Determinants of Competitors's Response Time to a New Product Introduction Douglas Bowman and Hubert Gatignon, Journal of Marketing Research (February 1995), pp. 42?53

1995 ◽  
Vol 12 (5) ◽  
pp. 452
2017 ◽  
Vol 13 (1) ◽  
pp. 33-54 ◽  
Author(s):  
Laura Marie Schons ◽  
Philipp Thöne

Current research suggests that social identification processes play an important role in markets. In this study, the authors propose that marketing research has neglected one important factor, which influences the success of a brand extension, namely the group processes between social groups and brand communities framing the new product introduction. Based on social identification theory, the authors derive a framework integrating identification and stereotyping processes, simultaneously testing for drivers of brand extension potential, which have been found to be important in past empirical studies. Using a structural equation modeling approach, the authors test for in-group and out-group effects in two hypothetical brand extension scenarios of one snowboard brand (Burton), and a surf brand (Billabong) into the ski market. They find that the social identification processes underlying the new product introduction significantly drive the potential success of the brand extension. By being the first study to explore the role of identification and stereotype effects in brand extension, the authors make an important contribution to research in this area. Moreover, our study provides important implications for brand managers planning to extend their brands into new product categories.


Author(s):  
Irina Wedel ◽  
Michael Palk ◽  
Stefan Voß

AbstractSocial media enable companies to assess consumers’ opinions, complaints and needs. The systematic and data-driven analysis of social media to generate business value is summarized under the term Social Media Analytics which includes statistical, network-based and language-based approaches. We focus on textual data and investigate which conversation topics arise during the time of a new product introduction on Twitter and how the overall sentiment is during and after the event. The analysis via Natural Language Processing tools is conducted in two languages and four different countries, such that cultural differences in the tonality and customer needs can be identified for the product. Different methods of sentiment analysis and topic modeling are compared to identify the usability in social media and in the respective languages English and German. Furthermore, we illustrate the importance of preprocessing steps when applying these methods and identify relevant product insights.


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