An industry and country analysis of technical efficiency in the European Union, 1980-2005

The research aim of this research is to identify and examine key resources, a conceptual framework drawing on the application of stochastic frontier models in obtaining measures of efficiency that enable a comparison of performance across industries and countries, explaining why, in the same country, some industries achieve superior efficiency performance. The important task is to relate efficiency to a number of factors that are likely to be determinants, and measure the extent to which they contribute to the presence of inefficiency. More specifically, the first step of this thesis is to review the literature concerned with techniques of efficiency estimation. This will facilitate an understanding of both the theoretical and application part of the research. The second step of this thesis is to highlight the pitfalls of the different relevant models and methodologies. The third and most important goal and contribution of this thesis is to suggest a concrete method to estimate industrial efficiency, avoiding the inherent problems. This thesis considers a European Union perspective efficiency analysis to increase the information base and derive broader conclusions about European Union productive performance within selected countries. This issue is of particular research relevance because empirical evidence shows that even though European Union industries are widely analyzed with respect to performance, yet little attention has been paid to the estimation of technical efficiency. Within this sample, it is of great importance to examine which determinants are significant, however, it is also important, to examine whether the interactions between technical progress, ICT investment, ICT investment share, R&D stock and economy openness, namely the process of the integration into the world economy, has any implications for technical efficiency. Special emphasis is given to the review of two of the main heterogeneity determining factors, namely innovation investments (as a proxy of knowledge creation) and economy openness (as a proxy of knowledge dissemination). In particular, this thesis explores whether the interactions between these factors have any implications for efficiency growth, and whether there are any complementarities between them and fostering technical efficiency growth. More specifically, this thesis aims to distinguish between the two main factors which affect total factor productivity, namely technical progress and technical efficiency, as well as what determines the production frontier itself and what determines the inefficiency term (both theoretically and empirically)

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

Cost efficiency in the Chinese banking sector : a comparison of parametric and non-parametric methodologies

Since the open door policy was embarked upon in 1979, China s banking sector has undergone gradual but notable reforms. A key objective of the reforms implemented by the Chinese government is to build an effective, competitive and stable banking system in order to improve its efficiency and reliability. This study employs both parametric stochastic frontier analysis (SFA) and non-parametric data envelopment analysis (DEA) methods to assess and evaluate the cost efficiency of Chinese banks over the period from 1994 until 2007, a period characterised by far-reaching changes brought about by the banking reforms. To this end, we first compare a number of specifications of stochastic cost frontier models to determine the preferred frontier model which are adopted in our efficiency analysis. The preferred model specification for our sample is the one stage SFA model that includes the traditional input prices, the outputs and the control variables (that is, equity, non-performing loans and the time trend) in the cost frontier and the environmental variables (that is, ownership structure, size, deregulation, market structure and market discipline) in the inefficiency term. Moreover, we also employ two cost DEA models (traditional DEA and New DEA) as a complement to the preferred SFA model for methodological cross-checking purposes. Similar to the previous empirical literature, we find that in most cases only moderate consistency across the different techniques. The cost efficiency of Chinese banks is found to be 91% on average, based on our SFA model, over the period from 1994 until 2007. Based on the results of the DEA and New DEA models, the average cost efficiency for Chinese banks over the sample period is about 89% and 87%, respectively. We find that Chinese banking efficiency has deteriorated after China s admission to the WTO, suggesting that the significant external environmental changes which arose from China s WTO entry may have had a negative impact on its banking efficiency. In addition, we find that the majority of Chinese banks reveal scale inefficiencies and as asset size increases, banks tend to pass from increasing, to constant, and then to decreasing returns to scale. Our findings also show that both state-owned banks and foreign banks are more efficient than domestic private banks and larger banks tend to be relatively more efficient than smaller banks. These and other results suggest that in order to enhance Chinese banking efficiency, the government needs to continue with the banking reform process and in particular, to open up banking markets, to improve risk management and corporate governance in Chinese banks and to encourage the expansion of banks.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Energy Efficiency

This book is one of the most comprehensive and up-to-date books written on Energy Efficiency. The readers will learn about different technologies for energy efficiency policies and programs to reduce the amount of energy. The book provides some studies and specific sets of policies and programs that are implemented in order to maximize the potential for energy efficiency improvement. It contains unique insights from scientists with academic and industrial expertise in the field of energy efficiency collected in this multi-disciplinary forum

Multiperiod modelling planning and productivity and energy efficient assessment of an industrial gases facility

El creixement de la demanda energètica i el continu desenvolupament tecnològic de la societat estan sobrepassant els límits mediambientals del nostre planeta. Sense les mesures adequades, aquesta situació podria derivar en importants problemes mediambientals que causarien danys irreversibles al medi ambient i al benestar de la humanitat. El sector industrial és el principal consumidor energètic, amb una demanda al voltant d’un terç de la global, un aspecte que té un evident efecte negatiu amb l’impacte mediambiental. Per tant, el repte de mitigar el canvi climàtic implicarà millores en l’ús de la energia a la industria, generant grans oportunitats d’estalvi energètic i reduint el seu impacte mediambiental. En aquest sentit, es essencial obtenir informació derivada de la investigació i l’anàlisi científic que permeti desenvolupar solucions focalitzades en la reducció de costos energètics. Aquesta tesis ha tractat les necessitats particulars de la producció de gasos industrials, creant eines basades en l’optimització matemàtica que permeten una presa de decisions operatives més àgil i efectiva i detectant àrees per la millora energètica. Aquestes eines fomenten i avancen cap a una industria més eficient que permeti un futur més sostenible. Aquesta tesis té dos contribucions principals. D’una banda, s’ha desenvolupat una eina d’optimització multiperiod que permet obtenir la configuració d’operació òptima (des del punt de vista econòmic i energètic) d’un procés de producció de gasos industrials, tenint en compte totes les seves variables. Per altra banda, s’utilitza la metodologia de Data Envelopment Analisis per a comparar diferents unitats de producció de gasos industrials, identificant els focus d’ineficiència i fent recomanacions per a resoldre’ls.El crecimiento de la demanda energética y el continuo desarrollo tecnológico de la sociedad están sobrepasando los límites medioambientales de nuestro planeta. Sin las medidas adecuadas, esta situación puede derivar en importantes problemas medioambientales que podrían causar daños irreversibles al medioambiente y al bienestar de la humanidad. El sector industrial es el principal consumidor energético, consumiendo alrededor de un tercio de la demanda energética global, lo que tiene una evidente relación negativa con el impacto ambiental. Por lo tanto, el reto de mitigar el cambio climático implicará mejoras del uso de la energía en la industria, creando grandes oportunidades de ahorro energético y reduciendo su impacto ambiental. Para ello, es esencial obtener información derivada de la investigación y el análisis científico que permita desarrollar soluciones enfocadas a la reducción de costes energéticos. Esta tesis ha tratado las necesidades particulares de la producción de gases industriales, creando herramientas basadas en la optimización matemática que permiten una toma de decisiones operativas más ágil y efectiva y detectando áreas para la mejora energética. Estas herramientas fomentan y avanzan hacia una industria más eficiente que permita un futuro más sostenible. Esta tesis tiene dos contribuciones principales. Por un lado, se crea una herramienta de optimización multiperiodo que permite obtener la configuración de operación óptima (desde el punto de vista económico y energético) de un proceso de producción de gases industriales, teniendo en cuenta todas sus variables. Por otro lado, se usa la metodología de Data Envelopment Analysis para comparar diferentes unidades de producción de gases industriales, identificando los focos de ineficiencia y haciendo recomendaciones para resolverlos. En definitiva, esta tesis ofrece un conjunto de herramientas prácticas y efectivas que apoyan el proceso de toma de decisiones en actividades industriales y permiten la identificación de oportunidades de mejora energética.The growth of energy demand and the continuous technological development of society are surpassing the environmental limits of our planet. Without adequate measures, this situation can lead to serious environmental problems that could cause irreversible damage to the environment and the well-being of humanity. The industrial sector is the largest energy consumer, with about one-third of global energy demand, which has an evident negative relationship with environmental impact. Therefore, the challenge of mitigating climate change will imply improvements in the energy use in industry, creating great opportunities for energy savings and reducing its environmental impact. In this sense, it is essential to obtain information derived from research and scientific analysis that allows developing solutions focused on the reduction of energy costs. This thesis has dealt with the particular needs of the production of industrial gases, by creating tools based on mathematical optimization models that allow much more agile and effective operational decision-making as well as the detection of areas for energy improvement. These tools encourage and move towards a more efficient industry that allow a more sustainable future. Two main contributions are derived from this thesis. On the one hand, it creates a multiperiod optimization tool that allows obtaining the optimal operational configuration (from the economic and energetic points of view) of an industrial gas manufacturing process, taking into account all the variables that affect the system. On the other hand, the Data Envelopment Analysis methodology is used to compare different industrial gas production units, identifying inefficiency sources and making recommendations to adopt the best practices to solve them. Summarizing, this thesis offers a set of practical and effective tools that support the decision making process in industrial activities and allows the identification of opportunities for energy improvement

The Impact of Port Technical Efficiency on Mediterranean Container Port Competitiveness

Port efficiency is a significant element that stimulates port competitiveness and enhances regional development. With increasing international maritime traffic and changing technology in the maritime transport sector, containerisation and enhanced logistic activities, infrastructure might be one of the main determining factors of port competition (Merk & Dang, 2012). Due to the increasing container traffic and the high quality of service required by the shipping lines, Mediterranean container ports are being compelled to enhance port efficiency to improve comparative advantages that will increase cargo traffic and satisfy the customers’ requirements. The Mediterranean Sea is a link point between Europe, Africa and Asia. This research aims to examine the impact of ports' technical efficiency on the improvement of Mediterranean container ports’ competitiveness. The research analyses the competitiveness and the relative efficiency of the top 22 container ports in the Mediterranean basin using a cross-section, panel data and window analysis application of data envelopment analysis (DEA) for the period between 1998 and 2012. The selected 15 year period enables the analysis of Mediterranean container port market dynamics and the benchmarking of the technical efficiency of the selected ports for three consecutive market cycles. This research can be classified as quantitative analytical research. The research follows the concept of the Industrial Organization (IO) and the Structuralism (Harvard school) methodology that analyses the market Structures, Conduct and Performance (SCP) of market players. The study conducts a simultaneous three-stage procedure: in the first stage, the competitiveness of the main container ports in the Mediterranean is analysed through the study of market structure and conduct. Market structure is assessed through measuring and analysing market concentration by using four different methods. These methods are: the K-Firm concentration ratio (K-CR), Hirshman-Herfindahl Index (HHI), the Gini coefficient (GC) and the generalized entropy index. Boston Consultant Group (BCG) matrix is also used to visualize the dynamics between ports in the defined market and assess the ports' competitive position. Market conduct is analysed using shift-share analysis (SSA) to get a thorough understanding of the issue of port traffic development. In the second stage, market performance is analysed through the use of the non-parametric models of Data Envelopment Analysis (DEA) which estimates the relative efficiency scores and ranking seaports according to their efficiency. Five DEA models are adopted for comparative purpose, the DEA- CCR, DEA-BCC, the Super-Efficiency (A&P, 1993), the sensitivity analysis and slack variable analysis models. In the third stage, to examine the impact of port efficiency on port competitiveness, a number of hypotheses are examined through the use of parametric correlation coefficients (Spearman’s rank order) and Simar and Wilson (2007) procedure to bootstrap the DEA scores with a truncated regression. Using this approach enables more reliable evidence compared to previous studies analysing the efficiency of seaports. The main findings demonstrate that the recent deconcentration tendency of the Mediterranean container port market is due to the increased number of market players which will in turn reshape the market structure, change the container port hierarchy and intensify the competition between ports as the market shifts from oligopoly to pure competition. The research findings also reveal the existence of inefficiency pertaining to the management of container ports in the region, since the total technical efficiency is found to be below 50% on average. This relatively limited technical efficiency of the Mediterranean container ports indicates the need for appropriate capital investments for ports’ infra/superstructure. In particular, those ports whose efficiency is not favoured by some factors such as size, geographical position and socio-economic conditions of the region in which they are located, must adopt suitable reform strategies to promptly improve their efficiency and competitive position. What differentiates this work from previous studies on the subject is that both cross-sectional and panel data have been collected and analysed at the level of individual container ports in the Mediterranean. The study is based on a wide range of methodologies, both parametric and non-parametric, that have ensured the validity of the empirical examination that has been undertaken and the results obtained. The research analysed the Mediterranean container ports competitiveness, benchmarked and ranked their efficiency by considering the Mediterranean in its totality, including South Europe, Middle East and North Africa. The study puts forward a way to assess container port efficiency based on simple, yet validated and meaningful physical efficiency measures

Comparative research between the Chinese and the Australian construction industries based on productivity and industrial competitiveness

In the last three decades, the Chinese construction industry has made significant achievements in the international market. Performance improvement of the Chinese construction industry in the international market is a widely held concern for academics, industry practitioners and policymakers in China. The performance gap between the Chinese and developed countries’ construction industries may still exist and it is important that we analyse this to improve industry performance and to assist policymakers formulate future development strategies. This research aims to understand the performance of the Chinese construction industry and generate strategies for future development by comparing the Chinese and the Australian construction industries based on the concepts of productivity and industrial competitiveness. The current measurement methods for a country, industry, and/or a firm’s status or level in the world are questionable. This study adapted the International Advanced Index (IAI) to measure the status and level of a country’s construction industry in the international market. Porter's Diamond Model is one of the most popular and complete competitiveness theories and it has been improved by various scholars since it was first introduced. However, another very important theme that could contribute to this area of competitiveness is the concept of sustainable development. The research on the relationship between industrial competitiveness and sustainable development is lacking. Building upon the previous research, the Internationalisation Sustainable Development Competitiveness Model (ISDC Model) was generated to enable the evaluation of industrial competitiveness. Sustainable development is a new element and it is composed of three sub-elements including economic sustainability, social sustainability and environmental sustainability. By using the Chinese and the Australian construction industries as cases, case study methodology is conducted in this research. The quantitative data was collected from several resources including; China Statistical Yearbook, Australian Bureau of Statistics, Engineering News Record, Dun & Bradstreet’s “Who owns Whom” Database and Companies’ Financial Reports. The data were analysed by various statistical methods including: Malmquist Productivity Index, Spearman Rank Correlation Coefficient, Degree of Coordination and Multivariate Cointegration Analysis. An important part of this thesis was to initiate the design and development of a practice based methodology that would be accessible by other researchers and potentially also by policymakers and industry analysts who could improve the way in which we measure the performance of the construction industry. After the methodology was developed it was tested and then evaluated. This study compared the status and level of the Chinese and the Australian construction industries by using the IAI and proposed that the Chinese construction industry should be involved in a greater number of construction fields (diversification) or improve the level of activity in each involved field (specialization). Compared with the previous models, this study illustrated that the IAI is more comprehensive in reflecting the status and level of a country’s construction industry in the international market. The index also provides a method to access and use data that is more readily available yet is still rigorous and robust. The Malmquist Productivity Index is adopted to explore the Total Factor Productivity (TFP) changes of the Chinese and the Australian construction industries in recent years and comparison were made. The gap in TFP between the Chinese and the Australian construction industries was significant and may become more significant due to the better growth rate of the Australian construction industry in productivity. The difference between the Chinese and the Australian construction industries industrial competitiveness was explored. As ‘activities of the multinational enterprises’ is new for Porter’s Diamond Model and it has not been quantitatively tested, this study tested it by exploring the relationship between the degree of internationalisation and the performance at a construction firm and country levels by using the Spearman Rank Correlation Coefficient. The results indicated that the activities of the multinational enterprises could be included in the international competiveness model and is considered a determinant factor. For the sustainable development element, the Social Sustainability Index of the Chinese construction industry is the only sub-element which is lower than the Australian construction industry. The Degree of Coordination and Multivariate Cointegration analysis indicates that the three sub-elements of sustainability are interdependent and that they interact. The Social Sustainability Index should be considered as the priority to be improved. However, it was also found that for a long term point of view, if the Environmental Sustainability index needs to be improved, the best way is to improve the Economic Sustainability index, not the Environmental Sustainability index itself, which proved the importance of the interactivity principle of systems thinking and the Long-Term Influence Theory is proposed, as follows: In order to improve the performance of an element/sub-system in a system for a long term point of view, stimulating the element/sub-system directly may be not the best way. It may be better to improve the other elements/sub-systems in the long term, because the dynamic and complex interrelationship among the elements/sub-systems exists within a system, and the influence level and direction between the elements/sub-systems may be different in the long term

Proceedings of USM-AUT International Conference 2012 Sustainable Economic Development: Policies and Strategies

This proceedings includes papers presented at the USM-AUT International Conference (UAIC 2012) carrying the theme “Sustainable Economic Development: Policies and Strategies”, held on 17-18 November 2012 at Bayview Beach Resort Penang Malaysia. This conference is jointly organized by the School of Social Sciences, Universiti Sains Malaysia (USM), Malaysia, and Faculty of Business and Law, Auckland University of Technology (AUT), New Zealand. We received a total of 167 papers from various institutions and organizations around the world where 82 papers were accepted for inclusion in this proceedings. The proceedings is compiled according to the three sub themes of the conference. It covers both theoretical and empirical works from the scholars globally. It is hoped that the collection of these conference papers will become a valuable reference to the conference participants, researchers, scholars, students, businesses and policy makers. The proceedings will be submitted to Thomson ISI for indexing

Exploring the Relationship between Tourism and Economic Growth in Small Island Economies: A Study of Fiji

This study examines the effect of tourism, measured by visitor arrivals) on the economic growth of Fiji, a small island economy, over the period 1975 to 2015. We use a neoclassical framework and regression analysis to examine the short-run and the long-run effects of tourism whilst accounting for structural breaks. We confirm the presence of a long-run association using the two-step procedure of Engle and Granger (1987) and the ARDL bounds test of Pesaran, Shin and Smith (2001). From the long-run results, we note that a 1% increase in visitor arrivals contribute about 0.22% to the GDP per capita. The short run elasticity is noted to be 0.19%. The study finds evidence of a unidirectional causality from economic growth to tourism, and mutually reinforcing effect between capital investment and tourism. Thus, we can expect greater impact of tourism on the economic growth through tourism related investment activities such as improvements in airports, roads, transportation, financial sector and telecommunications, and parks and beaches