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RETRACTED: Impact of online customer reviews and deep learning on product innovation empirical study on mobile applications

Huiliang Zhao, Qin Yang, Zhenghong Liu

Business Process Management Journal

ISSN: 1463-7154

Article publication date: 2 April 2021

Issue publication date: 12 October 2021

1105
This article was retracted on 6 Nov 2024.

Retraction notice

The publishers of the Business Process Management Journal wish to retract the article Zhao, H., Yang, Q. and Liu, Z. (2021), “Impact of online customer reviews and deep learning on product innovation empirical study on mobile applications”, Business Process Management Journal, Vol. 27 No. 6, pp. 1912-1925. https://doi.org/10.1108/BPMJ-12-2020-0542

An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald’s publishing ethics and the COPE guidelines on retractions. Despite numerous attempts to contact the authors, the journal has received no response; the response of the authors would be gratefully received. The publishers of the journal sincerely apologize to the readers.

Abstract

Purpose

The customer enables online reviews, discusses product features and enhances the user's experiences in online activities. Users generated product innovation and product reviews effect as market competition. This research study explains deep learning, online reviews and product innovation empirical evidence used by mobile apps.

Design/methodology/approach

Online reviews and product innovation are very important for every organization and firms to achieve a competitive advantage in a large business environment. When the authors see past traditional history, customers are not involved in product creating and innovating processes. Due to new technology changes, online systems and web 2.0 increase this ability.

Findings

For this research purpose, the authors use different analytical software to measure the impact among variables. This study is established on primary data; this study collected data from online customers and its users. For data collection, the authors use some questionnaires, and these questions are filled from 200 respondents.

Research limitations/implications

This research study used data from the Google app store – Google product selling application – and gathered customers' online reviews. Research found that customers' online reviews and deep learning positively and significantly influence product innovation through networking technology. This research-based online mobile application and its research reviews found that organizations convert their own business online and effectively and efficiently enhance creditability.

Originality/value

This research study used data from the Google app store Google product selling application and gathered customers' online reviews. Research founded that customers' online reviews and deep learning are positively and significantly influence product innovation through networking technology. This research-based online mobile application and its research reviews found that organizations convert their own business online and effectively and efficiently enhance creditability.

Keywords

Acknowledgements

Project supported by the Natural Science Foundation of the Guizhou Higher Education Institutions of China (Grant No. [2018]152, No. [2017]239). Project supported by the Humanity and Social Science Foundation of the Guizhou Higher Education Institutions of China (Grant No. 2018qn46).

Citation

Zhao, H., Yang, Q. and Liu, Z. (2021), "RETRACTED: Impact of online customer reviews and deep learning on product innovation empirical study on mobile applications", Business Process Management Journal, Vol. 27 No. 6, pp. 1912-1925. https://doi.org/10.1108/BPMJ-12-2020-0542

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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