Socio-Spatial Analysis for A.H. Entrepreneurship.pptx

Socio-Spatial Analysis for Animal Husbandry (A.H.) Entrepreneurship is very important to make proper decision, resources allocation and profit maximization.

1. Socio-Spatial Analysis for Animal Husbandry (A.H.) Entrepreneurship: Integrating GIS & Statistical Software for Data-Driven Insights Asif Mohammad Senior Scientist ICAR-National Dairy Research Institute, E.R.S., Kalyani-741235 West Bengal, India e-mail : [email protected]

2. Introduction GIS and statistical tools for analyzing resource allocation, market access, and policy impacts in A.H. entrepreneurship . Employs a complex systems approach to understand local spatial interactions and emergent behaviors, providing a holistic view of rural entrepreneurship . Demonstrates the effectiveness of a socio-spatial lens over traditional models in rural contexts for understanding and informing community-level policies . Highlights the influence of socio-spatial inequalities on economic performance and political stability . Links local cultural dynamics with spatial patterns of entrepreneurship, recognizing its role in uneven economic geographies . Emphasizes GIS-driven innovation and sustainable growth potential in SMEs.

3. Utilisation of Socio-Spatial Analysis in Animal Husbandry Entrepreneurship Optimum Utilization of Resources GIS data identifies suitable places based on natural assets. Spatial analysis aids efficient resource allocation, reducing waste. Encourages sustainable practices and improved financial results. Market Accessibility GIS data examines proximity to markets and transport infrastructure. Strategic location reduces costs, improves product delivery. Enhances planning, adapts to market conditions and logistical challenges.

4. Policy and Regulation Compliance GIS maps zoning rules, environmental laws, and incentives. Ensures compliance, identifies advantageous locations. Maximizes financial assistance, enhancing viability and profit. Social and Economic Impact Examines socioeconomic factors for informed business decisions. Aligns operations with local economic landscapes and needs. Promotes community development and economic growth.

5. Integrating GIS and Statistical Software Geographic Information Systems (GIS) GIS Tools : ArcGIS, QGIS, and Google Earth Engine for spatial data analysis. Functions : Visualize land use, analyze terrain, monitor environmental changes. Applications : Identify cattle breeds, feed, and fodder availability. Benefits : Overlay diverse data layers, optimize resource allocation, enhance viability. Statistical Software Tools : R, SAS, and SPSS for statistical analysis of datasets. Capabilities : Handle large datasets, run sophisticated tests, generate reliable results. Integration : Combine with GIS for comprehensive spatial and statistical analysis. Outcomes : Inform data-driven decisions, improve understanding of influencing factors .

6. Methodology for Socio-Spatial Analysis

7. Downloading shape files

8. Creating new ‘QGIS project’

9. Creating new layer in QGIS

10. Creation of Map using QGIS

11. Saving the map in print layout

12. Creation of map for entrepreneurship on Black Bengal goat

13. Socio-Spatial variation for Animal Husbandry Entrepreneurship Socio-Spatial Variation and Consumer Categorization Definition : Differences in preferences and behaviors across social groups and regions. Factors : Age demographics, income levels, social norms, and geographic preferences. Application : Identifies consumer preferences for targeted marketing and segmentation. Consumer Segmentation Age Groups : Young consumers prefer exotic products; older ones prefer traditional. Economic Background : High-income consumers buy organic; lower-income prioritize cost . Value Systems and Cultural Variations Impact : Ethnic and spiritual beliefs influence consumer decisions. Strategy : Design targeted marketing, optimize product lines, find niche markets. Product Stratification and Market Analysis Approach : Offer products for specific consumer segments, e.g., basic vs. premium lines. Goal : Maximize distribution and profitability through varied product offerings. Geographical Variations Importance : Understand regional demand for better resource allocation. Example : Regions may prefer sheep products due to local traditions or dairy products.

14. Statistical Tools and Techniques Chi-Square Test Purpose : Examines associations among categorical variables. Application : Reveals differences in preferences between social groupings ANOVA (Analysis of Variance) Purpose : Analyzes means of various groups for significant differences. Application : Determines product demand variances across regions or demographics. Cluster Analysis Purpose : Groups related data points to identify segments. Application : Discovers consumer segments with similar tastes for targeted marketing. Regression Analysis Purpose : Uncovers factors driving consumer demand. Application : Shows how income, age, and location affect product consumption.

15. Statistical software SPSS Capabilities : Performs complex statistical tests like Chi-square and ANOVA. Uses : Organizes data, conducts comprehensive statistical analysis. Excel Capabilities : Provides basic statistical operations for data management. Uses : Useful for simpler statistical analyses and data organization. JASP Capabilities : Open-source software with a user-friendly interface. Uses : Performs various statistical analyses including Bayesian analysis, PCA, SEM. Benefits for Entrepreneurs Insights : Understand consumer behavior and industry trends. Decision-Making : Informed decisions on product development, marketing, and growth. Advantages : Enhances efficiency, reduces risks, and increases profitability.

16. Conclusion Data-Driven Decision Making Tools : Combines GIS and statistical software for comprehensive socio-spatial analysis. Benefits : Enhances resource usage, market access, and decision-making efficiency. Optimizing Operations Site Selection : Identifies suitable farming locations based on spatial and statistical data. Evaluations : Assesses environmental, socioeconomic factors, and regulatory compliance. Increasing Efficiency and Profitability Informed Choices : Data-driven decisions improve operational efficiency and profitability. Sustainable Practices : Promotes responsible resource use, reducing environmental impacts. Inclusive Growth Marginalized Involvement : Develops strategies to include marginalized communities in the value chain. Enhancing Planning and Leadership Comprehensive Approach : Improves planning and operational leadership in A.H. entrepreneurship. Sector Goals : Aids in achieving socioeconomic development and sustainability objectives.

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