Identifying the Importance of Criteria for Passenger Choice of Sustainable Travel by Train Using ARTIW and IHAMCI Methods

Nowadays, travelers can use different modes of transport, and they usually choose the most suitable and reliable mode available. The choice of one mode of transport as an alternative to another is subjective. It is usually built upon passenger attitude toward the advantages and disadvantages of using a particular mode. This article proposes analytical methods for and research results on passenger choices for sustainable train journeys as an alternative to traveling by bus. The rank averages of all criteria and their normalized subjective weights were calculated with reference to new linear (ARTIW-L) and nonlinear (ARTIW-N) methods of average rank transformation into weight. A correlation between sub-criteria rank averages and normalized weights is presented, based on the minimum number of passengers required to be interviewed to provide reliable results. The average ranks assigned by passengers to the evaluation sub-criteria and their global weights were used for determining and describing the most and least important key criteria by applying the inverse hierarchy for assessment of main criteria importance (IHAMCI) method. The analysis shows that the most important key criterion belonged to the sub-criteria characterizing economy, while the less important key criteria included ride comfort. The least important key criteria described safety and environmental protection, whose normalized subjective overall weights were the lowest. Rail transport authorities and companies involved in transporting passengers can make this mode of transport more attractive to people by giving priority to improving the services they provide to passengers.

CAPABILITIES OF REVEALED PREFERENCE METHOD FOR HERITAGE PROPERTY VALUATION

In recent years, the increasing availability of large databases on real estate transaction has opened up new research possibilities using revealed preference method. Therefore, the aim of this paper is to investigate the capability of revealed preference method of ordinary least square and rank transformation regression models in valuing shophouse heritage property. This paper has provided the first application that consider the thin market effects by comparing the ordinary least square and rank transformation regression in obtaining the market value of shophouse heritage property. The original dataset consists of 893 commercial properties transacted from 2004 to 2014 in Kota Bharu, Kelantan Malaysia. After filtration process, only 25 units of shophouse heritage property were available and valid to be used. The findings suggest that rank transformation regression model performs better than the ordinary least square model with double-log as the best model. This suggests that rank transformation regression is capable for heritage property valuation in thin market situation.

A Business Failure Index Using Rank Transformation

The global financial crisis entails a renewed attention from financial institutions, academics, and practitioners to corporate distress analysis and its forecasting. This study aims to propose a model for predicting default risk based on a business failure index using rank transformation. The procedure suggested is able to capture firms’ financial difficulties and forecast bankruptcy through the construction of a failure index based on some relevant financial ratios. By means of the estimation of failure probability, it allows to classify and predict business distress in time to take mitigating action. This procedure is evaluated by some accuracy measures on a sample of Italian manufacturing firms, and is found to be a suitable instrument for preventing financial distress.

Testing the Use of Multiple Regression Analysis and Rank Transformation Regression for Heritage Property Valuation

The aim of this paper was to test the applicability of multiple regression analysis and rank transformation regression in assessing the values of private heritage property. The original dataset consists of 893 commercial properties transacted from 2004 to 2014 in Kelantan Malaysia. After filtration process, only 25 units of shophouse heritage property were available and valid to be used. The models have been constructed and their statistical performances have been compared. The results indicate that adopting statistical methods of valuation per se to overcome the issue of unavailability of market evidence could not solve the consequences of the limited data problem. Keywords: real estate; heritage property; multiple regression analysis; rank transformation regression eISSN 2398-4279 © 2019. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.

استخدام بعض الطرائق المعلمية واللامعلمية لتحليل التجارب العاملية مع تطبيق عملي

المستخلص تطرقنا في هذا البحث على التجارب العاملية واختبار معنوية التأثيرات الرئيسية، التفاعل للعوامل والتأثيرات البسيطة لها عن طريق اختبار F المعلمي (جدول تحليل التباين ANOVA) لتحليل بيانات التجربة العاملية وكما هو معروف ان تحليل التباين يتطلب عدة فروض (شروط) لتحقيقها لذا في حالة خرق في احد هذه الشروط نقوم بإجراء تحويل على البيانات لكي تطابق او تحقق شروط تحليل التباين الا انه لوحظ ان تلك التحويلات لا تعطي نتائج دقيقة لذا نلجأ الى استخدام الاختبارات او الطرائق اللامعلمية التي تعمل كحل او بديل عن الاختبارات (الطرائق) المعلمية وهي طريقة تحويل الرتبة RT)) Rank Transformation وطريقة تحويل الرتبة المتراصفة ART)) Aligned Rank Transformation وتطبيقها على بيانات تجربة حقيقية تم الحصول عليها من كلية الطب البيطري جامعة بغداد و بعد اختبار البيانات وجدنا انها لا تتوزع توزيع طبيعي وانها تعاني من مشكلة عدم تجانس التباينات , تم التوصل الى ان تطبيق تحليل التباين على تلك البيانات لم يعطي المعنوية لجميع تأثيرات العوامل كذلك بالنسبة للتحويلات اما عند تطبيق الطرائق اللامعلمية فكانت تعطي نتائج معنوية عالية لتأثيرات العوامل المدروسة .

Assessment of Heritage Property Values Using Multiple Regression Analysis and Rank Transformation Regression

The current practice of heritage property valuation is using sale comparison approach. However, there is a limitation in applying this approach for heritage property valuation because of unavailability of market evidence. Therefore, the aim of this paper was to evaluate the capability of Multiple Regression Analysis and Rank Transformation Regression in assessing the values of heritage property. The original dataset consists of 893 commercial properties transacted from 2004 to 2014 in Kota Bharu, Kelantan Malaysia. After filtration process, only 25 units of shophouse heritage property were available and valid to be used. The findings indicate that even we adopted statistical methods of analysis to overcome the issue of unavailability of market evidence this still could not solve the problem. Hence, the findings of this research contribute to the need for an improved method for heritage property valuation by proposing an extended sale comparison using statistical analysis for future investigation.