Artificial Intelligence (AI) and Technology Diffusion – Multinational Marketing Management Strategies
International Journal of Multinational Corporation Strategy Special Issue on: "Artificial Intelligence (AI) and Technology Diffusion – Multinational Marketing Management Strategies"
As technology revolutionises communication, financial flows and transportation, the world continues to feel smaller and smaller. It is now possible for companies to conduct business in almost any country around the world due to advances in global trade. Consequently, international and multinational marketing management are becoming more important; they support business activities, co-operations and consumer promotions. Multinational marketing can be simply categorised into two modes: business-to-business mode (B2B; industrial marketing) focuses on co-operations between organisations and resource sharing and integration, while business-to-consumer mode (B2C; promotional marketing) puts more emphasis on product and service positioning as well as promotions for end customers. From the B2B industrial marketing perspective, with the trend of AI development, global technology companies such as Google, IBM and NVIDIA have started to establish research centres and invest in skilled technical employees in host countries. These multinational enterprises (MNEs) work closely with local businesses in host countries and utilise the host country's information and communications technology (ICT) supply chain planning and technological manufacturing capabilities in the MNEs' AI research and development (R&D) and production. Having support from the governments of these host countries, such as the policy of promoting open, investment regimes and liberalised trade as a basis for economic growth, MNEs aim to build a consummate innovation ecosystem in these host countries.
Nevertheless, the innovation diffusion and collaborative R&D industrial strategies are facing significant challenges. For instance, MNEs' strategies in innovation diffusion and R&D collaboration are affected by host countries' industrial clusters, supply chains and related regulations (Cantwell & Zhang, 2011; Crescenzi, Gagliardi & Iammarino, 2015; Nygaard & Dahlstrom, 1992); resource integration is difficult as industrial marketing elements such as the host country's technology adoption capabilities of different industries and companies—including semiconductors, ICT, precision machinery manufacturing, and textiles—all need considerable evaluation and organisation (Castellani & Zanfei, 2002; Reddy, 1997). From the B2C marketing perspective, although more researchers and practitioners are devoted to promoting new AI applications, existing studies predominantly focus on maximising AI utility. For instance, the technology acceptance model (TAM) suggests that ease of use, usefulness, privacy issues and the possible risks of using an AI application can affect consumers adoption intentions (Davis, 1989; Duan, Edwards & Dwivedi, 2019).
However, more and more industrial reports indicate that the relevant AI utility factors are not sufficient enough to support the international marketing and promotional activities in most host countries, particularly host countries with companies who have recently established cooperative relationships with the MNEs (i.e. the AI applications are fairly new to consumers in these host countries) (Roth & Romeo, 1992; Carneiro & Faria, 2016). For instance, the Chinese brand Vivo frequently introduces innovative technologies but often encounters challenges when promoting in host countries such as Japan and Korea where Vivo develops AI applications with local businesses (Batra et al., 2000). Similarly, plastic payment such as debit cards and mobile payment are widely adopted in Western countries but are hard to promote in most Eastern societies such as India, even though many technological protocols are codeveloped with companies in India (Kesharwani & Bisht, 2012; Zhao, Anong & Zhang, 2019).
Furthermore, Facebook has been widely adopted by 24 billion users worldwide, but their Marketplace services are difficult to promote outside the U.S (Al-Heeti, 2018). In summary, although a good AI multinational co-operation might be established between the home country and the host country, the promotion of these AI applications in host countries can still be challenging. Some practitioners suggest that when introducing new technologies and AI applications to a new country or region, companies should create a character brand (Zhao & Balague, 2015). For example, “LINE”, an instant communication application for electronic devices, introduced “LINE FRIENDS” to create different characters or mascots for the brand. Such brand positioning strategies may help companies introduce new technology to other countries by capitalising on an emotional bond with consumers (Calder, Malthouse & Schaedel, 2009).
Nevertheless, when lacking a consistent theoretical foundation, it is hard to duplicate business success across nations. Unfortunately, only a few studies have investigated AI business co-operations with local organisations in host countries (B2B) or promotional strategies of AI applications (B2C) in these host countries. Our understanding of brand management, consumers' technology adoption intention, and cultural differences in managing and establishing multinational marketing management strategies is still limited. This call for papers seeks to provide multinational companies with AI development and management strategies from the B2B and B2C marketing perspectives, including government policy development, innovation diffusion and ecosystems, consumer behaviour and culture differences, and consumer AI adoption. Studies are encouraged to investigate industrial marketing perspectives and/or the consumer promotional marketing perspective of MNEs seeking to expand AI technologies to new foreign markets.
Subject Coverage Suitable topics include, but are not limited, to the following:
From the B2B perspective:
- MNE with AI development’s marketing and innovation diffusion
- MNE with AI development’s global innovation strategy on AI technology
- MNE with AI development and (local) innovation ecosystem
- MNE with AI development and host countries’ sectoral and technological innovation system
- MNEs with AI development’s innovation diffusion and host countries’ technology adoption
- AI innovation diffusion and industrial dynamics/transformation
From the B2C perspective:
- MNEs’ brand extension and management
- MNEs’ country of origin and country image on the execution of AI and introduction of new technology to a new market
- MNEs’ communication and promotional strategies
- MNEs’ AI personalisation and localisation of products
- Target market legislation or government policy barriers on MNEs’ introduction of AI and new technology products
Notes for Prospective Authors
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. (N.B. Conference papers may only be submitted if the paper has been completely rewritten and if appropriate written permissions have been obtained from any copyright holders of the original paper). All papers are refereed through a peer review process. https://www.dropbox.com/s/ih7pokks4wqhjxi/IJMCS%20CFP%20id4954.pdf?dl=0 All papers must be submitted online. To submit a paper, please read our Submitting articles page: https://www.inderscience.com/jhome.php?jcode=ijmcs
If you have any queries concerning this special issue, please email Dr. Yu-Lun Liu at email@example.com.
Manuscripts due by: 31 May, 2020
Notification to authors: 31 July, 2020
Final versions due by: 1 October, 2020
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