Intelligent Packaging Market Size, Share & Trends Analysis Report By Technology, By Application, By Level of packaging (Primary Packaging, Secondary Packaging, Tertiary Packaging), By End-Use, By Region, And By Segment Forecasts, 2024-2031

Report Id: 1435 Pages: 175 Last Updated: 18 April 2024 Format: PDF / PPT / Excel / Power BI
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Segmentation Of Intelligent Packaging Market

By Technology:

  • Indicators
    • Time-Temperature Indicators
    • Gas & Integrity Indicators
    • Freshness Indicators
  • Sensors
  • Interactive Packaging/Data Carriers
    • Quick response (Q.R. Codes)
    • Barcodes
    • Radio Frequency Identification (RFIDs)
    • Near Field Communications (NFCs)
    • Bluetooth Low Energy (BLE)
  • Active Packaging
    • Oxygen Scavengers
    • Ethylene Absorbers
    • Moisture Scavengers
    • Anti-microbial Packaging

intelligent packaging

By Level of Packaging:

  • Primary Packaging
  • Secondary Packaging
  • Tertiary Packaging

By Application:

  • Bottles and Jars
  • Blisters
  • Trays & Clamshells
  • Cans
  • Boxes & Cartons
  • Vials, Ampoules, & Prefilled Syringes
  • Bags & Pouches
  • Films & Wraps
  • Mailers
  • Labels, Tapes, & Tags
  • Others

By End Use:

  • Food
  • Meat, Poultry, & Seafood
    • Fruits & Vegetables
    • Dairy Products
    • Bakery & Confectionary
    • Processed Food
    • Ready to Eat Food
    • Others
  • Beverage
  • Healthcare
    • Medical Devices
    • Medical Supplies
    • Pharmaceuticals
  • Cosmetics
  • Logistics & Transport
  • Consumer Electronics
  • Consumer Goods
  • Personal Care & Homecare
  • Others

By Region-

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • Southeast Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and Africa

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Intelligent Packaging Market Snapshot

Chapter 4. Global Intelligent Packaging Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Investment and Funding Analysis

4.6. Industry Analysis – Porter’s Five Forces Analysis

4.7. Competitive Landscape & Market Share Analysis

4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: by Technology Estimates & Trend Analysis

5.1. by Technology & Market Share, 2019 & 2031

5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Technology:

5.2.1. Indicators

5.2.1.1. Time-Temperature Indicators

5.2.1.2. Gas & Integrity Indicators

5.2.1.3. Freshness Indicators

5.2.2. Sensors

5.2.3. Interactive Packaging/Data Carriers

5.2.3.1. Quick response (QR Codes)

5.2.3.2. Barcodes

5.2.3.3. Radio Frequency Identification (RFID)

5.2.3.4. Near Field Communications (NFCs)

5.2.3.5. Bluetooth Low Energy (BLE)

5.2.4. Active Packaging

5.2.4.1. Oxygen Scavengers

5.2.4.2. Ethylene Absorbers

5.2.4.3. Moisture Scavengers

5.2.4.4. Anti-microbial Packaging

Chapter 6. Market Segmentation 2: by Level of Packaging Estimates & Trend Analysis

6.1. by Level of Packaging & Market Share, 2019 & 2031

6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Level of Packaging:

6.2.1. Primary Packaging

6.2.2. Secondary Packaging

6.2.3. Tertiary Packaging

Chapter 7. Market Segmentation 3: by Application Estimates & Trend Analysis

7.1. by Application & Market Share, 2019 & 2031

7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:

7.2.1. Bottles and Jars

7.2.2. Blisters

7.2.3. Trays & Clamshells

7.2.4. Cans

7.2.5. Boxes & Cartons

7.2.6. Vials, Ampoules, & Prefilled Syringes

7.2.7. Bags & Pouches

7.2.8. Films & Wraps

7.2.9. Mailers

7.2.10. Labels, Tapes, & Tags

7.2.11. Others

Chapter 8. Market Segmentation 4: by End Use Estimates & Trend Analysis

8.1. by End Use & Market Share, 2019 & 2031

8.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by End Use:

8.2.1. Food

8.2.1.1. Meat, Poultry, & Seafood

8.2.1.2. Fruits & Vegetables

8.2.1.3. Dairy Products

8.2.1.4. Bakery & Confectionary

8.2.1.5. Processed Food

8.2.1.6. Ready to Eat Food

8.2.1.7. Others

8.2.2. Beverage

8.2.3. Healthcare

8.2.3.1. Medical Devices

8.2.3.2. Medical Supplies

8.2.3.3. Pharmaceuticals

8.2.4. Cosmetics

8.2.5. Logistics & Transport

8.2.6. Consumer Electronics

8.2.7. Consumer Goods

8.2.8. Personal Care & Homecare

8.2.9. Others

Chapter 9. Intelligent Packaging Market Segmentation 5: Regional Estimates & Trend Analysis

9.1. North America

9.1.1. North America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by Estimates and Forecasts by Technology, 2024-2031

9.1.2. North America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by Estimates and Forecasts by Level of Packaging, 2024-2031

9.1.3. North America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Application, 2024-2031

9.1.4. North America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by End Use, 2024-2031

9.1.5. North America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by Estimates and Forecasts by country, 2024-2031

9.2. Europe

9.2.1. Europe Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Technology, 2024-2031

9.2.2. Europe Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Level of Packaging, 2024-2031

9.2.3. Europe Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Application, 2024-2031

9.2.4. Europe Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by End Use, 2024-2031

9.2.5. Europe Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by country, 2024-2031

9.3. Asia Pacific

9.3.1. Asia Pacific Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Technology, 2024-2031

9.3.2. Asia Pacific Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Level of Packaging, 2024-2031

9.3.3. Asia-Pacific Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Application, 2024-2031

9.3.4. Asia-Pacific Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by End Use, 2024-2031

9.3.5. Asia Pacific Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by country, 2024-2031

9.4. Latin America

9.4.1. Latin America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Technology, 2024-2031

9.4.2. Latin America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Level of Packaging, 2024-2031

9.4.3. Latin America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Application, 2024-2031

9.4.4. Latin America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by End Use, 2024-2031

9.4.5. Latin America Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by country, 2024-2031

9.5. Middle East & Africa

9.5.1. Middle East & Africa Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Technology, 2024-2031

9.5.2. Middle East & Africa Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Level of Packaging, 2024-2031

9.5.3. Middle East & Africa Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by Application, 2024-2031

9.5.4. Middle East & Africa Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by End Use, 2024-2031

9.5.5. Middle East & Africa Intelligent Packaging Market Revenue (US$ Million) Estimates and Forecasts by by country, 2024-2031

Chapter 10. Competitive Landscape

10.1. Major Mergers and Acquisitions/Strategic Alliances

10.2. Company Profiles 

10.2.1. Material Providers

10.2.2. Dow Chemical Company

10.2.3. LyondellBasell Industries NV.

10.2.4. BASF SE

10.2.5. Exxon Mobil Corporation

10.2.6. Saudi Basic Industries Corporation

10.2.7. INEOS Group Limited

10.2.8. Eni S.p.A.

10.2.9. LG Chemical

10.2.10. LANXESS AG

10.2.11. Chevron Phillips Chemical Company, LLC

10.2.12. Packaging Manufacturers

10.2.13. Amcor plc.

10.2.14. Crown Holding Inc.

10.2.15. 3M Company

10.2.16. CCL Industries Inc.

10.2.17. Huhtamaki Global

10.2.18. DS Smith

10.2.19. Avery Dennison Corporation

10.2.20. Honeywell International Inc.

10.2.21. Tetra Pak International SA.

10.2.22. Sealed Air Corporation

10.2.23. Store Enso

10.2.24. WestRock Company

10.2.25. Ball Corporation

10.2.26. Mondi Plc.

10.2.27. International Paper Company

10.2.28. Georgia-Pacific LLC

10.2.29. UPM-Cymene Obj

10.2.30. Coveris Holdings SA.

10.2.31. DuPont Teijin Films US

10.2.32. Sigma Plastics Group

10.2.33. Technology Provider

10.2.34. Time strip UK Ltd

10.2.35. Var code, Ltd.

10.2.36. Tempie Corporation

10.2.37. Delta Trak, Inc.

10.2.38. EVIGENCE SENSORS

10.2.39. JRI Company

10.2.40. Vista International AB

10.2.41. LAXCEN TECHNOLOGY INC.

10.2.42. APK-ID

10.2.43. STARNFC Technologies Ltd.

10.2.44. Brand Owners

10.2.45. Nestlé S.A.

10.2.46. Coca-Cola Company

10.2.47. Johnson & Johnson

10.2.48. Pfizer Inc.

10.2.49. Unilever PLC

10.2.50. Procter & Gamble Company

10.2.51. XPO Logistics

10.2.52. DHL Supply Chain

10.2.53. Amazon.com, Inc.

10.2.54. Shopify Inc.

10.2.55. Other Prominent Players

 

Research Design and Approach

This study employed a multi-step, mixed-method research approach that integrates:

  • Secondary research
  • Primary research
  • Data triangulation
  • Hybrid top-down and bottom-up modelling
  • Forecasting and scenario analysis

This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.

Secondary Research

Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.

Sources Consulted

Secondary data for the market study was gathered from multiple credible sources, including:

  • Government databases, regulatory bodies, and public institutions
  • International organizations (WHO, OECD, IMF, World Bank, etc.)
  • Commercial and paid databases
  • Industry associations, trade publications, and technical journals
  • Company annual reports, investor presentations, press releases, and SEC filings
  • Academic research papers, patents, and scientific literature
  • Previous market research publications and syndicated reports

These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.

Secondary Research

Primary Research

Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.

Stakeholders Interviewed

Primary interviews for this study involved:

  • Manufacturers and suppliers in the market value chain
  • Distributors, channel partners, and integrators
  • End-users / customers (e.g., hospitals, labs, enterprises, consumers, etc., depending on the market)
  • Industry experts, technology specialists, consultants, and regulatory professionals
  • Senior executives (CEOs, CTOs, VPs, Directors) and product managers

Interview Process

Interviews were conducted via:

  • Structured and semi-structured questionnaires
  • Telephonic and video interactions
  • Email correspondences
  • Expert consultation sessions

Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.

Data Processing, Normalization, and Validation

All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.

The data validation process included:

  • Standardization of units (currency conversions, volume units, inflation adjustments)
  • Cross-verification of data points across multiple secondary sources
  • Normalization of inconsistent datasets
  • Identification and resolution of data gaps
  • Outlier detection and removal through algorithmic and manual checks
  • Plausibility and coherence checks across segments and geographies

This ensured that the dataset used for modelling was clean, robust, and reliable.

Market Size Estimation and Data Triangulation

Bottom-Up Approach

The bottom-up approach involved aggregating segment-level data, such as:

  • Company revenues
  • Product-level sales
  • Installed base/usage volumes
  • Adoption and penetration rates
  • Pricing analysis

This method was primarily used when detailed micro-level market data were available.

Bottom Up Approach

Top-Down Approach

The top-down approach used macro-level indicators:

  • Parent market benchmarks
  • Global/regional industry trends
  • Economic indicators (GDP, demographics, spending patterns)
  • Penetration and usage ratios

This approach was used for segments where granular data were limited or inconsistent.

Hybrid Triangulation Approach

To ensure accuracy, a triangulated hybrid model was used. This included:

  • Reconciling top-down and bottom-up estimates
  • Cross-checking revenues, volumes, and pricing assumptions
  • Incorporating expert insights to validate segment splits and adoption rates

This multi-angle validation yielded the final market size.

Forecasting Framework and Scenario Modelling

Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.

Forecasting Methods

  • Time-series modelling
  • S-curve and diffusion models (for emerging technologies)
  • Driver-based forecasting (GDP, disposable income, adoption rates, regulatory changes)
  • Price elasticity models
  • Market maturity and lifecycle-based projections

Scenario Analysis

Given inherent uncertainties, three scenarios were constructed:

  • Base-Case Scenario: Expected trajectory under current conditions
  • Optimistic Scenario: High adoption, favourable regulation, strong economic tailwinds
  • Conservative Scenario: Slow adoption, regulatory delays, economic constraints

Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.

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Frequently Asked Questions

The Intelligent Packaging Market Size is valued at USD 21.04 Billion in 2023 and is predicted to reach 43.36 Billion by the year 2031

The Intelligent Packaging Market is expected to grow at a 9.68 % CAGR during the forecast period for 2024-2031.

Material Provider, Dow Chemical Company, LyondellBasell Industries N.V., BASF SE, Exxon Mobil Corporation, Saudi Basic Industries Corporation, INEOS G
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