Determinants and their causal relationships affecting the adoption of cloud computing in science and technology institutions

Hwang, Bang‐Ning; Huang, Chi Yo; Yang, Chia Lee

doi:10.1080/14479338.2016.1203729

Cited by 30 publications

(30 citation statements)

References 69 publications

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“…Table 6 demonstrates the models and methodologies used in the selected articles. 17 Low et al; 18 Bharadwaj and Lal; 19 Borgman et al; 20 Oliveira et al; 21 Ali et al; 22 Lin and Chen; 50 Alshamaila et al; 51 Morgan and Conboy; 52 Dahiru et al; 53 Kuiper et al; 54 Stieninger and Nedbal; 55 Badie et al; 56 Gangwar et al; 57 Safari et al; 58 Wahsh and Dhillon; 59 Charlebois et al; 60 Hwang et al; 61 Isma'ili et al; 62 Kumar and Samalia; 63 Senyo et al 64…”

Section: Summarizing Stagementioning

confidence: 99%

“…  Lian et al; 12 Oliveira et al; 21 Ali et al; 22 Lin and Chen; 50 Alshamaila et al; 51 Morgan and Conboy; 52 Kuiper et al; 54 Stieninger and Nedbal; 55 Badie et al; 56 Gangwar et al; 57 Wahsh and Dhillon; 59 Charlebois et al; 60 Hwang et al; 61 Al-Mascati and Al-Badi; 65 17 Ali et al; 22 Lin and Chen; 50 Alshamaila et al; 51 Morgan and Conboy; 52 Kuiper et al; 54 Stieninger and Nedbal; 55 Badie et al; 56 Gangwar et al; 57 Safari et al; 58 Wahsh and Dhillon; 59 Charlebois et al; 60 Hwang et al; 61 Isma'ili et al; 62 Al-Mascati and Al-Badi 65 Technical readiness   Sulaiman and Magaireah; 16 Alharbi et al; 17 Oliveira et al; 21 Senyo et al; 64 Al-Mascati and Al-Badi; 65 Tsai and Hung 67 Security   Lian et al; 12 Sulaiman and Magaireah; 16 Ali et al; 22 Akar and Mardiyan; 24 Sabi et al; 27 Morgan and Conboy; 52 Dahiru et al; 53 Kuiper et al; 54 Badie et al; 56 Safari et al; 58 Wahsh and Dhillon; 59 Hwang et al;...…”

Section: Complexitymentioning

confidence: 99%

“…Magaireah 16 Structured Maqueira-Marín et al; 26 Kuiper et al; 54 Hwang et al; 61 Kumar and Samalia; 63 Noor; 66 Tsai and Hung; 67…”

Section: Sulaiman Andmentioning

confidence: 99%

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Evaluating the factors that influence cloud technology adoption—comparative case analysis of health and non-health sectors: A systematic review

Sadoughi

Ali

Erfannia

2019

Health Informatics J

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Cloud technology has brought great benefits to the health industry, including enabling improvement in the quality of services. The objective of this review study is to investigate the reported factors affecting the adoption of cloud in the health sector by comparing studies in the health and non-health sectors. This article is a systematized review of studies conducted in 2018. From 541 articles, 47 final articles were selected and classified into two categories: health and non-health studies; conclusions were drawn from the two sectors by comparing their effective factors. Based on the results of this review, the factors were categorized as technological, organizational, environmental, and individual. The results of this review study could be a beneficial guide to the health empirical research on cloud adoption. Individual domains have not been examined in health sector studies. Since the process of adoption of new technologies in organizations is time-consuming, due to the lack of managerial knowledge about the efficient factors, recognition of these factors by decision-makers while planning for cloud adoption becomes of great importance. The findings of this review study aim to help health decision-makers by increasing their awareness of the cloud and of the factors that impact decisions at both the organizational and individual levels.

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Section: Summarizing Stagementioning

confidence: 99%

Section: Complexitymentioning

confidence: 99%

See 1 more Smart Citation

Evaluating the factors that influence cloud technology adoption—comparative case analysis of health and non-health sectors: A systematic review

Sadoughi

Ali

Erfannia

2019

Health Informatics J

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“…The aim of the DEMATEL method is to identify direct and indirect causes and the strength of influence of considered factors by applying matrix computations. Unlike the classical approach of structural equation modeling (SEM), which requires a large sample size to derive causal relationships among variables, the expert opinion-driven DEMATEL method can yield good results from a relatively small sample size [84] and assess the associated cause and effect relationships [85].…”

Section: Dematel Methodsmentioning

confidence: 99%

A Derivation of Factors Influencing the Successful Integration of Corporate Volunteers into Public Flood Disaster Inquiry and Notification Systems

et al. 2018

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Flood hazards have become increasingly common and serious over the last few centuries. Volunteers can observe instant flood information in their local environment, which presents a great opportunity to gather flood information. The information provided by individual volunteers is too much for them to truly understand. Corporate volunteers can offer more accurate and truthful information due to their understanding of the roles and requirements of specific tasks. Past studies of factors influencing the success of corporate volunteers in flood disaster are limited. Thus, this research aims to derive the factors that enable corporate volunteers to successfully integrate the flood information to help reduce the number of injuries and deaths being caused by flood disasters. This research used the information success model and the Public-Private Partnership (PPP) model to develop an analytic framework. The nature of flood disaster management problems is inherently complex, time-bound, and multifaceted. Therefore, we proposed a novel hybrid multi-criteria decision-making (MCDM) model to address the key influence factors and the cause-effect relationships between factors. An empirical study in Taiwanese public flood disaster inquiry and notification systems was used to verify the effectiveness of the proposed methodology. The research results can serve as guidelines for improving the government's policies and the public sector in the context of corporate volunteer involvement in flood disaster inquiry and notification and in relation to other natural and manmade disasters.

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“…Fourth, a cloud environment also allows easy change in IT solution whenever there are changes in the business environment. The increased agility/adaptability [23], [26], [27], [28], [29], [30], [25] and flexibility/scalability [11], [12], [13], [14] further create an illusion of availability of infinite resources in the users' mind [18], [23], [26], [31], [32], [21], [33] while creating a greener computing environment [25]. This flexibility also improves business continuity, mobility, and productivity [34].…”

Section: B An Inventory Of Benefits Derived From Cloud Servicesmentioning

confidence: 99%

An Exploratory Study Of Factors Driving Decision Maker Intentions To Adopt Cloud Computing

Agrawal

Taylor

et al. 2019

ITMS

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United States based companies have invested more heavily in cloud services than companies in other nations. Despite numerous benefits claimed by cloud service providers, many organisations are still uncertain about the implementation of cloud computing. The aim of this study is to gain a better understanding of the factors that are important to the usage adoption decision of this information technology delivery model and the implications for organisations in the United States. Decision makers were surveyed to discover which attributes were important in their determination of cloud computing utilisation. Using a sample of executives from manufacturing and service sectors in the United States, multiple factors contributing to the recent growth in cloud computing have been identified using a factor analysis. Four factors emerged from the data analysis include extrinsic motivation, intrinsic motivation, perceived risks, and resource constraint.

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Determinants and their causal relationships affecting the adoption of cloud computing in science and technology institutions

Cited by 30 publications

References 69 publications

Evaluating the factors that influence cloud technology adoption—comparative case analysis of health and non-health sectors: A systematic review

Evaluating the factors that influence cloud technology adoption—comparative case analysis of health and non-health sectors: A systematic review

A Derivation of Factors Influencing the Successful Integration of Corporate Volunteers into Public Flood Disaster Inquiry and Notification Systems

An Exploratory Study Of Factors Driving Decision Maker Intentions To Adopt Cloud Computing

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