Family Communication Patterns and Influence of Children in Family Purchase Decisions

Family Communication Patterns and Influence of Children in Family Purchase Decisions

Shefali, Vijita Singh Aggarwal
Copyright: © 2019 |Pages: 20
DOI: 10.4018/IJABIM.2019100101
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Abstract

This article revolves around the validation of family communication pattern scale along with its subsequent influence on child influence in family purchase decisions. The perceptions of parents of 6-12 years old children in Delhi NCR were taken into consideration to carry out research. Both primary and secondary studies were conducted to complete the research process. Exploratory factor analysis and confirmatory factor analysis were used to validate family communication patterns scale and multiple linear regression was used to find the influence of family communication patterns on children influence in purchase decisions across product categories. The findings resulted in four factors of family communication patterns with an excellent fit. Also, there was a significant influence of family communication patterns on children influence on child goods and services and not on family-related goods.
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Introduction

India is one of the fastest growing consumer markets. It is touted to become the third largest consumer market by 2025, as the projected consumption is expected to rise to $4 trillion (Singhi et al., 2017). The primary reason behind this is shifting of consumers' aspirations and spending patterns in India. With the rise in digital exposure and its consumption and influence, changing family structure, expanding gender roles especially of women, and dual working parents—the involvement of family members in purchase-related decisions has increased manifold. Generation gap has reduced and is still reducing in families, thereby parents are getting closer to their children than they were in the earlier times, in lieu of the age gap before. A change in their relationship dynamics is noticed, with parents starting to pay attention to the opinions of their children. Owing to many factors like the changing face of the aforementioned family dynamics, time shortage, limited family support structures, etc.—children face decision making at a very young age. Children hold various roles and responsibilities in the family purchase decision-making process, but that role in purchase related matters may vary. This is because of differences in the consumer socialization of children, pertaining to them as a consumer and in their consumption process of the product/service (McNeal, 1992).

“Consumer socialization is the process by which young people acquire skills, knowledge, and attitudes relevant to their functioning as consumers in the market place” (Ward, 1974). Family communication about consumption is an essential variable of consumer socialization. It is the communication between family members on matters related to consumption. Traditional manner of family communication involved the process of learning by younger family members from elders about various things, contextually about purchase and consumption. But this view has been challenged with the advent of technology and in the modern scenario with the change in dynamics of family structure. In this contemporary environment, reciprocal consumer socialization is followed in families, wherein younger family members also educate older ones during communication with each other (Watne et al., 2014; Watne and Brennan, 2011). Yet different scales are used to measure family communication in such purchase related matters. Scales are deemed to be accurate when they have invariance across researchers, time, settings, and participants (Levine et al., 2006). Although many researchers have developed scales for measuring invariance, however these validated measures cannot be generalized to other populations than those they were measured on (Byrne and Watkins, 2003; Wichert et al., 2005). This is justified by the finding that—little modifications in the statement of an item of the questionnaire can lead to more significant changes in the model fit of the research project (Levine et al., 2006).

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