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2025年产业地产市场分化报告：产业园区承压与数据中心崛起

2025-12-08 17:24:21 来源：北方有色网责任编辑：王欣悦

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在房地产市场整体回调的传导效应下，产业链上的传统产业园区正遭遇租金与入住率的双重挤压，而数据中心作为新兴赛道却呈现逆势增长态势，产业地产领域的分化格局日益凸显。观点指数研究院《卓越指数·2025产业园区暨基础设施投资发展报告》及最新行业动态，清晰勾勒出这一市场图景。

一、传统产业园区：租金空置率“双杀”，调整期压力凸显

传统产业园区的经营指标已连续三年多呈下行趋势，市场调整进入深水区。租金方面，2022年一季度全国产业园区平均租金为138.0元/m²/月，此后进入持续下行通道，截至2025年三季度已降至105元/m²/月，创下三年半以来的新低，累计降幅达24%。这一数据背后，是企业承租能力减弱与市场供应过剩的双重作用，其中传统制造业、低端服务业所属园区受冲击更为明显。

入住率的下滑态势同样严峻。2022年一季度产业园区整体入住率尚维持在90%以上，此后逐年回落，2025年三季度已低至69.5%，首次跌破70%的关键关口。值得注意的是，园区普遍采用的“以价换量”策略效果正逐步减弱，难以扭转招商颓势。观点指数指出，目前全国超18亿平方米园区面积处于空置状态，企业扩张意愿不足、产业定位模糊、同质化竞争加剧(75%以上园区定位趋同)等因素，共同将传统产业园区推向阶段性调整期。

二、数据中心：数字经济驱动，实现逆势增长

与传统产业园区的低迷形成鲜明对比，数据中心市场在同期呈现出强劲的发展韧性，成为产业地产领域的“增长极”。收入端表现尤为突出，数据中心单方收入从2022年一季度的325.1元/m²/月持续上升，2025年三季度仍稳定保持在366元/m²/月以上，较产业园区同期租金高出248%。

这种增长动力源于双重支撑：一方面是数字经济快速发展带来的算力需求爆发式增长，截至2024年底我国算力总规模达280EFLOPS，智能算力占比达32%，云计算、人工智能等新兴产业形成刚性需求;另一方面得益于行业自身的高端化、智能化升级，华为等企业通过预制一体化模块、液冷技术等创新，实现数据中心安全可靠与绿色低碳的双重提升，推动价值持续增长。

核心运营指标同样稳健。签约率方面，数据中心市场虽有小幅波动，但始终维持高位，2022年一季度为95.3%，2025年三季度回升至92.3%，远超同期产业园区69.5%的入住率;计费率从2022年一季度的67.4%稳步提升至2025年三季度的74.5%，整体保持上升通道。资本层面，润泽科技、万国数据等头部企业营收增速均超10%，部分企业净利润增速突破200%，彰显赛道价值。

三、一线城市图景：供求失衡加剧，分化特征显著

北京、上海、广州、深圳四大一线城市作为产业地产核心市场，正面临供求失衡加剧的挑战，同时呈现出差异化调整特征。从供求比来看，四城均处于供过于求状态，上海以2.63的供求比成为压力最大的城市，北京、广州、深圳分别为1.88、1.77、1.45，供需错配问题持续凸显。

租金与空置率的反向变动进一步印证市场压力：四城园区平均租金均出现同比下滑，深圳以4.0%的降幅领先，北京、广州、上海分别下降3.7%、1.4%、2.2%，具体租金水平依次为138.5元/m²/月、68.6元/m²/月、133.8元/m²/月;空置率则同步上升，上海、广州、北京、深圳分别同比上涨1.2%、0.9%、0.5%、0.3%，市场去化压力短期内难以逆转。

四、REITs扩募破局：政策驱动存量资产盘活

在传统产业园区承压的背景下，REITs市场的扩募机制成为存量资产盘活的关键路径。2025年三季度，国内产业园区REITs呈现“运营分化加剧、扩募动能活跃”的特征，在政策与市场的双重推动下释放强劲活力。2025年9月证监会发布的《公开募集基础设施证券投资基金扩募指引》，从制度层面简化流程、取消规模限制，为扩募提供了重要支撑。

政策效应已快速显现，2025年1-10月，全国共有8只产业园区REITs完成或计划扩募，总扩募规模达58.6亿元，较去年同期增长42%。这种“以存量换增量”的模式，不仅为产业园区注入流动性，更通过资金反哺推动项目升级，例如部分REITs将募集资金用于绿色改造，进一步提升资产价值。

总结与展望

当前产业地产市场的分化，本质上是新旧发展动能转换的体现——传统产业园区依赖“空间租赁”的模式已难以为继，而数据中心依托数字经济红利实现价值跃升。对于传统园区而言，需通过明确产业定位、强化产业链协同、融入数字化升级等路径突破困境;数据中心则需持续聚焦安全可靠、弹性敏捷与绿色低碳发展，把握算力需求增长机遇。

REITs扩募机制的完善为整个行业提供了新的金融支撑，随着政策落地与市场成熟，有望推动更多存量资产实现高效运营，为产业地产高质量发展注入持久动力。

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[ SQL ] SELECT * FROM `tb_cate` WHERE `pid` = 13 AND ( `id` < 3871 AND `id` NOT IN (25,3243,3244) ) ORDER BY `sortid` ASC [ RunTime:0.002495s ]
[ SQL ] SELECT * FROM `tb_cate` WHERE `pid` = 14 AND ( `id` < 3871 AND `id` NOT IN (25,3243,3244) ) ORDER BY `sortid` ASC [ RunTime:0.002458s ]
[ SQL ] SELECT * FROM `tb_cate` WHERE `pid` = 19 AND ( `id` < 3871 AND `id` NOT IN (25,3243,3244) ) ORDER BY `sortid` ASC [ RunTime:0.002596s ]
[ SQL ] SELECT * FROM `tb_cate` WHERE `pid` = 15 AND ( `id` < 3871 AND `id` NOT IN (25,3243,3244) ) ORDER BY `sortid` ASC [ RunTime:0.002490s ]
[ SQL ] SELECT * FROM `tb_cate` WHERE `pid` = 16 AND ( `id` < 3871 AND `id` NOT IN (25,3243,3244) ) ORDER BY `sortid` ASC [ RunTime:0.002489s ]
[ SQL ] SELECT * FROM `tb_cate` WHERE `pid` = 17 AND ( `id` < 3871 AND `id` NOT IN (25,3243,3244) ) ORDER BY `sortid` ASC [ RunTime:0.002436s ]
[ SQL ] SELECT * FROM `tb_cate` WHERE `pid` = 3 AND ( `id` < 3871 AND `id` NOT IN (25,3243,3244) ) ORDER BY `sortid` ASC [ RunTime:0.002504s ]
[ SQL ] SELECT * FROM `tb_advert` WHERE `id` = 48 LIMIT 1 [ RunTime:0.000464s ]
[ SQL ] SELECT * FROM `tb_advert` WHERE `id` = 49 LIMIT 1 [ RunTime:0.000402s ]
[ SQL ] SELECT * FROM `tb_advert` WHERE `id` = 50 LIMIT 1 [ RunTime:0.000404s ]
[ SQL ] SELECT * FROM `tb_para` WHERE `id` = 1 LIMIT 1 [ RunTime:0.000533s ]

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