Exploring effective micro-level items for evaluating inclusive walking facilities on urban streets (applied in Johor Bahru, Malaysia)

• Main Authors: Asadi Shekari, Zohreh (Author), Moeinaddini, Mehdi (Author), Aghaabbasi, Mahdi (Author), Cools, Mario (Author), Shah, Muhammad Zaly (Author)
• Format: Article
• Language: English
• Published: Elsevier Ltd, 2019-08.
• Subjects: GV Recreation Leisure
• Online Access: Get fulltext

 Modern cities try to provide enough facilities for inclusive and pedestrian-friendly streets. Evaluating and designing models that consider a wide range of street users, including disabled people, can help urban planners to design these inclusive streets. The results of existing (but limited) studies evaluating street conditions for pedestrians do not include a wide range of street users. Therefore, this paper seeks to propose a new model for evaluating and improving urban streets, focusing on inclusive pedestrian facilities. This study introduces pedestrian mobility indicators using advanced design guidelines, existing literature and expert interviews. These indicators are evaluated by exploratory factor analysis (EFA) to find underlying patterns. Levels of association between observed and latent variables are tested by confirmatory factor analysis (CFA) and second-order confirmatory factor analysis (SOCFA). Structural equation modelling (SEM) is used to perform the CFA and SOCFA analyses. A questionnaire was used to collect data from 599 participants randomly selected from Setia Tropika residents (Johor, Malaysia). The resultant factor loading values are used as weights in an analytical points-based system, comparing existing facilities to a standard to estimate street facilities and infrastructure levels of service for pedestrians. This pedestrian level of service (PLOS) can be applied to various urban streets around the world, but in this study a street in Malaysia is evaluated using this method to check the accuracy of the proposed PLOS model. Existing street problems and potential improvements can be identified by this model.