Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis |
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| Affiliation: | 1. Department of Communication Sciences, University of Antwerp, Antwerp, Belgium;2. Wunderman Thompson, Antwerp, Belgium;3. Amsterdam School of Communication Research (ASCoR), University of Amsterdam, Netherlands;1. Università IULM, Italy;2. Huddersfield Business School, United Kingdom;1. University of San Diego School of Business, 5998 Alcalá Park, San Diego, CA 92110, USA;2. College of Business, Colorado State University, 1201 Campus Delivery, Fort Collins, CO 80523, USA;3. Meredith College School of Business, 3800 Hillsborough Street, Raleigh, NC 27607, USA;1. School of Business and Management, Shanghai International Studies University, 550 Dalian Road (W), Shanghai, 200083, China;2. School of Management, Shanghai University of International Business and Economics, 1900 Wenxiang Road, Shanghai, 201620, China;3. College of Economics and Management, Southwest University, 2 Tiansheng Road, Chongqing, 400715, China;1. School of Engineering and Applied Science, The George Washington University, 800 22nd St. NW, Washington, D.C. 20052, USA;2. Data Analytics Program, Graduate School, 3501 University Boulevard East, University of Maryland University College, Adelphi, MD 20783, USA;3. Psychology Dept., Hood College, 401 Rosemont Ave., Frederick, MD 21701, USA |
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| 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. |
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| Keywords: | Online customer assistance Artificial intelligence (AI) Chatbot Patent analysis Online retailing Conversational agents |
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