Informatica

Purpose: Few studies in the literature address the success of enterprise Information Systems (IS) projects, namely focusing on how success is influenced by project management practices. This research studied the impact of ISO 21500/PMBOK processes on the success of IS projects, aiming to contribute to a better understanding of management practices importance in the context of this type of projects. Design/methodology/approach: An international survey was used to collect data, which was analysed using descriptive and inferential statistics. Findings: The results show higher levels of success than usually reported in the literature. Furthermore, this research shows that overall success is strongly influenced by ISO/PMBOK project management processes, thus reinforcing the relevance of competent project management to improve the results of IS projects. Originality: Focusing on the specific case of IS projects, this study shows that higher levels of success are achieved by organizations with higher project management maturity.

Multidimensional scaling (MDS) is a widely used technique for mapping data from a high-dimensional to a lower-dimensional space and for visualizing data. Recently, a new method, known as Geometric MDS, has been developed to minimize the MDS stress function by an iterative procedure, where coordinates of a particular point of the projected space are moved to the new position defined analytically. Such a change in position is easily interpreted geometrically. Moreover, the coordinates of points of the projected space may be recalculated simultaneously, i.e. in parallel, independently of each other. This paper has several objectives. Two implementations of Geometric MDS are suggested and analysed experimentally. The parallel implementation of Geometric MDS is developed for multithreaded multi-core processors. The sequential implementation is optimized for computational speed, enabling it to solve large data problems. It is compared with the SMACOF version of MDS. Python codes for both Geometric MDS and SMACOF are presented to highlight the differences between the two implementations. The comparison was carried out on several aspects: the comparative performance of Geometric MDS and SMACOF depending on the projection dimension, data size and computation time. Geometric MDS usually finds lower stress when the dimensionality of the projected space is smaller.

The aim of the article is to identify drivers and limiters of the development of Business Process Management Systems (BPMS) from the point of view of the industry and the academia, and to formulate practical recommendations. Their identification is crucial in order to remove a considerable gap between the approach to knowledge-intensive business processes (kiBPs), which require dynamic management and are decisive with regard to the competitive position of the organization under the conditions of Industry 5.0, as well as the possibilities offered by ICT solution, and the current possibilities and needs of BPM practitioners. The authors applied a methodological approach based on a theoretical literature review and a review of practice through online structured expert interviews with key BPMS solution providers. According to the literature, the main drivers pertain to the enterprises’ efforts to reduce costs and improve their productivity and efficiency, develop technology, and enact changes in business models and business processes. According to vendors, the main drivers for the combination of BPMS and Case Management Systems (CMS) were the users’ expectations, technology identity, and further development perspectives. The main limiters of the decision to combine both classes of systems were technological problems predicted by vendors related to the unification of historically different technologies used in both classes of systems, as well as implementation-based problems related to the likely need to reconfigure the software environments of software users. The article formulated original recommendations for both vendors and users of iBPMS software, including the basic recommendation of the selection of the methodology of implementation of BPM and iBPMS in accordance with the context of the organization’s operations (the nature of its business processes).

We introduce a compact formulation for the fixed-destination multi-depot asymmetric travelling salesman problem (FD-mATSP). It consists of m salesmen distributed among D depots who depart from and return to their respective origins after visiting a set of customers. The proposed model exploits the multi-depot aspect of the problem by labelling the arcs to identify the nodes that belong to the same tour. Our experimental investigation shows that the proposed-two index formulation is versatile and effective in modelling new variations of the FD-mATSP compared with existing formulations. We demonstrate this by applying it for the solution of two important extensions of the FD-mATSP that arise in logistics and manufacturing environments.

This model describes the heat equation in 3D domains, and this problem is reduced to a hybrid dimension problem, keeping the initial dimension only in some parts and reducing it to one-dimensional equation within the domains in some distance from the base regions. Such mathematical models are typical in industrial installations such as pipelines. Our aim is to add two additional improvements into this methodology. First, the economical ADI type finite volume scheme is constructed to solve the non-classical heat conduction problem. Special interface conditions are defined between 3D and 1D parts. It is proved that the ADI scheme is unconditionally stable. Second, the parallel factorization algorithm is proposed to solve the obtained systems of discrete equations. Due to both modifications the run-time of computations is reduced essentially. Results of computational experiments confirm the theoretical error analysis and scalability estimates of the parallel algorithm.

One of the biggest difficulties in telecommunication industry is to retain the customers and prevent the churn. In this article, we overview the most recent researches related to churn detection for telecommunication companies. The selected machine learning methods are applied to the publicly available datasets, partially reproducing the results of other authors and then it is applied to the private Moremins company dataset. Next, we extend the analysis to cover the exiting research gaps: the differences of churn definitions are analysed, it is shown that the accuracy in other researches is better due to some false assumptions, i.e. labelling rules derived from definition lead to very good classification accuracy, however, it does not imply the usefulness for such churn detection in the context of further customer retention. The main outcome of the research is the detailed analysis of the impact of the differences in churn definitions to a final result, it was shown that the impact of labelling rules derived from definitions can be large. The data in this study consist of call detail records (CDRs) and other user aggregated daily data, 11000 user entries over 275 days of data was analysed. 6 different classification methods were applied, all of them giving similar results, one of the best results was achieved using Gradient Boosting Classifier with accuracy rate 0.832, F-measure 0.646, recall 0.769.

An extension of the Integrated Simple Weighted Sum Product (WISP) method is presented in this article, customized for the application of single-valued neutrosophic numbers. The extension is suggested to take advantage that the application of neutrosophic sets provides in terms of solving complex decision-making problems, as well as decision-making problems associated with assessments, prediction uncertainty, imprecision, and so on. In addition, an adapted questionnaire and appropriate linguistic variables are also proposed in the article to enable a simpler and more precise collection of respondents’ attitudes using single-valued neutrosophic numbers. An approach for deneutrosophication, i.e. the transformation of a single-valued neutrosophic number into a crisp number is also proposed in the article. Detailed use and characteristics of the presented improvement are shown on an example of the evaluation of rural tourist tours.

An image or volume of interest in positron emission tomography (PET) is reconstructed from gamma rays emitted from a radioactive tracer, which are then captured and used to estimate the tracer’s location. The image or volume of interest is reconstructed by estimating the pixel or voxel values on a grid determined by the scanner. Such an approach is usually associated with limited resolution of the reconstruction, high computational complexity due to slow convergence and noisy results.

Aimed at achieving the accurate restoration of Poissonian images that exhibit neat edges and no staircase effect, this article develops a novel hybrid nonconvex double regularizer model. The proposed scheme closely takes the advantages of total variation with overlapping group sparsity and nonconvex high-order total variation priors. The overlapping group sparsity is adopted to globally suppress the staircase artifacts, while the nonconvex high-order regularization plays the role of locally preserving the significant image features and edge details. Computationally, a quite efficient alternating direction method of multipliers, associated with the iteratively reweighted ${\ell _{1}}$ algorithm and the majorization-minimization method, is employed to settle the optimization problem iteratively. Finally, exhaustive simulation experiments are executed for recovering Poissonian images, which are made comparisons with several state-of-the-art restoration strategies, indicate the brilliant performance of our model in terms of intuitive effects and accuracy evaluation.

The software Randentropy is designed to estimate inequality in a random system where several individuals interact moving among many communities and producing dependent random quantities of an attribute. The overall inequality is assessed by computing the Random Theil’s Entropy. Firstly, the software estimates a piecewise homogeneous Markov chain by identifying the change-points and the relative transition probability matrices. Secondly, it estimates the multivariate distribution function of the attribute using a copula function approach and finally, through a Monte Carlo algorithm, evaluates the expected value of the Random Theil’s Entropy. Possible applications are discussed as related to the fields of finance and human mobility.