Porcine circovirus type 3 (PCV3) is a new-emerging circovirus belonging to the genus Circovirus in the family Circoviridae in which PCV type 1 (PCV1) and PCV type 2 (PCV2) were well documented (Palinski et al. 2017). PCV1 is a cell culture-derived virus and is considered to be nonpathogenic for swine, whereas PCV2 is the primary etiological agent of porcine circovirus-associated diseases (PCVAD) that causes severe economic losses in the swine industry worldwide (Zhai et al. 2014). PCV3 was firstly reported in the United States of America in 2016 (Palinski et al. 2017). After that, PCV3 has been detected in Poland,

Investment on product greenness in green supply chain is always restricted by the emerging supplier’ financial constraints, so manufacturers always share the suppliers’ investment to encourage the suppliers’ green innovation. Based on the two-stage cooperation model between one manufacturer and one emerging supplier, and the assumption that emerging suppliers need to reach a certain survival threshold at the end of each period, this paper studies investment on product greenness and sustainability of cooperation in the supply chain. The impacts of consumers’ preference for greenness (CPG), market volatility, financial constraints, and investment-sharing proportion are also examined. It was found that when market volatility and CPG exist at the same time, compared with the deterministic environment, emerging suppliers will improve (or reduce) the wholesale price and greenness at the same time to balance the short-term bankruptcy risk and the long-term profit, and suppliers’ green investment would be stimulated by the increasing demand uncertainty. Besides, when suppliers’ financial constraints increase, manufacturers will also increase its sharing proportion of green investment. Lastly, there always exists an investment-sharing proportion that optimizes the sustainability of cooperation and profits jointly.

Based on the provincial panel data from 2004 to 2019, this paper constructs a more comprehensive industrial structure upgrading coefficient and uses a moderated mediation model to verify the mechanism of OFDI reverse green innovation technology on industrial upgrading. It is found that OFDI has a reverse green technology innovation effect, which can positively promote China’s industrial upgrading. From the perspective of a moderated mediating effect, the increase of domestic R&D investment is conducive to shortening the technological gap with developed countries, and the enhancement of domestic environmental regulation also encourages multinational enterprises to implement green technology cooperation. Both of them strengthen the reverse green technology innovation effect of OFDI, and correspondingly have a greater promoting effect on the upgrading of industrial structure. The reverse green technology innovation of OFDI mainly promotes strategic green innovation of noninvention types, but the enhancement of R&D capability and the improvement of environmental regulation can strengthen the reverse substantive green innovation of OFDI. After endogenous processing and replacing the core explanatory variables, the results are still significant.

In this study, we propose an adaptive multiscale ensemble (AME) learning approach, which consists of variational mode decomposition (VMD) and least square support vector regression (LSSVR) for seasonal and trend forecasting of tourist arrivals. In the formulation of AME learning approach, the original tourist arrival series is decomposed into the trend, seasonal, and remaining volatility components. Then, ARIMA is used to forecast the trend component, SARIMA is used to forecast the seasonal component, and LSSVR is used to forecast the remaining volatility components. The empirical results demonstrate that our proposed AME learning approach can achieve higher forecasting accuracy.

The profits of the ESCO (Energy Services Company) and EU (Energy Using Organization) in the EPCP (energy performance contracting project) rely on the signing of the shared savings contract and the successful operation of the project, and the probability of the project's success is decided by the complementary efforts of the ESCO and EU. However, the effort selection of the two sides face the bidirectional moral hazard caused by asymmetric information. Based on the robustness of shared savings contract, this paper establishes a bidirectional moral hazard model under asymmetric information to analyze the complementary efforts selection of the ESCO and EU with the given revenue sharing rules, and analyzes the differences of the complementary efforts under symmetric and asymmetric information conditions and the impacts of those efforts on the shared savings contract's robustness by using a numerial simulation. The results show that compared with information symmetry, the bidirectional moral hazard will erode the project's value under information asymmetry, the project's success probability and the level of the parties' efforts will decrease, which reveals the negative impact of asymmetric information on the robustness of the shared savings contract, and the significance of eliminating information asymmetry effectively as well as incentivizing the parties to increase the degree of complementary efforts to enhance the probability of the project's success. Finally, policy recommendations regarding the introduction of incomplete contracts, promoting guaranteed savings contracts, and improving energy savings audits for the enhancement of the robustness of the shared savings contract are provided. This research will be helpful to improve the theoretical research on the contract's robustness, perfect the design of the energy service contract, and formulate the related support policies.