Stochastic computer‐simulation models have been constructed of the clothing supply chain and applied to retail inventory control. This quantifies the performance of quick response procedures for seasonal merchandise, thus creating an analytical tool. They are designed to investigate the effects of improved retailing and supply procedures on financial and other performance measures using two supply strategies: fixed quantity re‐ordering and fixed interval re‐ordering. These offer a wide range of options in experimentation. They permit an evaluation of both purchasing systems in relation to different quantities and lead‐time scenarios. Experimental work with both models has shown that if the replenishment time exceeds two weeks, the potential for lost sales greatly increases. This provides a benchmark figure for assessing the responsiveness of clothing industry supply chains.

Building maintenance has until recently been a neglected field of quantitative modelling and of academic study. It has not attracted very much attention despite being regarded as under‐funded, unproductive and poorly managed, or the recognition that many of its managerial problems are demanding more research and skills than those of new works. Discusses the priorities, categories of maintenance work, and factors affecting demand for maintenance. Based on general statistics obtained, identifies and quantifies both major problems areas (in terms of cost and frequency of maintenance activities) and the nature and cause of the demand for maintenance in a major hospital complex. They have revealed no coherent picture, in that demand from wards and building seems independent of patient throughput and age of buildings. The demand for maintenance, for the main trades involved, namely plumbing, joinery, electrical and mechanical have been forecast and arrival rate of jobs per trade has been estimated. This would enhance the management process and work planning which would result in a more economic use of resources and a corresponding reduction in the total cost of maintaining property to a standard.

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Purpose -The purpose of this research is to assess the service quality of central blood bank from blood donors' perspective. Design/methodology/approach -Data were collected by empirical study in a central blood bank. The instrument captured 354 blood donors' using a SERVQUAL questionnaire. The study looked at perception and expectation levels of blood donors. After that, the gap five scores were determined. Findings -The paper finds that, for the blood donors, gap (five) scores are all positive implying that the blood donors' tend to be satisfied. Practical implications -Based on the results, central blood bank management may consider measures in order to diagnose, analyze, and identify opportunities of improvements of service quality. Originality/value -This study attempts to explore the relatively less explored area of measuring service quality of a central blood bank from blood donors' perspectives through implementation of the SERVQUAL model.

Explains that UK consumers currently spend over £9 billion on do-it-yourself (DIY) home improvement products. States that in the 1980s this was the UK's fastest growing major retail sector, and the booming UK housing market, especially the number of house moves, was widely thought to be the main stimulus for this growth. Reveals that the annual number of house moves has fallen by 50 per cent since 1988 but the DIY market has still grown, which suggests that the link between DIY and the housing market has either changed or is not as strong as previously believed. Reassesses the major factors which affected the DIY market in the 1980s through data analysis and multiple regression techniques. Suggests from the results that the effect of house moves on the DIY market is less than conventional wisdom would indicate. Notes that the most significant factors have been identified and are being used in a five-year forecast which shows growth in line with increases in the general economy in a new, mature DIY market. Concludes that the results highlight the care needed when basing forecasts on a single factor which may no longer be valid.