Edwards, D J and Nicholas, J (2001) Telescopic handler machine park prediction using sales trends. Journal of Financial Management of Property and Construction, 6(2), pp. 109-118. ISSN 1366-4387
Abstract
A univariant Auto Regressive Integrated Moving Average (ARIMA) (3,0,0) model is presented to forecast the number of telescopic handlers in the UK machine park. Machine park is defined as the total number of construction machines available and/or physically operational in the UK construction industry. Telescopic handlers have received special attention because the growth in their sales has risen significantly over the last two decades. Further, these machines now represent a large proportion of those plant items used on construction sites. Manufacturers of telescopic handlers (and machine component suppliers) will benefit from using the derived ARIMA model becuase they will be provided with insight into future sales trends, as well as the spare parts and replacement components demand for these machines. A database of telescopic hndler machines sales, obtained from a major plant manufacturer, covering a twenty-year range (1980 - 1999) was used to build the ARIMA model. The model identifies that the trend in telescopic handler machine park can be accurately forecast based on the preceding three years’ sales; and that such trends are highly susceptible to the fluctuating macroeconomic environment. Using this ARIMA model, a forecast of telescopic handler machine park numbers is produced for this (2000) and the next two years (2001 and 2002). The ARIMA (3,0,0) model predicts that the trend in telescopic handler machine park is likely to increase by over thirty-six per cent up to 2002. The statistical power of the ARIMA model is reinforced by it exhibiting and R2 of 0.9978 and MAD of 136 machines.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | telescopic handlers, machine park, autoregressive moving average, forecasting, construction plant |
| Index terms: | manufacturer, construction site, replacement, construction plant, forecasting, database, construction industry |
| Subjects: | practitioner, materials science, data management, industry analysis, construction equipment, work location, prediction and forecasting |
| Topics: | Site Management, Digital Applications, Roles and Professions, Plant and Equipment, Research Practice, Engineering Principles |
| Descriptive scope: | 4 PCTA |
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