Decision-making model for designing telecom products/services based on customer preferences and non-preferences
The design of the packages of products/services to be offered by a telecom company to its clients is a complex decision-making process that must consider different criteria to achieve both customer satisfaction and optimization of the company’s resources. In this process, Intuitionistic Fuzzy Sets...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Vilnius Gediminas Technical University
2022-10-01
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| Series: | Technological and Economic Development of Economy |
| Subjects: | |
| Online Access: | https://jcem.vgtu.lt/index.php/TEDE/article/view/17734 |
| Summary: | The design of the packages of products/services to be offered by a telecom company to its clients is a complex decision-making process that must consider different criteria to achieve both customer satisfaction and optimization of the company’s resources. In this process, Intuitionistic Fuzzy Sets (IFSs) can be used to manage uncertainty and better represent both preferences and non-preferences expressed by people who value each proposed alternative. We present a novel approach to design/develop new products/services that combines the Lean Six Sigma methodology with IFSs. Its main contribution comes from considering both preferences and nonpreferences expressed by real clients, whereas existing proposals only consider their preferences. By also considering their non-preferences, it provides an additional capacity to manage the high uncertainty in the selection of the commercial plan that best suits each client’s needs. Thus, client satisfaction is increased while improving the company’s corporate image, which will lead to customer loyalty and increased revenue. To validate the presented proposal, it has been applied to a real case study of the telecom sector, in which 2135 users have participated. The results obtained have been analysed and compared with those obtained with a model that does not consider the non-preferences expressed by users.
First published online 27 October 2022
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| ISSN: | 2029-4913 2029-4921 |