The Moderating Role of Digital Maturity in the Relationship Between Emerging Technologies Adoption and Performance of Five-Star-Rated Hotels in Zanzibar
Main Article Content
Keywords
Digital maturity, emerging technologies, five-star-rated hotels, Zanzibar, hotel performance
Abstract
Hotels in developing countries are increasingly adopting emerging technologies, particularly Cloud Computing Technologies (CCT), Big Data and Analytics (BDA), Virtual and Augmented Reality (VAR), Internet of Things (IoT), and Blockchain Technologies (BCT), including artificial intelligence (AI), to improve performance. However, studies remain fewer and more fragmented, and digital maturity is often conceptualized broadly rather than examined as an organizational capability that determines how hotels translate technology adoption into performance. Digital maturity determines how hotels translate emerging technologies into performance outcomes. This study determines the moderating effect of digital maturity on the relationship between the adoption of emerging technologies and performance in five-star-rated hotels in Zanzibar. This study used a quantitative research design to collect data from 392 hotel managers across 56 five-star-rated hotels via a structured questionnaire. Partial least squares structural equation modeling (PLS-SEM) was used to test the moderating effects of digital maturity on the relationship between the adoption of emerging technologies and operational efficiency, financial performance, and employee performance. Digital maturity exerted strong positive direct effects on employee performance (β = 0.904, p < 0.001) and financial performance (β = 0.805, p < 0.001), but a negative direct effect on operational efficiency (β = −0.130, p < 0.01). The moderating effect was significant only for operational efficiency (β = 0.106, p = 0.040), with non-significant moderation for financial performance (β = 0.016, p = 0.771) and employee performance (β = −0.049, p = 0.141). The model explained 83.5% of the variance in employee performance and 64.1% of the variance in financial performance, but only 9.0% of the variance in operational efficiency. This study used a mixed-methods convergent parallel design, with moderation analysis conducted using PLS-SEM to examine operational efficiency, financial performance, and employee performance. The model strongly explained employee performance (R² = 0.835; adjusted R² = 0.833) and substantially explained financial performance (R² = 0.641; adjusted R² = 0.637), but weakly explained operational efficiency (R² = 0.090; adjusted R² = 0.079). Digital maturity significantly moderated only the relationship between adoption of emerging technologies and operational efficiency (β = 0.106, t = 2.052, p = 0.040). Simultaneously, moderation was not significant for financial performance (β = 0.016, p = 0.771) or employee performance (β = -0.049, p = 0.141). The study concluded that digital maturity selectively enhances the operational value of emerging technologies in the hospitality sector. Hotels strengthen alignment across their digital strategies, staff digital competence, leadership support, cybersecurity, and data privacy. The study contributes context-specific evidence from Zanzibar by showing that digital maturity has performance-specific effects and selectively moderates the relationship between emerging technology adoption and hotel performance.
References
Anwar, F. A., Deliana, D., & Suyamto, S. (2024). Digital transformation in the hospitality industry: Improving efficiency and guest experience. International Journal of Management Science and Information Technology, 4(2), 428–437. https://doi.org/10.35870/ijmsit.v4i2.3201
Banerjee, P., & Bhat, A. (2025). Transforming Smart Hospitality: Leveraging AI and IoT for sustainable tourism, enhanced guest experience, and cybersecurity resilience. Eco-Tourism and Sustainable Development, 1(1), 14–26. https://doi.org/10.63385/etsd.v1i1.87
Bititci, U. S., Garengo, P., Ates, A., & Nudurupati, S. S. (2015). Value of maturity models in performance measurement. International journal of production research, 53(10), 3062-3085. https://doi.org/10.1080/00207543.2014.970709
Chandra Shekhar (2018). A Study of Technology Used In the Hospitality Industry. International Journal of Science and Research (IJSR) ISSN: 2319-7064. https://www.ijsr.net/archive/v8i8/ART2020169.pdf
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3), 297-334. https://www.cambridge.org/core/journals/psychometrika/article/abs/coefficient-alpha-and-the-internal-structure-of-tests/81D0CB193FA731FF5220FEB678FC4FAA
Cronbach, L. J., & Shavelson, R. J. (2004). My current thoughts on coefficient alpha and successor procedures. Educational and psychological measurement, 64(3), 391-418.
Ersoy, A., & Ehtiyar, R. (2023). The impact of artificial intelligence on hospitality employees’ work outcomes. Advances in Hospitality and Tourism Research (AHTR), 11(4), 505-526. https://dergipark.org.tr/en/pub/ahtr/article/1264966
Ezzaouia, I., & Bulchand-Gidumal, J. (2023). The impact of information technology adoption on hotel performance: Evidence from a developing country. Journal of Quality Assurance in Hospitality & Tourism, 24(5), 688-710. https://
doi.org/10.1080/1528008X.2022.2077886
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Fornells Herrera, A., Paradela Morgan, A., & Ficapal Mestres, J. (2024). Navigating the technological landscape in hospitality: Added values and entry barriers of technologies 4.0. Sage Open, 14(4), 21582440241296237. https://doi.org/10.1177/21582440241296237
Gajić, T., Petrović, M. D., Pešić, A. M., Conić, M., & Gligorijević, N. (2024). Innovative approaches in hotel management: integrating artificial intelligence (AI) and the internet of things (IoT) to enhance operational efficiency and sustainability. Sustainability, 16(17), 7279. https://doi.org/10.3390/su16177279
Garbin Praničević, D., Alfirević, N., & Indihar Štemberger, M. (2011). Information system maturity and the hospitality enterprise performance. Economic and Business Review, 13(4), 2. https://www.ebrjournal.net/home/vol13/iss4/2/
Godolja, M., Tavanxhiu, T., & Sevrani, K. (2025). Strategic Readiness for AI and Smart Technology Adoption in Emerging Hospitality Markets: A Tri-Lens Assessment of Barriers, Benefits, and Segments in Albania. Tourism and Hospitality, 6(4), 187. https://doi.org/10.3390/tourhosp6040187
Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research methods in applied linguistics, 1(3), 100027. https://www.sciencedirect.com/science/article/pii/S2772766122000246
Irani, F. (2024). Exploring the future of tourism: A qualitative study on the integration of robotics in North Cyprus hospitality and destination development. Worldwide Hospitality and Tourism Themes, 16(6), 694-705.. https://doi.org/10.1108/whatt-05-2024-0097
Jabbar, U. A., Prabowo, B. A., & Hanafi, R. A. (2024). Digital transformation in hotel management: Optimizing guest experience in the industry 4.0 era. Proceeding of The International Global Tourism Science and Vocational Education, 1(1), 177-190.
Jie, H., Gooi, L. M., & Lou, Y. (2025). Digital maturity, dynamic capabilities and innovation performance in high-tech SMEs. International Review of Economics & Finance, 99, 103971. https://www.sciencedirect.com/science/article/pii/S1059056025001340
Jöreskog, K. G., & Sörbom, D. (1989). LISREL 7: A guide to the program and applications.
Khlusevich, A., Inversini, A., & Schegg, R. (2024, January). Artificial intelligence and hospitality: a challenging relationship. In ENTER e-Tourism Conference (pp. 247-258). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-58839-6_27
Leung, R. (2019). Smart hospitality: Taiwan hotel stakeholder perspectives. Tourism Review, 74(1), 50-62. https://doi.org/10.1108/TR-09-2017-0149
Madanchian, M., Taherdoost, H., & Mohamed, N. (2023). AI-based human resource management tools and techniques; a systematic literature review. Procedia Computer Science, 229, 367-377. https://www.sciencedirect.com/science/article/pii/S187705092302029X
Marsh, H. W., Hau, K. T., & Grayson, D. (2005). Goodness of fit in structural equation models. https://psycnet.apa.org/record/2005-04585-010
Mihalič, T., & Buhalis, D. (2013). ICT as a new competitive advantage factor–case of small transitional hotel sector. Economic and business review, 15(1), 2. https://www.ebrjournal.net/home/vol15/iss1/2/
Mwakiremba, J. M. (2020). Effect Of Information Communication Technology On Financial Performance Of Hospitality Firms In Kenya (Doctoral dissertation, Kca University).
Parry, E., & Battista, V. (2023). The impact of emerging technologies on work: a review of the evidence and implications for the human resource function. Emerald Open Research, 1(4). https://doi.org/10.1108/EOR-04-2023-0001
Peng, X., Zhu, J., Lee, S., Zhou, D., Song, W., & Ying, T. (2024). Digital transformation in the hospitality industry: A bibliometric review from 2000 to 2023. International Journal of Hospitality Management, 120, 103761. https://www.sciencedirect.com/science/article/pii/S0278431924000732
Rönkkö, M., & Cho, E. (2022). An updated guideline for assessing discriminant validity. Organizational research methods, 25(1), 6-14. https://doi.org/10.1177/1094428120968614
Sakhanova, G., Duiskenova, R., & Konyrbekov, M. (2025). Digital Transformation and Innovation-Driven Evolution of the Hospitality Industry in Kazakhstan. Eurasian Journal of Economic and Business Studies, 69(4), 90-103.
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online, 8(2), 23-74.
Schumacker, R. E., & Lomax, R. G. (1996). A beginner’s guide to structural equation modeling. Mahwah, NJ: Lawrence Erlbaum Associates, Inc. New Jersey London
Shangwa, E. T., & Salama, M. (2024, December). Hotel Sector Digital Transformation Business Model. A Case Study of the International Hotel Sector Companies in Southern and Eastern Africa. In 2024 International Conference on Decision Aid Sciences and Applications (DASA) (pp. 1-5). IEEE.
Stankova, M., & Kaleychev, S. (2024). The significance of the digitalization and online communication tools used by five-star restaurants in Bulgaria. Turyzm/Tourism, 34(2), 171-180. https://www.ceeol.com/search/article-detail?id=1299395
Stieglitz, S., & Brockmann, T. (2012). Increasing organizational performance by transforming into a mobile enterprise. MIS quarterly executive, 11(4).
Suder, M., Kusa, R., Duda, J., & Karpacz, J. (2025). Exploring impact of entrepreneurial orientation on firm performance–moderators’ variability under changing market conditions. Review of Managerial Science, 19(3), 797-842. https://doi.org/10.1007/s11846-024-00775-9
Tan, A. S. I., Sia, B. C., Yeong, W. M., & Falahat, M. (2026). Digital transformation: the role of digital maturity and its determinants on business performance. Journal of Asia Business Studies, 20(2), 541-564. https://doi.org/10.1108/JABS-08-2024-0480
Thordsen, T., Murawski, M., & Bick, M. (2020, April). How to measure digitalization? A critical evaluation of digital maturity models. In Conference on e-Business, e-Services and e-Society (pp. 358-369). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-030-44999-5_30
Vo, D. T. T., Abu Afifa, M., Bui, D. V., Van, H. V., & Nguyen, N. (2024). Nexus among cloud-based accounting, employee job performance, employee digital skills and operational performance: a mediating–moderating model. Meditari Accountancy Research, 32(6), 2321-2347. https://doi.org/10.1108/MEDAR-02-2024-2362
World Bank Group. (2019). Zanzibar: A pathway to tourism for all: Integrated strategic action plan.
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Samwel Savunyu, Department of Hotel and Hospitality Management, School of Tourism, Hospitality and Events Management, Moi University, P.O. Box 3900, Eldoret, Kenya
Department of Hotel and Hospitality Management, School of Tourism, Hospitality and Events Management, Moi University, P.O. Box 3900, Eldoret, Kenya
Jacqueline Korir, Department of Hotel and Hospitality Management, School of Tourism, Hospitality and Events Management, Moi University, P.O. Box 3900, Eldoret, Kenya
Department of Hotel and Hospitality Management, School of Tourism, Hospitality and Events Management, Moi University, P.O. Box 3900, Eldoret, Kenya
Belsoy Sawe, Department of Hotel and Hospitality Management, School of Tourism, Hospitality and Events Management, Moi University, P.O. Box 3900, Eldoret, Kenya
Department of Hotel and Hospitality Management, School of Tourism, Hospitality and Events Management, Moi University, P.O. Box 3900, Eldoret, Kenya