Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459504
Mahmoud Khalifa, W. Nageab
In recent years, Geospatial Information Systems (GIS) have witnessed a significant shift towards smart spatial analytics, which involves the processing of large volumes of geographic data, known as big geographic data (Geodata Big). This processing and analysis enable the extraction of valuable information that can be utilized in decision-making processes. Smart maps, as geographic information platforms, play a crucial role in decision-making by providing data, statistics, and information about geographic features and phenomena. Three-dimensional maps offer the capability to visualize and analyze geographic and temporal data on Earth's surface or custom maps. They enable users to observe changes over time and create interactive visual tours that can be shared with others. The applications of smart maps are diverse and include surveillance, monitoring, navigation, and determining optimal routes to specific locations. Artificial-Geo intelligence (AI-Geo) applications have further enhanced GIS capabilities by utilizing intelligent models trained on various datasets. These models enable the identification and extraction of geographic phenomena from satellite imagery, aerial photographs, and other sources. AIGeo applications have found utility in numerous domains beyond mapping, providing valuable insights and facilitating decision-making processes. This abstract highlights the growing importance of smart spatial analytics in GIS, particularly through the use of smart maps and AI-Geo applications. By leveraging these technologies, organizations can harness the power of geospatial data to make informed decisions and gain deeper insights into geographic phenomena.
{"title":"Use of Three-Dimensional Maps in the Study of the Political Geography Course as One of the Applications of Artificial Intelligence","authors":"Mahmoud Khalifa, W. Nageab","doi":"10.1109/ICETSIS61505.2024.10459504","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459504","url":null,"abstract":"In recent years, Geospatial Information Systems (GIS) have witnessed a significant shift towards smart spatial analytics, which involves the processing of large volumes of geographic data, known as big geographic data (Geodata Big). This processing and analysis enable the extraction of valuable information that can be utilized in decision-making processes. Smart maps, as geographic information platforms, play a crucial role in decision-making by providing data, statistics, and information about geographic features and phenomena. Three-dimensional maps offer the capability to visualize and analyze geographic and temporal data on Earth's surface or custom maps. They enable users to observe changes over time and create interactive visual tours that can be shared with others. The applications of smart maps are diverse and include surveillance, monitoring, navigation, and determining optimal routes to specific locations. Artificial-Geo intelligence (AI-Geo) applications have further enhanced GIS capabilities by utilizing intelligent models trained on various datasets. These models enable the identification and extraction of geographic phenomena from satellite imagery, aerial photographs, and other sources. AIGeo applications have found utility in numerous domains beyond mapping, providing valuable insights and facilitating decision-making processes. This abstract highlights the growing importance of smart spatial analytics in GIS, particularly through the use of smart maps and AI-Geo applications. By leveraging these technologies, organizations can harness the power of geospatial data to make informed decisions and gain deeper insights into geographic phenomena.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459594
Nada Tarek
Through a case study of a 19th century residential structure in Glina, Croatia, this research paper investigates preservation engineering application of an earthquake-damaged historic buildings. Following the 2020 Petrina quakes, the cultural site of the case study received studies and minimally invasive retrofits to strike a ratio between preservation and seismic resistance. fabric-reinforced cementitious matrix FCRM and adding concrete to the floors was employed to improve structural integrity and increase its ability to resist seismic waves. The research paper concludes to effective approaches for preserving authentic heritage elements while improving life safety by combining preservation standards and structural engineering.
{"title":"Preservation Conservation Engineering: A Case Study","authors":"Nada Tarek","doi":"10.1109/ICETSIS61505.2024.10459594","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459594","url":null,"abstract":"Through a case study of a 19th century residential structure in Glina, Croatia, this research paper investigates preservation engineering application of an earthquake-damaged historic buildings. Following the 2020 Petrina quakes, the cultural site of the case study received studies and minimally invasive retrofits to strike a ratio between preservation and seismic resistance. fabric-reinforced cementitious matrix FCRM and adding concrete to the floors was employed to improve structural integrity and increase its ability to resist seismic waves. The research paper concludes to effective approaches for preserving authentic heritage elements while improving life safety by combining preservation standards and structural engineering.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459703
A. M. Alawag, W. Alaloul, Baker Nasser Saleh Al-dhawi, Abdullah O. Baarimah, Mahmood A. Bazel, Ahmed W. Mushtaha
Construction, like any other industry, is prone to conflicts. The construction industry has witnessed a rapid transformation driven by advancements in technology, with a particular focus on smart construction projects aimed at improving efficiency, transparency, and collaboration. Blockchain technology offers a decentralized method of managing the data and promotes the performance and sustainability of building projects. Nevertheless, a comprehensive analysis of the present status of blockchain research integration has not been undertaken utilizing scientometric analysis. This paper presents a comprehensive review and bibliometric analysis of blockchain technology adoption within the context of intelligent construction projects from 2018 through 2023. A total of 1079 papers were extracted from the Scopus database. The VOSviewer tool was used to visually represent the literature including various countries, scholarly publications, and keywords. Moreover, using an analysis of often-used phrases, three significant study fields associated with blockchain have been identified “Management,” “Project,” and “Building.”. This article contributes to the existing body of knowledge by synthesizing the current state of research on blockchain technology in smart construction projects, offering a holistic view of its applications, and highlighting areas that require further investigation.
{"title":"A Review and Bibliometric Analysis of Blockchain Adoption Within the Context of Smart Construction Projects","authors":"A. M. Alawag, W. Alaloul, Baker Nasser Saleh Al-dhawi, Abdullah O. Baarimah, Mahmood A. Bazel, Ahmed W. Mushtaha","doi":"10.1109/ICETSIS61505.2024.10459703","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459703","url":null,"abstract":"Construction, like any other industry, is prone to conflicts. The construction industry has witnessed a rapid transformation driven by advancements in technology, with a particular focus on smart construction projects aimed at improving efficiency, transparency, and collaboration. Blockchain technology offers a decentralized method of managing the data and promotes the performance and sustainability of building projects. Nevertheless, a comprehensive analysis of the present status of blockchain research integration has not been undertaken utilizing scientometric analysis. This paper presents a comprehensive review and bibliometric analysis of blockchain technology adoption within the context of intelligent construction projects from 2018 through 2023. A total of 1079 papers were extracted from the Scopus database. The VOSviewer tool was used to visually represent the literature including various countries, scholarly publications, and keywords. Moreover, using an analysis of often-used phrases, three significant study fields associated with blockchain have been identified “Management,” “Project,” and “Building.”. This article contributes to the existing body of knowledge by synthesizing the current state of research on blockchain technology in smart construction projects, offering a holistic view of its applications, and highlighting areas that require further investigation.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459406
Ali Ateeu, M. Alaghbari, A. Al-Refaei, Ammar Yousif Ahmed
This research investigates the use and consequences of environmentally-friendly technology in the operational activities of universities. We evaluate the incorporation of sustainable practices into the instructional structure and operational strategies of higher education institutions by conducting a thorough examination of relevant literature and conducting a comparative study. The methodological approach is based on a conceptual framework that combines the Triple Bottom Line theory with scholarly stakeholder involvement, offering a comprehensive view of sustainability from several angles. We use a variety of multidisciplinary research to assess the effectiveness of green technology in promoting an environmentally conscious campus culture and decreasing the ecological impact. Initial results indicate that while universities are making progress in adopting green technology, there is still much potential for improving policies and involving the community in order to achieve complete sustainability. This study enhances the discussion on green technology in academia and provides a solid groundwork for future research avenues.
{"title":"Sustainable Solutions: The Impact of Green Technologies in University Operations","authors":"Ali Ateeu, M. Alaghbari, A. Al-Refaei, Ammar Yousif Ahmed","doi":"10.1109/ICETSIS61505.2024.10459406","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459406","url":null,"abstract":"This research investigates the use and consequences of environmentally-friendly technology in the operational activities of universities. We evaluate the incorporation of sustainable practices into the instructional structure and operational strategies of higher education institutions by conducting a thorough examination of relevant literature and conducting a comparative study. The methodological approach is based on a conceptual framework that combines the Triple Bottom Line theory with scholarly stakeholder involvement, offering a comprehensive view of sustainability from several angles. We use a variety of multidisciplinary research to assess the effectiveness of green technology in promoting an environmentally conscious campus culture and decreasing the ecological impact. Initial results indicate that while universities are making progress in adopting green technology, there is still much potential for improving policies and involving the community in order to achieve complete sustainability. This study enhances the discussion on green technology in academia and provides a solid groundwork for future research avenues.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459390
Navneet Tiwari, Jinesh Thakkar, Om Bansode, Hanmant Magar
This research paper addresses the escalating risk of fraud signatures in banking transactions. It introduces a Signature Forgery Detection System that utilizes offline verification and diverse geometric measures to discern genuine from forged signatures. With the prevalence of signature-based identity verification in financial transactions and the absence of foolproof systems, the proposed system aims to enhance the security of banking by efficiently detecting and preventing signature forgery.
{"title":"Signature Forgery and Veracity Detection using Machine Learning","authors":"Navneet Tiwari, Jinesh Thakkar, Om Bansode, Hanmant Magar","doi":"10.1109/ICETSIS61505.2024.10459390","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459390","url":null,"abstract":"This research paper addresses the escalating risk of fraud signatures in banking transactions. It introduces a Signature Forgery Detection System that utilizes offline verification and diverse geometric measures to discern genuine from forged signatures. With the prevalence of signature-based identity verification in financial transactions and the absence of foolproof systems, the proposed system aims to enhance the security of banking by efficiently detecting and preventing signature forgery.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/icetsis61505.2024.10459577
{"title":"Other reviewers","authors":"","doi":"10.1109/icetsis61505.2024.10459577","DOIUrl":"https://doi.org/10.1109/icetsis61505.2024.10459577","url":null,"abstract":"","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459669
Meroua Sahraoui, Fouad Maliki, M. Bennekrouf
Production planning and control research has long emphasized scheduling strategies to address fluctuating demand and resource limitations. The Lot Sizing and Scheduling Problem (LSP) remains a significant challenge due to its complexity. In multi-line production systems, finding the right amount of each product to create each time is the difficult task of lot sizing. Getting lot sizing right is crucial because it directly affects both inventory levels and customer satisfaction. This work proposes a novel model for optimizing production planning in multi-line workshops, implemented using the CPLEX solver. The model aims to maximize gains by determining the optimal production batches.
{"title":"A Multi-Line Production System Lot Sizing Problem (Desing and Resolution)","authors":"Meroua Sahraoui, Fouad Maliki, M. Bennekrouf","doi":"10.1109/ICETSIS61505.2024.10459669","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459669","url":null,"abstract":"Production planning and control research has long emphasized scheduling strategies to address fluctuating demand and resource limitations. The Lot Sizing and Scheduling Problem (LSP) remains a significant challenge due to its complexity. In multi-line production systems, finding the right amount of each product to create each time is the difficult task of lot sizing. Getting lot sizing right is crucial because it directly affects both inventory levels and customer satisfaction. This work proposes a novel model for optimizing production planning in multi-line workshops, implemented using the CPLEX solver. The model aims to maximize gains by determining the optimal production batches.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459498
M. Alaghbari, A. Ateeq, Mohammed Alzoraiki, Marwan Milhem, B. Beshr
This research investigates the significant impact of technology on the transformation of Human Resource Management (HRM), with a specific emphasis on the modernization of conventional HR procedures. The integration of technology into Human Resource Management (HRM) is essential in the contemporary business landscape to augment organizational efficiency and effectiveness. This research provides a critical evaluation of the influence of digital breakthroughs, such as Artificial Intelligence (AI), Machine Learning (ML), Big Data analytics, and cloud computing, on human resources (HR) operations. The use of these technologies is significantly influencing diverse human resources strategies, namely in the areas of recruiting, performance management, and employee engagement. This is achieved via the incorporation of predictive analytics and datadriven approaches, which facilitate informed decision-making processes. The study emphasizes the impact of these technology instruments on enhancing operational effectiveness and enabling HR practitioners to transition from administrative responsibilities to strategic positions in workforce planning, talent management, and organizational growth. This research explores the ramifications of technological advancements on workers and employers, specifically focusing on the difficulties and advantages associated with incorporating technology into human resource management. Through a comprehensive examination of contemporary scholarly literature and empirical investigations, this research tries to establish a connection between theoretical constructs and their tangible application. This resource is very beneficial for professionals in the field of human resources, as well as researchers and organizational leaders. It assists them in effectively navigating and managing the intricate challenges of modern human resource management within a technologically sophisticated environment.
{"title":"Integrating Technology in Human Resource Management: Innovations and Advancements for the Modern Workplace","authors":"M. Alaghbari, A. Ateeq, Mohammed Alzoraiki, Marwan Milhem, B. Beshr","doi":"10.1109/ICETSIS61505.2024.10459498","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459498","url":null,"abstract":"This research investigates the significant impact of technology on the transformation of Human Resource Management (HRM), with a specific emphasis on the modernization of conventional HR procedures. The integration of technology into Human Resource Management (HRM) is essential in the contemporary business landscape to augment organizational efficiency and effectiveness. This research provides a critical evaluation of the influence of digital breakthroughs, such as Artificial Intelligence (AI), Machine Learning (ML), Big Data analytics, and cloud computing, on human resources (HR) operations. The use of these technologies is significantly influencing diverse human resources strategies, namely in the areas of recruiting, performance management, and employee engagement. This is achieved via the incorporation of predictive analytics and datadriven approaches, which facilitate informed decision-making processes. The study emphasizes the impact of these technology instruments on enhancing operational effectiveness and enabling HR practitioners to transition from administrative responsibilities to strategic positions in workforce planning, talent management, and organizational growth. This research explores the ramifications of technological advancements on workers and employers, specifically focusing on the difficulties and advantages associated with incorporating technology into human resource management. Through a comprehensive examination of contemporary scholarly literature and empirical investigations, this research tries to establish a connection between theoretical constructs and their tangible application. This resource is very beneficial for professionals in the field of human resources, as well as researchers and organizational leaders. It assists them in effectively navigating and managing the intricate challenges of modern human resource management within a technologically sophisticated environment.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459604
Saira Yaqub, Saikat Gochhait, Hafiz Abdul Haseeb Khalid, Syeda Noreen Bukhari, Ayesha Yaqub, Muhammad Abubakr
WhatsApp has become a widely used medium to communicate in the modern era of technology, fostering diverse conversations and expressions among millions of users worldwide. This research introduces a robust analytical tool, the “WhatsApp Chat Ana-lyzer,” crafted to dissect and visualize the multifaceted landscape of group chats on WhatsApp. Imbued with Python's prowess and fortified by Streamlit, matplotlib, and Seaborn, the tool transcends conventional analyses by providing nuanced insights into user behavior, message statistics, and emerging content trends. In this research, we embark on an exploratory journey to decipher the complex dynamics embedded within WhatsApp group chats. By amalgamating sophisticated data preprocessing techniques, advanced statistical analyses, and captivating visualizations, the “WhatsApp Chat Analyzer” stands as a testament to our commitment to unraveling the facts of modern digital communication.
{"title":"WhatsApp Chat Analysis: Unveiling Insights through Data Processing and Visualization Techniques","authors":"Saira Yaqub, Saikat Gochhait, Hafiz Abdul Haseeb Khalid, Syeda Noreen Bukhari, Ayesha Yaqub, Muhammad Abubakr","doi":"10.1109/ICETSIS61505.2024.10459604","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459604","url":null,"abstract":"WhatsApp has become a widely used medium to communicate in the modern era of technology, fostering diverse conversations and expressions among millions of users worldwide. This research introduces a robust analytical tool, the “WhatsApp Chat Ana-lyzer,” crafted to dissect and visualize the multifaceted landscape of group chats on WhatsApp. Imbued with Python's prowess and fortified by Streamlit, matplotlib, and Seaborn, the tool transcends conventional analyses by providing nuanced insights into user behavior, message statistics, and emerging content trends. In this research, we embark on an exploratory journey to decipher the complex dynamics embedded within WhatsApp group chats. By amalgamating sophisticated data preprocessing techniques, advanced statistical analyses, and captivating visualizations, the “WhatsApp Chat Analyzer” stands as a testament to our commitment to unraveling the facts of modern digital communication.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459383
A. Al-Alawi, Fatema Ahmed AlBinAli
Disengagement and turnover of employees are significant costs to organizations worldwide. In many organizations, it isn't easy to foster continuous engagement among employees. Analytically-driven performance management aims to capture and analyze workplace data with advanced analytical techniques to develop a sustainable solution. This systematic literature review (SLR) examines and analyzes frameworks proposed for optimizing engagement and retention through performance analytics. Among the forty initial papers screened, twenty-four highly relevant sources were selected and analyzed. Human resources (HR) related key themes included bias issues, text analysis of reviews, personalized HR management, talent assessments, augmenting HR work with Artificial Intelligence (AI), and integration challenges. According to the findings, a reliable emphasis was placed on the balance of human and machine perspectives. While analytics and algorithms offer insightful information, human judgment is needed to contextualize this data. If datadriven methods are the only ones used, complicated personal aspects that influence experience may be overlooked. Consequently, a human-machine strategy working together is crucial. Furthermore, effective integration requires both strategy alignment and cultural preparedness. Longitudinal evaluations and more real-world case studies help close gaps in the literature. Analytics with human-centric frameworks can maximize engagement and performance management.
{"title":"Unveiling the Retention Puzzle for Optimizing Employee Engagement and Loyalty Through Analytics-Driven Performance Management: A Systematic Literature Review","authors":"A. Al-Alawi, Fatema Ahmed AlBinAli","doi":"10.1109/ICETSIS61505.2024.10459383","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459383","url":null,"abstract":"Disengagement and turnover of employees are significant costs to organizations worldwide. In many organizations, it isn't easy to foster continuous engagement among employees. Analytically-driven performance management aims to capture and analyze workplace data with advanced analytical techniques to develop a sustainable solution. This systematic literature review (SLR) examines and analyzes frameworks proposed for optimizing engagement and retention through performance analytics. Among the forty initial papers screened, twenty-four highly relevant sources were selected and analyzed. Human resources (HR) related key themes included bias issues, text analysis of reviews, personalized HR management, talent assessments, augmenting HR work with Artificial Intelligence (AI), and integration challenges. According to the findings, a reliable emphasis was placed on the balance of human and machine perspectives. While analytics and algorithms offer insightful information, human judgment is needed to contextualize this data. If datadriven methods are the only ones used, complicated personal aspects that influence experience may be overlooked. Consequently, a human-machine strategy working together is crucial. Furthermore, effective integration requires both strategy alignment and cultural preparedness. Longitudinal evaluations and more real-world case studies help close gaps in the literature. Analytics with human-centric frameworks can maximize engagement and performance management.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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