Analytical Study of Korea Social Employee Recognition System (2023 to 2033)

The adoption of the social employee recognition system in Korea is likely to exhibit a compound annual growth rate of 9.4% through 2033. By 2033, the adoption of a social employee recognition system in Korea is likely to secure US$ 389.5 million.

The social employee recognition system industry in Korea is poised to witness significant opportunities with a US$ 193.7 million valuation in 2023. Increased technological advancement across industrial categories is the primary driver expected to drive the development of the Korean social employee recognition system.

Attributes Details
Industry size of Korea in 2023 US$ 193.7 million
Expected Industry Size of Korea in 2033 US$ 389.5 million
Forecasted CAGR between 2023 and 2033 9.4%

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Key Insights - Highlights to Understand Emerging and Fast-growing Opportunities

  • The adoption of social employee recognition software in Korea is expected to see a steady rise as new employee recognition software and systems are being launched.
  • Many Korean businesses have adopted performance-driven cultures, where recognition is tied to achievements and contributions. Social recognition systems help transparently link performance with rewards and appreciation.
  • Technological advancements in the workplace and innovations are fuelling new trends and practices, driving the demand for social employee recognition platforms.

Key Trends Influencing Demand for Employee Recognition System in Korea

  • The growing technological proliferation in workplaces, innovations in workplace technology, and rising awareness about employee recognition are some of the major factors propelling the sales of the social employee recognition system industry in Korea.
  • Social recognition systems provide a platform for ongoing, real-time appreciation, which boosts engagement.
  • Increasing focus on sustainability and green initiatives in Korea. Digital recognition systems reduce the need for physical awards or certificates, aligning with sustainability goals.
  • The growing adoption of global best practices in human resources and talent management in Korea, social employee recognition systems are seen as a standard practice in many international companies.
Sudip Saha
Sudip Saha

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Country-wise Insights

Growing Demand in Various Industries to Fuel the Growth in South Gyeongsang

South Gyeongsang is home to many global and multinational companies. These organizations often adopt global HR practices, including employee recognition programs, to maintain consistency across their operations. Social employee recognition systems help foster a positive work environment by acknowledging and rewarding employees' contributions and achievements, leading to increased engagement.

Employee recognition systems that offer customization and localization features can be attractive to businesses in South Gyeongsang. They may seek solutions that allow them to adapt recognition practices to fit their unique organizational culture and values.

Strong Focus on Employee Engagement to Boost the Social Employee Recognition System in North Jeolla

Increasing demand for technically advanced employee recognition systems in North Jeolla has increased demand for more efficient and advanced employee engagement solutions, driving the need for social employee recognition systems.

With a strong focus on employee engagement and productivity. Social recognition systems are gaining traction as organizations seek to boost morale and enhance teamwork.

Jeju Shows All Vital Signs of Growth Owing to Increased Demand from SMEs

The social employee recognition systems in Jeju are growing. The country's diverse workforce and focus on work-life balance make recognition systems appealing to businesses. The rapid growth of the IT and services sector has contributed to increased adoption as companies look to engage and retain talent.

The small & medium enterprises in Jeju are increasingly recognizing the importance of employee engagement and motivation. Jeju-based organizations may prioritize employee training and development programs. Recognition systems can be used to acknowledge and reward employees who invest in their own growth.

Category-wise insights

Category Market Share
Cloud-Based 40.5%
Retail & Consumer Goods 35.3%

Cloud based Services to witness Fast Growth Rate

The employee recognition system deployed on cloud-based is expected to be the highest revenue-generating category, projected to register a share of 40.5% through 2033. The capacity of cloud-based services to reduce operating expenses and improve the number of individuals who may participate in a particular application is also propelling the cloud-based employee recognition system business ahead.

Cloud-based solutions are accessible from anywhere with an internet connection. Employees can access the recognition platform from various devices and locations, enhancing user engagement.

The cost efficiency of cloud-based solutions appeals to businesses of all sizes, from small startups to large enterprises, making cloud-based recognition systems accessible to a broad range of organizations.

Retail & Consumer Goods Reach Higher as Compared to Other Industry Types

Based on industry type, retail & consumer goods is the leading category, expected to account for 35.3% of the market by the end of 2033. Retail and consumer goods are highly competitive industries. Social employee recognition programs can help attract and retain top talent, creating a competitive advantage in the industry.

The social employee recognition system is mainly used in retail as retail and consumer goods companies typically have a sizable workforce, including front-line employees, sales representatives, store managers, and support staff. Employee recognition systems can help improve employee retention by acknowledging and rewarding the efforts of these workers.

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Competitive Landscape

With their extensive expertise, resources, and focus on sustainability, social employee recognition system companies are actively contributing to expansion. Some market participants are concentrating on securing the largest possible market share by introducing the most cutting-edge technology through research & development tactics.

Many big players are also using mergers & acquisitions as a key strategy for expanding their geographical presence and for more business in terms of revenue.

  • In October 2023, Kudos announced a new technology partnership with UKG.
  • Kakao Enterprise, a subsidiary of Kakao Corporation, offers various HR and employee engagement solutions, including recognition and rewards programs

Some of the key players in the social employee recognition system in the Korea include the following.

  • Kudos
  • Peoplecart
  • Blueboard
  • Xoxoday
  • Kakao Enterprise
  • NICE Employee Recognition
  • HRPia

Scope of the Report

Attribute Details
Estimated Industry Size in 2023 US$ 193.7 million
Projected Industry Size in 2033 US$ 389.5 million
Anticipated CAGR between 2023 to 2033 9.4% CAGR
Historical Analysis of Demand for Social Employee Recognition System in Korea 2018 to 2022
Demand Forecast for Social Employee Recognition System in Korea 2023 to 2033
Report Coverage Industry Size, Industry Trends, Analysis of key factors influencing Social Employee Recognition System in Korea, Insights on Global Players and their Industry Strategy in Korea, Ecosystem Analysis of Local and Regional Korean Providers
Key Cities Analyzed While Studying Opportunities in Social Employee Recognition System in Korea South Gyeongsang, North Jeolla, South Jeolla, Jeju
Key Companies Profiled Kudos; Peoplecart; Blueboard; Xoxoday; Kakao Enterprise; NICE Employee Recognition; HRPia

Key Segments

By Deployment:

  • Cloud
  • On-Premise

By Enterprise Type:

  • SMEs
  • Large Enterprises

By Industry Type:

  • Retail & CGs
  • IT & Telecom
  • Healthcare
  • Media
  • Travel
  • Manufacturing
  • Others

By Region/City:

  • South Gyeongsang
  • North Jeolla
  • South Jeolla
  • Jeju

Frequently Asked Questions

How big is the social employee recognition system in Korea?

The estimated valuation of the social employee recognition system in Korea is US$ 193.7 million in 2023.

At what Rate is the social employee recognition system growing in Korea?

The anticipated CAGR for the social employee recognition system in Korea through 2033 is 9.4%.

How big will the social employee recognition system Industry be in Korea?

Social employee recognition systems demand in Korea will be US$ 389.5 million by 2033.

Which is the preferred deployment type for Korea's social employee recognition system industry?

The cloud-based segment is expected to dominate social employee recognition systems demand.

Which industry type category contributes significantly?

The retail & consumer goods segment will likely remain a key contributor to social employee recognition systems demand in Korea

Table of Content
1. Executive Summary
    1.1. Market Outlook
    1.2. Demand-side Trends
    1.3. Supply-side Trends
    1.4. Technology Roadmap Analysis
    1.5. Analysis and Recommendations
2. Market Overview
    2.1. Market Coverage / Taxonomy
    2.2. Market Definition / Scope / Limitations
3. Market Background
    3.1. Market Dynamics
        3.1.1. Drivers
        3.1.2. Restraints
        3.1.3. Opportunity
        3.1.4. Trends
    3.2. Scenario Forecast
        3.2.1. Demand in Optimistic Scenario
        3.2.2. Demand in Likely Scenario
        3.2.3. Demand in Conservative Scenario
    3.3. Opportunity Map Analysis
    3.4. Investment Feasibility Matrix
    3.5. PESTLE and Porter’s Analysis
    3.6. Regulatory Landscape
        3.6.1. By Key Regions
    3.7. Regional Parent Market Outlook
4. Industry Analysis and Outlook 2018 to 2022 and Forecast, 2023 to 2033
    4.1. Historical Market Size Value (US$ Million) Analysis, 2018 to 2022
    4.2. Current and Future Market Size Value (US$ Million) Projections, 2023 to 2033
        4.2.1. Y-o-Y Growth Trend Analysis
        4.2.2. Absolute $ Opportunity Analysis
5. Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033, By Deployment
    5.1. Introduction / Key Findings
    5.2. Historical Market Size Value (US$ Million) Analysis By Deployment, 2018 to 2022
    5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment, 2023 to 2033
        5.3.1. Cloud
        5.3.2. On-Premise
    5.4. Y-o-Y Growth Trend Analysis By Deployment, 2018 to 2022
    5.5. Absolute $ Opportunity Analysis By Deployment, 2023 to 2033
6. Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033, By Enterprise Type
    6.1. Introduction / Key Findings
    6.2. Historical Market Size Value (US$ Million) Analysis By Enterprise Type, 2018 to 2022
    6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Enterprise Type, 2023 to 2033
        6.3.1. SMEs
        6.3.2. Large Enterprises
    6.4. Y-o-Y Growth Trend Analysis By Enterprise Type, 2018 to 2022
    6.5. Absolute $ Opportunity Analysis By Enterprise Type, 2023 to 2033
7. Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033, By Industry Type
    7.1. Introduction / Key Findings
    7.2. Historical Market Size Value (US$ Million) Analysis By Industry Type, 2018 to 2022
    7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Industry Type, 2023 to 2033
        7.3.1. Retail & CGs
        7.3.2. IT & Telecom
        7.3.3. Healthcare
        7.3.4. Media
        7.3.5. Travel
        7.3.6. Manufacturing
        7.3.7. Others
    7.4. Y-o-Y Growth Trend Analysis By Industry Type, 2018 to 2022
    7.5. Absolute $ Opportunity Analysis By Industry Type, 2023 to 2033
8. Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033, By Region
    8.1. Introduction
    8.2. Historical Market Size Value (US$ Million) Analysis By Region, 2018 to 2022
    8.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2023 to 2033
        8.3.1. South Gyeongsang
        8.3.2. North Jeolla
        8.3.3. South Jeolla
        8.3.4. Jeju
        8.3.5. Rest of Korea
    8.4. Market Attractiveness Analysis By Region
9. South Gyeongsang Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033
    9.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
    9.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
        9.2.1. By Deployment
        9.2.2. By Enterprise Type
        9.2.3. By Industry Type
    9.3. Market Attractiveness Analysis
        9.3.1. By Deployment
        9.3.2. By Enterprise Type
        9.3.3. By Industry Type
    9.4. Key Takeaways
10. North Jeolla Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033
    10.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
    10.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
        10.2.1. By Deployment
        10.2.2. By Enterprise Type
        10.2.3. By Industry Type
    10.3. Market Attractiveness Analysis
        10.3.1. By Deployment
        10.3.2. By Enterprise Type
        10.3.3. By Industry Type
    10.4. Key Takeaways
11. South Jeolla Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033
    11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
    11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
        11.2.1. By Deployment
        11.2.2. By Enterprise Type
        11.2.3. By Industry Type
    11.3. Market Attractiveness Analysis
        11.3.1. By Deployment
        11.3.2. By Enterprise Type
        11.3.3. By Industry Type
    11.4. Key Takeaways
12. Jeju Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033
    12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
    12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
        12.2.1. By Deployment
        12.2.2. By Enterprise Type
        12.2.3. By Industry Type
    12.3. Market Attractiveness Analysis
        12.3.1. By Deployment
        12.3.2. By Enterprise Type
        12.3.3. By Industry Type
    12.4. Key Takeaways
13. Rest of Industry Analysis and Outlook 2018 to 2022 and Forecast 2023 to 2033
    13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2018 to 2022
    13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2023 to 2033
        13.2.1. By Deployment
        13.2.2. By Enterprise Type
        13.2.3. By Industry Type
    13.3. Market Attractiveness Analysis
        13.3.1. By Deployment
        13.3.2. By Enterprise Type
        13.3.3. By Industry Type
    13.4. Key Takeaways
14. Market Structure Analysis
    14.1. Competition Dashboard
    14.2. Competition Benchmarking
    14.3. Market Share Analysis of Top Players
        14.3.1. By Regional
        14.3.2. By Deployment
        14.3.3. By Enterprise Type
        14.3.4. By Industry Type
15. Competition Analysis
    15.1. Competition Deep Dive
        15.1.1. Salesforce.com Inc.
            15.1.1.1. Overview
            15.1.1.2. Product Portfolio
            15.1.1.3. Profitability by Market Segments
            15.1.1.4. Sales Footprint
            15.1.1.5. Strategy Overview
                15.1.1.5.1. Marketing Strategy
        15.1.2. Globoforce Ltd.
            15.1.2.1. Overview
            15.1.2.2. Product Portfolio
            15.1.2.3. Profitability by Market Segments
            15.1.2.4. Sales Footprint
            15.1.2.5. Strategy Overview
                15.1.2.5.1. Marketing Strategy
        15.1.3. REFFIND Ltd.
            15.1.3.1. Overview
            15.1.3.2. Product Portfolio
            15.1.3.3. Profitability by Market Segments
            15.1.3.4. Sales Footprint
            15.1.3.5. Strategy Overview
                15.1.3.5.1. Marketing Strategy
        15.1.4. Achievers Solutions Inc.
            15.1.4.1. Overview
            15.1.4.2. Product Portfolio
            15.1.4.3. Profitability by Market Segments
            15.1.4.4. Sales Footprint
            15.1.4.5. Strategy Overview
                15.1.4.5.1. Marketing Strategy
        15.1.5. Kudos Inc.
            15.1.5.1. Overview
            15.1.5.2. Product Portfolio
            15.1.5.3. Profitability by Market Segments
            15.1.5.4. Sales Footprint
            15.1.5.5. Strategy Overview
                15.1.5.5.1. Marketing Strategy
        15.1.6. Madison Performance Group
            15.1.6.1. Overview
            15.1.6.2. Product Portfolio
            15.1.6.3. Profitability by Market Segments
            15.1.6.4. Sales Footprint
            15.1.6.5. Strategy Overview
                15.1.6.5.1. Marketing Strategy
        15.1.7. Recognize Services Inc.
            15.1.7.1. Overview
            15.1.7.2. Product Portfolio
            15.1.7.3. Profitability by Market Segments
            15.1.7.4. Sales Footprint
            15.1.7.5. Strategy Overview
                15.1.7.5.1. Marketing Strategy
        15.1.8. Aurea Software Inc.
            15.1.8.1. Overview
            15.1.8.2. Product Portfolio
            15.1.8.3. Profitability by Market Segments
            15.1.8.4. Sales Footprint
            15.1.8.5. Strategy Overview
                15.1.8.5.1. Marketing Strategy
        15.1.9. BI Worldwide Ltd.
            15.1.9.1. Overview
            15.1.9.2. Product Portfolio
            15.1.9.3. Profitability by Market Segments
            15.1.9.4. Sales Footprint
            15.1.9.5. Strategy Overview
                15.1.9.5.1. Marketing Strategy
        15.1.10. Terryberry
            15.1.10.1. Overview
            15.1.10.2. Product Portfolio
            15.1.10.3. Profitability by Market Segments
            15.1.10.4. Sales Footprint
            15.1.10.5. Strategy Overview
                15.1.10.5.1. Marketing Strategy
        15.1.11. YouEarnedIt
            15.1.11.1. Overview
            15.1.11.2. Product Portfolio
            15.1.11.3. Profitability by Market Segments
            15.1.11.4. Sales Footprint
            15.1.11.5. Strategy Overview
                15.1.11.5.1. Marketing Strategy
16. Assumptions & Acronyms Used
17. Research Methodology
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