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The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

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.

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.

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.

This research aims to identify, examine and evaluate barriers to the adoption of digital servitization in manufacturing firms in the case of the Sri Lankan manufacturing sector and analyze the inter-relationships among digital servitization barriers.

Based on the comprehensive literature review, 13 barriers were identified. The grey decision-making trial and evaluation laboratory (grey-DEMATEL) approach was used to uncover and analyze the relationships among barriers in terms of their overall influence and dependencies.

A prominent barrier to the success of adopting digital servitization in the Sri Lankan manufacturing sector is the lack of digital strategy in developing activities related to the design of digital service packages, organizational structures and processes. Supply chain integration is the most influential factor, which plays an important role in developing a competitive advantage by encouraging innovation process capabilities in servitized companies.

Industry practitioners can develop guidelines for adopting digital servitization practices based on the importance and interdependencies of different barriers and thereby prioritize projects within a program of digital servitization adoption in their organizations.

Research studies on barriers to digital servitization are limited to exploratory nature and have adopted mainly the qualitative approach, such as in-depth interviews. No empirical study has investigated the inter-relationships among digital servitization adoption barriers in the manufacturing sector. This study provides a holistic view of different barriers to the adoption of digital servitization in the manufacturing sector as a basis for developing comprehensive digital servitization strategies to manage and leverage complexity in digital transformation.

Despite servitization being widely regarded as an essential catalyst to improve manufacturing firms' survival and competitiveness, how to attain servitization remains debatable. The primary objective of this research is to explore whether or not, how, and when the dynamic capabilities affect servitization in the digital economy background. This research investigates the relationships between servitization and dynamic capabilities by incorporating firm ownership, firm lifecycle stage, digital economy level and environmental uncertainty as contingency factors in the research framework.

This research develops and verifies a conceptual framework for manufacturing servitization by employing the fuzzy-set qualitative comparative analysis (fsQCA) in analyzing the secondary longitudinal data from 148 China-listed manufacturing firms involved in servitization from 2015 to 2020.

The analytical results of fsQCA identify several configurational solutions for the success of manufacturing servitization. Each factor can be an enabler for servitization success despite none of the factors discovered as an absolute condition. Manufacturing servitization success within the digital economy depends on the interactions between dynamic capabilities and contingency factors such as digital economy level, environmental uncertainty, firm ownership, and lifecycle stage.

All of the construct's measurements in this research adopt secondary data, and further investigation calls for primary data (e.g. survey) for higher validity.

This research extends the current view of servitization by proposing an integrative conceptual framework, allowing manufacturing servitization to be examined more pertinently and comprehensively. Second, the research is an initial attempt that adopts fsQCA in servitization studies. The study sheds light on the mechanisms of attaining servitization by revealing the importance of dynamic capabilities and their interactions with the contingency factors. Third, the research extends the application scopes of dynamic capability theory, firm lifecycle theory, contingency theory, and institutional theory. Fourth, the research findings enrich the understanding of servitization in the digital economy and give business practitioners insights on leveraging dynamic capabilities in different conditions to attain successful servitization under the current circumstances.

Circular economy denotes future sustainability that allows optimum utilization of resources. In the present era of technology, plenty of innovations are happening across the world, and digital manufacturing is one of such innovations. However, there are several barriers which are impeding adoption of digital manufacturing in circular economy environment. The study explores the barriers of digital manufacturing initiatives in a circular economy and develops a methodological model to prioritize the identified challenges for automotive parts manufacturing industry.

Seven categories of challenges namely process, human resources, financial, collaboration, technological, security and leadership challenges were identified from literature and further validated with subsequent discussions with experts from the industry. The study is conducted in two phases, where in the first phase, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is used to define the priority and importance of seven categories of challenges. In second phase, the barriers are ranked using a Fuzzy Performance Important Index (FPII), taking into account contextual factors associated with the challenges and linked barriers, to determine the extent to which they impede the adoption of digital manufacturing in the sample automotive parts manufacturing company.

The “risk of data security and information privacy in connection with use of external data and protecting customer data” appeared as the most significant barrier to digital manufacturing in circular economy. Furthermore, technological challenges emerged as the most significant category of challenges followed by financial challenges in adoption of digital manufacturing in circular economy.

Identification of the identified barriers and understanding the interrelationships will lead to easier adoption of digital manufacturing in circular economy.

Despite all the potential benefits of implementing Industry 4.0 technologies in manufacturing industries, the adoption thereof is still in nascent phase with significant challenges yet to be overcome to accelerate the pace of adoption. Hence, this study explores the barriers preventing companies from adopting and benefiting from digital manufacturing initiatives and further develops a methodological model.

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.

This paper aims to disentangle the mechanism linking digital servitization and manufacturing firm performance. The contributions of the service networks and slack resources are analyzed.

Drawing on a survey of manufacturing firms that have implemented or are implementing digital service projects in China, this paper examines the mediation effect of service networks and the moderated mediation effect of slack resources to capture the role of service networks and slack resources in the relationship between digital servitization and manufacturing firm performance.

Both basic and advanced digital services can equally contribute to manufacturing firm performance. Service networks mediate the relationship between basic digital servitization and manufacturing firm performance. No moderated mediation effect of slack resources is found, but slack resources negatively moderate the effects of basic digital services on service networks and positively impact service networks.

The mediating mechanism of service networks in the relationship between digital servitization and manufacturing firm performance is theorized, and it is clarified that service networks mediate the association between basic digital services and manufacturing firm performance but not advanced digital services. Additionally, there is no significant difference in performance implications when manufacturing firms provide basic versus advanced digital services, answering the call for research on the various types of digital servitization. This paper also identifies firms’ slack resources as the boundary conditions under which basic digital services influence service networks and the positive impacts of slack resources on service networks, bridging the network literature, organizational slack literature and digitalization literature under the framework of service ecosystem research.

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.