Analysis and Optimization of a Buffet Pricing Strategy in the Telecommunication Industry Using the Particle Swarm Optimization (PSO) Algorithm

Silvia Merdikawati, Revina Dwi Oktaviani, Salahuddin Salahuddin, Afni Khadijah

Sari


Flat-rate pricing (buffet pricing) is a common strategy in the global telecommunications industry, yet its adoption in Indonesia remains limited due to regulatory challenges, network capacity constraints, and diverse customer preferences. This study aims to optimize buffet pricing by considering user segmentation and varied service consumption patterns. A metaheuristic approach, specifically Particle Swarm Optimization (PSO), is employed to determine the optimal pricing that maximizes operator profit while maintaining customer satisfaction. A customer demand model is developed using a triangular distribution to reflect the asymmetric variability of usage. Results indicate that heavy users benefit significantly from flat-rate plans, whereas light users are better served by a hybrid pricing scheme. PSO demonstrates superior adaptability and efficiency compared to conventional methods, particularly when parameter tuning accelerates convergence. The study also highlights the importance of pricing flexibility to address heterogeneous customer needs. This study offers practical contributions to the development of data-driven, competitive pricing strategies in the evolving telecommunications market.

Teks Lengkap:

PDF

Referensi


J. S. Gans, S. P. King, and N. G. Mankiw, Principles of Microeconomics, 8th ed. Boston, MA: Cengage Learning, 2019.

J. Haucap and T. Stühmeier, “Competition and regulation in telecommunications markets,†Telecommunications Policy, vol. 40, no. 8, pp. 729–741, 2016.

S. Anwar, “Strategi Penetapan Harga pada Pasar Oligopoli Industri Komunikasi,†Kompasiana, 2023. [Online]. Available: https://www.kompasiana.com

R. Tyasti and N. Hayati, “Analisis Model Pasar Oligopoli dan Strategi pada Industri Layanan Telekomunikasi di Indonesia,†ResearchGate, 2022. [Online]. Available: https://www.researchgate.net

R. Iyengar, K. Jedidi, and R. Kohli, “A conjoint approach to multipart pricing,†Journal of Marketing Research, vol. 45, no. 2, pp. 195–210, 2008. doi: 10.1509/jmkr.45.2.195

P. J. Danaher, M. D. Smith, and R. Telang, “The effect of digital unlimited pricing strategies on consumer behavior,†Marketing Science, vol. 36, no. 6, pp. 855–877, 2017.

G. J. Tellis, “Beyond the many faces of price: An integration of pricing strategies,†Journal of Marketing, vol. 50, no. 4, pp. 146–160, 1986.

C. Shapiro and H. R. Varian, Information Rules: A Strategic Guide to the Network Economy, Boston, MA: Harvard Business Press, 1999.

H. Chen, R. H. L. Chiang, and V. C. Storey, “Business intelligence and analytics: From big data to big impact,†MIS Quarterly, vol. 36, no. 4, pp. 1165–1188, 2012.

J. Kennedy and R. Eberhart, “Particle swarm optimization,†in Proc. IEEE Int. Conf. Neural Networks, Perth, WA, Australia, 1995, pp. 1942–1948.

C. Blum and A. Roli, “Metaheuristics in combinatorial optimization: Overview and conceptual comparison,†ACM Computing Surveys, vol. 35, no. 3, pp. 268–308, 2003.

C. Schlereth, T. Stepanchuk, and B. Skiera, “Optimization and analysis of the profitability of tariff structures with two-part tariffs,†European Journal of Operational Research, vol. 206, no. 2, pp. 691–701, 2010. doi: 10.1016/j.ejor.2010.03.038

S.-W. Lin, S. Merdikawati, S.-F. Wu, and R.-H. Yeh, “Optimization and analysis of three-part tariff pricing strategies,†OR Spectrum, 2023. doi: 10.1007/s00291-023-00730-2

S. Merdikawati, S. Lin, and R.-H. Yeh, “Optimal three-part tariff pricing and marketing strategies for consumer overconfidence,†PLOS ONE, vol. 19, pp. 1–28, 2024. doi: 10.1371/journal.pone.0297819

S. Merdikawati, R. D. Oktaviani, and N. Rahmah, “Analisis dampak segmentasi konsumen terhadap strategi pemasaran dalam tarif dua bagian menggunakan algoritma metaheuristics,†Jurnal Ilmu Pengetahuan dan Teknologi, vol. 9, pp. 12–18, 2025.

L. Zhou, Y. Shi, Y. Li, and W. Zhang, “Parameter selection, analysis and evaluation of an improved particle swarm optimizer with leadership,†Artificial Intelligence Review, vol. 34, no. 4, pp. 343–367, 2010.

M. Ş. Ayas and E. Şahin, “Parameter effect analysis of particle swarm optimization algorithm in PID controller design,†International Journal of Optimization and Control: Theories & Applications, vol. 9, no. 1, pp. 1–10, 2019.

Y. ShiYuan, “Reinforcement learning based parameters adaption method for particle swarm optimization,†arXiv preprint, arXiv:2206.00835, 2022.

M. R. Bonyadi, “A theoretical guideline for designing an effective adaptive particle swarm,†arXiv preprint, arXiv:1802.04855, 2018.

Investopedia, “How is profit maximized in a monopolistic market?†[Online]. Available: https://www.investopedia.com/ask/answers/041315/how-profit-maximized-monopolistic-market.asp

D. T. Nigatu, T. G. Dinka, and S. L. Tilahun, “Convergence analysis of particle swarm optimization algorithms for different constriction factors,†Frontiers in Applied Mathematics and Statistics, vol. 10, Art. no. 1304268, 2024.

J. Kennedy and R. Eberhart, “Particle swarm optimization,†in Proc. IEEE Int. Conf. Neural Networks, Perth, WA, Australia, 1995, pp. 1942–1948.

S. Mirjalili, “Evolutionary algorithms and neural networks,†in Evolutionary Algorithms and Neural Networks: Theory and Applications, Springer, 2019, pp. 1–25.

F. Jallat and F. Ancarani, “Yield management, dynamic pricing and CRM in telecommunications,†Journal of Services Marketing, vol. 22, no. 6, pp. 465–478, 2008. [Online]. Available: https://www.researchgate.net/publication/242021161

A. Khalik, R. Perdana, and H. Saputra, “Hybrid pricing strategy optimization based on customer segmentation in telecom services,†West Science Information and Systems Technology, vol. 3, no. 2, pp. 45–51, 2022.




DOI: http://dx.doi.org/10.30811/jaise.v5i2.6954

Refbacks

  • Saat ini tidak ada refbacks.


Indexing :

Creative Commons License
Journal of Artificial Intelligence and Software Engineering (JAISE) licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.