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Global Connected Agriculture Market to reach USD XX billion by the end of 2029.

Global Connected Agriculture Market Size study & Forecast, by Service (Micro-Lending services, Micro- Insurance services, Mobile payment services and Mobile information services), by Solution (Trading, Bartering and Tendering), by Application (Smart logistics and Smart irrigation) and Regional Analysis, 2022-2029

Product Code: OIRAL-54742637
Publish Date: 24-04-2023
Page: 200

Global Connected Agriculture Market is valued at approximately USD XX billion in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. Through the use of mobile technology, connected agriculture supports various stakeholders along the farming or agricultural value chain. This technology consists of a wide range of devices and sub-segments, including voice, data, and connectivity networks. Access to financial solutions has improved with the emergence of linked agriculture. Also, with connected agriculture technologies, access to reasonable financial solutions can be tailored to agricultural needs. In addition, technology makes it possible for business owners to connect with buyers, sellers, traders, and more. The increasing adoption of agri-mobile driven solutions and growing investment from leading telecom operators are key factors driving the market growth.

Over the years the adoption of agri-mobile driven solutions in agriculture has significantly increased creating strong demand for Global Connected Agriculture Market. For instance – as per Statista – in 2018, the global agricultural IoT market was valued at USD 14.79 billion, and it further increased to USD 28.64 billion in 2023. Moreover, leading telecom operators worldwide are investing in connected agriculture hence this factor would positively influence the market during the projected period. For instance – in December 2019, Telus, the Canadian telecommunications company, acquired Canadian farmtech startup Decisive Farming. Additionally, Decisive Farming specializes in precision agronomics, crop marketing, and information management services among others. Also, growing emergence of AI & ML technologies as well as favorable initiatives from government authorities would offer lucrative opportunities for the market over the forecast period. However, lack of awareness towards connected agriculture hinders the market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Connected Agriculture Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to the dominance of branded products and the availability of required technological infrastructure in the region. Whereas Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as rising number of initiatives from government authorities as well as rising penetration of leading market players in the region. For instance – in Feb 2023, in New Delhi, India the Ministry of Agriculture & Farmers Welfare of the Government of India and Digital Green inked a Memorandum of Understanding to create a national-level digital extension platform. The website will house a digital library of well-vetted content in multiple languages and formats, making it easier for extension workers to access and share content with farmers.

Major market players included in this report are:
Trimble Navigation Limited
SAP SE
IBM Corporation
Syspro Inc
Microsoft Corporation
Orange Business Services
Cisco Systems, Inc.
Epicor Software Corporation
SAGE Group Plc
AT&T Inc.

Recent Developments in the Market:
Ø In September 2022, Ericsson and the Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW), funded by the National Science Foundation and a consortium of industry partners, entered into a collaboration for advancement of the use of 5G for drone operations in support of smart agriculture.

Global Connected Agriculture Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Service, Solution, Application, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Service
Micro-Lending services
Micro- Insurance services
Mobile payment services
Mobile information services

By Solution
Trading
Bartering
Tendering

By Application
Smart logistics
Smart irrigation

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
RoLA
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Connected Agriculture Market, by Region, 2019-2029 (USD Billion)
1.2.2. Connected Agriculture Market, by Service, 2019-2029 (USD Billion)
1.2.3. Connected Agriculture Market, by Solution, 2019-2029 (USD Billion)
1.2.4. Connected Agriculture Market, by Application, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Connected Agriculture Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Connected Agriculture Market Dynamics
3.1. Connected Agriculture Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing adoption of agri-mobile driven solutions
3.1.1.2. Growing investment from leading telecom operators
3.1.2. Market Challenges
3.1.2.1. Lack of awareness towards connected agriculture
3.1.3. Market Opportunities
3.1.3.1. Growing emergence of AI & ML technologies
3.1.3.2. Favourable initiatives from government authorities
Chapter 4. Global Connected Agriculture Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Connected Agriculture Market, by Service
6.1. Market Snapshot
6.2. Global Connected Agriculture Market by Service, Performance – Potential Analysis
6.3. Global Connected Agriculture Market Estimates & Forecasts by Service 2019-2029 (USD Billion)
6.4. Connected Agriculture Market, Sub Segment Analysis
6.4.1. Micro-Lending services
6.4.2. Micro- Insurance services
6.4.3. Mobile payment services
6.4.4. Mobile information services
Chapter 7. Global Connected Agriculture Market, by Solution
7.1. Market Snapshot
7.2. Global Connected Agriculture Market by Solution, Performance – Potential Analysis
7.3. Global Connected Agriculture Market Estimates & Forecasts by Solution 2019-2029 (USD Billion)
7.4. Connected Agriculture Market, Sub Segment Analysis
7.4.1. Trading
7.4.2. Bartering
7.4.3. Tendering
Chapter 8. Global Connected Agriculture Market, by Application
8.1. Market Snapshot
8.2. Global Connected Agriculture Market by Application, Performance – Potential Analysis
8.3. Global Connected Agriculture Market Estimates & Forecasts by Application 2019-2029 (USD Billion)
8.4. Connected Agriculture Market, Sub Segment Analysis
8.4.1. Smart Logistics
8.4.2. Smart Irrigation
Chapter 9. Global Connected Agriculture Market, Regional Analysis
9.1. Connected Agriculture Market, Regional Market Snapshot
9.2. North America Connected Agriculture Market
9.2.1. U.S. Connected Agriculture Market
9.2.1.1. Service breakdown estimates & forecasts, 2019-2029
9.2.1.2. Solution breakdown estimates & forecasts, 2019-2029
9.2.1.3. Application breakdown estimates & forecasts, 2019-2029
9.2.2. Canada Connected Agriculture Market
9.3. Europe Connected Agriculture Market Snapshot
9.3.1. U.K. Connected Agriculture Market
9.3.2. Germany Connected Agriculture Market
9.3.3. France Connected Agriculture Market
9.3.4. Spain Connected Agriculture Market
9.3.5. Italy Connected Agriculture Market
9.3.6. Rest of Europe Connected Agriculture Market
9.4. Asia-Pacific Connected Agriculture Market Snapshot
9.4.1. China Connected Agriculture Market
9.4.2. India Connected Agriculture Market
9.4.3. Japan Connected Agriculture Market
9.4.4. Australia Connected Agriculture Market
9.4.5. South Korea Connected Agriculture Market
9.4.6. Rest of Asia Pacific Connected Agriculture Market
9.5. Latin America Connected Agriculture Market Snapshot
9.5.1. Brazil Connected Agriculture Market
9.5.2. Mexico Connected Agriculture Market
9.5.3. Rest of Latin America Connected Agriculture Market
9.6. Rest of The World Connected Agriculture Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Trimble Navigation Limited
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. SAP SE
10.2.3. IBM Corporation
10.2.4. Syspro Inc
10.2.5. Microsoft Corporation
10.2.6. Orange Business Services
10.2.7. Cisco Systems, Inc.
10.2.8. Epicor Software Corporation
10.2.9. SAGE Group Plc
10.2.10. AT&T Inc.
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Data Collection:
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Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
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Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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