A logistic regression approach to estimating customer profit loss due to lapses in insurance

This article focuses on business risk management in the insurance industry. A methodology for estimating the profit loss caused by each customer in the portfolio due to policy cancellation is proposed. Using data from a European insurance company, customer behaviour over time is analyzed in order to estimate the probability of policy cancelation and the resulting potential profit loss due to cancellation. Customers may have up to two different lines of business contracts: motor insurance and other diverse insurance (such as, home contents, life or accident insurance). Implications for understanding customer cancellation behaviour as the core of business risk management are outlined.

Reverse logistics in the editorial sector: An exploratory study

Nowadays, the Reverse Logistics field is becoming very important. On one hand, laws areimposing companies to be responsible for the contamination made by their products. On theother hand, companies have discovered the profits derived from a good Reverse Logisticsprocess. This paper is the result of the work done by a group of companies from the SpanishEditorial sector to understand and improve their Reverse Logistics process. The paperdescribes the characteristics of the Reverse Logistics process in this sector and theimprovements identified by the work group .

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

A recoverable production planning model

Aware of the importance of developing new alternatives to improve the performance of the companies, our purpose in this paper is to develop a medium term production planning model that deals with the concepts of Partnership and Reverse Logistics. Our model takes advantage of the synergies of integration, developing a model for global production planning that generates the optimal production and purchasing schedule for all the companies integrating a logistic chain. In a second part of the paper we incorporate products returns to the first model proposed, and analyze the implications they have over this model. We use some examples with different configurations of supply chains varying the number of production plants, distribution centers and recovery plants. To solve the model we have combined optimization and simulation procedures.

Adapting football to the child: an application of the logistic regression model in observational mewthodology.

Logistic regression is included into the analysis techniques which are valid for observationalmethodology. However, its presence at the heart of thismethodology, and more specifically in physical activity and sports studies, is scarce. With a view to highlighting the possibilities this technique offers within the scope of observational methodology applied to physical activity and sports, an application of the logistic regression model is presented. The model is applied in the context of an observational design which aims to determine, from the analysis of use of the playing area, which football discipline (7 a side football, 9 a side football or 11 a side football) is best adapted to the child"s possibilities. A multiple logistic regression model can provide an effective prognosis regarding the probability of a move being successful (reaching the opposing goal area) depending on the sector in which the move commenced and the football discipline which is being played.

The unfathomable secret remains: a reverse engineering study of SEO factors on Google's search engine

The vast majority of users don’t seek results beyond the second page offered by the search engine, so if a site fails to be among the top 20 (second page), it says that this page does not have good SEO and, therefore, is not visible to the user. The overall objective of this project is to conduct a study to discover the factors that determine (or not) the positioning of websites in a search engine.

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Phase behavior and rheological analysis of reverse liquid crystals and W/I2, W/H2 gel emulsions using an amphiphilic block copolymer.

This article reports the phase behavior determi- nation of a system forming reverse liquid crystals and the formation of novel disperse systems in the two-phase region. The studied system is formed by water, cyclohexane, and Pluronic L-121, an amphiphilic block copolymer considered of special interest due to its aggregation and structural proper- ties. This system forms reverse cubic (I2) and reverse hexagonal (H2) phases at high polymer concentrations. These reverse phases are of particular interest since in the two-phase region, stable high internal phase reverse emulsions can be formed. The characterization of the I2 and H2 phases and of the derived gel emulsions was performed with small-angle X-ray scattering (SAXS) and rheometry, and the influence of temperature and water content was studied. TheH2 phase experimented a thermal transition to an I2 phase when temperature was increased, which presented an Fd3m structure. All samples showed a strong shear thinning behavior from low shear rates. The elasticmodulus (G0) in the I2 phase was around 1 order of magnitude higher than in theH2 phase. G0 was predominantly higher than the viscousmodulus (G00). In the gel emulsions,G0 was nearly frequency-independent, indicating their gel type nature. Contrarily to water-in-oil (W/O) normal emulsions, in W/I2 and W/H2 gel emulsions, G0, the complex viscosity (|η*|), and the yield stress (τ0) decreased with increasing water content, since the highly viscous microstructure of the con- tinuous phase was responsible for the high viscosity and elastic behavior of the emulsions, instead of the volumefraction of dispersed phase and droplet size. A rheological analysis, in which the cooperative flow theory, the soft glass rheology model, and the slip plane model were analyzed and compared, was performed to obtain one single model that could describe the non-Maxwellian behavior of both reverse phases and highly concentrated emulsions and to characterize their microstructure with the rheological properties.