Abstract
In this paper we analyze the relationship between the marketing mix and new product diffusion models. The goal is to obtain a general new product diffusion model that incorporates the classic 4Ps model of the Marketing Mix: Product, Price, Place, Promotion. An empirical study was conducted using mobile broadband adoption data in Japan. © 2022 Elsevier B.V.. All rights reserved.

Abstract
Churn and how to deal with it is an essential issue in the telecommunications sector. Within the scope of actionable knowledge, we argue that it is crucial to find effective personalized interventions that can lead to a reduction in dropouts and that, at the same time, make it possible to determine the causal effect of these interventions. Considering an intervention that encourages clients to opt for a longer-term contract for benefits, we used Uplift modeling and the Transformed Outcome Approach as a machine learning-based technique for individual-level prediction. The result is actionable profiles of persuadable customers that increase retention and strike the right balance between the campaign budget.

Abstract
The digital learning transformation brings the extension of the traditional libraries to online repositories. Learning object repositories are employed to deliver several functionalities related to the learning object's lifecycle. However, these educational resources usually are not described effectively, lacking, for example, educational metadata and learning goals. Then, metadata incompleteness limits the quality of the services, such as search and recommendation, resulting in educational objects that do not have a proper role in teaching/learning environments. This work proposes to bring an active role to all educational resources, acting on the analysis generated from the usage statistics. To achieve this goal, we created a multi-agent architecture that complements the common repository's functionalities to improve learning and teaching experiences. We intend to use this architecture on a repository focused on ocean literacy learning objects. This paper presents some steps toward this goal by enhancing, when needed, the repository to adapt itself.

Abstract
Customer retention is nowadays a challenge that requires concrete and personalized actions. Traditional data mining studies focused on predictive analytics, neglecting the business domain. This work aims to present an actionable knowledge discovery based on specific, actionable attributes and measuring of their effects. It is common to use matching, and propensity score approaches in healthcare to evaluate causality. After performing matching using the actionable attributes in this analysis, the causal effect is quantified. This work concludes that the difference between having a yearly contract versus having a monthly contract affects the churn of around 34%.

Abstract
This data article describes a dataset of corruption approach and possible variables related, and this dataset was created by integrating eight different systems of Brazilian federal government and Federal District. We present real data from civil servants and militaries to comply with GDPR legislation, the attributes that could identify a person were removed, making the data anonymized. (C)D 2022 The Authors. Published by Elsevier Inc.

Abstract
The software industry still struggles with adverse effects of a weak alignment between requirements and testing. The Software Pattern Metamodel (SoPaMM) aligns requirements and test patterns under the influence of agile practices. However, these patterns will be more beneficial for professionals if development activities are supported by a software tool. This paper presents the behaviour-DRivEn Application Model generator (DREAM) tool, automatically generating requirements and test specifications from SoPaMM-based patterns. We show how DREAM supports requirements elicitation and specification, test case elaboration, and software documentation using a patterns catalogue for electronic health record systems.