Greening the digital revolution: assessing the impact of digital transformation on green total factor productivity in Chinese enterprises.

The green digital revolution has changed the production mode of enterprises. This article explores the green value of digital transformation. The study calculates the digital transformation index and green total factor productivity (EGTFP) index of Chinese enterprises from 2012 to 2021 and uses a panel data model and intermediary effect to conduct empirical tests. The results show that digital transformation has a positive impact of 0.371 units on the EGTFP. This positive effect is proven to be stable after distinguishing between substantive and tactical digital transformation, where the effect of substantive digital transformation increases over time. At the same time, enterprise property rights and location affect the role of digital transformation; moreover, digital transformation performs better when grouping the nonstate-owned enterprises and the eastern region. In addition, energy efficiency, green technology innovation, and environmental responsibility are important intermediaries, as digital transformation can affect EGTFP by improving energy efficiency, promoting green technology innovation, and strengthening environmental responsibility. These research conclusions help evaluate the economic and environmental effects of digital transformation and provide empirical evidence for the high-quality development of enterprises.

Identification positively affects the creativity of family business: The mediating role of family business support.

With the arbitrariness of family business decision-making and the complexity of interests become increasingly prominent, the transformation and innovation of family business are imminent. Under the above background, via analysis of data from 259 valid questionnaires from more than ten family businesses in China as a sample and with the help of the SPSS and AMOS, this study explored the impacts of identification on creativity of the family business as well as the mediating role of family business support by constructing a mediating model. The results show that the employee's identification has a positive impact on the creativity of the family business. Besides, identification has a positive impact on family business support and family business support has a partial mediating role between identification and family business creativity. Especially, the emotional support does not have a mediating role, whereas the instrumental support has a complete mediating role between identification and family business creativity.

Large-Scale Customized Production Scheduling of Multiagent-Based Medical 3D Printing.

Three-dimensional (3D) printing, also known as additive manufacturing, has unique advantages over traditional manufacturing technologies; thus, it has attracted widespread attention in the medical field. Especially in the context of the frequent occurrence of major public health events, where the medical industry's demand for large-scale and customized production is increasing, traditional 3D printing production scheduling methods take a long time to handle large-scale customized medical 3D printing (M-3DP) production and have weak intelligent collaboration ability in the face of job-to-device matching under multimaterial printing. Given the problem caused by M-3DP large-scale customized production scheduling, an intelligent collaborative scheduling multiagent-based method is proposed in this study. First, a multiagent-based optimization model is established. On this basis, an improved genetic algorithm embedded with the product mix strategy and the intelligent matching mechanism is designed to optimize the completion time and load balance between devices. Finally, the effectiveness of the proposed method is evaluated using numerical simulation. The simulation results indicated that compared with the simple genetic algorithm, particle swarm optimization, and snake optimizer, the improved genetic algorithm could better reduce the M-3DP mass customization production scheduling time, optimize the load balance between devices, and promote the "intelligent manufacturing" process of M-3DP mass customization.

Patients' Self-Disclosure Positively Influences the Establishment of Patients' Trust in Physicians: An Empirical Study of Computer-Mediated Communication in an Online Health Community.

With the development of telemedicine and e-health, usage of online health communities has grown, with such communities now representing convenient sources of information for patients who have geographical and temporal constraints regarding visiting physical health-care institutions. Many previous studies have examined patient-provider communication and health-care service delivery in online health communities; however, there is a dearth of research exploring the relationship between patients' level of self-disclosure and the establishment of patients' trust in physicians. Consequently, this study aims to explore how patients' self-disclosure affects the establishment of patients' trust in physicians. "Good Doctor," which is a China-based online health community, was used as a data source, and a computer program was developed to download data for patient-physician communication on this community. Then, data for communications between 1,537 physicians and 63,141 patients were obtained. Ultimately, an empirical model was built to test our hypotheses. The results showed that patients' self-disclosure positively influences their establishment of trust in physicians. Further, physicians' provision of social support to patients showed a complete mediating effect on the relationship between patients' self-disclosure and patients' establishment of trust in physicians. Finally, evidence of "hope-for-help" motivation in patients' messages weakened the effect of patients' self-disclosure when physicians' social support was text-based, but strengthened it when physicians' social support was voice-based.

The Positive Effects of Unneeded Consumption Behaviour on Consumers during the COVID-19 Pandemic.

The COVID-19 pandemic has become an important global contagion that requires workers to implement necessary behaviours to cope. Based on the conservation of resources theory, the present studies explore the effects of unneeded consumption behaviour on consumers' recovery level and work engagement and the moderated mediating process of such relationships. Using a purchasing experiment, study 1 examined the positive effect of unneeded consumption behaviour on recovery among 100 MBA students. Using the experience sampling method, the data in study 2 were collected from 115 consumers (employees) using ten iterations of 2-day continual questionnaires (Sunday and the following Monday) during the COVID-19 pandemic. The results from multilevel structural equation modelling indicate that unneeded consumption behaviour positively impacts work engagement in a moderated mediating mode. Consumer indulgence positively moderates the mediating effect of recovery level on the relationship between indulgent consumption behaviour and work engagement, while perceived consumer effectiveness negatively moderates the mediating effect of recovery level. This paper also identifies the value of transformation from consumption to work during the COVID-19 pandemic.

Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies.

Significant public health emergencies greatly impact the global supply chain system of production and cause severe shortages in personal protective and medical emergency supplies. Thus, rapid manufacturing, scattered distribution, high design degrees of freedom, and the advantages of the low threshold of 3D printing can play important roles in the production of emergency supplies. In order to better realize the efficient distribution of 3D printing emergency supplies, this paper studies the relationship between supply and demand of 3D printing equipment and emergency supplies produced by 3D printing technology after public health emergencies. First, we fully consider the heterogeneity of user orders, 3D printing equipment resources, and the characteristics of diverse production objectives in the context of the emergent public health environment. The multi-objective optimization model for the production of 3D printing emergency supplies, which was evaluated by multiple manufacturers and in multiple disaster sites, can maximize time and cost benefits of the 3D printing of emergency supplies. Then, an improved non-dominated sorting genetic algorithm (NSGA-II) to solve the multi-objective optimization model is developed and compared with the traditional NSGA-II algorithm analysis. It contains more than one solution in the Pareto optimal solution set. Finally, the effectiveness of 3D printing is verified by numerical simulation, and it is found that it can solve the matching problem of supply and demand of 3D printing emergency supplies in public health emergencies.

Multi-energy conversion based on game theory in the industrial interconnection.

The multi-energy conversion system (MCS) plays an important role in improving the utilization of energy resources and realizing the energy transition. With the application of the new generation of information technologies, the new MCS can realize real-time information interaction, multi-energy collaboration, and real-time demand response, in which energy suppliers can intelligently motivate consumers' energy use behavior. In this paper, an MCS coupled with a cloud platform is proposed to address information explosion and data security issues. Due to the development of Internet technology, the increasing energy data, and the serious energy coupling, it is difficult for traditional optimization methods to deal with the interaction between participants of the MCS. Therefore, the non-cooperative game is used to formulate the interactions between participants with the aim of maximizing the energy suppliers' profit and minimizing the customers' cost. It is proved that the game model is an ordinary game with one Nash equilibrium. The simulation was performed with a gradient projection algorithm and the results show that the proposed MCS improves energy utilization efficiency through energy conversion while ensuring consumer satisfaction, and benefits both the customers and suppliers by reducing the energy consumption cost and the peak load demand, which effectively improve the supply quality and enrich the energy consumption patterns.

Applying advanced technologies to improve clinical trials: a systematic mapping study.

The increasing demand for new therapies and other clinical interventions has made researchers conduct many clinical trials. The high level of evidence generated by clinical trials makes them the main approach to evaluating new clinical interventions. The increasing amounts of data to be considered in the planning and conducting of clinical trials has led to higher costs and increased timelines of clinical trials, with low productivity. Advanced technologies including artificial intelligence, machine learning, deep learning, and the internet of things offer an opportunity to improve the efficiency and productivity of clinical trials at various stages. Although researchers have done some tangible work regarding the application of advanced technologies in clinical trials, the studies are yet to be mapped to give a general picture of the current state of research. This systematic mapping study was conducted to identify and analyze studies published on the role of advanced technologies in clinical trials. A search restricted to the period between 2010 and 2020 yielded a total of 443 articles. The analysis revealed a trend of increasing research interests in the area over the years. Recruitment and eligibility aspects were the main focus of the studies. The main research types were validation and evaluation studies. Most studies contributed methods and theories, hence there exists a gap for architecture, process, and metric contributions. In the future, more empirical studies are expected given the increasing interest to implement the AI, ML, DL, and IoT in clinical trials.

The Influence of Individual and Team Mindfulness on Work Engagement.

Mindfulness metacognitive practice that can be performed in the workplace. Drawing on the theory of conservation of resources, we test a moderated mediating model of how and when employee mindfulness has a positive effect on work engagement. Via analysis of data from 311 employees from 83 teams at different times, this study investigates the relationship between employee mindfulness and work engagement as well as the moderating effect of team mindfulness and the mediating effect of recovery level. The results from this multi-wave field study show that the mindfulness of the individual employee has a positive influence on work engagement and that recovery level plays a mediating role. Team mindfulness positively moderates the relationship between individual mindfulness and work engagement. This conclusion may bridge the relationship between mindfulness and work engagement theory.