A pricing optimization modelling for assisted decision making in telecommunication product-service bundling
Product service bundle (PSB) is a marketing strategy that offers attractive product-service packages with competitive pricing to ensure sustained profitability. However, designing suitable pricing for PSB is a non-trivial task that involves complex decision-making. This paper explores the significan...
Published in: | International Journal of Information Management Data Insights |
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2-s2.0-85183022609 Zakaria A.F.; Lim S.C.J.; Aamir M. A pricing optimization modelling for assisted decision making in telecommunication product-service bundling 2024 International Journal of Information Management Data Insights 4 1 10.1016/j.jjimei.2024.100212 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183022609&doi=10.1016%2fj.jjimei.2024.100212&partnerID=40&md5=08d9a6c99c19530e9bb4dbaf5ec89ce2 Product service bundle (PSB) is a marketing strategy that offers attractive product-service packages with competitive pricing to ensure sustained profitability. However, designing suitable pricing for PSB is a non-trivial task that involves complex decision-making. This paper explores the significance of pricing optimization in the telecommunication industry, focusing on product-service bundling (PSB). It delves into the challenges associated with pricing PSB and highlights the transformative impact of big data analytics on decision-making for PSB strategies. The study presents a data-driven pricing optimization model tailored for designing appropriate pricing structures for product-service bundles within the telecommunication services domain. This model integrates customer preference knowledge and involves intricate decision-making processes. To demonstrate the feasibility of the proposed approach, the paper conducts a case study encompassing two design scenarios, wherein the results reveal that the model offers competitive pricing compared to existing telecommunication service providers, facilitating PSB design and decision-making. The findings from the case study indicate that the data-driven pricing optimization model can significantly aid PSB design and decision-making, leading to competitive pricing strategies that open avenues for new market exploration and ensure business sustainability. By considering both product and service features concurrently, the proposed model provides a pricing reference for optimal decision-making. The case study validates the feasibility and effectiveness of the approach within the telecommunication industry and highlights its potential for broader applications. The model's capability to generate competitive pricing strategies offers opportunities for new market exploration, ensuring business growth and adaptability. © 2024 The Author(s) Elsevier B.V. 26670968 English Article All Open Access; Gold Open Access |
author |
Zakaria A.F.; Lim S.C.J.; Aamir M. |
spellingShingle |
Zakaria A.F.; Lim S.C.J.; Aamir M. A pricing optimization modelling for assisted decision making in telecommunication product-service bundling |
author_facet |
Zakaria A.F.; Lim S.C.J.; Aamir M. |
author_sort |
Zakaria A.F.; Lim S.C.J.; Aamir M. |
title |
A pricing optimization modelling for assisted decision making in telecommunication product-service bundling |
title_short |
A pricing optimization modelling for assisted decision making in telecommunication product-service bundling |
title_full |
A pricing optimization modelling for assisted decision making in telecommunication product-service bundling |
title_fullStr |
A pricing optimization modelling for assisted decision making in telecommunication product-service bundling |
title_full_unstemmed |
A pricing optimization modelling for assisted decision making in telecommunication product-service bundling |
title_sort |
A pricing optimization modelling for assisted decision making in telecommunication product-service bundling |
publishDate |
2024 |
container_title |
International Journal of Information Management Data Insights |
container_volume |
4 |
container_issue |
1 |
doi_str_mv |
10.1016/j.jjimei.2024.100212 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183022609&doi=10.1016%2fj.jjimei.2024.100212&partnerID=40&md5=08d9a6c99c19530e9bb4dbaf5ec89ce2 |
description |
Product service bundle (PSB) is a marketing strategy that offers attractive product-service packages with competitive pricing to ensure sustained profitability. However, designing suitable pricing for PSB is a non-trivial task that involves complex decision-making. This paper explores the significance of pricing optimization in the telecommunication industry, focusing on product-service bundling (PSB). It delves into the challenges associated with pricing PSB and highlights the transformative impact of big data analytics on decision-making for PSB strategies. The study presents a data-driven pricing optimization model tailored for designing appropriate pricing structures for product-service bundles within the telecommunication services domain. This model integrates customer preference knowledge and involves intricate decision-making processes. To demonstrate the feasibility of the proposed approach, the paper conducts a case study encompassing two design scenarios, wherein the results reveal that the model offers competitive pricing compared to existing telecommunication service providers, facilitating PSB design and decision-making. The findings from the case study indicate that the data-driven pricing optimization model can significantly aid PSB design and decision-making, leading to competitive pricing strategies that open avenues for new market exploration and ensure business sustainability. By considering both product and service features concurrently, the proposed model provides a pricing reference for optimal decision-making. The case study validates the feasibility and effectiveness of the approach within the telecommunication industry and highlights its potential for broader applications. The model's capability to generate competitive pricing strategies offers opportunities for new market exploration, ensuring business growth and adaptability. © 2024 The Author(s) |
publisher |
Elsevier B.V. |
issn |
26670968 |
language |
English |
format |
Article |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809678153752248320 |