To study how the collocational networks method could be used to analyze textual contents in listed companies' annual reports written in Chinese, in an attempt to identify hidden…
Abstract
Purpose
To study how the collocational networks method could be used to analyze textual contents in listed companies' annual reports written in Chinese, in an attempt to identify hidden facts that are not released in a listed company's financial statements.
Design/methodology/approach
This research extended the collocation network analysis method from English textual contents to Chinese textual contents. The extended collocation network method was used to analyze an Information Technology company, Clever, listed in Shanghai stock exchange of China.
Findings
Using the extended collocational networks method, some hidden facts about a Chinese listed company's financial status could be identified, which were not reported in company's officially released financial statements.
Practical implications
The extended collocation network method may supplement the commonly practiced fundamental financial analysis method in helping investors have a better understanding about the financial soundness of listed companies. This is especially important to investors in stock markets of some developing countries, including China. In addition, this method may help regulators of stock market, especially in developing countries, to identify possible loopholes of existing financial regulations as well as some inappropriate practices of some listed companies in disclosing misleading or incorrect financial data in their financial statements.
Originality/value
The first study using the collocational networks method to analyze annual reports of Chinese corporations listed in Shanghai stock exchange, a newly established stock market.
Details
Keywords
Yong Ye and Yuanqin Ge
The research mainly aims at the hotspot of inventory management by knowledge mapping and provides a visualization reference in this research field.
Abstract
Purpose
The research mainly aims at the hotspot of inventory management by knowledge mapping and provides a visualization reference in this research field.
Design/methodology/approach
First, inventory management journals during 1986 to 2017 were selected as the research object and text formatting in the Web of Science (WOS) database is exported. Then inventory management knowledge mapping is done and clustering keywords are extracted by using CiteSpace and VOSviewer software. Based on co-word analysis, the three special clusters are exported: inventory optimization strategy, inventory pricing and inventory technology. Besides, the clustering structure and time evolution are analysed. Finally, bibliographic item co-occurrence matrix builder (BICOMB) was used to extract the “journal” and “researchers” keywords in the inventory management research fields. Setting three parameters such as the cited half-life, centrality, frequency and keywords for data mining, it can infer the trend keywords of future research.
Findings
Results showed that inventory management research has been abundant in literature over the past 30 years and has experienced a change from focusing on inventory optimization strategy to inventory pricing and inventory technology in process. It shows that inventory management research focused on the classic topics and includes economic order quantity, dynamic pricing, design and technology, and the new topics include channel coordination, hierarchical price and simulation.
Research limitations/implications
Based on knowledge mapping, this study is still relatively macro and cannot cover all areas of inventory management. This study only investigated the state of correlational research in WOS and Google Trends and not additional databases.
Originality/value
The current research mainly builds on knowledge mapping for the research hotspot of inventory management and provides visual references for future research in this field.