Influence of new-age technologies on marketing: A research agenda
By Vinod Kumar, D. Ramachandran, B. Kumar. 2020
381 citations recorded by the source corpus.
Abstract This study focuses on four key new-age technologies – the Internet of Things, Artificial Intelligence, Machine Learning, and Blockchain – and their respective roles in marketing. Specifically, the study examines each of these four technologies in depth, to understand their key elements, the domains in which they operate, and current use cases pertaining to these technologies. The adoption of these new-age technologies is expected to have an impact on the outcomes for firms and customers. However, these are dynamically evolving technologies that have not yet been completely explored and whose full potential has yet to be uncovered. This study presents some research questions that are pertinent to key entities (firms, customers, intermediaries, developers, and regulators), and which merit deeper investigation in the future. This study also highlights major areas that need managerial focus in the adoption of these new-age technologies.
Subfields: Information Systems, Information Systems and Management, Management Information Systems
View Paper: https://www.semanticscholar.org/paper/d350f4b8c53af00e0f70f35c981a0e90bb7e1302
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In Management Information Systems
Citations in the corpus
- Artificial intelligence in supply chain management: A systematic literature review (2021, neutral): “The world has been moving towards a digital future over the years, and Industry 4.0 technologies are considered to be the way of the future (Kumar et al., 2020).”
- Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics (2020, neutral): “Bitcoin is one of the most popular applications of blockchain that runs on an open ledger (Kumar et al. 2020).”
- Artificial intelligence in marketing: A systematic literature review (2021, background): “Use of AI in developing nations, such as India, and within the gamut of a specific sector, such as healthcare (Kumar & Ramachandran, 2020), and delving deep into the effect and sustainability of experimental AI applications at the overall business level (Jarek & Mazurek, 2019) are more promising…”