A Study on Relationship of BDBA(Big Data Business Analytics) System and Supply Chain Management

2019 ◽  
Vol 19 (2) ◽  
pp. 89-107
Author(s):  
Seong Ho Kim
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Business Analytics ◽  
Chain Management ◽  
Relationship Of

scholarly journals The impact of big data and business analytics on supply chain management

2015 ◽  
Vol 9 (1) ◽  
Author(s):  
Hans W. Ittmann
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Business Analytics ◽  
Chain Management ◽  
Business Competitiveness ◽  
The Impact ◽  
Proper Analysis

Background: Change is inevitable and as supply chain managers prepare for the future they face many challenges. Two major trends over the last few years are the growing importance of ‘big data’ and analysing these data though ‘analytics’. The data contain much value and companies need to capitalise on the variety of data sources by in-depth and proper analysis through the use of ‘big data’ analytics.Objective: This article endeavours to highlight the evolving nature of the supply chain management (SCM) environment, to identify how the two major trends (‘big data’ and analytics) will impact SCM in future, to show the benefits that can be derived if these trends are embraced and to make recommendations to supply chain managers.Method: The importance of extracting value from the huge amounts of data available in the SCM area is stated. ‘Big data’ and analytics are defined and the impact of these in various SCM applications clearly illustrated.Results: It is shown, through examples, how the SCM area can be impacted by these new trends and developments. In these examples ‘big data’ analytics have already been embraced, used and implemented successfully. Big data is a reality and using analytics to extract value from the data has the potential to make a huge impact.Conclusion: It is strongly recommended that supply chain managers take note of these two trends, since better use of ‘big data’ analytics can ensure that they keep abreast with developments and changes which can assist in enhancing business competitiveness.

scholarly journals Use of Big Data in Supply Chain Management

2021 ◽  
Vol 9 (9) ◽  
pp. 2082-2087
Author(s):  
Sudhanshu Gupta
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Business Intelligence ◽  
Big Data Analytics ◽  
Research Progress ◽  
Business Analytics ◽  
Chain Management ◽  
Scor Model ◽  
Comprehensive Picture

Abstract: The rapidly expanding interest in the application of big data analytics (BDA) in supply chain management (SCM) among academics and practitioners has prompted an assessment of current research progress in order to define a new agenda. the use of sophisticated analytics tools to improve supply chain management The apps are divided into three categories: descriptive, predictive, and prescriptive analytics, as well as the supply chain operations reference (SCOR) model domains of plan, source, make, deliver, and return. This review answers to the demand by offering a new classification scheme that provides a comprehensive picture of current literature on where and how BDA has been used in SCM. The classification system is based on Mayring's (2008) content analysis method and addresses four research questions: (1) In which aspects of SCM is BDA used? (2) To what extent is BDA employed in these SCM domains in terms of analytics? (3) What are the different types of BDA models utilised in SCM? (4) How are these models developed using BDA techniques? The consideration of these four topics reveals several research gaps, pointing to future study directions. Purpose - Rapid innovation and globalisation have created a plethora of opportunities and choices for businesses and consumers in the marketplace. Due to competitive pressures, sourcing and manufacturing are now done on a global basis, resulting in a huge increase in product availability. The purpose of this article is to determine whether real-time business intelligence (BI) is required in supply chain analytics. Design/methodology/approach – The paper argues for and analyses the benefits and drawbacks of BI. Findings – The article focuses on the need to review the classic BI notion of integrating and consolidating information in an organisation in order to help service-oriented businesses that want to keep their customers. Using a BI methodology to improve the effectiveness and efficiency of supply chain analytics is a vital component of a company's ability to establish a competitive edge. Originality/value – This study contributes to a better understanding of the difficulties surrounding the usage of business intelligence tools in supply chains. Keywords: Supply chain management, Business analytics, Information systems, Big Data, Big data analysis

Big Data Analytics in the Agribusiness Supply Chain Management

2021 ◽  
Vol 9 (3) ◽  
pp. 32-42
Author(s):  
Marisol Valencia-Cárdenas ◽  
Jorge Anibal Restrepo-Morales ◽  
Francisco Javier Día-Serna
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Structural Equation Model ◽  
Inventory Management ◽  
Latent Variables ◽  
Structural Equation ◽  
Big Data Analytics ◽  
Equation Model ◽  
Chain Management

Importance and impact of the systems related to Agribusiness and Agri-food, are increasing around the world and demand a paramount attention. Collaboration in the inventory management is an integral part of the supply chain management, related to proactive integration among the chain actors facilitating production and supply, in especial in the agroindustrial sector of the Departamento de Antioquia, Colombia. This research establishes the main relationships between latent variables as collaboration, technology, models, optimization and inventory management, based on a literature review and applying a Structural Equation Model to a survey data of a sample of agribusiness companies. The results show that Available Technologies associated with Big Data, generates improvement of Collaboration Strategies, improving also Forecasting and Optimization; besides, Inventory Planning and Collaboration are related to Available Technologies associated with Big Data. A Poisson regression model and a Structural Equation Model estimations detect that the increasing strategies of technologies and Big Data are favorable to apply collaboration in the supply chain management, increasing possibilities to the enterprise competitiveness.

scholarly journals Uncovering the Relationship of Supply Chain Management and Firm Performance: Evidence from Textile Sector of Pakistan

2018 ◽  
Vol 10 (2) ◽  
pp. 23-29
Author(s):  
Zahid Hussain ◽  
Ahmad Bin Jusoh ◽  
Muhammad Sarfraz ◽  
Khalil Ur Rehman Wahla
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Firm Performance ◽  
Research Paper ◽  
Chain Management ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship ◽  
Textile Sector

The purpose of this research paper was to find the impact of the supply chain on firm performance in Textile firm of Pakistan. Data was collected through questioners in the month of March 2018, Approximately 30 questioners were distributed among the managers of the ten textile organizations in Faisalabad which are expected to have the best knowledge about the supply chain operations and its impact on the performance of the organization, all of them responded positively. It is found that dimensions associated with SCM methods as well as explain the connection amongst SCM methods, aggressive benefit, as well as firm performance. The actual study focuses on the causal associations in between SCM exercise, aggressive benefit as well as firm performance as well as ignores the actual feasible recursive associations.  

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