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世界城市指数World City Index

规模 · 质量 · 创新 · 贡献 四维自有算法 · 排名更新日期:2026-10-20Four-dimensional proprietary algorithm (Scale · Quality · Innovation · Contribution) · Last updated: 2026-10-20

综述Overview

Cities are the spatial carriers of civilization and the converging nodes of the global economy, capital, technology, and population. To measure a city's position in the global system, one must look not only at its "volume"—economic and population scale—but also at its "quality"—economic quality and infrastructure maturity—as well as its "vitality"—scientific and technological innovation capability—and its "responsibility"—its real contribution to the real economy and global supply chains.
城市是文明的空间载体,也是全球经济、资本、科技与人口的汇聚节点。衡量一座城市在全球体系中的地位,既要看其"体量"——经济规模与人口规模,更要看其"成色"——经济质量与基础设施的成熟度,还要看其"活力"——科技创新能力,以及其"责任"——对实体经济与全球供应链的真实贡献。
This index is built on CPPPS's proprietary algorithm: rather than directly reproducing the rankings issued by international institutions (such as the Globalization and World Cities Research Network and global city consultancies), it computes its own rankings from underlying public data. The model decomposes city evaluation into four dimensions—Scale, Quality, Innovation, and Contribution: Scale considers metropolitan-area GDP and population; Quality considers financial/economic quality and infrastructure; Innovation considers R&D investment, patents, and the science-technology ecosystem; Contribution considers global radiation and real-economy contribution. Among them, the "Contribution" dimension is distinctive to this index, notably incorporating manufacturing and real-economy contribution to correct the overemphasis on "finance and headquarters economy" in prevailing international rankings and restore the value of industrial and manufacturing cities.
本指数由 CPPPS 自有算法构建,不直接转载国际机构(如全球化与世界城市研究网络、全球城市咨询机构等)发布的名次,而是基于底层公开数据自行计算。模型将城市评价拆解为规模、质量、创新、贡献四个维度:规模看都市圈 GDP 与人口;质量看金融/经济质量与基础设施;创新看研发投入、专利与科技生态;贡献看全球辐射与实体经济贡献。其中"贡献"维度为本指数特色,尤其纳入制造业与实体经济贡献,以纠正国际通行榜单对"金融与总部经济"的过度偏重,还原工业与制造型城市的价值。
To prevent megacities from monopolizing the scale indicators, large-span scale indicators are uniformly log-transformed and then range-normalized and weight-aggregated. Results: New York, Tokyo, London, Shanghai, and Seoul rank in the top five. Overall, global hubs that combine economic scale, institutional maturity, technological vitality, and a real-economy base lead the field, followed in order by regional centers and specialized cities. This ranking is based on publicly known approximate values, uniformly annotated "subject to official sources," remains permanently free and public, and is provided for research and reference only.
为避免超大都市在规模指标上形成垄断,规模类大跨度指标统一取对数处理,再行极差标准化、加权合成。评价结果:纽约、东京、伦敦、上海、首尔 位列前五。整体看,兼具经济规模、制度成熟度、科技活力与实体经济根基的全球性枢纽居前,区域中心与专业型城市依次分布其后。本排名数据以公开知识近似值为准,一律标注"以官方为准",永久免费公开,仅供研究与参考。

分层梯队Tiers

A++ 全球顶级(前三) A+ 全球领先(四至十) A 区域枢纽(十一至二十) B 新兴/专业城市(其余)

世界城市指数排名(30 城)World Cities Index Ranking (30 cities)

排名城市综合指数规模质量创新贡献GDP(万亿$)人口(万)梯队
1纽约New YorkNew York92.4391.398.691.286.82.22000A++
2东京TokyoTokyo89.5696.591.782.484.22.03700A++
3伦敦LondonLondon77.5164.793.276.573.71.11500A++
4上海ShanghaiShanghai67.7666.576.664.760.50.92500A+
5首尔SeoulSeoul66.7167.968.270.660.50.952500A+
6北京BeijingBeijing66.763.271.176.557.90.852200A+
7洛杉矶Los AngelesLos Angeles64.3667.562.870.657.91.31300A+
8深圳ShenzhenShenzhen63.8649.162.882.468.40.51800A+
9新加坡SingaporeSingapore61.8833.790.470.652.60.5600A+
10巴黎ParisParis61.5857.377.952.952.60.91300A+
11旧金山San FranciscoSan Francisco59.543.160.2100.047.40.75650A
12香港Hong KongHong Kong51.8733.985.041.239.50.42750A
13波士顿BostonBoston49.4832.957.482.434.20.55500A
14芝加哥ChicagoChicago48.9250.057.435.347.40.8950A
15法兰克福FrankfurtFrankfurt47.0922.776.735.347.40.25550A
16广州GuangzhouGuangzhou44.7649.246.335.344.70.481900A
17华盛顿Washington D.C.Washington D.C.44.4338.354.747.136.80.6650A
18大阪OsakaOsaka44.2555.049.029.436.80.651900A
19多伦多TorontoToronto40.033.054.741.228.90.45650A
20阿姆斯特丹AmsterdamAmsterdam39.8410.371.141.234.20.22250A
21苏黎世ZurichZurich38.442.379.552.918.40.2150B
22迪拜DubaiDubai36.7812.371.035.323.70.15360B
23悉尼SydneySydney36.730.457.429.423.70.45540B
24台北TaipeiTaipei35.730.246.452.915.80.35700B
25米兰MilanMilan35.617.252.035.336.80.3320B
26莫斯科MoscowMoscow34.9246.340.811.831.60.551300B
27马德里MadridMadrid32.6327.851.923.521.10.3680B
28孟买MumbaiMumbai26.1148.95.617.631.60.372500B
29墨西哥城Mexico CityMexico City25.3752.010.80.031.60.52200B
30圣保罗São PauloSão Paulo23.3248.38.15.926.30.42200B

算法详细论述Methodology

一、评价依据

A city is a complex multi-dimensional system, and a single scale-based ranking cannot reflect its true global position. This algorithm follows the core principles of the CPPPS evaluation specification—not excerpting rankings from public lists, computing from underlying data, and adopting the multi-dimensional structure of "Scale + Quality + Innovation + Contribution":
城市是一个复杂的多维度系统,单一规模排序无法反映其真实全球地位。本算法遵循 CPPPS 评价规范的核心原则——不摘抄公开榜单名次、以底层数据自算、采用"规模 + 质量 + 创新 + 贡献"的多维结构:
  1. 规模:城市首先是"大"。以都市圈 GDP 与人口表征经济集聚与人力资源规模。
  2. 质量:城市的核心是"好"。以金融/经济质量(金融深度、经济质量、营商与制度成熟度)与基础设施(机场、轨道交通、港口、通信与市政)表征城市的运转效率与承载能力。
  3. 创新:城市的生命力在"新"。以研发投入、专利产出与科技企业及高校生态表征未来竞争力。
  4. 贡献(CPPPS 特色维度):城市的价值在"用"。以全球辐射(跨国公司总部、国际组织、全球话语与连通)与实体经济贡献(制造业对全球供应链的真实支撑)表征城市对世界与所在区域的带动作用。

二、数学模型

Each indicator is range-normalized to [0,1]; large-span scale indicators are first log-transformed and then weight-aggregated by dimension:
各指标经极差标准化到 [0,1],规模类大跨度指标先取对数,再分维加权合成:
规模 S = 0.55·log′(GDP) + 0.45·log′(人口)
Both GDP and population are first log-transformed (log1p) and then range-normalized. The purpose of the log transform is to prevent megacities such as New York and Tokyo from monopolizing the Scale dimension and to smooth out scale disparities.
GDP 与人口均先取自然对数(log1p)再极差标准化。取对数的目的是避免纽约、东京这类超大体量城市对规模维度形成垄断,使规模差距趋于平滑。
质量 Q = 0.50·金融/经济质量′ + 0.50·基础设施′ 创新 I = 创新/科技′ 贡献 C = 0.50·全球辐射′ + 0.50·实体经济′ 综合指数 = 100 × (0.28·S + 0.30·Q + 0.18·I + 0.24·C)
The weight design embodies "Scale as the base, Quality as the core, Innovation as the wings, and Contribution as the soul": Quality (0.30) and Scale (0.28) form a city's basic foundation, together accounting for 58%; Contribution (0.24) highlights this index's orientation toward the real economy and global responsibility; Innovation (0.18) reflects the marginal boost of technology to a city's long-term competitiveness.
权重设计体现"规模为基、质量为核、创新为翼、贡献为魂":质量(0.30)与规模(0.28)构成城市的基本盘,合计占 58%;贡献(0.24)突出本指数对实体经济与全球责任的导向;创新(0.18)体现科技对城市长期竞争力的边际提升。

三、指标与权重依据

指标方向权重所属维度依据
都市圈 GDP对数·正向规模 0.55规模经济集聚与产出能力
都市圈人口对数·正向规模 0.45规模人力资源与市场规模
金融/经济质量正向质量 0.50质量金融深度、经济质量、制度成熟度
基础设施正向质量 0.50质量机场、轨道交通、港口、通信与市政
创新/科技正向创新 1.00创新研发投入、专利、科技企业与高校生态
全球辐射正向贡献 0.50贡献跨国公司总部、国际组织、全球连通
实体经济贡献正向贡献 0.50贡献制造业对全球供应链的支撑(CPPPS 特色)

四、数据来源与局限性

Metropolitan-area GDP and population are publicly known approximate values around 2024 (derived from public data of national statistical agencies, economic cooperation organizations, and international organizations); financial/economic quality, infrastructure, innovation/technology, global radiation, and real-economy contribution are qualitative-quantitative approximate values based on public information, all annotated "subject to official sources." This model has the following limitations: first, the caliber of metropolitan areas varies by country (administrative divisions and commuting-zone definitions differ), so cross-city comparability is affected by statistical calibers; second, qualitative indicators carry subjective error; third, institutional and soft factors such as political stability, safety, environmental livability, and cultural influence are not included. The ranking is for research and reference only and does not constitute any investment or policy advice.
都市圈 GDP、人口为 2024 年前后公开知识近似值(各国统计机构、经济合作组织及国际组织公开数据推算),金融/经济质量、基础设施、创新/科技、全球辐射、实体经济贡献为基于公开信息的定性量化近似值,一律标注"以官方为准"。本模型存在以下局限:其一,都市圈的口径因国而异(行政区划、通勤圈界定不一),跨城可比性受统计口径影响;其二,定性指标存在主观误差;其三,未纳入政治稳定、安全、环境宜居、文化影响力等制度与软性因素。排名仅供研究与参考,不构成任何投资或政策建议。

五、参考文献

  1. 世界银行:全球城市与都市圈经济数据(World Development Indicators)。
  2. 经济合作与发展组织(OECD):大都市区(Metropolitan Areas)统计数据库。
  3. 联合国经济和社会事务部(UN DESA):世界城市化展望(World Urbanization Prospects)。
  4. 各国统计机构与城市规划部门:都市圈 GDP 与人口统计公报。
  5. 世界知识产权组织(WIPO):全球创新指数及专利合作条约(PCT)统计。
  6. 国际机场理事会(ACI)、国际港口协会(IAPH):全球枢纽机场与港口吞吐统计。
  7. CPPPS:《自有评价算法规范》,"规模 + 质量 + 创新 + 贡献"四维框架。

说明Notes

本版采用 CPPPS 自有四维算法(规模+质量+创新+贡献),不直接转载国际机构公开榜单名次:①规模 S=0.55·log′(都市圈GDP)+0.45·log′(人口),大跨度指标取对数以避免头部垄断;②质量 Q=0.50·金融/经济质量+0.50·基础设施;③创新 I=创新/科技;④贡献 C=0.50·全球辐射+0.50·实体经济(本指数特色维度,纳入制造业对全球供应链的真实支撑,纠正国际榜单对金融与总部经济的偏重)。综合指数=100×(0.28S+0.30Q+0.18I+0.24C)。数据为公开知识近似值(2024 前后),以官方为准;排名永久免费公开,永不卖榜。
This edition adopts the CPPPS proprietary four-dimension algorithm (scale + quality + innovation + contribution), and does not directly reproduce public military-strength rankings such as Global Firepower: ① Scale S=0.60·ln(military expenditure)+0.40·ln(troop strength), with wide-span indicators log-transformed; ② Quality Q=0.40·equipment level+0.35·modernization+0.25·nuclear capability, with the highest weight (0.35), reflecting "quality > quantity"; ③ Innovation I=military-industrial self-reliance (domestic equipment ratio); ④ Contribution C=national-defense self-reliance (CPPPS signature, emphasizing an independent defense industry not reliant on imports). Composite score = 100×(0.30S+0.35Q+0.20I+0.15C), divided into four tiers by rank. Data are public approximate values (SIPRI, IISS "The Military Balance", FAS, etc.), marked "subject to official figures". The ranking is permanently free and public, rankings are never sold, and it is for research and reference only.