# Personalizing Environmental Awareness through Smartphones Using AHP and PROMETHE II
## 6 Conclusions  
In this paper, the main purpose was to increase environmental awareness of smartphone users in a personalized way by combining AHP and PROMETHEE II. The mobile application contains a user model with different information, such as place of residence (e.g., city, mountain, sea, etc.), age, and user habits, such as waste management activities, natural resource conservation activities, general environmental protection activities, and biodiversity activities. After the initialization of the user model, the system uses AHP and PROMETHEE II to provide the user with recommendations to increase environmental awareness. The criteria, considered when evaluating environmental recommendations, include the compatibility of the user's current location, living environment, habits, interests, needs, age, and season.  
AHP is one of the multi-criteria decision-making methods, which is powerful yet simple. AHP breaks complex decision-making problems into multiple hierarchical levels.  
The weights of each criterion and alternatives are evaluated in a pairwise comparison, and then priority is calculated.  
PROMETHEE II is one of the most extensively studied and commonly used outranking methods, developed to solve problems of multiple criteria. The main reason for utilizing the PROMETHEE II method is that the particular model can be effectively implemented in the domain presented and all information gathered in the decision matrix can be completely and effectively calculated in making final decisions. Moreover, compared to other MCDM methods, PROMETHEE II is a fairly simple ranking method in concept and practice.  
The combination of the aforementioned methods and theories makes decision-making more qualitative and thus it offers a more personalized experience to users, since they receive advice which is tailored to their needs and preferences in awakening their environmental awareness.  
The evaluation results are very promising, showing a high degree of usability and acceptance of the developed application, which is due to the user-friendly interface, as well as the useful and suitable to user model advice. Moreover, the findings reveal that the proposed approach has significant impact on users' consciousness regarding environmental issues, leading to the improvement of environmental awareness regarding the conscious consuming, the reduction of waste and recycling, and energy saving.  
Part of our future work is to extend the evaluation sample, including people from different ages, education levels, economic class, and geographic area, and enrich the evaluation procedure using the assessment of the user acceptance of the presented mobile application. Furthermore, it is in our plans to design a model with ensemble learning methods for decision making and the comparison of different MCDM approaches, being tailored to environmental awareness, to check their superiority.  
Conceptualization, A.K., K.K. and C.T.; methodology, A.K., K.K. and C.T.; software, A.K., K.K. and C.T.; validation, A.K., K.K. and C.T.; formal analysis, A.K., K.K. and C.T.; investigation, A.K., K.K. and C.T.; resources, A.K., K.K. and C.T.; data curation, A.K., K.K. and C.T.; writing--original draft preparation, A.K., K.K. and C.T.; writing--review and editing, A.K. and C.T.; visualization, A.K., K.K. and C.T.; supervision, K.K. and C.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The data, used to support the findings of this study, have not been made available because they contain information that could compromise research participant privacy/consent.  
The authors declare no conflict of interest.