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With the deep development of the new technological revolution and industrial transformation, the development, application, expansion and integration of digital technology provide opportunities for transforming the manufacturing industry from traditional manufacturing to intelligent manufacturing. However, little research currently focuses on analyzing the influencing factors of intelligent development in this field. There is a lack of research from the perspective of the digital innovation ecosystem to explore the intrinsic mechanism that drives intelligent development. Therefore, this article starts with high-end equipment manufacturing enterprises as the research subject to explore how their digital innovation ecosystem promotes the effectiveness of enterprise intelligent development, providing theoretical support and policy guidance for enterprises to achieve intelligent development at the current stage.

This article constructs a logical framework for the digital innovation ecosystem using a “three-layer core-periphery” structure, collects data using crawling for subsequent indicator measurement and assessment and uses the fuzzy set Qualitative Comparative Analysis method (fsQCA) to explore how the various components of the digital innovation ecosystem in high-end equipment manufacturing enterprises work together to promote the development of enterprise intelligently.

This article finds that the various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises, through mutual coordination, can help improve the level of enterprise intelligence. Empirical analysis shows four specific configuration implementation paths for the digital innovation ecosystem of high-end equipment manufacturing enterprises to promote intelligent development. The core conditions and their combinations that affect the intelligent development of enterprises differ in each configuration path.

Firstly, this article discusses the practical problems of intelligent transformation and development in the manufacturing industry and focuses on the intelligent development effectiveness of various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises in the context of digitalization. Secondly, this article uses crawling, text sentiment analysis and other methods to creatively collect relevant data to overcome the research dilemma of being limited to theoretical analysis due to the difficulty in obtaining data in this field. At the same time, based on the characteristics of high-end equipment manufacturing enterprises, the “three-layer core-periphery” digital innovation ecosystem framework constructed in this article helps to gain a deep understanding of the development characteristics of the industry's enterprises, provides specific indicator analysis for their intelligent development, opening the “black box” of intelligent development in the industry's enterprises and bridging the gap between theory and practice. Finally, this study uses the fsQCA research method of configuration analysis to explore the complexity of the antecedents and investigate the combined effects of multiple factors on intelligent development, providing new perspectives and rich research results for relevant literature on the intelligent development of high-end equipment manufacturing enterprises.

The purpose of this paper is to investigate the current situation of China's local valve industry, the maturity of intelligent manufacturing and the way to promote intellectual development.

Firstly, a macro analysis of the valve market environment from the domestic and international perspective was conducted. Secondly, online surveys and in-depth interviews were administered to understand the current status of IM development and future development goals. Finally, case studies were conducted to demonstrate whether the hypothesis of the development approach is feasible.

This study finds that the overall maturity level of the local valve industry is still in the planning stage since the local valve industry lacks concentration and is relatively scattered. In addition, the feasible development approach is dependent on smart devices to improve production efficiency, ensure quality management and effectively control costs.

The research is conducted and focused on the Yangtze River Delta region instead of the whole country, and the size of the sample is small. Therefore, there may be some characteristics omitted in the analysis.

Manufacturers can upgrade to smart manufacturing through intelligent software platforms in order to complete an automatic interaction of data and devices. In addition, manufacturers should complete cross-regional collaborative development through the industrial Internet of things.

There is little or none of research work completed for the development strategy of the valve industry internationally. Therefore, research findings of this area can provide a fundamental understanding of China's local valve industry and contribute to the existing knowledge.

This paper aims to make a systematic study on the factors that hinder the development of China’s intelligent automobile manufacturing industry; based on comprehensive understanding of these obstacles and by optimization means, ultimately, the healthy and sustainable development of intelligent automobile manufacturing industry in China can be promoted.

Based on a questionnaire survey of intelligent automobile manufacturing listed companies in China, first, fuzzy semantic scale was adopted to collect respondents’ choices, the fuzzy score function is used to calculate the fuzzy score value and these data are used as the basis for subsequent model analysis. Then, structural equation modeling (SEM) was adopted to analyze the causal relationship between influencing factors to explore the main hinder factors.

It is found that, in the short term, the backwardness of technological industrialization is the main reason leading to low permeability of intelligent automobile; in the medium term, the imperfect industrial R&D ability and the insufficiency of infrastructure are major causes for high manufacturing cost and low competitiveness of intelligent automobile manufacturing industry; in the long term, the lack of national policy and industrial strategic planning is the main factors affect intelligent automobile manufacturing cost and the industry competitiveness.

The research conclusion has important policy implications for promoting intelligent automobile manufacturing sustainable development. In recent years, China’s intelligent automobile manufacturing industry has gradually stepped out of breeding period; therefore, the role of government should be gradually transformed from participants to managers and regulators. Considering the fact that intelligent automobile cost is very high, and still higher than the cost of fuel vehicle, government should focus on the issues such as improving R&D capabilities, infrastructure construction, policy framework system, legal system and technological industrialization. Specifically, in short-term planning, improving technological industrialization level is the key to development; in medium-term planning, policymakers should focus on the improvement of R&D capabilities and infrastructure; considering the long-term development, establishing appropriate national policies and dealing with the adverse impact of imperfect strategic planning are the most sensible choice.

This paper analyzes the factors that hinder the development of China’s intelligent automobile manufacturing industry for the first time, and provides the basic logic of integration factors at different levels with the development of intelligent automobile to reveal the uniqueness and facts of China’s economic development.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

In the last decade, cloud manufacturing (CMfg) has attracted considerable attention from academia and industry worldwide. It is widely accepted that the design and analysis of cloud manufacturing architecture (CMfg-A) are the basis for developing and applying CMfg systems. However, in existing studies, analysis of the status, development process and internal characteristics of CMfg-A is lacking, hindering an understanding of the research hotspots and development trends of CMfg-A. Meanwhile, effective guidance is lacking on the construction of superior CMfg-As. The purpose of this paper is to review the relevant research on CMfg-A via identification of the main layers, elements, relationships, structure and functions of CMfg-A to provide valuable information to scholars and practitioners for further research on key CMfg-A technologies and the construction of CMfg systems with superior performance.

This study systematically reviews the relevant research on CMfg-A across transformation process to internal characteristics by integrating quantitative and qualitative methods. First, the split and reorganization method is used to recognize the main layers of CMfg-A. Then, the transformation process of six main layers is analysed through retrospective analysis, and the similarities and differences in CMfg-A are obtained. Subsequently, based on systematic theory, the elements, relationships, structure and functions of CMfg-A are inductively studied. A 3D printing architecture design case is conducted to discuss the weakness of the previous architecture and demonstrate how to improve it. Finally, the primary current trends and future opportunities are presented.

By analyzing the transformation process of CMfg-A, this study finds that CMfg-A resources are developing from tangible resources into intangible resources and intelligent resources. CMfg-A technology is developing from traditional cloud computing-based technology towards advanced manufacturing technology, and CMfg-A application scope is gradually expanding from traditional manufacturing industry to emerging manufacturing industry. In addition, by analyzing the elements, relationships, structure and functions of CMfg-A, this study finds that CMfg-A is undergoing a new generation of transformation, with trends of integrated development, intelligent development, innovative development and green development. Case study shows that the analysis of the development trend and internal characteristics of the architecture facilitates the design of a more effective architecture.

This paper predominantly focuses on journal articles and some key conference papers published in English and Chinese. The reason for considering Chinese articles is that CMfg was proposed by the Chinese and a lot of Chinese CMfg-A articles have been published in recent years. CMfg is suitable for the development of China’s manufacturing industry because of China’s intelligent manufacturing environment. It is believed that this research has reached a reliable comprehensiveness that can help scholars and practitioners establish new research directions and evaluate their work in CMfg-A.

Prior studies ignore the identification and analysis of development process and internal characteristics for the current development of CMfg-A, including the main layers identification of different CMfg-As and the transformation process analysis of these main layers, and in-depth analysis of the inner essence of CMfg-A (such as its elements, relationships, structure and functions). This study addresses these limitations and provides a comprehensive literature review.

The continuous development of information technology leads to intelligent education research. In the context of internationalisation, the study aims to understand the relevant research status worldwide, research similarities and differences that need to be discovered, and research frontiers that need to be explored.

Web of Science (WoS) core collection was used as the data source, descriptive statistical analysis, geographic data visualisation and coupling analysis are used to reveal coupling relationships, present a cooperative situation and discover research frontiers.

Intelligent education research has been widely carried out in countries around the world, and there is extensive scientific research cooperation. According to coupling analysis results, the coupling strength of bibliographic between countries has been continuously improved, while the coupling strength of keywords has remained balanced, and there is standardisation and diversity of research.

The weakness of the research lies in the limitations of the data sources. Important research achievements on a certain topic in many non-English speaking countries are usually published in native journals. In the future research direction, more coupling analysis objects can be carried out, such as focussing on authors and institutions.

Through the coupling analysis of country bibliographic and keywords, it reveals the consistency and divergence of intelligent education research between different countries at different time spans.

Design and implement country bibliographic coupling (CBC) and country keyword coupling (CKC) strength indicators to calculate the strength of coupling between countries.

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

The purpose of this paper is to provide a better understanding of the development of intelligent agriculture (IA) in China, which is an important tendency in advancing the agricultural productivity in the coming era.

Considering publications as featured evidence of an emerging phenomenon, the authors review publications of IA. Specifically, the use of term, definition and examples of IA, both English and Chinese literature, and government policies of China are all reviewed. Additionally, the authors use basic statistical and thematic analysis to help synthesizing the literature and drawing conclusions. Findings from various sources of publications supplement with each other.

IA in China has shown three main characteristics: unbalanced geographic distribution, an early stage of the trend and attention mainly focused on a limited range of technologies. Compared with the development of IA in other countries, such as Japan, India and the USA, featured with diversified properties, similarities and differences of IA development in China and in other countries are also discussed.

This general review contributes by uncovering the emergence of IA, identifying its general definition with a comprehensive set of practical examples and pointing out the present characteristics and problems of IA development in China. The general review provides a necessary summary for the policy makers and researchers to have a systematic understanding of IA and better promote its future development. At last, the paper calls for a process-based strategy with different goals at different stages, a sustainable mechanism coordinated by multiple participants, and a localized consideration for relevant policy making.

The authors intend to expand the literature on the relationship between intelligent technology and human resources in operating cost, and firm value of financial institutions in emerging markets by integrating the influence of intelligent technology and contribute to a growing body of literature on the determinants of firm value.

This paper empirically investigates the impact of intelligent technology investment on employment compensation and firm value using a sample of 86 listed financial institutions in China from 2010 to 2019.

This paper reports robust evidence that an increase in intelligent technology investment has a significantly negative effect on employment compensation in financial institutions. In addition, this inhibitory effect is persistent. The increase in intelligent investment has a significant two-year lag effect on firm value, which is positive and sustained. This indicates that intelligent technology investment has a short-term “useless” effect but brings long-term “gains” for Chinese financial institutions.

These findings may shed light on the decision-making processes of financial institutions, which helps practitioners better understand that firms need to reasonably deal with the subsequent cost of growth caused by intelligent technology input. Alternatively, they may wish to select the appropriate accounting method of depreciation or amortization to smooth its impact.

This paper aims to use the concept of machine learning to enable people and machines to interact more certainly to extend and expand human expertise and cognition.

Intelligent code reuse recommendations based on code big data analysis, mining and learning can effectively improve the efficiency and quality of software reuse, including common code units in a specific field and common code units that are not related to the field.

Focusing on the topic of context-based intelligent code reuse recommendation, this paper expounds the research work in two aspects mainly in practical applications of smart decision support and cognitive adaptive systems: code reuse recommendation based on template mining and code reuse recommendation based on deep learning.

On this basis, the future development direction of intelligent code reuse recommendation based on context has prospected.