scholarly journals Research on Technological Innovation Efficiency of Tourist Equipment Manufacturing Enterprises

2018 ◽  
Vol 10 (12) ◽  
pp. 4826 ◽  
Author(s):  
Yuanyuan Lin ◽  
Nianqi Deng ◽  
Hailian Gao
Keyword(s):  
Technological Innovation ◽  
Manufacturing Industry ◽  
Malmquist Index ◽  
Manufacturing Companies ◽  
Tobit Regression ◽  
Government Ownership ◽  
Management Level ◽  
Independent Innovation ◽  
Manufacturing Enterprises ◽  
Equipment Manufacturing

With the lack of quantitative literature related to the tourist equipment manufacturing industry, this study used the innovation input and output data from 12 listed tourist equipment manufacturing companies in 2011–2017 and employed data envelopment analysis (DEA)–Malmquist to analyze the change of technological innovation efficiency. The Malmquist index and its decompositions were used as dependent variables separately, and government ownership, cooperation with academics, and cooperation with international corporations as independent variables to construct a Tobit regression model. The results of static DEA show that the efficiencies of 12 tourist equipment manufacturing enterprises display a slight decline rule, and DEA–Malmquist analysis showed that the decline of technological innovation efficiency main derives from both the decline of technical efficiency and technical level. Moreover, other innovative subjects have different impacts on the technological innovation efficiency of China’s tourist equipment manufacturing enterprises. Thus, enterprises need to increase input of innovation and enhance the management level. In addition, they should manage the relationship between these innovative subjects and enhance the ability of collaborative innovation and independent innovation.

scholarly journals Innovation Efficiency of China’s High-End Manufacturing Industry: Evidence from Super-SBM Model and Malmquist Index

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Qiaochu Li ◽  
TingLi Liu
Keyword(s):  
Technological Innovation ◽  
Manufacturing Industry ◽  
Dynamic Change ◽  
Malmquist Index ◽  
Core Competitiveness ◽  
Management Level ◽  
Sbm Model ◽  
Incentive Policies ◽  
Low Efficiency ◽  
The Impact

Technological innovation is an important engine to support the development of China from a big manufacturing country to a powerful manufacturing country. With the support of government policies, China’s high-end manufacturing industry urgently needs to solve the problems of insufficient technological innovation and weak core competitiveness. This paper uses the super-SBM model to measure the impact of incentive policies related to high-end manufacturing industry on innovation efficiency of China’s high-end manufacturing industry in 2012–2017. The DEA Malmquist model is used to analyse the dynamic change trend of efficiency. The results show that the innovation efficiency of China’s high-end manufacturing industry shows a trend of gradual optimization, stepping into the middle and high-end levels, but there are large differences in innovation efficiency among industries, and the optimization process is not stable; at the same time, China’s high-end industry is not stable. Manufacturing industry needs to improve its pure technical efficiency as soon as possible and solve the problems of low efficiency of system and management level. Accordingly, this paper puts forward a series of policy suggestions, such as increasing financial and talent support, encouraging technological innovation, and promoting industrial synergy.

Grey relation analysis of 4S service pilot in high-end equipment manufacturing industry

2021 ◽  
pp. 1-13
Author(s):  
Chunyue Xiao ◽  
Jian Sun
Keyword(s):  
Manufacturing Industry ◽  
Relevant Literature ◽  
Competitive Advantages ◽  
Product Model ◽  
Model Framework ◽  
Manufacturing Enterprises ◽  
Customer Interaction ◽  
Cooperative Production ◽  
Equipment Manufacturing ◽  
Equipment Manufacturing Industry

Servitization has a significant impact on the upgrading and reform of the equipment manufacturing industry. From the perspective of application of high-end servitization theory in business practice of equipment manufacturing industry, based on the review of relevant literature, this paper analyzes the concept of integration delay strategy mechanism of cooperative production between enterprises and customers, and thus constructs the theoretical model framework of 4S service pilot high-end equipment manufacturing product-customer interaction experience. With the Liaoning equipment manufacturing industry as a case for quantitative analysis, the feasibility of using delay strategy in the 4S service pilot program is demonstrated, and the three-stage development plan of Liaoning 4S service pilot is outlined. The results show that: At present, in the trend of servitization of China’s equipment manufacturing enterprises, 4S service pilot high-end manufacturing product model enables equipment manufacturing enterprises to delay production time and produce according to customer orders, improve service efficiency and optimize resource allocation, and help enterprises to obtain new exclusive competitive advantages.

Study on Development Strategies of Chinese Equipment Manufacturing Industry

2014 ◽  
Vol 945-949 ◽  
pp. 2996-2999
Author(s):  
Liu Ping Chen
Keyword(s):  
Development Strategy ◽  
Manufacturing Industry ◽  
Production Capacity ◽  
Industry Structure ◽  
Export Trade ◽  
Production Scale ◽  
Independent Innovation ◽  
Equipment Manufacturing ◽  
Equipment Manufacturing Industry ◽  
Innovation Capacity

The achievement, which Chinese Equipment Manufacturing Industry had accomplished in the ten years after China accessed the World Trade Organization, is first analyzed through the production scale, the export trade, the industry structure and the comprehensive strength and so on in the paper. The problems, which exist in the products, the production capacity, the independent innovation capacity, the production means and the internal and external environment of Chinese Equipment Manufacturing Industry, are pointed out. Some suggestion on the future development strategy is last put forward.

scholarly journals Role of Servitization, Digitalization, and Innovation Performance in Manufacturing Enterprises

2021 ◽  
Vol 13 (17) ◽  
pp. 9878
Author(s):  
Lei Shen ◽  
Cong Sun ◽  
Muhammad Ali
Keyword(s):  
Manufacturing Industry ◽  
Dynamic Capabilities ◽  
Innovation Performance ◽  
Manufacturing Companies ◽  
Business Innovation ◽  
Manufacturing Enterprises ◽  
Enterprise Innovation ◽  
The Impact ◽  
The Relationship

The structure of the manufacturing industry has forced manufacturing companies to understand the importance of digitalization and servitization transformation, in terms of production and R&D. In this study, we examine the relationship between servitization, digitization, and enterprise innovation performance through the lens of dynamic capabilities within enterprises. We also discuss the impact of the transformation servitization strategy on business innovation, and the mechanisms by which it impacts business innovation performance. The study’s findings indicate that servitization significantly contributes to innovation performance, and digitalization acts as a mediating mechanism between the proposed relationships. Thus, this article argues for the integration and growth of servitization and digitization.

scholarly journals Classification of Japanese Electrical Equipment Manufacturing Industry Recovery Patterns after Disasters: Case Study of August 2019

2020 ◽  
Vol 11 (6) ◽  
pp. 150-155
Author(s):  
Kenji Yamaguchi ◽  
◽  
Yukari Shirota ◽  
Keyword(s):  
Stock Prices ◽  
Manufacturing Industry ◽  
Matrix Theory ◽  
Electrical Equipment ◽  
Manufacturing Companies ◽  
Tree Model ◽  
Class A ◽  
Equipment Manufacturing ◽  
Company Group ◽  
Inventory Turnover

In the paper, we analyze the recovery pattern of Japanese electrical equipment manufacturing companies after the President Trump remark in August 2019. The President’s remark made the companies’ stock prices decreased severely. The research consists of two parts. In the first part, we conducted Random Matrix Theory to extract representative decline/recovery patterns. Then we tagged A/B/C/D to the companies’ recovery types. The class A means a strong recover power. Then as the second part, we conducted machine learning tree-based classification using the tags A/B/C. The predictors are eight variables like ROA, ROE, and VAR. The resultant Decision Tree model provided us with the two different approaches to the class A group. The recovery and repulsion power will be higher in the company with high ROA and in the company that manufactured the product with high VAR. In addition, another class A company group is made and the feature is the high inventory turnover ratio.

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