Huimin Liu, Fuying Lu, Binyan Shi, Ying Hu and Min Li
As global supply chains continue to develop, uncertainty grows and supply chains are frequently threatened with disruption. Although big data technology is being used to improve…
Abstract
Purpose
As global supply chains continue to develop, uncertainty grows and supply chains are frequently threatened with disruption. Although big data technology is being used to improve supply chain resilience, big data technology's role in human–machine collaboration is shifting between “supporters” and “substitutes.” However, big data technology's applicability in supply chain management is unclear. Choosing appropriate big data technology based on the enterprise's internal and external environments is important.
Design/methodology/approach
This study built a three-factor structural model of the factors “management support,” “big data technology adoption” and “supply chain resilience”. Big data technology adoption was divided into big data-assisted decision-making technology (ADT) and big data intelligent decision-making technology (IDT). A survey was conducted on more than 260 employees from supply chain departments in Chinese companies. The data were analyzed through structural equation modeling using Analyze of Moment Structures (AMOS) software.
Findings
The study's empirical results revealed that adopting both ADT and IDT improved supply chain resilience. The effects of both types of big data were significant in low-dynamic environments, but the effect of IDT on supply chain resilience was insignificant under high-dynamic environments. The authors also found that government support had an insignificantly effect on IDT adoption but significantly boosted ADT adoption, whereas management support factors promoted both ADT and IDT adoption.
Originality/value
By introducing two types of big data technology from the perspectives of the roles in human–machine collaborative decision-making, the research results provide a theoretical basis and management implications for enterprises to reduce the supply chain risk of enterprises.
Details
Keywords
Fuying Zhang and Yuanhao Zhang
This paper aims to study the effect of isosceles triangle micro concave texture with different parameters on the performance of oil seal to obtain a reasonable combination of…
Abstract
Purpose
This paper aims to study the effect of isosceles triangle micro concave texture with different parameters on the performance of oil seal to obtain a reasonable combination of parameters.
Design/methodology/approach
Based on the theory of elastohydrodynamic lubrication, a numerical model is established by coupling the texture parameters of isosceles triangle with concave lip with the two-dimensional average Reynolds equation considering surface roughness.
Findings
The results show that there is an optimal combination of parameters to improve the performance of the oil seal. When hp = 5µm-6.5 µm, a = 110°−130°, O = 1.4, C = 1.6 mm-2.2 mm, the oil seal with isosceles triangle micro concave texture can show good lubrication characteristics, friction characteristics and sealing ability.
Originality/value
The model provides a new idea for the design of new oil seal products and provides a theoretical support for the application of surface texture technology in the sealing field in the future.