利用农场异质性提高生活收入:Côte科特迪瓦可可种植系统的性别敏感类型

Q1 Social Sciences
Franziska OLLENDORF , Claudia CORAL , Constant Yves ADOU YAO , Stefan SIEBER , Katharina LÖHR
{"title":"利用农场异质性提高生活收入:Côte科特迪瓦可可种植系统的性别敏感类型","authors":"Franziska OLLENDORF ,&nbsp;Claudia CORAL ,&nbsp;Constant Yves ADOU YAO ,&nbsp;Stefan SIEBER ,&nbsp;Katharina LÖHR","doi":"10.1016/j.regsus.2025.100245","DOIUrl":null,"url":null,"abstract":"<div><div>About 44% of the world’s cocoa is produced in one single country, Côte d’Ivoire. Providing this important raw material, most Ivorian cocoa farmers live in severe poverty, which, despite a multitude of sector interventions, is still widespread, affecting social and environmental sustainability in cocoa production. In this context, cocoa farmers are still often treated as a homogeneous group of small-scale producers (mainly males), resulting in interventions being conceptualized as one-size-fits-all approaches and failing to deliver support schemes that take farmers’ specific conditions appropriately into account. Applying a broader typology approach that combines farm characteristics with farmers’ characteristics, this study aims to delineate Ivorian cocoa farmers and their farms into specific types in order to improve advice for targeted sustainability interventions and living income (LI) potentials. Principal component analysis and hierarchical clustering analysis of a household dataset collected in 2022 in five cocoa-growing regions of Côte d’Ivoire were chosen to identify types of male-headed farms. To assure gender sensitive analysis, a female-headed farm type was created artificially. The specific characteristics of the identified types were captured using descriptive analysis. Descriptive statistics and non-parametric tests were then applied to examine the relationships between these farm types and various outcomes. Additionally, a binary logistic model was used to estimate the probability of these links in relation to variables relevant for achieving a LI. Finally, Spearman non-parametric correlation was used to identify eventual differences in the strength of relationships between key variables per farm type. Three different types of male-headed farms are identified: type 1 (the most productive and diversified farms with larger size), type 2 (middle-sized farms with strong focus on cash crops), and type 3 (small-sized farms with a good level of diversification for self-consumption). The artificially created type 4 represents female-headed farms with the smallest size. On average, none of these farm types achieves a LI. However, type 1 shows the smallest LI gap, while type 4 is by far the worst. Our analyses reveal underlying socio-economic factors systematically disadvantaging female-headed cocoa farms, most notably limited access to land and other material assets. The key contribution of this study lies in the empirical identification of the different characteristics of farms in a given farming system, thereby identifying the need for targeted support interventions. Type-specific recommendations are made, showing pathways to provide tailored programs to farmers of different types in order to reduce their LI gaps.</div></div>","PeriodicalId":34395,"journal":{"name":"Regional Sustainability","volume":"6 4","pages":"Article 100245"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Leveraging farm heterogeneity to enhance living incomes: A gender-sensitive typology of cocoa farming systems in Côte d’Ivoire\",\"authors\":\"Franziska OLLENDORF ,&nbsp;Claudia CORAL ,&nbsp;Constant Yves ADOU YAO ,&nbsp;Stefan SIEBER ,&nbsp;Katharina LÖHR\",\"doi\":\"10.1016/j.regsus.2025.100245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>About 44% of the world’s cocoa is produced in one single country, Côte d’Ivoire. Providing this important raw material, most Ivorian cocoa farmers live in severe poverty, which, despite a multitude of sector interventions, is still widespread, affecting social and environmental sustainability in cocoa production. In this context, cocoa farmers are still often treated as a homogeneous group of small-scale producers (mainly males), resulting in interventions being conceptualized as one-size-fits-all approaches and failing to deliver support schemes that take farmers’ specific conditions appropriately into account. Applying a broader typology approach that combines farm characteristics with farmers’ characteristics, this study aims to delineate Ivorian cocoa farmers and their farms into specific types in order to improve advice for targeted sustainability interventions and living income (LI) potentials. Principal component analysis and hierarchical clustering analysis of a household dataset collected in 2022 in five cocoa-growing regions of Côte d’Ivoire were chosen to identify types of male-headed farms. To assure gender sensitive analysis, a female-headed farm type was created artificially. The specific characteristics of the identified types were captured using descriptive analysis. Descriptive statistics and non-parametric tests were then applied to examine the relationships between these farm types and various outcomes. Additionally, a binary logistic model was used to estimate the probability of these links in relation to variables relevant for achieving a LI. Finally, Spearman non-parametric correlation was used to identify eventual differences in the strength of relationships between key variables per farm type. Three different types of male-headed farms are identified: type 1 (the most productive and diversified farms with larger size), type 2 (middle-sized farms with strong focus on cash crops), and type 3 (small-sized farms with a good level of diversification for self-consumption). The artificially created type 4 represents female-headed farms with the smallest size. On average, none of these farm types achieves a LI. However, type 1 shows the smallest LI gap, while type 4 is by far the worst. Our analyses reveal underlying socio-economic factors systematically disadvantaging female-headed cocoa farms, most notably limited access to land and other material assets. The key contribution of this study lies in the empirical identification of the different characteristics of farms in a given farming system, thereby identifying the need for targeted support interventions. Type-specific recommendations are made, showing pathways to provide tailored programs to farmers of different types in order to reduce their LI gaps.</div></div>\",\"PeriodicalId\":34395,\"journal\":{\"name\":\"Regional Sustainability\",\"volume\":\"6 4\",\"pages\":\"Article 100245\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Regional Sustainability\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666660X25000532\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Regional Sustainability","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666660X25000532","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0

摘要

世界上大约44%的可可产自一个国家,Côte科特迪瓦。提供这种重要的原料,大多数科特迪瓦可可农民生活在严重贫困中,尽管许多部门进行了干预,但这种贫困仍然普遍存在,影响了可可生产的社会和环境可持续性。在这种情况下,可可种植者仍然经常被视为同质的小规模生产者群体(主要是男性),导致干预措施被概念化为一刀切的方法,无法提供适当考虑到农民具体情况的支持计划。本研究采用将农场特征与农民特征相结合的更广泛的类型学方法,旨在将科特迪瓦可可农民及其农场划分为特定类型,以便为有针对性的可持续性干预措施和生活收入(LI)潜力提供改进建议。对2022年在Côte科特迪瓦五个可可种植区收集的家庭数据集进行主成分分析和分层聚类分析,以确定男性户主农场的类型。为了保证性别敏感的分析,人为地创造了一个女性为首的农场类型。使用描述性分析捕获已识别类型的具体特征。然后应用描述性统计和非参数检验来检查这些农场类型与各种结果之间的关系。此外,还使用二元逻辑模型来估计与实现LI相关的变量相关的这些链接的概率。最后,使用Spearman非参数相关性来确定每个农场类型的关键变量之间关系强度的最终差异。确定了三种不同类型的男性户主农场:类型1(规模较大、生产力最高和多样化的农场)、类型2(高度重视经济作物的中型农场)和类型3(自我消费多样化程度较高的小型农场)。人工创造的4型代表最小规模的女性户主农场。平均而言,这些农场类型都没有达到LI。然而,类型1显示出最小的LI差距,而类型4是迄今为止最糟糕的。我们的分析揭示了潜在的社会经济因素系统性地对女性领导的可可农场不利,最明显的是土地和其他物质资产的有限获取。本研究的关键贡献在于对特定农业系统中农场的不同特征进行实证识别,从而确定有针对性的支持干预措施的必要性。提出了针对不同类型的建议,为不同类型的农民提供量身定制的方案,以缩小他们的LI差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging farm heterogeneity to enhance living incomes: A gender-sensitive typology of cocoa farming systems in Côte d’Ivoire
About 44% of the world’s cocoa is produced in one single country, Côte d’Ivoire. Providing this important raw material, most Ivorian cocoa farmers live in severe poverty, which, despite a multitude of sector interventions, is still widespread, affecting social and environmental sustainability in cocoa production. In this context, cocoa farmers are still often treated as a homogeneous group of small-scale producers (mainly males), resulting in interventions being conceptualized as one-size-fits-all approaches and failing to deliver support schemes that take farmers’ specific conditions appropriately into account. Applying a broader typology approach that combines farm characteristics with farmers’ characteristics, this study aims to delineate Ivorian cocoa farmers and their farms into specific types in order to improve advice for targeted sustainability interventions and living income (LI) potentials. Principal component analysis and hierarchical clustering analysis of a household dataset collected in 2022 in five cocoa-growing regions of Côte d’Ivoire were chosen to identify types of male-headed farms. To assure gender sensitive analysis, a female-headed farm type was created artificially. The specific characteristics of the identified types were captured using descriptive analysis. Descriptive statistics and non-parametric tests were then applied to examine the relationships between these farm types and various outcomes. Additionally, a binary logistic model was used to estimate the probability of these links in relation to variables relevant for achieving a LI. Finally, Spearman non-parametric correlation was used to identify eventual differences in the strength of relationships between key variables per farm type. Three different types of male-headed farms are identified: type 1 (the most productive and diversified farms with larger size), type 2 (middle-sized farms with strong focus on cash crops), and type 3 (small-sized farms with a good level of diversification for self-consumption). The artificially created type 4 represents female-headed farms with the smallest size. On average, none of these farm types achieves a LI. However, type 1 shows the smallest LI gap, while type 4 is by far the worst. Our analyses reveal underlying socio-economic factors systematically disadvantaging female-headed cocoa farms, most notably limited access to land and other material assets. The key contribution of this study lies in the empirical identification of the different characteristics of farms in a given farming system, thereby identifying the need for targeted support interventions. Type-specific recommendations are made, showing pathways to provide tailored programs to farmers of different types in order to reduce their LI gaps.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Regional Sustainability
Regional Sustainability Social Sciences-Urban Studies
CiteScore
3.70
自引率
0.00%
发文量
20
审稿时长
21 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信