Discourse network analysis: policy debates as dynamic networks

Political discourse is the verbal interaction between political actors. Political actors make normative claims about policies conditional on each other. This renders discourse a dynamic network phenomenon. Accordingly, the structure and dynamics of policy debates can be analyzed with a combination of content analysis and dynamic network analysis. After annotating statements of actors in text sources, networks can be created from these structured data, such as congruence or conflict networks at the actor or concept level, affiliation networks of actors and concept stances, and longitudinal versions of these networks. The resulting network data reveal important properties of a debate, such as the structure of advocacy coalitions or discourse coalitions, polarization and consensus formation, and underlying endogenous processes like popularity, reciprocity, or social balance. The added value of discourse network analysis over survey-based policy network research is that policy processes can be analyzed from a longitudinal perspective. Inferential techniques for understanding the micro-level processes governing political discourse are being developed

Efficient development of complex statecharts

Modeling systems based on graphical formalisms, such as Statecharts, has become standard practice in the design of embedded devices. Using paradigms established so far often results in complex models that are difficult to comprehend and maintain. To overcome this, we present a methodology to support the easy development and understanding of complex Statecharts. Central to our approach is the use of secondary notations to aid readability. We employ an automated layout mechanism to transform any given Statechart to a Statechart Normal Form. The Kiel Integrated Environment for Layout is a prototypical modeling tool to explore our editing, browsing and simulation paradigms in the design of complex reactive systems. An empirical study on the usability and practicability of our Statechart editing techniques, including a Statechart layout comparison, indicates significant performance improvements in terms of editing speed and model comprehension compared to traditional modeling approaches

Sensitivity analysis of agent-based models: a new protocol

Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such critiques, we propose a systematic approach to conducting sensitivity analyses of ABMs. Our approach deals with a feature that can complicate sensitivity analyses: most ABMs include important non-parametric elements, while most sensitivity analysis methods are designed for parametric elements only. The approach moves from charting out the elements of an ABM through identifying the goal of the sensitivity analysis to specifying a method for the analysis. We focus on four common goals of sensitivity analysis: determining whether results are robust, which elements have the greatest impact on outcomes, how elements interact to shape outcomes, and which direction outcomes move when elements change. For the first three goals, we suggest a combination of randomized finite change indices calculation through a factorial design. For direction of change, we propose a modification of individual conditional expectation (ICE) plots to account for the stochastic nature of the ABM response. We illustrate our approach using the Garbage Can Model, a classic ABM that examines how organizations make decisions

Sensitivity analysis of agent-based models: a new protocol

Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such critiques, we propose a systematic approach to conducting sensitivity analyses of ABMs. Our approach deals with a feature that can complicate sensitivity analyses: most ABMs include important non-parametric elements, while most sensitivity analysis methods are designed for parametric elements only. The approach moves from charting out the elements of an ABM through identifying the goal of the sensitivity analysis to specifying a method for the analysis. We focus on four common goals of sensitivity analysis: determining whether results are robust, which elements have the greatest impact on outcomes, how elements interact to shape outcomes, and which direction outcomes move when elements change. For the first three goals, we suggest a combination of randomized finite change indices calculation through a factorial design. For direction of change, we propose a modification of individual conditional expectation (ICE) plots to account for the stochastic nature of the ABM response. We illustrate our approach using the Garbage Can Model, a classic ABM that examines how organizations make decisions

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

An exploration of integrality in project productions and its final outcome : the mobile production cells

Tese de doutoramento. Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 200

Industrial Symbiosis Recommender Systems

For a long time, humanity has lived upon the paradigm that the amounts of natural resources are unlimited and that the environment has ample regenerative capacity. However, the notion to shift towards sustainability has resulted in a worldwide adoption of policies addressing resource efficiency and preservation of natural resources.One of the key environmental and economic sustainable operations that is currently promoted and enacted in the European Union policy is Industrial Symbiosis. In industrial symbiosis, firms aim to reduce the total material and energy footprint by circulating traditional secondary production process outputs of firms to become part of an input for the production process of other firms.This thesis directs attention to the design considerations for recommender systems in the highly dynamic domain of industrial symbiosis. Recommender systems are a promising technology that may facilitate in multiple facets of the industrial symbiosis creation as they reduce the complexity of decision making. This typical strength of recommender systems has been responsible for improved sales and a higher return of investments. That provides the prospect for industrial symbiosis recommenders to increase the number of synergistic transactions that reduce the total environmental impact of the process industry in particular

Hierarchy in industry architecture : transaction strategy under technological constraints

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 154-163).Motivation -- Industrial firms survive, sustain and co-evolve by participating in the sector of innovation and production through industrial transactions with each other. However, it is difficult for specialized firms to be aware of and manage accordingly the kind of systemic constraints and opportunities induced by relevant but indirect transactions, as well as the technological and economic requirements of their value chains, which they cannot control or even sufficiently observe. The myopia may cause specialized firms to implement incorrect strategies, leave them vulnerable to system failures or ignorant of emerging opportunities. This implies a paradox: the simultaneous needs to specialize and to understand and manage the big picture of the eco-system. Goal -- Previous industry studies have focused on the question if a transaction with an external firm is needed rather than in-house production, and on empirical work from single industries or bilateral relationships between firms. Meanwhile, the firms' positions in the sectoral transactional network are also influential to the success and performance of firms. In this dissertation, I conduct transactional network analysis to explore how firms are organized in the sector of aggregated industries, in order to shed light on the set of previously ignored knowledge on industrial transactions, which is valuable to single firms in designing strategies and managing operations but is not available from firm- and industry-level analysis. Hierarchy in Industry Architecture -- At the sector level, existing theories often assumed hierarchical or non-hierarchical relationships among industrial firms, and quantitative evidence on variable degrees of hierarchy in industry sectors is lacking. This dissertation first identifies and defines the type of hierarchy relevant to industry studies -flow hierarchy, develops a network-based metric on the degree of hierarchy (one-way flow of transactions), and applies it to the transaction data from two industrial sectors in Japan. The empirical results show that the electronics sector exhibits a significantly lower degree of hierarchy than the automotive sector due to the presence of many transaction cycles. It shows that the simplistic hierarchy hypothesis for production sectors does not always hold. Industrial Network Model and Transaction Specificity -- I further create a network simulation model with random networks to relate sector-level hierarchy degrees to firm-level behavioral variables, and infer transaction specificity, i.e. the extent to which a firm is captive to a niche of customers positioned closely in the industrial network hierarchy. The model builds on three basic rules on market structures, i.e. hierarchy, niche, and the mapping relationship between roles and positions. Transaction specificity provides a way to quantify the tendency of a firm to fix or institutionalize its role according to its relative network position, or where the transactions of a firm are oriented in the value chains, whereas traditional studies analyze whether a transaction versus in-house production is needed. The result shows that transaction specificity in the electronics sector is quantitatively much lower than that in the automotive sector. Interviews and Firm Boundary Strategies -- I further conducted interviews with nine firms in the two sectors and found that, with decision rationales related to product modularity, innovation dynamics and asset specificity, the major electronics firms take the permeable vertical boundary strategy and diversified horizontal boundary strategy, which decrease transaction specificity so that many transaction cycles emerge in the electronics sector. My analysis shows the permeability of a firm's vertical boundary, i.e. playing multiple value chain roles, is the necessary condition for transaction cycles to emerge. Meanwhile, these two strategies are not feasible in the automotive sector according to interviews. They are also not observed in the American electronics sector. My data show the American electronics firms tend to be vertically specialized in the value chains. Social-Technical Arguments -- Linking network analysis results, interview data, and the prior work on the physical limits to product modularity, I argue that higher power level of a sector's technologies leads to higher transaction specificity, and more hierarchical transaction lows across the sector. High power technologies constrain strategic transaction choices, while lower power technologies enable a larger option space of transaction strategies, for companies to explore and exploit. Implications -- For academics, the use of network analysis permits transaction cost analysis, or more general analysis of transaction-related decisions, to be extended from the boundary of a firm to the architecture of a sector comprising related industries. It gives us a bird's-eye view to observe firm-level transaction behaviors and create new knowledge on transaction specificity. In addition, the analysis of the physical properties of product technologies allows us to interpret the difference in transaction specificities and hierarchy degrees of different sectors, which economic and sociology theories cannot explain. For industry practitioners, this research suggests that firms' choices for industrial transactions are under some predictable constraints from product technologies. A better understanding of the linkages between industry architecture, firm transaction strategy, and product technology, in turn can guide companies to tailor transaction strategies to implicit technological constraints and to adequately explore strategic options made feasible by technologies.by Jianxi Luo.Ph.D