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Analyzing Consumption Behaviors of Pet Owners in a Veterinary Hospital

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Data Mining and Big Data (DMBD 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10387))

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Abstract

The purpose of this study is to identify different consumption behaviors of pet owners in a veterinary hospital so as to provide proper marketing strategies. A case study was conducted by combining data mining techniques and RFM model for a veterinary hospital located in Taichung City, Taiwan by examining its transactions data focusing on pet mice in 2014. The development of marketing strategies for the veterinary hospital is important to improve its service quality and strengthen the positive relationship between the pet owners and the case veterinary hospital.

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Author information

Authors and Affiliations

  1. International Business Department, Providence University, Taichung City, Taiwan

    Jo Ting Wei

  2. Department of Tourism, Leisure and Hospitality Management, National Chi Nan University, Nantou, Taiwan

    Shih-Yen Lin

  3. Department of Business Administration, National Changhua University of Education, Changhua, Taiwan

    You-Zhen Yang & Hsin-Hung Wu

Authors
  1. Jo Ting Wei
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  2. Shih-Yen Lin
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  3. You-Zhen Yang
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  4. Hsin-Hung Wu
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Corresponding author

Correspondence to Hsin-Hung Wu .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  3. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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© 2017 Springer International Publishing AG

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Wei, J.T., Lin, SY., Yang, YZ., Wu, HH. (2017). Analyzing Consumption Behaviors of Pet Owners in a Veterinary Hospital. In: Tan, Y., Takagi, H., Shi, Y. (eds) Data Mining and Big Data. DMBD 2017. Lecture Notes in Computer Science(), vol 10387. Springer, Cham. https://doi.org/10.1007/978-3-319-61845-6_18

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  • DOI: https://doi.org/10.1007/978-3-319-61845-6_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61844-9

  • Online ISBN: 978-3-319-61845-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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