Lecture Notes in Networks and Systems, Volume 453 LNNS, Pages 32-42 , 01/01/2022
Discovery of Business Model Transform in Commerce Using LSA Approach with Firm Information Disclosure
Abstract
In order to survive and grow in rapidly changing settings, incumbents and established commerce enterprises must adapt their business models. However, changing a business model is a difficult task because there is no best practice provided. In our study, we wanted to learn from the best-performing firms in order to find such an effective solution. We used data from annual reports of enterprises in the Stock Exchange of Thailand’s commerce business sector to perform Latent Semantic Analysis (LSA). Tobin’s Q ratio and CAGR were used to select successful and fast-growing businesses, resulting in a final sample of 14 prominent businesses. Our TF-IDF calculations yielded 5,596 words after the text preparation step. Our analyses indicated that our corpus contained three latent topics. We may conclude, based on the key terms for each topic, that developing online sales channels alongside traditional business forms is an essential business model transformation approach for companies looking to survive and grow in the digital age.
Document Type
Conference Paper
Source Type
Book Series
ISBN
[9783030999476]
ISSN
23673370, 23673389
Keywords
Business model transformInformation disclosureLatent semantic analysis
ASJC Subject Area
Engineering : Control and Systems EngineeringComputer Science : Signal ProcessingComputer Science : Computer Networks and Communications