Tourism product consumers clustering for developing the tailored marketing mix
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DOIhttp://dx.doi.org/10.21511/im.21(1).2025.23
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Article InfoVolume 21 2025, Issue #1, pp. 281-295
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The constant change in consumer preferences requires adjusting sales strategies according to the consumer’s current needs. The study aims to cluster the consumers of tourism products based on the factors influencing their decision-making process when choosing tourism products and to classify them according to the marketing mix. The study is based on the analysis of data from 196 respondents in the Lviv region, collected through an online survey using Google Forms in the first decade of 2023. The sample is representative, as it was calculated considering the population of the Lviv region aged 16 and above, ensuring the results’ reliability and relevance. The results revealed that representatives of each cluster are, on average, willing to spend up to 10,000 UAH per person during their vacation. In the decision-making process regarding the purchase of components of a tourist product, accommodation holds the most significant importance for representatives of the first and second clusters (4.51 and 3.27, respectively), insurance is the most important for the third cluster (4.71), and food is the priority for the fourth cluster (2.54). The decisive components of tourist services and risks for all clusters include up-to-date information about the vacation destination and pandemics/diseases, although the significance of their influence varies. Additionally, the clusters differ regarding the elements of place and promotion of tourist products. The results demonstrate that the marketing mix elements vary across clusters despite certain similarities in respondents’ assessments.
- Keywords
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JEL Classification (Paper profile tab)Z33, Z31, M31
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References52
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Tables2
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Figures8
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- Figure 1. Research conceptual model
- Figure 2. Algorithm of tourism product сonsumers сlustering for developing the tailored marketing mix
- Figure 3. Average values of assessments of the impact of tourism product components by cluster
- Figure 4. Average values of assessments of the impact of tourism service components by cluster
- Figure 5. Average values of assessments of the impact of tourism risk components by cluster
- Figure 6. Group values of tourism product components by cluster
- Figure 7. Group values of tourism service components by cluster
- Figure 8. Group values of tourism risk components by cluster
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- Table 1. Overall scores for each component by clusters
- Table 2. Marketing mix for forming strategies by clusters
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- Ahani, A., Nilashi, M., & Ibrahim, O. (2017). Market segmentation and travel choice prediction in Spa hotels through TripAdvisor’s online reviews. International Journal of Hospitality Management, 80, 52-77.
- Balladares, G., Miralles, F., & Kennett, C. (2016). The role of perceived risk in online information search and pre-purchase alternative evaluation of products with significant experiential attributes. In Kavoura, A. (Ed.), Strategic Innovative Marketing (рр. 44-53). Switzerland: Springer.
- Biao, L., Liru, L., & Ying, S. (2021). Understanding the Influence of Consumers’ Perceived Value on Energy-Saving Products Purchase Intention. Frontiers in Psychology, 12.
- Brainberry. (2024). The Role of Personalization in Travel.
- Bremner, C. (2023). Understanding Consumer Preferences for Destination.
- Brown, M., Muchira, R., & Gottlieb, U. (2007). Privacy Concerns and the Purchasing of Travel Services Online. Information Technology & Tourism, 9.
- Buhaljoti, A. (2013). Identifying Key Factors Affecting Customer’s Decision-Making of Internet Service Providers in Albania. Management Dynamics in the Knowledge Economy, 7(3), 407-422.
- Chen, C.-M., Lin, Y.-L., & Hsu, C.-L. (2017). Does air pollution drive away tourists? A case study of the Sun Moon Lake National Scenic Area, Taiwan. Transportation Research, 53, 398-402.
- Crouch, G. I. (1995). A Meta-Analysis of Tourism Demand. Annals of Tourism Research, 22, 103-118.
- DART (2024). [Turystychna statystyka Ukrainy za I kvartal 2024 roku [Tourism statistics of Ukraine for the first quarter of 2024]. (In Ukrainian).
- Deng, W., Su, T., Zhang, Y., & Tan, C. (2021). Factors Affecting Consumers’ Online Choice Intention: A Study Based on Bayesian Network. Frontiers in Psychology, 12, 731850.
- Djeri, K., Plavša, J., & Cerovic, S. (2007). Analysis of potential tourists’ behaviour in the process of deciding upon a tourist destination based on a survey conducted in Bačka region. Geographica Pannonica, 11, 70-76.
- Dolnicar, S. (2007). Market segmentation in tourism. In Woodside, A., & Martin, D. (Eds.), Tourism management: analysis, behaviour and strategy (pp. 129-150). Cambridge: CAB International.
- Fernández-Morales, A. (2021). Cluster Analysis in Tourism. In Jafari, J., & Xiao, H. (Eds.), Encyclopedia of Tourism (pp. 1-2). Cham: Springer.
- Fleischer, A., & Rivlin, J. (2009). Quality, Quantity and Duration Decisions in Household Demand for Vacations. Tourism Economics, 15(3), 513-530.
- Gasimova, M. (2016). The Study of the Factors, Affecting Consumer Choice. Path of Science, 2(12), 39-43.
- Haley, R. I. (1968) Benefit segmentation: a decision–oriented research tool. Journal of Marketing, 32, 30-35.
- Haubl, G., & Trifts, V. (2000). Consumer decision making in online shopping environments: the effects of interactive decision aids. Marketing Science, 19, 4-21.
- Huang, X., Dai, S., & Xu, H. (2020). Predicting tourists’ health risk preventative behaviour and travelling satisfaction in Tibet: Combining the theory of planned behaviour and health belief model. Tourism Management Perspectives, 33, 100589.
- Ioannou, A., Tussyadiah, I., & Miller, G. (2021). That’s Private! Understanding Travelers’ Privacy Concerns and Online Data Disclosure. Journal of Travel Research, 60(7), 1510-1526.
- Khan, S. A., Liang, Y., & Shahzad, S. (2015). An empirical study of perceived factors affecting customer satisfaction to re-purchase intention in online stores in China. Journal of Service Science and Management, 8, 291-305.
- Klebanova, T. S., Gur’janova, L. S., & Chagovec’, L. O. (2018). Biznes-analityka bagatovymirnyh procesiv [Business Analysis of Multidimensional Processes] (272 p.). Kharkiv: KHNEU im. S. Kuznetsya. (In Ukrainian).
- Kotler, P., & Turner, R. (1993). Marketing management: analysis, planning, and control. Prentice-Hall Englewood Cliffs.
- Li, X. R., Meng, F., Uysal, M., & Mihalik, B. (2013). Understanding China’s long-haul outbound travel market: an overlapped segmentation approach. Journal of Business Research, 66(6), 786-793.
- Mashuta, Yu. (2024, November 19). Tested by war. What the survey of the tourist business in 2024 showed [Vyprobuvannia viinoiu. Shcho pokazalo opytuvannia turystychnoho biznesu v 2024 rotsi.]. (In Ukrainian).
- March, R. (1997). Diversity in Asian outbound travel industries: A comparison between Indonesia, Thailand, Taiwan, South Korea and Japan. International Journal of Hospitality Management, 16, 231-238.
- Mckercher, B., Chan, A., & Lam, C. (2008). The Impact of Distance on International Tourist Movements. Journal of Travel Research, 47, 208-224.
- Moutinho, L. (1987). Consumer Behaviour in Tourism. European Journal of Marketing, 21(10), 3-44.
- Neumayer, E. (2004). The Impact of Political Violence on Tourism: Dynamic Cross-National Estimation. The Journal of Conflict Resolution, 48(2), 259-281.
- Orisys Infotech (2018). Factors Influencing the Consumer Decision for Travel Planning.
- Pinto, I., & Castro, C. (2019). Online travel agencies: factors influencing tourists’ purchase decisions. Tourism & Management Studies, 15(2), 7-20.
- Rjasna, M. V., & Lytvynenko, Ju. O. (n.d.). Klasternyi analiz v marketynhovykh doslidzhenniakh [Cluster analysis in marketing research]. (In Ukrainian).
- Prastiwi, I., & Fitria, T. (2021). Benefit Perception Analysis, Risk Perception, Hedonic Motivation, Psychological Factors, Web Design To Online Shop Purchase Decisions. RELEVANCE Journal of Management and Business, 4(1), 039-057.
- Robaina, M., Madaleno, M., Silva , S., Eusébio, C., Carneiro, M. J., & Gama, C. (2020). The relationship between tourism and air quality in five European countries. Economic Analysis and Policy, 67, 261-272.
- Rodrigues, V., Carneiro, M. J., Eusébio, C., Madaleno, M., Robaina, M., Gama, C., . . . Monteiro, A. (2021). How important is air quality in travel decision-making? Journal of Outdoor Recreation and Tourism, 35, 100380.
- Rosselló, J., Becken, S., & Santana-Gallego, M. (2020). The effects of natural disasters on international tourism: A global analysis. Tourism Management, 79, 104080.
- Shi, T., Liu, X., & Li, J. (2018). Market Segmentation by Travel Motivations under a Transforming Economy: Evidence from the Monte Carlo of the Orient. Sustainability, 10, 3395.
- Singh, S., & Jang, S. (2020). Search, purchase, and satisfaction in a multiple-channel environment: how have mobile devices changed consumer behaviors? Journal of Retailing and Consumer Services, 10, 10-16.
- Smith, V. L. (1998). War and tourism: An American ethnography. Annals of Tourism Research, 25, 202-227.
- Sonmez, S., & Graefe, A. (1998). Influence of terrorism risk on foreign tourism. Annals of Tourism Research, 25(1), 112-144.
- Statista (2024). Global tourism industry – statistics & facts.
- Tiwari, M., & Tripathi, S. (2023). Application of Clustering Algorithms on Tourism Industry. International Journal for Research in Applied Science and Engineering Technology, 11(5), 2290-2294.
- Um, S., & Crompton, J. L. (1990). Attitude Determinants in Tourism Destination Choice. Annals of Tourism Research, 17, 432-448.
- Walters, G., Wallin, A., & Hartley, N. (2019). The Threat of Terrorism and Tourist Choice Behavior. Journal of Travel Research, 58(3), 370-382.
- Wang, M., Sun, L.-L., & Hou, J.-D. (2021). How emotional interaction affects purchase intention in social commerce: the role of perceived usefulness and product type. Psychology Research and Behavior Management, 14, 467-481.
- Woodside, A. G., & Lysonski, S. (1989). A General Model of Traveler Destination Choice. Journal of Travel Research, 17, 8-14.
- Yarcan, Ş., & Cetin, G. (2021). Tour Operating Business. Istanbul: Istanbul University Press.
- Zauner, A., Koller, M., & Hatak, I. (2015). Customer perceived value – Conceptualization and avenues for future research. Cogent Psychology, 2(1).
- Zhao, J., & Zhu, C. (2023). Modeling and Quantifying the Impact of Personified Communication on Purchase Behavior in Social Commerce. Behavioral Sciences, 13(8), 627.
- Zhao, S., & Chen , L. (2021). Exploring residents’ purchase intention of green housings in China: an extended perspective of perceived value. International Journal of Environmental Research and Public Health, 18, 4074.
- Zou, Y., & Meng, F. (2019). Chinese tourists’ sense of safety: perceptions of expected and experienced destination safety. Current Issues in Tourism, 23(15), 1886-1899.
- WTTC (2021). Emerging consumer trends in Travel & Tourism in 2021 and beyond trending in travel.