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Previous studies on social influence and virtual product adoption have mainly taken users’ purchase behavior as a dichotomous variable (i.e. purchasing or not). Given the prevalence of competing versions (basic vs upgraded) of a virtual product in online communities, this paper investigated the differences in the effect of social influence on users’ adoption of basic and upgraded choices of a virtual product. It also examined how the effect varies with users’ social status and user-level network density.

A natural experiment was conducted in an online game community. Two competing versions (basic vs upgraded) of a virtual product were provided for in-game purchase while a random set of users selected from 897,765 players received the notification of their friends’ adoption information. A competing-risk model was used to test the hypotheses.

Social influence exerts a stronger positive effect on users’ adoption of the upgraded virtual product than of the basic virtual product. Middle-status users have the greatest (least) susceptibility to social influence in adopting the upgraded (basic) virtual product than low- and high-status users. User’s network density enhances the effect of social influence on adoption of both virtual products, even more for the upgraded one.

This research contributes to the social influence and product adoption literature by disentangling the different effects of social influence on basic and upgraded versions of a virtual product. It also identifies the boundary conditions that social influence works for each version of the virtual product.

This paper aims to understand the current development situation of scientific data management policy in China, analyze the content structure of the policy and provide a theoretical basis for the improvement and optimization of the policy system.

China's scientific data management policies were obtained through various channels such as searching government websites and policy and legal database, and 209 policies were finally identified as the sample for analysis after being screened and integrated. A three-dimensional framework was constructed based on the perspective of policy tools, combining stakeholder and lifecycle theories. And the content of policy texts was coded and quantitatively analyzed according to this framework.

China's scientific data management policies can be divided into four stages according to the time sequence: infancy, preliminary exploration, comprehensive promotion and key implementation. The policies use a combination of three types of policy tools: supply-side, environmental-side and demand-side, involving multiple stakeholders and covering all stages of the lifecycle. But policy tools and their application to stakeholders and lifecycle stages are imbalanced. The development of future scientific data management policy should strengthen the balance of policy tools, promote the participation of multiple subjects and focus on the supervision of the whole lifecycle.

This paper constructs a three-dimensional analytical framework and uses content analysis to quantitatively analyze scientific data management policy texts, extending the research perspective and research content in the field of scientific data management. The study identifies policy focuses and proposes several strategies that will help optimize the scientific data management policy.

E-commerce live streaming is a new influencer advertising method that allows influencers to interact directly with consumers on e-commerce platforms. Although evidence suggests that influencer live-streaming advertisements (ads) on social media can increase consumers’ buying impulses, little research examined how this similar but new advertising method on e-commerce platforms may influence consumers’ urge to buy impulsively. This study explores the role of influencer credibility, celebrity effect, perceived entertainment, trust and perceived usefulness on consumers’ attitudes toward influencer ads and their urge to buy impulsively.

A questionnaire containing seven constructs was developed and distributed to participants using a convenient sample and snowball sampling approach. The constructs were measured based on validated measurement items from the literature and adjusted according to this study’s focus. A total of 236 valid responses were obtained from the survey and used for data analysis. A partial least squares structural equation modeling approach was employed for parameter estimation and model testing.

The empirical results show that all constructs influenced consumers’ urge to buy impulsively via attitude toward influencer ads. The proposed research model explains 61.7% of the variance in attitude toward influencer ads and 19.4% of the urge to buy impulsively.

This is an early study investigating the relationship between influencer advertising and impulse buying. The results provide valuable insights into improving the design of influencer ads and marketing strategies.

1. I-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.

2. Consumers’ attitude towards influencer ads affects their urge to buy impulsively.

3. Influencer credibility affects consumer attitude via celebrity effect as a mediator.

4. Trust affects consumer attitude via perceived usefulness as a mediator.

5. Entertaining ads help develop favorable consumer attitude.

I-eIB model tests the mechanism of influencer ads on consumers’ buying impulse.

Consumers’ attitude towards influencer ads affects their urge to buy impulsively.

Influencer credibility affects consumer attitude via celebrity effect as a mediator.

Trust affects consumer attitude via perceived usefulness as a mediator.

Entertaining ads help develop favorable consumer attitude.

This study develops an empirical framework to address how large third-party sellers (TPSs) can apply customer acquisition strategies to improve their performance in consumers’ person-goods matching process and how the platform firm’s similar strategies moderate the effects of TPSs’ strategies.

Using data collected from the top ten TPSs from a Chinese e-commerce platform, the fixed effect model is used to validate the conceptual model and hypotheses.

The study results show that both market detection strategy and matching optimization strategy can help large TPSs improve their sales performance. Moreover, the similar market detection strategy applied by the platform firm weakens the effect of large TPSs’ customer acquisition strategies, while the similar matching optimization strategy applied by the platform firm strengthens the effect of large TPSs’ customer acquisition strategies.

This study provides firsthand evidence on the performance of large TPSs’ and the platform firm’s strategies. It demonstrates the effectiveness of large TPSs’ market detection strategy and matching optimization strategy, which can be adopted to meet consumers’ search and evaluation motivations in their person-goods matching process respectively. Moreover, it identifies the role of platform firms by showing the moderating effect of similar strategies adopted by the platform firm on the effect of large TPSs’ customer acquisition strategies.

China has recently introduced a new audit law that aims to increase the scope of audit supervision and raise the standards for preventing risks in auditing national public projects. This paper presents a systematic research study on the causes of audit risks in national public projects and discusses the process by which these causes contribute to the emergence of such risks. Furthermore, the paper investigates the core risk sources in various types of national construction project audit. This paper aims to provide theoretical support for auditors of national construction projects in risk avoidance when conducting audits.

In this study, the authors carefully selected five national public audit projects from China and performed a comprehensive analysis of 85 relevant audit documentation. The textual analysis was conducted using Nvivo12 software, and the grounded theory approach was adopted for generalization purposes.

Based on the research results, the findings suggest that there are five key causes contributing to the audit risk of national construction projects: professional competence, risk awareness, management capacity, level of attention and deliberate fraud. The most critical factor identified is management capability, with 59.93% of the data supporting this view. This conclusion was based on an analysis of state-owned enterprises, administrative organs and public institutions. Building upon this, a framework titled “the mechanism of audit risk factors with management capability as the core” was constructed.

This paper employs qualitative analysis methods to examine national construction projects in China, contributing new literature to the theoretical study of audit risk management. The article also provides practical recommendations for auditors on how to mitigate audit risks and improve the quality of audit services in national project governance.

A successful process of design concept evaluation has positive influence on subsequent processes. This study aims to consider the evaluation information at multiple stages and the interaction among evaluators and improve the credibility of evaluation results.

This paper proposes a multi-stage approach for design concept evaluation based on complex network and bounded confidence. First, a network is constructed according to the evaluation data. Depending on the consensus degree of evaluation opinions, the number of evaluation rounds is determined. Then, bounded confidence rules are applied for the modification of preference information. Last, a planning function is constructed to calculate the weight of each stage and aggregate information at multiple evaluation stages.

The results indicate that the opinions of the evaluators tend to be consistent after multiple stages of interactive adjustment, and the ordering of design concept alternatives tends to be stable with the progress of the evaluation.

Updating preferences according to the bounded confidence rules, only the opinions within the trust threshold are considered. The attribute information of the node itself is inadequately considered.

This method addresses the need for considering the evaluation information at each stage and minimizes the impact of disagreements within the evaluation group on the evaluation results.

Innovation ambidexterity is crucial for fostering growth and gaining a competitive advantage in small and medium enterprises (SMEs). Previous research indicates that achieving a balance between exploration and exploitation is a multifaceted phenomenon occurring across various levels. This paper aims to examine the influence of individual, organizational and institutional factors on the ambidextrous innovation of Chinese niche leaders using a configurational perspective.

This study uses secondary data collected from 69 Chinese niche leaders in the new equipment manufacturing industry. The authors use fuzzy-set qualitative comparative analysis to investigate how owner openness, age, digitization, the formal institutional environment and the informal institutional environment jointly influence innovation ambidexterity.

By using fuzzy set analysis, this study categorizes combinations of interdependent factors that promote innovation ambidexterity. In particular, the authors pinpoint three configurations that foster high innovation ambidexterity and two configurations that lack such high levels of innovation ambidexterity. The analysis results suggest that innovation paradoxes in SMEs are linked to a nested system comprising leadership, organizational factors and the institutional environment.

This study elucidates the mechanism of innovation ambidexterity through a configurational perspective. This research proposes and validates a framework that enables SMEs to develop ambidextrous innovation capabilities, thereby integrating organizational ambidexterity theory and shedding light on the intricately complex nature of innovation ambidexterity.

This study aims to using Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy and scanning electron microscope/energy dispersive Xray spectrometer to identify different automotive coatings for forensic purpose.

Two four-layered samples in a hit-and-run case were compared layer by layer with three different methods. FTIR spectroscopy was used to primarily identify the organic and inorganic compositions. Raman spectrum and scanning electron microscope/energy dispersive Xray spectrometer (SEM-EDS) were further used to complement the FTIR results.

Two weak and tiny peaks in one layer found between two samples by FTIR, Raman microscope and SEM-EDS verified the result of differences. The study used the three instruments in combination and found it’s effective in sensing coatings, especially in the inorganic additives.

Using these three instruments in combination is more accurate than individually in multilayered coating analysis for forensic purpose.

The three different instruments all present unique information on the composition, and provided similar and mutually verifiable results on the two samples.

With this method, scientists could identify and discriminate important coating evidences with tiny but characteristic differences.

This study aims to propose a more precise method for robust design optimization of mechanical structures with black-box problems, while also considering the efficiency of uncertainty analysis.

The method first introduces a dual adaptive chaotic flower pollination algorithm (DACFPA) to overcome the shortcomings of the original flower pollination algorithm (FPA), such as its susceptibility to poor accuracy and convergence efficiency when dealing with complex optimization problems. Furthermore, a DACFPA-Kriging model is developed by optimizing the relevant parameter of Kriging model via DACFPA. Finally, the dual Kriging model is constructed to improve the efficiency of uncertainty analysis, and a robust design optimization method based on DACFPA-Dual-Kriging is proposed.

The DACFPA outperforms the FPA, particle swarm optimization and gray wolf optimization algorithms in terms of solution accuracy, convergence speed and capacity to avoid local optimal solutions. Additionally, the DACFPA-Kriging model exhibits superior prediction accuracy and robustness contrasted with the original Kriging and FPA-Kriging. The proposed method for robust design optimization based on DACFPA-Dual-Kriging is applied to the motor hanger of the electric multiple units as an engineering case study, and the results confirm a significant reduction in the fluctuation of the maximum equivalent stress.

This study represents the initial attempt to enhance the prediction accuracy of the Kriging model using the improved FPA and to combine the dual Kriging model for uncertainty analysis, providing an idea for the robust optimization design of mechanical structure with black-box problem.

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.

This study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.

The results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.

There are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.

This analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.

The study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.