The analytic hierarchy process—what it is and how it is used

Saaty, Rozann W.

doi:10.1016/0270-0255(87)90473-8

Cited by 3,541 publications

(2,589 citation statements)

References 10 publications

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“…We employ the use of an analytic hierarchy process [13] which uses a multiple criteria decision making method. The process employs a procedure of multiple comparisons to rank alternative solutions to a multi objective decision problem.…”

Section: Qos Evaluation Methodsologymentioning

confidence: 99%

Quality of Service Evaluation of a Deployed 3G Data Network for a Campus wide e-Learning Platform

PAgyekum¹,

Tchao²,

Affum³

2014

IJCA

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In Ghana, the increase in the adoption of e-learning methodologies is improving the way teachers and students interact. With the combination of internet, multimedia and network technologies, e-learning is changing typical teaching and learning using its methodologies to improve access to education on many university campuses. A third generation (3G) data network has been deployed on Kwame Nkrumah University of Science and Technology (KNUST) campus with the aim of improving connectivity for students and lecturers to enable them access an implemented e-learning platform anywhere on the university campus. This paper evaluates the Quality of Service (QoS) provided by the 3G cellular data network. It addresses the gap between the technical capabilities and the QoS experienced by students and teachers who use the 3G network to access the platform. The analysis in the paper is based on live data which were collected on the network. An Analytic Hierarchy Process (AHP) methodology has been used to assess the QoS based on selected Key Performance Indicators (KPIs).

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Section: Qos Evaluation Methodsologymentioning

confidence: 99%

Quality of Service Evaluation of a Deployed 3G Data Network for a Campus wide e-Learning Platform

PAgyekum¹,

Tchao²,

Affum³

2014

IJCA

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“…This mode is used in Saaty's [5,6,7] Analytic Hierarchy Process (AHP), a multicriteria decision methodology that is widely used as a foundation for decision support systems. For optimal quality, exhaustive pairwise comparison is required between each possible pair of design options.…”

Section: Visual Assessment Methodsologiesmentioning

confidence: 99%

Community design of a light rail transit-oriented development using casewise visual evaluation (CAVE)

Bailey

Grossardt

Pride-Wells

2007

Socio-Economic Planning Sciences

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“…The AHP is a multi-criteria decision analysis method that supports the creation of weights based on experts´judgments, and evaluates the reliability of these weights by applying a consistency test. The key aspect of the AHP is the construction of a pairwise comparison matrix (Boroushaki and Malczewski 2008;Saaty 1977;Saaty 1987). This is a n × n matrix where n is the number of indicators and its inputs are the Saaty's scales (Table 2) and can be defined as a matrix Table 1 Indicators used to construct the deprivation index Indicators A: percent of the population that have a long-term disability (for more than one year) B: percent of the population that does not have any level of formal education or instruction C: percent of the population that has no public social/health insurance D: percent of the population that works in unpaid jobs E: percent of households with four or more persons per dormitory F: percent of households without access to drinking water from the public system G: percent of households without access to the sewerage system H: percent of households without access to the public electricity grid I: percent of households without garbage collection service J:distance (meters)to the nearest primary healthcare service X with the elements a ij (Chen et al 2010):…”

Section: Calculation Of the Deprivation Indexmentioning

confidence: 99%

Deprivation, Healthcare Accessibility and Satisfaction: Geographical Context and Scale Implications

Cabrera-Barona

Blaschke

Gaona

2017

Appl. Spatial Analysis

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Indices explaining health phenomena are important tools for identifying and investigating health inequalities and to support policy making. Some of these indices are expressed at area-level, and the investigation of the areal influences of these indices on individual health outcomes have scale and geographical contextual implications that need to be assessed. In this study we calculated two area-level indices: one deprivation index and one index of healthcare accessibility. Using multilevel modelling, we calculated the area-level influences of these indices on an individual-level index of healthcare satisfaction considering three kinds of areas or contexts: a context of deprivation, a context of healthcare accessibility and a context combining the two characteristics of healthcare accessibility and deprivation. We evaluated two kinds of geographical problems using the statistical results of these area-level influences: the modifiable areal unit problem (MAUP) and the uncertain geographic context problem (UGCoP). Regarding the MAUP we evaluated the scale effects at two scales: census blocks and census tracts. Regarding the UGCoP we evaluated the differences in areal influences between the three kinds of contexts for both scales. The case study area was the city of Quito, Ecuador. The results of the performed analyses showed no severe MAUP and UGCoP, and revealed important evidence of the area-level influence of deprivation and healthcare accessibility on healthcare satisfaction.

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The analytic hierarchy process—what it is and how it is used

Cited by 3,541 publications

References 10 publications

Quality of Service Evaluation of a Deployed 3G Data Network for a Campus wide e-Learning Platform

Quality of Service Evaluation of a Deployed 3G Data Network for a Campus wide e-Learning Platform

Community design of a light rail transit-oriented development using casewise visual evaluation (CAVE)

Deprivation, Healthcare Accessibility and Satisfaction: Geographical Context and Scale Implications

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