Purpose This study assesses the capability of artificial intelligence integrated customer relationship management (AI-CRM) technology for sustaining family businesses in times of crisis, such as the COVID-19 pandemic. The study also investigates the moderating role of strategic intent in sustaining family businesses in times of crisis. Design/methodology/approach The authors used dynamic capability view theory and related literature on family business and technology adoption to develop a conceptual model. This model has been validated using the structural equation modeling technique considering 332 usable responses from people of India involved in family businesses and technology adoption. The study also uses multigroup analysis to examine the moderating role of strategic intent. Findings The study finds that adoption of AI-CRM technology significantly and positively impacts dynamic capabilities of the family businesses, such as sensing, seizing and transforming capabilities, which in turn positively and significantly influences their sustainability during crises. The study also highlights the significant moderating impact of strategic intent for sustaining family business firms in uncertain times. Practical implications This study has highlighted the importance for family businesses to adopt AI-CRM technology and its influence on their dynamic capabilities. The study also provides important inputs to the management of family businesses regarding adoption of new technologies and their significance during crises. The study also documents that strategic intent could help family businesses to survive during such times. The study is conducted in India and thus cannot be generalized. Originality/value This study table is unique in that it investigates the influence of AI-CRM technology and the moderating role of strategic intent on family business sustainability in times of crisis. Moreover, the proposed theoretical model is a unique model with explanative power of 71%.
机构:
Imperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, EnglandImperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, England
Anderson, Roy M.
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Heesterbeek, Hans
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机构:
Univ Utrecht, Dept Populat Hlth Sci, Utrecht, NetherlandsImperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, England
Heesterbeek, Hans
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Klinkenberg, Don
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Natl Inst Publ Hlth & Environm RIVM, Bilthoven, NetherlandsImperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, England
Klinkenberg, Don
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Hollingsworth, T. Deirdre
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Univ Oxford, Li Ka Shing Ctr Hlth Informat & Discovery, Big Data Inst, Oxford, EnglandImperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, England
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Michigan State Univ, Sch Journalism, Room 344,404 Wilson Rd, E Lansing, MI 48824 USAMichigan State Univ, Sch Journalism, Room 344,404 Wilson Rd, E Lansing, MI 48824 USA
机构:
Imperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, EnglandImperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, England
Anderson, Roy M.
;
Heesterbeek, Hans
论文数: 0引用数: 0
h-index: 0
机构:
Univ Utrecht, Dept Populat Hlth Sci, Utrecht, NetherlandsImperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, England
Heesterbeek, Hans
;
Klinkenberg, Don
论文数: 0引用数: 0
h-index: 0
机构:
Natl Inst Publ Hlth & Environm RIVM, Bilthoven, NetherlandsImperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, England
Klinkenberg, Don
;
Hollingsworth, T. Deirdre
论文数: 0引用数: 0
h-index: 0
机构:
Univ Oxford, Li Ka Shing Ctr Hlth Informat & Discovery, Big Data Inst, Oxford, EnglandImperial Coll London, MRC Ctr Global Hlth Anal, Dept Infect Dis Epidemiol, London W2 1PG, England
机构:
Michigan State Univ, Sch Journalism, Room 344,404 Wilson Rd, E Lansing, MI 48824 USAMichigan State Univ, Sch Journalism, Room 344,404 Wilson Rd, E Lansing, MI 48824 USA