Modelling the factors affecting global economy during COVID-19 using ISM approach

Priya, Meenu Shant; Jain, Vineet; Kabiraj, Sajal; Priya, Samant Shant

doi:10.1504/ijsem.2021.118460

Cited by 4 publications

(2 citation statements)

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“…Using reachability and antecedent sets, the levels are established in an iterative process. These levels are used to develop an ISM model for factors in the adoption of AI technologies (Dixit and Priya, 2021; Priya et al , 2021a; Priya et al , 2021b; Dixit et al , 2021).…”

Section: Methodsmentioning

confidence: 99%

Modelling the factors in the adoption of artificial intelligence in Indian management institutes

Priya¹,

Jain²,

Priya

et al. 2022

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Purpose This study aims to examine which organisational and other factors can facilitate the adoption of artificial intelligence (AI) in Indian management institutes and their interrelationship. Design/methodology/approach To determine the factors influencing AI adoption, a synthesis-based examination of the literature was used. The interpretative structural modelling (ISM) method is used to determine the most effective factors among the identified ones and the inter-relationship among the factors, while the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to analyse the cause-and-effect relationships among the factors in a quantitative manner. The approaches used in the analysis aid in understanding the relationship among the factors affecting AI adoption in management institutes of India. Findings This study concludes that leadership support plays the most significant role in the adoption of AI in Indian management institutes. The results from the DEMATEL analysis also confirmed the findings from the ISM and Matrice d’ Impacts croises- multiplication applique and classment (MICMAC) analyses. Remarkably, no linkage factor (unstable one) was reported in the research. Leadership support, technological context, financial consideration, organizational context and human resource readiness are reported as independent factors. Practical implications This study provides a listing of the important factors affecting the adoption of AI in Indian management institutes with their structural relationships. The findings provide a deeper insight about AI adoption. The study's societal implications include the delivery of better outcomes by Indian management institutes. Originality/value According to the authors, this study is a one-of-a-kind effort that involves the synthesis of several validated models and frameworks and uncovers the key elements and their connections in the adoption of AI in Indian management institutes.

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Section: Methodsmentioning

confidence: 99%

Modelling the factors in the adoption of artificial intelligence in Indian management institutes

Priya¹,

Jain²,

Priya

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…ISM technique has been extensively used in fields such as classroom communication barriers [ 49 ], barriers in controlling TB [ 50 ], factors affecting global economy [ 51 ], QOL in diabetics [ 52 ], lean management [ 53 ], and selection of reverse logistics provider [ 54 ]. An ISM-based analysis has been used to conduct barrier analysis in implementing green supply chain management [ 55 ].…”

Section: Methodsmentioning

confidence: 99%