Search results

1 – 3 of 3
Article
Publication date: 12 October 2023

R.L. Manogna and Aayush Anand

Deep learning (DL) is a new and relatively unexplored field that finds immense applications in many industries, especially ones that must make detailed observations, inferences…

Abstract

Purpose

Deep learning (DL) is a new and relatively unexplored field that finds immense applications in many industries, especially ones that must make detailed observations, inferences and predictions based on extensive and scattered datasets. The purpose of this paper is to answer the following questions: (1) To what extent has DL penetrated the research being done in finance? (2) What areas of financial research have applications of DL, and what quality of work has been done in the niches? (3) What areas still need to be explored and have scope for future research?

Design/methodology/approach

This paper employs bibliometric analysis, a potent yet simple methodology with numerous applications in literature reviews. This paper focuses on citation analysis, author impacts, relevant and vital journals, co-citation analysis, bibliometric coupling and co-occurrence analysis. The authors collected 693 articles published in 2000–2022 from journals indexed in the Scopus database. Multiple software (VOSviewer, RStudio (biblioshiny) and Excel) were employed to analyze the data.

Findings

The findings reveal significant and renowned authors' impact in the field. The analysis indicated that the application of DL in finance has been on an upward track since 2017. The authors find four broad research areas (neural networks and stock market simulations; portfolio optimization and risk management; time series analysis and forecasting; high-frequency trading) with different degrees of intertwining and emerging research topics with the application of DL in finance. This article contributes to the literature by providing a systematic overview of the DL developments, trajectories, objectives and potential future research topics in finance.

Research limitations/implications

The findings of this paper act as a guide for literature review for anyone interested in doing research in the intersection of finance and DL. The article also explores multiple areas of research that have yet to be studied to a great extent and have abundant scope.

Originality/value

Very few studies have explored the applications of machine learning (ML), namely, DL in finance, which is a much more specialized subset of ML. The authors look at the problem from the aspect of different techniques in DL that have been used in finance. This is the first qualitative (content analysis) and quantitative (bibliometric analysis) assessment of current research on DL in finance.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 3 October 2023

Priya Kataria and Shelly Pandey

The purpose of this paper is to study the experiences of middle-class working mothers from the ITES (Information Technology Enabled Service) sector in India during the COVID-19…

111

Abstract

Purpose

The purpose of this paper is to study the experiences of middle-class working mothers from the ITES (Information Technology Enabled Service) sector in India during the COVID-19 pandemic. Their experiences of work from home are studied in the backdrop of the ideal worker model at work and the adult worker model at home. Further, the study aims to identify the need for sustainable, inclusive practices for working mothers in Indian organizations to break the male breadwinner model in middle-class households.

Design/methodology/approach

A qualitative approach to collect data from 39 middle-class mothers working in MNCs in four metro cities in India. The semi-structured, in-depth interviews focused on their experiences of motherhood, care and work before, during and after the COVID-19 pandemic.

Findings

The pandemic made it evident that the ideal worker model in organizations and the adult worker model at home were illusions for working mothers. The results indicate a continued obligation of the “ideal worker culture” at organizations, even during the health crisis. It made the working mothers realize that they were chasing both the (ideal worker and adult worker) norms but could never achieve them. Subsequently, the male breadwinner model was reinforced at home due to the matrix of motherhood, care and work during the pandemic. The study concludes by arguing the reconstruction of the ideal worker image to make workplaces more inclusive for working mothers.

Originality/value

The study is placed in the context of Indian middle-class motherhood during the pandemic, a demography less explored in the literature. The paper puts forth various myths constituting the gendered realities of Indian middle-class motherhood. It also discusses sustainable, inclusive workplace practices for mothers from their future workplaces' standpoint, especially in post-pandemic times.

Details

Equality, Diversity and Inclusion: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-7149

Keywords

Article
Publication date: 6 July 2023

G. Citybabu and S. Yamini

The purpose of this paper is to investigate the research landscape of LSS 4.0 papers published in two well-known repositories, Scopus and Web of Science (WoS), in terms of…

323

Abstract

Purpose

The purpose of this paper is to investigate the research landscape of LSS 4.0 papers published in two well-known repositories, Scopus and Web of Science (WoS), in terms of publication trends, article distribution by author, journal, affiliations and country, and article clustering based on keywords, authors and countries. In addition, a literature review was carried out to build a conceptual framework of integrated Lean Six Sigma and Industry 4.0 (LSS 4.0) that encompasses operational, sustainability and human factors or ergonomics aspects.

Design/methodology/approach

The literature review of integrated Lean Six Sigma and I4.0 publications published in Scopus and WoS databases in the current decade was conducted for the present study. This study categorizes LSS, I4.0 and related research articles based on publication patterns, journals, authors and affiliations, country and continental-wise distribution and clustering the articles based on keywords and authors from the Scopus and WoS databases from 2011 to 2022 using the search strings “Lean”, “Six Sigma”, “Lean Six Sigma” and “Industry 4.0” in the Title, Abstract and Keywords using Biblioshiny, VOS viewer and Microsoft Excel.

Findings

In the recent three years, from 2020 to 2022, LSS 4.0 has been substantially increasing and is seen as an emerging and trending area. This research identifies the most influential authors, most relevant affiliations, most prolific countries and most productive journals and clusters based on keywords, authors and countries. Further, a conceptual framework was developed that includes the impact of operational, sustainability and ergonomic or human factors in LSS 4.0.

Research limitations/implications

This article assists in comprehending the trends and patterns of LSS 4.0. Further, the conceptual framework helps professionals and researchers understand the significance and impact of integrating LSS and Industry 4.0 in the aspects of human factors/ergonomic, sustainability and operations. Also, the research induce professionals to incorporate all these factors while designing and implementing LSS 4.0 in their organization.

Originality/value

This conceptual framework and bibliometric analysis would aid in identifying potential areas of research and providing future directions in the domain of LSS 4.0. It will be beneficial for academicians, professionals and researchers who are planning to apply and integrate techniques of LSS and technologies of I4.0 in their organizations and research.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

1 – 3 of 3