Big Data Analysis and Data Mining

Branding has been emerged as a competetive strategy in the recent times. There are two dominant theories regarding the evaluation of a brand’s value; the first is costumer-based, and the second is financial-based. The customer-based viewpoint belongs to the marketing and behaviorists, while the financial-based point of view is related to financial data and involves the hard aspect of the issue. In the second approach, Tobin’s Q index has been used as brand value since the early 1990s. Using a financial-based approach in automobile industry of Tehran stock exchange, applying a real data set, this paper makes an effort to identify the brand value and the financial factors that affect it. By reviewing the literature, templates, and the results of previous researches, we used data mining methods as a proper means. Decision tree techniques used to investigate the severity of factors. The results of C-5 decision tree method indicate that the brand’s age positively affects the brand value at a rate of 84%. Also, Quest Tree method indicates that the brand’s age positively affects the brand value at the similar rate. Hence, it is confirmed that the brand age positively affects its brand value. Moreover, according to the another hypothesis related to the effectiveness of market share, Quest Tree and C-5 results also show that the market share positively affects brand value at a rate of 16%. The results of Quest Tree and C-5 were same in this case too. However, due to the data mininig used methods, the expenses related to the marketing and research and development do not affect the brand value.