Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles

Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles

Gaurav Nagpal, Udayan Chanda, Naga Vamsi Krishna Jasti, Sachin Gupta
Copyright: © 2022 |Pages: 22
DOI: 10.4018/IJEA.306241
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Abstract

In this paper, the multi-period EOQ model is developed for the technology products that have multiple generations co-existing in the market, with each of them having a very short product life cycle. The paper first develops the framework for computation of inventory-related costs and then minimizes the total replenishment costs using random search technique and approximating the non-linear expressions while using Simpson’s Rule for integration. The paper also provides numerical illustrations and establishes a few important theorems that relate the EOQ to the innovation of diffusions. It is found that the total replenishment cost curve, drawn on the EOQ axis in the case of technology generations is convex to the origin. Since the objective function is highly non-linear, the genetic algorithm has been used to find the solution to the problem. The study also suggests that the faster diffusion of the next generations has a conflicting effect on the EOQ of the first generation in the case of pooled and non-pooled logistics.
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1. Introduction

In this age of digitalization, technology gadgets play an important role in our day-to-day life. With the invention of increasingly advanced gadgets, it becomes easy to forget what life was like before we had them. Such products with added features and functions get introduced from time to time, leading to a situation in which multiple generations of a product co-exist in the market. Often, the life cycle of these products is very short. Also due to changing consumer preferences and technology innovations, newer generations of products cannibalize the sales of the earlier generations of products at a faster rate. It has also been observed that some of the successful companies in digital gadgets not only create new products but also do not hesitate to cannibalize the existing products for the sake of a better future. For example, the employees of Apple often say that they have been told to be never afraid to eat their babies (Dormehl, L. 2019). In 2005, the demand for the Apple iPod mini was enormous. Nevertheless, Apple launched the iPod nano which brought about a substantial impact on the sales of the iPod mini. Two years later, Apple launched its smartphones that eliminated the need for a dedicated music device. Apple sees cannibalization as a huge opportunity instead of fearing it. The organization believes that it tries to avoid cannibalization, then somebody else will just cannibalize it.

A disruptive digitalization has been expedited by the Covid-19 pandemic across the sectors (De et al., 2020; Zahra, 2021). This has led to the higher sales volumes of technology products, which in turn, coupled with immense competition among the players has led to a very short product life cycle for technology products. Gone are the days when the technology products used to be electrical or mechanical devices. Today, these products are an integration of sensors, processors, memory, etc. so that they can be connected (Porter and Heppelman, 2014; Iansiti and Lakhani, 2014). Digital homes can be considered to be an example to illustrate this point (Peng et al. 2009). Also, since the products are a combination of hardware and software, they get upgraded when the new generations of software come to the market which addresses the consumer needs better. Therefore, every business needs to become a technology master over a period (Mazzone, 2014; Westerman and Bonnet, 2014; Khosla and Sharan, 2017; Sacolick, 2017; Porter and Heppelman, 2017).

In such a scenario with multiple generations of the products co-existing in the market and competing among themselves for the same market share, understanding the demand dynamics is very essential for the inventory managers and practitioners. The inventory managers have to plan the inventory replenishment norms while considering the interplay of demand for the various generations of the products. Since there is a tight linkage between demand planning and inventory management in an organization; the inventory norms, if worked out in a silo, will not result in the global optimum for the organization.

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