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Digital transformation and innovation-driven development have become an international consensus. The purpose of this paper is to examine the effects of relationships, mechanisms and economic consequences between digital transformation and enterprise innovation quality in order to provide a benchmark for developing countries to implement digital transformation strategies and innovation-driven strategies and provide a major support for economic recovery in the post-coronavirus disease 2019 (COVID-19) era.

Using microdata from A-share listed enterprises in Shanghai and Shenzhen from 2010 to 2021, this study examines the relationship between digital transformation and enterprise innovation quality and further reveals the internal logic and economic consequences of digital transformation to improve enterprise innovation quality through the mediating effect and moderating effect models.

The results demonstrate that digital transformation is beneficial for improving enterprise innovation quality. The heterogeneity test demonstrates that digital transformation has a larger effect on improving enterprise innovation quality in non-state-owned enterprises and eastern enterprises in China. The mechanism test demonstrates that digital transformation can improve enterprise innovation quality by improving internal control quality and analyst attention. Furthermore, with the increase in enterprise innovation inputs, digital transformation plays a significantly stronger role in improving enterprise innovation quality. The extended analysis demonstrates that digital transformation can significantly improve enterprise financial performance by improving innovation quality.

First, the construction of the core explanatory variable digital transformation index in this study is based on the Python data analysis software, which calculates the frequency of digital transformation in the text of the business situation analysis portion of the annual report of the listed companies and then obtains the degree of digital transformation of the company in this year. There may be some deviation from the degree of digital transformation in the actual production and operation of enterprises. Second, in addition to internal control quality and analyst attention, are there other mediating mechanisms for the impact of digital transformation on the quality of enterprise innovation? Third, whether the moderating effect of innovation input on digital transformation and innovation quality is related to human capital factors of the research and development (R&D) team, such as the technical background of R&D personnel, etc.

This study enriches the relevant theories of digital transformation and broadens the research boundaries of digital transformation and enterprise innovation. This study's result provides an empirical basis for enterprises to improve enterprise innovation quality and financial performance from the perspective of digital transformation at the micro level and points out specific practical directions, combining theory with practice.

Risk factors related delay hinder the schedule performance of most construction projects in the world. It is a critical challenge to realize the advantages of prefabricated construction projects (PCPs) under the negative effect of schedule delay. This paper aims to propose an exhaustive list of risk factors impeding the progress of PCPs and evaluate the collected risk factors based on the cause–effect relations. The ultimate goal is to improve the understanding of the complex relations among various risk factors related delay in PCPs, and also offer managers a reference on aspect of schedule risk management.

This paper proposes a hybrid method of GT–DEMATEL–ISM, that is combing grounded theory, DEMATEL (decision-making trial and evaluation laboratory) and ISM (Interpretative Structural Modeling), to collect, evaluate and structure risk factors related delay for PCPs. The research procedure of this methodology is divided into three stages systematically involving qualitative and quantitative analysis. In the first stage, GT is utilized to implement qualitative analysis to collect the risk factors leading to schedule delay in PCPs. While, the quantitative analysis is to analyze and evaluate the collected risk factors based on the cause–effect relations in the next two stages evaluation by the DEMATEL focuses on quantifying the priority and intensity of the relations between factors. Additionally, ISM is employed to construct the hierarchical structure and graphically represent the pairwise relations between factors.

The outcome of qualitative investigation by grounded theory proposes a theoretical framework of risk factors related delay for PCPs. The framework contains three levels of category, namely, core category, main category and initial category and provides a list of risk factors related delay. Following this finding, evaluation results by the DEMATEL classify factors into cause and effect groups and determine 11 critical delay risk factors. Meanwhile, the findings show that risks referring to organizational management issue foremost impact the progress of PCPs. Furthermore, a systemic multilevel hierarchical structure model is visually constructed by ISM to present the pairwise linkages of critical factors. The model provides the risk transmission chains to map the spread path of delay impact in the system.

The contribution of the study involves twofold issues. Methodologically, this research proposes a hybrid method GT–DEMATEL–ISM used to identify and analyze factors for a complex system. It is also applicable to other fields facing similar problems that require collecting, evaluating and structuring certain elements as a whole in a comprehensive perspective. The theoretical contribution is to fill the relevant research gap of the existing body of knowledge. To the best knowledge of the authors, this paper is the first attempt to integrate qualitative and quantitative research for risk analysis related delay and take the insight into the whole process of PCPs covering off-site manufacture and on-site construction. Furthermore, the analysis of findings provided both a micro view focusing on individual risk factor and a managerial view from a systematic level. The findings also contribute the effective information to improve the risk management related schedule delay in PCPs.

The construction industry is widely recognized as one of the most hazardous sectors in the world. Despite extensive research on safety management, a critical issue remains that insufficient attention is devoted to safety practices in rural areas. Notably, accidents frequently occur during the construction of rural self-built houses (RSH) in China. Safety management tends to be overlooked due to the perceived simplicity of the construction process. Furthermore, it is essential to acknowledge that China currently lacks comprehensive laws and regulations governing safety management in RSH construction. This paper aims to analyze the behavior of key stakeholders (including households, workmen, rural village committee and the government) and propose recommendations to mitigate safety risks associated with RSH construction.

This paper applies evolutionary game theory to analyze the symbiotic evolution among households, workmen and rural village committee, in situations with or without government participation. Additionally, numerical simulation is utilized to examine the outcomes of various strategies implemented by the government.

Without government participation, households, workmen, and rural village committee tend to prioritize maximizing apparent benefits, often overlooking the potential safety risks. Numerical simulations reveal that while government involvement can guide these parties towards safer decisions, achieving the desired outcomes necessitates the adoption of reasonable and effective strategies. Thus, the government needs to offer targeted subsidies to these stakeholders.

Considering that during the construction phase, stakeholders are the main administrators accountable for safety management. However, there exists insufficient research examining the impact of stakeholder behavior on RSH construction safety. This study aims to analyze the behavior of stakeholders about how to reduce the safety risks in building RSH. Thus, the authors intend to contribute to knowledge in this area by establishing evolutionary game model. Firstly, this study carried out a theoretical by using tripartite evolutionary game to reveal the reasons for the high safety risk during building RSH. Practically, this research points out the important role of households, workmen and rural village committee in improving safety management in rural areas. Besides, some suggestions are proposed to the government about how to reduce construction safety risks in rural areas.

Prefabricated construction is often hindered by scheduling delays. This paper aims to propose a schedule delay prediction model system, which can provide the key information for controlling the delay effects of risk-related factors on scheduling in prefabricated construction.

This paper combines SD (System Dynamics) and BP (Back Propagation) neural network to predict risk related delays. The SD-based prediction model focuses on dynamically presenting the interrelated impacts of risk events and activities along with workflow. While BP neural network model is proposed to evaluate the delay effect for a single risk event disrupting a single job, which is the necessary input parameter of SD-based model.

The established model system is validated through a structural test, an extreme condition test, a sensitivity test, and an error test, and shows an excellent performance on aspect of reliability and accuracy. Furthermore, 5 scenarios of case application during 3 different projects located in separate cities prove the prediction model system can be applied in a wide range.

This paper contributes to academic research on combination of SD and BP neural network at the operational level prediction, and a practical prediction tool supporting managers to take decision-making in a timely manner against delays.

The purpose of this study is to investigate the heat resistance and heat-resistant oxygen aging of 4-nitrophthalonitrile-etherified cardanol-phenol-formaldehyde (PPCF) to further use and develop the resin as the matrix resin of high-temperature resistant adhesives and coatings.

PPCF resin was synthesized by 4-nitrophthalonitrile and cardanol-phenol-formaldehyde (PCF). The structures of PPCF and PCF were investigated by Fourier transform infrared, differential scanning calorimetry and proton nuclear magnetic resonance. In addition, the heat resistance and processability of PPCF and PCF resins were studied by dynamic mechanical analysis, thermogravimetric analysis, scanning electronic microscopy (SEM), X-ray diffraction (XRD) techniques and rheological studies.

The results reveal that PPCF forms a cross-linked network at a lower temperature. PPCF resin has excellent resistance under thermal aging in an air atmosphere and that it still had a certain residual weight after aging at 500°C for 2 h, whereas the PCF resin is completely decomposed.

4-Nitrophthalonitrile was introduced into PCF resin, and XRD and SEM were used to investigate the high temperature residual carbon rate and heat-resistant oxygen aging properties of PPCF and PCF resins.

In the construction sector, the knowledge-based process outgrows its emphasis on technological aspects. Yet, there is a lack of applied studies showing how a procurement system (PS) could be selected in the digital age. In particular, there is a radical need to establish an innovative process to visualise novel PS decision. Therefore, this paper aims to present a knowledge visualised framework for aiding construction PS decision-making.

This paper describes the construction of process innovation. The framework (process) is supported by four influential decision supporting methods (mean utility values, analytic hierarchy process, fuzzy set theory and Delphi method) and computer programming (Matlab).

There are four stages of this framework: (1) uniform rating for decision alternatives; (2) group decision for determining the decision attribute; (3) determining the final choice; (4) reporting the cognitive computing process. Supported by individual and groups decision dynamics, this framework emphasises how the dashboard aided innovative approach enables the induction of understanding, cognitive computing for decision-making and how the information would precisely be represented, which are vital requirements of modern construction.

The contribution of this paper presents two leverage points that support the modern PS decision. Firstly, this paper provides a holistic view of the decision supporting methods on the basis of how a suitable PS would be systematically sought. Based on the existing studies, this paper upgrades into a visualised knowledge decision supporting process. It helps the participants understand and improve their cognitive learning. Secondly, this framework allows the participants to have a view of the individual and group decisions. It sheds light on the development of the collaborative decision-making process.

This study aims to clarify the risk management practices of banks as supply chain finance (SCF) service providers.

Using 4,014 evaluation and approval reports, this study constructed five risk management factors and examined their functions with secondary data. Two text-mining techniques (i.e. word sense induction, TF–IDF) were used to equip the classic routine of dictionary-based content analysis.

This research successfully identified four important risk management factors: relationship-based assessment, asset monitoring, cash flow monitoring and supply chain collaboration. The default-preventing effect of these factors are different and contingent on the type of financing contexts (i.e. preshipment, postshipment).

The empirical evidences provide practical implications for SCF service providers to manage risk. SCF service providers are suggested to pay more attention to cash flow monitoring when providing postshipment financing services and shift the focus to relationship building and supply chain collaboration when providing preshipment financing services.

The study shows that a large volume of textual materials can provide adequate clues for researches as long as they are mined with suitable analytic techniques and approaches. Based on the results, SCF service providers can identify problems of their operations and directions for improvement. In addition, the risk management vocabulary from the E&A reports can be utilized by SCF service providers to digitize their loan approving process and, further, to facilitate the decision-makings.

This paper aims to provide an improved multifractal method to extract the pavement cracks in the complicated background. Furthermore, the pavement surface images with or without crack can also be distinguished by this method.

The framework of analyzing the image singularity is based on the sub‐pixel multifractal measure (SPMM). Performing the SPMM can give the sub‐pixel local distribution of the image gradient and a more precise singularity exponent distribution in the image. Meantime, using the singularity exponents and the most singular manifold (MSM), the image can be decomposed into a series of sets with different statistical and physical properties automatically and easily. One can extract the cracks according to the MSM.

The example shows that the physical and geometrical properties of the pavement images can be obtained by analyzing the distribution of singularity exponents and the greatest singularity exponent. The simulation results show that the SPMM has higher quality factor in the image edge detection. And the MSM detected this way reflects the most important information of the image.

Performing the SPMM can give a more precise singularity exponent distribution in the image.

An enterprise social network (ESN) is part of the landscape of information reform by enterprises, using Web 2.0. In terms of the marketing targets of typical Web 2.0 techniques, enterprise knowledge sharing in Web 2.0 can be classified into different types (individual interaction type, group interaction type, social interaction type, real‐time interaction type and delay interaction type). The purpose of this paper is to summarize the features and modes of different enterprises' knowledge sharing and study enterprise knowledge sharing quantitatively from an ESN perspective by selecting real‐time interaction type as the case.

Because of the area of research, the authors supplemented social network analysis (SNA) with a mathematical modeling method and additional in‐depth interviews.

The Web 2.0 era provides the opportunity to quantify knowledge sharing. Also, SNA can quantitatively and visually diagnose the knowledge sharing status of the enterprise and guide the enterprise's knowledge‐sharing process.

Only a case study regarding real‐time interaction type is presented; other types of interaction are not studied empirically.

SNA, combined with a mathematical modeling method and additional in‐depth interviews with team leaders or key managers in organizations, can diagnose quantitatively, visually and comprehensively the knowledge‐sharing status of the enterprise.

This paper systematically summarizes the features and modes of Web 2.0 enterprise knowledge sharing, and the multiple‐method research design represents a sound approach to targeting enterprise knowledge sharing.

Post-merger integration (PMI) is driven by coevolving processes. By integrating the literature on acquisitions with that of knowledge networks, this paper highlights different reconstruction mechanisms for dual knowledge networks during PMI – namely, internal knowledge network coupling and external knowledge network embeddedness. This paper aims to examine their coevolutionary relationships with PMI.

A coevolutionary framework is tested using a latent growth model and cross-lagged models. The analysis is based on longitudinal data collected from 116 Chinese technology-sourcing overseas merger and acquisition firms.

This paper unearths a novel idea that variations in post-merger reconstruction of dual knowledge networks can explain why some acquirers increase the degree of integration faster than the others. The results show that the internal knowledge network coupling leads to more knowledge similarity and, in turn, causes a higher degree of integration. The external knowledge network embeddedness also causes higher relative network status of the acquirer, which consequently leads to a higher degree of integration. Furthermore, results from cross-lagged models confirm that an increase in the degree of integration positively influences subsequent changes in the internal knowledge network coupling and external knowledge network embeddedness, thus forming a coevolutionary relationship over time.

This paper responds to recent calls for more insights into the dynamics of PMI. By highlighting different reconstruction mechanisms for internal and external knowledge networks during PMI, this paper explains why it is important to understand PMI dynamics from a dual knowledge network perspective. This paper is the first to adopt a coevolutionary perspective and provide a more comprehensive dynamic framework between PMI and reconstruction of dual knowledge networks. Besides, this paper contributes to the research on emerging market multinational corporations’ cross-border merger and acquisition integration from a dynamic perspective, revealing the time effects of traditionally favored light-touch integration.