This study examines how environmental, social, and governance (ESG) investment criteria are reflected in smart-city infrastructure project selection in Shenzhen, China. It adopts a qualitative secondary-data case-study design based on document analysis. The study does not use interviews, surveys, or direct project-performance measurements; instead, it analyzes publicly available policy documents, procurement/project-selection materials, corporate ESG/CSR reports, and related academic and policy literature published between 2020 and 2025. The coding of the ESG indicators under the environmental, social, governance, and life-cycle performance and the finance/risk dimensions was done through a qualitative approach of document analysis. As the results indicate, the environmental indicators were most commonly represented, in particular, energy efficiency, carbon reduction, green construction, and smart mobility. Social indicators existed in the language of public service and livability, but few standards were regularly expressed as formal requirements. Other indicators of governance, such as cybersecurity, transparency, data sharing and accountability were very relevant to digital infrastructure but were not evenly represented in terms of selection criteria. The work contributes to the coding framework of ESG on a project level, and it demonstrates how secondary-data case analysis can be of help in determining the gap between corporate ESG disclosure and implementation at the asset level.

Yinting Lou. Impact of ESG Investment Criteria on Smart City Infrastructure Project Selection. Academic Journal of Business & Management (2026), Vol. 8, Issue 8: 109-119. https://doi.org/10.25236/AJBM.2026.080813.

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