Top Executives Cognition and Corporate Innovation Investment: The Moderating Role of Environmental Factors

Author(s):  
Shouming Chen ◽  
Binqi Tang
2017 ◽  
Vol 60 (5) ◽  
pp. 1915-1931 ◽  
Author(s):  
Amy Y. Ou ◽  
Jungmin (Jamie) Seo ◽  
Dongwon Choi ◽  
Peter W. Hom

2021 ◽  
Vol 13 (16) ◽  
pp. 9477
Author(s):  
Amjad Hussain ◽  
Mohsin Jamil ◽  
Muhammad Umar Farooq ◽  
Muhammad Asim ◽  
Muhammad Zeeshan Rafique ◽  
...  

Successful project completion is a challenging phenomenon for project managers. Various factors play an indispensable role in the success of a project. The objective of this study is to examine the role of project managers’ personalities in project success with the moderating role of external environmental factors i.e., political, economic, social. The study includes 145 project managers from 36 large-scale construction projects, from both the public and private sectors. The big five personality model was used to evaluate the personality traits of project managers and triple constraint criteria (cost, time, and quality) was used to gauge project success. Data has been collected through a well-structured questionnaire. The analysis of data indicated that personality traits like extraversion and openness are positive predictors of project success, whereas conscientiousness, agreeableness, and neuroticism did not have any direct relationship with project success. Importantly, the findings of this study concluded that external environmental factors—like political, economic, and social—moderately influence the link of specific project managers’ personality traits to project success. The role of external environmental factors as moderators has been discussed. The findings indicate the essential personality traits, as well as the role of external factors for achieving project success. The research contributions have relevance to both theory and practice and provide a deeper insight that is useful for individuals, organizations, researchers, practitioners, and decision-makers.


Author(s):  
Hang Wu ◽  
Yiying Qu

Carrying out green innovation is beneficial for firms to cope with environmental protection pressure and achieve sustainable development. Existing research has paid enough attention to the driver of green innovation, but still does not reveal how green innovation can be conceived and realized. This paper answers the above question from the perspective of international M&As, examines the relationship between exploratory international M&As, exploitative international M&As and green innovation performance, and further probes into how strategic and environmental factors moderate the green innovation effectiveness of exploratory and exploitative M&As. Results indicate that exploratory and exploitative international M&As both are beneficial for green innovation performance, and to maximize green innovation performance, implementing exploratory M&As is more beneficial for firms pursuing high green image and operating in a high green subsidy environment. By contrast, carrying out exploitative M&As is more effective for firms pursuing low green image and operating in a low green subsidy environment. Theoretical and managerial implications are discussed.


The purpose of this research is to conduct a comparative study between Asean and European countries to find out the level of public company’s ability to utilize big data. The research also aims to determine the role that organisational culture plays in the adoption of Big Data technologies. A survey in the form of questionnaire will be distributed through random sampling. Data will be collected from both Asean and EU countries. Smart PLS will be used to test the hypothesis. Recommendations will be made to the Asean and EU government about the policies and strategies to implement so as to encourage more public organisation to adopt Big Data so as to increase their competitiveness and survival rate based on the result of the hypothesis.


2020 ◽  
Vol 11 (2) ◽  
pp. 85-91 ◽  
Author(s):  
Jin-Fang Tian ◽  
Chao Pan ◽  
Rui Xue ◽  
Xiao-Tong Yang ◽  
Chen Wang ◽  
...  

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