Pub Date : 2022-09-06DOI: 10.36965/ojakm.2022.10(1)24-42
D. Patrishkoff, S. Bronsburg, Mariah Ali
This research focuses on predicting the patient discharge disposition with initial patient assessment and therapy data as well as determining which therapy intervention text had positive impacts on hypertension heart disease patients in home healthcare environments. Older adults prefer to stay in their home, which is known as aging in place. Home healthcare is the last line of defense before advancing to other expensive healthcare options. This research used aggregate transactional data from 2,181 home healthcare patients in the United States (U.S.) from 2016-2022. We used the Centers for Disease Control and Prevention (CDC) Patient Driven Groupings Model and focused on the cardiac circulatory patient’s subcategory of hypertensive heart disease. Data was analyzed from Activity of Daily Life (ADL) assessment scores, the number of disease diagnosis codes per patient, the number of additional cardiac comorbidities, gender, age, standardized hospitalization risks, number of medications per patient, number of interventions per patient, and the length of stay in home healthcare. Machine learning and advanced text analysis were applied to determine which factors and therapy intervention text had the biggest impact on hypertensive heart disease patient outcomes. This research also identified those interventions with the best Signal to Noise (SN) ratios that are currently being piloted in home healthcare settings.
{"title":"Applying machine learning and text analysis to identify factors that may predict hypertensive heart disease patient outcomes in home healthcare","authors":"D. Patrishkoff, S. Bronsburg, Mariah Ali","doi":"10.36965/ojakm.2022.10(1)24-42","DOIUrl":"https://doi.org/10.36965/ojakm.2022.10(1)24-42","url":null,"abstract":"This research focuses on predicting the patient discharge disposition with initial patient assessment and therapy data as well as determining which therapy intervention text had positive impacts on hypertension heart disease patients in home healthcare environments. Older adults prefer to stay in their home, which is known as aging in place. Home healthcare is the last line of defense before advancing to other expensive healthcare options. This research used aggregate transactional data from 2,181 home healthcare patients in the United States (U.S.) from 2016-2022. We used the Centers for Disease Control and Prevention (CDC) Patient Driven Groupings Model and focused on the cardiac circulatory patient’s subcategory of hypertensive heart disease. Data was analyzed from Activity of Daily Life (ADL) assessment scores, the number of disease diagnosis codes per patient, the number of additional cardiac comorbidities, gender, age, standardized hospitalization risks, number of medications per patient, number of interventions per patient, and the length of stay in home healthcare. Machine learning and advanced text analysis were applied to determine which factors and therapy intervention text had the biggest impact on hypertensive heart disease patient outcomes. This research also identified those interventions with the best Signal to Noise (SN) ratios that are currently being piloted in home healthcare settings.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128130219","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 : 2021-12-26DOI: 10.36965/ojakm.2021.9(2)65-85
Mical Michelle Ramim, Angel Hueca
Capacity building of human capital can be described as the experience, knowledge, skill sets, and intangible assets that add economic value to individuals and the organizations they work for. With the ever-growing gap in cybersecurity skill sets, it is essential to have a shared understanding of the necessary current skills and what those skills represent in the form of human capital to not only individuals, but also the organizations they work for. As nations around the world are struggling with the increased dependencies on Information Systems (IS) and the massive cybersecurity incidents resulting from adversaries, it is evident that cybersecurity human capital is the key in overcoming such challenges. With that said, while major players fighting cyber adversaries such as the United States (U.S.) and other western nations are struggling with their own significant cybersecurity human capital shortage, less developed nations are even further challenged. For example, African nations continue to acquire and implement ISs, the pace in which these technologies are adopted outnumbers the rate at which the skills to protect these technologies are captured. In this study we introduce the concept of cybersecurity human capital at the national level in the African region, as well as specific steps necessary to develop and embed current cybersecurity skills in cybersecurity human capital. We discuss the challenges faced by Sub-Saharan African nations in the journey to develop their cybersecurity human capital at the national level. An overview of the programs developed by the U.S. Department of State’s Office of the Coordinator for Cyber Issues is provided across three case studies.
{"title":"Cybersecurity capacity building of human capital: Nations supporting nations","authors":"Mical Michelle Ramim, Angel Hueca","doi":"10.36965/ojakm.2021.9(2)65-85","DOIUrl":"https://doi.org/10.36965/ojakm.2021.9(2)65-85","url":null,"abstract":"Capacity building of human capital can be described as the experience, knowledge, skill sets, and intangible assets that add economic value to individuals and the organizations they work for. With the ever-growing gap in cybersecurity skill sets, it is essential to have a shared understanding of the necessary current skills and what those skills represent in the form of human capital to not only individuals, but also the organizations they work for. As nations around the world are struggling with the increased dependencies on Information Systems (IS) and the massive cybersecurity incidents resulting from adversaries, it is evident that cybersecurity human capital is the key in overcoming such challenges. With that said, while major players fighting cyber adversaries such as the United States (U.S.) and other western nations are struggling with their own significant cybersecurity human capital shortage, less developed nations are even further challenged. For example, African nations continue to acquire and implement ISs, the pace in which these technologies are adopted outnumbers the rate at which the skills to protect these technologies are captured. In this study we introduce the concept of cybersecurity human capital at the national level in the African region, as well as specific steps necessary to develop and embed current cybersecurity skills in cybersecurity human capital. We discuss the challenges faced by Sub-Saharan African nations in the journey to develop their cybersecurity human capital at the national level. An overview of the programs developed by the U.S. Department of State’s Office of the Coordinator for Cyber Issues is provided across three case studies.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134379719","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 : 2021-12-22DOI: 10.36965/ojakm.2021.9(2)28-45
Sandra Bissoon-Maharaj, R. Maharaj
There appears to exist limited research regarding the integration of Knowledge Management (KM) and International Organization for Standardization (ISO)’s ISO9001 Quality Management Systems (QMS) for Small and Medium Sized Enterprises (SMEs), for Trinidad and Tobago (TT) and the Caribbean Region. TT has over 16,000 SMEs and approximately 10,000 micro enterprises, representing over 70% of all registered businesses, that employs over 50% of the workforce. SMEs spark competition, create jobs, as well as promote innovation and knowledge transfer, thus are the engine of economic growth. SMEs in TT need to develop KM practices to compete regionally and globally, especially with the advent of the COVID-19 pandemic, which has triggered the deepest economic recession worldwide. Existing integrated KM models in other jurisdictions cannot be adopted in TT as KM is a culturally sensitive platform that needs to be customized to its applied environment. Results of a survey identified the Critical Success Factors (CSFs) for both Quality Management (QM) and KM required for the successful implementation of a Knowledge Management System (KMS). Data obtained showed that although the SMEs in TT demonstrated insignificant KM maturity, there is KM readiness, due to the existence of QMSs, significant information systems, human resource support, technical infrastructure, and senior management commitment. A five phase KM/QM integration model for SMEs in TT is proposed. Managers of SMEs and other similar operations may apply the findings of this study to develop strategies to integrate QM and KM to improve business results.
{"title":"Development of an integrated knowledge management and quality management model for small and medium sized companies in Trinidad and Tobago","authors":"Sandra Bissoon-Maharaj, R. Maharaj","doi":"10.36965/ojakm.2021.9(2)28-45","DOIUrl":"https://doi.org/10.36965/ojakm.2021.9(2)28-45","url":null,"abstract":"There appears to exist limited research regarding the integration of Knowledge Management (KM) and International Organization for Standardization (ISO)’s ISO9001 Quality Management Systems (QMS) for Small and Medium Sized Enterprises (SMEs), for Trinidad and Tobago (TT) and the Caribbean Region. TT has over 16,000 SMEs and approximately 10,000 micro enterprises, representing over 70% of all registered businesses, that employs over 50% of the workforce. SMEs spark competition, create jobs, as well as promote innovation and knowledge transfer, thus are the engine of economic growth. SMEs in TT need to develop KM practices to compete regionally and globally, especially with the advent of the COVID-19 pandemic, which has triggered the deepest economic recession worldwide. Existing integrated KM models in other jurisdictions cannot be adopted in TT as KM is a culturally sensitive platform that needs to be customized to its applied environment. Results of a survey identified the Critical Success Factors (CSFs) for both Quality Management (QM) and KM required for the successful implementation of a Knowledge Management System (KMS). Data obtained showed that although the SMEs in TT demonstrated insignificant KM maturity, there is KM readiness, due to the existence of QMSs, significant information systems, human resource support, technical infrastructure, and senior management commitment. A five phase KM/QM integration model for SMEs in TT is proposed. Managers of SMEs and other similar operations may apply the findings of this study to develop strategies to integrate QM and KM to improve business results.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"7 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133411627","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 : 2021-12-22DOI: 10.36965/ojakm.2021.9(2)46-64
Rodolfo Vareschi, W. Picoto
Due to the rapid global spread of the pandemic caused by the new coronavirus, companies and institutions adopted precautionary measures to reduce the risk of contagion, such as asking employees to work remotely from their homes. In this scenario, cloud computing technology has proven to be a great ally of companies to overcome the crisis caused by the pandemic as it provides the necessary infrastructure to access the organizational systems and resources from anyplace, anywhere, and anytime. Although current research identifies important factors for cloud computing adoption, none has yet analyzed whether those are the same given the crisis cause by the pandemic. For this purpose, 18 factors were identified and presented to experts in cloud computing technology, to seek a consensus regarding the order of importance of these factors. Using the Delphi method conducted with two rounds of questions, an ordered list according to the degree of importance of the main factors that influence the adoption of cloud computing was obtained. According to the results, the six most important factors are: (1) adoption, migration, and acquisition cost; (2) availability and accessibility; (3) scalability; (4) cost of data confidentiality and availability loss; (5) security, and (6) customization.
{"title":"The critical factors for cloud computing adoption during SARS-CoV-2 pandemic","authors":"Rodolfo Vareschi, W. Picoto","doi":"10.36965/ojakm.2021.9(2)46-64","DOIUrl":"https://doi.org/10.36965/ojakm.2021.9(2)46-64","url":null,"abstract":"Due to the rapid global spread of the pandemic caused by the new coronavirus, companies and institutions adopted precautionary measures to reduce the risk of contagion, such as asking employees to work remotely from their homes. In this scenario, cloud computing technology has proven to be a great ally of companies to overcome the crisis caused by the pandemic as it provides the necessary infrastructure to access the organizational systems and resources from anyplace, anywhere, and anytime. Although current research identifies important factors for cloud computing adoption, none has yet analyzed whether those are the same given the crisis cause by the pandemic. For this purpose, 18 factors were identified and presented to experts in cloud computing technology, to seek a consensus regarding the order of importance of these factors. Using the Delphi method conducted with two rounds of questions, an ordered list according to the degree of importance of the main factors that influence the adoption of cloud computing was obtained. According to the results, the six most important factors are: (1) adoption, migration, and acquisition cost; (2) availability and accessibility; (3) scalability; (4) cost of data confidentiality and availability loss; (5) security, and (6) customization.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131532603","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 : 2021-12-20DOI: 10.36965/ojakm.2021.9(2)1-27
Joanna Krywalski Santiago, Miguel Pimenta
This paper follows the recent areas of interest trucked by Google Trends to investigate the importance of the customers’ technological savviness and firm’s social media communication at creation of brand equity. A special attention is paid at the so called ‘Net generation’ and its behavior during COVID-19 pandemic. The data was collected through an online survey distributed in Portugal with the assistance of Qualtrics online survey platform and counted with respondents that had a prior experience in following or engaging with brands on social media. To understand the relationships between Customer Technology Savviness (CTS), firm’s Social Media Communication (SMC) and Customer-Based Brand Equity (CBBE), this study applies the Partial Last Squares method of Structural Equation Modeling (PLS-SEM). The results of the multigroup analysis show that customers who used social media more heavily during pandemic denoted a stronger relationship between CTS and CBBE, CTS and SMC and between SMC and CBBE, of which the last was not confirmed in case of customers who made less use of social media since the outbreak of COVID-19 pandemic.
{"title":"The Net generation in times of pandemic: Customers’ technology savviness and social media communication impact on customer-based brand equity","authors":"Joanna Krywalski Santiago, Miguel Pimenta","doi":"10.36965/ojakm.2021.9(2)1-27","DOIUrl":"https://doi.org/10.36965/ojakm.2021.9(2)1-27","url":null,"abstract":"This paper follows the recent areas of interest trucked by Google Trends to investigate the importance of the customers’ technological savviness and firm’s social media communication at creation of brand equity. A special attention is paid at the so called ‘Net generation’ and its behavior during COVID-19 pandemic. The data was collected through an online survey distributed in Portugal with the assistance of Qualtrics online survey platform and counted with respondents that had a prior experience in following or engaging with brands on social media. To understand the relationships between Customer Technology Savviness (CTS), firm’s Social Media Communication (SMC) and Customer-Based Brand Equity (CBBE), this study applies the Partial Last Squares method of Structural Equation Modeling (PLS-SEM). The results of the multigroup analysis show that customers who used social media more heavily during pandemic denoted a stronger relationship between CTS and CBBE, CTS and SMC and between SMC and CBBE, of which the last was not confirmed in case of customers who made less use of social media since the outbreak of COVID-19 pandemic.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125908073","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 : 2021-11-23DOI: 10.36965/ojakm.2021.9(1)62-81
G. Kaupins
As a variety of electronic monitoring methods such as global positioning systems are available, monitoring employees without notice is a consideration even though several laws ban it and ethical questions remain. Monitoring without notice has risks that Human Resources (HR) managers should consider when they set monitoring policies to enhance knowledge management. A total of 174 HR managers were asked about their top reasons to electronically monitor employees with or without notice. About half received information that a company did not notify employees of electronic monitoring and the other half received the opposite information. Prospect theory was the basis for collecting data to understand the importance of risk in setting policies. It states that people in perceived good conditions avoid risk because they feel there is more to lose than to gain. The leading reason to electronically monitor employees for both groups was computer virus and malware protection. Organizational threats associated with legal issues showed more HR support for monitoring without notice. Opportunities associated with employee productivity indicated relatively more support for monitoring with notice. As a result of this research, perceived threats in the workplace are significant reasons why HR managers might not provide notice of monitoring in the workplace. This has potential legal and ethical implications.
{"title":"Effects of employee monitoring notification policies on HR manager opinions","authors":"G. Kaupins","doi":"10.36965/ojakm.2021.9(1)62-81","DOIUrl":"https://doi.org/10.36965/ojakm.2021.9(1)62-81","url":null,"abstract":"As a variety of electronic monitoring methods such as global positioning systems are available, monitoring employees without notice is a consideration even though several laws ban it and ethical questions remain. Monitoring without notice has risks that Human Resources (HR) managers should consider when they set monitoring policies to enhance knowledge management. A total of 174 HR managers were asked about their top reasons to electronically monitor employees with or without notice. About half received information that a company did not notify employees of electronic monitoring and the other half received the opposite information. Prospect theory was the basis for collecting data to understand the importance of risk in setting policies. It states that people in perceived good conditions avoid risk because they feel there is more to lose than to gain. The leading reason to electronically monitor employees for both groups was computer virus and malware protection. Organizational threats associated with legal issues showed more HR support for monitoring without notice. Opportunities associated with employee productivity indicated relatively more support for monitoring with notice. As a result of this research, perceived threats in the workplace are significant reasons why HR managers might not provide notice of monitoring in the workplace. This has potential legal and ethical implications.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134461697","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 : 2021-11-23DOI: 10.36965/ojakm.2021.9(1)46-61
André Rosendorff, A. Hodes, Benjamin Fabian
Artificial Intelligence (AI) is becoming increasingly important in many industries due to its diverse areas of application and potential. In logistics in particular, increasing customer demands and the growth in shipment volumes are leading to difficulties in forecasting delivery times, especially for the last mile. This paper explores the potential of using AI to improve delivery forecasting. For this purpose, a structured theoretical solution approach and a method for improving delivery forecasting using AI are presented. In doing so, the important phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, a standard process for data mining, are adopted and discussed in detail to illustrate the complexity and importance of each task such as data preparation or evaluation. Subsequently, by embedding the described solution into an overall system architecture for information systems, ideas for the integration of the solution into the complexity of real information systems for logistics are given.
{"title":"Artificial intelligence for last-mile logistics - Procedures and architecture","authors":"André Rosendorff, A. Hodes, Benjamin Fabian","doi":"10.36965/ojakm.2021.9(1)46-61","DOIUrl":"https://doi.org/10.36965/ojakm.2021.9(1)46-61","url":null,"abstract":"Artificial Intelligence (AI) is becoming increasingly important in many industries due to its diverse areas of application and potential. In logistics in particular, increasing customer demands and the growth in shipment volumes are leading to difficulties in forecasting delivery times, especially for the last mile. This paper explores the potential of using AI to improve delivery forecasting. For this purpose, a structured theoretical solution approach and a method for improving delivery forecasting using AI are presented. In doing so, the important phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, a standard process for data mining, are adopted and discussed in detail to illustrate the complexity and importance of each task such as data preparation or evaluation. Subsequently, by embedding the described solution into an overall system architecture for information systems, ideas for the integration of the solution into the complexity of real information systems for logistics are given.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125422762","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 : 2021-08-26DOI: 10.36965/ojakm.2021.9(1)16-30
S. Scipioni
As a dynamic phenomenon that interacts across different levels – individual, group, organizational, interorganizational – the development of a unique multilevel theory of Organizational Learning (OL) is absent and challenging. The intent of this paper is to contribute to the advancement of such a theory. In this context, a systematic review of the 2004-2020 literature was carried out, with analysis of 120 papers selected from management and organization science top-ranked journals. Based on the conceptualization of OL as multiple processes of knowledge creation, transfer, and retention, the reviewed papers highlight that internal and external environments, organizational culture, strategy, structure, leadership, technology, and shared environments need to be considered for a comprehensive understanding of vertical trickle-down OL processes, and of bottom-up emerging OL processes, in both single and multi-level OL analyses. This study contributes to the theory of OL with the presentation of a novel taxonomy of contextual factors that could help researchers in the development of comprehensive OL studies. The implications offered should support the definition of a multilevel theory for OL that embraces all the relevant factors that influence its processes across the different organizational levels. The review closes with specific recommendations for further studies in OL.
{"title":"A novel taxonomy of organizational learning contextual factors: Review of 2004–2020 top-ranked journals","authors":"S. Scipioni","doi":"10.36965/ojakm.2021.9(1)16-30","DOIUrl":"https://doi.org/10.36965/ojakm.2021.9(1)16-30","url":null,"abstract":"As a dynamic phenomenon that interacts across different levels – individual, group, organizational, interorganizational – the development of a unique multilevel theory of Organizational Learning (OL) is absent and challenging. The intent of this paper is to contribute to the advancement of such a theory. In this context, a systematic review of the 2004-2020 literature was carried out, with analysis of 120 papers selected from management and organization science top-ranked journals. Based on the conceptualization of OL as multiple processes of knowledge creation, transfer, and retention, the reviewed papers highlight that internal and external environments, organizational culture, strategy, structure, leadership, technology, and shared environments need to be considered for a comprehensive understanding of vertical trickle-down OL processes, and of bottom-up emerging OL processes, in both single and multi-level OL analyses. This study contributes to the theory of OL with the presentation of a novel taxonomy of contextual factors that could help researchers in the development of comprehensive OL studies. The implications offered should support the definition of a multilevel theory for OL that embraces all the relevant factors that influence its processes across the different organizational levels. The review closes with specific recommendations for further studies in OL.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131296082","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 : 2021-07-26DOI: 10.36965/ojakm.2021.9(1)31-45
Emily Africk, Y. Levy
Data breach incidents are reported in the media to be on the rise with continuously increasing numbers. Additionally, data breaches serve a major negative impact to organizations. This study focuses on combining experience in data analytics, visualization, and quantitative analysis for business intelligence in the context of cybersecurity big-data over a period of 15-years. A large data set containing 9,015 data breaches was provided via the Privacy Rights Clearinghouse data breach database from the start of 2005 to the end of 2019. The aim of this work was to slice the data as well as represent it into a business-related visualization using time-series analysis that can help executives understand complex cybersecurity breaches, their impact, and their trend over time. We have created visualization figures along with explanations of what each visualization means in the context of cyber-attacks over time. This project was set to serve as a breakdown of the important findings from the Privacy Rights Clearinghouse data breach database of over 15-years. These findings are communicated through both key numbers and quantitative analyses for business intelligence. While our project does not cover every aspect of the dataset (due to its significant size), it serves more as a focus on one particular part of the data: incident types and their volume over the 15-year timeframe to help business executives visualize cybersecurity trends. This paper ends with a conclusion and discussion on how such cybersecurity visualizations can help industries along with future research needed.
媒体报道的数据泄露事件呈上升趋势，数量不断增加。此外，数据泄露会对组织产生重大的负面影响。本研究的重点是结合15年来网络安全大数据背景下商业智能的数据分析、可视化和定量分析经验。从2005年初到2019年底，Privacy Rights Clearinghouse数据泄露数据库提供了一个包含9015个数据泄露的大型数据集。这项工作的目的是对数据进行切片，并使用时间序列分析将其表示为与业务相关的可视化，这可以帮助高管了解复杂的网络安全漏洞、它们的影响以及它们随时间的趋势。随着时间的推移，我们创建了可视化图形，并解释了每种可视化在网络攻击背景下的含义。本项目旨在对隐私权信息交换所数据泄露数据库中超过15年的重要发现进行分类。这些发现通过关键数字和商业智能的定量分析来传达。虽然我们的项目没有涵盖数据集的每个方面(由于其规模很大)，但它更多地关注数据的一个特定部分:事件类型及其在15年时间框架内的数量，以帮助企业高管可视化网络安全趋势。本文最后总结并讨论了网络安全可视化如何帮助各行业以及未来所需的研究。
{"title":"An examination of historic data breach incidents: What cybersecurity big data visualization and analytics can tell us?","authors":"Emily Africk, Y. Levy","doi":"10.36965/ojakm.2021.9(1)31-45","DOIUrl":"https://doi.org/10.36965/ojakm.2021.9(1)31-45","url":null,"abstract":"Data breach incidents are reported in the media to be on the rise with continuously increasing numbers. Additionally, data breaches serve a major negative impact to organizations. This study focuses on combining experience in data analytics, visualization, and quantitative analysis for business intelligence in the context of cybersecurity big-data over a period of 15-years. A large data set containing 9,015 data breaches was provided via the Privacy Rights Clearinghouse data breach database from the start of 2005 to the end of 2019. The aim of this work was to slice the data as well as represent it into a business-related visualization using time-series analysis that can help executives understand complex cybersecurity breaches, their impact, and their trend over time. We have created visualization figures along with explanations of what each visualization means in the context of cyber-attacks over time. This project was set to serve as a breakdown of the important findings from the Privacy Rights Clearinghouse data breach database of over 15-years. These findings are communicated through both key numbers and quantitative analyses for business intelligence. While our project does not cover every aspect of the dataset (due to its significant size), it serves more as a focus on one particular part of the data: incident types and their volume over the 15-year timeframe to help business executives visualize cybersecurity trends. This paper ends with a conclusion and discussion on how such cybersecurity visualizations can help industries along with future research needed.","PeriodicalId":325473,"journal":{"name":"Online Journal of Applied Knowledge Management","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115357720","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 : 2021-07-26DOI: 10.36965/ojakm.2021.9(1)1-15
Vered Silber Varod, Ingo Siegert, O. Jokisch, Yamini Sinha, N. Geri
Despite the growing importance of Automatic Speech Recognition (ASR), its application is still challenging, limited, language-dependent, and requires considerable resources. The resources required for ASR are not only technical, they also need to reflect technological trends and cultural diversity. The purpose of this research is to explore ASR performance gaps by a comparative study of American English, German, and Hebrew. Apart from different languages, we also investigate different speaking styles – utterances from spontaneous dialogues and utterances from frontal lectures (TED-like genre). The analysis includes a comparison of the performance of four ASR engines (Google Cloud, Google Search, IBM Watson, and WIT.ai) using four commonly used metrics: Word Error Rate (WER); Character Error Rate (CER); Word Information Lost (WIL); and Match Error Rate (MER). As expected, findings suggest that English ASR systems provide the best results. Contrary to our hypothesis regarding ASR’s low performance for under-resourced languages, we found that the Hebrew and German ASR systems have similar performance. Overall, our findings suggest that ASR performance is language-dependent and system-dependent. Furthermore, ASR may be genre-sensitive, as our results showed for German. This research contributes a valuable insight for improving ubiquitous global consumption and management of knowledge and calls for corporate social responsibility of commercial companies, to develop ASR under Fair, Reasonable, and Non-Discriminatory (FRAND) terms
尽管自动语音识别(ASR)越来越重要，但其应用仍然具有挑战性，局限性，语言依赖性，并且需要大量资源。ASR所需的资源不仅是技术资源，还需要反映技术趋势和文化多样性。本研究的目的是通过对美国英语、德语和希伯来语的比较研究来探讨ASR的表现差距。除了不同的语言，我们还研究了不同的说话风格——来自自发对话的话语和来自正面演讲的话语(类似ted的类型)。该分析包括使用四个常用指标对四个自动语音识别引擎(Google Cloud, Google Search, IBM Watson和WIT.ai)的性能进行比较:单词错误率(WER);字符错误率;单词信息丢失;和匹配错误率(MER)。正如预期的那样，研究结果表明英语ASR系统提供了最好的结果。与我们关于资源不足语言的ASR低性能的假设相反，我们发现希伯来语和德语ASR系统具有相似的性能。总的来说，我们的研究结果表明，ASR的表现依赖于语言和系统。此外，ASR可能是体裁敏感的，正如我们对德语的研究结果所显示的那样。本研究为改善全球无处不在的知识消费和管理提供了有价值的见解，并呼吁商业公司履行企业社会责任，在公平、合理和非歧视(FRAND)的条件下发展ASR
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