## 4 Identification and Summary of Main Contributions  
After the previous analyses, a complete picture is obtained of which authors and organisations group knowledge around the complexity of aerospace. It is also known which specific topics are of interest within complexity studies. This information lets us determine which works are or have been influential. This is the last step of the bibliometric analysis, and it will help to know explicitly which studies have been carried out and extract the advantages and/or weaknesses of these models. This final study answers the questions \"What are the main solutions proposed by academia to the complexity problem?\" and \"What are the weaknesses and strengths of the main complexity indicators?\". By answering these questions, the bibliometric analysis is completed. The identification of the main contributions was carried out considering a combination of the following criteria:  
* Number of citations: The number of citations considers the number of times that this document has been used as a reference in other studies. Therefore, the number of citations is highly relevant when deciding whether a publication is relevant or not. Figure 10: Network of co-occurrence of keywords. Evolution over the last few years. * Authors: Whether the publication has been written by authors considered relevant is also a selection criterion. Thanks to the performance analysis, it is possible to identify the most relevant authors, so their works will also be relevant. * Topic: Works have been selected that fall within the topics considered important in the keyword study. According to these criteria, the main contributions considered to the topic of air traffic complexity are [11; 45; 46; 47; 48]. The order of analysis of these publications is in chronological order from the earliest to the latest publication. Table 5 presents the citations, authors, and topics of each of the references. Table 5 presents the citations in order to see that the articles are indeed important, and the topic of each paper is presented in order to see in a preliminary way what the air traffic complexity studies focus on. The main contributions focus on the definition of complexity indicators and their prediction. This is the main concern in the sector. Only one of the papers aims to review indicators. In this section, an explanation of each of the papers will be given, identifying the subject of each publication and the advantages offered by each of the publications, but also the possible limitations that they may have. The first publication under consideration is [45]. Here, an analysis is made of the complexity maps of a sector in response to disturbances. [PERSON] defines a disturbance as an event that requires controller action to maintain aircraft management, and he defines the complexity map as a map detailing controller activity as a function of the parameters describing the disturbances. This publication analyses a two-dimensional sector, and details, in the form of complexity maps, the response of controllers to incoming aircraft. This analysis allows scalar indicators of complexity to be obtained, and the analysis can also be extrapolated to different disturbances, such as time. In conclusion, this paper addresses the complexity problem from the point of view of a system responding to disturbances. It is concluded that complexity can be defined in terms of how the system responds. This approach has the advantage of not having to consider the traffic characteristics to define complexity. But, it also has the limitation that only limited causes of disturbances have been studied, and that it has made a two-dimensional approximation when height is a fundamental parameter in air traffic management. Subsequently, Ref. [46] maps are made to identify cases of low or high complexity by modelling a dynamic system. To measure complexity, a model based on the Lapunov exponent is used to characterise complexity by identifying different scenarios according to the trajectory of the different aircraft.