scholarly journals Effectiveness of Use-value Assessment in Preserving Farmland: A Search-theoretic Approach

1995 ◽  
Vol 27 (2) ◽  
pp. 626-635 ◽  
Author(s):  
Edmund M. Tavernier ◽  
Farong Li
Keyword(s):  
Agricultural Land ◽  
Past Research ◽  
Farm Income ◽  
Reservation Price ◽  
Theoretic Approach ◽  
Use Value ◽  
Value Assessment ◽  
Tax Rate ◽  
The Difference ◽  
The Impact

AbstractSearch theory is used to present a theoretically defensible model to examine the effectiveness of use value assessment (UVA) in preserving farmland. The model is empirically tractable and supports the findings of past research. The analysis considers the impact of farm income, uncertainty, and the distribution of the offer price on the effectiveness of UVA in preserving farmland and shows, through the effect on the reservation price, that for a given distribution of the offer price, property-tax rate, and the difference between market-value and use-value of land, the preservation of agricultural land only takes place within a relevant range.

scholarly journals Retweet Prediction Based on User Behavior

2021 ◽  
Author(s):  
Syeda Nadia Firdaus
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Prediction Model ◽  
Matrix Factorization ◽  
Information Diffusion ◽  
User Behavior ◽  
Past Research ◽  
The Difference ◽  
The Impact

Social network is a hot topic of interest for researchers in the field of computer science in recent years. These social networks such as Facebook, Twitter, Instagram play an important role in information diffusion. Social network data are created by its users. Users’ online activities and behavior have been studied in various past research efforts in order to get a better understanding on how information is diffused on social networks. In this study, we focus on Twitter and we explore the impact of user behavior on their retweet activity. To represent a user’s behavior for predicting their retweet decision, we introduce 10-dimentional emotion and 35-dimensional personality related features. We consider the difference of a user being an author and a retweeter in terms of their behaviors, and propose a machine learning based retweet prediction model considering this difference. We also propose two approaches for matrix factorization retweet prediction model which learns the latent relation between users and tweets to predict the user’s retweet decision. In the experiment, we have tested our proposed models. We find that models based on user behavior related features provide good improvement (3% - 6% in terms of F1- score) over baseline models. By only considering user’s behavior as a retweeter, the data processing time is reduced while the prediction accuracy is comparable to the case when both retweeting and posting behaviors are considered. In the proposed matrix factorization models, we include tweet features into the basic factorization model through newly defined regularization terms and improve the performance by 3% - 4% in terms of F1-score. Finally, we compare the performance of machine learning and matrix factorization models for retweet prediction and find that none of the models is superior to the other in all occasions. Therefore, different models should be used depending on how prediction results will be used. Machine learning model is preferable when a model’s performance quality is important such as for tweet re-ranking and tweet recommendation. Matrix factorization is a preferred option when model’s positive retweet prediction capability is more important such as for marketing campaign and finding potential retweeters.

scholarly journals Retweet Prediction Based on User Behavior

2021 ◽  
Author(s):  
Syeda Nadia Firdaus
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Prediction Model ◽  
Matrix Factorization ◽  
Information Diffusion ◽  
User Behavior ◽  
Past Research ◽  
The Difference ◽  
The Impact

Social network is a hot topic of interest for researchers in the field of computer science in recent years. These social networks such as Facebook, Twitter, Instagram play an important role in information diffusion. Social network data are created by its users. Users’ online activities and behavior have been studied in various past research efforts in order to get a better understanding on how information is diffused on social networks. In this study, we focus on Twitter and we explore the impact of user behavior on their retweet activity. To represent a user’s behavior for predicting their retweet decision, we introduce 10-dimentional emotion and 35-dimensional personality related features. We consider the difference of a user being an author and a retweeter in terms of their behaviors, and propose a machine learning based retweet prediction model considering this difference. We also propose two approaches for matrix factorization retweet prediction model which learns the latent relation between users and tweets to predict the user’s retweet decision. In the experiment, we have tested our proposed models. We find that models based on user behavior related features provide good improvement (3% - 6% in terms of F1- score) over baseline models. By only considering user’s behavior as a retweeter, the data processing time is reduced while the prediction accuracy is comparable to the case when both retweeting and posting behaviors are considered. In the proposed matrix factorization models, we include tweet features into the basic factorization model through newly defined regularization terms and improve the performance by 3% - 4% in terms of F1-score. Finally, we compare the performance of machine learning and matrix factorization models for retweet prediction and find that none of the models is superior to the other in all occasions. Therefore, different models should be used depending on how prediction results will be used. Machine learning model is preferable when a model’s performance quality is important such as for tweet re-ranking and tweet recommendation. Matrix factorization is a preferred option when model’s positive retweet prediction capability is more important such as for marketing campaign and finding potential retweeters.

scholarly journals Precio de la tierra con presión urbana: Un modelo para España

2011 ◽  
Vol 8 (1) ◽  
pp. 3 ◽  
Author(s):  
Esther Decimavilla ◽  
Carlos San Juan ◽  
Stefan Sperlich
Keyword(s):  
Panel Data ◽  
Agricultural Land ◽  
Housing Prices ◽  
Farm Income ◽  
Land Type ◽  
Regional Specialization ◽  
Agricultural Income ◽  
Key Variables ◽  
Agricultural Land Prices ◽  
The Impact

This paper examines agricultural land prices and the variables that affect them as a way of identifying and explaining the recent price cycle in Spain. The key variables in our panel data model are location and expected farm income as fundamental factors and housing prices and increases in irrigated areas as nonfundamental dependant variables. The price cycle is also related to regional specialization and the impact of integration in the CAP. The novelty of the paper consists in the use of panel data models to identify fundamental factors related to agricultural productivity (expected agricultural income) and location and nonfundamental or speculative factors (housing prices, irrigated areas and demographic changes) using regional data associated with land type.

scholarly journals Smallholder Coffee Productivity as Affected by Socioeconomic Factors and Technology Adoption

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Daniel M. Wambua ◽  
Bernard M. Gichimu ◽  
Samuel N. Ndirangu
Keyword(s):  
Technology Adoption ◽  
Socioeconomic Factors ◽  
Land Tenure ◽  
Agricultural Land ◽  
Smallholder Farmers ◽  
Farm Income ◽  
Small Scale ◽  
Farm Level ◽  
Positive Effects ◽  
The Impact

Despite the increase in area under coffee in Kenya in the last decade, productivity has been on the decline. Numerous production technologies have been developed through on-station research but there has been limited on-farm research to assess the impact of these technologies at the farm level. On the other hand, smallholder farmers are endowed differently and this would positively or negatively affect the adoption of recommended technologies and hence coffee productivity. This study was carried out to evaluate the effects of socioeconomic factors and technology adoption on smallholder coffee productivity at the farm level. The study employed stratified random sampling where 376 farmers were randomly sampled from six cooperative societies which had been preselected using probability proportional to the size sampling technique. The effects of socioeconomic factors and technology adoption on coffee productivity were analyzed using the stochastic Cobb-Douglas production function. The study revealed that off-farm income, access to credit, type of land tenure, and land size had significant positive effects on coffee productivity. Therefore, coffee farmers should be encouraged to diversify their income sources and to embrace credit financing, as the government reviews land use policies to avail adequate agricultural land. The study further revealed that the adoption of recommended application rates of manure, fungicides, and pesticides had significant positive effects on coffee productivity. The adoption of these technologies should therefore be enhanced among small-scale farmers to improve coffee productivity at the farm level.

scholarly journals Assessing the Impact of Rythu Bandhu Scheme in Warangal District of Telangana

2021 ◽  
pp. 335-340
Author(s):  
C. D. Amitha ◽  
C. Karthikeyan ◽  
M. Nirmala Devi
Keyword(s):  
Farm Income ◽  
Purchasing Power ◽  
Agricultural Activities ◽  
Cropping Intensity ◽  
Significant Difference ◽  
Before And After ◽  
Telangana State ◽  
The Difference ◽  
The Government ◽  
The Impact

Rythu Bandhu Scheme (RBS) also Farmers investment Support Scheme is a welfare program to support farmer investment for two crops a year where the cash is paid directly by the Government of Telangana. A sample of 60 beneficiaries were selected from Warangal district of Telangana state. In order to find out the impact of RBS on beneficiaries - inputs purchasing power, continuity in farming, rural indebtedness, productivity, farm income(in Rs.) and cropping intensity were studied before and after implementation of RBS i.e., in 2016-17 and 2020-21 for beneficiaries.  Based on the results in respective year, “Z” test was applied to find out the difference after the implementation of scheme. From the analysis, it was found that significant difference was observed among respondents with respect to inputs purchasing power (6.74*), continuity in farming (2.93*), rural indebtedness (4.02*), productivity (3.72*), farm income (4.53*). RBS is increasing the beneficiaries capacity to purchase inputs with timely performing agricultural activities, their likeliness to continue farming and better coping with debt.

scholarly journals Assessment of an Impact of Mechanical Regulation on Selected Morphometric and Productive Parameters of Invasive Species Solidago Canadensis Population in Agricultural Land

2015 ◽  
Vol 61 (4) ◽  
pp. 121-128
Author(s):  
Lýdia Končeková ◽  
Eva Zahradníková ◽  
Eduard Pintér ◽  
Daniela Halmová
Keyword(s):  
Agricultural Land ◽  
Dry Weight ◽  
Effective Control ◽  
Solidago Canadensis ◽  
Growing Period ◽  
Anthropogenic Habitat ◽  
The Difference ◽  
The Impact ◽  
Number Of Individuals ◽  
Mechanical Regulation

Abstract Repeated mowing is considered as one of the effective control methods against species of the genus Solidago. This paper evaluates the impact of the repeated mowing on selected morphometric and productive characteristics of the invasive neophyte Solidago canadensis in the district of Rimavská Sobota in Central Slovakia. Permanent research plots (PRPs) were established within anthropogenic habitat on an abandoned land that was divided into two variants. In the first variant, the mechanical regulation - mowing was applied. The second variant was without the regulation. The mechanical regulation of the populations was carried out in June and August during the growing season 2011. The results showed that the mechanical regulation did not have a clear impact on the population density. The decreasing trend of the number of shoots within the mowed variant was found only in one research plot (PRP3). The other plots showed an increase in the number of individuals by 2.7 and 32.7% between the mowings. Statistically highly significant differences in terms of the mowing impact on the height of the individuals were found in all PRPs. The difference in the weight of dry aboveground biomass between the mowings was 221.87 g, which represents 36.41%. Double the difference (48.8%) was recorded in the dry weight of the underground biomass in the regulated stand compared with the unregulated stand (165.1 and 322.5 g/m2, respectively). Although there was a short-term success achieved by the application of the two mowings during the growing period, the pursued objective was not reached.

scholarly journals KESESUAIAN SOSIAL EKONOMIPERLINDUNGAN LAHAN PERTANIAN PANGAN BERKELANJUTAN DI KABUPATEN KUNINGAN

2016 ◽  
Vol 3 (2) ◽  
Author(s):  
Danang Pramudita ◽  
Arya Hadi Dharmawan ◽  
Baba Barus
Keyword(s):  
Food Production ◽  
Agricultural Land ◽  
Technical Problem ◽  
Farm Income ◽  
Land Conversion ◽  
Land Preservation ◽  
Economic Characteristic ◽  
Agriculture Labor ◽  
The Impact ◽  
Program Data

Economic development in Indonesia since 1980s is dealing with conversion of agricultural land to industry, housing, and other sector in city and its periphery. Land conversion have a great impact to food production rather than the impact from technical problem (drought and pest problem). Government need to preserve agricultural land in order to maintain food production. Thus government made a mandatory approach byissued Law No. 41 year 2009. The aim of this research are to identify an actual socioeconomic characteristics in the area of land preservation program (LP2B) in Kuningan Regency, to identify farmers perception on LP2B and to analyze socioeconomic suitability in the areaof LP2B program. Data were analyzed by descriptive statistics and likert scale. Based on the result, there are nine socioeconomic indicator on land preservation program (LP2B) in Kuningan Regency, namely; land conversion rate, food balance, disparity between farm and non-farm income, agriculture households, agriculture labor, farmers’ groups, spatial planning policies and farmers perceptions. Farmers have a positive perception on LP2B program. Land preservation program (LP2B) priority should be donein Cilimus sub district due to low support of socio economic characteristic. Meanwhile Ciawigebang and Cibingbin sub district become a next priority of preservation.<br />Keyword : farmer’s perception, food security, land conversion, socioeconomic of LP2B

scholarly journals Analysis of the impact of Praganna Irrigation Project (PIP) on income and employment in Dang District of Nepal

2015 ◽  
Vol 16 ◽  
pp. 142-151
Author(s):  
Yadav Pradhyoti ◽  
Jay Prakash Dutta ◽  
Punya Prasad Regmi ◽  
Narendra Kumar Chaudhary
Keyword(s):  
Simple Random Sampling ◽  
Farm Income ◽  
Variable Cost ◽  
Command Area ◽  
Gini Coefficients ◽  
Irrigation Project ◽  
Significant Difference ◽  
The Difference ◽  
On Farm ◽  
The Impact

A survey research was conducted to assess the performance of Praganna Irrigation Project with respect to farm income and employment in Dang district of Nepal. Simple random sampling was used to select 60 beneficiaries and 30 non-beneficiaries as sampling units to comprise a sample size of 90. Representatives of WUGs and officials of PIP were interviewed through checklists. Altogether there were 75 WUGs, which are responsible for distribution of irrigation water equitably and collection of irrigation charges effectively. A comparative study was made between the beneficiaries and nonbeneficiaries under PIP. The total farm assets of beneficiaries were estimated at NRs. 1,150,975 and differed significantly with the non-beneficiaries with total farm assets of NRs. 875,185. A significant difference was observed between on farm income of beneficiaries (NRs.183,260) and non– beneficiaries (NRs. 31,453). The net farm income of the beneficiaries and non-beneficiaries were estimated at NRs. 79,993 and NRs. 13,077 respectively and the difference were significant among the categories of respondents. The total farm income was significantly affected by landholding, total variable cost, cropping intensity, and employment in case of beneficiaries whereas only employment significantly affected total farm income in case of non-beneficiaries. Gini coefficients for gross household and gross farm income were calculated at 0.37 and 0.44 respectively for beneficiaries and 0.44 and 0.27 respectively for non-beneficiaries. So, there existed inequality in distribution of gross household and gross farm incomes within both categories. The study also indicated the huge potentiality of PIP for increasing farm income in the command area of PIP.

scholarly journals DAMPAK KONVERSI LAHAN PERTANIAN TERHADAP PENDAPATAN RUMAH TANGGA PETANI DI KABUPATEN KARANGANYAR

2017 ◽  
Vol 27 (1) ◽  
pp. 93
Author(s):  
Umi Barokah ◽  
Suprapti Supardi ◽  
Sugiharti Mulya Handayani
Keyword(s):  
Household Income ◽  
Agricultural Land ◽  
Secondary Data ◽  
Farm Households ◽  
Primary Data ◽  
Farm Income ◽  
Test Analysis ◽  
Field Function ◽  
The Impact

<p>This study aims to (1) analyzing the amount of land conversion and the factors that affect, (2) identify and analyze changes in household income structure of farm households, (3) analyze the impact of conversion on agricultural land to the income distribution, employment and welfare of farm households. The basic method on this study is a descriptive analytic. Determination of the districts location is based on (1) the number of people who worked as farmers themselves, (2) the amount and type of existing industries and (3) ease of reaching the central interconnected economy. Sub-district is elected Jumantono and Jaten. Type of data used include (1) primary data is the results of interviews with farm households, (2) secondary data from relevant instances. The results showed (1) during the 12 years there is a change 0,120 ha of wet rice field function per household farmer and owned land is the only factor affecting the conversion of agricultural land; (2) The proportion of farm income reduced by 8.30% from 42% to 33.7% and the proportion of outside farm income increased 10.30% from 54% to 64.30%), (3) the results of t test analysis with α = 5 % shows the employment and household income of farmers before the conversion is not the same as after the conversion of agricultural land (revenue increased to Rp 1.482 million per year). </p>

scholarly journals PERANAN PEMELIHARAAN TANAMAN MANGGIS TERHADAP PENDAPATAN PETANI DI JAWA BARAT

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Eti Suminartika
Keyword(s):  
Family Income ◽  
Foreign Market ◽  
Primary Data ◽  
Survey Method ◽  
Farm Income ◽  
Cultivation Method ◽  
The Family ◽  
Plant Maintenance ◽  
The Difference ◽  
The Impact

ABSTRAKPangsa pasar manggis masih terbuka lebar baik di dalam maupun di luar negeri, namun hanya 10persen manggis kita yang dapat diekspor, hal tersebut disebabkan oleh budidaya tanaman manggismasih sangat tradisional, jarang dipupuk, dibersihan dan dipangkas. Tujuan penelitian ini adalahmenganalisis pemeliharaan tanaman manggis, menganalisis perbedaan pendapatan usahatanimanggis dan menganalisis kontribusi pendapatan usahatani manggis terhadap pendapatan keluargapetani. Penelitian ini menggunakan data sekunder dan primer dengan menggunakan metoda survey.Selanjutnya data dianalisis dengan menggunakan analisis deskriptif, matematik dan ekonometrik.Penelitian dilaksanakan di sentra produksi manggis Jawa Barat yaitu di kabupaten Tasikmalaya danSubang. Hasil penelitian menunjukkan petani manggis di kabupaten Tasikmalaya lebih lebihmemelihara tanaman manggisnya dibandingkan di kabupaten Subang, meskipun demikianpemeliharaan tanaman di kedua kabupaten tersebut masih dibawah standar, dampaknya, pendapatandan keuntungan usahatani manggis di kabupaten Tasikmalaya lebih tinggi dibanding di kabupatenSubang dengan perbedaan yang signifikan secara statistik, oleh karenanya, pendapatan usahatanimanggis memiliki peranan yang besar terhadap pendapatan keluarga petani di kabupatenTasikmalaya.Kata kunci: manggis, pendapatan, keuntungan, pemeliharaan tanaman.ABSTRACTMarket share of mangosteen is still high both in the local and foreign market, but only 10 per cent ofIndonesian mangosteen can be exported. This is due to improper cultivation method such as rarelyfertilizing, weeding and other maintenance. Lack of maintenance of mangosteen farm can lowers thequality and productivity of trees. The purpose of this study was to analyse the maintenance ofmangosteen farm, the differences of mangosteen farm income and the contribution of mangosteenfarm income to the family income. This study used secondary and primary data which obtained fromfarmers, by using survey method. The data were analysed by using descriptive, mathematics andeconometrics analysis. Research was conducted in two of mangosteen production centres in WestJava, namely Tasikmalaya and Subang district. The results show that mangosteen farmers in theTasikmalaya is better at maintaining their garden than those in Subang, though the maintenance ofthe two districts are still below standard. The impact of the mangosteen farm income in Tasikmalayais higher than in Subang, the difference of income is statistically significant for both area. Therefore,mangosteen farm income has a major contribution on the family income, especially in Tasikmalaya.Keywords: mangosteen, farm income, plant maintenance.

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