A hybrid multiple-criteria decision-making model for podcaster selection from the perspective of Taiwanese mattress brands

Chui-Yu Chiu; Mei-Niang Tseng; Kuei-Lun Chang; Chui-Yu Chiu; Mei-Niang Tseng; Kuei-Lun Chang

doi:10.3934/math.2023318

AIMS Mathematics

2023, Volume 8, Issue 3: 6288-6308. doi: 10.3934/math.2023318

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A hybrid multiple-criteria decision-making model for podcaster selection from the perspective of Taiwanese mattress brands

1.
Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei City 106, Taiwan, ROC
2.
College of Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei City 106, Taiwan, ROC
3.
Department of New Media and Communication Administration, Ming Chuan University, 250, Sec. 5, Zhongshan N. Rd., Taipei City 111, Taiwan, ROC

Received: 16 September 2022 Revised: 05 December 2022 Accepted: 21 December 2022 Published: 03 January 2023
MSC : 03E72, 90B50, 90B60

The year 2020 has been called the first year of the podcast in Taiwan. In recent years, Taiwan's podcast industry has witnessed gradual growth in the number of listeners, as well as in programme variety. Podcast subscribers can choose their favourite content, receive new content, and can choose what they want to listen to and download it through different hosting platforms. Additionally, a growing number of companies are attempting to use podcasts to market their brands, achieve targeted brand effects, and build their customer base, especially among the lead generation. This study developed a hybrid multiple-criteria decision-making (MCDM) model to assist Taiwanese mattress brand executives in selecting podcasters to market their brands. This is a major issue that has not yet been explored in the literature. First, 12 sub-criteria (SC) were selected using the fuzzy Delphi method (FDM) and categorised to establish the hierarchical structure. Then, a combination of decision making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and technique for order preference by similarity to ideal solution (TOPSIS) was adopted to assist the case company's executives in selecting the best podcaster. The integrated operations performed in this study are logically coherent, practical, and functional. This hybrid MCDM model allows companies and decision-makers to make objective, efficient, and accurate decisions.
- ANP,
- DEMATEL,
- FDM,
- podcaster,
- TOPSIS
Citation: Chui-Yu Chiu, Mei-Niang Tseng, Kuei-Lun Chang. A hybrid multiple-criteria decision-making model for podcaster selection from the perspective of Taiwanese mattress brands[J]. AIMS Mathematics, 2023, 8(3): 6288-6308. doi: 10.3934/math.2023318

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Abstract

The year 2020 has been called the first year of the podcast in Taiwan. In recent years, Taiwan's podcast industry has witnessed gradual growth in the number of listeners, as well as in programme variety. Podcast subscribers can choose their favourite content, receive new content, and can choose what they want to listen to and download it through different hosting platforms. Additionally, a growing number of companies are attempting to use podcasts to market their brands, achieve targeted brand effects, and build their customer base, especially among the lead generation. This study developed a hybrid multiple-criteria decision-making (MCDM) model to assist Taiwanese mattress brand executives in selecting podcasters to market their brands. This is a major issue that has not yet been explored in the literature. First, 12 sub-criteria (SC) were selected using the fuzzy Delphi method (FDM) and categorised to establish the hierarchical structure. Then, a combination of decision making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and technique for order preference by similarity to ideal solution (TOPSIS) was adopted to assist the case company's executives in selecting the best podcaster. The integrated operations performed in this study are logically coherent, practical, and functional. This hybrid MCDM model allows companies and decision-makers to make objective, efficient, and accurate decisions.

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