Does User Feedback Matter for Product Development?

Author:

Lenger Aslı Diyadin1,Candemir Aykan2

Affiliation:

1. İstanbul Gelişim University, Turkey

2. Ege University, Turkey

Abstract

This chapter investigates to what extent the feelings and thoughts of consumers are effective in the process of new product development and improvement. Inspired by the user innovation theory, the study analyzes the online feedback of the users of a smartphone brand in Turkey. This analysis covers a sentiment analysis performed using the support vector machines, the random forest, and the recurrent neural networks algorithms. By studying 2005 reviews, the chapter concludes that two strategies are proposed for the firms. A first strategy is a hybrid approach: Given the imported input-dependency, we know that the cost of imported inputs matters for firms. The second strategy is repositioning the brand in the long term. This chapter attempts to contribute to the literature by providing new evidence in a developing country case whether user comments are effective on the modified versions of a high-tech product.

Publisher

IGI Global

Reference89 articles.

1. Agarwal, A., Xie, B., Vovsha, I., Rambow, O., & Passonneau, R. (2011). Sentiment Analysis of Twitter Data. In Proceedings of the Workshop on Language in Social Media. Association for Computational Linguistics.

2. User Involvement Method in The Early Stage of The New Product Development Process For A Successful Product.;H.Alli;Alam Cipta: International Journal of Sustainable Tropical Design Research and Practice,2018

3. An adaptable fine-grained sentiment analysis for summarization of multiple short online reviews

4. Enhancing deep learning sentiment analysis with ensemble techniques in social applications

5. A Novel, Gradient Boosting Framework for Sentiment Analysis in Languages where NLP Resources Are Not Plentiful: A Case Study for Modern Greek

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