scispace - formally typeset
H

Houshang Taghizadeh

Researcher at Islamic Azad University

Publications -  32
Citations -  193

Houshang Taghizadeh is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Corporate social responsibility & Fuzzy logic. The author has an hindex of 6, co-authored 32 publications receiving 161 citations. Previous affiliations of Houshang Taghizadeh include University of Cape Town & Islamic Azad University of Tabriz.

Papers
More filters
Journal ArticleDOI

The Effect of Customer Satisfaction on Word of Mouth Communication

TL;DR: In this paper, the authors investigated the effect of customer satisfaction on word of mouth communication and found that employee competence has a negative effect on word-of-mouth communication and physical evidence has a positive effect on the word ofmouth communication.
Journal ArticleDOI

The investigation of supply chain's reliability measure: a case study

TL;DR: Using supply chain operational reference, the reliability evaluation of available relationships in supply chain is investigated and the reliability of each system and ultimately the whole system is investigated.
Journal ArticleDOI

Selection of industrial robots using the Polygons area method

TL;DR: In this paper, the maximum polygons area obtained from the attributes of an alternative robot on the radar chart is introduced as a decision-making criterion for robot selection, and the results of this method are compared with other typical multiple attribute decision making methods (SAW, WPM, TOPSIS, and VIKOR) by giving two examples.
Journal Article

Project Duration Performance Measurement By Fuzzy Approach under Uncertainty

TL;DR: In this article, linguistic terms are used to describe progress of activities rather to evaluate it deterministically and a fuzzy approach is applied on EDM methodology, which derived development of new fuzzy indices which are capable of measuring project duration performance under uncertainty.

A multi-objective grey wolf optimization algorithm for aircraft landing problem

TL;DR: The proposed model improves the efficiency of flight scheduling, reduces time costs, minimizes delays and reduces fuel consumption, and a multi-objective optimization function is used and some expenses such as the cost of apron and parking are reduced.