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In recent years, Industry 4.0 has received immense attention from academic community, practitioners and the governments across nations resulting in explosive growth in the publication of articles, thereby making it imperative to reveal and discern the core research areas and research themes of Industry 4.0 extant literature. The purpose of this paper is to discuss research dynamics and to propose a taxonomy of Industry 4.0 research landscape along with future research directions.

A data-driven text mining approach, Latent Semantic Analysis (LSA), is used to review and extract knowledge from the large corpus of the 503 abstracts of academic papers published in various journals and conference proceedings. The adopted technique extracts several latent factors that characterise the emerging pattern of research. The cross-loading analysis of high-loaded papers is performed to identify the semantic link between research areas and themes.

LSA results uncover 13 principal research areas and 100 research themes. The study discovers “smart factory” and “new business model” as dominant research areas. A taxonomy is developed which contains five topical areas of Industry 4.0 field.

The data set developed is based on systematic article refining process which includes the keywords search in selected electronic databases and articles limited to English language only. So, there is a possibility that other related work may not be captured in the data set which may be published in other than examined databases and are in non-English language.

To the best of the authors’ knowledge, this study is the first of its kind that has used the LSA technique to reveal research trends in Industry 4.0 domain. This review will be beneficial to scholars and practitioners to understand the diversity and to draw a roadmap of Industry 4.0 research. The taxonomy and outlined future research agenda could help the practitioners and academicians to position their research work.

In the framework of Industry 4.0, the study seeks to clarify the intricate connection between modern digitalization and sustainability and the ways in which these developing technologies support sustainable practices in the societal, environmental and economic spheres. Utilizing a conceptual framework, this study integrates insights from existing literature and provides a structured investigation to explore the impact of Industry 4.0 technologies, including smart manufacturing, artificial intelligence, the internet of things (IoT) and blockchain, on sustainability. The research reveals that the integration of environmental, social, economic and human aspects of sustainability. The study emphasizes how these elements support Industry 4.0 by encouraging moral and sustainable business practices. The insights derived from this research offer practical implications for policymakers, industry leaders and researchers. By understanding the symbiotic relationship between digitalization and sustainability, stakeholders can formulate strategies that leverage new-age technologies to achieve optimal efficiency while ensuring ethical and sustainable business practices. The originality lies in the holistic approach to understanding the environmental, social and economic dimensions impacted by new-age digitalization offering a comprehensive examination of the interplay between Industry 4.0 and sustainability.