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

被引:7
作者
Priya, Samant Shant [1 ]
Jain, Vineet [2 ]
Priya, Meenu Shant [3 ]
Dixit, Sushil Kumar [4 ]
Joshi, Gaurav [5 ]
机构
[1] Lal Bahadur Shastri Inst Management, Dept Mkt Management, New Delhi, India
[2] Mewat Engn Coll, Dept Mech Engn, Nuh, India
[3] Galgotias Univ, Sch Business, Greater Noida, India
[4] Lal Bahadur Shastri Inst Management, Dept Strateg Management, Delhi, India
[5] Lal Bahadur Shastri Inst Management, Dept Mkt Management, Delhi, India
来源
FORESIGHT | 2023年 / 25卷 / 01期
关键词
Artificial intelligence; Adoption; DEMATEL; ISM; MICMAC; Indian management institutes; FMS PERFORMANCE VARIABLES; INDUSTRIAL-REVOLUTION; TECHNOLOGY; ISM; CHALLENGE; IMPACT; SEM; AI;
D O I
10.1108/FS-09-2021-0181
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
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.
引用
收藏
页码:20 / 40
页数:21
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