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People usually try to avoid uncertainty. Recently, however, uncertainty has become an emerging marketing tool in the hedonic product industry. In the case of blind box consumption, for example, the consumers become addicted to the uncertainty created by businesses, leading to repeat purchases and even indulgences. Previous research has, yet, to focus on the impact of uncertainty on indulgence and the role of emotions.

This paper constructs and validates a chain mediation model of uncertainty triggering indulgent consumption based on the information gap theory, positive emotion theory and uncertainty resolution theory and examines the difference between resolved and unresolved uncertainty. This study also explores differences in the impact of whether uncertainty is resolved on emotions. The uncertainty-resolved group elicited a more positive emotional response than the uncertainty-unresolved group, leading to a more indulgent consumption.

The results of three studies show that uncertainty influences indulgent consumption through curiosity and positive emotion, and that curiosity and positive emotion play separate and chain mediating roles between uncertainty and indulgent consumption, respectively. We validate our central hypothesis with questionnaires among blind box consumer groups, examining the moderating role of perceived luck and risk preferences.

The findings shed new light on firms' use of uncertainty to promote consumer purchases.

This study aims to examine the effects of vocational training programs for people with disabilities on their income.

It conducted a multinomial regression analysis of 10,469 survey responses from 31 provincial administrative areas in mainland China.

It finds the following antecedents all influence the trainees’ self-reported income, including their perception of the quality of the program, the training subject, the degree of consistency between their current job and this subject, their employment sector, their motivation and access to training resources and the geographical location of the program.

The findings are not representative of people with disabilities across mainland China because the respondents were not randomly sampled.

The findings suggest that to increase the income of people with disabilities, the training can be designed according to the needs of employers by teaching subjects relevant to the needs of the labor market, reaching out to motivated trainees and enhancing the quality of training. Training institutions, employers and governments are recommended to work together to integrate class-based learning with workplace-based learning and practices. More training resources can be devoted to the self-employed people with disabilities or those who operate in the informal sector and are in less-developed areas.

The improvement of employment opportunities and income of people with disabilities supports the safeguarding of their social economic rights and the building of an inclusive society.

Few studies have empirically explored and explained the effects of vocational training programs on people with disabilities’ income. This article fills this gap by assessing the performance of China's vocational training programs funded by the Federation of Disabled Persons at all levels.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

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.

Prior research on green innovation has shown that institutional pressure stimulates enterprises to adopt green innovation. However, an institutional perspective does not explain why firms that face the same amount of institutional pressure execute different environmental practices and innovations. To address this research gap, the authors linked institutional theory with upper echelons theory and organization performance to build a comprehensive research model.

A total of 800 questionnaires were issued. The final usable questionnaires were 195, yielding a response rate of 24.38%. AMOS 23.0 was used to analyze the data and examine the relationships between the constructs in our model.

Institutional pressures affected both green innovation adoption (GIA) and the top management team's (TMT's) response. TMT's response influenced GIA. GIA was an important factor affecting firm performance. Furthermore, TMT's response mediated the relationship between institutional pressure and GIA. Institutional pressures indirectly affected green innovation performance but did not influence economic performance through GIA. Finally, TMT's response indirectly impacted firm performance through GIA.

The authors draw on institutional theory, upper echelons theory, and a performance-oriented perspective to explore the antecedents and consequences of GIA. This study has interesting implications for leaders and managers looking to implement green innovation and leverage it for firm performance to out compete with market rivals as well as to make the changes in collaboration with many other companies including market rivals to gain success in green innovation.

Although it is acknowledged that entrepreneurial networks play a crucial role in fostering business model innovation (BMI) for start-ups, it is unclear how and when these networks affect BMI. This research developed a moderated mediation model to explore the impact of entrepreneurial networks on BMI in start-ups and examined the dual mediating effects of causation and effectuation, as well as the moderation of environmental dynamism.

The proposed framework was tested by hierarchical regression analyses and bootstrapping using samples of 248 start-ups in China.

The results showed that entrepreneurial networks significantly positively impacted start-up BMI. Causation and effectuation played dual mediating roles between entrepreneurial networks and BMI. Furthermore, the entrepreneurial networks-effectuation-BMI association was more substantial in highly dynamic environments, whereas the entrepreneurial networks-causation-BMI relationship was unaffected.

There are several theoretical contributions resulting from this research. The findings offer new insights for understanding the antecedents of start-up BMI from the network perspective. This research adds to the growing literature on resource orchestration (RO) by exploring the dual mediating influences of causation and effectuation in resource management. This investigation revealed the boundary condition between entrepreneurial networks and BMI by testing the moderating influence of environmental dynamism.

Start-ups must effectively use external resources embedded within networks to advance BMI. Start-up entrepreneurs should apply causation and effectuation to transform entrepreneurial network resources into BMI. Start-up entrepreneurs must dynamically manage resources in response to ever-changing environmental conditions. Resource acquisition and management of entrepreneurial networks can vary significantly in their influence on start-up BMI under different environmental contexts.

Unlike previous BMI research focused on internal organizational factors, this study highlighted the critical importance of entrepreneurial networks as a prerequisite for achieving start-up BMI, contributing to the literature on open innovation and resource-based view. Examining the dual mediating roles of causation and effectuation illustrated the bridging role of strategic decision-making logic in connecting resources to value creation, contributing to the developing RO literature. The moderating influence of environmental dynamism was explored, clarifying how start-up BMI benefits from entrepreneurial networks in differing situations. A framework for reconciling contradictory findings concerning the association between entrepreneurial networks and innovation is provided.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

The purpose of this study is to examine the relationship between the corporate social responsibility (CSR) performance of job-hopping executives at their former and subsequent firms.

We conduct regression analyses using a sample of firms listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2020 to examine whether CSR performance is similar from one firm to the next as executives switch jobs.

We find a positive relationship between the CSR performance of former and subsequent firms under job-hopping executives. This relationship is the strongest in the year of the job switch; it weakens in the second year and eventually disappears in the third year. In addition, we show that this relationship benefits different CSR stakeholder groups and is contingent on executive and subsequent firm attributes and job-hopping characteristics. Furthermore, we demonstrate that firms that hire a new chief executive officer from a firm with a strong track record in CSR, the new firm experiences a significant surge in CSR performance compared with firms that do not experience such a shock.

This study has implications for executive hiring decisions.

This study extends the understanding of CSR determinants through the lens of inter-organisational ties associated with job-hopping executives.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

The global economy has been affected by the COVID-19 pandemic, which has placed greater responsibility on companies to fulfill their obligations to Corporate Social Responsibility (CSR) amid the crisis. This chapter investigates the role of a Chief Executive Officer (CEO) attributes in improving a firm's CSR in the emerging economy of Jordan and how the COVID-19 pandemic modifies this relationship. Using a Jordanian sample of 655 firm-year observations during the 2014–2021 period, the research results show that older CEOs, well-educated CEOs, CEOs' remuneration, and CEOs' ownership positively correlate with CSR reporting. However, long-tenured CEOs are associated with lower CSR initiatives. The subsample analysis findings also validate the significance of CEO attributes in improving CSR practice during the COVID-19 pandemic compared to the prepandemic period. These findings are beneficial for the regulatory setters to understand better whether CEO attributes are linked to engagement in CSR-related information. This research is among the limited number of studies that have explored how CEO attributes impact CSR reporting for the stakeholder's welfare. Moreover, it uniquely concentrated on contrasting the findings before and during the COVID-19 pandemic.