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In order to effectively promote the deep integration of artificial intelligence and the real economy and empower real enterprises to improve quality and efficiency, this study regards the CEO as a high-end innovation resource and aims to empirically test the impact of scholar-type CEOs on the industrial artificial intelligence (AI) transformation of manufacturing enterprises.

Grounded on the upper echelons theory, this paper preliminarily selects A-share manufacturing listed companies in Shanghai Stock Exchange and Shenzhen Stock Exchange that are affiliated to enterprise groups from 2014 to 2020 as samples. Furthermore, the Logit regression is conducted to analyze the influence of scholar-type CEOs about industrial AI transformation.

The results show that scholar-type CEO plays a significant role in promoting industrial AI transformation. The parent-subsidiary corporations executives' ties positively moderates the impact of scholar-type CEOs on industrial AI transformation. Further, internal control quality plays a partial mediating role between scholar-type CEOs and industrial AI transformation. Compared with private enterprises, scholar-type CEOs play a stronger role in promoting industrial AI transformation of state-owned enterprises.

First, this paper expands the research related to the influencing factors of industrial AI transformation based on upper echelons theory and clarifies the influencing mechanism of scholar-type CEOs affecting industrial AI transformation from the perspective of executives' behavior. Second, this study further enriches the research framework on the economic consequences of scholar-type CEOs and provides a useful supplement to the research literature in the field of upper echelons theory. Third, this paper is not limited to a single enterprise but involves the management practice of resource allocation within the enterprise groups, further clarifies the internal logic of the decision-making of industrial AI transformation of listed companies within the framework of enterprise groups, providing theoretical reference for the scientific design of the governance mechanism of parent-subsidiary companies.

The purpose of this paper is to reveal the inner mechanisms of the role of industrial internet platforms in empowering the digital transformation of SMEs. This ROOTCLOUD-based case study shows that knowledge integration and knowledge sharing and driving play essential empowering roles in the impact of industrial internet platforms on the digital transformation of SMEs. The industrial internet platform promotes knowledge integration on the supply side, empowers cross-domain knowledge sharing and shapes the knowledge-driven digital supply chain system in the digital transformation processes of SMEs.

This paper presents a qualitative analysis of the knowledge empowerment role played by industrial internet platforms in the digital transformation process of SMEs. Based on theoretical sampling, this paper selects ROOTCLOUD as a typical case to analyse the implementation mechanism of the industrial internet platform in solving the digital transformation problems and challenges faced by SMEs.

Knowledge management (knowledge integration, sharing and driving) plays an important intermediary role between the empowerment of industrial internet platform and the digital transformation of SMEs. Specifically, the industrial internet platform empowers SMEs with knowledge, empowers supply-side knowledge integration, empowers cross-domain knowledge sharing and facilitates the formation of knowledge-driven supply chain systems.

This study clarifies the mechanism underlying the digital transformation of SMEs empowered by industrial internet platforms, that is, the empowerment of industrial internet platform enhances the level of knowledge integration and sharing of SMEs, thus improving the effectiveness of SMEs in achieving digital transformation. Further empirical studies should be conducted on the above mechanism.

Based on the theoretical perspective of knowledge management, this paper discusses the problems and challenges faced in the digital transformation of SMEs through knowledge empowerment by the industrial internet platform ROOTCLOUD and proposes that knowledge empowerment in the industrial internet platform helps supply-side knowledge integration, promotes cross-domain knowledge sharing and contributes to forming a knowledge-driven supply chain system, thereby promoting the digital transformation of SMEs. System architects and relevant policy departments should pay attention to data-centred system construction, improve the construction of data-based collaborative application ecology and encourage industrial internet platforms to provide more targeted knowledge empowerment solutions for SMEs.

The scale of urban land has been expanding because the speed of urban development has increased the population. Thus, certain improvement in planning and construction based on circular economy is required. Industrial resource-based city planning and construction is particularly important based on the aforementioned problems and development background. The development of industrial resource cities in the transformation stage based on the circular economy was considered as the breakthrough point. The development, function, and concept of the new district planning were analyzed in view of the design strategy of the current domestic resource-based urban planning; moreover, the planning principles (integration of regional and harmonious resource constructions and coordinated organization function) that are suitable for resource industrial city were presented. In this study, taking the industrial transformation and resource-based city of Yichun as an example, the infrastructure and the general situation of the new district planning in the future were deeply analyzed. In the light of the functional development and planning structure of the transformation and development planning of resource-based industrial cities, the following planning and development strategies were proposed: the centralized small-scale space should be constructed. Diversion control should be carried out on bicycle lane and motorized lane in new area. The three-dimensional layout of the grid should be applied to the overall planning of the road, and according to the expressway, main roads, secondary roads and ordinary sections, there must be four kinds of traffic system, so as to construct a diversified traffic diversion system. The original industrial land should be extended into a continuous space, and the allocation of new district resources after transformation must be suitable for the development plan of brand strategy, so as to perfect the forestry land of Sun Yue gorge street and transform it into RBD recreational and entertainment community, and build a friendly eco city.

The digitization process has increased the pressure on large firms to transform. However, current frameworks on digital transformation are not well explaining what factors contribute to, or hinder, a firm's digital transformation. Innovation diffusion theories could complement existing frameworks, and for this reason, the purpose of this paper is to expand the existing body of knowledge on what contributes to, or hinders, an industrial firm's digital transformation by applying a validated framework based on innovation diffusion theories on two pioneer cases: General Electric and Siemens EHR/Health Services.

The framework used in this paper is based on several years' empirical studies and iterative literature reviews on innovation diffusion theories. Further, each use case is based on literature reviews and unique empirical data, collected by the authors of this paper as a result of taking active part of respective company's multi-years transformation.

Common drivers of, and clear inhibitors to the two firms' transformation, were identified. The innovation diffusion framework was found to work very well in identifying those factors.

The implications are that researchers better can analyze/explain a digital transformation of a firm, and business managers can better plan or improve their firms' transformation processes.

The theoretical contributions of this paper are two: first, complement existing frameworks with a validated framework for innovation diffusion; second, provide an extension of our body of knowledge on factors that contributes to, or hinders, industrial firm's digital transformation.

Industry 4.0 is a promising concept that allows industries to meet customers’ demands with flexible and resilient processes, and highly personalised products. This concept is made up of different dimensions. For a long time, innovative digital technology has been thought of as the only dimension to succeed in digital transformation projects. Other dimensions have been identified such as organisation, strategy, and human resources as key while rolling out digital technology in factories. From these findings, researchers have designed industry 4.0 theoretical models and then built readiness models that allow for analysing the gap between the company initial situation and the theoretical model. Nevertheless, this purely deductive approach does not take into consideration a company’s background and context, and eventually favours one single digital transformation model. This article aims at analysing four actual digital transformation projects and demonstrating that the digital transformation’s success or failure depends on the combination of two variables related to a company’s background and context. This research is based on a double approach: deductive and inductive. First, a literature review has been carried out to define industry 4.0 concept and its main dimensions and digital transformation success factors, as well as barriers, have been investigated. Second, a qualitative survey has been designed to study in-depth four actual industry digital transformation projects, their genesis as well as their execution, to analyse the key variables in succeeding or failing. 46 semi-structured interviews were carried out with projects’ members; interviews have been analysed with thematic content analysis. Then, each digital transformation project has been modelled regarding the key variables and analysed with regards to succeeding or failing. Investigated projects have consolidated the models of digital transformation. Finally, nine digital transformation types have been identified.

To better understand the role of industrial big data in promoting digital transformation, the authors propose a theoretical framework of industrial big-data-based affordance in the form of an illustrative metaphor – what the authors call the “organizational drivetrain.”

This study investigates the effective use of industrial big data in the process of digital transformation based on the technology affordance–actualization theoretical lens. A software platform and services provider with more than 4,000 industrial enterprise clients in China was selected as the case study object for analyzing the digital affordance and actualization driven by industrial big data.

Drawing on a revelatory case study, the authors identify three affordances of industrial big data in the organization, namely developing data-driven customized projects, provisioning equipment-data-driven life cycle services, establishing data-based trust and determining affordance actualization actions driven by technology and market. In addition, the authors reveal the underlying drivetrain mechanisms to advance industrial big data affordance and actualization: stabilizing, enriching and pioneering.

This study builds a drivetrain model on digital transformation by industrial big data affordance actualization. The authors also provide practical implications that can help practitioners to implement digital transformation effectively and extract value from their investment.

The internationalization of business has grown the production value chains and created performance challenges for industrial production. Industry 4.0, the digital transformation of industrial processes, promises to deliver performance improvements through smart functionalities. This study investigates how digital transformation translates to performance gain by adopting a systems perspective to drive smartness.

This study uses qualitative research to collect data on the lived experiences of digital transformation practitioners for theory development. It uses semi-structured interviews with industry experts and applies the Gioia methodology for analysis.

The study determined that enterprise smartness is an organizational capability developed by digital transformation, it is a function of integration and the enabler of organizational performance gains in the Industry 4.0 context. The study determined that performance gains are experienced in productivity, sustainability, safety and customer experience, which represents performance metrics for Industry 4.0.

This study contributes a model that inserts smartness in the linkage between digital transformation and organizational outcomes to the digital transformation and production management literature.

The study indicates that digital transformation programs should focus on developing smartness rather than technology implementations, which must be considered an enabling activity.

Existing studies recognized the positive impact of technology on performance in industrial production. The study addresses a missing link in the Industry 4.0 value creation process. It adopts a systems perspective to establish the role of smartness in translating technology use to performance outcomes. Smart capabilities have been the critical missing link in the literature on harnessing digital transformation in organizations. The study advances theory development by contributing an Industry 4.0 value model that establishes a link between digital technologies, smartness and organizational performance.

This study aims to evaluate the potential of using the components of the quadruple helix and quintuple helix models, which are extensions of the triple helix university-private sector-public sector cooperation model. Thus, the triple helix model shaped by university-private-public sector cooperation has transformed into a quadruple helix innovation model with the inclusion of the media and culture-oriented public helix. In this context, while the triple helix emphasizes tripartite networks and hybrid organizations, the quadruple helix system focuses on intertwined collaborations, coevolution, and specialization within the framework of firms, institutions, and stakeholders. In the quadruple helix innovation system, the coevolution of art and innovation has assumed a central role in knowledge generation and innovation. In the quintuple helix innovation model, the natural environment of society is added to the quadruple helix. This study consists of three parts. In the first part, the literature on triple helix, quadruple helix, and quintuple helix models is reviewed. In the second part, digital transformation and technological innovations from Industrial Revolution 1.0 to Industry 5.0 are analyzed. In the third section, the contribution of the quintuple helix model to Industry 5.0 and Society 5.0 is explained.

Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.

Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.

The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.

Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.

The purpose of this paper is to address the specific challenges with which resource‐based cities are faced when they begin along the path of industrial transformation and to employ empirical studies to determine whether relevant reforms in resource‐based cities (taking Pingxiang, one of the first round of resource‐exhausted cities acting as pilot cities in the national sustainable development transformation program, as an example), promoted by local government in recent years, have brought significant changes to their development modes and facilitated the real transition.

The paper carried out some empirical studies from different angles: employing the “vertical table graph” method, to turn Pingxiang's statistical data (1997‐2010) into a graph that visually shows Pingxiang's economic and social development; comparing several major economic and social development indicators (especially the energy consumption per unit of GDP) of 11 cities within Jiangxi Province in order to learn Pingxiang's relative positions; based on time series data from 1997 to 2009, calculating the change rates, the variation coefficients and the shift‐share indexes of industrial structure so as to measure the quality of Pingxiang's structural transformation; comparing the above results with the cities of Jiaozuo, Benxi and Dalian; and comparing economic and social development state of 16 resource‐based cities (which are all among the list of 44 national resource‐exhausted cities) from the perspective of “green GDP”.

Although Pingxiang has gained great progress in economic development, its industrial structure is not rational enough, and shows great dependence on mining industry with a too high share of the secondary industry and a too small proportion of the tertiary industry. Its heavy dependence on resources and investment does not suggest a fundamental change in development modes. Accordingly, the city's development idea should be switched from GDP‐orientation to sustainable development. It should proceed with the optimization of the industrial structure adjustment, increase manpower capital investment and develop new green substitutable industries, so as to catalyze the success of transition.

This integration of empirical analysis methods from three angles in multivariate statistical analysis, environmental economics, and industrial economics is novel in the field of research on resource‐city and industry change. It not only could be of some help in decision making for Pingxiang municipal government, but also could provide reference for other cities dependent on resource exploitation.