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Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis

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  • Pantano, Eleonora
  • Pizzi, Gabriele

Abstract

The main goal of this research is to provide a comprehensive understanding of the actual progresses in artificial intelligence, with emphasis on chatbots as emerging forms of customer assistance in online retailing. Drawing upon an analysis of the chatbot patents in the past 20 years, our findings show the increasing technology push towards the adoption of new conversational agents based on natural language. Findings also highlight the extent to which the research and development efforts are attempting to improve artificial intelligence systems that characterize chatbots. To this end, technology advancements are mainly focusing on: (i) improving chatbot ability to automatically draw inferences on users starting from multiple data sources, and (ii) using consumers’ knowledge adaptively to provide more customized solutions. Finally, results show the tight relationship between the digital assistants’ analytical skills and their ability to automatically interact with the users.

Suggested Citation

  • Pantano, Eleonora & Pizzi, Gabriele, 2020. "Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    • Handle: RePEc:eee:joreco:v:55:y:2020:i:c:s0969698919311865
    DOI: 10.1016/j.jretconser.2020.102096
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    1. Ashlee Humphreys & Rebecca Jen-Hui Wang & Eileen FischerEditor & Linda PriceAssociate Editor, 2018. "Automated Text Analysis for Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(6), pages 1274-1306.
    2. Grewal, Dhruv & Roggeveen, Anne L. & Nordfält, Jens, 2017. "The Future of Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 1-6.
    3. Ming-Hui Huang & Roland T. Rust, 2017. "Technology-driven service strategy," Journal of the Academy of Marketing Science, Springer, vol. 45(6), pages 906-924, November.
    4. Elena Belavina & Karan Girotra & Ashish Kabra, 2017. "Online Grocery Retail: Revenue Models and Environmental Impact," Management Science, INFORMS, vol. 63(6), pages 1781-1799, June.
    5. Läpple, Doris & Renwick, Alan & Thorne, Fiona, 2015. "Measuring and understanding the drivers of agricultural innovation: Evidence from Ireland," Food Policy, Elsevier, vol. 51(C), pages 1-8.
    6. Arnaud De Bruyn & John C. Liechty & Eelko K. R. E. Huizingh & Gary L. Lilien, 2008. "Offering Online Recommendations with Minimum Customer Input Through Conjoint-Based Decision Aids," Marketing Science, INFORMS, vol. 27(3), pages 443-460, 05-06.
    7. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Stylos, Nikolaos, 2018. "Knowledge Push Curve (KPC) in retailing: Evidence from patented innovations analysis affecting retailers' competitiveness," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 150-160.
    8. Roland T. Rust & Ming-Hui Huang, 2014. "The Service Revolution and the Transformation of Marketing Science," Marketing Science, INFORMS, vol. 33(2), pages 206-221, March.
    9. Keeling, Kathleen & McGoldrick, Peter & Beatty, Susan, 2010. "Avatars as salespeople: Communication style, trust, and intentions," Journal of Business Research, Elsevier, vol. 63(8), pages 793-800, August.
    10. Yavuz A. Bozer & Francisco J. Aldarondo, 2018. "A simulation-based comparison of two goods-to-person order picking systems in an online retail setting," International Journal of Production Research, Taylor & Francis Journals, vol. 56(11), pages 3838-3858, June.
    11. Quentin André & Ziv Carmon & Klaus Wertenbroch & Alia Crum & Douglas Frank & William Goldstein & Joel Huber & Leaf Boven & Bernd Weber & Haiyang Yang, 2018. "Consumer Choice and Autonomy in the Age of Artificial Intelligence and Big Data," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 28-37, March.
    12. Xueming Luo & Siliang Tong & Zheng Fang & Zhe Qu, 2019. "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases," Marketing Science, INFORMS, vol. 38(6), pages 937-947, November.
    13. Larivière, Bart & Bowen, David & Andreassen, Tor W. & Kunz, Werner & Sirianni, Nancy J. & Voss, Chris & Wünderlich, Nancy V. & De Keyser, Arne, 2017. "“Service Encounter 2.0”: An investigation into the roles of technology, employees and customers," Journal of Business Research, Elsevier, vol. 79(C), pages 238-246.
    14. Khalid Aldiri & Dave Hobbs & Rami Qahwaji, 2008. "The Human Face of E-Business: Engendering Consumer Initial Trust Through the Use of Images of Sales Personnel on E-Commerce Web Sites," International Journal of E-Business Research (IJEBR), IGI Global, vol. 4(4), pages 58-78, October.
    15. Chang, Shann-Bin, 2012. "Using patent analysis to establish technological position: Two different strategic approaches," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 3-15.
    16. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    17. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Sorace, Stefano & Iazzolino, Gianpaolo, 2017. "Does innovation-orientation lead to retail industry growth? Empirical evidence from patent analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 88-94.
    18. Zoubin Ghahramani, 2015. "Probabilistic machine learning and artificial intelligence," Nature, Nature, vol. 521(7553), pages 452-459, May.
    19. Murray, Kyle B. & Häubl, Gerald, 2009. "Personalization without Interrogation: Towards more Effective Interactions between Consumers and Feature-Based Recommendation Agents," Journal of Interactive Marketing, Elsevier, vol. 23(2), pages 138-146.
    20. Willems, Kim & Smolders, Annelien & Brengman, Malaika & Luyten, Kris & Schöning, Johannes, 2017. "The path-to-purchase is paved with digital opportunities: An inventory of shopper-oriented retail technologies," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 228-242.
    21. Kim, Gabjo & Bae, Jinwoo, 2017. "A novel approach to forecast promising technology through patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 228-237.
    22. Yoo, Weon-Sang & Lee, Yunjung & Park, JungKun, 2010. "The role of interactivity in e-tailing: Creating value and increasing satisfaction," Journal of Retailing and Consumer Services, Elsevier, vol. 17(2), pages 89-96.
    23. Park, Yongtae & Yoon, Byungun & Lee, Sungjoo, 2005. "The idiosyncrasy and dynamism of technological innovation across industries: patent citation analysis," Technology in Society, Elsevier, vol. 27(4), pages 471-485.
    24. Nelson, Andrew & Earle, Andrew & Howard-Grenville, Jennifer & Haack, Julie & Young, Doug, 2014. "Do innovation measures actually measure innovation? Obliteration, symbolic adoption, and other finicky challenges in tracking innovation diffusion," Research Policy, Elsevier, vol. 43(6), pages 927-940.
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