Locating fire stations: An integrated approach for Belgium

This paper illustrates the potential of a decision-support system developed for Belgium by a consortium of universities and a private firm, in the framework of a public call made by the Ministry of the Interior. The system is designed to provide the Belgian emergency management administration with a complete decision-aid tool for the location of fire stations. The originality of the project is that it includes a risk-modeling approach developed at a national scale. This analysis involves a multiscale GIS that includes a thorough representation of the physical, human and economic spatial realities, a risk-modeling approach, an adequate optimal location and allocation model (taking into account both queuing and staffing problems). The final result is an interactive operational tool for defining locations, equipment allocations, staffing, response times, the cost/efficiency trade-off, etc. This flexible tool can be used in an assessment as well as a prospective context. It has been used to draw a national reorganization plan for fire stations that started being implemented in 2010.     

How well does a national newspaper reporting system profile drowning?

In Finland, the Finnish Association for Swimming Instruction and Life Saving (SUH) and Statistics Finland (SF) both provide nationwide data on unintentional drowning. The SUH database relies on rapid reporting from a newspaper clipping service and additional local police information, whereas the SF database relies on the later release of the death certificate information, which is based on extensive medico-legal investigation. The aim of the study was to explore the main differences between the SUH and SF databases for drowning and to evaluate the capacity of the former to characterize drowning events in Finland from 1998 to 2000. Computerized files of death certificates tabulated by SF were linked with the SUH database by deterministic methods. SF and SUH databases allowed the identification of 704 and 567 unintentional drownings, respectively, giving an unintentional drowning rate of 4.5 and 3.6/100?000 per year. Of the 704 drownings described by SF, 418 (59.4%) were also found in the SUH database. The SUH database markedly underreported drowning fatalities in certain settings, such as bath, ditch and swimming pool drownings; fall- and land-traffic-related drownings; and drownings occurring in South Finland. The narrative text of SUH drownings contributed limited information to characterize the drowning events. It was concluded that the newspaper-based SUH data provide more timely data on individual drownings but are not representative of all drownings. Conversely, the SF vital statistics data are more accurate but may take up to 2 years to become available. Both SUH and SF data provide little detailed information on drowning events. A multidisciplinary national surveillance system for drowning is necessary to provide more accurate and timely drowning data, analyse risk factors and design follow-up studies for developing and monitoring prevention strategies.     

Estimating Armington elasticities for sawnwood and application to the French Forest Sector Model

Domestic and foreign forest products consumptions are considered imperfectly substitutable in the French Forest Sector Model (FFSM). This assumption is justified by product heterogeneities that depend on production places, by the consumers habits or by the market structure. It leads us to implement the international trade in the FFSM via the Armington's theory of the demand for products distinguished by place of production. In this paper we propose a calibration of Armington's elasticities of substitution between French and foreign forest products. System-GMM estimators are applied to identify robust parameters using a panel data from France customs service.     

The differing and mediating roles of trust and relationship commitment in service relationship maintenance and development

Relationship maintenance (customer retention and exclusivity) and development (increased service usage and cross-buying) are top priorities in Customer Relationship Management. This paper examines how service companies can effectively influence customer patronage behaviors by leveraging overall customer satisfaction, trust and relationship commitment. Using a longitudinal design over a two-year period, we merge survey metrics with actual patronage behaviors taken from a bank’s database. We show that relationship commitment just enhances retention and exclusivity while trust directly influences service usage and cross-buying. As a consequence, trust appears to be highly critical for service relationship development and company profits. Furthermore, trust and relationship commitment mediate the entire impact of satisfaction which appears as a necessary but not sufficient condition for relationship maintenance and development. Satisfaction, and more generally service evaluations, must be efficiently converted into trust and relationship commitment before providing business results. Finally, we establish the temporal antecedence and the predictive power of trust and relationship commitment. Relationship commitment in year t predicts the number of service providers in year t + 1 (exclusivity vs. polygamy), while trust in year t predicts the number of bank products (cross-buying) as well as the service usage level in year t + 1. We then discuss managerial implications for customer relationship maintenance and development.     

Manufacturing output and extreme temperature: Evidence from Canada

This paper analyzes the effects of extreme temperature on manufacturing output using a data set covering the universe of manufacturing establishments in Canada from 2004 to 2012. Extreme temperature can affect manufacturing activity directly through its impact on labour productivity and indirectly through a change in demand for products. Using a panel fixed effects method, our results suggest a non-linear relationship between outdoor extreme temperature and manufacturing output. Each day where outdoor mean temperatures are below $-18$ °C or above 24 °C reduces annual manufacturing output by 0.18% and 0.11%, respectively, relative to a day with mean temperature between 12 ° and 18 °C. In a typical year, extreme temperatures, as measured by the number of days below $-18$ °C or above 24 °C, reduce annual manufacturing output by 2.2%, with extreme hot temperatures contributing the most to this impact. Given the predicted change in climate for the mid- and end of century, we predict annual manufacturing output losses due to extreme temperature to range between 2.8% and 3.7% in mid-century and 3.7% and 7.2% in end of century.