مقاله انگلیسی رایگان در مورد تنوع کیفیت خدمات حمل و نقل در ایستگاه راه آهن – الزویر ۲۰۱۸

مقاله انگلیسی رایگان در مورد تنوع کیفیت خدمات حمل و نقل در ایستگاه راه آهن – الزویر ۲۰۱۸

 

مشخصات مقاله
ترجمه عنوان مقاله تنوع فضایی کیفیت خدمات حمل و نقل در ایستگاه های راه آهن
عنوان انگلیسی مقاله Spatial variation of the perceived transit service quality at rail stations
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۱۷ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه الزویر
نوع نگارش مقاله مقاله پژوهشی (Research article)
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مهندسی عمران، مهندسی راه آهن
گرایش های مرتبط برنامه ریزی حمل و نقل، مهندسی خط و سازه های ریلی – مهندسی حمل و نقل ریلی
مجله تحقیقات حمل و نقل – Transportation Research Part A
دانشگاه University of Calabria – Department of Civil Engineering – Italy
کلمات کلیدی کیفیت خدمات حمل و نقل، ایستگاه های راه آهن، درک مسافران، تنوع فضایی
کلمات کلیدی انگلیسی Transit service quality, Rail stations, Passengers’ perception, Spatial variation
شناسه دیجیتال – doi
https://doi.org/10.1016/j.tra.2018.01.032
کد محصول E8980
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بخشی از متن مقاله:
۱٫ Introduction

The assessment of transit service quality is a matter of academic interest since over thirty years already, and several research studies highly covered the scientific literature since the beginning of the new millennium. The growing interest for this topic also from transit enterprises and authorities is due to the awareness that the knowledge of the transit service performances can be used for monitoring the services and for identifying potential weak points, with the aim to increase passenger’s satisfaction and finally attract new transit users and retaining the usual ones. In fact, it is well known that in recent years users’ travel behaviour has become more complex, and people prefer private car for moving, because it is perceived as the most comfortable, flexible, and fast mode compared with the other ones. The urban sprawl and low density areas rising also contributed to increase the attractiveness of car as the most convenient transportation mode from all the points-of-view, with undesirable consequences in terms of environmental pollution, energy consumption and quality of life (Nocera and Cavallaro, 2016; Ayyildiz et al., 2017). In order to reduce these problems, travel demand has to be moved from private car to more sustainable mode as public transit systems. Consequently, transport companies have to operate interventions aimed to reduce travel time and increase service quality over all the aspects, since improvements in service quality can have a significant positive impact on the willingness of potential users to choose public over private transport (de Oña et al., 2014; Eboli et al., 2016). Transit service quality can be measured by different approaches. The most common approach is based on transit users’ opinions about the used services, collected by means of surveys. When service quality is measured from the customer’s perspective, transit quality depends on the passengers’ perceptions about each attribute characterising the service (de Oña et al., 2013). In recent years, the most popular methods for capturing transit users’ perceptions were: (1) traditional Customer Satisfaction Surveys (CSS), where users express their opinions by rating the various service characteristics (Weinstein, 2000; Cavana et al., 2007; Joewono and Kubota, 2007; Pakdil and Aydın, 2007; Dell’Olio et al., 2011; Eboli and Mazzulla, 2010, 2012b; Jen et al., 2011; Habib et al., 2011); and (2) Stated Preference surveys, where the importance given by the users to the service attributes indirectly derives from exercises based on the stated preferences according to which users express their opinions by choosing (or rating of ranking) alternative hypothetical services (Cirillo et al., 2011; Eboli and Mazzulla, 2008a, 2008b, 2010; Hensher and Prioni, 2002; Hensher et al., 2003; Dell’Olio et al., 2011). An alternative approach entails using different variables of the transit system demand and operation to calculate the ‘efficiency’ indicators (e.g. Badami and Haider, 2007; Lao and Liu, 2009; Eboli and Mazzulla, 2012a). There are also some studies integrating the two mentioned approaches (e.g. Sheth et al., 2007; Abreha, 2007; Nathanail, 2008; Eboli and Mazzulla, 2011).

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