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The purpose of this paper is to demonstrate that applied spatial modelling can inform the planning, delivery and evaluation of retail services, offering improvements over traditional retail impact assessment (RIA), especially within localities which experience seasonal fluctuations in demand.

The paper first describes a new theoretically informed tourist-based spatial interaction model (SIM) which has been custom-built and calibrated to capture the dynamics of the grocery sector in Cornwall, UK. It tests the power of the model to predict store performance for stores not used in the original calibration process, using client data for a new store development. The model is operationalised for the evaluation of various retail development schemes, demonstrating its contribution across a full suite of location decision making application areas.

The paper demonstrates that this highly disaggregate modelling framework can provide considerable insight into the local economic and social impacts of new store developments, rarely addressed in the retail location modelling literature.

Whilst SIMs have been widely used in retail location research by the private sector, the paper shows that such a model can have considerable value for public sector retail planning, a sector which seemed to have abandoned such models from the 1980s onwards, replacing them with often very limited and crude RIA.

The ability to review the forecasting capabilities of a model (termed post-investment review) are very rare in academic research. This paper offers new evidence that SIMs can support the RIA process.

We describe a new approach to intelligent building systems, that utilises an intelligent agent approach to autonomously governing the building environment. We discuss the role of learning in building control systems, and contrast this approach with existing IB solutions. We explain the importance of acquiring information from sensors, rather than relying on pre‐programmed models, to determine user needs. We describe how our architecture, consisting of distributed embedded agents, utilises sensory information to learn to perform tasks related to user comfort, energy conservation, safety and monitoring functions. We show how these agents, employing a behaviour‐based approach derived from robotics research, are able to continuously learn and adapt to individuals within a building, while always providing a fast, safe response to any situation. Finally, we show how such a system could be used to provide support for older people, or people with disabilities, allowing them greater independence and quality of life.

Graham S. Clarke, TD MA FCA FRSA, financial director of Fairey Holdings for the last four years, has been appointed managing director of its Energy and Military Engineering Division.

In January 2010, Benedict Clarke, general partner of a small real estate private equity venture, faced difficulty with one of his properties. When purchased in early 2007, Tulaberry Plaza was a thriving retail shopping center outside Orlando, Florida. The financial crisis and severe economic downturn forced Tulaberry's anchor tenant into bankruptcy and weakened the other tenants in the plaza. Clarke now faces pressures placed on him by his limited partners, who were shown rosy projections of the returns they would receive, and by his lender, who is presently taking most of the property's cash flow to satisfy required debt service. Clarke must devise a plan that presents the most logical and profitable way forward, while also justifying his actions to elicit the necessary support from the others involved in the transaction. The case asks students to make decisions from the perspective of Clarke, giving them an appreciation not only of the details of strategic decision-making in real estate leasing, but also of the interplay between lenders and equity partners when managing a commercial property in distress.

After reading and analyzing the case, students will be able to:

• Choose the right tenant for a retail establishment, with an understanding that it may not be the one that promises to pay the most rent

• Identify the connections among commercial property performance, mortgage loan covenants, and partnership agreements, all of which can influence optimal decision-making

Choose the right tenant for a retail establishment, with an understanding that it may not be the one that promises to pay the most rent

Identify the connections among commercial property performance, mortgage loan covenants, and partnership agreements, all of which can influence optimal decision-making

“Food deserts” in British cities are partly the result of the expansion of multiple food retailing. New large stores force smaller stores to close down, thus depriving local residents of food shopping opportunities. Examines this proposition through an analysis of changes in consumer access to food shopping in Cardiff over the last 20 years. Shows that although accessibility scores have increased in Cardiff since 1980 they have increased at a faster rate in higher income areas. In a pocket of deprived areas accessibility has declined over the decade. Thus, there has been a polarisation effect with a widening gap in accessibility scores across the city.

Computer matching is a mass surveillance technique involving the comparison of data about many people, which have been acquired from multiple sources. Its use offers potential benefits, particularly financial savings. It is also error‐prone, and its power results in threats to established patterns and values. The imperatives of efficiency and equity demand that computer matching be used, and the information privacy interest demands that it be used only where justified, and be subjected to effective controls. Provides background to this important technique, including its development and application in the USA and in Australia, and a detailed technical description. Contends that the technique, its use, and controls over its use are very important issues which demand research. Computing, telecommunications and robotics artefacts which have the capacity to change society radically need to be subjected to early and careful analysis, not only by sociologists, lawyers and philosophers, but also by information technologists themselves.

The purpose of this paper is to understand the contribution of visitor demand to the seasonal sales variations experienced at grocery retailers in Cornwall, South West England.

Working collaboratively with a major UK retailer provides access to store trading information and customer data from a popular loyalty card scheme. The authors use spatial analysis to identify revenue originating from outside the store catchment, and explore the spatial and temporal nature of the visitor demand recorded in‐store.

The paper demonstrates the significant degree of seasonality experienced around stores in terms of their revenue generated from out‐of‐catchment visitors, and highlights implications for store location planning. Most notably, visitor expenditure tends to demonstrate far more spatial and temporal clustering than residential demand. The authors argue that it is essential for retailers to ensure that their location planning makes full use of all available consumer data to understand the local nature of demand, including the impact of visitor expenditure.

The authors aim to use this insight to develop a spatial decision support system (SDSS) for use within site location planning in the retail sector. This would incorporate a spatial interaction model to estimate and account for variation in local demand generated by seasonal tourist visits.

Customer level loyalty card data are rarely available for academic investigations and the authors are able to provide a unique insight into customer expenditure in tourist locations. There has been little exploration of seasonal tourist demand in store location planning, and this study addresses an identified academic and commercial need.

There is a body of evidence that indicates mental illnesses are more prevalent in urban settings. However, to date no research has been carried out on the urban/rural incidence of mental illness in Ireland. This paper seeks to examine the micro level determinants of admissions to psychiatric hospitals between urban and rural areas.

Data from the National Psychiatric In‐patient Reporting System (NPIRS) and multivariate regression models are used.

Results from this analysis found that, in Ireland, rural residents had a higher probability of being admitted to a psychiatric hospital for schizophrenia and depression compared to urban residents.

The results presented here are only applicable to individuals that have been admitted to a psychiatric hospital. Findings cannot be extrapolated to the general population. Future research will involve the simulation of mental health characteristics for the entire Irish population.

The analysis presented in the paper contributes to the current understanding of the social and spatial profile of psychiatric admissions in Ireland, whilst providing additional research to the international debate regarding urban/rural differentials in acute psychiatric hospital admissions.