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Social media and sensemaking patterns in new product development: demystifying the customer sentiment

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journal contribution
posted on 2020-08-17, 11:23 authored by Mihalis Giannakis, Rameshwar Dubey, Shishi Yan, Konstantina Spanaki, Thanos Papadopoulos
Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers’ emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers’ appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms.

History

School

  • Business and Economics

Department

  • Business

Published in

Annals of Operations Research

Volume

308

Pages

145-175

Publisher

Springer (part of Springer Nature)

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Acceptance date

2020-08-14

Publication date

2020-08-29

Copyright date

2022

ISSN

0254-5330

eISSN

1572-9338

Language

  • en

Depositor

Dr Konstantina Spanaki. Deposit date: 14 August 2020

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