Analytic Hierarchy Process Technique Research Articles

Construction and application of standardized training effect evaluation system for new nurses in operating room

AbstractBackgroundThis study aims to develop and validate a Structured Training Effectiveness Evaluation (STEE) tool based on the Kirkpatrick model for newly graduated registered nurses in the operating room in China.MethodsThe first phase will involve focus group and individual interviews with nursing educators and newly graduated registered nurses selected using purposive sampling. The data will be analyzed thematically to identify key components necessary to develop the STEE tool. The second phase will develop and validate the STEE tool through a panel of experts using the Delphi method. The item weights will be determined with the analytic hierarchy process technique. The third phase will involve implementation and evaluation of the STEE tool with an exploratory, nonexperimental, and comparative analysis. Descriptive and inferential statistical analyses will be performed with SPSS version 23.ResultsThe STEE tool for newly graduated registered nurses in the operating room will be useful for evaluating training effectiveness during standardized training. The results obtained with this tool will clarify the effectiveness of training, thereby helping transform nursing students into competent nurses.ConclusionIn this way, this study will provide practical guidance for improving standardized training programs and help newly graduated nurses manage their transition to the clinical work environment and remain in their posts.

Attractiveness measurement of bai kuyao ethnic tourism attractors from the perspective of tourist perception

Named after the men donning white pants, Bai kuyao, a subgroup of the Yao ethnic community, preserves a substantial portion of its original ethnic heritage. The utilization of these ethnic traditions within the realm of tourism development has emerged as a pivotal concern. This study, initiated from the vantage point of tourists' perceptions, established an evaluative framework for assessing the attractiveness of Bai kuyao ethnic tourism. The framework was constructed through expert interviews and literature analysis. Utilizing the fuzzy analytic hierarchy process and IPA analysis techniques, the ethnic tourism appeal of Bai kuyao was quantified. The analysis of data disclosed that Bai kuyao's clothing culture, folk traditions, architectural heritage, and experiential activities hold considerable allure for tourists. However, tourists' overall satisfaction with their tourism experiences remains relatively low. The findings of this research offer valuable insights, serving as recommendations for the development and sustainable progression of tourism initiatives in Bai kuyao.

Application of Monte Carlo Analytic Hierarchy Process (MAHP) in Underground Mining Access Selection

This paper presents the application of risk analysis associated with the multicriteria decision method, through the MAHP (Monte Carlo analytic hierarchy process) technique for mining. As an example of application, the problem of choosing an access and transportation route for an underground mine is addressed. A decision can be made based on a technical, economic, and social-environmental approach. As a topic of interest for the modeling of mining projects, this work presents how the technique can qualify the decision-making process, reducing its subjectivity. It is verified that in comparison with the traditional AHP (analytic hierarchy process) method, the risk analysis allows considering the variability of weights and preferences assigned to criteria and options. In the example case, the following options are evaluated: shaft, ramp by diesel or electric truck, and conveyor belt.

Driver–passenger guidance model for Chinese freeway service areas based on path selection and parking delay

The driver–passenger guidance model proposed in this article is designed for large-scale freeway service areas that integrate various services such as shopping, leisure and catering. The model focuses on analyzing the impact of perceived travel distance and parking delay on path selection and parking space selection to optimize passenger flow efficiency. A perceived travel distance function is used to construct a pedestrian path selection model whose parameters are calibrated by a stated preference survey. An optimal parking space selection model is established based on the analytic hierarchy process-technique for order of preference based on similarity to the ideal solution method and considers parking distance, outdoor walking distance, indoor perceived travel distance after parking, and the impact of pedestrian crossings on parking delays. The model also calculates the vehicle arrival rate with parking time and the critical gap to ensure pedestrian safety. A parking delay calculation model is established based on the acceptable gap theory. The model is verified using the Yihezhuang service area of the Xiongan freeway as an example. The results show that the pedestrian path selection model improves passenger flow balance and reduces the variance in road passenger flow by 12% and per capita travel time by 9%. The proposed parking delay calculation model reduces parking delays by 30 s compared to models that do not consider pedestrian crossings, indicating its smoothness and convenience.

Geospatial investigation of site suitability for ecotourism development using AHP and GIS techniques in Uttara Kannada district, Karnataka state, India

The study aimed to spatially examine the viability and site suitability of ecotourism in the Uttara Kannada district, India. Karnataka is a fantastic destination for a variety of travel and has a lot of potentials to promote ecotourism, which has acquired popularity in recent years. Ecotourism is important to the conservation and safeguarding of biodiversity. Consequently, the current research aims to find potential ecotourism areas in the Uttara Kannada district, utilizing the analytic hierarchy process (AHP) and Geographical Information System-Remote sensing (GIS-RS) methodologies. The study is based on the application of GIS-RS factors for landscape naturalness, climatic features, accessibility parameters, topographic attributes, protected and reserved regions, and natural attractiveness in the GIS platform via a weighted overlay method. To analyze and appraise the ecotourism potential in the study area, the research uses satellite and weighted overlays of auxiliary data from AHP. As an outcome, 53.54 % of the highly suitable land was found over the forest regions and finally, the Unsuitable regions were mainly indicated over the miscellaneous area (47.46 %). The majority of the most suitable ecotourism sites that fall under category S1 are located in the Taluks like Joida (27 %) and Karwar (15 %). The outcome of this paper as expected is that very high and moderately suitable regions were initiated in the forest region. The study's findings and methodology will be useful to decision-makers and planners.

Modeling and Mapping of Groundwater Potential Zones of the Shewasoor Sub-Basin Using Analytical Hierarchy Process, RS and GIS Techniques in Kirkuk, Northeastern Iraq

Groundwater is considered one of the most vital natural resources for sustaining life. The demand for water in the Shewasoor sub-basin is constantly increasing due to formidable population growth and the development of human activities. Besides, groundwater is scarce due to climatic changes in arid and semi-arid. This study aims to determine spatial distribution of groundwater potential in the Shewasoor sub-basin. This study relied on seven layers (geology, slope, elevation, lineament, drainage density, soil, and land use/land covers) using geographic information systems, remote sensing, and applying the analytical hierarchy process method after determining the weights for each parameter by a multi-criteria decision analysis; to model the groundwater potential map in the Shewasoor sub-basin. The result appeared as a map of groundwater potential categorized into five zones. The majority of the sub-basin (61.8 km2) falls under a very high-high groundwater potential zone, which distributes over an area of elevations, drainage density, and slopes low of the Bai-Hassan Formation; from the center towards the north of the sub-basin. The moderate groundwater potential zone (47.6 km2) mainly encompasses an area of elevations and slopes moderate to the Bai-Hassan formation. About 49.6 km2 is a very low to low groundwater potential zone, mainly found over the area of the elevations and slopes high within the Mukdadiyah Formation east of the sub-basin; in addition to, low groundwater potential within the Bai-Hassan Formation in the south, west, and some part center of the sub-basin due of the elevations and slopes high.

Challenges of Smart Cities: Methods of Prioritization

Smart city development has gotten considerable recognition in systematic literature and international policies throughout the world. The study aims to identify the key barriers to smart cities from the review of existing literature and the views of experts in this area. This work further made an attempt on the prioritization of barriers to recognize the most important barrier category and ranking of specific barriers within the categories to the development of smart cities in India. Through the existing literature, this work explored 31 barriers to smart cities development and divided them into six categories. This research work employed the fuzzy Analytic Hierarchy Process (AHP) technique to prioritize the selected barriers. Findings reveal that ‘Governance’ is documented as the most significant category of barriers to smart city development followed by ‘Economic; ‘Technology’; ‘Social’; ‘Environmental’ and ‘Legal and Ethical’. In this work, author also performed sensitivity analysis to show how robust is the findings of study. This research is useful to the government and policymakers for eradicating the potential interferences in smart city development initiatives in developing country like India.

Examining and prioritizing the effect of sustainable energy on the job market to advance China's green workforce

China, the world's greatest emitter of greenhouse gases, has committed to reaching peak carbon dioxide emissions by 2030 and carbon neutrality by 2060. One strategy to accomplish this aim is switching to a low-carbon economy via advancing renewable energy (RE) projects. Therefore, this study focuses on solar, wind, biomass, and hydropower and examines the beneficial employment effects of RE projects in China. The study uses fuzzy-based Multi-Criteria Decision Making (MCDM) methodologies, such as the Analytical Hierarchy Process (AHP) and Weighted Aggregated Sum Product Assessment (WASPAS), to evaluate numerous employment effect criteria and sub-criteria. Based on these evaluations, the report prioritizes four main types of RE projects. According to the fuzzy AHP technique results, direct employment, skill requirements, and local employment are the most crucial employment effect factors. The study then employed the fuzzy WASPAS approach to assessing various RE initiatives' employment prospects. According to the findings, hydropower is the best choice for creating jobs, followed by wind and solar power initiatives. In recent years, the hydro, wind, and solar power industries have experienced rapid expansion, creating numerous job possibilities in production, installation, operation, and maintenance. Additionally, creating RE projects can boost regional economic growth and lessen poverty.

Determination of Ömerli Groundwater Potential using GIS Based Analytical Hierarchy Process (AHP) approach

Water, which is an indispensable element of human life, is a basic need for other living things and nature. Groundwater, which is the world's freshwater resource, has low cost usage opportunities because it is generally of good quality and does not need to be treated. Accordingly, in recent years, there has been an excessive increase in the use of groundwater due to the low rainfall and limited surface waters. Therefore, it has become important to know the hydraulic properties of the aquifer in the evaluation techniques of groundwater resources. It is important that the methods used in the evaluation are suitable for the structure of the aquifer in order to obtain healthy results. In support of these explanations, the AHP technique, one of the GIS supported MCDM methods, was used in order to reveal the underground water potential of the Mardin province Omerli district basin. Raster maps were first created in the GIS program ArcGis ArcMap environment, and then reclassified maps were produced. These data regarding the press study were obtained from official institutions and private drilling companies dealing with groundwater. In the first stage of the study, data related to groundwater potential such as static water level, dynamic water level, well yield, depth and residual were modeled. In the second stage, these data are weighted in AHP and then the result map; It was created and interpreted with very bad, bad, moderate, good and very good values. In the third and last stage, the results and recommendations are discussed.

THE APPLICATION OF ANALYTIC HIERARCHY PROCESS (AHP) FOR SELECTING COMMUNITY PROBLEMS: MULTICRITERIA DECISION- MAKING APPROACH ON ENVIRONMENTAL HEALTH ASPECTS

Addressing environmental health problems within communities necessitates an approach that considers multiple factors. A multicriteria method can identify useful decisions for carrying out alternative aspects of environmental health. This cross-sectional study illustrates the utility of the Analytic Hierarchy Process (AHP) technique, which is suitable for combining qualitative and quantitative factors across a wide area. This study aims to apply a multicriteria decision-making approach. Stakeholder opinions were collected and the Expert Choice software was utilised. The results showed that solid waste management was the most suitable alternative in addressing problems in the community, with a significance level of 34.3% (Consistency Ratio; CR ≤ 0.1). Other alternatives were wastewater management (26.8%), air pollution management (25.3%), water consumption and quality (8.1%), and food safety and sanitation (5.6%). This study recommends the use of AHP as a crucial tool for prioritising environmental management plans to allocate resources necessary to mitigate adverse environmental health aspects within the community

Introduction of a new index to assess pavement functional condition

AbstractFor most countries, the construction of the road network is completed to a great extent. As a result, the road operators have focused on the management of the current road constructions. The pavement management systems have been the determinative answer to the above need finding the optimal and more efficient solution which minimizes the maintenance cost. In this context, the present paper aims at the development of an index that assesses sections of road networks based both on the pavement essential demands and surface characteristics. This project presents a model for the rating of highway sections taking into consideration criteria and sub-criteria related to the pavement function. The developed model has been formed based on the opinion of a group of experts. The technique of the fuzzy analytic hierarchy process (FAHP) has been used to mathematically analyze the above opinions and manipulate uncertainty and subjectivity. This method ends up by calculating the weights of significance which are the factors of the index equation. The index is composed in combination with the variables which have come up from the regular measurements of pavement characteristics assessing the pavement functional condition. The results are compared to those of the regular AHP highlighting the degree of influence by the uncertainty of experts’ judgments in some factors of the index. Furthermore, the suitability and ease in the fitting of the FAHP method are verified in pavement management problems. In this project data related to the checks on surface characteristics in the National Highway Network are displayed.

Determining Priorities in Infrastructure Management Using Multicriteria Decision Analysis

This paper aims to form a concept of infrastructure management based on a multicriteria approach to determining management priorities. As the complexity of infrastructure construction and maintenance management requires looking at this problem from different aspects, the proposed multicriteria approach in this paper is based on the application of a two-phase analytical hierarchy process (AHP) method and technique for order of preference by similarity to ideal solution (TOPSIS) method. Using the two-phase AHP method, the process of determining the relative weights of the criteria is improved with the aim of providing better management of stakeholders as one of the essential preconditions for the success of the entire management process. In this way, it is desired to simulate the decision-making process as realistically as possible, in which the opinions and interests of all stakeholders are respected, but the key decision-maker is responsible for the final decision. Furthermore, with the help of the TOPSIS method, a ranking list of maintenance management priorities is formed, based on which it is possible to distribute limited financial resources intended for annual maintenance more rationally. The stability of the TOPSIS results was confirmed by a sensitivity analysis when changing the relative weights of the criteria. The proposed allocation of financial resources represents the basis for a better design of the maintenance management plan of the analyzed infrastructure elements, thus completing the observed gap in the existing literature. The aim of the above is to improve the planning function and at the same time to improve the implementation, monitoring, and control management functions, which creates a more efficient management system that can preserve the value of the analyzed infrastructure elements and extend their lifetime.

Leveraging IT for the Preservation of Baduy Indigenous Communities: A Digital Strategy by the Culture and Tourism Department of Lebak District

INTRODUCTION: The Lebak Regency Government and the Lebak DPRD in 2001 issued Regional Regulation No. 32 of 2001 concerning Protection of the Ulayat Rights of the Baduy Community. Disturbance to the preservation of the Baduy environment which consists of the natural environment and socio-cultural systems that depend on several factors, these factors are external (originating from outside the community) and internal (originating from within the community).
 OBJECTIVE: This research aim to analyze local wisdom in protecting the Baduy indigenous people and determine the most appropriate local wisdom strategy to implement.
 METHOD: The method used in this research is descriptive research method and strategy analysis using the Analytical Hierarchy Process (AHP) technique.
 RESULT: The results of the study show the dimensions that determine the application of local wisdom in the protection of the Baduy indigenous people by the Lebak Regency Culture and Tourism Office are the dimensions of local knowledge, local values, local skills, local resources, and elements of decision-making mechanisms. CONCLUSION: Strategy for Optimizing Local Wisdom in Protecting the Baduy Indigenous Community, the Lebak Regency Government, especially the Tourism and Culture Office, needs to take strategic steps by referring to digital-based policy strategy patterns by prioritizing the following dimensions: first, the dimension of local wisdom. local resources, second, the dimension of local skills, third, the dimension of local values, fourth, the dimension of decision-making mechanisms, fifth, the dimension of institutional support, and sixth, the dimension of local knowledge.

Evaluating the technical efficiency of Saudi Arabian telecommunications companies using window DEA and AHP techniques

PurposeThis study aims to evaluate the efficiency of the three telecommunications companies in Saudi Arabia: Saudi Telecom Company (STC), Mobily and Zain over the period of 2010–2019. This evaluation is a step toward improving the performance of the Saudi telecommunications sector.Design/methodology/approachThree multicriteria decision-making (MCDM) techniques were used to calculate technical efficiency. These techniques include the traditional data envelopment analysis (DEA), window DEA and analytical hierarchy process (AHP). The three inputs used were total assets, operating expenses and capital expenditures, whereas the two outputs were sales revenue and total stockholders’ equity.FindingsSTC was ranked first using the three techniques, followed by Zain, and then Mobily. According to the DEA window analysis, these three companies were all efficient only in 2012. The efficiency was high in the initial years, 2010–2013, when it was above 0.90, and it dropped below 0.90 in the subsequent years, 2014–2019. In addition, the efficiency of STC remained high, with an average of 0.990. However, the average efficiencies of Zain and Mobily during this period were 0.807 and 0.804, respectively.Originality/valueThis is the first study to use the three MCDM techniques to evaluate the performance of telecommunications providers. The results show that window DEA is better than the other two techniques at evaluating performance over time, as it has a higher discrimination power than either the traditional DEA or AHP.

Groundwater Potential Zones Assessment Using Geospatial Models in Semi-Arid Areas of South Africa

Water resources are under tremendous pressure as a result of the growing demand for water to meet human needs. Hence, it is necessary to delineate groundwater potential zones (GWPZs) to sustainably develop and manage groundwater resources. In this study, the geospatial-based analytical hierarchy process (AHP) and frequency ratio (FR) techniques were used to identify the GWPZs. Seven factors (geology, rainfall, slope, lineament density, soil, drainage density, and land use/land cover), which partially or entirely influence the groundwater potentiality of an area, were accessed separately and later combined to create GWPZ maps. Weights and ranks were assigned to the factors to perform the AHP model using existing knowledge. The FR was performed by calculating the percentage ratio between the dependent variable (boreholes) and the independent variable (factors). The preparation of the contributing factors and the creation of the resulting models was done using ArcGIS 10.8. The final GWPZ maps were classified into five zones: very low, low, moderate, high, and very high. About 80 boreholes in the study area were randomly subset into training and testing datasets; 58% were used for model training, and the remaining 42% were used for validation purposes. The receiver operating characteristic (ROC) curves for the GWPZs models were generated, and the areas under the curves (AUC) were calculated. Validation of the models shows that the FR model is more efficient (85.3% accuracy) than the AHP model (83.2% accuracy). The findings show that the AHP and FR models are reliable and can be adopted to characterize GWPZs in arid or semi-arid environments.

Ordering vs. AHP. Does the intensity used in the decision support techniques compensate?

The manifestation of the intensity in the judgment of one alternative versus another in the peer comparison processes is a central element in some decision support techniques, such as the Analytical Hierarchy Process (AHP). However, its contribution regarding quality (expected performance) with respect to the priority vector has not been evaluated so far. Using the Intentional Bounded Rationality Methodology (IBRM), this work analyzes the gains obtained from requiring the decision-maker to report an intensity judgment in pairs (AHP) with respect to a technique that only requires expressing a preference (Ordering). The results show that when decision-makers have low levels of expertise, it is possible that a less informative and computational cheap technique (Ordering) performs better than a more informative and computational expensive one (AHP). When decision-makers have medium and high levels of expertise, AHP technique obtains modest gains with respect to the Ordering technique. This study proposes a cost-benefit analysis of decision support techniques contrasting the gains of a technique that requires more resources (AHP) against other that require less resources (Ordering). Our results can change the managing approach of the information obtained from experts’ judgments.

Sustainability assessment of energy supply scenarios: case study of Mali

Mali is endowed with significant untapped renewable energy potentials paradoxically the country is identified as an energy-poor nation characterized by very high dependency on imports of petroleum products and heavy reliance on biomass (wood-fuel and charcoal). Access to electricity remains very low, with significant disparities across urban and rural remote areas. The gap between the electricity demand and supply keeps increasing yearly, and power shortages get frequent and longer, especially during dry periods from March to June. The energy demand increase, due to of population grow and rapid urbanization (causing more use of fossil fuels resources in the energy mix) bears the unsustainability of the country’s current energy supply. The challenge for the country is then to meet this growing energy demand with a sustainable energy supply system. In the present work, Analytical Hierarchy Process technique is applied to perform Multicriteria Decision Making analysis to identify and assess the most sustainable long-term energy supply options in Mali considering technical, environmental, social, and economic dimensions. The current situation and five alternatives of energy supply based on the country’s current and future energy supply and climate change policies are proposed for assessment. Results show that the highest priority indicators by stakeholders’ survey are under economical dimension followed by the technical ones. The best scenario considers deploying renewable energy to up to 42% of the energy mix as the sustainable option for energy supply. Adopting such scenario requires measures as a strong political will to subsidize renewable energy equipment in order to make them affordable and also policies that encourage the use of renewable energy (such as lower taxes and duties). The suggested framework gives decision-makers, authorities, practitioners, and researches an effective tool for the country future energy planning.

Flood Susceptibility Assessment and its Management in Malda District of West Bengal through Geospatial Technique

Flood is one of the most popular natural hazards that create havoc in the society. Flood involves inundation of a huge tract of area under water owing to heavy rainfall. Occurrence of flood lays a severe impact upon the agricultural sector. Flood not only brings about destruction of crops but also brings down the productivity of the soil. Malda district of West Bengal is not an exception in this regard. The district is one of the most flood prone districts and involves a lot of loss in crop production. The present study aims to identify the flood susceptible zones of the district through the application of Analytical Hierarchy Process and geospatial techniques and also makes an attempt to detect how much cropland falls within the very high susceptible flood prone area so that proper precautionary measures can be taken to minimize the maximum damage. The study results reveal that the western part of the district is more flood prone and about 55.27% of very high flood prone area is dominated by croplands. Hence, proper flood management techniques have to be adopted in this area to reduce the loss of production of crops owing to floods.

Dissolved Gas Analysis of Transformer: An Approach Based on ML and MCDM

In the electric power business, power transformers are one of the most common and expensive components. The conventional diagnostic tool for understanding insulation incipient failures is the dissolved gas analysis (DGA) of transformers. Nonetheless, interpreting DGA fault gases remains a significant difficulty for engineers. Along with offline methods, a number of computational approaches have been created for DGA fault classification. Still there exist significant hurdles in applying those methods for DGA fault classification. To establish an effective fault classification system, very diversified and massive DGA data sets of in-service transformers were collected from various utilities for this study. The dataset consists of 3147 instances with four classes: No fault, Thermal fault, Low energy discharge and high energy discharge. Models were built using various machine learning approaches like Quadratic Discriminant Analysis (QDA), Gradient Boosting (GB), Extra Trees (ET), Light Gradient Boosting Machine(LGBM), Random Forest (RF), K Nearest Neighbors (KNN), Naive Bayes (NB), Decision Tree (DT), Ada Boost (AB), Logistic Regression (LR), Linear Discriminant Analysis (LDA), Ridge Classifier, and SVM - Linear Kernel. The proposed work adopts Analytic Hierarchy Process (AHP) technique for the estimation of weights of the criteria. Based on the generated weights, the performance of the various classifiers is assessed and ranked using Multi-Objective Optimization based on the Ratio Analysis (MOORA) approach. QDA is selected as the best classifier model by the proposed technique.

Ranking load in microgrid based on fuzzy analytic hierarchy process and technique for order of preference by similarity to ideal solution algorithm for load shedding problem

<span lang="EN-US">This paper proposes a method to rank the loads in the microgrid by means of a weight that combines the criteria together in terms of both technical and economic aspects. The fuzzy analytic hierarchy process technique for order of preference by similarity to ideal solution (fuzzy AHP TOPSIS) algorithm is used to calculate this combined weight. The criteria to be considered are load importance factor (LIF), voltage electrical distance (VED) and voltage sensitivity index (VSI). The fuzzy algorithm helps to fuzzy the judgment matrix of the analytic hierarchy process (AHP) method, making it easier to compare objects with each other and remove the uncertainty of the AHP method. The technique for order of preference by similarity to ideal solution (TOPSIS) algorithm is used to normalize the decision matrix, determine the positive and negative ideal solutions to calculate the index of proximity to the ideal solution, and finally rank all the alternatives. The combination of fuzzy AHP and TOPSIS algorithms is the optimal combination for decision making and ranking problems in a multi-criteria environment. The 19-bus microgrid system is applied to calculate and demonstrate the effectiveness of the proposed method.</span>