TY - GEN
T1 - IDENTIFYING AN OPTIMAL ECOSYSTEM MODEL OF REFUGEE-RELATED BUSINESSES VIA AN ONLINE SYSTEMS-BASED EVOLUTIONARY LEARNING LABORATORY
T2 - 65th Annual Meeting of the International Society for the Systems Sciences, ISSS 2021
AU - Nakamura, Eri
AU - Yasui, Toshiyuki
AU - Kusano, Koki
AU - Kohtake, Naohiko
AU - Shirasaka, Seiko
N1 - Funding Information:
The authors would like to express their gratitude to the Refugee-Lens Investment Network (RIN) for their advice on this study and the team of Knowledge Management Network of Private Sector Development, Department of Economic Development, Japan International Cooperation Agency (JICA), and other JICA experts for their cooperation and valuable comments during the course of this research. This work was also supported by the “Sumitomo Life Child Raising Project.”
Publisher Copyright:
© ISSS 2021. All right reserved.
PY - 2021
Y1 - 2021
N2 - The number of refugees in the world peaked at 26.3 million as of mid-2020. More than 75 percent of these refugees are in a protracted situation, one in which refugees find themselves in a long-lasting and intractable state of limbo. However, the budget for refugee protection and care has not been sufficient for years. Due to the limited humanitarian and developmental budget, the role of refugee-related businesses is gaining more attention. The aim of this study is to show the feasibility of the partially online systems-based Evolutionary Learning Laboratory (ELLab) approach in the COVID-19 era via a case study of Uganda and to identify the current systems model of refugee-related businesses, their leverage points, and the action plans necessary for the development of an optimal systems model for refugee-related businesses. The authors suggested the efficacy of the online system-based ELLab and provided new ways for the application of the ELLab method in the COVID-19 era. They also managed to identify the current systems model of refugee-related businesses, their leverage points, and their action plans through the ELLab process.
AB - The number of refugees in the world peaked at 26.3 million as of mid-2020. More than 75 percent of these refugees are in a protracted situation, one in which refugees find themselves in a long-lasting and intractable state of limbo. However, the budget for refugee protection and care has not been sufficient for years. Due to the limited humanitarian and developmental budget, the role of refugee-related businesses is gaining more attention. The aim of this study is to show the feasibility of the partially online systems-based Evolutionary Learning Laboratory (ELLab) approach in the COVID-19 era via a case study of Uganda and to identify the current systems model of refugee-related businesses, their leverage points, and the action plans necessary for the development of an optimal systems model for refugee-related businesses. The authors suggested the efficacy of the online system-based ELLab and provided new ways for the application of the ELLab method in the COVID-19 era. They also managed to identify the current systems model of refugee-related businesses, their leverage points, and their action plans through the ELLab process.
KW - Evolutionary Learning Laboratory (ELLab)
KW - Uganda
KW - business
KW - online
KW - refugees
KW - systems thinking
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M3 - Conference contribution
AN - SCOPUS:85132901286
T3 - Proceedings of the 65th Annual Meeting of the International Society for the Systems Sciences, ISSS 2021 - The Art and Science of the Impossible: The Human Experience
BT - Proceedings of the 65th Annual Meeting of the International Society for the Systems Sciences, ISSS 2021 - The Art and Science of the Impossible
PB - International Society for the Systems Sciences (ISSS)
Y2 - 8 July 2021 through 13 July 2021
ER -
