Comparison Of Analytic Hierarchy Process Research Articles

Sensitivity Comparison of AHP with The Combination of AHP and SAW for Facial Wash Recommendation System based on Skin Type

Purpose: This research aims to design a facial wash recommendation system based on all skin types, namely normal, dry, oily, combination, and sensitive. This is to tackle the limitation of previous systems that were developed based on limited skin types which are normal, dry, and oily using Promethee II, Fuzzy Logic, and SAW methods.Design/methodology/approach: This research uses the Analytic Hierarchy Process (AHP) method and a combination of AHP and Simple Additive Weighting (SAW) to consider the importance values of each criterion. Four criteria data are used, namely price, rating, content, and availability, along with 70 alternative data of facial wash products.Finding/Result: Sensitivity testing was conducted on both methods, and the combination of AHP and SAW produced a higher sensitivity percentage, which is 67.51%, whereas the AHP method provided a lower sensitivity percentage of 59.26%.Originality/state of the art: The combination of AHP and SAW is an innovation in designing a facial wash recommendation system, and the research results demonstrate that the combination of AHP and SAW is a superior method for recommending facial wash products.

Potential of Urban Green Infrastructure for Climate Change Adaptation in Karongi Town, Rwanda

Objective: This research aims at analyzing potential for green infrastructures to mitigate the impacts of climate change in Karongi city. Methods: This study used the analytic hierarchy process (AHP) software for the multiple criteria decision-making method that was originally developed by Prof. Saaty, ArcGIS data and excel spreadsheet. Five main criteria (Geo-physical, accessibility, blue and green infrastructure, urban land, and Vegetation data), sixteen sub-criteria and climate factors were analyzed. The comprehensive literature review and observation on ground contributed to the selection of criteria. Each criterion was ranked by using scale (1-9). Sub-criteria weighting was performed by using pairwise comparison in AHP. Results: The results indicated that available green infrastructures did not fully facilitate city residents to enjoy their benefits. Additionally, 20 years ago, Karongi city faced a land use decrease in forested areas in favor of built-up space as well as variation in rainfall pattern. Accessibility to urban green infrastructure by urban communities was at a low level, and this was an indication of vulnerability to climate change. Conclusion: The multi-scale planning approach has an impressive contribution in ecological multi-scale connections between various ecological infrastructures offering the prospect of a more sustainable landscape for well-being, biodiversity and adaptability to climate change in Karongi city. Even though these issues may have more importance than a simple term, gathering them under the umbrella of a term like green infrastructure could accentuate their interconnections and dependence on each other, hence providing contribution to climate change adaptation.

Comparison of AHP and BWM methods based on ArcGIS for ecological suitability assessment of Panax notoginseng in Yunnan Province, China

Panax notoginseng (P. notoginseng) is a traditional Chinese medicinal material with high economic and medicinal value. There is an urgent need to find new cultivation areas due to continuous cropping barriers and the effects of climate change. This study integrated the geographical environment of Yunnan with the necessary requirements for a suitable habitat for P. notoginseng and comprehensively analyzed climatic, topographical and soil factors. Furthermore, the criteria were weighted and prioritized by the analytic hierarchy process (AHP) and the best worst method (BWM) respectively, and the overlay analysis method was used to present the suitability map in the GIS environment. Two ecological suitability assessment models were established and compared to explore the ecological suitability regionalization of P. notoginseng in Yunnan Province, China. The results showed that:(1) Among the 12 driving factors, precipitation in the hottest season is the most important, followed by average temperature in the coldest season, average temperature in the hottest season, altitude, and annual precipitation. (2) The most suitable, suitable, and unsuitable regions obtained by the AHP-GIS model accounted for respective 17.98%, 33.41%, and 48.61% of the total area of Yunnan. The values for BWM-GIS model were 13.93%, 40.25%, and 45.81%, respectively. (3) The suitable regions obtained by the two models were overlayed and concentrated in Wenshan, Qujing, Kunming, Chuxiong, Baoshan, Dali, Lijiang, Honghe and Yuxi in central Yunnan, while the unsuitable regions were distributed in Xishuangbanna, Puer, Dehong, Diqing, and southwestern Zhaotong. The sensitivity of the assessment model was analyzed, and its reliability was verified by receiver operating characteristic (ROC) and area under curve (AUC). The BWM-GIS model (AUC=0.85) had higher accuracy than AHP-GIS model (AUC=0.822), and was more suitable for ecological suitability analysis of P. notoginseng. Our research results provide a theoretical basis for the rational expansion of cultivation regions of P. notoginseng and agricultural layout planning in Yunnan Province of China.

Analytic hierarchy process and data envelopment analysis: A match made in heaven

Analytic hierarchy process (AHP) and data envelopment analysis (DEA) are two popular decision science methods with many business, science, and engineering applications. AHP is a Multi-Attribute Decision-Making (MADM) method for prioritizing alternatives, and DEA is a non-parametric method for estimating production frontiers. Each method has known strengths and weaknesses, and the strengths in one method can overcome the weaknesses in the other. We study several strategies to diminish the weaknesses of DEA with the strengths of pairwise comparisons in AHP. We tackle the low discrimination power inherent to conventional DEA methods. AHP, with its pairwise comparison capability, has been consistently used to increase the discrimination power and accuracy in DEA. We propose and evaluate several new hybrid MADM-DEA models of different computational complexity and consistency, including combinations of the best-worst method (BWM) and its variants with DEA as well as a novel method composed of Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) and DEA. We further develop a new technique for evaluating the similarity among multiple ranking results in MADM. The new simple but powerful technique is called Rank Absolute Deviation (RAD) and is inspired by the mean absolute deviation method. Several numerical examples and a real-world problem are used to demonstrate the applicability and efficacy of the new BWM-DEA, MACBETH-DEA, and RAD methods proposed in this study. We illustrate how less computationally demanding MADM-DEA techniques provide rankings that are highly correlated with the benchmark DEA-AHP and different consensus ranking models.

Comparison of AHP and SAW Methods to Determine Outstanding Lecturers

The selection of outstanding lecturers in an Information Systems study program at XYZ University is currently still done conventionally. That is, it is still subjective and has not used special calculation methods to support decisions. Thus, it is necessary to have an appropriate decision support system to assist in determining outstanding lecturers objectively. The method used in this research is the analytical hierarchy process (AHP) and simple additive weighting (SAW). From the calculation of the two methods, the final result is a decision to select an outstanding lecturer in the same Information Systems study program, namely Mr. Argiyan Dwi Pritama. The results obtained from the AHP calculation yield a value of 1.46 while the SAW calculation produces a value of 0.522. From the AHP calculation, it can be concluded that the use of too many alternatives makes the ranking process too complex. Meanwhile, based on the SAW calculation, the technical calculation is very suitable for many alternatives, so it is more effective and efficient to use.

Performance Comparison of AHP and Saw Methods For Selection of Doc Broiler Chicken Suppliers

Choosing the most suitable day-old chick (DOC) broiler chicken supplier is currently one of the most important issues that must be addressed. This is because selecting the most suitable supplier can reduce the amount spent on purchases and the risk of sick chickens being delivered by the supplier. Another problem related to supplier selection that has been happening so far is the quality of products that are not following company standards or rejected products. The number of products provided does not match what was ordered by the company. The decision support system (DSS) can evaluate and select suppliers using multi-criteria characteristics related to the solutions offered based on parameters quality, price, delivery, supplier certificates, and death claims after the chickens have been delivered. The Analytical Hierarchy Process (AHP) and the Simple Additive Weighting (SAW) methods are used in this study as a comparison to produce the best-recommended accuracy value to get the best decision results based on ranking. The test results state that the AHP and SAW methods go well. The test was carried out using a dataset of the last ten months of history of purchasing docs broiler chicken from suppliers. The comparison of the results of the F1-score value between the AHP and SAW methods is 94% and 87%, respectively. The results state that the AHP method is superior as a system recommendation that can produce the best alternative supplier.

Consideration of reciprocal judgments through Decomposed Fuzzy Analytical Hierarchy Process: A case study in the pharmaceutical industry

The number of academic research considering improvements/applications in the multiple criteria decision-making (MCDM) field has been increasing in the literature day by day. Among these works, the most used MCDM method is undoubtedly the analytic hierarchy process (AHP). Decomposed Fuzzy Sets (DFS) have been recently proposed to the literature in order to measure the inconsistency in expert judgments by providing optimistic and pessimistic point of view. The main objective of this paper is to extend AHP method by using DFS. DFS makes pairwise comparisons in AHP more reliable by considering the individual answers given by the decision makers to the reciprocal questions under vagueness and impreciseness. The proposed method, Decomposed Fuzzy Analytic Hierarchy Process (DF-AHP), is applied to determine the importance degrees of evaluation criteria in the pharmaceutical industry in order to illustrate the applicability of the approach. Based on the results, the “quality” is determined to be the most significant criterion in this industry. The results obtained from DF-AHP are compared with the results obtained from both traditional AHP and Pythagorean fuzzy AHP. The comparative analysis has also shown the most significant criterion is the same with the proposed method but slightly differences in the rank of the sub-criteria. The research can help businesses better understand the critical risks in the pharmaceutical industry.

Groundwater vulnerability and contamination risk mapping of semi-arid Totko river basin, India using GIS-based DRASTIC model and AHP techniques

Totko river basin is a semi-arid watershed, which undergoes severe water crisis during the dry season. Presently, due to increase in population, demand of food has increased leading to a rise in growth of high yield crop variety and usage of chemical fertilizers and pesticides. So, surface water as well as groundwater is getting polluted. In this study assessment of groundwater vulnerability of Totko river basin has been done using DRASTIC and Analytic Hierarchy Process (AHP) models. For this, seven hydrogeological parameters have been considered which are; Depth to water level (D), Net Recharge (R), Aquifer media (A), Soil media (S), Topography (T), Impact of vadose zone (I) and Hydraulic Conductivity (C). Weight and rating analysis of the seven criteria and their sub-criteria have been done using generic DRASTIC algorithm and AHP comparison matrix. Ground Water Vulnerability Map (GWV) obtained from DRASTIC and AHP analysis has been divided into five vulnerable classes. Area of very high vulnerable zone is 6.53% more in AHP based vulnerability as compared to Generic DRASTIC. Similarly, these regions show a high nitrate concentration (30–50 ppm) in groundwater. GWV maps have been validated through nitrate concentration and the accuracy of the models have been assessed through Pearson's correlation coefficient and Kappa coefficient. To prevent groundwater contamination proper land use planning and watershed management are necessary, for which vulnerable zones need to be demarcated and DRASTIC is a useful model for vulnerability assessment.

Comparison of Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (f-AHP) for the Sustainability Assessment of a Water Supply Project

Comparison of Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (f-AHP) for the Sustainability Assessment of a Water Supply Project

Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models.

Flooding is one of the most destructive natural catastrophes that can strike anywhere in the world. With the recent, but frequent catastrophic flood events that occurred in the narrow stretch of land in southern India, sandwiched between the Western Ghats and the Arabian Sea, this study was initiated. The goal of this research is to identify flood-vulnerable zones in this area by making the local self governing bodies as the mapping unit. This study also assessed the predictive accuracy of analytical hierarchy process (AHP) and fuzzy-analytical hierarchy process (F-AHP) models. A total of 20 indicators (nine physical-environmental variables and 11 socio-economic variables) have been considered for the vulnerability modelling. Flood-vulnerability maps, created using remotely sensed satellite data and geographic information systems, was divided into five zones. AHP and F-AHP flood vulnerability models identified 12.29% and 11.81% of the area as very high-vulnerable zones, respectively. The receiver operating characteristic (ROC) curve is used to validate these flood vulnerability maps. The flood vulnerable maps, created using the AHP and F-AHP methods, were found to be outstanding based on the area under the ROC curve (AUC) values. This demonstrates the effectiveness of these two models. The results of AUC for the AHP and F-AHP models were 0.946 and 0.943, respectively, articulating that the AHP model is more efficient than its chosen counterpart in demarcating the flood vulnerable zones. Decision-makers and land-use planners will find the generated vulnerable zone maps useful, particularly in implementing flood mitigation plans.

Highway Route Planning via Least Cost Path Algorithm and Multi Criteria Decision Analysis Integration, a Comparison of AHP, TOPSIS and VIKOR

Highways are one of the main structures of cities in the field of economic, social, and environmental facilities that connect cities, regions, and people each other. Determining the suitable highway routes includes difficult and complex processes due to the construction costs. Additionally, priorities, expectations, and constraints for economic, social, and environmental parameters must be considered together to provide efficient solutions to requirements. Multi Criteria Decision Analysis (MCDA) techniques such as Analytical Hierarchy Process (AHP), Ideal Solution Similarity Selection Ranking Technique (TOPSIS), and Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Least Cost Path Algorithm (LCPA) with Geographical Information Systems (GIS) combination are the most suitable way to overcome these complexities. In this study, slope, aspect, geology, elevation, distances to roads, settlements, water bodies, fault lines, buildings, natural disasters, protected sites, population, and land use were selected to determine most suitable highway construction areas and route. The AHP, TOPSIS, and VIKOR methods were applied to calculate cost surfaces for least cost paths generation with LCPA, and the generated three routes were compared. As a result of the comparisons VIKOR route was the most suitable route considering the topographical statistics and all the three methods consistent with each other and current road.

High Voltage Overhead Powerlines Routing in Central Nigeria using GIS-MCDA Approach and Environmental Impact Factors

High voltage overhead transmission line route selection has become a vital component of the power transmission line project life cycle as demand for electricity has increased and global awareness of the environmental implications of large-scale power projects has grown. The project necessitates meticulous planning, engineering designs, facility installations, commissioning, and maintenance, as any errors made at this stage may have a flowing detrimental impact on the following phase, which may be too costly to fix. Using geographic information system (GIS), multi-criteria decision analysis approach, and environmental impact factors strategies, this study determines the best route from existing geographical space between Lafia 330/132/33kV Substation in Nasarawa State and New Apo (Pigba) 330/132/33/kV Substation in the Federal Capital Territory, Central Nigeria, Abuja. Land use, land cover, and other environmental data were obtained by performing image classification on Landsat 8 satellite image using ArcGIS 10.1 to achieve this goal. Three key terrain elements were identified to define the land cover types: built-up areas, vegetation, and water bodies. These layers were created to reveal the locations of significant settlements, geological formations, and the HV-OHTL route that avoided crossing protected areas. Using pair-wise comparison of analytic hierarchy process (AHP) approach, each criterion evaluated was assigned relative weight that shows their level of influence on the proposed power transmission line, and these were provided as GIS layers for visualizations. To build the cost surfaces assessed during route selection for HV-OHTL, weights derived from AHP method for each decision makers were applied to all layers to create the cost surfaces analyzed during route selection for HV-OHTL.

Using improved Group 2 and Linguistic Z-numbers combined approach to analyze the causes of railway passenger train derailment accident

In recent years, several passenger train derailment accidents occurred in the world. In order to guarantee the reliability and normal operations of railway passenger trains, an improved Group 2 and Linguistic Z-numbers (IG2-LZs) combined approach is proposed to analyze the causes of railway passenger train derailment accident (RPTDA). The weight and attribute value of each cause of accident are calculated by IG2 and LZs, respectively. In order to relax the three limitations of previous G2 approach, the Fault Tree is applied to figure out the least important cause of accident from all causes of accident; the minimum nonempty intersection sets, which can reflect the opinions of experts, are introduced to improve the interval assignment; left offset rate and right offset rate are introduced to improve the risk attitude factor from the experts. The Puyuma case happened in Taiwan is applied as the case study. The calculation results show that, the failure of Automatic Train Protection (ATP) belongs to the most contributed cause. A comparison of Analytic Hierarchy Process (AHP), IG2-Triangular Fuzzy Number and previous G2-LZs show that the IG2-LZs is more reliable and reasonable than AHP, IG2-TFN or G2-LZs.

An approach to evaluate CAM software alternatives

ABSTRACTThe selection process for the best computer-aided manufacturing (CAM) software among a set of potential number of alternatives in market has been critical issue for most companies that aim to make their design/manufacturing-related activities automated. Because this selection process is very vital for companies because a wrong decision might put them into a difficult position in terms of economical, market share and time spent. Therefore, today’s companies have used different multiple-criteria decision making (MCDM) methods for the evaluation study of CAM software alternatives to make this complex process easily applicable and not time-consuming. Among the MCDM methods in literature, the analytic hierarchy process (AHP) method has been widely used for various MCDM problems in both academic researches and industrial practices. However, in some cases, because of the vagueness and uncertainty on the judgments of decision maker(s), the crisp pair wise comparison in the conventional AHP seems to be insufficient and imprecise to capture the right judgments of decision maker(s). Therefore, a fuzzy logic method is integrated in the pair wise comparison of AHP to make up for this deficiency in the conventional AHP, called as fuzzy AHP. Moreover, the proposed approach is also realized on a case study.

ปัจจัยที่มีผลต่อการตัดสินใจเลือกติดตั้งระบบผลิตไฟฟ้าด้วยแสงอาทิตย์สาหรับบ้านอยู่อาศัยโดยวิธีการวิเคราะห์เชิงลำดับชั้น (Factors Influencing the Decision to Install a Solar Power System for Residential Homes by Using Analytic Hierarchy Process)

Thai Abstract: การวจ ย นมว ต ถประสงคเ พอ ศก ษาถงปจ จย ตางๆ ทม ผ ลตอการตด สน ใจเลอ กตดตง ระบบผลต ไฟฟาดวยแสงอาทต ยส าหรบบานอยอาศย โดยใชการวเคราะหเชงล าดบชนเปนเครองมอในการศกษา จากการสอบถามผเชยวชาญในธรกจพลงงานจ านวน 20 ตวอยาง และยง มการเกบขอมลความพงพอใจของปจ จย ตางๆ จากกลมผบรโ ภคจานวน 400ตวอยาง เพอใหขอมลและผลการวจย ทไดมความสมบรณ ผลการวจย พบวา ปจ จย หลก ทสาคญ ทสดในการเลอกตด สน ใจไดแ ก ปจ จย ดา นความนาเชอ ถอ ผต ด ตง มค ะแนนความส าคญ 38.94% ซง ปจ จย รองสาคญ ทส ดไดแ ก ปจ จยดา นคณภาพบรก าร รองลงมาไดแ ก ปจ จย หลก ดา นสวนประสมทางการตลาด 4P มคะแนนความส าคญ 34.17% ซงปจ จย รองสาคญ ทส ดไดแก ปจ จย ดานราคา ซงผลของขอมลมค าความสอดคลอง ตามหลกการเปรยบเทยบการวเคราะหเชงล าดบชน และสอดคลองกบผลความพงพอใจทงกลมผเชยวชาญและกลมผบรโภค English Abstract: The purposes of this research are study to analyze the key factors of decision to install a solar power system for residential homes by using Analytic Hierarchy Process from experts in the energy business 20 samples and also collecting information about the satisfaction of various factors 400 samples from consumer groups to provide complete information. The results of the study were as follow: The most important main factor of decision is the reliability factor for installers at the importance factor level of 38.94% and the most important sub-factor is service quality factor. Followed by main factor is the marketing mix 4P at the importance factor level of 34.17 % and the most important sub-factor is price factor. From processing, The Consistency Ratio is based on the principle of comparison of Analytic Hierarchy Process and according with the satisfaction of both the expert group and the consumer group.

Comparison of analytical hierarchy process and certain factor models in landslide susceptibility mapping in Rwanda

The aim of this study was to compare the performance of the Analytical Hierarchy Process (AHP) and Certain Factor (CF) models in landslide susceptibility mapping (LSM) in the western province of Rwanda. At first, landslide inventory map was prepared using 96 points localized by field surveying. Then, 65.63% (63 of 96 landslides) were randomly selected for building landslide susceptibility and the remaining 34.37% (33 of 96 landslides) were used to validate the models. Eight conditioning factors: elevation, slope angles, distance to roads, land use and land cover, rainfall, lithology, soil texture, and normalized difference vegetation index were analysed. The produced susceptibility maps were zoned into very low, low, moderate, high, and very high susceptibility. The validation of landslides susceptibility maps was accomplished by the area under the curve (AUC) method. The CF model generated high accuracy and prediction rates (74.62 and 74.012%) than that of AHP model (73.063 and 73.83%), respectively. The produced landslide susceptibility maps can help to recognize landslide hazard mitigation and adaptation needs.

Comparison of AHP and a Utility-Based Theory Method for Selected Vertical and Horizontal Forest Structure Indicators in the Sustainability Assessment of Forest Management in the Sierra de Guadarrama National Park, Madrid Region

This paper compares two pairwise comparison methods, the analytic hierarchy process (AHP) and a utility theory based method (UTB method), for sustainability assessment in forest management at the local level. Six alternatives were ranked, corresponding to six different types of forest management in the Sierra de Guadarrama National Park in the Madrid Region in Spain. The methods were tested by postgraduate students enrolled in a “Decision Support Systems” course at Universidad Politécnica de Madrid. Three sustainability indicators were considered: structural diversity, timber yield, and amount of biomass. The utility theory based method was the first to be compared, which is implemented in the computer program SILVANET. For each pair of alternatives, the students were asked which one they considered to be more sustainable. In the case of the Analytic Hierarchy Process, the students compared the indicators and the alternatives for each indicator. The Spearman’s correlation coefficient indicated that there was no correlation between the rankings for most of the students. The results revealed that the convergence in opinion in the AHP method was higher than in the utility based method for a low number of participants, and distinguished the differences between the alternatives more accurately. However in the case of the UTB method, the participants considered sustainability as a whole and made a more context-based comparison.

Application and Comparison of Analytical Hierarchy Process (AHP) and Network Methods in Path Finding of Pipeline Water Transmission System, from Taleghan’s Dam to Hashtgerd New City, Tehran, Iran

These instructions give you guidelines for preparing determination of optimum path by considering technical and engineering, environment and cost management visions. In this point of view from Taleghan’s dam to Hashtgerd New City case study, we need to distinguish and apply the essential parameters such as topographic and morphologic conditions, environmental issues by consideration on sustainable development, population distribution patterns, roads and etc. by using base map and extraction of expected points geometrical location from Google Earth, position land surveying done. Then the mentioned co-parameters data layer loaded in GIS environment and after allocation the special coefficient and value for weighting parameters and combine them based on MCE method and the cost map made based on AHP method which Lead to determination of optimum path by using LCPA method. Paths include of ABFA path and two evaluated optimum path compared and indicated that two optimum paths overlapped mostly. Cost comparison between optimum path and ABFA path imply 14% decrease in expenditure Which the main extra expense of ABFA path due to more intersection with rivers, roads and necessity construct of structures to keep water natural regimes, passing unauthorized areas and personal parcels need to pay, path finding only by personal experience underestimating academic science, data analyzing software’s which Cause to increasing the length of water supply pipeline.

Comparison of Analytic Hierarchy Process, Catastrophe and Entropy techniques for evaluating groundwater prospect of hard-rock aquifer systems

Groundwater is a treasured underground resource, which plays a central role in sustainable water management. However, it being hidden and dynamic in nature, its sustainable development and management calls for precise quantification of this precious resource at an appropriate scale. This study demonstrates the efficacy of three GIS-based multi-criteria decision analysis (MCDA) techniques, viz., Analytic Hierarchy Process (AHP), Catastrophe and Entropy in evaluating groundwater potential through a case study in hard-rock aquifer systems. Using satellite imagery and relevant field data, eight thematic layers (rainfall, land slope, drainage density, soil, lineament density, geology, proximity to surface water bodies and elevation) of the factors having significant influence on groundwater occurrence were prepared. These thematic layers and their features were assigned suitable weights based on the conceptual frameworks of AHP, Catastrophe and Entropy techniques and then they were integrated in the GIS environment to generate an integrated raster layer depicting groundwater potential index of the study area. The three groundwater prospect maps thus yielded by these MCDA techniques were verified using a novel approach (concept of ‘Dynamic Groundwater Potential’). The validation results revealed that the groundwater potential predicted by the AHP technique has a pronounced accuracy of 87% compared to the Catastrophe (46% accuracy) and Entropy techniques (51% accuracy). It is concluded that the AHP technique is the most reliable for the assessment of groundwater resources followed by the Entropy method. The developed groundwater potential maps can serve as a scientific guideline for the cost-effective siting of wells and the effective planning of groundwater development at a catchment or basin scale.

Comparison of AHP and Monte Carlo AHP Under Different Levels of Uncertainty

Despite the extensive application of Monte Carlo analytic hierarchy process (MCAHP) in various fields of decision making, its performance has not been compared with the classic analytic hierarchy process (AHP). Both of these methods are heavily affected by individual or group preferences and thus provide subjective rankings. Since the mere difference between their results does not necessarily warrant the superiority of one against the other, a reliable and robust ranking of alternatives should be available as a comparison basis so that the results of these two methods can be evaluated. In this paper, we use a simulation approach to compare the results of AHP with MCAHP under different levels of uncertainty. We validate our simulation results by comparing the performance of these two alternatives against a real world and reliable ranking of blogs. Our simulation results show that as long as the variation in different pairwise comparisons is less than 0.24, the performance of AHP is not statistically different from the performance of MCAHP. When the uncertainty in terms of variation grows beyond 0.24, MCAHP provides more precise rankings. The findings of this research add to the current body of knowledge in the multicriteria decision analysis as well as Information Systems literature and provide insights for managerial applications of these techniques.