سیاست های موجودی بهینه برای نسل های متوالی از یک محصول با فن آوری بالا
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|43053||2014||15 صفحه PDF||سفارش دهید||6750 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : The Journal of High Technology Management Research, Volume 25, Issue 2, 2014, Pages 148–162
In today's era of globalization, periodically new products with better value and added features are introduced into the market. The rapid technological breakthroughs are creating significant risks of obsolescence at the product level. It creates enormous challenges to coordinate between technology management and inventory control policies. Due to the dynamic nature of the market, it becomes essential to integrate technological substitution along with diffusion of new products while formulating economic ordering policies for technological products. The literature of estimating and forecasting innovation diffusion patterns for technology product is fairly rich. In recent years these models were applied extensively to derive economic order policies under different economic situations. Unfortunately study on impact of technology substitution on economic order policies is still scarce. The proposed model acknowledged the relationship between substitution rates of product categories and the inventory policies. In this paper an attempt has been made to generate economic inventory policies for technology products under the condition of its diminishing demand. The model is based on the assumption that technological advancements do not essentially imply that existing generation products will be withdrawn from the market immediately. The results are very encouraging and the findings are consistent with the idea that optimal EOQ policies are highly receptive towards the dynamics of the product substitutions and hence it is imperative to identify the trend. A simple solution procedure in the form of algorithm is presented to determine the optimal cycle time and optimal order quantity using the cost function.