Empirical Analysis of the Impacts of Emission Trading from the Perspective of Firm Decision Making

2020 ◽  
Vol 11 (222) ◽  
pp. 539-546
Author(s):  
Youngduk Kim ◽  
Hyun-Ok Han
2021 ◽  
pp. 014920632110578
Author(s):  
Daisuke Uchida

In the face of increasing pressure to comply with institutional norms, firm managers may retreat from previous commitments to comply once they realize the challenges involved. This study examines how firms respond to institutional pressures in a particular way called reversion, in which an organization's managers temporarily comply when there are no consequences but resist when it is in their interest to resist. By integrating institutional and agency theories, we model the reversion decision as a tension between institutional constituents and organizational managers. An empirical analysis of a sample of Japanese firms that scheduled annual shareholder meetings during the 2001 through 2014 period was performed. Our findings show that although organizations’ susceptibility to certain institutional pressures determines initial organizational compliance, managers whose interests diverge from those of the institutional constituents can revert their decisions, especially when they have discretion in decision making to protect their own interests. These findings highlight the temporary nature of organizational responses to institutional pressures and help us understand how organizational agency can limit institutional control over an organization's actions.


Author(s):  
K. Abumani ◽  
R. Nedunchezhian

Data mining techniques have been widely used for extracting non-trivial information from massive amounts of data. They help in strategic decision-making as well as many more applications. However, data mining also has a few demerits apart from its usefulness. Sensitive information contained in the database may be brought out by the data mining tools. Different approaches are being utilized to hide the sensitive information. The proposed work in this article applies a novel method to access the generating transactions with minimum effort from the transactional database. It helps in reducing the time complexity of any hiding algorithm. The theoretical and empirical analysis of the algorithm shows that hiding of data using this proposed work performs association rule hiding quicker than other algorithms.


Sign in / Sign up

Export Citation Format

Share Document