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Global Street Cleaning Machine Market to reach USD 1.28 billion by the end of 2029.

Global Street Cleaning Machine Market Size study & Forecast, by Product Type (Walk-behind, Ride-on and truck mounted), by Product category (Sweepers, Washers), by Mode of operation (Electric, Manual and ICE), by Business type (New sales, Aftermarket) and Regional Analysis, 2022-2029

Product Code: OIRIME-26061515
Publish Date: 25-01-2023
Page: 200

Global Street Cleaning Machine Market is valued at approximately USD 0.73 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 7.3% over the forecast period 2022-2029. Street Cleaning Machines also known as road sweeping machines utilized for cleaning roads and streets. These machines are used by government authorities such as municipal corporations for effective cleaning of streets. These machines are comprised of motors and vacuum based suction cups that are attached to the lower part of the cleaning machine. The suctions cups collect dust and waste and store it in the tank attached to the upper part of the machine. These machines are available in manual handling and automatic modes. The increasing expansion of waste management sector and growing investment in road networks as well as strategic initiatives from leading market players are key factors accelerating the market growth.

The rapid expansion of waste management industry worldwide is contributing to the growth of the Global Street Cleaning Machine Market. For instance, according to Statista – in 2020, the global waste management market was estimated at USD 1.61 trillion, and it is projected to grow to USD 2.5 trillion by 2030. Also, rising technological advancements in automotive sector and growing awareness towards street cleaning & sanitization would create lucrative growth prospects for the market over the forecast period. However, high deployment costs associated with street cleaning machines and periodic maintenance requirements impede the market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Street Cleaning Machine Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America is the leading region in terms of market share owing to presence of leading market players and increasing focus on street and road cleaning in the region. Whereas Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as rising number of initiatives from leading market players to promote cleanliness and increasing penetration of leading market players.

Major market players included in this report are:
Alfred Karcher GMBH & Co. KG
Bortex Industries
Boschung Mecatronic AG
Dulevo SpA
Fayat Group
Global Environmental Products, Inc
Hako Group
Kam Avida Enviro Engineers
Schwarze Industries
Tennant Company

Recent Developments in the Market:
 In October 2020, Finland based street maintenance technology company Trombia Technologies launched high-power electric, autonomous street sweeper.

 In April 2022, China based WeRide, an autonomous driving company unveiled a new Robo Street Sweeper. This new robot is a mass-produced and purpose-built self-driving sweeper vehicle.

Global Street Cleaning Machine 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 Product Type, Product Category, Mode of Operation, Business Type, 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 Product Type
Ride-on and truck mounted

By Product category

By Mode of operation
Manual and ICE

By Business Type
New sales

By Region:
North America
Asia Pacific
South Korea
Latin America
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. Street Cleaning Machine Market, by Region, 2019-2029 (USD Billion)
1.2.2. Street Cleaning Machine Market, by Product Type, 2019-2029 (USD Billion)
1.2.3. Street Cleaning Machine Market, by Product Category, 2019-2029 (USD Billion)
1.2.4. Street Cleaning Machine Market, by Mode of Operation, 2019-2029 (USD Billion)
1.2.5. Street Cleaning Machine Market, by Business Type, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Street Cleaning Machine 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 Street Cleaning Machine Market Dynamics
3.1. Street Cleaning Machine Market Impact Analysis (2019-2029)
3.1.1. Market Drivers Increasing expansion of waste management sector Growing investment in road networks Strategic initiatives from leading market players
3.1.2. Market Challenges High deployment cost associated with street cleaning machines Periodic maintenance requirement
3.1.3. Market Opportunities Rising technological advancements in automotive sector Growing awareness towards street cleaning & Sanitization
Chapter 4. Global Street Cleaning Machine 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 Street Cleaning Machine Market, by Product Type
6.1. Market Snapshot
6.2. Global Street Cleaning Machine Market by Product Type, Performance – Potential Analysis
6.3. Global Street Cleaning Machine Market Estimates & Forecasts by Product Type 2019-2029 (USD Billion)
6.4. Street Cleaning Machine Market, Sub Segment Analysis
6.4.1. Walk-behind
6.4.2. Ride-on and truck mounted
Chapter 7. Global Street Cleaning Machine Market, by Product Category
7.1. Market Snapshot
7.2. Global Street Cleaning Machine Market by Product Category, Performance – Potential Analysis
7.3. Global Street Cleaning Machine Market Estimates & Forecasts by Product Category 2019-2029 (USD Billion)
7.4. Street Cleaning Machine Market, Sub Segment Analysis
7.4.1. Sweepers
7.4.2. Washers
Chapter 8. Global Street Cleaning Machine Market, by Mode of Operation
8.1. Market Snapshot
8.2. Global Street Cleaning Machine Market by Mode of Operation, Performance – Potential Analysis
8.3. Global Street Cleaning Machine Market Estimates & Forecasts by Mode of Operation 2019-2029 (USD Billion)
8.4. Street Cleaning Machine Market, Sub Segment Analysis
8.4.1. Electric
8.4.2. Manual and ICE
Chapter 9. Global Street Cleaning Machine Market, by Business Type
9.1. Market Snapshot
9.2. Global Street Cleaning Machine Market by Business Type, Performance – Potential Analysis
9.3. Global Street Cleaning Machine Market Estimates & Forecasts by Business Type 2019-2029 (USD Billion)
9.4. Street Cleaning Machine Market, Sub Segment Analysis
9.4.1. New Sales
9.4.2. Aftermarket
Chapter 10. Global Street Cleaning Machine Market, Regional Analysis
10.1. Street Cleaning Machine Market, Regional Market Snapshot
10.2. North America Street Cleaning Machine Market
10.2.1. U.S. Street Cleaning Machine Market Product Type breakdown estimates & forecasts, 2019-2029 Product Category breakdown estimates & forecasts, 2019-2029 Mode of Operation breakdown estimates & forecasts, 2019-2029 Business Type breakdown estimates & forecasts, 2019-2029
10.2.2. Canada Street Cleaning Machine Market
10.3. Europe Street Cleaning Machine Market Snapshot
10.3.1. U.K. Street Cleaning Machine Market
10.3.2. Germany Street Cleaning Machine Market
10.3.3. France Street Cleaning Machine Market
10.3.4. Spain Street Cleaning Machine Market
10.3.5. Italy Street Cleaning Machine Market
10.3.6. Rest of Europe Street Cleaning Machine Market
10.4. Asia-Pacific Street Cleaning Machine Market Snapshot
10.4.1. China Street Cleaning Machine Market
10.4.2. India Street Cleaning Machine Market
10.4.3. Japan Street Cleaning Machine Market
10.4.4. Australia Street Cleaning Machine Market
10.4.5. South Korea Street Cleaning Machine Market
10.4.6. Rest of Asia Pacific Street Cleaning Machine Market
10.5. Latin America Street Cleaning Machine Market Snapshot
10.5.1. Brazil Street Cleaning Machine Market
10.5.2. Mexico Street Cleaning Machine Market
10.5.3. Rest of Latin America Street Cleaning Machine Market
10.6. Rest of The World Street Cleaning Machine Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. Alfred Karcher GMBH & Co KG Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
11.2.2. Bortex Industries
11.2.3. Boschung Mecatronic AG
11.2.4. Dulevo SpA
11.2.5. Fayat Group
11.2.6. Global Environmental Products, Inc
11.2.7. Hako Group
11.2.8. Kam Avida Enviro Engineers
11.2.9. Schwarze Industries
11.2.10. Tennant Company
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
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Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
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.
Market Size Estimation:
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.
Insight Generation & Report Presentation:
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Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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