2018
DOI: 10.1007/s00500-018-3559-1
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Sustainability efficiency evaluation of seaports in China: an uncertain data envelopment analysis approach

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Cited by 26 publications
(9 citation statements)
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“…[91], specialize in identifying, measuring, and/or valuating environmental externalities. We also observe that: (a) the research area of sustainability/environmental raking of ports/port cities is concentrated mostly after 2016 (for example, see [92][93][94]), and (b) research for multidisciplinary composite indicators is even more concentrated between 2017 and 2021 (for example, see [95][96][97]).…”
Section: Tipple Bottom Line Approach: Economic-social-environmentalmentioning
confidence: 86%
“…[91], specialize in identifying, measuring, and/or valuating environmental externalities. We also observe that: (a) the research area of sustainability/environmental raking of ports/port cities is concentrated mostly after 2016 (for example, see [92][93][94]), and (b) research for multidisciplinary composite indicators is even more concentrated between 2017 and 2021 (for example, see [95][96][97]).…”
Section: Tipple Bottom Line Approach: Economic-social-environmentalmentioning
confidence: 86%
“…The efficiency of port sustainability addresses the comparative relationship between the input in terms of port resources and the actual effective outputs (including the economic, environmental, and social output) as a synthesized measure of the operational status and sustainable development potential of the port [36]. Sustainable seaport business contributes to strategic goals of seaports through increased revenue and market share; reduced cost of operations; reduced environmental and financial risk; more efficient use of financial, human, and natural resources; enhanced brand image; enhanced access to capital; increasing employee productivity; easier hiring and retention of best talent; improved relationship with key stakeholders; more efficient approval of regulatory permits, and an enhanced ability to maintain a license to operate and grow [30].…”
Section: Theoretical Frameworkmentioning
confidence: 99%
“…Nevertheless, in many practical issues, such as oil reserves, bridge emphasis, and securities' returns [16,17], the input and output variables of DMUs are often not accurately obtained for technical or economic reasons. Generally, they can only be estimated based on the knowledge and preference of domain experts.…”
Section: Introductionmentioning
confidence: 99%
“…In order to further judge whether the DMU is in a state of increasing returns to scale, decreasing returns to scale, or constant returns to scale, the uncertain DEA models for scale-efficiency evaluation were proposed and improved [21,22]. Afterward, with the application of uncertain DEA in practical problems [16], some other uncertain DEA models were proposed such as the network DEA models [23], which can identify the internal structure of DMUs, and the uncertain random DEA models [24], which contain both random variables and uncertain variables. However, the above uncertain DEA models mainly focused on self evaluation, and can only distinguish the DMUs into efficient and inefficient units, rather than ranking them.…”
Section: Introductionmentioning
confidence: 99%