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Author: search.filters.author.Nagpal, GauravSubject: search.filters.subject.EOQ Model

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    Economic order quantity model for two generation consecutive technology products under permissible delay in payments
    (IDEAS is a RePEc, 2021) Chanda, Udayan; Nagpal, Gaurav
    In this article, we discussed optimal replenishment policies for two succeeding generations' technology products under partial trade credit financing. It is often seen that in technology market, advanced generation product plays an important role in cannibalising the market of existing generation product. Thus, precise estimation of demand of technology generations' product is critical for taking any policy decisions. Demand estimation of technology products is a complex process, as the consumer buying behaviour of technology generational products is not only depends on marketing mix variables but also associated with the time-to-market phenomenon of new technologies. In technology market, interaction among users of different generational products controls the rate of substitution of older technology products with the new one. Therefore, due to the substitution nature of demand of multi-generation product, it is important to incorporate the interaction-substitution effect in replenishment policies for this kind of products. We used life cycle dynamics to project demand rates of technology generations. In this paper, we formulate the total cost function for five different situations depending upon the new generation introduction timing and length of the trade credit period. A detail sensitivity analysis is been performed to explore the efficacy of the model in a given situation.
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    Multi-Period EOQ Model for Multi-Generation Technology Products With Short Product Life Cycles
    (ACM Digital Library, 2022-07) Chanda, Udayan; Nagpal, Gaurav; Jasti, Naga Vamsi Krishna
    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.