A Product Innovation Method: Considering Cultural Differences In Online Customer Reviews

In the Internet era,more and more customers express their opinions and suggestions regarding products on various social network platforms,online forums,and e-commerce websites.These unstructured comments have a huge amount of information.Through text mining,they can be turned into useful customer knowledge that not only helps customers make better purchasing decisions,but also helps manufacturers make product improvements and innovations.With the rapid development of economic globalization,increasing numbers of products are produced and sold in different countries.Therefore,it is important to understand the perceptions,needs and preferences of customers with different cultural backgrounds for imported or local products,so that manufacturers can better customize products in international markets to meet the needs of customers in different cultural contexts.Thus effectively improve customer satisfaction in the international market.The existing research focuses on the usefulness of online customer reviews and their impact on product sales,while few focuses on whether customers with different cultures may have different opinions about the same product in online customer reviews.There are also few studies using text mining techniques to explore their differences in product opinions from online reviews of different cultural customers,and to organize them into knowledge networks for product innovation.To fill the gap in the literature,firstly,based on the user innovation theory and Hofstede’s cultural dimension theory,this paper analyzes the product innovation mechanism that incorporates the cultural differences in online customer reviews,including the motivation of product innovation,product innovation framework and its connotation.Secondly,this paper proposes a product innovation method considering cultural differences in online customer reviews.This study uses web crawler technology to extract online customer reviews,then uses text mining technology based on double propagation algorithm to extract key information from online customer reviews,and build online customer review knowledge network and supernetwork.According to the knowledge network,this study establishes a product innovation model that incorporates cultural differences.Thirdly,this paper takes 4754 online customer reviews on Amazon.com and Amazon.cn as an example to verify the method proposed in this paper.In total,1933 feature-opinion pairs are analyzed.The product features that need improvement and innovation are therefore analyzed.Finally,the study also proposes some product innovation management strategies that incorporates cultural differences in online customer reviews.Companies need to fully understand the importance of cultural differences in product innovation and build product innovation knowledge system,so that companies can further expand the multicultural market,and improve customer satisfaction in the international market.