Commuting efficiency, a measure of how effectively workers utilise their time and resources for journeys to work, is generally assessed through an excess commuting framework. This approach quantifies the disparity between the theoretical minimum and actual commutes. However, conventional methods often make oversimplified assumptions of industry homogeneity and temporal invariance, neglecting the intricate dynamics of commuting efficiency. To bridge the gap, this study scrutinises cross-year commuting efficiency across 13 industry sectors by developing a disaggregated excess-commuting framework. An analysis of substantial data encompassing 11 million commuters in Shenzhen over the period from 2017 to 2021 reveals that: (1) secondary sectors and industries requiring relatively lower skills demonstrate higher commuting efficiency compared to their tertiary, high-skilled counterparts; (2) increases in industry-related minimum and random commuting significantly contribute to the growth of commuting distances, whereas local self-contained employment helps mitigate this effect; and (3) addressing jobs-housing imbalance in absolute ratio may not necessarily reduce commuting distances for all industry sectors. Urban policy development should be specifically tailored to the unique evolution of commuting efficiency performance within individual industries, rather than adopting a generic one-size-fits-all approach.

中文翻译：

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揭示通勤效率的异质性和动态：基于分类的过度通勤框架，对不断变化的效率差距进行行业层面的洞察

通勤效率是衡量员工如何有效利用上班时间和资源的指标，通常通过过度通勤框架进行评估。这种方法量化了理论最低通勤时间与实际通勤时间之间的差异。然而，传统方法往往对行业同质性和时间不变性做出过于简单的假设，忽略了通勤效率的复杂动态。为了弥合这一差距，本研究通过开发分类的过度通勤框架来仔细审查 13 个行业部门的跨年度通勤效率。通过对2017年至2021年深圳1100万通勤者的大量数据分析发现：（1）与第三产业和高技能行业相比，第二产业和技能要求相对较低的行业表现出更高的通勤效率；（2）与行业相关的最低限度和随机通勤的增加显着促进了通勤距离的增长，而当地自给自足的就业有助于减轻这种影响；(3)解决职住绝对比例失衡问题并不一定会减少所有行业的通勤距离。城市政策的制定应针对各个行业内通勤效率绩效的独特演变进行专门定制，而不是采用通用的一刀切的方法。