Strategic Partnerships in the Satellite and Telecommunications Sectors: A Conceptual Review of Data Analytics-Enabled Identification and Capitalization of Synergies

Purpose Electronic government (e-government) initiatives are critical in bringing about transparency, accessibility and efficiency in public service delivery. Drawing upon e-government literature and the political system theory, this paper aims into the challenges faced by businesses in using e-government applications and how the implementation of e-government can be improved. Design/methodology/approach Using a qualitative research method, data was gathered through in-depth interviews with top executives of businesses in the Greater Accra region of Ghana. Thematic analysis was used to analyze the data. Findings This study reveals that uneven access to digital technology, security concerns and resistance to change are the main challenges hampering the use of e-government applications by the business sector. Furthermore, this study identifies opportunities for facilitating the implementation of e-government including seeking for feedback from the business community, benchmarking and monitoring and collaboration among government agencies. Research limitations/implications This study highlights the challenge of digital divide, which hinders the full realization of the benefits of e-government services for the business sector. Policymakers need to prioritize e-government programs that bridge the gap by way of improving internet connectivity, digital literacy and access to technology. Policymakers should embark on targeted infrastructure development, information, communication and technology training and programs to advance adoption of the e-government among underserved business communities. Practical implications Government agencies must conduct training programs on digital skills and cyber-security for businesses. In addition, businesses should introduce change management initiatives that promote culture of ingenuity and flexibility. Originality/value This study contributes to the filling the dearth of knowledge on the discourse on e-government adoption in developing economies, particularly in the context of business to government e-government model.

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A Framework for the Characterization of Aviation Construction Projects: The Case of UAE

Alketbi,

Dalalah,

Dweiri

2024

Buildings

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This article contributes to the existing literature by modeling and automating the learning process from previous aviation construction projects (ACPs) using artificial intelligence tools, where it will be easier to characterize aviation construction projects and identify the specifications of different aspects of the projects throughout their entire life cycle. An artificial intelligence (AI) framework is proposed for the categorization of aviation construction projects using different machine-learning (ML) methods with a focus on the UAE as a source of data. Airport construction projects have been seen to share a good deal of similar attributes, which should simplify the decision-making process regarding layouts, design, equipment, labor, budget, complexity, etc. However, the gap in reality is that the huge and scattered sources of data, project specifications, characteristics, and the knowledge from past projects are not utilized in an automated way that could simplify the navigation through projects for better future decision-making. The utilization of AI/ML tools is expected to be useful here in order to reduce the revisions of design and construction rework by classifying the projects and the elements that managers need to consider. The planning, design, and construction of new projects can be improved by identifying the attributes of past projects and categorizing them according to similarities, differences, and complexities. Specifically speaking, a framework of hierarchical clustering and neural networks is integrated together to form the classification model. Upon implementing hierarchical classification and neural networks, it was found that neural networks could demonstrate remarkable classification results; the error in classification was minimal in most of the cases. The advantage of such classification is to help decision-makers utilize best practice from the groups of previous projects, which were classified using both hierarchical and neural networks models. With this classification, rework can be minimized, overhead costs may be reduced, and past best practices can be utilized.

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Strategic Partnerships in the Satellite and Telecommunications Sectors: A Conceptual Review of Data Analytics-Enabled Identification and Capitalization of Synergies

Cited by 4 publications

References 38 publications

Regulatory and spectrum policy challenges for combined airspace and non-terrestrial networks

Regulatory and spectrum policy challenges for combined airspace and non-terrestrial networks

Digital inclusivity: exploring e-government use among businesses in Ghana

A Framework for the Characterization of Aviation Construction Projects: The Case of UAE

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