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Real estate development appraisal is a quantification of future expectations. The appraisal model relies upon the valuer/developer having an understanding of the future in terms of the future marketability of the completed development and the future cost of development. In some cases the developer has some degree of control over the possible variation in the variables. However, other variables are totally dependent upon the vagaries of the market at the completion date. To try to address the risk of a different outcome to the one expected the developer will often carry out a sensitivity analysis on the development. This paper aims to look at the processes for so doing and the role of the decision maker in the analysis.

Traditional sensitivity analysis has generally only looked at the best and worst scenarios and has focused on the anticipated or expected outcomes. This does not take into account uncertainty and the range of outcomes that can happen. A fuller analysis should include examination of the uncertainties in each of the components of the appraisal and account for the appropriate distributions of the variables. This requires a standardised approach and the use of a generic forecasting software package.

There are numerous risks involved in the development of real estate. By allowing the decision maker to contribute to the assessment of these risks, the analysis provides the decision maker with a greater understanding of the critical variables and their impact upon the viability of the final scheme.

This analysis shows that developers can get a better understanding of the upside and downside risks associated with their project.

Heralding a new era in the leisure aviation market was the arrival early in February at Luton International Airport of Britannia Airways' new Boeing 767—the first in Europe.

This paper aims to explore the impact of inventory system inaccuracies on the benefits of collaborative supply chain practices under various supply chain scenarios. To achieve this purpose, two popular collaboration initiatives are considered in a four‐stage supply chain. The first practice is a vendor managed inventory program where the distributor takes the full responsibility of managing the retailer's inventory. The second practice is a collaborative planning, forecasting, and replenishment program where all members work together to plan, forecast, and replenish the product.

The study utilizes Monte Carlo computer simulation in an experimental design.

The analysis suggests that while the inaccurate inventory records result in significant performance reductions for all supply chain configurations, their impact is substantially greater for the supply chains where members collaborate more closely on key supply chain management activities. In addition, the author also realize that the adverse impact of inaccurate inventory information is stronger under the conditions where lead times are shorter and/or where demand uncertainty in market place is lower.

This analysis provides a means for practitioners to realize the importance of inventory accuracy to successful adaptation of collaborative supply chain practices. Moreover, this research also helps in understanding the supply chain conditions where the attempts of eliminating or reducing errors in inventory information are more crucial and more beneficial.

Although there is a range of research focusing on collaborative practices, none of these studies considered the errors in inventory information. This is the first study to investigate the impact of inaccurate inventory information on the benefits of collaborative practices.

Inventory control is not the same as stock control ‐ it means control of each item that goes to make up the total inventory. In this exercise Keith Padden shows how his hypothetical range of crystal balls ‐ by which he means baked beans, soft drinks, instant coffee, or anything else ‐ can be rationalised. The result can be a release of working capital sufficient to make good the deficit in cash flow ‐ or to buy sites, build and fit out six 15,000 sq ft supermarkets.

Uncertainty affects all aspects of the property market, but one area where the impact of uncertainty is particularly significant is within feasibility analyses. Any development is impacted by differences between market conditions at the conception of the project and the market realities at the time of completion. This paper sets out to address this issue

The feasibility study needs to address the possible outcomes based on an understanding of the current market. This requires the appraiser to forecast the most likely outcome relating to the sale price of the completed development, the construction costs and the timing of both. It also requires the appraiser to understand the impact of finance on the project.

This allows the appraiser to address the issues of uncertainty involved and thus provide the decision maker with a better understanding of the risk of development. This technique is then refined using a “two‐dimensional technique” to distinguish between “uncertainty” and “variability” and thus create a more robust model.

The feasibility study needs to address the possible outcomes based on an understanding of the current market. This requires the appraiser to forecast the most likely outcome relating to the sale price of the completed development, the construction costs and the timing of both. It also requires the appraiser to understand the impact of finance on the project.

Valuation is often said to be “an art not a science” but this relates to the techniques employed to calculate value not to the underlying concept itself. Valuation is the process of estimating price in the market place. Yet, such an estimation will be affected by uncertainties. These input uncertainties will translate into an uncertainty with the output figure, the valuation. The degree of the uncertainties will vary according to the level of market activity; the more active a market, the more credence will be given to the input information. In the UK at the moment the Royal Institution of Chartered Surveyors (RICS) is considering ways in which the uncertainty of the valuation can be conveyed to the use of the valuation, but as yet no definitive view has been taken apart from a single Guidance Note (GN5). One of the major problems is that valuation models (in the UK) are based on comparable information and rely on single inputs. They are not probability‐based, yet uncertainty is probability driven. This paper discusses the issues underlying uncertainty in valuations and suggests a probability‐based model (using Crystal Ball) to address the shortcomings of the current model.

Sales of industrial oils and fluids in the United States reached US $2.8 billion in 1986. However, due to falling crude oil prices in that year, and thus lower prices for several product catagories, the industrial lube market is actually down slightly in value from US $2.9 billion in 1985, according to a report recently released by Kline & Co, international petroleum industry consultants.