Impact of Artificial Intelligence on Business in Emerging Markets
Call for papers for: International Journal of Emerging Markets
• Zhilin Yang, City University of Hong Kong: [email protected]
• Michael R. Hyman, New Mexico State University: [email protected]
• Xinyue Zhou, Zhejiang University: [email protected]
• Gang Li, North China University of Water Resources & Electric Power: [email protected]
With the rapid advances of artificial intelligence (AI) technologies, firms from emerging markets have started adopting AI applications to enhance their productivity and find ways to expand their business. Leading developing nations like China are witnessing an upward trend in AI applications. The rapid development of machine learning and deep learning has produced huge strides in cognitive computing and natural language processing, laying the foundations for AI business applications (Bughin et al., 2017). AI is poised to reshape most aspects of emerging markets; for example, finance, labor, human resource management, marketing, advertising, business strategy, supply chain management, services, retail, and information systems. Consequently, savvy entrepreneurs are exploring the potential of facial, image, and speech recognition to reduce the costs and barriers of doing business, which in turn should improve productivity.
In emerging markets, AI provides a technological solution to the economic challenges faced by governments, firms, and people at the bottom of the economic pyramid. Integrating data from multiple sources (e.g., websites, social media, and traditional channels) can help firms build data management platforms, develop sound business strategies, low barriers to doing business, create innovative business models, and spur economic development (Arora, Rahman, & Alon, 2017). Firms in developing countries may use innovative AI-based solutions to enhance autonomous goods and service delivery, implement production automation, and develop mobile AI apps for services and credit access (Strusani & Houngbonon, 2019). By enhancing productivity, business process automation, financial solution, and government services, AI-based technologies can create opportunities and expand markets. Powered by AI, the public and private sectors in emerging markets can find leapfrogging solutions and work together to reduce poverty and inequality while boosting economic mobility and prosperity (Andrews et al., 2019).
As businesses embrace AI solutions, new challenges have emerged in the corporate adoption, utilization, integration, and implementation of AI in emerging markets. Several conceptual studies have addressed the challenges of AI in services (Huang and Rust, 2017, 2018; Van Doorn et al., 2017; Wirtz et al., 2018), personalization (Kumar et al., 2019), advertising (Kietzmann et al., 2018), sales management (Singh et al., 2019), industrial marketing (Martínez-López and Casillas, 2013), automation in business logistics systems (Klumpp, 2018), market research (Wirth, 2018), smart warehousing readiness (Mahroof, 2019), AI platforms (Dawar and Bendle, 2018), tourism management (Stalidis et al., 2015), and ethics (Fullerton et al., 2017; Nunan and Di Domenico, 2017). Despite increasing interest, academic contributions to business-related AI in emerging economies remain scant. The institutional environments in developing countries differ vastly from those in developed countries, which creates obstacles and legitimacy issues for AI-power business applications (Yang et al., 2012). Hence, we call for more theoretical and empirical studies to tackle the challenges of AI in emerging markets.
The goals of this thematic symposium are threefold. First, it is meant to encourage new AI-related frameworks drawn from traditional theories and models, with the focus on emerging markets. A scientifically sound mindset would prompt a reassessment of traditional theoretical assumptions. For example, the fundamental concept of microeconomic theory—rationality—should be redefined in the context of AI to manifest new devices for making and augmenting rational decision making (Parkes and Wellman, 2015). Machina economicus reflects the profound effects of AI on economic reasoning. Similarly, new conceptual frameworks for AI in business should suggest important research directions (Hartmann et al., 2015; Kumar et al., 2016; Yadav and Pavlou, 2014).
Second, researchers can use AI-powered tools – such as facial recognition, speech recognition system, image recognition, machine learning, and natural language processing – in their research about business problems in emerging markets. With the overwhelming amount of data now available, innovative data analysis approaches are needed to augment often-insufficient purposive and rule-based data analyses. Third, empirical studies can help firms identify and understand AI’s disruptive potential as well as the obstacles and challenges of adopting and integrating AI into business in emerging economies.
The overarching goal of this thematic symposium is to help scholars and practitioners think more systematically about AI’s influence on emerging markets. Many diverse topics are suitable. We welcome original manuscripts from a range of theoretical, methodological, and multidisciplinary perspectives, and invite submissions on, but not limited to, the following topics:
• What new value propositions or business models can be created with AI applications to cater to the needs of the underserved in emerging markets?
• How will the value of business be realized and appropriated when AI is applied? In essence, how can firms monetize AI in emerging markets?
• Regarding the obstacles to AI adoption in emerging markets, how do the institutional, political and economic environments in emerging markets affect AI-related business strategy and applications?
• Which aspects of business are suitable for AI solutions? Which aspects are inappropriate?
• What are the key roles of AI in reducing poverty and boosting shared prosperity?
• What changes should firms in emerging markets make to accommodate the AI revolution?
• How can a business harness the opportunities AI offers in emerging markets?
• What is the impact of AI on the working environment and employee welfare in emerging markets?
• What organizational culture should firms nurture to maximize AI-related benefits?
• How should marketers use AI to predict and change consumer behaviors—from customer awareness, information search, evaluation, and purchase decision making, to post-purchase behaviors?
• How can managers in emerging markets leverage AI to manage customer experience and engagement?
• How will AI affect services marketing (e.g., service design, co-creation, customer engagement, real-time customer support, service recovery, satisfaction, loyalty, complaints, and customer churn)?
• How will AI facilitate value co-creation by consumers and firms in emerging nations?
• How will human-computer interaction (voice, personification) influence green consumer behavior?
• What role should government play to harness the opportunities AI offers in emerging markets? Should it set standards, provide seed money, open access to big data, support related policies, et cetera?
• How will AI transform audience selection, account-based marketing, offers and content channels, analysis, forecasting, and anomaly detection based on a prospect’s activities, firmographics, and buying stage?
• What role will AI play in personalization, disintermediation, search, assortment planning, voice ordering, customer support, and self-checkout services?
• How will AI platforms (e.g., Apple Siri, Microsoft Cortana, Amazon Alexa, and Google Assistant) reshape marketing strategies such as branding, advertising, and promotion?
• What are the effects of AI on logistics activities such as predictive risk management, transportation, intelligent route optimization, intelligent robot sorting, and visual inspection of logistics assets?
• How can AI-related challenges in logistics management (e.g., inventory planning and control, production planning, and scheduling) be resolved in emerging markets?
• What are the ethical, legal, and social issues resulted from AI usage in emerging markets?
• How should firms deal with the erosion of human self-determination due to the invisibility and influence of AI in business?
• What are the moral responsibilities of regulators, marketers, and customers in AI-based businesses?
• How do AI-related business applications in emerging markets differ from those in developed countries?
• How will AI technology disrupt and transform traditional job requirements?
• What are the negative externalities of jobs returning from emerging markets to mature markets due to AI-induced productivity gains?
• How can multinational corporations use AI to enhance the social welfare of people at the bottom of the economic pyramid?
• How can AI help human capital development?
• How will AI affect the traditional export-led path to economic growth in emerging markets?
• What are the socioeconomic driving forces behind AI in an emerging economy?
• How will AI affect consumer self-service and service automation?
• How will big data, cloud computing, and data mining for accurate warning and prevention of safety risks affect emerging markets?
• How will AI and data mining affect tourism consumption in emerging markets?
• How will consumer psychology interact with AI-powered service convenience and its privacy protection in the emerging markets?
• How can the issues of privacy, security, and public trust be addressed?
• Will AI increase the technological divide between emerging and mature nations?
Authors should refer to the International Journal of Emerging Markets author guidelines for submission instructions.
Submission to the special thematic symposium issue—by October 31, 2020—is required through online submission. Upon submission, please indicate if your submission is to this thematic symposium.
Please direct questions about expectations, requirements, appropriateness of a topic, and the like to one of the guest editors: Zhilin (Forrest) Yang, Michael Hyman, Xinyue Zhou, and Gang Li.
As an additional resource, a symposium on the effect of AI on marketing will be held at North China University of Water Resources & Electric Power on March 14, 2020. Scholars interested in attending the symposium should submit an outline or abstract of their intended manuscript (250 words) to one of the guest co-editors by February 15, 2020. These submissions and expressions of interest should not be submitted through the International Journal of Emerging Markets website. Conference attendance is not required for publication in this thematic symposium issue.
Backgrounds of the proposed Guest Editors
Dr. Zhilin Yang is Professor of Marketing at City University of Hong Kong. He has published over 80 articles in such leading journals as Journal of Marketing, Journal of Marketing Research, and Journal of International Business Studies. His widely cited publications have garnered several distinctions, among which are Emerald Citations of Excellence for 2015 and 2013 University Research Excellence Award. Dr. Yang serves as an Editor-in-Chief of Asian Journal of Business Research; Associate Editor of European Journal of Marketing, and is a member of the editorial board for Journal of Business Research, Industrial Marketing Management, Asia Pacific Journal of Marketing and Logistics, and EsicMarket. He has co-edited special issues for Journal of Business Ethics (2009), Industrial Marketing Management (2010, 2012), Journal of Business Research (2011), and International Marketing Review (2019). His research interests include international business, marketing strategy, and service marketing.
Dr. Michael R. Hyman is Distinguished Achievement Professor of Marketing at New Mexico State University in Las Cruces, New Mexico. His roughly 100 academic journal articles, 60 conference papers (12 ‘best paper’ award winners), four co-authored/co-edited books, 30 other academic contributions, and 60 non-academic works, attest to this writing compulsion. He has served on 15 journal editorial boards and as a journal co-editor. Currently, he is a section editor for Journal of Business Ethics and an associate editor for Journal of Marketing Theory and Practice. He has co-edited special issues of Journal of the Academy of Marketing Science, Journal of Advertising (2), Journal of Business Research (2), Journal of Business Ethics (2), European Journal of Marketing, and International Marketing Review. His research interests include consumers' responses to advertising, ethics in marketing, survey research methods, knowledge acquisition in academia, and philosophical analyses in marketing.
Dr. Gang Li is Distinguished Achievement Professor of Management and Dean of the School of Management and Economics at North China University of Water Resources & Electric Power in Zhengzhou, China. He has led many projects funded by the National Social Science Fund of China, Soft Science Foundation of Henan province, and Program for Science & Technology Innovation Talents in Universities of Henan Province. He has authored over 40 academic publications, including 36 journal papers and five books. Currently, he is a section editor of Chinese Journal of Management and Management Review. His research interests include marketing theory, artificial intelligence in business, management science, and service innovation and entrepreneurship.
Dr. Xinyue Zhou is Professor of Psychology and Professor of Marketing at Zhejiang University, Hangzhou, China. She is currently an associate editor of the Asian Journal of Social Psychology and Journal of Pacific Rim Psychology. Her research interests focus on complex emotions and the psychology of money. Zhou has authored more than 40 professional publications. Her research has garnered widespread academic and media attention. Her work has been featured or reported in Nature, Scientific American, Time, Newsweek, Wall Street Journal and The New York Times, and wrote the most viewed article at the Faculty of 1000 Medicine in September 2009. She received the Outstanding Youth Award from the National Natural Science Foundation of China and was named as one of the most highly cited Chinese scholars by Elsevier.
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