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This paper aims to explore what factors influence the possibility of internal and external risk propagation in R&D networks and investigate how government intervention moderates the associations between the influencing factors and risk propagation.

The authors divided government intervention into directive and facilitative intervention and adopted an empirical research approach in this study. They collected 228 questionnaires from managers and R&D personnel participating in R&D projects in Shanghai and Jiangsu province through e-mail and in person. The data were used to carry out multiple regression analysis to test hypotheses.

The results show that the probability and consequence of risks positively affect the possibility of internal and external risk propagation; risk perception and transformation ability negatively influence the possibility of internal and external risk propagation; both directive and facilitative intervention weaken the relationship between the probability of risks and internal risk propagation when they are high than low the association between transformation ability and internal risk propagation is weaker when directive intervention is high than low, whereas facilitative intervention presents the insignificant moderation effect on the relationships between risk perception ability and internal and external risk propagation.

This study provides a distinctive theoretical perspective for risk conduction theory, government intervention theory and risk management. It also offered managers and the government a clear understanding of how to reduce or avoid risk propagation by leveraging directive and facilitative government intervention.

The purpose of this study is to enhance the comprehensive understanding of the roles of resource investments, explicit contracts and three components of guanxi (i.e. renqing, ganqing and mianzi) in asymmetric research and development (R&D) partnerships. Treating dependence asymmetry as a multidimensional construct, this study examines the moderating effects of these elements on the relationships between resources and information asymmetry and opportunism.

The study was executed by issuing questionnaires to R&D managers participating in R&D projects and collaborations in the Shanghai and Jiangsu provinces via e-mail and face to face surveys. A multiple regression analysis was used to test the hypotheses.

The empirical test generally supported the conceptual model and produced the following findings: first, resources and information asymmetry significantly and positively affect opportunism. Second, the partner’s resource investments can weaken the effect of resources and information asymmetry on the partner’s opportunism. Third, explicit contracts can reduce the impact of information asymmetry on the partner’s opportunism. Fourth, renqing and ganqing but not mianzi can weaken the influence of information asymmetry on the partner’s opportunism.

This study provides a comprehensive and clear understanding of how opportunism can be curbed by jointly considering resource investments, explicit contracts and guanxi in asymmetric R&D cooperative relationships. Moreover, dependence asymmetry and guanxi are measured as a multidimensional construct and reveal their underlying structure, which expands previous understandings of risk management in R&D collaborations.

The purpose of this study is to investigate the influence mechanisms of multi-level ecological participants on technological innovation capabilities within the focal small and mid-size enterprises' (SME) innovation ecosystem. The author examines the moderating role of the innovation ecological environment.

With the lenses of innovation ecosystem theory, technological innovation theory and ecological theory, the author constructs and empirically tests a conceptual framework for exploring the effects of the focal SME's connections with universities and research institutions, and the industrial chain and ecosphere on their independent and collaborative innovation capabilities. The innovation ecological environment is employed as a moderating variable in the proposed model. The author issued email questionnaires to managers at innovative SMEs in Shenzhen, Shanghai and Jiangsu provinces. The data were used for multiple regression analyses to test the hypotheses.

As predicted, the author found that SMEs’ cooperation with universities and research institutions positively affects independent and collaborative innovation capability. The relationships between the industrial chain, the ecosphere and independent and collaborative innovation capabilities are all inverted U-shaped. Additionally, the author demonstrates that the innovation ecological environment positively moderates relationships between the focal SME's ecological participants and these two types of technological innovation capabilities.

The results enrich research on innovation ecosystems and technological innovation capability and provide important managerial implications for Chinese SMEs to enhance their technological innovation capability by constructing and coordinating innovation ecosystems. It also allows China, as well as other developing countries, to cultivate world-class enterprises as an innovative nation.

The purpose of this paper is twofold: first, to explore how the number of structural holes influences the possibility of risk propagation in R&D networks; and second, to investigate how the specific context of tie strength and common cognition moderate the association between structural holes and risk propagation.

This study focuses on how structural holes influence risk propagation under the specific context of relationship and cognitive dimension by drawing on social capital theory. Risk sharing and risk perception as mediating variables are employed in the proposed conceptual model. The authors issued questionnaires to managers and R&D personnel participating in R&D projects and collaboration in Shanghai and Jiangsu province through e-mail and face to face. The data were used to carry out multiple regression analysis to test hypotheses.

The results show that relationship between structural holes and risk propagation of R&D network is U-shaped. Risk perception and risk sharing partially mediate the relationship between structural holes and risk propagation. Tie strength significantly moderates the relationship between structural holes and risk sharing, but insignificantly moderates the association between structural holes and risk perception. Common cognition significantly moderates the associations between structural holes and risk sharing, and structural holes and risk perception, respectively.

This study provides a distinctive theoretical perspective for social capital and risk management. It also offers managers a clear understanding of how to reduce or to avoid risk propagation by jointly leveraging the number of structural holes, tie strength and common cognition.

To provide valuable information for scholars to grasp the current situations, hotspots and future development trends of reliability analysis area.

In this paper, recent researches on efficient reliability analysis and applications in complex engineering structures like aeroengine rotor systems are reviewd.

The recent reliability analysis advances of engineering application in aeroengine rotor system are highlighted, it is worth pointing out that the surrogate model methods hold great efficiency and accuracy advantages in the complex reliability analysis of aeroengine rotor system, since its strong computing power can effectively reduce the analysis time consumption and accelerate the development procedures of aeroengine. Moreover, considering the multi-objective, multi-disciplinary, high-dimensionality and time-varying problems are the common problems in various complex engineering fields, the surrogate model methods and its developed methods also have broad application prospects in the future.

For the strong demand for efficient reliability design technique, this review paper may help to highlights the benefits of reliability analysis methods not only in academia but also in practical engineering application like aeroengine rotor system.

Mining user-concerned actionable and interpretable hot topics will help management departments fully grasp the latest events and make timely decisions. Existing topic models primarily integrate word embedding and matrix decomposition, which only generates keyword-based hot topics with weak interpretability, making it difficult to meet the specific needs of users. Mining phrase-based hot topics with syntactic dependency structure have been proven to model structure information effectively. A key challenge lies in the effective integration of the above information into the hot topic mining process.

This paper proposes the nonnegative matrix factorization (NMF)-based hot topic mining method, semantics syntax-assisted hot topic model (SSAHM), which combines semantic association and syntactic dependency structure. First, a semantic–syntactic component association matrix is constructed. Then, the matrix is used as a constraint condition to be incorporated into the block coordinate descent (BCD)-based matrix decomposition process. Finally, a hot topic information-driven phrase extraction algorithm is applied to describe hot topics.

The efficacy of the developed model is demonstrated on two real-world datasets, and the effects of dependency structure information on different topics are compared. The qualitative examples further explain the application of the method in real scenarios.

Most prior research focuses on keyword-based hot topics. Thus, the literature is advanced by mining phrase-based hot topics with syntactic dependency structure, which can effectively analyze the semantics. The development of syntactic dependency structure considering the combination of word order and part-of-speech (POS) is a step forward as word order, and POS are only separately utilized in the prior literature. Ignoring this synergy may miss important information, such as grammatical structure coherence and logical relations between syntactic components.

In intelligent scheduling, parallel batch processing can reasonably allocate production resources and reduce the production cost per unit product. Hence, the research on a parallel batch scheduling problem (PBSP) with uncertain job size is of great significance to realize the flexibility of product production and mass customization of personalized products.

The authors propose a robust formulation in which the job size is defined by budget constrained support. For obtaining the robust solution of the robust PBSP, the authors propose an exact algorithm based on branch-and-price framework, where the pricing subproblem can be reduced to a robust shortest path problem with resource constraints. The robust subproblem is transformed into a deterministic mixed integer programming by duality. A series of deterministic shortest path problems with resource constraints is derived from the programming for which the authors design an efficient label-setting algorithm with a strong dominance rule.

The authors test the performance of the proposed algorithm on the extension of benchmark instances in literature and compare the infeasible rate of robust and deterministic solutions in simulated scenarios. The authors' results show the efficiency of the authors' algorithm and importance of incorporating uncertainties in the problem.

This work is the first to study the PBSP with uncertain size. To solve this problem, the authors design an efficient exact algorithm based on Dantzig–Wolfe decomposition. This can not only enrich the intelligent manufacturing theory related to parallel batch scheduling but also provide ideas for relevant enterprises to solve problems.

This paper aims to analyse the changes in the extent of the green space in the city of Srinagar, a unique urban Himalayan destination, and examine whether the difference in the green space has a significant effect on the destination business performance measured in terms of loss of ecological attractiveness.

This study was carried out in two phases in the study area. In phase I, the changes in the extent of the green space area were analysed using Landsat TM and Sentinel Images for classification. The study has used the period from 2001 to 2018 to understand changes in the green space. The Post-Classification Comparison technique was used to investigate the variation in the green space zones in the city of Srinagar. In phase II, the paper evaluated the impact of change in the green space on the destination business performance. The data was collected from the tour operation companies through a questionnaire survey, and the impact path was examined using structural equation modelling.

Results reveal that the green space in the city of Srinagar has decreased over the past 18 years, and the decreasing green space has a significant effect on the destination business performance.

Identifying the impact of decreasing green space on the destination business performance of the study area under investigation is essential for tourism development both in terms of new product development and resource preservation. Developing a measurement scale showing the impact of decreasing green space on destination business performance could offer destination managers a means of identifying the essence of the green space in the destination regions. These findings add to the growing literature on the attributes of tourism destinations, providing scholars with new insights into the role of green space in destination performance. The current study offers evidence of the impact of decreasing green space on the destination's performance. This provides a new perspective for future studies on visitor satisfaction as a potential mediator of the relationship between reducing greenspace and destination business performance. The main limitation of this study is that the researchers have only analysed the impact of decreasing green space on the destination business performance in terms of its ecological competitiveness. Other destinations business performance verticals, such as hotels, restaurants and grocery stores were not considered by this study and can be taken up for future investigation.

This study provides empirical insights that can have significant implications for researchers, policymakers, destination management organizations, academia and practitioners and further enrich the existing literature by establishing an empirical argument in the context of urban destinations positioned with a fragile Himalayan ecosystem.

This study aims to assist the urban administrators in improving the green space ecosystem in the region, which can help attain the sustainability of the city environment and assist in economic regeneration in urban settings.

This paper aims to study the effects of MnO₂ on the ZnO–Bi₂O₃-based varistor prepared via flash sintering (FS)

MnO₂-doped ZnO–Bi₂O₃-based varistors were successfully prepared by the FS with a step-wise increase of the .current in 60 s at the furnace temperature <750°C under the direct current electric field of 300 V cm⁻¹. The FS process, microstructure and the electrical performance of ZnO–Bi₂O₃-based varistors were systematically investigated.

The doping of MnO₂ significantly decreased the onset temperature of FS and improved the electrical performance of FS ZnO varistor ceramic. The sample with 0.5 mol% MnO₂ doping shows the highest improvement, with the nonlinear coefficient of 18, the leakage current of 16.82 µA, the threshold voltage of 459 V/mm and the dielectric constant of 1,221 at 1 kHz.

FS is a wonderful technology to enhance ZnO varistors for its low energy consumption, and a short sintering time can reduce grain growth and inhabit Bi₂O₃ volatilize, yet few research studies work on that. In this research, the authors analyzed the FS process and improved the electrical characteristics through MnO₂ doping.

The purpose of this paper is to focus on examining the first day returns of initial public offerings (IPOs) and the role of information on their performance. The study tries to optimize the returns of the new issues during 2005-2012 with risk as a constraint.

The initial returns are measured through the market-adjusted excess return and the risk associated with the new issue is measured through underwriters’ reputation. The returns have been optimized through a mixed integer linear problem using the Maple software.

The previous studies show that various informational variables affect the listing day returns significantly. The results of the present study indicate that the mean of initial returns for IPOs during 2005-2012 is 18.03 and the mean risk for these issues is 0.46. The findings also suggest that the optimal returns are obtained in the pre-recession era (2005-2008) and the value for the same is 50.02 percent.

The current study contributes in the investment decisions for global investors as every investor wants to maximize his/her returns. The optimal returns with risk as a constraint will help the investors in improving their investment decision as a prudent investor does not aim solely at maximizing the expected return of an investment but is also interested in optimizing with the minimization of risk.