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Competitor identification is an essential component of corporate strategy. With the rapid development of artificial intelligence, various data-mining methodologies and frameworks have emerged to identify competitors. In general, the competitiveness among companies is determined by both market commonality and resource similarity. However, because resource information is more difficult to obtain than market information, existing studies primarily identify competitors via market commonality. To address this limitation, we introduce multisource company descriptions as well as heterogeneous business relationships, and we propose a novel method for simultaneously mining themarket commonality and resource similarity. First, we use multisource company descriptions to represent companies and transform the heterogeneous business relationships into a heterogeneous business network. Then, we propose a novel multisource data fusion-based heterogeneous graph attention network (MHGAT) to learn the pairwise competitive relationships between companies. Specifically, a graph neural network-based model is proposed to learn the embeddings of companies by preserving their competition, and a multilevel attention framework is designed to integrate the embeddings from neighboring company level, heterogeneous relationship level, and multisource description level. Finally, experiments on a real-world dataset verify the effectiveness of our proposed MHGAT and demonstrate the usefulness of company descriptions and business relationships in competitor identification [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyze the relationship between the visual landscape and soundscape factors of the public spaces in old residential areas and their attention restoration benefits for residents and to determine the main influencing factors. In this paper, the public spaces of six typical old residential areas in Tianjin were selected as the research object, and the restorative benefits of the respondents were analyzed through virtual reality environment, subjective evaluation, and attention testing methods. The results showed that the attention restoration benefits of the central square in the old residential area were better than those of the public space along the street. Second, greenery satisfaction, environmental cleanliness, architectural aesthetics, sky visibility, and soundscape evaluation are all significantly positively correlated with the attention restoration level. Finally, a "visual landscape and soundscape perception evaluation--attention restoration level" structural equation model was constructed. According to the model, both the visual landscape factors and soundscape evaluation factors in old residential areas had a direct positive impact on the attention restoration level, with a greater impact exerted by visual landscape factors than by soundscape evaluation factors. The findings from this study can provide significant information for the renewal of old residential areas. [ABSTRACT FROM AUTHOR]

In this article, we consider time-series, ordinary least-squares, and instrumental-variable regressions and introduce a new pair of commands, har and hart, that implement more accurate heteroskedasticity- and autocorrelationrobust (HAR) F and t tests. These tests represent part of the recent progress on HAR inference. The F and t tests are based on the convenient F and t approximations and are more accurate than the conventional chi-squared and normal approximations. The underlying smoothing parameters are selected to target the type I and type II errors, which are the two fundamental objects in every hypothesis testing problem. The estimation command har and the postestimation test command hart allow for both kernel HAR variance estimators and orthonormalseries HAR variance estimators. In addition, we introduce another pair of new commands, gmmhar and gmmhart, that implement the recently developed F and t tests in a two-step generalized method of moments framework. For these commands, we opt for the orthonormal-series HAR variance estimator based on the Fourier bases because it allows us to develop convenient F and t approximations as in the first-step generalized method of moments framework. Finally, we present several examples to demonstrate these commands. [ABSTRACT FROM AUTHOR]

The article concentrates on the criticism of the Chinese Qing dynasty's national anthem's musical score made by a prominent court musician, Cao Xinquan. The traditional Confucian view of music based upon principles expounded in the "Book of Rites" is quite familiar to Cao. The anthem, he argued, ignored those principles and hastened the demise of the dynasty.