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D.Com. (Transport Economics) / Please refer to full text to view abstract

This thesis is concerned with measuring and explaining the productive efficiency of firms or organizations. In particular, the study compares three alternative methods of measuring efficiency, namely, the deterministic frontier method, the stochastic frontier method, and the data envelopment analysis method (DEA). The dissertation consists of two parts. In Part I, the relative merits of the three methods are discussed and evaluated through a Monte Carlo study under certain known conditions. The study focuses on the effects of exogenous variables on efficiency estimates. The results show that the stochastic frontier method generally produces better efficiency estimates than the other two methods. The DEA, however, has a slight advantage in cases where there are weak input substitution and large variations in input variables. In Part II, the three methods are examined empirically through their applications to a panel of 19 railways in OECD countries and a panel of 36 international airlines. Comparison of the three sets of efficiency estimates confirms that on average the stochastic frontier method yields higher efficiency estimates than the other two methods, as indicated by the Monte Carlo results. The efficiency estimates by the two parametric methods are highly correlated, whereas there are considerable differences between the DEA estimates and those from the parametric methods. This is also consistent with the Monte Carlo results. By comparing the alternative efficiency estimates in the two applications, it is found that there is less discrepancy among the three sets of efficiency estimates in the airline case than in the railway case. This can be partly attributed to the fact that there are fewer variations in the operating environments in the airline case than in the railway case. The simulation results in Part I provide some general guidelines regarding the relative merits of the three alternative methods under certain known conditions. The two applications of the three methods in Part II serve as examples of how these three methods can be applied to practical problems where no a priori knowledge of either the production technology nor the efficiency profile exists. They illustrate some of the problems that may be encountered in empirical applications.

This thesis is concerned with measuring and explaining the productive efficiency of firms or organizations. In particular, the study compares three alternative methods of measuring efficiency, namely, the deterministic frontier method, the stochastic frontier method, and the data envelopment analysis method (DEA). The dissertation consists of two parts. In Part I, the relative merits of the three methods are discussed and evaluated through a Monte Carlo study under certain known conditions. The study focuses on the effects of exogenous variables on efficiency estimates. The results show that the stochastic frontier method generally produces better efficiency estimates than the other two methods. The DEA, however, has a slight advantage in cases where there are weak input substitution and large variations in input variables. In Part II, the three methods are examined empirically through their applications to a panel of 19 railways in OECD countries and a panel of 36 international airlines. Comparison of the three sets of efficiency estimates confirms that on average the stochastic frontier method yields higher efficiency estimates than the other two methods, as indicated by the Monte Carlo results. The efficiency estimates by the two parametric methods are highly correlated, whereas there are considerable differences between the DEA estimates and those from the parametric methods. This is also consistent with the Monte Carlo results. By comparing the alternative efficiency estimates in the two applications, it is found that there is less discrepancy among the three sets of efficiency estimates in the airline case than in the railway case. This can be partly attributed to the fact that there are fewer variations in the operating environments in the airline case than in the railway case. The simulation results in Part I provide some general guidelines regarding the relative merits of the three alternative methods under certain known conditions. The two applications of the three methods in Part II serve as examples of how these three methods can be applied to practical problems where no a priori knowledge of either the production technology nor the efficiency profile exists. They illustrate some of the problems that may be encountered in empirical applications. / Business, Sauder School of / Graduate

Crew schedules on the South African Transport Services are done by roster compilers at depots. A method that uses heuristic and mathematical programming algorithms was developed to replace existing hand methods. It is a two stage method that will use a microcomputer to assist roster compilers to draw up crew schedules. Initially timetables are subdivided into shifts and then they are combined into crew schedules. The solution, which produces a significant improvement compared with an existing crew schedule and an existing method, has been accepted in principle and computer programming has begun. In Appendix E another heuristic for the scheduling of league matches is described.

Thesis (M.S.)--Massachusetts Institute of Technology, Alfred P. Sloan School of Management, 1980. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY. / Includes bibliographies. / by Randall Richard Reyff. / M.S.

Thesis: M.S., Massachusetts Institute of Technology, Department of Civil Engineering, 1978 / Bibliography: leaves 73-74. / M.S. / M.S. Massachusetts Institute of Technology, Department of Civil Engineering

Thesis: M.S., Massachusetts Institute of Technology, Department of Civil Engineering, 1978 / Bibliography: leaves 149-150. / M.S. / M.S. Massachusetts Institute of Technology, Department of Civil Engineering

Thesis: M.S., Massachusetts Institute of Technology, Department of Civil Engineering, 1978 / Includes bibliographical references. / M.S. / M.S. Massachusetts Institute of Technology, Department of Civil Engineering