Impact of LULC on debris flow using linear aggression model from Gilgit to Khunjerab with emphasis on urban sprawl.

In this research, the impact of land use and land cover (LULC) on debris flow was evaluated in the Gilgit to Khunjerab region. Two events have been done: (i) LULC stimulations for 2026 and 2030 using the MOLUSCE plugin and (ii) debris flow susceptibility mapping using linear aggression model. The evaluation of LULC on debris flow susceptibility is based on two scenarios: (i) existing (2010, 2014, 2018, 2022) LULC scenarios and (ii) stimulated (2026, 2030) LULC scenarios. The linear aggression model has 16 contributing factors to developing the debris flow susceptibility mapping. The main contributing components in debris flow susceptibility mapping are slope and LCCS. According to the linear aggressiveness model, debris flow susceptibility grows as the LULC changes, and the high susceptibility zones' share increases. For the current years 2010, 2014, 2018, and 2022, as well as the stimulated years 2026 and 2030, the model had high success rates (> 90.0%) and prediction rates (> 85.0%). The findings backed up prior research and suggested that the impact of LULC will grow in the future.

Impact role stress on turnover intentions of Pakistan's healthcare workers: Mediating and moderating role of organizational cynicism and self-efficacy.

Nurses make up most of the global healthcare system, thus justifying their significance in the respective industry. The healthcare profession is amongst the very few careers that are attributed to a very high level of stress and imbalanced work-life equilibrium. Over past decades, the said nature of work has been observed to coerce countless nurses to leave their respective organizations. Considering this, the current study primarily evaluates the impact of role stressors on the turnover intentions of nurses employed in the healthcare industry of Pakistan. Secondly, the study examines the mediatory role of organizational cynicism between the role stressors and turnover intentions to explain the escalating trend of nurses intending to leave the industry. Lastly, it assesses the moderating role of self-efficacy between the organizational cynicism and the intended turnover of a nurse, to gauge the amount of variation self-efficacy can cause to mitigate the negative attitudes of employed individuals. The current study was conducted in the twin metropolitans of Pakistan i.e., Rawalpindi and Islamabad. A total of 394 responses were statistically evaluated using SmartPLS 3.0. The results of the current study indicated a significant impact of role stressors on the turnover intentions of nurses. Also, organizational cynicism was observed as a significant mediator between role stressors and turnover intentions. Further, self-efficacy as well was observed as a significant moderator between organizational cynicism and the intent of healthcare workers to leave the organization. The present study addressed the conceptual research gap by exploring the direct cumulative effect of role stress (role ambiguity, role conflict, role stressors, work-family conflict) in developing the intents of professionals to quit their employing organizations, the mediatory role of organizational cynicism, and the moderation effect of self-efficacy between the undertaken variables. While in terms of abridging the contextual research gap, the current study evaluated the proposed research model within the healthcare sector of Pakistan. The findings of the current study commended the management personnel of the healthcare industry to provide the nurses with healthy professional environments to work in, as well as catering to their professional and personal expectations to a better extent. Hence, increasing the ownership of an individual depicted towards his/her employing organization.

Evaluation of Different Landslide Susceptibility Models for a Local Scale in the Chitral District, Northern Pakistan.

This work evaluates the performance of three machine learning (ML) techniques, namely logistic regression (LGR), linear regression (LR), and support vector machines (SVM), and two multi-criteria decision-making (MCDM) techniques, namely analytical hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS), for mapping landslide susceptibility in the Chitral district, northern Pakistan. Moreover, we create landslide inventory maps from LANDSAT-8 satellite images through the change vector analysis (CVA) change detection method. The change detection yields more than 500 landslide spots. After some manual post-processing correction, the landslide inventory spots are randomly split into two sets with a 70/30 ratio for training and validating the performance of the ML techniques. Sixteen topographical, hydrological, and geological landslide-related factors of the study area are prepared as GIS layers. They are used to produce landslide susceptibility maps (LSMs) with weighted overlay techniques using different weights of landslide-related factors. The accuracy assessment shows that the ML techniques outperform the MCDM methods, while SVM yields the highest accuracy of 88% for the resulting LSM.

Effect of multiple climate change scenarios and predicted land-cover on soil erosion: a way forward for the better land management.

The ecosystem, biodiversity, and anthropological existence in the Chitral district are in danger due to the sediments and soil erosion stemming from the changes in the land-cover and climate. This research aims to practice the RUSLE model with the changes in the land-cover and climate in upcoming situations for 2030 and 2040 to evaluate soil erosion annually as per the spatial dissemination and the tendency of sediment yield. The multilayer perceptron (MLP), an artificial neural network (ANN), besides the Markov chain analysis was used to model upcoming land-cover. The Max Planck Institute model, which demonstrated a revised bias as well as downscaled grid size under the Representative Concentration Pathways (RCPs), was used for examining the future changes in the climate. The modeled land-cover showed that the areas that are primarily comprised of natural trees and shrubs were transformed largely to agriculture and build-up areas. The average rainfall in the future under different RCP situations was elevated compared to the rainfall through historical time. The continuous variability in the R and C factors affects the probable soil erosion rate and sediment yield. Under RCP8.5 for both future years of 2030 and 2040, the extreme erosion rate was assessed at around 500 and 550 t/ha/year. Additionally, under the different RCP scenarios in 2030 and 2040, the outcomes of sediment yield were more significant than the sediment yield through historical time. The results showed that lower regions of the Chitral district are at risk of amplified soil erosion and sediment yield presently, as shown by the historical data and in the future. The produced soil erosion maps using ArcGIS 10.2 can play a valuable role in managing sustainable development, conservation of the watershed of the Chitral River, and reducing soil loss. Effective measures to overcome these concerns and mitigate the possible effects need to be planned and practiced, particularly the decrease in the storage volume of the reservoirs situated on the river.

Exploring and Validating the Effects of Mega Projects on Infrastructure Development Influencing Sustainable Environment and Project Management.

The study is based on validating and exploring the effects of a mega project plan (CPEC) on infrastructure development and Sustainable Project Management. The CPEC has great importance to infrastructure development and economy-boosting. The current study's primary aim is to deal with environmental protection, economic boost up, international relations influencing to the Project's success. The paper also addressed project management as a moderator between environmental protection, economic boost up, international relations, and the CPEC project's success. The primary data has been gathered by using questionnaires, and PLS-SEM has been employed for the analysis. The results revealed that environmental protection, economy boost up, and international relations have a positive association with the success of CPEC. The outcomes also exposed that project management moderating among the nexus of economy boosts up the international relations and success of CPEC. The present study results guided how Pakistan and China make the CPEC project stronger with the efficient implementation of practices required for protecting the environment, with the economic growth and boost up, and good strong relations with foreign countries. This study was an attempt to validate the different factors to check their association with each other in a new environment, resulting in a leading edge for the success of mega projects that influence project management.

Impact of agile management on project performance: Evidence from I.T sector of Pakistan.

Over the past several years, global project management teams have been facing dynamic challenges that continue to grow exponentially with the increasing number of complexities associated with the undertaken tasks. The ever-evolving organizational challenges demand project managers to adapt novel management practices to accomplish organizational goals rather than following traditional management practices. Considering which, the current study aims to explain the effect of agile management practices upon project performance directly as well as while being mediated through project complexity. Furthermore, the aforementioned mediatory relationship is evaluated in terms of the moderating effect of leadership competencies. The current study utilized the survey approach to collect the data from registered I.T firms deployed in the potential metropolitans of each province of Pakistan including, Peshawar, Islamabad, Lahore, Sialkot, Faisalabad, Hyderabad, Sukkur, and Karachi. A total of 176 responses were utilized for statistical evaluations. As result, it was observed that the negative influence anticipated by project complexity on project performance was compensated by the agile management practices. Further, the leadership competencies played a pivotal role in managing project complexity while implementing agile management practices and therefore enhancing project performance. The current study abridges the potential knowledge gap conceptually by evaluating the direct impact of agile management upon project performance while considering all of its aspects, exploring the mediatory role of project performance and evaluating the moderating role of leadership competencies in attaining optimum project performance. In contextual terms, the current study fills the knowledge gap by gauging the implications of agile management practices within the I.T sector of Pakistan. The results of the current study can be a potential guide for both the academicians and the industry professionals.

Scientific risk performance analysis and development of disaster management framework: A case study of developing Asian countries.

Disaster is a state of serious disruptions in the functionality of any society or county. Disasters pose serious economic or environmental impacts that surpass the capacity of the affected country or society to compete with the use of their assets. Recently, Pakistan significantly prone to health disasters due to COVID-19 among developing South Asian countries. The long-term impact of health disasters and other natural hazards put additional pressure mostly on the government's economic policy. It forces the government to follow a constructive approach like a disaster relief-based approach rather than a conventional mitigation management formation to reduce the impact of disaster risk. This study elaborates on the main issues associated with disaster preparedness as well as recovery of the economy and businesses of the country. For Scientific risk performance analysis, open-source data from the National Institute of Disaster Management (NDMA) has been utilized to study the current situation of COVID-19 in Pakistan. Results show Pakistan has been facing a highly vulnerable situation as more than three hundred and fifty thousand confirmed cases have been reported. Poor health and technical management facilities have been exposed against COVID-19 as Pakistan has a low heath budget because of its declining GDP growth rate in the world. This research will help in disaster preparedness and the development of a disaster risk management framework while designing strategies to deal with such pandemics in the future.

Analyzing the Importance of Driver Behavior Criteria Related to Road Safety for Different Driving Cultures.

Driver behavior has been considered as the most critical and uncertain criteria in the study of traffic safety issues. Driver behavior identification and categorization by using the Fuzzy Analytic Hierarchy Process (FAHP) can overcome the uncertainty of driver behavior by capturing the ambiguity of driver thinking style. The main goal of this paper is to examine the significant driver behavior criteria that influence traffic safety for different traffic cultures such as Hungary, Turkey, Pakistan and China. The study utilized the FAHP framework to compare and quantify the driver behavior criteria designed on a three-level hierarchical structure. The FAHP procedure computed the weight factors and ranked the significant driver behavior criteria based on pairwise comparisons (PCs) of driver's responses on the Driver Behavior Questionnaire (DBQ). The study results observed "violations" as the most significant driver behavior criteria for level 1 by all nominated regions except Hungary. While for level 2, "aggressive violations" is observed as the most significant driver behavior criteria by all regions except Turkey. Moreover, for level 3, Hungary and Turkey drivers evaluated the "drive with alcohol use" as the most significant driver behavior criteria. While Pakistan and China drivers evaluated the "fail to yield pedestrian" as the most significant driver behavior criteria. Finally, Kendall's agreement test was performed to measure the agreement degree between observed groups for each level in a hierarchical structure. The methodology applied can be easily transferable to other study areas and our results in this study can be helpful for the drivers of each region to focus on highlighted significant driver behavior criteria to reduce fatal and seriously injured traffic accidents.