This study aimed to synthesize the literature on Metaverse to highlight its current research, opportunities, and applications in e-healthcare and education to reduce inequalities and for delivering fair and equal opportunities and solutions. The authors employed preferred reporting items for systematic reviews and meta-analyses (PRISMA) to rapidly map the field of a metaverse in health and education. Two major application domains emerged in the literature from the 88 research publications, which include (1) Metaverse in healthcare and (2) Metaverse in education. This study will act as a road map to help academics who desire to continue their research work in the Metaverse for various healthcare and educational services. However, its implementation is required in the future to improve mental healthcare and the effectiveness of mental health services, particularly in low and medium-income (LMIC) and conflict-affected areas.
{"title":"Metaverse!: Possible Potential Opportunities and Trends in E-Healthcare and Education","authors":"E. Mohamed, T. Naqishbandi, G. Veronese","doi":"10.4018/ijea.316537","DOIUrl":"https://doi.org/10.4018/ijea.316537","url":null,"abstract":"This study aimed to synthesize the literature on Metaverse to highlight its current research, opportunities, and applications in e-healthcare and education to reduce inequalities and for delivering fair and equal opportunities and solutions. The authors employed preferred reporting items for systematic reviews and meta-analyses (PRISMA) to rapidly map the field of a metaverse in health and education. Two major application domains emerged in the literature from the 88 research publications, which include (1) Metaverse in healthcare and (2) Metaverse in education. This study will act as a road map to help academics who desire to continue their research work in the Metaverse for various healthcare and educational services. However, its implementation is required in the future to improve mental healthcare and the effectiveness of mental health services, particularly in low and medium-income (LMIC) and conflict-affected areas.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129008616","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}
This paper focuses on determining the age-based differences among consumers in terms of the acceptance of mobile social media. In doing so, the younger age group is represented by Generation Y and the elderly by Baby Boomers. Further, the famous UTAUT2 model is applied, and relationships mentioned in it are evaluated for the two age groups. For this purpose, a sample of 249 respondents was obtained from the online survey conducted in the state of Punjab in India. The statistical technique of multi-group path analysis using structural equation modelling (SEM) is applied to the generated data. The findings of the study reveal that the young age and elderly groups differ significantly in terms of the impact of effort expectancy, facilitating conditions, hedonic motivation on behavioral intention, and facilitating conditions on use behavior. It may provide important implications for future research related to internet marketing and mobile social media.
{"title":"Age in the Acceptance of Mobile Social Media: A Comparison of Generation Y and Baby Boomers Using UTAUT2 Model","authors":"Savdeep Vasudeva","doi":"10.4018/ijea.316173","DOIUrl":"https://doi.org/10.4018/ijea.316173","url":null,"abstract":"This paper focuses on determining the age-based differences among consumers in terms of the acceptance of mobile social media. In doing so, the younger age group is represented by Generation Y and the elderly by Baby Boomers. Further, the famous UTAUT2 model is applied, and relationships mentioned in it are evaluated for the two age groups. For this purpose, a sample of 249 respondents was obtained from the online survey conducted in the state of Punjab in India. The statistical technique of multi-group path analysis using structural equation modelling (SEM) is applied to the generated data. The findings of the study reveal that the young age and elderly groups differ significantly in terms of the impact of effort expectancy, facilitating conditions, hedonic motivation on behavioral intention, and facilitating conditions on use behavior. It may provide important implications for future research related to internet marketing and mobile social media.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123590258","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}
S. Sneha, Avijit Singh, Anshu Singh, Madhu Bhadauria, Christopher Burgess, Lisero Mugula
As a result of COVID-19, a new approach for delivering eye care services to rural underprivileged areas were needed to improve eye disease outcomes. Sitapur Eye Hospital used a door-to-door model of medical delivery to alleviate the inability of rural residents from not receiving appropriate eye care during the COVID-19 pandemic. Sitapur Eye Hospital utilizes a healthcare delivery model that involves visiting patients door-to-door. The total number of patients that Sitapur Eye Hospital examined went from screening no patients in the months of April and May to screening 31,017 patients via the door-to-door service that was implemented in June 2020. Sitapur Eye Hospital managed to keep the prevalence of people who had severe eye impairment at pre-pandemic levels by offering a door-to-door service to patients who were unable to access appropriate medical care. The door-to-door healthcare model shows that leveraging telehealth and ride-hailing services alleviate certain barriers that make it difficult for people in rural areas to access eye care.
{"title":"Teleophthalmology: A Case of Eye Care Delivery","authors":"S. Sneha, Avijit Singh, Anshu Singh, Madhu Bhadauria, Christopher Burgess, Lisero Mugula","doi":"10.4018/ijea.316538","DOIUrl":"https://doi.org/10.4018/ijea.316538","url":null,"abstract":"As a result of COVID-19, a new approach for delivering eye care services to rural underprivileged areas were needed to improve eye disease outcomes. Sitapur Eye Hospital used a door-to-door model of medical delivery to alleviate the inability of rural residents from not receiving appropriate eye care during the COVID-19 pandemic. Sitapur Eye Hospital utilizes a healthcare delivery model that involves visiting patients door-to-door. The total number of patients that Sitapur Eye Hospital examined went from screening no patients in the months of April and May to screening 31,017 patients via the door-to-door service that was implemented in June 2020. Sitapur Eye Hospital managed to keep the prevalence of people who had severe eye impairment at pre-pandemic levels by offering a door-to-door service to patients who were unable to access appropriate medical care. The door-to-door healthcare model shows that leveraging telehealth and ride-hailing services alleviate certain barriers that make it difficult for people in rural areas to access eye care.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125978279","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}
Gaurav Nagpal, A. K. Ray, Nitisha Kharkwal, N. Jasti, Ankita Nagpal
Business analytics are transforming every industry in modern times, and the retail sector is not an exception to this. However, the adoption of analytics among small and medium enterprises is quite limited. There is a decent amount of research that has been done in the recent past on identifying the barriers of digitalization for small and medium enterprises. But any such work is missing in the case of analytics. Also, the small retailer, in particular, has been left untouched by the existing research studies when it comes to identifying what prohibits him from the use of analytics for making business decisions. Using a scientific way of data collection from small and mid-sized retailers and from retail industry experts, this study explores why the local retailers are reluctant to use analytics in their work and what can be done to make them more comfortable with the use of analytics. The study also proposes a novel framework for adoption of data analytics and titles it “SPEFSERT Framework.”
{"title":"Challenges in Adoption of Business Analytics by Small Retailers: An Empirical Study in the Indian Context","authors":"Gaurav Nagpal, A. K. Ray, Nitisha Kharkwal, N. Jasti, Ankita Nagpal","doi":"10.4018/ijea.316539","DOIUrl":"https://doi.org/10.4018/ijea.316539","url":null,"abstract":"Business analytics are transforming every industry in modern times, and the retail sector is not an exception to this. However, the adoption of analytics among small and medium enterprises is quite limited. There is a decent amount of research that has been done in the recent past on identifying the barriers of digitalization for small and medium enterprises. But any such work is missing in the case of analytics. Also, the small retailer, in particular, has been left untouched by the existing research studies when it comes to identifying what prohibits him from the use of analytics for making business decisions. Using a scientific way of data collection from small and mid-sized retailers and from retail industry experts, this study explores why the local retailers are reluctant to use analytics in their work and what can be done to make them more comfortable with the use of analytics. The study also proposes a novel framework for adoption of data analytics and titles it “SPEFSERT Framework.”","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128278236","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}
E-adoption of emerging technology plays an important role during the pandemic. The COVID-19 pandemic taught us that everyone must make himself healthy and immune to viral disease. Diabetes is the most common disease in the Indian population found in people of every age. The objective of this research work is to use the emerging technologies such as machine learning to implement e-adoption in the healthcare system. The proposed methodology can predict the diabetes disease by using vital parameters like age, glucose level, blood pressure, etc. This proposed model is implemented into Python programming language and various machine learning classifiers such as random forest, decision tree, logistic regression, and XGBoost are used on PIMA database. Thereafter, comparative analysis is performed to test which technique is better for predicting and diagnosing diabetes disease. The method founds XGBoost classifier gives the highest accuracy (i.e., 84%) among all classifiers with single database and single classifier.
{"title":"Advancement in Healthcare Systems by Automated Disease Diagnostic Process Using Machine Learning","authors":"S. Goel, R. Bharti, A. N. Rao","doi":"10.4018/ijea.310002","DOIUrl":"https://doi.org/10.4018/ijea.310002","url":null,"abstract":"E-adoption of emerging technology plays an important role during the pandemic. The COVID-19 pandemic taught us that everyone must make himself healthy and immune to viral disease. Diabetes is the most common disease in the Indian population found in people of every age. The objective of this research work is to use the emerging technologies such as machine learning to implement e-adoption in the healthcare system. The proposed methodology can predict the diabetes disease by using vital parameters like age, glucose level, blood pressure, etc. This proposed model is implemented into Python programming language and various machine learning classifiers such as random forest, decision tree, logistic regression, and XGBoost are used on PIMA database. Thereafter, comparative analysis is performed to test which technique is better for predicting and diagnosing diabetes disease. The method founds XGBoost classifier gives the highest accuracy (i.e., 84%) among all classifiers with single database and single classifier.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115001224","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}
Vidushi Mishra, Narendra Singh, Manisha Agarwal, A. Shrivastava
In the 21st century, COVID-19 made a profound impact on the world. This pandemic had a detrimental impact worldwide, causing massive economic damage and enormous mortality. Emerging technologies play an essential role in every sector, and the health sector is not exceptional in this line. This paper examines the health sector before, during, and after the COVID-19 era by taking a view of emerging technologies. Artificial intelligence, cloud computing, IoT, learning paradigms, blockchain, and others are emerging technologies. E-adoption of these technologies becomes important to face critical situations during COVID-19. Using these technologies, it is possible to care for and monitor remote patients by keeping medical record management. This study includes a brief examination of similar work. In addition, the impact of e-adoption on health sector is discussed in this research. Furthermore, this study suggested a paradigm for comprehending the application of developing technologies to manage and overcome the health sector's burden. Finally, research is concluded with remarks on the future.
{"title":"E-Adoption of Emerging Technology in the Health Sector During COVID-19","authors":"Vidushi Mishra, Narendra Singh, Manisha Agarwal, A. Shrivastava","doi":"10.4018/ijea.309999","DOIUrl":"https://doi.org/10.4018/ijea.309999","url":null,"abstract":"In the 21st century, COVID-19 made a profound impact on the world. This pandemic had a detrimental impact worldwide, causing massive economic damage and enormous mortality. Emerging technologies play an essential role in every sector, and the health sector is not exceptional in this line. This paper examines the health sector before, during, and after the COVID-19 era by taking a view of emerging technologies. Artificial intelligence, cloud computing, IoT, learning paradigms, blockchain, and others are emerging technologies. E-adoption of these technologies becomes important to face critical situations during COVID-19. Using these technologies, it is possible to care for and monitor remote patients by keeping medical record management. This study includes a brief examination of similar work. In addition, the impact of e-adoption on health sector is discussed in this research. Furthermore, this study suggested a paradigm for comprehending the application of developing technologies to manage and overcome the health sector's burden. Finally, research is concluded with remarks on the future.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114080625","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}
Since 2020, the coronavirus disease 2019 (COVID-19) pandemic and lockdown policy have changed our life drastically. Due to this, companies, offices, schools, etc. are running in online mode. Therefore, the demand for internet bandwidth is very popular nowadays. Due to an increase in demand for internet bandwidth and the availability of multihomed devices, multipath TCP (MPTCP), and e-adoption of emerging technology enhanced bandwidth by utilizing the bandwidth of all available networks simultaneously. This paper analyzes the working principle of the MPTCP so that each internet device can easily use MPTCP to achieve high bandwidth. Load distribution and its performance mainly depend on the congestion control algorithm and the packet scheduler. MPTCP has various existing packet scheduling algorithms and congestion control algorithms. Here, the authors compare the performance of MPTCP with each congestion control algorithm and packet scheduler one by one and try to find out the best-performing MPTCP. This paper also shows that the MPTCP helps COVID-19 patients in various aspects.
{"title":"An Enhanced Multipath TCP: E-Adoption of Emerging Technology for Better Internet Bandwidth","authors":"R. Chaturvedi, S. Chand, M. Tyagi","doi":"10.4018/ijea.309998","DOIUrl":"https://doi.org/10.4018/ijea.309998","url":null,"abstract":"Since 2020, the coronavirus disease 2019 (COVID-19) pandemic and lockdown policy have changed our life drastically. Due to this, companies, offices, schools, etc. are running in online mode. Therefore, the demand for internet bandwidth is very popular nowadays. Due to an increase in demand for internet bandwidth and the availability of multihomed devices, multipath TCP (MPTCP), and e-adoption of emerging technology enhanced bandwidth by utilizing the bandwidth of all available networks simultaneously. This paper analyzes the working principle of the MPTCP so that each internet device can easily use MPTCP to achieve high bandwidth. Load distribution and its performance mainly depend on the congestion control algorithm and the packet scheduler. MPTCP has various existing packet scheduling algorithms and congestion control algorithms. Here, the authors compare the performance of MPTCP with each congestion control algorithm and packet scheduler one by one and try to find out the best-performing MPTCP. This paper also shows that the MPTCP helps COVID-19 patients in various aspects.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133582175","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}
The accumulation of the blood leaks on the retina is known as diabetic macular edema (DME), which can result in irreversible blindness. Early diagnosis and therapy can stop DME. This study presents an e-adoption of emerging technology such as RadioDense model for detecting and classifying DME from retinal fundus images. The proposed model employs a modified version of DenseNet121, radiomics features, and the gradient boosting classifier. The authors evaluated many classifiers on the concatenated features. The efficacy of the classifier is determined by comparing each classifier's accuracy values. According to the evaluation results, the concatenated features extraction using gradient boosting classifier outperforms all other classifiers on the IDRiD dataset. For multi-class classification, the suggested electronic adoption of emerging technology such as RadioDense model outperformed these classifiers and attained an accuracy of 87.4%. It can help to decrease the strain of ophthalmologists diagnosing the DME during locking and unlocking the worldwide lockdown.
{"title":"Risk Identification of Diabetic Macular Edema Using E-Adoption of Emerging Technology","authors":"Ajay Kumar, Anand Shanker Tewari","doi":"10.4018/ijea.310000","DOIUrl":"https://doi.org/10.4018/ijea.310000","url":null,"abstract":"The accumulation of the blood leaks on the retina is known as diabetic macular edema (DME), which can result in irreversible blindness. Early diagnosis and therapy can stop DME. This study presents an e-adoption of emerging technology such as RadioDense model for detecting and classifying DME from retinal fundus images. The proposed model employs a modified version of DenseNet121, radiomics features, and the gradient boosting classifier. The authors evaluated many classifiers on the concatenated features. The efficacy of the classifier is determined by comparing each classifier's accuracy values. According to the evaluation results, the concatenated features extraction using gradient boosting classifier outperforms all other classifiers on the IDRiD dataset. For multi-class classification, the suggested electronic adoption of emerging technology such as RadioDense model outperformed these classifiers and attained an accuracy of 87.4%. It can help to decrease the strain of ophthalmologists diagnosing the DME during locking and unlocking the worldwide lockdown.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123154026","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}
Ashokkumar Palanivinayagam, V. Vinothkumar, T. Mahesh, Krishnavir Singh, Akansha Singh
In recent years, several machine learning models were successfully deployed in various fields. However, a huge quantity of data is required for training good machine learning. Data are distributivity stored across multiple sources and centralizing those data leads to privacy and security issues. To solve this problem, the proposed federated-based method works by exchanging the parameters of three locally trained machine learning models without compromising privacy. Each machine learning model uses the e-adoption of CT scans for improving their training knowledge. The CT scans are electronically transferred between various medical centers. Proper care is taken to prevent identify loss from the e-adopted data. To normalize the parameters, a novel weighting scheme is also exchanged along with the parameters. Thus, the global model is trained with more heterogeneous samples to increase performance. Based on the experiment, the proposed algorithm has obtained 89% of accuracy, which is 32% more than the existing machine learning models.
{"title":"Machine Learning-Based COVID-19 Classification Using E-Adopted CT Scans","authors":"Ashokkumar Palanivinayagam, V. Vinothkumar, T. Mahesh, Krishnavir Singh, Akansha Singh","doi":"10.4018/ijea.310001","DOIUrl":"https://doi.org/10.4018/ijea.310001","url":null,"abstract":"In recent years, several machine learning models were successfully deployed in various fields. However, a huge quantity of data is required for training good machine learning. Data are distributivity stored across multiple sources and centralizing those data leads to privacy and security issues. To solve this problem, the proposed federated-based method works by exchanging the parameters of three locally trained machine learning models without compromising privacy. Each machine learning model uses the e-adoption of CT scans for improving their training knowledge. The CT scans are electronically transferred between various medical centers. Proper care is taken to prevent identify loss from the e-adopted data. To normalize the parameters, a novel weighting scheme is also exchanged along with the parameters. Thus, the global model is trained with more heterogeneous samples to increase performance. Based on the experiment, the proposed algorithm has obtained 89% of accuracy, which is 32% more than the existing machine learning models.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125111680","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}
The escalating of mobile banking apps has decongested the banking hall, especially in developing countries, and the penetration of mobile banking apps is crucial for both financial institutions and customers. This study reviewed existing relevant literature from the Web of Science to position this study well and dwelled on a theoretical foundation for the exposition of the interrelation of trust and privacy as an antecedent of mobile banking app security. The quantitative method was employed and banking customers data using SmartPLS 3.0 version with different data analysis techniques such as structural equation modelling, multigroup data analysis, interaction effects, and importance-performance analysis. This study results show the intervention of gender and education. It also indicates that the orientation and persuasion of banking customers to the point of higher trust is a determinant of security assurance of using mobile banking apps. This study discusses the theoretical and managerial impacts with the limitation of the study and projects into the future.
手机银行应用程序的不断升级已经缓解了银行大厅的拥挤，特别是在发展中国家，手机银行应用程序的渗透对金融机构和客户都至关重要。本研究对Web of Science已有的相关文献进行了梳理，为本研究定位，并为阐述信任与隐私之间的相互关系作为手机银行应用安全的前提奠定了理论基础。采用定量分析方法，银行客户数据采用SmartPLS 3.0版本，采用结构方程建模、多组数据分析、交互效应分析、重要性-绩效分析等不同的数据分析技术。本研究结果显示性别与教育的介入。这也表明银行客户的导向和说服到更高的信任点是使用手机银行应用安全保障的决定因素。本研究讨论了理论和管理影响与研究的局限性和未来的项目。
{"title":"Demystifying Mobile Banking App Security Through Gender, Education, Privacy, and Trust Intervention","authors":"O. S. Balogun, S. Olaleye","doi":"10.4018/ijea.294859","DOIUrl":"https://doi.org/10.4018/ijea.294859","url":null,"abstract":"The escalating of mobile banking apps has decongested the banking hall, especially in developing countries, and the penetration of mobile banking apps is crucial for both financial institutions and customers. This study reviewed existing relevant literature from the Web of Science to position this study well and dwelled on a theoretical foundation for the exposition of the interrelation of trust and privacy as an antecedent of mobile banking app security. The quantitative method was employed and banking customers data using SmartPLS 3.0 version with different data analysis techniques such as structural equation modelling, multigroup data analysis, interaction effects, and importance-performance analysis. This study results show the intervention of gender and education. It also indicates that the orientation and persuasion of banking customers to the point of higher trust is a determinant of security assurance of using mobile banking apps. This study discusses the theoretical and managerial impacts with the limitation of the study and projects into the future.","PeriodicalId":354119,"journal":{"name":"Int. J. E Adopt.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123780128","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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