Modal choice between air and rail : a social efficiency benchmarking analysis that considers CO2 emissions

The problem of modal choice between rail and air arises as public awareness of carbon dioxide (CO2) emissions by the transportation sector rises. In this paper, we answer this question quantitatively by performing an efficiency benchmarking analysis that takes into account life-cycle CO2 emission due to transport service provision. The paper employs nonparametric efficiency estimation methods, namely a slacks-based inefficiency measure, as well as a more conventional directional distance function approach. We apply them to a panel data set for three major railway companies and the aviation sector in Japan for the period from 1999 to 2007. Results shows that, contrary to the common argument, air transport can still be more socially efficient than rail transport, even when the environmental load due to CO2 emission is incorporated. This is due to the aviation sector's extremely low user cost, measured in terms of in-vehicle time. In other words, aviation is a necessary transportation mode for those with a very high willingness to pay for their time.

Cost efficiency of Japanese steam power generation companies : a Bayesian comparison of random and fixed frontier models

This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.

Technical efficiency, regulation and heterogeneity in Japanese airports

In this paper, the random stochastic frontier model is used to estimate the technical efficiency of Japanese airports, with regulation and heterogeneity included in the variables. The airports are ranked according to their productivity for the period 1987-2005 and homogeneous and heterogeneous variables in the cost function are disentangled. Policy implications are derived.

Service quality and performance measurement : evidence from the Indian Water Sector

The conventional measures of benchmarking focus mainly on the water produced or water delivered, and ignore the service quality, and as a result the 'low-cost and low-quality' utilities are rated as efficient units. Benchmarking must credit utilities for improvements in service delivery. This study measures the performance of 20 urban water utilities using data from an Asian Development Bank survey of Indian water utilities in 2005. It applies data envelopment analysis to measure the performance of utilities. The results reveal that incorporation of a quality dimension into the analysis significantly increases the average performance of utilities. The difference between conventional quantity-based measures and quality-adjusted estimates implies that there are significant opportunity costs of maintaining the quality of services in water delivery.

Improving the transparency, openness and efficiency of e-government in Qatar in the era of Open Government Data, and beyond

This thesis investigates how Open Government Data (OGD) concepts and practices might be implemented in the State of Qatar to achieve more transparent, effective and accountable government. The thesis concludes with recommendations as to how Qatar, as a developing country, might enhance the accessibility and usability of its OGD and implement successful and sustainable OGD systems and practices.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

The influence of fleet safety climate on occupational driver behaviours

The concepts of traffic safety culture and climate hold considerable impact on road safety outcomes. Data sourced from four Australian organisations revealed a five factor structure that was consistent with previous research, which were: management commitment; work demands; relationships; appropriateness of rules; and communication. Correlation and regression analyses were conducted to identify which aspects of fleet safety climate were related to driver behaviours. The findings suggest that organisations may be able to reduce the likelihood of employees engaging in unsafe driving behaviours as a result of fatigue or distractions through increasing aspects of fleet safety climate, including: management commitment; level of trust; safety communication; appropriateness of work demands; and appropriateness of safety policies and procedures. To assist practitioners in enhancing fleet safety climate and managing occupational road risks, recommendations are made based on these findings, such as fostering a supportive environment of mutual responsibility.

Implications of differences in technical efficiency of fishing boats for capacity measurement and reduction

Capacity measurement and reduction is a major international issue to emerge in the new millennium. However, there has been limited assessment of the success of capacity reduction schemes (CRS). In this paper, the success of a CRS is assessed for a European fishery characterised by differences in efficiency levels of individual boats. In such a fishery, given it is assumed that the least efficient producers are the first to exit through a CRS, the reduction in harvesting capacity is less than the nominal reduction in physical fleet capacity. Further, there is potential for harvesting capacity to increase if remaining vessels improve their efficiency.

Dimensions of effectiveness and efficiency: A case study on industry–school partnerships

Internationally, the delivery of vocational education and training is being challenged by increasing skills shortages in certain industries and/or rapidly changing skill requirements. To respond to this challenge, rigid and centralised state bureaucracies are increasingly adopting partnerships between schools and industry as a strategy to encourage school-to-work transition programmes to address the local labour market demand. Drawing on experiences in Australia, this paper reports on a case study of government led partnerships between schools and industry. The Queensland Gateway to industry schools initiative currently involves over 120 schools. The study investigated how two commonly used partnership principles were understood by the Gateway to industry partners. Twelve school–industry partnerships from four industry sectors were analysed in terms of the principles of ‘efficiency’ and ‘effectiveness’ derived from the public–private partnership literature. The study found that some evidence of partnership activities associated with efficiency and effectiveness may be assigned to Gateway schools projects. However, little evidence was found that the above underlying principles were addressed systematically. Some of these partnerships were tenuously facilitated by individuals who had limited infrastructure or strategic support. Implications are that industry–school partnership stakeholders would benefit from applying partnership principles regarding implementation and management to ensure the sustainability of partnerships.

Standard business reporting in Australia : efficiency, effectiveness, or both?

The benefits of using eXtensible Business Reporting Language (XBRL) as a business reporting standard have been widely canvassed in the extant literature, in particular, as the enabling technology for standard business reporting tools. One of the key benefits noted is the ability of standard business reporting to create significant efficiencies in the regulatory reporting process. Efficiency-driven cost reductions are highly desirable by data and report producers. However, they may not have the same potential to create long-term firm value as improved effectiveness of decision making. This study assesses the perceptions of Australian business stakeholders in relation to the benefits of the Australian standard business reporting instantiation (SBR) for financial reporting. These perceptions were drawn from interviews of persons knowledgeable in XBRL-based standard business reporting and submissions to Treasury relative to SBR reporting options. The combination of interviews and submissions permit insights into the views of various groups of stakeholders in relation to the potential benefits. In line with predictions based on a transaction-cost economics perspective, interviewees who primarily came from a data and report-producer background mentioned benefits that centre largely on asset specificity and efficiency. The interviewees who principally came from a data and report-consumer background mentioned benefits that centre on reducing decision-making uncertainty and decision-making effectiveness. The data and report consumers also took a broader view of the benefits of SBR to the financial reporting supply chain. Our research suggests that advocates of SBR have successfully promoted its efficiency benefits to potential users. However, the effectiveness benefits of SBR, for example, the decision-making benefits offered to investors via standardised reports, while becoming more broadly acknowledged, remain not a priority for all stakeholders.