A Decision Model for Farm Management Information System Selection (MSc)

Short description

Farm Management Information Systems (FMISs) are essential tools that assist farmers in planning, monitoring, and controlling their agricultural operations. These systems offer features like crop monitoring, irrigation scheduling, financial planning, workflow management, and data analytics. Examples of FMISs tailored for arable farming include:

• CropX: Provides enterprise resource planning with workflow management and data analytics for efficient operations.
• AgroVision: Offers a suite of tools for crop management, livestock tracking, and financial planning designed to improve efficiency and decision-making in farming operations.
• 365FarmNet: Provides an all-in-one platform for comprehensive farm management, including crop planning, field monitoring, and cost analysis.
• FarmMaps: Specializes in geospatial data integration, allowing farmers to optimize their operations through precise mapping and field data insights.
• Cropin: Delivers AI-driven insights and farm-to-fork traceability, enhancing productivity and sustainability for modern agricultural enterprises.

Selecting the right FMIS and implementation partner is crucial for successful adoption, but it is often challenging and time-consuming to match FMIS capabilities with user requirements. This project addresses the challenge by developing a structured decision model to evaluate FMIS solutions for arable farming.

The project involves gathering data on existing FMIS features through market analysis and expert evaluation, followed by the creation of a decision model to help stakeholders make informed choices. The developed decision model will be validated using real-world case studies to ensure practical applicability and robustness.

The primary objective of this project is to create a structured decision model and selection tool that can assist stakeholders in evaluating and choosing the most suitable FMIS for their needs.

Objectives

The work in this project entails:

• Based on literature and document analysis, develop a decision model for evaluating Farm Management Information Systems (FMISs).
• Evaluate the decision model’s effectiveness using real-world case studies.

Tasks

The work in this master thesis entails:

1. Gathering and analyzing data on current FMIS platforms, including their technical features and functionalities, through document analysis.
2. Designing and conducting interviews with industry experts to validate and refine the identified features and characteristics of FMISs.
3. Developing a decision model to match FMIS capabilities with user requirements.
4. Applying the decision model to real-world case studies, analyzing its effectiveness, and iterating improvements based on the outcomes.

Literature

• Tummers, J., Kassahun, A., & Tekinerdogan, B. (2019). Obstacles and features of Farm Management Information Systems: A systematic literature review. Computers and Electronics in Agriculture, 157, 189-204.
• Farshidi, S., Jansen, S., de Jong, R., & Brinkkemper, S. (2018). A decision support system for software technology selection. Journal of Decision Systems, 27(sup1), 98-110.
• Verdouw, C. N., Robbemond, R. M., & Wolfert, J. (2015). ERP in agriculture: Lessons learned from the Dutch horticulture. Computers and Electronics in Agriculture, 114, 125-133.

Requirements

• Courses: Data Science Concepts (INF-34306) (Optional)
• Required skills/knowledge: Basic understanding of farm management, Basic understanding of data analysis and decision-making frameworks.

Key words: Farm MIS, Data Science, Decision Support Systems

Contact person(s)

Siamak Farshidi (siamak.farshidi@wur.nl)

Cor Verdouw (cor.verdouw@wur.nl)