Humanitarian supply chain: a bibliometric analysis and future research directions

2020 ◽  
Author(s):  
Samuel Fosso Wamba
Keyword(s):  
Supply Chain ◽  
Bibliometric Analysis ◽  
Future Research ◽  
Research Directions ◽  
Future Research Directions ◽  
Humanitarian Supply Chain

scholarly journals Mapping and Clustering Analysis on Environmental, Social and Governance Field a Bibliometric Analysis Using Scopus

2021 ◽  
Vol 13 (13) ◽  
pp. 7304
Author(s):  
Shang Gao ◽  
Fanchen Meng ◽  
Zhouyang Gu ◽  
Zhiyuan Liu ◽  
Muhammad Farrukh
Keyword(s):  
Bibliometric Analysis ◽  
Clustering Analysis ◽  
Research Agenda ◽  
Future Research ◽  
Unique Contribution ◽  
Research Directions ◽  
Current Trends ◽  
Bibliographic Data ◽  
Future Research Directions ◽  
Scopus Database

Academic interest in ESG has grown significantly in recent years. Nevertheless, bibliometric and visualization research on this topic is still insufficient. This study aims to conduct publication metrics on the literature connected with ESG and attempt to give a research agenda for future research. In this study, we used data from the Scopus database. Various bibliometric techniques, such as bibliographic coupling and co-occurrence analysis, were combined with assorted themes to present an overview. To the best of our knowledge, there is no study that analyses the bibliographic data on ESG fields; this study is a unique contribution to the literature. This study also provides an overview of the trends and trajectories with a visual and schematic frame for the research of this topic. This may help researchers understand the current trends and future research directions, and enable future authors to conduct their studies more effectively.

A systematic review of the literature on supply chain agility

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bharat Singh Patel ◽  
Murali Sambasivan
Keyword(s):  
Supply Chain ◽  
Cost Benefit ◽  
Business Environment ◽  
Future Research ◽  
Research Directions ◽  
Content Type ◽  
Trade Offs ◽  
Supply Chain Agility ◽  
Agility Assessment ◽  
Future Research Directions

Purpose The purpose of this study is to critically examine the scholarly articles associated Murali Sambasivan with the diverse aspects of supply chain agility (SCA). The review highlights research insights, existing gaps and future research directions that can help academicians and practitioners gain a comprehensive understanding of SCA. Design/methodology/approach The present study has adopted author co-citation analysis as the research methodology, with a view to thoroughly investigating the good-quality articles related to SCA that have been published over a period of 22 years (1999-2020). In this study, 126 research papers on SCA – featuring diverse aspects of agility – from various reputed journals have been examined, analysed and assimilated. Findings The salient findings of this research are, namely, agility is different from other similar concepts, such as flexibility, leanness, adaptability and resilience; of the 13 dimensions of agility discussed in the literature, the prominent ones are quickness, responsiveness, competency and flexibility; literature related to SCA can be categorised as related to modelling the enablers, agility assessment, agility implementation, leagility and agility maximisation. This research proposes a more practical definition and framework for SCA. The probable areas for future research are, namely, impediments to agility, effective approaches to agility assessment, cost-benefit trade-offs to be considered whilst implementing agility, empirical research to validate the framework and SCA in the domain of healthcare and disaster relief supply chains. Practical implications This paper provides substantial insights to practitioners who primarily focus on measuring and implementing agility in the supply chain. The findings of this study will help the supply chain manager gain a better idea about how to become competitive in today’s dynamic and turbulent business environment. Originality/value The originality of this study is in: comprehensively identifying the various issues related to SCA, such as related concepts, definitions, dimensions and different categories of studies covered in literature, proposing a new definition and framework for SCA and identifying potential areas for future research, to provide deeper insights into the subject and highlight areas for future research.

Retail Customer Engagement

2019 ◽  
pp. 1-26
Author(s):  
Andrea Moretta Tartaglione ◽  
Giuseppe Granata
Keyword(s):  
Literature Review ◽  
Bibliometric Analysis ◽  
Scientific Community ◽  
State Of The Art ◽  
Customer Engagement ◽  
Future Research ◽  
Research Directions ◽  
Study Results ◽  
Research Findings ◽  
Future Research Directions

Customer engagement is one of the most debated topics in marketing literature. The great interest of the scientific community resulted in a large amount of research on this topic making it difficult for scholars to understand how to really contribute to advance the research. Based on these considerations, this chapter aims to provide an overview of the research findings and trends of previous studies to guide the researcher to the most influential works, results, and issues that need more insights. In particular, this chapter offers a literature review on customer engagement and retail customer engagement using bibliometric analysis and scientific mapping study. Results show the most productive authors, most cited publications, most frequent words, and clusters of related words. The analysis provides a description of the state of the art of retail customer engagement and suggests future research directions.

Big Data Analytics Driven Supply Chain Transformation

2019 ◽  
pp. 106-124 ◽  
Author(s):  
Mondher Feki
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Research Directions ◽  
Digital Platforms ◽  
New Frontier ◽  
Future Research Directions ◽  
Chain Transformation

Big data has emerged as the new frontier in supply chain management; however, few firms know how to embrace big data and capitalize on its value. The non-stop production of massive amounts of data on various digital platforms has prompted academics and practitioners to focus on the data economy. Companies must rethink how to harness big data and take full advantage of its possibilities. Big data analytics can help them in giving valuable insights. This chapter provides an overview of big data analytics use in the supply chain field and underlines its potential role in the supply chain transformation. The results show that big data analytics techniques can be categorized into three types: descriptive, predictive, and prescriptive. These techniques influence supply chain processes and create business value. This study sets out future research directions.

scholarly journals Supply chain risk management modelling: A systematic literature network analysis review

2020 ◽  
Vol 31 (4) ◽  
pp. 387-416
Author(s):  
Marcus Vinicius Carvalho Fagundes ◽  
Eduardo Oliveira Teles ◽  
Silvio A B Vieira de Melo ◽  
Francisco Gaudêncio Mendonça Freires
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Network Analysis ◽  
Future Research ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Risk Models ◽  
Research Directions ◽  
Research Areas ◽  
Future Research Directions

Abstract The modelling of supply chain risk management (SCRM) has attracted increasing attention from researchers and professionals. However, a systematic network analysis of the literature to understand the development of research over time is lacking. Therefore, this study reviews SCRM modelling and its evolution as a scientific field. We collected 566 papers published in the Scopus database and shortlisted 120 for review. We have analysed the field's performance, mapped the most influential studies, as well as the generative and evolutionary research areas, and derived future research directions. Using bibliometric methods and tools for citation network analysis to understand the field's dynamic development, we find that five generative research areas provide the fundamental knowledge for four evolutionary research areas. The interpretation of gaps and trends in these areas provides an SCRM modelling timeline with 14 future research directions, which should consider adopting a holistic SCRM approach and developing prescriptive and normative risk models. The holistic approach enables more research on key factors—like process integration, design, information risk, visibility and risk coordination—that directly impact industry, decision-makers and sustainability needs. Risk models with evolved prescriptive and normative typology should respect both business model strategies and actual supply chain performance.

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