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This paper aims to address the effective selection of customers for direct marketing campaigns. It introduces a new method to forecast campaign-related uplifts (also known as incremental response modeling or net scoring). By means of these uplifts, only the most responsive customers are targeted by a campaign. This paper also aims at calculating the financial impact of the new approach compared to the classical (gross) scoring methods.

First, gross and net scoring approaches to customer selection for direct marketing campaigns are compared. After that, it is shown how net scoring can be applied in practice with regard to different strategical objectives. Then, a new statistic for net scoring based on decision trees is developed. Finally, a business case based on real data from the financial sector is calculated to compare gross and net scoring approaches.

Whereas gross scoring focuses on customers with a high probability of purchase, regardless of being targeted by a campaign, net scoring identifies those customers who are most responsive to campaigns. A common scoring procedure – decision trees – can be enhanced by the new statistic to forecast those campaign-related uplifts. The business case shows that the selected scoring method has a relevant impact on economical indicators.

The contribution of net scoring to campaign effectiveness and efficiency is shown by the business case. Furthermore, this paper suggests a framework for customer selection, given strategical objectives, e.g. minimizing costs or maximizing (gross or lift)-added value, and presents a new statistic that can be applied to common scoring procedures.

Despite its lever on the effectiveness of marketing campaigns, only few contributions address net scores up to now. The new χ²-statistic is a straightforward approach to the enhancement of decision trees for net scoring. Furthermore, this paper is the first to the application of net scoring with regard to different strategical objectives.

This chapter introduces the KontoSensor, a digital service offered by Deutsche Bank since September 2018, as an example of data processing using predictive analytics. We present the motivation behind this digital service, the use cases and methods currently implemented, the way they have been created, and measures to increase the usage of the KontoSensor. With KontoSensor, Deutsche Bank offers a digital service to its clients to analyze their transactions on their current accounts using methods from predictive analytics and to inform them when irregularities are found. Twelve months after the start, 90,000 clients are already using this service and experiencing the results of data science firsthand.

The purpose of this paper is to present some new results about reflective cold protective clothing (i.e. those featuring metal coatings), and compare and contrast the data with other recent research work.

The authors used a thermal manikin and a guarded hot plate to determine the thermal resistance of different textile assemblies and garment featuring plasma-deposited metal-coated insulation and interlayers.

Depending on the exact approach, the authors show that metal coatings can increase the thermal resistance of textile assemblies by ∼30-75 per cent.

New data on reflective cold weather clothing show that metal coatings could be an important addition to cold weather clothing, especially those featuring high air permeability/optical porosity insulation. Plasma-deposited metal coatings cause the lowest increase in weight.

This paper provides new data about the efficacy, in terms of thermal resistance, of metal coatings for cold weather clothing.

The purpose of this investigation was to measure the changes in effective thermal insulation caused by three different types of outer garment ventilation features (chest zips, back zips and pit zips) when combined with either a high or low air permeability insulating layer.

The measurements in this investigation were made with a thermal manikin and with a 26 zone thermal torso. Measurements were made at two air flow speeds with each manikin; the different air flow characteristics for each manikin allowed investigation of how ventilation features interact with different air flow distributions.

It was established in this study that high permeability insulation increases the efficacy of ventilation features by an average of 7 per cent at the low wind speed and 10 per cent at the high wind speed. No particular ventilation feature was found to be consistently the most effective; the data suggest that garment openings should simply be located in well-ventilated areas.

This investigation analysed the ventilation characteristics of protective clothing ensembles with different ventilation features, allowing designers to create more comfortable clothing for work and leisure activities.

The purpose of this paper is to determine the validity and inter-/intra-laboratory repeatability of the first part of a novel, three-phase experimental procedure using a sweating Torso device.

Results from a method comparison study (comparison with the industry-standard sweating guarded hotplate method) and an inter-laboratory comparison study are presented.

A high correlation was observed for thermal resistance in the method comparison study (r=0.97, p<0.01) as well as in the inter-laboratory comparison study (r=0.99, p<0.01).

The authors conclude that the first phase of the standardised procedure for the sweating Torso provides reliable data for the determination of the dry thermal resistance of single and multi-layer textiles, and is therefore suitable as standard method to be used by different laboratories with this type of device. Further work is required to validate the applicability of the method for textiles with high thermal resistance.

This study provides the first “round-robin” data for measuring thermal resistance using a Torso device. In future publications the authors will provide similar data examining the repeatability of measurements that quantify combined heat and mass transfer.

This paper aims to focus on different approaches to variable pre-selection for building net score models (also known as uplift modelling or incremental response modelling). The application of these models supports the identification of customers whose response can be traced back to be an effect of the campaign under consideration.

First, a net scoring methodology based on decision trees is presented. Then, derived from research contributions on this subject and analytics performed on real data from the financial sector, different approaches of variable pre-selection are discussed and compared numerically.

Net-χ2 and net information value as well as the rank lift impact correlation for interval variables would be preferred when performing variable pre-selection for net score models. Simulations showed that the results were relatively stable with respect to the number of cross-validation samples.

Variable pre-selection is required since it reduces computational effort that comes along with the complexity of net score models and the availability of a large amount of potential predictors. Some pre-selection methods result in a set of predictors quite close to the application of net scores itself.

Despite its lever on the effectiveness of marketing campaigns, only few contributions address net scores up to now and yet fewer authors deal with variable pre-selection for those models. In this regard, this article is the first to develop and compare different approaches.

The purpose of this paper is mainly to develop the adjoint method within the method of magnetic moment (MMM) and thus, to provide an efficient new way to solve topology optimization problems in magnetostatic to design 3D-magnetic circuits.

First, the MMM is recalled and the optimization design problem is reformulated as a partial derivative equation-constrained optimization problem where the constraint is the Maxwell equation in magnetostatic. From the Karush–Khun–Tucker optimality conditions, a new problem is derived which depends on a Lagrangian parameter. This problem is called the adjoint problem and the Lagrangian parameter is called the adjoint parameter. Thus, solving the direct and the adjoint problems, the values of the objective function as well as its gradient can be efficiently obtained. To obtain a topology optimization code, a semi isotropic material with penalization (SIMP) relaxed-penalization approach associated with an optimization based on gradient descent steps has been developed and used.

In this paper, the authors provide theoretical results which make it possible to compute the gradient via the continuous adjoint of the MMMs. A code was developed and it was validated by comparing it with a finite difference method. Thus, a topology optimization code associating this adjoint based gradient computations and SIMP penalization technique was developed and its efficiency was shown by solving a 3D design problem in magnetostatic.

This research is limited to the design of systems in magnetostatic using the linearity of the materials. The simple examples, the authors provided, are just done to validate our theoretical results and some extensions of our topology optimization code have to be done to solve more interesting design cases.

The problem of design is a 3D magnetic circuit. The 2D optimization problems are well known and several methods of resolution have been introduced, but rare are the problems using the adjoint method in 3D. Moreover, the association with the MMMs has never been treated yet. The authors show in this paper that this association could provide gains in CPU time.

The archives of François Perroux deposited at IMEC bear witness to the fact that he has devoted, beyond his scientific production, great energy to the most material aspects of research: setting up and maintaining networks to publicize his work and that of other economists, either directly or through the institutes and the journals he headed; organize seminars and symposiums; take care of relations with colleagues and the press; create collections and journals; and so on.

In this chapter, we concentrate our attention on the archives relating to the management of the institutes, those attesting to the lines and themes of the producer’s research, and those concerning his important correspondence.

Thanks to the archives deposited at IMEC, it is possible to follow the development of the theoretical work of François Perroux by contextualizing it. They also show the itinerary of a Christian intellectual, whose attachment to social Catholicism constitutes a guiding thread and is reflected in all his activities. Finally, the archives illuminate his substantial role in the institutionalization of research in economics in the France of the twentieth century.