Purpose The purpose of this research paper is to adapt and validate a useful instrument to diagnose the knowledge, attitudes, behaviours and intention to participate (KABIP) towards Sustainable Development Goals (SDGs) in higher education institutions (HEIs) from the public administration in developing countries. Design/methodology/approach The study was carried out using the Delphi technique, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). For the Delphi method, 30 experts participated in three rounds. For the EFA and CFA, a sample of 790 people was selected. The instrument items were extracted from relevant scales on the topic. Findings The reliability and internal consistency of the instrument were tested and confirmed. Therefore, this study gives a scientific tool to measure the KABIP towards SDGs in different sectors of the public administration, and it can be used in developing countries. Originality/value The new questionnaire with 66 items and four dimensions can be used to diagnose KABIP towards SDGs at HEIs in developing countries. It has a very important implications because, although attention for SDGs around the world is increasing, only a limited number of valid scientific instrument that measure aspects related to it is available. Furthermore, the knowledge, attitudes, behaviour and intention to participate scale can facilitate the creation of new strategies regarding SDGs in developing countries.

Environmentally friendly behaviour and the equitable and sustainable use of natural resources can contribute to solving various environmental, economic, and social problems in different countries. The analysis of the perception of young students is important because schools are suitable for educating future generations and shaping their attitudes to also include a greater concern for the environment. This research aims to determine the degree of influence that a series of Likert-type questions of knowledge, attitudes, and behaviours about sustainable development has on a series of items of the student profile (gender, age, course, and household members) in a developing country. For this, an artificial neural network is used that allows us not only to quantify the degree of influence but also to obtain an estimation of the student’s profile according to the responses obtained on sustainable development. The network developed allows us to obtain, through a determined collection of answers to questions about sustainable development, the estimation of a specific profile of a student from a developing country. This can be useful to educational communities interested in optimising economic resources through sustainable development, allowing them to know which issues they should focus more (or less) on according to the profile of the student they are targeting.