The importance of service quality attributes in public transportation: Narrowing the gap between scientific research and practitioners' needs

• Customer Satisfaction Surveys (CSS) have become an important tool for public transport planners.
• The literature shows that the importance of quality attributes has until now been estimated indirectly, derived from the CSI.
• The main aim of this paper is to develop a new technique to directly estimate the stated importance of quality attributes.
• The new survey technique was validated using a conventional survey with the same sample in a bus corridor in Madrid (Spain).
• Results show that the stated importance of quality attributes can be estimated directly, reducing the length of the questionnaire.

Customer Satisfaction Surveys (CSS) have become an important tool for public transport planners, as improvements in the perceived quality of certain service attributes can lead to greater use of public transport and lower traffic pollution. The literature shows that the importance of quality attributes has until now been estimated indirectly, as they are derived from the Customer Satisfaction Index using various different and complex techniques. Little work has been dedicated to its direct estimation (stated importance) by designing ad-hoc surveys, an approach that represents a considerable reduction in the length of the questionnaire.This paper contributes to the limited existing literature by developing a survey technique based on hierarchy processes to estimate the stated importance of quality attributes, and compares the results with the derived importance obtained using conventional surveys with the same sample. The added value of this research is that it provides the first comparison between two quality survey methods using the same real case study in Madrid (Spain). The results achieved using this pioneer survey method (293 valid questionnaires) were validated using conventional face-to-face surveys (520 valid questionnaires). Factorial analysis, multiple regression analysis and Multiple Indicators Multiple Causes (MIMIC) models were applied to the conventional survey sample to analyse and derive the importance of the attributes. The results clearly show that, after a few teething troubles, the stated importance of quality attributes can be estimated directly, thus providing transport management companies with a simple and useful tool to implement in their Customer Satisfaction Surveys (CSS), and narrowing the gap between practitioners’ needs and scientific research.