Analytical Hierarchical Process Model Research Articles

Delineation of groundwater prospective zones using multivariate and spatial analysis techniques in Henan Province North China Plain

Groundwater is an essential resource that meets all of humanity’s daily water demands, supports industrial development, influences agricultural output, and maintains ecological equilibrium. The objective behind this research is to find groundwater prospective zones and their sustainable development in Henan Province, located in the North China Plain, with the help of analytical hierarchical process (AHP) and frequency ratio (FR) models. Consequently, a groundwater inventory map was created, utilizing 70% of the data for training and 30% for testing purposes. The resulting maps were overlaid with groundwater levels and the locations of wells within the study area. The performance and validation of the models were assessed using the Area Under Curve (AUC) curve, which indicated an accuracy of 70% for the AHP model and 69% for the FR model. The study indicates that areas with suitable gradients and rainfall patterns generally have high groundwater prospective zonation (GWPZ), i.e., Zhumadian and Nanyang (ZN). However, AHP demonstrated a higher predictive capability in comparison to FR the broader context. Whereas GIS-RS methodology aligns with existing wells and field data that validate it in range of good and excellent. In conclusion, this study provides valuable insights for effective groundwater exploration and sustainable water supply planning in Henan Province.

Analytical hierarchy process model for managing cloud security

PurposeThis paper aims to explore key management actions for implementing security on the cloud, which is a critical issue as many organizations are moving business processes and data on it. The cloud is a flexible, low cost and highly available technology, but it comes with increased complexity in maintaining the cloud consumer’s security. In this research, a model was built to assist strategic decision-makers in choosing from a diverse range of actions that can be taken to manage cloud security.Design/methodology/approachPublished research from 2010 to 2022 was reviewed to identify alternatives to management actions pertaining to cloud security. Analytical hierarchical process (AHP) was applied to rate the most important action(s). For this, the alternatives, along with selection criteria, were summarized through thematic analysis. To gauge the relative importance of the alternatives, a questionnaire was distributed among cloud security practitioners to poll their opinion. AHP was then applied to the aggregated survey responses.FindingsIt was found that the respondents gave the highest importance to aligning information security with business needs. Building a cloud-specific risk management framework was rated second, while the actions: enforce and monitor contractual obligations, and update organizational structure, were rated third and fourth, respectively.Research limitations/implicationsThe research takes a general view without catering to specialized industry-based scenarios.Originality/valueThis paper highlights the role of management actions when implementing cloud security. It presents an AHP-based multi-criteria decision-making model that can be used by strategic decision-makers in selecting the optimum mode of action. Finally, the criteria used in the AHP model highlight how each alternative contributes to cloud security.

Delineation of Ground Water Potential Zoning Using GIS and Remote Sensing by AHP of Sunsari District (Koshi Basin) Area of Nepal

This study assesses the groundwater potential in Sunsari district of Nepal by using a multi-criteria decision analysis tool along with remote sensing and geographic information system (GIS).The study has taken precipitation, Land use/cover (LULC), slope, geology, drainage density, lineament density, soil, and canal density as key influencing factors for determining the groundwater potential of the study area. The Analytical Hierarchical Process (AHP) technique was adopted in deriving the relative weights of these criteria and sub-criteria based on a review of the literature according to their relative importance in recharging the groundwater. The final thematic map of groundwater potential zones was prepared based on a groundwater potential index computed by aggregating the selected thematic layer with appropriate weights. The groundwater potential zones are classified into three zones based on the score of the groundwater potential index. The generated groundwater potential zones were further validated with ground truth data using a confusion matrix with a kappa coefficient and analysis of the receiver operating curve (ROC). The validation indicated fair predictability of groundwater potential zone with the AHP and GIS model. The areas under “Poor”, “Moderate” and “Good” are 13.6%, 36.0%, and 50.4% of the study area, respectively. The areas under the “Good” potential category are concentrated in the lower southern and western parts of the study area, while the east central part with highly dense built-up area falls under the “Poor” potential category. Also, the area just north of the central part is under the “Moderate” zone. There is a good coherence of precipitation and LULC with groundwater potential zones and less coherence of other factors.

Zoning Analysis of Iron Age Sites Using Analytic Hierarchical Process (AHP) Methods in the Middle Atrak River Basin, Northeast of Iran

Iron Age settlements in the Middle Atrak Basin in Iran have a particular distribution pattern due to environmental, social, and economic variables, among which geographical factors play an essential role in creating and dispersing settlements. Some of these factors play a more effective and stable role than others. The present study examines and evaluates the role of geographical factors in the distribution of Iron Age sites to determine factors that have a more significant role than others. Moreover, the zoning map of the Middle Atrak Basin should be presented using four different types of location, grouped in terms of those with a perfectly suitable, relatively suitable, suitable, and unsuitable location. To achieve this goal, seven natural factors, including the distance of sites from the river, altitude, slope, slope direction, distance from communication routes, soil type, and land use, were selected as influential factors in choosing the location of the Iron Age sites. In this study operating maps were prepared digitally using ArcGIS, and then the weight of each index was determined using the AHP model. The results of this study show that 46.7% of the Iron Age settlements (or 28 sites) were located in a perfectly suitable environment and geography, 24 sites (29.3%) in a relatively suitable location, seven sites (11.4%) in a suitable place, and one site (1.6%) in a completely unsuitable environment. This last type of location in the region’s landscape indicates the choice of different livelihoods, including agriculture and animal husbandry with both seasonal and permanent methods.

Blockchain in sustainable supply chain management: an application of the analytical hierarchical process (AHP) methodology

Purpose The analytical hierarchical process (AHP)’s main purpose is to assess higher hierarchy levels based on the cooperation of its various levels. It results in a well-designed model-based method in which the weights for the selected attribute are calculated using dimensions, criteria, and indicators. This paper aims to highlight the benefits of blockchain in supply chain management with the help of a literature review along with opinions of experts from various sectors.Design/methodology/approachWith the goal of enhancing the use of blockchain technology in supply chain management, particularly when comparing within the same industry, the AHP methodology has been used. In order to develop the AHP model, a total of eight elements are examined in this study, which are decentralization, resiliency, security, smart contracts, sustainability, traceability, transparency and trust. A calculation of a Desirability Index for conventional supply chain and blockchain-enabled supply chains has been also developed.FindingsFindings where that in a blockchain-enabled supply chain, the global weights of individual benefit variables are considerably larger than in conventional supply chains. When the score of the Desirability Index for conventional supply chain and blockchain-enabled supply chain is compared, the blockchain-enabled supply chain significantly surpasses the conventional supply chain in terms of increasing sustainable development in today’s supply networks.Originality/valueThis study takes into account the AHP methodology applying it on blockchain. This has not been done before in the academic world, at least as far as the authors may be aware of. The originality of combining such process with a recent technology such as blockchain highlights the value of this research.

Assessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India

Floods have received global significance in contemporary times due to their destructive behavior, which may wreak tremendous ruin on infrastructure and civilization. The present research employed an integration of the Geographic information system (GIS) and Analytical Hierarchy Process (AHP) method for identifying the flood susceptibility zonation (FSZ), flood vulnerability zonation (FVZ), and flood risk zonation (FRZ) of the humid subtropical Uttar Dinajpur district in India. The study combined a large number of thematic layers (N = 12 for FSZ and N = 9 for FVZ) to achieve reliable accuracy and included the multicollinearity analysis of these variables to overcome the issues related to highly correlated variables. According to the findings, 27.04, 15.62, and 4.59% of the area were classified as medium, high, and very high FRZ, respectively. The ROC-AUC, MAE, MSE, and RMSE of the model exhibited a good prediction accuracy of 0.73, 0.15, 0.16, and 0.21, respectively. The performance of the AHP model has been evaluated using sensitivity analyses. It also highly recommends that persistent improvement in this subject, such as sensitivity studies on modifying criteria thresholds, changing the relative significance of criteria, and changing the desired matrix, will permit GIS and MCDA to be progressively adapted to real hazard-management issues.

Identification of groundwater potential zone using analytical hierarchical process (AHP) and multi-criteria decision analysis (MCDA) for Bhavani river basin, Tamil Nadu, southern India

The present study aimed to identify groundwater potential zones was involving the collection of both spatial and non-spatial datasets for water management practice. The Bhavani river basin groundwater is the major source for agriculture, domestic, industry, etc. The basin area is divided into lower and upper sub-basins of an area of 4207 km2. To delineate the Groundwater Potential Zone (GWPZ) ten thematic layers (geology, geomorphology, land use land cover, drainage and lineament density, slope, elevation, soil texture, rainfall, groundwater) were prepared using Arc GIS 10.3 software. The Analytical Hierarchical Process (AHP) based Multi-Criteria Decision Analysis (MCDA) was used to calculate the weightage value for each parameter. For parameter validation consistency index and consistency ratio were used. The identified groundwater potential zone was categorized into five classes based on the groundwater potential availability, as very high (1599 km2), high (1430 km2), moderate (547 km2), low (421 km2), and very low (210 km2). In the middle portion of the basin, 38% of the area falls under very good GWPZ and is followed by high (34%), moderate (13%), low (10%), and very low (5%) identified the different location of the basin. Further, GWPZ were classified based on firka and compared to the Public Work Department (PWD) 2011 and 2020 reports. From the report, 22 firkas are over-exploited from 2011 to 2020. In the present study GIS coupled with the AHP model gives accurate groundwater recharge zones. It's more helpful for drought risk assessment and planning recharge structures for agriculture engineers and government agencies.

Modelling wildfire susceptibility in Belize’s ecosystems and protected areas using machine learning and knowledge-based methods

Wildfires are serious threats to Belize’s protected areas and ecosystems. In Belize the spatial variability of wildfire susceptibility and influencing factors at a national scale are poorly understood which hinders wildfire management interventions. Hence, in this research we conducted a joint application and performance comparison of AHP (Analytical Hierarchical Process), RF (Random Forest) and FAHP (Fuzzy Analytical Hierarchical Process). The analysis revealed that RF (AUC = 83.1%) is the model with better predictive accuracy followed by FAHP (AUC = 71.2) and AHP (AUC = 66.8). The RF, AHP and FAHP models classified 22%, 32% and 37% of the country as having high and very high wildfire susceptibility, respectively. These susceptible areas are located mainly in lowland savanna and lowland broad-leaved moist forest; especially, in areas that are unprotected, the outer boundaries of protected areas and small and isolated protected areas. The main factors that are influencing wildfire susceptibility in Belize are distance to agriculture, landcover and temperature. The comparison of these methods provides a better understanding of the implementation and performance of knowledge-based methods (AHP and FAHP) in comparison with a well-established machine learning method (RF) in a country where local data availability, accessibility and reliability are an issue. Our study also provides new wildfire susceptibility information to Belize’s wildfire managers and demonstrates the need to improve wildfire management.

Multifunctional resilience of river health to human service demand in an alluvial quarried reach: a comparison amongst fuzzy logic, entropy, and AHP-based MCDM models.

Riverine ecosystem services to human beings are dynamically evaluated by harmonic relationships; however, over growing human service demands (HSDs) are leading to deteriorate the river health resilience. In this study, an assessment index system of river health involving pressure-state-response (PSR) based on twenty indicators of riparian, channel geomorphic, hydroecological, and social attributes was developed to detect the multifunctional reliability and resilience of river system integrity for HSDs at upper (US), middle (MS), and lower segments (LS) of Kangsabati River using fuzzy logic, analytical hierarchical process (AHP), and entropy weight-basedmulti-criteria decision matrix (MCDM) methods. Borda integrating MCDM results revealed that overall indicator performance is high health score in US (77), medium score in MS (69), but mostly unhealthy score in LS (34); thus, entropy-MCDM models give highest rank to US, medium rank to MS, and least rank to LS, while AHP and fuzzy MCDM models assigned as high priority rank to MS, medium rank to US, and least rank to LS, respectively. According to model validation performances, entropy-MCDM models (RMSE < 2.48) are rationalized to the harmonic relationship of riverine system, whereas fuzzy and AHP-MCDM models (RMSE < 2.79) are signified to HSDs, and these results are closer to real problems. With the acceptability of AHP-MCDM models through the percentage change (73.89%) and intensity change (17.16) assessment, it points that over HSDs are crucial factors for river health degradation. Moreover, final outcome of the present research helps to find out the sick river health sites for ecological restoration.

Assessment of Risk and Uncertainty Factors Inherent in Nigerian Highway Project Using Analytical Hierarchical Process

The study presents a framework through which risk and uncertainties in Nigeria highway projects can be appraised using the analytical hierarchical process model. Pairwise comparison matrix was performed on eleven (11) risk and uncertainty factors that affect highway project performance through a questionnaire survey conducted among two hundred and four (204) respondents, which involved various stakeholders in the highway construction industry using Saaty’s AHP rating scale. The relative weights (significance/impact level) of each of the highway risk factors were estimated during the AHP model development. The results in descending order of risk factors priorities are Standard &amp; Regulations (S&amp;R), Construction (C), Project Staff (PS), Project Sponsor (PSp), Design (D), Project Finance (PF), Economic (E), Equipment (EQ), Environmental &amp; Geotechnical (En&amp;G), Site Location (SL) and Subcontractor (S) with impact levels of 16.6%, 14.2%, 13.9%, 13%, 12.7%, 12.2%, 10.8%, 9.8%, 6.2%, 4.2%, and 3.8% respectively. The model was validated using the statistical consistency test, with the model showing a consistency ratio equal to 0.1. The model was then applied to five (5) highway construction projects which had been constructed to predict the ones with the most and least risks. The result was in tandem with that which was given by the project managers from experiences on the project. This study showed that the Analytical Hierarchical Process (AHP) decision support model can effectively be used for risk assessment and prioritization of highway construction projects for efficient resource utilization in Nigeria.

Determinants of employee creative behavior in the UAE public sector

PurposeService levels between public organizations in the United Arab Emirates (UAE) differ and fluctuate. Service levels were found to increase with the level of employee creative behavior (ECB), which is currently a focal point in organizational policies by the federal UAE government. While the literature presents an ample array of determinants of ECB, local context typically influences which determinants provide more leverage than others. Therefore, this research aims to present a customized ranking of determinants that enables managers in the UAE public sector to successfully stimulate ECB.Design/methodology/approachThrough a systematic literature review, this study identified 21 determinants at four different levels and subsequently utilized the analytic hierarchical process (AHP) to map their relative importance. Data were attained from 33 experts: managers and senior employees from different organizations.FindingsFindings indicate that, overall, the individual level is seen as the most important leverage point to stimulate ECB, followed by the team level. Comparing the determinants under each level, management support (organizational level) is perceived as the most impactful, followed by coworker support (team level), and enhancing creative self-efficacy (individual level).Originality/valueThis study compares obtained levels from other studies with new levels in building the AHP model. These insights guide managers in the UAE public sector who aim to enhance ECB, which will contribute to increased service quality. The study introduced a comprehensive ECB framework of 21 determinants. Even though many ECB studies applied in different countries and industries, but to researchers' knowledge, this is the first ECB study that applied at the UAE's public sector using the AHP model.

Landslide susceptibility mapping using integrated approach of multi-criteria and geospatial techniques at Nilgiris district of India

Nilgiris district of Tamil Nadu, India, is one of the landslide-prone zones. In recent years, this district has suffered a lot from landslides. A study was done using the geospatial technology–based analytical hierarchical process (AHP) model, a multi-criteria approach integrated with representation operating characteristics (ROC)–area under curve (AUC) validation technique to map the landslides susceptible zones of this district. The weights of the landslide triggering (or influencing or inducing) factors (criteria) obtained the AHP model are slope (0.377), geology (0.281), distance from the faults (0.119), distance from the drainage (0.071), rainfall (0.062), Land Use Land Cover (LULC) (0.039), elevation (0.027), and slope aspect (0.023). The obtained weights of respective influencing factors of this region illustrate their priorities in the order from very high to very low with a Consistency Ratio (CR) value equal to 0.07 (< 0.1) that indicates the acceptability of the weightage. Resulted landslide-susceptible (potential) zones of this district have revealed that 22.65% of the study area is very low susceptible, whereas 20.17%, 15.88%, 13.32%, and 27.98% of the regions are low, medium, very highly vulnerable to landslides, respectively. It was also found that the Udagamandalam block (north-central part of the Nilgiris district) is the most susceptible to landslides where Gudalur (north-west) is the least susceptible block. However, Coonoor (south-east) and Kotagiri (north-east) have acquired the second and third places, respectively. The empirical and binormal ROC curve estimates the accuracy nearly equal, i.e., 75.35% and 75.36%, respectively, that signifies the good performance of the AHP model in this region. Obtained landslide susceptible map of Nilgiris can be further used by the local or state or central authorities to make the policies and planning for the sustainable development of the region.

A Proposed Corporate Social Responsibility Model to Develop a Coherent Sustainability Commitment

This study develops a proposed model based on the Analytical Hierarchical Process model (AHP) and Standard and Poor's/ Egypt Stock Exchange Environmental, Social and Governance Index (S&amp;P/EGX ESG) to measure and maximize the company's corporate social responsibility (CSR) performance. The results confirm that the company that successfully undertakes this model can develop a coherent sustainable disclosure commitment that contributes to a never-ending journey of continuous improvement in the company's CSR performance. Furthermore, based on the empirical results of the proposed model implemented at SC which is the targeted company used for the case study, we find that this model enables the company to identify, measure and track its CSR performance over three years from 2017 to 2019 and in comparison with the S&amp;P/EGX ESG benchmark at the KPIs level. In addition, the researchers develop a sustainability outcomes report to reflect the strengths and weaknesses in the current situation of SC. Therefore, it enables the company to transparently communicate the results of its performance in a high-quality report, which finally contributes to the achievement of sustainable development as an end vision.

Evaluation Model of Remote Sensing Satellites Cooperative Observation Capability

This paper proposed a new remote sensing observation capability evaluation model (RSOCE) based on analytic hierarchy process to quantitatively evaluate the capability of multi-satellite cooperative remote sensing observation. The analytic hierarchical process model is a combination of qualitative and quantitative analysis of systematic decision analysis method. According to the objective of the remote sensing cooperative observation mission, we decompose the complex problem into several levels and a number of factors, compare and calculate various factors in pairs, and obtain the combination weights of different schemes. The model can be used to evaluate the observation capability of resource satellites. Taking the optical remote sensing satellites, such as China’s resource satellite series and GF-4, as examples, this paper verifies and evaluates the model for three typical tasks: point target observation, regional target observation, and moving target continuous observation. The results show that the model can provide quantitative reference and model support for comprehensive evaluation of the collaborative observation capability of remote sensing satellites.

Identification and characterization the sources of aerosols over Jharkhand state and surrounding areas, India using AHP model

The Aerosol Optical Depth (AOD) has measured using remote sensing and GIS methods, with MODIS data collected in Jharkhand from 2011 to 2017. The state's eastern and northern borders have greater aerosol loadings (AOD: >0.5) while the southern and western parts have lower aerosol loadings (AOD: <0.3). Primary, secondary, tertiary, and quaternary aerosol sources have been identified and categorized using the Analytic Hierarchical Process (AHP). Only 1.29% of the study area, which still emits the most aerosols, is covered by primary sources. Industrial zones, mining regions, thermal power plants, cement industries, high road density, and stone crushers are found in many locations throughout the country. Secondary sources of aerosols account for 5.23% of the study and are located near the main sources. The quaternary (54.08%) and tertiary (39.4%) aerosol sources mainly covered the Southern, Western, and North-Western portions of the state, which is enveloped by a heavily vegetated region. AOD, sources of aerosols, wind direction, and velocity were examined here. There were non-separable connections in this area and also AOD distribution is connected to aerosol sources, wind direction, and wind velocity. Finally, it employs the AOD values to identify different aerosol kinds and source heterogeneity to elucidate their influence.

Selection of intense energy welding process for high strength aluminum alloy using AHP

In the automobile industry, the reduction of the overall weight of vehicles faced a global challenge in terms of achieving better fuel economy and reducing the co2 emission levels. Aluminum alloys are widely used in the automotive industry due to their high strength to weight ratio than steel. In recent years, high strength aluminum alloy sheets are used in the aeronautical and automotive industries for constructing body structures. However, joining this high-strength aluminum alloy during mass production is difficult by using conventional welding processes. The family of intense energy welding like plasma arc welding, electron beam welding, and laser beam welding is generally employed to weld the high-strength aluminium alloys. This study aims in evaluating and selecting the best intense energy welding process to produce high strength aluminum alloy joints for automotive application by using the Analytical Hierarchical Process (AHP). Thus, the proposed AHP model was also verified with SuperDecision v3.2 software.

Identification of effective factors to select energy recovery technologies from municipal solid waste using multi-criteria decision making (MCDM): A review of thermochemical technologies

Thermochemical technologies used to burn municipal solid waste are one of the relatively new and appropriate methods for waste management. By burning waste, heat and gases have arisen which can be used as the energy source to generate electricity. Due to the high cost, pollution emissions and diversity of such power plants, comprehensive studies are required. Therefore, the purpose of this study is to investigate the thermal methods in the field of waste management and to optimum for the most suitable methods. The selected thermochemical technologies include incineration, gasification, plasma, and pyrolysis. Data gathering was done through a questionnaire completed by experts. The decision-making models based on the Analytical Hierarchical Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are proposed to select the best thermochemical technology by the technical, economic, and environmental criteria. Ultimately, the environmental criteria (0.355), economic criteria (0.338) and, technical criteria (0.307) were introduced as the most effective criterion in choosing thermal methods respectively. The results of both AHP and TOPSIS models showed that the plasma method is the optimal thermochemical technology in terms of three existing criteria. Incinerator, gasification, and pyrolysis systems were ranked next.

Develop QFD and AHP Models for Liquid Gas Valve for Product Developmen

This new methodology utilizes Quality Function Deployment (QFD) with Analytic Hierarchical Process (AHP) together for improving product planning stage, hence, the product development, because this stage precedes the manufacturing stage and is regarded as an important stage in the product development. The proposed methodology consists of two models; namely: (1) Curent QFD Model. (2) Current AHP Model. It was applied practically to demonstrate the models' applicability and suitability, and develop liquid Gas Cylinder Valve produced at Al-Ikhaa General Company (IGC) for Mechanical Industries. "Thus it was possible to find out the critical and important specifications for improving product planning which should be considered in product development". These specifications have high ranking and Scaled Value Technical Ratings (SVTR) of over (50%). SVTR have values as follows: (1) (1.0000) for Pad (H1), then (2) (0.9270) for piston (H4), (3) (0.9195) for gasket (H12), (4) (0.8236) for safety valve (H6), (5) (0.8156) for sealing 1 (H5), (6) (0.6935) for sealing 2 (H9), (7) (0.5441) for installing the regulator with valve (H10) and (8) (0.5220) for spring2 (H7). When applying AHP method, various results were obtained. Based on the final score of Al-Ikhaa Company, where the highest defects value was (45%) was reported in the production processes. Also, values of maintenance dismantling 23%, Product assemblage 12% and maintenance assemblage 9% of the Product values.

Street foods: contemporary preference of tourists and its role as a destination attraction in India

PurposeThe study aims to assess and find out the preference of street-foods amongst the foreign tourists visiting India. It will also discuss in detail the important factors that lead to the selection of street-foods outlining the relevance of food as a destination attraction.Design/methodology/approachThe study applied the use of location intercept technique through one to one interview using a structured survey scale to take the responses from 586 outbound foreign tourists at the departure gates of International Airport at New Delhi. The street-food preference of foreign tourists was analysed using the analytical hierarchical process model and Chi-square statistics.FindingsThis study resulted in identification of 18 street-foods which were preferred mostly by the foreign tourist in India, with Tandoori Chicken tikka being the most favoured and Kathi Kebab being least preferred. This study also confirmed that amongst the all factors which were considered to have an influence on the street-food preference of foreign tourists only marital status was found to be insignificant.Practical implicationsThis study suggested that street-food vending can be considered to be a strategic management instrument that can (re)create a destination image and sustain or rejuvenate tourist movements towards a gastronomically rich destination like India. It might help the shareholders in the street-food vending businesses across India to devise strategies to showcase India on a global gastronomic platform.Originality/valueIt is the first study which has tried to exploit the foreign tourists’ emotions through their street-food preference which can be used by the local street vendors to attract, reconnect and increase their repeat visits in India. It will also help sensitising the local street-food vendors including restaurants, catering joints and hotels to include the preferred delicacies in their operational menus for maximising the earnings from tourists.

Análisis AHP de proveedores de servicio de cloud computing para organizaciones de educación superior en el Ecuador

Cloud Computing services provide dynamically scalable services through the Internet on demand, so the provisioning of services plays an important role when using them in enterprises. Business organizations in general, including educational ones, must be able to select the appropriate services according to their needs. This work briefly details the concept of Cloud Computing, the methodology for solving the problem in the selection of Cloud Computing services for Higher Education Organizations using the AHP (Analytical Hierarchical Process) model, where criteria were established such as type of service, service characteristics, technical support, network protection, web protection and virtual infrastructure. Finally, the results of the analysis of the instrument that shows the selection of the Cloud Computing service provider for Higher Education organizations in Ecuador are presented.