A method for the competitiveness estimation of the incremental new product through user-generated content

The current dynamic market environment challenges successful incremental new product (INP) launches, compelling enterprise managers to promptly recognize and respond to competitive situations. Estimating INP competitiveness before sale helps enterprise managers adjust their strategies effectively and in a timely manner to ensure successful INP launches. However, a lack of historical evaluation information challenges the estimation. Given that INPs are updates of existing products, massive user-generated content (UGC) regarding existing products and the new product launch provides an appropriate data source for estimating INPs' competitiveness. Therefore, this study proposes a method for estimating the competitiveness of INP using UGC. First, the INP product attributes are classified as non-updated or updated. For the former, existing products containing the same attribute values are used as references, and their reference values are measured based on the time and price of the first sale. UGC regarding the launch of INPs serves as a data source for the latter. Sentiment analysis is performed on the UGC concerning product attributes to obtain the sentiment tendency and sentiment intensity for constructing an intuitive fuzzy number, which represents INP's attribute performance. INP's product performance is estimated by considering attribute weights determined by customer attention. INP's competitiveness in the market environment is then estimated by comparing its product performance with that of competing products. Finally, the proposed method is applied to a mobile phone, and its effectiveness and applicability are verified. •Propose a method to estimate the competitiveness of INP before the sale through UGC.•Design an algorithm to measure reference degree of existing products to INP.•Propose a method to construct the IFN by combining sentiment tendency and intensity.