Is that Environmental Factor Affected the Distressed Farmers’ most!? - An Exploratory Factor Analysis of Constraint and Amelioration Strategies in National Calamity Hit Region of India

Abstract

The Kosi River is infamous in India for its rapid and recurrent changes of course and the widespread flood damages it causes almost annually. But, the flood of 18th August, 2008 was the most devastating down the memory lane of the survival. The destruction was of such a magnitude that state government of Bihar had to seek World Bank (Project ID: P122096) assistance. Keeping this in view, an earnest effort was made to study the perceived constraints of distressed farmers and strategies for its amelioration. To materialize pretested closed structured interview schedule the application of the principle axis factoring vis-à-vis exploratory factor analysis (EFA) was done among 60 respondents from the non-sample. EFA extracted 4 latent broad constraints having Eigen value >1 that was rechristened as: environmental, pecuniary, policy and miscellaneous constraints. Finally, 20 specific constraints under 4 broad constraints were used to collect data from 160 respondents in the sample area. Garret methodology was used to rank the specific constraints under broad constraints. Friedman two-way ANOVA by ranks test deciphered that severity order of broad constraints was environmental, pecuniary, miscellaneous and policy constraints respectively. Since, the World Bank project is running in full swing in the calamity stricken region and so the four broad constraints as well as the 20 specific constraints identified and suggestion to ameliorate these can be vital for policy formulation and its implementation. The authors also suggest that in case of dearth of fund the most severe environmental constraints should be given due weightage followed by severity of other broad constraints.

Procedural Impediments in e-NAM System Faced by Stakeholders in Guntur Mandi of Andhra Pradesh

“…So, the respondents were fi rst asked to rank the particular constraint. The order of merit thus given by the respondents was converted into percent position by using the formula as used by Lal et al (2016):…”

Profile Characteristics and Analysis of the Constraints Faced by the Dairy Farmers of Urban and Peri-Urban Areas of Indian National Capital Region vis-a-vis Using Mobile Android Application “Eco-Dairy”

“…Constraints analysis is very prevalent in survey-based research as Lal et al, (2016b) through exploratory factor analysis (EFA) explored 4 latent broad constraints having Eigen value >1, which was rechristened as: environmental, pecuniary, policy and miscellaneous constraints. Moreover, responses of the dairy farmers on extent of severity of constraints faced after national calamity was expounded by Lal et al, (2016a) by using Friedman test and it statistically identified that the most severe broad constraints perceived by dairy farmers was "technical constraints" followed by "economical constraints", "physical constraints", and "social constraints".…”

Illustrating the way to harmony amid wildlife and agriculture near sivalik mountain range of northern India: an empirical

“…13 There are 4 broad steps in conducting a case study 11,14 explained in Figure 2. Interview schedule method is widely adopted primary data collection tool [2][3][4][5][6][7] and was used to figure out and prioritize the benefits gained by the intervention. Benefits analysis is common in extension study to know the results of any intervention.…”

“…Benefits analysis is common in extension study to know the results of any intervention. The ranking procedure followed may be different for measuring perceived benefits viz., Garrett's ranking method, 6,15 mean score ranking procedure, 4 and Alfares ranking procedure. 3,16 To determine the ranking in Alfares model least-squares regression was applied to S n versus n: n 37.75756 S 3.19514 n + = Therefore, for any set of n ranked benefits (in the present manuscript n represents 4 benefits), assuming a weight of 100 percent for the first-ranked benefit, the percentage weight of benefits ranked as r is given by: Standardized Multivariate Regression Analysis 17 and Polytomous Universal Model.…”

“…Farmers in India and overseas face serious threats from pests, 1 natural calamities, [2][3][4][5][6][7] spoilage by animals 8 and other various types of crop losses, resulting in yield loss. 1 When one consider about farming near mountain range, it encompasses a lot of challenges viz., irrigation, wild animals and marketing of produce.…”