| | Resources | Theory basis | Methodology | Adoption (DV) | Determinants (IV) |
| | [17] | No specific theory is used | PLS | Intention to adopt CC | Perceived accessibility, perceived scalability, perceived cost-effectiveness, perceived lack of security | | [18] | TAM | PLS | Behavioral intention | Social influence, attitude toward mobile innovation, perceived benefits, perceived usefulness, perceived ease of use, behavioral intention, marketing efforts, security, and trust | | [19] | TOE, DOI, INT | No specific methodology is used. | Intention to adopt cloud | Availability, reliability, security, privacy, trust, relative advantage, compatibility, complexity, top management support, organization size, technology readiness, compliance with regulations, competitive pressure, trading partner pressure, physical location | | [5] | TOE | Regression analysis | CC adoption | Relative advantage, complexity, compatibility, top management support, firm size, technology readiness, competitive pressure, trading partner pressure | | [20] | TAM3 | Path analysis | Actual usage of CC | Access to software, ease of travel, personal innovativeness, technology anxiety, instructor support, reliability, usefulness, ease of use | | [21] | TOE | SEM | Intention to adopt CC | Cloud security, compatibility, reliability and availability, extendibility of existing APPs to cloud, compliance policy, lack of IT standards, business scalability, cost flexibility, market adaptability, hidden complexity, share best practices, adopter’s style | | [22] | No specific theory is used | PLS | Usage and adoption of CC | Reliability, ease of use and convenience, cost reduction, sharing and collaboration, security and privacy | | [23] | TOE, DOI | SEM | CC adoption | Relative advantage, complexity, compatibility, security concerns, cost savings, technology readiness, top management support, firm size, competitive pressure, regulatory support | | [24] | TOE | Analysis of variance | The adoption decision of CC | CIO innovativeness, perceived technical competence, data security, complexity, compatibility, cost, relative advantage, top management’s support, adequate resource, benefits, government policy, perceived industry pressure | | [25] | TOE | SEM | Cloud adoption intention | Perceived benefits, business concerns, IT capability, external pressure | | [26] | TOE | Semistructured interviews | Intention to adopt cloud | Availability, reliability, security, privacy, trust, relative advantage, compatibility, complexity, top management support, organization size, technology readiness, compliance with regulations, competitive pressure, trading partner pressure, physical location | | [27] | TOE | SEM | Attitude toward SaaS, intention to use SaaS | IT infrastructure, top management support, relative advantage, simplicity, compatibility, experience ability, competitor pressure, partner pressure | | [28] | TOE | PLS | CC adoption | Relative advantage, complexity, compatibility, management support, vendor lock, data concern, government regulation, peer pressure | | [29] | TOE, DOI | Binomial test, fuzzy AHP | SaaS adoption | Relative advantage, competitive pressure, security and privacy, sharing and collaboration culture, social influence, compatibility, IT resource, observability, complexity, trialability | | [7] | TOE | SEM | Cloud service transformation intention | Reliability, information security, institutional pressure, structure assurance, vendor scarcity, size, international scope, IT competence, entrepreneurship | | [30] | No specific theory is used | Hierarchical multiple regression analysis | Cloud service adoption intention | Relative advantage, compatibility, observability, trialability, perceived complexity, subjective norms, new technology self-efficacy, network externality | | [31] | TOE | Analysis of variance, PLS | A firm’s intention to adopt CC services | Relative advantage, ease of use, compatibility, trialability, observability; security, firm size, global scope, financial costs, satisfaction with existing IS, competition intensity, regulatory environment | | [32] | TAM | Quantitative research | Respondents’ intention to use CC | Perceived ease of use, personal innovativeness, threat and high scores in respondents’ challenge, self-efficacy, openness to experience, computer competence, and in social media use | | [33] | No specific theory is used | Structural-equations model | Adoption on public CC | Alignment, adaptation, security, cost-effectiveness, operational risk, IT compliance, management/controlling power | | [34] | SLA, DOI, trust theory, TAM | Descriptive analysis, CFA, correlation analysis, fsQCA, SEM | Cloud service adoption intention | Trust of firms concerning cloud services, perceived usefulness of loud service, trust in cloud service, foundation characteristics specific to cloud service, perceived compatibility regarding cloud service, perceived relative advantage regarding cloud services | | [35] | DOI, TAM | SEM | Intention to adopt CC, actual usage of CC | Awareness, cost-effectiveness, risk, data security, infrastructure, relative advantage, compatibility, complexity, observability, trialability, results demonstrable, ease of use, usefulness, sociocultural | | [36] | TOE, DOI, INT | PLS | Three stage of SaaS diffusion: Intention, adoption, routinization | Relative advantage, compatibility, complexity, technology competence, top management support, coercive pressures, normative pressures, mimetic pressures | | [15] | No specific theory is used | SEM, EFA, CFA | CC adoption | Security, need, cost saving, supplier availability, integration, maintenance, virtualization, reliability, performance | | [37] | TOE, INT, PVT | SEM | The intention to adopt SaaS, the adoption of SaaS | Representation capability of SaaS, reach capability of SaaS, monitoring capability of SaaS, technology competence, top management support, coercive pressure, normative pressure, mimetic pressures | | [38] | DOI, TAM | SPSS, SEM | The intent to adopt CC, actual usage of CC | Awareness, upfront cost saving, running cost, risk, data security, availability of good information and communications technology infrastructure, relative advantage, compatibility, complexity, observability, trialability, results demonstrable, ease of use, usefulness, sociocultural factors, the age of the university, the size of the university, the location of the university, the age of university information and communications technology experts and decision-makers | | [39] | TAM | SEM | Behavioral intention to use | Perceived usefulness, perceived ease of use, top management support, training, communication, technological complexity, organization size | | [40] | No specific theory is used | SEM, CFA | The level of CC adoption | R&D institutions over an organization, the influence of technology providers, public administration on a given organization, managers’ awareness of killer applications based on cloud computing, managers’ awareness of success cases in cloud computing | | [41] | TOE, grounded theory | Coding | E-Government cloud adoption | Comparative advantage, technological concern, cloud provider characteristic, cloud provider competence, cloud provider presence, top management support, organization inertia, the scale and complexity of information resource, policy and regulation, industry standards, competition pressure, requirement of citizen, best practice, financial fund, initial trust, perceived benefit-based trust | | [42] | TOE | SEM, artificial neural network | CC adoption | Perceived IT security risk, risk analysis, technology innovation, usage of technology, industry usage, trust, management style | | [43] | TOE | PLS | SaaS adoption | Coercive pressures, normative pressures, mimetic pressures, technology competence, top management support | | [12] | TOE, DOI | Quantitative analysis, logistic regression | CC adoption | Manager cloud computing expertise, employee’s know-how, perceived business benefit, cost reduction, security and privacy, cooperation with cloud providers, the government support, employee’s information access, manager’s innovation capacity, trialability |
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