Information discovery methods using statistical processing to facilitate innovation creation Online publication date: Fri, 05-Jan-2024
by Takayuki Suzuki; Kiminori Gemba; Atsushi Aoyama
International Journal of Business and Systems Research (IJBSR), Vol. 18, No. 1, 2024
Abstract: In the past, products were classified by hand, using qualitative judgement. This research proposes a method of discovering information that facilitates the creation of innovation using statistical processing, and an external theory targeting information associated with products. Word-of-mouth information concerning home appliances, aggregated during a specific period, was collectively analysed without dividing the total duration of the period. It was found that information lead to the emergence of innovation. This study aimed to discover information that supplements innovation through statistical processing (i.e., principal component analysis, non-negative matrix factorisation, and latent Dirichlet allocation). In the future, it will be crucial to re-examine various discussions that can be expressed in two dimensions or those that independently deal with product characteristics. Going forward, it will be essential to perform quantitative analysis of the relationship of product characteristics with each period of the product life cycle.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business and Systems Research (IJBSR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com