Purpose – Real operational data are used to optimise the performance measurement of air cargo capacity demand management at Virgin Atlantic Cargo by identifying the best KPIs from the range of outcome-based KPIs in current use. Design/methodology/approach – Intelligent fuzzy multi-criteria methods are used to generate a ranking order of key outcome-based performance indicators. More specifically, KPIs used by Virgin Atlantic Cargo are evaluated by experts against various output criteria. Intelligent fuzzy multi-criteria group making decision-making methodology is then applied to produce rankings. Findings – A useful ranking order emerges from the study albeit with the important limitation that the paper looked solely at indices focussing exclusively on outcomes while ignoring behavioural complexity in the production of outcomes. Originality/value – This paper offers a practical overview of the development of performance measures useful for air cargo capacity demand management.

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This article sought to facilitate the optimisation of key performance measures utilised for demand management in air cargo operations. The focus was on the Revenue Management team at Virgin Atlantic Cargo and a fuzzy group decision-making method was used. Utilising intelligent fuzzy multi-criteria methods, the authors generated a ranking order of ten key outcome-based performance indicators for Virgin Atlantic air cargo Revenue Management. The result of this industry-driven study showed that for Air Cargo Revenue Management, ‘Network Optimisation’ represents a critical outcome-based performance indicator. This collaborative study contributes to existing logistics management literature, especially in the area of Revenue Management, and it seeks to enhance Revenue Management practice. It also provides a platform for Air Cargo operators seeking to improve reliability values for their key performance indicators as a means of enhancing operational monitoring power.

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We have introduced a semi-analytical IS technique suitable for multipole, rational function reflection coefficients, and used it for the design of dispersion-engineered planar waveguides. The technique is used to derive extensive dispersion maps, including higher dispersion coefficients, corresponding to three-, five- and seven-pole reflection coefficients. It is shown that common features of dispersion-engineered waveguides such as refractive-index trenches, rings and oscillations come naturally from this approach when the magnitude of leaky poles in increased. Increasing the number of poles is shown to offer a small but measureable change in higher order dispersion with designs dominated by a three pole design with a leaky pole pair of the smallest modulus.