Abstract
Product bundling is a widespread practice in the current e-commerce environment. However, there are few investigations about bundled commodities mining. Because no efficient method of product bundling is currently available, an expert selection of appropriate product bundling is a complex process. This is time-consuming and cannot efficiently meet the enterprise's need. It is essential for a company to develop product bundling based on analyzing the related information that fits different requirements and maximizes the benefit. This study proposes a method of incorporating GA and rough set theory. The superiority of the proposed GA is its ability to model problems and explore solutions generically. The proposed method improves GA performance by reducing the domain range of the initial population and constrained crossover using rough set theory. The experimental results in this study confirm that this approach is highly effective and very promising.
| Original language | English |
|---|---|
| Pages (from-to) | 393-410 |
| Number of pages | 18 |
| Journal | International Journal of Information and Management Sciences |
| Volume | 26 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2015 Dec |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Management Information Systems
- Strategy and Management
- Industrial and Manufacturing Engineering
- Information Systems and Management
Cite this
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Product bundling in the electronic commerce environment : A hybrid approach. / Liang, Wen Yau; Huang, Chun Che.
In: International Journal of Information and Management Sciences, Vol. 26, No. 4, 12.2015, p. 393-410.Research output: Contribution to journal › Article
TY - JOUR
T1 - Product bundling in the electronic commerce environment
T2 - A hybrid approach
AU - Liang, Wen Yau
AU - Huang, Chun Che
PY - 2015/12
Y1 - 2015/12
N2 - Product bundling is a widespread practice in the current e-commerce environment. However, there are few investigations about bundled commodities mining. Because no efficient method of product bundling is currently available, an expert selection of appropriate product bundling is a complex process. This is time-consuming and cannot efficiently meet the enterprise's need. It is essential for a company to develop product bundling based on analyzing the related information that fits different requirements and maximizes the benefit. This study proposes a method of incorporating GA and rough set theory. The superiority of the proposed GA is its ability to model problems and explore solutions generically. The proposed method improves GA performance by reducing the domain range of the initial population and constrained crossover using rough set theory. The experimental results in this study confirm that this approach is highly effective and very promising.
AB - Product bundling is a widespread practice in the current e-commerce environment. However, there are few investigations about bundled commodities mining. Because no efficient method of product bundling is currently available, an expert selection of appropriate product bundling is a complex process. This is time-consuming and cannot efficiently meet the enterprise's need. It is essential for a company to develop product bundling based on analyzing the related information that fits different requirements and maximizes the benefit. This study proposes a method of incorporating GA and rough set theory. The superiority of the proposed GA is its ability to model problems and explore solutions generically. The proposed method improves GA performance by reducing the domain range of the initial population and constrained crossover using rough set theory. The experimental results in this study confirm that this approach is highly effective and very promising.
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UR - http://www.scopus.com/inward/citedby.url?scp=84964781229&partnerID=8YFLogxK
U2 - 10.6186/IJIMS.2015.26.4.5
DO - 10.6186/IJIMS.2015.26.4.5
M3 - Article
AN - SCOPUS:84964781229
VL - 26
SP - 393
EP - 410
JO - International Journal of Information and Management Sciences
JF - International Journal of Information and Management Sciences
SN - 1017-1819
IS - 4
ER -