Title: Early internationalisation of entrepreneurial firms: the role of artificial intelligence enhanced business models

Authors: Tahseen Anwer Arshi; Venkoba Rao; Vazeerjan Begum; Nejat Çapar

Addresses: American University of Ras Al Khaimah, 75, Sheikh Humaid Bin Mohamed, Seih Al Araibi, Ras Al Khaimah, 72603, United Arab Emirates ' Majan University College, Ruwi, Muscat PC-112, Oman ' American University of Ras Al Khaimah, 75, Sheikh Humaid Bin Mohamed, Seih Al Araibi, Ras Al Khaimah, 72603, United Arab Emirates ' KIMEP University, Abay Ave 2, Almaty 050010, Kazakhstan

Abstract: The internationalisation of new firms has become an important research topic in recent years with the emergence of such firms. Consequently, an increased amount of research has been published examining the nature of the internationalisation of new firms. This study proposes an artificial intelligence-enabled business model design that helps entrepreneurs with early internationalisation by overcoming the limitations that new firms might be facing. Entrepreneurs face early internationalisation challenges due to limited resources that restrict their ability to internationalise quickly. This study is based on a sample of 337 new international entrepreneurial firms from India. The study utilises an artificial intelligence (AI) model based on a neural network model to predict the effect of business model design measures on the performance of firms. The results show that our model could predict entrepreneurial capability and financial performance outcomes. In other words, the model allows firms to increase their success in international markets by reducing the risks, learning time, and efforts linked with early internationalisation.

Keywords: internationalisation; entrepreneurial firms; emerging economies; business model; artificial intelligence; entrepreneurial capability; financial performance.

DOI: 10.1504/JIBED.2022.130387

Journal for International Business and Entrepreneurship Development, 2022 Vol.14 No.4, pp.536 - 556

Received: 23 Feb 2023
Accepted: 14 Mar 2023
Published online: 18 Apr 2023 *

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