Analytical Hierarchical Process Research Articles

Delineation of the Groundwater Potential Zones using Integrated Geospatial Techniques and Multi-criteria Decision Approach in the Cretaceous Lower Benue and Niger Delta Basins of Abia State, Southern Nigeria

Delineation of the groundwater potential zones in the Cretaceous Lower Benue and Niger Delta basins of Abia state, Nigeria with geographic information system (GIS) / remote sensing (RS) multi-criteria decision approach (MCDA) considered the significant hydrogeomorphological factors affecting the availability of groundwater resources. The factors (geology, rainfall, slope, drainage density, lineament density, soil type, and land use land cover) were ranked using the analytical hierarchical process, a multi-criteria decision-making tool. The integration of the factors into a geographic information system (GIS) and weighted overlay analysis were then carried out using ArcGIS software. The result indicates 31.5% of zones of high to very high groundwater occurrence are in the southern section, and 41.6% of poor to very poor zones in the northern section. While the moderate zones make up the 26.8% of the study area. The study demonstrates that the groundwater occurrence in the study area is primarily controlled by the interactive impact of geology, rainfall, and slope factors, thus revealing the causes of the incessant random borehole failures in the moderate zones. Thus, the groundwater resources can be sustainably exploited, developed, and managed with the help of the map produced from the resulting demarcation of groundwater potential zones in the study.

Exploring the Spatiotemporal Dynamics and Simulating Heritage Corridors for Sustainable Development of Industrial Heritage in Foshan City, China

Industrial heritage serves as a testament to the historical and cultural legacy of industrialization, and its preservation and adaptive reuse are crucial for promoting sustainable urban development. This study explores the spatiotemporal dynamics of industrial heritage in Foshan City, China, and simulates potential heritage corridors to inform effective conservation and revitalization strategies. By employing Kernel Density Estimation (KDE) and Standard Deviational Ellipse (SDE) methods, the research investigates the spatial and temporal distribution patterns of industrial heritage across different historical periods and industrial types. An Analytic Hierarchical Process (AHP) is used to construct a hierarchical model of resistance factors, which serves as the basis for simulating potential heritage corridors using the Minimum Cumulative Resistance (MCR) model. The results unveil distinct spatiotemporal distribution patterns, with concentrations of industrial heritage in the central Chancheng District and southeastern Shunde District. Two primary potential heritage corridors are identified, and prioritized strategies for their adaptive reuse are proposed. The findings contribute to a comprehensive understanding of industrial heritage distribution in Foshan City and provide valuable insights for the conservation, planning, and sustainable development of these significant sites. The study highlights the importance of integrating spatiotemporal analysis and heritage corridor modeling in the decision-making process for industrial heritage revitalization, ensuring the preservation of invaluable industrial history and culture while fostering sustainable urban growth.

Study of the future economists’ readiness to use artificial intelligence based on the hierarchy analysis method

Introduction. The article examines the problem of increasing the level of digital literacy of future economists in the context of interaction with artificial intelligence systems. The purpose of the study is to assess the readiness of future economists to use artificial intelligence in the context of digital prospects of the socio-economic space. Materials and Methods. The methodological basis of the study is the sustainable development strategy, which identifies educational opportunities, resources and technologies as a global driving force for achieving the Sustainable Development Goals. The main research method is T. Saaty’s Analytical Hierarchical Process method, which enables to build a flexible hierarchical model for studying the dynamics of future economists’ readiness to use artificial intelligence in the context of developing digital literacy. The authors conducted an online survey of students from the Financial University under the Government of the Russian Federation, Astrakhan State University, Omsk State Technical University, and schoolchildren from economics classes (Gymnasium 19, Omsk) to assess the future economists’ readiness to use artificial intelligence in the context of the transition to a digital economy. Results. The authors identified gender differences in respondents’ preferences in the use of artificial intelligence: female participants show higher results than the general sample, when choosing one answer about the purposes of personal use of artificial intelligence, and lower, when choosing a combination of answers, male participants show the opposite results, which is explained by the attitude towards risk in terms of gender stereotypes of behavior. When comparing the choice of respondents’ answers for different age groups (16-20 years old), no age peculiarities were discovered, as well as the ambiguous nature of the influence of artificial intelligence on the younger generation of future economists in terms of a decrease in the natural intelligence of young people against the backdrop of digitalization reaching all spheres of life. A high level of awareness of students and schoolchildren regarding the prospects and problem areas of using artificial intelligence in the field of economics and finance was also revealed. Conclusions. The study concludes that future economists are actively interacting with artificial intelligence systems, promoting the formation of digital literacy in the interests of sustainable development.

Strategy For Improving Taxpayer Compliance Motorized Vehicles: (Case Study Of SAMSAT Grobogan Regency)

The increasing volume of vehicles should have great potential for motor vehicle tax revenue in Grobogan Regency. SAMSAT has set motor vehicle tax targets in accordance with regional potential, but the realization is still not optimal. This investigate points to decide and analyze the viability and development rate of engine vehicle assess income from the One-Stop Single Organization Framework (SAMSAT) of Grobogan Rule in 2018-2023, analyze the deterrents confronted in expanding engine vehicle citizen compliance in Grobogan Rule, analyze approach procedures for progressing engine vehicle citizen compliance in Grobogan Rule which can be taken by the territorial government to extend engine vehicle citizen compliance. The secondary data came from the Grobogan Regency Statistics Center (BPS) and Samsat report data. Primary data is a way of collecting data using survey research methods so that data is obtained from respondents using direct interview techniques and questionnaires, quantitative methods with a descriptive approach to hierarchical process analysis. The research results show that the performance in achieving PKB targets in Grobogan Regency experienced fluctuations during 2018-2023. Meanwhile, the growth rate of target achievement experienced significant volatility during 2018-2023. In 2023, the growth rate will experience a significant decline and show performance that is not successful in achieving targets. From the policy priority results obtained, it is hoped that policymakers will focus more on the highest weighting criteria, namely "Policy Providing various payment facilities such as online payments or collaborating with retail outlets" compared to other policies, but this does not mean that other policies are unimportant, because every The policy taken by the government will still have an impact, both positive and negative.

Evaluating pedestrian facilities for enhancing pedestrian safety in Addis Ababa city

Transport demand has been increasing in most third-world countries. However, poorly maintained facilities and poor planning exposed pedestrians to high-traffic accidents. This paper aims to evaluate pedestrian facilities using the pedestrian level of service to enhance pedestrian safety in Addis Ababa. Relevant data was collected through field measurement and direct observation from 13 purposively identified pedestrian sites across the Piyasa to Bole bridge and Megenagna to Torihayloch road corridors. Pedestrian level of service derivation considered capacity, traffic, comfort, safety, and security conditions and their sub-components. The weight of each criterion and sub-factor was decided according to the Saaty scale using the judgment of experts under the analytical hierarchical process. The result of the study strongly stipulates the presence of the problem of pedestrian facilities in Megenagna, Mexico, Urael Church, and Golagol which can affect the level of pedestrian safety. However, Denibel City, Legahare, Torhayloch, and National Theater sites have scored better Pedestrian level of service for the walking population. Finally, the study recommended the requirement of prior attention for the sites with very poor and poor pedestrian levels of service by the concerned sectors.

A risk decision support model for hydrogen refueling stations based on cloud-analytic hierarchy process

With the rapid development of the hydrogen energy industry and the vigorous promotion of the application of hydrogen fuel cell vehicles, hydrogen refueling station (HRS) has gradually penetrated into cities, mostly built in densely populated areas. Once leakage, fire, and/or explosion accident occurs, it is highly likely to cause casualties, property damage, and environmental pollution. In order to avoid HRS risks, this paper establishes a risk decision support model based on Cloud-Analytic Hierarchy Process for HRS. Firstly, the static and dynamic features of HRS emergency plan selection are analyzed, and the weight coefficient of each feature is determined by using the cloud analysis hierarchy process. Then, the case-based reasoning theory and the weighted Euclidean distance based on the cloud model are used to establish a decision support model based on emergency plan optimization. Finally, taking the HRS hydrogen storage tank fire as an example, the risk decision support model based on the cloud analysis hierarchical process is applied to form the optimal scheme of the HRS hydrogen storage tank fire emergency plan. The results show that the weighted Euclidean distance scheme selection method based on cloud model can be effectively combined with the weight acquisition method based on cloud analysis hierarchy process to provide decision support for HRS emergency risk management and control.

Identification of critical success factors (CSFs) for successful project management in manufacturing sector

PurposeThis research has been carried out to study the impact of critical success factors (CSFs) on successful project management of projects in the manufacturing sector. These success factors will pave the way for the successful completion of projects for the manufacturing sector. CSFs play a vital role in the timely conclusion of projects in any organization. For the projects to be successful certain essential factors must be taken into account. These essential factors are identified through this research.Design/methodology/approachDuring this study an adaptive survey of the literature was conducted, after a detailed literature review certain success factors were identified for project management in the manufacturing sector. The number of success factors was reduced to 40 factors based on the level of incidence in the literature. The length of the questionnaire was also given due importance to make the survey more interesting and effective. After that Fuzzy Delphi Method (FDM) was employed to screen the most essential factors. In the end, the Fuzzy Analytical Hierarchical Process (FAHP) was used to rank these factors in order of importance.FindingsProject Manager Leadership Skills, Economic Environment, Top Management Support, Project Planning, Clear and realistic Goals, and Financial Support have come out to be the most important CSFs for successful project management in the manufacturing sector.Originality/valueThis is novel research to identify CSFs for project management in the manufacturing sector. Previously, most of the studies remained focused on construction and software projects.

Spatial Analysis and Risk Evaluation for Port Crisis Management Using Integrated Soft Computing and GIS-Based Models: A Case Study of Jazan Port, Saudi Arabia

A hazard zoning map is the most essential tool during the crisis management cycle’s prevention and risk reduction phase. In this study, a geographic information system (GIS) is applied to the crisis management of ports through the preparation of a risk zoning map in Jazan Port, Saudi Arabia, using a novel integrated model of the fuzzy hierarchical analysis process and emotional artificial neural network (FAHP-EANN). The objective is to more accurately identify the highly potential risk zones in the port through hybrid techniques, which mitigates the associated life and financial damages through proper management during a probable hazard. Prior to creating the risk zoning map, every potential port accident is identified, categorized into six criteria, and assigned a weight through the utilization of a machine learning algorithm. The findings indicate that the three most effective criteria for the risks of Jazan Port are land fires, pollution and dangerous substances, and human behavior, respectively. A zoning map of all risks in Jazan Port was generated by using the weights obtained for each of the major accidents. This map may be utilized in the development of crisis prevention measures for the port and in the formation of crisis management units.

Delineation of groundwater potential zones in coastal alluvial region using remote sensing, geographic information system and analytical hierarchy process techniques

Delineation of groundwater potential zone in coastal region is a challenging task. One of the reasons for that is lack of understanding of the geogenic factors in the coastal alluvial areas such as geomorphology, lithology etc. These factors can influence the locations of the groundwater potential zones over the coastal alluvial terrains. The present study is an attempt to analyse the multiple factors to delineate groundwater potential zones in the coastal region of Contai Sub-division, West Bengal, India. In this study, remote sensing, geographic information system (GIS) and multi-criteria decision analysis (MCDA) techniques have been utilized to delineate the groundwater potential zones. Weights were assigned to the parameters using the analytical hierarchical process (AHP) and different classes within each parameter have been ranked on the basis of their relative importance regarding groundwater potentiality. The results of the study were validated by water yield data, water level fluctuation data and geophysical survey. The outcome of validation reveals that a strong correlation (80%) exists between water yield data and groundwater potential zones. Similarly, a good relation occurs for the water level fluctuation data and groundwater potential zones, where the overall accuracy and kappa coefficients are 84.2% and 0.76 respectively. The output of the study reveals that geomorphologically older deltaic plain, older alluvial plain and older coastal plain are good indicators of high groundwater potential regions. Furthermore, the outcome of the study also unveils that lithologically the well sorted medium grained sand is important feature to delineate high groundwater potential regions in coastal alluvial areas. The findings, thus, could establish that present methodology using GIS and AHP techniques has a better potential to identify and map the groundwater potential zones more realistically and can be applied for future planning of groundwater resource management and groundwater exploration in wider coastal alluvial terrain.

Integration of geospatial analysis, frequency ratio, and analytical hierarchy process for landslide susceptibility assessment in the maze catchment, omo valley, southern Ethiopia

This investigation was conducted in southern Ethiopia's Maze watershed in the Omo River Valley. Frequency ratio (FR) and analytic hierarchy process (AHP) techniques were used to assess landslide susceptibility in the region. Identifying causative components and landslide inventory data achieved the goal. Remote sensing and on-site investigations found 793 landslide polygons. To assess vulnerability, the landslide inventory information is categorized into two groups: the training dataset (70%) and the validation dataset (30%). This study examined “slope, aspect, curvature, lithology, land use and cover, normalized vegetation index, and proximity to fault lines, rivers, and distance to road as landslide controlling factors”. The spatial analysis capabilities in Arc GIS were used to overlay the weights of all landslide-causing components to create the susceptibility map. A final landslide susceptibility map is produced using FR and AHP methods and categorized as “very low,” “low,” “moderate,” “high,” and “very high.” The frequency ratio method divides the region into susceptibility classes by frequency. The very low, low, medium, high, and very high susceptibility groups cover 25%, 20%, 18%, and 19% of the territory. The analytical hierarchical process technique shows that 3%, 7%, 26%, 36%, and 28% of the area are very low, low, medium, moderate, and very high landslide susceptibility. The receiver operating characteristic curve was employed to validate the area-underlayer susceptibility maps. The success rates were determined using the FR and AHP approaches, resulting in AUC numbers of 0.873 and 0.87. Similarly, the prediction rates were determined to be 0.81 and 0.80. The landslide susceptibility maps will significantly influence land resource allocation.

Using the analytic hierarchical process to identify potential sites for rural ecological infrastructure investment in South Africa: examples from Cacadu and Tsitsa Catchments

Climate change, population growth, and land degradation are causing various socio‐economic consequences in low‐ to medium‐income countries. To address this, it is essential to prioritize restoration interventions at specific locations to maximize their effectiveness and the supply of valuable ecosystem services, such as water regulation. A stakeholder‐driven spatial multi‐criteria analysis was applied in two degraded and rural catchments in the Eastern Cape (the Cacadu and Tsitsa River Catchments), South Africa. The process combined metrics for ecosystem health, hydrological functionality, and socio‐economic benefit to visualize areas that can be targeted to maintain or enhance flow regulation. These criteria were identified based on the guidance of local stakeholders concerning their valuable ecological infrastructure (EI). The EI types investigated were wetlands, riverbanks, rangelands, and old croplands. Human and climate change impacts threaten these EIs but are the most relevant for communal needs and sustainability. According to the analysis, more places require better management to maintain the existing flow regulation service of focal catchments than areas that require a high level of human intervention (implying areas that can enhance flow regulation). This work highlights the importance of including and contextualizing the socio‐economic benefits expected from Nature‐based Solutions or EI investment initiatives.

Analytical hierarchal process of environmental ethics decision making for environmental sustainability

Analytical hierarchal process of environmental ethics decision making for environmental sustainability

Inventory and GLOF susceptibility of glacial lakes in Chenab basin, Western Himalaya

Global warming causes glacial mass loss, leading to the growth of high-mountain glacial lakes. The presence of glacial lakes poses a significant threat to downstream communities, as they can produce destructive Glacial Lake Outburst Floods (GLOFs). Timely basin-scale inventory and GLOF susceptibility assessments are crucial, considering past GLOF events in the Himalayan region. Here, an updated inventory of glacial lakes in the Chenab basin, Western Himalayas was generated based on Sentinel-2 datasets for 2022. We assessed temporal changes and GLOF susceptibility for glacial lakes (>0.05 km2) through a multi-criteria based Analytical Hierarchical Process, classifying them into low, medium, high, and very high susceptibility classes. The results reveal 419 lakes (>0.001 km2; 9.97 ± 0.67 km2) in the basin in 2022. Glacial lakes (>0.05 km2) area increased by ∼75%, from 3.92 ± 0.58 to 6.86 ± 0.25 km2 during 1990–2022. Of the 42 lakes (>0.05 km2) evaluated, four showed very high GLOF susceptibility. The study emphasizes the impact of local geomorphology and glacier-lake interaction under warming climate, likely to increase the GLOF susceptibility in the region. Regular monitoring and detailed fieldwork for these susceptible lakes are crucial for early warning and disaster risk reduction for downstream communities.

Mapping of Groundwater Recharge Zones in Hard Rock Aquifer through Analytic Hierarchy Process in Geospatial Platform

Extensive use of groundwater is a result of the growing population; in relation to this, studies have focused on groundwater conservation measures. This study identified groundwater artificial recharge zones (GWARZs) in the upper Manimuktha sub-basin through the application of remote sensing and GIS. A spatial analysis using the analytical hierarchical process (AHP) and weighted overlay analysis (WOA) was employed by integrating several spatial thematic layers such as geology, geomorphology, aquifer thickness, lineament density (LD), drainage density (DD), soil, slope, rainfall, and land use/land cover (LULC) in order to classify the GWARZs. The geomorphology along with lithology, higher aquifer thickness, low lineament densities, higher drainage densities, and gentle slope regions, were identified as suitable areas for artificial recharge zones. The study area was divided up into five classifications based on the integration analysis: excellent (41.1 km2), good (150.6 km2), moderate (123.9 km2), bad (125.5 km2), and very poor (57.7 km2). Excellent and good GWARZs were identified in the eastern and central regions of the study area. The final outcomes of this research were evaluated with seasonal electrical conductivity (EC) variations. The majority of samples with minor seasonal EC variations were observed in the excellent and good GWARZ categories. The results showed that the spatial analysis tool is useful for GWARZ delineation and sustainably managing groundwater resources.

Multi-Criteria Analysis for Assessing Flood Susceptibility in the Municipality of Conselheiro Lafaiete (MG)

Objective: To evaluate the susceptibility to flooding in the municipality of Conselheiro Lafaiete – Minas Gerais, using the Hierarchical Analytical Process method. Theoretical Framework: Floods are events that affect several Brazilian cities, where the main related factors are denoted by the morphometric characteristics of the river basin(s) that comprise them, associated with slope, hypsometry, soil typology and use and land occupation. In this sense, multi-criteria analyzes are fundamental for mapping areas of susceptibility to flooding in river basins. Method: The study proceeded by characterizing the study area, integrating the diagnosis of the drainage system, morphometric analysis of the river basin in which Conselheiro Lafaiete is integrated, and the application of the Hierarchical Analysis Method (AHP) to map areas susceptibility to flooding of the river basin. Results and Discussion: The results obtained revealed [synthesize the main results of the research]. In the discussion section, these results are contextualized in light of the theoretical framework, highlighting the implications and relationships identified. Possible discrepancies and limitations of the study are also considered in this section. Research Implications: The study indicates gaps in Conselheiro Lafaiete PMSB with regard to urban drainage and points out, through mapping, the areas of the municipality most susceptible to the occurrence of flood events. Originality/Value: The mapping of areas susceptible to flooding carried out for Conselheiro Lafaiete considered a multi-criteria approach, integrating anthropogenic factors. The product can be applied as a basic tool for public management regarding urban drainage and flood risk management in the municipality.

Application of the AHP-QFD methodology in the sustainability analysis of a trifunctional adsorbent for inorganic micropollutants from contaminated water

An alternative approach to addressing water pollution is through the development of adsorbent materials. Na-jarosite is a promising material capable of removing simultaneously multiple ions from contaminated water. Employing four Quality Functional Deployment (QFD) matrices alongside the hierarchical analysis process (AHP) methodology, this study aimed to select materials, preparation methods, equipment, and processing conditions of Na-jarosite to remove As(V), Pb(II) and F (-) from contaminated water. The analysis of QFD matrices 1 and 2 identified electrical heating as the optimal method for synthesizing Na-jarosite, exhibiting removal capacities of removal capacity of 65.56 mg g−1 for As(V), 94 mg g−1 for Pb(II) and 2.45 mg g−1 for F(-). Rotating disc granulation was chosen for adsorbent formation, demonstrating environmental viability based on E Factor (0.6 kg of waste) and Eco scale (89) indicators. Further analysis of the QFD 3 matrix allowed the selection of essential equipment, including an electrical heating oven, a rotating disc granulator, and an extended tray for synthesis, granulation, and drying processes, respectively. Additionally, the QFD 4 matrix analysis identified drying the adsorbent at temperatures below 100 °C as a critical parameter for effective adsorbent formation. QFD and AHP analyses findings highlight the potential of Na-jarosite as a trifunctional adsorbent material for addressing water pollution challenges.

A quantitative priority-based approach using a multi-criteria decision-making model for sustainable coastal city development

AbstractThroughout history, water availability has been an essential factor in shaping the development, culture, transportation, economic activities, and access to food in cities. The socioeconomic and cultural development of a city or country with a coast depends on the active use of the coast and the impact of the coast on urban life. In this context, for the development of coastal cities, it is necessary to determine coastal city criteria and specify their strategies in line with these criteria in order to increase coastal qualities. This research determined Bursa, located northwest of Turkey, as the study area. However, factors such as the absence of a coastal plan for the city and the inability of the coast to integrate into urban life have weakened the coastal city’s qualities of it. For this reason, this study aims to define Bursa’s coastal city criteria and determine strategies to increase the coastal city quality. The coastal city criteria developed depending on the examples of coastal cities in the world were evaluated by surveying local people and experts. The results of these surveys were digitized according to their priorities using Analytical Hierarchical Process (AHP), one of the multi-criteria decision-making (MCDM) methods. The results of this study determined the highest priority criteria among the three main and nine sub-coastal city criteria in evaluating the coastal city in Bursa. This study proposes a numerical method that develops effective and sustainable coastal design and planning strategies for Turkey and underdeveloped countries.

A Novel Security Risk Analysis Using the AHP Method in Smart Railway Systems

Transportation has an essential place in societies and importance to people in terms of its social and economic aspects. Innovative rail systems need to be integrated with developing technologies for transportation. Systemic failures, personnel errors, sabotage, and cyber-attacks in the techniques used will cause a damaged corporate reputation and revenue losses. In this study, cybersecurity attack methods in smart rail systems were determined, and cyber events occurring worldwide through these technologies were analyzed. Risk analysis in terms of transportation safety in smart rail systems was determined by considering the opinions of 10 different experts along with the Analytic Hierarchical Process (AHP) performance criteria. Informatics experts were selected from a group of people with at least 5–15 years of experience. According to these risk analysis calculations, cybersecurity stood out as the most critical security risk at 27.74%. Other risky areas included physical security, calculated at 14.59%, operator errors at 16.20%, and environmental security at 10.93%.

Why do Chinese multinationals in South Africa get benefits from digital business strategy?

Background: Chinese multinational enterprises (MNEs) are obsessed with implementing digital business strategy in global competition, but there is limited knowledge about how and when the MNEs can achieve performance.Aim: This study aims to clarify the influence of digital business strategy on MNEs’ performance in South Africa, and whether this impact is mediated by exploratory and exploitative learning and moderated by organisational memory level and dispersion.Setting: Senior executives from the MNEs participated in the year-long survey. Before the survey, the participants were communicated and agreed, and the survey was completed by email.Method: Two-stage data from 314 MNEs in South Africa were obtained. Hierarchical regression analysis and Hayes Process Macros were used.Results: The results show that digital business strategy positively influenced performance, and the relationship was mediated by exploratory and exploitative learning. Organisational memory level and dispersion had an inverted U-shaped moderating effect on the relationship between digital business strategy and exploratory and exploitative learning.Conclusion: This study provides the first insight into the relationship between digital business strategy and MNEs’ performance in South Africa. It reveals the mediating mechanism and boundary conditions of this relationship, making an important contribution to the literature concerning digital business strategy.Contribution: This study encourages MNEs in South Africa to implement digital business strategies according to local conditions. What’s more, exploratory and exploitative learning is a strategic process that cannot be ignored, and moderate organisational memory can help these MNEs benefit from digital business strategy better.

SWOT analysis of agricultural colleges for entrepreneurship: Delphi-Fuzzy and fuzzy hierarchical application

PurposeThe present study aims to seek the strategic analysis of the entrepreneurship of agricultural colleges (AC).Design/methodology/approachIn terms of approach, this research was a combination of exploratory and hybrid methods. The present study was conducted in four stages. In the first stage, an open-ended questionnaire was designed to identify the strengths, weaknesses, opportunities and threats of entrepreneurship in AC (qualitative method). In the second stage, the Delphi-Fuzzy questionnaire was designed based on the results obtained from the first stage. In the third stage, the criteria of strengths, weaknesses, opportunities and threats of entrepreneurship of AC were analyzed based on the pairwise comparison (quantitative method) by the sample using a fuzzy hierarchical analysis process (FHAP). In the fourth stage, presented strategies were ranked based on pairwise comparison using FHAP.FindingsFrom the analysis of weaknesses, strengths, opportunities and threats facing AC for entrepreneurship, 12 strategies were presented in 4 groups of aggressive, conservative, competitive and defensive.Originality/valueThe literature review showed that no research has been done so far to identify strengths, weaknesses, opportunities and threats facing university entrepreneurship, especially AC. So the present study analyzes the weaknesses, strengths, opportunities and threats and proposes practical strategies for moving toward the formation of entrepreneurship AC. According to the gaps in providing SWOT of the AC, the results of this research can pave the way for policy makers and planners in this field.