Doing qualitative research: a practical handbook, by David Silverman, Los Angeles, Sage, 2010, 456 pp., AU$65.00, ISBN 978-1-84860-033-1, ISBN 978-1-94960-034-8. Available in Australia and New Zeal...

Doing qualitative research: a practical handbook

How to conduct a bibliometric analysis: An overview and guidelines

Globalisation of supply chains makes their management and control more difficult. Blockchain technology, as a distributed digital ledger technology which ensures transparency, traceability, and sec...

Blockchain technology and its relationships to sustainable supply chain management

527 articles related to imbalanced data and rare events are reviewed.Viewing reviewed papers from both technical and practical perspectives.Summarizing existing methods and corresponding statistics by a new taxonomy idea.Categorizing 162 application papers into 13 domains and giving introduction.Some opening questions are discussed at the end of this manuscript. Rare events, especially those that could potentially negatively impact society, often require humans decision-making responses. Detecting rare events can be viewed as a prediction task in data mining and machine learning communities. As these events are rarely observed in daily life, the prediction task suffers from a lack of balanced data. In this paper, we provide an in depth review of rare event detection from an imbalanced learning perspective. Five hundred and seventeen related papers that have been published in the past decade were collected for the study. The initial statistics suggested that rare events detection and imbalanced learning are concerned across a wide range of research areas from management science to engineering. We reviewed all collected papers from both a technical and a practical point of view. Modeling methods discussed include techniques such as data preprocessing, classification algorithms and model evaluation. For applications, we first provide a comprehensive taxonomy of the existing application domains of imbalanced learning, and then we detail the applications for each category. Finally, some suggestions from the reviewed papers are incorporated with our experiences and judgments to offer further research directions for the imbalanced learning and rare event detection fields.

Learning from class-imbalanced data

Risk assessment and risk management: Review of recent advances on their foundation

Green supply chain management: A review and bibliometric analysis

Quantitative models for managing supply chain risks: A review

This paper aims to examine the past and present research on ‘green ports and maritime logistics’ in order to identify established research streams and fertile research areas with potential for future investigations. Using rigorous bibliometric and network analysis tools, the paper completes a systemic mapping of the existing literature and identifies the key investigators, collaboration patterns, research clusters and interrelationships, and the “seminal research areas” that have provided the field with the foundational knowledge, concepts, theories, tools, and techniques. Major articles within each seminal research area are also identified. This will allow new researchers to quickly build understanding in a particular sub-field by reading these major articles. The findings obtained from the evolution of seminal research areas over time are important from both research and practice perspectives and can help the field grow in many dimensions.

Greening ports and maritime logistics: A review

The main purpose of this research is to provide an agenda for future warehousing research relevant for both academic development and practitioners’ needs. In order to suggest a practically relevant future research agenda, first a comprehensive literature review was performed to identify research areas covered in the literature. Then, 15 warehouse managers and senior consultants were interviewed to add empirical input to the development of potential future research areas. The literature review reveals gaps, both methodology- and topic-wise. A considerable methodological imbalance is observed. Some of the highlighted managerial concerns have been investigated in the literature extensively, but the managerial concerns emphasized mostly do not belong to the most researched categories. While most of the practitioners’ concerns relate to supportive aspects of warehousing business, a relatively high number of the reviewed studies highlight operational problems. The suggested future research agenda highlights the importance of supportive aspects of the warehousing business, employment of real data in analysis and empirical research methods. The insights from practitioners stress the expected trends of business environment such as more volatile demand, higher desire for customized services and more expansion of e-commerce.

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Toward a relevant agenda for warehousing research: literature review and practitioners’ input

As a result of globalization in the past two decades, supply chains are encountering more unknown conditions and risks. One important category of risks is disruptions that block material flowing through a supply chain and that may even result in end-product manufacturing failure. This paper uses a Petri nets-based model as a tool to understand the dissemination of disruptions and to trace the operational performance of a supply chain. The presented approach models how changes propagate through a supply chain and calculates the impact of disruptions on supply chain attributes by concluding the states that are obtainable from a given initial status in the supply chain.

Hoda Davarzani

Papers

Green supply chain management: A review and bibliometric analysis

Quantitative models for managing supply chain risks: A review

Greening ports and maritime logistics: A review

Toward a relevant agenda for warehousing research: literature review and practitioners’ input

Developing a supply chain disruption analysis model: Application of colored Petri-nets