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The Study of Purchase Intention for Men's Facial Care Products with K-Nearest Neighbour


Affiliations
1 Yango College, Fuzhou, 350015, China
2 Department of Business Management, National Kaohsiung Normal University, Kaohsiung, 80201, Taiwan, Province of China
3 Institute of Human Resource Management, National Sun Yat-Sen University, Taiwan, Province of China
 

Inventory management was a major issue for all the industries. The supplied of products to customers required the readiness of the inventory. This allowed rapid delivery and reduced waiting time for customers so that companies could profit from it. Any stock out or insufficiency would lead to loss of customers because their needs cannot be met. This would hurt firm profitability and market competitiveness. Inventory control was critical to retain liquidity and avoid overstocking. This was also the key to firm's survival and sustainability. To ensure an appropriate level of inventory, it was necessary to manage the inventory levels with sales forecast on an on-going basis. This paper tried to find out its inventory control in order to assisted Company T to improve its inventory control. Firstly, the products offered by Company T are classified into groups. The R programming language was then used to stimulate and forecast future sales of different products. Different techniques were applied to manage the inventory levels according to the results of categorizations and forecasts.; 3.Consolidation of all the product items and grouping them into activity-based classifications; 4.Simulation and forecasting of future sales according to the categorization results; 5. Formulation of different controlled techniques based on the simulations and forecasts, and application of these methods to inventory management.

Keywords

Improvement of Inventory Control, Forecast, Activity-Based Classification.
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  • G.M., ullet, and M., arson,, Analysis of Purchase Intent Scales Weight by Probability of Actual Purchase, Journal of Marketing Research, 22(1), 93-96.1985.
  • P. Kolter, , Marketing Management: Analysis, Planning, Implementation, & Control Englewood Cliffs, Prentice-Hall, Inc.: N. J.1991
  • L. G., Schiffman, andL. L., Kanuk, , Consumer Behavior Upper Saddle River, New Jersey PrentHall.2000.
  • Resul D.and T.C. Ibrahim, meaningful data from web logs for improving the impressiveness of a website by using path analysis method[J]Expert Systems with Applications, 36 (3), pp. 6635-6644. 2009.
  • H. Jiawei, and K. Micheline, Data Mining Concept and Techniques(2nd), Morgan Kaufmann Publishers, 285–350, 2006.
  • Lantz, B., Machine Learning with R, Packt Publishing Ltd.2013)
  • Agrawal, R. et al, Mining Association Rules between Sets of Items in Large Databases, Proceedings of the ACM SIGMOD Conference on Management of Data, 207–216.1993.
  • Chiang, H.J., Tseng, C.C., and Tomg, C.C, A Retrospective Analysis of Prognostic Indicators in Dental Implant Therapy Using The C5.0 Decision Tree Algorithm, Journal of Dental Sciences, 8, 248-255.2013.
  • F. Chen, et al, , Principal Association Mining: An Efficient Classification Approach, KnowledgeBased Systems, 67, 16-25.2014.
  • W.Y. Liu, et al, On Gender Differences in Consumer Behavior for Online Financial Transaction of Cosmetics, Mathematical and Computer Modelling, 58, 238-253.2013
  • D.A., Adeniyi, Z.Wei,, and Y.Yongquan, Automated Web Usage Data Mining and Recommendation System Using K-Nearest Neighbor (KNN) Classification method,Applied Computing and Informatics, 12, 90-108.2015
  • Aghekyan-Simonian, M. et al, The Role of Product Brand , 2012.

Abstract Views: 216

PDF Views: 139




  • The Study of Purchase Intention for Men's Facial Care Products with K-Nearest Neighbour

Abstract Views: 216  |  PDF Views: 139

Authors

Jui-Chan Huang
Yango College, Fuzhou, 350015, China
Pei-Yu Shao
Department of Business Management, National Kaohsiung Normal University, Kaohsiung, 80201, Taiwan, Province of China
Tzu-Jung Wu
Institute of Human Resource Management, National Sun Yat-Sen University, Taiwan, Province of China

Abstract


Inventory management was a major issue for all the industries. The supplied of products to customers required the readiness of the inventory. This allowed rapid delivery and reduced waiting time for customers so that companies could profit from it. Any stock out or insufficiency would lead to loss of customers because their needs cannot be met. This would hurt firm profitability and market competitiveness. Inventory control was critical to retain liquidity and avoid overstocking. This was also the key to firm's survival and sustainability. To ensure an appropriate level of inventory, it was necessary to manage the inventory levels with sales forecast on an on-going basis. This paper tried to find out its inventory control in order to assisted Company T to improve its inventory control. Firstly, the products offered by Company T are classified into groups. The R programming language was then used to stimulate and forecast future sales of different products. Different techniques were applied to manage the inventory levels according to the results of categorizations and forecasts.; 3.Consolidation of all the product items and grouping them into activity-based classifications; 4.Simulation and forecasting of future sales according to the categorization results; 5. Formulation of different controlled techniques based on the simulations and forecasts, and application of these methods to inventory management.

Keywords


Improvement of Inventory Control, Forecast, Activity-Based Classification.

References