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In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.

The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.

Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.

While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.

Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.

Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.

The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.

In the face of frequent supply chain disruptions, this study aims to identify the relationships between human capital (HC), digital supply chain practice (DSCP) and supply chain robustness and resilience (i.e. SCRO and SCRE).

To examine the proposed conceptual model based on the resource-based view and organizational information processing theory, an empirical study was conducted using a sample of Chinese manufacturers. Hierarchical regression is applied to understand the direct effect, mediating effect and moderating effect among HC, DSCP, SCRO, SCRE and digital culture.

The results reveal that HC positively influences digital maturity and supply chain resilience. DSCP positively affects both SCRO and SCRE. However, HC does not significantly influence the adoption of digital tools, and only employees’ capital has a positive relationship with SCRO. In addition, the moderating effect of digital culture on the relationship between HC and DSCP was examined.

As an early exploration of the relationships among HC, DSCP, SCRO and SCRE, this study enriches the literature by offering new insights and responding to the call for more empirical research and theoretical application. It emphasizes the importance of HC and DSCP as strategic resources and highlights the need for a digital culture to implement DSCP.

High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

This paper proposes a framework for director evaluation in the context of Chinese state-owned enterprises (SOEs), taking into account the influences of traditional and modern Chinese ideologies.

Following the Delphi method, a series of semi-structured interviews were conducted with Chinese SOE directors.

The framework used has been validated by examining seven dimensions of virtue and four dimensions of competence functions in Chinese SOEs. Effective and representative characteristics of each dimension are identified through interviews.

First, through this research, indicators of virtue have been materialized and those of competence have been specified in a broader range. Second, this research provides advice for training of candidate directors whose experience were in private firms before they step in as SOE directors.

This study investigates the influence of trading mechanisms on cross-market integration between stocks and corporate bonds on the Tel Aviv Stock Exchange (TASE) during the COVID-19 crisis. Unlike the worldwide practice of trading corporate bonds on an over-the-counter (OTC) market, TASE uses a limit-order-book (LOB) for both stocks and bonds, potentially creating unique volatility dynamics through direct information spillover. We analyze the volatility dynamics and spillover effects between TASE’s stock and corporate bond markets.

We employ an exponential general autoregressive conditional heteroskedastic (EGARCH)(1,1) model to assess the impact of stock market fear, measured by implied volatility, on Tel-Bond 20 Index returns and volatility. A bivariate diagonal Baba-Engle-Kraft-Kroner (BEKK) model is also applied to capture time-series integration and cross-volatility spillovers between the TA-35 Index (stocks) and the Tel-Bond 20 Index (corporate bonds), especially during financial stress.

The EGARCH model reveals a significant contagion effect, with increased stock market fear lowering corporate bond returns and increasing bond volatility. It also indicates a leverage effect, where negative shocks disproportionately amplify bond volatility. Diagonal BEKK results confirm strong cross-market volatility persistence, especially during crises, highlighting substantial financial contagion between stocks and bonds in TASE. While TASE’s market design improves the overall market quality, these findings underscore the LOB trading mechanism in facilitating financial contagion and systemic risk.

The LOB trading in TASE facilitates direct information flow, intensifying volatility spillover and cross-market integration, with the degree of integration fluctuating based on market conditions. Investors and managers should consider alternative hedging strategies during volatile periods, as stock market sentiment significantly impacts bond stability. Regulators should assess how trading mechanisms affect market integration and risk, especially during periods of distress.

This study offers new insights into how trading mechanisms influence cross-market dynamics, contributing to the literature on market design and financial contagion.

This study aims to optimize the construction site layout planning (CSLP) problem, with a focus on prefabricated projects. It proposes the use of the oMOAHA algorithm, an enhanced version of the multi-objective artificial hummingbird algorithm (MOAHA), to address challenges related to search space exploration and local optimization in CSLP.

The study integrates three techniques – opposition-based learning (OBL), quasi-opposition and quasi-reflection – into the initialization phase of the MOAHA algorithm, creating the oMOAHA variant. This model is applied to all three types of CSLP problems – pre-determined location, grid system and continuous space – to evaluate its effectiveness. Six objective functions (three related to cost, two to safety and one to tower crane efficiency) and four site-related constraints are considered through three case studies taken from previous research and one real project involving prefabricated steel structures.

The oMOAHA algorithm demonstrates superior performance compared to previous models, consistently outperforming traditional approaches in CSLP optimization for prefabricated projects. In the real case study, the proposed model exceeded the actual project plan by 28–43%, indicating its potential to significantly improve both solution quality and project outcomes.

This study is the first to apply an optimization model to all three types of CSLP problems – pre-determined location, grid system and continuous space – within a unified framework. The integration of advanced techniques into the MOAHA algorithm and the model’s successful application in a real prefabricated project underscore its high applicability and effectiveness in modern construction management.

The study aims to investigate the influence of stakeholder pressure on sustainability practices via the mediating effect of green innovation (GI) from a developing economy in Sub-Saharan Africa (SSA).

The study used primary data from 567 respondents in manufacturing and mining firms in Ghana to conduct the Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis using Smart-PLS, Version 4.0. Data was gathered using survey questionnaire. A purposive sampling method was used to choose participants' companies.

The findings revealed that shareholder and government pressure significantly and positively influence sustainability practices, while pressure from the community has an insignificant beneficial impact on sustainability practices. Consumer pressure revealed an insignificant detrimental influence on sustainability practices. The study discovered that green innovation fully and substantially mediates the association between stakeholder pressure and sustainability practices.

The study has limitations, including the exclusion of control variables and its focus on four different stakeholders, excluding other stakeholders that who also impact sustainability practices.

The study’s findings can assist Ghanaian companies in making strategic decisions to enhance corporate reputation, acknowledging the effect of stakeholder pressure on sustainability practices.

The study outcome may enable companies to implement more inclusive sustainable development initiatives, benefiting their bottom line while contributing to the well-being of local communities and the environment.

The study’s originality stems from integrating green innovation in examining stakeholders' influence and sustainability practices of firms, a gap that remained unexplored. It highlights the essence of green innovation in shaping a company’s sustainability practices, highlighting the need for businesses to integrate technology and sustainability in their operations.

Our study aimed to verify the role of the digital economy in economic growth in Egypt and the availability of the technological capabilities of the business sector for digital transformation, based on the negative impact of the epidemic on all economic sectors in the world in general and Egypt in particular.

This was verified based on the standard Error correction package modeling (VECM) study and analysis using Xlstat 2023 and EViews 10.

The results of the study conducted during the period (1996–2022) showed that there is a co-integration relationship in the short and long term between the impact of the digital economy and economic growth. We found a positive, statistically significant relationship between the variables of mobile phone subscriptions and Internet use that had a strong positive effect. At the same time, trade openness hurt economic growth in the short term. In the long run, both mobile phone subscriptions and trade openness had a significant positive effect, and the speed of adjustment toward equilibrium was very severe, estimated at 4.7 years (1/0.21).

The work is limited to the economies of Egypt, which is part of Africa. We suggest conducting further research on evidence from other emerging and developed economies.

The results are of great importance to policymakers in Egypt as an African country, as the estimation results were positive between the digital economy and economic growth in the Egyptian economy, and this is consistent with the endogenous growth model of economic growth, which assumes that knowledge is the main driver of economic growth.

The paper documents the importance of the digital economy in boosting economic growth, which impacts social life more than the traditional digital economy, especially in times of crisis.

Based on the existing literature, this paper identified various research gaps. First, no consensus has been reached on the concept of the digital economy, and its index system is inadequate. While existing literature concentrates on examining the influence of ICT on economic development in terms of the number of Internet users, fixed broadband Internet users and mobile subscribers. These measures cannot adequately capture the broader implications of the digital economy. Furthermore, research has largely investigated the significance of digitalization in economic development and reached ambiguous conclusions.

The purpose of this study is to examine the impact of customers' environmental concern on corporate green innovation and its underlying mechanisms.

This study empirically examines the impact of customer environmental concern on corporate green innovation using 967 company-customer-year observations of Chinese A-share listed companies over the period 2012–2022.

The empirical results show that customer environmental concern significantly enhances corporate green innovation. Furthermore, executive environmental awareness and research and development (R&D) investment play a partial mediating role in this relationship. The heterogeneity analysis reveals that state-owned customers, customers located in the same province with the corporate and the intellectual property model cities contribute to strengthening this relationship. Moreover, corporate performance analysis shows that customer environmental concern can significantly increase corporate financial performance and sustainable performance.

This study innovatively proposes a measure of customer environmental concern and examines its impact on corporate green innovation and its underlying mechanisms. In addition, this study also proposes some insights for policymakers.

This study aims to examine the effect of digital fashion marketing on consumer purchase intentions. Rooted in the stimulus–organism–response framework, it explores how digital marketing strategies in the fashion industry influence consumer attitudes and satisfaction, ultimately affecting their purchasing decisions.

It is mainly focused on the attitudes, satisfaction, and purchase intentions of young consumers in China and South Korea toward fashion brands stimulated by digital fashion shows and non-fungible tokens. This study modifies the research model through case studies, collects data through questionnaires, and analyzes the data using fsQCA and AMOS.

The findings of the fsQCA study show that stimuli impact consumers’ attitudes, satisfaction, involvement, and willingness to rewatch. The multigroup analysis shows that social norms and images have a greater influence on individuals in China, whereas Korea has a higher direct effect of individual involvement on consumption behavior.

The study is useful for global fashion brands because it emphasizes the role of digital innovations in shaping consumer–brand relationships and makes strategic recommendations for sustainable growth in the digital fashion landscape.