scholarly journals Social media data analytics to improve supply chain management in food industries

2018 ◽  
Vol 114 ◽  
pp. 398-415 ◽  
Author(s):  
Akshit Singh ◽  
Nagesh Shukla ◽  
Nishikant Mishra
Keyword(s):  
Social Media ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Data Analytics ◽  
Social Media Data ◽  
Chain Management ◽  
Food Industries ◽  
Media Data ◽  
Improve Supply Chain

Adoption of Big Data Analytics in Supply Chain Management

2021 ◽  
Vol 14 (2) ◽  
pp. 88-107
Author(s):  
Amin Khalil Alsadi ◽  
Thamir Hamad Alaskar ◽  
Karim Mezghani
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Top Management ◽  
Management Support ◽  
Chain Management ◽  
Top Management Support ◽  
Intention To Adopt

Supported by the literature on big data, supply chain management (SCM), and resource-based theory (RBT), this study aims to evaluate the organizational variables that influence the intention of Saudi SCM professionals to adopt big data analytics (BDA) in SCM. A survey of 220 supply chain respondents revealed that both top management support and data-driven culture have a high significant influence on their intention to adopt BDA. However, the firm entrepreneurial orientation showed no significant effect. Also, the findings revealed that supply chain connectivity positively moderates the link between top management support and intention. This study contributes to the practical field, offering valuable insights for decision makers considering BDA adoption in SCM. It also contributes to the literature by helping minimize the research gap in BDA adoption in the Saudi context.

Big Data and Cloud Computing

2018 ◽  
pp. 1-28 ◽  
Author(s):  
Marcus Tanque ◽  
Harry J Foxwell
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Data Analytics ◽  
Large Scale ◽  
Big Data Analytics ◽  
Chain Management ◽  
Computing Services ◽  
Cloud Computing Services

Big data and cloud computing are transforming information technology. These comparable technologies are the result of dramatic developments in computational power, virtualization, network bandwidth, availability, storage capability, and cyber-physical systems. The crossroads of these two areas, involves the use of cloud computing services and infrastructure, to support large-scale data analytics research, providing relevant solutions or future possibilities for supply chain management. This chapter broadens the current posture of cloud computing and big data, as associate with the supply chain solutions. This chapter focuses on areas of significant technology and scientific advancements, which are likely to enhance supply chain systems. This evaluation emphasizes the security challenges and mega-trends affecting cloud computing and big data analytics pertaining to supply chain management.

Big Data Analytics in Supply Chain Management

2021 ◽  
pp. 2443-2457
Author(s):  
Nenad Stefanovic
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Data Analytics ◽  
Data Science ◽  
Big Data Analytics ◽  
Current Approach ◽  
Data Systems ◽  
Chain Management ◽  
Big Data Systems

The current approach to supply chain intelligence has some fundamental challenges when confronted with the scale and characteristics of big data. In this chapter, applications, challenges and new trends in supply chain big data analytics are discussed and background research of big data initiatives related to supply chain management is provided. The methodology and the unified model for supply chain big data analytics which comprises the whole business intelligence (data science) lifecycle is described. It enables creation of the next-generation cloud-based big data systems that can create strategic value and improve performance of supply chains. Finally, example of supply chain big data solution that illustrates applicability and effectiveness of the model is presented.

Social Media Data Analytics for the U.S. Construction Industry: Preliminary Study on Twitter

2017 ◽  
Vol 33 (6) ◽  
pp. 04017038 ◽  
Author(s):  
LiYaning Tang ◽  
Yiming Zhang ◽  
Fei Dai ◽  
Yoojung Yoon ◽  
Yangqiu Song ◽  
...  
Keyword(s):  
Social Media ◽  
Construction Industry ◽  
Data Analytics ◽  
Social Media Data ◽  
Preliminary Study ◽  
Media Data ◽  
The U.S
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