| Issue |
E3S Web Conf.
Volume 214, 2020
2020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|
|
|---|---|---|
| Article Number | 01029 | |
| Number of page(s) | 6 | |
| Section | Big Data Analysis Application and Energy Consumption Research | |
| DOI | https://doi.org/10.1051/e3sconf/202021401029 | |
| Published online | 07 December 2020 | |
Exploring the Impact of Organizational Implants of a Manufacturing Company on Service Innovation in the context of big data: A case study of XI’AN SHAANGU POWER
1 School of Modern Posts, Xi’an University of Posts & Telecommunications Xi’an, China
2 Department of Industrial Systems Engineering and Management, National university of Singapore, Singapore
3 School of Economics and Management, Xi’an University of Technology Xi’an, China
a wangronganqi@126.com
b zhudan@u.nus.edu
c chen-juhong@163.com
Service innovation has become an important way for manufacturing companies to obtain and maintain their competitive advantages. Organizational implants have been proven to enhance service innovation in manufacturing companies, while the rise of big data offers new opportunities for it. This study aims to explore the impact path from organizational implants of a manufacturing company to service innovation in the context of big data with the application of Single Case Study Method, and XI’AN SHAANGU POWER is selected as research object. The findings are suggested as follows: (1) There are two ways of organizational implants to achieve service innovation for manufactures. One is employee implants, and the other is device implants. (2) Employee implants can create relationship capital, and device implants can generate data resources. (3) Relationship capital has a direct and indirect positive impact on service innovation through professional knowledge acquisition and customer demands mining. (4) Data resources have an indirect positive impact on service innovation through customer demands mining and product technology upgrading.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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