Analytic Hierarchy Process Research Articles

Purpose – This study investigates the evolution of the Knowledge-Based Performance Management System (KBPMS) in the public construction sector, focusing on the integration of performance management, digitalization, and data-driven decision-making. It aims to identify research trends, thematic clusters, and conceptual foundations for designing knowledge-oriented systems that enhance transparency and efficiency in public procurement. Design/methodology/approach – A bibliometric analysis of 145 Scopus-indexed journal articles published between 2015 and 2025 was conducted using VOSviewer and Biblioshiny. The analysis mapped publication patterns and keyword co-occurrence networks to visualize the intellectual structure and emerging themes within KBPMS-related research. Findings – The results reveal a progressive convergence between performance management and digital technologies in construction governance. Four major clusters were identified, representing decision-making frameworks such as the Analytic Hierarchy Process (AHP), data-driven construction management, risk and safety performance systems, and cost–benefit–based evaluation. These clusters reflect a transition toward integrated and knowledge-based performance models supported by digital tools like Business Intelligence (BI) and Building Information Modelling (BIM). Practical implications – The findings provide insights for policymakers and project managers to design and implement digital performance management systems that support data-informed decision-making, transparency, and sustainable governance in public construction projects. Originality/value – This study is among the first to apply bibliometric techniques to examine KBPMS research within the public construction context. It contributes by linking performance management, digital transformation, and evaluation frameworks into a unified knowledge-based approach for improving accountability and efficiency in public sector project management.

Traditional gross domestic product ignores environmental and resource costs, making it difficult to reflect the sustainability of economic activities. This study constructs a green GDP accounting model based on the United Nations System of Environmental-Economic Accounting, integrating resource consumption, environmental degradation losses, and pollution control costs. It quantifies the economic impact on the environment through 12 indicators. Using a green restoration rate model and the analytic hierarchy process, it assesses the potential for global climate mitigation using rainfall, greenhouse gas emissions, sea level, and biodiversity as indicators. Weighted analysis shows that biodiversity and greenhouse gas emissions have the greatest impact. Based on data from 2015 to 2023, the study uses China as a case study to combine climate impact models and entropy analysis in examining the multidimensional impacts of green GDP, with results showing that the environmental dimension holds the highest weighting at 39.2% and a projected 4.3% reduction in fossil fuel consumption over the next five years.. The study validates the application value of green GDP in global and Chinese climate mitigation efforts, providing scientific basis for optimizing resource allocation and formulating environmental policies, thereby contributing to the achievement of sustainable development goals.

Abstract Biodiversity is increasingly threatened by challenges such as climate change, new land-use management, and emerging societal dynamics, emphasizing the pressing need for its conservation. The European Union prioritizes biodiversity conservation, as reflected in initiatives like the Green Deal Agenda and the Biodiversity Strategy for 2030. Sustainable hunting is increasingly recognized for its role in biodiversity conservation, balancing ecological, economic, and cultural considerations. While hunting impacts biodiversity both positively and negatively, effective management requires collaboration among communities, researchers, and authorities to develop strategic plans. These plans are particularly relevant in agricultural and rural contexts, where hunting regulations intersect with land management, crop protection, and the socio-economic development of local communities. This study proposes an integrated participatory approach to strengthen public decision-making processes in biodiversity management. By combining different aspects of backcasting, participatory SWOT analysis, and the Analytic Hierarchy Process, the research demonstrates how structured stakeholder engagement can bridge the gap between scientific knowledge and policy implementation, contributing to more widely supported, sustainable, and actionable plans. The case study of the Apulia Region highlights the transformative potential of participation in wildlife planning. The results emphasize the importance of precise land allocation for hunting, with updated methodologies to accurately reflect the current land use. Regularly revising regional maps—including those for land use, renewable energy installations, and protected areas—are vital for effective management. The study offers both practical and theoretical contributions. Firstly, it supports policymakers in crafting strategies through participatory methods that boost implementation success. In addition, it fosters research that builds a scientific collaborative community by integrating real-world social and political factors.

Climate change and flood susceptibility in Bocas del Toro, Panama: A multi-criteria spatial analysis approach.

This study addresses the critical conflict between livelihood preservation and commercial tourism in the residential historic districts of small-town China—a context often overlooked in urban studies. Taking Meizhou’s “One Town, Two Lanes” as a case, we propose a novel multi-source data fusion framework integrating POIs, population heatmaps, and questionnaire surveys. By applying Analytic Hierarchy Process (AHP), Poisson regression, and spatial correlation analysis, we quantitatively diagnose spatial disorders. The results reveal a dual-suppression mechanism: residential vitality, reliant on public services, is suppressed by commercial tourism, while tourist vitality is diminished by experience–quality gaps. This conflict manifests as pronounced vitality fractures. Our methodology and findings provide a replicable framework for diagnosing and resolving spatial conflicts in similar historic districts, emphasizing the imperative of prioritizing residential continuity.

Construction buildings have a significant and continuously increasing impact on the global environment as they consume a lot of resources, energy and contribute a large share of carbon emissions. Green buildings have become a key approach to improve building performance while minimising environmental issues. There are various available green certification schemes, for example LEED, BREEAM, CASBEE, TREES, and Green Mark. However, the cost of green building varies mainly depending on building location. TREES (Thailand Rating of Energy and Environmental Sustainability) is a national green building certification that provides a framework for assessing building performance and built environment sustainability. Despite its advantages, various studies show that green buildings can cost up to 2-4 times more than conventional building constructions. This cost barrier can cause investors and developers to hesitate when considering green construction initiatives. Therefore, green building selection requires a careful trade-off between sustainability and cost. This research uses a mixed-methods approach, integrating the Analytical Hierarchy Process (AHP) with a stochastic cost assessment model to enhance decision-making in TREES-certified building projects. Different levels of TREES-certified buildings are compared, where AHP ranks alternatives based on sustainability criteria, and Monte Carlo simulations assess lifecycle cost variations. The finding indicated that highly sustainable buildings rate higher in AHP but also show larger cost variation due to the use of advanced green technologies, such as photovoltaic, smart metre etc. In contrast, buildings with moderate sustainability ratings and more stable costs may offer a better balance between investment and environmental benefits. This study provides a quantitative decision-making framework aims to help green building developers, investors, and policymakers that minimise financial risks while optimising sustainability.

Abstract The Himalayan region’s complex terrain and ecological fragility make it increasingly vulnerable to vegetation stress and landslides, driven by both natural and human factors. This study focuses on a 2663.92 km² area encompassing Rudraprayag, Ukhimath, Gopeshwar, and Joshimath, aiming to develop a Vegetation Health Index (VHI) and explore its link with landslide susceptibility. Six key parameters such as NDVI, NDMI, soil, rainfall, slope, and road proximity were selected for their relevance and tested for multi-collinearity. All variables showed VIF values below 5, confirming their independence and suitability. Expert weights were applied on six critical parameters using the Analytic Hierarchy Process (AHP) with a Consistency Ratio of 0.093 establishing reliability. The GIS-weighted overlay technique was used to create the spatially varied Vegetation Health Index (VHI) map. Validation using sensitivity analysis, LAI regression (R² = 0.62), and AUC_ROC analysis (0.423) revealed 57.7% occurrence of previous landslides in low VHI areas, establishing a negative relationship between vegetation status and landslide susceptibility. The hybrid geospatial-statistical model is a reliable predictor of ecologically and geologically sensitive regions and an effective tool for land degradation mapping and disaster risk reduction. The results provide vital data for future mountain environmental planning, slope management, and policy formulation.

In today’s digital economy, creating a strong brand is critically important for IT sector entrepreneurs in terms of sustainable growth and competitive advantage. However, many technology ventures founded primarily on technical expertise encounter various challenges in implementing branding processes. This study aims to analyze the extent to which digital enterprises operating in the IT sector are able to implement branding strategies, and to identify the factors that facilitate or hinder this process. Using the Analytic Hierarchy Process (AHP) method, the factors affecting the applicability of branding were evaluated through a multi-criteria approach. Based on expert opinions, the criteria—management vision, financial capacity, human resource competence, strategic alignment, marketing ability, and technical expertise—were weighted and prioritized. The findings indicate that, in addition to entrepreneurs’ level of awareness regarding branding, tangible obstacles in the implementation process (such as budget constraints and lack of expertise) are also decisive. The study contributes both to academic literature and provides strategic guidance for technology ventures.

Tar-rich coal (with a tar yield ≥ 7%), as a special coal-based oil and gas resource, is of great significance for ensuring national energy security and promoting the clean conversion of coal. The selection of suitable geological sites represents a core challenge for the safe and efficient application of its in situ pyrolysis technology. Focusing on the tar-rich coal seams in the Santanghu Basin, this study constructed a comprehensive geological evaluation system for site selection by integrating numerical simulation, data mining, and laboratory experiments. The Analytic Hierarchy Process (AHP) and a fuzzy comprehensive evaluation method were employed to achieve a quantitative assessment and identify favorable areas within the study region. The results indicate that resource scale, coal seam conditions, and the properties of the roof and floor strata are the key controlling factors. One optimally comprehensive Class I favorable area (Tiao IV block) was successfully identified. This block exhibits a large resource scale, favorable coal seam conditions, a high tar yield, excellent geological sealing, and superior engineering compatibility, making it the recommended priority target for pilot testing. The evaluation system developed in this study can provide a theoretical basis and technical reference for the geological site selection of in situ pyrolysis of tar-rich coal in similar mining areas and advance its industrialization.

The governance of smart cities is essential for addressing complex urban challenges, advancing sustainability, and improving citizens' quality of life. This study explores governance models for smart cities through a hybrid Analytical Hierarchy Process (AHP)–Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) framework. Expert evaluations were employed to prioritize and rank governance alternatives. The results show Smart Urban Collaboration as the most effective governance framework, owing to its capacity to foster inclusivity and sustainability. The analysis underlines the critical role of social inclusion in urban governance, emphasizing the importance of involving diverse stakeholders in decision-making processes. These participatory approaches are crucial in building citizens' trust and collaboratively developing innovative solutions to urban challenges. Next in priority is sustainability, drawing attention to the need for such urban governance frameworks to tackle environmental issues like climate change and resource scarcity. Smart cities can move towards sustainable development goals through strategic utilization of technology in stakeholders’ involvement. This work offers practical recommendations and insights for policymakers, urban planners, and academics to create an urban environment that is resilient, inclusive, and sustainable.

ABSTRACT Renewable energy communities (RECs) serve as a highly promising stance to endorse the growth of sustainable and decentralised energy systems. Although previous studies have predominantly concentrated on the advantages and incentives for participating in RECs, there has been insufficient focus on the significant hurdles encountered by stakeholders in emerging economies. The study addresses the gap by identifying and ranking the primary barriers to REC implementation and proposing concrete strategies to improve stakeholder participation and effectiveness. Furthermore, a novel aspect of this research is the combination of two existing methods: the Spherical Fuzzy Analytic Hierarchy Process for assessing the importance of obstacles and the Triangular Fuzzy Multi-Attributive Border Approximation Area Comparison for prioritising the best strategies. The findings indicate that regulatory and bureaucratic (33.28%) barriers and financial (27.44%) constraints are the most significant. The TF-MABAC method reveals that streaming and support are essential for addressing obstacles. To overcome these obstacles, authorities need to encourage cooperation among stakeholders, simplify regulations, and offer financial incentives. This study improves methodological approaches in REC research by utilising sophisticated multi-criteria decision-making methodologies. The research immediately enhances global sustainability initiatives by promoting the shift to clean energy, therefore aligning with the aims of SDG-7 and SDG-13.

This study proposes a competency model to analyse the entrepreneurship ecosystem and assess the performance of incubation firms in Türkiye. A comprehensive field study is conducted across various incubation firms in the country, utilising a detailed survey to collect data from entrepreneurs. The survey focuses on key dimensions: Customer, Technology, Research and Development (R&D), Competition, Investment, Marketing, Environment & Sustainability, Human Resources (HR) and Commercialisation. The survey responses are compiled into a database for performance analysis. Five experts perform pairwise evaluations to determine each dimension's relative importance. Based on their insights, the Fuzzy Analytic Hierarchy Process (FAHP) approach is employed to assign weights to each decision criterion. The analysis identifies Commercialisation and R&D as the most critical, followed by Technology and Competition. Environment & Sustainability is given the least weight, as it is considered a secondary factor that supports overall performance. The WASPAS (Weighted Aggregated Sum Product Assessment) method is applied to evaluate and rank the performance of incubation firms. High-performing firms align innovative strategies with market demands, leverage R&D, and secure intellectual and industrial property rights. Low-performing firms exhibit weaknesses, particularly in customer, marketing, and technology issues. The analysis highlights that the Marmara Region, particularly Istanbul, is a key hub for high-performing incubation firms. Other regions demonstrate more limited entrepreneurial potential, indicating that regional differences significantly affect the concentration of entrepreneurial activities. Successful firms are predominantly concentrated in the software and information technology sectors. This analysis provides strategic insights to help entrepreneurs and supporting organisations enhance firm performance and entrepreneurship ecosystem.

Beekeeping plays a vital role in agricultural sustainability and biodiversity conservation, yet identifying ecologically suitable areas for apiculture remains challenging. The objective of this study is to evaluate and compare two Multi-Criteria Decision-Making (MCDM) methods—the Analytical Hierarchy Process (AHP) and the Full Consistency Method (FUCOM)—within a Geographic Information Systems (GIS) framework to identify optimal beekeeping areas in Mardin Province, Türkiye. Nine environmental, climatic, topographical, logistic, and socio-economic factors were selected through literature review, legal regulations, expert consultation, and field observations. Suitability maps were generated and validated using field-verified hive locations and Receiver Operating Characteristic–Area Under the Curve (ROC–AUC) analysis. The results show that land use/cover, proximity to water sources, and precipitation were the most influential factors. Overall, 83% of hive locations coincided with areas classified as moderately suitable or higher. AHP achieved slightly higher predictive accuracy (AUC = 0.774) than FUCOM (AUC = 0.754), while FUCOM required substantially fewer pairwise comparisons, underscoring its efficiency. These findings confirm the robustness of the framework and provide a practical tool for sustainable apicultural land-use planning, offering transferable insights for policymakers, decision-makers, and beekeepers in Türkiye and other regions with similar ecological conditions.

Soil erosion is a major environmental challenge in Mediterranean regions, where climatic variability, steep slopes, and human activities accelerate land degradation. In the north-central region of Algeria, the Mitidja Plain faces increasing erosion pressure, threatening biodiversity, agricultural productivity, and long-term soil sustainability. This study aims to assess soil erosion risk by integrating the Revised Universal Soil Loss Equation (RUSLE), the Analytical Hierarchy Process (AHP), and Geographic Information System (GIS) techniques within a Cloud-Based Geospatial (CBG) framework using the Google Earth Engine (GEE) platform. High-resolution datasets on rainfall, topography, soil properties, and land cover were processed in GEE to derive five RUSLE factors: rainfall runoff erosivity (RE), soil erodibility (KS), slope length steepness (LS), cropping management (CM), and management practices (PC). The analysis revealed that 41% of the Mitidja Plain is at severe erosion risk, with an average soil loss of 88.72 t ha⁻¹ yr⁻¹ and a maximum of 161.13 t ha⁻¹ yr⁻¹. Erosion hotspots correspond to areas where slopes exceed 22°, vegetation cover is sparse, and rainfall intensity is high. The AHP-weighted integration achieved strong predictive accuracy (AUC = 0.87), identifying slope characteristics as the most influential factor (weight = 0.292). Forested areas reduced erosion risk in 30% of the region, while unprotected mountainous zones covering 22% of the study area require urgent intervention. These findings demonstrate the effectiveness of CBG-enhanced modeling for mapping priority conservation areas. Recommendations include terracing, check dams, vegetation restoration, and adaptive agricultural practices to reduce soil loss, particularly in agricultural lands with moderate to high vulnerability (48% of the plain). The methodology provides a replicable framework for other Mediterranean regions facing similar erosion pressures, offering robust spatial data to guide soil management and conservation planning.

Purpose This study aims to define key elements for creating sustainable urban living environments in earthquake-prone areas of Turkey and other developing countries, using expert assessments and student projects to develop a checklist for evaluating housing and urban design in affected resettlement areas. Design/methodology/approach In this study, the design and evaluation process for architectural projects focusing on “Sustainable Living in Earthquake Zones” was conducted by senior architecture students. The projects aimed to create livable, resilient urban spaces in disaster-affected areas in Turkey. Experts weighted 28 sub-criteria under the categories of functionality, aesthetic quality, social and cultural aspects and environmental aspects using the Analytic Hierarchy Process. The evaluations were aimed at identifying the best designs for sustainable and active urban living, with final scores reflecting a combination of criteria weighting and expert ratings. Findings In evaluating architectural designs for sustainable living in earthquake zones, functionality and environmental aspects were deemed most important by experts. The highest-rated design integrated public spaces and sustainability near the Asi River in Hatay. Other notable projects focused on blending traditional and modern elements, emphasizing community spaces and regional identity. Overall, designs highlighted functionality over aesthetics and demonstrated varied attention to environmental considerations. Originality/value This study pioneers a practical checklist for sustainable urban design in earthquake-prone areas by integrating expert assessments and student projects. This paper offers novel insights to advance urban resilience and sustainability in post-disaster resettlement contexts, providing a valuable framework applicable to Turkey and similar regions, bridging academic research with practical implementation.

<div>Magnetorheological brakes based on MR technology are being investigated for their potential use for automotive purposes. Among the design decisions, the selection of an appropriate MR fluid for the brake application remains an unexplored key issue. This article proposes an MCDM-based framework comprising analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) to select an appropriate MR fluid for the automotive brake application. Three commercially available MR fluids from Lord Corporation (MRF-122EG, MRF-132DG, and MRF-140CG) are assessed against six criteria, viz. density, temperature range, yield stress, viscosity, magnetic saturation limit, and solid content. Considering all the criteria, the AHP ranked MRF-140CG highest, while TOPSIS chose MRF-122EG. Excluding the temperature range, both methods converged on MRF-122EG as the optimal choice. The proposed framework can be used for the MR fluid selection problem of other MR devices as well.</div>

Purpose The aim of this study is to develop a comprehensive index for evaluating the audit opinion shopping. To achieve this, various criteria have been taken into account to create an index that effectively assesses the extent of this practice. Ultimately, the study aims to provide a practical tool for a more precise analysis and evaluation of audit opinion shopping. Design/methodology/approach The composite index was developed using a linear composite method, with weights determined through Multiple-Criteria Decision-Making (MCDM) employing the Analytic Hierarchy Process (AHP) based on pairwise comparisons. Data from companies listed on the Tehran Stock Exchange (2017–2022) were collected to measure the index. Findings The composite index provides a more nuanced reflection of audit opinion shopping due to its multidimensional approach. Among the criteria, abnormal audit fees exhibited the highest coefficient, indicating their significant role in motivating managers to seek unqualified audit opinions. In contrast, changing the audit partner had the lowest coefficient, reflecting its cost-effective and less transparent nature as a strategy for achieving unqualified audit opinions. Research limitations/implications The reliability of the proposed index could be enhanced with additional applications and retests. Moreover, as with all expert-based methods, the coefficients of the criteria might vary with changes in the expert panel. Practical implications Implementing this composite index can help stakeholders verify the authenticity of financial statement reliability as audited. It also enables awareness of the broader economic, social, and political consequences of audit opinion shopping. Social implications The study addresses audit quality's social and economic impact by providing a tool for stakeholders to identify and mitigate opportunistic behaviors in audit practices, fostering greater transparency and accountability. Originality/value This study contributes to the audit literature by exploring audit opinion shopping in emerging markets, such as Iran, where institutional and auditing practices differ significantly from developed economies. It provides a basis for regulatory bodies to design policies related to audit contracts and competition. Furthermore, the index offers insights to investors, companies, and researchers for evaluating audit quality, supporting decision-making, and conducting further research in this area.

Hedge algebra is a powerful and flexible tool for handling linguistic information, enabling precise quantitative computations and enhancing the effectiveness of multi-criteria decision-making (MCDM). This study proposes a novel integrated fuzzy MCDM approach that combines an enhanced fuzzy analytic hierarchy process (EFAHP) with a 4-tuple hedge algebra semantics model to assess digital transformation in retail enterprises. In this approach, the EFAHP method is integrated with hedge algebra to determine the priorities of pillars and criteria while providing a rigorous mathematical mechanism to transform ambiguous linguistic evaluations into numerical values. This transformation leverages the semantic structure of linguistic variable domains and incorporates fuzziness measures for both atomic words and intensity-modifying words (hedges). Furthermore, a new consistency index formula is introduced to evaluate the reliability of the EFAHP results, with validation being limited to the case study dataset. The 4-tuple hedge algebra semantic model is then employed to assess and rank the digital transformation levels of retail enterprises in Vietnam. Finally, a sensitivity analysis verifies the robustness of the proposed approach by illustrating how variations in pillar and criterion weights influence enterprise rankings.

Flooding is an actual hazard at several watersheds in Tulkarm governorate of Palestine. The lack of integrated planning and appropriate preparedness lead to increased hazard of flood events. This study aims to develop a flood hazard map, using a group of parameters: slope, elevation, drainage density, precipitation, soil texture, land use/land cover, flow accumulation and population density. Analytic Hierarchy Process method and Geographic Information System program were used to weighted parameters. The result showed a flood hazard map with a 12.5 m resolution for Tulkarm study area categorized into five classes (percentage): very low (2%), low (26%), medium (37%), high (28%) and very high (7%) flood hazards. Results were compared with previous studies from the literature, and verified using ground truthing to examine the certainty of the results in three different locations. A group of interventions (structural and non-structural) were proposed for each flood hazard class so that competent authorities could better manage flood hazards. Some of these interventions for high flood vulnerable areas are, applying heavily-engineered structural measures and regular maintenance of rainwater culverts and valley streams. Mapping the flood hazard is an integral part during phases of flood hazard management from mitigation, preparedness, response and recovery.

Prolonged and intensive mining operations in the Huainan Coal Mining Area (HCMA), have damaged its environment, jeopardizing the Huainan city's sustainability. However, there is a lack of studies on the primary influence factors and evolutionary patterns of the ecological environment vulnerability (EEV) in the HCMA. Therefore, this study employed 12 indices such as elevation, slope, and soil type to establish the evaluation index system, used the sensitivity-resilience-pressure (SRP) model and analytic hierarchy process (AHP) to study the evolutionary patterns and primary influencing factors of the EEV in the HCMA from 2010 to 2020. The results showed that (1) in terms of time, EEV was generally moderate and gradually weakening. In terms of spatial distribution, EEV was generally high in the northwest, low in the central, and highest in the southeast, decreasing then increasing from northwest to southeast. (2) The ecological conditions in the northern new coal mining area and the southern old coal mining area were generally improving. Coal mining and vegetation cover primarily affected the north, and coal mining and ecological restoration projects primarily affected the south. The southeastern built-up area's ecological environment showed minimal change and it was primarily impacted by urban construction activities. (3) Coal mining and the implementation of ecological environment management and restoration projects are the primary factors influencing the EEV of the HCMA. The ecological environment management and restoration projects such as filling mining, comprehensive recycling and utilization of coal gangue, backfilling of subsidence areas, in CMSWA can reduce the ecological vulnerability of local areas and improve their ecological environment.