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When Does Prosocial Motivation Deliver? A Dual-Motivations Approach to Social Enterprise Outcomes.

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Title: When Does Prosocial Motivation Deliver? A Dual-Motivations Approach to Social Enterprise Outcomes.
Authors: Au, Kevin1 (AUTHOR), Jeong, Sophia Soyoung2 (AUTHOR), Hsu, Anna J. C.3 (AUTHOR), Xiao, Yingzhao4 (AUTHOR) yingzhao@tju.edu.cn
Source: Journal of Business Ethics. Aug2024, Vol. 193 Issue 1, p159-178. 20p.
Subject Terms: *Motivation (Psychology), *Extrinsic motivation, *Intrinsic motivation, Prosocial behavior, Social enterprises, Business ethics
Abstract: Scholars and leaders have assumed that prosocial motivation is the primary driver for social enterprises (SEs) to do good. Despite the significance of prosocial motivation, we argue that it may not be the single driver for SE motivation. A dual-motivations approach based on insights from motivation research is proposed to examine how different types of SE motivation can act together to influence the outcomes of SEs. Empirical findings based on survey data from Hong Kong demonstrate that dual motivations—prosocial-intrinsic and prosocial-extrinsic motivations—explain the outcomes of SEs beyond what the direct effects of prosocial motivation can explain separately. Based on moderation analyses, intrinsic motivation enhances the positive relationships between prosocial motivation and business and social outcomes, whereas extrinsic motivation undermines the relationship related to business outcomes. Implications for research on social entrepreneurship and business ethics are discussed. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Business Ethics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: When Does Prosocial Motivation Deliver? A Dual-Motivations Approach to Social Enterprise Outcomes.
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  Data: *<searchLink fieldCode="DE" term="%22Motivation+%28Psychology%29%22">Motivation (Psychology)</searchLink><br />*<searchLink fieldCode="DE" term="%22Extrinsic+motivation%22">Extrinsic motivation</searchLink><br />*<searchLink fieldCode="DE" term="%22Intrinsic+motivation%22">Intrinsic motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Prosocial+behavior%22">Prosocial behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Social+enterprises%22">Social enterprises</searchLink><br /><searchLink fieldCode="DE" term="%22Business+ethics%22">Business ethics</searchLink>
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  Data: Scholars and leaders have assumed that prosocial motivation is the primary driver for social enterprises (SEs) to do good. Despite the significance of prosocial motivation, we argue that it may not be the single driver for SE motivation. A dual-motivations approach based on insights from motivation research is proposed to examine how different types of SE motivation can act together to influence the outcomes of SEs. Empirical findings based on survey data from Hong Kong demonstrate that dual motivations—prosocial-intrinsic and prosocial-extrinsic motivations—explain the outcomes of SEs beyond what the direct effects of prosocial motivation can explain separately. Based on moderation analyses, intrinsic motivation enhances the positive relationships between prosocial motivation and business and social outcomes, whereas extrinsic motivation undermines the relationship related to business outcomes. Implications for research on social entrepreneurship and business ethics are discussed. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Business Ethics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10551-023-05452-7
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        Text: English
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              Text: Aug2024
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