The main thrust of this research is the development of a capital investment decision support with reference to the shipping industry. This decision support system as developed is illustrated on the route to a developing part of the world (Liverpool/West Africa trade route) using a ship type particularly suited to the operating requirements of such a route; the multipurpose of Combi (for combination) carriers (chapter two). This ship design type was adopted to operationalise the general capital investment appraisal procedures as developed in this research and embodied in a comprehensive decision support model. The particular capital investment decision criteria as conceived in this study is the maximisation of the net present value of the investment but the objective function is also subject to risk analysis as measured by the coefficient of variability for outcomes. Plausible decision variables were incorporated for the accomplishment of the research objective by a process of parameterisation and the decision criteria adopted necessitated the estimation of a comprehensive system of cost and revenue functions. Ship capital and operating cost function were separately estimated (Chapter Six). It was necessary as a first step in the estimation of ship operating cost functions to aggregate component operating costs into broad categories, namely; Fuel and Lubricants, Wages and Personnel Insurance payments and contributions, Stores and Provision, Repairs and Administration and ship insurance including 'club calls'. Operating 2 cost functions were then estimated for each of the above operating cost aggregates. Ship time in port has operating cost implications particularly with regard to 'hotel load' fuel consumptions and service levels. A ship turnround time forecasting function was duly estimated to cover this category of operating expenses. (chapter five). The ship turn round function as estimated enabled the investigation of a hypothesis topical amongst researchers in shipping that the size of a ship affects its turnround time in port on the study route. The marginal effect on component operating cost functions of variations in managerially controllable variables was also investigated. The revenue model constructed is based on forecasting shipping freight tonnage demand for the provided operating capacity. As a result a freight demand forecasting model was estimated. This estimation was based on least squares and a market/market share demand function estimation procedure was used. The assumptions made for the freight demand model estimation was that national freight demand trend could be approximated by a time series model of the Box-Jenkins type while the route annual demand would be casually dependent on the national trend and relative effort level on the study route. An assumed proxy measure for annual effort level on the route was the corresponding total tonnage offered. Demand share models were also estimated along the lines of the main freight rate commodity categories i.e. foodstuffs, basic materials and manufactured goods (chapter seven). The different facets of the research as developed were subsequently integrated into a computer package which matched not 3 only the particular characteristics of the chosen problem but also general shipping problems (chapter eight). The variable selection procedure adopted for model development was a stratified Monte Carlo sampling technique. It was also desired that as part of the ex-post rationalisation of decision should be the projection of 'optimal' economic life of the investment. To this end a purpose ship residual value forecasting model was estimated and applied adopting a gross present value economic life determination criterion. The model selected a net present value maximising ship size from the parametrised decision variables of 8,000 dead weight tonnage (d.w.t.) and also included ship sizes 9,000 and 14,000 d.w.t. amongst the efficient set. These ship sizes were considered efficient to the extent that they offered plausible trade-offs between expected return and variability relative to the optimum. The model predicted an optimum ship economic life of ten years. Also the predictions of the model were found not to be sensitive to marginal variations in most of the assumptions made in model development.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:253565 |
| Date | January 1981 |
| Creators | Chizea, B. I. |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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