When making choices and decisions, very seldom does the situation arise that a decision-maker very seldom bases their assessment of the options available on only one criterion. Frequently, many aspects of the available solutions are considered – both in terms of potential benefits and costs. In order to support decision makers, the Multiple-Criteria Decision Analysis (MCDA) is used for selecting the solution which is the best in several respects.

Neuromarketing is a multidisciplinary field of research whose aim is to investigate the consumers' reaction to advertisements from a neuroscientific perspective. In particular, the neuroscience field is thought to be able to reveal information about consumer preferences which are unobtainable through conventional methods, including submitting questionnaires to large samples of consumers or performing psychological personal or group interviews. In this scenario, we performed an experiment in order to investigate cognitive and emotional changes of cerebral activity evaluated by neurophysiologic indices during the observation of TV commercials. In particular, we recorded the electroencephalographic (EEG), galvanic skin response (GSR), and heart rate (HR) in a group of 28 healthy subjects during the observation of a series of TV advertisements that have been grouped by commercial categories. Comparisons of cerebral indices have been performed to highlight gender differences between commercial categories and scenes of interest of two specific commercials. Findings show how EEG methodologies, along with the measurements of autonomic variables, could be used to obtain hidden information to marketers not obtainable otherwise. Most importantly, it was suggested how these tools could help to analyse the perception of TV advertisements and differentiate their production according to the consumer's gender.

Composite indices have substantially gained in popularity in recent years. Despite their alleged disadvantages, they appear to be very useful in measuring the level of certain phenomena that are too complex to express with a single indicator. Most rankings based on composite indicators are created at regular intervals, such as every month, every quarter or every year. A common approach is to base rankings solely on the most current values of single indicators, making no reference to previous results. The absence of dynamics from such measurements deprives studies of information on change in these phenomena and may limit the stability of classifications.This article presents the possibility of creating reliable, dynamic rankings of measured items and measuring the complex phenomena with the use of composite indices. Potential solutions are presented on the basis of a review of the international literature. Some advantages and disadvantages of the presented solutions are described and an example of a new approach is shown.