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This paper aims to explore the promotion decisions of heterogeneous sellers on a decentralized platform under competitive conditions and analyze how seller behaviors impact platform profit, seller revenue, buyer surplus and social welfare.

This paper considers a Cournot model consisting of a platform charging a commission rate and two sellers with different conversion rates and browsing costs. Promotion efforts by sellers can increase traffic, but they also incur promotion costs for sellers. The sellers decide on promotion effort by weighing these two effects. The authors also explore the equilibrium when the platform charges a fixed usage fee.

The seller’s profit improves as its conversion rate increases and worsens as browsing costs increase. Also, increasing the commission rate charged by the platform makes the seller invest less in promotional efforts. Therefore, the platform must consider this trade-off to determine an optimal rate. The analysis shows that the seller with a high conversion rate and high browsing cost plays a greater role in generating more overall revenue. When the market favors such a seller, the platform tends to charge less in order not to impair its profitability.

This paper incorporates conversion rate, buyer’s browsing cost, unit promotion cost and the fee charged by the platform into the model to study sellers’ promotion decisions on decentralized platforms.

Binary classification on imbalanced data is a challenge; due to the imbalance of the classes, the minority class is easily masked by the majority class. However, most existing classifiers are better at identifying the majority class, thereby ignoring the minority class, which leads to classifier degradation. To address this, this paper proposes a twin-support vector machines for binary classification on imbalanced data.

In the proposed method, the authors construct two support vector machines to focus on majority classes and minority classes, respectively. In order to promote the learning ability of the two support vector machines, a new kernel is derived for them.

(1) A novel twin-support vector machine is proposed for binary classification on imbalanced data, and new kernels are derived. (2) For imbalanced data, the complexity of data distribution has negative effects on classification results; however, advanced classification results can be gained and desired boundaries are learned by using optimizing kernels. (3) Classifiers based on twin architectures have more advantages than those based on single architecture for binary classification on imbalanced data.

For imbalanced data, the complexity of data distribution has negative effects on classification results; however, advanced classification results can be gained and desired boundaries are learned through using optimizing kernels.

In the era of the service economy, the personalized needs of customers are increasing rapidly. It often occurs that front-line employees bend organizational rules to help customers. The study sought to explore the influence mechanism of servant leadership on specific dimensions of customer-oriented deviance from the manager’s perspective, examine the mediating role of psychological security, and the moderating role of error management climate in the process.

We conducted an online survey study in China from April 10 to 29, 2023. We use online survey questionnaire technique and random sampling method for data collection. The authors collected 385 questionnaires from China and tested the model by SPSS 26.0 and AMOS 24.0.

The results show that servant leadership significantly promotes employees' deviant customer-oriented behaviors, psychological security plays a mediating role between servant leadership and deviant customer-oriented behaviors, and error management climate has a positive moderating effect between servant leadership and deviant customer-oriented behaviors.

This study explores the influence mechanism of servant leadership on deviant customer-oriented behaviors. The results of this study not only enrich the theoretical research on the formation mechanism of deviant customer-oriented behaviors but also provide a reference for leaders to correctly view and effectively manage employees' deviant customer-oriented behaviors.

Team social capital (TSC) has been attracting increasing research attention aiming to explore team effectiveness through within- and cross-team resource conduits. This study bridges two disconnected theories – TSC and evolutionary theory – to examine gaming clans and analyzes mechanisms of the clans' TSC building from an evolutionary perspective.

This research draws longitudinal data from a sample of gaming teams (N = 1,267) from anonymized player data from the game World of Tanks spanning 32 months. The authors explored teams' evolutionary patterns using hidden Markov models and applied longitudinal multilevel modeling to test hypotheses.

The results showed that teams of different sizes and levels of evolutionary fitness vary in team closure and bridging social capital. The authors also found that larger teams are more effective than smaller ones. The positive association between team-bridging social capital and effectiveness is more substantial for smaller teams.

This research advances the theoretical development of TSC by including the constructs of teams' evolutionary status when analyzing strategic social capital building. Adding to existing literature studying the outcome of TSC, this research also found a moderating effect of team size between TSC and effectiveness. Finally, this study also contributes to a longitudinal view of TSC and found significant evolutionary patterns of teams' membership, TSC, and effectiveness.

This study aims to comprehensively investigate the relationship between government subsidies and innovation performance in Chinese enterprises listed on the SSE STAR Market.

An unbalanced sample, covering 285 observations in 215 enterprises listed on the SSE STAR Market from 2019 to 2020, was used to explore the relationships between government subsidies, R&D investment, CEO shareholding and innovation performance. Counterfactual analysis is added for robustness testing.

Empirical evidence confirms that government subsidies have an inverted U-shaped relationship with R&D investment and innovation performance. Meanwhile, R&D investment is a mediating variable between government subsidies and innovation performance. Moreover, CEO shareholding plays a moderating role between government subsidies and R&D investment. The higher the CEO ownership, the steeper the inverted U-shaped relationship.

The government should introduce a dynamic mechanism to reasonably control subsidy amounts and strengthen the supervision of subsidy use. Enterprise managers should be aware of how incentives affect the firm’s innovation and implement a coordinated development of government subsidy policies and internal enterprise governance.

This study adds new empirical evidence for the relationship between government subsidies and enterprise innovation performance. The risk incentive provided by stock options is an important micro mechanism to compensate for the lack of government subsidies. The study identifies ways to promote firm innovation based on the synergistic effect of internal and external mechanisms.

In today's complex and rapidly changing business environment, cross-boundary growth is increasingly critical to the survival or even success of organizations. The purpose of this study is to examine the forming mechanism of firm’s cross-boundary growth by integrating the two important antecedent factors of performance pressure and managerial discretion into a united framework and theoretically analyze the direct role of performance pressure on firm’s cross-boundary growth as well as reveal the moderating role of managerial discretion. Also, the authors select listed manufacturing companies in China as samples to empirically test the research hypotheses.

The authors design a multiple regression model to perform empirical analysis by using a panel of 4,002 year-observations in 1,334 listed manufacturing companies between 2013 and 2016. The sample data sources mainly come from the Wind Database, which is mainland China's leading financial database and software services provider. The hypotheses proposed are tested by adopting a panel data set of the listed manufacturing companies of China.

Empirical results show that performance pressure has a positive effect on the cross-industry growth and cross-domestic regional growth but a negative effect on the cross-international regional growth, and managerial discretion has a different moderating effect. Specifically, capital intensity strengthens the positive effect of performance pressure on cross-industry growth but weakens the negative effect of performance pressure on cross-international regional growth. State ownership enhances the positive effect of performance pressure on cross-domestic regional growth but decreases the negative effect of performance pressure on cross-international regional growth. CEO duality increases the negative impact of performance pressure on cross-international regional growth.

This study provides several implications for top executives, including how to dialectically consider the double-edged effect of performance pressure on cross-boundary growth of firms, create an appropriate environments of managerial discretion and design the types of cross-boundary growth strategies that top executives can follow in the volatility, uncertainty, complexity and ambiguity era.

Although the relevant literature highlights the importance of performance pressure, it has not been related to the cross-boundary growth of firms. This paper makes an incremental contribution to the literature on the forming mechanisms of firm’s cross-boundary growth by providing an important perspective of performance pressure to firm growth determinants and taking into account the moderating role of managerial discretion.

The present paper constructed a new framework for government data governance based on the concept of a data middle platform to elicit the detailed requirements and functionalities of a government data governance framework.

Following a three-cycle activity, the design science research (DSR) paradigm was used to develop design propositions. The design propositions are obtained based on a systematic literature review of government data governance and data governance frameworks. Cases and experts further assessed the effectiveness of the implementation of the artifacts.

The study developed an effective framework for government data governance that supported the digital service needs of the government. The results demonstrated the advantages of the framework in adapting to organizational operations and data, realized the value of data assets, improved data auditing and oversight and facilitated communication. From the collection of data to the output of government services, the framework adapted to the new characteristics of digital government.

Knowledge of the “data middle platforms” generated in this study provides new knowledge to the design of government data governance frameworks and helps translate design propositions into concrete capabilities. By reviewing earlier literature, the article identified the core needs and challenges of government data governance to help practitioners approach government data governance in a structured manner.

The purpose of this paper is to investigate the interaction effect between customer satisfaction and monetary incentives on online reviews and test the moderating effect of personal characteristics, filling the research gap in online review behavior from the senders.

Using a project role-playing technique that is widely applied in the marketing field, the authors conducted two experimental studies in a laboratory setting with student subjects and collected 390 and 362 acceptable samples for analysis in Studies 1 and 2, respectively.

This research confirms the positive effects of satisfaction and incentives on review scores and tests the interaction effect between satisfaction and incentives on review scores with the moderating effects of moral judgment and sensitivity of promotion. Incentives could strengthen customers’ review scores except under small incentives situation where dissatisfied customers decrease scores instead. Additionally, the moderating effects of moral judgment and sensitivity of promotion are more significant in the case of dissatisfaction.

As this study focuses exclusively on a single service context and uses student samples, limitations persist regarding the generalizability of the results.

The research provides new insights for marketers on designing effective incentive programs, as well as how to better balance costs and benefits in promotion strategies.

This is one of the first studies to explore the interaction effect between satisfaction and incentives on online reviews considering the moderating effects of moral judgment and sensitivity of promotion. As a result, a new model is forwarded.

The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.

The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.

This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.

By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

The purpose of this paper is to investigate how, in China, postings on social media site Weibo reflect as well as accelerate the reshaping of traditional values. As Chinese social media extend their reach outside China, the displays of visible desire, hedonism and materialism could influence global consumption ethos.

Using interpretive content analysis, over 250 Weibo postings of 8 selected Weibo users, from the network of one of the authors, were identified, coded and interpreted. The users were selected based on their frequency, variety and expressiveness of postings.

Weibo is playing a critical role in transforming Chinese consumer values. Via Weibo, personal consumption experiences are available for public gaze. Consequently, desire for powerfully signified objects and experiences is more visible; “enjoy now” is turning out to be an appreciated life attitude, and materialism and hedonism are growing irresistibly. As a result, the traditional Chinese consumer values – suppressing desire, delaying gratification and thriftiness – are losing ground in Chinese society. Also, as Weibo makes the influence of the elite as well as electronic word-of-mouth very powerful, the values of the elite and grassroots groups are actually converging instead of being separated by substantial chasms that have existed historically.

Sina Weibo had a US initial public offering (IPO) of its stock in April, 2014, and many other China-based Internet firms were getting set for US IPOs. This paper provides unique insights for Chinese social media companies’ potential global impact. Future social media contexts would be shaped by collision as well as convergence of Asia-centric and USA-centric platforms. This paper lays the groundwork for studying such interactions.

In-depth interpretations of Weibo postings contribute to our understanding of how social media impact Chinese society now and would potentially affect global societies later. This is a pioneering study on the massive influences of social media on the macro-level consumer behavior.