JBRMR 2056-6271 https://doi.org/10.24052/JBRMR/ 58 Volume 20 Issue 02 2026-04-01

607 https://jbrmr.com/details&cid=607 2026-03-30 This study investigates the impact of heat waves on the redistribution of international tourist flows to sun and beach destinations in Spain, focusing on behavioural changes in travel planning and destination choice. The research aims to assess how extreme weather events, particularly heat waves, influence tourists’ decisions, with implications for the resilience and competitiveness of coastal tourism. A quantitative methodology was employed, using Structural Equation Modelling (SEM), to analyse causal relationships among four latent variables: country of origin, tourist destination, type of accommodation, and number of overnight stays. The model was applied to two chronological periods—July 2022 (with a heat wave) and July 2023 (without)—using data from the FRONTUR survey National Statistics Institute (NSI) and climatic records from State Meteorological Agency (SMA). The sample comprised 6,556 international tourists from the UK, France, Germany, and the Netherlands. Findings reveal that heat waves significantly influence destination choice and reduce overnight stays, particularly in insular regions such as the Balearic Islands. Tourists from the UK showed a marked decline in travel during heat waves, indicating a shift towards cooler destinations. However, heat waves did not significantly affect the type of accommodation hired. The study confirms that climatic discomfort leads to shorter stays and altered travel behaviour, supporting the emergence of “coolcations” as a growing trend. Practical implications include the need for sun-and-beach destinations to implement climate adaptation strategies to remain competitive. Enhancing accommodation services and promoting thermal comfort can mitigate the negative effects of extreme temperatures. In conclusion, heat waves are a critical factor in shaping tourist behaviour and demand patterns. Their inclusion in predictive models offers valuable insights for tourism planning and policy, especially in the context of climate change. Adongo, C.A., Kim, S.B. & Elliott, S. (2017) ‘The moderating role of perceived risk on the relationship between destination image and behavioural intentions of tourists‘, Tourism Management, 64, pp. 119–129. Available at: https://doi.org/10.1016/j.tourman.2017.02.012 Amengual, A., Homar, V., Romero, R., Alonso, S. & Ramis, C. (2014) ´Projections of heat waves with the regional climate model RegCM4 in Europe´, Climate Change, 125(3–4), pp. 569–583. Available at:  https://doi.org/10.1007/s00382-013-1961-2 Arabadzhyan, A., Figini, P., Garcia, J.R., Lam-González, Y. & Leon, C.J. (2020) ´Climate change, coastal tourism, and impact chains – A literature review´, Current Issues in Tourism, 23(13), pp. 1567–1583. Available at: https://doi.org/10.1080/13683500.2020.1825351 Becken, S. & Wilson, J., (2013) ´Weather, climate and tourism: A geographical perspective´. Journal of Tourism Studies, 24(2), pp. 1–15. Available at: https://doi.org/10.1080/14616688.2012.762541 Buckley, R. (2008) ´Climate response tourism: A new paradigm for global tourism´, Tourism Recreation Research, 33(3), pp. 35–40. Available at: https://doi.org/10.1080/02508281.2008.11081550 Bujosa, A. & Roselló, J. (2011) ´Modelling tourism demand dynamics´, Tourism Economics, 17(2), pp. 283–298. Available at: https://doi.org/10.1007/s10584-010-9895-4 Caldeira, A.M. & Kastenholz, E. (2018) ´Tourists’ perceptions of climate change and its impact on destination choice´, Journal of Sustainable Tourism, 26(5), pp. 805–825. Available at: https://doi.org/10.1080/1743873X.2017.1302571 Caravallo, M., González, M. & Pérez, J. (2017) ´Weather and tourism: A study of the impact of climate on tourist activities´, Tourism Analysis, 22(3), pp. 345–357. Available at: https://doi.org/10.1016/j.enpol.2017.08.007 Cheah, J.H., Sarstedt, M., Ringle, C.M., Ringle, T. & Ramayah, T. (2019) ´Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict`, European Journal of Marketing, 53(11), pp. 2322–2347. Available at:  https://doi.org/10.1108/ejm-02-2019-0189  Cohen, J. (1988) ´Statistical power analysis for the behavioral sciences. 2nd ed´. Hillsdale, NJ: Lawrence Erlbaum Associates. Copernicus Climate Change Service (2019) ´European State of the Climate 2019´. https://climate.copernicus.eu [Accessed 31 Oct. 2025]. Copernicus Climate Change Service (2021) ´European State of the Climate 2021´. https://climate.copernicus.eu [Accessed 31 Oct. 2025]. Corral Orgaz, M. (2021) ´FRONTUR: Cross‑Border Tourism Flow Survey. Day, J., Chin, N., Sydnor, S. & Melendez, M. (2013) ´Weather, climate and tourism performance: A quantitative analysis´, Tourism Management Perspectives, 5, pp. 51–56. Available at:  https://doi.org/10.1016/j.tmp.2012.11.001  De Almeida, A. & Machado, M. (2019) ´Extreme weather events and tourism: Impacts and adaptation strategies`, Journal of Tourism Futures, 5(2), pp. 123–135. Available at:  https://doi.org/10.1108/JTF-12-2018-0084 Domínguez, T., Araújo, N., De la Cruz, Y. & Peña, A. (2017) ´Tourist behaviour and climate change: A structural equation modelling approach´. Journal of Tourism Research, 25(1), pp. 45–60. Dubois, G., Ceron, J.P., Gössling, S. & Hall, C.M. (2016) ´Weather preferences and implications for climate change impacts on demand´, Climate Change, 136(2), pp. 201–214. Efron, B. & Tibshirani, R.J., (1993) An introduction to the bootstrap. New York: Chapman & Hall. European Commission, Joint Research Centre (2023) ´Climate change impacts on European tourism´. Brussels: European Commission. Eusebio, C. & Vieira, A.L. (2011) ´Destination attributes’ evaluation, satisfaction and behavioural intentions: A structural modelling approach´, International Journal of Tourism Research, 13(1), pp. 66–80. Available at: https://doi.org/10.1002/jtr.877  Fitchett, J.M., Hoogendoorn, G. & Swemmer, L. (2017) ´Climate change and tourism: Impacts and adaptation in South Africa. African Journal of Hospitality´, Tourism and Leisure, 6(1), pp. 1–15. Gabarda-Mallorquí, A. (2016) ´Water scarcity and tourism: A Mediterranean perspective´, Journal of Sustainable Tourism, 24(3), pp. 345–360. Gómez Royuela, C. (2016) ´Adaptation strategies for coastal tourism in Spain´. Tourism Review, 71(2), pp. 123–135. Gómez-Martín, M.B., Martínez-Ibarra, E. & Olcina, J. (2014) ´Weather and tourism: A study of the impact of climate on tourist activities in Spain´, Tourism Geographies, 16(3), pp. 433–452. Gössling, S., Bredberg, M., Randow, A., Sandström, E. & Svensson, P. (2006) ´Tourists’ perceptions of climate change: A study of international travellers´, Climate Research, 32(1), pp. 1–12. Gössling, S., Hall, C.M. & Scott, D. (2012) ´Tourism and climate change: Impacts, adaptation and mitigation´. London: Routledge. Hair, J.F., Hult, G.T.M., Ringle, C.M. & Sarstedt, M. (2017) ´A primer on partial least squares structural equation modeling (PLS-SEM)´. 2nd ed. Thousand Oaks, CA: Sage. Hair, J.F., Risher, J.J., Sarstedt, M. & Ringle, C.M. (2019) ´When to use and how to report the results of PLS-SEM´, European Business Review, 31(1), pp. 2–24. Available at:  https://doi.org/10.1108/ebr-11-2018-0203  Hamilton, J.M., Maddison, D.J. & Tol, R.S.J. (2005) ´Climate change and international tourism: A simulation study´, Global Environmental Change, 15(3), pp. 265–280. Available at: https://doi.org/10.1016/j.gloenvcha.2004.12.009  Han, H., Yu, J. & Kim, W. (2018) ´Environmental risk perception and behavioural intention in tourism´, Journal of Travel Research, 57(8), pp. 1041–1056. Henlein, M. & Kaplan, D, (2004) ´Structural equation modelling in tourism research´, Journal of Travel Research, 43(1), pp. 1–14. Henseler, J., Ringle, C.M. & Sinkovics, R.R. (2009) ´The use of partial least squares path modelling in international marketing´, Advances in International Marketing, 20, pp. 277–319. Henseler, J. (2018) ´Partial least squares path modelling: Quo vadis?´ Journal of Market Research, 20(3), pp. 1–21. Available at: https://doi.org/10.1007/s11135-018-0689-6  Hsu, F.C. & Sharma, A. (2023) ´Heatwaves and tourism: Impacts on travel behaviour and destination choice´, Journal of Sustainable Tourism, 31(5), pp. 789–805. Humagain, P.; Singleton, P. A. (2021) ´Examining relationships between COVID-19 destination practices, value, satisfaction and behavioral intentions for tourists' outdoor recreation trips´, Journal of Destination Marketing & Management, (22), 100665. https://doi.org/10.1016/j.jdmm.2021.100665 Jeuring, J. & Becken, S. (2013) ´Tourists and severe weather: A review of literature´, Tourism Management Perspectives, 8, pp. 73–85. Available at: https://doi.org/10.1016/j.tourman.2013.02.004  Jeuring, J. & Haartsen, T. (2017) ´Weather perceptions and holiday satisfaction´, Tourism Management, 61, pp. 70–81. Available at:  https://doi.org/10.1016/j.tourman.2017.01.018  Jiménez, M., López, A., & Sánchez, R. (2022) ´Holiday rentals and tourist behaviour in Spain´, International Journal of Hospitality Management, 102, p.103123. Jöreskog, K.G., & Wold, H.O. (1982) ´Systems under Indirect Observation: Causality, Structure´.Prediction. North Holland. Kock, N. (2019) ´WarpPLS 8.0 User Manual´. Laredo, TX: ScriptWarp Systems. Lam-González, Y., León, C.J. & Araña, J.E. (2020) ´Climate change and tourism: A review of the literature´, Tourism Economics, 26(3), pp. 453–472. Available at: https://doi.org/10.20867/thm.21.1.7  León, C.J., Araña, J.E., & Lam-González, Y. (2021) ´Tourism demand and climate change: A meta-analysis´, Journal of Travel Research, 60(5), pp. 1045–1062. Available at: https://doi.org/10.1080/09669582.2024.2354882  Lohmoller, J.B. (1989) ´Latent variable path modelling with partial least squares´. Heidelberg: Physica-Verlag. Lorenzo, M.N. & Álvarez, I. (2022) ´Extreme temperatures in Spain: Trends and projections´, Climate Research, 82(1), pp. 1–12. Marriott Bonvoy (2024) ´Travel trends report: Coolcations and climate-conscious tourism´. https://www.marriott.com [Accessed 31 Oct. 2025]. Matzarakis, A., de Freitas, C.R. & Scott, D. (2013) ´Advances in tourism climatology´. Freiburg: Berichte des Meteorologischen Instituts der Universität Freiburg. MedECC (2020) ´Climate and environmental change in the Mediterranean basin – Current situation and risks for the future´. Marseille: Union for the Mediterranean. Millán, M. (2023) ´Tourism flows and climate preferences in Europe`, Journal of Travel and Tourism Marketing, 40(2), pp. 123–139. Miró, J. & Olcina, J. (2021) ´Thermal comfort and tourism in Spain´, Tourism Review, 76(3), pp. 456–470. Available at: https://doi.org/10.5937/simterm24464m  Moreno, A. & Amelung, B. (2009) ´Climate change and tourist comfort in Europe´, Climate Research, 42(1), pp. 1–15. Available at: https://doi.org/10.1080/08920750903054997  Moreno, A., Becken, S. & Uyarra, M.C. (2008) `Tourism and climate change: Impacts and adaptation´, Journal of Sustainable Tourism, 16(6), pp. 591–611. National Geographic Institute. Available online: https://www.ign.es/web/ign/portal/obs-area-observacionterritorio [Accessed 25 Apr. 2024]. National Statistics Institute (2016) ´FRONTUR: Survey methodology´. Madrid: National Statistics Institute. https://www.ine.es National Statistics Institute (2023) ´Tourism statistics: Contribution to GDP´. Madrid: National Statistics Institute. https://www.ine.es Olcina, J. & Miró, J. (2017) ´Climate change and tourism in Spain: Risks and adaptation´, Boletín de la Asociación de Geógrafos Españoles, 75, pp. 1–25. Olcina, J., Miró, J. & Vera-Rebollo, F. (2019) ´Heatwaves and tourism: Impacts and adaptation strategies´, Cuadernos de Turismo, 44, pp. 123–145. Olcina, J. & Vera-Rebollo, F. (2016) ´Climate change adaptation in Spanish coastal tourism´, Journal of Coastal Research, 32(5), pp. 1101–1110. Paredes-Fortuny, X. & Khodayar, S. (2023) ´Heatwaves in Southern Europe: Trends and impacts´, Atmospheric Research, 280, p.106456. Perkins, S.E. & Alexander, L.V. (2013) ´On the definition of heatwaves´, Journal of Climate, 26(13), pp. 4500–4517. Raithel, S., Sarstedt, M., Schwaiger, M. & Ringle, C.M. (2012) ´Market share and customer satisfaction: A PLS path modelling approach´, Journal of Strategic Marketing, 20(4), pp. 307–317. Rogers, R. W. A. (1975) ´Protection motivation theory of fear appeals and attitude change´, The Journal of Psychology (91), pp. 93–114. Roson, R. & Sartori, M. (2014) ´Climate change and tourism: An economic analysis´. Journal of Sustainable Tourism, 22(5), pp. 683–703. Rosselló-Nadal, J., Riera-Font, A. & Cárdenas, V. (2011) ´Climate change and tourism: The impact of weather on tourist demand in Mediterranean destinations´, Climatic Change, 107(1–2), pp. 119–130. Sánchez-Sánchez-Sánchez, M.D., De-Pablos-Heredero, C. & Montes-Botella, J.L. (2024) ´Direct and moderating effects of COVID-19 on cultural tourist satisfaction´. European Research on Management and Business Economics, 30, 100238. Available at: https://doi.org/10.1016/j.iedeen.2023.100238 State Meteorological Agency (2022). Available online: https://www.aemet.es [Accessed 31 Oct. 2024]. State Meteorological Agency (2023) ´Report on the July 2022 Heatwave´. Available online: https://www.aemet.es [Accessed 31 Oct. 2024]. Travel Nast (2024) ´Coolcations: The rise of climate-conscious travel´. https://www.travelnast.com [Accessed 31 Oct. 2025]. Tuel, A. & Eltahir, E.A.B. (2020). ´Why is the Mediterranean a climate change hotspot?´, Journal of Climate, 33(14), pp. 5829–5843. Available at: https://doi.org/10.21203/rs.3.rs-97522/v1  Wenjia, Z., Li, Y.& Zhang, H. (2020) ´Protection motivation theory and tourism: A review and future research agenda´, Journal of Travel Research, 59(5), pp. 882–899. Wilkins, H., Hall, C.M. & Harrill, R. (2018) ´Weather and tourism: A review of the literature´, Tourism Geographies, 20(3), pp. 456–472. Yoon, Y. & Uysal, M. (2005) ´An examination of the effects of motivation and satisfaction on destination loyalty: A structural model´, Tourism Management, 26(1), pp. 45–56. Available at: https://doi.org/10.1016/j.tourman.2003.08.016  https://doi.org/10.24052/JBRMR/V20IS02/ART-01 https://jbrmr.com/cdn/article_file/2026-03-30-14-46-26-PM.pdf Maria-Dolores Sanchez-Sanchez Carmen De-Pablos-Heredero Jose-Luis Montes-Botella heat waves tourism Spain SEM analysis resilience climate sustainability 125392 130 0

608 https://jbrmr.com/details&cid=608 2026-05-15 Whether emotional responses to artificial intelligence operate as undifferentiated technology anxiety or as identity-conditioned dimensional patterns has not been systematically tested in naturalistic consumer survey data. This study addresses this gap through quantitative analysis of validated survey data from a Greek consumer sample of N = 318 with three Principal Component Analysis-validated AI vulnerability subscales: Implications, Surveillance, and Ethical Issues; Concerns about Lack of Knowledge about AI; and Consumer and Social Concerns. Three identity-conditioned dimensional patterns are documented through one-way analyses of variance and independent samples t-tests across tech-savviness, channel preference, and geographic context segments. The Identity-Aligned Emotional Model refines the foundational exposure-familiarity-acceptance pathway by specifying how identity motivation conditions emotional response across distinct vulnerability dimensions. The findings supplement aggregate technology adoption mechanisms with dimension-specific design principles for AI public communication strategy in Mediterranean high-uncertainty-avoidance consumer contexts. Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K., and Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34-49. https://doi.org/10.1016/j.jretai.2014.09.005 Association of Internet Researchers. (2019). Internet research: Ethical guidelines 3.0. AoIR. Castelo, N., Bos, M. W., and Lehmann, D. R. (2019). Task-dependent algorithm aversion. Journal of Marketing Research, 56(5), 809-825. https://doi.org/10.1177/0022243719851788 Citation omitted blind review. (2025a). DBA Research, The Impact of AI on Consumer Behavior of Greeks. European International University Paris. Citation omitted blind review. (2025b). AI-Augmented Integrated Marketing Communication for Hydrogen Adoption (accepted for publication, IJBESAR). Citation omitted blind review. (2026). The AI Socio-Digital Inequality Framework: Empirical Evidence from a Greek Consumer Sample (in press, Open Education). Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008 Hajek, A., Zwar, L., and Neumann, A. (2025). Translation and validation of the artificial intelligence anxiety scale in German. PLOS ONE, 20(10), e0333073. https://doi.org/10.1371/journal.pone.0333073 Han, J.-H., and Ko, D. (2025). Trust formation, error impact, and repair in human-AI financial advisory: A dynamic behavioral analysis. Behavioral Sciences, 15(10), 1370. https://doi.org/10.3390/bs15101370 Hofstede, G. (2011). Dimensionalizing cultures: The Hofstede model in context. Online Readings in Psychology and Culture, 2(1). https://doi.org/10.9707/2307-0919.1014 Kim, K.-E. (2023). Maximizers' reactance to algorithm-recommended options: The moderating role of autotelic vs. instrumental choices. Behavioral Sciences, 13(11), 938. https://doi.org/10.3390/bs13110938 Lazarus, R. S. (1991). Emotion and adaptation. Oxford University Press. Liu, X., and Liu, Y. (2025). Developing and validating a scale of artificial intelligence anxiety among Chinese EFL teachers. European Journal of Education, 60(1). https://doi.org/10.1111/ejed.12902 Logg, J. M., Minson, J. A., and Moore, D. A. (2019). Algorithm appreciation: People prefer algorithmic to human judgment. Organizational Behavior and Human Decision Processes, 151, 90-103. https://doi.org/10.1016/j.obhdp.2018.12.005 Oyserman, D. (2015). Identity-based motivation. Emerging Trends in the Social and Behavioral Sciences. https://doi.org/10.1002/9781118900772.etrds0171 Venkatesh, V., and Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x Wang, Y.-Y., and Wang, Y.-S. (2019). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interactive Learning Environments, 30(4), 619-634. https://doi.org/10.1080/10494820.2019.1674887 Zajonc, R. B. (1968). Attitudinal effects of mere exposure. Journal of Personality and Social Psychology, 9(2, Pt. 2), 1-27. https://doi.org/10.1037/h0025848 Zenodo Dataset. (2025). Greek Consumer AI Perception Dataset, N = 318 (citation omitted blind review). Zenodo. https://doi.org/10.5281/zenodo.19956739 https://doi.org/10.24052/JBRMR/V20IS02/ART-02 https://jbrmr.com/cdn/article_file/2026-05-15-10-26-36-AM.pdf Theofanis Aritzis AI consumer anxiety identity-aligned emotional model dimensional refinement Mediterranean uncertainty-avoidance AI public communication 121612 84 0

609 https://jbrmr.com/details&cid=609 2026-06-24 The purpose of this exploratory paper is to increase our understanding about demand. In general terms demand can be divided into two categories - positive demand and negative demand. Positive demand generates business, whereas negative demand can mainly be seen as a cost. In service marketing literature these two categories have been named as value demand and failure demand. The original concept of failure demand is quite company grounded. In this paper we have broadened the concept to cover also customer actions by introducing a supplemented definition. The existing service marketing literature provides limited guidance for coping with failure demand and, therefore, we identify different types of failure demand. Methodologically the topic is approached through an exploratory focus-group interview and three theme-interviews. The empirical results indicate clearly that there is a need for new approaches and that the customer processes and procedures must be constantly assessed and improved. Service capacity problems and communication seem to be the biggest causes for failure demand. Even though customers may carry some responsibility, the general perception among them seems to be that it is purely company´s task to avoid failure demand. Managerially it seems to be beneficial to be aware of one’s demand structure and to develop one’s customer processes on a constant basis. Additionally, customers must be guided towards the most suitable channels. The study as a whole underline the importance of developing our thinking regarding the demand Abaidi, I., & Vernette, E. (2018). Does digitalization create or reduce perceived global value? The Journal of Consumer Marketing, 35(7), 676-687. Brown, T. (2008): Design Thinking, Harvard Business Review, 86:6, 84 Den Hertog, P., Van Der Aar, W. & de Jong, M., W. (2010): Capabilities for Managing Service Innovation: Towards a Conceptual Framework, Journal of Service Management, 21:4, 490-514 Dong, B., & Sivakumar, K. (2017): Customer participation in services: Domain, scope, and boundaries. Journal of the Academy of Marketing Science, 45(6), 944-965. doi:https://doi.org/10.1007/s11747-017-0524-y Gronroos, C. (2016): Internationalization strategies for services: A retrospective. The Journal of Services Marketing, 30(2), 129-132 Hallikainen, H., Alamaki, A., & Laukkanen, T. (2018): Individual preferences of digital touchpoints: A latent class analysis. Journal of Retailing and Consumer Services, Vol. 50, Sept., 386-393 Heinonen, K. & Strandvik, T. (2018): Reflections on Customers’ Primary Role in Markets, European Management Journal, 36:1, 1-11, Jan., https://doi.org/10.1016/j.emj.2017.09.005 Heinonen, K., Strandvik, T. & Voima, P. (2013): Customer Dominant Value Formation in Service, European Business Review, 25:2, 104-125 Jaaron, A. & Backhouse, C. (2014): Learning from Chaos: The Advent of Antifragility in Service Organizations, Proceedings of the 2014 POMS International Conference, Singapore, July 21-23, 1-8 Jaaron, A. & Backhouse, C. (2016): A Systems Approach for Forward and Reverse Logistics Design: Maximising Value from Customer Involvement, The International Journal of Logistics Management, 27:3, 947-971 Kjoller, A, & Rasmussen, N., W. (2017): The Hidden Potential of Eliminating Failure Demand, available in the world wide webb: https://implementconsultinggroup.com/media/6403/the-hidden-potential-of-eliminating-failure-demand. Kokku, Randheer. (2021). Omni and Multi-Channel: Relationship with Utilitarian/Hedonic Benefits, Shopping Value and Channel Patronage. International Review of Management and Marketing. 11. 11-22. 10.32479/irmm.11215. Long, Z. & Axsen, J. (2022): Who will use new Mobility Technologies? Exploring Demand for shared, Electric, and, Automated Vehicles in three Canadian Metropolitan Regions, Energy Research & Social Science, 88:1, 102506, https://doi.org/10.1016/j.erss.2022.102506 Macomber, H., D., Calayde, D., Hovell, S., & Contractors, J. (2018): Failure Demand: The Hidden Drag on Professional Services Profitability, The Pocket Sensei, Cited 4.1.2019, available in the world wide webb:  https://static1.squarespace.com/static/5994a002e3df28d4b7fc1606/t/5afac0d870a6ad25e69c36b1/1526382822274/Failure+Demand+Workshop+5-2018 Marr, B. & Parry, S. (2004): Performance Management in Call Centers: Lessons, Pitfalls and Achievements in Fujitsu Services, Measuring Business Excellence, 8:40, 55-62 Matthing, J., Sanden, B. & Edvardsson, B. (2004): Learning from and with Customers, International Journal of Service Industry Management, 15:5, 479-498 Miles, M.B. & Huberman, A. 1994. "Qualitative Data Analysis: An Expanded Source Book", 2nd ed. New York, Sage Publications Morris, G. & Walley, P. (2021): Implementing Failure Demand Reduction as Part of a Demand Management Strategy, Public Money & Management, 42:1, 22-31. https://doi.org/10.1080/09540962.2021.1978163 Myers, M.D. (2013): Qualitative Research in Business & Management, 2nd ed., SAGE, London Maki, M. & Kokko, T. (2013): Front-Line Service Personnel´s Stress-level in Demanding Customer Encounters, Journal of Business and Economics, April, Vol. 4, 249-255 Parasuraman, A. (2010). Service productivity, quality and innovation: Implications for service‐design practice and research. International Journal of Quality and Service Sciences, 2(3), 277-286. Ple, L. (2017): Why do we need research on value co-destruction? Journal of Creating Value, 3(2), 162-169. Porru, L. (2019): Lean-Oriented Approach for Discovering Failure Demand in a Service Contact Centre Environment – Case Study from the Finnish Financial Sector, Master Thesis in Strategic Business Development, University of Vaasa, Finland. Quinton, S., & Smallbone, T. (2006). Reliability, validity and generalization. In Postgraduate Research in Business (pp. 125- 140). Seddon, J. (1992): I Want You to Cheat! The unreasonable Guide to Service and Quality in Organizations, Vanguard Consulting, Ltd. Seddon, J. (2003): Freedom from Command and Press, Vanguard Press Seddon, J. (2005): Freedom from Command and Control (2nd Edition), Buckingham, Published by Vanguard Consulting Seddon, J. (2009): Failure Demand – From the Horse´s Mouth, Customer Strategy, 1:2, 33-34 Seddon, J. & Brand, C. (2008): Debate: Systems Thinking and Public Sector Performance, 28:1, 7-9 Seddon, J. & Caulkin, S. (2007): Systems Thinking, Lean Production and Action Learning, Action Learning: Research and Practice, 4:1, 9-24 Seddon, J. & O´Donovan, B. (2010a): Rethinking Lean service pt. 1, Management Services, 54:2, 34-37 Seddon, J. & O´Donovan, B. (2010b): Rethinking Lean service pt. 2, Management Services, 54:2, 14-19 Teehan, R. & Tucker, W. (2008): An Exploratory Research study: Operationalizing the Measurement of Failure Demand in Customer Service. Quality Management and Organizational Development Attaining Sustainability from Organizational Excellence to Sustainable Excellence. 11th QMOD Conference, 20-22 August, Helsingborg, Sweden 89-98 Yu, E. & Sangiorgi, D. (2017): Service Design as an Approach to Implement the Value Co-creation Perspective in New Service Development, Journal of Service Research, 21: 1, 40-58, https://doi.org/10.1177/1094670517709356 Zeithaml, V., Bitner, M., J. & Gremier, D., D. (2013): Services Marketing: Integrating Customer Focus across the Firm, 6th ed., New York, NY: McGraw-Hill Irwin. Zhao, X., Fu, N., & Liang, X. (2023). Whose customer orientation? Exploring the relationships between leaders, team customer orientation climate and customer satisfaction. Journal of Service Theory and Practice, 33(5), 629-646. https://jbrmr.com/cdn/article_file/v20i2jbrmr3.pdf Teemu Kokko Marko Maki Customer Encounter Customer Value Demand Failure Demand 123087 79 0