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Relevant bibliographies by topics / Farm management – Decision making – Ethiopia

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Dissertations / Theses

Academic literature on the topic 'Farm management – Decision making – Ethiopia'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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Dissertations / Theses on the topic "Farm management – Decision making – Ethiopia"

1

Kebede, Yohannes. "Household decision-making : the adoption of agricultural technologies in Ethiopia." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=41250.

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Technology adoption has been seen as key to the development of more productive agriculture in lesser developed countries. But the adoption and adaptation of new agricultural technology occurs at the level of farm families where decisions are made based on perceived risks and benefits of the new technology, and its fit within the knowledge and practices of existing agricultural system.<br>The processes and consequences of household decision-making are investigated using unidisciplinary methods of decision analysis involving statistical, mathematical, psychological, anthropological and econometr

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2

Negussie, Achalu D. "Farm forestry decision making strategies of the Guraghe households, Southern-Central Highlands of Ethiopia." Doctoral thesis, Tharandt : Inst. für Internat. Forst- und Holzwirtschaft, 2004. http://deposit.d-nb.de/cgi-bin/dokserv?idn=971015996.

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Negussie, Achalu D. "Farm forestry decision-making strategies of the Guraghe Households, Southern-Central Highlands of Ethiopia." Doctoral thesis, Technische Universität Dresden, 2003. https://tud.qucosa.de/id/qucosa%3A24322.

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In this study, farm forestry decision criteria were elicited by adopting a behavioral decision-making study approach from households in ten Peasant Associations of the study district. Major decision objectives, available alternatives, constraints, and the likelihood of the chance events were elicited through a questionnaire survey, participatory observation, detailed discussion, and review of archival information. It was found that farmers generally, plant various tree and shrub species for meeting various household needs and for generating cash incomes. The goal of cash generation is for sust

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4

Negussie, Achalu D. [Verfasser]. "Farm forestry decision making strategies of the Guraghe households, Southern-Central Highlands of Ethiopia / Achalu D. Negussie." Tharandt : Inst. für Internat. Forst- und Holzwirtschaft, 2004. http://d-nb.info/971015996/34.

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5

Boda, Gayatri. "Benchmarking dairy information using interactive visualization for dairy farm decision making." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=97910.

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The main goal of this research was to explore the use of benchmarking in the dairy industry. This includes descriptions of the various sectors in North America where benchmarking has been used successfully on a continuous basis or in research. Benchmarking methods that are currently used in the Quebec dairy industry are examined. An improvement to such methods is proposed through the use of visualization, coupled with interactivity, and with a focus on adaptability and usage. The advantages of such an interactive tool are discussed in light of on-farm decision-making, and a further use of visu

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6

Powers, Laura A. "IMPROVING FARM MANAGEMENT DECISIONS BY ANALYZING SITE-SPECIFIC ECONOMIC DATA DEVELOPED FROM YIELD MAPS." UKnowledge, 2002. http://uknowledge.uky.edu/gradschool_theses/167.

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This thesis examines the use of precision agriculture data, specifically yield maps, for makingsite-specific economic decisions for improved farm management. The adoption of precisionagriculture on farms has allowed producers to collect a greater quantity and more specificinformation about production than ever before. With such information, site-specific decisions canbe made. Incorporating economic data with yield map data, two primary decision examples aredeveloped: defining areas of production and nonproduction and managing temporal risk spatiallyacross a field. Included with the production/

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7

Merrill, John C. "Water Management and Decision-Making in the Nile Basin: A Case Study of the Nile Basin Initiative." Scholar Commons, 2008. https://scholarcommons.usf.edu/etd/402.

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The management of international waterways presents riparian nations with a challenging set of political, economic, environmental, and geographic difficulties. Historically, the Nile Basin has exemplified many of these problems as witnessed by inter-basin conflict, devastating floods, crippling drought, and unstable political and economic development. Despite their tumultuous past the ten riparian nations of the Nile Basin established a supranational water management institution in 1999, the Nile Basin Initiative (NBI), in order to develop collective solutions to their common water related prob

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8

Marchant, David Durack. "A study of the effects of dairy farmers' personalities on their risk attitudes, decision making processes and risk management /." St. Lucia, Qld, 2003. http://adt.library.uq.edu.au/public/adt-QU20031231.130542/index.html.

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9

Komicha, Hussien Hamda. "Farm household economic behaviour in imperfect financial markets : empirical evidence and policy implications on saving, credit and production efficiency in Southeastern Ethiopia /." Uppsala : Dept. of Economics, Swedish University of Agricultural Sciences, 2007. http://epsilon.slu.se/200778.pdf.

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10

Robinson, Jeffrey Brett, University of Western Sydney, of Science Technology and Environment College, and School of Environment and Agriculture. "Understanding and applying decision support systems in Australian farming systems research." THESIS_CSTE_EAG_Robinson_J.xml, 2005. http://handle.uws.edu.au:8081/1959.7/642.

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Decision support systems (DSS) are usually based on computerised models of biophysical and economic systems. Despite early expectations that such models would inform and improve management, adoption rates have been low, and implementation of DSS is now “critical” The reasons for this are unclear and the aim of this study is to learn to better design, develop and apply DSS in farming systems research (FSR). Previous studies have explored the merits of quantitative tools including DSS, and suggested changes leading to greater impact. In Australia, the changes advocated have been: Simple, flexibl

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