeneity in technology across firms. Overall speaking, geographical industrial concentration, export intensity and urbanisation positively influence output in both sectors. Technical progress contributes to TFP growth in both sectors; however, TC is biased towards capital in the high-tech sector and driven by labour in the KIBS sector. In addition to TC, TFP growth in the high-tech and KIBS sectors also benefits from EC and IDC, respectively.

Technological development and eco-efficiency: Drivers of total factor productivity in OECD countries

This study delves into the total factor productivity growth in OECD countries, focusing on the crucial role of technological advancement and environmental management. By utilizing the Malmquist-Luenberger index, the paper encompasses both positive and negative outputs, such as pollution, providing a comprehensive productivity analysis by breaking it down into efficiency and technical change. Data from 36 OECD countries from 2000 to 2021 were examined to uncover trends and patterns in productivity growth and its unintended environmental consequences. The results emphasize the dominant influence of technological progress, particularly after 2006, as the primary driver of productivity growth, surpassing improvements in technical efficiency. A significant increase in technical change (1.56 in 2021) compared to technical efficiency (1.05) underscores the importance of sustained investment in research and development (R&D), which correlates positively with patent generation and technological advancement. The study also illustrates that OECD countries have effectively integrated eco-efficient practices, aligning with global trends in environmentally conscious productivity analyses. By integrating environmental outputs such as PM2.5 pollution, the analysis demonstrates that countries mitigating these adverse effects achieve higher productivity growth. These findings challenge conventional productivity models, where productivity diminishes when environmental aspects are considered. The analysis emphasizes the necessity for tailored policy approaches to address disparities in R&D investments, technological adoption, and eco-efficiency among countries. Countries with more significant R&D investments consistently demonstrate superior technological advancement in patents (0.745). Policymakers are urged to prioritize long-term strategies that foster technological innovation and environmental sustainability to ensure sustained productivity growth and economic resilience.

The High-Quality Development of the Construction Industry in the Context of the Digital Economy—Based on the Mediating Effect of Entrepreneurship

The digital economy is an important engine in leading the high-quality development of the economy, and entrepreneurship is an endogenous force propelling economic growth. These factors are essential drivers for advancing the transformation and upgrading of the construction industry and improving efficiency. This study integrates entrepreneurship into the analytical framework of industrial development and explores the primary pathways and theoretical mechanisms of the digital economy for the high-quality development of the construction industry from the dimensions of entrepreneurial innovation spirit and entrepreneurial pioneering spirit. On this basis, we empirically test the role mechanism between the digital economy, entrepreneurship, and the high-quality development of the construction industry. The results of this study indicate that (1) the digital economy significantly promotes the high-quality development of the construction industry through an improvement in technical efficiency; (2) the innovation and entrepreneurship of entrepreneurs are important mechanisms for the digital economy to promote the high-quality development of the construction industry, and at this stage, entrepreneurial spirit promotes more than the spirit of innovation; and (3) the development of the digital economy plays a greater role in enhancing low-productivity regions and the central and eastern regions, and the inclusive characteristics of the digital economy are beginning to emerge.

Digitalization and Agricultural Green Total Factor Productivity: Evidence from China

Based on panel data of 31 provinces (autonomous regions and municipalities) in China from 2011 to 2022, this paper empirically examines the impact of digitalization on the inputs and outputs of the agricultural production process, and thereby derives the effects and mechanisms by which digitalization empowers the growth of agricultural green total factor productivity. The study finds that agricultural and rural areas’ digitalization significantly improves agricultural green total factor productivity, and this promotion mainly comes from the improvement of technical efficiency. Further analysis shows that digitalization mainly reduces land input and labor input, increases expected output, and reduces undesired output during the agricultural production process to achieve an improvement in agricultural green total factor productivity, indicating that digitalization has altered the allocation of agricultural factors. Heterogeneity analysis finds that the effect of digitalization on the growth of agricultural green total factor productivity is more pronounced in the eastern regions, southern regions, and areas with higher levels of agricultural digitalization, indicating that the development of digitalization exacerbates the gap in agricultural green total factor productivity among regions.

Macro, meso, and micro decomposition of energy consumption in Ghana: Role of shocks (local and global) and energy policy interventions

This study conducted a macro, meso, and micro index decomposition analysis of energy consumption in Ghana from 2013 to 2020, highlighting the roles of local (e.g., power crisis) and global (e.g., COVID-19) shocks, as well as energy policy initiatives on technical efficiency improvement. We found that technical efficiency improvements varied at different times of the implementation period of energy policy initiatives and across various macro, meso, and micro-sectors of the economy. Technical efficiency improvement varied significantly across these sectors but worsened much more in service sector during periods of local and global shocks. Additionally, the importance of activity, structural, and intensity effects differed over time and across the macro, meso, and micro-sectors of the economy. We discuss the policy implications of these findings.

Solar empowerment in agriculture: investigating photovoltaic energy’s impact on efficiency among wheat farmers

Persistent electricity shortages in Pakistan, causing prolonged grid power load shedding, have adversely impacted various sectors, notably agriculture and the livelihoods of rural farmers. Literature suggests that adopting photovoltaic solar energy can mitigate these issues. This research aims to measure the impact of photovoltaic solar energy on the technical efficiency of food productivity in Khyber Pakhtunkhwa, Pakistan, applying data from 580 respondents. Addressing self-selective bias through ESR and stochastic frontier production function model is utilized to assess technical efficiency. The findings of this study reveal that farmers using solar energy experience a significant improvement in technical efficiency, with 15.8 percent of them achieving a 7.643 percent increase, after accounting for self-selection bias. Furthermore, the positive effects are more pronounced among larger farms and those with greater farming experience. This study underscores the importance of evidence-based approaches in implementing solar energy solutions, highlighting their potential to foster sustainability and equitable development at the grassroots level. The research culminates with policy recommendations that underscore the importance of promoting the photovoltaic solar energy use among farmers to improve food security and increase agricultural productivity.

Data Envelopment Analysis (DEA) to Estimate Technical and Scale Efficiencies of Smallholder Pineapple Farmers in Ghana

This study focuses on evaluating the technical and scale efficiencies of smallholder pineapple farmers in Ghana’s Central Region. We surveyed 320 participants selected using random sampling and applied an input-oriented Data Envelopment Analysis (DEA) method to gauge their technical, pure, and scale efficiencies. Our findings indicate that the mean technical efficiency among these farmers is 0.505, with individual scores ranging from 0.079 to 1.000. Notably, 90.82% of the farmers are operating below maximum efficiency levels, suggesting a potential input reduction of up to 49.5% while maintaining current production levels. Relaxing the assumption of constant returns under Variable Returns to Scale (VRS) conditions reveals a notable improvement in technical efficiency, with 10.82% more farmers achieving optimal efficiency levels. Furthermore, our analysis highlights scale inefficiencies, with 67.26% of farmers operating below optimal scale levels. By increasing production by 22.8%, these scale-inefficient farmers could enhance their efficiency and productivity within existing technological frameworks. These findings underscore the importance of collaborative efforts among policymakers, practitioners, and stakeholders within the agricultural value chain to implement interventions such as improving access to technology and innovation for smallholder farmers and making necessary investments in farmer education and training programs to enhance both technical and scale efficiencies in Ghana’s pineapple sector. Such initiatives can drive sustainable growth, improve farmers’ livelihoods, and bolster the sector’s overall competitiveness.

Evaluating China's primary healthcare services' efficiency and spatial correlation: a three-stage DEA-Malmquist model.

Enhancing the efficiency of primary healthcare services is essential for a populous and developing nation like China. This study offers a systematic analysis of the efficiency and spatial distribution of primary healthcare services in China. It elucidates the fundamental landscape and regional variances in efficiency, thereby furnishing a scientific foundation for enhancing service efficiency and fostering coordinated regional development. Employs a three-stage DEA-Malmquist model to assess the efficiency of primary healthcare services across 31 provincial units in mainland China from 2012 to 2020. Additionally, it examines the spatial correlation of efficiency distribution using the Moran Index. The efficiency of primary healthcare services in China is generally suboptimal with a noticeable declining trend, highlighting significant potential for improvement in both pure technical efficiency and scale efficiency. There is a pronounced efficiency gap among provinces, yet a positive spatial correlation is evident. Regionally, efficiency ranks in the order of East > Central > West. Factors such as GDP per capita and population density positively influence efficiency enhancements, while urbanization levels and government health expenditures appear to have a detrimental impact. The application of the three-stage DEA-Malmquist model and the Moran Index not only expands the methodological framework for researching primary healthcare service efficiency but also provides scientifically valuable insights for enhancing the efficiency of primary healthcare services in China and other developing nations.

Rising Tides of Knowledge: Exploring China’s Higher Education Landscape and Human Capital Growth

AbstractThis study examines the status of human capital in China’s higher education system by analyzing the quantity of higher education institutions as a metric. The results show a general enhancement in human capital in all regions, along with an optimized structure. This is demonstrated by a decline in the primary education demographic, a consistent growth in secondary education, and a rapid surge in the higher education demographic. The percentage of junior college students has remained steady, whereas the ratios of undergraduate and graduate students have been consistently increasing. The Malmquist index method is used to analyze changes in total factor productivity (TFP) among provinces and regions by breaking it down into technical level and efficiency changes. From 2005 to 2010, there was a general increase in total factor productivity (TFP) and technical proficiency, although technical efficiency showed only slight enhancement. TFP and technical level growth decelerated from 2011 to 2020, while technical efficiency stayed above 1. These findings indicate that China’s total factor productivity (TFP) growth is mainly driven by technological advancements, with minimal improvements in technical efficiency.

Fiscal space for the immunisation program in Zambia– an efficiency analysis approach

ObjectiveThe immunisation programme in Zambia remains one of the most effective public health programmes. Its financial sustainability is, however, uncertain. Using administrative data on immunisation coverage rate, vaccine utilisation, the number of health facilities and human resources, expenditure on health promotion, and the provision of outreach services from 24 districts, we used Data Envelopment Analysis to determine the level of technical efficiency in the provision of immunisation services. Based on our calculated levels of technical efficiency, we determined the available fiscal space for immunisation.ResultsOut of the 24 districts in our sample, 9 (38%) were technically inefficient in the provision of immunisation services. The average efficiency score, however, was quite high, at 0.92 (CRS technology) and 0.95 (VRS technology). Based on the calculated level of technical efficiency, we estimated that an improvement in technical efficiency can save enough vaccine doses to supply between 5 and 14 additional districts. The challenge, however, lies in identifying and correcting for the sources of technical inefficiency.

Evaluation of Carbon Emission Efficiency of Chinese Oil and Gas Enterprises

This paper constructs a carbon emission efficiency evaluation model using the non-expected output SBM model and the Global-Malmquist-Luenberger model to statically and dynamically evaluate the carbon emission efficiency of 69 oil and gas enterprises from 2016 to 2021. The results found that the overall carbon emission efficiency of China's oil and gas enterprises is at a relatively low level, but with an upward trend. The results also show that there are differences in carbon emission efficiency among oil and gas enterprises, and that the carbon emission efficiency of most oil and gas enterprises improves thanks to the improvement of technical efficiency.

Environmental insurance and green productivity: A firm-level evidence from China

Green transformation is currently a major challenge for both developed and developing economies, while the role of environmental insurance (EI) in green productivity in developing economies remains unclear. Using firm-level data from Chinese A-shape listed companies, this study investigates the relationship between EI on green total factor productivity (GTFP) along the period 2010–2019. To do so, a slack-based measurement model integrated with Global Malmquist-Luenberger approach (SBM-GML) is applied in GTFP calculation, and then a time-varying difference-in-difference (DID) setup is employed for empirical analysis, as well as its combination with propensity score matching method (PSM-DID) to overcome the sample self-selection bias. We find that EI significantly promotes firm's GTFP by about 0.22 units, which is mainly driven by the improvement of technical efficiency rather than technological progress. Further analysis exploring channels suggests that EI promotes GTFP by alleviating financing constraints and stimulating green innovation. However, the heterogeneity analysis shows that both financing constraint mechanism and technological innovation mechanism are mainly observed in heavily polluting and non-state-owned enterprises (non-SOEs). Our findings provide a new insight for policy-makers that utilizing environmental insurance can promote green productivity, but which should be focused more on those enterprises who are difficult to absorb external financing and technological innovation resources.

Drivers of unconditional income convergence

We decompose economic growth into technical efficiency change, technological change, and capital accumulation to analyze the drivers of unconditional income convergence across countries observed in recent decades. Our analysis suggests that technical efficiency improvement and capital accumulation are the main drivers of the observed unconditional convergence. Specifically, developing countries experienced faster efficiency improvement than developed countries in the period of unconditional convergence (1995–2019), which was not the case in the preceding period characterized by the lack of income convergence (1970–1995).

Technical standardization and total factor productivity in innovation-driven development: Evidence from China.

Innovation drive differs from investment drive and resource drive in that it focuses on knowledge and skills to promote productivity growth. By integrating technical standards within the framework of an innovation-driven development system in this work, theoretical implications for this development strategy may be revealed. Following our theoretical study, we built a PECM utilizing China's inter-provincial panel data from 2007 to 2020 to investigate the long and short-term relationships between standardization, R&D, and innovation-driven development. The following are the key findings: First, both standardization and R&D are the nation's critical engines of innovation-driven development. Second, standardization has the greatest impact on TFP through improving technical efficiency, whereas R&D drives both technical development and technical efficiency improvement. Third, while the influence of technical standard drafters' production scale on scale efficiency was insignificant from 2007 to 2013, it became substantial after 2014 with China's macroeconomic reform of "transforming the mode and changing the structure."

Drivers of global energy export dependency: A decomposition analysis

Exploring energy export dependency under the carbon neutrality target is crucial for energy security and low-carbon transition. Currently, few studies have examined drivers of energy export dependency; furthermore, most of them failed to capture the impact of technology on energy change and were unable to explain the causal factors of energy intensity decline. This study analyzed the trends and drivers of energy export dependency in 40 major countries from 2000 to 2019 through a decomposition approach, and explained the decline of energy intensity caused by technological progress. The empirical results indicate that energy prices and energy export importance are the key drivers of the increase in energy export dependency in OECD countries, while technological progress can effectively reduce the energy export dependency of non-OECD countries by decreasing energy intensity. In addition, OECD countries pay attention to capital-energy substitution capacity, while non-OECD countries attach importance to the improvement of technical efficiency. These findings provide a scientific reference for energy transition and sustainable development in various countries.

Efficiency and productivity analysis of maternal and infant healthcare services in Sub-Saharan Africa.

The paper examines the efficiency and productivity of Sub-Saharan African (SSA) countries towards maternal and infant healthcare services between 2015 and 2019. Data envelopment analysis is utilised to evaluate efficiency, and Malmquist-Luenberger's (ML) productivity estimation is employed for productivity analysis. The results indicate inefficiency in SSA maternal and infant healthcare services. Average efficiency is pegged at 85%, and 60% of the countries evaluated had below-average efficiency. Effects of socioeconomic dynamics of countries were analysed. Preliminary estimations on the impact of Gross domestic product (GDP), education, urban population, and total population on efficiency are not significant. Although GDP and education sometimes show that they influence efficiency positively. Sensitivity analysis indicates efficiency to be more responsive to health expenditure, as well as to nurses and midwives. ML Productivity decomposition into technical efficiency change and technological change indicates improvement in technical efficiency as the principal driver of efficiency and productivity. Policy recommendations are made in line with the findings, requirements, and constraints of SSA countries.

The Financial Density and Improvement of Urban Technological Efficiency: An Estimation Based on the Stochastic Frontier Approach

Exploring the relationship between finance and economic growth is a key direction of financial economics. However, most of the literature starts from the aggregate perspective and uses the GDP or per capita GDP as the explained variable to study the role of finance. Such a perspective ignores the heterogeneity of financial activities with respect to geographical distribution and makes it difficult to distinguish the roles of factor input and efficiency improvement. Because of this, this article introduces a “density” perspective on new economic geography and the measurement of the efficiency of the transition of development economics into financial economics. This article uses the stochastic frontier analysis (SFA) method to measure the technical efficiency (TE) of 272 cities in China from 2005 to 2018 and then, based on “forward-looking” and “backward-looking” methods, measures the impact of financial density on urban technical efficiency. This study found that overall, before the financial crisis in 2008, the contribution of financial density to technical efficiency showed a downward trend, and in the regional and provincial dimensions, the distribution of financial density’s contribution to technical efficiency was generally in line with that of backward regions, with less regularity in developed regions. In the urban dimension, the contribution rate of financial density to resource-based cities with slow technological progress or advanced cities with rich financial resources is not very prominent and may even play a negative role; however, cities that are at a medium level of development, rich in population resources, have convenient transportation, and have a certain industrial foundation can greatly promote the improvement of technical efficiency. Therefore, it may be possible to optimize the marginal contribution of urban financial density to the technical efficiency of Chinese cities by encouraging the flow of financial resources and activities from cities with small marginal effects to those with large marginal effects.

OVERCOMING THE BARRIERS TO THE DIGITAL TRANSFORMATION OF INDUSTRIAL ENTERPRISES THROUGH THE BUSINESS MODEL SELECTION MECHANISM

The article describes the main barriers to digital transformation faced by industrial enterprises in various industries, such as: lack of appropriate funding, information security risks, insufficient digital skills of employees, insufficient maturity of current processes, internal resistance to change, insufficient awareness of managers, lack of certainty over the future of digital standards. To analyse the barriers, the author used a three-step approach, including a literature review, a primary research with representatives of the companies, and a qualitative comparative analysis that are based on the Kruskal – Wallis test and used to identify differences between groups of enterprises. To overcome the barriers identified by the author it was offered to use a mechanism of a business model selection, which takes into account the assessment of obtained competitive advantages (improvement of operational, financial and technical efficiency), digital maturity (digital culture level, staff qualifications, the quality of business process organisation and access to digital infrastructure) and risks (non-receipt of expected income from business model implementation, information security, reputational and personnel). The novelty of the proposed business model selection mechanism for an industrial enterprise is to improve the classification and develop a multi-criteria mechanism for choosing a business model, which would be implemented using a knowledge-based system incorporating a fuzzy inference mechanism.