Abstract:
"Predictive analytics is gleaned from predictive modelling which encompasses several statistical tools and methodologies which incorporates machine learning algorithms which is used in prediction of future results based on past and current data.
As a result of extreme nature of competition in market, creation and development of brand equity has become a crucial derivation of differentiation. In terms of the past few decades brand equity has evolved itself recognising as a key factor for marketers as well as enterprises to enhance its profitability. Literature involves an extensive understanding of the consumer brand relationship and greater analysis on the components of brand equity and its influence on purchase intention.
Regardless of the studies that was conducted, the studies on predictive analysis on the purchasing intention based on brand equity of the Y and Z generation in relation to Sri Lankan apparel brands is not much in existence.
This is research was developed on such predictive analysis to identify and the components of brand equity that affects the consumer intention in relation to local apparel brands and to ascertain the relationship between Sri Lankan Y and Z generation consumers’ brand equity and the purchase intention of the local apparel brands and finally to develop a predictive model using multiple machine learning techniques. The optimal model is chosen after extensive assessment of all the models developed using machine learning techniques where Random Forest was identified as such.
The findings of this study were based on a questionnaire, delivered to respondents in an electronic platform from which 261 feedbacks were gathered from the consumers of Y and Z generation in the context of local apparel brands from Colombo District, Sri Lanka.
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