Conducting product comparative analysis to outperform competitor’s product using Teardown JST Model

2021 ◽  
pp. 1063293X2110472
Author(s):  
Cuiqing Jiang ◽  
Abdullah Alqadhi ◽  
Mahmood Almesbahi

Due to the massive number of products being produced every year in every industry, firms have witnessed a tremendous growth in innovation of methods to create a sustainable competitive advantage. For the past decade and with the availability of online consumer reviews, companies and researchers have developed many approaches utilizing electronic Word-of-Mouth to improve and develop products and services to outperform competitors. The purpose of this study is to construct an effective method to perform a better product comparative analysis based on online consumer reviews. We propose a novel framework called Teardown Joint Sentiment-Topic analysis model consisting of a combination of text analytical approaches incorporated with a developed method of the traditional teardown analysis product comparative approach. The proposed approach is fully unsupervised model that employs Latent Dirichlet Allocation topic modeling to form topics which are classified according to their sentiments. Topics are then analyzed against competitive products and critical topics are identified using a developed teardown method. A case study analyzing online customer reviews of competing products in two domains (i.e., mobile phones and surveillance cameras) is conducted. The identified critical topics are further analyzed in view of products’ specifications perspective. We found that the detected aspects of the selected products are indeed critical, and hence, they need to be improved in order to gain a competitive advantage. The significant result of this study shows that the proposed method is effective in conducting products comparative analysis and provides valuable insights into utilizing the consumer reviews for product development.

2021 ◽  
Vol 13 (4) ◽  
pp. 2024
Author(s):  
Do-Hyung Park

Today, consumer-created information such as online consumer reviews have become important and popular, playing a key role in consumer decision making. Compared with expert-created information, each piece of information is less powerful or persuasive, but their aggregation can be more credible and acceptable. This concept is called collective intelligence knowledge. This study focuses on the persuasive effect on consumer product attitudes of consumer-created information compared to expert-created information. Using source credibility and familiarity theory, the study reveals how prior brand attitudes can play a moderating role in the persuasive effect of consumer-created information and expert-created information. Specifically, this study shows how consumer-created information is more persuasive when consumers have more favorable prior brand attitudes, while expert-created information is more persuasive when consumers have less favorable prior brand attitudes. Based on the results, this study proposes practical strategies for information structure, curation, and presentation. If a company has a good-quality brand evaluation of its products, it should increase the weight of consumer-created information such as online consumer reviews. Otherwise, the company needs to first improve brand evaluation through expert-created information such as third-parties or power-blogger reviews.


2017 ◽  
pp. 43-74
Author(s):  
Oshin Anand ◽  
◽  
Praveen Ranjan Srivastava ◽  
Atanu Rakshit ◽  
◽  
...  

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