Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive

Hui-Hsin Huang

doi:doi:10.11648/j.ajdmkd.20190401.18

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Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive

Hui-Hsin Huang

Published in American Journal of Data Mining and Knowledge Discovery (Volume 4, Issue 1)

Received: 17 April 2019 Accepted: 31 May 2019 Published: 24 June 2019

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Abstract

In the rapidly changing market, there is a never-ending sequence of marketing actions and competitive reactions. Customer may consume much volume to stockpile more than they need when the price promotion or some benefit that retail gives. Thus this paper explores the customer purchase rate, the speed of product consumption and the inactive probability with extending queue model. A real data set from the customer purchase behavior in two electronic business retailers website includes purchase volume, the duration of customer consumption (which is the interpurchase time between purchase behavior with the same product in the same brand) and the duration of variety-seeking (which is defined as customer purchase the same categories but different brand of product) to estimate the parameters and calculate the expectation value of product consumption and product stockpile volume. This result can make application for other industries such as e-commerce.

Published in	American Journal of Data Mining and Knowledge Discovery (Volume 4, Issue 1)
DOI	10.11648/j.ajdmkd.20190401.18
Page(s)	53-56
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Queue, Purchase Rate, The Speed of Product Consumption, Inactive Probability

References

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[5]	Lismont, J., Ram, S., Vanthienen, J., Lemahieu, W. and Baesens, B. (2018) Predicting interpurchase time in a retail environment using customer-product networks: An empirical study and evaluation. Expert Systems with Applications104 (15) 22-32.
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[7]	Igari, R. amd Hoshino, T. (2018) A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing. Computational Statistics & Data Analysis 126, 150-166.
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[9]	Schweidel, A. D., Park, Y. H. and Zainab, J. (2014) A Multiactivity Latent Attrition Model for Customer Base Analysis. Marketing Science 33 (2) 273-286.
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[14]	Hyewook, G. J. and Aimee, D. (2016) Variety-seeking as an emotional coping strategy for chronically indecisive consumers. Marketing Letters 27 (1) 55-62.
[15]	Huang, Z., Liang, Y., Weinberg, B. C. and Gorn, J. G. (2019) The Sleepy Consumer and Variety Seeking. Journal of Marketing Research 56 (2) 1-18.
[16]	Niu, B., Chen, L., Liu, Y. and Jin, Y. (2019) Joint price and quality decisions considering Chinese customers' variety seeking behavior. International Journal of Production Economics 213 97-107.

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APA Style

Hui-Hsin Huang. (2019). Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive. American Journal of Data Mining and Knowledge Discovery, 4(1), 53-56. https://doi.org/10.11648/j.ajdmkd.20190401.18

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ACS Style

Hui-Hsin Huang. Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive. Am. J. Data Min. Knowl. Discov. 2019, 4(1), 53-56. doi: 10.11648/j.ajdmkd.20190401.18

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AMA Style

Hui-Hsin Huang. Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive. Am J Data Min Knowl Discov. 2019;4(1):53-56. doi: 10.11648/j.ajdmkd.20190401.18

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@article{10.11648/j.ajdmkd.20190401.18,
  author = {Hui-Hsin Huang},
  title = {Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive},
  journal = {American Journal of Data Mining and Knowledge Discovery},
  volume = {4},
  number = {1},
  pages = {53-56},
  doi = {10.11648/j.ajdmkd.20190401.18},
  url = {https://doi.org/10.11648/j.ajdmkd.20190401.18},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajdmkd.20190401.18},
  abstract = {In the rapidly changing market, there is a never-ending sequence of marketing actions and competitive reactions. Customer may consume much volume to stockpile more than they need when the price promotion or some benefit that retail gives. Thus this paper explores the customer purchase rate, the speed of product consumption and the inactive probability with extending queue model. A real data set from the customer purchase behavior in two electronic business retailers website includes purchase volume, the duration of customer consumption (which is the interpurchase time between purchase behavior with the same product in the same brand) and the duration of variety-seeking (which is defined as customer purchase the same categories but different brand of product) to estimate the parameters and calculate the expectation value of product consumption and product stockpile volume. This result can make application for other industries such as e-commerce.},
 year = {2019}
}

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TY  - JOUR
T1  - Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive
AU  - Hui-Hsin Huang
Y1  - 2019/06/24
PY  - 2019
N1  - https://doi.org/10.11648/j.ajdmkd.20190401.18
DO  - 10.11648/j.ajdmkd.20190401.18
T2  - American Journal of Data Mining and Knowledge Discovery
JF  - American Journal of Data Mining and Knowledge Discovery
JO  - American Journal of Data Mining and Knowledge Discovery
SP  - 53
EP  - 56
PB  - Science Publishing Group
SN  - 2578-7837
UR  - https://doi.org/10.11648/j.ajdmkd.20190401.18
AB  - In the rapidly changing market, there is a never-ending sequence of marketing actions and competitive reactions. Customer may consume much volume to stockpile more than they need when the price promotion or some benefit that retail gives. Thus this paper explores the customer purchase rate, the speed of product consumption and the inactive probability with extending queue model. A real data set from the customer purchase behavior in two electronic business retailers website includes purchase volume, the duration of customer consumption (which is the interpurchase time between purchase behavior with the same product in the same brand) and the duration of variety-seeking (which is defined as customer purchase the same categories but different brand of product) to estimate the parameters and calculate the expectation value of product consumption and product stockpile volume. This result can make application for other industries such as e-commerce.
VL  - 4
IS  - 1
ER  -

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Author Information

Hui-Hsin Huang

Department of Business Administration, Aletheia University, New Taipei City, Taiwan

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APA Style

Hui-Hsin Huang. (2019). Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive. American Journal of Data Mining and Knowledge Discovery, 4(1), 53-56. https://doi.org/10.11648/j.ajdmkd.20190401.18

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ACS Style

Hui-Hsin Huang. Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive. Am. J. Data Min. Knowl. Discov. 2019, 4(1), 53-56. doi: 10.11648/j.ajdmkd.20190401.18

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AMA Style

Hui-Hsin Huang. Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive. Am J Data Min Knowl Discov. 2019;4(1):53-56. doi: 10.11648/j.ajdmkd.20190401.18

Copy | Download

@article{10.11648/j.ajdmkd.20190401.18,
  author = {Hui-Hsin Huang},
  title = {Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive},
  journal = {American Journal of Data Mining and Knowledge Discovery},
  volume = {4},
  number = {1},
  pages = {53-56},
  doi = {10.11648/j.ajdmkd.20190401.18},
  url = {https://doi.org/10.11648/j.ajdmkd.20190401.18},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajdmkd.20190401.18},
  abstract = {In the rapidly changing market, there is a never-ending sequence of marketing actions and competitive reactions. Customer may consume much volume to stockpile more than they need when the price promotion or some benefit that retail gives. Thus this paper explores the customer purchase rate, the speed of product consumption and the inactive probability with extending queue model. A real data set from the customer purchase behavior in two electronic business retailers website includes purchase volume, the duration of customer consumption (which is the interpurchase time between purchase behavior with the same product in the same brand) and the duration of variety-seeking (which is defined as customer purchase the same categories but different brand of product) to estimate the parameters and calculate the expectation value of product consumption and product stockpile volume. This result can make application for other industries such as e-commerce.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Extending the Queue Question to Customer Purchase Rate to Predict the Probability of Customer Inactive
AU  - Hui-Hsin Huang
Y1  - 2019/06/24
PY  - 2019
N1  - https://doi.org/10.11648/j.ajdmkd.20190401.18
DO  - 10.11648/j.ajdmkd.20190401.18
T2  - American Journal of Data Mining and Knowledge Discovery
JF  - American Journal of Data Mining and Knowledge Discovery
JO  - American Journal of Data Mining and Knowledge Discovery
SP  - 53
EP  - 56
PB  - Science Publishing Group
SN  - 2578-7837
UR  - https://doi.org/10.11648/j.ajdmkd.20190401.18
AB  - In the rapidly changing market, there is a never-ending sequence of marketing actions and competitive reactions. Customer may consume much volume to stockpile more than they need when the price promotion or some benefit that retail gives. Thus this paper explores the customer purchase rate, the speed of product consumption and the inactive probability with extending queue model. A real data set from the customer purchase behavior in two electronic business retailers website includes purchase volume, the duration of customer consumption (which is the interpurchase time between purchase behavior with the same product in the same brand) and the duration of variety-seeking (which is defined as customer purchase the same categories but different brand of product) to estimate the parameters and calculate the expectation value of product consumption and product stockpile volume. This result can make application for other industries such as e-commerce.
VL  - 4
IS  - 1
ER  -

Copy | Download