According to PayNXT360, the quick commerce market in South Korea is expected to grow by 6.9% annually, reaching US$5,833.5 million by 2025. The quick commerce market in the country has experienced ro...
According to PayNXT360, the quick commerce market in South Korea is expected to grow by 6.9% annually, reaching US$5,833.5 million by 2025. The quick commerce market in the country has experienced robust growth during 2020-2024, achieving a CAGR of 6.5%. This upward trajectory is expected to continue, with the market forecast to grow at a CAGR of 6.6% from 2025 to 2029. By the end of 2029, the quick commerce market is projected to expand from its 2024 value of US$5,459.0 million to approximately US$7,544.2 million. Key Trends & Drivers 1.Condensed delivery-time expectations are becoming standard •In South Korea, leading players are pushing delivery windows to be as short as 30-60 minutes or less. For example, Coupang’s “Rocket” network established same-day/overnight norms, and now the company is racing into hyper-local “quick commerce” from local stores. Another example: convenience-store chain CU partnered with Naver’s “Now Delivery” service to cover a ~1.5km radius with one-hour turnarounds for convenience/grocery goods. •Industry commentary describes the “quick-commerce war” deepening among big-box, e-commerce, and logistics players. South Korea has high smartphone and digital payment penetration, and consumers already expect rapid fulfilment from e-commerce. •Urban concentration around the Seoul metropolitan region means shorter distances to fulfilment, and dense demand makes ultra-fast delivery more operationally feasible. Competitive pressure: once overnight/next-day delivery becomes the baseline, companies seek further differentiation through faster delivery and local store networks. •Retailers and convenience chains are leveraging their physical store footprints as delivery nodes in this model (e.g., CU linking its stores). Delivery-time compressions will intensify: we can expect more players offering < 30-minute or “within an hour” promises, especially in dense urban zones. •Fulfillment networks will shift further toward micro-hubs, store-based inventory, or dark stores to meet tighter SLAs. Regional expansion (beyond Seoul) will be more challenging; in lower-density areas, the cost/value trade-off will limit ultra-fast promises so that the model will bifurcate into “premium quick” for urban and “standard express” elsewhere. •Margins will come under pressure as the cost of ultra-fast delivery remains high; companies will need to find business model offsets (higher order frequency, premium delivery fees, subscriptions) to sustain profitability. 2.Physical retail footprint + store-as-fulfilment-node models are gaining prominence •Offline retailers and convenience chains are becoming a core part of the quick commerce fulfillment network. For example, CU has partnered with Naver’s one-hour “Now Delivery” service, using its widespread store network to enable faster local deliveries. •The quick-commerce segment in South Korea is evolving from purely e-commerce warehouses toward hybrid models local stores acting as micro-fulfilment bases, enabling same-day/quick dispatch. Big-box retailers are sounding alarm bells about the intensifying “quick delivery war.” •The geography (dense cities), digital adoption, and consumer expectation for convenience make store-node models attractive. Traditional offline retailers aim to defend and extend their relevance by participating in rapid-delivery ecosystems rather than being disintermediated. •Cost considerations: utilising existing store networks for inventory and delivery reduces the investment needed for entirely new dark-store networks, improving unit economics if managed well. Consumer behaviour: many purchases in quick commerce are impulse or urgent (e.g., snacks, everyday essentials), which suit proximate store-based fulfilment rather than remote warehousing. •Retail chains with dense store networks will be leveraged for Q-commerce growth, expect announcements of partnerships or in-house quick-delivery arms by convenience chains and supermarket groups. Retailers that fail to convert their physical footprint into rapid-delivery fulfillment may lose market share to those who do. •The logistics network architecture will become more complex, with a multi-tiered approach (dark stores, store nodes, and last-mile specialised fleets) becoming the norm. Operational challenges, including inventory accuracy, store fulfillment staffing, and return handling, will become more acute. Winners will be those who effectively integrate store operations with digital supply chains. 3.Category expansion and basket diversification beyond core groceries •While grocery remains foundational, quick-commerce platforms in Korea are broadening into adjacent categories and small-basket everyday goods. For example, Coupang Eats (traditionally food-delivery) launched a “Shopping” category delivering goods from local shops (flowers, stationery, pet supplies) within ~30-60 minutes. •The broader online grocery market in Korea is forecast to grow rapidly, and consumer preferences are shifting toward “essentials, staples, snacks” via online channels. Delivery use-cases are increasingly being perceived as part of “daily routine commerce” rather than purely “occasional big-ticket buy.” •Consumers increasingly expect any category they use regularly to be available instantly (or near-instantly) online; the “why wait?” mindset is spreading. Retail margins and differentiation in grocery are under pressure, so platforms are seeking to plug growth via higher-margin or higher-frequency categories (household supplies, personal care, impulse goods). • The physical store footprint (see Trend 2) enables broad category inventory to be held locally and delivered quickly, making it operationally feasible to extend category breadth. For platforms, increasing the number of daily “touchpoints” (orders) improves stickiness and economics (higher order frequency = better unit economics). • We should see quick-commerce offers cover a broader portfolio of SKUs, including non-food everyday items, impulse products, and potentially services (e.g., pharmacy/OTC). Order frequency will increase as more categories become available; the convenience access model becomes more embedded in daily life rather than occasional. • Platforms will need to manage category-specific logistics (e.g., perishables, household goods, fragile items) and ensure local inventory breadth without sacrificing delivery speed or increasing complexity. Competitive pressure will mount around the “more SKUs, same speed” platforms, as those that can deliver depth and speed will win market share; others may retrench or specialize. 4. Technology-enabled logistics and inventory optimisation are becoming strategic levers • Quick-commerce in South Korea is increasingly underpinned by advanced logistics, automation, and digital inventory management to support tight delivery windows and dense urban fulfilment. For example, the broader e-commerce logistics market in Korea is expected to experience significant growth, with automation and smart systems identified as key drivers of this growth. • Platforms such as Coupang emphasize their logistics infrastructure as a competitive advantage, delivering in hours, leveraging robotics/AI, and operating dense fulfillment networks. Research into Korean urban delivery data is revealing how lifestyle clusters correlate with delivery patterns, highlighting how big data is being used to optimize fulfillment. • With delivery-time expectations compressed (see Trend 1), logistics efficiency becomes increasingly critical for both cost and service delivery. Without automation, costs rise sharply under tighter SLAs. • Inventory location optimization (which SKUs to hold where) becomes more complex in Q-commerce local fulfillment nodes must stock the right mix to satisfy rapid orders with limited pick zones. Urban density in Korea supports technology-enabled micro-fulfillment/hyperlocal networks – shorter distances and more predictable demand zones make robotics and AI systems more viable. • Cost pressure: As players scale their quick-commerce operations, a margin squeeze forces them to invest in technology to drive productivity and reduce per-order costs. • Investment in micro-fulfilment centres, robotics, AI-based routing, and store (node) inventory optimisation will rise significantly. Companies that delay will be cost-disadvantaged. Engineering and logistics talent will become a key differentiator in the Korean market; partnerships with robotics/logistics tech vendors may accelerate. • Data-driven demand forecasting at the hyper-local level (street block/neighborhood) will become standard, improving availability and reducing stockouts or overstocks at fulfillment nodes. As these systems scale, unit-delivery costs per order are expected to decline, enabling faster delivery at sustainable margins. Platforms lacking in technology will struggle to keep up or may withdraw from ultra-fast segments. Competitive Landscape In the next two to four years, South Korea’s quick commerce industry is projected to move into a phase of operational consolidation, with competitiveness increasingly defined by scale, efficiency, and ecosystem integration. Major players are expected to optimize fulfillment networks and diversify product categories, raising entry barriers for new participants. Convenience store chains and supermarket operators will further convert their physical outlets into micro-fulfillment centers, strengthening their role within the urban delivery network. Nonetheless, long-term profitability will hinge on cost optimization and technology-led efficiency gains, given the capital-intensive nature of rapid delivery operations. New entrants will find it challenging to compete without established delivery fleets, high fulfillment density, or an integrated customer base. The industry’s next evolution will likely centre on strategic alliances, platform-to-platform and platform-to-retailer partnerships creating shared infrastructure for speed and coverage rather than isolated networks. Current State of the Market • South Korea’s quick commerce sector has entered a phase of rapid expansion and consolidation, marked by high competitive intensity among retail, e-commerce, and delivery ecosystem players. The market has grown from a niche experiment in 2020 into a mainstream channel projected to surpass KRW 5 trillion by 2025. The shift toward one-hour or faster deliveries has been accelerated by dense urbanisation, high smartphone penetration, and digitally mature consumers concentrated in the Seoul metropolitan area. • Traditional retail formats such as hypermarkets and department stores are seeing slower growth, while quick commerce is increasingly capturing discretionary and impulse spending through greater convenience and immediacy. The basis of competition has shifted beyond delivery speed to include service integration, assortment depth, and strategic platform collaborations. This marks a transition from standalone dark-store models to a hybrid ecosystem in which retailers, logistics providers, and digital platforms work together to enable on-demand fulfillment. Key Players and New Entrants • South Korea’s quick commerce market is led by major incumbents that have embedded rapid delivery within their larger retail and e-commerce operations. Woowa Brothers runs Baemin’s B-Mart, one of the country’s most prominent quick commerce services, utilizing dark stores in major cities to deliver groceries and everyday essentials. GS Retail has transformed its GS25 convenience stores and GS The Fresh supermarkets into local fulfillment hubs, working with delivery partners to provide one-hour service in dense urban areas. • Coupang has broadened its Coupang Eats platform beyond food to include general merchandise, leveraging its logistics network for small-basket, instant deliveries. Additionally, digital giants like Naver and Kakao are incorporating quick commerce capabilities into their wider platform ecosystems to strengthen customer engagement. Rather than new standalone entrants, the recent market dynamic is characterized by incumbents with existing infrastructure strengthening their position through platform tie-ups and fulfillment optimization. Recent Launches, Mergers, and Acquisitions • Over the past year, South Korea’s quick commerce sector has been shaped by a wave of partnerships and new service launches, reflecting how retailers are adapting to the evolving fulfillment landscape. Baemin expanded its B-Mart offering to include early-morning grocery delivery, positioning itself to compete with convenience chains by integrating food and daily essentials on a unified digital platform. • GS Retail strengthened its partnership with Naver through the “Now Delivery” service, enabling one-hour deliveries from GS25 stores, while also collaborating with platforms such as Baemin, Coupang Eats, and Yogiyo to extend its distribution reach. Broader ecosystem alignment is also evident in large-scale alliances like the 2025 joint venture between Alibaba’s AliExpress Korea and Shinsegae Group’s Gmarket, signaling rising cross-border interest in Korea’s digital retail infrastructure. Together, these initiatives indicate a market shifting from fragmented competition toward multi-platform collaboration and ecosystem integration. This report provides a detailed data-centric analysis of the quick commerce industry in South Korea offering comprehensive coverage of both overall and quick commerce markets. It includes more than 100+ KPIs, covering gross merchandise value, gross merchandise volume, average order value, and order frequency. The report offers an in-depth analysis of quick commerce, including product type, payment mode, age group, location tier, business model, and delivery time. It further categorizes the market by revenue streams (advertising, delivery fee, and subscription-based models). In addition, the analysis captures consumer demographics by age and location alongside behavioral indicators such as subscription uptake and average delivery time. Collectively, these datasets provide a comprehensive view of market size, consumer behavior, and operational efficiency within the quick commerce ecosystem. PayNXT360’s research methodology is based on industry best practices. It's unbiased analysis leverages a proprietary analytics platform to offer a detailed view of emerging business and investment market opportunities.
This report provides a detailed data-driven analysis of the quick commerce market in South Korea, focusing on the rapid delivery ecosystem and its growth trajectory. It examines key market segments, operational models, and consumer behavior shaping the evolution of instant delivery services: • South Korea Quick Commerce Market Size and Growth Dynamics -- Gross Merchandise Value -- Gross Merchandise Volume -- Average Order Value -- Order Frequency per Year • South Korea Quick Commerce Market Segmentation by Product Type -- Groceries and Staples -- Fruits and Vegetables -- Snacks and Beverages -- Personal Care and Hygiene -- Pharmaceuticals and Health Products -- Home Décor -- Clothing and Accessories -- Electronics -- Others • South Korea Quick Commerce Market Segmentation by Payment Mode -- Instant Bank Transfer -- Wallets and Digital Payments -- Credit and Debit Cards -- Cash on Delivery • South Korea Quick Commerce Market Segmentation by Age Group -- Gen Z (15–25) -- Millennials (26–39) -- Gen X (40–55) -- Baby Boomers (Above 55) • South Korea Quick Commerce Market Segmentation by Location Tier -- Tier 1 Cities -- Tier 2 Cities -- Tier 3 Cities • South Korea Quick Commerce Market Segmentation by Business Model -- Inventory-led Model -- Hyper-local Model -- Multi-vendor Platform Model -- Others • South Korea Quick Commerce Market Segmentation by Delivery Time -- Delivery in 30 Minutes -- Delivery 30–60 Minutes -- Delivery in 3 Hours • South Korea Quick Commerce Consumer Behavior and Demographics -- Average Subscription Uptake by Age Group -- Average Subscription Uptake by Location Tier -- Average Subscription Uptake -- Average Delivery Time • South Korea Quick Commerce Revenue Structure and Composition -- Advertising Revenue -- Delivery Fee Revenue -- Subscription Revenue • South Korea Quick Commerce Operational Metrics by Product Type -- Gross Merchandise Value by Product Type -- Gross Merchandise Volume by Product Type -- Average Order Value by Product Type -- Order Frequency by Product Type • South Korea Quick Commerce Operational Metrics by Payment Mode -- Gross Merchandise Value by Payment Mode -- Gross Merchandise Volume by Payment Mode -- Average Order Value by Payment Mode • South Korea Quick Commerce Operational Metrics by Age Group -- Gross Merchandise Value by Age Group -- Gross Merchandise Volume by Age Group -- Average Order Value by Age Group • South Korea Quick Commerce Operational Metrics by Location Tier -- Gross Merchandise Value by Location Tier -- Gross Merchandise Volume by Location Tier -- Average Order Value by Location Tier -- Order Frequency by Location Tier • South Korea Quick Commerce Operational Metrics by Business Model -- Gross Merchandise Value by Business Model -- Gross Merchandise Volume by Business Model -- Average Order Value by Business Model • South Korea Quick Commerce Operational Metrics by Delivery Time -- Gross Merchandise Value by Delivery Time -- Gross Merchandise Volume by Delivery Time -- Average Order Value by Delivery Time -- Order Frequency by Delivery Time
• Comprehensive Market Intelligence: Gain a holistic understanding of the overall quick commerce with detailed operational metrics such as gross merchandise value, gross merchandise volume, average order value, and order frequency across key product categories. • Granular Segmentation and Cross-Analysis: Explore the fast-growing quick commerce ecosystem through detailed segmentation by product type, payment mode, age group, location tier, business model, and delivery time, providing data into evolving consumer behavior and purchasing dynamics. • Consumer Behavior and Ecosystem Readiness: Understand how demographics and payment method adoption are shaping consumer preferences and driving the expansion of instant delivery services in both urban and semi-urban markets. • Data-Driven Forecasts and KPI Tracking: Access a comprehensive dataset of 100+ key performance indicators (KPIs) with historical and forecast data through 2029, offering visibility into growth drivers, market trends, and investment opportunities across the quick commerce sector. • Decision-Ready Databook Format: Presented in a structured, data-centric format compatible with analytical and financial modeling, the Databook enables quick commerce companies, retailers, investors, and logistics partners to make informed, evidence-based strategic decisions.
1. About this Report 1.1 Summary 1.2 Methodology 1.3 Definitions 1.4 Disclaimer 2. South Korea Quick Commerce Industry Attractiveness 2.1 South Korea Quick Commerce – Gross Merchandise Value Trend Analysis, 2020-2029 2.2 South Korea Quick Commerce – Gross Merchandise Volume Trend Analysis, 2020-2029 2.3 South Korea Quick Commerce – Average Order Value Trend Analysis, 2020-2029 2.4 South Korea Quick Commerce – Order Frequency Trend Analysis, 2020-2029 2.5 South Korea Quick Commerce – Market Share Analysis by Key Players, 2024 3. South Korea Quick Commerce Operational KPIs 3.1 South Korea Quick Commerce Revenue and Growth Trend, 2020-2029 3.2 South Korea Quick Commerce Revenue Structure, Composition, and Growth Analysis by Segment, 2024 3.2.1 Advertising Revenue, 2020-2029 3.2.2 Delivery Fee Revenue, 2020-2029 3.2.3 Subscription Revenue, 2020-2029 4. South Korea Quick Commerce Analysis by Product Type 4.1 South Korea Quick Commerce Segment Share by Product Type, 2024 4.2 South Korea Quick Commerce Analysis by Groceries & Staples: Market Size and Forecast, 2020-2029 4.2.1 Groceries & Staples- Gross Merchandise Value Trend Analysis, 2020-2029 4.2.2 Groceries & Staples- Gross Merchandise Volume Trend Analysis, 2020-2029 4.2.3 Groceries & Staples- Average Order Value Trend Analysis, 2020-2029 4.2.4 Groceries & Staples- Order Frequency Trend Analysis, 2020-2029 4.3 South Korea Quick Commerce Analysis by Fruits & Vegetables: Market Size and Forecast, 2020-2029 4.3.1 Fruits & Vegetables- Gross Merchandise Value Trend Analysis, 2020-2029 4.3.2 Fruits & Vegetables- Gross Merchandise Volume Trend Analysis, 2020-2029 4.3.3 Fruits & Vegetables- Average Order Value Trend Analysis, 2020-2029 4.3.4 Fruits & Vegetables- Order Frequency Trend Analysis, 2020-2029 4.4 South Korea Quick Commerce Analysis by Snacks & Beverages: Market Size and Forecast, 2020-2029 4.4.1 Snacks & Beverages- Gross Merchandise Value Trend Analysis, 2020-2029 4.4.2 Snacks & Beverages- Gross Merchandise Volume Trend Analysis, 2020-2029 4.4.3 Snacks & Beverages- Average Order Value Trend Analysis, 2020-2029 4.4.4 Snacks & Beverages- Order Frequency Trend Analysis, 2020-2029 4.5 South Korea Quick Commerce Analysis by Personal Care & Hygiene: Market Size and Forecast, 2020-2029 4.5.1 Personal Care & Hygiene- Gross Merchandise Value Trend Analysis, 2020-2029 4.5.2 Personal Care & Hygiene- Gross Merchandise Volume Trend Analysis, 2020-2029 4.5.3 Personal Care & Hygiene- Average Order Value Trend Analysis, 2020-2029 4.5.4 Personal Care & Hygiene- Order Frequency Trend Analysis, 2020-2029 4.6 South Korea Quick Commerce Analysis by Pharmaceuticals & Health Products: Market Size and Forecast, 2020-2029 4.6.1 Pharmaceuticals & Health Products- Gross Merchandise Value Trend Analysis, 2020-2029 4.6.2 Pharmaceuticals & Health Products- Gross Merchandise Volume Trend Analysis, 2020-2029 4.6.3 Pharmaceuticals & Health Products- Average Order Value Trend Analysis, 2020-2029 4.6.4 Pharmaceuticals & Health Products- Order Frequency Trend Analysis, 2020-2029 4.7 South Korea Quick Commerce Analysis by Home Décor: Market Size and Forecast, 2020-2029 4.7.1 Home Décor- Gross Merchandise Value Trend Analysis, 2020-2029 4.7.2 Home Décor- Gross Merchandise Volume Trend Analysis, 2020-2029 4.7.3 Home Décor- Average Order Value Trend Analysis, 2020-2029 4.7.4 Home Décor- Order Frequency Trend Analysis, 2020-2029 4.8 South Korea Quick Commerce Analysis by Clothing & Accessories: Market Size and Forecast, 2020-2029 4.8.1 Clothing & Accessories- Gross Merchandise Value Trend Analysis, 2020-2029 4.8.2 Clothing & Accessories- Gross Merchandise Volume Trend Analysis, 2020-2029 4.8.3 Clothing & Accessories- Average Order Value Trend Analysis, 2020-2029 4.8.4 Clothing & Accessories- Order Frequency Trend Analysis, 2020-2029 4.9 South Korea Quick Commerce Analysis by Electronics: Market Size and Forecast, 2020-2029 4.9.1 Electronics- Gross Merchandise Value Trend Analysis, 2020-2029 4.9.2 Electronics- Gross Merchandise Volume Trend Analysis, 2020-2029 4.9.3 Electronics- Average Order Value Trend Analysis, 2020-2029 4.9.4 Electronics- Order Frequency Trend Analysis, 2020-2029 4.10 South Korea Quick Commerce Analysis by Other Product Category: Market Size and Forecast, 2020-2029 4.10.1 Other Product Category- Gross Merchandise Value Trend Analysis, 2020-2029 4.10.2 Other Product Category- Gross Merchandise Volume Trend Analysis, 2020-2029 4.10.3 Other Product Category- Average Order Value Trend Analysis, 2020-2029 4.10.4 Other Product Category- Order Frequency Trend Analysis, 2020-2029 5. South Korea Quick Commerce Analysis by Payment Method 5.1 South Korea Quick Commerce Segment Share by Payment Method, 2020-2029 5.2 South Korea Quick Commerce Analysis by Instant Bank Transfer: Market Size and Forecast, 2020-2029 5.2.1 Instant Bank Transfer- Gross Merchandise Value Trend Analysis, 2020-2029 5.2.2 Instant Bank Transfer- Gross Merchandise Volume Trend Analysis, 2020-2029 5.2.3 Instant Bank Transfer- Average Order Value Trend Analysis, 2020-2029 5.3 South Korea Quick Commerce Analysis by Wallets & Digital Payments: Market Size and Forecast, 2020-2029 5.3.1 Wallets & Digital Payments- Gross Merchandise Value Trend Analysis, 2020-2029 5.3.2 Wallets & Digital Payments- Gross Merchandise Volume Trend Analysis, 2020-2029 5.3.3 Wallets & Digital Payments- Average Order Value Trend Analysis, 2020-2029 5.4 South Korea Quick Commerce Analysis by Credit & Debit Cards: Market Size and Forecast, 2020-2029 5.4.1 Credit & Debit Cards- Gross Merchandise Value Trend Analysis, 2020-2029 5.4.2 Credit & Debit Cards- Gross Merchandise Volume Trend Analysis, 2020-2029 5.4.3 Credit & Debit Cards- Average Order Value Trend Analysis, 2020-2029 5.5 South Korea Quick Commerce Analysis by Cash on Delivery: Market Size and Forecast, 2020-2029 5.5.1 Cash on Delivery- Gross Merchandise Value Trend Analysis, 2020-2029 5.5.2 Cash on Delivery- Gross Merchandise Volume Trend Analysis, 2020-2029 5.5.3 Cash on Delivery- Average Order Value Trend Analysis, 2020-2029 6. South Korea Quick Commerce Analysis by Age Group 6.1 South Korea Quick Commerce Segment Share by Age Group, 2024 6.2 South Korea Quick Commerce Analysis by Gen Z (15–25) Age Group: Market Size and Forecast, 2020-2029 6.2.1 Gen Z (15–25) Age Group- Gross Merchandise Value Trend Analysis, 2020-2029 6.2.2 Gen Z (15–25) Age Group- Gross Merchandise Volume Trend Analysis, 2020-2029 6.2.3 Gen Z (15–25) Age Group- Average Order Value Trend Analysis, 2020-2029 6.3 South Korea Quick Commerce Analysis by Millennials (26–39) Age Group: Market Size and Forecast, 2020-2029 6.3.1 Millennials (26–39) Age Group- Gross Merchandise Value Trend Analysis, 2020-2029 6.3.2 Millennials (26–39) Age Group- Gross Merchandise Volume Trend Analysis, 2020-2029 6.3.3 Millennials (26–39) Age Group- Average Order Value Trend Analysis, 2020-2029 6.4 South Korea Quick Commerce Analysis by Gen X (40–55) Age Group: Market Size and Forecast, 2020-2029 6.4.1 Gen X (40–55) Age Group- Gross Merchandise Value Trend Analysis, 2020-2029 6.4.2 Gen X (40–55) Age Group- Gross Merchandise Volume Trend Analysis, 2020-2029 6.4.3 Gen X (40–55) Age Group- Average Order Value Trend Analysis, 2020-2029 6.5 South Korea Quick Commerce Analysis by Baby Boomers (Above 55+) Age Group: Market Size and Forecast, 2020-2029 6.5.1 Baby Boomers (Above 55+) Age Group- Gross Merchandise Value Trend Analysis, 2020-2029 6.5.2 Baby Boomers (Above 55+) Age Group- Gross Merchandise Volume Trend Analysis, 2020-2029 6.5.3 Baby Boomers (Above 55+) Age Group- Average Order Value Trend Analysis, 2020-2029 7. South Korea Quick Commerce Analysis by Location 7.1 South Korea Quick Commerce Segment Share by Location, 2020-2029 7.2 South Korea Quick Commerce Analysis by Tier 1 Cities: Market Size and Forecast, 2020-2029 7.2.1 Tier 1 Cities- Gross Merchandise Value Trend Analysis, 2020-2029 7.2.2 Tier 1 Cities- Gross Merchandise Volume Trend Analysis, 2020-2029 7.2.3 Tier 1 Cities- Average Order Value Trend Analysis, 2020-2029 7.2.4 Tier 1 Cities- Order Frequency Trend Analysis, 2020-2029 7.3 South Korea Quick Commerce Analysis by Tier 2 Cities: Market Size and Forecast, 2020-2029 7.3.1 Tier 2 Cities- Gross Merchandise Value Trend Analysis, 2020-2029 7.3.2 Tier 2 Cities- Gross Merchandise Volume Trend Analysis, 2020-2029 7.3.3 Tier 2 Cities- Average Order Value Trend Analysis, 2020-2029 7.3.4 Tier 2 Cities- Order Frequency Trend Analysis, 2020-2029 7.4 South Korea Quick Commerce Analysis by Tier 3 Cities: Market Size and Forecast, 2020-2029 7.4.1 Tier 3 Cities- Gross Merchandise Value Trend Analysis, 2020-2029 7.4.2 Tier 3 Cities- Gross Merchandise Volume Trend Analysis, 2020-2029 7.4.3 Tier 3 Cities- Average Order Value Trend Analysis, 2020-2029 7.4.4 Tier 3 Cities- Order Frequency Trend Analysis, 2020-2029 8. South Korea Quick Commerce Analysis by Business Model 8.1 South Korea Quick Commerce Segment Share by Business Model, 2024 8.2 South Korea Quick Commerce Analysis by Inventory Model: Market Size and Forecast, 2020-2029 8.2.1 Inventory Model- Gross Merchandise Value Trend Analysis, 2020-2029 8.2.2 Inventory Model- Gross Merchandise Volume Trend Analysis, 2020-2029 8.2.3 Inventory Model- Average Order Value Trend Analysis, 2020-2029 8.3 South Korea Quick Commerce Analysis by Hyperlocal Model: Market Size and Forecast, 2020-2029 8.3.1 Hyperlocal Model- Gross Merchandise Value Trend Analysis, 2020-2029 8.3.2 Hyperlocal Model- Gross Merchandise Volume Trend Analysis, 2020-2029 8.3.3 Hyperlocal Model- Average Order Value Trend Analysis, 2020-2029 8.4 South Korea Quick Commerce Analysis by Multi-vendor Platform Model: Market Size and Forecast, 2020-2029 8.4.1 Multi-vendor Platform Model- Gross Merchandise Value Trend Analysis, 2020-2029 8.4.2 Multi-vendor Platform Model- Gross Merchandise Volume Trend Analysis, 2020-2029 8.4.3 Multi-vendor Platform Model- Average Order Value Trend Analysis, 2020-2029 8.5 South Korea Quick Commerce Analysis by Other Business Models: Market Size and Forecast, 2020-2029 8.5.1 Other Business Models- Gross Merchandise Value Trend Analysis, 2020-2029 8.5.2 Other Business Models- Gross Merchandise Volume Trend Analysis, 2020-2029 8.5.3 Other Business Models- Average Order Value Trend Analysis, 2020-2029 9. South Korea Quick Commerce Analysis by Delivery Time 9.1 South Korea Quick Commerce Segment Share by Delivery Time, 2020-2029 9.2 South Korea Quick Commerce Analysis by Delivery Time In 30 Minutes: Market Size and Forecast, 2020-2029 9.2.1 Delivery Time In 30 Minutes- Gross Merchandise Value Trend Analysis, 2020-2029 9.2.2 Delivery Time In 30 Minutes- Gross Merchandise Volume Trend Analysis, 2020-2029 9.2.3 Delivery Time In 30 Minutes- Average Order Value Trend Analysis, 2020-2029 9.2.4 Delivery Time In 30 Minutes- Order Frequency Trend Analysis, 2020-2029 9.3 South Korea Quick Commerce Analysis by Delivery Time 30–60 Minutes: Market Size and Forecast, 2020-2029 9.3.1 Delivery Time 30–60 Minutes- Gross Merchandise Value Trend Analysis, 2020-2029 9.3.2 Delivery Time 30–60 Minutes- Gross Merchandise Volume Trend Analysis, 2020-2029 9.3.3 Delivery Time 30–60 Minutes- Average Order Value Trend Analysis, 2020-2029 9.3.4 Delivery Time 30–60 Minutes- Order Frequency Trend Analysis, 2020-2029 9.4 South Korea Quick Commerce Analysis by Delivery Time In 3 Hours: Market Size and Forecast, 2020-2029 9.4.1 Delivery Time In 3 Hours- Gross Merchandise Value Trend Analysis, 2020-2029 9.4.2 Delivery Time In 3 Hours- Gross Merchandise Volume Trend Analysis, 2020-2029 9.4.3 Delivery Time In 3 Hours- Average Order Value Trend Analysis, 2020-2029 9.4.4 Delivery Time In 3 Hours- Order Frequency Trend Analysis, 2020-2029 10. South Korea Quick Commerce Consumer Behaviour and Adoption 10.1 South Korea Quick Commerce- Average Subscription Uptake, 2024 10.2 South Korea Quick Commerce- Average Subscription Uptake by Age Group, 2024 10.3 South Korea Quick Commerce- Average Subscription Uptake by Location, 2024 10.4 South Korea Quick Commerce- Average Delivery Time, 2024 11. Further Reading 11.1 About PayNXT360 11.2 Related Research
Table 1: South Korea Quick Commerce – Gross Merchandise Value (US$ Million), 2020–2029 Table 2: South Korea Quick Commerce – Gross Merchandise Volume (Millions), 2020–2029 Table 3: South Korea Quick Commerce – Average Order Value (US$), 2020–2029 Table 4: South Korea Quick Commerce – Order Frequency (Orders per Year), 2020–2029 Table 5: South Korea Quick Commerce Revenue and Growth Trend (US$ Million), 2020–2029 Table 6: Advertising Revenue (US$ Million), 2020–2029 Table 7: Delivery Fee Revenue (US$ Million), 2020–2029 Table 8: Subscription Revenue (US$ Million), 2020–2029 Table 9: Groceries & Staples – Gross Merchandise Value (US$ Million), 2020–2029 Table 10: Groceries & Staples – Gross Merchandise Volume (Millions), 2020–2029 Table 11: Groceries & Staples – Average Order Value (US$), 2020–2029 Table 12: Groceries & Staples – Order Frequency (Orders per Year), 2020–2029 Table 13: Fruits & Vegetables – Gross Merchandise Value (US$ Million), 2020–2029 Table 14: Fruits & Vegetables – Gross Merchandise Volume (Millions), 2020–2029 Table 15: Fruits & Vegetables – Average Order Value (US$), 2020–2029 Table 16: Fruits & Vegetables – Order Frequency (Orders per Year), 2020–2029 Table 17: Snacks & Beverages – Gross Merchandise Value (US$ Million), 2020–2029 Table 18: Snacks & Beverages – Gross Merchandise Volume (Millions), 2020–2029 Table 19: Snacks & Beverages – Average Order Value (US$), 2020–2029 Table 20: Snacks & Beverages – Order Frequency (Orders per Year), 2020–2029 Table 21: Personal Care & Hygiene – Gross Merchandise Value (US$ Million), 2020–2029 Table 22: Personal Care & Hygiene – Gross Merchandise Volume (Millions), 2020–2029 Table 23: Personal Care & Hygiene – Average Order Value (US$), 2020–2029 Table 24: Personal Care & Hygiene – Order Frequency (Orders per Year), 2020–2029 Table 25: Pharmaceuticals & Health Products – Gross Merchandise Value (US$ Million), 2020–2029 Table 26: Pharmaceuticals & Health Products – Gross Merchandise Volume (Millions), 2020–2029 Table 27: Pharmaceuticals & Health Products – Average Order Value (US$), 2020–2029 Table 28: Pharmaceuticals & Health Products – Order Frequency (Orders per Year), 2020–2029 Table 29: Home Décor – Gross Merchandise Value (US$ Million), 2020–2029 Table 30: Home Décor – Gross Merchandise Volume (Millions), 2020–2029 Table 31: Home Décor – Average Order Value (US$), 2020–2029 Table 32: Home Décor – Order Frequency (Orders per Year), 2020–2029 Table 33: Clothing & Accessories – Gross Merchandise Value (US$ Million), 2020–2029 Table 34: Clothing & Accessories – Gross Merchandise Volume (Millions), 2020–2029 Table 35: Clothing & Accessories – Average Order Value (US$), 2020–2029 Table 36: Clothing & Accessories – Order Frequency (Orders per Year), 2020–2029 Table 37: Electronics – Gross Merchandise Value (US$ Million), 2020–2029 Table 38: Electronics – Gross Merchandise Volume (Millions), 2020–2029 Table 39: Electronics – Average Order Value (US$), 2020–2029 Table 40: Electronics – Order Frequency (Orders per Year), 2020–2029 Table 41: Others – Gross Merchandise Value (US$ Million), 2020–2029 Table 42: Others – Gross Merchandise Volume (Millions), 2020–2029 Table 43: Others – Average Order Value (US$), 2020–2029 Table 44: Others – Order Frequency (Orders per Year), 2020–2029 Table 45: Instant Bank Transfer – Gross Merchandise Value (US$ Million), 2020–2029 Table 46: Instant Bank Transfer – Gross Merchandise Volume (Millions), 2020–2029 Table 47: Instant Bank Transfer – Average Order Value (US$), 2020–2029 Table 48: Wallets & Digital Payments – Gross Merchandise Value (US$ Million), 2020–2029 Table 49: Wallets & Digital Payments – Gross Merchandise Volume (Millions), 2020–2029 Table 50: Wallets & Digital Payments – Average Order Value (US$), 2020–2029 Table 51: Credit & Debit Card – Gross Merchandise Value (US$ Million), 2020–2029 Table 52: Credit & Debit Card – Gross Merchandise Volume (Millions), 2020–2029 Table 53: Credit & Debit Card – Average Order Value (US$), 2020–2029 Table 54: Cash on Delivery – Gross Merchandise Value (US$ Million), 2020–2029 Table 55: Cash on Delivery – Gross Merchandise Volume (Millions), 2020–2029 Table 56: Cash on Delivery – Average Order Value (US$), 2020–2029 Table 57: Gen Z (15–25) Age Group – Gross Merchandise Value (US$ Million), 2020–2029 Table 58: Gen Z (15–25) Age Group – Gross Merchandise Volume (Millions), 2020–2029 Table 59: Gen Z (15–25) Age Group – Average Order Value (US$), 2020–2029 Table 60: Millennials (26–39) Age Group – Gross Merchandise Value (US$ Million), 2020–2029 Table 61: Millennials (26–39) Age Group – Gross Merchandise Volume (Millions), 2020–2029 Table 62: Millennials (26–39) Age Group – Average Order Value (US$), 2020–2029 Table 63: Gen X (40–55) Age Group – Gross Merchandise Value (US$ Million), 2020–2029 Table 64: Gen X (40–55) Age Group – Gross Merchandise Volume (Millions), 2020–2029 Table 65: Gen X (40–55) Age Group – Average Order Value (US$), 2020–2029 Table 66: Baby Boomers (Above 55+) Age Group – Gross Merchandise Value (US$ Million), 2020–2029 Table 67: Baby Boomers (Above 55+) Age Group – Gross Merchandise Volume (Millions), 2020–2029 Table 68: Baby Boomers (Above 55+) Age Group – Average Order Value (US$), 2020–2029 Table 69: Tier 1 Cities – Gross Merchandise Value (US$ Million), 2020–2029 Table 70: Tier 1 Cities – Gross Merchandise Volume (Millions), 2020–2029 Table 71: Tier 1 Cities – Average Order Value (US$), 2020–2029 Table 72: Tier 1 Cities – Order Frequency (Orders per Year), 2020–2029 Table 73: Tier 2 Cities – Gross Merchandise Value (US$ Million), 2020–2029 Table 74: Tier 2 Cities – Gross Merchandise Volume (Millions), 2020–2029 Table 75: Tier 2 Cities – Average Order Value (US$), 2020–2029 Table 76: Tier 2 Cities – Order Frequency (Orders per Year), 2020–2029 Table 77: Tier 3 Cities – Gross Merchandise Value (US$ Million), 2020–2029 Table 78: Tier 3 Cities – Gross Merchandise Volume (Millions), 2020–2029 Table 79: Tier 3 Cities – Average Order Value (US$), 2020–2029 Table 80: Tier 3 Cities – Order Frequency (Orders per Year), 2020–2029 Table 81: Inventory Model – Gross Merchandise Value (US$ Million), 2020–2029 Table 82: Inventory Model – Gross Merchandise Volume (Millions), 2020–2029 Table 83: Inventory Model – Average Order Value (US$), 2020–2029 Table 84: Hyperlocal Model – Gross Merchandise Value (US$ Million), 2020–2029 Table 85: Hyperlocal Model – Gross Merchandise Volume (Millions), 2020–2029 Table 86: Hyperlocal Model – Average Order Value (US$), 2020–2029 Table 87: Multi-vendor Platform Model – Gross Merchandise Value (US$ Million), 2020–2029 Table 88: Multi-vendor Platform Model – Gross Merchandise Volume (Millions), 2020–2029 Table 89: Multi-vendor Platform Model – Average Order Value (US$), 2020–2029 Table 90: Others – Gross Merchandise Value (US$ Million), 2020–2029 Table 91: Others – Gross Merchandise Volume (Millions), 2020–2029 Table 92: Others – Average Order Value (US$), 2020–2029 Table 93: Delivery Time in 30 Minutes – Gross Merchandise Value (US$ Million), 2020–2029 Table 94: Delivery Time in 30 Minutes – Gross Merchandise Volume (Millions), 2020–2029 Table 95: Delivery Time in 30 Minutes – Average Order Value (US$), 2020–2029 Table 96: Delivery Time in 30 Minutes – Order Frequency (Orders per Year), 2020–2029 Table 97: Delivery Time 30–60 Minutes – Gross Merchandise Value (US$ Million), 2020–2029 Table 98: Delivery Time 30–60 Minutes – Gross Merchandise Volume (Millions), 2020–2029 Table 99: Delivery Time 30–60 Minutes – Average Order Value (US$), 2020–2029 Table 100: Delivery Time 30–60 Minutes – Order Frequency (Orders per Year), 2020–2029 Table 101: Delivery Time in 3 Hours – Gross Merchandise Value (US$ Million), 2020–2029 Table 102: Delivery Time in 3 Hours – Gross Merchandise Volume (Millions), 2020–2029 Table 103: Delivery Time in 3 Hours – Average Order Value (US$), 2020–2029 Table 104: Delivery Time in 3 Hours – Order Frequency (Orders per Year), 2020–2029
Figure 1: PayNXT360’s Methodology Framework Figure 2: South Korea Quick Commerce – Gross Merchandise Value (US$ Million), 2020–2029 Figure 3: South Korea Quick Commerce – Gross Merchandise Volume (Millions), 2020–2029 Figure 4: South Korea Quick Commerce – Average Order Value (US$), 2020–2029 Figure 5: South Korea Quick Commerce – Order Frequency (Orders per Year), 2020–2029 Figure 6: South Korea Quick Commerce – Market Share Analysis by Key Players (%), 2024 Figure 7: South Korea Quick Commerce Revenue and Growth Trend (US$ Million), 2020–2029 Figure 8: South Korea Quick Commerce Revenue Structure, Composition, and Growth Analysis by Segment (US$ Million), 2024 Figure 9: Advertising Revenue (US$ Million), 2020–2029 Figure 10: Delivery Fee Revenue (US$ Million), 2020–2029 Figure 11: Subscription Revenue (US$ Million), 2020–2029 Figure 12: South Korea Quick Commerce Segment Share by Product Type, 2024 Figure 13: Groceries & Staples – Gross Merchandise Value (US$ Million), 2020–2029 Figure 14: Groceries & Staples – Gross Merchandise Volume (Millions), 2020–2029 Figure 15: Groceries & Staples – Average Order Value (US$), 2020–2029 Figure 16: Groceries & Staples – Order Frequency (Orders per Year), 2020–2029 Figure 17: Fruits & Vegetables – Gross Merchandise Value (US$ Million), 2020–2029 Figure 18: Fruits & Vegetables – Gross Merchandise Volume (Millions), 2020–2029 Figure 19: Fruits & Vegetables – Average Order Value (US$), 2020–2029 Figure 20: Fruits & Vegetables – Order Frequency (Orders per Year), 2020–2029 Figure 21: Snacks & Beverages – Gross Merchandise Value (US$ Million), 2020–2029 Figure 22: Snacks & Beverages – Gross Merchandise Volume (Millions), 2020–2029 Figure 23: Snacks & Beverages – Average Order Value (US$), 2020–2029 Figure 24: Snacks & Beverages – Order Frequency (Orders per Year), 2020–2029 Figure 25: Personal Care & Hygiene – Gross Merchandise Value (US$ Million), 2020–2029 Figure 26: Personal Care & Hygiene – Gross Merchandise Volume (Millions), 2020–2029 Figure 27: Personal Care & Hygiene – Average Order Value (US$), 2020–2029 Figure 28: Personal Care & Hygiene – Order Frequency (Orders per Year), 2020–2029 Figure 29: Pharmaceuticals & Health Products – Gross Merchandise Value (US$ Million), 2020–2029 Figure 30: Pharmaceuticals & Health Products – Gross Merchandise Volume (Millions), 2020–2029 Figure 31: Pharmaceuticals & Health Products – Average Order Value (US$), 2020–2029 Figure 32: Pharmaceuticals & Health Products – Order Frequency (Orders per Year), 2020–2029 Figure 33: Home Décor – Gross Merchandise Value (US$ Million), 2020–2029 Figure 34: Home Décor – Gross Merchandise Volume (Millions), 2020–2029 Figure 35: Home Décor – Average Order Value (US$), 2020–2029 Figure 36: Home Décor – Order Frequency (Orders per Year), 2020–2029 Figure 37: Clothing & Accessories – Gross Merchandise Value (US$ Million), 2020–2029 Figure 38: Clothing & Accessories – Gross Merchandise Volume (Millions), 2020–2029 Figure 39: Clothing & Accessories – Average Order Value (US$), 2020–2029 Figure 40: Clothing & Accessories – Order Frequency (Orders per Year), 2020–2029 Figure 41: Electronics – Gross Merchandise Value (US$ Million), 2020–2029 Figure 42: Electronics – Gross Merchandise Volume (Millions), 2020–2029 Figure 43: Electronics – Average Order Value (US$), 2020–2029 Figure 44: Electronics – Order Frequency (Orders per Year), 2020–2029 Figure 45: Other Product Category – Gross Merchandise Value (US$ Million), 2020–2029 Figure 46: Other Product Category – Gross Merchandise Volume (Millions), 2020–2029 Figure 47: Other Product Category – Average Order Value (US$), 2020–2029 Figure 48: Other Product Category – Order Frequency (Orders per Year), 2020–2029 Figure 49: South Korea Quick Commerce Segment Share by Payment Method, 2024 Figure 50: Instant Bank Transfer – Gross Merchandise Value (US$ Million), 2020–2029 Figure 51: Instant Bank Transfer – Gross Merchandise Volume (Millions), 2020–2029 Figure 52: Instant Bank Transfer – Average Order Value (US$), 2020–2029 Figure 53: Wallets & Digital Payments – Gross Merchandise Value (US$ Million), 2020–2029 Figure 54: Wallets & Digital Payments – Gross Merchandise Volume (Millions), 2020–2029 Figure 55: Wallets & Digital Payments – Average Order Value (US$), 2020–2029 Figure 56: Credit & Debit Cards – Gross Merchandise Value (US$ Million), 2020–2029 Figure 57: Credit & Debit Cards – Gross Merchandise Volume (Millions), 2020–2029 Figure 58: Credit & Debit Cards – Average Order Value (US$), 2020–2029 Figure 59: Cash on Delivery – Gross Merchandise Value (US$ Million), 2020–2029 Figure 60: Cash on Delivery – Gross Merchandise Volume (Millions), 2020–2029 Figure 61: Cash on Delivery – Average Order Value (US$), 2020–2029 Figure 62: South Korea Quick Commerce Segment Share by Age Group, 2024 Figure 63: Gen Z (15–25) Age Group – Gross Merchandise Value (US$ Million), 2020–2029 Figure 64: Gen Z (15–25) Age Group – Gross Merchandise Volume (Millions), 2020–2029 Figure 65: Gen Z (15–25) Age Group – Average Order Value (US$), 2020–2029 Figure 66: Millennials (26–39) Age Group – Gross Merchandise Value (US$ Million), 2020–2029 Figure 67: Millennials (26–39) Age Group – Gross Merchandise Volume (Millions), 2020–2029 Figure 68: Millennials (26–39) Age Group – Average Order Value (US$), 2020–2029 Figure 69: Gen X (40–55) Age Group – Gross Merchandise Value (US$ Million), 2020–2029 Figure 70: Gen X (40–55) Age Group – Gross Merchandise Volume (Millions), 2020–2029 Figure 71: Gen X (40–55) Age Group – Average Order Value (US$), 2020–2029 Figure 72: Baby Boomers (Above 55+) Age Group – Gross Merchandise Value (US$ Million), 2020–2029 Figure 73: Baby Boomers (Above 55+) Age Group – Gross Merchandise Volume (Millions), 2020–2029 Figure 74: Baby Boomers (Above 55+) Age Group – Average Order Value (US$), 2020–2029 Figure 75: South Korea Quick Commerce Segment Share by Location, 2024 Figure 76: Tier 1 Cities – Gross Merchandise Value (US$ Million), 2020–2029 Figure 77: Tier 1 Cities – Gross Merchandise Volume (Millions), 2020–2029 Figure 78: Tier 1 Cities – Average Order Value (US$), 2020–2029 Figure 79: Tier 1 Cities – Order Frequency (Orders per Year), 2020–2029 Figure 80: Tier 2 Cities – Gross Merchandise Value (US$ Million), 2020–2029 Figure 81: Tier 2 Cities – Gross Merchandise Volume (Millions), 2020–2029 Figure 82: Tier 2 Cities – Average Order Value (US$), 2020–2029 Figure 83: Tier 2 Cities – Order Frequency (Orders per Year), 2020–2029 Figure 84: Tier 3 Cities – Gross Merchandise Value (US$ Million), 2020–2029 Figure 85: Tier 3 Cities – Gross Merchandise Volume (Millions), 2020–2029 Figure 86: Tier 3 Cities – Average Order Value (US$), 2020–2029 Figure 87: Tier 3 Cities – Order Frequency (Orders per Year), 2020–2029 Figure 88: South Korea Quick Commerce Segment Share by Business Model, 2024 Figure 89: Inventory Model – Gross Merchandise Value (US$ Million), 2020–2029 Figure 90: Inventory Model – Gross Merchandise Volume (Millions), 2020–2029 Figure 91: Inventory Model – Average Order Value (US$), 2020–2029 Figure 92: Hyperlocal Model – Gross Merchandise Value (US$ Million), 2020–2029 Figure 93: Hyperlocal Model – Gross Merchandise Volume (Millions), 2020–2029 Figure 94: Hyperlocal Model – Average Order Value (US$), 2020–2029 Figure 95: Multi-vendor Platform Model – Gross Merchandise Value (US$ Million), 2020–2029 Figure 96: Multi-vendor Platform Model – Gross Merchandise Volume (Millions), 2020–2029 Figure 97: Multi-vendor Platform Model – Average Order Value (US$), 2020–2029 Figure 98: Other Business Models – Gross Merchandise Value (US$ Million), 2020–2029 Figure 99: Other Business Models – Gross Merchandise Volume (Millions), 2020–2029 Figure 100: Other Business Models – Average Order Value (US$), 2020–2029 Figure 101: South Korea Quick Commerce Segment Share by Delivery Time, 2024 Figure 102: Delivery Time in 30 Minutes – Gross Merchandise Value (US$ Million), 2020–2029 Figure 103: Delivery Time in 30 Minutes – Gross Merchandise Volume (Millions), 2020–2029 Figure 104: Delivery Time in 30 Minutes – Average Order Value (US$), 2020–2029 Figure 105: Delivery Time in 30 Minutes – Order Frequency (Orders per Year), 2020–2029 Figure 106: Delivery Time 30–60 Minutes – Gross Merchandise Value (US$ Million), 2020–2029 Figure 107: Delivery Time 30–60 Minutes – Gross Merchandise Volume (Millions), 2020–2029 Figure 108: Delivery Time 30–60 Minutes – Average Order Value (US$), 2020–2029 Figure 109: Delivery Time 30–60 Minutes – Order Frequency (Orders per Year), 2020–2029 Figure 110: Delivery Time in 3 Hours – Gross Merchandise Value (US$ Million), 2020–2029 Figure 111: Delivery Time in 3 Hours – Gross Merchandise Volume (Millions), 2020–2029 Figure 112: Delivery Time in 3 Hours – Average Order Value (US$), 2020–2029 Figure 113: Delivery Time in 3 Hours – Order Frequency (Orders per Year), 2020–2029 Figure 114: South Korea Quick Commerce – Average Subscription Uptake, 2024 Figure 115: South Korea Quick Commerce – Average Subscription Uptake by Age Group, 2024 Figure 116: South Korea Quick Commerce – Average Subscription Uptake by Location, 2024 Figure 117: South Korea Quick Commerce – Average Delivery Time, 2024
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