Abstract
AbstractUnderstanding of consumer behavior, their changing demands due to increase in social interactions and communications, adoption of latest technologies over existing products have always been a set of fundamental activities for the firms. Keeping the objective of minimum process disruptions and discouraging product proliferation, firms always endeavor to match heterogeneous demands of consumers by emphasizing on the product line. Also, with globalization, rivalry amongst firms has reached a next level. Brands are trying to capture the market by coming up with various combinations of new product mix. Amongst various attributes of product mix, product line has helped firms to attract new potential buyers to a significantly good extent. Therefore, in today’s cutthroat competitive scenario, the concept of product line provides an opportunity for a firm to provide same kind of products with some variation at an altered pricing. The objective of this study is to understand how customers behave (with so many options) and deviate from one product to another product (within and outside the brand). All the possible customers’ shifting combinations that might impact the overall sales of product are captured through the proposed model. A mathematical innovation diffusion model is developed that is motivated by the concept of Bass model and multiple generational diffusion models. This modelling framework describes the scenario of competitive brands that offer multiple products in a marketplace and observing the shifting behavior of the customers and predict the sales when product lines are available. Validation of the model has been done on real-life sales data sets for automobiles industries of two different brands i.e., Hyundai and Maruti Suzuki. The importance of this study is to deliver a solution to the manufacturers that how consumer shifts from one brand to another brand. Therefore, it is imperative for the companies to develop such a product that would lead to customers’ loyalty towards the brand.
Publisher
Springer Science and Business Media LLC
Subject
Management of Technology and Innovation,Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management
Reference61 articles.
1. Adamuthe AC, Thampi GT (2019) Technology forecasting: a case study of computational technologies. Technol Forecast Soc Chang 143:181–189
2. Aggrawal D, Agarwal M, Mittal R, Anand A (2021) Assessing the impact of negative WOM on diffusion process. Int J Syst Assur Eng Manag 1–8
3. Agarwal M, Aggrawal D, Anand A, Singh O (2017) Modeling multi-generation innovation adoption based on conjoint effect of awareness process. Int J Math Eng Manag Sci 2(2):74–84
4. Aggrawal D, Anand A, Singh O, Kapur PK (2015) Modelling successive generations for products-in-use and number of products sold in the market. Int J Oper Res 24(2):228–244
5. Anand A, Aggrawal D, Agarwal M (2019) Market assessment with OR applications. CRC Press
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