corporate annual reports
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2021 ◽  
Vol 275 ◽  
pp. 01043
Author(s):  
Chi Zhang ◽  
Zhixin Liu ◽  
Lei Lv

This article investigates the extent to which inflation perceptions affect firms’ innovation input and investment expenditure. We adopt dummy variables data to quantify the firm inflation perceptions of China’s listed manufacturing companies from corporate annual reports during the period from 2008–2018. Results reveal that inflation perceptions have a positive Tobin effect on investment spending decisions of the firms whose inflation perceive risen, vice versa. Besides, the investment expenditure of large manufacturing/ SOEs enterprises are more sensitive than small/non-SOEs firms when inflation perceptions have risen, and small/non-SOEs companies tend to reduce much more investment spending when inflation perceptions decline. Our results have significant implications for policymakers and firm managers.


2021 ◽  
Vol 9 (3) ◽  
pp. 189-204
Author(s):  
Michael Adelowotan ◽  

This paper presents evidence from a user of a computer-assisted qualitative data analysis software (CAQDAS) referred to as ATLAS.ti on its usefulness and challenges in the content analysis of corporate annual reports (CARs) of top South African companies. The paper illustrates how ATLAS.ti was employed to perform the content analysis of 60 corporate annual reports to determine the extent of human capital disclosures by the top South African companies. Useful reports generated from the “hermeneutic unit” known as “AdePhD” include the primary document list, the code list, the code families, the code summary, the code-primary document list, the codequotation list, and the network views. The reports from this qualitative analysis software facilitated the observations on the frequency of ninety-one human capital disclosure items analyzed from the corporate annual reports of companies in our sample. Findings indicate that the use of ATLAS.ti enabled a faster and robust analysis that would have taken a much longer time if done manually. It also facilitated more coherent results. Nevertheless, the major challenge is the lack of adequate institutional support for users when compared with the level of institutional support available for quantitative data analysis software such as the Statistical Package for the Social Sciences (SPSS).


2020 ◽  
Vol 5 (4) ◽  
pp. 599-613
Author(s):  
Ranny Sharah ◽  
Musfiari Haridhi

This study aims to see differences in the implementation of Good Corporate Governance in Bank Aceh Syariah before and after cut off. The type of this study is descriptive qualitative. The object of this study is Good Corporate Governance Bank Aceh Syariah. The type of data is secondary data as corporate annual reports of 2014-2017. The results of this study show that there was no significant difference in the implementation of Good Corporate Governance in Bank Aceh Syariah for the year of this research. The mechanism and tools for the effective implementation  of  Good  Corporate  Governance  are  relatively  the  same.  There  was  additional  organizational structure after cut off in the implementation of Good Corporate Governance with the establishment of a Sharia Supervisory Board, tasked with overseeing the business activities of the bank to fit the Fatwa of The National Sharia Council


2020 ◽  
Vol 26 (6) ◽  
pp. 1422-1443
Author(s):  
Renáta Myšková ◽  
Petr Hájek

Models that predict corporate financial risk are important early-warning systems for corporate stakeholders. Most models to date have been developed using financial indicators. However, in financial decision-making, increasing attention is being paid to the role of textual information, which may provide additional insight into managerial opinions and intentions and which has recently been used to more effectively predict corporate financial performance. Previous approaches in this regard have predominantly focused on sentiment analysis of managerial communication. However, the role of context-related sentiment remains poorly understood in the financial risk domain. Here, we investigate how risk-related sentiment in verbal managerial communication might predict corporate financial performance, including indebtedness, profitability, market value and bankruptcy risk. To ensure deductive content validity, we propose specific word lists for each type of corporate financial risk and assign each word with positive / negative labels. Our findings provide evidence for a major role of risk-related sentiment as an indicator of corporate performance in terms of financial risks. Notably, using novel risk-related word lists in regression models, we show that a proactive and opportunity-seeking risk management has a significantly positive impact on financial performance, implying that stakeholders should carefully consider the risk-related managerial communication in corporate annual reports.


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