A big data based architecture for collaborative networks: Supply chains mixed-network

2021 ◽  
Author(s):  
Lahcen Tamym ◽  
Lyes Benyoucef ◽  
Ahmed Nait Sidi Moh ◽  
Moulay Driss El Ouadghiri
Keyword(s):  
Big Data ◽  
Supply Chains ◽  
Collaborative Networks ◽  
Mixed Network

scholarly journals How to evaluate sustainability of supply chains? A dynamic network DEA approach

2017 ◽  
Vol 117 (9) ◽  
pp. 1866-1889 ◽  
Author(s):  
Vahid Shokri Kahi ◽  
Saeed Yousefi ◽  
Hadi Shabanpour ◽  
Reza Farzipoor Saen
Keyword(s):  
Big Data ◽  
Supply Chains ◽  
Real World ◽  
Performance Optimization ◽  
Network Dynamic ◽  
Network Dea ◽  
Content Type ◽  
Dea Model ◽  
Proposed Model ◽  
First Time

Purpose The purpose of this paper is to develop a novel network and dynamic data envelopment analysis (DEA) model for evaluating sustainability of supply chains. In the proposed model, all links can be considered in calculation of efficiency score. Design/methodology/approach A dynamic DEA model to evaluate sustainable supply chains in which networks have series structure is proposed. Nature of free links is defined and subsequently applied in calculating relative efficiency of supply chains. An additive network DEA model is developed to evaluate sustainability of supply chains in several periods. A case study demonstrates applicability of proposed approach. Findings This paper assists managers to identify inefficient supply chains and take proper remedial actions for performance optimization. Besides, overall efficiency scores of supply chains have less fluctuation. By utilizing the proposed model and determining dual-role factors, managers can plan their supply chains properly and more accurately. Research limitations/implications In real world, managers face with big data. Therefore, we need to develop an approach to deal with big data. Practical implications The proposed model offers useful managerial implications along with means for managers to monitor and measure efficiency of their production processes. The proposed model can be applied in real world problems in which decision makers are faced with multi-stage processes such as supply chains, production systems, etc. Originality/value For the first time, the authors present additive model of network-dynamic DEA. For the first time, the authors outline the links in a way that carry-overs of networks are connected in different periods and not in different stages.

A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions

2021 ◽  
Vol 170 ◽  
pp. 120927
Author(s):  
Yigit Kazancoglu ◽  
Muhittin Sagnak ◽  
Sachin Kumar Mangla ◽  
Muruvvet Deniz Sezer ◽  
Melisa Ozbiltekin Pala
Keyword(s):  
Big Data ◽  
Supply Chains ◽  
Decision Framework

Big Data Analytics for Climate-Resilient Food Supply Chains: Opportunities and Way Forward

2021 ◽  
pp. 181-192
Author(s):  
Navin Kumar C. Twarakavi ◽  
Kamal Das ◽  
Mohamed Akram Zaytar ◽  
Fred Otieno ◽  
Jitendra Singh ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chains ◽  
Food Supply ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Food Supply Chains

Theorizing Supply Chains with Qualitative Big Data and Topic Modeling

2020 ◽  
Vol 56 (2) ◽  
pp. 7-18 ◽  
Author(s):  
Pratima (Tima) Bansal ◽  
Jury Gualandris ◽  
Nahyun Kim
Keyword(s):  
Big Data ◽  
Supply Chains ◽  
Topic Modeling

scholarly journals A multi-agent based system with big data processing for enhanced supply chain agility

2016 ◽  
Vol 29 (5) ◽  
pp. 706-727 ◽  
Author(s):  
Mihalis Giannakis ◽  
Michalis Louis
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Semantic Web ◽  
Supply Chains ◽  
Multi Agent Systems ◽  
Content Type ◽  
Agent Based ◽  
Agent Systems ◽  
Supply Chain Agility ◽  
Multi Agent

Purpose Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored. Design/methodology/approach For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled. Findings Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility. Research limitations/implications The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems. Practical implications The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis. Originality/value A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.

scholarly journals BIG DATA APPLIED TO CYBER-PHYSICAL LOGISTIC SYSTEMS: CONCEPTUAL MODEL AND PERSPECTIVES

2015 ◽  
Vol 12 (2) ◽  
pp. 330 ◽  
Author(s):  
Enzo Morosini Frazzon ◽  
Moisés Lima Dutra ◽  
William Barbosa Vianna
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Acquisition ◽  
Supply Chains ◽  
Conceptual Model ◽  
Critical Issue ◽  
Research Management ◽  
Conceptual Approach ◽  
Flow Of Information ◽  
Innovative Techniques

<p>The management of supply chains and their subsystems embodies strategic and contemporaneous challenges. The competitiveness of supply chains depends increasingly on their flexibility. Logistics as a supply chain function has to compensate increasing requirements regarding flexibility by means of a higher information density and the employment of innovative techniques for data acquisition and analytics. Indeed, the flow of information that commands the physical flow embodies a critical issue for the management of supply chains. Hence, by means of a theoretical and conceptual approach, this paper aims to propose to research management perspectives and propose a model for the application of innovative techniques for data acquisition and analytics in Cyber-Physical Logistic Systems.</p>

Big data and predictive analytics in humanitarian supply chains

2018 ◽  
Vol 29 (2) ◽  
pp. 485-512 ◽  
Author(s):  
Rameshwar Dubey ◽  
Zongwei Luo ◽  
Angappa Gunasekaran ◽  
Shahriar Akter ◽  
Benjamin T. Hazen ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chains ◽  
Survey Data ◽  
Predictive Analytics ◽  
Cross Sectional ◽  
Content Type ◽  
Humanitarian Supply Chains ◽  
Swift Trust ◽  
Humanitarian Supply Chain

PurposeThe purpose of this paper is to understand how big data and predictive analytics (BDPA), as an organizational capability, can improve both visibility and coordination in humanitarian supply chains.Design/methodology/approachThe authors conceptualize a research model grounded in contingent resource-based view where the authors propose that BDPA capabilities affect visibility and coordination under the moderating effect of swift trust. Using ordinary least squares regression, the authors test the hypotheses using survey data collected from informants at 205 international non-government organizations.FindingsThe results indicate that BDPA has a significant influence on visibility and coordination. Further, the results suggest that swift trust does not have an amplifying effect on the relationships between BDPA and visibility and coordination. However, the mediation test suggests that swift trust acts as a mediating construct. Hence, the authors argue that swift trust is not the condition for improving coordination among the actors in humanitarian supply chains.Research limitations/implicationsThe major limitation of the study is that the authors have used cross-sectional survey data to test the research hypotheses. Following Guide and Ketokivi (2015), the authors present arguments on how to address the limitations of cross-sectional data or use of longitudinal data that can address common method bias or endogeneity-related problems.Practical implicationsManagers can use this framework to understand: first, how organizational resources can be used to create BDPA, and second, how BDPA can help build swift trust and be used to improve visibility and coordination in the humanitarian supply chain.Originality/valueThis is the first research that has empirically tested the anecdotal and conceptual evidence. The findings make notable contributions to existing humanitarian supply chain literature and may be useful to managers who are contemplating the use of BDPA to improve disaster-relief-related activities.

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