Innovation in an Emerging Market: A Bibliometric and Latent Dirichlet Allocation Based Topic Modeling Study

Autor: Mohammad Tasyriq Che Omar, Mohd Faiz Hilmi, Yanti Mustapha
Rok vydání: 2020
Předmět:
Zdroj: 2020 International Conference on Decision Aid Sciences and Application (DASA).
DOI: 10.1109/dasa51403.2020.9317278
Popis: Innovation has been recognized as an important factor influencing organizational performance. Malaysia as an emerging market has also been pushing for innovation to be the stimulant for growth. Due to huge number of research articles published related to innovation in Malaysia, there is a need to understand the existing state of research related to the topic. This study examines 1824 papers published from 1973 to 2019. Data was extracted from SCOPUS and analyzed using descriptive figures and tables. Additionally this study present the key features of topic modeling based on Latent Dirichlet Allocation (LDA) by extracting coherent research topics that are the focus of the papers analyzed. Through the topic modelling approach this study are able to extract ten coherent research topics from 1824 papers analyzed. This study aim to demonstrate themes related to research on innovation in an emerging market and contributes by summarizing the common keywords used in both the title and abstract of articles published until 2019. Furthermore, this study identified 10 topics based on the abstract of the published articles.
Databáze: OpenAIRE