At present, most of the review papers related to blood supply chain mainly focus on research issues, methods, trends, and challenges, lacking comprehensive research on blood supply chain management from the perspective of data application. Therefore, in this paper, 116 academic papers were reviewed using bibliometric methods to visually display the cooperation and hot spots related to blood supply chain management based on big data, based on which, the research hotspots of blood collection management, blood inventory and distribution management, and blood supply chain network design were explored from the perspective of big data. In addition, a PAGE framework was proposed for blood supply chain management based on big data to elaborate future research directions. This paper will help scholars more accurately track and focus on the research frontiers and topics of big data application in blood supply chain management, and provide important guidance for the industry to manage blood supply chain utilizing big data methods.

Using the rich data from online judicial auctions in China, this paper empirically investigated the performance and inherent mechanism of a common bidding strategy, i.e., jumping bidding, in online auctions with a soft-closing mechanism. The result shows that jump bidding increases the probability of winning for bidders but at the same time, increases their payment cost. The signaling theory can better explain the phenomenon of jump bidding in online auctions. Due to the soft closing mechanism, jump bidding before delay is invalid. When the signal is stronger, there is less irrational jump bidding, and when bidders are sophisticated, the payment cost for using the jump bidding strategy is lower. The excessive payment cost may be the result of responding to market noise.

In a secondary supply chain consisting of a single manufacturer and a supplier, the supplier’s financial constraints and private information about their production effort costs significantly influence the manufacturer’s procurement strategy. To delve into this dynamic, the Stackelberg game model constructed under the buyer-direct financing (BDF) mode uniquely integrates the concepts of supply chain finance and information asymmetry, presenting distinctiveness characteristics compared to existing literature. Scenarios of both information symmetry and asymmetry are encompassed, with a focus on analyzing how the manufacturer formulate optimal procurement contracts under conditions of information asymmetry. In addition, how the type and precision of information acquired by the manufacturer impact the decisions and benefits of all parties in the supply chain is further explored. It is revealed that the supplier’s asset collateral value, the type of information obtained, and the precision of information significantly influence the manufacturer’s decisions on procurement prices and loan interest rates. In situations of information asymmetry, different types of information have varying effects on the tradable range. When the manufacturer acquires information for free, increasing information precision aids the manufacturer in making more rational decisions, thereby achieving higher expected profits, especially when facing information disadvantages. However, when the manufacturer incurs costs to obtain information, the optimal information precision for maximizing profits is not always higher but is constrained by the costs of information acquisition.

In the “Port before Factory” mode, the port provides high-quality value-added services for steel mill production operations, forming a “chain” and “chain” alliance with the port service supply chain and the steel mill production supply chain. In addition, a fair and reasonable benefit distribution plan is a key factor affecting the stability and performance of the alliance. Therefore, in order to promote the effective operation of the “Port before Factory” supply chain alliance, this paper, taking into account the characteristics of the “chain” and “chain” alliances, considering the factors of service contribution and service duration, and aiming at maximizing the overall benefit of the alliance, constructs a benefit distribution model. However, because the model is non-linear, non-differentiable, and requires high accuracy of the results, a bacterial foraging optimization algorithm with a wide search range and a large evolutionary space is selected to solve the problem. The new algorithm combining foraging dynamics and the foraging optimization algorithm designed in this paper overcomes the defect of the poor stability caused by the uncertain flip direction of a single foraging optimization algorithm, which improves the accuracy and stability of the algorithm. The simulation verification using Python shows that the result of benefit distribution conforms to the principles of the overall rationality and individual rationality in the cooperative game theory, which proves that the benefit distribution model is fair and effective, and provides scientific basis and theoretical methods for the “integration of advanced manufacturing and modern service industries.”

This paper, considering the impact of decision maker’s cost-benefit perception bias on quality decision, and introducing the prospect theory and mental account theory into the shared manufacturing multi-subject evolutionary game process, builds a shared manufacturing quality synergy game model in different cost-benefit allocation mechanisms, and analyzes the dynamic evolutionary law of each game subject. The results show that the quality synergy improvement of shared manufacturing is the result of multiple factors, which is not only influenced by external factors, but also regulated by the decision maker’s own subjective factors. Cost-benefit allocation mechanisms can effectively change the evolutionary stability of shared manufacturing quality synergy, of which, the dynamic cost-benefit allocation mechanism is the most effective. The introduction of incentive mechanisms can effectively fill the effectiveness gap of the cost-benefit allocation mechanisms and promote the evolution and development of the stable strategy in the shared decision-making system towards “Pareto optimality”.

Quality problem is one of the main reasons for reworking of project, and the skill level of personnel is the key factor affecting the quality of project activities. Based on the general multi-skilled resource-constrained project scheduling problem, this paper comprehensively considers the influence of skill level of personnel and the quality transmission between activities on the activity completion quality, and further describes the reworking subnet and the reconstructed project network, in combination with a case study of a large shipbuilding project. The results show that the model proposed in this paper can effectively balance the allocation of limited human resources among different activities, reduce the diffusion of reworking risk and shorten the total project duration. Moreover, through random experiments of disturbance parameters of quality interval as well as skill level, it verifies the robustness of the model proposed for the two parameters.

In order to reveal how the complex interaction between social demographic factors and situational factors contributes to employee low-frequency safety violation (LSV), this paper, integrating the configuration approach into the individual-situation interaction theory, and using the fuzzy-set qualitative comparative analysis (fsQCA), explores the configurational effects of both individual (employment type and gender) and situational (safety violation frequency of coworkers, enterprise safety investment, enterprise employee size, and industrial hazard level) antecedents on employee LSV with the survey data from 1294 employees. The results suggest that no single factor constitutes a necessary condition for employee LSV. The employee LSV can be motivated by three configurations consisted of individual and situational antecedents, i.e., low frequency safety violation of coworkers in non-high-risk industries, high safety investment and low frequency safety violation of coworkers, and high safety investment from large enterprises in non-high-risk industries. In four out of five configurational solutions, coworker low frequency safety violation is found to be the core condition to motivate employee LSV. By exploring the configurational effect of individual and situational antecedents on employee LSV by introducing the fsQCA, this paper not only expands the understanding of specific configurations that contributes to employee LSV, but also helps to advocate for the application of the configurational approach in safety behavior research.

The systemic risk of social security incidents in China has become prominent under new situations, making it more difficult to judge the emergency response level. Aiming at the problem of inconsistent judgment of emergency response level among experts, a decision-making method considering self-confidence adjustment is proposed to judge emergency response level. The trust degree and familiarity degree provided by experts are used to construct a binary function to describe the trust relationship between experts, and the adjustment mechanism of self-confidence is established. By analyzing the uncertainty of expert judgment contained in incomplete confidence, the decision problem of emergency response level is modeled based on the evidence theory. On this basis, taking into account the importance of the source of evidence and its own credibility, a method for calculating the reliability of evidence considering decision-makers’ risk preferences is proposed to assign different importance to evidence. Then, the evidence discount combination method is used to fuse the judgements provided by experts. Finally, the practicality and superiority of the proposed method are verified by an example. The results show that the method proposed has a wider applicability, a higher credibility, and a stronger practicability than other common decision-making methods such as voting, and authority.

Based on the resource-based theory and focusing on the stability and flexibility characteristics of resilient enterprises, this paper explores the impact of technological diversification on enterprise resilience in the digital transformation context. With a sample of listed high-tech firms in China from 2018 to 2022, before and after COVID-19, an OLS (ordinary least squares) regression and survival analysis is conducted for empirical analysis. The results show that both unrelated technological diversification and related technological diversification have an inverted U-shaped relationship with the stability of enterprises after a shock. Unrelated technology diversification negatively affects the flexibility of enterprises after a shock, while related technology diversification has a positive effect on the flexibility of enterprises after a shock. Digital transformation enhances the inverted U-shaped relationship between related technology diversification and the stability of enterprises after a shock, and can weaken the negative effect of unrelated technology diversification on the flexibility of enterprises after a shock. The findings enrich and expand the research on technology diversification and enterprise resilience, and provide reference for enterprises to develop appropriate technology diversification strategies to enhance enterprise resilience.

Based on the data of 130 sample countries, this paper empirically explores the relationship between national innovation systems, knowledge-based dynamic capability, and achievement of national sustainable development goals. It compares and analyzes the impact of national innovation systems and knowledge-based dynamic capabilities on the achievement of national sustainable development goals at different stages of economic development and different dimensions of goals. The research results show that national innovation systems contribute to the achievement of the sustainable development goals, but its constituent elements have heterogeneous effects on the achievement of national sustainable development goals at different stages of economic development, and the effects on the economic, social, and environmentally sustainable development goals are also different. In addition, the knowledge-based dynamic capability is an important driving force for the achievement of national sustainable development goals, but its constituent dimensions play different roles in the achievement of national sustainable development goals at different stages of economic development, and also show differences in the achievement of the economic, social, and environmentally sustainable development goals. This also means that there is a complex relationship between national innovation systems, knowledge-based dynamic capacity, and achievement of sustainable development goals.

Green innovation is an important force to improve the quality and efficiency of regional economy. How to promote green innovation and improve urban green competitiveness is an important issue to be answered in the field of innovation. This paper, integrating the transaction cost theory, the knowledge spillover theory, and the resource allocation theory, analyzes the data of 254 prefecture-level and above cities by using qualitative comparative analysis (QCA), non-compartmental analysis (NCA), and propensity score matching (PSM), and by exploring the linkage effect of heterogeneous environmental policies, institutional environment, and agglomeration effect on urban green innovation from the overall perspective, as well as whether different green innovation paths are conducive to the improvement of urban green competitiveness. The results show that a single antecedent does not constitute a necessary condition for the generation of high green innovation, nor does it constitute a sufficient condition for the generation of high green innovation. Heterogeneous environmental regulation, institutional environment, and agglomeration effect are linked and matched, forming a diversified configuration form of urban green innovation, with obvious characteristics of “different paths leading to the same destination”. It is embodied in the institutional environment-oriented model, the command-and-control oriented-model, the market incentive-oriented model, and the policy combination-oriented model. There are significant differences in the impact of the four green innovation models on urban competitiveness, with the characteristics of “different ways leading to different effects”, and the impact of different green innovation modes on urban competitiveness has a hysteretic effect. The research conclusion reached in this paper provides a decision-making basis for cities to conduct green innovation and enhance competitiveness from the perspective of configuration, compensate for the limitations of traditional quantitative analysis on this issue, and enriche the green innovation theory to a certain extent.

This paper, by employing text mining techniques, analyzes the text of management discussion and analysis (MD&A) content in annual reports of listed companies and constructs an MD&A evaluation system from the perspectives of text similarity, text readability, text tone, and management expectations. By constructing a cost-sensitive gradient boosting decision tree (csGBDT) model, it examines the impact of multidimensional MD&A indicators on corporate default prediction and further analyzes the MD&A indicators that have a significant impact on corporate default status and their marginal effects on the role of default status. It is found that MD&A indicators can be used as an alternative data source to accurately predict the default status of listed companies. MD&A indicators are less effective predictors compared to traditional default prediction variables. MD&A indicators provide additional information content on top of traditional default discriminators. The csGBDT model significantly improves the discriminatory ability of firms (especially for defaulted firms) in the large scale of default prediction data methods, which has obvious advantages. Among the many MD&A indicators that have a significant impact on corporate default are, in order, text similarity compared to the previous year, total vocabulary, sentiment tone 2, total vocabulary/number of sentences, sentiment tone 1 and whether management has issued a performance forecast. This paper extends the research boundary of corporate default prediction from structured data to unstructured textual data, which helps to curb the risk of corporate default due to information asymmetry.

This paper explores the estimation of implicit government guarantees for quasi-municipal corporate bonds (“Chengtou” bonds) issued by local government financing platforms (LGFPs). It holds that although the new Budget Law prohibits local governments from providing guarantees for any institutions, the market prices of Chengtou bonds suggest that investors still believe that local governments will provide implicit guarantees for Chengtou bonds, i.e., there exists what is known in the industry as “Chengtou beliefs”. This paper defines Chengtou beliefs as “the probability of government providing guarantee for Chengtou bonds implied in the market price”, and analyzes the prices of Chengtou bonds in two states: government providing guarantee and government not providing guarantee. Then, it gives the pricing formula of Chengtou bonds considering the Chengtou beliefs based on the option pricing theory, as well as the method and example of measuring the implicit guarantees by using the trading price data of Chengtou bonds. The method given in this paper is based on the product level of Chengtou bonds rather than the industry level, and can be used to examine in more depth the impact of implicit government guarantee on the price of Chengtou bonds when Chengtou beliefs become increasingly differentiated, and evaluate the implicit guarantee of Chengtou bonds in a more rational way.

The impact of digital economy development on income gap is related to the overall realization of inclusive growth. Based on the panel data combining the individual level and the provincial level from 2010 to 2020, this paper empirically tests the influence and mechanism of digital economy development on the income gap between low-and medium-skilled labor and high-skilled labor by using the two-way fixed effect model. The research findings reveal that the development of digital economy widens the income gap, and industrial intelligence has played an intermediary role in this process. Additionally, the heterogeneity analysis shows that in eastern China and non-agricultural registered permanent residence labor groups, the role of digital economy in widening the income gap has been enhanced. However, in the central and western regions of China and agricultural registered permanent residence labor force, the impact of digital economy on the income gap is narrowing and has no significant impact. Moreover, it is found that the digital economy has no significant effect on the income gap in the early stage of development, but the effect of expanding the income gap gradually appears in the later stage. The conclusion expands the relevant research on digital economy and income gap, and provides operational suggestions for the government to formulate corresponding policies, which is helpful to promote inclusive growth of digital economy in the future.

In the context of “common prosperity”, charitable donations, considered as a means of “the third distribution”, can effectively promote social equity. In China, companies are the main source of charitable donations. However, it is an abnormal behavior for companies to make a large charitable donation even when they are in a state of losing money. Therefore, it is worthy of exploring the logic behind this behavior. From the perspective of legitimacy, this paper, using a mixture of necessity condition analysis (NCA) and regression analysis, explores the mechanism by which charitable donations affect the loss reversal of money-losing companies. The analysis of money-losing companies of publicly traded firms indicates that these companies face a failing legitimacy and can improve their external legitimacy through charitable donations, particularly when they treat their employees better. The gained legitimacy can increase their chance of obtaining government subsidies and, thus, engender a better financial performance. Charitable donations, in interaction with a better social responsibility toward employees, are the boundary condition for companies to achieve loss recovery, and government subsidies play an intermediary role between charitable donations and loss recovery. This paper deepens the theoretical understanding of the relationship between charitable donations, government subsidies, and loss reversal of companies, providing practical implications and policy recommendations for money-losing companies to achieve profitability.

This paper intends to explore the effect of family supportive supervisor behavior (FSSB) on employee innovation. Based on the conservation of resources theory and the social cognitive theory, it proposes the mediating role of general self-efficacy and the moderating role of gender (including employees’ gender and supervisors’ gender). The results of a three-wave survey on married employees with children (Study 1, n=222) show that FSSB has a positive impact on employee general self-efficacy. General self-efficacy has a positive impact on employee innovative behavior, further, mediates the relationship between FSSB and employee innovative behavior. These direct and indirect relationships are moderated by employees’ gender, such that they are significant for female employees. These findings are replicated by a supervisor-subordinate matched survey study (Study 2, employee n=158, and supervisor n=32). Moreover, supervisors’ gender moderates the relationship between FSSB and employee general self-efficacy, such that this direct relationship is stronger for male supervisors. This paper provides a nuanced view on the linkage between FSSB and employee innovative behavior, and, in the meanwhile, offers some insight into innovation management.

This paper explores how brand positioning strategies work together with plot design in brand narrative to influence consumers’ brand attitudes. Specifically, this paper studies the interactive effect between brand positioning strategies and narrative plot design on consumers’ brand attitudes in revenge-themed brand stories. A qualitative study identifies two brand revenge narrative design elements: brand role (revenge tool versus revenge purpose) and revenge focus (revenge for oneself versus revenge for others). Then, two experiments are conducted. It is found that a top-dog brand designed as a revenge tool will improve consumers’ brand attitude, while an underdog brand designed as the revenge purpose will improve consumers’ attitude. Revenges for oneself will improve consumers’ attitude for top-dog brands, while revenges for others will improve consumers’ attitude for underdog brands. 

In order to explore the dynamic evolution process of the formation mechanism of international reputation of high-speed railway (HSR) enterprises, a method combining the structural equation model and fuzzy cognitive map was used to conduct simulation analysis. The results of prediction analysis show that macro factors, enterprise capability, and perception of capability are positively correlated with international reputation, and the order of correlation with international reputation is macro factors > enterprise capability > perception of capability. The results of diagnostic analysis show that macro factors are the most fundamental cause of international reputation. The results of hybrid analysis prove that the comprehensive intervention measures with macro factors as the core have a better effect on the improvement of international reputation. Based on the results, recommendations are proposed to improve the international reputation for HSR enterprises. This combined method simulates the dynamic interaction among these factors and performs the simulation analysis under different scenarios which reveals the dynamic evolution process of the formation mechanism. The results are helpful to expand the knowledge system of international reputation formation mechanism and provide practical reference for HSR enterprises to adopt targeted strategies to improve the international reputation.