Location Quotients (LQs) remain an important tool for geographical analysis, particularly in terms of assessing industrial specialisation and clustering. LQs as decision aids are typically understood through the use of arbitrarily set cut-off values. However, LQs are rarely accompanied by an associated level of variance that can be connected with the estimated data used to calculate them. This paper reveals the importance of understanding this variance and shows how confidence intervals can be estimated for employment-based LQs. A systematic process is introduced, through which the arbitrariness of cut-off-value choice can be mitigated and borderline industry cases in terms of their LQ values and the considered cut-off value, identified. A case from a UK region is used to illustrate the issues covered in the paper.

Understanding the factors that make a location more rural or urban is an important task for planners and policymakers. Traditional individual characteristics of rurality sometimes hide the more complex social as well as physical dynamics of a locality. This paper builds on early work which applied factor analysis to construct a single index of rurality. An approach is developed with a combined metric encompassing multiple measures. These are capable individually of defining rurality but together they deliver greater insight on more complex patterns and help to redefine the simple notion of rurality. The paper then utilises a novel graphical method, the constellation graph, providing a diagnostic and visual framework to aid planners when assessing the spatial dimensions of a locality.

Numerous studies have looked at the multitude of aspects affecting the utility workers gain from their job. Within these studies, a common proxy for utility is job satisfaction, measured as a self-reported score. A variable often neglected within this research has been commuting time and modes of transport. This article utilizes a unique survey conducted in a UK city region and analyses the effect of commuting time and mode of transport on self-reported job satisfaction. Two cohorts of respondents are constructed based upon income levels, thus establishing the offsetting effect of income on commute. The study finds that commuting time has a negative effect on the utility of workers. However, the effect is found to be income dependent, with those earning the most having no negative effect from commuting time. Using a number of modes of transport is found to not have an effect on the utility of workers.

This paper considers the work of the European Cluster Observatory (ECO) in light of current debates around the notion of clusters. Examining the definitions employed by the ECO, questions are posed about how effective policy can be when using highly restrictive means of analysis. Further, the work contends that, far from this being purely an analytical problem, there also exists a fundamental semantic issue regarding the term 'economic cluster'.

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