Sustainable port development: the role of Chinese seaports in the 21st century Maritime Silk Road

Wang, Chuanxu; Haralambides, Hercules; Zhang, Le

doi:10.1504/ijstl.2021.112924

Cited by 20 publications

(13 citation statements)

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“…The majority of indicators is concentrated in the environmental dimension (40%). Within this dimension, most of the indicators relate to the measurement and assessment of air quality (17), waste management (13), sediments (12), and soil (11) quality in ports. This is a clear indication that measurement of environmental effects is considered as a focus area, outlining ways for ports to address negative environmental externalities and improve their environmental performance.…”

Section: Slr Results-key Quantitative Datamentioning

confidence: 99%

“…Thus, within the sustainability framework comprised by the economic, environmental, and social dimensions, often referred to as the triple bottom line of sustainability [11], ports aim to enhance efficiency and performance and, hence, their competitiveness and economic impact to the wider economy. At the same time, ports are adopting a more active social approach to local communities and a more robust environmental management, abiding to regulations [12,13]. Lu et al [14] argued that there is almost no unequivocal measure or criteria for either promoting or assessing sustainable development in ports while considering the triple bottom line dimensions; notwithstanding, a decade later, a novel and growing body of academic literature on the subject has started to emerge.…”

Section: Introductionmentioning

confidence: 99%

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Promoting Sustainability through Assessment and Measurement of Port Externalities: A Systematic Literature Review and Future Research Paths

Stylıadıs

Angelopoulos

Leonardou³

et al. 2022

Sustainability

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In an attempt to mitigate and balance economic, environmental, and societal externalities that ports exert, port sustainability is becoming increasingly important as a key priority. This work embarks on an effort to explore the boundaries, provide a holistic view, and establish a knowledge map of contemporary research in the field of port externalities and impacts, by conducting a systematic literature review (SLR) by carrying out a three-stage procedure (planning, execution, and reporting), enhancing objectivity, while limiting errors and bias. The literature under study pertains to research domains focusing on: (a) identifying port externalities and impacts, (b) utilizing metrics and indicators to measure and quantify the positive or negative impact of port externalities, and (c) promoting an inclusive framework for sustainable port development. Our results include, among others, the classification of methodologies and particularly, of indicators established per type of externality to measure and monitor sustainable port performance, as well as identification of trends and gaps within the contemporary literature. We find considerable room for exploring new concepts and research paths within the domain of port impacts and externalities, both within individual dimensions of sustainability (economic, social, environmental), and on a multidisciplinary level.

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Section: Slr Results-key Quantitative Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Promoting Sustainability through Assessment and Measurement of Port Externalities: A Systematic Literature Review and Future Research Paths

Stylıadıs

Angelopoulos

Leonardou³

et al. 2022

Sustainability

View full text Add to dashboard Cite

show abstract

“…Similarly, the authors of reference [25] investigated those environmental problems in 18 ports of China. Using a diferent machine learning technique, the authors of reference [26] benchmarked 15 seaports in China in terms of wasted water treatment as well as air quality evaluation and energy-saving expenditures. Moreover, the authors of reference [27] evaluated the environmental effciency of the Kaohsiung container port in Taiwan, considering the same problems.…”

Section: Overall Port Areasmentioning

confidence: 99%

“…In this regard, for benchmarking ports in terms of environmental sustainability, hierarchical clustering is used to create dendrograms or cluster trees. For instance, the authors of references [26,30] evaluated and benchmarked several ports in Europe and China considering energy consumption, rate of wastewater treatment, standard-reaching rate of nearshore water, the green coverage rate in developed areas, and expenditure on energy-saving investments per capita. Based on the revealed clusters, they both concluded that the ports in the same cluster with the best performance in terms of technical effciency showed a better eco-efciency performance than other clusters.…”

Section: Unsupervised Learningmentioning

confidence: 99%

“…Tey showed the beneft of PCA as a data preprocessing tool for fnding the relationship between principal components of an equation in polynomial regression models. Moreover, for ranking ports based on several environmental sustainability factors, [26] utilized PCA to identify the independent variables. Tey proposed the rate of treatment of wastewater, the standard-reaching rate of nearshore water, the green coverage rate in developed areas, and expenditure on energy-saving investments per capita as the input variables.…”

Section: Unsupervised Learningmentioning

confidence: 99%

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Machine Learning for Promoting Environmental Sustainability in Ports

Mansoursamaei

Moradi

González-Ramírez

et al. 2023

Journal of Advanced Transportation

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Maritime transportation is one of the essential drivers of the global economy as it enables both lower transportation costs and intermodal operations across multiple forms of transportation. Maritime ports are essential interfaces that support cargo handling between sea and hinterland transportation. Besides, in this area, environmental protection is becoming extremely important. Global warming, air pollution, and greenhouse gas emissions are all having a detrimental influence on the environment and will most likely continue to do so for future generations. Hence, there is a growing need to promote environmental sustainability in maritime-based transportation. The application of machine learning (ML), as one of the main subdomains of artificial intelligence (AI), can be considered a component within the process of digital transformation to advance green activities in maritime port logistics. Thus, this article presents the results of a systematic literature review of the recent literature on machine learning for promoting environmentally sustainable maritime ports. It collects and analyses the articles whose contributions lie in the interplay between three main dimensions, i.e., machine learning, port-related operations, and environmental sustainability. Throughout a review protocol, this research is constituted on the major focuses of impact, problems, and techniques to discern the current state of the art as well as research directions. The research findings indicate that the articles using polynomial regression models are dominant in the literature, and the recurrent neural network (RNN) and long short-term memory (LSTM) are the most recent approaches. Moreover, in terms of environmental sustainability, emissions and energy consumption are the most studied problems. mAccording to the research gaps observed in the review, two broad directions for future research are identified: (i) altering attention on a greater diversity of machine learning approaches for promoting environmental sustainability in ports and (ii) leveraging new outlooks to perform more green practical works on port-related operations.

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Sustainability Assessment of Master Commercial European Ports Through Environmental Prismas

Koskeridi,

Balla

2023

Tourism, Travel, and Hospitality in a Smart and Sustainable World

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Sustainable port development: the role of Chinese seaports in the 21st century Maritime Silk Road

Cited by 20 publications

References 0 publications

Promoting Sustainability through Assessment and Measurement of Port Externalities: A Systematic Literature Review and Future Research Paths

Promoting Sustainability through Assessment and Measurement of Port Externalities: A Systematic Literature Review and Future Research Paths

Machine Learning for Promoting Environmental Sustainability in Ports

Sustainability Assessment of Master Commercial European Ports Through Environmental Prismas

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