An Ahp-Ism Approach for Considering Public Preferences in a Public Transport Development Decision

Abstract

Recently, there has been a transparent need to involve public in transport development decisions not only in the EU but also in other countries worldwide. Public involvement in decision-making, however, suffers from two critical issues: lack of expertise and lack of enthusiasm. This paper aims to overcome the first problem: how to amend passenger preferences related to public transport development with expert knowledge on transport systems. For this purpose, a new research methodology has been created which combines the well proven Analytic Hierarchy Process (AHP) and Interpretive Structural Modelling (ISM) methods in a novel way. ISM is used to reveal the non-hierarchical connections of the transport system elements and by this, AHP results are modified with the consideration of element interactions. The first stage of the three-stage-survey has been conducted in Yurihonjo (Japan), the second and third in an international workshop with the participation of experts. Results show that the original AHP scores – gained from passenger evaluations – are significantly modified by adding expert knowledge on factor interactions, thus new preference order is gained related to the importance of the development of public transport system elements. The introduced procedure can be applied for other public transport system improvement decision-making situations in which passenger involvement is required.

An Alternate Unsupervised Technique Based on Distance Correlation and Shannon Entropy to Estimate λ0-Fuzzy Measure

“…As a result, a more realistic ranking of the websites can be expected, and the hospitals can make the decisions for improvement with a greater perspective. Additionally, future work can include the consideration of using different types of non-linear operators or MADM techniques such as Bonferroni mean, weighted Pythagorean fuzzy interaction power Bonferroni mean, Zhenyuan integral, interval AHP [84], AHP-ISM [85], Pythagorean fuzzy AHP [86], and spherical fuzzy TOPSIS method [87] to evaluate the websites and compare the results to obtain a definitive ranking. Step 4-Since the distance variance of c 1 , dVar(c 1 ) = dCov(c 1 , c 1 ), and distance variance of c 2 , dVar(c 2 ) = dCov(c 2 , c 2 ), then these two values can be calculated by repeating step 1-3 accordingly.…”

Analysing Stakeholder Consensus for a Sustainable Transport Development Decision by the Fuzzy AHP and Interval AHP

“…The AHP method is based on an additive weighting process, in which several relevant criteria are represented through their relative importance. The AHP approach was extensively applied by academics and professionals in many areas and problems, mainly in engineering fields like transport engineering [2,3,13,[39][40][41][42], in construction engineering and accuracy assessment [43,44], in architecture [45,46] and in many different engineering fields [18,[47][48][49][50].…”

Introduction and comparative analysis of the multi-level parsimonious AHP methodology in a public transport development decision problem

“…The proposed multi-level Parsimonious AHP model has been tested on a real decision making problem: the possible improvement of a public bus transport system in an emerging city: Mersin, Turkey. From methodological point of view the chosen case study seemed fortunate, since previous experience of this problem has been available, published in Duleba andMoslem (2018, 2019). The applied decision structure of criteria has become the same as used in other different AHP surveys (Duleba, 2019;Duleba et al, 2012Duleba et al, , 2013 as exhibited in Figure 1.…”