Multi‐scenario simulation on reducing CO 2 emissions from China's major manufacturing industries targeting 2060

2021 ◽  
Author(s):  
Sheng Zhou ◽  
Alun Gu ◽  
Qing Tong ◽  
Yuefeng Guo ◽  
Xinyang Wei
Keyword(s):  
Manufacturing Industries ◽  
Scenario Simulation

Regional Economic Potentials and Wages of Manufacturing Industries

2016 ◽  
Vol 46 (1) ◽  
pp. 63-82
Author(s):  
Atsushi WATANABE ◽  
Ryohei NAKAMURA
Keyword(s):  
Manufacturing Industries ◽  
Regional Economic

Technology Transfer in India: A Facet of Manufacturing Industries

2017 ◽  
Vol 12 (1) ◽  
pp. 15
Author(s):  
Rao K.S. Sekhara ◽  
Divya V. Sri ◽  
◽  
Keyword(s):  
Technology Transfer ◽  
Manufacturing Industries

Influential Factors of Collaborative Networks in Manufacturing: Validation of a Conceptual Model

10.28945/2120 ◽  
2015 ◽  
Vol 10 ◽  
pp. 001-019 ◽  
Author(s):  
Danny Wee Hock Quik ◽  
Nevan Wright ◽  
Ammar Rashid ◽  
Sivadass Thiruchelvam
Keyword(s):  
Organizational Support ◽  
Influential Factors ◽  
Perceived Usefulness ◽  
Manufacturing Industries ◽  
Collaborative Networks ◽  
Collaborative Network ◽  
Perceived Effectiveness ◽  
External Stakeholders ◽  
Technical Systems ◽  
External Learning

The purpose of the study is to identify influential factors in the use of collaborative networks within the context of manufacturing. The study aims to investigate factors that influence employees’ learning, and to bridge the gap between theory and praxis in collaborative networks in manufacturing. The study further extends the boundary of a collaborative network beyond enterprises to include suppliers, customers, and external stakeholders. It provides a holistic perspective of collaborative networks within the complexity of the manufacturing environment, based on empirical evidence from a questionnaire survey of 246 respondents from diverse manufacturing industries. Drawing upon the socio-technical systems (STS) theory, the study presents the theoretical context and interpretations through the lens of manufacturing. The results show significant influences of organizational support, promotive interactions, positive interdependence, internal-external learning, perceived effectiveness, and perceived usefulness on the use of collaborative networks among manufacturing employees. The study offers a basis of empirical validity for measuring collaborative networks in organizational learning and knowledge/information sharing in manufacturing.

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