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The main purpose of this chapter is to define the concept, scope and importance of a feasibility study when developing a new business venture. It also presents the main components of a feasibility study by describing a feasibility study template.

A literature review was conducted on conceptual issues and practical aspects of the feasibility analysis and study by presenting a hypothetical case of study of a boutique hotel.

This chapter highlights the importance of both feasibility analysis and study, and the main reasons why all entrepreneurs should carry them out. It presents a simple template that shows the key components of a feasibility study and also a hypothetical case of study of a boutique hotel that helps in relating the concepts and ideas previously developed.

This chapter introduces both theoretical and practical approaches by presenting a model or template on how to develop the feasibility analysis and study. This template can be applied at any stage of assessment process of a business project.

The concept of a feasibility study is accompanied by a practical template and a case study. This approach contributes to a better understanding of the value and utility of feasibility analysis and study in assessing tourism business ventures.

This article aims to propose an adaptation algorithm that combines the analytical hierarchy process (AHP), a rule-based system, and a k-means clustering algorithm. Informatic tools are very useful to enhance the learning process in the classroom. The large variety of these tools require advanced decision-making techniques to select parameters, such as student profiles and preferences, to adjust content and information display, according to specific characteristics and necessities of students. They are part of the Kamachiy–Idukay (KI), a platform to offer adaptative educational services to students with learning difficulties or disabilities.

The design and implementation of the adaptation algorithm comprises the following phases: utilization of the AHP to determine the most important student parameters, parameter to take into account in the adaptation process, such as preferences, learning styles, performance in language, attention and memory aspects and disabilities; designing the first part of the adaptation algorithm, based on a rule-based system; designing the second part of the adaptation algorithm, based on k-means clustering; integration of the adaptation algorithm to KI; and validation of the approach in a primary school in Bogotá (Colombia).

The main approach is the application of computational techniques, namely, rule-based systems and k-means clustering, plus an AHP prioritization at design time to yield a system to support the teaching–learning process for students with disabilities or learning difficulties.

The algorithm found several groups of students with specific learning difficulties that required adapted activities. The algorithm also prioritized activities according to learning style and preferences. The results of the application of this system in a real classroom yielded positive results.

The algorithm performs adaptation for students with mild disabilities or learning difficulties (language, attention and memory). The algorithm does not address severe disabilities that could greatly affect cognitive abilities.

The main contribution of this paper is an adaptation algorithm with the following distinctive characteristics, namely, designed utilizing the AHP, which ensures a proper prioritization of the student characteristics in the adaptation process, and utilizes a rule-based system to identify different adaptation scenarios and k-means clustering to group students with similar adaptation requirements.