How well can ChatGPT manage service failures?
How well can ChatGPT manage service failures?
Barra lateral del artículo
PDF (English)
FLIP
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Contenido principal del artículo
Resumen
Este estudio examina la efectividad de ChatGPT-4o en los procesos de recuperación de fallas de servicio en empresas hoteleras. Los datos del estudio se recopilaron por medio de entrevistas semiestructuradas con empresas hoteleras y clientes. Se crearon dos formularios de entrevista diferentes. El primero fue codificado como Entrevista-1, para empleados y gerentes de empresas hoteleras. El segundo, Entrevista-2, se aplicó a los clientes que hubiesen experimentado al menos un fallo en el servicio en el pasado y que se hayan alojado en el negocio hotelero durante el último año. Se aplicó un muestreo intencional en ambas entrevistas. En el marco de estos criterios, se realizaron entrevistas a nueve empleados de empresas hoteleras (incluidos directivos) y a diecinueve clientes. Los resultados indican que ChatGPT-4o podría ser más efectivo que los recursos humanos en la recuperación de fallas de servicio y que desempeña un papel importante en la mejora de la satisfacción del cliente. Este estudio evalúa el potencial de ChatGPT-4o en los procesos de recuperación de servicios y ofrece soluciones innovadoras para mejorar la calidad del servicio y la satisfacción del cliente en el sector turístico.
Descargas
Detalles del artículo
Referencias (VER)
Akarsu, T. N., Marvi, R., & Foroudi, P. (2023). Service failure research in the hospitality and tourism industry: A synopsis of past, present and future dynamics from 2001 to 2020. International Journal of Contemporary Hospitality Management, 35(1), 186-217. https://doi.org/10.1108/IJCHM-11-2021-1441
Albrecht, A. K., Walsh, G., & Beatty, S. E. (2017). Perceptions of group versus individual service failures and their effects on customer outcomes: The role of attributions and customer entitlement. Journal of Service Research, 20(2), 188-203. https://doi.org/10.1177/1094670516675416
Akdu, U. (2019). Otel işletmelerinde uygulanan hizmet hatası telafi stratejilerinin hizmet kalitesi algısına etkisi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 21(2), 625-646. https://doi.org/10.32709/akusosbil.525109
Ali, F., El-Manstrly, D., & Abbasi, G. A. (2023). Would you forgive me? From perceived justice and complaint handling to customer forgiveness and brand credibility-symmetrical and asymmetrical perspectives. Journal of Business Research, 166, 114138. https://doi.org/10.1016/j.jbusres.2023.114138
Ali, F., & OpenAI, Inc, C. (2023). Let the devil speak for itself: Should ChatGPT be allowed or banned in hospitality and tourism schools? Journal of Global Hospitality and Tourism, 2(1), 1-6. https://www.doi.org/10.5038/2771-5957.2.1.1016
Altun, O., Saydam, M. B., Karatepe, T., & Dima, Ş. M. (2024). Unveiling ChatGPT in tourism education: Exploring perceptions, advantages and recommendations from educators. Worldwide Hospitality and Tourism Themes, 16(1), 105-118. https://doi.org/10.1108/WHATT-01-2024-0018
Augustyn, M. M., & Seakhoa-King, A. (2005). Is the Servqual scale an adequate measure of quality in leisure, tourism and hospitality? In J. S. Chen (Ed.), Advances in hospitality and leisure (Vol. 1, pp. 3-24). Emerald Group Publishing Limited. https://doi.org/10.1016/S1745-3542(04)01001-X
Ayyildiz, T., Ayyildiz, A. Y., & Koc, E. (2024). Illusion of control in service failure situations: Customer satisfaction/dissatisfaction, complaints, and behavioural intentions. Current Psychology, 43(1), 515-530. https://doi.org/10.1007/s12144-023-04292-y
Bae Suk, J., Hwan Chung, S., Choi, K., & Park, J. (2009). The causal relationship on quality-centered organizational culture and its impact on service failure and service recovery. Asian Journal on Quality, 10(1), 37-51. https://doi.org/10.1108/15982680980000626
Bagherzadeh, R., Rawal, M., Wei, S., & Saavedra, J. L. (2020). The journey from customer participation in service failure to co-creation in service recovery. Journal of Retailing and Consumer Services, 54, 102058. https://doi.org/10.1016/j.jretconser.2020.102058
Bambauer-Sachse, S., & Rabeson, L. (2015). Determining adequate tangible compensation in service recovery processes for developed and developing countries: The role of severity and responsibility. Journal of Retailing and Consumer Services, 22, 117-127. https://doi.org/10.1016/j. jretconser.2014.08.001
Bergel, M., & Brock, C. (2018). The impact of switching costs on customer complaint behavior and service recovery evaluation. Journal of Service Theory and Practice, 28(4), 458-483. https://doi. org/10.1108/JSTP-02-2017-0035
Bernard, H. R. (2017). Research methods in anthropology: Qualitative and quantitative approaches (6th ed.). Rowman & Littlefield.
Boshoff, C. (2005). A re-assessment and refinement of RECOVSAT: An instrument to measure satisfaction with transaction-specific service recovery. Managing Service Quality: An International Journal, 15(5), 410-425. https://doi.org/10.1108/09604520510617275
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
Brinkmann, S. (2014). Unstructured and semi-structured interviewing. In P. Leavy (Ed.), The Oxford handbook of qualitative research (pp. 277-299). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199811755.013.030
Carvalho, I., & Ivanov, S. (2024). ChatGPT for tourism: Applications, benefits and risks. Tourism Review, 79(2), 290-303. https://doi.org/10.1108/TR-02-2023-0088
Chen, H.-J. (2024). Assessing the influence of optimism on users’ continuance use intention of ChatGPT: An Expectation-Confirmation Model perspective. International Journal of Management Studies and Social Science Research, 6(1), 347-353. https://doi.org/10.56293/IJMSSSR.2024.4831
Cheng, X., Chen, Y., Wang, P., Zhou, Y., Wei, X., Luo, W., & Duan, Q. (2024). A novel ChatGPT-based multimodel framework for tourism review mining: A case study on China’s five sacred mountains. Journal of Hospitality and Tourism Technology, 15(4), 592-609. https://doi.org/10.1108/JHTT-06-2023-0170
Choi, B., & Choi, B.-J. (2014). The effects of perceived service recovery justice on customer affection, loyalty, and word-of-mouth. European Journal of Marketing, 48(1/2), 108-131. https://doi.org/10.1108/EJM-06-2011-0299
Choi, S., Mattila, A. S., & Bolton, L. E. (2021). To err is human (-oid): How do consumers react to robot service failure and recovery? Journal of Service Research, 24(3), 354-371. https://doi.org/10.1177/1094670520978798
Christensen, J., Hansen, J. M., & Wilson, P. (2025). Understanding the role and impact of Generative Artificial Intelligence (AI) hallucination within consumers’ tourism decision-making processes. Current Issues in Tourism, 28(4), 545-560. https://doi.org/10.1080/13683500.2023.2300032
Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). Sage.
Cropanzano, R., Prehar, C. A., & Chen, P. Y. (2002). Using social exchange theory to distinguish procedural from interactional justice. Group & Organization Management, 27(3), 324-351. https:// doi.org/10.1177/1059601102027003002
Dalgıç, A. (2023). Restoran İşletmelerine Yapılan Olumsuz Yorumları ChatGPT Değerlendirebilir Mi? TripAdvisor’da Bir Uygulama. İşletme Araştırmaları Dergisi, 15(4), 3069-3080. https://doi. org/10.20491/isarder.2023.1766
Dalgıç, A., Yaşar, E., & Demir, M. (2024). ChatGPT and learning outcomes in tourism education: The role of digital literacy and individualized learning. Journal of Hospitality, Leisure, Sport & Tourism Education, 34, 100481. https://doi.org/10.1016/j.jhlste.2024.100481
Davidow, M. (2003). Organizational responses to customer complaints: What works and what doesn’t. Journal of Service Research, 5(3), 225-250. https://doi.org/10.1177/1094670502238917
Demir, M., & Demir, Ş. Ş. (2023a). Is ChatGPT the right technology for service individualization and value co-creation? Evidence from the travel industry. Journal of Travel & Tourism Marketing, 40(5), 383-398. https://doi.org/10.1080/10548408.2023.2255884
Demir, Ş. Ş., & Demir, M. (2023b). Professionals’ perspectives on ChatGPT in the tourism industry: Does it inspire awe or concern? Journal of Tourism Theory and Research, 9(2), 61-77. https://doi. org/10.24288/jttr.1313481
Dwivedi, Y. K., Pandey, N., Currie, W., & Micu, A. (2024). Leveraging ChatGPT and other generative artificial intelligence (AI)-based applications in the hospitality and tourism industry: Practices, challenges and research agenda. International Journal of Contemporary Hospitality Management, 36(1), 1-12. https://doi.org/10.1108/IJCHM-05-2023-0686
Edström, A., Nylander, B., Molin, J., Ahmadi, Z., & Sörqvist, P. (2022). Where service recovery meets its paradox: Implications for avoiding overcompensation. Journal of Service Theory and Practice, 32(7), 1-13. https://doi.org/10.1108/JSTP-06-2021-0120
Elbaz, A. M., Soliman, M., Al-Alawi, A., Al-Romeedy, B. S., & Mekawy, M. (2023). Customer responses to airline companies’ service failure and recovery strategies: The moderating role of service failure habit. Tourism Review, 78(1), 1-17. https://doi.org/10.1108/TR-03-2022-0108
Gursoy, D., Li, Y., & Song, H. (2023). ChatGPT and the hospitality and tourism industry: An overview of current trends and future research directions. Journal of Hospitality Marketing & Management, 32(5), 579-592. https://doi.org/10.1080/19368623.2023.2211993
Heider, F. (2013). The psychology of interpersonal relations. Psychology Press. First edition, 1958.
Ho, T. H., Tojib, D., & Tsarenko, Y. (2020). Human staff vs. service robot vs. fellow customer: Does it matter who helps your customer following a service failure incident? International Journal of Hospitality Management, 87, 102501. https://doi.org/10.1016/j.ijhm.2020.102501
Javaid, M., Haleem, A., & Singh, R. P. (2023). A study on ChatGPT for Industry 4.0: Background, potentials, challenges, and eventualities. Journal of Economy and Technology, 1, 127-143. https://doi.org/10.1016/j.ject.2023.08.001
Johnston, R. (2001). Linking complaint management to profit. International Journal of Service Industry Management, 12(1), 60-69. https://doi.org/10.1108/09564230110382772
Joshi, K. (1990). An investigation of equity as a determinant of user information satisfaction. Decision Sciences, 21(4), 786-807. https://doi.org/10.1111/j.1540-5915.1990.tb01250.x
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., ... Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kim, J. H., Kim, J., Kim, S., & Hailu, T. B. (2024). Effects of AI ChatGPT on travelers’ travel decision-making. Tourism Review, 79(5), 1038-1057. https://doi.org/10.1108/TR-07-2023-0489
Koç, F., Şahin, N. K., & Özbek, V. (2014). Hizmet hataları ve algılanan kalite arasındaki ilişki üzerinde değiştirme maliyetinin düzenleyici etkisi: küçük işletmeler ve hizmet satın aldıkları muhasebecilere yönelik bir uygulama. Pazarlama ve Pazarlama Araştırmaları Dergisi, 7(14), 21-46. https://dergipark.org.tr/tr/pub/ppad/issue/61007/906077
Koc, E. (Ed.). (2017). Service failures and recovery in tourism and hospitality: A practical manual. CABI. https://doi.org/10.1079/9781786390677.0000
Koc, E., Hatipoglu, S., Kivrak, O., Celik, C., & Koc, K. (2023). Houston, we have a problem!: The use of ChatGPT in responding to customer complaints. Technology in Society, 74, 102333. https://doi.org/10.1016/j.techsoc.2023.102333
Kwon, S., & Jang, S. (2012). Effects of compensation for service recovery: From the equity theory perspective. International Journal of Hospitality Management, 31(4), 1235-1243. https://doi.org/10.1016/j.ijhm.2012.03.002
Lee, W. J., Kwag, S. I., & Ko, Y. D. (2020). Optimal capacity and operation design of a robot logistics system for the hotel industry. Tourism Management, 76, 103971. https://doi.org/10.1016/j.tourman.2019.103971
Lv, X., Yang, Y., Qin, D., Cao, X., & Xu, H. (2022). Artificial intelligence service recovery: The role of empathic response in hospitality customers’ continuous usage intention. Computers in Human Behavior, 126, 106993. https://doi.org/10.1016/j.chb.2021.106993
Madgavkar, A., Manyika, J., Krishnan, M., Ellingrud, K., Yee, L., Woetzel, L., Chui, M., Hunt, D. V., & Balakrishnan, S. (2019). The future of women at work: Transitions in the age of automation. McKinsey Global Institute. https://www.mckinsey.com/featured-insights/gender-equality/ the-future-of-women-at-work-transitions-in-the-age-of-automation
Marshall, M. N. (1996). Sampling for qualitative research. Family Practice, 13(6), 522-526. https://doi.org/10.1093/fampra/13.6.522
Maxham III, J. G., & Netemeyer, R. G. (2002). Modeling customer perceptions of complaint handling over time: The effects of perceived justice on satisfaction and intent. Journal of Retailing, 78(4), 239-252. https://doi.org/10.1016/S0022-4359(02)00100-8
Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Sage.
Olcay, A., Özekici, Y. K. (2015). Yiyecek-İçecek İşletmelerinde Hizmet Hataları, Telafi Yön-temleri ve Müşteri Memnuniyeti İlişkisi (Gaziantep Örneği). Uluslararası Sosyal Araştırmalar Dergisi, 8(41), 1254-1268. http://sosyalarastirmalar.net/cilt8/sayi41_pdf/6iksisat_kamu_isletme/olcay_atinc_yakupkemalozekici.pdf
Olson, E. D., & Ro, H. (2020). Company response to negative online reviews: The effects of procedural justice, interactional justice, and social presence. Cornell Hospitality Quarterly, 61(3), 312-331. https://doi.org/10.1177/1938965519892902
Othman, Z., Zahari, MS M., & Radzi, SM. (2013). Customer behavioral intention: Influence of service delivery failures and service recovery in Malay restaurants. Procedia-Social and Behavioral Sciences, 105, 115-121. https://doi.org/10.1016/j.sbspro.2013.11.013
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service qual-ity and its implications for future research. Journal of Marketing, 49(4), 41-50. https://doi.org/10.1177/002224298504900403
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40. https://www.marketeurexpert.fr/wp-content/uploads/2023/12/servqual.pdf
Park, J., & Jeong, E. (2019). Service quality in tourism: A systematic literature review and keyword network analysis. Sustainability, 11(13), 3665. https://doi.org/10.3390/su11133665
Park, J.-J., & Park, J.-W. (2016). Investigating the effects of service recovery quality elements on passengers’ behavioral intention. Journal of Air Transport Management, 53, 235-241. https://doi.org/10.1016/j.jairtraman.2016.03.003
Pham, H. C., Duong, C. D., & Nguyen, G. K. H. (2024). What drives tourists’ continuance intention to use ChatGPT for travel services? A stimulus-organism-response perspective. Journal of Retailing and Consumer Services, 78, 103758. https://doi.org/10.1016/j.jretconser.2024.103758
Puri, G., & Singh, K. (2018). The role of service quality and customer satisfaction in tourism industry: A review of SERVQUAL Model. International Journal of Research and Analytical Reviews, 5(4). 745-751. https://ssrn.com/abstract=3846760
Shams, G., Rather, R., Abdur Rehman, M., & Lodhi, R. N. (2021). Hospitality-based service recovery, outcome favourability, satisfaction with service recovery and consequent customer loyalty: An empirical analysis. International Journal of Culture, Tourism and Hospitality Research, 15(2), 266-284. https://doi.org/10.1108/IJCTHR-04-2020-0079
Shan, M., Zhu, Z., Chen, H., & Sun, S. (2024). Service robot’s responses in service recovery and service evaluation: The moderating role of robots’ social perception. Journal of Hospitality Marketing & Management, 33(2), 145-168. https://doi.org/10.1080/19368623.2023.2246456
Shi, J., Lee, M., Girish, V. G., Xiao, G., & Lee, C.-K. (2024). Embracing the ChatGPT revolution: Unlocking new horizons for tourism. Journal of Hospitality and Tourism Technology, 15(3), 433- 448. https://doi.org/10.1108/JHTT-07-2023-0203
Shin, H., & Kang, J. (2023). Bridging the gap of bibliometric analysis: The evolution, current state, and future directions of tourism research using ChatGPT. Journal of Hospitality and Tourism Management, 57, 40-47. https://doi.org/10.1016/j.jhtm.2023.09.001
Truong, N. T., Dang-Pham, D., McClelland, R. J., & Nkhoma, M. (2020). Service innovation, customer satisfaction and behavioural intentions: A conceptual framework. Journal of Hospitality and Tourism Technology, 11(3), 529-542. https://doi.org/10.1108/JHTT-02-2019-0030
Van Vaerenbergh, Y., Varga, D., De Keyser, A., & Orsingher, C. (2019). The service recovery journey: Conceptualization, integration, and directions for future research. Journal of Service Research, 22(2), 103-119. https://doi.org/10.1177/1094670518819852
Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world: Service robots in the frontline. Journal of Service Management, 29(5), 907-931. https://doi.org/10.1108/JOSM-04-2018-0119
Xie, Y., & Peng, S. (2009). How to repair customer trust after negative publicity: The roles of competence, integrity, benevolence, and forgiveness. Psychology & Marketing, 26(7), 572-589. https://doi.org/10.1002/mar.20289
Xing, X., Song, M., Duan, Y., & Mou, J. (2022). Effects of different service failure types and recovery strategies on the consumer response mechanism of chatbots. Technology in Society, 70, 102049. https://doi.org/10.1016/j.techsoc.2022.102049
Xu, X., & Liu, J. (2022). Artificial intelligence humor in service recovery. Annals of Tourism Research, 95, 103439. https://doi.org/10.1016/j.annals.2022.103439
Yadav, A., & Dhar, R. L. (2021). Linking frontline hotel employees’ job crafting to service recovery performance: The roles of harmonious passion, promotion focus, hotel work experience, and gender. Journal of Hospitality and Tourism Management, 47, 485-495. https://doi.org/10.1016/j. jhtm.2021.04.018
Yang, W., & Mattila, A. S. (2012). The role of tie strength on consumer dissatisfaction responses. International Journal of Hospitality Management, 31(2), 399-404. https://doi.org/10.1016/j. ijhm.2011.06.015
Yang, Z., Zhou, J., & Yang, H. (2023). The impact of AI’s response method on service recovery satisfaction in the context of service failure. Sustainability, 15(4), 3294. https://doi.org/10.3390/ su15043294
Zhang, Y., & Prebensen, N. K. (2024). Co-creating with ChatGPT for tourism marketing materials. Annals of Tourism Research Empirical Insights, 5(1), 100124. https://doi.org/10.1016/j. annale.2024.100124
Citado por
