Integrating artificial intelligence and machine learning is taking the global predictive maintenance market to a new level. The market is slated to grow considerably, recording a CAGR of 10.9% from 2024 to 2034.
The market indicates a valuation of US$ 80,200.0 million by 2034. The market is further set to reach US$ 10,510.0 million in 2024. Demand for predictive maintenance recorded a y-o-y growth of 6.9% in 2023.
| Attributes | Key Insights |
|---|---|
| Base Value (2023) | US$ 9,606.03 million |
| Global Predictive Maintenance Market Size (2024E) | US$ 10,510.0 million |
| Predictive Maintenance Market Value (2034F) | US$ 80,200.0 million |
| Value-based CAGR (2024 to 2034) | 10.9% |
Compared to traditional market intelligence solutions, companies are evaluating IoT data with amazing precision, accuracy, and speed because of the use of AI and ML technologies.
Predictive maintenance provides ways to minimize the time and costs associated with repairs and maintenance while lowering unscheduled downtime of production-critical equipment. Furthermore, maintenance systems ensure that assets are constantly available and in optimal operating condition.
Increasing use of predictive maintenance in mammography, X-ray, and tomography to improve operational efficiency and decision-making skills are further set to fuel the market.
The market is propelled by increasing use in several sectors, including manufacturing, aerospace, energy, defense, and transportation. The market is also projected to grow due to increasing demand for real-time streaming analytics for data processing and analysis.
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Optimizing maintenance activities by regularly monitoring equipment health and addressing minor issues is fueling demand for predictive maintenance. Growing adoption of technologies such as IoT, cloud computing, artificial intelligence, and machine learning would further increase demand and operational efficiency of predictive maintenance.
Rising demand for maintenance solutions to reduce cost & downtime and the need for real-time data analytics to process and analyze data across various industries are propelling demand.
Inadequate availability of skilled workforce with knowledge about predictive maintenance solutions is set to hinder the market. High initial costs of establishing and implementing the program, including equipment and employee training, are projected to impede the market.
Several companies face difficulty managing and analyzing the massive amounts of data required for predictive maintenance, including data collection, storage, and analysis.
Large-scale data collection, transmission, and storage inevitably raise concerns regarding security & privacy. The initiation of modern maintenance requires high capital expenditure which is set to act as a limiting factor for companies to invest in new systems.
Principal Consultant
Rising demand for efficient IT infrastructure creates opportunities for predictive maintenance solutions. Expansion of predictive maintenance solutions to healthcare devices and navigation systems for improved reliability is set to create opportunities for manufacturers.
Integrating digital twins and augmented reality (AR) are emerging technologies that enhance the visualization and simulation of maintenance scenarios. Edge computing and blockchain implementation are being increasingly used in predictive maintenance to enhance trust, transparency, and efficiency of maintenance transactions.
Implementing inspection technologies, such as infrared thermography, ultrasonic analysis, vibration monitoring, and robotic inspection to prevent equipment failures, are fueling market growth.
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From 2019 to 2023, the market experienced a CAGR of 7.6%, reaching a size of US$ 9,606.03 million in 2023. Demand for predictive maintenance solutions grew significantly from 2019 to 2023, propelled by adoption in the construction, transportation, energy, and healthcare industries.
Innovations in IoT sensors, AI algorithms, and cloud computing further enhanced the capabilities and accessibility of maintenance solutions. Several companies are using predictive analytics to shift from reactive scheduled maintenance to proactive, predictive strategies, improving operational efficiency and equipment reliability.
The market grew significantly from 2019 to 2023 as more organizations realized the benefits of predictive insights, preventing costly failures and providing the optimal asset lifecycle.
The market is set to rise at a CAGR of 10.9% from 2024 to 2034. The market size is projected to reach US$ 80,200.0 million during the forecast period. The forecast for 2024 to 2034 shows accelerated growth caused by innovations in AI, IoT, and data analytics technologies.
The table presents the projected CAGR for the market over several semi-annual periods from 2023 to 2034. In the first half (H1) of the decade from 2023 to 2033, the market is set to surge at a CAGR of 8.2%, followed by a slightly higher growth rate of 8.4% in the second half (H2) of the same decade.
Moving into the subsequent period, from H1 2024 to H2 2034, the CAGR is projected to increase to 9.6% in the first half and remain steady at 9.8% in the second half. These values offer insights into the anticipated growth trends for the market, aiding stakeholders and investors in making informed decisions regarding investments & strategies.
| Particular | Value CAGR |
|---|---|
| H1 | 8.2% (2023 to 2033) |
| H2 | 8.4% (2023 to 2033) |
| H1 | 9.6% (2024 to 2034) |
| H2 | 9.8% (2024 to 2034) |
The section below showcases the CAGRs and values of the significant countries present in predictive maintenance market. By scrutinizing themes from qualitative data of the market, the United States emerged as the leading country.
| Countries | Value CAGR (2024 to 2034) |
|---|---|
| United States | 8.6% |
| Germany | 6.1% |
| United Kingdom | 4.3% |
The United States is projected to hold a market share of 79.2% by 2024. The country is set to surge at a CAGR of 8.6% through 2034.
Increasing investments in developing technologies such as IoT, artificial intelligence, and machine learning for process manufacturing industries are set to create ample opportunities for manufacturers in the United States. Growing presence of maintenance manufacturers in the United States is also projected to fuel the market.
Germany is estimated to rise at a CAGR of 6.1% during the forecast period. Germany’s manufacturing sector is highly developed and technology-oriented, with a strong emphasis on manufacturing precision and control.
This makes predictive maintenance a key factor in optimizing production and reducing time implemented on the project. Improved configuration facilitates the integration of IoT sensors, data analytics systems, and AI-powered predictive protection solutions into industrial operations.
Germany is actively promoting innovation, research, and development by utilizing the latest technologies in predictive safety training. Hence, rising demand for maintenance technologies is creating a massive opportunity for various players in Germany.
The United Kingdom is set to contribute a CAGR of 4.3% to the global market by 2034. Increasing awareness of the importance of customized maintenance technologies and surging institutional investments are fueling demand for maintenance services in the United Kingdom. The country, which contributes significantly to global revenue, is experiencing new opportunities due to rising industrial automation.
The section below showcases the top segments in the market, including industry, enterprise size, and components. The manufacturing segment in terms of industry is set to rise at 7.3% CAGR through 2034. Based on enterprise size, the medium-sized enterprise segment is projected to witness a CAGR of 7.1% through 2034.
| Segment | Value CAGR (2024 to 2034) |
|---|---|
| Manufacturing (Industry) | 7.3% |
| Medium-sized Enterprise (Enterprise Size) | 7.1% |
| Software (Component) | 8.5% |
Predictive maintenance software combines powerful monitoring tools with data analytics to analyze asset performance and predict potential equipment failures. Key companies use this information to develop proactive maintenance strategies to minimize unplanned downtime.
Instead of waiting until a piece of equipment breaks down to get repaired, maintenance software automates the entire process by scheduling maintenance at the first sign of a potential mechanical problem.
This software provides data management, integration, visualization, and reporting services, enabling organizations to optimize maintenance systems, improve asset reliability, and make more data-focused decisions.
Medium-sized enterprises are using maintenance solutions for improved asset performance, reduced uptime, and lower maintenance costs. Affordable IoT sensors and cloud-based predictive analytics platforms have made these solutions more flexible and cost-effective for medium-sized enterprises than traditional maintenance methods.
Medium-sized enterprises' scalability and flexibility in maintenance solutions align with their dynamic needs and resource constraints, contributing to significant growth in the evolving landscape.
The rising need for maintenance of manufacturing equipment, such as machinery, elevators, pumps, and industrial robots for reducing downtime is surging demand for predictive maintenance.
With the advent of Industry 4.0 for manufacturing, companies are using technologies to monitor and gain deeper insight into their operations in real-time to increase production efficiency and reduce costs.
With predictive maintenance, manufacturers have real-time visibility into the current state of production equipment and receive automated alerts when machines are ready for service or aren’t functioning properly.
Using data gathered from machine-mounted sensors, AI and machine learning algorithms prescribe customized maintenance schedules based on how production equipment is used.
Leading companies are investing in research and development to enhance their product range, which is set to fuel the market. Key companies are also developing strategies to increase their global footprint, including new product launches, mergers, and acquisitions.
Leading companies invest in research and development to create sophisticated maintenance solutions that deliver improved performance, security, and scalability. They also invest in quality data management and integration capabilities to ensure accurate and reliable data collection and analysis, as high-quality data is essential for effective future planning.
The market is growing rapidly as key companies often surge into emerging areas. This diversification allows them to tap into new customer bases and support start-ups in emerging economies with their maintenance solutions.
Key Developments
The market is set to reach US$ 10,510.0 million in 2024.
Demand for predictive maintenance is slated to rise at a 10.9% CAGR by 2034.
The market is set to reach US$ 80,200.0 million in 2034.
Microsoft Azure, IBM Cloud, Siemens, Hitachi, Ltd, and General Electric (GE) are the key players.
Software segment is estimated to hold a significant market share in 2024.
Medium-sized enterprise segment is estimated to surge at a CAGR of 7.1%.
1. Executive Summary 1.1. Global Market Outlook 1.2. Demand Side Trends 1.3. Supply Side Trends 1.4. Analysis and Recommendations 2. Market Overview 2.1. Market Coverage / Taxonomy 2.2. Market Definition / Scope / Limitations 3. Pricing Analysis 3.1. Weighted Average Pricing Analysis, By Hardware/Device Type 3.2. Software Pricing Models 3.2.1. Subscription-based 3.2.2. Perpetual Licenses 3.3. Regional Pricing Analysis Benchmark 4. VC Funding Outlook 4.1. Key & Noticeable Startups in Predictive Maintenance 4.2. Growth in VC Funding 2021 vs 2022 vs 2023 4.3. Latest Funding Received, by Startups 4.4. Major Investors 5. Market Background 5.1. Macro-Economic Factors 5.2. Forecast Factors - Relevance & Impact 5.3. Value Chain 5.4. COVID-19 Crisis - Impact Assessment 5.4.1. Current Statistics 5.4.2. Short-Mid-Long Term Outlook 5.4.3. Likely Rebound 5.5. Market Dynamics 5.5.1. Drivers 5.5.2. Restraints 5.5.3. Opportunity Analysis 6. Global Market Demand (in Value in US$ million) Analysis 2019 to 2023 and Forecast, 2024 to 2034 6.1. Historical Market Size (US$ million) Analysis, 2019 to 2023 6.2. Current and Future Market Size (US$ million) Projections, 2024 to 2034 6.2.1. Y-o-Y Growth Trend Analysis 6.2.2. Absolute $ Opportunity Analysis 7. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, by Component 7.1. Introduction / Key Findings 7.2. Historical Market Size (US$ million) Analysis By Component, 2019 to 2023 7.3. Current and Future Market Size (US$ million) Analysis and Forecast By Component, 2024 to 2034 7.3.1. Hardware 7.3.1.1. IoT Sensors 7.3.1.1.1. Temperature Sensors 7.3.1.1.2. Vibration Sensors 7.3.1.1.3. Position Sensors 7.3.1.1.4. Others 7.3.1.2. IoT Gateways 7.3.1.3. Other Devices 7.3.2. Software 7.3.2.1. Software 7.3.2.2. IoT Platforms (Cloud-based) 7.3.2.3. AI-based CMMS Software 7.3.2.4. Other Software 7.3.3. Services 7.3.3.1. Professional Services 7.3.3.1.1. Condition Monitoring Services 7.3.3.1.2. Integration & Implementation Services 7.3.3.1.3. Consulting & Advisory Services 7.3.3.1.4. Support & Maintenance 7.3.3.2. Managed Services 7.4. Market Attractiveness Analysis By Component 8. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, by Enterprise Size 8.1. Introduction / Key Findings 8.2. Historical Market Size (US$ million) Analysis By Enterprise Size, 2019 to 2023 8.3. Current and Future Market Size (US$ million) Analysis and Forecast By Enterprise Size, 2024 to 2034 8.3.1. Small Offices (1 to 9 employees) 8.3.2. Small Enterprises (10 to 99 employees) 8.3.3. Medium-sized Enterprise (100 to 499 employees) 8.3.4. Large Enterprises (500 to 999 employees) 8.3.5. Very Large Enterprises (1,000+ employees) 8.4. Market Attractiveness Analysis By Enterprise Size 9. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, by Industry 9.1. Introduction / Key Findings 9.2. Historical Market Size (US$ million) Analysis By Industry, 2019 to 2023 9.3. Current and Future Market Size (US$ million) Analysis and Forecast By Industry, 2024 to 2034 9.3.1. Automotive & Transportation 9.3.1.1. Engine Health Monitoring 9.3.1.2. Brake System Monitoring 9.3.1.3. Battery Health Management 9.3.1.4. Tire Health Monitoring 9.3.2. Aerospace & Defense 9.3.2.1. Aircraft Engine Health Monitoring 9.3.2.2. Avionics System Monitoring 9.3.2.3. Weapons System Monitoring 9.3.2.4. Structural Health Monitoring 9.3.3. Manufacturing 9.3.3.1. Machine Health Monitoring 9.3.3.2. Motor Health Monitoring 9.3.3.3. Supply Chain Optimization 9.3.3.4. Predictive Quality Control 9.3.4. Healthcare 9.3.4.1. Medical Imaging Equipment 9.3.4.2. Life Support and Monitoring Devices 9.3.4.3. Drug Delivery Systems 9.3.4.4. Laboratory Equipment 9.3.5. Telecommunications 9.3.5.1. Network Equipment Health Monitoring 9.3.5.2. Fiber Optic Cable Monitoring 9.3.5.3. Antenna Health Monitoring 9.3.5.4. Power System Monitoring 9.3.6. Others 9.4. Market Attractiveness Analysis By Industry 10. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, by Region 10.1. Introduction 10.2. Historical Market Size (US$ million) Analysis By Region, 2019 to 2023 10.3. Current and Future Market Size (US$ million) Analysis and Forecast By Region, 2024 to 2034 10.3.1. North America 10.3.2. Latin America 10.3.3. East Asia 10.3.4. South Asia and Pacific 10.3.5. Western Europe 10.3.6. Eastern Europe 10.3.7. Middle East and Africa 10.4. Market Attractiveness Analysis By Region 11. North America Market Analysis 2019 to 2023 and Forecast 2024 to 2034 11.1. Introduction 11.2. Historical Market Size (US$ million) Analysis By Market Taxonomy, 2019 to 2023 11.3. Current and Future Market Size (US$ million) Forecast By Market Taxonomy, 2024 to 2034 11.3.1. By Country 11.3.1.1. United States 11.3.1.2. Canada 11.3.1.3. Mexico 11.3.2. By Component 11.3.3. By Enterprise Size 11.3.4. By Industry 11.4. Market Attractiveness Analysis 11.4.1. By Country 11.4.2. By Component 11.4.3. By Enterprise Size 11.4.4. By Industry 11.5. Market Trends 11.6. Key Market Participants - Intensity Mapping 12. Latin America Market Analysis 2019 to 2023 and Forecast 2024 to 2034 12.1. Introduction 12.2. Historical Market Size (US$ million) Analysis By Market Taxonomy, 2019 to 2023 12.3. Current and Future Market Size (US$ million) Forecast By Market Taxonomy, 2024 to 2034 12.3.1. By Country 12.3.1.1. Brazil 12.3.1.2. Chile 12.3.1.3. Latin America 12.3.2. By Component 12.3.3. By Enterprise Size 12.3.4. By Industry 12.4. Market Attractiveness Analysis 12.4.1. By Country 12.4.2. By Component 12.4.3. By Enterprise Size 12.4.4. By Industry 12.5. Market Trends 12.6. Key Market Participants - Intensity Mapping 13. South Asia and Pacific Market Analysis 2019 to 2023 and Forecast 2024 to 2034 13.1. Introduction 13.2. Historical Market Size (US$ million) Analysis By Market Taxonomy, 2019 to 2023 13.3. Current and Future Market Size (US$ million) Forecast By Market Taxonomy, 2024 to 2034 13.3.1. By Country 13.3.1.1. India 13.3.1.2. ASEAN 13.3.1.3. Australia & New Zealand 13.3.1.4. South Asia & Pacific 13.3.2. By Component 13.3.3. By Enterprise Size 13.3.4. By Industry 13.4. Market Attractiveness Analysis 13.4.1. By Country 13.4.2. By Component 13.4.3. By Enterprise Size 13.4.4. By Industry 13.5. Market Trends 13.6. Key Market Participants - Intensity Mapping 14. East Asia Market Analysis 2019 to 2023 and Forecast 2024 to 2034 14.1. Introduction 14.2. Historical Market Size (US$ million) Analysis By Market Taxonomy, 2019 to 2023 14.3. Current and Future Market Size (US$ million) Forecast By Market Taxonomy, 2024 to 2034 14.3.1. By Country 14.3.1.1. China 14.3.1.2. Japan 14.3.1.3. South Korea 14.3.2. By Component 14.3.3. By Enterprise Size 14.3.4. By Industry 14.4. Market Attractiveness Analysis 14.4.1. By Country 14.4.2. By Component 14.4.3. By Enterprise Size 14.4.4. By Industry 14.5. Market Trends 14.6. Key Market Participants - Intensity Mapping 15. Western Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034 15.1. Introduction 15.2. Historical Market Size (US$ million) Analysis By Market Taxonomy, 2019 to 2023 15.3. Current and Future Market Size (US$ million) Forecast By Market Taxonomy, 2024 to 2034 15.3.1. By Country 15.3.1.1. Germany 15.3.1.2. Italy 15.3.1.3. France 15.3.1.4. United Kingdom 15.3.1.5. Spain 15.3.1.6. BENELUX 15.3.1.7. Nordics 15.3.1.8. Western Europe 15.3.2. By Component 15.3.3. By Enterprise Size 15.3.4. By Industry 15.4. Market Attractiveness Analysis 15.4.1. By Component 15.4.2. By Enterprise Size 15.4.3. By Industry 15.4.4. By Country 15.5. Market Trends 15.6. Key Market Participants - Intensity Mapping 16. Eastern Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034 16.1. Introduction 16.2. Historical Market Size (US$ million) Analysis By Market Taxonomy, 2019 to 2023 16.3. Current and Future Market Size (US$ million) Forecast By Market Taxonomy, 2024 to 2034 16.3.1. By Country 16.3.1.1. Russia 16.3.1.2. Poland 16.3.1.3. Balkan and Baltics 16.3.1.4. Eastern Europe 16.3.2. By Component 16.3.3. By Enterprise Size 16.3.4. By Industry 16.4. Market Attractiveness Analysis 16.4.1. By Component 16.4.2. By Enterprise Size 16.4.3. By Industry 16.4.4. By Country 16.5. Market Trends 16.6. Key Market Participants - Intensity Mapping 17. Middle East and Africa Market Analysis 2019 to 2023 and Forecast 2024 to 2034 17.1. Introduction 17.2. Historical Market Size (US$ million) Analysis By Market Taxonomy, 2019 to 2023 17.3. Current and Future Market Size (US$ million) Forecast By Market Taxonomy, 2024 to 2034 17.3.1. By Country 17.3.1.1. KSA 17.3.1.2. Other GCC 17.3.1.3. Türkiye 17.3.1.4. South Africa 17.3.1.5. Middle East and Africa 17.3.2. By Component 17.3.3. By Enterprise Size 17.3.4. By Industry 17.4. Market Attractiveness Analysis 17.4.1. By Country 17.4.2. By Component 17.4.3. By Enterprise Size 17.4.4. By Industry 17.5. Market Trends 17.6. Key Market Participants - Intensity Mapping 18. Country-wise Market Analysis 18.1. United States Market Analysis 18.1.1. By Component 18.1.2. By Enterprise Size 18.1.3. By Industry 18.2. Canada Market Analysis 18.2.1. By Component 18.2.2. By Enterprise Size 18.2.3. By Industry 18.3. Mexico Market Analysis 18.3.1. By Component 18.3.2. By Enterprise Size 18.3.3. By Industry 18.4. Brazil Market Analysis 18.4.1. By Component 18.4.2. By Enterprise Size 18.4.3. By Industry 18.5. Chile Market Analysis 18.5.1. By Component 18.5.2. By Enterprise Size 18.5.3. By Industry 18.6. Germany Market Analysis 18.6.1. By Component 18.6.2. By Enterprise Size 18.6.3. By Industry 18.7. Italy Market Analysis 18.7.1. By Component 18.7.2. By Enterprise Size 18.7.3. By Industry 18.8. France Market Analysis 18.8.1. By Component 18.8.2. By Enterprise Size 18.8.3. By Industry 18.9. United Kingdom Market Analysis 18.9.1. By Component 18.9.2. By Enterprise Size 18.9.3. By Industry 18.10. Spain Market Analysis 18.10.1. By Component 18.10.2. By Enterprise Size 18.10.3. By Industry 18.11. Russia Market Analysis 18.11.1. By Component 18.11.2. By Enterprise Size 18.11.3. By Industry 18.12. China Market Analysis 18.12.1. By Component 18.12.2. By Enterprise Size 18.12.3. By Industry 18.13. Japan Market Analysis 18.13.1. By Component 18.13.2. By Enterprise Size 18.13.3. By Industry 18.14. South Korea Market Analysis 18.14.1. By Component 18.14.2. By Enterprise Size 18.14.3. By Industry 18.15. India Market Analysis 18.15.1. By Component 18.15.2. By Enterprise Size 18.15.3. By Industry 18.16. ASEAN Market Analysis 18.16.1. By Component 18.16.2. By Enterprise Size 18.16.3. By Industry 18.17. Australia & New Zealand Market Analysis 18.17.1. By Component 18.17.2. By Enterprise Size 18.17.3. By Industry 18.18. Other GCC Market Analysis 18.18.1. By Component 18.18.2. By Enterprise Size 18.18.3. By Industry 18.19. KSA Market Analysis 18.19.1. By Component 18.19.2. By Enterprise Size 18.19.3. By Industry 18.20. Türkiye Market Analysis 18.20.1. By Component 18.20.2. By Enterprise Size 18.20.3. By Industry 18.21. South Africa Market Analysis 18.21.1. By Component 18.21.2. By Enterprise Size 18.21.3. By Industry 19. Market Structure Analysis 19.1. Market Analysis by Tier of Companies 19.2. Market Share Analysis of Top Players 20. Competition Analysis 20.1. Competition Dashboard 20.1.1. Dashboard of Major Vendors 20.1.2. Dashboard of Key Startups 20.2. Ranking of Major Vendors, By Key Criteria 20.2.1. By Product Capabilities 20.2.2. By Business Expertise Outlook 20.3. Matrix for Industry Footprint/Coverage, By Vendors 20.4. Matrix for Region Footprint/Coverage, By Vendors 20.5. Competition Deep Dive (Established & Major Vendors) 20.5.1. IBM Corporation 20.5.1.1. Business Overview 20.5.1.2. Product Portfolio and Strengths 20.5.1.3. Key Clients Footprint 20.5.1.4. Industry Coverage 20.5.1.5. Go-to-Market Approach & Strategies 20.5.1.6. Recent Developments (Partnerships, Mergers etc.) 20.5.2. SAP 20.5.3. Siemens 20.5.4. Microsoft 20.5.5. GE 20.5.6. Robert Bosch 20.5.7. ABB 20.5.8. Schneider Electric 20.5.9. Honeywell 20.5.10. Rockwell Automation 20.5.11. Emerson 20.5.12. PTC 20.5.13. Hitachi 20.5.14. eMaint by Fluke Corporation 20.5.15. SKF 20.6. Key Startups in Predictive Maintenance 20.6.1. Stratio 20.6.1.1. Business Overview 20.6.1.2. Funding Rounds/Funding Raised 20.6.1.3. Major Investors 20.6.1.4. Solution Capabilities 20.6.1.5. Business Strategies 20.6.2. Digitread Connect 20.6.3. MachineMetrics 20.6.4. Gastops 20.6.5. Predictive-sigma 20.6.6. Semiotic Labs 20.6.7. Quadrical Ai 20.6.8. ai-omatic solutions GmbH 20.6.9. Predikto 20.6.10. UptimeAI 21. Assumptions and Acronyms Used 22. Research Methodology
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Predictive Maintenance Market
