Can intelligent manufacturing empower manufacturing? – an empirical study considering ambidextrous capabilities
| DOI | https://doi.org/10.1108/IMDS-11-2021-0718 |
| Published date | 31 May 2022 |
| Date | 31 May 2022 |
| Pages | 188-203 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Na Lu,Wei Zhou,Zhi Wu Dou |
Can intelligent manufacturing
empower manufacturing? –an
empirical study considering
ambidextrous capabilities
Na Lu
Business School, Yunnan University of Finance and Economics, Kunming, China and
School of Economics and Management, Qujing Normal University, Qujing, China
Wei Zhou
School of Finance, Yunnan University of Finance and Economics, Kunming,
Kunming, China, and
Zhi Wu Dou
School of International Business, Zhejiang Yuexiu University, Shaoxing, China
Abstract
Purpose –Intelligent manufacturing has attracted extensive attention from national strategy, academic
research and enterprises’practices. The purpose of this study is to investigate the influence of intelligent
manufacturing on performance in manufacturing firms. Moreover, how intelligent manufacturing technology
affects enterprise performance, this study provided a practice that can be replicated by other businesses.
Design/methodology/approach –This study uses text mining to collect the intelligence level of Chinese
listed companies. It uses quantitative analysis to test the proposed model based on samples of 2,091
manufacturers.
Findings –Intelligent manufacturing has positive effect on short-term performance and long-term
performance. Intelligent manufacturing can empower firms with ambidextrous capabilities, including
exploit capability and explore capability. Exploit capability has positive effects on short-term performance and
long-term performance. Explore capability has negative effects on short-term performance, but has positive
effects on long-term performance.
Originality/value –On the theoretical side, it enriches the research framework between intelligent
manufacturing and enterprise performance. This study explains the preconditions and results of ambidextrous
capabilities. Moreover, based on the practice-based view (PBV), this study proposes that technologies can be
used as strategies, filling a gap in the existing research on strategic management. On the practicalside, how to
quantify the intelligent manufacturing level of enterprises provides a certain reference. Also, this study
provides an easy to imitate practice that can serve as a model for under-performing enterprises.
Keywords Intelligent manufacturing, Enterprise performance, Exploit capability, Explore capability, PBV
Paper type Research paper
1. Introduction
With the advances of new technologies such as CPS, IOT, cloud manufacturing, big data,
additive manufacturing, sensors, anthropomorphic intelligence and other technologies,
manufacturing can deeply integrate these new technologies to realize the intelligence of
manufacturing equipment and manufacturing process. Intelligent manufacturing leadership
coalition described the increased use of the advanced information technologies in
manufacturing as “Intelligent manufacturing (Smart Manufacturing)”. Intelligent
manufacturing is a collection of various technologies through the convergence of humans,
technology,and information (Kang et al.,2016). So far, intelligent manufacturing has attracted
extensive attention from national strategy, academic research and enterprises practices.
IMDS
123,1
188
This work was supported by the Natural Science Foundation of China (No. 72071176).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 25 November 2021
Revised 10 February 2022
23 March 2022
Accepted 8 April 2022
Industrial Management & Data
Systems
Vol. 123 No. 1, 2023
pp. 188-203
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-11-2021-0718
Driven by the new generation of technology, many countries have proposed national
strategies for manufacturing development, such as advanced manufacturing in the United
States, Industry 4.0 plan in Germany, “La Nouvelle France Industrielle”in France and made in
China 2025. The common aim for them is to achieve intelligent manufacturing.
In the literature, the impact of technology on enterprise performance presents different
results: (1) IT payoff: technologies have positive effects on performance (Devaraj and Kohli,
2003;El-Tamimi et al., 2012;Brynjolfsson and McElheran, 2016;Ilmudeen et al., 2019;Zhang
et al., 2019;Dhyne et al., 2020;Terence et al., 2020;Wei and Sun, 2021;Xuan and Zhang, 2021).
(2) IT paradox: the application of technology may not really improve performance (Sun et al.,
2017;Grant and Yeo, 2018).
China hasimplemented intelligentmanufacturing demonstrationpilot work since 2015,and
the Ministryof Industry and InformationTechnology will announce sometypical projects and
enterprises every year. Driven by the pilot demonstration enterprises, more and more
enterprises have begun to carry out intelligent transformation. On one hand, intelligent
manufacturing increases benefits to enterprises, such as reduced costs, flexibility, speed,
quality (Olsen and Tomlin, 2020). On the other hand, intelligent manufacturing also brings
great challenges to enterprises, such as high capital investment, uncertain income, locking
impact (Zhang,2021). Because of the huge investment at earlystage and the uncertain payoff,
many enterprises have taken a more cautious attitude towards intelligent manufacturing
technology(Nordensvard et al., 2018).Enterprises act as themain implementation of intelligent
manufacturingtechnology. The intelligent transformation of China’smanufacturing industry
can be realized only when enterprises truly improve their performance.
This study uses Chinese enterprises as the subject because China’s intelligent
manufacturing development path is unique (Zhou, 2015;Zhou et al., 2019). The practice-
based view (PBV) sees technology as one of the most critical reasons for performance, and
how firms use technology is also important. Intelligent manufacturing technology reflect
resources owned by enterprises, but whether resources can play roles also needs to be
combined with the enterprise’s other resources (Park and Mithas, 2020). The integration of
resources helps the company develop ambidextrous capabilities, which can explain how
companies apply technologies.
The following are some of the possible marginal contributions of this study: (1) On the
theoretical side: first, it enriches the research framework between intelligent manufacturing
and enterprise performance. Second, this study explains the preconditions and antecedent
result of ambidexterity capabilities. Third, this study suggests that technologies can be used
as strategies to improve performance, filling a gap in existing strategic management
research. (2) On the practical side: first, quantifying the intelligent manufacturing level
provides a certain reference. Second, this study provides an easy to imitate practice, which
can provide some reference for those under-performing enterprises.
This study aims to address the following research questions: RQ1: open the black box of
“IT business value puzzle”(Melville et al., 2004). RQ2: What is the antecedent variable and the
antecedent result of ambidexterity capabilities? RQ3: under which circumstances does this
practice have guiding significance for other enterprises?
The reminder of this study is organized as follows: Section 2 givens a theoretical
background and hypothesis development. Research methods are provided in Section 3.
Sections 4 provides the study results. Finally, our discussions are given in Section 5.
2. Theoretical background and hypothesis development
2.1 The practice-based view
The PBV suggests that the use of publicly known practices significantly influences firm
performance (Bromiley and Rau, 2014). The practice is a define activity or set of actives which
The influence
of intelligent
manufacturing
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