The cloud computing adoption in higher learning institutions in Kenya: Hindering factors and recommendations for the way forward

Njenga, Kennedy; Garg, Lalit; Bhardwaj, Amit Kumar; Prakash, Vijay; Bawa, Seema

doi:10.1016/j.tele.2018.10.007

Cited by 58 publications

(58 citation statements)

References 55 publications

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“…In addition, lecturers cannot assess the students perfectly due to the lack of interaction. This might affect the number of enrolled students and reduce the revenues of the university [43].…”

Section: Figure 1 Three Phases Of Economic Challenges Of CCmentioning

confidence: 99%

Economic challenges of cloud computing in Iraqi educational institutions using exploratory analysis

Jawad

2021

IJEECS

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<span>Cloud computing (CC) implementation for educational services is confronting several challenges. Prior research focused on the technological related challenges while few examine the economic challenges. The purpose of this study is to examine the economic challenges for using CC in educational institutions in Iraq. Articles pertaining to the topics were extracted from main databases. Based on the review, the critical challenges were identified. To confirm their relatedness to Iraqi context, a questionnaire related to the challenges was developed. A total of 204 respondents working as IT professional has participated in this study. The findings showed that the challenges mainly related to the infrastructure readiness, internet connection, cost of establishing and managing the CC. The challenges were divided into three phases. The pre-implementation phase includes the challenges of selecting service provider and deployment as well as the readiness of stakeholders, training, and infrastructure readiness. The implementation phase includes the challenges of maintaining the bandwidth, compatibility, legacy system, internet connection, reliability, availability, connectivity, and management. The post-implementation phase includes the challenges of security, privacy, quality of education, switching cost, and lock-in. The most critical challenges in all phases are related to infrastructure readiness, internet connection, switching cost and management of CC. The findings were discussed and limitations of the study as well as the direction for future works were given. </span>

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Section: Figure 1 Three Phases Of Economic Challenges Of CCmentioning

confidence: 99%

Economic challenges of cloud computing in Iraqi educational institutions using exploratory analysis

Jawad

2021

IJEECS

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“…Studies on CC in educational institutions in developing nations are scarce [12], especially in Malaysia [13,14]. The successful adoption of any novel technology such as CC does not depend only on universities and cloud service providers' support but also on users' willingness and intention to adopt and utilize these services [12,15,16]. Therefore, the adoption of any new technology depends on the innovativeness of the decision-makers.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Analytical Approach to Predict the Determinants of Cloud Computing Adoption in Higher Education Institutions

et al. 2020

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Cloud computing (CC) delivers services for organizations, particularly for higher education institutions (HEIs) anywhere and anytime, based on scalability and pay-per-use approach. Examining the factors influencing the decision-makers’ intention towards adopting CC plays an essential role in HEIs. Therefore, this study aimed to understand and predict the key determinants that drive managerial decision-makers’ perspectives for adopting this technology. The data were gathered from 134 institutional managers, involved in the decision making of the institutions. This study applied two analytical approaches, namely variance-based structural equation modeling (i.e., PLS-SEM) and artificial neural network (ANN). First, the PLS-SEM approach has been used for analyzing the proposed model and extracting the significant relationships among the identified factors. The obtained result from PLS-SEM analysis revealed that seven factors were identified as significant in influencing decision-makers’ intention towards adopting CC. Second, the normalized importance among those seven significant predictors was ranked utilizing the ANN. The results of the ANN approach showed that technology readiness is the most important predictor for CC adoption, followed by security and competitive pressure. Finally, this study presented a new and innovative approach for comprehending CC adoption, and the results can be used by decision-makers to develop strategies for adopting CC services in their institutions.

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“…e application domains of cloud computing technology in education include e-learning (such as curriculum content management, virtual lab environment, office productivity suite, library management, and collaborative learning), communication (e-mail and notifications), and administration (such as students registration management and human resources management) [137]. Cloud computing has not only been used in the education sector but also in other sectors such as healthcare [138], manufacturing, entertainment, transportation, and energy [139].…”

Section: Cloud Computingmentioning

confidence: 99%

Exponential Disruptive Technologies and the Required Skills of Industry 4.0

Bongomin

Ocen

Nganyi

et al. 2020

Journal of Engineering

136

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The 21st century has witnessed precipitous changes spanning from the way of life to the technologies that emerged. We have entered a nascent paradigm shift (industry 4.0) where science fictions have become science facts, and technology fusion is the main driver. Thus, ensuring that any advancement in technology reach and benefit all is the ideal opportunity for everyone. In this study, disruptive technologies of industry 4.0 were explored and quantified in terms of the number of their appearances in published literature. The study aimed at identifying industry 4.0 key technologies which have been ill-defined by previous researchers and to enumerate the required skills of industry 4.0. Comprehensive literature survey covering the field of engineering, production, and management was done in multidisciplinary databases: Google Scholar, Science Direct, Scopus, Sage, Taylor & Francis, and Emerald Insight. From the electronic survey, 35 disruptive technologies were quantified and 13 key technologies: Internet of Things, Big Data, 3D printing, Cloud computing, Autonomous robots, Virtual and Augmented reality, Cyber-physical system, Artificial intelligence, Smart sensors, Simulation, Nanotechnology, Drones, and Biotechnology were identified. Both technical and personal skills to be imparted into the human workforce for industry 4.0 were reported. The review identified the need to investigate the capability and the readiness of developing countries in adapting industry 4.0 in terms of the changes in the education systems and industrial manufacturing settings. This study proposes the need to address the integration of industry 4.0 concepts into the current education system.

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The cloud computing adoption in higher learning institutions in Kenya: Hindering factors and recommendations for the way forward

Cited by 58 publications

References 55 publications

Economic challenges of cloud computing in Iraqi educational institutions using exploratory analysis

Economic challenges of cloud computing in Iraqi educational institutions using exploratory analysis

A Multi-Analytical Approach to Predict the Determinants of Cloud Computing Adoption in Higher Education Institutions

Exponential Disruptive Technologies and the Required Skills of Industry 4.0

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