Landslide susceptibility analysis of Karakoram highway using analytical hierarchy process and scoops 3D

Landslides are prevalent,regular,and expensive hazards in the Karakoram Highway(KKH)region.The KKH connects Pakistan with China in the present China-Pakistan Economic Corridor(CPEC)context.This region has not only immense economic importance but also ecological significance.The purpose of the study was to map the landslide-prone areas along KKH using two different techniquesAnalytical Hierarchy Process(AHP)and Scoops 3 D model.The causative parameters for running AHP include the lithology,presence of thrust,land use land cover,precipitation,and Digital Elevation Model(DEM)derived variables(slope,curvature,aspect,and elevation).The AHP derived final landslide susceptibility map was classified into four zones,i.e.,low,moderate,high,and extremely high.Over 80%of the study area falls under the moderate(43%)and high(40%)landslide susceptible zones.To assess the slope stability of the study area,the Scoops 3 D model was used by integrating with the earthquake loading data.The results of the limit equilibrium analysis categorized the area into four groups(low,moderate,high,and extremely high mass)of slope failure.The areas around Main Mantle Thrust(MMT)including Dubair,Jijal,and Kohistan regions,had high volumes of potential slope failures.The results from AHP and Scoops 3 D techniques were validated with the landslides inventory record of the Geological Survey of Pakistan and Google Earth.The results from both the techniques showed similar output that coincides with the known landslides areas.However,Scoops 3 D provides not only susceptible zones but also the range of volume of the potential slope failures.Further,these techniques could be used in other mountainous areas,which could help in the landslide mitigation measures.

Sequential Role of Artificial Intelligence and Environmental Performance Between the Association of Block Chain and Organizational Performance

In the context of the China-Pakistan Economic Corridor,this article evaluates how block chain technology might improve organizational performance(CPEC)through the sequential mediating role of artificial intelligence and environmental performance.Cross-sectional data were collected from one hundred respondents through a close-ended questionnaire-based survey of manufacturing companies,which was then analyzed using structural equation modeling,which structural equation modelling was used to analyze.The block chain technology benefits businesses in terms of the environment and economics.There is a focus on technology in every industry as the Industry 4.0 era gets underway.Block chain technology,a relatively new phenomenon,offers several opportunities for company operations improvement.Our findings showed that block chain technology favors the organizational performance through the sequential mediation of artificial intelligence and environmental performance,especially thanks to features like visibility,transparency,relationship management,and smart contracts.Also,it was discovered that block chain practices had a good relationship with both the environmental and economic paths to the firms’performance.At the same time,environmental performance is also positively correlated with the firm’s economic well-being.The study found that improved economic and environmental performance were key drivers of increased organizational performance.