What drives MLOps adoption? An analysis using the TOE framework

Das, Sibanjan; Bala, Pradip Kumar

doi:10.1080/12460125.2023.2214306

Cited by 9 publications

(2 citation statements)

References 105 publications

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“…In the context of AI and blockchain in auditing, institutional theory can be used to explore the external pressures and institutional forces that drive or impede the adoption and acceptance of these technologies in the audit profession. It can shed light on the role of professional bodies, regulatory bodies, and industry norms in shaping the use of AI and blockchain in audits [ 16 ].…”

Section: Literature Review and Theoretical Frameworkmentioning

confidence: 99%

Influence of blockchain and artificial intelligence on audit quality: Evidence from Turkey

Qader,

Cek

2024

Heliyon

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Section: Literature Review and Theoretical Frameworkmentioning

confidence: 99%

Influence of blockchain and artificial intelligence on audit quality: Evidence from Turkey

Qader,

Cek

2024

Heliyon

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“…Another study in the context of AI [42] conducted a comparative case study to explore the adoption of artificial intelligence in public organizations, providing insights into the factors and dynamics shaping AI adoption in the public sector. Another study has investigated the antecedents of MLOps (machine learning operations) adoption, employing the TOE framework for analysis [54].…”

Section: Literature Review 21 Technology-organization-environment (To...mentioning

confidence: 99%

Artificial Intelligence Adoption by SMEs to Achieve Sustainable Business Performance: Application of Technology–Organization–Environment Framework

Badghish,

Soomro

2024

Sustainability

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The primary purpose of this study was to investigate and present a theoretical model that identifies the most influential factors affecting the adoption of artificial intelligence (AI) by SMEs to achieve sustainable business performance in Saudi Arabia by integrating the Technology–Organization–Environment (TOE) framework. The authors utilized a quantitative method, using a survey instrument for this research. Data for this research were collected from managers working in six different sectors. Subsequently, based on company size, firms were divided into two groups, allowing multi-group analysis of small and medium-sized businesses to explore group differences. Hence, firm size played a moderating role in the conceptualized model. Data analysis was performed on SmartPLS 3, and the results suggest that dimensions of the TOE framework, such as relative advantage, compatibility, sustainable human capital, market and customer demand, and government support, play a significant role in the adoption of AI. Moreover, this study found a significant influence of AI on SMEs’ operational and economic performance. The multi-group analysis (MGA) results reveal significant group differences, with a medium-sized firm strengthening the relationship between relative advantage and AI adoption compared to small-size firms. The findings lead to practical implications for companies on how to increase the adoption of AI to help SMEs embrace their technological challenges in KSA and obtain sustainable business performance to contribute to the economy.

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Leveraging cognitive digital twins in industry 5.0 for achieving sustainable development goal 9: An exploration of inclusive and sustainable industrialization strategies

Sharma,

Gupta

2024

Journal of Cleaner Production

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What drives MLOps adoption? An analysis using the TOE framework

Cited by 9 publications

References 105 publications

Influence of blockchain and artificial intelligence on audit quality: Evidence from Turkey

Influence of blockchain and artificial intelligence on audit quality: Evidence from Turkey

Artificial Intelligence Adoption by SMEs to Achieve Sustainable Business Performance: Application of Technology–Organization–Environment Framework

Leveraging cognitive digital twins in industry 5.0 for achieving sustainable development goal 9: An exploration of inclusive and sustainable industrialization strategies

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