Third-generation biofuel supply chain: A comprehensive review and future research directions

2021 ◽  
Vol 323 ◽  
pp. 129100
Author(s):  
Mostafa Abbasi ◽  
Mir Saman Pishvaee ◽  
Shayan Mohseni
Keyword(s):  
Supply Chain ◽  
Future Research ◽  
Third Generation ◽  
Research Directions ◽  
Comprehensive Review ◽  
Biofuel Supply Chain ◽  
Future Research Directions ◽  
Generation Biofuel

scholarly journals Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification

2020 ◽  
Author(s):  
Zheng Wang ◽  
Zhixiang Wang ◽  
Yinqiang Zheng ◽  
Yang Wu ◽  
Wenjun Zeng ◽  
...  
Keyword(s):  
Video Analysis ◽  
State Of The Art ◽  
Future Research ◽  
Low Resolution ◽  
Research Directions ◽  
Comprehensive Review ◽  
Practical Applications ◽  
Future Research Directions

An efficient and effective person re-identification (ReID) system relieves the users from painful and boring video watching and accelerates the process of video analysis. Recently, with the explosive demands of practical applications, a lot of research efforts have been dedicated to heterogeneous person re-identification (Hetero-ReID). In this paper, we provide a comprehensive review of state-of-the-art Hetero-ReID methods that address the challenge of inter-modality discrepancies. According to the application scenario, we classify the methods into four categories --- low-resolution, infrared, sketch, and text. We begin with an introduction of ReID, and make a comparison between Homogeneous ReID (Homo-ReID) and Hetero-ReID tasks. Then, we describe and compare existing datasets for performing evaluations, and survey the models that have been widely employed in Hetero-ReID. We also summarize and compare the representative approaches from two perspectives, i.e., the application scenario and the learning pipeline. We conclude by a discussion of some future research directions. Follow-up updates are available at https://github.com/lightChaserX/Awesome-Hetero-reID

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.

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.

scholarly journals Lean and Agile model implementation for managing the supply chain

2020 ◽  
Vol 14 (1) ◽  
pp. 847-858
Author(s):  
Youssef Hassani ◽  
Ioana Ceauşu ◽  
Adrian Iordache
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Scientific Literature ◽  
Supply Chain Integration ◽  
Future Research ◽  
Research Directions ◽  
Demand And Supply ◽  
Chain Management ◽  
Future Research Directions ◽  
Agile Model

AbstractEven though both researchers and practitioners propose several approaches to supply chain management research and the scientific literature shows that several methods have been implemented for supply chain management, the studies carried out have not revealed a formalized process or a clear method for supply chain integration. Indeed, there is a specific way to achieve this integration in the supply chain and there are differences in how one company does it compared to another. More recently, an alternative based on the Lean and Agile paradigms has been presented. The implementation of the Lean and Agile models to the supply chain aims to improve and simplify the production and the process of minimizing or eliminating wastes of all kinds, raise the productivity of the supply chain, increase the capability to respond quickly to unpredictable and changing customer demands and to take advantage of the uncertainty and the volatility of the market in the medium term. The main objective of this paper is to conduct an impact study on the implementation of Lean and Agile models in the supply chain, based on a review of the scientific literature concerning the models implemented to improve the productivity of the supply chain. We aim to identify and analyze the research carried out regarding the implementation of Lean and Agile models in order to improve the supply chain management, the results achieved and future research directions. Although the Lean and Agility paradigms are distinct and can be developed differently, they can be successfully integrated into a well-designed supply chain integration that involves a substantial degree of ambiguity in terms of significance and level of application across different supply chains, in order to increase the capacity to act, react and adapt to changes in demand and supply.

scholarly journals Graph Neural Networks: Taxonomy, Advances, and Trends

2022 ◽  
Vol 13 (1) ◽  
pp. 1-54
Author(s):  
Yu Zhou ◽  
Haixia Zheng ◽  
Xin Huang ◽  
Shufeng Hao ◽  
Dengao Li ◽  
...  
Keyword(s):  
Neural Networks ◽  
Real World ◽  
Research Community ◽  
Future Research ◽  
Research Directions ◽  
Comprehensive Review ◽  
Future Research Directions ◽  
Graph Neural Networks ◽  
Low Dimensional

Graph neural networks provide a powerful toolkit for embedding real-world graphs into low-dimensional spaces according to specific tasks. Up to now, there have been several surveys on this topic. However, they usually lay emphasis on different angles so that the readers cannot see a panorama of the graph neural networks. This survey aims to overcome this limitation and provide a systematic and comprehensive review on the graph neural networks. First of all, we provide a novel taxonomy for the graph neural networks, and then refer to up to 327 relevant literatures to show the panorama of the graph neural networks. All of them are classified into the corresponding categories. In order to drive the graph neural networks into a new stage, we summarize four future research directions so as to overcome the challenges faced. It is expected that more and more scholars can understand and exploit the graph neural networks and use them in their research community.

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