Total-factor Framework Research Articles

Measuring safety performance of construction employees using data envelopment analysis: A case in Australia

Introduction: Safety is one of the critical and persistent challenges in the construction industry. Measuring safety performance could allow decision-makers to check safety production processes and enhance the health and safety environment. Method: This study developed a total-factor framework based on the global Data Envelopment Analysis (DEA) method to measure safety performance. The performance trend and influencing factors of pure technical efficiency and scale efficiency were separately investigated. The safety performance of construction employees in Australia was measured as a case study. Results: The results demonstrate that the safety performance in the Australian construction industry has been evidently enhanced, which is mainly promoted by the progress of pure technical elements. The scale factors did not play a positive and important role in driving the performance. Conclusions: The increasing regional differences in safety performance could be reduced by learning the practices from the benchmark construction industry, such as a young worker program, small business safety program, workplace mental health program, and advanced construction technologies. Practical Applications: The method can be utilized to measure safety performance and investigate the pathways to enhance performance without influencing production inputs and outcomes. The model and experiences of how to promote safety performance on the policymakers and employers were recognized.

Agricultural tridimension pollution emission efficiency in China: An evaluation system and influencing factors

We innovated traditional one-sided agricultural carbon emission efficiency research, comprehensively explored the agricultural tridimension pollution emission efficiency (ATPEE), constructed an ATPEE evaluation system considering technological heterogeneity characteristics based on the meta-frontier nonradial directional distance function (NDDF) model in a total-factor framework, evaluated the ATPEE in 30 mainland China provinces from 1997 to 2021 for the first time, and empirically studied the factors influencing the ATPEE in China with the Tobit model. The results showed the following: (1) ATPEE improvement potentials of 75.16 % and 50.88 % occur under the meta and group frontiers, respectively. (2) The eastern region represents the potential optimal agricultural tridimension pollution emission technology, while the central and western regions exhibit a large gap with the national potential optimal technology level. (3) The ATPEE loss in the eastern and western regions mainly results from management inefficiency, while that in the central region largely results from technology gap inefficiency. (4) The effects of the industrialization rate, urban–rural income gap, agricultural production structure, financial support for agriculture, natural conditions and effective irrigation rate on the ATPEE in the different regions vary.

Total Factor Efficiency of Energy and Carbon Emissions in 18 Asian Countries: An Empirical Assessment

Energy efficiency is crucial for reducing energy consumption and mitigating the negative impact of carbon dioxide emissions on the environment. The present study aims to evaluate the energy efficiency and emissions efficiency of 18 Asian countries using the undesirable slack-based data envelopment model and a total factor framework for the period 2001–2020. It has been observed that none of the countries had significantly improved energy efficiency. The total factor energy efficiency (TFEE) index shows that Asian countries have varying levels of energy efficiency, with some countries having high potential for improvement and others already performing well. Kazakhstan and Iran have the most room for improvement, while China and the UAE have seen fluctuations in their TFEE scores. The category with the highest number of countries includes Singapore, Hong Kong, Pakistan, India, Japan, Saudi Arabia, Israel, the Philippines, Bangladesh, and Indonesia, with some experiencing significant drops in TFEE scores over the years. Similar patterns can be seen in the total factor carbon emissions efficiency (TFCEE) Index, suggesting that no country is entirely efficient in reducing carbon emissions. Kazakhstan maintains its position at the bottom of the ranking for lowering carbon emissions, while Bangladesh has shown more success. Overall, there is a need for continued efforts to improve energy efficiency in these nations to reduce their carbon footprint and contribute to global sustainability goals.

Regional green total factor performance analysis of China's construction industry based on a unified framework combining static and dynamic indexes.

It has an important meaning to improve green total factor performance in the construction industry for China's green and high-quality development. In addition to the traditional desirable economic output and undesirable CO2 emission output, the indicators representing social welfare of China's construction industry were incorporated into the total factor framework. On this basis, a global non-radial DEA approach was employed to explore the sources and the key factors leading to changes in regional green total factor performance of China's construction industry from both static and dynamic perspectives. The results were concluded as follows: (1) The lower energy efficiency and CO2 emission efficiency were the main reasons for low level of green total factor efficiency. During the sample period, energy efficiency increased rapidly while capital efficiency remained almost unchanged. (2) The green total factor productivity demonstrated an increasing trend, which was driven by technological progress rather than technical efficiency. An in-depth decomposition revealed that the deterioration of technical efficiency was mainly caused by the negative effect of CO2 emissions. (3) Regional green total factor performance of China's construction industry demonstrated obvious spatial heterogeneity. Each province should comprehensively consider its own characteristics of green development in the construction industry to formulate the corresponding optimization strategy. These findings can help decision makers design specific policies on regional-oriented green development of China's construction industry.

Empirical Analysis and Research on Urban Energy Efficiency Measurement Based on Computer Technology and Total Factor Framework

The utilization rate of energy can reflect the economic development quality and technical level of a country and a region, which directly affects the sustainable economic development. With the rapid progress of China’s urbanization, the total energy consumption is constantly rising, among which the urban energy consumption accounts for more than two thirds of the total energy consumption. Therefore, the urban energy utilization efficiency largely determines the overall level of China’s energy utilization. The results show that the growth rate of energy efficiency and the growth rate of energy use technology efficiency decrease under the constraint of environment. At the same time, due to the neglect of energy emission reduction technologies, the growth rate of technological progress in energy use decreases. As is known to all, carbon dioxide emitted by energy consumption causes a surge in greenhouse gases, leading to global climate anomalies, and China’s carbon dioxide emissions have now surpassed the United States as the number one carbon dioxide emitter. Energy efficiency is an important “energy source”. Drew Warren (1982) regards energy efficiency as the “fifth energy source” alongside coal, oil, natural gas and electricity. Energy efficiency needs to play a major role as a “source of energy” as it can reduce reliance on energy. Based on the analysis of the urban energy research framework, the article of urban energy efficiency measures are divided into broad sense and narrow sense two aspects, combined with domestic and foreign research results, respectively, the energy efficiency at home and abroad to use comparative evaluation index, energy consumption data acquisition method, from two aspects of theory and practical application discusses the applicable scope of different measure methods and its advantages and limitations in the urban energy efficiency analysis, and points out how to enhance the applicability of the overseas related research methods and clear policy boundary scope of relevant research conclusion.

From the Total-Factor Framework to Food Cost Performance Disaggregation—Developing an Innovative Model to Enhance Menu Performance

The menu serves as a form of advertisement and has also been recognized as an important marketing communication tool between restaurant and consumer. Extant literature have assessed the menu item performance by using the multi-factor efficiency index. However, there is a paucity of literature focusing on the efficiency disaggregation in order to improve the performance of individual food, labor, and other resources. The aim of this study was to determine the input targets for each menu item by comparing the efficiency frontier established by all menu items in two types of restaurant chains. In order to achieve this goal, the study sought to establish the food and labor cost performance assessment model utilizing the total-factor framework combined with a slack-based measure (SBM) of efficiency in data envelopment analysis (DEA) (SBM-DEA). Resource-saving target ratios (RSTR) for panel data with 35 menu items in these two different cultural type of restaurant chains including Chinese-style and Japanese-style restaurants for twelve months were assessed in a total-factor framework. The four-quadrant analysis based on efficiency and unit profit offered different strategies to the restaurateur being studied. The empirical findings indicated that the average total-factor food cost efficiency (TFFCE) was better than the total-factor labor cost efficiency (TFLCE) in these two types of restaurants. The TFFCE (80%) and TFLCE (61%) of the Chinese-style restaurant were better than those (TFFCE (76%) and TFLCE (50%)) of the Japanese-style restaurant in the observant periods. Even though the Chinese-style restaurant had a better resource efficiency, the restaurateur was still able to improve at least 20% in terms of food cost efficiency and 39% of labor cost efficiency, respectively. Managerial discussion and future study are also discussed.

Perspective of Local Government on the Performance Assessment of District Sports and Leisure Centers

This paper addresses the problem of performance management of operate-transfer (OT) project finance for public sports and leisure centers (SLC) from the perspective of local government. This study contributes to use an evolutionary theory of competitive advantage and mixed-methods, including a modified Delphi method to develop the efficiency-based performance model (EPM) under OT project finance for the public SLCs. The total-factor framework disaggregating the efficiency into an innovative output surplus target ratio (OSTR) provides local governments with a contracted period to manage the SLCs through further specific improvement advice. This study further proposed the four-quadrant matrix formulated by long-term efficiency and short-term profitability to identify the benchmark and improvement directions. The empirical results indicated that there are fifteen SLCs located in the benchmark quadrant. This study provides policy makers in the local governments with a scientific reference to keep or drop the current operating private enterprise in the next concession period. The most underperforming SLCs could follow this proposed quadrant analysis and OSTR index, utilizing their internal resources to develop more attractive and reasonable-price exercise courses for participant growth.

Total factor energy efficiency and economic development in Africa

This paper presents an energy efficiency assessment of 46 African countries and analyzes possible bidirectional relationship between energy efficiency and economic development within a three-stage framework. In the first stage, energy efficiency is measured within a total factor framework using the slack-based measure with undesirable output and sub-regional comparisons are done. The second stage assesses the determinants of energy efficiency in Africa by way of a bootstrapped truncated regression. The third stage tests the reverse causal relationship between energy efficiency and economic development using 2-stage least squares. The results showed African countries to be on average, 56% energy efficient within the study period. Other African sub-regions could adopt the energy efficiency policies of North Africa as benchmark to improve energy efficiency. Economic development and technological progress are found to have significant positive effects on energy efficiency of African countries, while higher energy prices lead to higher inefficiency. Also, a bi-causal relationship is found to exist between total factor energy efficiency and economic development, giving support to the concept of sustainable development and confirming the International Energy Agency’s assertion on the positive macroeconomic impacts of energy efficiency. African countries are therefore, encouraged to invest in energy efficiency technologies and policies to drive sustainable economic development.

A Dual Challenge in China’s Sustainable Total Factor Productivity Growth

Since total factor productivity growth plays an essential role in China’s economic growth, the source of this growth has been a critical issue over the past decades. Hence, this paper applies an input slack-based productivity (ISP) index to investigate the contributors (i.e., labor and capital inputs) to China’s total factor productivity growth. The ISP index, combining the features of the directional distance function and Luenberger productivity index, can calculate the productivity change of each input factor under the total factor framework. According to the decomposition analyses, we find that China is confronting a dual challenge in total factor productivity growth: first, capital productivity growth exhibits a remarkable slowdown after the mid-1990s; second, although labor productivity continually expands, the relative labor efficiency among provinces has deteriorated since the 2000s. The results imply that the government should not only advocate upgrading industrial structure, but also consider balanced regional development policies for China’s sustainable growth.

Measurement and convergence of carbon productivity across Shanghai’s manufacturing sectors

Purpose Increasing carbon productivity is an effective way to reduce carbon emissions, while boosting economic prosperity. For appropriate formulating and enforcement of energy saving and carbon emissions reduction policies in various sectors, it is of great significance to investigate the evolution characteristics and convergence modes of carbon productivity across the manufacturing sectors. Design/methodology/approach Using slack-based measure directional distance function (SBM-DDF) and global Malmquist–Luenberger (GML) productivity index, this paper measures the carbon productivities of 29 manufacturing subsectors in Shanghai, China, from 2001 to 2016 under the total factor framework. Furthermore, based on the convergence theories, it empirically examines the convergence of carbon productivity across these manufacturing sectors. Findings The measurement results suggest that the carbon productivities of the manufacturing sectors in Shanghai show an increasing tendency on the whole, and technical efficiency instead of technological change makes a main contribution to the increase. It is found that there is no obvious σ convergence across the manufacturing sectors in Shanghai, but there exist both absolute ß convergence and conditional ß convergence. Moreover, there is heterogeneity in convergence characteristics between the clean sectors and polluting sectors. The findings also show that firm size and industry structure have significant positive impacts on the growth of carbon productivities of the manufacturing sectors, whereas the impacts of capital deepening and energy consumption structure are significantly negative. Originality/value This paper measures the carbon productivities of the manufacturing subsectors by applying SBM-DDF and GML index, so as to improve the accuracy. It provides an insight into the convergence of carbon productivity across the manufacturing sectors.

China’s provincial total-factor air pollution emission efficiency evaluation, dynamic evolution and influencing factors

Abstract In recent years, air pollution situation becomes more severe and has seriously threatened sustainable economic development and public health in China. Combining the improved slacks-based measure (SBM) model, global Malmquist-Luenberger (GML) productivity index and panel Tobit model, this paper investigates the regional differences, dynamic evolution and influencing factors of China’s provincial air pollution emission efficiency over the period 2006–2015 under the total-factor framework. Our results show that: (1) China’s total-factor air pollution emission efficiency is relatively low and exhibits significant regional differences; (2) technological progress is the main contributor to ameliorate China’s provincial total-factor air pollution emission efficiency; (3) the total-factor air pollution emission efficiency gap between the higher- and the lower-efficient provinces will probably widen in the future; (4) China’s provincial total-factor air pollution emission efficiency is significantly positive related to the level of economic development, industrial structure optimization, technological innovation and foreign direct investment (FDI), is significantly negative related to the energy consumption structure. The above results indicate that China has made remarkable achievements in improving regional total-factor air pollution emission efficiency. However, there is considerable potential for further improvement. Policy options for China’s regional total-factor air pollution emission efficiency improvement include but not limited to optimizing industrial and energy consumption structure, promoting environmental technology innovation, strengthening cooperation and exchange between different regions, deepening the reform of energy market and energy pricing mechanism, actively introducing foreign investment, and further improving environmental regulation level.

The efficiency of electricity-use of China and its influencing factors

The consumption of electricity accounts for a higher and higher proportion of the terminal energy structure. The efficiency of electricity-use thus should be of great concern, especially under the background of energy saving and emission reduction. Instead of measuring the efficiency of electricity-use via electricity intensity, the input-oriented epsilon-based measure (EBM) model under variable returns to scale, supported by a total-factor framework, is employed to evaluate the efficiency of electricity-use of China’s 30 regions spanning from 2006 to 2015. Then kernel density estimation and Moran’s I index are used to depict its dynamic evolution characteristics and spatial agglomeration characteristics. Finally, a penalized panel quantile regression model with fixed effects, taking unobserved individual heterogeneity and distributional heterogeneity into account, is applied to estimate the effects of probable determinants on the efficiency of electricity-use. It found that there are significant differences in the efficiency of electricity-use in terms of time and space dimensions, whose distribution seems to be a projection of the level of regional economic development. The regional efficiency of electricity-use exhibits a descending trend and is positively spatially autocorrelated. The impacts of various factors, namely, income level, population size, industrial structure, urbanization and FDI intensity, are obvious heterogeneous throughout the distribution.

DO TEXT OR PHOTO MATTER FOR THE MARKETING PERFORMANCE OF SOCIAL MEDIA MESSAGE?

This paper utilized the dual coding theory (Yang, Hlee, Lee, & Koo, 2017) and theory of latent state–trait (LST) (Steyer, Schmitt and Eid, 1999) to the application of consumer impulse purchasing behaviors and further revealed that the number of reaching can thus be identified as a trigger for impulse buying on social media. Three inputs (number of color, text length, number of photo) and three outputs (number of likes; number of comments, and shares; and number of clicks on post) are used to develop this marketing message performance assessment model in the social medial based on the literature and expert opinions through data envelopment analysis (DEA). The disaggregate efficiencies are also assessed in order to improve the individual input resource performance in a total-factor framework. Resource-saving target ratios (RSTR) for 60 marketing message in a five-star hotel chain. The empirical findings indicate that the average total-factor text length efficiency (TFTLE) is worse than the total-factor photo efficiency (TFPE) in the Facebook platform in the five-star hotel chain. This result suggests that photo message is more attractive for viewer than the text message. Managerial discussion and the future studies are discussed.

Total-factor energy efficiency of coal consumption: An empirical analysis of China's energy intensive industries

Improvement of coal consumption efficiency is very important both for China in solving its problems of energy security and environmental pollution and for the world in addressing the issue of greenhouse gas emissions. Using a total-factor framework, this paper employs a data envelopment analysis (DEA) approach to evaluate the coal consumption efficiency of six energy intensive sub-industries in China in 2015. Coal consumption efficiency is factorized into economic efficiency and environmental efficiency, with sulfur dioxide, nitrogen oxide, and industrial smoke, dust and soot emissions treated as undesirable outputs of energy consumptions. The results show the following. (1) Of the six energy intensive sub-industries studied, two exhibit both DEA-effective coal economic efficiency and coal environmental efficiency. Coal economic efficiency is found to be greater than coal environmental efficiency, indicating that the benefits of economic efficiency have masked the negative effects of the environmental impact. China should therefore pay more attention to the clean utilization of coal. (2) Low environmental efficiency mainly resulted from the joint effects of pure technical efficiency and scale efficiency; therefore, enterprises in these industries must engage in management efforts to improve their ability to manage large enterprises. (3) The energy intensive industries characterized by coal environmental efficiency that failed to achieve pure technological effectiveness all exhibited input redundancy or output inadequacy of varying degrees while showing a potential for energy conservation and emissions reductions.

International Comparison of Total Factor Ecology Efficiency: Focused on G20 from 1999–2013

Little attention has been paid to international ecological efficiency, especially taking ecological footprint (EF), labor, and capital into account as multi-inputs to produce GDP in the total-factor framework. This study evaluates the total-factor ecological efficiency (TFEcE) of G20 during the period of 1999–2013 by employing slack-based measure (SBM) with EF as the index of comprehensive ecological inputs. Findings show that the average level of TFEcE of G20 from 1999 to 2013 is at a low level of about 0.54, which means there is a large space for the improvement of TFEcE. Furthermore, TFEcE of G20 is very imbalanced and there is a big gap between developed countries and developing countries in the G20. For the developing countries and developed countries in the G20, the analysis of factors that affect national TFEcE shows different statistical significance in the truncated regression model.

Total-factor ecology efficiency of regions in China

This paper combines the concept of Ecological Footprint (EF) with the framework of total-factor energy efficiency to develop a new index of total-factor ecology efficiency (TFEcE), which is constructed as the ratio of the target EF input obtained from SBM (slack-based measure) model to the actual ecology input under the consideration of labor and capital inputs. This paper computes the TFEcE of 28 provinces in China for the period 2000–2012. Findings show that China’s TFEcE remains a low level of 0.5, which urgently needs to be improved. China’s regional TFEcE is extremely unbalanced and the eastern area ranks first with the highest score. Compared with total-factor energy efficiency and traditional single-factor ecological efficiency, The TFEcE index evaluates ecology efficiency more comprehensively through taking EF in conjunction with the total-factor framework.

Understanding drivers of energy efficiency changes in China

Under a total-factor framework, this manuscript constructs a slacks-based measure data envelopment analysis (SBM-DEA) model and an index of total-factor energy efficiency (TFEE) to investigate the energy efficiency of the 29 provincial-administrative regions (PARs) in China during 1997–2011. Applying spatial panel data models to explore the regional clustering and influential factors of energy efficiency in China’s 29 provincial-administrative regions during 1997–2011, results show that China experienced a continuing increase in energy efficiency during the sample period. In addition, we find evidence of the diffusion of energy efficiency improvements. Research and development investment, particularly when interacted with increases in energy prices, and when government intervention is low, are a powerful drivers of efficiency improvements. We illustrate heterogeneous impacts across Chinese regions. Income gains in more industrialized provinces and education gains in less industrialized provinces also produce efficiency improvements. In contrast to existing literature, we do not find responsiveness to changes in energy prices, growth rates, or income per capita in less industrialized regions. These results highlight the uniqueness of the Chinese experience and warrant more in-depth exploration of the drivers of energy efficiency in China.

Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey

Regional energy and environmental efficiency measurement is a noteworthy research topic regarding regional development. Data Envelopment Analysis is a suitable technique in the studies of energy and environmental efficiency. This study investigates the efficiency and total-factor energy efficiency scores of the manufacturing industry in 26 regions of Turkey between the years 2003 and 2012, using four data envelopment analysis models supported by a total-factor framework. The first and the second models are based on absence and presence of undesirable outputs, respectively; the third model and the proposed new model aims to maximize energy saving potential considering undesirable outputs. The empirical results show that TR10-Istanbul region is the best performer and acts as a model for inefficient regions with its production composition. Total electricity saving potential is investigated per each region and for the manufacturing industry per each year between years 2003–2012. It is observed that Turkish manufacturing industry has an average electricity saving potential of 39.7%, which reaches its highest in 2004 and lowest in 2012. Another important finding of this study is the existence of a U-shaped relationship between gross value added per capita as regional development indicator and efficiency as well as total-factor energy efficiency index.

Measuring China's industrial energy efficiency, both DEA and directional distance function approach at the provincial level

Evaluation of the provincial industrial energy efficiency has recently attracted an increasing interest. A lot of previous researches were conducive to the evaluation of regional energy efficiency employing various types of DEA model. Using data envelopment analysis (DEA) and directional distance function (DDF) approach, this article constructs two models based on the total factor framework and analyses the energy efficiency and the energy-saving potential in China during 2008-2012; meanwhile, it combines partial factor energy efficiency and the total factor energy efficiency based on two models, and introduces the target energy intensity indicator measures the energy intensity efficiency of each province. The empirical study results show that in the target course of the study, east China is more effective than west and central China, thanks to the higher energy saving and emissions reduction in east China. The energy efficiency differences are significant among areas, and energy-saving and output expansions also have a great improvement potential. Thus, changing economic growth pattern from 'extensive type' to 'intensive type' is still a strategic priority for a very long time in China.

Provincial Energy Conservation Visual Potential Analysis Based on DEA Model

As the basic study of energy conservation, Apparent Potential of Energy Saving and Emission Reduction (AP-ESER) analysis is a key link of energy conservation work in China. Compared with developed countries, the performances of energy conservation are not remarkable in most developing countries, which ensured the dominant position of apparent potential in the whole potential field. Based on the non-parametric Data Envelopment Analysis (DEA) method model and total-factor framework, the study established an AP-ESER analysis system. We investigated a sample of 30 provinces in China, used K-means clustering method, GIS special labeling method and radar graphic method to analyze the results, and divided the 30 provinces into 5 clusters according to the visual potential of energy conservation. At the same time, we tried to find the key factors of energy conservation in each province following the status comparison of radar graphic method, and listed it under the sort of critical degree of the factors.