Sustainable knowledge management in the digital era: leveraging natural language processing to identify trends, challenges and future directions

Purpose – Despite the growing shift to a sustainable knowledge-based economy, there is a substantial disparity in how vast knowledge is stored and applied at the individual and organizational levels. This study aims to investigate the current status, trends and dark side of achieving sustainable knowledge management (SKM) in the digital era using published literature and natural language processing. Design/methodology/approach – The study uses topic modeling to investigate the current discussion, term frequency-inverse document frequency (TF-IDF) and keyword analysis to estimate trends in SKM in the digital era and explores the negative aspects of achieving it using published literature. Findings – This study shows that the literature on SKM has increased exponentially, indicating the growing importance of integrating sustainability into organizational knowledge practices, specifically through digital transformation. The study found four themes, out of which two themes, “Ethical Dilemmas, Digital Divide, and Knowledge Inequality” and “Knowledge Obsolescence and Information Overload, ” focus on the various negative aspects of achieving SKM in the digital era. Based on the outcome, future research directions are also proposed. Practical implications – The findings of this study help knowledge-based organizations understand the role of digital transformation in developing technological advancement at their workplace to handle the issues of ethical dilemmas, digital divide, knowledge inequality, obsolescence and information overload in achieving SKM. The study also provides future research directions to academic researchers and industry practitioners. Originality/value – To the best of the authors’ knowledge, this review is among the first to explore the dark side of achieving SKM in the digital era using published literature and natural language processing.