Journal of Intelligent Management
JIM
Journal of Intelligent Management
Edited By: Editorial Office | Online ISSN: 3080-2350 | Print ISSN: 3008-1742
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Latest IssueVolume 2, Issue 1June 2026
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Abstract

Cold chain logistics is essential for supplying fresh food, pharmaceuticals, and other temperature sensitive goods in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), but its heavy reliance on refrigeration and road transport makes it energy intensive and carbon emissions intensive. This study evaluates the low carbon efficiency of cold chain logistics in the GBA and examines the mechanisms through which internal resource inputs and external conditions shape performance. We construct an efficiency assessment framework that treats carbon emissions as an undesirable output and applies a three stage Data Envelopment Analysis (DEA): (i) initial efficiency measurement; (ii) adjustment for environmental factors and statistical noise using economic development, government support, and market environment variables; and (iii) a re estimation of managerial (intrinsic) efficiency. Building on Resource Based Theory, Stakeholder Theory, and Ecological Modernization Theory, we further propose a mechanism model linking capital, labor, technical investment, and energy inputs to low carbon efficiency, with generalized total factor productivity and energy structure as mediators and external conditions as moderators. Preliminary evidence highlights the importance of technological upgrading, route and facility optimization, and policy support in improving both economic output and emissions performance. The findings provide actionable implications for targeting green technology adoption, strengthening regulatory incentives, and addressing cold storage and refrigerated transport capacity gaps to support high quality, low carbon logistics development in the GBA.

Keywords

Cold chain logistics, DEA, Efficiency, Greater Bay Area, Low-carbon

Authors & Affiliations

Citation

Xiao, L., Wang, G., Chen, W., & Shaharudina, M. S. (2026). Assessment and Mechanism Analysis of Low Carbon Efficiency in Cold Chain Logistics in the Guangdong-Hong Kong-Macao Greater Bay Area. Journal of Intelligent Management, 2(1), 10-24

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1.Introduction

The significance of cold chain logistics has grown dramatically in recent years, particularly in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), an economic center that is expanding quickly. A vital part of the supply chain for sectors including chemicals, food, and pharmaceuticals is cold chain logistics, which deals with the movement and storage of goods that are sensitive to temperature. Sustainability is severely hampered by this industry's high energy consumption and the huge rise in carbon emissions from transportation and refrigeration. Accordingly, reaching regional and international environmental targets now depends on increasing the cold chain logistics' low-carbon efficiency (Liu et al., 2023; He et al., 2023). The objective of this research is to assess and examine the GBA's cold chain logistics' low-carbon efficiency while taking environmental and financial performance into account. In particular, this study examines the variables that affect cold chain logistics companies' efficiency by taking into account both desired and undesirable outcomes, such as carbon emissions and freight volume and economic growth. In order to accomplish this, the study uses a Three-Stage Data Envelopment Analysis (DEA) as its main instrument for assessing cold chain logistics companies' performance. This method enables a thorough evaluation that takes into consideration external influences on efficiency as well as environmental aspects (Ma et al., 2023). The current inefficiencies in the cold chain logistics industry and their significant contribution to regional carbon emissions are highlighted in the research's problem statement. The particular problem of lowering emissions while preserving economic performance has not yet been entirely resolved, despite considerable attempts to increase logistical efficiency (Xu et al., 2024). Improving the sustainability of the GBA's logistics operations is essential for local stakeholders as well as the region's global competitiveness, given its strategic location as a key economic center (Zhang et al., 2024). Three major theories form the theoretical basis of this research: Ecological Modernization Theory (EMT), Stakeholder Theory, and Resource-Based Theory (RBT). RBT offers information on how logistics companies use internal resources, like labor and capital, to cut emissions and increase efficiency (Barney, 1991). Stakeholder theory emphasizes how different stakeholders, such as consumers, governments, and businesspeople, may support low-carbon activities (Freeman, 1984). EMT highlights how regulatory changes and technology developments propel sustainability in logistics (Mol & Spaargaren, 2000). When combined, these ideas offer a thorough understanding of how cold chain logistics might improve low-carbon efficiency while striking a balance between environmental and economic effects. According to Yang et al. (2023), the research objectives are well-defined and center on evaluating the effectiveness of cold chain logistics, investigating the fundamental mechanisms that impact performance, and identifying variables like market conditions, economic development, and government support that moderate efficiency outcomes. The research questions that direct the study are also presented in this chapter, such as: How can cold chain logistics' low-carbon efficiency be quantified? Which are the main determinants of efficiency? In what ways are these interactions moderated by outside factors?

1.1 The Role and Environmental Challenges of Cold Chain Logistics in the Greater Bay Area

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) encompasses nine mainland cities alongside Hong Kong and Macao. As one of the world’s most dynamic urban clusters, its growing demand for fresh food, pharmaceuticals, and other temperature-sensitive goods has made cold chain logistics increasingly vital. However, the energy-intensive nature of cold chain logistics, heavily reliant on refrigeration and transportation infrastructure, poses significant environmental challenges (Zhang et al., 2020). In 2023, China’s cold chain logistics demand reached 350 million tons, with a 6.1% year-on-year growth. Refrigerated trucks exceeded 430,000 units (a 12.8% increase), and refrigerated storage volume reached 228 million cubic meters, with high-standard cold storage accounting for 62% (Guangdong Statistical Yearbook, 2024). While cold chain logistics has spurred economic growth, balancing economic performance with environmental sustainability remains a critical challenge for the GBA (Liu et al., 2023). Cold chain logistics faces multiple environmental challenges due to its reliance on energy-intensive technologies. Key issues include: High energy consumption and carbon emissions: refrigeration systems and transportation are major sources of energy use and greenhouse gas (GHG) emissions. Globally, the logistics sector accounts for approximately 24% of total CO2 emissions, with cold chains contributing around 5% due to their reliance on fossil fuels (IEA, 2023). In the GBA, carbon emissions from refrigeration and transportation equipment have grown at an average annual rate of 3.5% (Guangdong Statistical Yearbook, 2024). Refrigerant Use: Common refrigerants, such as hydrofluorocarbons (HFCs), have high global warming potential and significantly contribute to climate change if improperly managed (Hu et al., 2022). Studies indicate that HFC emissions from refrigerant leakage account for approximately 15% of total cold chain emissions (Wang et al., 2021). Waste Generation: Poorly managed cold chains lead to food spoilage, wasting resources, and generating methane, a potent GHG. Additionally, outdated refrigeration equipment contributes to electronic waste (Boschiero et al., 2019). Transportation Inefficiencies: Inefficient logistics routes and aging refrigerated vehicles increase fuel consumption and emissions. In 2023, transportation energy consumption accounted for nearly 70% of the total energy used in the GBA’s cold chain logistics (Chen et al., 2023). In the GBA, these challenges are further exacerbated by regional climate factors such as high ambient temperatures, which increase refrigeration energy demands. Addressing these issues requires adopting renewable energy technologies, improving efficiency through technological innovation, and strengthening regulatory frameworks (Yan et al., 2022). As the GBA continues to develop as a global logistics hub, transitioning to sustainable cold chain practices will play a pivotal role in achieving regional economic and environmental goals.

1.2 Rising Trends in Global Energy Consumption and CO2 Emissions

With an expected 37.9 billion tons of CO2 emissions in 2024—a 1.3% increase from the year before—global energy-related CO2 emissions are still on the rise (IEA, 2023a). Fossil fuel dependence is still a major element, particularly in developing nations, even though this growth rate is somewhat slower than the 3% world GDP increase (IEA, 2023b). Fossil fuels continue to be responsible for more than 80% of CO2 emissions, which have increased by 1.9% annually on average between 2000 and 2024 (IEA, 2023b). Significant regional disparities exist: established economies such as the US and the EU have cut emissions by 2.4% and 4.2%, respectively, while Asia—particularly China and India—has witnessed an increase in emissions, with China alone accounting for 35% of global CO2 emissions in 2024 (IEA, 2023c).

Figure 1 Global Energy-Related CO2 Emissions and Annual Changes (2000-2024)

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Changlong Li, Y.,Z., B., H.(2022)"Identification of Typical Ecosystem Types By Integrating Active and Passive Time Series Data of The Guangdong-Hong Kong-Macao Greater Bay Area, China",International Journal of Environmental Research and Public Health.

Dian Prama Irfani, D., M., (2019)"Design of A Logistics Performance Management System Based on The System Dynamics Model",Measuring Business Excellence.

Dian Prama Irfani,D., M.(2019) "Integrating Performance Measurement, System Dynamics, and Problem-solving Methods",International Journal of Productivity and Performance.

Galimkair Mutanov, S., A.(2020)"Application of System-Dynamic Modeling to Improve Distribution Logistics Processes in The Supply Chain", Communications.

Heping Xie, Y.,Y., Q.,Z.,J.(2021) "A Case Study of Development and Utilization of Urban

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Haining Huang, X., Y.(2020)"A Probe Into The Cultivation Model of The Undergraduate

Business English Major in Universities Under The Background of Guangdong-Hong Kong-Macao Greater Bay Area", 2020 3rd International Conference on e-Education.

Jieyu Lai,X.(2020)"Design of Intelligent Logistics Information Platform Based on Block Chain Technology:Research on Urban Integration Development of Guangdong-Hong Kong -Macao Greater Bay Area",2020 International Conference on Computer Network.

Jianjun Dong,Y.,B., R.,Z.(2019) "The Impact of Underground Logistics System on Urban Sustainable Development: A System Dynamics App16roach",Sustainability.

KERRY LIU.(2020)"China's Guangdong-Hong Kong-Macao Greater Bay Area: A Primer",The Copenhagen Journal of Asian Studies.

Pragya Arya,M.,M.(2019)"Modelling Environmental and Economic Sustainability of Logistics", Asia-Pacific Journal of Business Administration.

Xiaoyan Wang,L.,S.(2021)"Integrated Model Framework for The Evaluation and Prediction of The Water Environmental Carrying Capacity in The Guangdong-Hong Kong-Macao Greater Bay Area", Ecological Indicators

Xu Tan,S.,Y.,Z.,Y.,J.,H.(2022)"Impacts of Climate Change and Land Use/Cover Change on Regional Hydrological Processes:Case of The Guangdong-Hong Kong-Macao Greater Bay Area", Frontiers in Environmental Science .

Xuesong Guo, N.(2019)"Engaging Stakeholders for Collaborative Decision Making in Humanitarian Logistics Using System Dynamics",Journal of Homeland Security and Emergency Management.

Y.H. Pan,T., M. ,G.(2020)"Digital Twin Based Real-time Production Logistics Synchronization System in A Multi-level Computing Architecture", Journal of ManufacturingSystems.

Ya Zhou,Y.,G., D.(2018) "Emissions and Low-carbon Development in Guangdong-Hong Kong-Macao Greater Bay Area Cities and Their Surroundings",Applied Energy.