Analysis of cloud adoption determinants by using BOCR analysis and DEMATEL

Hidayanto, Achmad Nizar; Abednego, Nathan; Aminah, Siti; Sucahyo, Yudho Giri

doi:10.1504/ijbis.2015.067265

Cited by 7 publications

(4 citation statements)

References 40 publications

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“…While all cloud projects had different significantly intentions to adopt the E-government cloud (Hidayanto et al, 2015). The dissimilar intentions might be due to the differences in E-government cloud adoption driven factors .Emergent concepts will be discussed as they appeared from the case analyses.…”

Section: Resultsmentioning

confidence: 98%

Exploring the Determinants Affecting E-Government Cloud Adoption in China

Ji¹,

Liang²

2016

IJBM

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Cloud computing is the popular tendency in information application and services, and E-Government cloud is no exception. This study uses a case study to explore the determinants of E-Government cloud adoption in China which is influenced by multiple factors. In this study, a combinational model based on the TOE and DOI is applied to gain insights concerning all contextual influences on the adoption of E-Government cloud in China. The results show that the positive and negative influences from cloud technology characteristics, organizational and environmental context, which can reflect the adoption of E-government cloud. These findings not only contribute to academic research, but also expand the understanding of E-government cloud applications.

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Section: Resultsmentioning

confidence: 98%

Exploring the Determinants Affecting E-Government Cloud Adoption in China

Ji¹,

Liang²

2016

IJBM

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“…Results of the study highlighted that a factor, namely, "senior management support" was the most significant. Hidayanto et al (2015) employed benefits, opportunities, costs and risks and DEMATEL methodology for analysing the influence of organisational factors on CCA in the mining service sectors. It was concluded that a factor, namely, "availability of resources" influences CCA significantly.…”

Section: Applications Of Mcdm Methodologies In the Cloud Computing Areamentioning

confidence: 99%

To investigate the determinants of cloud computing adoption in the manufacturing micro, small and medium enterprises

Raut

Gardas²,

Narkhede

et al. 2019

BIJ

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Purpose The purpose of this paper is to identify the critical factors influencing the cloud computing adoption (CCA) in the manufacturing micro, small and medium enterprises (MSMEs) by employing a decision-making trial and evaluation laboratory (DEMATEL) methodology. Design/methodology/approach Through literature review and expert opinions, 30 significant factors were identified, and then a DEMATEL approach was applied for exploring the cause–effect relationship between the factors. Findings The results of study highlighted that five factors, namely, “hardware scalability and standardisation”, “cost (subscription fees, maintenance cost and implementation cost (CS1)”, “innovation”, “installation and up gradation (CS28)”, and “quality of service” were the most significant factors influencing the CCA in the case sector. Research limitations/implications The DEMATEL model was developed by considering expert inputs, and these inputs could be biased which can influence the reliability of the model. This study guides the organisational managers, cloud service providers and governmental organisations in formulating the new policies/strategies or modifying the existing ones for the effective CCA in the case sector. Originality/value For the first time. interdependency between the critical factors influencing CCA was discussed by employing the DEMATEL approach in the Indian manufacturing MSMEs context.

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“…DEMATEL method was applied for evaluating direct and indirect influences among criteria in multi-criteria decision scenarios (Gandhi et al 2015). DEMATEL was applied for prioritizing of investment projects portfolio, agri-food supply chains for sustainable initiatives, and analysis of cloud adoption determinants (Hidayanto et al 2015;Altuntas and Dereli 2015;Mangla et al 2018). This method was also applied to evaluate green supply chain management practices and enablers in solar power developments (Lin 2013;Luthra et al 2016).…”

Section: Dematel Approachmentioning

confidence: 99%

Big data analytics application for sustainable manufacturing operations: analysis of strategic factors

Kumar

Singh

2021

Clean Techn Environ Policy

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In the present era of Industry 4.0, organizations are transforming from traditional production systems to digital production systems. This transformation is in terms of additional deployment of technologies that lead to digitization and integration of products and services, business processes and customers, etc. A high volume of unstructured data is being created across different processes due to digitization. The digitization captures the data that includes text, images, multimedia, etc., due to multiplicity of platforms, e.g., machine-to-machine communications, sensors networks, cyber-physical systems, and Internet of Things. Managing this huge data generated from different sources has become a challenging task. Big data analytics (BDA) may be helpful in managing this unstructured data for effective decision making and sustainable operations. Many organizations are struggling to integrate BDA with their manufacturing processes for sustainable operations. The application of BDA from a sustainability perspective is not extensively researched in the current literature. Therefore, firstly this study explores the contribution of BDA in sustainable manufacturing operations. It further identifies strategic factors for the successful application of BDA in manufacturing for sustainable operations. For a detailed analysis of strategic factors in manufacturing, a hybrid approach comprising the analytic hierarchy process, fuzzy TOPSIS and DEMATEL is used. Results revealed that development of contract agreement among all stakeholders, engagement of top management, capability to handle big data, availability of quality and reliable data, developing team of knowledgeable, and capable decision-makers have emerged as major strategic factors for the application of BDA in the manufacturing sector for sustainable operations. Major contribution of this study is in analyzing BDA benefits for manufacturing sector, identifying major strategic factors in implementation and categorization of these factors into cause and effect group. These findings may be used by managers as guidelines for successful implementation of BDA across different functions in their respective organization to achieve sustainable operations goal. The results of this study will also motivate industry professionals to integrate BDA with their manufacturing functions for effective decision making and sustainable operations.

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Analysis of cloud adoption determinants by using BOCR analysis and DEMATEL

Cited by 7 publications

References 40 publications

Exploring the Determinants Affecting E-Government Cloud Adoption in China

Exploring the Determinants Affecting E-Government Cloud Adoption in China

To investigate the determinants of cloud computing adoption in the manufacturing micro, small and medium enterprises

Big data analytics application for sustainable manufacturing operations: analysis of strategic factors

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