References for Theme: AI in Service Industries
- Belk, Russell
- Gittleman, Maury; Monaco, Kristen
- "Truck-Driving Jobs: Are They Headed for Rapid Elimination?" (2020)
(p.22) Fears that new technology will lead to massive unemployment are not new, though many researchers contend that this time the outcome will differ because of the potentially powerful effects of computers, robots, and otherdigital technologies. While we have not tried to address the question of what will happen to employment in the economy as a whole, we have examined an important occupation, and one in which employment levels many predict will be hit hard in the not-too-distant future by technologies that were difficult to foresee as recently as a decade or two ago. Our case study of truck drivers suggests, however, that, at least for now,...
- "Truck-Driving Jobs: Are They Headed for Rapid Elimination?" (2020)
- Huang, Ming-Hui; Rust, Roland T
- Li, Minglong; Yin, Dexiang; Qiu, Hailian; Bai, Billy
- Libai, Barak; Bart, Yakov; Gensler, Sonja; Hofacker, Charles F; Kaplan, Andreas; Kötterheinrich, Kim; Kroll, Eike Benjamin
- "Brave New World? On AI and the Management of Customer Relationships" (2020)
(p.4) AI-CRM [Artificially Intelligent, Customer Relationship Management] capabilities do not need to achieve full human empathy to complement or even replace human CRM judgment. Consider employees of advertising agencies as an illustration. Whether these are the mass-market advertising specialists who come up with ad execution, high-performance sales personnel who close the deal, or direct marketing copywriters whose words jump off the screen, the ability to tell a brand's story or write compelling copy has thus far been restricted to humans. There is reason to believe that this human monopoly on creative marketing capabilities has ended or will shortly end.
- "Brave New World? On AI and the Management of Customer Relationships" (2020)
- Luo, Xueming; Tong, Siliang; Fang, Zheng; Qu, Zhe
- "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases" (2019)
(p.938) Our data suggest that undisclosed chatbots that incur almost zero marginal costs can outperform the paid underdogs by five times in purchase rates. These findings imply that the potential replacement of underperforming human workers by AI chatbots and other new automation technologies is an inevitable trend.
- "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases" (2019)
(p.945) This research examines AI chatbots, a timely and managerially relevant topic. On the basis of a six-condition field experiment, it finds that the disclosure of chatbot machine identity reduces purchase rates substantially. Further analyses reveal that customers tend to purchase less and even terminate the calls early because they perceive the disclosed chatbot as less knowledgeable and empathetic.
- "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases" (2019)
- "Machines versus Humans: The Impact of AI Chatbot Disclosure on Customer Purchases" (2019)
- Medina-Borja, Alexandra
- Nhat, Lu Vinh; Wirtz, Jochen; Kunz, Werner H; Paluch, Stefanie; Gruber, Thorsten; Martins, Antje; Patterson, Paul G
- "Service robots, customers and service employees: what can we learn from the academic literature and where are the gaps?" (2020)
(p.2) According to the Service Robot Deployment model (Paluch et al., 2020; Wirtz et al., 2018), service robots will be able to deliver service tasks with almost any degree of cognitive complexity and virtually all tasks with low emotional/social complexity. However, service tasks high in emotional/social complexity will largely have to be delivered by frontline employees as service robots will not be able to engage in deep emotional acting and will not have agency for the foreseeable future. Finally, tasks high in cognitive and emotional complexity are expected to be delivered by humans supported by robots (Wirtz et al., 2018).
- "Service robots, customers and service employees: what can we learn from the academic literature and where are the gaps?" (2020)
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