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
Author(s):  
Robert Glenn Richey ◽  
Tyler R. Morgan ◽  
Kristina Lindsey-Hall ◽  
Frank G. Adams

Purpose Journals in business logistics, operations management, supply chain management, and business strategy have initiated ongoing calls for Big Data research and its impact on research and practice. Currently, no extant research has defined the concept fully. The purpose of this paper is to develop an industry grounded definition of Big Data by canvassing supply chain managers across six nations. The supply chain setting defines Big Data as inclusive of four dimensions: volume, velocity, variety, and veracity. The study further extracts multiple concepts that are important to the future of supply chain relationship strategy and performance. These outcomes provide a starting point and extend a call for theoretically grounded and paradigm-breaking research on managing business-to-business relationships in the age of Big Data. Design/methodology/approach A native categories qualitative method commonly employed in sociology allows each executive respondent to provide rich, specific data. This approach reduces interviewer bias while examining 27 companies across six industrialized and industrializing nations. This is the first study in supply chain management and logistics (SCMLs) to use the native category approach. Findings This study defines Big Data by developing four supporting dimensions that inform and ground future SCMLs research; details ten key success factors/issues; and discusses extensive opportunities for future research. Research limitations/implications This study provides a central grounding of the term, dimensions, and issues related to Big Data in supply chain research. Practical implications Supply chain managers are provided with a peer-specific definition and unified dimensions of Big Data. The authors detail key success factors for strategic consideration. Finally, this study notes differences in relational priorities concerning these success factors across different markets, and points to future complexity in managing supply chain and logistics relationships. Originality/value There is currently no central grounding of the term, dimensions, and issues related to Big Data in supply chain research. For the first time, the authors address subjects related to how supply chain partners employ Big Data across the supply chain, uncover Big Data’s potential to influence supply chain performance, and detail the obstacles to developing Big Data’s potential. In addition, the study introduces the native category qualitative interview approach to SCMLs researchers.


2020 ◽  
Vol 10 (1) ◽  
pp. 62
Author(s):  
Poppy Laksita Rini

Disaster supply chain management is different from the supply chain management of commercial organization because of the high level of uncertainty. The high level of uncertainty significantly affects the availability of logistic supplies that are  needed  by the victims of the disaster. This study discovers the key success factors of the disaster supply chain management based on the perspective of the government. The re- search specifically study the Government of the D.I. Yogyakarta that are represented by Badan Penanggulangan Bencana Daerah (BPBD). Due the fact that Yogyakarta as one of the regions that have the high risk of catastrophic nature in Indonesia. The study will be carried out in a qualitative methodology by conducting deep interview with the Representative of Logistics Department in BPBD. The results of in-depth interviews with four representative of BPBD found that there are six key success factors of disasater management supply chain management which are : (1) Quality of the TRC Team Assessment Results; (2) BPBD Coordination with Government and Non-Government; (3) Effective Rules and Regulations; (4) Character and Attitude of the Community in Dealing with Disasters; (5) BPBD Warehouse Inventory Management; (6) Management Information Systems and Data Updates.


2018 ◽  
Vol 78 ◽  
pp. 19-27
Author(s):  
Rafał Matwiejczuk

Firms are constantly looking for ways to create a competitive advantage. An important place among the factors affecting the way in which this advantage is gained is taken by success factors including, but not limited to, the so-called key success factors that may be related to the domains of logistics and supply chain management. The aim of the article is to identify the basic characteristics of the concept of key success factors in logistics and supply chain management. The article presents the essence and importance of success factors in the context of creating the business competitive advantage, the basic concepts of key success factors related to resource-based and market-based strategic management as well as the most significant characteristics of the concept of key success factors in logistics and supply chain management.


2020 ◽  
Vol 13 (1) ◽  
pp. 56
Author(s):  
Tino Herden

Purpose: Analytics research is increasingly divided by the domains Analytics is applied to. Literature offers little understanding whether aspects such as success factors, barriers and management of Analytics must be investigated domain-specific, while the execution of Analytics initiatives is similar across domains and similar issues occur. This article investigates characteristics of the execution of Analytics initiatives that are distinct in domains and can guide future research collaboration and focus. The research was conducted on the example of Logistics and Supply Chain Management and the respective domain-specific Analytics subfield of Supply Chain Analytics. The field of Logistics and Supply Chain Management has been recognized as early adopter of Analytics but has retracted to a midfield position comparing different domains.Design/methodology/approach: This research uses Grounded Theory based on 12 semi-structured Interviews creating a map of domain characteristics based of the paradigm scheme of Strauss and Corbin.Findings: A total of 34 characteristics of Analytics initiatives that distinguish domains in the execution of initiatives were identified, which are mapped and explained. As a blueprint for further research, the domain-specifics of Logistics and Supply Chain Management are presented and discussed.Originality/value: The results of this research stimulates cross domain research on Analytics issues and prompt research on the identified characteristics with broader understanding of the impact on Analytics initiatives. The also describe the status-quo of Analytics. Further, results help managers control the environment of initiatives and design more successful initiatives.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Isaac Sakyi Damoah

PurposeThis study explores the critical success factors (CSFs) in humanitarian supply chain management (HSCM) by focussing on flood disaster management (FDM) in Ghana.Design/methodology/approachAn in-depth semi-structured interview and questionnaire surveys in a sequential data collection approach were used to collect data from definitive stakeholders of humanitarian organisations. The data was analysed using exploratory factor analysis (EFA), confirmatory factors analysis (CFA) and structural equation modelling (SEM) techniques.FindingsSeventy-four factors were identified as success factors of HSCM of flood disaster management. However, 41 of these factors were statistically significant and considered as critical. In descending order, these factors relate to management practices, education and training, stakeholder involvement and cooperation, infrastructure, innovation and technology, materials and resources, administrative practices, socio-cultural and economic. Whilst some factors are internal to the humanitarian organisations, others are external factors that are beyond the control of humanitarian organisations.Research limitations/implicationsEven though this study offers empirical results that could guide policymakers in their decision-making about humanitarian operations, care needs to be taken since the data is within one country and within a specific disaster context – hence, policymakers need to consider the local contextual dynamics. Future studies could look at different disasters context to make a comparative analysis of various types of disaster operations.Practical implicationsInstitutions such as World Health Organization, Red Cross organisations and UN seeking to curbs global-warming-related disasters and the reduction of the effects of flood disaster can use findings as a guide during the formulation of HSCM policies and strategies.Originality/valueUnlike previous studies of humanitarian operations that focussed extensively on theoretical expositions, simulations, conceptual frameworks and models, this present study offers empirical evidence of humanitarian operations in the context of SCM. Further, by highlighting on the HSCM CSFs, this study contributes to disaster reduction and their effects on humanity in the context of FDM. This research could be used as guide by governments and FDM organisations to make informed decisions on SCM areas to focus the most during FDM.


2011 ◽  
Vol 5 (17) ◽  
pp. 7240-7247 ◽  
Author(s):  
Chin Thoo Hon Tat Huam Ai ◽  
Md Yusoff Rosman ◽  
Md Rasli Amran ◽  
Bakar Abd Hamid Abu

DECISION ◽  
2018 ◽  
Vol 45 (1) ◽  
pp. 3-25 ◽  
Author(s):  
Dayal S. Prasad ◽  
Rudra P. Pradhan ◽  
Kunal Gaurav ◽  
Partha P. Chatterjee ◽  
Inderpal Kaur ◽  
...  

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