Clima2025 paper
MULTIFILE
this thesis was simply a research done to see how the manor amsterdam can use technologies to enhance its guest eperience. Surveys and intervews were conducted to see what the guest preferences were after which an implementation process was also drawn up.
MULTIFILE
Cleanliness is one of the key determinants of overall customer satisfaction in train stations. Customers’ perception of cleanliness is not limited to cleaning only but depends on multiple predictors. A better understanding of these predictors may contribute to the optimisation of perceived cleanliness in train stations. The current study was designed to examine how objective predictors (measures of cleaning quality), subjective predictors (e.g., customers’ perception of lighting, scent, staff), and demographic variables relate to perceived cleanliness in train stations. Data on cleaning quality were gathered by trained cleaning inspectors and data on subjective predictors of cleanliness were obtained through surveys collected at 25 train stations in the Netherlands (N = 19.206). Data were examined using correlation and regression analysis. Positive and significant correlates of perceived cleanliness in train stations were found, including: perception of scent, lighting, colour, and staff. In regression analysis, customers’ perception of scent and lighting appeared to be powerful predictors of perceived cleanliness. These findings underline that customers’ perception of cleanliness is not only influenced by cleaning quality, but also by other predictors, such as scent, lighting, colour, and staff behaviour.
