Moral imagination and management decision-making: An empirical study

移情 利斯雷尔 社会学 道德推理 社会心理学 心理学 企业社会责任 公共关系 结构方程建模 政治学 计算机科学 机器学习
作者
Sobia Mahmood,Bakhtiar Ali
出处
期刊:African Journal of Business Management [Academic Journals]
卷期号:5 (4): 1466-1480 被引量:9
标识
DOI:10.5897/ajbm10.1083
摘要

Moral imagination is the mental ability to create or use ideas, images, discern moral aspects implanted within a situation and develop a range of possible solutions of the situation from a moral point of view. In this research, management decision makers were taken into consideration to dig out the factors that are affecting the decision-making process of management. Business industry has witnessed good and bad business leaders, those who have taken good moral decisions that result in mutual benefit to the company and wider society and those who have taken bad moral decisions that result in wider damage to the society, as well as to the business. Mostly, managers lack the ability to imagine a range of possible issues, consequences and solutions. So just because of their shorter insight and limited conceptual schema, they make wrong moral decisions which later give undesirable impacts to society and business as well. To analyse the complex relationship between the variables, Structure Equation Modelling (SEM) methodology was used. The data collected from 113 respondents in Pakistan were used to test the model by using LISREL 8.80. The model suggested that mutually beneficial decision-making is directly associated with moral imagination, whereas it is not mutually associated with demographic imagination; and on the other hand, moral imagination is significantly associated with empathy, dogmatism and egotism. However, mutual benefit is significantly associated with discerning moral issues and developing alternatives. Key words: Moral imagination, discerning moral issues, developing alternatives, mutual benefit, empathy, dogmatism, egotism, social corporate responsibility (CSR), non-government organization (NGO), structural equation modeling (SEM), goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), non-normed fit index (NNFI), root mean square residual (RMSR), comparative fit index (CFI), root mean square error of approximation (RMSEA).

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