Examination on the Trend of Researches on Absorptive Capacity using Text Mining Technique

Abstract

Background/Objectives: This paper is investigated the trend of researches on absorptive capacity through search of Scopus Database by using text mining technique for academic theses related to absorptive capacity.

Methods/Statistical analysis: This study used Text Mining Technique, discovering hidden meanings in big data such as extraction of information from large volume of documents or finding linkages, classification, clustering and summarization by using the method of NLP.

Findings: As a result of analysis on the keywords related to absorptive capacity, most frequently used words were ‘capacity’ followed by ‘absorptive’, ‘knowledge’, ‘firm’, ‘innovation’, 'study', 'performance', 'research', 'results', 'model', 'effect', 'development' and 'technology' in descending order. Absorptive capacity is the very core of current convergence era, many studies are expected to be conducted related to absorptive capacity in the digital transformation era.

Improvements/Applications: The trend of researches on absorptive capacity and related studies in the leading academic thesis database, Scopus, and drew out and analyzed 20 keywords.In the future, related researches will be continuously conducted as well.

 Keywords: Big Data, Absorptive Capacity, Text mining, Trend, Scopus, R.