scholarly journals Bringing Kano’s Perspective to AHP: The 2D-AHP Decision Model

2016 ◽  
Vol 7 (4) ◽  
pp. 16-26
Author(s):  
Uk Jung ◽  
Seongmin Yim ◽  
Sunguk Lim ◽  
Chongman Kim
Keyword(s):  
Hybrid Model ◽  
Decision Model ◽  
Hybrid Approach ◽  
Survey Study ◽  
Test Case ◽  
Problem Structure ◽  
Kano Model ◽  
Two Dimension ◽  
True Hybrid ◽  
Decision Making Model

AbstractAHP and the Kano model are such prevalent TQM tools that it may be surprising that a true hybrid decision-making model has so far eluded researchers. The quest for a hybrid approach is complicated by the differing output perspective of each model, namely discrete ranking (AHP) versus a multi-dimensional picture (Kano). This paper presents a hybrid model of AHP and Kano model, so called two-dimension AHP (2D-AHP).This paper first compares the two approaches and justifies a hybrid model based on a simple conceit drawn from the Kano perspective: given a decision hierarchy, child and parent elements can exhibit multi-dimension relationships under different circumstances. Based on this premise, the authors construct a hybrid two-dimension AHP model whereby a functional-dysfunctional question-pair technique is incorporated into a traditional AHP framework.Using the proposed hybrid model, this paper provides a practical test case of its implementation. The 2D-AHP approach revealed important evaluation variances obscured through AHP, while a survey study confirmed that the 2D-AHP approach is both feasible and preferred in some respects by respondents.Although there have been rich research efforts to combine AHP and Kano model, most of them is simply about a series of individual usage of each methodology. On the other hand, the type of hybridization between AHP and Kano model in this paper is quite unique in terms of the two dimensional perspective. The model provides a general approach with application possibilities far beyond the scope of the test case and its problem structure, and so calls for application and validation in new cases.

Applying the Multi-Criteria Decision Making Model for Ranking Commercial Banks: The Case of Vietnam

2019 ◽  
pp. 125-133
Author(s):  
Duong Truong Thi Thuy ◽  
Anh Pham Thi Hoang
Keyword(s):  
Decision Making ◽  
Commercial Banks ◽  
Decision Model ◽  
Business Models ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Decision Making Model

Banking has always played an important role in the economy because of its effects on individuals as well as on the economy. In the process of renovation and modernization of the country, the system of commercial banks has changed dramatically. Business models and services have become more diversified. Therefore, the performance of commercial banks is always attracting the attention of managers, supervisors, banks and customers. Bank ranking can be viewed as a multi-criteria decision model. This article uses the technique for order of preference by similarity to ideal solution (TOPSIS) method to rank some commercial banks in Vietnam.

Hybrid approach combining EMD, ARIMA and monte carlo for multi-step ahead medical tourism forecasting

2021 ◽  
pp. 1-17
Author(s):  
Nuzhat Fatema ◽  
H Malik ◽  
Mutia Sobihah Binti Abd Halim
Keyword(s):  
Monte Carlo ◽  
Hybrid Model ◽  
Medical Tourism ◽  
Moving Average ◽  
Hybrid Approach ◽  
Mode Decomposition ◽  
Hybrid Forecasting ◽  
Input Variables ◽  
Intelligent Approach

This paper proposed a hybrid intelligent approach based on empirical mode decomposition (EMD), autoregressive integrated moving average (ARIMA) and Monte Carlo simulation (MCS) methods for multi-step ahead medical tourism (MT) forecasting using explanatory input variables based on two decade real-time recorded database. In the proposed hybrid model, these variables are 1st extracted then medical tourism is forecasted to perform the long term as well as the short term goal and planning in the nation. The multi-step ahead medical tourism is forecasted recursively, by utilizing the 1st forecasted value as the input variable to generate the next forecasting value and this procedure is continued till third step ahead forecasted value. The proposed approach firstly tested and validated by using international tourism arrival (ITA) dataset then proposed approach is implemented for forecasting of medical tourism arrival in nation. In order to validate the performance and accuracy of the proposed hybrid model, a comparative analysis is performed by using Monte Carlo method and the results are compared. Obtained results shows that the proposed hybrid forecasting approach for medical tourism has outperformance characteristics.

Aesthetical design of a car profile: a Kano model-based hybrid approach

2012 ◽  
Vol 67 (9-12) ◽  
pp. 2137-2155 ◽  
Author(s):  
H. C. Yadav ◽  
Rajeev Jain ◽  
A. R. Singh ◽  
P. K. Mishra
Keyword(s):  
Hybrid Approach ◽  
Kano Model ◽  
Model Based

scholarly journals Evaluation of a Scale-Resolving Methodology for the Multidimensional Simulation of GDI Sprays

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2699 ◽  
Author(s):  
Giovanni Di Ilio ◽  
Vesselin K. Krastev ◽  
Giacomo Falcucci
Keyword(s):  
Turbulence Modeling ◽  
Direct Injection ◽  
Test Procedure ◽  
Hybrid Approach ◽  
Development Trend ◽  
Standard Test ◽  
Gasoline Direct Injection ◽  
Model Parameters ◽  
Test Case ◽  
Passenger Cars

The introduction of new emissions tests in real driving conditions (Real Driving Emissions—RDE) as well as of improved harmonized laboratory tests (World Harmonised Light Vehicle Test Procedure—WLTP) is going to dramatically cut down NOx and particulate matter emissions for new car models that are intended to be fully Euro 6d compliant from 2020 onwards. Due to the technical challenges related to exhaust gases’ aftertreatment in small-size diesel engines, the current powertrain development trend for light passenger cars is shifted towards the application of different degrees of electrification to highly optimized gasoline direct injection (GDI) engines. As such, the importance of reliable multidimensional computational tools for GDI engine optimization is rapidly increasing. In the present paper, we assess a hybrid scale-resolving turbulence modeling technique for GDI fuel spray simulation, based on the Engine Combustion Network “Spray G” standard test case. Aspects such as the comparison with Reynolds-averaged methods and the sensitivity to the spray model parameters are discussed, and strengths and uncertainties of the analyzed hybrid approach are pointed out. The outcomes of this study serve as a basis for the evaluation of scale-resolving turbulence modeling options for the development of next-generation directly injected thermal engines.

scholarly journals Framing a Consent Form to Improve Consent Understanding and Determine How This Affects Willingness to Participate in HIV Cure Research: An Experimental Survey Study

2020 ◽  
pp. 155626462098120
Author(s):  
John A. Sauceda ◽  
Karine Dubé ◽  
Brandon Brown ◽  
Ashley E. Pérez ◽  
Catherine E. Rivas ◽  
...  
Keyword(s):  
Decision Making ◽  
Consent Form ◽  
Survey Study ◽  
Willingness To Participate ◽  
Hiv Cure ◽  
Complex Information ◽  
Complex Information Processing ◽  
Decision Making Model ◽  
Hiv Cure Research ◽  
Experimental Survey

HIV cure research carries serious risks and negligible benefits. We investigated how participants understand these risks and what influences their willingness to participate. Through internet-based and in-person convenience sampling, 86 HIV+ participants completed an experimental survey. Participants were randomized to read a standard consent form describing a hypothetical HIV cure study or one adapted using Fuzzy Trace Theory—a decision-making model to facilitate complex information processing. We measured consent understanding and cognitive (e.g., safe/harmful) and affective (e.g., concerning, satisfying) evaluations of HIV cure research. Participants who read the adapted consent form had improved consent understanding, but only positive affective evaluations were associated with a willingness to participate. Consent processes can use decision-making theories to facilitate comprehension of study information.

A HYBRID, QUANTUM-CLASSICAL APPROACH FOR THE COMPUTATION OF DISLOCATION PROPERTIES IN REAL MATERIALS: METHOD, LIMITATIONS AND APPLICATIONS

2009 ◽  
Vol 20 (09) ◽  
pp. 1399-1409
Author(s):  
FRANCESCA TAVAZZA ◽  
LYLE E. LEVINE ◽  
ANNE M. CHAKA
Keyword(s):  
Ab Initio ◽  
Large Scale ◽  
Hybrid Approach ◽  
Test Case ◽  
Classical Approach ◽  
Single Vacancy ◽  
Embedded Atom ◽  
Classical Simulation ◽  
Consistent Manner ◽  
Ab Initio Approach

In this work we introduce a hybrid ab initio-classical simulation methodology designed to incorporate the chemistry into the description of phenomena that, intrinsically, require very large systems to be properly described. This hybrid approach allows us to conduct large-scale atomistic simulations with a simple classical potential (embedded atom method (EAM), for instance) while simultaneously using a more accurate ab initio approach for critical embedded regions. The coupling is made through shared atomic shells where the two atomistic modeling approaches are relaxed in an iterative, self-consistent manner. The magnitude of the incompatibility forces arising in the shared shell is analyzed, and possible terminations for the embedded region are discussed, as a way to reduce such forces. As a test case, the formation energy of a single vacancy in aluminum at different distances from an edge dislocation is studied. Results obtained using the hybrid approach are compared to those obtained using classical methods alone, and the range of validity for the classical approach is evaluated.

Group Decision Model Based on Ordered Weighted Distance to Aid Decisions on Logistics

2018 ◽  
Vol 26 (02) ◽  
pp. 233-254 ◽  
Author(s):  
Jose Leao E Silva Filho ◽  
Danielle Costa Morais
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Decision Model ◽  
Group Decision ◽  
Decision Rules ◽  
Decision Makers ◽  
Weighted Distance ◽  
Model Based ◽  
Decision Making Model

This paper presents a group decision-making model using a distance aggregator based on Ordered Weighted Distance (OWD) which offers a solution that can reduce disagreement between decision makers (DMs). This paper discusses decision rules and sets out measures to evaluate compensatory effects that have a bearing on DMs’ opinions. The model uses formulations of distances to reveal the differences in opinion among DMs and discusses the meanings of distance and the information presented by each DM. Finally, a case study of a logistics problem is used to illustrate how the model is applied.

A New Semantic Relations-Based Hybrid Approach for Implicit Aspect Identification in Sentiment Analysis

2020 ◽  
Vol 19 (03) ◽  
pp. 2050019
Author(s):  
Hajar El Hannach ◽  
Mohammed Benkhalifa
Keyword(s):  
Sentiment Analysis ◽  
Hybrid Model ◽  
Opinion Mining ◽  
Short Term Memory ◽  
Hybrid Approach ◽  
Active Phase ◽  
Semantic Relations ◽  
Term Extraction ◽  
Supervised Classifiers ◽  
Restaurant Reviews

Within the next few years, sentiment analysis or opinion mining is set to become an important component of real-world applications for product manufacturers, e-commerce companies, and potential customers. Sentiment analysis deals with the computational assessment of people’s opinions apparent or hidden within the text according to three levels: document, sentence and aspect levels. The aspect-level is increasingly becoming an active phase of sentiment analysis. At this level, the aim is to determine the hidden target of opinion represented in datasets, known as aspect term identification. This paper proposes an original hybrid model combining semantic relations and frequency-based approach with supervised classifiers for implicit aspect identification (IAI). The proposed approach is directed towards improving the F1-performances for traditional supervised classifiers commonly used in this field based on eager and lazy learning, and deep learning technique using long short-term memory whit attention mechanism applied for IAI. Particularly, this work addresses aspect term extraction and aggregation, the two sub-tasks of IAI, involving adjectives and verbs. The effects of this approach are empirically examined on multiple datasets of electronic products and restaurant reviews with multiple aspect granularity levels. Comparing this method with similar approaches clearly shows the benefits of this method: (i) the use of an appropriately selected WordNet semantic relations of adjectives and verbs that significantly helps classifiers for IAI. (ii) Using the hybrid model helps classifiers better handle these selected WordNet semantic relations and therefore deal better with IAI.

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