The world of network science is fascinating and filled with complex phenomena that we aspire to understand. One of them is the dynamics of spreading processes over complex networked structures. Building the knowledge-base in the field where we can face more than one spreading process propagating over a network that has more than one layer is a challenging task, as the complexity comes both from the environment in which the spread happens and from characteristics and interplay of spreads’ propagation. As this cross-disciplinary field bringing together computer science, network science, biology and physics has rapidly grown over the last decade, there is a need to comprehensively review the current state-of-the-art and offer to the research community a roadmap that helps to organise the future research in this area. Thus, this survey is a first attempt to present the current landscape of the multi-processes spread over multilayer networks and to suggest the potential ways forward.

This data article describes the analysis of 56 MCDA (Multi-Criteria Decision Analysis) methods in regards to 9 decision-making problem characteristics structured into 3 levels. The impact of uncertainty in decision-making problem description on MCDA method selection is studied. 450,000 possible descriptions of a decision problem were studied, resulting in sets of rules which can serve as input to uncertainty-aware MCDA method selection decision support systems. Comprehensive analyses of the obtained rule sets are provided. An exemplary decision support system based on the presented data was created and is available at http://www.mcda.it. Moreover the technical documentation needed to create and expand such system is provided in this data article. The data and system can be easily extended and the authors invite all researchers to contribute.

Purpose: The purpose of this paper is to develop and test a method that can gradually find a sweet spot between user experience and visual intensity of website elements to maximise user conversion with minimal adverse effect. Design/methodology/approach: In the first phase of the study, the authors develop the method. In the second stage, the authors test and evaluate the method via an empirical study; also, an experiment was conducted within web interface with the gradual intensity of visual elements. Findings: The findings reveal that the negative response grows faster than conversion when the visual intensity of the web interface is increased. However, a saturation point, where there is coexistence between maximum conversion and minimum negative response, can be found. Practical implications: The findings imply that efforts to attract user attention should be pursued with increased caution and that a gradual approach presented in this study helps in finding a site-specific sweet spot for a level of visual intensity by incrementally adjusting the elements of the interface and tracking the changes in user behaviour. Originality/value: Web marketing and advertising professionals often face the dilemma of determining the optimal level of visual intensity of interface element. Excessive use of marketing component and attention-grabbing visual elements can lead to an inferior user experience and consequent user churn due to growing intrusiveness. At the same time, too little visual intensity can fail to steer users. The present study provides a gradual approach which aids in finding a balance between user experience and visual intensity, maximising user conversion and, thus, providing a practical solution for the problem.

The COMET method is a new multi-criteria decision-making (MCDM) method using the elements of fuzzy sets theory to identify a decision-making model in the space of a problem. This technique is entirely free of the rank reversal phenomenon, which is one of the most critical challenges in the MCDM field. The COMET method was primarily developed for dealing only with real-valued data. However, in many cases it is hard to present precisely the exact values of attributes for decision-making criteria. Therefore, intervals or fuzzy numbers should be used instead of numerical values in complex decision-making problems with data uncertainty.This paper proposes a new direct approach to use uncertain input data by using the COMET method in the decision-making process. We present a procedure to evaluate the preferences for the considered alternatives, which are described by using intervals or fuzzy numbers. A simple numerical example along with short discussion is presented for both cases.