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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.

The purpose of this paper is to examine the nuanced effects of downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. Intelligent manufacturing is considered to clarify their boundary conditions.

The ordinary least squares regression was conducted, based on the data collected from 136 high-tech firms in China.

Horizontal downstream complexity has a positive effect on supply chain resilience significantly, while the negative impact of vertical downstream complexity on supply chain resilience is not significant. Contingently, intelligent manufacturing plays a negative moderating role in the relationship between horizontal downstream complexity and supply chain resilience, while it positively moderates the relationship between vertical downstream complexity and supply chain resilience.

This study disentangles the nuanced effects of both horizontal and vertical downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. It also clarifies their boundary conditions by considering the focal firm's intelligent manufacturing level as the contingent factor.

The purpose of this paper is to examine the mediating role of strategic supplier partnership and moderating role of information sharing (IS), in the relationship between lean manufacturing and firms’ financial performance (FP).

Utilizing the contingency approach, this study develops a research model to validate the proposition that a proper integration of supply chain (SC) practices enhances the financial performance of the firm. The study uses data from one hundred and fifty-seven manufacturing firms. The results are generated on structural equation modeling (SEM) using AMOS software.

The study finds that strategic supplier partnership partially mediates the relationship between lean manufacturing and FP, whereas, empirically, it could not demonstrate that IS significantly moderates the relationship between lean manufacturing and FP.

The paper theoretically develops logic for and empirically shows that strategic supplier partnership is an appropriate practice for mediating the impact of lean manufacturing on FP.

This strategic supply chain integration contributes to theory and demonstrates that SC practices’ correct synchronization and orchestration may realize superior FP. In addition, this research provides a sustainable strategic SC model that creates value and provides a competitive advantage for firms in the long term.

This study aims to investigate the impact of sustainable innovation and disruptive innovation on sustainable supply chain performance of manufacturing firms in Malaysia. The study also examined the moderating role of supply chain clockspeed in the relationship between sustainable innovation, disruptive innovation and sustainable supply chain performance.

The data were collected from 231 respondents in manufacturing firms in Malaysia. The data were analyzed using the partial least square-based structural equation modelling (PLS-SEM) technique.

The findings revealed that sustainable innovation and disruptive innovation had a significant and positive effect on sustainable supply chain performance. Supply chain clockspeed moderated the relationship between sustainable innovation and sustainable supply chain performance. The findings also identified that there was no moderating effect on the relationship between disruptive innovation and sustainable supply chain performance.

This study merely focuses on sustainable supply chain performance in Malaysian manufacturing firms. Samples from manufacturing firms in Malaysia were used in the current study, and the outcomes may vary for different nations.

To increase the firm’s commercial success, it is necessary to promote sustainable supply chain practices, including supply chain clockspeed, sustainable innovation and disruptive innovation.

This study adds to the body of knowledge by explaining the positive influence of sustainable innovation and disruptive innovation on sustainable supply chain performance in Malaysian manufacturing firms while also emphasizing the moderating role of supply chain clockspeed in this relationship. The contribution of this study could enable managers to develop sustainable supply chain performance in the manufacturing sector, based on sustainable innovation, disruptive innovation and supply chain clockspeed.

The firms’ adoption and improvement of big data analytics capabilities to improve economic and environmental performance have recently increased. This makes it important to discover the underlying mechanism influencing the association between big data analytics (BDA) and economic and environmental performance, which is missing in the existing literature. The present study discovers the indirect effect of green innovation (GI) and the moderating role of corporate green image (CgI) on the impact of BDA capabilities, including big data management capability (MC) and big data talent capability (TC), on economic and environmental performance.

A time-lagged design was employed to collect data from 417 manufacturing firms, and study hypotheses were evaluated using Mplus.

The empirical outcomes indicate that both BDA capabilities of firms significantly influence green innovation (GI), which significantly mediates the relationship between BDA and economic and environmental performance. Our findings also revealed that CgI strengthened the effect of GI on economic and environmental performance. The empirical evidence provides important theoretical and practical repercussions for manufacturing SMEs and policymakers.

This study contributes to the literature on BDA by empirically exploring the effects of MC and TC on improving the EcP and EnP of manufacturing firms. It does so through the indirect impact of GIs and the moderating effect of CgI, thereby extending the Dynamic capabilities view (DCV) paradigm.

This study aims to examine the relationship between green technology implementation (GTI), knowledge management (KM) process and knowledge workers' operational performance (KWOP). The research postulates that a specific combination of GTI and KM processes can lead to improving KWOP.

The sample data (304) were taken from those manufacturing firms that are utilizing green technology. The examination was conducted by Smart PLS-SEM and fuzzy set qualitative comparative analysis (fsQCA). The Smart PLS 3.29 is used to verify certain variable relationships. Moreover, fsQCA is used to investigate multiple configuration paths to enhance KWOP.

The study's outcome indicated that GTI positively influences the KM process in manufacturing firms, and the KM process enormously improves KWOP. The fsQCA analysis result explores various integrations (communication, collaboration, supporting role and improved performance) with the KM (acquisition, sharing and utilization) process identified to enhance the performance of KWOP. The current study supports two merging methods to deepen understanding of employee operational performance.

The study methodologically contributes by integrating direct and configuration approaches to develop firms' operational performance. This study contributes to bridging research gaps in the prior literature and advances insight into the association between GTI, KM process and KWOP.

The purpose of this research is to investigate the R&D investment (RDI) of manufacturing firms from the perspective of supply chain network, especially the effect of firms' supply chain network structures (network power and network cohesion) on its RDI, and further to explore the contingency conditions of this effect within the context of Chinese manufacturing supply chains.

The authors collect a large sample of Chinese manufacturing firms over the period 2014–2019 and construct a large-scale supply chain network, and finally obtain 2,390 firms from 20,483 observations. Ordinary least squares regression was adopted to analyse how supply chain network structures affect RDI in manufacturing firms.

It is surprising that firm's supply chain network structures have a negative effect on RDI. In addition, knowledge and technology intensity (KTI) positively moderate the relationship between network cohesion and RDI.

This study contributes to the innovation stream from the perspectives of supply chain network, and provides the empirical findings that the negative role of a firm's supply chain network structure on its RDI for the first time. The rationale for these negative effects is straightforward according to the social capital theory that manufacturing firms with a high level of social capital that are possibly to accept established patterns of thinking and behaviour, causing them to decrease the enthusiasm of RDI.

This paper aims to discuss the firm productivity premium for servitized firms. It discusses servitization across the product value chain and estimates the effects of the range and extent of servitization on productivity premium in manufacturing firms.

This paper develops a conceptual framework and tests the hypotheses on the effects of servitization on productivity premium using linear regression models with a sample of 20,837 Russian manufacturing firms gathered from the Ruslana Bureau van Dijk database and the Russian customs service.

Servitized firms exhibit higher total factor productivity and labor productivity. The labor productivity premium increases with the number of services offered. However, the impact of services on productivity varies along the product value chain: postmanufacturing and postsales services enhance productivity premium, while manufacturing and back-office services diminish them. The effect of establishment services remains ambiguous.

This paper offers an analytical framework for firms to assess their servitization strategies. These strategies should be gradual, focused on enhancing firm efficiency rather than being an end goal. Firms should initiate the process by introducing services at the postproduction and postsales stages of the product creation chain to achieve productivity premium.

The paper extends the evidence on firm-level productivity drivers and contributes to the servitization theory. A servitization strategy should be portfolio-based, considering both the potential gains and losses in productivity resulting from the implementation of specific services.

Recently, the concept of the circular economy (CE) has witnessed significant momentum in academic and professional circles. However, there is a dearth of research that studies the enabling factors of the CE in the era of digital transformation. The existing research aimed to identify the impact of Industry 4.0 readiness on the CE in manufacturing firms operating in Jordan, as well as to identify the mediating role of the industrial Internet of things and big data analytics.

For this work objectives, 380 questionnaires were analyzed. Convergent validity and discriminant validity tests were performed through partial least squares-structural equation modelling (PLS-SEM) in the Smart-PLS programme. Data reliability was confirmed. A bootstrapping technique was used to analyze the data and then hypothesis testing was performed.

The results indicate that Industry 4.0 readiness, industrial Internet of things (IIoT) and big data analytics positively enable CE, also the IIoT and big data analytics positively mediate the nexus between Industry 4.0 readiness and CE.

This study promotes the idea of focusing on Industry 4.0 readiness to enhance CE in the Jordanian manufacturing sector and knowing the effect of IIoT and big data analytics in this relationship.

This research developed a theoretical model to understand how Industry 4.0 readiness might enhance the CE in manufacturing firms by invoking the IIoT and big data analytics as mediating constructs in the relationship between Industry 4.0 readiness and CE. This paper offers new theoretical and practical contributions that add value to industry 4.0 and CE literature by testing these constructs' mediation models in the manufacturing sector.

Drawing on the resource dependence theory (RDT), this paper investigates ownership composition, export intensity, and industry class as moderating factors to investigate the role of imported raw materials in performance of inward foreign direct investment (IFDI) in Ethiopia.

The hypotheses were tested using secondary data obtained from the 2016 Central Statistical Agency (CSA) on Large- and Medium-Scale Manufacturing and Electricity Industries Survey. The data included basic quantitative information on the country's manufacturing industry. The data items for the 2016 manufacturing and electricity industries surveyed are the numbers of proprietors or establishments involved in various sectors. The report did not record small firms that employed fewer than 10 people and did not use power-driven machinery. Two-Stage least squares (2SLS) regression analysis was performed to test the proposed hypotheses.

The results of this study indicate that three moderators (ownership composition, export intensity, and industry classification) interact with the hypothetical relationships between imported raw materials and performance. These findings enrich the knowledge of IFDI firms' operations in Ethiopia and in other least-developed countries (LDCs). The findings could provide information for IFDI firms that are looking to invest in LDCs.

Like all social science research, this study has some limitations. First, the research was conducted with the data found in the Report on Large- and Medium-Scale Manufacturing and Electricity Industries Survey In 2016. This was the first year of the second five-year Growth and Transformation Plan (GTP II), a national development plan for the 2016–2020 period. Continual research on IFDI in Ethiopia in the following years will be needed to get a full picture of the effects of the determinants on IFDIs.

To IFDI investors, the result of this thesis demonstrates several alternatives to overcoming hurdles in manufacturing operation. The results find that J.V. firms make better use of imported raw materials than W.O. subsidiaries in order to achieve better performance. Concerning the choice between focusing on export or domestic markets, the study suggests that domestic market—oriented companies require less imported raw materials to achieve better performance. Concerning the comparative advantage on different industries, this study found the performance of firms in Industry 12 depended on imported raw materials. These findings highlight the challenges and opportunities for potential foreign investors. Ownership composition, market factors, and industry factors should be well considered in making investment decisions.

This is one of few studies on IFDI in Ethiopia, the most populous LDC. Ownership composition, export intensity, and industry class are used as moderating variables to investigate the difference between imported raw materials and the level of expatriate deployment to IFDI performance. For IFDI investors, the results of this study demonstrate several alternatives to overcoming hurdles in manufacturing operation.