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Researchers continue to seek understanding of industrialization as a state managed process. How to create and implement new industries based on advanced knowledge is on the policy agenda of many advanced nations. Measures that promote these developments include national capacity building in science and technology, the formation of technology transfer systems, and the establishment of industrial clusters. What these templates often overlook is an analysis of use. This chapter aims to increase the understanding of the processes that embed new solutions in structures from an industrial network perspective. The chapter describes an empirical study of high-technology industrialization in Taiwan that the researcher conducts to this end. The study shows that the Taiwanese industrial model is oversimplified and omits several important factors in the development of new industries. This study bases its findings on the notions that resource combination occurs in different time and space, the new always builds on existing resource structures, and the users are important as active participants in development processes.

The purpose of the paper is to examine the coevolutionary dynamics between multistage overseas mergers and acquisitions (M&A) integration and knowledge network reconfiguration and the impact of this coevolution on industrial technology innovation.

This paper builds a coevolution analysis framework in stages and constructs structural equation models for empirical tests using the Chinese technology-sourcing overseas M&A events that occurred from 2001 to 2012.

Overseas M&A integration and knowledge network reconfiguration are in a coevolutionary relationship, driving industrial technology innovation. The acquirer adopts initial integration degree that matches the resource relatedness between the acquiring and acquired parties, promoting initial industrial technology innovation through initial knowledge network reconfiguration. Initial knowledge network reconfiguration will feed back to the M&A integration decision in the mid-to-late stage through increasing knowledge similarity and narrowing network position difference. The higher the improvement of mid-to-late integration degree, the more it can drive mid-to-late industrial technology innovation through mid-to-late knowledge network reconfiguration.

Future research can accurately classify overseas M&A integration stages through case tracking and explore other network attributes.

Practical guidelines are provided for managers on how to implement a multistage overseas M&A integration strategy, optimize knowledge network reconfiguration and promote industrial technology innovation. Significant practical implications are presented, especially in academia, society and quality of life.

Different from the previous research considering M&A integration as a single-stage decision, this paper emphasizes the dynamics of the M&A integration process and explores the coevolution mechanism of multistage overseas M&A integration and knowledge network reconfiguration.

Knowledge input development and innovation implementation are new features of industrial technology innovation. The purpose of this study is to find the process of coordination and ecological spiral in the ambidextrous innovation of industrial technology.

To design the model of industrial technology ambidextrous innovation based on knowledge ecology spiral, an input-output model of knowledge for ambidextrous innovation and a spiral model of knowledge ecology were constructed based on an improved Lotka-Volterra model. Then, the equilibriums in different knowledge inputs and the spiral evolution of knowledge ecology were analyzed. Finally, the ambidextrous coordination mechanism of the core organization was revealed.

By coordinating the knowledge inputs and the knowledge ecology spiral, enterprises extend the R&D investments in the innovation chain, which will facilitate the knowledge inputs of the exploitative and exploratory innovation. Implementing the ambidextrous coordination in the technology innovation chain and the knowledge ecology chain has the advantage of promoting knowledge inputs, mobility and ecological spiral. Meanwhile, it can achieve the “multi-source, integration and coordination” development of industrial technology innovation.

The two-element innovative knowledge input coordination model and the knowledge ecological spiral model based on the improved Lotka-Volterra model are constructed, which extends the modeling way of the traditional knowledge input-output profit model. It is expected to reduce the amount of knowledge input of a single member and provide theoretical reference for improving the efficiency of knowledge input by constructing the inter-dependent regenerative and inter-generative knowledge interaction.

The authors observe the influence of intellectual capital (IC) on innovation performance with the mediating role of interorganizational learning (IOL) in the Pakistani automotive industry. Besides, industrial Internet of things (IoT) technology is used as moderating variables between IOL and innovation performance.

Structural equation modeling (SEM) presents scholars with extra flexibility and enhanced research conclusions. SEM is described as a statistical methodology and the best tool used for hypothesis testing. The authors used partial least squares SEM for testing hypotheses. The simple random sampling technique followed to collect data from respondents, and 492 questionnaires were used for analysis.

The outcomes reveal that IC enhances innovation performance and IOL. Moreover, IOL increases innovation performance. IOL significantly mediates between IC and innovation performance. Industrial IoT technology improves innovation performance. Finally, industrial IoT technology strengthens the positive association between IOL and innovation performance.

This study concentrates on the issue of how managers use IOL and industrial IoT technology to take higher advantage of IC that increases innovation performance.

This is the initial study that builds a theoretical framework to integrate IC, IOL, industrial IoT technology and innovation performance. Although prior researchers observe the association between IC and innovation performance, less concentration was paid to understand the role of interorganizational leadership and industrial IoT technology in leveraging organizational IC.

This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.

A quantitative analysis of the Tai-Xin Integrated Economic Zone in China is conducted using data collected through a questionnaire survey. An evaluation index for the development level of advanced manufacturing clusters is constructed, and a structural equation model is used to identify key influencing factors and governance pathways.

This paper reveals that factors such as industrial foundation, technological innovation capability, social institution environment and government policies have a significant positive impact on the development of digital innovation ecosystem in advanced manufacturing clusters. It constructs a governance model for the digital innovation ecosystem and proposes three major pathways: integration of heterogeneous innovation resources, enhancement of digital capabilities, and fostering digital collaborative governance. The crucial role of digital technology in improving data processing efficiency, optimizing resource allocation and promoting collaboration among entities is emphasized. These pathways can optimize resource allocation, boosting the competitiveness and innovation capacity of clusters.

By incorporating advanced manufacturing clusters into the digital innovation ecosystem framework, this paper enriches theoretical research on both fronts. It offers specific governance pathways and policy recommendations, providing valuable references and guidance for promoting the digital transformation and ecosystem construction of manufacturing clusters.

This paper aims to investigate the performance of Jiangsu Province industrial technology innovation strategy alliance.

Through a preliminary investigation of 30 Jiangsu industrial technology innovation strategic alliances, this paper analyzed the status and extracted 18 alliances to conduct an in-depth investigation. By grey evaluation method based on center-point triangular whitenization weight function, the paper classified and analyzed alliances.

The results show that university or research institutions-oriented alliance perform better, but the government/enterprise-oriented alliance perform diverse, and majority is rated “general”.

The paper succeeds in clustering analysis to Jiangsu Province industrial technology innovation strategy alliance with insufficient data. And according to the result of clustering, it analyzes the causes, which provide value information for the sustainable development of Jiangsu Province industrial technology innovation strategy alliance.

This thesis deeply studies the impact mechanism of digital service trade on the high-quality development of the manufacturing industry from the aspects of technological innovation and industrial structure.

In this thesis, 40 countries from 2010 to 2020 were selected as samples, and the panel fixed-effect model and intermediary effect model were used to empirically analyze the impact path of digital service trade on the high-quality development of global manufacturing.

Overall, digital service trade has a positive impact on the high-quality development of the global manufacturing industry. Through the analysis of the intermediary effect mechanism, it is found that digital service trade can further positively affect the high-quality development of the global manufacturing industry by promoting technological innovation and industrial structure upgrading.

Based on the empirical results, targeted countermeasures and suggestions are given in this paper.

Through the test of national heterogeneity, it is found that in developing countries, digital service trade mainly acts on the high-quality development of the manufacturing industry by promoting industrial structure upgrading.

In developed countries, digital service trade mainly promotes the high-quality development of manufacturing through technological innovation; from the perspective of industry heterogeneity, the three service industries of information and communication technology (ICT), other business services and property have the intermediary effect of technological innovation and industrial structure.

This manuscript suggests that trade in digital services should be promoted as a national trade priority.

Innovation is vital for sustainable regional development. Government is generally not a source of innovation per se, but the authors shows that by establishing and funding an industrial innovation ecosystem, it can create fertile conditions for research institutions to introduce innovative technologies into industry and for industry to introduce its gaps and needs to motivate and direct academic research. This paper aims to present a case study of the Jiangsu Industrial Technology Research Institute (JITRI) as a “triple helix” collaboration model engaging Industry-University-Research (IUR) institutions. The authors aim to provide a fresh perspective on constructing innovation ecosystems, promoting value creation and advancing the adoption of industrial technology.

Taking JITRI as a case study, this research examines its innovative approaches to interfacing with IUR organizations within China’s Yangtze Delta region. The authors propose a multilayered framework where JITRI serves as the core, facilitating the formation of a robust innovation ecosystem with diverse IUR entities.

This framework comprises three layers: core, platform and support. JITRI acts as the central nexus, binding these elements together and fostering a cohesive innovation ecosystem. By analyzing the operational mechanisms of the Jiangsu Provincial innovation system, the authors gain valuable insights into how JITRI bridges the gap between academia and industry. This facilitates the efficient commercialization of technologies. The success of the JITRI approach presents a compelling model for emulation by other provincial innovation ecosystems seeking to enhance their innovation capabilities.

This study enriches the ongoing conversation on innovation ecosystems, proposing novel avenues for further research. However, the field requires continuous monitoring through longitudinal studies. Given the long-term nature of such initiatives, the full impact of this approach might only be realized over several decades.

JITRI aims to create a robust and innovative provincial innovation ecosystem through its focus on IUR collaboration. This unique approach offers valuable insights and ideas for fostering the development of thriving innovation ecosystems in other provinces. These insights encompass new perspectives on innovation ecosystem development, value creation and industrial advancement.

This study pioneers the use of the JITRI system as a case study, offering valuable insights with potential application to innovation ecosystems across China and globally.

Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The purpose of this paper is to bring new empirical evidence to the controversial role of early adopters in the diffusion of innovations in industrial markets.

The authors apply an actor market configuration perspective to the analysis of four longitudinal case studies regarding the commercialization of new products in the textile, plastic and energy industries.

The diffusion of innovation is an interactive and iterative process where the commercializing firm engages in repeated interactions with different categories of companies that are targeted as potential early adopters. This process ends when the commercializing firm identifies a category of early adopters that can stimulate subsequent acceptance in the later market, by playing one of the following two roles, i.e. word-of-mouth trigger and industry benchmark. During this process, through which the role of the early adopters is constructed proactively by the commercializing firm, the product innovation is also subject to changes to provide a better fit with the selected category of early adopters.

The paper calls for a re-conceptualization of the diffusion process, from a passive identification of early adopters to an interactive process that entails a trial-and-error approach in the targeting and involvement of different categories of early adopters, which ends when the innovation reaches the desired levels of diffusion.

The study provides managers with a number of recommendations for selecting the most proper category of early adopters for their innovations, depending on the role they are more likely to play and the influence they will exert on subsequent acceptance in the later market.

The study provides managers with a number of recommendations for targeting, through a trial-and-error process, early adopters and working with them to champion the dissemination of new technologies.

This paper significantly adds to existing literature on the diffusion of innovation, which has up to now conceived early adopters as static and given entities, which cannot be proactively selected by the commercializing firm, and innovation as an immutable object.