ارائه الگویی برای ارزیابی عملکرد کیفیت خدمات قطارهای مسافری از نگاه مسافران

صنعت حمل‌ونقل یکی از ارکان اصلی رشد هر جامعه است و صرفه جویی در مصرف انرژی و کاهش آلایندگی، امتیازاتی هستند که هر کشوری می‌تواند با توسعه این صنعت به دست آورد. صنعت حمل و نقل ریلی در صورتی می تواند از رشد و توسعه‌ خوبی برخوردار باشد که به کیفیت خدمات خود و رضایت مسافران بیشتر توجه داشته باشد. با وجود اهمیت ارزیابی عملکرد در رشد و توسعه این سازمان ها مطالعات در این زمینه در داخل کشور محدود است. بنابراین، در این مطالعه رویکردی برای ارزیابی کمی خدمات کیفی قطارهای مسافری در یک مسیر پر تردد از نگاه مسافران و مبتنی بر تحلیل پوششی داده ها، پیشنهادشده است. برای این منظور ابتدا شاخص های ارزیابی قطارها با مطالعه ادبیات موضوع استخراج و سپس مهم‌ ترین آن‌ها بر اساس نظرات خبرگان و متخصصان حوزه‌ حمل و نقل ریلی شناسایی شد. فرآیند تحلیل سلسله مراتبی برای تعیین وزن زیرمعیارهای شناسایی‌ و استفاده شد و سطح مطلوبیت و رضایت مندی هر یک از شاخص‌ ها برای 16 نوع قطار مسافری به دست آمد. سپس برای تعیین کارایی قطارهای مسافری بر اساس کیفیت خدمات آن‌ها، الگوهای خروجی محور در شرایط بازدهی نسبت به مقیاس ثابت و بازدهی نسبت به مقیاس متغیر مورداستفاده قرار گرفت. کارایی قطارها بر اساس این دو الگو محاسبه شد و با استفاده از روش اندرسون پیترسن رتبه‌بندی شدند. نتایج نشان داد از نگاه مسافران قطارهای صبا (عادی)، صبا (تندرو)، نور، زندگی، پرستو، فدک، پردیس، خلیج‌فارس بیشترین کارایی را دارند و صنعت حمل‌ونقل ریلی می تواند به‌منظور افزایش سودآوری، از نتایج به‌دست‌آمده این مطالعه برای تعیین بهترین ترکیب استفاده از قطارها بهره‌برداری کند.

proposal of a model for evaluating the quality performance of passenger train services from the perspective of passengers

aim and introduction transportation is considered one of the fundamental elements for the growth and development of any society. in this context, rail transport has allocated itself a special and effective role. the importance of rail transport in societal development is crucial, highlighting the significance of passenger satisfaction for the success of the industry. providing services to passengers that enhance customer satisfaction and ultimately increase train usage is a critical factor in this industry. the shortcomings of the rail passenger sector are highlighted through an evaluation of its performance within a scientific framework, and appropriate solutions are proposed for the management team. to maximize the profitability of the national transportation industry, it is advisable to optimize the optimal use of trains throughout the day, considering budget constraints and capacity limitations. this approach should prioritize the efficiency of train use from the passengers' perspective. for this study, we conducted research on one of the busiest rail routes in iran, treating each passenger train as a decision-making unit within a data envelopment analysis model. the inputs consist of the ticket prices for each train, while the outputs include the facilities and services provided to passengers. these are identified through criteria and sub-criteria, with their values determined by the importance coefficient from the perspective of passengers and their satisfaction. the significance and weighting of sub-criteria are determined through expert opinions and a hierarchical analysis process. to evaluate the efficiency of passenger trains, output-oriented measures are employed, focusing on both scale efficiency and variable scale efficiency. ultimately, a comprehensive ranking of trains is provided based on the anderson-peterson method.case study the case study presented in the article focuses on all rail transport companies operating on the mashhad to tehran route, with the statistical population comprising the passengers utilizing these services. according to the schedule of passenger trains provided by the railways administration of khorasan, there are a total of 16 different types of trains on this route.methodology in this study, the data envelopment analysis (dea) method has been utilized as a powerful tool for evaluating and calculating the relative and overall efficiency of passenger trains. after collecting data on all trains, the values for each criterion pertaining to every passenger train were obtained. mathematical modeling was conducted using two assumptions: constant returns to scale and variable returns to scale, employing an output-oriented approach. following the calculation of the efficiency of decision-making units, both effective and inefficient units were identified. subsequently, based on the results obtained, the current situation and the desired weights of inputs and outputs were established. finally, the ranking of efficient units was conducted using the petersen-anderson method.findingbased on the findings from the study in the transportation industry, the analysis utilizing the analytic hierarchy process (ahp) revealed significant criteria and sub-criteria that influence passenger satisfaction. results indicated that specific trains, including noor, saba (high-speed), saba (regular), zendegi, and parastoo, demonstrated efficiency based on the constant returns to scale approach. additionally, the variable returns to scale approach identified several efficient trains, including noor, pardis, fadak, and khalij-e fars. inefficient trains were also identified based on surplus inputs and deficiencies in output. the evaluation highlighted several deficiencies across various criteria, with specific trains notably lacking in areas such as environmental factors, services, and equipment. the petersen-anderson method was employed to rank the results, identifying saba (regular) and saba (high-speed) trains as the top-ranked options based on the two approaches.discussion and conclusionthe primary objective of this study is to quantitatively assess the quality of passenger train services from the perspective of travelers on one of the busiest routes in iran. for this purpose, the data envelopment analysis (dea) method was employed in both constant and variable returns to scale to evaluate the efficiency of trains. additionally, for each of the inefficient trains, efficient trains were introduced as reference points. the results indicate that trains identified as efficient in the constant returns to scale model are also regarded as efficient in the variable returns to scale model. the average efficiency in the variable returns to scale model is 96.0, while in the constant returns to scale model, it is 94.0. utilizing these results, improvement strategies for inefficient units can be developed based on established reference patterns. it is essential to note that this evaluation is relative; if there are changes in the set of units under investigation, the results will also be subject to change.