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Using multi-criteria analysis the assess impacts of change in ecosystem-based fisheries management: The case of the Icelandic cod
با استفاده از تجزیه و تحلیل چند معیار ارزیابی اثرات تغییر در مدیریت شیلات مبتنی بر اکوسیستم: مورد COD ایسلندی-2020 This paper presents the outcome of one of the case-studies of the EU-funded FP7 research project MareFrame.
The project sought to remove the barriers preventing more widespread use of the ecosystem-based approach to
fisheries management by developing integrated ecosystem-based assessment methods and a decision support
framework for the management of marine resources. The findings are intended to support the implementation of
the Common Fisheries Policy (CFP) and Marine Strategy Framework Directive (MSFD). The case study focused on the
Icelandic cod fishery which is by far the most important fishery in Iceland, accounting for 43% of the country’s
total export values of seafood in 2016. Sound biological and economic management of the fishery is therefore
essential for both the nation as a whole as well as individual fisheries-dependent communities. The analysis is
done in two main steps. We first use the statistical multi-species model Gadget, developed by the Icelandic
Marine and Freshwater Research Institute, to estimate the development of catches by fleet segments (trawl, net
and longline) and stock size. Comparisons are made with two scenarios: a) adhering to the present harvest
control rule or b) changing the effort to a level corresponding to fishing mortality associated with maximum
sustainable yield (FMSY). In the second step, the two outcomes and their socio-economic effects are examined
using a three-stage analytic hierarchy process. The case study has been developed in close cooperation with
Icelandic stakeholders, and in this paper we describe how the co-creation approach was employed in an
ecosystem-based fisheries management framework. Keywords: Ecosystem-based fisheries management | Co-creation | Gadget | Multi-criteria analysis | Analytic hierarchy process | Cod |
مقاله انگلیسی |
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Risk evaluation of large-scale seawater desalination projects based on an integrated fuzzy comprehensive evaluation and analytic hierarchy process method
ارزیابی ریسک پروژه های آب شیرین کن در مقیاس بزرگ بر اساس یک ارزیابی جامع فازی یکپارچه و روش فرآیند سلسله مراتبی تحلیلی-2020 Desalination projects play a vital role in the water supply of coastal regions with scarce water resources. The
risks associated with desalination projects are worth investigating, especially for large-scale projects. This paper
presents the risk identification and evaluation processes of large-scale desalination projects. Two levels of risk
indicators are identified and the first-level risks include water intake and outfall risk, processing risk, financial
risk and circumstance risk. With the identified risk indicators, an integrated fuzzy comprehensive evaluation
(FCE) and analytic hierarchy process (AHP) method is introduced to conduct quantitative risk evaluations for
large-scale desalination projects. Twenty experts in desalination-related fields are invited to vote to determine
the weighting vectors for the FCE through the AHP. They also participate in deciding the membership matrixes
in the FCE for three practical desalination projects. The evaluation results indicate that the overall risks of all the
considered projects are at the “Very low” level. Finally, to diminish the potential risks, several instructions and
recommendations are suggested that depend on the evaluation outcomes. It is expected that the current risk
evaluation research will make remarkable contributions to the risk management and control of large-scale desalination
projects and further promote the development of the desalination industry. Keywords: Desalination project | Risk identification | Risk evaluation | Fuzzy comprehensive evaluation | Analytic hierarchy process |
مقاله انگلیسی |
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Exploring the impact of dynamic capabilities on sustainable supply chain firms performance using Grey-Analytical Hierarchy Process
بررسی تاثیر توانایی های پویا در عملکرد شرکت های زنجیره تامین پایدار با استفاده از روند سلسله مراتبی تحلیلی خاکستری-2017 Dynamic capabilities (DCs) are the inherent capabilities developed by firms through the implementation
of Sustainable Supply Chain practices. These DCs serve as a backbone for the firms to achieve competitive
advantages in contemporary ever-changing markets. The present study focuses on exploring the impact
of the DCs on the firms performance, by offering a review of literature to identify the various associated
DCs and performance measures of a firm cited in peer reviewed journals. The impact of the collected DCs
on the enhancement of firms performance is then analyzed with the help of six performance measures
identified from the literature. First, through a questionnaire survey with industrial experts from south
India as respondents, the initial list of 77 DCs is confined to a list of 40 essential DCs. Second, the
shortlisted 40 DCs are grouped under six performance measures; a logical interpretation of which DC
will best enhance which performance measure was selected with the help of the industrial experts.
Third, Analytical Hierarchy Process pair-wise comparisons of the seven groups of DCs are done to identify
the influential DCs in each of the seven performance measure categories. Priority weights and rankings
are obtained both within the category and globally. Finally, a Grey-Analytical Hierarchy Process is used to
get a better understanding of the overall impact of the DCs in enhancing the performance measures of
the firm for a sustained competitive advantage. The obtained results help industrial managers to identify
specific influential DCs for each performance measure category by overcoming the limitations of few
experts through the application of the grey multi criteria decision making system. Identifying and
prioritizing performance-specific DCs allow sustainable supply chain oriented firms to concentrate on
the DCs most relevant to the specific performances needing improvement.
Keywords:Dynamic capabilities|Firms performance measures|Grey-Analytical Hierarchy Process |
مقاله انگلیسی |