Search results

1 – 10 of over 1000
Article
Publication date: 2 February 2021

Yusra Qamar and Taab Ahmad Samad

This paper aims to identify the current research trends and set the future research agenda in the area of human resource (HR) analytics by an extensive review of the…

2601

Abstract

Purpose

This paper aims to identify the current research trends and set the future research agenda in the area of human resource (HR) analytics by an extensive review of the existing literature. The paper aims to capture state of the art and develop an exhaustive understanding of the theoretical foundations, concepts and recent developments in the area.

Design/methodology/approach

A portfolio of 125 articles collected from the Scopus database was systematically analyzed using a two-tier method. First, the evolution, current state of the literature and research clusters are identified using bibliometric techniques. Finally, using content analysis, the research clusters are studied to develop the future research agenda.

Findings

Based on the bibliometric analysis, network analysis and content analysis techniques, this study provides a comprehensive review of the existing literature. The study also highlights future research themes by identifying knowledge gaps based on content analysis of research clusters.

Research limitations/implications

The evolution and the current state of the HR analytics literature are presented. Some specific research questions are also provided to help future research.

Originality/value

This study enriches the literature of HR analytics by integrating bibliometric analysis and content analysis to develop a more systematic and exhaustive understanding of the research area. The findings of this study may assist fellow researchers in furthering their research in the identified research clusters.

Details

Personnel Review, vol. 51 no. 1
Type: Research Article
ISSN: 0048-3486

Keywords

Article
Publication date: 27 December 2021

Anjali Shishodia, Rohit Sharma, R. Rajesh and Ziaul Haque Munim

The study identifies nine important research areas and critically maps the structural relationships among supply chain resilience (SCRES) dimensions, namely…

1596

Abstract

Purpose

The study identifies nine important research areas and critically maps the structural relationships among supply chain resilience (SCRES) dimensions, namely, vulnerabilities, capabilities, strategies and performance metrics. The analysis also revealed various influential authors, journals, institutions and trending articles, across SCRES literature.

Design/methodology/approach

This study performs a bibliometric analysis of 771 articles published over the 32 years from 1988 to 2020, and network analysis in combination with content analysis of 90 most cited articles published in research fronts of SCRES.

Findings

The results demonstrate the underlying research areas within the SCRES, which are clustered into nine research themes: (1) conceptual development of SCRES, (2) recent developments of designing resilient supply chain (SC) networks, (3) focus on identifying drivers of SC vulnerability and risks, (4) impact of risks on network resilience, (5) risk assessment to avoid breakdowns/disruptions, (6) measuring resilience approaches/drivers to improve SC performance, (7) building resilient capabilities by integrating other SC dimensions, (8) quantification of SC network and (9) emphasis on developing robustness in SC networks.

Practical implications

This research offers implications for classifying the works in literature based on bibliometric information and network analysis techniques. This can help researchers and practitioners to understand the prominent areas in SCRES and provide guidelines for future research in this area.

Originality/value

This study provides an overview of the evolution of SCRES over time in the domain of supply chain management and also outlines a future research agenda claimed by the trending articles to encourage further investigations in the field of SCRES.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 8 November 2019

Pulkit Tiwari, P. Vigneswara Ilavarasan and Sushil Punia

The purpose of this paper is to provide a systematic literature review on the technological aspects of smart cities and to give insights about current trends, sources of…

Abstract

Purpose

The purpose of this paper is to provide a systematic literature review on the technological aspects of smart cities and to give insights about current trends, sources of research, contributing authors and countries. It is required to understand technical concepts like information technology, big data analytics, Internet of Things and blockchain needed to implement smart city models successfully.

Design/methodology/approach

The data were collected from the Scopus database, and analysis techniques like bibliometric analysis, network analysis and content analysis were used to obtain research trends, publications growth, top contributing authors and nations in the domain of smart cities. Also, these analytical techniques identified various fields within the literature on smart cities and supported to design a conceptual framework for Industry 4.0 adoption in a smart city.

Findings

The bibliometric analysis shows that research publications have increased significantly over the last couple of years. It has found that developing countries like China is leading the research on smart cities. The network analytics and article classification identified six domains within the literature on smart cities. A conceptual framework for the smart city has proposed for the successful implementation of Industry 4.0 technologies.

Originality/value

This paper explores the role of Industry 4.0 technologies in smart cities. The bibliometric data on publications from the year 2013 to 2018 were used and investigated by using advanced analytical techniques. The paper reviewS key technical concepts for the successful execution of a smart city model. It also gives an idea about various technical considerations required for the implementation of the smart city model through a conceptual framework.

Details

Benchmarking: An International Journal, vol. 28 no. 5
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 31 May 2019

Lulu Qiu, Elsie Zhou, Tiffany Yu and Neil Smyth

Librarians are challenged by technology transformations in research data metrics to re-position in the evolving cycles of research production, communication and…

399

Abstract

Purpose

Librarians are challenged by technology transformations in research data metrics to re-position in the evolving cycles of research production, communication and evaluation. They are also are challenged by the new and emerging strategic needs of universities for data-driven research intelligence that provides a comparative edge in the global world of higher education. This paper aims to discover how libraries can support universities in applying international assessment standards by delivering new reference and information services based on data analytics.

Design/methodology/approach

This paper focuses on a new reference and information service Research Data Analytics in China that was launched in 2017. There is a discussion of how new university needs have provided the strategic drive for librarians to develop skills.

Findings

The Research Data Analytics service development is significant for showcasing a new role for librarians in relation to research data evaluation metrics linked to publication strategies for authors and strategic intelligence for institutions. This has driven the development of the library’s position and influence in strategic research intelligence services.

Originality/value

The future for librarians is about being adventurous. Librarians are experts who will sparkle and shine beyond the bubble of the library walls. They can demonstrate a commitment to supporting university colleagues in professional services and academia to blossom and flourish. Distinctive visual technologies can be adopted for exploring research data which transform research production, communication and evaluation and therefore transform our position and future through technology-enabled innovations.

Article
Publication date: 31 March 2020

Zeeshan Inamdar, Rakesh Raut, Vaibhav S. Narwane, Bhaskar Gardas, Balkrishna Narkhede and Muhittin Sagnak

The volume of data being generated by various sectors in recent years has increased exponentially. Consequently, professionals struggle to process essential data in the…

2084

Abstract

Purpose

The volume of data being generated by various sectors in recent years has increased exponentially. Consequently, professionals struggle to process essential data in the current competitive world. The purpose of the study is to explore and provide insights into the Big Data Analytics (BDA) studies in different sectors.

Design/methodology/approach

This study performs a systematic literature review (SLR) with bibliometric analysis of BDA adoption (BDAA) in the supply chain and its applications in various sectors from 2014 to 2018. This paper focuses on BDAA studies have been carried out across different countries and sectors. Also, the paper explores different tools and techniques used in BDAA studies.

Findings

The benefits of adopting BDA, coupled with a lack of adequate research in the field, have motivated this study. This literature review categorizes paper into seven main areas and found that most of the studies were carried out in manufacturing and service.

Practical implications

This research insight and observations can provide practitioners and academia with guidance on implementing BDA in different sustainable supply chain sectors. The article indicates a few remarkable gaps in the future direction and trends regarding the integration of BDA and sustainable supply chain development.

Originality/value

The study derives a new categorization of BDA, which investigates how data is generated, organized, captured, interpreted and evaluated to give valuable insights to manage the sustainable supply chain.

Details

Journal of Enterprise Information Management, vol. 34 no. 1
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 4 February 2019

Riccardo Rialti, Giacomo Marzi, Cristiano Ciappei and Donatella Busso

Recently, several manuscripts about the effects of big data on organizations used dynamic capabilities as their main theoretical approach. However, these manuscripts still…

3526

Abstract

Purpose

Recently, several manuscripts about the effects of big data on organizations used dynamic capabilities as their main theoretical approach. However, these manuscripts still lack systematization. Consequently, the purpose of this paper is to systematize the literature on big data and dynamic capabilities.

Design/methodology/approach

A bibliometric analysis was performed on 170 manuscripts extracted from the Clarivate Analytics Web of Science Core Collection database. The bibliometric analysis was integrated with a literature review.

Findings

The bibliometric analysis revealed four clusters of papers on big data and dynamic capabilities: big data and supply chain management, knowledge management, decision making, business process management and big data analytics. The systematic literature review helped to clarify each clusters’ content.

Originality/value

To the authors’ best knowledge, minimal attention has been paid to systematizing the literature on big data and dynamic capabilities.

Details

Management Decision, vol. 57 no. 8
Type: Research Article
ISSN: 0025-1747

Keywords

Article
Publication date: 20 July 2021

Eymen Çağatay Bilge and Hakan Yaman

This study aims to identify the trends that have changed in the field of construction management over the last 20 years.

Abstract

Purpose

This study aims to identify the trends that have changed in the field of construction management over the last 20 years.

Design/methodology/approach

In this study, 3,335 journal articles published in the years 2000–2020 were collected from the Web of Science database in construction management. The authors applied bibliometric analysis first and then detected topics with the latent Dirichlet allocation (LDA) topic detection method.

Findings

In this context, 20 clusters from cluster analysis were found and the topics were extracted in clusters with the LDA topic detection method. The results show “building information modeling” and “information management” are the most studied subjects, even though they have emerged in the last 15 years “building information modeling,” “information management,” “scheduling and cost optimization,” “lean construction,” “agile approach” and “megaprojects” are the trend topics in the construction management literature.

Research limitations/implications

This study uses bibliometric analysis. The authors accept that the co-citation and co-authorship relationship in the data is ethical. They accept that honorary authorship, self-citation or honorary citation do not change the pattern of the construction management research domain.

Originality/value

There has been no study conducted in the last 20 years to examine research trends in construction management. Although bibliometric analysis, systematic literature reviews and text mining methods are used separately as a methodology for extracting research trends, no study has used enhanced bibliometric analysis and the LDA topic detection text mining method.

Details

Engineering, Construction and Architectural Management, vol. 29 no. 8
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 23 May 2018

Chien-wen Shen, Duong Tuan Nguyen and Po-Yu Hsu

The purpose of this paper is to bibliometrically analyze the gerontology-related research articles for a comprehensive understanding of the gerontology literature.

1620

Abstract

Purpose

The purpose of this paper is to bibliometrically analyze the gerontology-related research articles for a comprehensive understanding of the gerontology literature.

Design/methodology/approach

This study employed the approach of visual analytics on 32 journals with a total of 99,204 articles published after 2000 to identify the main subfields, keywords, and growth trend. The investigated journals are either open access online or listed in the Social Sciences Citation Index. In addition, the 200 most frequently cited papers were analyzed through bibliographic coupling, co-word, and co-citation analysis.

Findings

The selected most cited papers were mostly published before 2007, and psychiatry and psychology were the top research subfields. Dementia, older adult, and Alzheimer’s disease were the three most frequently occurring keywords, both in Author Keywords and KeyWords Plus. While coupling analysis yielded 12 research groups, co-word analysis classified the most frequently used 20 Author Keywords into two categories. Four research clusters were identified by the co-citation analysis.

Originality/value

This research provides a comprehensive view of the gerontology research as well as an understanding of the subfields and their interrelations. It also provides government departments with directions for formulating and executing policies affecting older people not only in setting academic and professional priorities but also in understanding the key topics related to older people.

Details

Library Hi Tech, vol. 37 no. 1
Type: Research Article
ISSN: 0737-8831

Keywords

Content available
Article
Publication date: 13 August 2021

Runyue Han, Hugo K.S. Lam, Yuanzhu Zhan, Yichuan Wang, Yogesh K. Dwivedi and Kim Hua Tan

Although the value of artificial intelligence (AI) has been acknowledged by companies, the literature shows challenges concerning AI-enabled business-to-business (B2B…

2064

Abstract

Purpose

Although the value of artificial intelligence (AI) has been acknowledged by companies, the literature shows challenges concerning AI-enabled business-to-business (B2B) marketing innovation, as well as the diversity of roles AI can play in this regard. Accordingly, this study investigates the approaches that AI can be used for enabling B2B marketing innovation.

Design/methodology/approach

Applying a bibliometric research method, this study systematically investigates the literature regarding AI-enabled B2B marketing. It synthesises state-of-the-art knowledge from 221 journal articles published between 1990 and 2021.

Findings

Apart from offering specific information regarding the most influential authors and most frequently cited articles, the study further categorises the use of AI for innovation in B2B marketing into five domains, identifying the main trends in the literature and suggesting directions for future research.

Practical implications

Through the five identified domains, practitioners can assess their current use of AI and identify their future needs in the relevant domains in order to make appropriate decisions on how to invest in AI. Thus, the research enables companies to realise their digital marketing innovation strategies through AI.

Originality/value

The research represents one of the first large-scale reviews of relevant literature on AI in B2B marketing by (1) obtaining and comparing the most influential works based on a series of analyses; (2) identifying five domains of research into how AI can be used for facilitating B2B marketing innovation and (3) classifying relevant articles into five different time periods in order to identify both past trends and future directions in this specific field.

Details

Industrial Management & Data Systems, vol. 121 no. 12
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 8 August 2016

Deepa Mishra, Angappa Gunasekaran, Stephen J. Childe, Thanos Papadopoulos, Rameshwar Dubey and Samuel Wamba

The emergent field of Internet of Things (IoT) has been evolving rapidly with a geometric growth in the number of academic publications in this field. The purpose of this…

4716

Abstract

Purpose

The emergent field of Internet of Things (IoT) has been evolving rapidly with a geometric growth in the number of academic publications in this field. The purpose of this paper is to review the literature of IoT in past 16 years using rigorous bibliometric and network analysis tools, offering at the same time future directions for the IoT research community and implications for managers and decision makers.

Design/methodology/approach

The authors adopted the techniques of bibliometric and network analysis. The paper reviewed the articles published on IoT from 2000 to 2015.

Findings

This study identifies top contributing authors; key research topics related to the field; the most influential works based on citations and PageRank; and established and emerging research clusters. Scholars are encouraged to further explore this topic.

Research limitations/implications

This study focusses only on vision and applications of IoT. Scholars may explore various other aspects of this area of research.

Originality/value

To the best of authors’ knowledge, this is the first study to review the literature on IoT by using bibliometric and network analysis techniques. The study is unique as it spans a long time period of 16 years (2000-2015). The study proposes a five-cluster classification of research themes that may inform current and future research in IoT.

Details

Industrial Management & Data Systems, vol. 116 no. 7
Type: Research Article
ISSN: 0263-5577

Keywords

1 – 10 of over 1000