Rationalizing the Costs of Short Life-Cycle Products in a Dynamic Business Environment Using Artificial Intelligence Forecasting Techniques and Dynamic Quality Function Deployment – Empirical Study | ||||
| المجلة الدولية للبحوث الإدارية و الاقتصادية | ||||
| Volume 1, Issue 1, September 2024, Page 302-354 PDF (823.62 K) | ||||
| Document Type: المقالة الأصلية | ||||
| DOI: 10.21608/ijade.2024.314418.1025 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
محمود زين  1; إسراء ابو دهب2
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| 1كلية إدارة الأعمال - جامعة النهضة | ||||
| 2كلية ادارة الاعمال - جامعة النهضة | ||||
| Abstract | ||||
| The life-cycle of the products doesn’t have the same length in all types of products but there are some long term and medium term products. Due to the rapid growth and the quick innovation of the industry, the life-cycle of some products have been shortened resulting what’s known as “The short life-cycle products”. The short life-cycle products are those products with a life-cycle between three months and one year, mostly are the fashion based and technology based products. In order to reach the desired cost rationalization, the organization should focus only on eliminating or minimizing the waste as any arbitrary cutting of the costs would result a declining in the quality of the products. It was proposed by this paper to use the dynamic quality function deployment which relies on designing the products according to specific attributes and costs which is doable in case of having an accurate insight in the whole cost structure of the entire value chain of the product. A matter like that requires a huge amount of data to be collected which is only applicable using AI tools. As the SLCPs have a unique nature which limits the organization ability to collect historical data of these products due to its novelty, the demand of these products is very much uncertain, a matter which hinders any cost rationalization attempt. Accordingly, it was proposed to use the machine learning technique as an AI predictive tool that supports both demand and cost estimation of these newly introduced products. | ||||
| Keywords | ||||
| Cost rationalization- Short life-cycle products-Artificial intelligence (AI); -Dynamic quality function deployment (DQFD); Forecasting techniques; -Demand Enhancement- | ||||
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