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Environmental sustainability is quickly becoming one of the most critical issues in industry development. This study aims to conduct a systematic literature review through which the author can provide various research areas to work on for future researchers and provide insight into Industry 4.0 and environmental sustainability.

This study accomplishes this by performing a backward analysis using text mining on the Scopus database. Latent semantic analysis (LSA) was used to analyze the corpus of 4,364 articles published between 2013 and 2023. The authors generated ten clusters using keywords in the industrial revolution and environmental sustainability domain, highlighting ten research avenues for further exploration.

In this study, three research questions discuss the role of environmental sustainability with Industry 4.0. The author predicted ten clusters treated as recent trends on which more insight is required from future researchers. The authors provided year-wise analysis, top authors, top countries, top sources and network analysis related to the topic. Finally, the study provided industrialization’s effect on environmental sustainability and the future aspect of automation.

The reliability of the current study may be compromised, notwithstanding the size of the sample used. Poor retrieval of the literature corpus can be attributed to the limitations imposed by the search words, synonyms, string construction and variety of search engines used, as well as to the accurate exclusion of results for which the search string is insufficient.

This research is the first-ever study in which a natural language processing technique is implemented to predict future research areas based on the keywords–document relationship.

The case on Moodcafe captures the journey of the start-up and its entrepreneurs from the beginning till the fund-raising stage. The case brings forth critical decisions that each entrepreneur or the team of co-founders have to address during their start-up journey. This short case gives opportunity to delve into two aspects mainly a) As a founder, which investor should one choose for seeking funds and what should be the terms and conditions of investment? and b) How can one review and assess the business model of a start-up?

The purpose of this paper is to perform a meta-bibliometric analysis of the banking service quality and to provide various research streams. Another goal is to provide future research questions to explore these areas in more detail.

The authors used three major academic databases (Scopus, ProQuest and EBSCO) from 1980–2021 and found 226 papers, where they performed the meta-bibliometric analysis by performing co-citation analysis, co-authorship analysis, cartographic analysis and content analysis.

The SERVQUAL model is the most used conceptual framework and model to study banking service quality. Structural equation modeling (SEM), followed by partial least squares SEM, is a majorly used method. There are three research streams in the literature: retail banking service quality, internet banking service quality and mobile banking service quality. Retail banking is the most studied stream, whereas mobile banking is the least studied stream. The study on banking service quality was initially conducted in developed markets, and later in emerging markets. All three streams have scope for further exploration, and hence, 44 future research questions have also been proposed.

This study has implications for bank managers, academicians and future researchers.

This study is unique in that it examines the meta-bibliometric dimensions of banking service quality and provides directions for future research for academicians and researchers.