Suchergebnisse

The study analyzed the interactive relationship between energy transformation and economic growth through the Ramsey model. The energy factor was introduced as an independent factor into the Ramsey model and an application improvement design was carried out. From a micro perspective, the impact of energy and economic factors on net output was analyzed. The research results indicate that the estimated coefficients of fossil energy output elasticity, labor output elasticity, capital output elasticity, and renewable energy output elasticity are 0.740602, 0.708407, 0.454672, and 0.304065, respectively. In addition, the significance tests were all below 0.05, indicating significance. Meanwhile, the elasticity of capital output and labor output complement each other; The output elasticity of fossil fuels and renewable energy are also complementary to each other. In a complementary relationship, the downward trend of one element is often accompanied by the upward trend of another element. This study sorts out the interactive relationship between energy transformation and economic growth, pointing out the direction for the future development of China's energy economy.

I conducted an online survey with 356 WeChat Official Account users to explore how user donation intention was affected by antecedents related to the charitable and consumptive attributes of their donation. I used structural equation modeling and hierarchical regression analysis to
test the hypotheses, and found that the antecedents of emotional attachment (related to the charitable attribute) and perceived fairness (related to the consumptive attribute) were positively related to user donation intention. In addition, identification and interaction were positively related
to emotional attachment, WeChat Official Account article value and other users' donation behavior were positively related to perceived fairness, and impulse buying tendency strengthened (vs. weakened) the positive relationship between emotional attachment (vs. perceived fairness) and user
donation intention. Theoretical and practical implications are discussed.

Social media greatly enables people to participate in online activities and shatters the barrier for online users to create and share information at any place at any time. However, the explosion of user-generated content poses novel challenges for online users to find relevant information, or, in other words, exacerbates the information overload problem. On the other hand, the quality of user-generated content can vary dramatically from excellence to abuse or spam, resulting in a problem of information credibility. The study and understanding of trust can lead to an effective approach to addressing both information overload and credibility problems. Trust refers to a relationship between a trustor (the subject that trusts a target entity) and a trustee (the entity that is trusted). In the context of social media, trust provides evidence about with whom we can trust to share information and from whom we can accept information without additional verification. With trust, we make the mental shortcut by directly seeking information from trustees or trusted entities, which serves a two-fold purpose: without being overwhelmed by excessive information (i.e., mitigated information overload) and with credible information due to the trust placed on the information provider (i.e., increased information credibility). Therefore, trust is crucial in helping social media users collect relevant and reliable information, and trust in social media is a research topic of increasing importance and of practical significance. This book takes a computational perspective to offer an overview of characteristics and elements of trust and illuminate a wide range of computational tasks of trust. It introduces basic concepts, deliberates challenges and opportunities, reviews state-of-the-art algorithms, and elaborates effective evaluation methods in the trust study. In particular, we illustrate properties and representation models of trust, elucidate trust prediction with representative algorithms, and demonstrate real-world applications where trust is explicitly used. As a new dimension of the trust study, we discuss the concept of distrust and its roles in trust computing

AbstractResearch Question/IssueRelying on enhanced market power and improved information environment associated with institutional cross‐ownership, this paper examines the relation between institutional cross‐ownership and trade credit in China.Research Findings/InsightsListed firms with cross‐ownership can obtain more trade credit. The main conclusion is robust when we consider endogeneity problems, alternative measures of institutional cross‐ownership, and the effect of a financial crisis. Further, we perform several tests to examine the influencing mechanisms, confirming that the positive relation between institutional cross‐ownership and trade credit is more pronounced for listed firms in more competitive industries, or with poorer information environment. Further analysis also finds that the positive effect of institutional cross‐ownership on trade credit is more prominent for listed firms with fewer bank loans.Theoretical/Academic ImplicationsThis paper emphasizes information sharing and cooperation among listed firms with institutional cross‐ownership and argues that the information improvement effect is a relatively more important mechanism in affecting listed firms' decisions.Practitioner/Policy ImplicationsChina's market‐oriented reform is in progress and shows some weaknesses in corporate governance and investor protection. The research focusing on institutional cross‐ownership can provide useful suggestions for policy makers on how to improve corporate governance and construct efficient capital markets.

Rapid development of e-commerce and mobile communication opens a new era of big data. In this article, the authors put big data and e-commerce security together. They construct electronic commerce security system from these aspects: the creation of database, the security of information storage, the mining of information based on big data environment thoroughly. The second-generation product distributed platform- Apache Hadoop which is more popular and instant has been brought in. what's more, this article expounds the structure and working process. On the base of this platform, this article analyses the certainty and security of e-commerce transactions data developed on the condition of big data. It puts forward a construction view that people should guide and monitor the behavior of e-commerce, and improve the security system of electronic commerce on the base of data.