When platform exploits data analysis advantage: change of OEM-led supply chain structure

Purpose The purpose of this paper is to discuss the roles of a supply chain management (SCM) department. To achieve that, this study empirically examines the relationship between internal supply chain structure and operational performance, using survey data collected from 108 Japanese manufacturers. Design/methodology/approach Based on a literature review of not only organizational theory but also other fields such as marketing, logistics management, operations management and SCM, this study focused on two structural properties, formalization and centralization and divided operational performance to firm-centric efficiency and customer-centric responsiveness. To examine the analytical model using these dimensions, this study conducted a structural equation modeling. Findings The correlation between centralization of operational tasks and centralization of strategic tasks, the impacts of centralization of both tasks on formalization and the effect of formalization on responsiveness performance were demonstrated. In addition, the reasons for formalization not positively influencing efficiency performance were explored through follow-up interviews. Practical implications Manufacturers need to formalize, as much as possible, a wide range of SCM tasks to realize operational excellence. To establish such formalized working methods, it is effective to centralize the authorities of both operational and strategic tasks in a particular department. In addition, inefficiency due to strict logistics service levels is a problem that all players involved in the supply chain of various industries should work together to solve. Originality/value The theoretical contribution of this study is that the authors established an empirical process that redefined the constructs of formalization and centralization, developed these measures and examined the impacts of these structural properties on operational performance.

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Supply Chain Structure as a Critical Driver of Sustainable Supplier Practices

Cross-Sector Leadership for the Green Economy ◽

10.1057/9781137015891_11 ◽

2011 ◽

pp. 195-219

Author(s):

Amrou Awaysheh ◽

Robert D. Klassen

Keyword(s):

Supply Chain ◽

Chain Structure ◽

Supply Chain Structure

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A Computational Intelligence Approach to Supply Chain Demand Forecasting

Machine Learning ◽

10.4018/978-1-60960-818-7.ch603 ◽

2012 ◽

pp. 1551-1565 ◽

Cited By ~ 1

Author(s):

Nicholas Ampazis

Keyword(s):

Supply Chain ◽

Computational Intelligence ◽

Demand Forecasting ◽

Business Environment ◽

Chain Structure ◽

Support Vector ◽

Customer Demand ◽

Public Data ◽

Vector Machines ◽

Supply Chain Structure

Estimating customer demand in a multi-level supply chain structure is crucial for companies seeking to maintain their competitive advantage within an uncertain business environment. This work explores the potential of computational intelligence approaches as forecasting mechanisms for predicting customer demand at the first level of organization of a supply chain where products are presented and sold to customers. The computational intelligence approaches that we utilize are Artificial Neural Networks (ANNs), trained with the OLMAM algorithm (Optimized Levenberg-Marquardt with Adaptive Momentum), and Support Vector Machines (SVMs) for regression. The effectiveness of the proposed approach was evaluated using public data from the Netflix movie rental online DVD store in order to predict the demand for movie rentals during the critical, for sales, Christmas holiday season.

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Real World Applications

Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-4666-9644-0.ch004 ◽

2016 ◽

pp. 113-132

Author(s):

Ibibia K. Dabipi ◽

Judy A. Perkins ◽

Tierney Moore

Keyword(s):

Supply Chain ◽

Supply Chain Management ◽

Real World ◽

Chain Structure ◽

Total Asset ◽

Chain Management ◽

Real World Applications ◽

End To End ◽

Supply Chain Structure

Over the years the supply chain industry has been transforming to improve the end-to-end (production to delivery) process. Supply chain management (SCM) allows various industries to oversee and better handle how their product is manufactured and delivered. It allows them to track and identify the location of the product and to be more efficient in delivery. Integrating total asset visibility (TAV) technology into the supply chain structure can provide excellent visibility of a product. This kind of visibility complemented with various packaging schemes can assist in accommodating optimization strategies for visualizing the movement of a product throughout the entire supply chain pipeline. The chapter will define SCM, discuss TAV, review how transportation as well as optimization impacts SCM and TAV, and examine the role of packaging in the context of SCM and TAV.

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