Analytic Hierarchy Process Technique Research Articles

Flood vulnerability assessment in the flood prone area of Khyber Pakhtunkhwa, Pakistan

Floods are among the most destructive natural disasters, causing extensive damage to human lives, property, and the environment. Pakistan is susceptible to natural calamities, such as floods, resulting in millions of people being impacted yearly. It has been demonstrated that flood severity is rising and may continue to escalate in the coming years because of climate change-induced changes in monsoon precipitation in the country. Given the country’s exposure to flooding, it is essential to assess the vulnerability to floods to prepare for and mitigate their impact in Pakistan. This study provides a new conceptual framework for assessing flood risk and vulnerability in Charsadda, a flood-prone district in Pakistan. It evaluates the vulnerability of settlements to floods based on four indicators: population density, the average gross domestic product (GDP) of land, the distance between settlements and rivers, and land use and cover (LULC). The analytical hierarchy process (AHP) technique was integrated with the geographical information system (GIS) to assess the level of vulnerability to floods in the study area. The results reveal a higher degree of vulnerability to floods in the region. The spatial pattern of vulnerable areas reveals a significant connection between high-risk flood areas and densely populated areas during different flood seasons. The results further reveal that more than 60% of the area is arable land and is highly susceptible to flood. The population and their land-use setup show high and extremely high values of vulnerability in the normalized threshold of 0.3–0.4, respectively. The study provides an in-depth and comprehensive analysis of the chosen indicators, evaluation methods, and results, making this a valuable contribution to the field of flood vulnerability assessment. The findings of this study also include thematic maps and related information to the stakeholders for effective vulnerability management in the study area.

Groundwater delineation for sustainable improvement and development aided by GIS, AHP, and MIF techniques

Exploration of groundwater is an integral part of viable resource growth for society, economy, and irrigation. However, uncontrolled utilization is mainly reported in urban and industries due to the increasing demand for water in semi-arid and arid regions of the world. In the background, groundwater demarcation for potential areas is vital in meeting necessary demand. The current study applied an integrated method comprising the analytical hierarchy process (AHP), multiple influence factors (MIF), combined with a linear regression curve and observatory well data for groundwater prospects mapping. Thematic maps such as flow direction, flow accumulation, elevation map, land use land cover, slope, soil texture, hill shade, geomorphology, normalized vegetation index, and groundwater depth map were generated utilizing remote sensing techniques. The relative weight of each parameter was estimated and then assigned to major and minor parameters. Potential zones for groundwater were classified into five classes, namely very good, good, moderate, poor, and very poor, based on AHP and MIF methods. A spatially explicit sensitivity and uncertainty analysis method to a GIS-based multi-criteria groundwater potential zone model is presented in this research. The study addressed a flaw in the way groundwater potential mapping results are typically presented in GIS-based multi-criteria decision analysis studies, where discrete class outputs are used without any assessment of their certainty with respect to variations in criteria weighting, which is one of the main contributors to output uncertainty. The study region is categorized based on inferred results as very poor, poor, marginal, and very good in potential ground quality 3.04 km2 is considered extremely poor, 3.33 km2 is considered poor, 64.42 km2 is considered very good, and 85.84 km2 is considered marginal zones, which shows reliable and potential implementation. The outcomes of AHP and MIF were validated by linear regression curve and actual water table in a study area. The study results help to formulate the potential demarcation of groundwater zones for future sustainable planning and development of groundwater sources. This study may be helpful to provide a cost-effective solution to water resources crises. The current study finding may be helpful for decision-makers and administrative professionals for sustainable management of groundwater resources for present and future demands.

Developing a causal framework of internet of things adoption barriers for agile manufacturing in post COVID-19

In order to remain competitive in a post-COVID-19 scenario, manufacturing organizations should use the pandemic scenario as a lever to make IoT adoption more agile and faster by reinventing their business models. Although, IoT has vast potential in multiple sensors’ direct integration without human intervention, its adoption has observed significant barriers during COVID-19. In this context, the current research aims to identify, prioritize, categorize, and investigate inter-dependencies among the significant barriers to adopting IoT technologies in the manufacturing industry. The analysis used two-stage integrated AHP-TOPSIS (Analytical Hierarchy Process-Technique for Order Preference by Similarity to Ideal Solution) and ISM (Interpretative Structural Modeling) techniques. For AHP and ISM techniques, a group of 8 experts from academia and industry with at least 10 years of experience was surveyed to capture their perceptions. Whereas, for TOPSIS, data were collected from 433 operational-level users. The research discloses that the significant driver barriers that hamper the adoption of IoT technologies are: poor internet infrastructure, high adoption & operating costs and lack of government regulations. This study will assist practitioners, decision-makers and organizations in understanding the significant barriers to seamless IoT implementation.

Agricultural land suitability analysis of Southern Punjab, Pakistan using analytical hierarchy process (AHP) and multi-criteria decision analysis (MCDA) techniques

Agricultural land suitability analysis of Southern Punjab, Pakistan using analytical hierarchy process (AHP) and multi-criteria decision analysis (MCDA) techniques

Application of Analytic Hierarchy Process and Simple Additive Weighting in Designing The Best Employee Selection Decision Support System at PT Pos Indonesia

The purpose of this study is to compare the best employee evaluation outcomes using the analytical hierarchy process (AHP) technique and simple additive weighting (SAW) method as a support system for best employee suggestions. The author employed four different approaches for gathering data for this study: literature studies, interviews, observation, and similar literature studies. The RAD paradigm is being used in the development of this decision support system (DSS). The unified modeling language, or UML, tool is used in this system development methodology. It's time to put the system into action after it has been designed and analyzed. The black box testing methodology will be used for the experiments. Based on the research results, it was found that this system was able to assist decision makers in providing employee assessments quickly and precisely according to the predetermined time, whereas previously managers were always late and exceeded the time limit when assessing employees. The output of this system is that it can provide direct reports to the employees being assessed to find out the results of the scores obtained and make decisions about selecting the best employees. A decision support system for employee performance assessment uses the PHP and MySQL programming languages as the database. AHP and SAW methods, rapid application development (RAD) system development methods, and system testing with black box testing.

Delineation of environmentally sustainable urban settlement using GIS-based MIF and AHP techniques

Choosing appropriate locations for built-up growth while maintaining natural balance has become necessary for sustainable urban planning. To this end, two multi-criteria decision-making (MCDM) approaches—the multi-influencing factor (MIF) and the analytical hierarchy process (AHP)—have been applied in this work. The MIF model results show that 23.546% of the study region was very highly suitable for newly built-up areas, and 18.786% was restricted for urban settlement, whereas, in the AHP model, 28.907% of the area was highly suitable, 17.619% was restricted for urban settlement. Finally, the dependability and efficiency of the two models used for the study area were assessed through the receiver operating curve (ROC) and area under curve (AUC) analysis. The comparative analysis demonstrates that the MIF approach (AUC 0.817) is more suitable and reliable than the AHP (AUC 0.783). The present work provides new insights to integrate GIS tools with MCDM for practical urban land suitability assessment.

Evaluation of entrepreneurship failure education in higher education from the perspective of the CIPP model and AHP-FCE methods

Entrepreneurial failure education aims to equip entrepreneurs with the knowledge and skills necessary to navigate entrepreneurial setbacks and enhance their ability to manage failure effectively. The evaluation system of EFE is a crucial tool to estimate the development of entrepreneurial failure education (EFE) in universities and colleges, which ensures the high-quality development of EFE in universities and colleges. Based on the concept of EFE in universities and colleges, we built an evaluation index system of entrepreneurship education in universities and colleges in the context of the CIPP model. In addition, an evaluation model of EFE in colleges and universities was constructed by employing the fuzzy comprehensive evaluation (FCE) and analytic hierarchy process (AHP) technique. Moreover, the sample data from five universities in Hebei, Shanxi, and Jiangsu were chosen for evaluation research. The findings indicated that the EFE in higher education institutes was typically in an "average" state; the status of context, input, process, and product were relatively "strong", "very weak", "average", and "relatively weak". Thus, universities and colleges must strengthen the management ability of entrepreneurial failure, support the development of teachers, enhance the cultivation of entrepreneurial practice ability, construct the curriculum system of EFE in universities and colleges, and execute the implementation of entrepreneurial policies. This study provides an effective evaluation tool for EFE in colleges and universities and an essential reference for the quality of EFE in colleges and universities.

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

GIS-Based Multi-Criteria Decision Analysis (MCDA) and Analytical Hierarchy Process (AHP) Techniques to Derive Flood Risks Management on Rice Productivity in Gishari Marshland

A model to define a real estate investment risk index for the administrative municipalities of Naples

Real estate redevelopment processes represent an important avenue for achieving sustainable development goals, but at the same time, they pose complex and opaque decision-making problems. Most existing risk assessment tools involve aggregate-scale analysis or require knowledge of extensive project financial data, which is often not yet available under ex-ante evaluation conditions. The aim of the work is to define a specific index through a spatial decision support system based on an innovative model that enables public and private entities to conduct effective ex-ante risk assessment at a sub-municipal territorial scale for public-private partnership risks. The proposed model adopts the flexibility of the Analytic Hierarchy Process (AHP) technique and the GIS system’s ability to clearly display the spatial distribution of real estate risk.

Safeguarding Financial Integrity with Interval-Valued Neutrosophic Analytic Hierarchy Process for Sustainable Accounting Systems

Nowadays, financial integrity within sustainable accounting systems is critical endeavor in ensuring intricate landscape of sustainable finance. Detection of financial fraud within sustainable accounting systems is crucial for upholding environmental, social, and governance (ESG) standards and sustaining the integrity of financial practices. Leveraging advanced AI-driven technologies, these systems can effectively analyze abundance of financial data to detect suspicious patterns and anomalies indicative of fraudulent activities. Incorporating Neutrosophic logic into sustainable accounting systems improves the efficiency of financial fraud detection by accommodating inherent uncertainty in complex financial data. By leveraging this ground-breaking technology, organizations can effectively navigate the complex financial landscape while ensuring the integrity of their accounting practices. Neutrosophic logic facilitates the modelling of contradictory and ambiguous information, enabling more nuanced detection and analysis of fraudulent activities that may remain unnoticed. This study develops an automated financial fraud detection using improved sparrow search algorithm with Interval-Valued Neutrosophic Analytic Hierarchy Process (ISSA-IVNAHP) technique. The ISSA-IVNAHP technique aims to protect financial integrity via the identification of financial frauds in Sustainable Accounting Systems. The ISSA-IVNAHP technique incorporates a two-stage process. Initially, the ISSA-IVNAHP method designs ISSA-based feature subset selection approach for the optimal feature selection. Next, in the second stage, the ISSA-IVNAHP technique uses IVNAHP technique for decision-making process that enables to detection of the presence and absence of financial fraud. The simulation results of the ISSA-IVNAHP technique can be examined on financial fraud database. The experimental values reported that the ISSA-IVNAHP methodology attains maximum effeciency over other models

Critical success factors of blockchain technology adoption in banking and financial sector using diamond fuzzy AHP

Blockchain technology is creating significant interest among a wide range of industries in the world due to the continuing applications in the banking sector. Thus, the aim of this research is to introduce an outline for examining critical factors that affect the success of the adoption of Blockchain-technologies in the sector of Finance and arranges them using the fuzzy analytical hierarchy process technique. First, it identifies thirteen critical success factors under three categories: technological, organizational, and environmental, taking the assistance of the extensive literature review and expert-opinion. Then, these factors are given a ranking that is based on their relative weightage. It is concluded that top management attitude, organization readiness, government regulation, immutability, and disintermediation are the detrimental factors for widespread blockchain adoption. The findings of this study will empower the stakeholders in the financial sector to improve their performance using blockchain technologies.

Enhancing healthcare security measures in IoTT applications through a Hesitant Fuzzy-Based integrated approach

<abstract> <p>Due to their impact on transportation, Internet of Transportation Things (IoTT) devices have garnered attention recently. Their most notable use is in healthcare, where transportation has been significantly influenced by Internet of Things (IoT) devices. However, threats to infrastructure integrity, medical equipment vulnerabilities, encryption, data integrity threats, and various other security issues make these devices particularly vulnerable. They transmit a considerable amount of sensitive data via sensors and actuators. Given their susceptibility to various attacks, securing the application security of IoTT is crucial. Consequently, IoTT device-based applications must undergo thorough security screening before integration into the healthcare network. Additionally, the authentication technique employed must be robust and reliable. IoTT device evaluation should be impartial and take into account security risk issues. This study proposes an evaluation approach for IoTT devices that utilizes key security risk factors to ensure reliable and secure authentication. Employing hybrid multicriteria decision-making, the suggested strategy evaluates authentication features to select the optimal hospital information system. The hesitant fuzzy analytic hierarchy process-technique for order of preference by similarity to ideal solution (Hesitant Fuzzy AHP-TOPSIS) method is used to systematically examine security risks in a real-time case study with seven alternatives. Results indicate that mediXcel electronic medical records are the most viable, while the Caresoft hospital information system is the least viable, providing valuable insights for future studies and IoTT application professionals. This research addresses security issues to enhance patient data integrity and privacy, facilitating the seamless integration of IoTT applications into healthcare, particularly in emergency healthcare.</p> </abstract>

Flood hazard zonation using GIS-based multi-parametric Analytical Hierarchy Process

Flood is considered to be a serious environmental hazard, especially in the tropical countries owing to its devastating consequence on human life. Tripura, a small hilly state of northeast India has faced large scale flood events over the last few decades. The present study is an attempt to identify flood hazard zones along the lower course of the Dhalai River flowing through the Dhalai district of Tripura State. An integrated approach of remote sensing and GIS coupled together with Analytical Hierarchy Process (AHP) was applied to identify the flood hazard zones of the study area and nine parameters were selected for this purpose. Thematic maps of the parameters were reclassified after assigning ranks to different classes. A pair-wise comparison matrix among all the parameters was prepared using AHP to determine the relative weight of each parameter. Finally, flood hazard zoning (FHZ) map of the study area was prepared by multiplying the reclassified values with the weighted values using raster calculator of Arc GIS 10.1. The outcome of the study revealed that 109.69 km2 (27.65%) of the study area fall under low flood risk category. At the same time, around 114.46 km2 (28.85%) and 90.43 km2 (22.80%) areas fall under moderate and high flood risk zone respectively. The study also disclosed that the high risk zone has maximum concentration of agricultural land (68.63%) and settled area (9.77%) in comparison to the other two zones which has increased vulnerability of flood hazard. The results validated the efficiency of AHP technique in generating fast and cost effective information regarding flood hazard assessment, especially in no data regions. Hence, the derived information could be very much helpful for the planners to prepare proper strategies to reduce the vulnerability of this hazard.

Delineation of groundwater potential zone using geospatial tools and analytical hierarchy process (AHP) in the state of Uttarakhand, India

Groundwater plays a vital role in global climate change and substantial human needs. However, the groundwater potential zone (GWPZ) delineation is essential for fulfilling livelihood needs. In recent years, studies based on geographic information systems (GIS) have acquired much attention in groundwater exploration. Thus, in order to determine the groundwater potential zone in the state of Uttarakhand, we employ a multi-criteria decision analysis (MCDA) based analytical hierarchy process (AHP) model with overlay weighted linear combination approach in this study. For groundwater potential zone demarcation, nine thematic layers such as geology, geomorphology, LULC, drainage density, slope, rainfall, soil, TWI, and curvature were created using remote sensing (RS) images and conventional data for a geographic information system (GIS). Furthermore, the weight of the parameters has been determined using AHP technique and overlay analysis was determined using GIS tools. A thematic map was categorized as “very poor,” “poor,” “moderate,” “good,” “very good,” and “excellent” in order to determine the groundwater potential zone. According to the results, the area covered by the 'very poor' categories is 187.43 km2 (0.16 %) followed by 'poor' 2109.66 km2 (3.99 %), 'moderate' 29024.06 km2 (54.78 %), 'good' 15151.13 km2 (28.67 %), 'very good' 6537.19 km2 (12.37 %), and 'excellent' 814.84 km2 (1.55 %) with the accuracy of 89.9 %. The 'very poor' and 'moderate' groundwater potential zones were observed as 0.16 % and 54.78 %, respectively, and the possibility for GPZ gradually increased from the northeast to the southwest. The findings of this study have implications for future research on sustainable groundwater use, basin management of agriculture, and the link between groundwater and climate change.

Investigation for the optimum selection of hybrid AA2024 – ceramic particulate alloy composite materials prepared through stir casting using the hybrid AHP-TOPSIS MCDM technique

ABSTRACT In most of the manufacturing industries, the selection of optimal material among the finite available alternatives becomes more difficult with the more required performance criteria to satisfy certain objectives. In such scenarios, Multi-Criteria-Decision-Making (MCDM) techniques, such as hybrid AHP (Analytical hierarchy process) – TOPSIS (Technique for Order Preferences by Similarity to Ideal Solution) and others assist in quantitative decision-making by accounting for qualitative human judgments. The present work illustrates the application of a hybrid AHP-TOPSIS technique to the ranking of alloy composites. The properties defining data such as physical, mechanical, thermal, thermo-mechanical, etc. are weighted using the AHP technique; thereafter, relative weights are used to rank the alloy composite compositions by the TOPSIS method. The compositions comprise the AA2024 alloy as the matrix phase and the reinforcing phase consists of silicon carbide, silicon nitride and graphite particulates. The ranking analysis orders are consistent with subjective analysis.

Sustainable planning and design for eco-industrial parks using integrated multi-objective optimization and fuzzy analytic hierarchy process

ABSTRACT The increasing growth of industrial facilities calls for sustainable planning and design. In this research, the multiple objective optimization model is developed to plan for Eco-Industrial Parks, in which economic, social, and environmental criteria are evaluated. Our proposed optimization model is integrated with the simulation-based risk profile based on emergency scenarios. Varied chemical substances and explosive locations are further analyzed to assess the impact of risk. Then, the Fuzzy Analytic Hierarchy Process technique is applied to examine uncertain decisions. Next, this study presents the proposed model with the case study of selective industrial-building types in an industrial park, in which industrial plants, hazardous material plants, warehouse buildings, and office space are included. Our analysis reveals that tradeoffs exist in designing an industrial estate with various industrial plants under conflicting objectives. Finally, tradeoffs are investigated using Pareto analysis resulting in sustainable planning for an industrial estate.

Groundwater potentiality mapping: A case study in Baba and Sidri watersheds, South Sinai, Egypt

Groundwater potential zone (GWPZ) mapping is a multi-parameters approach that can assess the groundwater potentiality in mountainous terrain and coastal areas. This approach utilizes the geomorphology, lithology, rainfall, structure lineaments density, drainage density and slope which are the major effective factors controlling the groundwater potentiality. Primarily, these factors are prepared in the form of thematic layers using GIS technique, and then assigned different weights for these thematic layers using Analytical Hierarchy Process (AHP) technique to explore the GWPZ. This GWPZ is generated by the linear weighted sequence of all the prepared thematic layers. The moderate GWPZ (41.8%) sites are located in the main Wadi channels and alluvial fan at western portion; whereas, the high GWPZ (29.8%) concentrates in Homaier depression at the eastern region. Vertical electrical soundings (VES) and time-domain electromagnetic soundings (TEM) measurements have been achieved at high GWPZ to estimate depth and thickness of both saturated and unsaturated areas with water. This geophysical investigation has been done to confirm and support the effectiveness of applied factors of GWPZ mapping. The findings of these measurements are validated by standardizing the measured electrical resistivity values with the sequential layering layout and data records for five wells drilled at the locations of the geophysical soundings. VES and TEM data show the existence of moderately thick adjacent aquifers, covered with a dry area of different thicknesses (18–50 m). The aquifer units with thickness ranging from 43 to 71 m has resistivity values of 22–50 Ω m which is an indicator of freshwater content.

Benefits, enablers and barriers in deploying PPP when developing smart infrastructure in non-urban areas

PurposeThe widespread lockdown restrictions brought by the global COVID-19 epidemic inculcated a culture of “work-from-home”. However, most rural areas lack reliable and effective community amenities including transportation, health and education, thereby impeding healthy living and productive employment. Therefore, the underlying goal of this research is to investigate the development of smart infrastructure (SI) in non-urban areas. However, governments' resource limitations must be addressed to develop SI, which urges the research on the potential for public-private partnerships (PPP) to supplement public sector resources when necessary.Design/methodology/approachThis paper examined and evaluated the “benefits and enablers” and “barriers” to deploying PPPs to create SI in non-urban areas, using a thorough literature review, five expert interviews and analytic hierarchy process (AHP)-based questionnaire responses. The AHP technique and content analysis were used to analyse the results and generate the conclusions.FindingsThe availability of a favourable investment climate and legal framework were identified as the significant factors among the “benefits and enablers” of adopting PPP in SI developments in non-urban areas, while low community acceptance of the private sector involvement, and community culture and values were identified as the significant factors among the “barriers”. These highlight the significance of removing barriers connected to community culture and “values”.Originality/valueThe findings and conclusions of this study provide a strong foundation to support the growth of SI in non-urban settings, facilitating more sustainable development that is more evenly distributed in the post-COVID-19 future.

Risk of Land Degradation: A Case Study of Phu Yen Province, Vietnam

The issue of the land degradation vulnerability index (LDVI) is multifaceted, encompassing climate, soil, vegetation, policy formulation, and human actions. In Vietnam, the convergence of climatic fluctuations and human impact results in phenomena, such as soil sealing, erosion, salinization, and landscape fragmentation. These phenomena are recognized as significant triggers of land degradation. This paper seeks to present a method for assessing a land's susceptibility to degradation by utilizing ten ecological 10 criteria: NDVI; slope; bulk density (cg/cm3); cation exchange capacity in the soil (CEC; mmol(c)/kg); Soil organic carbon stock (SOC; dg/kg), pH; Nitrogen (N; cg/kg); soil thickness (cm); soil surface temperature LST (0C); precipitation of the driest quarter (mm). The research results show that Song Hinh and Son Hoa communes are standing on the most land degradation vulnerability. Some criteria that are considered important in assessing land degradation by the analytic hierarchy process (AHP) technique are NDVI, followed by slope, nitrogen, bulk density, and soil thickness. The results of the study are consistent with records in localities that are often under pressure from drought. Extreme LDVI areas were larger identified on low mountains, slope terrain, and precipitation of driest quarter under 200mm, expanding on the agricultural areas with 40km2 total province agriculture area, followed by grassland (20.3 km2), natural forests (17.2 km2), plantation forests (8.2 km2), residences (8.2 km2), and bare land (8.15 km2). Poor land management practices, such as improper construction, inadequate water management, and lack of terracing, can contribute to soil erosion and land degradation. This LDVI assessment process can be applied to some tropical countries. The NDVI index combined with the slope, nitrogen, bulk density, and soil thickness can be exploratory indicators of land sensitivity to land degradation.

Analysis of factors and strategies for the implementation of sustainable tourism in a green economic structure in China

The tourism industry significantly contributes to the economic development of numerous emerging countries by facilitating the expansion of local enterprises. However, tourism may adversely affect the environment, local communities, and cultural heritage when it is not managed effectively. In this study, the case of Guilin city of China is undertaken for the analysis. Guilin, a popular tourist destination in southern China, has experienced rapid growth in tourism, generating economic benefits but also posing challenges related to environmental sustainability and social impact. This study uses Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify the most important criteria, sub-criteria, and effective policy strategies for promoting sustainable tourism in developing economies. Therefore, the study identified five criteria, twenty sub-criteria, and six policy strategies for sustainable tourism development in Guilin, China. The results of Fuzzy AHP method has identified economic viability, infrastructure and services, and social and cultural impact are the most suitable criteria for sustainable tourism. The results of Fuzzy TOPSIS method has recognized community-based tourism, sustainable tourism certification, and public-private partnerships as most effective strategies. This research provides useful insights for policymakers and stakeholders, enabling them to contribute to the sustainable development of the tourism industry and support the achievement of the United Nations sustainable development goals.