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Issue title: Artificial Intelligent Techniques and its Applications
Guest editors: Mahalingam Sundhararajan, Xiao-Zhi Gao and Hamed Vahdat Nejad
Article type: Research Article
Authors: Ma, Chuanhui | Ruan, Yongping | Zheng, Kai; *
Affiliations: School of Business, East China University of Science and Technology, Shanghai, China
Correspondence: [*] Corresponding author. Kai Zheng, School of Business, East China University of Science and Technology, Shanghai, China. E-mail: [email protected].
Abstract: Enterprise operating liabilities refers to the debt involved in sale of goods or services; they are one of the most important external financing resources for enterprises. Based on the theory of industry economics and corporate finance, using data of A-share listed companies from year 2000 to 2014, this paper discusses two mechanisms product market competition and enterprise asset strategy, and their influence on enterprise operating liabilities. It finds out that, when the product market competition is fiercer, the operating liabilities are more; when the enterprise implements “heavy” assets strategy, the operating liabilities are more; when the enterprise is in the fierce market competition, and the heavy-asset enterprise’s operating liabilities become lower. The further research tests the relationship and the changing speed of the operating liabilities and financial liabilities of firms, by contrast, it finds out the financial liabilities have totally different features and characteristics from operating liabilities. With panel data, hybrid recommender systems method using for reference to our model design, thus, this paper starts from an innovative research perspective, and the research findings have broadened and enriched the strategic theory research, and have some kind of practical significance to the enterprise financing decision in practice for them to achieve the maximum value of enterprises.
Keywords: Product market competition, enterprise asset strategy, operating liabilities
DOI: 10.3233/JIFS-169397
Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 2, pp. 1033-1043, 2018
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