Total factor productivity of land urbanization under carbon emission constraints: a case study of Chengyu urban agglomeration in China

In consideration of energy and environmental inefficiency brought about by urban construction, sustainable urbanization has become a hot issue in recent years. In the process of land urbanization, the source of economic growth can be attributed to technical progress and efficiency improvement. To explore the driving factors of land urbanization efficiency and its dynamic changes, the total factor productivity (TFP) and its components of land urbanization was introduced. The spatial-temporal variations of land urbanization of Chengyu urban agglomeration in Western China were estimated by using the Malmquist-Luenberger (ML) productivity index with undesirable output in this study. Results demonstrate that: (1) the average TFP of land urbanization (LUTFP) of Chengyu urban agglomeration in China over time with carbon emissions (1.029) is 1.2 percent lower than that without carbon emissions (1.041). Furthermore, the LUTFP with CO2 emissions is lower than the LUTFP without CO2, demonstrating that land urbanization generates social and economic benefits at the cost of resource consumption. (2) LUTFP of Chengyu urban agglomeration under carbon emission constraints presents a generally rising trend in the past ten years and technical progress is the major source of such growth. Efficiency has become a major barrier against the improvement of productivity. (3) LUTFP indexes in Chongqing City and Chengdu plain economic region are generally higher than those of the south and northeast Sichuan economic zones. However, LUTFP of different cities tends to be in equilibrium gradually

Sustainability and Related Factors of High Speed Railways

High-Speed Railways (HSR), which represent a safe and sustainable mode of transportation, provide access and mobility for the society, and support the growth of the economy in addition to creating new jobs, supporting welfare, and promoting local business activities. This research addresses the shortage of knowledge in evaluating the performance of selected HSR systems and in distinguishing the factors that contribute to the sustainable performance of HSRs. The aim of this study is to evaluate the sustainability of selected HSRs and identify factors that affect such sustainability. The objectives of this research are to evaluate productivity, technical and technological efficiency of the selected HSRs, define the factors that can affect productivity and efficiency scores and make suggestions for improving the sustainability of HSRs. The secondary data methodology has been used, supported by empirical evidence. Most of the data was gathered from the Internet, research in depth of the high-speed railways in the selected countries, and International Union of Railway’s websites in addition to analysing railway statistics and data from European and institutional publications. This includes the use of a multi-stage approach of applying three specialised software packages, namely, NVivo, DEA, and ISM SPSS. The main findings show that HSRs in Asia has higher productivity and higher efficiency scores than that of HSRs in Europe. The research found that the key factors among all the identified factors that affected the productivity and efficiency of HSRs are; density of population, average traction power of HSR trains, average time that passengers spend on trains and average distance that passengers travel on the HSR. The findings of this research can help develop strategic guidelines to improve the performance and, by the result, the sustainability of HSRs. The recommendations are drawn for more research expansion, including the consideration of other HSRs, particularly their best practices

A systematic review of empirical methods for modelling sectoral carbon emissions in China

© 2019 Elsevier Ltd A number of empirical methods have been developed to study China's sectoral carbon emissions (CSCE). Measuring these emissions is important for climate change mitigation. While several articles have reviewed specific methods, few attempts conduct a systematic analysis of all the major research methods. In total 807 papers were published on CSCE research between 1997 and 2017. The primary source of literature for this analysis was taken from the Web of Science database. Based on a bibliometric analysis using knowledge mapping with the software CiteSpace, the review identified five common families of methods: 1) environmentally-extended input-output analysis (EE-IOA), 2) index decomposition analysis (IDA), 3) econometrics, 4) carbon emission control efficiency evaluation and 5) simulation. The research revealed the main trends in each family of methods and has visualized this research into ten research clusters. In addition, the paper provides a direct comparison of all methods. The research results can help scholars quickly identify and compare different methods for addressing specific research questions

Deregulation, Entry of Foreign Banks and Bank Efficiency in Australia

This study considers the efficiency of banking in Australia during the post-deregulation period 1988-2001. Since 1986 restrictions upon foreign bank entry and foreign ownership have been affectively abolished. Using Data Envelopment Analysis (DEA) and Malmquist Indices, we find that the new foreign banks are more (input) efficient than domestic banks, mainly due to their superior scale efficiency. However, this superior efficiency did not necessarily result in superior profits. Our results are consistent with the limited global advantage hypothesis of Berger et al (2000). We argue that the major Australian banks have used size as a barrier to entry to the new entrants in the post-deregulation period. Furthermore, bank efficiency seems to have increased post-deregulation and the competition resulting from diversity in bank types was important to prompt improvements in efficiency. Finally, the recession of the early 1990s resulted in a distinct shift in the process of efficiency changes.foreign banks, deregulation, data envelopment analysis, Malmquist indices

Strategy Tripod Perspective on the Determinants of Airline Efficiency in A Global Context: An Application of DEA and Tobit Analysis

The airline industry is vital to contemporary civilization since it is a key player in the globalization process: linking regions, fostering global commerce, promoting tourism and aiding economic and social progress. However, there has been little study on the link between the operational environment and airline efficiency. Investigating the amalgamation of institutions, organisations and strategic decisions is critical to understanding how airlines operate efficiently. This research aims to employ the strategy tripod perspective to investigate the efficiency of a global airline sample using a non-parametric linear programming method (data envelopment analysis [DEA]). Using a Tobit regression, the bootstrapped DEA efficiency change scores are further regressed to determine the drivers of efficiency. The strategy tripod is employed to assess the impact of institutions, industry and resources on airline efficiency. Institutions are measured by global indices of destination attractiveness; industry, including competition, jet fuel and business model; and finally, resources, such as the number of full-time employees, alliances, ownership and connectivity. The first part of the study uses panel data from 35 major airlines, collected from their annual reports for the period 2011 to 2018, and country attractiveness indices from global indicators. The second part of the research involves a qualitative data collection approach and semi-structured interviews with experts in the field to evaluate the impact of COVID-19 on the first part’s significant findings. The main findings reveal that airlines operate at a highly competitive level regardless of their competition intensity or origin. Furthermore, the unpredictability of the environment complicates airline operations. The efficiency drivers of an airline are partially determined by its type of business model, its degree of cooperation and how fuel cost is managed. Trade openness has a negative influence on airline efficiency. COVID-19 has toppled the airline industry, forcing airlines to reconsider their business model and continuously increase cooperation. Human resources, sustainability and alternative fuel sources are critical to airline survival. Finally, this study provides some evidence for the practicality of the strategy tripod and hints at the need for a broader approach in the study of international strategies

CO2 emissions reduction of Chinese light manufacturing industries:a novel RAM-based global Malmquist-Luenberger productivity index

Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO2 emissions reduction in China. In China industry contributes 84.2% of the total CO2 emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO2 emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist-Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO2 emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed

Performance of cultural heritage institutions: A regional perspective

Producción CientíficaMost studies on performance evaluation in the cultural sector are based on the efficiency assessment of a network of institutions. Nevertheless, very few works take territorial divisions as the case study. Under this approach, we design a spatial production function which merges several cultural resources in order to optimize the impact of a regional system of cultural institutions in terms of cultural production and use of services provided. The aim of this paper is therefore to evaluate the efficiency of cultural heritage institutions in Spain from a regional perspective. We take regional networks of museums and libraries as emblematic case studies over a long period, from 2002 to 2020. We first apply a dynamic-network DEA model to measure efficiency, which allows the production function to be divided into stages and time intervals, considering inter-reliant inputs between production phases and time lapses. We also apply truncated regression models to study the effect of external variables on regional cultural efficiency, especially those related to socioeconomic conditions in regions, the scope of the cultural and tourist sector, and institutional indicators. Results show that regional cultural efficiency depends on the level of training and on the demographic structure rather than on economic wealth. Differences are also found between the goals of cultural production and cultural consumption (visitor impact). These findings might prove useful for policy implications regarding resource allocation vis-à-vis defining and accomplishing cultural purposes at a regional scale, and also for revealing causes of inefficiency with a view to improving quality in institutions –which ultimately drives economic development

Eco-productivity analysis of the municipal solid waste service in the Apulia region from 2010 to 2017

This paper presents a dynamic efficiency study of the solid waste management in the municipalities of the Apulia region (Southern Italy). The study employs the non-parametric Global Malmquist Index to measure the change in productivity of the municipal solid waste service from 2010 to 2017. Three different DEA-based models are implemented to measure productivity. The first model computes the service productivity solely from the economic perspective, while the second and third models compute the service productivity from both the economic and environmental perspectives. Adopting two distinct perspectives provides a more comprehensive insight into the performance of the waste management service considering the productivity and the eco-productivity of service provision. The results from the productivity analysis show that, between 2010 and 2017, the municipal solid waste sector was still facing a transitional period characterized by low cost-efficiency and productivity growth measurements. Vice versa, the efficiency and productivity indicators improve when the analysis is performed accounting for the environmental impact. Indeed, both the eco-efficiency and eco-productivity measures increase from 2010 to 2017. Findings demonstrate the critical importance to include environmental indicators in the efficiency and productivity analysis

A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries

This paper aims to address the problem of allocating the CO2 emissions quota set by government goal in Chinese manufacturing industries to different Chinese regions. The CO2 emission reduction is conducted in a three-stage phases. The first stage is to obtain the total amount CO2 emission reduction from the Chinese government goal as our total CO2 emission quota to reduce. The second stage is to allocate the reduction quota to different two-digit level manufacturing industries in China. The third stage is to further allocate the reduction quota for each industry into different provinces. A new inverse data envelopment analysis (InvDEA) model is developed to achieve our goal to allocate CO2 emission quota under several assumptions. At last we obtain the empirical results based on the real data from Chinese manufacturing industries