The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Cloud computing adoption by SMEs in the north east of England: A multi‐perspective framework
Abstract
Purpose: The purpose of this paper is to contribute to a growing body of research on cloud computing, by studying the small to medium‐sized enterprise (SME) adoption process. If SMEs have access to scalable technologies they could potentially deliver products and services that in the past only large enterprises could deliver, flattening the competitive arena. Design/methodology/approach: By adopting the Technological, Organisational and Environmental (TOE) framework as a theoretical base, this qualitative exploratory study used semi‐structured interviews to collect data in 15 different SMEs and service providers in the north east of England. The north east of England was selected as it is a region that aspires to become home to innovative digital firms and most of the companies in the region are SMEs. Findings: The main factors that were identified as playing a significant role in SME adoption of cloud services were: relative advantage, uncertainty, geo‐restriction, compatibility, trialability, size, top management support, prior experience, innovativeness, industry, market scope, supplier efforts and external computing support. In contrast, this study did not find enough evidence that competitive pressure was a significant determinant of cloud computing adoption. Research limitations/implications: These findings have important implications and great value to the research community, managers and information and communication technologies (ICT) providers, in terms of formulating better strategies for cloud computing adoption. For service providers, using the research model in this study can assist in increasing their understanding of why some SMEs choose to adopt cloud computing services, while seemingly similar ones facing similar market conditions do not. Also, cloud computing providers may need to improve their interaction with SMEs which are involved in the cloud computing experience, in an effort to create a healthy environment for cloud computing adoption, and to remove any vagueness surrounding this type of technology. Originality/value: This study is an attempt to explore and develop an SME cloud computing adoption model that was theoretically grounded in the TOE framework. By adopting the TOE framework this study has shown that the three contexts of this framework (technological, organisational, and environmental) are connected to each other.
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Citations
Cites
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Chatterjee, S., Rana, N. P., Dwivedi, Y. K., & Baabdullah, A. M. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120880 · Cited by 825
Examining cloud computing adoption intention, pricing mechanism, and deployment model
Hsu, P.-F., Ray, S., & Li-Hsieh, Y.-Y. (2014) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2014.04.006 · Cited by 444
Adoption of AI-empowered industrial robots in auto component manufacturing companies
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Information technology adoption: a review of the literature and classification
Salahshour Rad, M., Nilashi, M., & Mohamed Dahlan, H. (2018) · Universal Access in the Information Society · doi:10.1007/s10209-017-0534-z · Cited by 181
A cloud-based supply chain management system: effects on supply chain responsiveness
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Metadata
- Authors
- Alshamaila, Y., Papagiannidis, S., & Li, F.
- Venue
- Journal of Enterprise Information Management
- Publisher
- Emerald
- Published
- 2013-04-12
- Volume
- 26
- Issue
- 3
- Pages
- 250-275
- ISSN
- 1741-0398 (ISSN-L)
- OpenAlex
- W1599579283
- Cited by
- 756
- References
- 17
- FWCI
- 88.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- Alshamaila, Y., Papagiannidis, S., & Li, F. (2013). Cloud computing adoption by SMEs in the north east of England: A multi‐perspective framework. Journal of Enterprise Information Management. https://doi.org/10.1108/17410391311325225
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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