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This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.

The main aim of this paper is to establish a reasonable and scientific evaluation index system to assess the high quality and full employment (HQaFE).

This paper uses a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria framework to evaluate the quality and quantity of employment, wherein the integrated weights of attributes are determined by the combined the Criteria Importance Through Inter-criteria Correlation (CRITIC) and entropy approaches.

Firstly, the gap in the Yangtze River Delta in employment quality is narrowing year by year; secondly, employment skills as well as employment supply and demand are the primary indicators that determine the HQaFE; finally, the evaluation scores are clearly hierarchical, in the order of Shanghai, Jiangsu, Zhejiang and Anhui.

A scientific and reasonable evaluation index system is constructed. A novel CRITIC-entropy-TOPSIS evaluation is proposed to make the results more objective. Some policy recommendations that can promote the achievement of HQaFE are proposed.

The consulting team intervenes in the integrated construction consulting (ICC) network structure centered on “client-contractor-consultant.” Team boundary-spanning behavior (TBB) driven by the network structure is crucial to project performance. This article investigated how to stimulate the consulting project performance (CPP) improvement by considering the interactive effect of network structure and TBB. To be specific, this paper explored the configuration between structural characteristics of project networks, the dimension of TBB, and project performance in ICC projects.

Network density and centrality were used to reflect network structure. This study collected 216 valid responses from construction professionals (including project managers, department managers, and project engineers) via a questionnaire survey and analyzed the data using fsQCA.

Combining with the corresponding typical project case and analysis, the results concluded four types of configurations for achieving high performance in the ICC projects. Meanwhile, network centrality, density, ambassadorial behavior, coordination behavior, and detection behavior significantly impact high consulting project performance. Matching ICC network characteristics with the TBB is important. There are also three low performance configurations for the ICC projects. Low performance state also occurs when network centrality or density and coordination behavior is simultaneously low. Only the right match between the network characteristics and TBB can produce high consulting project performance.

The network centrality and density, the implementation of TBB vary, and the paths to achieve high consulting project performance are different. Clients, ICC projects, and consulting teams should choose the appropriate development paths according to the actual situation. (1) Clients should commit to applying the ICC project model with high network centrality, density, and coordination behavior of ICC enterprises to promote project performance. (2) Consulting enterprises should carry out ICC business based on detecting behavior and coordinating behavior. (3) The market should cultivate head consulting enterprises with independence and integration, and bring into play the effectiveness of consulting team ambassadorial behavior.

Comparing the results of the four high CPP configurations, the network structure characteristics are essential, which means that in the Chinese consulting practice between the owner and the consulting firm pay attention to the use of appropriate ICC organizational structure model and arrange the degree of centralization of authorized responsibilities. Coordination behavior is necessary to achieve high CPP. Therefore, Chinese consulting firms should pay attention to effective communication and exchange with project contractors in order to get high CPP in conducting business; meanwhile, enabling behavior can achieve high CPP both in the presence and absence of configuration H1 and H4, which indicates that enabling behavior has substitution effect. Comparing the three low CPP configurations also contrarily confirms the indispensability of coordinating behavior. Comparing the results of high and low CPP configurations, the TBB is seriously missing and not properly applied in CPP enhancement. In detail, Chinese consulting firms have been regarded as independent third parties providing services, and less attention has been paid to the TBB of Chinese consulting firms in past practice, thus leading to the dilemma of inadequate empowerment of consulting firms due to their unclear status. To solve this dilemma, the findings of this paper offer a solution at the micro level to change the previous perception of consulting and demonstrate that Chinese consulting practice needs to pay attention to TBB with owners and contractors, and apply it well to enhance the reputation, management consulting level and capability, and experience and expertise of consulting firms to achieve high CPP.

The research results changed from the previous bilateral project governance to a new perspective of network embedding. It provided a theoretical basis for the improvement path of high consulting project performance, as well as providing ideas for clients on the organizational design of ICC projects. On the other hand, it provided a practical reference for TBB positioning of ICC enterprises for transformation and upgrading development.

The purpose of this paper is to create a model that connects drivers between organizational innovation and business model innovation (BMI) to guide empirical research and the design of innovation management strategies.

The model was designed based on the results of a systematic literature review over the past 25 years that provides common predictor variables to build bridges between these two types of innovations.

It is a conceptual relationship between organizational innovation and BMI based on processes, new structures and customer relationship management. Moreover, there are five bridges from common predictors: strategy, top management, exploratory learning, technological innovation and environmental complexity.

The relationships between organizational innovation and BMI have been neglected in the literature. The model fills this gap by proposing hypotheses for empirical research and critical variables and relationships to steer organizational and business model innovation.

The study aims to evaluate the influence of capital structure decisions and asset structure on firms' performance for East African listed nonfinancial firms.

The research is descriptive and employs secondary data from the East African capital markets' websites. The generalized method of moments approach is used to estimate the relationship due to its ability to account for endogeneity problems.

The result shows that capital structure decisions and asset structure strongly influence the firms' performance. When long-term debts, short-term debts and tangible fixed assets increase, the return on total assets increases. An increase in the total debt ratio raises the return on equity (ROE). However, the increase in long-term debt lowers the ROE.

The results will help investors and potential investors decide on a financing policy that maximizes performance. Likewise, governments and other policymakers review the capital markets' frameworks to attract institutional and individual investors to the markets for financial availability and to increase profitability.

The research provides evidence on the influence of capital structure decisions and asset structure on firms' performance. Furthermore, its results contribute to firms' financing policy formulation and the corporate finance literature.

This study aims to investigate how the presence of female executives on the board affects a company’s capital structure decisions. The critical mass of female executives on the board was also considered to observe their impact on capital structure.

Samples were taken from nonfinancial sector companies listed on the Indonesia Stock Exchange between 2012 and 2021 (3,707 firm-year observations). Capital structure was measured using four approaches, namely, debt-to-total asset ratio (DAR), debt-to-equity ratio (DER), short-term debt-to-total assets (STD) and long-term debt-to-total assets (LTD). The data were analyzed using panel data regression analysis, including a fixed effects model with clustered standard errors.

The presence of female executives on the board is significantly negatively related to capital structure as measured by DER and STD. The critical mass of women provided no evidence of a relationship with a firm’s capital structure. Robustness checks were performed, and the results were consistent with those in the main analysis.

Female executives can be appointed to management boards when determining a strategy to achieve the capital structure desired by a company.

This study increases the diversity of research in corporate governance by synthesizing various indicators from female executives into a single study to determine their relationships with companies’ capital structures. In addition, this study stands out by incorporating four distinct indicators for assessing capital structure and diverging from the norm observed in many other studies, many of which rely on just two indicators: DAR and DER. Moreover, it strongly emphasizes the unique economic, legal, social and cultural landscapes of developing countries like Indonesia in comparison to their developed counterparts, particularly Western nations.

The purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market.

This paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples.

The empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility.

This paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets.

This study aims to answer the question: What dynamic capabilities do diverse humanitarian organizations have?

We examine this question through the lens of dynamic capabilities with sensing, seizing and reconfiguring capacities. The research team interviewed 15 individuals from 12 humanitarian organizations that had (a) different geographic scopes (global versus local) and (b) different missions (emergency response versus long-term development aid). We also gathered data from secondary sources, including standard operating procedures, company websites, and news databases (Factiva, Reuters and Bloomberg).

The findings identify the operational and dynamic capabilities of global and local humanitarian organizations while distinguishing between their mission to provide long-term development aid or emergency relief. (1) The global organizations, with their beneficiary responsiveness, reconfigured their sensing and seizing capacities throughout the COVID-19 pandemic by pivoting quickly to local procurement or regional supply chains. The long-term development organizations pivoted to multi-year supplier agreements with fixed pricing to counter price uncertainty and accessed social capital with government bodies. In contrast, emergency response organizations developed end-to-end supply chain visibility to sense changes in supply and demand. (2) Local humanitarian organizations developed the capacity to sense demand and supply changes to reconfigure based on their experiential learning working with the local community. The long-term-development local organizations used un-owned and scalable relief infrastructure to seize opportunities to rebuild affected areas. In contrast, emergency response organizations developed their capacity to seize opportunities to provide aid stemming from their decentralized decision-making, a lack of structured procedures, and the authority for increased expenditure.

We propose a theoretical framework to identify humanitarian organizations' operational and dynamic capabilities, distinguishing between global and local organizations and their emergency response and long-term aid missions.

The literature has dealt with the relationship between board characteristics (BC) and firm performance (FP) on a large scale. However, it yielded inconsistent results. Thus, this paper aims to examine the indirect relationship between BC and FP through the mediating role of the capital structure (CS).

This study used a sample of 528 non-financial companies listed on Bursa Malaysia from 2015 to 2019. Also, a two-step system generalised method of moments estimation technique was applied.

The results show that board diversity and the frequency of board meetings positively affect financial performance, and it is negatively influenced by board turnover, size and independence. Also, the results indicate a positive relationship between the independence of the board and all CS variables. Importantly, the findings support the policy-setting role of the board of directors where CS (measured by total debt and short-term debt) suppresses some governance mechanisms’ detrimental effect on FP. Hence, the board of directors, apart from the monitoring function, introduce various policies (financial and non-financial) that enhance the overall performance of companies.

These results are consistent with the agency’s perspective that management practices in selecting the optimal capital reduce agency costs and improve performance. The findings contribute to developing a broader theoretical framework that accounts for the policy-setting role of the board of directors. The current study model of corporate governance offers insight for policymakers into the role of corporate governance other than monitoring functions in organisations and how CS should be taken into consideration with corporate governance and FP association.

This study examines the differences in the economic stimulus effects, transmission mechanisms, and output multipliers of government consumption, government traditional investment, and government science and technology investment.

This study constructs and estimates a New Keynesian model of endogenous technological progress embedded in the research and development (R&D) and technology transfer sectors. Using Chinese macroeconomic time series data from 1996 to 2019, this study calibrates and estimates the model and analyzes the impulse response function and a counterfactual simulation of expenditure structure adjustment.

The results show that compared with the traditional dynamic stochastic general equilibrium (DSGE) model, the endogenous process of technological progress amplifies the impact of government consumption shock and traditional government investment shock on the macroeconomy, leading to greater economic cycle fluctuations. As government investment in science and technology has positive external spillover effects on firm R&D activities and the application of innovation achievements, it can promote more sustainable economic growth than government consumption and traditional investment in the long run.

This study constructs an extended New Keynesian model with different types of government spending, which includes endogenous technological progress within the R&D and technology transfer sectors, thereby linking fiscal policy, business cycle fluctuations and long-term economic growth. This model can study the macroeconomic impact of fiscal expenditure structure adjustment when fiscal expansion is limited. In the Bayesian estimation of model parameters, this study not only uses macroeconomic variables but also adds a sequence of private R&D investment.