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The information contained in news articles plays a key role on
financial markets. It may describe changes in the fundamentals of a company
or influence the way investors perceive the risk associated with it. This paper
aims at measuring with mathematical means the main underlying semantic
content of news articles, such that it captures information useful to forecast
volatility.

A modified EGARCH model with external factors, obtained from a latent semantic alaysis on news articles, is proposed to measure the impact on volatility induced by the latent semantic content of the textual news data. I find that several semantic dimensions play an important
role in explaining observed volatility, while others are useful to forecast it. It
is likely, that with further research, a model based on semantic content could
greatly improve our understanding of the market’s response to news releases.

LSA --- GARCH --- EGARCH --- GARCH-X --- Latent Semantic Analysis --- Volatility Forecasting --- S&P500 --- Lagged corredlations --- Reuters --- News --- News Articles --- Conditional Volatility --- Sciences économiques & de gestion > Finance

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In recent years, the industrial environment has been changing radically due to the introduction of concepts and technologies based on the fourth industrial revolution, also known as Industry 4.0. After the introduction of Industry 4.0 in large enterprises, SMEs have moved into the focus, as they are the backbone of many economies. Small organizations are increasingly proactive in improving their operational processes, which is a good starting point for introducing the new concepts of Industry 4.0. The readiness of SME-adapted Industry 4.0 concepts and the organizational capability of SMEs to meet this challenge exist only in some areas. This reveals the need for further research and action plans for preparing SMEs in a technical and organizational direction. Therefore, special research and investigations are needed for the implementation of Industry 4.0 technologies and concepts in SMEs. SMEs will only achieve Industry 4.0 by following SME-customized implementation strategies and approaches and realizing SME-adapted concepts and technological solutions. Thus, this Special Issue represents a collection of theoretical models as well as practical case studies related to the introduction of Industry 4.0 concepts in small- and medium-sized enterprises.

History of engineering & technology --- latent semantic analysis --- virtual quality management --- concept investigation --- concept disambiguation --- knowledge discovery --- sustainable methodologies --- small and medium sized enterprises --- material handling systems --- simulation --- ARENA®, time study --- overall equipment effectiveness --- manufacturing performance --- Industry 4.0 --- manufacturing sustainability --- manufacturing process model --- business process management --- hierarchical clustering --- similarity --- BPMN --- human factors --- cyber-physical systems --- cyber-physical production systems --- anthropocentric design --- Operator 4.0 --- human–machine interaction --- energy efficient operation --- manufacturing system --- stochastic event --- digital twin --- Max-plus Algebra --- MATLAB-Simulink --- advanced manufacturing --- industry 4.0 --- SME --- technology adoption model --- assembly supply chain --- sustainability --- complexity indicators --- testing criteria --- SMEs --- e-business modelling --- LSP Lifecycle Model --- Quality Function Deployment --- Best-Worst Method --- Internet of Things --- India --- awareness --- small and medium-sized enterprises --- assessment model --- collaborative robotics --- physical ergonomics --- human-robot collaboration --- human-centered design --- assembly --- small and medium sized enterprise --- positive complexity --- negative complexity --- infeasible configurations --- product platform --- customer’s perception --- assessment --- field study --- smart manufacturing --- cloud platform --- artificial intelligence --- machine learning --- deep learning --- smart logistics --- logistics 4.0 --- smart technologies --- sustainable agriculture --- plant factory --- latent semantic analysis --- virtual quality management --- concept investigation --- concept disambiguation --- knowledge discovery --- sustainable methodologies --- small and medium sized enterprises --- material handling systems --- simulation --- ARENA®, time study --- overall equipment effectiveness --- manufacturing performance --- Industry 4.0 --- manufacturing sustainability --- manufacturing process model --- business process management --- hierarchical clustering --- similarity --- BPMN --- human factors --- cyber-physical systems --- cyber-physical production systems --- anthropocentric design --- Operator 4.0 --- human–machine interaction --- energy efficient operation --- manufacturing system --- stochastic event --- digital twin --- Max-plus Algebra --- MATLAB-Simulink --- advanced manufacturing --- industry 4.0 --- SME --- technology adoption model --- assembly supply chain --- sustainability --- complexity indicators --- testing criteria --- SMEs --- e-business modelling --- LSP Lifecycle Model --- Quality Function Deployment --- Best-Worst Method --- Internet of Things --- India --- awareness --- small and medium-sized enterprises --- assessment model --- collaborative robotics --- physical ergonomics --- human-robot collaboration --- human-centered design --- assembly --- small and medium sized enterprise --- positive complexity --- negative complexity --- infeasible configurations --- product platform --- customer’s perception --- assessment --- field study --- smart manufacturing --- cloud platform --- artificial intelligence --- machine learning --- deep learning --- smart logistics --- logistics 4.0 --- smart technologies --- sustainable agriculture --- plant factory

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In recent years, the industrial environment has been changing radically due to the introduction of concepts and technologies based on the fourth industrial revolution, also known as Industry 4.0. After the introduction of Industry 4.0 in large enterprises, SMEs have moved into the focus, as they are the backbone of many economies. Small organizations are increasingly proactive in improving their operational processes, which is a good starting point for introducing the new concepts of Industry 4.0. The readiness of SME-adapted Industry 4.0 concepts and the organizational capability of SMEs to meet this challenge exist only in some areas. This reveals the need for further research and action plans for preparing SMEs in a technical and organizational direction. Therefore, special research and investigations are needed for the implementation of Industry 4.0 technologies and concepts in SMEs. SMEs will only achieve Industry 4.0 by following SME-customized implementation strategies and approaches and realizing SME-adapted concepts and technological solutions. Thus, this Special Issue represents a collection of theoretical models as well as practical case studies related to the introduction of Industry 4.0 concepts in small- and medium-sized enterprises.

latent semantic analysis --- virtual quality management --- concept investigation --- concept disambiguation --- knowledge discovery --- sustainable methodologies --- small and medium sized enterprises --- material handling systems --- simulation --- ARENA®, time study --- overall equipment effectiveness --- manufacturing performance --- Industry 4.0 --- manufacturing sustainability --- manufacturing process model --- business process management --- hierarchical clustering --- similarity --- BPMN --- human factors --- cyber-physical systems --- cyber-physical production systems --- anthropocentric design --- Operator 4.0 --- human–machine interaction --- energy efficient operation --- manufacturing system --- stochastic event --- digital twin --- Max-plus Algebra --- MATLAB-Simulink --- advanced manufacturing --- industry 4.0 --- SME --- technology adoption model --- assembly supply chain --- sustainability --- complexity indicators --- testing criteria --- SMEs --- e-business modelling --- LSP Lifecycle Model --- Quality Function Deployment --- Best-Worst Method --- Internet of Things --- India --- awareness --- small and medium-sized enterprises --- assessment model --- collaborative robotics --- physical ergonomics --- human-robot collaboration --- human-centered design --- assembly --- small and medium sized enterprise --- positive complexity --- negative complexity --- infeasible configurations --- product platform --- customer’s perception --- assessment --- field study --- smart manufacturing --- cloud platform --- artificial intelligence --- machine learning --- deep learning --- smart logistics --- logistics 4.0 --- smart technologies --- sustainable agriculture --- plant factory

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Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems.

Information technology industries --- multiple-criteria decision-making --- underground mines --- mining methods --- expert knowledge --- failure mode and effects analysis --- solar panel systems --- step-wise weight assessment ratio analysis --- grey relational analysis --- Z-number theory --- B2C e-commerce factors --- website --- MCDM --- Fuzzy AHP --- TOPSIS-Grey --- China --- IoT --- platform selection --- multi criteria decision analysis (MCDA) --- AHP --- PROMETHEE-II --- Industry 4.0 --- data envelopment analysis --- conjoint analysis --- experimental design --- criteria importance --- weight restrictions --- subjective and objective teacher efficiency --- multi-objective planning --- reverse supply chain --- robust optimization --- uncertainty --- meta-heuristic algorithm --- steel making industry --- fuzzy PIPRECIA --- fuzzy EDAS --- railway --- multi-criteria decision-making --- transport policy --- Six Sigma (6σ) --- DMAIC --- vehicle fleet --- optimization --- text mining --- Multi-Attribute Decision Making (MADM), criteria selection --- weighting --- Prospective MADM --- Latent Semantic Analysis (LSA) --- SIMUS --- decision tree --- transport plan --- Laplace’s criterion --- Hurwitz’s criterion --- q-rung orthopair fuzzy numbers --- q-rung orthopair fuzzy prioritized weighted average operator --- q-rung orthopair fuzzy prioritized weighted geometric operator --- green supply chain management --- fuzzy theory --- sustainable development --- SCOR model --- FAHP --- PROMETHEE II --- textile and garments industry --- sustainable supplier selection --- MCDA --- efficiency --- DEA --- SFA --- classification --- dimensionality reduction --- q-ROFNs --- Einstein operators --- prioritized aggregation operators --- multi-criteria group decision making --- hazardous materials --- vehicle route model (VRP) --- uncertainty theory --- chance constrained programming model --- hybrid intelligent algorithm --- linear Diophantine fuzzy set --- linear Diophantine fuzzy soft rough set --- soft rough linear Diophantine fuzzy set --- upper reduct and lower reduct --- core set --- multi-criteria decision making --- q-Rung orthopair fuzzy sets --- geometric aggregation operators based on generalized and group-generalized parameters --- water loss management --- decision making --- intuitionistic fuzzy sets --- the COMET method --- service quality --- fuzzy set --- Jensen–Shannon divergence --- shapley function --- TODIM --- port-hinterland transportation system --- bi-objective programming --- intermodal transportation --- carbon emissions --- uncertain demand --- distributionally robust --- chance constraint --- Yangtze River Economic Belt --- multi-criteria decision-analysis --- MCDA benchmark --- normalization --- entropy --- decision-making methods --- multi-criteria problems --- evolutionary algorithms --- machine learning --- fuzzy logic --- uncertain data --- consistency weights --- fuzzy preference relation (FPR) --- hesitant fuzzy preference relation (HFPR) --- Łukasiewicz consistency --- normal hesitant fuzzy preference relation (NHFPR) --- multiple criteria decision-making (MCDM) --- outsourcing provider --- DEMATEL --- CRITIC --- TOPSIS --- comparison measure --- representation --- disjoint --- multiplicative preference relation (MPR) --- group decision-making (GDM) --- incomplete fuzzy preference relation (IFPR) --- TL-consistency --- cubic m-polar fuzzy set --- Dombi’s operations --- cubic m-polar fuzzy aggregation operators with P-order (R-order) --- SIR technique --- complex networks --- social networks --- viral marketing --- information propagation --- crisp probability --- interval probability --- influence diagrams --- circuit breakers --- granular computing --- interval-valued --- intuitionistic fuzzy set --- multiple granulation --- ordered information system --- multiple-criteria decision-making --- underground mines --- mining methods --- expert knowledge --- failure mode and effects analysis --- solar panel systems --- step-wise weight assessment ratio analysis --- grey relational analysis --- Z-number theory --- B2C e-commerce factors --- website --- MCDM --- Fuzzy AHP --- TOPSIS-Grey --- China --- IoT --- platform selection --- multi criteria decision analysis (MCDA) --- AHP --- PROMETHEE-II --- Industry 4.0 --- data envelopment analysis --- conjoint analysis --- experimental design --- criteria importance --- weight restrictions --- subjective and objective teacher efficiency --- multi-objective planning --- reverse supply chain --- robust optimization --- uncertainty --- meta-heuristic algorithm --- steel making industry --- fuzzy PIPRECIA --- fuzzy EDAS --- railway --- multi-criteria decision-making --- transport policy --- Six Sigma (6σ) --- DMAIC --- vehicle fleet --- optimization --- text mining --- Multi-Attribute Decision Making (MADM), criteria selection --- weighting --- Prospective MADM --- Latent Semantic Analysis (LSA) --- SIMUS --- decision tree --- transport plan --- Laplace’s criterion --- Hurwitz’s criterion --- q-rung orthopair fuzzy numbers --- q-rung orthopair fuzzy prioritized weighted average operator --- q-rung orthopair fuzzy prioritized weighted geometric operator --- green supply chain management --- fuzzy theory --- sustainable development --- SCOR model --- FAHP --- PROMETHEE II --- textile and garments industry --- sustainable supplier selection --- MCDA --- efficiency --- DEA --- SFA --- classification --- dimensionality reduction --- q-ROFNs --- Einstein operators --- prioritized aggregation operators --- multi-criteria group decision making --- hazardous materials --- vehicle route model (VRP) --- uncertainty theory --- chance constrained programming model --- hybrid intelligent algorithm --- linear Diophantine fuzzy set --- linear Diophantine fuzzy soft rough set --- soft rough linear Diophantine fuzzy set --- upper reduct and lower reduct --- core set --- multi-criteria decision making --- q-Rung orthopair fuzzy sets --- geometric aggregation operators based on generalized and group-generalized parameters --- water loss management --- decision making --- intuitionistic fuzzy sets --- the COMET method --- service quality --- fuzzy set --- Jensen–Shannon divergence --- shapley function --- TODIM --- port-hinterland transportation system --- bi-objective programming --- intermodal transportation --- carbon emissions --- uncertain demand --- distributionally robust --- chance constraint --- Yangtze River Economic Belt --- multi-criteria decision-analysis --- MCDA benchmark --- normalization --- entropy --- decision-making methods --- multi-criteria problems --- evolutionary algorithms --- machine learning --- fuzzy logic --- uncertain data --- consistency weights --- fuzzy preference relation (FPR) --- hesitant fuzzy preference relation (HFPR) --- Łukasiewicz consistency --- normal hesitant fuzzy preference relation (NHFPR) --- multiple criteria decision-making (MCDM) --- outsourcing provider --- DEMATEL --- CRITIC --- TOPSIS --- comparison measure --- representation --- disjoint --- multiplicative preference relation (MPR) --- group decision-making (GDM) --- incomplete fuzzy preference relation (IFPR) --- TL-consistency --- cubic m-polar fuzzy set --- Dombi’s operations --- cubic m-polar fuzzy aggregation operators with P-order (R-order) --- SIR technique --- complex networks --- social networks --- viral marketing --- information propagation --- crisp probability --- interval probability --- influence diagrams --- circuit breakers --- granular computing --- interval-valued --- intuitionistic fuzzy set --- multiple granulation --- ordered information system