Increasing public transport use is recognized by many countries as crucial to the pursuit of a global strategy for environmental sustainability and improving urban mobility. Understanding what users value in a public transport service is essential to carry out this strategy. Using fuzzy clustering, we developed an index that measures individual user satisfaction with the public transport service in the metropolitan area of Lisbon and subsequently identified the possible determinants of satisfaction by means of a regression tree model. The results achieved unveil a hierarchical partition of the data, highlighting the diversified level of satisfaction among public transport users that is reflected in the distribution of the index. The managerial implications of the findings for the public transport service are addressed.

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Fuzzy clustering,Public transport,Regression trees,Service quality attributes

• Ciências Químicas - Ciências Naturais
• Ciências da Terra e do Ambiente - Ciências Naturais
• Outras Ciências Naturais - Ciências Naturais
• Engenharia do Ambiente - Engenharia e Tecnologia
• Geografia Económica e Social - Ciências Sociais