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The purpose of this paper is to develop a quantitative risk assessment method for agricultural products cold chain logistics to assess the condition of the fresh agricultural products cold chain process objectively and accurately.

A risk assessment index system of agricultural products cold chain logistics is designed on the basis of the risk identification for the process of agricultural products cold chain logistics. This paper first uses catastrophe progression method and a new maximum deviation method to build an improved catastrophe progression assessment model for agricultural products cold chain logistics. In order to verify the reliability and validity of the model, two representative enterprises are selected as the case in the study.

The results in the empirical research indicate strong support for the assessment model and coincide with the reality. The risk assessment index system can also reflect the key risk factors from agricultural products cold chain logistics scientifically. In addition, the improved catastrophe progression assessment method proposed in this paper can be scientific and reasonable to predict risk.

This paper contributes to provide a new risk assessment model for agricultural products cold chain logistics. The new model overcomes the limitation of subjective empowerment and it increases the objectivity and scientificity in the process of cold chain logistics risk assessment. This paper also shows that practitioners involved in the field of products cold chain logistics can manage the potential risk by a set of scientific methods for assessing the risk before the accident.

The paper provides a practical guideline to practitioners, especially for cold chain logistics managers, relevant management departments, and cold chain logistics management consultants. It is proved that the new risk assessment method and the risk assessment index system of agricultural products cold chain logistics can help them assess the risk scientifically and reasonably.

Although the calculation is simple, the new model can overcome the limitation of subjective empowerment scientifically and reasonably, and thus has important practical value.

The purpose of this paper is to examine the impact of common ownership on corporate innovation, including innovation input, innovation output and postgrant patents.

This paper uses the ordinary least square model and the difference-in-differences technique to evaluate the effect of institutional interlocking shareholdings on the life cycle of corporate innovation.

The results show that common ownership impedes innovation measured by patent grants and citations through reduced R&D expenditures. However, common ownership protects postgrant patents by lowering the likelihood that a co-owned firm gets involved in patent litigation and by accelerating the settlement of lawsuits between co-owned firms.

From a regulatory perspective, common ownership in younger firms that rely heavily on R&D investment to produce innovation outputs is detrimental and needs to be regulated. However, common ownership in mature firms, which hold a big pool of patents or rely on acquiring patents to compete, is of less concern because of the protective role detected.

The paper provides a first comprehensive look into how same-industry common ownership affects innovation input, innovation output and postgrant patents. The research also reconciles the anticompetitive effect and the coordinative effect of common ownership documented in the literature.

This paper seeks to examine the impact of foreign direct investments (FDI) on air pollution in China using 286 cities from 2001 to 2007. It is a particular interest of this paper to observe the relationship between FDI and air pollution in particular after China joined to World Trade Organization in 2001. This paper provides a better understanding of economic growth and foreign investment while maintaining a sustainable environment. In order to achieve this task, this paper tests whether or not FDI inflow has impact on environmental deterioration in particular on air quality.

Since the data are both cross‐sectional and time series, panel data analyses (fixed effects and random effects) were applied. In order to detect the presence of serial correlation of error term, Durbin‐Watson test was used. As serial correlation problem was determined, generalized least square (GLS) using Ar(1) model was used to overcome serial correlation.

The findings show that FDI has no negative impact on the air quality in China. Contrary to expectations, the presence of FDI reduces the air pollution. This result can be attributed by the role of FDIs in the economy that FDIs are perceived as main sources of advanced technology in China. One of the striking findings of the paper shows that FDI has no significant impact on air quality in the central and western cities. The reason is that low level of FDI inflows to cities located in the Center and West. The findings are robust under both panel data (fixed effects and random effects) and GLS estimations.

The results provide a wide array of information useful to practitioners, policy makers. Since the paper shows that FDI has no negative impact on the air quality, this result is crucial in attracting FDI to China.

This paper provides the largest sample including 286 cities all over China from 2001 to 2007. Considering the distribution of FDI across China, the sample is divided into three regions. Making sub‐samples of the FDI distribution allowed us to examine how the impact of FDI differs on air quality in the East, Central and West regions.

The purpose of this paper is to concern the design of a robust model predictive controller for distributed networked systems with transmission delays.

The overall system is composed of a number of interconnected nonlinear subsystems with time-varying transmission delays. A distributed networked system with transmission delays is modeled as a nonlinear system with a time-varying delay. Time delays appear in distributed systems due to the information transmission in the communication network or transport of material between the sub-plants. In real applications, the states may not be available directly and it could be a challenge to address the control problem in interconnected systems using a centralized architecture because of the constraints on the computational capabilities and the communication bandwidth. The controller design is characterized as an optimization problem of a “worst-case” objective function over an infinite moving horizon.

The aim is to propose control synthesis approach that depends on nonlinearity and time varying delay characteristics. The MPC problem is represented in a time varying delayed state feedback structure. Then the synthesis sufficient condition is provided in the form of a linear matrix inequality (LMI) optimization and is solved online at each time instant. In the rest, an LMI-based decentralized observer-based robust model predictive control strategy is proposed.

The authors develop RMPC strategies for a class of distributed networked systems with transmission delays using LMI-Based technique. To evaluate the applicability of the developed approach, the control design of a networked chemical reactor plant with two sub-plants is studied. The simulation results show the effectiveness of the proposed method.

The purpose of this paper is to examine the difference between the daytime (open-to-close) and overnight (close-to-open) returns of CSI 300 index and its derivative futures.

The paper explores the difference between the daytime and overnight time returns by using nonparametric techniques. Moreover, investigation on some factors such as short selling, trading rules, risks are made to seek the sources of the day and night effects based on a large number of empirical analysis. In the end, further analyses on daytime and overnight returns are given by the use of high-frequency data and linear regression technique.

The authors show that the daytime returns of CSI 300 index are no less than its overnight returns, while the daytime returns of CSI 300 index futures are no more than its overnight returns, even after removing the heteroscedasticity of the researched time series. Specifically, the PM returns (13:05 to close) play a quite important role in the intra-day time. The findings also suggest that the unique “T+1 trading rule” in China may be a reason that incurs the lower opening price in the morning and the higher closing price in the afternoon, resulting in the statistically significant differences between the daytime and overnight returns.

The findings are of great importance for investors to decide when to buy and sell stock and futures portfolios in Chinese financial markets.

This study empirically analyzes why there the higher daytime returns and the lower overnight returns exist in the Chinese stock markets from different aspects and contributes the existing literature on day and night effects because of periodic market closures.

Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked.

A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt.

Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments.

This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.

WeChat is the largest acquaintance social networking platform in China, in which users can view and reshare web pages shared by friends. This paper aims to analyze the spatio-temporal dynamics of web pages diffused in WeChat and advice on commercials.

A large number of web pages diffused in WeChat are collected and exclusively divided into four categories according to their titles, including advertisements, news bulletins, holiday greetings and emotional essays. For each web page, an information cascade (tree structure) is constructed to describe the diffusion trace. Based on the categories, the spatio-temporal popularity is characterized; the topological, temporal and spatial properties are examined; and the spatio-temporal diffusion velocity is explored.

Through comparative analysis, different categories of pages show diversity. For spatio-temporal popularity, there is no significant difference in cascade size; holiday greetings usually last for a relatively short time on average; emotional essays are more likely to spread to more provinces. For topological, temporal and spatial characteristics, the diffusion process of advertisements is more likely to be broadcasting than other categories; news bulletins and holiday greetings have an obvious bursty; the number of viewing behavior decreases from east to west in general. For spatio-temporal diffusion velocity, emotional essays diffuse the fastest in topological and spatio-temporal dimensions.

These findings contribute to promoting products and providing support for data driven modeling of information diffusion and human activity in spatio-temporal dimensions.

The deposition of particles onto a substrate during the cold spraying (CS) process relies on severe plastic deformation, so there are various micro-defects induced by insufficient deformation and severe crushing. To solve the problems, many post-treat techniques have been used to improving the quality by eliminating the micro-defects. This paper aims to help scholars and engineers in this field a better and systematic understand of CS technology by summarizing the post-treatment technologies that have been investigated recently years.

This review summarizes the types of micro-defects and introduces the effect of micro-defects on the properties of CS coating/additive manufactured, illustrates the post-treatment technologies and its effect on the microstructure and performances, and finally outlooks the future development trends of post-treatments for CS.

There are significant discoveries in post-treatment technology to change the performance of cold spray deposits. There are also many limitations for post-treatment methods, including improved performance and limitations of use. Thus, there is still a strong requirement for further improvement. Hybrid post-treatment may be a more ideal method, as it can eliminate more defects than a single method. The proposed ultrasonic impact treatment could be an alternative method, as it can densify and flatten the CS deposits.

It is the first time to reveal the influence factors on the performances of CS deposits from the perspective of microdefects, and proposed corresponding well targeted post-treatment methods, which is more instructive for improving the performances of CS deposits.

This study aims to investigate countries without national property insurance and see how experience affects behavior toward higher-risk flood prone property.

Using a unique data set that captures the flood experiences of homeowners that search for new housing, the authors examine the premiums or discounts of such experience on homes at risk. The authors use hedonic property modeling to estimate the effects of experience on values.

The authors find that such experiences play a strong role in convincing buyers of the real risks imposed by climate change and sea level rise and the authors expect these demand-side behavioral changes to persist. This finding is unlike more developed markets where insurance may be subsidized and negative effects on value dissipate within a few years.

The world is starting to pay more attention to climate risk and the results in developed countries have been biased by the extensive insurance provided by the government or emergency funding.

Providing market transparency on climate risks will result in permanent market effects, if not otherwise subsidized.

The governments should encourage market disclosure.

No one has ever had a data set like this before where the authors get to observe the behavior of those already experiencing property losses from flooding.