Most recent issue published online in the International Journal of Information Technology and Management.
International Journal of Information Technology and Management
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© 2024 Inderscience Publishers Ltd
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International Journal of Information Technology and Management
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http://www.inderscience.com/browse/index.php?journalID=18&year=2024&vol=23&issue=1
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OpenStack: a virtualisation overview
http://www.inderscience.com/link.php?id=136181
The major cloud computing software companies offer a new concept, on which resources are virtualised to provide these as a service on the internet. Currently, there are multiple service providers, and additional options to virtualise services on-premises. OpenStack is an open-source alternative to create virtual local or cloud setups, which supports petabytes of data, unlimited scale, and configurable networking. These features make this tool suitable for large scale virtualisation, reducing maintenance costs and optimising hardware resource utilisation (e.g., schools, government). This paper presents an overview of the study of the OpenStack software, oriented to build a scalable hosting architecture suitable for an educational setup. Functional and architectural details are discussed to implement unique cloud computing to fit virtualisation purposes. An experimental virtualisation setup is described in the scope of an educational scenario. Finally, a guideline to configure OpenStack is given.
OpenStack: a virtualisation overview
Faouzi Mechraoui; Pedro Martins; Filipe Caldeira
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 1 - 12
The major cloud computing software companies offer a new concept, on which resources are virtualised to provide these as a service on the internet. Currently, there are multiple service providers, and additional options to virtualise services on-premises. OpenStack is an open-source alternative to create virtual local or cloud setups, which supports petabytes of data, unlimited scale, and configurable networking. These features make this tool suitable for large scale virtualisation, reducing maintenance costs and optimising hardware resource utilisation (e.g., schools, government). This paper presents an overview of the study of the OpenStack software, oriented to build a scalable hosting architecture suitable for an educational setup. Functional and architectural details are discussed to implement unique cloud computing to fit virtualisation purposes. An experimental virtualisation setup is described in the scope of an educational scenario. Finally, a guideline to configure OpenStack is given.]]>
10.1504/IJITM.2024.136181
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 1 - 12
Faouzi Mechraoui
Pedro Martins
Filipe Caldeira
UCLL, University of Leuven Limburg, Leuven, Belgium ' CISeD †Research Centre in Digital Services, Polytechnic of Viseu, Portugal ' CISeD †Research Centre in Digital Services, Polytechnic of Viseu, Portugal
OpenStack
infrastructure as a service
IaaS
virtualisation
cloud computing
open source
2024-01-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
23
1
1
12
2024-01-22T23:20:50-05:00
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Consequential effects of leading technology-driven offensive strategy in a universal bank
http://www.inderscience.com/link.php?id=136182
Globally, banking industry is saddled with intense competition. Management of banking firms are required to formulate effective strategies to drive their capabilities to compete, discover and defend their positions in a competitive industry. İn Ghana, universal banks are leveraging the capabilities of information technology to devise technology-driven offensive strategies. The core of these strategies is embarking on innovative activities to enhance performance and respond to business challenges. A qualitative analysis was performed using primary data from 17 participants. Using NVivo, consequential effects of IS-technological innovation (ISTI) on business challenges, innovation performance, operational performance; and specific moderating factors of ISTI were assessed. Strategic-IS Project impacts strong (<i>r</i> = 0.634601) and positive on ISTI than the other moderators. ISTI impacts strongly (<i>r</i> = 0.644951) and positively on operational performance. With <i>r</i> = 0.7422, innovation performance positively and strongly influences operational performance. ISTI impacts positively on business challenges.
Consequential effects of leading technology-driven offensive strategy in a universal bank
Asare Yaw Obeng; Alfred Coleman
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 13 - 32
Globally, banking industry is saddled with intense competition. Management of banking firms are required to formulate effective strategies to drive their capabilities to compete, discover and defend their positions in a competitive industry. İn Ghana, universal banks are leveraging the capabilities of information technology to devise technology-driven offensive strategies. The core of these strategies is embarking on innovative activities to enhance performance and respond to business challenges. A qualitative analysis was performed using primary data from 17 participants. Using NVivo, consequential effects of IS-technological innovation (ISTI) on business challenges, innovation performance, operational performance; and specific moderating factors of ISTI were assessed. Strategic-IS Project impacts strong (<i>r</i> = 0.634601) and positive on ISTI than the other moderators. ISTI impacts strongly (<i>r</i> = 0.644951) and positively on operational performance. With <i>r</i> = 0.7422, innovation performance positively and strongly influences operational performance. ISTI impacts positively on business challenges.]]>
10.1504/IJITM.2024.136182
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 13 - 32
Asare Yaw Obeng
Alfred Coleman
Computer Science Department, Kumasi Technical University, P.O. Box 854, Kumasi, Ghana ' School of Computing, College of Science, Engineering and Technology, GJ Gerwel Building C4-61, University of South Africa Private Bag X6, Florida, 1710, South Africa
bank
business challenges
Ghana
information systems
moderating factors
offensive strategy
qualitative analysis
technological innovation
2024-01-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
23
1
13
32
2024-01-22T23:20:50-05:00
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AQINM: an adaptive QoS management framework based on intelligent negotiation and monitoring in cloud
http://www.inderscience.com/link.php?id=136183
More and more federated cloud platforms have been constructed to deal with non-trivial large-scale applications, which typically require certain level of quality-of-service (QoS) guarantee. However, most of existing cloud-oriented QoS solutions are likely to introduce extra overheads on either resource allocation or task execution, which is especially true in federated cloud environments. In this paper, we design and implement a QoS-enhancing framework, namely adaptive QoS management based on intelligent negotiation and monitoring (AQINM), which provides three QoS-enhancing services including policy management, service level agreement (SLA) negotiation, and SLA monitoring. Unlike the conventional QoS-enable middleware, these services in the AQINM framework introduce several novel mechanisms to offer more cost-effective and efficient solutions to enforcing the QoS management in federated clouds. The implementation of our AQINM framework are tested in a campus federated cloud platform by using different applications as experimental benchmarks, and its performance are compared with other similar solutions. The experimental results show that the proposed AQINM is capable of reducing the costs of SLA negotiation and monitoring for large-scale cloud application that deployed in federated cloud environments.
AQINM: an adaptive QoS management framework based on intelligent negotiation and monitoring in cloud
Zeng Saifeng
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 33 - 47
More and more federated cloud platforms have been constructed to deal with non-trivial large-scale applications, which typically require certain level of quality-of-service (QoS) guarantee. However, most of existing cloud-oriented QoS solutions are likely to introduce extra overheads on either resource allocation or task execution, which is especially true in federated cloud environments. In this paper, we design and implement a QoS-enhancing framework, namely adaptive QoS management based on intelligent negotiation and monitoring (AQINM), which provides three QoS-enhancing services including policy management, service level agreement (SLA) negotiation, and SLA monitoring. Unlike the conventional QoS-enable middleware, these services in the AQINM framework introduce several novel mechanisms to offer more cost-effective and efficient solutions to enforcing the QoS management in federated clouds. The implementation of our AQINM framework are tested in a campus federated cloud platform by using different applications as experimental benchmarks, and its performance are compared with other similar solutions. The experimental results show that the proposed AQINM is capable of reducing the costs of SLA negotiation and monitoring for large-scale cloud application that deployed in federated cloud environments.]]>
10.1504/IJITM.2024.136183
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 33 - 47
Asare Yaw Obeng
Alfred Coleman
School of Computer and Communication, Hunan Institute of Engineering, Xiangtan 411104, China
cloud computing
quality-of-service
QoS
service level agreement
SLA
resource virtualisation
2024-01-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
23
1
33
47
2024-01-22T23:20:50-05:00
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Applying machine learning algorithms to determine and predict the reasons and models for employee turnover
http://www.inderscience.com/link.php?id=136187
In recent years, organisations have struggled with the turnover of employees, which has become one of the biggest issues that not only has inadvertent consequences for an organisation's growth, productivity, and performance but also has negative implications for the intrinsic cost associated with it. To cater to this problem, one such method is the use of machine learning algorithms. But one of the biggest issues in HR information system (HRIS) analysis is the presence of noise in data, leading to inaccurate predictions. This paper tries to examine the efficiency of six such algorithms, to determine the robustness, accuracy in real-time analysis of data, and then use that company's historical data to predict employee turnover for the present year. The dataset was mined from the HRIS database of a global organisation in the USA and Canada in the span of ten years to compare these algorithms to examine voluntary turnover, using Python and RStudio analytical tools.
Applying machine learning algorithms to determine and predict the reasons and models for employee turnover
Shardul Shankar; Ranjana Vyas; Vijayshri Tewari
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 48 - 63
In recent years, organisations have struggled with the turnover of employees, which has become one of the biggest issues that not only has inadvertent consequences for an organisation's growth, productivity, and performance but also has negative implications for the intrinsic cost associated with it. To cater to this problem, one such method is the use of machine learning algorithms. But one of the biggest issues in HR information system (HRIS) analysis is the presence of noise in data, leading to inaccurate predictions. This paper tries to examine the efficiency of six such algorithms, to determine the robustness, accuracy in real-time analysis of data, and then use that company's historical data to predict employee turnover for the present year. The dataset was mined from the HRIS database of a global organisation in the USA and Canada in the span of ten years to compare these algorithms to examine voluntary turnover, using Python and RStudio analytical tools.]]>
10.1504/IJITM.2024.136187
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 48 - 63
Shardul Shankar
Ranjana Vyas
Vijayshri Tewari
Department of Management Studies, Indian Institute of Information Technology, Allahabad †211015, India ' Department of Information Technology, Indian Institute of Information Technology, Allahabad †211015, India ' Department of Management Studies, Indian Institute of Information Technology, Allahabad †211015, India
employee turnover
machine learning
predictive algorithms
classification
voluntary turnover
2024-01-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
23
1
48
63
2024-01-22T23:20:50-05:00
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If you cannot fly, then run: a model of BIM implementation taxonomies and thresholds
http://www.inderscience.com/link.php?id=136194
The barriers to BIM adoption are various and overpowering. These barriers should be continuously defeated through a recursive BIM implementation strategy and evaluation. The point of this paper is to recognise the key reduction indicators for tracking BIM adoption barriers and lay out whether the key reduction indicators will give a model of BIM implementation taxonomies and thresholds for assessing BIM implementation performance. Meta-analysis methodology was utilised to synthesise the diverse findings. These key reduction indicators were sorted into three BIM implementation thresholds: <i>BIM advanced industry</i>, <i>BIM emerging industry</i>, and <i>BIM frontier industry</i>. It was observed that BIM implementation taxonomies have various levels of the implementation plan, levels of market adequacy, and levels of goals. The study inferred that the proposed model would assist with smoothing out the necessities and instruct on the BIM implementation needs concerning different construction industries, most especially the developing construction industries.
If you cannot fly, then run: a model of BIM implementation taxonomies and thresholds
Oluseye Olugboyega; Godwin Ehis Oseghale; Clinton O. Aigbavboa
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 64 - 88
The barriers to BIM adoption are various and overpowering. These barriers should be continuously defeated through a recursive BIM implementation strategy and evaluation. The point of this paper is to recognise the key reduction indicators for tracking BIM adoption barriers and lay out whether the key reduction indicators will give a model of BIM implementation taxonomies and thresholds for assessing BIM implementation performance. Meta-analysis methodology was utilised to synthesise the diverse findings. These key reduction indicators were sorted into three BIM implementation thresholds: <i>BIM advanced industry</i>, <i>BIM emerging industry</i>, and <i>BIM frontier industry</i>. It was observed that BIM implementation taxonomies have various levels of the implementation plan, levels of market adequacy, and levels of goals. The study inferred that the proposed model would assist with smoothing out the necessities and instruct on the BIM implementation needs concerning different construction industries, most especially the developing construction industries.]]>
10.1504/IJITM.2024.136194
International Journal of Information Technology and Management, Vol. 23, No. 1 (2024) pp. 64 - 88
Oluseye Olugboyega
Godwin Ehis Oseghale
Clinton O. Aigbavboa
Faculty of Environmental Design and Management, Department of Building, Obafemi Awolowo University, Ile-Ife, Nigeria ' Faculty of Environmental Design and Management, Department of Building, Obafemi Awolowo University, Ile-Ife, Nigeria ' cidb Centre of Excellence, University of Johannesburg, South Africa
building information modelling
BIM
BIM implementation
BIM adoption
BIM adaptation
BIM application
BIM utilisation
BIM adoption barriers
BIM implementation taxonomies
BIM implementation thresholds
2024-01-22T23:20:50-05:00
Copyright © 2024 Inderscience Enterprises Ltd.
23
1
64
88
2024-01-22T23:20:50-05:00