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Deep learning (DL) technologies assist manufacturers to manage their business operations. This research aims to present state-of-the-art insights on the trends and ways forward for DL applications in manufacturing operations.

Using bibliometric analysis and the SPAR-4-SLR protocol, this research conducts a systematic literature review to present a scientific mapping of top-tier research on DL applications in manufacturing operations.

This research discovers and delivers key insights on six knowledge clusters pertaining to DL applications in manufacturing operations: automated system modelling, intelligent fault diagnosis, forecasting, sustainable manufacturing, environmental management, and intelligent scheduling.

This research establishes the important roles of DL in manufacturing operations. However, these insights were derived from top-tier journals only. Therefore, this research does not discount the possibility of the availability of additional insights in alternative outlets, such as conference proceedings, where teasers into emerging and developing concepts may be published.

This research contributes seminal insights into DL applications in manufacturing operations. In this regard, this research is valuable to readers (academic scholars and industry practitioners) interested to gain an understanding of the important roles of DL in manufacturing operations as well as the future of its applications for Industry 4.0, such as Maintenance 4.0, Quality 4.0, Logistics 4.0, Manufacturing 4.0, Sustainability 4.0, and Supply Chain 4.0.

This study aims to extend the study of COVID-19 effects by identifying different consumer behaviors beyond panic buying during the pandemic.

A systematic review was based on Herjanto et al.’s (2020a) thematic analysis and Paul et al.’s (2021) 5W1H framework, and the authors analyzed 52 related papers.

The result findings indicated that during the COVID-19 pandemic, consumers fell into five different consumer behavior categories: health-related behaviors, consumption behaviors, ethical behaviors, behavioral intentions, and other related behaviors, and social connectedness behaviors. Findings show that consumer behaviors were increasingly complex and dynamic during the pandemic.

This systematic review will provide significant contributions to academia by offering general and technical insights and to practitioners by presenting guidelines on dealing with such different behaviors.

Integrated reporting (<IR>) promotes transparency in corporate reporting and communicate detailed information on how a firm creates value in the short, medium and long-term. The purpose of this paper is to systematically review <IR> to provide insights into theories, determinants, consequences, contingent variables and methods that have been used in previous studies.

The study was based on a systematic review of 17 articles published between 2017 and 2020.

Nine theories were used in prior studies. Board size, diversity, independence, level of activity of the board, the establishment of Higher Education Institutions (before or after 1992), adoption of IR framework, size, institutional ownership, sustainability committee and the use of non-financial performance measures in executives’ compensation contracts and separate risk management committees are determinants of <IR>. Further, the positive impact of <IR> on information asymmetry, market valuation of environmental, social and governance performance, financial performance, intellectual capital, sustainability embeddedness and organisational change, external sense of legitimacy and reputation, revenue growth, corporate environmental performance and circular economy-related information, with mixed findings for analyst earnings forecast accuracy, company value and market value. Only three studies used moderating and mediating variables to examine <IR>. Quantitative research approach and secondary data are most preferred by <IR> scholars.

Some papers may have been omitted unintentionally, although the author did his best to include most of the prior published articles using a rigorous methodology.

This paper set out future research agenda on how <IR> research could be enhanced.

Contrary to prior systematic reviews that consider individual constructs/concept, the review herein adopts a comprehensive approach and considers moderating and mediating variables aside from theories, effects and determinants of integrated reporting.

To overcome and solve the problems of all the research community, in this chapter we offer everyone to focus on the Planning, Operationalizing, Writing, Embedding, and Reflecting (POWER) framework of conducting literature review. The framework guides the scholarly community on how to create and evaluate literature review papers to overcome the merit dilemma on the contribution made by review papers. With the sole focus toward review of literature, we are pleased to present “Review of Management Literature (RoML)” and introducing the first volume. This chapter and volume answers the present tensions accruing in the existing literature as well as present strategies on bridging the gaps. The chapters included in the first volume belong to emerging research areas such as marketing, human resources, international businesses, supply chain management, artificial neural network, luxury consumption, financial technology (FINTECH), mergers and acquisition, social media platforms like Instagram, cultural diversity, services, sustainability, quality 4.0, entrepreneurial ecosystem, and dividend decisions. The first volume is going to be useful to scholars in exploring future research areas across business management disciplines.