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The purpose of this paper is to examine how advertising is used by real estate companies as an instrument for managing the adverse effects of a catastrophe.

Through a theoretical analysis, types of post-disaster advertising messages were identified. On the basis of the likely variations in post-disaster advertising, a content analysis was conducted of a sample of 4,150 property print advertisements to identify advertising messages related to the earthquake. Finally, the message changes in these earthquake-related advertisements were evaluated and compared with the dimension of time to explore the development of advertising strategies.

The authors found that 12 types of advertising messages were used by developers in response to the Wenchuan earthquake. The initial advertising strategy was mainly to manage public relations, then the strategy was to reduce or compensate for the increased earthquake risk perceptions of buyers.

The findings provide valuable references for helping enterprises adopt effective advertising messages and strategies to reduce the negative effects of disasters.

There are only a few studies on advertising campaigns, especially in the real estate industry, that have been conducted in the wake of catastrophes. This study sought to expand upon the scarce findings in this particular field.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

The purpose of this paper is to detect abnormal data of complex and sophisticated industrial equipment with sensors quickly and accurately. Due to the rapid development of the Internet of Things, more and more equipment is equipped with sensors, especially more complex and sophisticated industrial equipment is installed with a large number of sensors. A large amount of monitoring data is quickly collected to monitor the operation of the equipment. How to detect abnormal data quickly and accurately has become a challenge.

In this paper, the authors propose an approach called Multiple Group Correlation-based Anomaly Detection (MGCAD), which can detect equipment anomaly quickly and accurately. The single-point anomaly degree of equipment and the correlation of each kind of data sequence are modeled by using multi-group correlation probability model (a probability distribution model which is helpful to the anomaly detection of equipment), and the anomaly detection of equipment is realized.

The simulation data set experiments based on real data show that MGCAD has better performance than existing methods in processing multiple monitoring data sequences.

The MGCAD method can detect abnormal data quickly and accurately, promote the intelligent level of smart articles and ultimately help to project the real world into cyber space in CrowdIntell Network.

Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI.

First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs.

IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs.

The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.

Corporate social responsibility (CSR) is significant in the financial market. Despite plenty of existing research on CSR, few studies have quantified the fine-grained aspects of CSR and examined how diverse CSR aspects are associated with firms' trade credit. Based on the released CSR reports, this paper strives to measure the CSR fulfillment of firms and examine the relationships between CSR and trade credit in terms of textual features presented in these reports.

This research proposes a natural language processing-based framework to extract the overall readability and the sentiment of fine-grained aspects from CSR reports, which can signal the performance of firms' CSR in diverse aspects. Furthermore, this paper explores how the textual features are associated with trade credit through partial dependence plots (PDPs), and PDPs can generate both linear and nonlinear relationships.

The study’s results reveal that the overall readability of the reports is positively associated with trade credit, while the performance of the fine-grained CSR aspects mentioned in the CSR reports matters differently. The performance of the environment has a positive impact on trade credit; the performance of creditors, suppliers and information disclosure, shows a U-shaped influence on trade credit; while the performance of the government and customers is negatively associated with trade credit.

This study expands the scope of research on CSR and trade credit by investigating fine-grained aspects covered in CSR reports. It also offers some managerial implications in the allocation of CSR resources and the presentation of CSR reports.

The shipper selects a suitable shipping route and plans for a voyage in order to import and export cargo on the basis of published sailing schedules. The reliability of the sailing schedule will influence the shipper’s logistics expense, which means that the logistics costs will depend on the reliability of schedules published by container shipping companies. Therefore, it is important to consider factors which can cause delays would for container ships sailing on sea routes. The reliability of published sailing schedules can be affected by a number of different factors. This study adopts the multi-criteria decision making (MCDM) method to estimate the importance of the delaying factors in a sailing schedule. In addition, the consistent fuzzy preference relations (CFPR) method is applied to identify the subjective importance (weights) of the delaying factors. The entropy weight method combined with the actual performance of the container shipping company are both used when estimating the objective importance (weights) of the delaying factors. According to the analysis results, the criteria can be divided into four quadrants with different management implications, which indicate that instructions for chase strategy, sailing schedule control, fleet allocation, transship operation arrangement and planning for ports in routes are often ignored by container shipping companies. Container shipping companies should consider adjusting their operational strategies, which would greatly improve their operational performance.

In a state capitalist country such as China, an important influence on company reporting is the government, which can influence company decision-making. The nature and impact of how the Chinese government uses its symbolic power to promote corporate environmental reporting (CER) have been under-studied, and therefore, this paper aims to address this gap in the literature by investigating the various strategies the Chinese government uses to influence CER and how political ideology plays a key role.

This study uses discourse analysis to examine the annual reports and corporate social responsibility (CSR) reports from seven Chinese companies between 2007 and 2011. And the data analysis presented is informed by Bourdieu's conceptualisation of symbolic power.

The Chinese government, through exercising the symbolic power, manages to build consensus, so that the Chinese government's political ideology becomes the habitus which is deeply embedded in the companies' perception of practices. In China, the government dominates the field and owns the economic capital. In order to accumulate symbolic capital, companies must adhere to political ideology, which helps them maintain and improve their social position and ultimately reward them with more economic capital. The findings show that the CER provided by Chinese companies is a symbolic product of this process.

The paper provides contributions around the themes of symbolic power wielded by the government that influence not only state-owned enterprises (SOEs) but also firms in the private sector. This paper also provides an important contribution to understanding, in the context of a strong ideologically based political system (such as China), how political ideology influences companies' decision-making in the field of CER.

Crowdfunding has become a popular and achievable means of funding projects worldwide. The purpose of this study is to determine which personal and social traits can increase individuals’ intention to participate in crowdfunding.

This study examines innovativeness, attitudes toward helping others and interpersonal connectivity as determinants of consumers’ intention to participate in crowdfunding. Social identification with the crowdfunding community is proposed as a mediator in the model.

The results show that both social identification with the crowdfunding community and innovativeness have a positive effect on intention to participate. In addition, attitudes toward helping others and interpersonal connectivity indirectly affect intention to participate in crowdfunding through social identification with the crowdfunding community.

This study analyzes a general audience of potential crowdfunders; therefore, the results identify just the indications for potential intentions to participate in crowdfunding activities.

Companies or fund-seekers currently using or expecting to use crowdfunding have to develop strategies focused on promoting social identification with the crowdfunding community. More effort should be devoted for developing consumers’ social relationships and ties within the crowdfunding community.

This study contributes to the literature by clarifying the characteristics that potential crowdfunders should have to be more prone to participate in these types of projects.

El crowdfunding se ha convertido en un medio popular y factible de financiar proyectos en todo el mundo. El objetivo principal de este estudio es determinar qué características personales y sociales pueden aumentar la intención de los individuos de participar en el crowdfunding.

Esta investigación examina la capacidad de innovación, las actitudes hacia ayudar a los demás y la conectividad interpersonal como determinantes de la intención de los consumidores de participar en el crowdfunding. La identificación social con la comunidad de crowdfunding se propone como un mediador en el modelo.

Los resultados muestran que tanto la identificación social con la comunidad de crowdfunding y la capacidad de innovación tienen un efecto positivo en la intención de participar en proyectos de crowdfunding. Además, las actitudes hacia ayudar a los demás y la conectividad interpersonal afectan indirectamente la intención de participar en el crowdfunding a través de la identificación social con la comunidad de crowdfunding.

Esta investigación analiza una audiencia general de posibles “crowdfunders”, por lo tanto, los resultados identificaron solo indicaciones de intenciones potenciales para participar en actividades de crowdfunding.

Las empresas o emprendedores que actualmente usan o esperan usar el crowdfunding como método de financiación, deben desarrollar estrategias enfocadas en promover la identificación social con la comunidad de crowdfunding; así como fomentar el desarrollo de las relaciones y las relaciones sociales de los consumidores dentro de la comunidad de crowdfunding.

Esta investigación contribuye a la literatura explicando las características sociales y personales de los individuos que con más propensión participarían en este tipo de proyectos.

This study explores whether religion plays an important role in corporate poverty alleviation. Religious atmosphere affects managers' attitude towards corporate social responsibility (CSR) and then influences corporate poverty alleviation. This study first examines the impact of religious atmosphere on corporate poverty alleviation and then investigates whether formal institutions, such as law enforcement environments and ownership, influence the relationship between religious atmosphere and corporate poverty alleviation behavior.

In 2016, the Chinese government initiated a nationwide campaign aiming to eliminate poverty in China by 2020. The authors conduct empirical tests with data on Chinese listed firms from 2016 to 2020. The religious atmosphere is measured by the number of Buddhist monasteries and Taoist temples within a certain radius around Chinese listed firms' registered addresses. The authors adopt the ordinary least squares (OLS) method for regression and take the two-stage least squares (2SLS) method to address the endogeneity issue.

The results show a positive relationship between religious atmosphere and corporate poverty alleviation donations. Law enforcement attenuates the positive association between the religious atmosphere and corporate poverty alleviation donations. Religion and corporate poverty alleviation donations have a more positive association for non-state-owned enterprises (non-SOEs) than for state-owned enterprises (SOEs).

The authors' findings have important implications. First, this study inspires incorporating the ethical value of traditional culture, such as religion, into CSR. Second, the findings imply that informal institutions have a greater impact on corporate decision-making when formal institutions are weak, suggesting that informal institutions should be emphasized when promoting CSR in countries where formal institutions are relatively weak. The study investigates only religious influence on corporate poverty alleviation based on Buddhism and Taoism, but the authors do not examine the impacts of other religions. Future research may examine the relationships between other religions and corporate poverty alleviation in China.

This study illustrates the positive role played by religion in promoting CSR by relating religious atmosphere to corporate poverty alleviation. It fills the research gap between religion and CSR and also contributes to the literature on determinants of corporate poverty alleviation.