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

journal contribution
posted on 17.08.2020 by Mihalis Giannakis, Rameshwar Dubey, Shishi Yan, Konstantina Spanaki, Thanos Papadopoulos
Artificial Intelligence (AI) 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

Publisher

Springer (part of Springer Nature)

Version

AM (Accepted Manuscript)

Publisher statement

This is a post-peer-review, pre-copyedit version of an article published in Annals of Operations Research. The final authenticated version is available online at: http://dx.doi.org/[insert DOI].

Acceptance date

14/08/2020

ISSN

0254-5330

eISSN

1572-9338

Language

en

Depositor

Dr Konstantina Spanaki. Deposit date: 14 August 2020

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