In the Internet era, consumers prefer products with the attributes of social responsibility. Supply chain enterprises strengthen corporate social responsibility (CSR) management for their own ...development. To improve CSR throughout the supply chain, it requires coordination and cooperation among the members of the supply chain. In this paper, we consider a three-tier supply chain system consisting of a supplier, a manufacturer, and a retailer and use stochastic differential game to study the CSR coordination of the supply chain. The following indicators are investigated under four decision situations, such as the optimal level of CSR effort for the supply chain members, the optimal value of profit for the supply chain members and the supply chain system, and the expectation and variance of CSR goodwill. Some important results are obtained. (i) Compared with decentralized decision-making, the optimal level of CSR effort increases for the supplier and the manufacturer under local alliance decision-making without cost sharing, whereas the optimal level of CSR effort remains unchanged for the retailer. (ii) Compared with local alliance decision-making without cost sharing, the optimal level of CSR effort remains unchanged for the supplier and the manufacturer under local alliance decision-making with cost sharing. When the sum of the marginal profit for the supplier and the manufacturer is greater than half of the marginal profit for the retailer, the optimal level of CSR effort increases for the retailer. (iii) Compared with local alliance decision-making with cost sharing, the optimal level of CSR effort increases for the supply chain members under overall alliance decision-making. (iv) From decentralized decision-making to local alliance decision-making without cost sharing, to local alliance decision-making with cost sharing, and then to overall alliance decision-making, the optimal value of profit increases for the supply chain members and the supply chain system. Also, the expectation and variance of CSR goodwill increase.
It is of great significance to accurately grasp the demand for air travel to promote the revival of long-distance travel and alleviate public anxiety. The main purpose of this study is to build a ...high-precision air travel demand forecasting framework by introducing effective Internet data. In the age of big data, passengers before traveling often look for reference groups in search engines and make travel decisions under their informational influence. The big data generated based on these behaviors can reflect the overall passenger psychology and travel demand. Therefore, based on big data mining technology, this study designed a strict dual data preprocessing method and an ensemble forecasting framework, introduced search engine data into the air travel demand forecasting process, and conducted empirical research based on the dataset composed of air travel volume of Shanghai Pudong International Airport. The results show that effective search engine data is helpful to air travel demand forecasting. This research provides a theoretical basis for the application of big data mining technology and data spatial information in air travel demand forecasting and tourism management, and provides a new idea for alleviating public anxiety.
Before making travel plans, people often use the Internet to collect relevant information to help themselves make better decisions. Among the numerous information search channels, Internet search ...engine is used by the vast number of travelers because of its low cost and high efficiency. To a large extent, Internet search behavior is the external manifestation of users’ psychological activities, reflecting their concerns, needs and preferences. Therefore, Internet search data can reflect the air passenger demand information to a certain extent. In this manuscript, a novel decomposition ensemble model is proposed to discuss the role of Internet search data in air passenger demand forecasting. In the empirical study, the relevant data of Shanghai Pudong International Airport and Beijing Capital International Airport are taken as samples. The results show that the proposed forecasting model can integrate the advantages of decomposition-ensemble strategy and deep learning algorithm, and achieve more accurate and reliable prediction results than all benchmark models. This further indicates that adding Internet search data into the forecasting model can effectively improve the prediction performance of air passenger demand, and can provide scientific and reliable decision support for air transport management.
In the Internet era, with the widespread application of digital technology, the way people travel has changed. Compared with traditional taxis, more and more people prefer to choose online ...car-hailing. The rapid development of the online car-hailing industry has solved the problem of taxi-hailing to a certain extent, but it has also brought some new problems. To change the dilemma of the online car-hailing industry, it is necessary to strengthen the regulation of the online car-hailing industry. In this study, we consider the regulatory system composed of a local government and an enterprise and use the differential game to study the regulation of online car-hailing. In the Nash non-cooperative game, Stackelberg master–slave game, and cooperative game, we, respectively, investigate the indicators, such as the optimal regulatory effort of the government, the optimal regulatory effort of the enterprise, the optimal benefit function of the government, the optimal benefit function of the enterprise, the optimal benefit function of the system, the optimal trajectory of the service quality level for the enterprise, and the optimal trajectory of the goodwill for the enterprise. Moreover, we analyze the corresponding conclusions through examples. We obtained some important results. (i) In the Stackelberg master–slave game, the optimal ratio of the local government subsidy to the enterprise's regulatory cost is only related to the benefit distribution coefficient and has nothing to do with other factors. Moreover, when the benefit distribution coefficient is >1/3, the local government is willing to share the regulatory cost of the enterprise. Otherwise, the local government refuses to share the regulatory cost of the enterprise. (ii) Compared with the Nash non-cooperative game, the optimal regulatory effort of the local government remains unchanged in the Stackelberg master–slave game, but the optimal benefit of the local government increases. Moreover, when the benefit distribution coefficient is >1/3, both the optimal regulatory effort and the optimal benefit of the enterprise increase. (iii) Compared with the Stackelberg master–slave game, in the cooperative game, the optimal regulatory effort of both government and enterprise increases, and the system's optimal benefit also increases. (iv) From the Nash non-cooperative game to the Stackelberg master–slave game and then to the cooperative game when the benefit distribution coefficient is >1/3, the service quality level and goodwill of the enterprise all increase.
This paper introduces a hybrid framework for port container throughput forecasting, which is essential in global trade and transportation systems. It uses a multidisciplinary method that combines ...artificial intelligence, link prediction, and complex networks. To better grasp the interconnection and dynamics of port operations, time series data are first transformed using complex network theory into a network structure. The framework applies 13 similarity metrics, encompassing various aspects of network structural similarity, to form a feature set representing the complex port operation network. The most effective features are selected using the maximum relevance minimum redundancy (mRMR) method, adhering to systems theory’s efficiency principles. These features are processed through SVM, DNN, and LSTM models for link prediction, which is crucial for forecasting in port logistics. Finally, the methodology concludes with regression analysis to obtain container throughput forecasts, which is a key metric in port systems management. Case studies of Shanghai Port and Shenzhen Port validate the framework’s effectiveness, demonstrating a significant improvement in forecasting accuracy over the baseline models. This study contributes to systems analysis by showcasing a hybrid, AI-enhanced approach for managing and forecasting critical aspects of maritime trade systems.
As the global process of digitalization accelerates and breakthroughs in internet technology emerge, governments worldwide are advocating for data-driven decision-making, aiming to enhance public ...service efficiency and stimulate economic growth. Against this backdrop, this study focuses on utilizing search engine data (SED) to improve air passenger demand forecasting, responding to national policies aimed at enhancing data analysis capabilities and promoting the development of intelligent transportation systems; however, the existing research is confined to the exploration of the temporal dependency between SED and air passenger demand variables with ignoring the spatial dependency. In order to eliminate this blind spot and catch from various parts of tourist attention, this study proposes a novel SED-driven hybrid forecasting architecture inspired by the theory of spatial effect between adjacent tourist destinations. The architecture includes three main steps: (1) construction of spatial-temporal SED variables, based on two-stage data preprocessing method; (2) variable decomposition and reconstruction, based on TVF-EMD algorithm; (3) prediction of different components of air passenger demand, employed ARIMA model and IHGS-KELM based multi-model fusion strategy respectively, where the IHGS algorithm integrates the circle chaos initialization strategy and the nonlinear convergence factor strategy. To confirm the practical applicability of this hybrid architecture, five comparative experiments based on the actual dataset are designed. The principal results are concluded as follows: (1) spatial-temporal SED is conducive to a fairly accurate air passenger demand forecasting; (2) the multi-model fusion strategy can integrate the fortes of various types of prediction models to obtain better prediction accuracy; (3) the adaptive ensemble method based on IHGS-KELM can contribute to the upgradation of prediction performance of air passenger demand.
•Spatial-temporal search engine data is conducive to a fairly accurate air passenger demand forecasting.•The multi-model fusion strategy can integrate the advantages of different prediction models to obtain better prediction accuracy.•The adaptive ensemble method based on IHGS-KELM is helpful to improve the prediction performance of air passenger demand.
As an archetypal antiperovskite nitride compound, GeNCr3 undergoes a temperature-driven first-order antiferromagnetic-paramagnetic transition at approximately 418 K, accompanied with a structural ...phase transition from space group P-421m to I4/mcm. In this paper, we show that the critical temperature of GeNCr3 can be tuned from 418 to 240 K by doping manganese ions. Simultaneously, the evolution of the magnetic transition is consistent with the structural transition. Using temperature-dependent X-ray diffraction and X-ray photoelectron spectroscopy, in combination with first-principles calculations, we demonstrate that doping manganese ions tend to occupy the equatorial plane of the nitrogen octahedron.
•The magnetic transition accompanied by a structural transition in GeNCr3 can be significantly shifted from 418 to 240 K by doping Mn ions.•The position of doping Mn is accurately identified at the atomic level by DFT.•The physical mechanism is discussed and analyzed from the perspective of crystal structure.
Fms-like tyrosine kinase 1 (FLT1) has been shown to regulate processes such as angiogenesis, neurogenesis, and cognitive impairment. However, the role of FLT1 in prenatal stress (PS) is unclear. The ...purpose of this study was to investigate the role of FLT1 in PS mothers and their offspring. Wire mesh restrainers were used to construct PS rat model. The levels of FLT1, IL-1β, IL-6, and ROS in clinical samples and rat samples were detected by qRT-PCR, ELisa kit, and DCFH-DA fluorescence kit. Morris water maze assay and forced swimming assay were used to test the cognitive function of offspring young rats. The apoptosis level of hippocampal neurons and the expression of NMDARs were detected by MTT assay, TUNEL assay, and Western blot. The results showed that FLT1 was upregulated in PS mothers and positively correlated with PS degree. The level of FLT1 was elevated in PS model rats. Knockdown of FLT1 reduced maternal ROS and MDA levels and increased SOD levels in PS rats. Knockdown of FLT1 also reduced the secretion of IL-1β, IL-6, and cortisol in PS rats. Inhibition of FTL1 alleviated cognitive impairment in PS offspring pups. Inhibition of FTL1 reduced hippocampal neuronal apoptosis and increased the expression of NMDARs in PS progeny. In conclusions, we demonstrated that knockdown of FLT1 inhibits maternal oxidative stress, inflammation, and cortisol secretion in PS rats. In addition, knockdown of FLT1 also alleviated cognitive dysfunction and neurodevelopmental abnormalities in PS offspring pups.
We report the structure, magnetic and electrical/thermal transport properties of the antiferromagnet MnSn
. Importantly, the existence of the two antiferromagnetic states below
(∼320 K) is confirmed ...by magnetism and electrical transport measurements. An unsaturated positive magnetoresistance up to 150% at ∼9
was observed at 5 K, whereas the magnetoresistance becomes negative in the whole range at high temperatures (
> 74 K). Systematic investigations of the Hall transport and thermoelectric properties reveal that the hole-type carriers are the majority carriers in MnSn
. The kink around 320 K in the Seebeck coefficient originates from the effect of the antiferromagnetic phase on the band structure, while the pronounced peak around 231 K is attributed to the phonon-drag effect. The results suggest that the spin arrangement plays a vital role in the magnetic, electrical, and thermal transport properties in MnSn
.
We report the structure, magnetic and electrical/thermal transport properties of the antiferromagnet MnSn
2
. Importantly, the existence of the two antiferromagnetic states below
T
N2
(∼320 K) is ...confirmed by magnetism and electrical transport measurements. An unsaturated positive magnetoresistance up to 150% at ∼9
T
was observed at 5 K, whereas the magnetoresistance becomes negative in the whole range at high temperatures (
T
> 74 K). Systematic investigations of the Hall transport and thermoelectric properties reveal that the hole-type carriers are the majority carriers in MnSn
2
. The kink around 320 K in the Seebeck coefficient originates from the effect of the antiferromagnetic phase on the band structure, while the pronounced peak around 231 K is attributed to the phonon-drag effect. The results suggest that the spin arrangement plays a vital role in the magnetic, electrical, and thermal transport properties in MnSn
2
.
We report the structure, magnetic and electrical/thermal transport properties of the antiferromagnet MnSn
2
.
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