User centric cloud service model in public sectors: Policy implications of cloud services

Shin, Dong‐Hee

doi:10.1016/j.giq.2012.06.012

Cited by 111 publications

(72 citation statements)

References 37 publications

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“…Furthermore, Heart (2010) found that vendor credibility has a positive impact on SaaS adoption intention and a negative impact on perceived risk (Heart, 2010). Similarly, Shin (2013) conducted an empirical study whose results showed that security affects cloud computing adoption (Shin, 2013). Thus we present the following hypotheses:…”

Section: Perceived Risk and Perceived Trustmentioning

confidence: 93%

“…Rogers (2002) believes that most individuals would evaluate a technology innovation in terms of subjective evaluations by other adopters who are their intimate friends or colleagues (Rogers, 2002), rather than relying on those with a specialized knowledge of the technology. Shin found that subjective norm affects adoption intention and perceived usefulness (PU) (Shin 2013;Shin et al, 2014). Both Cao and Bi, and Park and Ryoo found that social influence has a positive impact on cloud storage service adoption (Cao & Bi, 2014;Park & Ryoo, 2013).…”

Section: Subjective Normmentioning

confidence: 99%

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Critical Factors for Personal Cloud Storage Adoption in China

Jian-ya

2016

Journal of Data and Information Science

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Purpose: In order to explain and predict the adoption of personal cloud storage, this study explores the critical factors involved in the adoption of personal cloud storage and empirically validates their relationships to a user's intentions.Design/methodology/approach: Based on technology acceptance model (TAM), network externality, trust, and an interview survey, this study proposes a personal cloud storage adoption model. We conducted an empirical analysis by structural equation modeling based on survey data obtained with a questionnaire. Findings:Among the adoption factors we identified, network externality has the salient influence on a user's adoption intention, followed by perceived usefulness, individual innovation, perceived trust, perceived ease of use, and subjective norms. Cloud storage characteristics are the most important indirect factors, followed by awareness to personal cloud storage and perceived risk. However, although perceived risk is regarded as an important factor by other cloud computing researchers, we found that it has no significant influence. Also, subjective norms have no significant influence on perceived usefulness. This indicates that users are rational when they choose whether to adopt personal cloud storage. Research limitations:This study ignores time and cost factors that might affect a user's intention to adopt personal cloud storage.Practical implications: Our findings might be helpful in designing and developing personal cloud storage products, and helpful to regulators crafting policies. Originality/value:This study is one of the first research efforts that discuss Chinese users' personal cloud storage adoption, which should help to further the understanding of personal cloud adoption behavior among Chinese users.

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Section: Perceived Risk and Perceived Trustmentioning

confidence: 93%

Section: Subjective Normmentioning

confidence: 99%

Critical Factors for Personal Cloud Storage Adoption in China

Jian-ya

2016

Journal of Data and Information Science

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“…In the governmental context, cloud computing is used as a tool to facilitate information sharing, applications processing, and as a cost-saving measure compared to traditional technological architectures (Ali et al 2014;Shin 2013;Mukherjee and Sahoo 2010). Cloud computing platforms offer an operational model that can digitally combine geographically remote data centres into a common infrastructure, providing a prime gateway to government related services and data.…”

Section: Significance Of Cloud Computing In the Government Contextmentioning

confidence: 99%

Risks and rewards of cloud computing in the UK public sector: A reflection on three Organisational case studies

Jones¹,

Irani

Sivarajah

et al. 2017

Inf Syst Front

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Government organisations have been shifting to cloud-based services in order to reduce their total investments in IT infrastructures and resources (e.g. data centers), as well as capitalise on cloud computing's numerous rewards. However, just like any other technology investments there are also concerns over the potential risks of implementing cloud-based technologies. Such concerns and the paucity of scholarly literature focusing on cloud computing from a governmental context confirm the need for exploratory research and to draw lessons for government authorities and others in order to ensure a reduction in costly mistakes. This paper therefore investigates the implementation of cloud computing in both a practical setting and from an organisational user perspective via three UK local government authorities. Through the qualitative case study enquiries, the authors are able to extrapolate perceived rewards and risks factors which are mapped against the literature so that emergent factors can be identified. All three cloud deployments resulted in varying outcomes which included key rewards such as improved information management, flexibility of work practices and also posed risks such as loss of control and lack of data ownership to the organisations. These findings derived from the aggregated organisational user perspectives will be of benefit to both academics and practitioners engaged in cloud computing research and its strategic implementation in the public sector.

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“…TOE framework +People [44] TAM+ (TRA) [60] TOE framework [61] TOE model + conceptual model of Cloud Computing adoption [62] TOE framework [63] Technological & Organizational factors [64] TAM [65] First, we discuss the Technology, Organization, and Environment (TOE) Framework, which is a theoretical framework that was developed by Tornatzky and Fleischer in 1990 and still widely used by IS researchers till now [58]. Within this framework, the components of an organization which is studying the adoption of new technology are classified into three major classifications; namely: Technological, Organizational and Environmental elements and the second model to be discussed here is the Technology Acceptance Model (TAM), which is mainly used to examine the user's interaction with the new innovation from two major points.…”

Section: Adoption Model Of Cloud Computing In E-government Authormentioning

confidence: 99%