Theorizing compassionate leadership from the case of Jacinda Ardern: Legitimacy, paradox and resource conservation
| Autor: | Ace V Simpson, Arménio Rego, Marco Berti, Stewart Clegg, Miguel Pina e Cunha |
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| Přispěvatelé: | Veritati - Repositório Institucional da Universidade Católica Portuguesa |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
leadership
paradox Sociology and Political Science makt Strategy and Management compassion legitimacy Ciências Sociais::Economia e Gestão [Domínio/Área Científica] legitimitet empati Power Compassion Paradoxes Paradox Conservation of resources Samfunnsvitenskap: 200::Psykologi: 260 [VDP] Conservation of resources theory Legitimacy Jacinda Ardern politiske ledere |
| Zdroj: | Leadership Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP |
| Popis: | Copyright © The Author(s) 2021. During times of suffering such as that inflicted by the COVID-19 pandemic, compassion expressed by leaders helps to ease distress. Doing so, those in a position to provide resources that might facilitate coping and recovery are attentive to the situations of distress. Despite an abundance of leadership theorizing and models, there still is little academic literature on compassionate leadership. To address this limitation, we present an exploratory case study of New Zealand Prime Minister Jacinda Ardern, someone widely recognized for her compassionate leadership and frequently described in paradoxical terms (e.g. ‘kind and strong’; embodying ‘steel and compassion’). We address her compassionate leadership through the lenses of paradox theory, legitimacy theory and conservation of resources theory. We contribute a heuristic framework that sees various types of legitimacy leveraged synergistically to build resources and alleviate suffering – providing further legitimacy in an upward spiral of compassionate leadership. Fundação para a Ciência e a Tecnologia (UID/ECO/00124/2019, UIDB/00124/2020 and Social Sciences DataLab, PINFRA/22209/2016); POR Lisboa and POR Norte (Social Sciences DataLab, PINFRA/22209/2016); Fundação para a Ciência e a Tecnologia (UID/GES/00731/2019, UID/GES/00315/2019). |
| Databáze: | OpenAIRE |
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