Sustainability efficiency and carbon inequality of the Chinese transportation system: a robust bayesian stochastic frontier analysis

This study focuses on the sustainability efficiency of the Chinese transportation system by investigating the relationship between CO2 emission levels and the respective freight and passenger turnovers for each transportation mode from January 1999 to December 2017. A novel Robust Bayesian Stochastic Frontier Analysis (RBSFA) is developed by taking carbon inequality into account. In this model, the aggregated variance/ covariance matrix for the three classical distributional assumptions of the inefficiency term – Gamma, Exponential, and Half-Normal – is minimized, yielding lower Deviance Information Criteria when compared to each classical assumption separately. Results are controlled for the impact of major macro-economic variables related to fiscal policy, monetary policy, inflationary pressure, and economic activity. Results indicate that the Chinese transportation system shows high sustainability efficiency with relatively small random fluctuations explained by macro-economic policies. Waterway, railway, and roadway transportation modes improved sustainability efficiency of freight traffic while only the railway transportation mode improved sustainability efficiency of passenger traffic. However, the air transportation mode decreased sustainability efficiency of both freight and passenger traffic. The present research helps in reaching governmental policies based not only on the internal dynamics of carbon inequality among different transportation modes, but also in terms of macro-economic impacts on the Chinese transportation sector.Indisponível

Environmental and Energy Efficiency Evaluation Based on Data Envelopment Analysis (DEA)

Efficiency and productivity assessment are essential to ensure the long-term financial sustainability of countries, services and processes. In the last few years, there has been an increasing interest in the environmental effects of economic activities, and the need to assess the environmental and energy efficiency has been internationally recognized. Energy and environmental efficiency assessments of decision-making units (DMUs), such as countries, utilities, processes and services are relevant and have strong implications for companies, regulators, stakeholders, policy makers, and customers. To improve both the decision-making process and the management of DMUs, fundamental and practical knowledge about energy and environmental efficiency and productivity is essentia

Evolution of green shipping research: themes and methods

Over the past 30 years, there have been growing concerns on theenvironmental impacts of maritime transportation, which have attractedgreat attention from both academia and practitioners. Understandingdevelopments in this area can help guide future research. We conducteda comprehensive review of green shipping research, comprising 213papers published in transportation journals in SSCI of 2017 over theperiod 1988–2017. We find that research on green shipping hasincreased greatly since 2012, accounting for 77.5% of the reviewedpapers. The main focus today on green shipping was on air pollution,and the classification of green shipping practice, such as technical measures,operational options, market-based measures, and recycling andreusing, is becoming clear. According to the existing studies, futureresearch on green shipping must strengthen technology research tonot only solve practical problems, but also to establish a theoreticalgreen shipping system. Moreover, researchers from different countriescould cooperate with each other to give effective suggestions on settingstandards and laws of green shipping. Finally, we identify the futureresearch themes will focus on setting up green shipping system andlegislation and policy

Efficiency Evaluation of Pakistan Railways Using Data Envelopment Analysis

Rails are one of the safe, reliable and profitable transportation system for any country. The Pakistan Railways carried only 47 million passengers and 1.6 million tonne freight in 2013-14, compared to 113 million passengers and 11 million tonnes freight in 1985-86. There is greater need for efficiency evaluation of Pakistan Railways.  In this report we are using Data Envelopment Analysis (DEA) method to evaluate and compare the efficiency of Pakistan Railways from the year 1950 to 2014. We have used super efficiency model to rank the efficient years and reference units were introduced for every inefficient year and determine the amount of input decrease and output increase to make them efficient. We found that the minimum and maximum efficiency is 0.518 and 1.151, respectively and only six years were identified as efficient years. The results show that the efficiency of railway in the year after 1980 are inefficient years, except 2006-07 and 2008-09 which represents the declining trend of railways. Taken together, these results suggest that the mismanagement and lack of professional expertise plague the railways as a fast shrinking public sector organization. Keywords: Data Envelopment Analysis, Railways, Efficiency

Assessing the energy implications of replacing car trips with bicycle trips in Sheffield, UK

A wide range of evidence supports policies which encourage people to cycle more and drive less, for health and environmental reasons. However, the likely energy implications of such a modal shift have remained relatively unexplored. In this paper we generate scenarios for increasing the cycling rate in Sheffield between 2010 and 2020. This is done through the novel application of a simple model, borrowed from population ecology. The analysis suggests that pro-cycling interventions result in energy savings through reduced consumption of fuel and cars, and energy costs through increased demand for food. The cumulative impact is a net reduction in primary energy consumption, the magnitude of which depends on a number of variables which are subject to uncertainty. Based on the evidence presented and analysed in this paper, we conclude that transport policy has a number of important energy implications, some of which remain unexplored. We therefore advocate the formation of closer links between energy policy and transport policy in academia and in practice; our approach provides a simple yet flexible framework for pursuing this aim in the context of modal shift

Energy Demand and Efficiency: Explore the Potential of SFA and DEA as Tools for the Determination of the Efficiency of Energy in Mexico Transport and Industrial Sectors

This research presents the process of research of the energy efficiency and demand in the transport and industrial sectors of Mexico. To do this, two types of methodologies were used: a parametric one Stochastic Frontier Analysis (SFA) and a non-parametric Data Envelopment Analysis (DEA). Both estimate the energy efficiency and are commonly used in the field. Once the data was collected and the research was carried out, three types of models were created. The first one for the SFA and the other ones for DEA, where one model was used for the transport sector and the other for the industrial sector. The results indicate the levels of efficiency in the sectors selected. For the SFA, the data showed statistical significance and the results expected, due to the economic theory of the price and income elasticities for the energy demand. In addition, the inefficiency component was significant and estimated for the 17 sectors analysed. While DEA results were estimated separately for each sector and therefore, different variables were used. The findings for the transport sector indicate that only one sector is efficient and in the industrial sector 10 of 13 are efficient. In both sets of results, the transport sector seems to be more efficient than the industrial sector. The purpose of estimating the levels of efficiency was to reach a conclusion on which sector could improve its productivity. Furthermore, this research could be developed into a doctoral thesis, where it would be necessary to use a more complex model of the aforementioned model and carry out more research into the impact of the productivity and energy policies

An analysis of technical efficiency and service effectiveness for freight railways in African and European countries

For the past decades, technical efficiency and service effectiveness have become topical as performance measures in various sectors. However, a comparison of technical efficiency and service effectiveness for freight rail transport has received less attention in African and European countries. To address this challenge the current study seeks to analyse technical efficiency and service effectiveness of rail freight in African and European countries. Due to data unavailability in other countries, this study selected four African countries (South Africa, Morocco, Democratic Republic of Congo and Algeria) and four European countries (Lithuania, Austria, France and Germany). The data has been collected from the World Bank, International Union of Railway Statistics and Knoema for the period 2017. Input oriented and output oriented data envelope analysis (DEA) were used to analyze technical efficiency and service effectiveness, respectively. The application of DEA requires the selection of appropriate inputs, production and output variables. This study selected a number of employees and length of rail lines as input variables, gross train tonne kilometres (km) as production variable, tonnes carried and tonne kilometres (km) as output variables. The result shows that five out of eight countries were technical efficient and their services effective with values equal to 1.00. The Pearson correlation coefficient was used to analyse the relationship between technical efficiency and service effectiveness. The results indicate that there is a statistically significant positive correlation between technical efficiency and service effectiveness. To determine the impact exogenous variables on technical efficiency and service effectiveness, a Tobit regression analysis was conducted. The results show that technical efficiency and service effectiveness are not significantly affected by exogenous variables. On the other hand, technical efficiency is significantly affected by the number of employees while service effectiveness is significantly affected by gross train tonne km. This study recommends the use of less labour intensive assets and monitoring of gross train tonne km should be viewed as important strategies to improve technical efficiency and service effectiveness, respectively.Thesis (MCom) -- Faculty of Management and Commerce, 202

Reconciling energy and carbon emission performance for sustainability

Enerji ve çevresel verimlilik kavramları üretim süreci esnasında çok az ya da hiç kirlilik açığa çıkmamasını sağlayarak verimliliği yeniden tanımlar ve sürdürülebilir bir geleceğe erişimi sağlar. Konuyla ilgili literatür ülkelerin çevresel verimlilik ve performans ölçümlerinin sağlanması konusunda yeterli değildir. Bu çalışma, elektrik enerjisi üretiminde enerji ve CO2 salımı performansını üretim verimliliği açısından modeller. Bu çalışmada radyal olmayan mesafe fonksiyonu kullanılmış; enerji, çevre ve enerji-çevre performans indisleri 112 ülke için ve 1988-2011 periyotlarını kapsayacak şekilde oluşturulmuştur. Model IEA 2013 datasını kullanarak GAMS 23.5 programında çözülmüştür. Ülkeler, ilk etapta birleşik ısı ve güç üretim (CHP) teknolojisini kullanımlarına göre gruplanmış ve en iyi üretim sınır eğrisi oluşturulmuştur. İkinci grup ise G20 ülkelerinden oluşmakta olup, bu gruplama dünyadaki 20 majör ülkenin enerji, çevre ve enerji-çevre performanslarının karşılaştırılmasını sağlamaktadır. Son grup ise Türkiye'nin de içinde bulunduğu Birleşmiş Milletler İklim Değişikliği Çerçeve Sözleşmesi (UNFCCC) Ek I ülkelerinden oluşmaktadır. Data setteki en son yıl olan 2011 yılı için tüm performans indislerinde en iyi performans gösteren ülkeler şunlardır: CHP teknolojisini kullanan ülkeler arasında İsviçre ve İsveç; CHP teknolojisini kullanmayan ülkeler arasında Brezilya; G20 ülkeleri arasında Brezilya ve İngiltere; Ek I ülkeleri arasında ise Beyaz Rusya ve Slovak Cumhuriyeti. Literatürle uyumlu olarak Türkiye, kirliliğe sebep olan ana ülkelere göre daha iyi enerji ve çevresel performans sergilemiş olup, Ek I örneklem ülkeleri arasında ise medyanda yer almaktadır. Anahtar Kelimeler: Enerji Verimliliği, Çevresel Verimlilik, CO2 Salım Performansı, Elektrik Üretimi, Yönsel Mesafe Fonksiyonu, Veri Zarflama AnaliziThe concepts of energy and environmental efficiency, with creating less or no pollution in production processes, help to redefine efficiency in general and serve to attain a sustainable future. The relevant literature is underprovided in analyzing environmental efficiency and thus performance measures for countries over time. This study models energy and CO2 emission performance in electricity generation from the production efficiency point of view. It uses a non-radial directional distance function and constructs energy, environmental and energy-environmental performance indices for 112 countries over the period of 1988-2011. The models are run in GAMS 23.5 with IEA data 2013. The countries are grouped firstly with respect to their use of combined heat and power (CHP) technology to construct best practice frontier. The second group is G20 countries, which allows investigation of the tradeoffs amongst energy and environmental performances of top 20 countries in the world. The last group is UNFCCC Annex I countries, consisting of Turkey. The study shows that the majority of the countries still have room for improvement for energy and the environment. For the most current year in the dataset, 2011, for all the indices, the following countries are the best performers; Switzerland and Sweden in the group of countries with CHP technology, Brazil for the non-CHP countries, Brazil and United Kingdom among G20 countries, and Belarus and Slovak Republic in Annex I. Consistent with the literature, Turkey has better energy and environmental performance compared to the major polluters as it performs around the medians of sample countries in UNFCCC Annex I. Keywords: Energy efficiency, Environmental efficiency, CO2 emission performance, Electricity Generation, Directional distance function, Data envelopment analysis