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The digital transformation under Industry 4.0 is complex and resource-intensive, making a strategic digitalization guideline vital to small and medium-sized enterprises' success in the Industry 4.0 transition. The present study aims to provide manufacturing small and medium-sized enterprises (SMEs) with a guideline for digital transformation success under Industry 4.0.

The study first performed a content-centric literature review to identify digital transformation success determinants. The study further implemented interpretive structural modeling to extract the order at which the success determinants should be present to facilitate the SMEs’ digital transformation success optimally. The interpretive model and interpretive logic knowledge base matrix were also used for developing the digital transformation guideline.

Eleven success determinants are vital to SMEs’ digital transformation efforts. For example, results revealed that external support for digitalization is the first step in ensuring digital transformation success among SMEs, while operations technology readiness is the most inaccessible success determinant.

The study highlights the degree of importance of the 11 success determinants identified, which magnifies each determinant's strategic priority based on its driving power and dependence power. Theorizing the dependent variable of “digital transformation success” and quantitatively measuring the extent to which each success determinant contributes to explaining “digital transformation success” offers an exciting opportunity for future research.

Digital transformation success phenomenon within the Industry 4.0 context is significantly different from the digitalization success concept within the traditional literature. The digital transformation under Industry 4.0 is immensely resource-intensive and complex. Smaller manufacturers must have specific capabilities such as change management and digitalization strategic planning capability to reach a certain degree of information, digital, operations and cyber maturity.

The digital transformation success guide developed in the study describes each success determinants' functionality in relation to other determinants and explains how they might contribute to the digital transformation success within the manufacturing sector. This guide enables smaller manufacturers to better understand the concept of manufacturing digital transformation under Industry 4.0 and devise robust strategies to steer their digital transformation process effectively.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

The purpose of this paper is to identify the drivers of manufacturing transformation and upgrading and examine their influencing paths and effects. The study also dynamically evaluates and compares the achievements of the manufacturing transformation and upgrading of various economies.

This paper establishes the mechanism model of manufacturing transformation and upgrading based on the partial least squares approach to structural equation modeling. With the help of a mechanism model, the study carries out empirical analysis using panel data from the G20 for 2005–2015.

Innovation, measured by innovation input and innovation output, has the largest positive effect on manufacturing transformation and upgrading. Economic development has a negative direct effect, as well as positive indirect effects. Its total effect is positive but small. Economic openness has no significantly direct effect, but has significantly positive indirect effects. Its total effect is significantly positive, but is the smallest among drivers. Developed economies have relatively higher but decreasing achievements, whereas emerging economies have lower but increasing achievements and maintain the catch-up trend toward developed economies.

Few macro empirical studies examine the drivers and achievements of manufacturing transformation and upgrading. A need has arisen for evidence-based research and policies to guide governments in their efforts to promote manufacturing transformation and upgrading. This may be the first macro-level study to empirically analyze the drivers of manufacturing transformation and upgrading, and their influencing paths as well as achievements.

Under the influence of the digital economy, the digital transformation of manufacturing enterprises has attracted widespread attention from scholars at home and abroad due to its uniqueness and importance. However, the existing literature is still deficient in the inner mechanism of digital transformation and lacks research on the digital transformation process. Through in-depth interviews and rooted theory, this paper focuses on the key factors of digital development of manufacturing enterprises and constructs a model of the digital transformation process.

This paper takes China's manufacturing enterprises as research projects. First, through a literature search, the authors proposed three key factors for constructing sustainable competitiveness from digital transformation, that is, core technology innovation, business model re-engineering and organizational structure optimization. Second, the authors adopted the grounded theory approach to identify three sustainable competitive factors of manufacturing enterprises resulting from digital transformation and constructed a theoretical model. Third, based on Chinese manufacturing enterprises data, the authors used an empirical study to validate the three influencing factors. Finally, the authors identified the inner mechanism of the digital transformation of enterprises and put forward suggestions for enterprises to maintain sustainable competitiveness.

First, based on the existing literature, this paper identified the importance of digital transformation of manufacturing enterprises, and the essence of digital transformation of manufacturing companies was found to lie in the change in the combined effect of technological, market and organizational innovation. Second, based on the grounded theory, through in-depth interviews with manufacturing enterprises on digital transformation and open coding of interview transcripts, it was concluded that the key factors for the digital transformation manufacturing companies are core technology change, business model re-engineering and organizational structure optimization. Third, based on a dynamic perspective, the authors evaluated and validated digital transformation. The study found that manufacturing enterprises can improve their digital transformation capabilities through the trajectory of “core technology change – business model re-engineering – organizational structure optimization” to improve their sustainable competitive advantage.

Firstly, this study proposed three key factors for constructing sustainable competitiveness from digital transformation, that is, core technology innovation, business model re-engineering and organizational structure optimization, which enriched the theory of transformation and upgrading. Secondly, this study constructs the structural equation model of digital transformation and discovers the key factors pf digital transformation.

China's digital economy is flourishing and playing a pivotal role in the national economy. Government subsidies, as an important tool for the national treasury, are a “reassurance” for the digital transformation of manufacturing enterprises. The purpose of this paper is to investigate the relations between the digital transformation of manufacturing enterprises and government subsidies to provide inspiration for promoting the digitization and upgrading of China's manufacturing industry and facilitate enterprises' innovative development.

Based on the panel data of 2,928 manufacturing listed companies in China from 2016 to 2020, this paper empirically tests the effect of subsidies on the digital transformation of manufacturing enterprises using fixed-effect econometric regression.

The results illustrate that subsidies effectively incentivize digital transformation in manufacturing enterprises, and verify different situations through heterogeneity. Further analysis of the moderating effect shows that the innovation level and servitization level of manufacturing enterprises positively moderated the relationship between government subsidies and the enterprise's digital transformation.

Based on Chinese manufacturing enterprise samples, this paper empirically tests the incentive effect of government subsidies on the digital transformation of manufacturing enterprises, therefore clarifying the main regulatory effects. This paper could provide enlightenment for manufacturing enterprises to make good use of government subsidies to improve their digital ability, thereby enhancing competitiveness in the digital economy era.

The purpose of this paper is to explore the forms that combinations of digital manufacturing, logistics and equipment use are likely to take and how these novel combinations may affect the relationship among logistics service providers (LSPs), users and manufacturers of equipment.

Brian Arthur’s theory of combinatorial technological evolution is applied to examine possible digital manufacturing-driven transformations. The F-18 Super Hornet is used as an illustrative example of a service supply chain for a complex product.

The introduction of digital manufacturing will likely result in hybrid solutions, combining conventional logistics, digital manufacturing and user operations. Direct benefits can be identified in the forms of life cycle extension and the increased availability of parts in challenging locations. Furthermore, there are also opportunities for both equipment manufacturers and LSPs to adopt new roles, thereby supporting the efficient and sustainable use of digital manufacturing.

The phenomenon of digital manufacturing-driven transformations of service supply chains for complex product does not yet fully exist in the real world, and its study requires cross-disciplinary collaboration. Thus, the implication for research is to use a design science approach for early-stage explorative research on the form and function of novel combinations.

Digital manufacturing as a general-purpose technology gives LSPs an opportunity to consolidate demand from initial users and incrementally deploy capacity closer to new users. Reengineering the products that a manufacture currently uses is needed to increase the utilization of digital manufacturing.

The authors outline a typology of digital manufacturing-driven transformations and identify propositions to be explored in further research and practice.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This paper aims to investigate the characteristics and dynamics of the organizational changes needed to facilitate the management of an Industry 4.0 transformation in manufacturing SMEs and propose an approach to manage them.

This research focuses on a single manufacturing SME in North America, and data were collected using a research intervention method. Data were collected through observation and intervention within the SME over 27 months.

The research has shown that organizational changes are required in manufacturing SMEs to better manage their Industry 4.0 transformation projects.

Using the case study method limits the generalization of the results. The organizational changes observed, and their characteristics might be specific to the studied manufacturing. Although results could vary in different contexts, many manufacturing SMEs have similar characteristics to those observed in this study.

This research provides preliminary evidence of an iterative organizational change management approach that manufacturing SMEs must adopt to facilitate the management of their digital transformation.

This research provides a better understanding of how a manufacturing SME can improve its capabilities to manage its digital transformation by introducing iterative organizational changes. From these results, a link to the organizational learning literature can be drawn and developed upon.

The purpose of this paper is to investigate the relations between the digital transformation of manufacturing enterprises and enterprise innovation to provide inspiration for promoting the digitization and upgrading of China's manufacturing industry and facilitate enterprises' innovative development.

Based on a panel data of 584 listed manufacturing companies in China from 2016 to 2020, and using a fixed effects approach, this paper empirically examines the impact of digital transformation on corporate innovation in manufacturing enterprises, as well as examining the influential mechanisms and heterogeneity.

The research shows that the digital transformation of manufacturing enterprises has effectively improved the innovation capacity of enterprises and verifies different situations through heterogeneity. At the same time, the research clarifies the mediating effect of the innovation investment mechanism, cost control mechanism, and profit guarantee mechanism on the relations between the digital transformation of manufacturing enterprises and the innovation capacity of enterprises.

Based on Chinese manufacturing enterprise samples, this paper empirically tests the influential mechanism of digital transformation on the innovation capability of manufacturing enterprises, therefore clarifying the main mediating effects. This paper could provide inspiration for manufacturing companies to make good use of digital transformation rules according to their own situation and improve their innovation capabilities, thereby enhancing competitiveness in the digital economy era.