AHP Approach Research Articles

An AHP approach to airport choice by freight forwarder

An AHP approach to airport choice by freight forwarder

Selection of Industrial Sites Using a Web-Based Geographical Information System to Minimize Risks: A Case Study in West Java, Indonesia

The efficient selection of a perfect site for the development of an industrial site in spatial planning should consider the land condition and environmental factors to minimize the impacts and risks. This paper aimed to create a model to assess if an area that can be used for the development of an industrial site meets multiple criteria. The new method in this research integrates the GIS and AHP approaches into a web-based geographic information system application that is used to easily support widespread assessment and mapping. The assessment of the development potential of industrial areas in West Java Province showed that 77% of the land was appropriate for industrial sites, whereas the other 33% was less suitable for use as an industrial site location. The assessment of 23 industrial site development location points in the Industrial Site Spatial Plan of West Java Province showed that 14 locations were in the highly suitable category (P1) and 9 other locations were in the suitable category (P2).

Development of an Intelligent System to Determine Land Suitability for Horticultural Crops on Vegetable Commodities

Global climate change has a significant impact on the agricultural sector, including horticulture, with climate fluctuations such as increased temperatures and changes in rainfall patterns potentially affecting crop productivity. Sustainable horticultural agriculture is important for safeguarding natural resources and reducing environmental impacts. However, challenges from climate change and variations in land conditions can affect horticultural crop production. Identifying crops that are suitable for the climate and land conditions is key to agricultural sustainability. An intelligent and adaptive approach is needed in selecting the right crops to grow in the face of climate change. This research develops an artificial intelligence application for the recommendation of horticultural crop types according to land conditions and climate change. The model built involves AHP and MFEP methods. The model takes into account various land parameters with weights determined through the AHP approach, allowing this AI application to provide accurate recommendations based on data and modeling. Based on the tests conducted, the system was able to produce analysis with an accuracy rate of 85%.

3D Printer Technology Selection in Rapid Prototyping: A Spherical Fuzzy AHP Approach

The aim of this study is to make the best technology decision for an enterprise in the automotive sector that plans to purchase a 3D printer for the purpose of obtaining rapid product prototypes. The study includes seven criteria as accuracy, complex design, surface quality, ease of use, throughput, material cost, and equipment cost, and three alternative technologies as fused deposition modeling (FDM), selective laser sintering (SLS), and stereolithography (SLA). The weighting of the criteria has been carried out by three experts in the product development department, and the evaluation of alternatives has been carried out by a team of 3D printer manufacturers. The spherical fuzzy analytic hierarchy process (SF-AHP) method is applied in the study. It’s considered important for making the right technology decision in product development processes since this study seeks a solution to a real problem. As a result of the study, while the accuracy criterion is the highest priority, the ease of use of the selected printer is the least priority criterion. On the other hand, SLA 3D printer technology has been seen as the most ideal technology in terms of many criteria for prototyping automotive plastic material parts.

Determining The Main Criteria Required for The Green Transition of The Maritime Industry in Terms of MTME

In this study, the main criteria for the green transition of the maritime industry have been determined, taking into account the criteria determined by the International Maritime Organization (IMO) for the year 2050 and beyond. The criteria were prioritized using an AHP approach and the DEMATEL technique. The aim of the study is to determine whether the green conversion can meet the operational requirements of merchant ships. For this purpose, quantitative and qualitative research techniques were used as a hybrid. The ultimate goal of the study is to evaluate the impact of merchant ships, which will be built in the green concept, on the operational needs, within the framework of maritime transportation management engineering (MTME). At the end of the study, a gradual roadmap was presented to the maritime industry, which will prepare a strategic target plan within the scope of the green transition of the maritime industry.

Integrated Spatial Analysis of Forest Fire Susceptibility in the Indian Western Himalayas (IWH) Using Remote Sensing and GIS-Based Fuzzy AHP Approach

Forest fires have significant impacts on economies, cultures, and ecologies worldwide. Developing predictive models for forest fire probability is crucial for preventing and managing these fires. Such models contribute to reducing losses and the frequency of forest fires by informing prevention efforts effectively. The objective of this study was to assess and map the forest fire susceptibility (FFS) in the Indian Western Himalayas (IWH) region by employing a GIS-based fuzzy analytic hierarchy process (Fuzzy-AHP) technique, and to evaluate the FFS based on forest type and at district level in the states of Jammu and Kashmir, Himachal Pradesh, and Uttarakhand. Seventeen potential indicators were chosen for the vulnerability assessment of the IWH region to forest fires. These indicators encompassed physiographic factors, meteorological factors, and anthropogenic factors that significantly affect the susceptibility to fire in the region. The significant factors in FFS mapping included FCR, temperature, and distance to settlement. An FFS zone map of the IWH region was generated and classified into five categories of very low, low, medium, high, and very high FFS. The analysis of FFS based on the forest type revealed that tropical moist deciduous forests have a significant vulnerability to forest fire, with 86.85% of its total area having very high FFS. At the district level, FFS was found to be high in sixteen districts and very high in seventeen districts, constituting 25.7% and 22.6% of the area of the IWH region. Particularly, Lahul and Spiti had 63.9% of their total area designated as having very low FSS, making it the district least vulnerable to forest fires, while Udham Singh Nagar had a high vulnerability with approximately 86% of its area classified as having very high FFS. ROC-AUC analysis, which provided an appreciable accuracy of 79.9%, was used to assess the validity of the FFS map produced in the present study. Incorporating the FFS map into sustainable development planning will assist in devising a holistic strategy that harmonizes environmental conservation, community safety, and economic advancement. This approach can empower decision makers and relevant stakeholders to take more proactive and informed actions, promoting resilience and enhancing long-term well-being.

Combining SWOT with AHP for Analyzing the Adoption of a Circular Economy in the Apparel Industry in Brazil

The Brazilian fashion industry is the country’s second-largest generator of direct and indirect jobs. Despite Brazilian design being a world reference mainly for prints and summer-related collections, it is also the second most polluting industry in the country. We investigated the factors that impact adopting a circular economy in the textile industry using an association of a SWOT analysis and the AHP approach. We analyzed the adoption of a circular economy in the apparel industry. The opportunities, strengths, weaknesses, and threats were associated using the evaluators’ comparison of the selected SWOT items related to the application of a circular economy in the conventional apparel industry were used as criteria for the AHP approach. The case study used managers from two intimate apparel industries in northeastern Brazil and four academics in Production Engineering. By applying the concepts to the case study, we found that expanding products, upcycling, and increasing sustainability were the three vital criteria for reaching a circular economy in the studied apparel industry.

Maximizing financial management efficiency with a novel machine learning algorithm

Any firm must successfully manage its financial assets to succeed. To make wise choices for handling resources, possibilities for investment, and allocation of funds, accountants rely on reliable forecasting of finances. To enhance the effectiveness of Financial Management (FM), this research develops hybrid long short-term memory and hierarchical analytic process (HLSTM-AHP) technique. The LSTM approach is applied to develop the financial evaluation system, while the AHP approach is employed to establish the weightings of economic variables incorporated into the LSTM framework. To show how well the suggested HLSTM-AHP approach works at enhancing FM effectiveness, real-time accounting information from a company that is publicly traded are implemented. To further address the issue of anomalous data regarding finances, this research employs a unique sampling data collected by linear discriminant analysis (LDA) to develop a multiscale convolutional neural network (MCNN), which improves the framework's forecasting performance and demonstrates conclusively that machine earning (ML) is practicable in the study of FM forecasting, with plenty of opportunity for future investigations.

Multi-criteria land suitability assessment for mulberry-based agroforestry using AHP and GIS approach in Anantnag district of the Kashmir valley, India, to achieve sustainable agriculture

Multi-criteria land suitability assessment for mulberry-based agroforestry using AHP and GIS approach in Anantnag district of the Kashmir valley, India, to achieve sustainable agriculture

Prioritization and taxonomy of factors related to environmental tax reform (ETR) using fuzzy AHP approach

PurposeEnvironmental taxes have been in place for many years to reduce environmental damage and pay more attention to the environment. However, some of the adverse socio-economic impacts that may result from such taxes and the many challenges facing developing countries have necessitated policy reform. Therefore, identifying and prioritizing the factors related to environmental tax reform (ETR) is necessary to help governments and environmental protection agencies (EPAs) focus on this prioritizing to develop and improve this process. Awareness of the benefits of ETR encourages governments to use this policy to reduce adverse environmental impacts and contribute to economic growth.Design/methodology/approachThe primary purpose of this work is to prioritize and taxonomy the factors related to ETR using the Fuzzy Analytic Hierarchy Process (FAHP) approach. In the first stage, 25 factors were extracted from the available literature. These factors were divided into five categories for more accessible review. In the second stage, the FAHP as a Multiple-Criteria Decision-Making (MCDM) Technique was used to prioritize and develop the taxonomy of identified factors and the categories of these factors.FindingsThe results show that reducing carbon emissions (DF4) is the essential prioritization factor that governments and environmental organizations can achieve if the ETR is implemented. Following that, reducing greenhouse gas emissions (DF1), double benefit (EcF7) and increase sustainability reports (EnF4) can be achieved by implementing ETR.Research limitations/implicationsThis study is geographically limited to Iran. In terms of the study population, this study is limited to 25 academic, tax and public policy experts. Moreover, in this study, FAHP is the only approach used. For further research, the results of this study can be compared with that of other multi-criteria techniques like FAHP, fuzzy TOPSIS or BWM.Practical implicationsRatings of factors related to ETR can guide and help governments identify important factors that affect environmental tax reform, which can, in addition to controlling ecological pollution will, increase the economic benefits of governments.Originality/valueThis study is the first to identify factors related to environmental tax reform and to develop an MCDM technique for prioritizing these factors and finding important ones.

Development of a Spatial Accessibility Index for Assessing Health Infrastructure Using AHP Approach: A Case Study of Andhra Pradesh State

Development of a Spatial Accessibility Index for Assessing Health Infrastructure Using AHP Approach: A Case Study of Andhra Pradesh State

Development of flood susceptibility map using a GIS-based AHP approach: a novel case study on Idukki district, India

ABSTRACT Flooding is a regular danger in the Idukki district of Kerala causing serious damage to life and property. An attempt has been undertaken in this research to identify crucial zones in the Idukki district that are more susceptible to flooding. The AHP technique was used to give relative weights to 12 flood contributing parameters. The resultant flood susceptibility map shows that 1346.4 km2 of the total land in the Idukki district has a high to very high likelihood of flooding. Validation of the resultant map was achieved using the AUC-ROC approach, which showed good accuracy of 0.91.

What drives customers crazy for green vehicles? a fuzzy AHP approach

What drives customers crazy for green vehicles? a fuzzy AHP approach

A Combined Fuzzy AHP and GA Approach to Machine Scheduling Problems from an Environmental Perspective

With increasing concerns about the need for environmental protection and reduction of energy consumption, enterprises have to demonstrate their capabilities in lowering resource consumption by enhancing the efficiency of their systems. Although some approaches to quantifying the environmental burden generated by a product or service system such as life cycle assessment (LCA) and carbon auditing have been developed, expert judgments are often required to implement them. From an industry’s perspective, small- and medium-sized enterprises need an efficient tool to determine the best solution when considering various attributes simultaneously. Thus, a combination of fuzzy analytical hierarchy process and genetic algorithm has been introduced to solve scheduling problems and support the decision-making process. This study aims to effectuate the green scheduling on optimized machine-task assignments with fuzzy evaluation. The proposed approach is illustrated using a case example from a centralized dishwashing company. Results show that the global warming potential value can be reduced by 1.86% and the cost of operation is slightly increased by only 1.28%. The result of the proposed approach is presented simply in the form of machine-task assignments with optimized environmental impact values and associated costs. Therefore, no further result interpretation by environmental experts is required. This study can be a reference for government policymakers in formulating policies to synthesize operation optimization and business sustainability.

An integrating spherical fuzzy AHP and axiomatic design approach and its application in human–machine interface design evaluation

Human–machine interface (HMI) design evaluation is critical in interactive product development because it directly affects the cost of subsequent design and user experiments. The evaluation information of HMI design mainly depends on the subjective perception and preference of experts, especially the hesitancy degree is rarely considered. We propose an integrated spherical fuzzy AHP (SF-AHP) and spherical fuzzy axiomatic design (SF-AD) method to choose a reasonable HMI alternative, considering the potential risks caused by the hesitancy degree of experts. Firstly, we introduce a process of automatically repairing inconsistent spherical fuzzy preference relations (SFPR) for SF-AHP. After that, we build suitable evaluation criteria and calculate the criteria weight by the SF-AHP method. We further extend the axiomatic design to the spherical fuzzy environment and propose a multi-criteria decision-making (MCDM) method based on SF-AD to evaluate HMI alternatives. The case analysis results demonstrate the effectiveness of the proposed method in the HMI design evaluation process, and the sensitivity and comparative analysis results indicate that the proposed method is stable and reliable.

Strategies for economic empowerment via BUMDes: A path to sustainable development in Renah Alai Village

The BUMDes, a village business entity managed by local communities, bolsters local economies and is established based on village-specific needs and potential. While the BUMDes in Renah Alai remains nascent, its contributions to the village's development and local community welfare have been limited. For the enduring success of the community, an empowerment strategy for BUMDes involving the government, village officials, and local stakeholders should accentuate rural local wisdom, encompassing socio-demographic constructs, agricultural enterprises, and village institutional frameworks. This research sought to conceptualize and dissect the paradigm of village economic enhancement via BUMDes in Renah Alai, targeting sustainable village growth. The SWOT-AHP analytical tool was employed, with the AHP approach yielding strategic recommendations through the SWOT matrix. Data was amassed via surveys and comprehensive interviews and processed through Focus Group Discussions (FGD) with pertinent village agencies and officials. The SWOT matrix's cumulative weights revealed that the Weakness-Opportunity strategy matrix was paramount, marking it as a cornerstone for the Renah Alai BUMDes Empowerment roadmap. The SWOT-AHP analysis delineated four pivotal empowerment areas for BUMDes in Renah Alai: 1) Institutional fortification of BUMDes, 2) Human resource quality enhancement, 3) Infrastructure, and 4) Capital acquisition.

The Employee Performance Evaluation by using the Hybrid Multi-Criteria Decision-Making Approach

Objectives: This study is aimed to develop a multi-criteria decision-making model for evaluating employee performance and provide organizations with a guideline on how to quantify employee performance.Methodology: A hybrid approach of AHP and WSM was used in the development of the employee performance model. The AHP approach was employed to obtain the weight of each criterion. The obtained weight value is then used to calculate the performance score.Finding: Based on the literature review and interviews, nine criteria were used, namely the achievement of work targets, job knowledge, initiative, work discipline, responsibility, teamwork, integrity, communication, and cleanliness. Based on weight calculations, it was found that achievement of the work target has the highest importance weight, followed by job knowledge, initiative, work discipline, responsibility, teamwork, integrity, communication, and cleanliness.Conclusion: This study developed a multi-criteria decision-making model and a scoring guideline for evaluating employee performance. According to the results of the performance score, the assessed employee would fall into five categories i.e. unacceptable performance, performance is slightly under the minimum expectation, performance meets the standard and expectation, performance exceeds the standard and expectation, and extraordinary performance. The model can be used to help managers to make decisions regarding compensation which is to be given to employees by linking the employee performance category with compensation criteria.

Gauging investors' investment decisions in the crypto market through the PRISM of behavioral biases: a fuzzy AHP approach

PurposeResearch in the domain of behavioral finance has proven that investors demonstrate irrational behavior while making investment decisions. In a similar domain, the primary objective of this research is to prioritize the behavioral biases that influence cryptocurrency investors' investment decisions in the Indian context.Design/methodology/approachA fuzzy analytic hierarchy process (F-AHP) was used to prioritize the behavioral factors impacting cryptocurrency investors' investment decisions. Overconfidence and optimism, anchoring, representativeness, information availability, herding, regret aversion, and loss aversion are among the primary biases evaluated in the present study.FindingsThe findings suggested that the two most important influential criteria were herding and regret aversion, with loss aversion and information availability being the least influential criteria. Opinions of family, friends, and colleagues about investment in cryptocurrency, the sale of cryptocurrencies that have increased in value, the avoidance of selling currencies that have decreased in value, the agony of holding losing cryptocurrencies for too long rather than selling winning cryptocurrencies too soon, and the purchase of cryptocurrencies that have fallen significantly from their all-time high are the most important sub-criteria.Research limitations/implicationsThis survey only covered active cryptocurrency participants. Additionally, the study was limited to individual crypto investors in one country, India, with a sample size of 467 participants. Although the sample size is appropriate, a larger sample size might reflect the more realistic scenario of the Indian crypto market.Practical implicationsThe study is relevant to individual and institutional cryptocurrency investors, crypto portfolio managers, policymakers, researchers, market regulators, and society at large.Originality/valueTo the best of the authors' knowledge, no prior research has attempted to explain how the overall importance of various criteria and sub-criteria related to behavioral factors that influence the decision-making process of crypto retail investors can be assessed and how the priority of focus can be established, particularly in the Indian context.

Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

The optimal management of personal resources impacts everyone’s quality of life. An investment in graduate education is a sustainable opportunity for improved outcomes in human life, including cognition, behavior, life opportunities, salary, and career. Advanced technology dramatically reduces the risk of personal resources in graduate program admission recommendations that depend on multiple individual needs and preferences. In the digital age, a dynamic recommender system enhances the suitably effective solution for students’ university selections. This study focused on designing, developing, and testing a recommender system for graduate admission using a dynamic multi-criteria AHP and fuzzy AHP approach. The explicit multi-criteria recommender system was a platform as a service (PaaS) web application created to aid in graduate admissions management and decision-making. The design proposed that the bit representation store a dynamic explicit multi-criteria data structure. The recommendations adopting dynamic multi-criteria were validated by comparing them to the programs to which the students were actually admitted and enrolled. They individually ranked the evaluation outcomes of dynamic explicit multi-criteria and alternative preferences to provide graduate admission recommendations. Eighty graduate students in information technology evaluated the recommender system. Using top-1, top-2, and F1-score accuracy, the effective system accuracy performance on the dynamic multi-criteria recommender system was evaluated using AHP and fuzzy AHP approaches. The fuzzy AHP demonstrated marginally greater practical accuracy than the AHP method.

Fuzzy AHP Assessment of Urban Parks Quality and Importance in Novi Sad City, Serbia

This paper proposes an AHP approach that utilizes the fuzzy extent model to prioritize five city parks based on their present quality and projected importance for Novi Sad City, the capital of Vojvodina Province, in Serbia. The study involved an expert evaluation of a set of eight criteria to identify the most relevant subset of criteria for a detailed park assessment. The park evaluation took into account uncertainties (fuzziness), the expert’s risk tolerance, and different levels of optimism and pessimism. The obtained results could serve when defining upcoming city plans and management agendas related to green areas in the city. The proposed fuzzy-based methodology can be extended to group decision-making scenarios by involving more experts and stakeholder representatives. The park weights obtained through the fuzzy AHP methodology described in this paper can aid city planners and politicians in the strategic allocation of financial, organizational, and human resources for parks.