Journal of High Technology Management Research最新文献

{"title":"A qualitative study on the urgency of attitude in designing effective procurement certification training","authors":"Nurus Sa'adah ,&nbsp;Lawrence Arokiasamy","doi":"10.1016/j.hitech.2023.100472","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100472","url":null,"abstract":"<div><p>This analysis takes a psychological perspective on human resource management to determine what percentage of the three dimensions of competence (knowledge, skill, and attitude) should be included in certification training materials for procurement. To gather information, we used both online and offline Focus Group Discussion (FGD) sessions in addition to interviews and direct observation. Ten entry-level trainees participated in the offline FGD, while seven procurement officials monitored the online FGD. The certification candidates, training instructors, functional staff, and training organizers all participated in the interview. The training facility for the procurement certification is under observation. The findings demonstrated the importance of the mindset, since the psychological consideration of attitudes while performing the duties of a procurement officer had been left out of the procurement certification training materials.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100472"},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181917","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}

{"title":"AI enabled value-oriented collaborative learning: Centre for innovative education","authors":"J. Ramadevi ,&nbsp;C. Sushama ,&nbsp;K. Balaji ,&nbsp;Vamsidhar Talasila ,&nbsp;Nidhi Sindhwani ,&nbsp;Mukti","doi":"10.1016/j.hitech.2023.100478","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100478","url":null,"abstract":"<div><p>Collaborative learning allows students to pool their knowledge, skills, and experiences to better understand and learn from one another. Two of the most fundamental features of collaborative learning are the grouping of students and the gaining of knowledge through social interactions with peers. The term “blended learning” refers to a new approach to education that combines conventional and contemporary learning models, in which students' interaction with and education from their digital devices does not totally replace their interaction and education from their traditional teachers. However, there are a number of obstacles that prevent educators from fully grasping blended learning models and putting them into practice. There have been a number of difficulties in implementing blended learning models due to the varying degrees to which they are accepted and used. In this article, we talked about collaborative learning data analysis since it helps teachers determine if their pedagogical approaches are working and where they may be strengthened. These results have the potential to contribute to a more comprehensive knowledge of (Artificial Intelligence in Education) AIED and its consequences for educational policies, educational AI design, and instructional design geared toward improving (The School Advisory Council) SAC in education.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100478"},"PeriodicalIF":0.0,"publicationDate":"2023-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181853","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}

{"title":"IoT-based data quality and data preprocessing of multinational corporations","authors":"N. Sirisha ,&nbsp;M. Gopikrishna ,&nbsp;P. Ramadevi ,&nbsp;Raveendranadh Bokka ,&nbsp;K.V.B. Ganesh ,&nbsp;M. Kalyan Chakravarthi","doi":"10.1016/j.hitech.2023.100477","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100477","url":null,"abstract":"<div><p>Increasing numbers of devices that output large amounts of geographically referenced data are being deployed as the Internet of Things (IoT) continues to expand. Partly as a result of the IoT's dynamic, decentralized, and heterogeneous architecture. These are all examples of the Internet of items (IoT), despite the fact that we might be thinking that one of these items is different from the others. The physical and digital worlds are connected by the Internet of Things (IoT). Nowadays, one of the key goals of the Internet is its own development. This paper provides an in-depth analysis of IoT-based data quality and data preparation strategies developed with multinational corporations in mind. The goal is to make IoT data more trustworthy and practical so that MNCs may use it to their advantage in making educated business decisions. The proposed structure consists of three distinct actions: gathering data, evaluating data quality, and cleaning up raw data. Data preprocessing research is essential since it decides and significantly affects the accuracy of predictions made in later stages. Thus, the recommendation for a special and useful combination in the framework of different data preprocessing task types, which includes the following four technical elements and is briefly justified, is made. The Internet of Things (IoT) is a design pattern in which commonplace items can be equipped with classification, sensing, networking, and processing capabilities that will enable them to communicate with one another over the Internet to fulfill a specific function. The Internet of Things will eventually change physical objects into virtual objects with intelligence. In addition to a detailed analysis of the IoT layer, this article gives an overview of the existing Internet of Things (IoT), technical specifics, and applications in this recently growing field. However, this publication will provide future scholars who desire to conduct study in this area of Internet of Things with a better knowledge.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100477"},"PeriodicalIF":0.0,"publicationDate":"2023-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181851","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}

{"title":"Resource management projects in entrepreneurship and retain customer based on big data analysis and artificial intelligence","authors":"Pham Quang Huy ,&nbsp;Shavkatov Navruzbek Shavkatovich ,&nbsp;Zulkiflee Abdul-Samad ,&nbsp;D.K. Agrawal ,&nbsp;K.M. Ashifa ,&nbsp;Mahendran Arumugam","doi":"10.1016/j.hitech.2023.100471","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100471","url":null,"abstract":"<div><p>Retaining clients is turning into an estimation center in an industry with expanding rivalry. Because it is difficult to keep customers and easy for them to switch brands, the idea of customer retention has become the subject of research in the sales industry. Traditional human resource management systems are unable to manage and analyze data because of the rapid growth of enterprise-generated data's processing capacity. This exploration proposes novel strategy in human asset the executives for little new company business with their client hold utilizing Artificial intelligence (AI) procedures. Behavioral pattern analysis based on reinforcement radial fuzzy decision with quadratic kernel vector machine is utilized here for human resource management and customer relationship retention. In terms of prediction accuracy, area under the curve (AUC), average precision, sensitivity, and quadratic normalized square error, various human resource datasets based on entrepreneurship are the subjects of the experimental analysis. The proposed technique attained prediction accuracy of 98%, AUC of 89%, average precision of 83%, sensitivity of 66%, quadratic normalized square error of 59%.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100471"},"PeriodicalIF":0.0,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181854","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}

{"title":"Implementation and management of cloud security for industry 4.O - data using hybrid elliptical curve cryptography","authors":"N. Krishnamoorthy ,&nbsp;S. Umarani","doi":"10.1016/j.hitech.2023.100474","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100474","url":null,"abstract":"<div><p>Industry 4.0 places a premium on cloud security since more and more companies are moving their activities to the cloud to reap the benefits of the Fourth Industrial Revolution.The term “cloud computing” refers to a collection of Internet-based hardware and software tools. Providers of cloud services use data centers situated in various physical locations. Cloud computing makes life easier for users by making remote, simulated resources available over the internet. Google Apps and Microsoft SharePoint are two examples of popular cloud applications. In addition to its exciting potential, the “cloud computing” industry's lightning-fast expansion raises serious security concerns. When discussing security, cloud really suffers from Open Systems' and the internet's perennial problem. The only thing stopping the widespread use of cloud computing is the lack of trust in the system. There are a number of security concerns with cloud computing, including protecting user data and vetting cloud service providers' practices. Using encryption, confidential information can be sent over an unsecured channel without fear of data loss or manipulation. Data encryption using various protocols has been used in various settings. Different cryptosystems were developed and used at various times. Additionally, cloud computing enables multiple users to access and retrieve data simultaneously through their own personal Internet connections, which increases the risk of confidential data loss and exposure in a number of different places. Elliptic Curve Cryptography and other cryptographic algorithms have been used to develop numerous methods and protocols that guarantee the security and privacy of transmitted data. In this paper, we suggest a safe and efficient method for sharing information in the cloud without compromising its safety or integrity. The proposed system is able to guarantee authentication and data integrity because it uses a hybrid of the ECC and the Advanced Encryption Standard (AES) technique. The experimental results confirm the proposed approach outperforms the current gold standard.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100474"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181916","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}

{"title":"Cloud computing enabled business model innovation","authors":"Bhavana Godavarthi ,&nbsp;Nirmalajyothi Narisetty ,&nbsp;Kalpana Gudikandhula ,&nbsp;R. Muthukumaran ,&nbsp;Dhiraj Kapila ,&nbsp;J.V.N. Ramesh","doi":"10.1016/j.hitech.2023.100469","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100469","url":null,"abstract":"<div><p>Cloud computing's primary layer of security is its widespread adoption by businesses due to its ability to provide easy, on-demand network access to a large pool of configurable processing resources. Pressure from developed-world governments to keep up with the latest IT trends makes it challenging for colleges around the world to adopt cloud computing in engineering education. Although cloud computing as a concept has become more popular in recent times and quite a few studies have been conducted, the adoption and application level is still very low, particularly in developing countries. This study provides a realistic framework for gauging the sustainability of a company model. While digitalization is widely acknowledged to be crucial, the study's results reveal that the perceived available options for business model innovation depend not only on the value proposition itself but also on the position in the value network. The primary goal of this research is to create a cloud computing service provider business model that is built on circular economy principles and can guarantee the sustainable usage of cloud computing resources.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100469"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181918","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}

{"title":"Exploring human resource management intelligence practices using machine learning models","authors":"Sai Rama Krishna Indarapu ,&nbsp;Swathy Vodithala ,&nbsp;Naveen Kumar ,&nbsp;Siripuri Kiran ,&nbsp;Soora Narasimha Reddy ,&nbsp;Kumar Dorthi","doi":"10.1016/j.hitech.2023.100466","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100466","url":null,"abstract":"<div><p>The use of machine learning for recruitment has become one of the main themes in human resources ever since machine learning software investigated the first recruitment software and discovered that utilizing technology improves their effectiveness at work, speed, and makes the process simpler. In order to better handle employee files, profiles, turnover, data analytics, and the creation of electronic personal data sheets for government service records, a human resource information system that incorporates machine learning has been created. Using a supervised machine learning technique, it was designed to foresee staff turnover. From a theoretical perspective, machine learning apps may be able to perform the same tasks as HR specialists, if not better or faster. Supporting HR professionals in becoming a true business partner and providing them with accurate and reliable advice, the interaction between HR professionals and line top management believes that the HR professionals still has surplus over machine learning, alone. Human resources methods and the significance of machine learning are the primary focus of this paper. This paper's three goals are to (1) determine how much of an impact Machine learning can have on the organization's recruitment procedures, (2) examine the extent to which this technology has been adopted, and (3) examine the frequency with which complaints have been lodged during these crucial exercises.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100466"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181915","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}

{"title":"Machine learning models for evaluating the benefits of business intelligence systems","authors":"Mano Ashish Tripathi ,&nbsp;Kilaru Madhavi ,&nbsp;V.S. Prasad Kandi ,&nbsp;Vinay Kumar Nassa ,&nbsp;Banitamani Mallik ,&nbsp;M. Kalyan Chakravarthi","doi":"10.1016/j.hitech.2023.100470","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100470","url":null,"abstract":"<div><p>Due to the uncertainty of the market and the intensity of rivalry, business owners and managers are often compelled to experiment with a wide variety of strategies for enhancing their company's performance. By enhancing the timeliness and quality of inputs to the decision-making process, Business Intelligence (BI) is one such idea and tool that combines operational data with analytical tools to show complex and competitive information to planners and decision-makers. Business intelligence (BI) tools help companies rapidly generate insights that guide managers toward operational efficiencies, lead them to new opportunities, and set them apart from the competition. The literature study shows that there is a debate about whether BI tools have an effect on the quality of decisions and the development of businesses. The present research explores the varied empirical facets of BI application through ML models. This study concluded with a discussion of how Machine Learning models can be used to assess the value of BI tools. Machine learning models, fed with historical data and a wealth of input features, can foresee the effect of new systems on metrics like revenue development, customer behavior, and inventory management. Using these models, businesses will be able to better evaluate potential investments in new tools and systems.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100470"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181919","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}

{"title":"Artificial intelligence in steering the digital transformation of collaborative technical education","authors":"A. Jaya Lakshmi ,&nbsp;Ashok Kumar ,&nbsp;M. Sunil Kumar ,&nbsp;Syed Imran Patel ,&nbsp;S.K. Lokesh Naik ,&nbsp;J.V.N. Ramesh","doi":"10.1016/j.hitech.2023.100467","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100467","url":null,"abstract":"<div><p>In recent years, the United Arab Emirates (UAE) has been a leader in the global adoption of AI and online schooling. Despite using the traditional educational structure, military colleges have embraced this new technology. This research analyzed the present adoption rate, difficulties, and solutions for implementing an AI-based online education system. The results demonstrate that digital technology has a tangible impact on all facets of higher education if it is supported by the institution. The results also indicate that the organization plays a crucial role in the integration of digital technology into teaching and learning, and that an examination of the materiality already present in the Collaborative Technical Education (CTE) organization is necessary for comprehending the potential effects of new digital technology. Finally, this paper addressed how AI can make e-learning more interesting, efficient, and tailored to each individual learner, all of which contribute to better learning outcomes and wider access to technical education. The details of how artificial intelligence can be used to promote diversity and equity in the classroom are laid out. To motivate educators to create mixed-reality artifacts and conduct further research to support collaborative educational environments, this article discusses current works and visualizes the current state of the field.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100467"},"PeriodicalIF":0.0,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181920","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}

{"title":"Big data for the comprehensive data analysis of IT organizations","authors":"Sujatha Madugula,&nbsp;Sreenivas Pratapagiri,&nbsp;M.S.B. Phridviraj,&nbsp;V. Chandra Shekhar Rao,&nbsp;Niranjan Polala,&nbsp;P. Kumaraswamy","doi":"10.1016/j.hitech.2023.100465","DOIUrl":"https://doi.org/10.1016/j.hitech.2023.100465","url":null,"abstract":"<div><p>Businesses have begun using IT apps for a variety of reasons in recent years. The rapid advancement of new technologies has opened up vast prospects for businesses to digitise their operations, enhance their use of information systems, and compete more effectively in the global marketplace. Information technology (IT) businesses can benefit greatly from Big Data analytics due to the depth and breadth of their data analysis. Big data can be used to examine IT departments in the following ways: performance analysis, forecast maintenance, security analysis, and resource analysis. When it comes to boosting their business's dependability, speed, quality, and effectiveness, most companies rely on big data. Companies can gain a competitive edge thanks to the massive amounts of data that big data is able to collect, store, and manage. Big data analytics is being used by a growing number of businesses to make sense of their mountain of data. In this paper, we examine the ways in which IBM, TCS, and Cognizant use big data within their operations. Long-term planning strategies and business intelligence practises are also suggested in this research as means of protecting personal information.</p></div>","PeriodicalId":38944,"journal":{"name":"Journal of High Technology Management Research","volume":"34 2","pages":"Article 100465"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50181914","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}