scholarly journals RY BULK AND GENERAL CARGO TERMINALS IN THE SUPPLY CHAIN: A DELPHI STUDY FOR ALIAGA

2021 ◽  
Author(s):  
Gül DENKTAŞ ŞAKAR ◽  
Ali UZUN
Keyword(s):  
Supply Chain ◽  
Delphi Study ◽  
General Cargo

Dynamic supply chain design: a Delphi study of drivers and barriers

2017 ◽  
Vol 55 (22) ◽  
pp. 6846-6856 ◽  
Author(s):  
Thorsten Krægpøth ◽  
Jan Stentoft ◽  
Jesper Kronborg Jensen
Keyword(s):  
Supply Chain ◽  
Delphi Study ◽  
Supply Chain Design

Delphi study on supply chain flexibility

2005 ◽  
Vol 43 (13) ◽  
pp. 2687-2708 ◽  
Author(s):  
R. R. Lummus * ◽  
R. J. Vokurka ◽  
L. K. Duclos
Keyword(s):  
Supply Chain ◽  
Delphi Study ◽  
Chain Flexibility ◽  
Supply Chain Flexibility

scholarly journals Identifying barriers for implementing green supply chain management (GSCM) in footwear industry of Bangladesh: a Delphi study approach

2018 ◽  
Vol 18 (3) ◽  
pp. 175-186 ◽  
Author(s):  
Md. Rayhan Sarker ◽  
Faruk Ahmed ◽  
Amal Kanti Deb ◽  
Manjushree Chowdhury
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Delphi Study ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Chain Management ◽  
Study Approach ◽  
Footwear Industry

scholarly journals Information sharing across multiple supply chain tiers: A Delphi study on antecedents

2017 ◽  
Vol 193 ◽  
pp. 77-86 ◽  
Author(s):  
Joakim Kembro ◽  
Dag Näslund ◽  
Jan Olhager
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Delphi Study

Blockchain application in supply chain chemical substance reporting - a Delphi study

2021 ◽  
Vol 11 (1) ◽  
pp. 75
Author(s):  
Sukhraj Singh Takhar ◽  
Kapila Liyanage
Keyword(s):  
Supply Chain ◽  
Delphi Study ◽  
Chemical Substance

Understanding the key success factors of RFID use in Supply Chain Management: a Delphi study

2010 ◽  
Vol 8 (3) ◽  
pp. 313 ◽  
Author(s):  
Shin Yuan Hung ◽  
She I Chang ◽  
Chi Ping Ting
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Delphi Study ◽  
Success Factors ◽  
Chain Management ◽  
Key Success Factors

scholarly journals Practitioners understanding of big data and its applications in supply chain management

2018 ◽  
Vol 29 (2) ◽  
pp. 555-574 ◽  
Author(s):  
Morten Brinch ◽  
Jan Stentoft ◽  
Jesper Kronborg Jensen ◽  
Christopher Rajkumar
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Delphi Study ◽  
Questionnaire Survey ◽  
Chain Management ◽  
Content Type ◽  
Process Framework ◽  
Planning Processes ◽  
Process Perspective

Purpose Big data poses as a valuable opportunity to further improve decision making in supply chain management (SCM). However, the understanding and application of big data seem rather elusive and only partially explored. The purpose of this paper is to create further guidance in understanding big data and to explore applications from a business process perspective. Design/methodology/approach This paper is based on a sequential mixed-method. First, a Delphi study was designed to gain insights regarding the terminology of big data and to identify and rank applications of big data in SCM using an adjusted supply chain operations reference (SCOR) process framework. This was followed by a questionnaire-survey among supply chain executives to elucidate the Delphi study findings and to assess the practical use of big data. Findings First, big data terminology seems to be more about data collection than of data management and data utilization. Second, the application of big data is most applicable for logistics, service and planning processes than of sourcing, manufacturing and return. Third, supply chain executives seem to have a slow adoption of big data. Research limitations/implications The Delphi study is explorative by nature and the questionnaire-survey rather small in scale; therefore, findings have limited generalizability. Practical implications The findings can help supply chain managers gain a clearer understanding of the domain of big data and guide them in where to deploy big data initiatives. Originality/value This study is the first to assess big data in the SCOR process framework and to rank applications of big data as a mean to guide the SCM community to where big data is most beneficial.

scholarly journals ISO 9001 and Supply Chain Integration Principles Based Sustainable Development: A Delphi Study

2018 ◽  
Vol 10 (12) ◽  
pp. 4569 ◽  
Author(s):  
Ali Bastas ◽  
Kapila Liyanage
Keyword(s):  
Sustainable Development ◽  
Supply Chain ◽  
Conceptual Framework ◽  
Diagnostic Tool ◽  
Delphi Study ◽  
Triple Bottom Line ◽  
Supply Chain Integration ◽  
Iso 9001 ◽  
Organizational Sustainability ◽  
Bottom Line

Driven by the increasing stakeholder and societal pressures, organizations and supply chains face the multi-dimensional challenges of not only integrating economic, environmental and social agendas into their management systems but also driving continual sustainability performance improvement. Aiming to support organizations in this sustainable development challenge, this paper explores the strategic management principles of ISO 9001 and supply chain integration from the lens of triple bottom line sustainability. Derived from theoretical synergies, a conceptual framework for integration, measurement, and improvement of triple bottom line sustainability is constructed and a business diagnostic tool introduced to facilitate the implementation of the framework. The developed conceptual framework and diagnostic tool are verified through an expert panel-based Delphi study and positive relationships formulated between the management principles of ISO 9001, supply chain integration and sustainability management. The facilitating and catalyzing role of quality management and supply chain management principles for integration and improvement of organizational sustainability is outlined.

scholarly journals Traceability in Textile and Clothing Supply Chains: Classifying Implementation Factors and Information Sets via Delphi Study

2019 ◽  
Vol 11 (6) ◽  
pp. 1698 ◽  
Author(s):  
Tarun Agrawal ◽  
Rudrajeet Pal
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Delphi Study ◽  
High Agreement ◽  
Related Information ◽  
Factors Influencing ◽  
Information Sets ◽  
Product Specifications ◽  
Implementation Factors

The purpose of this study is twofold. First, to explore and classify factors influencing traceability implementation, and second, to cluster essential traceability-related information that demands recording and sharing with businesses and customers, in the context of the textile and clothing supply chain. A Delphi study is conducted with 23 experts (including research practitioners and industry experts) to explore, validate, and classify traceability factors and related information using distribution analyses and hierarchal clustering. As a result, 14 factors and 19 information sets are identified and classified with a moderately high agreement among the experts. Among these, risk management, product authentication, and visibility are the highest ranked and the most important factors influencing traceability implementation in the textile and clothing supply chain. While origin, composition, and sustainability-related information are crucial for sharing with customers, the information vital to businesses includes manufacturer/supplier details, product specifications, and composition. It is noteworthy that this research is among the few that classifies traceability factors and information through expert perspectives, and it creates decisive knowledge of traceability for the textile and clothing supply chain. It further provides insights on the extent to which this information can be shared among supply chain actors. Outcomes of this study can be helpful for the development of an information traceability framework. Policymakers can use the results to draft traceability guidelines/regulations, whilst top management can develop traceability-related strategies.

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