Mitigating Managerial Behavioral Biases through Smart Technologies: Implications for Organizational Sustainability and Green Growth

Abstract

The inability of the organization to achieve its sustainability and green growth objectives is 
attributed to the fact that managers make decisions based on behavioral biases. The process is 
caused by the biases that contain overconfidence, anchoring and herd behavior, and loss aversion, 
leading to resource allocation problems and sustainable innovation challenges and short-term 
orientation problems. Smart technologies that comprise artificial intelligence (AI) and big data 
analytics and digital decision-support systems offer organizations with a new approach to improve 
the decision-making process by offering more rationality and transparency. The research question 
is examined in terms of the way smart technologies operate to decrease managerial behavioral 
biases that subsequently lead to the benefits of organizational sustainability and green growth. The 
research team gathered survey data of managers in manufacturing and service industries in an 
emerging economy in order to test their connections using the structural equation modeling (SEM). 
With smart technologies, organizations can reduce the amount of managerial behavioral biases that 
will lead to better organizational sustainability and green growth. The research paper adds to the 
literature on administrative sciences and behavioral management by combining both behavioral 
bias theory and the use of smart technologies that provide practical recommendations to managers 
and policymakers.