Big Data Cooperative Assets for Sustainability: Aligning User Revenue Preferences with Sustainable Goals

In the context of the digital economy, big data cooperative assets serve as a critical pathway for enterprises to achieve sustainable development by enabling both immediate economic returns and long-term environmental and social value creation. How is sustainable development achieved through big data cooperative assets? This study examines how Chinese listed companies from 2000 to 2023 drive value realization across different time dimensions—including immediate economic value and sustainable value—by aligning with user revenue preferences (short-term profit orientation vs. long-term sustainability orientation) to leverage big data cooperative assets. Using patented indicators to measure innovation value and management-oriented indicators to identify types of return preferences, the study found the following: Firms aligned with short-term revenue preferences primarily enhance immediate economic value through operational data linkages, whereas those aligned with long-term sustainability preferences achieve sustained environmental and social value creation through strategic data insight mechanisms. Furthermore, heterogeneity analysis across industries reveals that construction firms tend to prioritize long-term sustainable value via data mechanisms, relatively deemphasizing short-term optimizations. This research not only elucidates the mechanisms through which big data drives sustainable development from a temporal preference perspective but also provides strategic insights for enterprises across different industries to balance short-term revenue and long-term sustainability goals. It holds significant theoretical and practical implications for the transformation toward sustainable business models.

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Publication Details

Journal
Sustainability
Published
2025-09-19
DOI
https://doi.org/10.3390/su17188403
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
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article

Big Data Cooperative Assets for Sustainability: Aligning User Revenue Preferences with Sustainable Goals

Yi Zhang, Patrick S.W. Fong, Xuze Bo
Sustainability
Smart Cities and Technologies
article

Big Data Cooperative Assets for Sustainability: Aligning User Revenue Preferences with Sustainable Goals

Yi Zhang, Patrick S.W. Fong, Xuze Bo
article en

Abstract

In the context of the digital economy, big data cooperative assets serve as a critical pathway for enterprises to achieve sustainable development by enabling both immediate economic returns and long-term environmental and social value creation. How is sustainable development achieved through big data cooperative assets? This study examines how Chinese listed companies from 2000 to 2023 drive value realization across different time dimensions—including immediate economic value and sustainable value—by aligning with user revenue preferences (short-term profit orientation vs. long-term sustainability orientation) to leverage big data cooperative assets. Using patented indicators to measure innovation value and management-oriented indicators to identify types of return preferences, the study found the following: Firms aligned with short-term revenue preferences primarily enhance immediate economic value through operational data linkages, whereas those aligned with long-term sustainability preferences achieve sustained environmental and social value creation through strategic data insight mechanisms. Furthermore, heterogeneity analysis across industries reveals that construction firms tend to prioritize long-term sustainable value via data mechanisms, relatively deemphasizing short-term optimizations. This research not only elucidates the mechanisms through which big data drives sustainable development from a temporal preference perspective but also provides strategic insights for enterprises across different industries to balance short-term revenue and long-term sustainability goals. It holds significant theoretical and practical implications for the transformation toward sustainable business models.

SustainabilityVol. 17(18)
Griffith University (AU), Hong Kong Polytechnic University (HK)
Openalex Percentile: Top 63%
Smart Cities and Technologies
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