# Key Factors in the Implementation of the Internet of Things in the Hotel Sector
## 3 Methodology  
The fuzzy cognitive maps methodology is one of the most relevant in the study of knowledge and is probably one of the most frequently used by researchers in their studies and projects in recent times [40]. The tool can be used in different situations or problems to identify, define, and validate the factors of a system and identify the cause effect relationships that exist between them in order to propose strategies and aid in decision-making [41]. In the scientific field, its applications include the following: descriptive (to describe a system using the factors intervening in that system), explanatory (to explain the \"why\" of the behavior of the factors intervening in a system), reflective (to make decisions as an instrument to support decision-making), and/or predictive (to predict the actions of the factors intervening in a system) [42]. For these reasons, in this study, we decided to use this methodology, a methodology that allowed us to confirm or rule out the influences of the factors obtained in the literary review regarding the decision of hotels to accept and implement the Internet of Things in their services. In addition, it allows us to identify whether or not there are influences between each of the factors that belong to this system and to determine the degrees of all these influences [43; 44]. To obtain data on the degrees of influence existing among factors, university professors who are experts in technology and hotels were selected as the \"population\" under study (people who get to know the most influential factors in the acceptance and decision by hotels to implement the Internet of Things in their services), and the size of the sample was set by the use of cumulative graphs showing the number of new influencing factors with respect to the number of individuals belonging to the sampled interest group. This method was suggested by [PERSON] and [PERSON] [45] for this type of study based on fuzzy cognitive maps, and studies with sample sizes of 45 [46], 41 [47], 29 [46], 8 [48; 49], 7 [50], and up to 4 experts [51] have previously been conducted. In this case, the sample consisted of 30 experts, none of whom added new influential factors, and it was decided to continue sampling until this number of interviewees was reached so that the results were the most significant possible without observing large differences between the values that the interviewees contributed for each relationship to be analyzed (which increased the significance of the results). To determine this number, the curve of the total number of factors contributed versus the number of interviews was examined, as well as the number of new variables added per interview. As can be seen in Figure 1, 30 experts was more than enough, as none of the participating experts added new factors. These experts in technologies and hotels were made up of two groups whose opinions had the same weights in the results: a group of 15 experts who were university professors from different countries with the title of doctor and had conducted research on the use of information and communications technologies in hotels and a group of 15 experts who were responsible for the technology department in international hotels and hotel chains of 4- and 5-star hotels. Interviews were the instrument used in this methodology to obtain data from the experts who formed the sample [45], and at the beginning of each of the interviews, as  
Figure 1: Sample size selection process. was done in a study by [PERSON] [50] using fuzzy cognitive maps as a study technique, each interviewee received a template with two tables, as follows:  
* A table showing the factors in this system, which served as an orientation guide for the interviewees (Table 1). It was intended that the interviewees would take this list of factors and give information on the causal connections that existed between factors in addition to contributing, if they felt it appropriate, new factors.