Understanding the determinants of cloud computing adoption
Abstract
Purpose The purpose of this paper is to investigate the factors that affect the adoption of cloud computing by firms belonging to the high-tech industry. The eight factors examined in this study are relative advantage, complexity, compatibility, top management support, firm size, technology readiness, competitive pressure, and trading partner pressure. Design/methodology/approach A questionnaire-based survey was used to collect data from 111 firms belonging to the high-tech industry in Taiwan. Relevant hypotheses were derived and tested by logistic regression analysis. Findings The findings revealed that relative advantage, top management support, firm size, competitive pressure, and trading partner pressure characteristics have a significant effect on the adoption of cloud computing. Research limitations/implications The research was conducted in the high-tech industry, which may limit the generalisability of the findings. Practical implications The findings offer cloud computing service providers with a better understanding of what affects cloud computing adoption characteristics, with relevant insight on current promotions. Originality/value The research contributes to the application of new technology cloud computing adoption in the high-tech industry through the use of a wide range of variables. The findings also help firms consider their information technologies investments when implementing cloud computing.
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Davis proposed that system usage is a human behavior that is user motivation driven and directly influenced by external stimulation like system's components and efficiency.
“According to [1], Davis proposed that system usage is a human behavior that is user motivation driven and directly influenced by external stimulation like system's components and efficiency.”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
In the 1970s, anticipating system growth became a niche due to growing technology demand and system adoption failure.
“In the 1970s, anticipating system growth became a niche of attraction to many researchers due to the growing technology demand and system adoption failure that goes with it [1].”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
A user's attitude is leveraged by perceived usefulness and perceived ease of use.
“A user's attitude is leverage by perceived usefulness and perceived ease of use.”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
Davis proposed that user interaction with any system is a reaction that can be interpreted and foreseen by user inspirations, shaped by foreign catalyst.
“Davis proposed that the user interaction with any system is a reaction that can be interpreted and foreseen by user inspirations, shaped by foreign catalyst [1].”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
User inspirations are shaped through a foreign catalyst that abides system's features and capabilities.
“As per [1] user inspirations are shaped through a foreign catalyst that abides system's features and capabilities.”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
TAM was proposed by Davis in 1985 during his studies at MIT Sloan School of Management.
“The TAM was then proposed by [10] in 1985 during his studies at MIT Sloan School of Management [1].”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
Davis's thesis on user's attitude towards a system is a major factor that determines if a user will use or reject a system.
“According to [1] Davis's thesis on user's attitude towards a system is a major factor that determents if a user will use or reject a system.”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
The most important variables of organisational context include financial resources, firm structure, organisational slack, innovation capacity, knowledge capability, operational capability, strategic use of technology, trust, technological resources, top management support, support for innovation, quality of human capital, organisational knowledge accumulation, expertise and infrastructure, and org
“As per [1-3, 9, 12, 18, 22, 32, 33, 35] the most important variables of organisational context includes “financial resources, firm structure, organisational slack, innovation capacity, knowledge capability, operational capability, strategic use of technology, trust, technological resources, top management support, support for innovation, quality of human capital, organisational knowledge”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
Aside from innovation variables, other significant variables like system absorption, digestion, trail ability, intricacy, seen direct advantages, seen backhanded advantages and normalization have been included by several research studies while observability is found insignificant.
“Aside from innovation variables, other significant variables like system absorption, digestion, trail ability, intricacy, seen direct advantages, seen backhanded advantages and normalization has been included by several research studies while observability is found insignificant [1, 2, 9, 12, 18, 22, 32-34].”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
The T-O-E system has no significant develops in the model and the factors in every unique circumstance.
“[1] likewise featured that T-O-E system has no significant develops in the model and the factors in every unique circumstance [33] states that there lack in power of technology and adoption variance is unexplained.”
From A Review on TAM and TOE Framework Progression and How These Models Integrate (2021) · cites this paper as [1]
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Oliveira, T., & Martins, M. F. (2010) · Industrial Management & Data Systems · doi:10.1108/02635571011087428 · Cited by 641 · see citing works
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“According to [1] Davis's thesis on user's attitude towards a system is a major factor that determents if a user will use or reject a system.”
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- Authors
- Low, C., Chen, Y., & Wu, M.
- Affiliations
- National Yunlin University of Science and Technology (TW)
- Graduate School of Technological & Vocational Education, National Yunlin University of Science & Technology, Douliou, Taiwan, Republic of China
- ORCID
- Low, Chinyao
- Venue
- Industrial Management & Data Systems
- Publisher
- Emerald
- Published
- 2011-08-23
- Volume
- 111
- Issue
- 7
- Pages
- 1006-1023
- ISSN
- 0263-5577 (ISSN-L)
- 1758-5783
- OpenAlex
- W2044744255
- Cited by
- 1,181
- References
- 4
- Citations by year
- 2026: 47 · 2025: 55 · 2024: 58 · 2023: 81 · 2022: 109 · 2021: 117 · 2020: 113 · 2019: 95 · 2018: 89 · 2017: 110 · 2016: 85 · 2015: 101 · 2014: 71 · 2013: 31 · 2012: 16
- FWCI
- 91.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Industrial Management & Data Systems (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
- Keywords
- cloud computing adoption, technology adoption, high-tech industry, relative advantage, top management support, firm size, competitive pressure, technology readiness, complexity, compatibility, IT investment
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