Development of a Model for Review Sharing in the Context of Mobile Phone Purchase Amongst Indian Millennials

Development of a Model for Review Sharing in the Context of Mobile Phone Purchase Amongst Indian Millennials

Som Sekhar Bhattacharyya (National Institute of Industrial Engineering, India), Sumi Jha (National Institute of Industrial Engineering, India), Shubham Khandelwal (National Institute of Industrial Engineering, India), Pulkit Jain (National Institute of Industrial Engineering, India) and Anshul Ekka (National Institute of Industrial Engineering, India)
Copyright: © 2021 |Pages: 20
DOI: 10.4018/IJABIM.20210401.oa9
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Online reviews provided important information towards affecting consumers' online shopping behavior. However, little research had been done in India how reviews influence young consumers' online buying behavior and review sharing. Millennials are experimental in nature and also are influenced by peers. The purpose of this research was to study the influence of online reviews on millennials' purchase behavior and study the characteristics. It was carried out in two phases in series (quantitative survey followed by qualitative interviews). The analysis was carried on primary data collected from a sample of 297 millennials with diverse backgrounds through an online survey. Factor analysis was then used in the first phase. Scale development was done to operationalize variables followed by structured equation modeling. A model on online customer reviews (OCR) sharing was developed. ANOVA was used for hypothesis testing. Qualitative findings arrived through content analysis. The research empirically attributed that reviews matter for individuals with distinguishing traits.
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1. Introduction

The modern world market has been existing because of brick and click economies (Kuan, & Bock, 2007). In the new millennium, click economy has become substantially potent in global market and online sales of goods and services has increasingly become omnipresent (Campo & Breugelmans, 2015). The sales and marketing of goods and services online have opened up new avenues of customer feedback (Duan, Gu & Whinston, 2008). Online Customer Reviews (OCR) entailed the product usage information voluntarily generated by internet users based on their personal experiences (Chen & Xie 2007). The nature of reviews (good or bad) were dependent upon the satisfaction level of the users who had been wilfully shared their experiences and commented (Somohardjo,2017). In the past customer reviews were traditionally provided through information regarding product features or services to new customers (Court, 2009). This had a significant influence on purchase decisions (Holleschovsky et al, 2016; Wang et al, 2016; Chong et al, 2015). In this era of mobile handheld interconnected devices, consumers have been exposed to substantial information (Agarwal, 2014). Customers have increased the possibility to compare the products available in the market, unlike that in the past. (Agarwal, 2014) This presence of information (online reviews), had provided customers, the opportunity to shape their buying intention and attitude towards products in purchase consideration (Javadi & Dolatabadi, 2012). Hence, customer reviews’ analysis has become a factor to be reckoned for firm’s marketing managers. This became a critical component in the new marketing communication mix. (Elwalda & Lu, 2014). Firms had been paying keen attention for product development and service offerings through customer feedbacks since the reviews were being read by a substantial audience base (Brightlocal, 2018). Thus, this has over the years emerged as a crucial factor for marketing managers to address the concerns and queries to maintain firms’ brand image (Chakraborty & Bhat, 2017). Many successful brands had been using social media platforms for sustaining and interacting with customers (Wicks, 2015).

Online Customer Reviews (OCR) had allowed users to have at an individual level information processing confidence and capability with confidence (Ahsan,2017). This high level of confidence had been influencing their buying intention and attitude towards a product, service or a brand (Lee & Ma, 2013). This has been specially so for the millennials. The reasons for the same were many. Younger population like (millennials), were believed to be more technology savvy and aware, as compared to their previous generations (like Gen X) (Smith, 2017). Millennials’ also exhibited high mobility and connectivity behaviours of millennials (Ahluwalia, 2019). Past research had also indicated that millennials have been very well connected through digital means and social media (Aluwalia,2017). Further, it has been noted that millennials also seldom hesitated in sharing their good/bad product experiences in digital media (Medallia, 2016). Finally, millennials formed a substantial section of Indian population using and generating online reviews (Morgan Stanley, 2017).Thus, it had become important to understand their behaviour towards online reviews (Bhattacharyya, 2011). This behaviour entailed three elements namely, actively reading and using the inputs of OCRs, passively just reading online reviews and finally writing and sharing online reviews (Agarwal, 2014).

It would be important to note that the Indian economy registered growth in the first decade of twenty first century along with the increasing population of youth in India (Bhattacharyya, Rangarajan & Vyas, 2012). This had made OCR analysis, very crucial for the firms in context to millennial customers in India (Raina, 2016). India was home to the largest millennial and Gen Z population scripting a promising consumer story. Millennial customers’ in India were adopting technology in a vibrant manner (Verma, & Bhattacharyya, 2016). As reported by a Boston Consulting Group study (Singhi, Sanghi, Jain, 2017), the disposable income of the middle-class population of India had also witnessed steep increase over the past few years. As reported by a Deloitte study (Talreja, Wahi, Ghosh, Marwah, & Verma, 2018), Indian customers had registered an exponential increase in spending mainly in the electronics sector. The number of phones in usage outnumbered the size of the Indian population (Statista, 2019).

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