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3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.

This study aims to explore the impact of ethical leadership on employee creative deviance, with job autonomy as a mediator and creative self-efficacy as a moderator between job autonomy and creative deviance.

A survey was developed based on construct measures from the literature. A total of 316 responses were received from employees of information and communication technology companies located in China's Pearl River Delta.

Both ethical leadership and job autonomy have a positive impact on employee creative deviance; job autonomy plays a mediating role between ethical leadership and creative deviance; creative self-efficacy does not have a significant moderating effect on the job autonomy-creative deviance relationship.

Future studies could explore the potential moderating role of both job autonomy and creative-self efficacy in the link between ethical leadership and creative deviance.

This study recommends that organizations should adopt and promote an ethical leadership approach to manage creative deviance at work. Organizations could explore alternative methods of task completion to support the job autonomy for the employees to mitigate the dilemmas associated with creative deviance.

This is one of few studies that examine the impact of ethical leadership on employee's creative deviance, despite the fact that the influence of ethical leadership on the followers has been extensively examined.

Global economic growth provides new opportunities for the development of clothing enterprises, but at the same time, the rapid growth of clothing customization demand and the gradual increase of clothing costs also pose new challenges for the development of clothing enterprises. In this context, 3D printing technology is injecting new vitality and providing a new development direction for the vigorous development of clothing enterprises. However, with the application of 3D printing technology, more and more clothing enterprises are facing the problem of business model innovation. In view of the lack of relevant research, it is necessary to carry out exploratory research on this issue.

The business model canvas method was adopted to design business model for clothing enterprises using 3D printing. The simulation model of the designed business model was constructed by a system dynamics method, and the application of the designed business model was analysed by a scenario simulation.

Mass selective customization-centralized manufacturing (MSC-CM) business model was constructed for clothing enterprises using 3D printing, and a static display was carried out using the BMC method. A dynamic simulation model of the MSC-CM business model was constructed. The future scenario of clothing enterprises using 3D printing was developed, and a simulated enterprise was analysed. The results show that the MSC-CM business model has a good application value. The simulation model of the MSC-CM business model performs the function of a business strategy experiment platform and also has a good practical application value.

The MSC-CM business model is only a typical business model for clothing enterprises using 3D printing. It is necessary to further develop other business models, and some elements of the MSC-CM business model need to be further improved. In addition, the MSC-CM business model simulation uses a general model, which is not suitable for all clothing enterprises using 3D printing. When the model is applied, the relevant enterprises can further adjust and optimize it, thereby improving the validity of the simulation model.

To the best of the authors’ knowledge, this is the first paper on the MSC-CM business model for garment enterprises using 3D printing. Secondly, it is the first time that the business model of clothing enterprises using 3D printing has been simulated. In particular, the proposed business model simulation provides the possibility for testing the business strategy of clothing enterprises using 3D printing. In addition, a positive attempt has been made in the collaborative research of using both a static display business model and a dynamic simulation business model.

This study aims to investigate the influence of soy protein isolate hydrolysates (SPIH) obtained using 4 h hydrolysis under 200 MPa on proximate composition, cooking loss, textural properties, color, water distribution, microstructure, thiobarbituric acid reactive substance (TBARS) value and carbonyl and sulfhydryl contents of emulsion sausages.

Sausages with SPIHs at four concentrations (0, 1.0, 2.0 and 3.0%) were prepared, and the sausage with 0.01% butylated hydroxyanisole (BHA) was used as a positive control. Some sausages were selected for the analyses of quality characteristics and microcosmic properties. Other sausages were stored under 4 °C for 0, 7, 14, 21 and 28 days to investigate the oxidative stability.

The addition of SPIHs at various levels (0–3.0%) or 0.01% BHA did not affect the proximate composition (protein, fat and ash) of emulsion sausages. The addition of 2.0% SPIH decreased cooking loss and increased moisture content, hardness, springiness, chewiness, resilience and L* value, compared to the sausages without SPIH and with 0.01% BHA (p < 0.05). Furthermore, low-field nuclear magnetic resonance results suggested that sausages with 2.0% SPIH had the shortest T2 relaxation time. In addition, 2.0% SPIH and 0.01% BHA could inhibit the oxidation of emulsion sausages when compared with the sample without SPIH (p < 0.05). Moreover, there were no differences between sausages with 2.0% SPIH and 0.01% BHA (p > 0.05).

These findings confirmed that the 2.0% SPIH obtained under 200 MPa can be used as a natural additive to improve quality properties and antioxidant potential of emulsion sausages during storage.

Since the outbreak of COVID-19, tremendous changes have taken place in the US economy – the economic growth in the whole year of 2020 was negative, and though it enjoyed a significant rebound for the first half of 2021, the growth rate began to decline rapidly by the third quarter, and inflation suddenly rises rapidly, which after came the all-time highs of the “misery index” consisted of the inflation rate and unemployment rate. All signs indicate that the US economy will likely enter a “stagflation” crisis.

This paper analyzes the institutional and social contradictions in the United States during the neoliberal era from the perspectives of domestic social structure of accumulation (SSA) and international SSA based on the SSA theory.

The current risk of stagflation in the US economy is a concentrated outbreak of the long-term accumulated contradictions in neoliberal SSA under the impact of the epidemic, which is the product of the irreconcilable contradictions inherent in the capitalist mode of production.

Based on this analysis, the paper points out that with the deepening of the crisis, the neoliberal SSA is likely to end and a new SSA will be established gradually.

The main purpose of this paper is to analyze the effect of fairness psychology on the motivation and behavior that drives managerial entrenchment. The paper also provides a theoretical basis to set up an effective incentive and restraining mechanism for corporations.

This paper conducts an experiment to investigate the effect of fairness preference on managerial entrenchment in enterprises.

The results of the experiment show that managers are very concerned about fair payoffs, i.e. the comparison of the principals’ earnings with managers’ market average levels of pay. The worse managers’ fairness preference becomes, the greater are the degrees of managerial entrenchment exhibited. In addition, a large payoff gap between managers and principals produces a higher sensitivity in high-ability managers, while a large payoff gap between managers and managers elsewhere in a market leads to a higher sensitivity in low-ability managers.

This paper provides new insights into incentives and constraints affecting the behaviors of managers at the corporate board level. Maintaining equity between managers’ payoffs, principals’ earnings and managers’ market average pay levels can restrain both the entrenchment behavior of managers caused by unfair psychology and also the increasing costs of staff switching jobs, thus producing greater profits for companies.

Compared with the high stiffness of traditional CNC machine tools, the structural stiffness of industrial robots is usually less than 1 N/µm. Chatter not only affects the quality of robotic milling but also reduces the accuracy of the milling process. The purpose of this paper is to reduce chatter in the robotic machining process.

First, the mode coupling chatter mechanism is analyzed. Then the milling force model and the principal stiffness model are established. Finally, the robot milling stability optimization method is proposed. The method considered functional redundancies, and a new robot milling stability index is proposed to improve the quality of milling operations.

The experimental results prove a significant reduction in force fluctuations and surface roughness after using the proposed robotic milling stability optimization method.

In this paper, a new robot milling stability index and a new robot milling stability optimization method are proposed. This method can significantly increase the milling stability and improve the milling quality, which can be widely used in the industry.

This paper aims to find the current situation of research data services by academic libraries and summarize some strategies for university libraries to reference. Recent years have seen an increasing number of university libraries extended their traditional roles and provided research data services.

This paper selected 87 libraries of the top 100 universities listed in the World’s Best Universities released by the USA News in October 2012 as samples and conducted a Web site investigation to check if there were any research data services provided. In addition, it made an interview with the Wuhan University Library’s Research Data Service Workgroup to understand the procedure, difficulties and experiences of their research data service. Based on the survey and interview, it analyzed the current status and difficulties of research data services in university libraries and proposed some strategies for others to reference.

Of the 87 university libraries investigated, 50 libraries have offered research data services. Most of the services can be divided into six aspects: research data introduction, data management guideline, data curation and storage service, data management training, data management reference and resource recommendation. Among these services, research data introduction is the most frequently provided (47.13 per cent), followed by data curation and storage services (43.68 per cent), data management guideline (42.53 per cent), data management reference (41.38 per cent), resource recommendation (41.38 per cent) and data management training (24.14 per cent). The difficulties met by research data service of Chinese academic libraries are also concluded.

Through Web site investigation and interview with the Wuhan University Library’s Research Data Service, this paper presented an overall picture of research data services in university libraries and identified the difficulties and experiences of research data services of the Wuhan University Library. Based on some successful examples, it put forward some strategies for university libraries to reference. This study is very useful for academic libraries to promote their research data services.

The purpose of this paper is to conduct performance evaluation of eight main scientific data sharing platforms in China and find existing problems, thus providing reference for maximizing the value of scientific data and enhancing scientific research efficiency.

First, the authors built an evaluation indicator system for the performance of scientific data sharing platforms. Next, the analytic hierarchy process was employed to set indicator weights. Then, the authors use experts grading method to give scored for each indicator and calculated the scoring results of the scientific data sharing platform performance evaluation. Finally, an analysis of the results was conducted.

The performance evaluation of eight platforms is arranged by descending order by the value of F: the Data Sharing Infrastructure of Earth System Science (76.962), the Basic Science Data Sharing Center (76.595), the National Scientific Data Sharing Platform for Population and Health (71.577), the China Earthquake Data Center (66.296), the China Meteorological Data Sharing Service System (65.159), the National Agricultural Scientific Data Sharing Center (55.068), the Chinese Forestry Science Data Center (56.894) and the National Scientific Data Sharing & Service Network on Material Environmental Corrosion (Aging) (52.528). And some existing shortcomings such as the relevant policies and regulation, standards of data description and organization, data availability and the services should be improved.

This paper is mainly discussing about the performance evaluation system covering operation management, data resource, platform function, service efficiency and influence of eight scientific data sharing centers and made comparative analysis. It reflected the reality development of scientific data sharing in China.

This paper explores the major factors influencing multinational companies’ (MNCs) propensity to change the level of resource commitments during financial crises in emerging markets. Favorable changes in the host government policies, market demand, firm strategy, and infrastructural conditions are hypothesized to influence the MNCs’ decision to increase resource commitments during a crisis. The hypotheses are tested with data collected in a survey of 82 MNCs during the recent Argentine financial crisis (late 2002). While all the above variables are considered by the respondents as generally important reasons for increasing resource commitments during a crisis, only favorable changes in government policies significantly influence MNCs’ decisions to change the level of resource commitments during the Argentine financial crisis. The research, managerial implications, and policy‐making implications are discussed.