Journal articles: 'Family farms'

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Klapoushchak, D. S., and Yu M. Pavliuchenko. "FARMS AND FAMILY FARMS: A COMPARATIVE ANALYSIS." Juridical scientific and electronic journal, no. 5 (2024): 255–57. http://dx.doi.org/10.32782/2524-0374/2024-5/61.

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Möllers, Judith, and Jana Fritzsch. "Individual farm exit decisions in Croatian family farms." Post-Communist Economies 22, no. 1 (March 2010): 119–28. http://dx.doi.org/10.1080/14631370903525645.

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Kostlivý, Vladimír, Zuzana Fuksová, and Tamara Rudinskaya. "Drivers of farm performance in Czech crop farms." Agricultural Economics (Zemědělská ekonomika) 66, No. 7 (July 21, 2020): 297–306. http://dx.doi.org/10.17221/231/2019-agricecon.

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When analysing drivers affecting the farm performance, the presence of different technologies should be taken into account. We assume that the technology used by crop farms is not the same for all producers and therefore we use latent class model to identify technological classes at first. Class definition is based on multidimensional classification and determination of indices given by the values of individual components. The principal components analysis is applied to estimate significant and robust weights for the index components. FADN (Farm Accountancy Data Network) database, Czech crop farms data from 2005 to 2017 were used and three groups of technology classes of farms were identified with a determinant influence of the structure index and localisation. The other indices characterise sustainability, innovation, technology, diversification, and individual characteristics. Three distinct classes of crop farms were found, one major class and two minor classes. Family driven farms are usually smaller farms in terms of acreage. Highly sustainable crop farms are most likely located in lower altitudes and not in less-favoured areas. Innovative farms are also likely to be more productive. The results indicate that agricultural production farms with a more sustainable way of farming are most likely to be more productive.

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SAVICKIENĖ, Jūratė, and Astrida MICEIKIENĖ. "Sustainable economic development assessment model for family farms." Agricultural Economics (Zemědělská ekonomika) 64, No. 12 (December 12, 2018): 527–35. http://dx.doi.org/10.17221/310/2017-agricecon.

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This article is aimed to address the issue of sustainable economic development assessment in family farms. A complex methodology of family farm sustainable economic development assessment based on the family farm sustainable economic development index has been created following analysis of family farm sustainable economic development assessment methodologies, which are proposed by scientists and used in practice. The Kruskal-Wallis test and hierarchical cluster analysis were used to check the relevance of the index in family farm sustainable economic development assessment. The index value range was calculated using descriptive statistics. The characteristics of the index allow creating models for family farm sustainable economic development classification types based on k-means clustering. The family farms were classified into nine types. Examples of Lithuanian family farms were provided to demonstrate practical applications of the index. Furthermore, analysis of Lithuanian family farm sustainable economic development types by specialisation enabled to identify the main reasons for the existing situation in the farms.

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Yang, Yinsheng, Qianwei Zhuang, Guangdong Tian, and Silin Wei. "A Management and Environmental Performance Evaluation of China’s Family Farms Using an Ultimate Comprehensive Cross-Efficiency Model (UCCE)." Sustainability 11, no. 1 (December 20, 2018): 6. http://dx.doi.org/10.3390/su11010006.

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Family farm emerged as a new form of agricultural production organization in China in recent years. For the purpose of sustainable development, decision-makers, such as farm owners and policy makers, require the precise information of a family farm’s state of operation to adopt measures for management improvement and agricultural contamination reduction. Considering this, we established two evaluation systems for the measurement of family farms’ management and environmental performance. As demonstrated in several recent studies, data envelopment analysis (DEA) cross efficiency is a useful approach for evaluating and comparing the performance of decision-making units (DMUs). Regarding family farms’ performance evaluation issues, we modified the traditional average cross-efficiency method to be the ultimate comprehensive cross-efficiency approach with the integration of two statistical quantities based on the full consideration of family farms’ unique features, such as vulnerability and seasonality, resulting from the influence of natural and social factors. Our proposed approach presents more excellent characteristics compared with CCR efficiency and average cross efficiency. Several conclusions regarding the operation of China’s family farms are drawn: (i) there is weak positive correlation between family farms’ management and environmental performance; (ii) there is an increasing trend for both management and environmental efficiency, along with the augmentation of the utilized agricultural area of family farms, and management performance is therefore more significant; (iii) demand for timely technological instruction to improve family farms’ management efficiency is expressed by farm owners who are willing to expand; (iv) to improve family farms’ environmental performance, several measures—such as introducing biotechnology, providing subsidies, and environmental education for farmers—should be adopted.

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Fuetsch, Elena. "What Drives Innovation in Family Farms? The Roles of Socioemotional Wealth and Diverse Information Sources." European Journal of Family Business 12, no. 2 (November 17, 2022): 184–204. http://dx.doi.org/10.24310/ejfbejfb.v12i2.13881.

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Family business literature barely addresses family farms and their innovation behavior. Innovation can be key to mitigate typical threats family farms are faced with, e.g., global competition and climate change. This article investigates socioemotional wealth (SEW) and diversity of information sources as innovation drivers. It also explores the role of diversity of information sources as a moderator. A sample of 911 family farms was used for linear regression analysis. The SEW dimension identification of the family members with the farm positively affects the implementation of innovation measures because the stronger the family members identify with the business, the more important is it for them to preserve the identity endowments. Since innovation is a way to do that, strong identification will motivate family members to innovate. Diversity of information sources is also positively linked to innovation measures. However, it has a negative moderating effect on the relationship between identification and innovation measures. While diverse information sources seem to increase a family farm’s ability to innovate by supporting the opportunity identification and utilization, it can also mitigate the farms willingness to innovate when information is ambiguous. The study integrates knowledge from agricultural, innovation and family business research and contributes to a better understanding of the peculiar business type “family farms” and SEW as a multidimensional concept.

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Par, V., and M. Njavro. "HORTICULTURAL FAMILY FARMS PROFITABILITY." Acta Horticulturae, no. 536 (September 2000): 293–300. http://dx.doi.org/10.17660/actahortic.2000.536.34.

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Pei-An, Liao, Chang Hung-Hao, He Junlin, and Saeliw Kannika. "Diversification of marketing strategies among small farms: empirical evidence from family farms in Taiwan." Agricultural Economics (Zemědělská ekonomika) 63, No. 11 (November 6, 2017): 493–501. http://dx.doi.org/10.17221/148/2016-agricecon.

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Farm marketing has been recognized as an important factor for a successful farm business. Due to the increasing interest of consumers in food safety, direct marketing of farm products to consumers in the local farmers’ markets has become very popular. Compared to traditional farm marketing channels, relatively little is known about the use of direct-to-consumer marketing strategies by farmers. This paper aims to provide a more comprehensive picture of farmers’ choices among available farm marketing channels using the case study of Taiwan. Using a population-based survey of 5600 family farms in Taiwan in 2014, in this study we quantify the extent to which demographic characteristics of farm operators, farm production and family conditions may influence the decision of farms to sell farm products to the government, wholesale markets, and in direct-to-consumer sales. We develop a trivariate probit model, and our results indicate that education level and engagement in the off-farm labour market of farm operators, the number of household members, farm size, land ownership, and the type of farm are the key factors in determining farmers’ choice of marketing channels. The findings of this study may have important implications for the design of more effective farm marketing programs by agricultural authorities.

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Nurmet, Maire, and Raul Omel. "ECONOMIC VIABILITY BY FARM SIZE OF ESTONIAN FAMILY FARMS." Problems of Agricultural Economics 362, no. 1 (March 16, 2020): 14–28. http://dx.doi.org/10.30858/zer/118265.

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10

Gilbert. "Comment: Family Farms, Agricultural Policy, and Small-Farm Essentialism." Agricultural History 95, no. 2 (2021): 971. http://dx.doi.org/10.3098/ah.2021.095.2.371.

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11

Soule, Meredith J. "Soil Management and the Farm Typology: Do Small Family Farms Manage Soil and Nutrient Resources Differently than Large Family Farms?" Agricultural and Resource Economics Review 30, no. 2 (October 2001): 179–88. http://dx.doi.org/10.1017/s106828050000112x.

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There is increasing recognition that farmers face constraints on their farming decisions depending on the their resources, stage in life, and lifestyle choices. These factors are captured in a new farm typology developed by the Economic Research Service. The farm typology's definition of small and large farms is used to test the commonly stated hypothesis that small farmers practice better land husbandry than do large farmers. The adoption of eleven different soil and nutrient management practices used by U.S. corn producers is analyzed with a bivariate logit model for each practice. The farm typology is found to be significantly associated with two of the practices—rotation with legumes and conservation tillage.

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12

Chen, Zhigang, Qianyue Meng, Kaixin Yan, and Rongwei Xu. "The Analysis of Family Farm Efficiency and Its Influencing Factors: Evidence from Rural China." Land 11, no. 4 (March 27, 2022): 487. http://dx.doi.org/10.3390/land11040487.

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Improving the efficiency of family farms is of great significance to rural revitalization and agricultural modernization in China. In order to find out the development status and shortcomings of family farms in China, and put forward targeted policy recommendations to improve the efficiency of various family farms, this paper applies the DEA model to measure the efficiency of family farms from a micro perspective by using the field survey data of the national family farm demonstration bases of Wuhan and Langxi, China. In addition, the Tobit model is further applied to explore the factors that affect the efficiency of full sample family farms, as well as to compare and analyze the differences in the efficiency in different regions and of different operation types. The results show that the efficiency of family farms is low, the efficiency of family farms in Wuhan is higher than that in Langxi, and the efficiency of breeding family farms is higher than that of planting family farms and mixed family farms. Capital input, farmers’ education level, market channels, brand registration, fertilizer usage and financial credit have positively affected the efficiency of family farms, while government subsidies and natural disasters have had negative effects on it. Specially, the land operating area shows a U-shaped relationship with farm efficiency. The efficiency of planting family farms is positively affected by labor input, while that of breeding and mixed family farms rely more on capital input and financial credit instead.

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13

White, Tom. "The Importance of Family Farms." Chesterton Review 24, no. 3 (1998): 413–16. http://dx.doi.org/10.5840/chesterton199824384.

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14

KOVAČIČ, Matija, Andrej UDOVČ, and Bernarda ČEBULJ. "Income on the family farms." Acta agriculturae Slovenica 77, no. 2 (December 15, 2001): 247–66. http://dx.doi.org/10.14720/aas.2001.77.2.15721.

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In the paper the problematic of measuring the economic effectiveness of the family farms is discussed. The base of the discussion is the theory, which treats the family farm as a whole of production-technical factors and farm household, and where household members often, with their non-agricultural activities, provide necessary income for its operation. After short overview of different methods for estimating farm income and economic status of family farms in Slovenia and some EU countries, the problem of comparative measuring of farm income from pure agricultural activities is discussed. Then the concept of “economic power of farm” and “index of economic power of farm –IGM” as its measure are introduced. At the end the usage of that index is demonstrated on example of some model farms.

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15

Wu, Fang. "Adoption and income effects of new agricultural technology on family farms in China." PLOS ONE 17, no. 4 (April 26, 2022): e0267101. http://dx.doi.org/10.1371/journal.pone.0267101.

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Family farms are the main force that promotes the direct application of new agricultural technology to production. So what are the factors that affect the adoption of new agricultural technology by family farms, and can the adoption of new technology increase the operating income of family farms? Using cross-sectional data from 847 family farms, this study examines the determinants and impacts of multiple new agricultural technologies adoption on family farms’ income in China. To account for selection bias from both observable and unobservable factors, an endogenous switching regression model is employed to evaluate the effects of new agricultural technology on family farms’ income. The empirical results show that the adoption of new agricultural technology is affected by the endowment of farmers and the characteristics of family farms. After controlling for the selection bias, the adoption of new agricultural technologies has a positive and significant impact on family farms’ income. And the impact on the non-adopter family farms is much larger than adopter family farms. Heterogeneity analysis indicates that family farms with a larger area of arable land earn more from the adoption of new technologies than small farms. In all types of technology investigated, the new methods of pest control and the new chemical fertilizer technology have a relatively large impact on family farms’ income, while the new mechanical technology has the least impact on family farms’ income. The adoption of new technologies by family farms is more important for promoting the progress of agricultural science and technology. Therefore, it is necessary to take effective measures to overcome the obstacles to the adoption of new agricultural technologies and pay more attention to the use of new agricultural technologies to improve agricultural production efficiency.

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Wu, Fang. "Adoption and income effects of new agricultural technology on family farms in China." PLOS ONE 17, no. 4 (April 26, 2022): e0267101. http://dx.doi.org/10.1371/journal.pone.0267101.

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Family farms are the main force that promotes the direct application of new agricultural technology to production. So what are the factors that affect the adoption of new agricultural technology by family farms, and can the adoption of new technology increase the operating income of family farms? Using cross-sectional data from 847 family farms, this study examines the determinants and impacts of multiple new agricultural technologies adoption on family farms’ income in China. To account for selection bias from both observable and unobservable factors, an endogenous switching regression model is employed to evaluate the effects of new agricultural technology on family farms’ income. The empirical results show that the adoption of new agricultural technology is affected by the endowment of farmers and the characteristics of family farms. After controlling for the selection bias, the adoption of new agricultural technologies has a positive and significant impact on family farms’ income. And the impact on the non-adopter family farms is much larger than adopter family farms. Heterogeneity analysis indicates that family farms with a larger area of arable land earn more from the adoption of new technologies than small farms. In all types of technology investigated, the new methods of pest control and the new chemical fertilizer technology have a relatively large impact on family farms’ income, while the new mechanical technology has the least impact on family farms’ income. The adoption of new technologies by family farms is more important for promoting the progress of agricultural science and technology. Therefore, it is necessary to take effective measures to overcome the obstacles to the adoption of new agricultural technologies and pay more attention to the use of new agricultural technologies to improve agricultural production efficiency.

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17

Wilson, Juliette, and Andrea Tonner. "Doing family: The constructed meanings of family in family farms." Journal of Rural Studies 78 (August 2020): 245–53. http://dx.doi.org/10.1016/j.jrurstud.2020.06.002.

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18

Lowder, Sarah K., Jakob Skoet, and Terri Raney. "The Number, Size, and Distribution of Farms, Smallholder Farms, and Family Farms Worldwide." World Development 87 (November 2016): 16–29. http://dx.doi.org/10.1016/j.worlddev.2015.10.041.

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Shang, Huifang, Xiaoyan Yi, Changbin Yin, Yinjun Chen, and Zewei Zhang. "How Does the Stability of Land Management Right (SLMR) Affect Family Farms’ Cultivated Land Protection and Quality Improvement Behavior (CLPQIB) in China?" Land 10, no. 10 (October 7, 2021): 1052. http://dx.doi.org/10.3390/land10101052.

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Protecting and improving cultivated land quality is a key way to the realization of agricultural modernization. The Chinese government advocates agricultural producers to implement cultivated land protection and quality improvement behavior (CLPQIB). However, the cultivated land management rights of family farms are not so stable. In order to study how stability of land management rights (SLMR) affects family farms’ CLQPIB, promoting family farms in adopting technologies to protect cultivated land, this study investigated 117 family farms in Anhui and Hubei provinces by stratified sampling and analyzed data through the logistic regression model and marginal effects model. The results showed that transferred land ratio, contract types, and contract duration affected family farms’ CLPQIB significantly. The probability of family farms applying organic fertilizer decreased by 0.9% for every 1% increase of the transferred land ratio. Family farms’ rented land through formal contracts have a 21.4% higher probability of adopting planting–breeding technology than family farms’ rented land through informal contracts. For every additional year of the rental contract duration, the possibility for family farms to replace chemical fertilizer with organic fertilizer, pesticides reduction, and integrated planting-breeding increase by 2.1%, 2.2%, and 1.3%, respectively. The results of this study can guide policy makers with further regulating land transfer behavior, guide family farms with signing formal lease contracts, and extending the duration of lease contracts, improving the cultivated land protection behavior of family farms.

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ŽUTINIĆ, Đ., and I. GRGIĆ. "Family farm inheritance in Slavonia region, Croatia." Agricultural Economics (Zemědělská ekonomika) 56, No. 11 (December 1, 2010): 522–31. http://dx.doi.org/10.17221/14/2010-agricecon.

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The aim of the study was to determine the chances of the Slavonian family farms for social reproduction in the next generation and to determine attitudes of farmers towards some aspects of family farm inheritance and the possible ways of preventing the division of land. The research was carried out on a sample of 202 family farms. The analysis showed that the chances to remain as integral production units in the next generation are realistic for only 48% of family farms. The traditional pattern of behavior is obvious with regard to inheritance and to postponing the transfer of management and control of the farm resources. The majority of the Slavonian farmers find that it would be proper if the state were to introduce special measures to regulate the integrity of the land and to offer subsidies and easements for the "entry" of the young into the agriculture.

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Wilson, Lesley‐Ann. "The Family Farm Business? Insights into Family, Business and Ownership Dimensions of Open‐Farms." Leisure Studies 26, no. 3 (July 2007): 357–74. http://dx.doi.org/10.1080/02614360600661120.

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Huang, Zhiping, Tianran Wang, and Na Li. "Reciprocal and Symbiotic: Family Farms’ Operational Performance and Long-Term Cooperation of Entities in the Agricultural Industrial Chain—From the Evidence of Xinjiang in China." Sustainability 15, no. 1 (December 26, 2022): 349. http://dx.doi.org/10.3390/su15010349.

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The family farm is an important entity in the modern agricultural industrial chain. It is of great significance to empirically study its operational performance improvement and sustainable development. This paper introduces symbiosis theory to establish a symbiosis system framework of the family farm industrial chain and analyzes family farms’ operational performance from the view of industrial symbiosis cooperation. We selected 552 agricultural planting family farms in China’s Xinjiang Production and Construction Corps as samples to measure the operational environment and performance of family farms using factor analysis and examining the effects of long-term cooperation among the industrial chain entities on family farms’ operational performance using the ordered probit model. The results show that the long-term cooperation of the family farms with other entities has a significant positive impact on the family farms’ operational performance, which can be enhanced by the improvement of cooperation and moderated by the external environment. Therefore, it is suggested to promote the long-term cooperation between family farms and other industrial chain entities, as well as the industrial environment optimization, to accelerate the healthy and sustainable development of family farms with a continuous, symmetrical, and reciprocal symbiotic model.

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Ratten, Vanessa, and Leo-Paul Dana. "Sustainable Entrepreneurship, Family Farms and the Dairy Industry." International Journal of Social Ecology and Sustainable Development 8, no. 3 (July 2017): 114–29. http://dx.doi.org/10.4018/ijsesd.2017070108.

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There has been increasing recognition that for regional competitiveness in rural areas there needs to be a focus on sustainable farming initiatives especially for family farms that are competing with global conglomerates. Family farms, whilst declining in number, are the purpose of this paper studying the rural entrepreneurship in family farms as they are at the heart of rural communities and the overall agricultural industry and comprise a high percentage of total farms. This paper takes a case study approach using in-depth semi structured interviews to delve into the types of entrepreneurial strategies that are distinctive of family farms in terms of their sustainability approach to farming. Dairy farms in the West Victorian area of Australia are studied and the findings suggest that family farms can increase their regional competitiveness and international standing by focusing on their collaborative, social and sustainable entrepreneurial strategies.

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Savickienė, Jūratė, Astrida Miceikienė, and Srdjan Lalić. "TREND OF SUSTAINABLE ECONOMIC DEVELOPMENT OF FAMILY FARMS: CASE OF LITHUANIA." Management Theory and Studies for Rural Business and Infrastructure Development 39, no. 4 (December 27, 2017): 465–89. http://dx.doi.org/10.15544/mts.2017.33.

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The Common Agricultural Policy post-2020 emphasizes that sustainable economic development is an important factor of family farms. Scientific problem: the trends of sustainable economic development of family farms and the recommendations for promotion of sustainability. Research aim: to provide suggestions on promotion of sustainability upon assessment of the trends of sustainable economic development of the Lithuanian family farms. Family farm sustainable economic development index has been used for identification of the trends. Nine types of sustainable economic development of family farms have been identified. Analysis of the types of sustainable economic development of Lithuanian family farms by specialization has been conducted and the causes which have determined the situation at the farms have been identified.

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Sani Issa, MS, AA Saidou, NS Jangorzo, and M. Karembe. "Characterising family farms and their constraints and agroecological intensification options: a case study from the Sahelian zone, Niger." African Journal of Food, Agriculture, Nutrition and Development 24, no. 1 (January 29, 2024): 25333–52. http://dx.doi.org/10.18697/ajfand.126.23390.

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ABSTRACT Family farms play an important role in food security and nutrition in West Africa. Family farms are rapidly changing and face many constraints. Thus, characterizing them is necessary for policy purposes. This study aimed to characterise family farms in Niger, focusing on the current constraints to family farms and existing agroecological intensification (AEI) options. A survey was conducted using a questionnaire administered to 108 family farms across the selected six study locations. We used descriptive statistics to characterise the family farms and the factorial analysis of mixed data (FAMD) and the Hierarchical Clustering of Principal Components (HCPC) to identify the types of family farms. Results showed that family farms, on average, encompass three households, and the majority (87.2%) of the family farms surveyed were managed by married persons where 25.7% of whom are female. Agriculture remains the primary source of income for 98.2% of people in the study locations, and the main second source of family income (47.7%) is animal husbandry. Family farms are mainly characterised by the presence of the main field (MF) (98%) led by the heads of households and the presence of the women fields (WF) (78%) led by the women. Regarding farm size, the average MF and the WF farm sizes were 3.0 ha and 1.5 ha, respectively. The main identified constraints to family farms were soil fertility decline (84.33%), a recurrent early end of the rainy season (84.33%), farmers’ low income (41.15%), and limited access to the market (24.70%). Twelve potential AEIs options across the study area were explored. In the MF, the major AEI options practised by farmers were: the application of organic manure as fertilizer (73.27%), cereal-legume intercropping (68.83%), and Farmer Managed Natural Regeneration (35.85%). Whereas in the WF, the AEI practices were the application of organic manure (55.28%), and cereal-legume intercropping (28.98%). Co-building an integrative approach that combines multiple AEI options in the same field is necessary to tackle the main drivers of the farming systems. Key words: Family farms, Agroecological intensification, diversity, farm typology, Niger

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Siqueira, Tiago Teixeira da Silva, Danielle Galliano, Geneviève Nguyen, and Ferenc Istvan Bánkuti. "Organizational Forms and Agri-Environmental Practices: The Case of Brazilian Dairy Farms." Sustainability 13, no. 7 (March 28, 2021): 3762. http://dx.doi.org/10.3390/su13073762.

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Understanding the relationship between the organizational characteristics of a farm and its environmental performance is essential to support the agro-ecological transition of farms. This is even more important as very few studies on the subject have been undertaken and as there is a growing diversity of organizational forms of farms that differ from the traditional family model. This paper proposes a comprehensively integrated approach of dairy farms in Brazil. A case study of six archetypes of farms with contrasted organizational characteristics is developed to explore the relations between, on the one hand, farms’ organizational structure and governance, and on the other hand, the adoption of agri-environmental practices. Results show that the adoption of agri-environmental practices varies across the wide range of farm’s organizational forms—from the family to the industrial models. Farms with limited internal resources depend more specifically on external sectoral or territorial resources to implement environmental practices. If the environment is conducive to the creation of incentives and coordination mechanisms underlying learning processes, farms will adopt agri-environmental practices, regardless of they are organized. The creation of local cooperatives, farmer’s networks and universities extension programs can strengthen farmers’ absorption, adaptation and transformation capacities and boost the adoption of environmental practices. Finally, considering farms as heterogeneous organizational forms in terms of human capital, resources, market, and informational access is essential to accelerate the agroecological transition.

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Sowula-Skrzyńska, Elżbieta, Grzegorz Skrzyński, Renata Matysik-Pejas, and Sabina Kurpan. "ECONOMIC VIABILITY OF FAMILY DAIRY FARMS." Annals of the Polish Association of Agricultural and Agribusiness Economists XIX, no. 6 (January 10, 2018): 206–12. http://dx.doi.org/10.5604/01.3001.0010.32.

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For optimal farm management, it is very important to research potential opportunities of raising its rental ability. These opportunities lie as by side of selling income as of its costs. It causes a necesity of constant cost control and of looking for new methods of reducing these costs. The aim of study was the assessment of economic viability of family dairy farms .The economic efficiency of these farms was analysed according to scale of production. Basic indicators and measures of the economic efficiency of production, such as net agricultural income, gross margin, production costs, parity income and break-even point were calculated. The paper presents the analyze of disproportion income between small and large farms. The executed analysis showed that from economic point of view the optimal dairy farms maintains about 60 cows.

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Sowula-Skrzyńska, Elżbieta, Grzegorz Skrzyński, Renata Matysik-Pejas, and Sabina Kurpan. "ECONOMIC VIABILITY OF FAMILY DAIRY FARMS." Annals of the Polish Association of Agricultural and Agribusiness Economists XIX, no. 6 (January 10, 2018): 206–12. http://dx.doi.org/10.5604/01.3001.0010.7932.

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For optimal farm management, it is very important to research potential opportunities of raising its rental ability. These opportunities lie as by side of selling income as of its costs. It causes a necesity of constant cost control and of looking for new methods of reducing these costs. The aim of study was the assessment of economic viability of family dairy farms .The economic efficiency of these farms was analysed according to scale of production. Basic indicators and measures of the economic efficiency of production, such as net agricultural income, gross margin, production costs, parity income and break-even point were calculated. The paper presents the analyze of disproportion income between small and large farms. The executed analysis showed that from economic point of view the optimal dairy farms maintains about 60 cows.

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Yu, Lili, Ziheng Niu, Shijiu Yin, Yang Gao, and Borui Tian. "Support policy preferences of grain family farms: evidence from Huang-huai-hai plain of China." International Food and Agribusiness Management Review 23, no. 5 (December 2, 2020): 697–712. http://dx.doi.org/10.22434/ifamr2019.0124.

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This study uses the choice experiment method with 570 grain family farms located in the Huang-huai-hai Plain and determine various support policy attributes and the attribute levels for the two dimensions of policy measures and policy communication channels. Ordering effects are eliminated by warming up subjects in advance and using information disclosure. This paper uses the inferred attribute non-attendance method to process attributes ignored by the grain family farms and analyzes grain family farms’ preferences for different support policies with a mixed logit model and then uses a latent class model to analyze how the characteristics of grain family farms relate to different preference types. We find that grain family farms have a strong preference for agricultural subsidies, credit support, and technical support (the mean coefficient is greater than 0.8). Moreover, the preferences of grain family farms over the policy communication channel (the mean coefficient is greater than 0.5) cannot be ignored. Faced with the same policy attribute combination, grain family farms with high education levels, reasonable scales of operation, and good understanding of support policies are more likely to improve their profit margins. There are four preference types of grain family farms: finance preference (43.2%), knowledge and technology preference (28.5%), land transfer preference (15.4%), and policy information preference (12.9%).

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Lillywhite, Jay M., and Michael Duffy. "Multifamily farms and America's farm structure: A new perspective on an old issue." American Journal of Alternative Agriculture 16, no. 4 (December 2001): 184–90. http://dx.doi.org/10.1017/s088918930000919x.

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AbstractThis study examined the extent and nature of multifamily farms in Iowa. Based on a random sample phone survey conducted in 1997, it was found that over one-fourth (26%) of Iowa's farms would be classified as multifamily farms. Multifamily farms showed significant differences from their single-family farm counterparts in several areas. They tended to have younger operators and larger operations, and the operators were more likely to consider farming as their principal occupation. In addition, they had more diverse operations and generated larger farm and family incomes. The farms were further classified based on their annual sales. As expected, non-commercial farms (sales less than $50,000) had the lowest percentage of multifamily farms (21%). Smallcommercial farms with sales from $50,000 to $250,000 were 30% multifamily, while large-commercial farms were 35% multifamily. The study also addressed whether or not policy restrictions based on age and income would discriminate against farms due to the multifamily farm phenomenon. A logit regression analysis was performed to determine if a multifamily structure was significant in predicting whether or not a farm was small. The results showed that multifamily relations were not a significant predictor. A growing phenomenon in U.S. agriculture, namely the multifamily farm, was examined. A significant percentage of Iowa farms was found to be multifamily. There were many differences between multifamily and single-family farms, but these differences did not display any predictive power. More research is needed in order to understand multifamily farms, a structure that will likely continue to grow and influence U.S. agriculture and outreach programs.

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Józef, Zegar. "THE PERSPECTIVES OF FAMILY FARMS – CONTINUATION." Problems of Agricultural Economics 263, no. 2 (June 23, 2020): 73–94. http://dx.doi.org/10.30858/zer/120606.

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Akcay, Yasar, and Selma Karabas. "Economic analysis of vegetable family farms." Journal of Applied Horticulture 06, no. 02 (December 15, 2004): 118–24. http://dx.doi.org/10.37855/jah.2004.v06i02.27.

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Spaskyi, Habriiel. "Development of family farms in region." Ekonomika APK, no. 5 (May 28, 2019): 49–59. http://dx.doi.org/10.32317/2221-1055.201905049.

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HILLEBRAND, HANS, and URSULA BLOM. "YOUNG WOMEN ON DUTCH FAMILY FARMS." Sociologia Ruralis 33, no. 2 (August 1993): 178–89. http://dx.doi.org/10.1111/j.1467-9523.1993.tb00959.x.

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Kimhi, Ayal, and Noga Nachlieli. "Intergenerational Succession on Israeli Family Farms." Journal of Agricultural Economics 52, no. 2 (May 2001): 42–58. http://dx.doi.org/10.1111/j.1477-9552.2001.tb00924.x.

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Jurek, Thomas J. "Children and Hazards on Family Farms." Journal of Rural Health 14, no. 1 (December 1998): 7. http://dx.doi.org/10.1111/j.1748-0361.1998.tb00855.x.

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Lobodzinska, Barbara. "Women on the polish family farms." International Review of Sociology 1, no. 1 (March 1990): 109–39. http://dx.doi.org/10.1080/03906701.1990.9971063.

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Baležentis, Tomas. "Structural efficiency in Lithuanian family farms." Management Theory and Studies for Rural Business and Infrastructure Development 37, no. 4 (December 22, 2015): 462–79. http://dx.doi.org/10.15544/mts.2015.39.

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Along with firm-specific technical inefficiency, sector-specific structural inefficiency might induce losses in productivity. This paper therefore aims to identify the trends in structural efficiency in Lithuanian family farms. Specifically, the four farming types are considered, namely cereal farming, field cropping, dairying, and mixed farming. Farm-level data from Farm Accountancy Data Network are used for the analysis. The research period spans over the years 2004–2011. The trends in technical and scale efficiency are presented. Furthermore, the prevailing returns to scale are discussed thus offering insights into the most productive scale size and deviations from it in Lithuanian family farms. Finally, the dynamics in structural efficiency are discussed. The results indicate that the aggregate output of certain farming types could be augmented by some 20–25% due to reallocation of inputs among farms. Anyway, technical inefficiency remains the major driver of structural inefficiency.

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Donovan, Michael. "The Intimate Geography of Family Farms." Comparative Studies in Society and History 43, no. 2 (April 2001): 273–97. http://dx.doi.org/10.1017/s0010417501003498.

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Hasperué, H. J., A. Nico, and R. Cieza. "Science for strengthening family flower farms." Societal Impacts 1, no. 1-2 (December 2023): 100023. http://dx.doi.org/10.1016/j.socimp.2023.100023.

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De Rosa, Marcello, and Gerard McElwee. "An empirical investigation of the role of rural development policies in stimulating rural entrepreneurship in the Lazio Region of Italy." Society and Business Review 10, no. 1 (February 9, 2015): 4–22. http://dx.doi.org/10.1108/sbr-08-2014-0041.

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Purpose – The purpose of the paper is to provide an analysis of the adoption of Rural Development Policies (Rdp) as the result of entrepreneurial behaviours carried out by family farms with a focus on the Lazio Region of Italy. Family farming is the backbone of the European model of agriculture. Rdp provide family farms with a set of opportunities which, if well exploited, could drum up farm’s development. Design/methodology/approach – An empirical analysis of a data base provided by the Lazion region of Italy on the adoption of Rdp by family farms in the Lazio region for the period of 2007-2013. Cluster analysis is the main analytical tool used. Findings – The results evidence significant differences in the adoption of rural policy on the basis of family life cycle and the composition of the family farm. The empirical analysis underlines the low degree of coherence by farms located in rural areas. Practical implications – Farmers’ success in accessing funds requires them to be proactive and take a strategic perspective to convince funders that they have a coherent strategy which meets the requirements of the particular Rdp which they are trying to access. Social implications – In terms of policy, a more nuanced understanding of the entrepreneurial nature of some practices in a rural setting and how they require multi-agency investigation. Originality/value – The paper is unique, in that it considers the consumption of policy by farmers who are entrepreneurial in their vision. By consumption of Rdp, we mean the farmer’s strategic capability to obtain funds from regional funding pots for rural development.

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Effland. "Small Farms/Family Farms: Tracing a History of Definitions and Meaning." Agricultural History 95, no. 2 (2021): 313. http://dx.doi.org/10.3098/ah.2021.095.2.313.

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Agarwal, Bina. "Can group farms outperform individual family farms? Empirical insights from India." World Development 108 (August 2018): 57–73. http://dx.doi.org/10.1016/j.worlddev.2018.03.010.

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Jedik, Andrej, and Aldona Stalgienė. "THE LIKELIHOOD OF FARMS BANKRUPTCY: THE CASE OF LITHUANIAN FAMILY FARMS." Management Theory and Studies for Rural Business and Infrastructure Development 40, no. 2 (June 21, 2018): 198–205. http://dx.doi.org/10.15544/mts.2018.19.

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In developing the measures of agriculture policy and purposeful usage of EU funds, also for financial organisations, farmers, advisors and scientists it is important to predict farm bankruptcy. This makes it possible to formulate the scientific problem: what is the likelihood of bankruptcy of different kinds of family farms? The aim of the investigation is to present the likelihood of the Lithuanian family farms bankruptcy based on the economic size and type of farming by analysing financial indicators of farms. Farm-level panel data for the year 2014–2016 from Farm Accountancy Data Network (FADN) was used. The estimated distribution of farm groups based on farm economic size demonstrated that about 40–60% of small farms were in the low likelihood of bankruptcy area. The share of cereals, oilseeds and protein crop farms in the high likelihood of bankruptcy area fluctuated from 13% till 30% during the year 2014–2016. The farm distribution by economic size and type of farming showed that more than 40% of small dairy farms had the high likelihood of bankruptcy in the year 2015–2016, as well as 30% of medium and large cereals, oilseeds and protein crops farms in 2016.

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Micu, Marius Mihai, Eduard Alexandru Dumitru, Catalin Razvan Vintu, Valentina Constanta Tudor, and Gina Fintineru. "Models Underlying the Success Development of Family Farms in Romania." Sustainability 14, no. 4 (February 21, 2022): 2443. http://dx.doi.org/10.3390/su14042443.

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A family farm is an important part of the countryside, both economically and especially socially. In recent years, legislative measures have encouraged the development of large farms, ensuring food security while neglecting family farms, which are characterised by a lack of organisation, the absence of proper classification and the absence of measures to encourage their development and protection. In order to identify the premises underlying the development of family farms, and to create a development model for those family farms in a poor economic situation, the BMC method and SWOT analysis of seven family farms considered successful models were used. The development of these types of farms could provide a solution to a major problem facing the Romanian countryside: the depopulation of rural areas. The results of the study show that the development of these types of farms is based on joining an associative form (cooperatives) and/or making investments in the processing/storage line of agricultural products.

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Stawicka, Ewa, and Michał Dudek. "Analysis of changes in selected socio-demographic factors of family farms in Poland in 2010-2016." Kwartalnik Nauk o Przedsiębiorstwie 50, no. 1 (March 26, 2019): 91–98. http://dx.doi.org/10.5604/01.3001.0013.2065.

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Agricultural holdings run by individual farmers, known as family farms, have long dominated the Polish agriculture. The purpose of the article was to characterize selected socio-demographic features of the agricultural population and the factor of transformations within family farms. In years 2010-2016, a decline in the number of family farms in Poland and individuals working there was observed, which was a continuation of the trend initiated in the period of economic transformation. The decrease in the number of family farms was accompanied by changes consisting of the improvement in the level of education, but also aging of those managing the farms, and the departure of family members from performing non-agricultural activities. On the one hand, these phenomena demonstrated the professionalization and specialization of some family farms, but they also demonstrated the increasing diversification of the economic activity of people in small entities that constitute the majority of the farms in Poland. The presented results were based on the CSO data and literature on the subject. The study used a comparative method and a statistical data analysis.

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Wang, Linwei, Yixin Hu, and Rong Kong. "The Impact of Bancassurance Interaction on the Adoption Behavior of Green Production Technology in Family Farms: Evidence from China." Land 12, no. 5 (April 22, 2023): 941. http://dx.doi.org/10.3390/land12050941.

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In the context of increasingly severe resource and environmental constraints, accelerating family farms to take the path of green agricultural development is an urgent practical problem to be solved. The bancassurance interaction, an innovative form of financial support policy for agriculture, can effectively alleviate the risks and credit rationing problems faced by family farms in the operation process, provide new opportunities for green production of family farms, and is of great significance to promoting sustainable agricultural development. This study uses data from 564 planting family farms in Shaanxi Province to analyze the impact of the bancassurance interaction on adopting green production technology in family farms and its mechanism, paying particular attention to the heterogeneous effects of the family life cycle and family economic level. The results of this study show that the bancassurance interaction has a significant positive impact on the adoption of green production technology by family farms. Compared with agricultural credit and insurance, the effect of the bancassurance interaction on adopting green production technologies is more evident. The analysis of the impact mechanism shows that the bancassurance interaction can promote the adoption of green production technology in family farms through three channels: increasing investment in agricultural production, expanding the scale of land management, and strengthening exchanges of green technology. Among them, the effect of increasing agrarian production investment is the most pronounced. The heterogeneity analysis shows that the impact of the bancassurance interaction on the green production technology of family farms varies significantly according to the family life cycle and economic level. Family farms at the dependency stage and low-income level were more willing to adopt green production technologies driven by the bancassurance interaction. Therefore, it is necessary to continuously innovate the interaction mode between banks and insurance companies, rationally allocating agricultural production factors and combining the actual situation of each family farm to strengthen the leading role of the bancassurance interaction in adopting green production technologies and promoting high-quality agricultural development.

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Sass, Roman. "EFFECTIVENESS AND COMPETITIVENESS OF FAMILY FARMS IN THE SUBREGION OF BYDGOSZCZ." Annals of the Polish Association of Agricultural and Agribusiness Economists XX, no. 4 (August 23, 2018): 168–75. http://dx.doi.org/10.5604/01.3001.0012.3057.

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The paper aims to determining the farms’ capabilities to develop measured with their technical and financial effectiveness as well as the investments’ net volume. The research covers the farms from the Bydgoszcz’s sub-region (former province of Bydgoszcz) which prior to accession to the European Union took advantage of preferential loans. At the same time in the years 2004-2015 they uninterruptedly conducted accountancy in the Polish FADN system. The technical effectiveness of the farms has been determined with the use of the non-parametric DEA method – Data Envelopment Analysis, while for the purposes of the financial standing of farms’ analysts, there has been used the value creation index. In order to determine farms’ development capacity (competitive farms) the Boston Consulting Group (BCG) modified matrix has been applied. It results from the conducted studies, that in the best situation are the farms which have been rated among the group of leaders, as were characterised by the highest technical and financial effectiveness and also the highest level of net investments. The endangered farms are in the worst situation. In spite of the fact that these farms’ technical effectiveness was high, the developmental restrictions result from low scale of production. Competitiveness of farms is closely connected with their area.

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BALEŽENTIS, Tomas. "STOCHASTIC PRODUCTION FRONTIER FOR THE LITHUANIAN FAMILY FARMS." Journal of Business Economics and Management 17, no. 2 (April 8, 2016): 283–98. http://dx.doi.org/10.3846/16111699.2013.770791.

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The research follows neo-classical methodology to analyse the trends of the agricultural efficiency. The paper fits the stochastic production frontier to the micro data describing the performance of the Lithuanian family farms during 2004–2009 in order to define the current trends of efficiency and productivity in the sector. Indeed, this is the first application of stochastic frontiers to gauge the performance of Lithuanian family farms. The technical efficiency of the Lithuanian family farms fluctuated around 80%. The analysis confirmed that the livestock farms were peculiar with higher mean technical efficiency if compared to that of mixed or crop farms. The estimated partial output elasticities imply that the intermediate consumption was the most productive factor, whereas assets were four to six times less productive depending on the farming type. The land factor was peculiar with the lowest partial output elasticities. The research contributes to the wider discussion on the patterns of efficiency and productivity in a transition European Union Member States following the accession.

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BALEŽENTIS, Tomas. "STOCHASTIC PRODUCTION FRONTIER FOR THE LITHUANIAN FAMILY FARMS." Journal of Business Economics and Management 17, no. 2 (April 8, 2016): 283–98. http://dx.doi.org/10.3846/10.3846/16111699.2013.770791.

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The research follows neo-classical methodology to analyse the trends of the agricultural efficiency. The paper fits the stochastic production frontier to the micro data describing the performance of the Lithuanian family farms during 2004–2009 in order to define the current trends of efficiency and productivity in the sector. Indeed, this is the first application of stochastic frontiers to gauge the performance of Lithuanian family farms. The technical efficiency of the Lithuanian family farms fluctuated around 80%. The analysis confirmed that the livestock farms were peculiar with higher mean technical efficiency if compared to that of mixed or crop farms. The estimated partial output elasticities imply that the intermediate consumption was the most productive factor, whereas assets were four to six times less productive depending on the farming type. The land factor was peculiar with the lowest partial output elasticities. The research contributes to the wider discussion on the patterns of efficiency and productivity in a transition European Union Member States following the accession.

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Journal articles on the topic 'Family farms'

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