by Lieve E. H. van der Donk, Marta Bermejo-Jambrina, John L. van Hamme, Mette M. W. Volkers, Ad C. van Nuenen, Neeltje A. Kootstra, Teunis B. H. Geijtenbeek
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by Demóstenes Zegarra Rodríguez, Ogobuchi Daniel Okey, Siti Sarah Maidin, Ekikere Umoren Udo, João Henrique Kleinschmidt
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by Shanshan Yang, Xiaohan Li, Zhenhua Jiang, Man Xiao
Based on the data of the Chinese A-share listed firms in China Shanghai and Shenzhen Stock Exchange from 2014 to 2021, this article explores the relationship between common institutional investors and the quality of management earnings forecasts. The study used the multiple linear regression model and empirically found that common institutional investors positively impact the precision of earnings forecasts. This article also uses graph... Читать дальше...
by Zhongbao Tan, Jian Zhang, Lan Xu, Huanjing Wang, Xuequn Mao, Rong Zou, Qingqing Wang, Zhuang Han, Zhenhai Di, Daguang Wu
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by Wanbo Lu, Yifu Wang, Xingjian Zhang
Precise and real-time measurements of economic prosperity are vital to a country’s economic system. This study aims to identify news topics that promoted economic prosperity in China from 2011–2021. By extracting economic topics from news text data, we construct a news coincidence index with comprehensive information and strong timeliness and reveal the trend of topic contribution. The Latent Dirichlet Allocation (LDA) topic model is applied to extract economic topics from the news. Читать дальше...
by Yunzhe Li, Peng Dong, Weimin Ye
The Graphical Evaluation and Review Technique (GERT) and complex networks are used to simulate and analyse complex product supply chain networks based on the characteristics of complex product supply chain networks. And the traditional GERT is improved by constructing a grey parametric GERT network with restricted output results, taking into account the fact that the duration, product quality and product cost of each supplier in a complex product supply... Читать дальше...
by Yu-Hua Yeh, Allison N. Tegge, Roberta Freitas-Lemos, Joel Myerson, Leonard Green, Warren K. Bickel
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by Juan Liu, Sha Mi
Driven by internet technology, online has become the main way of news dissemination, but redundant information such as navigation bars and advertisements affects people’s access to news content. The research aims to enable users to obtain pure news content from redundant web information. Firstly, based on the narrative characteristics of literary news, the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm is employed to extract pure news content from the analyzed web pages. Читать дальше...
by Fangjian Shang, Xiaodan Liu, Xin Ren, Yanlin Li, Lei Cai, Yujia Sun, Jian Wen, Xiaodan Zhai
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by Hid Felizardo Cordero-Franco, Ana María Salinas-Martínez, María José Esparza-Contró, Sofía Denisse González-Rueda, Francisco Javier Guzmán-de la Garza
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by Yue Tan, Chunxiang Guo
The rise of retail groups has strengthened their voice in the supply chain, drawing more attention from supply chain members to the issue of profit fairness. To explore the influence of fairness concerns on operational decisions in closed-loop supply chains after the formation of retail groups. In this paper, we first construct a secondary dual-channel closed-loop supply chain led by a retail group and followed by a manufacturer. Next, the corresponding game models are constructed under three scenarios... Читать дальше...
by Alex Barreto de Lima, Ana Torres-Costoso, Vera Zymbal, Élvio Rúbio Gouveia, Fátima Baptista
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by Faisal Mehmood, Hamed Mahzoon, Yuichiro Yoshikawa, Hiroshi Ishiguro
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by Rose M. Caston, Elliot H. Smith, Tyler S. Davis, Hargunbir Singh, Shervin Rahimpour, John D. Rolston
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by Linda Grüßer, Charlotte Eißing, Ana Kowark, András P. Keszei, Julia Wallqvist, Rolf Rossaint, Sebastian Ziemann
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by Farihah Ali, Cayley Russell, Ashima Kaura, Peter Leslie, Ahmed M. Bayoumi, Shaun Hopkins, Samantha Wells
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by Eniola Olubukola Cadmus, Lawrence Adekunle Adebusoye, Eme Theodora Owoaje
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by Zhonghao Lei, Dongmei Wang
Digital transformation plays a crucial role in improving the quality development of companies in this era of digital economy with ever-changing technologies. This paper empirically investigates the impact of corporate digital transformation on total factor productivity and the mechanism of action, using A-share listed companies in Shanghai and Shenzhen from 2011–2021 as the research sample, and found that the digital transformation of companies significantly improves total factor productivity... Читать дальше...
by Probir Kumar Ghosh, Md. Golam Dostogir Harun, Ireen Sultana Shanta, Ausraful Islam, Kaniz Khatun E. Jannat, Haider Mannan
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by Rengul Cetin-Atalay, Angelo Y. Meliton, Cevher Ozcan, Parker S. Woods, Kaitlyn A. Sun, Yun Fang, Robert B. Hamanaka, Gökhan M. Mutlu
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by Hoang Nam Pham, Linh Pham, Keisaku Sato
Primary biliary cholangitis (PBC) is an autoimmune disorder characterized by intrahepatic bile duct destruction and cholestatic liver injury. Diagnosis of PBC is generally based on the existence of anti-mitochondrial antibody (AMA) in blood samples; however, some PBC patients are negative for serum AMA tests, and invasive liver histological testing is required in rare PBC cases. The current study seeks novel candidate genes that are associated with... Читать дальше...
by Weimin Xiang, Yeqiang Lan, Qiao Qi, Lei Gan
The development of green finance and the promotion of green transformation and upgrading of high energy-consuming enterprises are of great significance for China to achieve the "double carbon" goal. This paper employs a dual fixed-effects model to examine the profound ramifications and intrinsic mechanisms of green finance development on the transformative innovation of high-energy-consumption enterprises, using a sample of 462 publicly traded... Читать дальше...
by Attiya Kalair, Matilde Pavan, Naomi Alpert, Saghi Ghaffari, Emanuela Taioli
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by Ashmita Karki, Corneel Vandelanotte, Saman Khalesi, Padam Dahal, Lal B. Rawal
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by Daiki Suzuki, Sho Tsugawa, Keiichiro Tsukamoto, Shintaro Igari
Analyzing the dynamics of information diffusion cascades and accurately predicting their behavior holds significant importance in various applications. In this paper, we concentrate specifically on a recently introduced contrastive cascade graph learning framework, for the task of predicting cascade popularity. This framework follows a pre-training and fine-tuning paradigm to address cascade prediction tasks. In a previous study... Читать дальше...