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Overreliance on energy from fossil fuels is unsustainable because of their regional depletion and associated environmental impacts. The British industrial sector accounts for around one fifth of final energy demand and one third of carbon emissions nationally. This thesis attempts to quantify the potential for industrial energy efficiency from the current baseline, by adopting thermodynamic and economic perspectives. The methodology involves a top-down analysis of energy trends within the manufacturing sector to determine the baseline against which changes are measured, leading to bottom-up case studies which explicitly consider the detailed mechanisms affecting energy demand. Top-down analysis highlights the diversity between industrial sectors, for which a sectoral classification based on process homogeneity is proposed. It also enables the long term, systemic potential for efficiency improvements to be estimated and identifies the barriers to uptake. Bottom-up case studies are better suited to identifying the sectoral potential in the short to medium term. Firstly, the technical potential for heat recovery from industrial sectors is quantified by recourse to thermodynamic quality and spatial considerations. Secondly, an energy and exergy analysis of a glass furnace enables a distinction between avoidable and unavoidable losses, leading to the identification of economic savings. Thirdly, a process integration study at a pulp and paper mill based on a pinch analysis and optimisation of a heat exchanger network highlights economic efficiency improvements. This thesis demonstrates that realising the full industrial energy efficiency potential requires improvements to public policy intended to overcome market-related barriers, especially the EU Emissions Trading Scheme and the Carbon Trust, with additional scope for a mandatory efficiency standard relating to motors. Energy efficiency has to part of a company’s overall strategy to be effective. Future work should focus on heterogeneous sectors and the broader effects on industrial energy efficiency of globalisation and the shift towards services.

Thesis (Ph. D.)--University of Hong Kong, 1999. / Includes bibliographical references (leaves 101-112).

Thesis (M.S.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Systems Science and Industrial Engineering, 2009. / Includes bibliographical references.

This is the first paper to measure the efficiency of the Japan Professional Football League clubs both the first and the second divisions. In Chapter 1, a non-parametric method Data Envelopment Development (DEA) is used and the data covers six seasons from 2005 to 2010. The input variables are payroll, cost besides payroll, and total assets. The output variables are attendance, revenue, and points awarded. I use different output combinations in order to check the sensitivity of the efficiency of the clubs after the original composition. This is also the first research to include more than one division of the Professional Football League and hence, the promotion and relegation impact on the efficiency can be analyzed using unique data such as Tokyo Verdy 1969. Tokyo Verdy 1969 operated inefficiently in the second division because it spent so much on inputs hoping for promotion. It was efficient when in the first division. The results indicate that athletic rank in the league is not correlated with the efficiency scores. The efficient clubs in the second division are all ranked at the bottom in the league and this is because they have limited resource inputs, no expectation to promote, and because the expansion policy of the league precludes relegation. Chapter 2 is an extension of Chapter 1. In this chapter I check the exogenous factors impacting the efficiency scores but not involved in the DEA analysis as the input variables. I aim to estimate the relationship between the input-oriented DEA efficiency scores under the constant returns to scale assumption and use an exogenous variable ordinary least square (OLS) model to check the relationship between the efficiency scores and exogenous variables. I regress the DEA efficiency scores on all of the exogenous variables collected from various resources during the sample period. Chapter 3 estimates the productivity and efficiencies of the football clubs in Japan Professional Football League. This chapter is an extension of the first chapter. In this chapter I check the dynamic change of Total Factor Productivity (TFP) based on the calculation of the Malmquist Index, which consists of efficiency change and technical change between two time periods. Additionally, the production frontier used in this chapter was built by the non-parametric input-oriented CRS DEA approach as applied in the first chapter. Based on the results of the Malmquist Index, we find if the change in the TFP growth as increasing, declining or remaining the same.

Thesis (Ph. D.)--University of Chicago Graduate School of Business, March 1999. / Includes bibliographical references. Also available on the Internet.

Thesis (Ph. D.)--University of Connecticut, 2004. / Includes bibliographical references (leaves 112-116).

Demand fluctuations will bias the measurement of productivity and efficiency. This dissertation described three ways to characterize the effect of demand fluctuations. First, a two-dimensional efficiency decomposition (2DED) of profitability is proposed for manufacturing, service, or hybrid production systems to account for the demand effect. The first dimension identifies four components of efficiency: capacity design, demand generation, operations, and demand consumption, using Network Data Envelopment Analysis (Network DEA). The second dimension decomposes the efficiency measures and integrates them into a profitability efficiency framework. Thus, each component's profitability change can be analyzed based on technical efficiency change, scale efficiency change and allocative efficiency change. Second, this study proposes a proactive DEA model to account for demand fluctuations and proposes input or output adjustments to maximize effective production. Demand fluctuations lead to variations in the output levels affecting measures of technical efficiency. In the short-run, firms can adjust their variable resources to address the demand fluctuates and perform more efficiently. Proactive DEA is a short-run capacity planning method, proposed to provide decision support to a firm interested in improving the effectiveness of a production system under demand uncertainty using a stochastic programming DEA (SPDEA) approach. This method improves the decision making related to short-run capacity expansion and estimates the expected value of effectiveness given demand. In the third part of the dissertation, a Nash-Cournot equilibrium is identified for an oligopolistic market. The standard assumption in the efficiency literature that firms desire to produce on the production frontier may not hold in an oligopolistic market where the production decisions of all firms will determine the market price, i.e. an increase in a firm's output level leads to a lower market clearing price and potentially-lower profits. Models for both the production possibility set and the inverse demand function are used to identify a Nash-Cournot equilibrium and improvement targets which may not be on the strongly efficient production frontier. This behavior is referred to as rational inefficiency because the firm reduces its productivity levels in order to increase profits.

Thesis (Ph.D.) - University of Queensland, 2004. / Includes bibliography.

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