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Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"
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Nkhoma and Dang (2013), "Contributing Factors of Cloud Computing Adoption: a Technology-Organisation-Environment Framework Approach"

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Cloud computing as an emerging high technology has been recognised by organisations and individuals for a wide range of potential applications. Since the concept’s first appearance in 2007, the …

Cloud computing as an emerging high technology has been recognised by organisations and individuals for a wide range of potential applications. Since the concept’s first appearance in 2007, the authors found a dominant amount of studies in the non-technological domains, including attempts to define and categorise cloud computing and the challenges and issues of the technology’s adoption. Nonetheless, few researches are dedicated to determine the drivers of adopting cloud computing thus the literature is limited on this topic. As more adopters are becoming familiar with the technology and implementing cloud computing in their daily work, understanding of what drives their adoption decision is essential to create opportunities for future cloud technologies to be tailored and aligned with the consumer’s needs thus promoting exploitations of the technology’s promising applications.

This research takes a quantitative approach by developing and validating a theory-based conceptual model. Among the theories that are commonly applied in Information Systems research, the authors found Technology-Organisation-Environment framework can encapsulate the adoption’s factors into one big picture. The authors conducted a secondary data analysis on the recent large-scale survey of IBM to investigate the drivers and barriers of cloud computing adoption. Structural Equation Modelling and Partial Least Square statistical methodologies provide rigid scientific procedures to validate the conceptual model.

This study contributes a statistically validated conceptual model of the drivers and barriers of cloud computing adoption. In addition, the research provides a comparison between two different discussions (i.e., industry report and academic research) on the same topic and data. The findings benefits are twofold. First, it seeks to clarify the profound knowledge on the factors surrounding cloud adoption to better understanding cloud computing. Second, it also provides directions for future research by suggesting validations on the proposed model while discussing the limitations of analysing commercial survey.

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  • 1. Contributing Factors of Cloud Computing Adoption:a Technology-Organisation-Environment FrameworkApproachMathews Z. Nkhoma & Duy P.T. DangSchool of Business IT & Logistics
  • 2. Cloud computing as an emergingtechnology• Cloud computing is an emerging technology that has been bringing manybenefits to businesses since 2007 (Aljabre 2012):–Only requires single-point, centralised installation Saves IT infrastructure costs through distributive hardware andsoftware– Supports flexible and dynamic changesEnables rapid business penetration to new markets; suitable forsmall and medium-sized businesses• Applications (Aljabre 2012):– Fosters distance collaboration (e.g. Google Drive)–Sharing repository (e.g. Dropbox)
  • 3. Why did we conduct this research• In a practical viewpoint, we aim to:– Support adoption of cloud computing to help foster businessefficiency, especially for SMEs with limited resources– Since cloud computing is relatively new in the market, continuous debatesand corrections are necessary to understand better the contributing factorsof its adoption– Make good use of the recent dataset conducted by IBM• In a theoretical viewpoint, we aim to:–Apply the Technology-Organisation-Environment framework to explain thephenomenon and contribute a conceptual model– Evaluate the use of secondary data analysis by using the public datasetfrom IBM
  • 4. Research questions•What are the contributing factors to theadoption of cloud computing in business?–What are the drivers?–What are the barriers?
  • 5. Research methodology• Positivism – Quantitative approach• Explain phenomenon by conducting statistical analysis and applying theory todevelop conceptual model• Statistical techniques:– Partial Least Square (PLS) (Ringle, C.M., Wende, S. and Will 2005) –secondary data analysis• Theory:– Technology-Organisation-Environment (TOE) framework (Tornatzky andFleischer 1990)• Dataset:– IBM Fast Track to The Future: The 2012 IBM Tech Trends Report– 1200 IT decision-makers from 16 industries in 13 countries–Insights about adoption of emerging technologies
  • 6. Proposed hypothesesHypothesisH1. Perceived Benefit (PB) has positive impact on Intention to adopt (ITA) cloudcomputing.H2. Perceived Environment Barriers (PEB) has negative impact on Intention toadopt (ITA) cloud computing.H3. Perceived Technology Barriers (PTB) has negative impact on Intention toadopt (ITA) cloud computing.H4. Adopter’s style (AS) has negative impact on Intention to adopt (ITA) cloudcomputing.H5. Adopter’s style (AS) has positive moderating impact on PerceivedTechnology Barriers (PTB).H6. Adopter’s style (AS) has positive moderating impact on PerceivedEnvironment Barriers (PEB).
  • 7. Analysed model
  • 8. Research findingsHypothesis ResultH1. Perceived Benefit (PB) has positive impact on Intention to adopt(ITA) cloud computing.Not supportedH2. Perceived Environment Barriers (PEB) has negative impact onIntention to adopt (ITA) cloud computing.Not supportedH3. Perceived Technology Barriers (PTB) has negative impact onIntention to adopt (ITA) cloud computing.Not supportedH4. Adopter’s style (AS) has negative impact on Intention to adopt(ITA) cloud computing.SupportedH5. Adopter’s style (AS) has positive moderating impact on PerceivedTechnology Barriers (PTB).Not supportedH6. Adopter’s style (AS) has positive moderating impact on PerceivedEnvironment Barriers (PEB).Not supported
  • 9. Discussion & LimitationCommercial report’s findings Statistical resultsInformation security is a majorchallenge to cloud computing adoptionPTB1 (InfoSec) has high loadingdespite its low statistical significanceMarket adaptability is a major driver ofadoption of cloud computingAlso has high loading but lowstatistical significanceAdoption of cloud computing dependson Adopter’s StyleConsistent result supported withstatistical significanceThe theory and results from data analysis slightly confirmed the report’sfindings the secondary dataset was our greatest challenge in this research
  • 10. Recommendations & Conclusion• We have evaluated the contributing factors of cloudcomputing adoption and the use of secondary commercialdataset• We have proposed the TOE framework-based conceptualmodel to explain the phenomenon• Future researches are strongly encouraged to developinstruments to capture data precisely and re-evaluate ourconceptual model
  • 11. Q & A–Dr. Mathews Z. Nkhomamathews.nkhoma@rmit.edu.vn–Mr. Duy P.T. Dangdptdang@gmail.com
  • 12. References• Aljabre, A. (2012), “Cloud Computing for Increased Business Value,”International Journal of Business and Social Science, Vol. 3 No. 1, pp. 234–239.• IBM Center for Applied Insights. (2012), Fast track to the future: The 2012IBM Tech Trends Report. Retrieved fromhttps://www.ibm.com/developerworks/mydeveloperworks/blogs/techtrends/?lang=en• Ringle, C.M., Wende, S. and Will, S. (2005), “SmartPLS 2.0 (M3) Beta,”Hamburg, Germany. http://www.smartpls.de.• Tornatzky, L.G. and Fleischer, M. (1990), The Processing of TechnologicalInnovation, Lexington, MA, Lexington Books.

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