Decision Support Systems and Knowledge Management for Sustainable Engineering

• Autore: Tsagarakis Konstantinos P
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 electronic resource (366 p.)
• Soggetto topico: History of engineering & technology
• Soggetto non controllato: higher education institutions; sustainability assessment; benchmarking; energy flow; carbon flow; sustainable development; problem-solving; incident command system; task ontology; knowledge management; sustainable healthcare supply chain; performance measurement; performance of perspectives and indicators; sustainability aspects; intangible characteristics; lifecycle assessment; recurrent embodied carbon; system dynamics; buildings; CO2 emissions; construction phase; stochastic analysis; Monte Carlo simulation; implications; fuzzy estimators; lake eutrophication; prediction model; corporate sustainability; business strategy; decision-making; decision support systems; road network; sustainability; analytic hierarchical process; crude-oil; sour gas; hydrogen sulfide; crude stabilization; hazard identification; HAZOP study; risk analysis; operability study; process safety; risk-matrix; DMRA; multi-criteria decision-making; Analytical-Hierarchy-Process; Typical-AHP; Fuzzy-AHP; index; sustainable mining; threshold values; sustainability indicators; environmental sustainability; environmental assessment; anthropogenic spatial entities; knowledge creation; healthcare organizations; hospital; organizational learning; sustainable knowledge management; strategy; validation; questionnaire; quality of care; renewable energy sources; energy policy; SWOT analysis; multi-criteria analysis; AHP; fuzzy TOPSIS; Morocco; Egypt; strategic environmental assessment; strategic environmental impact assessment; methods; techniques; Greece; MCDM; fuzzy AHP; PRAT; FTA; time-series; risk assessment; OSH; telecom technical projects; constructions; carrying capacity; regional sustainability assessment; ecological footprint; national park; risk management; performance assessment; performance management; performance evaluation; earned value analysis; construction projects; fuzzy numbers
• Persona (resp. second.): NikolaouIoannis; VavatsikosAthanasios P; KoulouriotisDimitrios E; TsagarakisKonstantinos P
• Sommario/riassunto: Modern engineering approaches focus on the design and operation of systems and products in a way that allows for the sustainable use of resources. Sustainable engineering aims to provide frameworks that ensure development without compromising the quality of the natural environment and the ability of future generations to meet their own needs. In this context, decision making processes must be enriched by approaches and tools that allow decision makers to consider a wide range of sustainable options. Recently, great progress has been taking place in the fields of operation research and management science, where intelligent quantitative analysis, statistics, and prediction analytics are employed in a variety of interdisciplinary research areas, aiming to assist policy makers and managers with the consideration of a variety of sustainable options. This Special Issue consists of a 17-paper collection with published approaches and models that are designed to give answers for environmental impact and sustainability assessment, risk and knowledge management assessment, lifecycle assessment and energy management. Five papers are dedicated to advances in different literature review topics. The remaining papers deal with a variety of engineering approaches to address decision making which involves: mulricriteria decision analysis, ecological footprint and biocapacity estimations, fuzzy prediction models, advanced statistical analysis, simulation, systems dynamics model, task ontology and integration definition function modeling.
• Titolo autorizzato: Decision Support Systems and Knowledge Management for Sustainable Engineering
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557375803321
• Lo trovi qui: Univ. Federico II