Search results

This study aims to explore how institutional quality impacts private capital participation in large-scale infrastructure development, particularly in public–private partnership (PPP) projects, aiming to enhance incentives for private sector involvement.

Building on new institutional theory, a triangular theoretical framework was constructed to analyze the high participation of private capital in PPP projects, focusing on seven key institutional factors. Data from 1,319 PPP projects across 36 Belt and Road Initiative (BRI) countries from 2015 to 2020 were then analyzed using a combination of necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis (fsQCA) to evaluate the combined impact and interactions of these factors.

Results indicate that high private capital participation does not hinge on a single institutional quality factor but results from the synergistic influence of multiple factors. The paths leading to high private capital participation can be categorized as regulatory-led, normative-cognitive synergistic, regulatory-normative synergistic and institutional failure-led. Among these, regulatory quality plays a central role in the regulatory-led; the synergy between political stability and voice and accountability is pivotal in the normative-cognitive synergistic, and the rule of law, in combination with voice and accountability, is essential to the regulatory-normative synergistic.

This research systematically examines the multidimensional impact of institutional quality, revealing how different institutional factors interact to influence private capital’s willingness to participate and behavior. It enriches applied research in institutional economics within PPP projects and provides a new theoretical perspective and methodological framework to the scholarly community.

Project portfolio benefit (PPB) evaluation is crucial for project portfolio management decisions. However, PPB is complex in composition and affected by synergy and ambidexterity. Ignoring these characteristics can result in inaccurate assessments, impeding the management and optimization of benefit. Considering the above complexity of PPB evaluation, this study aims to propose a refined PPB evaluation model to provide decision support for organizations.

A back propagation neural network optimized via genetic algorithm and pruning algorithm (P-GA-BPNN) is constructed for PPB evaluation. First, the benefit evaluation criteria are established. Second, the inputs and expected outputs for model training and testing are determined. Then, based on the optimization of BPNN via genetic algorithm and pruning algorithm, a PPB evaluation model is constructed considering the impacts of ambidexterity and synergy on PPB. Finally, a numerical example was applied to validate the model.

The results indicate that the proposed model can be used for effective PPB evaluation. Moreover, it shows superiority in terms of MSE and fitting effect through extensive comparative experiments with BPNN, GA-BPNN, and SVM models. The robustness of the model is also demonstrated via data random disturbance experiment and 10-cross-validation. Therefore, the proposed model could serve as a valuable decision-making tool for PPB management.

This study extends prior research by integrating the impacts of synergy and ambidexterity on PPB when conducting PPB evaluation, which facilitates to manage and enhance PPB. Besides, the structural redundancy of existing assessment methods is solved through the dynamic optimization of the network structure via the pruning algorithm, enhancing the effectiveness of PPB decision-making tools.

This study aims to explore the feasibility of adding Si₃N₄ nanoparticles to Sn58Bi and provides a theoretical basis for designing and applying new lead-free solder materials for the electronic packaging industry.

In this paper, Sn58Bi-xSi₃N₄ (x = 0, 0.2, 0.4, 0.6, 0.8, 1.0 Wt.%) was prepared for bonding Cu substrate, and the changes in thermal properties, wettability, microstructure, interfacial intermetallic compound and mechanical properties of the composite solder were systematically studied.

The experiment results demonstrate that including Si₃N₄ nanoparticles does not significantly impact the melting point of Sn58Bi solder, and the undercooling degree of solder only fluctuates slightly. The molten solder spreading area reached a maximum of 96.17 mm², raised by 19.41% relative to those without Si₃N₄, and the wetting angle was the smallest at 0.6 Wt.% of Si₃N₄, with a minimum value of 8.35°. When the Si₃N₄ nanoparticles reach 0.6 Wt.%, the solder joint microstructure is significantly refined. Appropriately adding Si₃N₄ nanoparticles will slightly increase the solder alloy hardness. When the concentration of Si₃N₄ reaches 0.6 Wt.%, the joints shear strength reached 45.30 MPa, representing a 49.85% increase compared to those without additives. A thorough examination indicates that legitimately incorporating Si₃N₄ nanoparticles into Sn58Bi solder can enhance its synthetical performance, and 0.6 Wt.% is the best addition amount in our test setting.

In this paper, Si₃N₄ nanoparticles were incorporated into Sn58Bi solder, and the effects of different contents of Si₃N₄ nanoparticles on Sn58Bi solder were investigated from various aspects.

To address challenges such as inadequate funding and inefficiency in public infrastructure construction, PPPs have gained significant global traction. This study aims to comprehensively assess the impacts and mechanisms of PPPs on the SDI and to provide rational policy recommendations based on the findings.

We collated a dataset from 30 Chinese provinces covering the years 2005–2020 as our research sample. The study’s hypotheses are tested using a double fixed-effects model, a chained mediated-effects model and a multidimensional heterogeneity analysis.

Our findings indicate that PPPs have a facilitating effect on SDI in general. This boost usually lags behind policy implementation and is cyclical in the time dimension. In the spatial dimension, PPPs contribute significantly to SDI in the eastern and western regions, but not in the central region. From the perspective of the dynamics of economic, social and industrial development, PPPs in economically backward areas are difficult to promote SDI, promote it the most in economically medium regions and are slightly less in economically developed regions than in medium regions. This promotion effect has an inverted U-shaped relationship with social development and diminishes with industrial structure upgrading. Finally, due to the negative relationship between PPPs and social development and between social development and SDI, PPPs are shown to contribute to SDI and are identified as critical paths. However, PPPs suppress SDI by inhibiting economic and industrial development.

This study makes three novel contributions to the existing body of knowledge: (1) we innovatively introduce the United Nations Sustainable Development Goals (SDGs) into the field of infrastructure research, offering fresh perspectives on SDI enhancement; (2) revealing the mechanisms by which PPPs affect SDI through the three dimensions of economic, social and industrial development enabling policymakers to better understand and optimize resource allocation and improve planning, design and management of PPP projects for sustainable infrastructure and (3) we assess the spatiotemporal variances of PPPs’ effects on SDI and the diversity across regions at different social, economic and industrial structures developmental stages, offering critical insights to global decision-makers to devise tailored policy measures.

The purpose of this paper is to empirically analyze the impact of directors’ and officers’ (D&O) liability insurance on enterprise strategic change. It also explores the mediating role of litigation risk, the moderating roles of enterprise science and technology level and precipitation organizational slack between them. In addition, it examines the joint moderating roles of the top management team (TMT) external social network and enterprise science and technology level, and enterprise scale and precipitation organizational slack.

Using the unbalanced panel data of A-share listed companies in the Shanghai and Shenzhen stock exchanges of China from 2002 to 2020 as the research sample, this paper uses the ordinary least square method and fixed-effect model to study the relationship between D&O liability insurance and enterprise strategic change. The study also focuses on the mediating mechanism and moderating mechanisms between them.

The authors find that D&O liability insurance has an “incentive effect,” which can significantly promote enterprise strategic change. Litigation risk plays a partial mediating role between D&O liability insurance and enterprise strategic change. Enterprise science and technology level and precipitation organizational slack negatively moderate the relationship between D&O liability insurance and enterprise strategic change. TMT external social network and enterprise science and technology level, and enterprise-scale and precipitation organizational slack have joint moderating effects on the relationship between D&O liability insurance and enterprise strategic change.

This paper confirms the “incentive effect hypothesis” of the impact of D&O liability insurance on enterprise strategic change, which not only broadens the research perspective of enterprise strategic management but also further expands the research scope of D&O liability insurance. Besides, this paper thoroughly explores the influencing mechanisms between D&O liability insurance and enterprise strategic change, providing incremental contributions to the research literature in the field of enterprise risk management and corporate governance. The findings have practical guiding significance for expanding the coverage of D&O liability insurance, promoting the implementation of strategic changes and improving the level of corporate governance of Chinese enterprises.

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.

Many waste-to-energy (WTE) plants are constructed and operated using the public-private partnership (PPP) mode in China. However, risk events of PPP WTE incineration projects sometimes occur. This study aims to clarify the relationship of risks in China's PPP WTE incineration projects and identify the key risks accordingly and risk transmission paths.

A risk list of PPP WTE incineration projects was obtained based on literature analysis. Moreover, a hybrid approach combining fuzzy sets, decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) was developed to analyze the causality of risks, explore critical risks and reveal the risk transmission paths. The quantitative analysis process was implemented in MATLAB.

The results show that government decision-making risk, government credit risk, government supervision behavior risk, legal and policy risk, revenue and cost risk and management capacity risk are the critical risks of PPP WTE incineration projects in China. These critical risks are at different levels in the risk hierarchy and often trigger other risks.

Currently, there is a lack of exploration on the interaction between the risks of PPP WTE incineration projects. This study fills this gap by examining the key risks and risk transfer pathways of PPP WTE incineration projects from the perspective of risk interactions. The findings can help the public and private sectors to systematically understand the risks in PPP WTE incineration projects, thus enabling them to identify the risks that need to be focused on when making decisions and to optimize risk prevention strategies. The proposed hybrid approach can offer methodological ideas for risk analysis of other types of PPP projects.

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.

Firms in emerging economies are generally at a disadvantage in terms of resources, which may limit their digital transformation. The Chinese government has designed and promulgated a series of wind power policies from the perspectives of support and regulation. The former provides scarce resources for enterprises and thus alleviating financial constraints. While the latter increases the demands for advanced technologies, thereby triggering resource bricolages. This study aims to clarify the impact of industrial policy on the digital transformation of the Chinese wind power industry, and the role of financing constraint and resource bricolage in the above relationship.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study clarifies the impact and mechanism of industrial policy on firm digital transformation with fixed effect regression models.

Empirical results indicate that both supportive and regulatory policies are the cornerstone of the digital transformation of the Chinese wind power industry. Financial constraint and resource bricolage, respectively, mediate the impact of supportive and regulatory policies. However, the mix of supportive and regulatory policies inhibits digital transformation. Moreover, industrial policies are more effective for the digital transformation of state-owned enterprises, as well as enterprises in economically underdeveloped regions.

This study investigates the path of government intervention driving firm digital transformation from the resource-related perspective (i.e. financial constraint and resource bricolage), and its analytical framework can be extended based on other theories. The combined effects of cross-sectoral policies (e.g. wind power policy and digital infrastructure policy) can be further assessed. The marginal net benefit of government intervention can be calculated to determine whether it is worthwhile.

This study emphasizes the necessity of government intervention in the digital transformation of enterprises in emerging economies. The governments should align the policy targets, clarify policy recipients and modify policy process of different categories of industrial policies to optimize the effectiveness of policy mix. Given that the effectiveness of government intervention varies among different categories of enterprises, the competent agencies should design and promulgate differentiated industrial policies based on the heterogeneity of firms to improve the effectiveness and efficiency of industrial policies.

This is one of the earliest explorations of industrial policies’ effect on the digital transformation of the renewable energy sector in emerging economies, providing new evidence for institutional theory. Meanwhile, this study introduces financial constraint and resource bricolage into the research framework and attempts to uncover the mechanism of industrial policy driving the digital transformation of enterprises in emerging economies. Besides, to expand the understanding of the complex industrial policy system, this study assesses the effectiveness of the industrial policy mix.

The digital evolution of production and logistics systems requires seamless integration of various functions. Cyber-physical systems (CPS) can streamline operations, reduce costs and optimise freight transport dynamics. Therefore, CPS adoption is essential to transform existing logistics infrastructure by connecting logistical equipment to cyberspace. This research addresses the critical issue of low CPS adoption in logistics. By analysing the barriers, the study proposes effective strategies to increase CPS integration significantly.

This study used the technology-organisation-environment (TOE) framework and identified 18 barriers to CPS adoption in freight logistics. The barriers were then analysed using the fuzzy data-driven multi-criteria decision-making (MCDM) method, i.e. fuzzy-based decision-making trial and evaluation laboratory (Fuzzy-DEMATEL).

The computational analysis of the proposed framework shows that “the complexity of CPS and lagged data-driven logistics infrastructure” (T₁) is a major technological inhibitor to CPS adoption. The “high cost of CPS technology” (O₈) and a “lack of top management support” (O₃) are the top causal inhibitors at the organisational level. “Lack of data governance and regulatory framework” (E₂) is the main environmental inhibitor.

The causal mapping of the TOE-based barriers helps policymakers and logisticians to develop strategies or follow recommended adoption strategies to improve CPS adoption in logistics.

This study is a pioneering effort to unveil the adoption barriers of CPS in the freight logistics industry and suggest strategies for fostering adoption. This research could provide valuable insights for logistics organisations to support CPS-driven logistics modernisation.