Joining forces for online feedback management: policy recommendations for human–AI collaboration
Online customer feedback management (CFM) is becoming increasingly important for businesses. Providing timely and effective responses to guest reviews can be challenging, especially as the volume of reviews grows. This paper explores the response process and the potential for artificial intelligence...
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2025-01-01
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| Series: | Data & Policy |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S2632324925000136/type/journal_article |
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| author | Dzmitry Katsiuba Mateusz Dolata Gerhard Schwabe |
| author_facet | Dzmitry Katsiuba Mateusz Dolata Gerhard Schwabe |
| author_sort | Dzmitry Katsiuba |
| collection | DOAJ |
| description | Online customer feedback management (CFM) is becoming increasingly important for businesses. Providing timely and effective responses to guest reviews can be challenging, especially as the volume of reviews grows. This paper explores the response process and the potential for artificial intelligence (AI) augmentation in response formulation. We propose an orchestration concept for human–AI collaboration in co-writing within the hospitality industry, supported by a novel NLP-based solution that combines the strengths of both human and AI. Although complete automation of the response process remains out of reach, our findings offer practical implications for improving response speed and quality through human–AI collaboration. Additionally, we formulate policy recommendations for businesses and regulators in CFM. Our study provides transferable design knowledge for developing future CFM products. |
| format | Article |
| id | doaj-art-3d02f5823f5a4efc936fcf56e002a450 |
| institution | OA Journals |
| issn | 2632-3249 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Data & Policy |
| spelling | doaj-art-3d02f5823f5a4efc936fcf56e002a4502025-08-20T02:08:12ZengCambridge University PressData & Policy2632-32492025-01-01710.1017/dap.2025.13Joining forces for online feedback management: policy recommendations for human–AI collaborationDzmitry Katsiuba0https://orcid.org/0000-0002-4341-5738Mateusz Dolata1Gerhard Schwabe2https://orcid.org/0000-0002-0453-9762Department of Informatics, University of Zurich, Zurich, SwitzerlandDepartment of Informatics, University of Zurich, Zurich, Switzerland Department of Political and Social Sciences, Zeppelin University, Friedrichshafen, GermanyDepartment of Informatics, University of Zurich, Zurich, SwitzerlandOnline customer feedback management (CFM) is becoming increasingly important for businesses. Providing timely and effective responses to guest reviews can be challenging, especially as the volume of reviews grows. This paper explores the response process and the potential for artificial intelligence (AI) augmentation in response formulation. We propose an orchestration concept for human–AI collaboration in co-writing within the hospitality industry, supported by a novel NLP-based solution that combines the strengths of both human and AI. Although complete automation of the response process remains out of reach, our findings offer practical implications for improving response speed and quality through human–AI collaboration. Additionally, we formulate policy recommendations for businesses and regulators in CFM. Our study provides transferable design knowledge for developing future CFM products.https://www.cambridge.org/core/product/identifier/S2632324925000136/type/journal_articleartificial intelligencehuman–AI collaborationmanagerial responseonline customer feedback management |
| spellingShingle | Dzmitry Katsiuba Mateusz Dolata Gerhard Schwabe Joining forces for online feedback management: policy recommendations for human–AI collaboration Data & Policy artificial intelligence human–AI collaboration managerial response online customer feedback management |
| title | Joining forces for online feedback management: policy recommendations for human–AI collaboration |
| title_full | Joining forces for online feedback management: policy recommendations for human–AI collaboration |
| title_fullStr | Joining forces for online feedback management: policy recommendations for human–AI collaboration |
| title_full_unstemmed | Joining forces for online feedback management: policy recommendations for human–AI collaboration |
| title_short | Joining forces for online feedback management: policy recommendations for human–AI collaboration |
| title_sort | joining forces for online feedback management policy recommendations for human ai collaboration |
| topic | artificial intelligence human–AI collaboration managerial response online customer feedback management |
| url | https://www.cambridge.org/core/product/identifier/S2632324925000136/type/journal_article |
| work_keys_str_mv | AT dzmitrykatsiuba joiningforcesforonlinefeedbackmanagementpolicyrecommendationsforhumanaicollaboration AT mateuszdolata joiningforcesforonlinefeedbackmanagementpolicyrecommendationsforhumanaicollaboration AT gerhardschwabe joiningforcesforonlinefeedbackmanagementpolicyrecommendationsforhumanaicollaboration |