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Top1. Introduction
Emerging economies are potential target markets for new product launches as they have a young population with rising disposable incomes and quick technology adoption (Kardes 2016). With internet penetration increasing at a rapid pace in these economies, companies have been quick to launch products based on IoT (Internet of Things), smart devices, e-commerce platforms, and digital technologies. In December 2018, India had 566 million internet users, which was expected to increase to 627 million users by December 2019 (ET 2019). This has resulted in the launch of several innovative and technology-based products, such as SSs. In 2017–18, Amazon and Google introduced Alexa and Google Home, the SSs for the Indian market. Effective ways are required by organizations to predict the penetration rate of innovative products to estimate their viability and to generate techniques to enhance their promotion along with augmenting their take rates. Conversely, in the diffusion process, the market potential should be established earlier by the organizations. According to a report, 74.2 million users in the USA had SSs (26% of internet users) in 2019 (eMarketer 2019). In comparison, 753,000 units of SSs were imported to India in 2018, which represents 20.7% of English-speaking households having internet access (IDC and Forbes, 2018). It was estimated that the SS market worldwide was $4.3 billion in 2017 and was expected to grow by 23.5% CAGR to reach $23.3 billion by 2025 (Allied Market research 2019). In India, Amazon's Alexa is the market leader with a 51% market share, followed by Google Home at 36%, and the remaining players constitute the remaining 13% of the market.
A Smart Speaker is a smart virtual assistant comprising speakers and microphones, along with interfaces, which are enabled by voice command. SS takes advantage of Artificial Intelligence (AI) together with Natural Language Processing (NLP) to recognize voice commands and process them with correctness. SSs are emerging with the incorporation of extra skills and options to attract innovators and early adopters in the coming years. Given the expected rise in product sales in the coming years, an estimation of SS diffusion in India is required to predict the purchase. A correct analysis of sales volume is also essential as it permits the firms to appropriate resources accordingly (Tseng 2008). It becomes very crucial to determine the sales accurately since many products are imported from foreign countries to local markets; thus, the window of opportunity to gain the first-mover advantage could be limited (Frynas et al., 2006). Therefore, organizations heavily depend on understanding technology diffusion in a particular market and employ forecasting techniques to predict demand and deploy suitable marketing strategies. A new product sales forecast depends upon the product's speed of diffusion and the potential of the target market. The return on investments can be estimated using these two variables, thereby helping the company design a pricing and investment strategy. Several well-known models exist that have become popular for assessing diffusion, viz., BM (1969) and Logistic Model (1961). However, there is a significant challenge in adopting these models; the demand forecast for the new products is based on historical sales. To estimate the parameters in diffusion models, at least 6–10 years of data is required, which is difficult to get in the case of new products (Tseng, 2008). To overcome this problem, the authors suggest that sales data of analogous products can be used to estimate the sales (Lee et al., 2008; Jun et al., 2000; Bayus, 1993).