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Sectoral brand management processes have presented planning, development and implementation challenges. With the aim of reducing these managerial problems, the purpose of this paper is to revise the structure and the processes of the sectoral brands management.

This is a qualitative exploratory study, with its unit of analysis being the process of managing the brand of the Brazilian fashion sector. Primary data collection was obtained through in-depth interviews with the seven industry associations and with the company responsible for the brand consulting. The secondary data used were reports about the branding process of the brand provided by respondents. Data analysis was provided by using the VSM to modeling sector structure and BPMN to processes modeling.

The results present a new sectoral brand structure and process to reduce existing barriers. Three sections were carried out: analysis and modeling of the current structure and processes of sectoral brand management; presentation of the current structure and processes problems; analysis and modeling of future structure and processes of sectoral brand management.

A theoretical contribution is provided in the literature of systems, processes and sectoral brands, since there are no previous studies that elaborated a system structure and process for sectoral brands. In addition, other theoretical contribution is the presentation of a future process model that relates brand management process with its system structure, that is, it relates BPM analysis with VSM.

It is also possible to indicate that VSM and BPM can contribute to the management of sectoral brands, through the structural and process problems identification and also by making possible to suggest future management improvements to reduce the barriers that were identified.

The present study originality is the approach of the first analysis of sector brand management with emphasis on its structure and processes that were experienced by the Brazilian fashion sector.

This chapter focuses on one particular practice that came to the forefront in over a dozen teacher education sessions with government schoolteachers in southern India- the reflective practice “Dialogic Modeling.” This chapter delves into two primary facets of dialogic modeling: how it operates and how it fosters opportunities to study the practices being modeled. To help supporters’ and critics’ reading, this chapter examines the form of several episodes of dialogic modeling. By form, the author refers to terms such as logic, structure, and conditions. This form and function analytic is critical to recognizing the mechanics of the practice, and provides an understanding of how a reflective dialogic practice can operate. The chapter also takes up why this form matters for how teachers learn to do their work, and how doing the work of teaching can be bolstered through reflective practice. By doing so, the chapter aims to provide additional warrants for the claims that teacher education can, and likely should, involve teacher-learners in the deliberate study of principled practices. Moreover, the author argues that modeling as it is commonly done leaves much to chance and squanders the opportunity to learn and build teachers’ capacities.

Business process modeling faces a difficult balance: on the one hand, organizations seek to enact, control and automate business processes through formal structures (procedures and rules). On the other hand, organizations also seek to embrace flexibility, change, innovation, value orientation, and dynamic capabilities, which require informal structures (unique user experiences). Addressing this difficulty, the authors propose the composite approach, which integrates formal and informal process structures. The composite approach adopts a socio-material conceptual lens, where both material and human agencies are supported.

The study follows a design science research methodology. An innovative artifact – the composite approach – is introduced. The composite approach is evaluated in an empirical experiment.

The experimental results show that the composite approach improves model understandability and situation understandability.

This research explores the challenges and opportunities brought by adopting a socio-material conceptual lens to represent business processes.

The study contributes an innovative hybrid approach for modeling business processes, articulating coordination and contextual knowledge. The proposed approach can be used to improve model understandability and situation understandability. The study also extends the socio-material conceptual lens over process modeling with a theoretical framework integrating coordination and contextual knowledge.

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of EXtensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user‐defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi‐structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three‐fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a viewdriven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction.

This paper aims to overcome the problem that the single structure of the driving term of the grey prediction model is not adapted to the complexity and diversity of the actual modeling objects, which leads to poor modeling results.

Firstly, the nonlinear law between the raw data and time point is fully mined by expanding the nonlinear term and the range of order. Secondly, through the synchronous optimization of model structure and parameter, the dynamic adjustment of the model with the change of the modeled object is realized. Finally, the objective optimization of nonlinear driving term and cumulative order of the model is realized by particle swarm optimization PSO algorithm.

The model can achieve strong compatibility with multiple existing models through parameter transformation. The synchronous optimization of model structure and parameter has a significant improvement over the single optimization method. The new model has a wide range of applications and strong modeling capabilities.

A novel grey prediction model with structure variability and optimizing parameter synchronization is proposed.

The highlights of the paper are as follows:

1. A new grey prediction model with a unified nonlinear structure is proposed.

2. The new model can be fully compatible with multiple traditional grey models.

3. The new model solves the defect of poor adaptability of the traditional grey models.

4. The parameters of the new model are optimized by PSO algorithm.

5. Cases verify that the new model outperforms other models significantly.

A new grey prediction model with a unified nonlinear structure is proposed.

The new model can be fully compatible with multiple traditional grey models.

The new model solves the defect of poor adaptability of the traditional grey models.

The parameters of the new model are optimized by PSO algorithm.

Cases verify that the new model outperforms other models significantly.

The aim of this paper is to present a new variation modeling method for fuselage structures in digital large aircraft assembly. The variation accumulated in a large aircraft assembly process will influence the dimensional accuracy and fatigue life of airframes. However, in digital large aircraft assembly, variation analysis and modeling are still unresolved issues.

An elastic structure model based on beam elements is developed, which is an equivalent idealization of the actual complex structure. The stiffness matrix of the structure model is obtained by summing the stiffness matrices of the beam elements. For each typical stage of the aircraft digital assembly process, including positioning, coordinating, joining and releasing, variation models are built using the simplified structure model with respective loads and boundary conditions.

Using position errors and manufacturing errors as inputs, the variations for every stage of the assembly process can be calculated using the proposed model.

This method has been used in a large fuselage section assembly project, and the calculated results were shown to be a good prediction of variation in the actual assembly.

Although certain assumptions have been imposed, the proposed method provides a better understanding of the assembly process and creates an analytical foundation for further work on variation control and tolerance optimization.

The multidimensional structure of boredom poses unique measurement challenges related to scale length and statistical modeling. We systematically address these concerns in two studies. In Study 1, we use item response theory to shorten the 29-item Multidimensional State Boredom Scale (MSBS) (Fahlman et al., 2013). In Study 2, we use structural equation modeling to compare two theoretically consistent multidimensional structures of boredom (superordinate and multivariate) with the most commonly used, yet theoretically inconsistent, structure in boredom research (unidimensional parallel model). Our findings provide support for modeling boredom as multidimensional and demonstrate the impact of model selection on effect sizes and significance.

On modern markets, supply chains (SC) shape the competition landscape. At the same time, considerable research advancements have been recently achieved in the area of collaborative networks. Trends in information technology progress for networked systems include development of cyber‐physical networks, cloud service environments, etc. The purpose of this paper is to identify an inter‐disciplinary perspective and modelling tools for new generation SCs which will be collaborative cyber‐physical networks.

This study addresses the above‐mentioned research goal by first, developing a methodical vision of an inter‐disciplinary modelling framework for SCM based on the existing studies on SC operations, control and systems theories; and second, by integrating elements of different structures with structures dynamics within an adaptive framework based upon the authors' own research.

The inter‐disciplinary modelling framework for multi‐structural SCs has been developed. A new inter‐disciplinary level of model‐based decision‐making support in those SCs is claimed based on the integration of previously isolated problems and modelling tools developed in such disciplines like operations research, control theory, system dynamics, and artificial intelligence.

The novelty of this paper is the consideration of SC modelling in the context of collaborative cyber‐physical systems. This topic is particularly relevant for researchers and practitioners who are interested in future generation SCs. Particular focus is directed towards the multi‐structural SC modelling, structure dynamics, and inter‐disciplinary problems and models in future SCs. Challenges of integrated optimization in the organizational and informational context are discussed.

The purpose of this paper is to present a simplified hybrid modeling (HYMOD) approach which overcomes limitations regarding computational cost and permits the simulation and prediction of the nonlinear inelastic behavior of full-scale RC structures.

The proposed HYMOD formulation was integrated in a research software ReConAn FEA and was numerically studied through the use of different numerical implementations. Then the method was used to model a full-scale two-storey RC building, in an attempt to demonstrate its numerical robustness and efficiency.

The numerical results performed demonstrate the advantages of the proposed hybrid numerical simulation for the prediction of the nonlinear ultimate limit state response of RC structures.

A new numerical modeling method based on finite element method is proposed for simulating accurately and with computational efficiency, the mechanical behavior of RC structures. Currently 3D detailed methods are used to model single structural members or small parts of RC structures. The proposed method overcomes the above constraints.

The purpose of this paper is to investigate strategies for expedited dimension scaling of electromagnetic (EM)-simulated microwave and antenna structures, exploiting the concept of variable-fidelity inverse surrogate modeling.

A fast inverse surrogate modeling technique is described for dimension scaling of microwave and antenna structures. The model is established using reference designs obtained for cheap underlying low-fidelity model and corrected to allow structure scaling at high accuracy level. Numerical and experimental case studies are provided demonstrating feasibility of the proposed approach.

It is possible, by appropriate combination of surrogate modeling techniques, to establish an inverse model for explicit determination of geometry dimensions of the structure at hand so as to re-design it for various operating frequencies. The scaling process can be concluded at a low computational cost corresponding to just a few evaluations of the high-fidelity computational model of the structure.

The present study is a step toward development of procedures for rapid dimension scaling of microwave and antenna structures at high-fidelity EM-simulation accuracy.

The proposed modeling framework proved useful for fast geometry scaling of microwave and antenna structures, which is very laborious when using conventional methods. To the authors’ knowledge, this is one of the first attempts to surrogate-assisted dimension scaling of microwave components at the EM-simulation level.