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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.

Despite arguments that traditional product costing and variance analysis operate contrary to the strategic goals of advanced manufacturing practices such as just in time (JIT), total quality management (TQM), and Six Sigma, little empirical evidence exists that cost accounting practices (CAP) are changing in the era of continuous improvement and waste reduction. This research supplies some of the first evidence of what CAP are employed to support the information needs of a world-class manufacturing environment. Using survey data obtained from executives of 121 U.S. manufacturing firms, the study examines the relationship between the use of JIT, TQM, and Six Sigma with various forms of traditional and non-traditional CAP. Analysis of variance tests (ANOVA) indicate that most traditional CAP continue to be used in all manufacturing environments, but a significant portion of world-class manufacturers supplement their internal management accounting system with non-traditional management accounting techniques.

To respond to increasing environmental uncertainty, manufacturers are enhancing flexible manufacturing competence (FMC) as a source of competitive advantage. This study aims to extend research on FMC to its antecedent variables by investigating the impacts of advanced manufacturing technology and operations improvement practices (OIP) on FMC.

Using survey data from 273 manufacturing firms, this research tests additive, mediating, and moderating models that relate these variables.

Among three alternative models, the moderating model is best supported. The results indicate that advanced manufacturing technology has a stronger positive impact on FMC when OIP are effectively implemented than when they are not.

The research focuses attention on the antecedent variables to production competence, rather than on the concept and positive performance effect of production competence.

For managers, the issue is not simply purchasing automation but developing OIP to effectively use advanced manufacturing technologies, thereby achieving the magnifying effects of human capital on FMC.

This paper investigates FMC and its antecedent variables by testing three alternative models, and it offers assistance to managers who are implementing advanced manufacturing technologies and OIP.

This paper presents an integrated framework for the selection of attributes used in the evaluation of advanced manufacturing systems. The primary focus in the development of this framework is the modularity of the framework so that it is applicable to a wide range of advanced manufacturing systems with differing process configurations and technologies. Based on data collected from industry and the current body of knowledge, decision attributes were identified and ranked relatively against each other, forming a hierarchy of decision attributes. To simplify the hierarchy, making it more user‐friendly in real‐world applications, each decision attribute was also evaluated relative to the strength of its relationships to other decision attributes. Several decision attributes were found to be highly correlated with others, resulting in a new, single decision attribute. The final decision attribute hierarchy provides managers responsible for making capital decisions involving advanced manufacturing technologies with a framework for their decision making.

The purpose of this paper is to assess the implications of organizational knowledge, source of information and functional orientation, resource-based view of the manufacturing and global orientation, on manufacturing practices which include advanced manufacturing strategies.

An empirical study approach has been used to assess the implications of advanced manufacturing strategies on firm performance.

This paper provides a framework for managers to: assess competitive priorities of the industry; identify order winners for the industry; identify key decision areas or practices for improvements; and to assess the role of implications of organizational knowledge on the manufacturing practices.

The limitations are as follows: the issue of organizational knowledge and learning is assessed from manufacturing view point only; plants located all over India are considered for study; and considers plants employing different manufacturing systems and products.

Saturated with the conventional manufacturing technologies, a growing number of small- and medium-scale industries began to explore advanced manufacturing technologies (AMTs). Investment in AMTs remains a promising but potentially risky venture. This paper helps the small- and medium-scale industries to adopt viable AMTs and business performance strategies and then provides guidelines for enhancing their competitiveness.

This paper may help all the stakeholders of small- and medium-scale industry.

This paper is based on one of the few studies conducted to assess the implications of advanced manufacturing strategies on firm performance in Indian scenario.

The purpose of this paper is to provide sector-specific empirical evidence on the comparative evaluation of total productive maintenance (TPM) and total quality management (TQM) approaches, implemented exclusively and collectively on improving manufacturing business performance.

This paper develops a multi-sector analysis framework to comparatively assess the synergistic and standalone effect of TPM and TQM improvement approaches. A total of 231 manufacturing organizations from food and beverages, textiles and electrical and electronics sectors have been extensively surveyed. These firms were further clustered into TPM focus, TQM focus and integrated TPM×TQM on the basis of their primary manufacturing strategy. Comparative assessment of these three manufacturing approaches has been evaluated using t-test statistics.

This paper highlights that adoption of integrated TPM×TQM approach is beneficial for food and beverages and electrical and electronics sectors. However, this supposition is rejected for firms operating in the textile sector.

The findings of this research are still exploratory. Future research using countrywide and cross-country approach can be undertaken to statistically generalize the findings of the present research. In-depth case studies are needed to further validate the findings of the study empirically.

The result of this study help managers and practitioners to make manufacturing strategic decision based on the nature of their operating business sector regarding adoption of TPM and TQM practices, which will further revive their firm’s competitiveness.

Every operating sector embraces a diversity of manufacturing activities based upon their competing priorities. This paper makes an attempt to present a multi-sectoral evaluation of joint implementation and effect of manufacturing programs.

Production of a high variety of products introduces complexities in the quality processes involved in a manufacturing system. Previous methods of quality assurance and control are not sufficient to manage the quality characteristics that are significant to each customer. Research into quality management for these environments has been isolated and segmented. No framework exists to holistically manage product quality within an unstable manufacturing environment. This paper seeks to propose a method of holistically managing product quality in a manufacturing environment with high customer input and product variety. The development of a reconfigurable inspection apparatus is discussed as a technological requirement for performing the quality control aspect of the management system.

The quality requirements of modern manufacturing systems were established. The required flow of information for an advanced quality management system was proposed and compared to the information flow in a traditional quality management system. The developed reconfigurable inspection apparatus was tested by performing an inspection of a product configuration within a part family of torches. Commercial products were used for the construction of the apparatus, including the electrical and software aspects. A commercially available simulation package was used to simulate the effects of a random customer order on production flow whilst implementing the developed apparatus.

Modular inspection equipment would prove essential to the implementation of quality control when considering advanced manufacturing environments. An overall management system is also needed for the verification of product quality as per individual customer requirements. Quality needs to be integrated as per TQM principles.

Traditional quality control tools may not always be applicable for unstable market demand. The research indicated the required progression of quality systems to successfully manage the quality for advanced manufacturing. The widespread availability of commercial components for the inspection apparatus verified the shift in supplier focus to meet the needs of shifting manufacturing requirements.

The proposed approach to assure and control quality, as well as the researched inspection apparatus, provided the capability of being implemented in a manufacturing environment that involves production of a variety of products as opposed to being limited to one part family. The use of modular mechanical, electrical and software components will ease the implementation of reconfigurable inspection stations into existing manufacturing setups.

Research indicated that quality systems need to be further developed for assuring and controlling product quality of products with high customer input. No system existed that could holistically consider the quality requirements of a product from design to delivery.

With ever-increasing global concerns over environmental degradation and resource scarcity, the need for sustainable manufacturing (SM) practices has become paramount. Industry 5.0 (I5.0), the latest paradigm in the industrial revolution, emphasizes the integration of advanced technologies with human capabilities to achieve sustainable and socially responsible production systems. This paper aims to provide a comprehensive analysis of the role of I5.0 in enabling SM. Furthermore, the review discusses the integration of sustainable practices into the core of I5.0.

The systematic literature review (SLR) method is adopted to: explore the understanding of I5.0 and SM; understand the role of I5.0 in addressing sustainability challenges, including resource optimization, waste reduction, energy efficiency and ethical considerations and propose a framework for effective implementation of the I5.0 concept in manufacturing enterprises.

The concept of I5.0 represents a progressive step forward from previous industrial revolutions, emphasizing the integration of advanced technologies with a focus on sustainability. I5.0 offers opportunities to optimize resource usage and minimize environmental impact. Through the integration of automation, artificial intelligence (AI) and big data analytics (BDA), manufacturers can enhance process efficiency, reduce waste and implement proactive sustainability measures. By embracing I5.0 and incorporating SM practices, industries can move towards a more resource-efficient, environmentally friendly and socially responsible manufacturing paradigm.

The findings presented in this article have several implications including the changing role of the workforce, skills requirements and the need for ethical considerations for SM, highlighting the need for interdisciplinary collaborations, policy support and stakeholder engagement to realize its full potential.

This article aims to stand on an unbiased assessment to ascertain the landscape occupied by the role of I5.0 in driving sustainability in the manufacturing sector. In addition, the proposed framework will serve as a basis for the effective implementation of I5.0 for SM.

The purpose of this paper is to explore the approaches to education and training adopted by manufacturing organisations to identify and develop a set of learning principles for the successful transition to Industry 4.0.

A case study of a manufacturing ecosystem in Queensland, Australia was undertaken, that included semi-structured interviews with a total sample of 22 manufacturing industry representatives, an analysis of secondary data including organisational documents and government reports, and embedded cases of two manufacturing organisations.

Manufacturers successfully transitioning to Industry 4.0 are distinguished by a culture which values learning, management development to understand and lead innovation, experimental learning on the job and strong links to education and training providers through internships and upskilling pathways. These four principles inform approaches to creating tailored training solutions that respond to the unique needs of diverse manufacturing organisations.

The two case studies describe exemplary high performing companies only and not companies at earlier stages of adopting Industry 4.0. Therefore, future research could include a broader spectrum of companies across the adoption spectrum. Nevertheless, considered as a study of a total manufacturing ecosystem, there is strong alignment of views of government, industry, union and education stakeholders regarding the key factors of transition to Industry 4.0.

There is a strong need for leaders of manufacturing organisations to enable a broad strategy of capability development beyond simple acquisition of new technologies. Detailed consideration and resourcing of on-the-job training and experimentation, talent attraction through innovation workplace cultures and strong relationships with education providers are important.

Given that Industry 4.0 technologies such as robotics and AI are now rapidly diffusing into other industry sectors, the research has broader implications for education and training for the future of work. These technologies could produce stark differences between efficiency versus innovation-oriented adoption strategies. Whilst the former could displace workers, the latter can open pathways for upskilling, product and process innovation and cross sector employment.

Through the ecosystem level case approach, multiple stakeholder perspectives provide triangulated insights into advanced manufacturer's education, skills and training strategies, uncovering four learning principles that underpin the approach of manufacturers successfully transitioning to Industry 4.0. The findings have practical implications for policy makers and industry bodies supporting the transition to advanced manufacturing and provide manufacturing managers with insights into successful education and skill strategies that can be adapted to specific organisational needs.

In order to analyze the level of independent controllability and its evolution of high-end equipment manufacturing industry from Jiangsu Province, this article introduces the dual-excitation control line method to construct a comprehensive evaluation model for independent controllability.

Through the collection of information of high-end equipment manufacturing industry's independent and controllable capabilities on different indicators, the three aspects of advancement, autonomy and controllability, an empirical evaluation of 10 enterprises in the high-end equipment cluster in Jiangsu Province was conducted in terms of advancement, autonomy and controllability.

It effectively reveals the area and evolution characteristics of the “reward” and “punishment” of different indicators of each representative enterprise and reflects the development status and different characteristics of each representative enterprise on the three indicators. The research results provide decision-making guidance for enterprises in the management and control of advanced manufacturing systems with independent and controllable capabilities.

Existing research focuses on the evaluation of enterprises' independent controllability only on a single angle or index. This paper maps the dynamic evaluation problem of multiple time-point data to the evaluation problem of single time-point multi-index data and investigates the fluctuation of the performance of the same enterprise under different indexes, so as to comprehensively evaluate the independent controllable level of high-end equipment manufacturing industry and analyze the reasons. Further, this paper first establishes an evaluation index system of independent controllable level of high-end equipment manufacturing industry and quantitatively measures the advanced, independent, controllable and other aspects of typical enterprises in this industry by constructing a double incentive control line evaluation model.