Inventory Replenishment Policies for Two Successive Generations of Technology Products Under Permissible Delay in Payments

Inventory Replenishment Policies for Two Successive Generations of Technology Products Under Permissible Delay in Payments

Gaurav Nagpal, Udayan Chanda, Himanshu Seth, Namita Ruparel
DOI: 10.4018/IJISSCM.287134
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Abstract

In this age of digitalization, when every industry is undergoing technological disruption, there is a big role of digital gadgets and technology products. A key feature of these digital gadgets is the short length of the product life cycle, since the newer and more advanced generations of technologies are developed regularly to replace the earlier conventional technologies. The traditional EOQ models that assume a constant demand cannot be used here. This research paper formulates an inventory optimization model for the multi-generational products under the trade credits and the credit-linked and innovation diffusion dependent demand. The study also performs a numerical illustration of the proposed model, and establishes important dynamics among the key variables. It also performs the sensitivity analysis with the cost of credit and the trade credit period. The paper concludes with the managerial implications for the inventory practitioners and the possible areas of extension for this research in the future.
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1. Introduction

The past few decades have witnessed fast growth in the penetration of technology products such as smartphones, smart wearables, portable devices, etc. These products have a very short product life cycle amid the changing consumer preferences and competitor dynamics. As a result, these products, within their respective categories, are substitutable since they perform the same intended function as the other products in the category.

The product variety in each of these categories is also increasing at a fast rate. The firms that manufacture the technology products are not afraid of launching the newer generations for the fear of cannibalization of existing products. Rather, they believe that cannibalizing their existing products by themselves is better than that by their competitors. Therefore, they are in the constant pursuit of identifying the stated and implied needs of the consumer, and anticipating the changing consumer preferences to incorporate the suitable features and functions to the products that can bring more value to the consumer. A few examples of the technology giants that have grown immensely during the past decades by embracing self-cannibalization are Google, Apple, Amazon, and Facebook. These companies have been proactive in replacing the existing products with newer products that are worth more in terms of functionality, form, or features. Netflix is another example of such a firm since it switched its business from selling DVDs to streaming media services that can be used on all the devices (Littleton & Roettgers, 2018). Some of the firms also track the metrics that mandate a certain percentage of their revenues to come from the newer range of products. For example, 3M has a rule that thirty percent of its revenues in any year have to come from the products launched in the last four years, a metric that it monitors rigorously (Govindarajan & Srinivas, 2013).

Thus, we can say that the technologies are at the constant risk of being outflanked. And therefore, the technology firms have to work with two faces, like the Roman god “Janus”, one face looking inward for sustaining incremental innovations in the existing products, and the other face looking outward for the disruptive business innovations. Knowing when the new technology will take off is very important for the firms not to miss upon the opportunity, and not to deplete their resources even before the take-off starts.

1.1. Diffusion of Innovations

The demand for technology products follows the process of innovation diffusion process (Rogers, 1971) The theory of diffusion of innovations said that the adoption of the new products follows a bell-shaped distribution over time and that the innovativeness of a customer influences his adoption timing of a product. To further add to this complexity of a highly non-linear demand pattern, multiple products are co-existing at the same time in the market. These different generations of products have an inter-play among themselves to influence the demand pattern which creates further stress for the supply chain. This type of substitution in which the consumers switch to another product due to its technological superiority is called technological substitution. Hung and Lai (2012) highlighted the non-linear behavior of demand when the older technologies are replaced by the newer ones.

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