The application of churn prevention represents an important step for mobile communication

companies aiming at increasing customer loyalty. In a machine learning perspective,

Customer Value Management departments require automated methods and processes to

create marketing campaigns able to identify the most appropriate churn prevention approach.

Moving towards a big data-driven environment, a deeper understanding of data

provided by churn processes and client operations is needed. In this context, a procedure

aiming at reducing the number of churners by planning a customized marketing campaign

is deployed through a data-driven approach. Decision Tree methodology is applied to drow

up a list of clients with churn propensity: in this way, customer analysis is detailed, as well

as the development of a marketing campaign, integrating the individual churn model with

viral churn perspective. The first step of the proposed procedure requires the evaluation of

churn probability for each customer, based on the influence of his social links. Then, the

customer profiling is performed considering (a) individual variables, (b) variables describing

customer-company interactions, (c) external variables. The main contribution of this work

is the development of a versatile procedure for viral churn prevention, applying Decision

Tree techniques in the telecommunication sector, and integrating a direct campaign from

the Customer Value Management marketing department to each customer with significant

churn risk. A case study of a mobile communication company is also presented to explain

the proposed procedure, as well as to analyze its real performance and results.

The exploration of mineral resources is an area of strategic importance for the pace of further development of all industries. The results of companies deciding to carry out exploration work depend on further investments of mining companies, i.e. the entities purchasing full deposit documentation. Being at the beginning of the entire mining process, junior mines assume a high risk related to investments enabling the commencement of works without providing high guarantees of the project’s success. Companies running these types of projects must seek funding in a variety of ways. One of these is to try to raise capital from the stock trading markets. However, the specificity of junior companies does not allow them to start on the main trading floors, hence the decision to enter alternative markets. In considering the broader context of the activities of junior mines, research was conducted on companies listed on the London Alternative Investment Market (AIM). In the first part, this concerned the market characteristics – the market value added values were determined for selected ranges of market capitalization. In the second part, which is a statistical study, factors that may affect their market value was checked. The analysis covered both traditional value drivers – related to revenues, the demand for net working capital, investment expenses and the cost of equity – and their supplementation with selected values of financial statements. The result of the analysis is a regression equation indicating the factors that have a statistically significant impact on the market value of junior mines listed on AIM London.

Today’s fast-changing environment for construction companies requires rapid responses and adaptation of their projects. Despite the multitude of tools applied for project cost management in engineering and construction companies, there is a need to form comprehensive solutions. The purpose of the study is to form a methodological approach to project cost management in the field of engineering construction based on alternative models to diagnose the development, assessment and selection of functional areas and content of cost management in the construction project, which allows one to increase adaptability and flexibility in the process of its implementation. The basis of research methodology is modeling, which allows one to adjust the economic and financial flows based on three S-curves, one for each component of the total cost of the work: direct costs, indirect costs and reserves. These curves include the direct cost curve for the main purchasing packages as well. This brings financial flows closer to reality because it is possible to adjust the S-curves according to the behavior of each subsystem. The contribution of the study is the proposed approach of integrating concepts related to the coordination and development of project design and production management (lean construction), forming a “3D model of management”, in a broad and comprehensive management system. It assumes a comprehensive and complete way to manage civil engineering projects. The proposed methodological approach can make a significant contribution to the preparation of forecasts and estimates by planners and controllers in the context of construction projects.