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This study aims to disclose how the nature of corporate ownership, stock efficiency and wage level affect the optimal proportion of employee stock.

This paper studies three duopoly markets: two private enterprises, two state-owned enterprises (SOEs) and a private enterprise and an SOE. The competitions between the two parties are taken as a two-stage dynamic sequential game and studied through back-induction.

The results reveal that the enterprise ownership has a directly bearing on the optimal proportion of employee stock and determines whether to implement the employee stock ownership plan (ESOP) and the specific level of the plan. The optimal proportion of employee stock is positively correlated with its contribution to enterprise efficiency. There are many influencing factors on the effect of wage level on the optimal proportion of employee stock, namely, the ownership nature of ESOP implementer and efficiency difference of different nature stocks.

The results of this study provide policy recommendations for companies preparing to implement ESOP.

The research findings provide policy implications for enterprises to prepare a suitable ESOP and the reform of national equities, especially the mixed-ownership reform in China.

The new campus of Tianjin University was designed, built and now operates following a green and sustainable concept. The campus’ eco-friendly water environment was formed by establishing a water recycling system. The campus is divided into three drainage sections based on the masterplan. Each drainage section adopts different methods of collecting, utilizing and discharging water according to specific conditions, aimed at achieving both high drainage capability and the efficient utilisation of rainwater. The campus was designed so runoff pollution is reduced through the utilisation of low-impact development methods, ensuring the quality of the recharge water. Through studying the fundamentals of treatment measures and models for simulating water quality, water circulation, constructed wetlands and pollution control of rain runoff, parameters for efficient water recycling could be mathematically forecast, ensuring that stakeholders can be continuously engaged in improving and preserving the water quality of landscaped water on campus. The overall system integrates a variety of measures being implemented into one cohesive entity, which contributes to establishing the sustainable and healthy water cycling system of the green campus.

The purpose of this paper is to build a symbiotic evolution model to analyze the symbiotic modes and dynamic equilibrium of mobile internet platform innovation ecosystem (MIPIE) in order to explore its evolutionary path.

From a symbiosis theory perspective, the authors studied the dynamic evolution stages and symbiotic mode of MIPIE. By adopting logistic model, the symbiotic evolution model of MIPIE is established. After calculating the steady conditions and equilibrium point of this model, numerical simulation was done with MATLAB software to illustrate the impact of symbiotic parameters on evolution path in this ecosystem.

The symbiotic evolution mode of MIPIE experienced parasitism, commensalism to asymmetric mutualism, and symmetry mutualism or independence. In given conditions, the dynamic evolution of MIPIE eventually tends to a steady equilibrium point. The evolutionary consequence of innovative subjects is not only determined by the natural growth rate, but symbiotic modes can also affect the evolutionary path. Different symbiotic modes result in different evolutionary paths.

Improved understanding of symbiosis in MIPIE could help policy makers to promote value co-creation and dynamic interests balance while facilitating the cooperation of others for successful platform ecosystem management.

The logistic model introduced here bridge theory and practice while establishing a stronger link between symbiosis theory and platform ecosystem management.

China's controversial one-child policy has been blamed for creating an ageing population, a generation of employees without siblings and a 4-2-1 family structure that places eldercare responsibility, primarily on women. Current understanding of how this affects contemporary employees' work–life interface is lacking. This study examined the moderating roles of family structure and gender in the relationships between work–life conflict (WLC), job satisfaction and career aspiration for university academics.

Online and self-administered surveys were used to collect data, which involved 420 academic staff in three Chinese research universities.

Our results revealed that WLC is positively related to career aspiration, and this relationship is stronger for academics with siblings and, within the only-children group, significantly stronger for women than for men. WLC is also negatively related to job satisfaction, and this relationship is stronger for only-children academics.

Results were limited by a cross-sectional sample of modest size. Nevertheless, this study contributes to the understanding of gender roles and changing family structure in the work–life interface of Chinese academics.

Our findings have implications for both universities seeking to improve staff well-being and for wider society. A number of support mechanisms are proposed to enhance the ability of only children, especially women, to operate as effective members of the labour market.

Our results showed that only-children academics face a unique set of difficulties across career and family domains, which have been previously neglected in literature.

The purpose of this paper is to build a System Dynamics model to reveal the structure and dynamics of knowledge coupling affecting firms' innovation results in the digital context.

Drawing on the recombined view of innovation, this paper divides knowledge coupling into two dimensions: component knowledge coupling and architectural knowledge coupling. Then, the authors build a system dynamics model to identify the interaction of knowledge coupling factors and use the professional Vensim PLE to conduct simulation analysis to capture the dynamic interaction of motivation factors in knowledge coupling system.

The results show that both technology resources and digital dynamic capability play positive effects in the mechanism of knowledge coupling influencing firms' innovation results, while organizational inertia negatively affects the process of knowledge coupling to achieve innovation outcomes.

This study develops a holistic system dynamics model to reveal and elaborate on the complex dynamic mechanism of knowledge coupling impacting firms' innovation results in the context of digitization and provides a theoretical reference for companies to effectively adopt digital technology to carry out knowledge coupling strategy.

The purpose of this paper is to examine the relationship between open innovation (OI) and innovative performance, and to explore the moderating effect of knowledge structure, including component knowledge and architectural knowledge, on this particular relationship.

The proposed model was tested with regression analysis of data collected through a questionnaire survey of 231 employees of Chinese manufacturing firms.

The findings indicate that inbound OI is positively related to innovative performance and that outbound OI has an inverted U-shaped effect on innovative performance. By presenting empirical evidence of the moderating effects of component and architectural knowledge, our analysis of results demonstrates that the strong alignment between knowledge structure and OI results in superior innovative performance.

This study addresses the controversial issues brought up by previous studies with findings of an inverted U-shaped effect of outbound OI on innovative performance. By exploring the moderating effect of knowledge structure, the authors provide insights into how internal contextual factors in relation to organizational knowledge can affect the efficacy of the inbound and outbound OI on innovative performance.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

This study aims to provide a comprehensive overview of the current state of the art in powder bed fusion (PBF) techniques for additive manufacturing of multiple materials. It reviews the emerging technologies in PBF multimaterial printing and summarizes the latest simulation approaches for modeling them. The topic of “multimaterial PBF techniques” is still very new, undeveloped, and of interest to academia and industry on many levels.

This is a review paper. The study approach was to carefully search for and investigate notable works and peer-reviewed publications concerning multimaterial three-dimensional printing using PBF techniques. The current methodologies, as well as their advantages and disadvantages, are cross-compared through a systematic review.

The results show that the development of multimaterial PBF techniques is still in its infancy as many fundamental “research” questions have yet to be addressed before production. Experimentation has many limitations and is costly; therefore, modeling and simulation can be very helpful and is, of course, possible; however, it is heavily dependent on the material data and computational power, so it needs further development in future studies.

This work investigates the multimaterial PBF techniques and discusses the novel printing methods with practical examples. Our literature survey revealed that the number of accounts on the predictive modeling of stresses and optimizing laser scan strategies in multimaterial PBF is low with a (very) limited range of applications. To facilitate future developments in this direction, the key information of the simulation efforts and the state-of-the-art computational models of multimaterial PBF are provided.

This paper aims to present a reverse engineering (RE) approach for three-dimensional (3D) model reconstruction and fast prototyping (FP) of broken chess pieces.

A case study involving a broken chess piece was selected to demonstrate the effectiveness of the proposed unconventional RE approach. Initially, a laser 3D scanner was used to acquire a (non-uniform rational B-spline) surface model of the object, which was then processed to develop a parametric computer aided design (CAD) model combined with geometric design and tolerancing (GD&T) technique for evaluation and then for FP of the part using a computer numerical controlled (CNC) machine.

The effectiveness of the proposed approach for reconstruction and FP of rotational parts was ascertained through a sample part. The study demonstrates non-contact data acquisition technologies such as 3D laser scanners together with RE systems can support to capture the entire part geometry that was broken/worn and developed quickly through the application of computer aided manufacturing principles and a CNC machine. The results indicate that design communication, customer involvement and FP can be efficiently accomplished by means of an integrated RE workflow combined with rapid product development tools and techniques.

This research established a RE approach for the acquisition of broken/worn part data and the development of parametric CAD models. Then, the developed 3D CAD model was inspected for accuracy by means of the GD&T approach and rapidly developed using a CNC machine. Further, the proposed RE led FP approach can provide solutions to similar industrial situations wherein agility in the product design and development process is necessary to produce physical samples and functional replacement parts for aging systems in a short turnaround time.

The operation safety of the high-speed railway has been widely concerned. Due to the joint influence of the environment, equipment, personnel and other factors, accidents are inevitable in the operation process. However, few studies focused on identifying contributing factors affecting the severity of high-speed railway accidents because of the difficulty in obtaining field data. This study aims to investigate the impact factors affecting the severity of the general high-speed railway.

A total of 14 potential factors were examined from 475 data. The severity level is categorized into four levels by delay time and the number of subsequent trains that are affected by the accident. The partial proportional odds model was constructed to relax the constraint of the parallel line assumption.

The results show that 10 factors are found to significantly affect accident severity. Moreover, the factors including automation train protection (ATP) system fault, platform screen door and train door fault, traction converter fault and railway clearance intrusion by objects have an effect on reducing the severity level. On the contrary, the accidents caused by objects hanging on the catenary, pantograph fault, passenger misconducting or sudden illness, personnel intrusion of railway clearance, driving on heavy rain or snow and train collision against objects tend to be more severe.

The research results are very useful for mitigating the consequences of high-speed rail accidents.