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Wyświetlanie 1-2 z 2
Tytuł:
How transit improvements are perceived by passengers? Results of a before-after customer satisfaction survey
Autorzy:
Sahraei, Mina
Mesbah, Mohamed
Habibian, Meeghat
Saeidi, Tara
Soltanpour, Amirali
Powiązania:
https://bibliotekanauki.pl/articles/27311783.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
improvements of transports
passengers' satisfaction
structural equation modelling
importance-performance analysis
usprawnienia transportu
zadowolenie pasażerów
modelowanie równań strukturalnych
analiza ważności
Opis:
Although customer satisfaction surveys are widely utilized by transit agencies, there are limited analyses in the literature on the perception of passengers as a result of service improvements. A before-after study can help to evaluate the effect of changes from customer’s points of view and thus guarantee a continuous improvement in the service. In this paper, customer satisfaction was directly observed through a Customer Satisfaction Survey (CSS) before and after certain changes. Furthermore, Structural Equation Modeling (SEM) is utilized to evaluate passenger’s perception of the service attribute importance. Finally, an Importance-Performance Analysis (IPA) is adapted to analyze the changes in satisfaction and importance from the passenger’s perspective on each service attribute. In both before and after cases, a consistent SEM structure is used. The follow-up IPA provides transit agencies with priorities to improve service attributes and helps managers to devote their resources to key attributes that matter to the riders. Metro line 3 in Tehran was selected as the case study which is 33.7 km long with 25 stations. Two surveys were performed one before (with the sample size of 300), and one after (with the sample size of 384) a set of changes the most important of which was a headway reduction. The SEM was developed with five latent variables of main service, comfort, information, protection, and physical appearance. This structure was assessed on both the before and after data collections and showed to be valid. Security at the station and security on board were the most important service attributes in both waves according to their factor loadings, while ethics and behavioral messages had the smallest factor loading and the least importance. Comparing the attributes in both surveys suggested that reducing the headway was effective, although it did not seem to be sufficient for enhancing the overall customer satisfaction and improvements need to be continued.
Źródło:
Archives of Transport; 2023, 65, 1; 56--66
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modeling and Predicting the Changes in Hearing Loss of Workers with the Use of a Neural Network Data Mining Algorithm : A Field Study
Autorzy:
Zare, Sajad
Ghotbiravandi, Mohammad Reza
Elahishirvan, Hossein
Ahsaeed, Mostafa Ghazizadeh
Rostami, Mina
Esmaeili, Reza
Powiązania:
https://bibliotekanauki.pl/articles/176392.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
noise
modeling
NIHL
noise induced hearing loss
neural network algorithm
Opis:
The aim of the study study was to model, with the use of a neural network algorithm, the significance of a variety of factors influencing the development of hearing loss among industry workers. The workers were categorized into three groups, according to the A-weighted equivalent sound pressure level of noise exposure: Group 1 (LAeq < 70 dB), Group 2 (LAeq 70-80 dB), and Group 3 (LAeq > 85 dB). The results obtained for Group 1 indicate that the hearing thresholds at the frequencies of 8 kHz and 1 kHz had the maximum effect on the development of hearing loss. In Group 2, the factors with maximum weight were the hearing threshold at 4 kHz and the worker’s age. In Group 3, maximum weight was found for the factors of hearing threshold at a frequency of 4 kHz and duration of work experience. The article also reports the results of hearing loss modeling on combined data from the three groups. The study shows that neural data mining classification algorithms can be an effective tool for the identification of hearing hazards and greatly help in designing and conducting hearing conservation programs in the industry.
Źródło:
Archives of Acoustics; 2020, 45, 2; 303-311
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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