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The purpose of this paper is to offer novel and complementary insights into the relationship between product modularity and product innovation by investigating the mediating role of module suppliers' relationship-specific investments which include both property-based relationship-specific investment (PRSI) and knowledge-based relationship-specific investment (KRSI).

This paper is an empirical study based on structural equation modelling, with a sample of 121 core firms of high-tech modular cooperation in China.

The findings indicated that product modularity had a significant positive effect on product innovation; product modularity was positively related to module suppliers' PRSI; module suppliers’ KRSI had a direct effect on product innovation while PRSI had an indirect effect on product innovation through KRSI; the relationship between product modularity and product innovation was serially multi-mediated by module suppliers’ PRSI and KRSI.

Modular product design and modular cooperation governance guidance for core firms and cooperative investment strategies guidance for module suppliers were provided.

This study is the first attempt to analyse how product modularity affects product innovation in the context of inter-firm modular cooperation by revealing the mediating role of module suppliers' relationship-specific investments.

With the widespread penetration of digital technologies, disruptive innovation is not developed by a single firm but is increasingly achieved by an ecosystem. However, limited research has examined the mechanisms involved in achieving disruptive innovation in the context of digitalization and ecosystems. To address this gap, we explore the impact of three dimensions of specialized complementary assets (SCAs) within the innovation ecosystem, human capital SCA (HCSCA), production SCA (PSCA) and marketing SCA (MSCA), on disruptive innovation in core firms through the mediation of digital capability, comprising digital operation capability (DOC) and digital resource collaborative capability (DRCC). Furthermore, innovation ecosystem embeddedness is examined as a moderator between digital capability and disruptive innovation.

Survey data were collected from 234 core firms in China’s high-tech industry. Hierarchical regression, AMOS, and PROCESS tools were used to examine the data.

The results reveal the following: (1) HCSCA and PSCA positively affect disruptive innovation, while MSCA is negatively correlated with disruptive innovation. (2) Digital capability mediates the relationship between HCSCA and disruptive innovation, as well as PSCA and disruptive innovation. However, it suppresses the negative impact of MSCA on disruptive innovation. (3) Innovation ecosystem embeddedness strengthens the influence of DOC on disruptive innovation, but weakens the influence of DRCC on disruptive innovation.

The findings advance the knowledge of disruptive innovation, SCAs within the innovation ecosystem, digital capability and innovation ecosystem embeddedness. They also provide practical insights into the effective implementation of disruptive innovation.

Technological standardization can promote the development of complex products and systems (CoPS) (e.g. large aircraft, high-speed trains). Many studies argue that a superior network position contributes to improving a firm's ability to innovate; however, few studies have considered the aforementioned line of research as falling under the purview of CoPS standardization. This study focuses on CoPS integrators, which hold the most important enterprise roles in CoPS manufacturing and innovation, to analyze whether the two types of superior positions (i.e. the central position and the brokerage position) help the integrator influence the standardization process in a process moderated by technological complexity.

Considering the outstanding market performance of the railway transportation industry in China, the abundance of cooperative activities in this industry, and data availability, we adopt integrators from this industry as samples for the empirical analysis in this study. A negative binomial regression analysis with random effects was conducted to analyze the acquired panel data.

The results show that the central position has an inverted U-shaped effect on the integrator's ability to influence standardization and that the brokerage position has a positive effect. We also find that the underlying mechanism of the two types of network positions impacts the integrator's ability to influence standardization and that it has two modes: knowledge integration in related domains and knowledge integration in nonrelated domains. Moreover, technological complexity attenuates the effect of the central position and strengthens the effect of the brokerage position on the integrator's ability to influence standardization.

This paper contributes to the theoretical research on CoPS manufacturing and innovation and complements knowledge-based theory. The results could prove enlightening for integrators facing complex technological environments, allowing them to establish a reasonable external knowledge search strategy and choose appropriate cooperation partners according to their knowledge domains.

Simulation-based optimisation (SO) is a popular optimisation approach for building and civil engineering construction planning. However, in the framework of SO, the simulation is continuously invoked during the optimisation trajectory, which increases the computational loads to levels unrealistic for timely construction decisions. Modification on the optimisation settings such as reducing searching ability is a popular method to address this challenge, but the quality measurement of the obtained optimal decisions, also termed as optimisation quality, is also reduced by this setting. Therefore, this study aims to develop an optimisation approach for construction planning that reduces the high computational loads of SO and provides reliable optimisation quality simultaneously.

This study proposes the optimisation approach by modifying the SO framework through establishing an embedded connection between simulation and optimisation technologies. This approach reduces the computational loads and ensures the optimisation quality associated with the conventional SO approach by accurately learning the knowledge from construction simulations using embedded ensemble learning algorithms, which automatically provides efficient and reliable fitness evaluations for optimisation iterations.

A large-scale project application shows that the proposed approach was able to reduce computational loads of SO by approximately 90%. Meanwhile, the proposed approach outperformed SO in terms of optimisation quality when the optimisation has limited searching ability.

The core contribution of this research is to provide an innovative method that improves efficiency and ensures effectiveness, simultaneously, of the well-known SO approach in construction applications. The proposed method is an alternative approach to SO that can run on standard computing platforms and support nearly real-time construction on-site decision-making.

This study aims to develop an improved understanding of the formation of citizens' purchase intention to increase the adoption of prefabricated housing (PH).

An integrative model of the theory of planned behavior (TPB) and norm activation model (NAM) was proposed based on previous studies. To verify the conceptual model, an analysis was conducted after data collection from a questionnaire survey. Lastly, findings were presented by explaining the formation of purchase intention in the egoistic and altruistic contexts. Practical implications were likewise discussed.

Findings manifest that citizens' purchase intention is influenced by egoistic and altruistic cognitions. An effective strategy is to show citizens the pro-environmental features of PH to promote its adoption because they value the environmental performance of housing. Meanwhile, consumers' social fitness also plays an essential role in decision-making, and the dual contradiction in the PH market is revealed.

This study extends the knowledge of psychological decision-making theories in the field of purchase intention toward PH by proposing an integrative framework of TPB and NAM. Results indicate a systematic and comprehensive understanding of consumers' decision-making in the PH domain. Moreover, results of this research contribute to specifying and refining the applicable contexts of TPB and NAM by adding two antecedents: subjective knowledge and environmental concern. This research contributes to the literature by being one of the first to investigate purchase intention toward a high-cost product with invisible technological innovation.

This study explores citizens’ acceptance of prefabricated housing (PH) from the perspective of socio-demographic and psychological factors, aiming to reveal the formation of PH acceptance and realize a sustainable development of PH.

This study proposed hypotheses drawing on procedural justice theory and uncertainty management theory. A survey of 245 respondents was conducted, and the collected data was analyzed in a stepwise multiple regression model. Then, the psychological influencing mechanism was demonstrated using a mediation model.

Results of the data analysis manifested that citizens’ acceptance of PH was influenced by socio-demographic and psychological factors, where psychological factors had more significant effects on acceptance than socio-demographic factors. The psychological mechanism was examined by verifying the mediating role of uncertainty between procedural justice and the acceptance of PH. Furthermore, a scientific strategy for developing PH was proposed based on this empirical study.

This study extends the knowledge of procedural justice theory by investigating people’s acceptance in the PH context. This study is also one of the first studies to unveil the psychological mechanism toward a high-cost product with invisible technological innovation. This study contributes to the literature by introducing uncertainty management theory to a controversial issue, examining and expanding its application in a complicated context. Moreover, results highlight the positive influence of fair processes on controversial issues.

Precast wall lifting during prefabricated building construction faces multiple non-lean problems, such as inaccurate lifting-time estimation, unreasonable resource allocation and improper process design. This study aims to identify the pathways for improving lifting performance to advance lean construction of prefabricated buildings.

This study developed a methodological framework that integrates the discrete event simulation method, the elimination, combination, rearrangement and simplification (ECRS) technique and intelligent optimization tool. Two schemes of precast wall lifting, namely, the enterprise's business as usual (BAU) and enterprise-leading (EL) schemes, were set to benchmark lifting performance. Furthermore, a best-practice (BP) scheme was modeled from the perspective of lifting activity ECRS and resource allocation for performance optimization.

A real project was selected to test the effect of the methodological framework. The results showed that compared with the EL scheme, the BP scheme reduced the total lifting time (TLT) by 6.3% and mitigated the TLT uncertainty (the gap between the maximum and minimum time values) by 20.6%. Under the BP scheme, increasing the resource inputs produces an insignificant effect in reducing TLT, i.e. increasing the number of component operators in the caulking subprocess from one to two only shortened the TLT by 3.6%, and no further time reduction was achieved as more component operators were added.

To solve non-lean problems associated with prefabricated building construction, this study provides a methodological framework that can separate a typical precast wall lifting process into fine-level activities. Besides, it also identifies the pathways (including the learning effect mitigation, labor and machinery resource adjustment and activities’ improvement) to reducing TLT and its uncertainty.

This paper aims to report a comprehensive analysis of literature on stakeholder relationships towards identifying patterns of relationships within the off-site construction context.

Key scholarly databases were accessed and after a filtering process, 74 relevant papers were retrieved for analysis. The papers were analysed using qualitative content analysis and scientometric techniques through the application of software Leximancer and VOSviewer.

Research synthesis methods used in the present study generate compatible results. Through text mining analysis, the key themes identified in the off-site construction stakeholder relationships literature included “collaboration”, “building information modelling”, “social network analysis”, supply chain. As a finding by scientometric analysis, collaboration, BIM, supply chain management, housing and social network analysis were the most frequently entered keywords context of off-site construction. Regarding authorship pattern, the whole network of collaboration was fragmented into multiple isolated clusters, implying that the authors had tendency to cooperate in small groups.

The paper can bring together an important area of research not previously studied in detail. It will primarily assist academics in the first instance; however, the research leads to important findings that will ultimately assist policymakers and practitioners better understand factors affecting stakeholder relationships and in particular network thinking and collaborative mind-sets.

The review contributes a needed systematic and theoretical foundation for future stakeholder relationship studies and practices in off-site construction sector. It provides the basis for future studies and is a seminal analysis of stakeholder management and off-site construction. The scientometric methodology offers scholars a different approach to analysing and visualising literature reviews.

The purpose of this paper is to investigate how the pay gap between the management and ordinary employees influence corporate technology innovation.

This study built a tournament model based on inventor innovation and career promotion. In addition, the authors use IV-GMM estimation method to address the possible endogeneity issue in the regressions.

Based on the unbalanced panel data of patents and pay gap in 1,501 Chinese listed manufacturing firms during 2001-2015, this paper finds that the pay gap could lead inventor innovation and improve technology innovation. The pay gap could encourage corporate innovation significantly: 1 percent increase in pay gap may increase the number of patents by 2 percent in the next year. The pay gap between the management and ordinary employees facilitates corporate innovation via two possible channels. First, inventor innovation and career promotion. Inventors are selected into the management mainly based on their innovation output. The larger the pay gap, the more innovation incentives and patents would gain. Second, investment increase in technology innovation. The pay gap and more patents that inventors gain would increase the ratio of inventors promoted to the management, who tend to pour more resources into R&D activities and absorb more inventors to the management due to their sectionalism and R&D preference. The above two channels constitute a positive feedback mechanism among technology innovation, inventor promotion and increase in R&D investment.

This paper highlights that pay gap between the management and ordinary employees is an important issue that could encourage corporate innovation. The conclusions imply that pay gap could encourage inventors to work hard and produce more patents, which could help them to enter into the management such as executives or directors.

This study contributes to the current literature by implying that pay gap could have positive effects on innovation through theoretical and empirical analysis. Also, this study finds that inventor promotion due to the pay gap is a critical channel to stimulate corporate technology innovation.