The Effect of Dynamic Pricing Strategy on Sales Performance through the Airbnb Platform: Evidence from Private Villas in Canggu, Bali

I Gusti Ayu Eka Widiningsih; Komang Agus Rudi Indra Laksmana; I Gusti Ayu Diah Werdhi Srikandi Wedasteraputri Suyasa

doi:10.55927/fjmr.v4i9.506

Authors

I Gusti Ayu Eka Widiningsih University of Mahendradatta
Komang Agus Rudi Indra Laksmana University of Mahendradatta
I Gusti Ayu Diah Werdhi Srikandi Wedasteraputri Suyasa University of Mahendradatta

DOI:

https://doi.org/10.55927/fjmr.v4i9.506

Keywords:

Dynamic Pricing Strategy, Market Conditions, Sales Performance, Airbnb, PLS-SEM

Abstract

This study investigates the impact of dynamic pricing strategy on sales performance in private villas listed on the Airbnb platform, focusing on the Canggu area of Bali. Market conditions were examined both as antecedent and moderating variables. Data were drawn from a population of 1,681 private villas in Canggu, with a sample of 323 villas selected using Slovin’s formula (e = 5%). Secondary data were obtained from Airbtics and AirDNA, leading platforms that provide analytics for Airbnb listings. The research applied Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate relationships among variables. Key performance indicators included Average Daily Rate (ADR), Revenue per Available Room (RevPAR), occupancy rate, and total revenue. The findings reveal that dynamic pricing strategy significantly improves sales performance. Market conditions significantly affect sales performance and strengthen the effect of dynamic pricing as a moderator. However, market conditions do not have a significant direct effect on the adoption of dynamic pricing. These results highlight the adaptive nature of pricing strategies to market dynamics and suggest that villa managers should design responsive and context-based pricing policies to maximize revenue.

References

Abdillah, Willy dan Jogiyanto. 2015. Partial Least Square (PLS) Alternatif Structural Equation Modeling (SEM) dalam Penelitian Bisnis. Ed.1. Yogyakarta: ANDI

Abrate, G., & Viglia, G. (2019). Dynamic pricing strategies in the hospitality industry: Evidence from hotel Revenue management. Tourism Management, 74.

Aguiar, L., Gallego, E. F., & Loizides, A. (2020). Factors Influencing Airbnb Prices: The Case of Bali. Journal of Tourism Research, 12(2).

Airbnb: Disruptive innovation and the rise of an informal tourism accommodation sector. Current Issues in Tourism, 18(12).

Amelia, D., & Arianti, F. (2023). Pengaruh Tingkat Hunian Hotel, Jumlah Wisatawan, dan Jumlah Objek Wisata terhadap Pendapatan Sektor Pariwisata di Kota Semarang Tahun 2000-2020. Analisis Regresi Linear Berganda. Amenitiz. (2018). Seasonality and the Hotel Industry: What You Need to Know. Artikel Industri.

Baker, T., Wood, R. C., & Ooi, C. S. (2021). Algorithmic pricing and consumer trust: Evidence from the hotel sector. Annals of Tourism Research, 87.

Dogru, T., Mody, M., & Suess, C. (2020). Airbnb and hotel performance in COVID-19: Findings from big data research. International Journal of Hospitality Management, 89.

Elmaghraby, W., & Keskinocak, P. (2003). Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions. Management Science, 49(10).

F, D. D. (2018). Analisis Daya Saing dan Permintaan Pariwisata Indonesia, 2000-2016 (Aplikasi Tourism Gravity Model). Model Gravity dengan Poisson Pseudo Maximum Likelihood (PPML). Universitas Gadjah Mada.

Gallego, G., & Van Ryzin, G. (1994). Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management Science, 40(8).

Garrido, E., & Wirth, F. (2022). Dynamic pricing and managerial inertia in hospitality: Why data doesn’t always translate to action. Journal of Hospitality and Tourism Management, 50.

Gibbs, C., Guttentag, D., Gretzel, U., Morton, J., & Goodwill, A. (2018). Use of dynamic pricing strategies by Airbnb hosts. International Journal of Contemporary Hospitality Management, 30(1).

Handayani, R. N., & Fahmi, I. (2021). Tingkat Daya Saing dan Faktor-Faktor yang Mempengaruhi Permintaan Pariwisata Indonesia di Pasar Potensial Asia. Regresi Data Panel Dinamis. Repository IPB.

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: The Guilford Press.

Kasmir. (2018). Manajemen Strategis. Jakarta: RajaGrafindo Persada.

Kertajaya, H., & Hermawan, K. (2017). Marketing 4.0: Moving from Traditional to Digital. Jakarta: Gramedia Pustaka Utama.

Kimes, S. E. (2011). The future of hotel revenue management. Journal of Revenue and Pricing Management, 10(1).

Li, Y., Zhang, Z., & Zhang, R. (2018). The effects of dynamic pricing on Revenue and customer satisfaction in the sharing economy: Evidence from Airbnb. Journal of Business Research, 92.

Ma, X., Zhang, J., & Zhang, Y. (2022). Pricing strategies and Revenue management in competitive markets: A systematic review. Journal of Revenue and Pricing Management, 21(3).

McCluskey, A., & Lalkhen, A. G. (2020). Statistics II: Descriptive statistics. Continuing Education in Anaesthesia Critical Care & Pain, 20(3)

Munanda, R., & Amar, S. (2019). Pengaruh Jumlah Kunjungan Wisatawan Mancanegara, Rata-Rata Pengeluaran, dan Tingkat Hunian Hotel terhadap PDRB Sektor Pariwisata di Sumatera Barat. Analisis Regresi Linear Berganda.

Neirotti, P., Raguseo, E., & Paolucci, E. (2018). Big data analytics capabilities and firm performance: An empirical investigation in the hotel industry. Tourism Management, 69.

Nguyen, T., Simkin, L., & Canhoto, A. (2020). The dark side of digital personalization: An agenda for research and practice. Journal of Business Research, 116.

Nisar, T. M., Tan, J., & Liu, Z. (2022). Dynamic pricing in the Sharing Economy: Case Study of Airbnb in Asia-Pacific Region. International Journal of Hospitality Management, 94.

Cheng, M., & Jin, X. (2019). What do Airbnb users care about? An analysis of online review comments. International Journal of Hospitality Management, 76.

Nurhaida, M. (2012). Analisis Faktor-Faktor yang Mempengaruhi Permintaan Pariwisata di Indonesia. Regresi Data Panel dengan Fixed Effect Model. Universitas Trisakti.

Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform Revolution: How Networked Markets Are Transforming the Economy. W. W. Norton & Company.

PlanetHMS. (2023). The Impact of Hotel Seasonality on Revenue Management Strategies. Analisis Strategi.

RateGain. (2023). The Impact of Seasonality on Hotel Revenue: Understanding the Highs and Lows. Analisis Industri.

Revnomix. (2023). Top Guide to Seasonality & Revenue Management in Hospitality. Panduan Praktis.

Rochet, J. C., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4).

Sainaghi, R., Phillips, P., & Corti, V. (2019). Measuring hotel performance: Using a balanced scorecard perspectives’ approach. International Journal of Hospitality Management, 78.

Schlosser, R., & Boissier, M. (2018). Dealing with the dimensionality curse in dynamic pricing competition: Using frequent repricing to compensate imperfect market anticipations. arXiv preprint.

Shao, Q., & Jiang, Z. (2020). Optimal Pricing Strategy for Airbnb Hosts Based on Dynamic pricing Models. Journal of Business Research, 113.

Shen, Y., Li, X., & Liu, W. (2021). Revenue Management in the Sharing Economy: A Dynamic pricing Approach for Airbnb Hosts. Journal of Revenue and Pricing Management, 20(4).

Sihite, H. (2023). Penerapan Metode Yield/Revenue dengan RevPAR: Studi pada Hotel and Conventions Kelapa Gading. Jurnal Attadbir, 5(2).

Singagerda, F. I., Oktaviani, R., Hakim, D. B., & Kustiari, R. (2014). Faktor-Faktor Penentu Aliran Investasi, dan Perdagangan Pariwisata, serta Dampaknya terhadap Permintaan dan Penawaran Pariwisata Indonesia. Model Panel Gravity dan Panel Least Square.

Stavins, J. (2001). Price discrimination in the airline market: The effect of market concentration. Review of Economics and Statistics, 83(1).

Sukirno, S. (2016). Mikroekonomi Teori Pengantar. Rajawali Pers.

Suryani, N. L. P. S., & Suryawan, I. B. (2023). Strategi Pemasaran dalam Meningkatkan Pendapatan Hotel di Masa Pandemi COVID-19. Jurnal Manajemen Perhotelan dan Pariwisata, 6(1).

Talluri, K. T., & Van Ryzin, G. J. (2004). The Theory and Practice of Revenue Management. Springer Science & Business Media.

Tjiptono, F. (2019). Strategi Pemasaran (4th ed.). Yogyakarta: ANDI.

Umar, H. (2021). Manajemen Pemasaran Strategik. Jakarta: Salemba Empat.

Utami, R. C., & Hartono, D. (2016). Analisis Daya Saing Harga Pariwisata Indonesia: Pendekatan Elastisitas Permintaan. Jurnal Gama Societa.

Wahyudi, W., & Pamungkas, B. D. (2018). Analisis Faktor-Faktor yang Mempengaruhi Pendapatan Hotel (Studi Kasus Hotel Baha-Baha Sekongkang Kabupaten Sumbawa Barat Tahun 2012-2016). Jurnal Gama Societa, 2(1).

Waluya, B. (2016). Aspek Permintaan dan Penawaran Pariwisata. Analisis Deskriptif. Universitas Pendidikan Indonesia.

Yang, J., & Chen, L. (2023). Pricing Strategies and Revenue Optimization on Airbnb: A Global Perspective. Journal of Hospitality & Tourism Research, 47(1).

Zervas, G., Proserpio, D., & Byers, J. W. (2017). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of Marketing Research, 54(5).

Zervas, G., Proserpio, D., & Byers, J. W. (2021). The Impact of Airbnb on the Hotel Industry: A Comprehensive Analysis. Journal of Marketing Research, 58(6)