scholarly journals Why Do Farmers Forward Contract In Factor Markets?

1992 ◽  
Vol 24 (1) ◽  
pp. 145-151 ◽  
Author(s):  
John J. Haydu ◽  
Robert J. Myers ◽  
Stanley R. Thompson
Keyword(s):  
Decision Making ◽  
Spot Market ◽  
Dominant Factor ◽  
Corn Production ◽  
Numerical Example ◽  
Forward Contract ◽  
Farmer Decision Making ◽  
Factor Markets ◽  
Reduce Risk ◽  
Forward Contracting

AbstractThis study investigated farmers' incentive to forward purchase inputs. A model of farmer decision making was used to derive an optimal forward contracting rule. Explicit in the model was the tradeoff between the quantity of input to be purchased in advance, and the remaining portion to be purchased later on the spot market. Results indicated that the primary reasons farmers contract inputs are to reduce risk and to speculate on favorable price moves. A numerical example of fertilizer used in corn production indicated that the size of the price discount was the dominant factor in forward contracting decisions.

scholarly journals Methodology of Analyzing Maize Density Loss in Smallholder’s Fields and Potential Optimize Approach

Agriculture ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 480
Author(s):  
Zhichao An ◽  
Chong Wang ◽  
Xiaoqiang Jiao ◽  
Zhongliang Kong ◽  
Wei Jiang ◽  
...  
Keyword(s):  
Decision Making ◽  
Food Security ◽  
Zea Mays L ◽  
Plant Density ◽  
Density Difference ◽  
Yield Gap ◽  
Farmer Decision Making ◽  
Yield Gaps ◽  
Farmer Survey ◽  
Experimental Plots

Increasing plant density is a key measure to close the maize (Zea mays L.) yield gap and ensure food security. However, there is a large plant density difference in the fields sown by agronomists and smallholders. The primary cause of this phenomenon is the lack of an effective methodology to systematically analyze the density loss. To identify the plant density loss processes from experimental plots to smallholder fields, a research methodology was developed in this study involving a farmer survey and measurements in a smallholder field. The results showed that the sowing density difference caused by farmer decision-making and plant density losses caused by mechanical and agronomic factors explained 15.5%, 5.5% and 6.8% of the plant density difference, respectively. Changing smallholder attitudes toward the value of increasing the plant density could help reduce this density loss and increase farm yields by 12.3%. Therefore, this methodology was effective for analyzing the plant density loss, and to clarify the primary causes of sowing density differences and plant density loss. Additionally, it was beneficial to identify the priorities and stakeholders who share responsibility for reducing the density loss. The methodology has wide applicability to address the sowing density differences and plant density loss in other areas to narrow crop yield gaps and ensure food security.

Possibility-Based ELECTRE II Method with Uncertain Linguistic Fuzzy Variables

2017 ◽  
Vol 31 (09) ◽  
pp. 1759016 ◽  
Author(s):  
Lidong Wang ◽  
Binquan Liao ◽  
Xiaodong Liu ◽  
Jingxia Liu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Economic Systems ◽  
Linguistic Variables ◽  
Concordance Index ◽  
Fuzzy Variables ◽  
Numerical Example ◽  
Deviation Index ◽  
Multiple Attribute

Linguistic variables can better approximate the fuzziness of man’s thinking, which are important tools for multiple attribute decision-making problems. This paper establishes the possibility-based ELECTRE II model under the environment of uncertain linguistic fuzzy variables and uncertain weight information. By introducing the degree of possibility to ELECTRE II model, the concordance set, the discordance set and the indifferent set are obtained, respectively. Furthermore, the concordance index is redefined by considering deviation index under the same attribute, by which the strong and weak relationships are constructed, and then the rank of alternatives is obtained. A numerical example about the evaluation of socio-economic systems is employed to illustrate the convenience and applicability of the proposed method.

scholarly journals Farmer Decision-Making on the Concept of Coexistence: A Comparative Analysis between Organic and Biotech Farmers in the Philippines

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 857
Author(s):  
Clarisse Mendoza Gonzalvo ◽  
Wilson Jr. Florendo Aala ◽  
Keshav Lall Maharjan
Keyword(s):  
Decision Making ◽  
The Philippines ◽  
Environmental Conservation ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Internal Factors ◽  
Organic Farmers ◽  
Farmer Decision Making ◽  
Decision Making Processes ◽  
Farmer Groups

Farmer perspectives are relevant for understanding agricultural issues and formulating policies. In this study, we conducted a cross-sectional survey on 70 Filipino farmers (i.e., 35 organic and 35 biotech) to understand farmers’ perspectives regarding coexisting farming methods. Internal response variables were tested to verify the type of decision-making processes being undertaken by biotech and organic farmers. Our results showed that a non-linear decision-making process, similar to the Stimulus–Organism–Response Model, was present for both farmer groups. The study also found that biotech farmers were more influenced by internal factors (e.g., consumer resources) than organic farmers, who rely more on external influences (e.g., culture and social interactions), in connection to their coexistence perspective. The presence of “maverick executives” within the organic farmers gives traction to the notion that coexistence can help empower farmers in choosing what farming method is most suitable to their needs. Our data can also provide insights to policymakers in terms of surveying farmer perspectives to balance farmer needs, primarily in yield and income security, with the national agricultural agenda centered on environmental conservation. Thus, farmer perspectives should be considered alongside ongoing studies and debates on coexistence.

scholarly journals PENGAMBILAN KEPUTUSAN HUTANG PADA USAHA KECIL DAN MENENGAH (UKM) DI PULAU LOMBOK: SUATU PERSPEKTIF BEHAVIORAL FINANCE

2018 ◽  
Vol 7 (4) ◽  
Author(s):  
Siti Aisyah Hidayati ◽  
Embun Suryani ◽  
M Muhdin
Keyword(s):  
Decision Making ◽  
Behavioral Finance ◽  
Loss Aversion ◽  
Sampling Method ◽  
Confirmation Bias ◽  
Sampling Technique ◽  
Factor Group ◽  
Dominant Factor ◽  
The Third ◽  
Lombok Island

The purpose of this study is to find out what factors determine decision making of debt and what are the most dominant factors in  decision making of debt for SMEs on the island of Lombok.  This research is an explanatory research with quantitative approach. The population is all SMEs located in Lombok island. The sample is selected by Non probability sampling technique with a judgment sampling method where the SMEs that selected as samples are SMEs in handicraft industry of pottery and already exporting the products. Of the existing population, there are 25 (twenty five) SMEs that can be sampled. Respondents in this study are managers who also the owner of the SMEs. Data was collected using questionnaire. To achieve the research objectives, the data obtained will be processed according to needs using Factor Analysis.The results of this study indicate there are three groups of factors that determine  decision making of debt, namely the First Factor Group consists of: Variable Excessive Optimism, Variable Overconfidence, Variable Confirmation Bias and Variable Aversion to sure loss. This factor is named Factor Overconfidence. The Second Factor Group consisted of Representativeness Variables, Avaibility Variables and Anchoring and Adjustment Variables. This factor is named the Avaibility Factor. The third factor group consists of Affect Variables and Aversion Loss Variables. This factor is named the Factor of Loss Aversion. The most dominant factor in determining debt decision making for SMEs in Lombok Island is the Overconfidence factor group consisting of Variable Excessive Optimism, Variable Overconfidence, Variable Confirmation Bias and Variable Aversion to sure loss .

New KEMIRA Method for Determining Criteria Priority and Weights in Solving MCDM Problem

2014 ◽  
Vol 13 (06) ◽  
pp. 1119-1133 ◽  
Author(s):  
Aleksandras Krylovas ◽  
Edmundas Kazimieras Zavadskas ◽  
Natalja Kosareva ◽  
Stanislav Dadelo
Keyword(s):  
Decision Making ◽  
Selection Criteria ◽  
Optimization Problem ◽  
Multiple Criteria Decision Making ◽  
Specific Task ◽  
Discrepancy Function ◽  
Numerical Example ◽  
Security Personnel ◽  
Criteria Weights ◽  
Elite Selection

This study presents a new KEmeny Median Indicator Ranks Accordance (KEMIRA) method for determining criteria priority and selection criteria weights in the case of two separate groups of criteria for solving multiple criteria decision making (MCDM) problem. Kemeny median method is proposed to generalize experts' opinion. Medians are calculated applying three different measure functions. Criteria weights are calculated and alternatives ranking accomplished by solving optimization problem — minimization of ranks discrepancy function calculated for two groups of criteria. A numerical example for solving specific task of elite selection from security personnel is given to illustrate the proposed method.

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