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The purpose of this paper is to present a novel strategy used for acceleration of free-vibration analysis, in which the hierarchical matrices structure and Compute Unified Device Architecture (CUDA) platform is applied to improve the performance of the traditional dual reciprocity boundary element method (DRBEM).

The DRBEM is applied in forming integral equation to reduce complexity. In the procedure of optimization computation, ℋ-Matrices are introduced by applying adaptive cross-approximation method. At the same time, this paper proposes a high-efficiency parallel algorithm using CUDA and the counterpart of the serial effective algorithm in ℋ-Matrices for inverse arithmetic operation.

The analysis for free-vibration could achieve impressive time and space efficiency by introducing hierarchical matrices technique. Although the serial algorithm based on ℋ-Matrices could obtain fair performance for complex inversion operation, the CUDA parallel algorithm would further double the efficiency. Without much loss in accuracy according to the examination of the numerical example, the relative error appeared in approximation process can be fixed by increasing degrees of freedoms or introducing certain amount of internal points.

The paper proposes a novel effective strategy to improve computational efficiency and decrease memory consumption of free-vibration problems. ℋ-Matrices structure and parallel operation based on CUDA are introduced in traditional DRBEM.

The purpose of this paper is to present a computationally efficient approach for the stochastic modeling of an inhomogeneous reluctivity of magnetic materials. These materials can be part of electrical machines such as a single-phase transformer (a benchmark example that is considered in this paper). The approach is based on the Karhunen–Loève expansion (KLE). The stochastic model is further used to study the statistics of the self-inductance of the primary coil as a quantity of interest (QoI).

The computation of the KLE requires solving a generalized eigenvalue problem with dense matrices. The eigenvalues and the eigenfunction are computed by using the Lanczos method that needs only matrix vector multiplications. The complexity of performing matrix vector multiplications with dense matrices is reduced by using hierarchical matrices.

The suggested approach is used to study the impact of the spatial variability in the magnetic reluctivity on the QoI. The statistics of this parameter are influenced by the correlation lengths of the random reluctivity. Both, the mean value and the standard deviation increase as the correlation length of the random reluctivity increases.

The KLE, computed by using hierarchical matrices, is used for uncertainty quantification of low frequency electrical machines as a computationally efficient approach in terms of memory requirement, as well as computation time.

The purpose of this paper is to investigate the problem faced by many Taiwanese restaurant owners who trying to set up their shops in Thailand.

Two surveys were conducted in this study. The first interview questionnaire was designed using the factors proposed by Parasuraman et al. (1988, 1991) and given to restaurant owners/managers who successfully set up shops in Thailand. The second questionnaire was constructed specifically for Thai consumers.

Gray relational analysis (GRA), theory of inventive problem-solving (teoriya resheniya izobreatatelskikh zadatch, TRIZ) and interpretive structural model (ISM) were used to identify potential difficulties and to determine the key factors impacting the shop establishment and development in Thailand. The results provide a set of strategic sequence when launching restaurant in Thailand.

A result of GRA determined 14 important factors that influence customer perception of quality service. A TRIZ analytic process provided 17 strategies when setting up overseas shop and the ISM class diagram shown the three phases needed to be considered before restaurant owners can set up shops abroad. The three phases are construction, operation and competition phases. These set of strategies sequence when launching a restaurant in Thailand.

There is growing dissatisfaction with the static, reductionist, socially insensitive and unimaginative methods used in construction management research. The present paper challenges the emerging view that methods are strictly associated with philosophies, and in particular, that quantitative methods are at odds with interpretative aspirations. It does so by providing a practical example of social network analysis, a quantitative method which is sympathetic to these aspirations. The example is set within a crisis management context, and illustrates the dangers of using qualitative or quantitative methods in isolation. The present paper concludes by questioning the association of quantitative methods with causality and the production of universal models, and argues that both quantitative and qualitative methods have a role to play in understanding the complexity of people's changing social roles, positions and behaviours within construction organizations.

The purpose of this paper is to find the efficient iterative methods for solving the general matrix equation A1X+ XA2+A3XH+XHA4=B (including Lyapunov and Sylvester matrix equations as special cases) with the unknown complex (reflexive) matrix X.

By applying the principle of hierarchical identification and the Hermitian/skew‐Hermitian splitting of the coefficient matrix quadruplet A1; A2; A3; A4 the authors propose a shift‐splitting hierarchical identification (SSHI) method to solve the general linear matrix equation A1X+XA2+A3XH+XHA4=B. Also, the proposed algorithm is extended for finding the reflexive solution to this matrix equation.

The authors propose two iterative methods for finding the solution and reflexive solution of the general linear matrix equation, respectively. The proposed algorithms have a simple, neat and elegant structure. The convergence analysis of the methods is also discussed. Some numerical results are given which illustrate the power and effectiveness of the proposed algorithms.

So far, several methods have been presented and used for solving the matrix equations by using vec operator and Kronecker product, generalized inverse, generalized singular value decomposition (GSVD) and canonical correlation decomposition (CCD) of matrices. In several cases, it is difficult to find the solutions by using matrix decomposition and generalized inverse. Also vec operator and Kronecker product enlarge the size of the matrix greatly therefore the computations are very expensive in the process of finding solutions. To overcome these complications and drawbacks, by using the hierarchical identification principle and the Hermitian=skew‐Hermitian splitting of the coefficient matrix quadruplet (A1; A2; A3; A4), the authors propose SSHI methods for solving the general matrix equation.

To provide first insight onto the application of hierarchical matrices and adaptive cross approximation (ACA) techniques for electromagnetic scattering problems.

The shielding effectiveness of metallic casings with apertures is analyzed via an electric field integral equation. To reduce the storage needs and the complexity of matrix equation solution, a technique combining the use of hierarchical matrices (H‐matrix) in conjunction with the ACA technique is used.

Provides first results for compression of a matrix resulting from a Helmholtz problem by means of hierarchical matrices and ACA techniques. Gives insight into the importance of obtaining a “cheap” preconditioner.

The technique resides on the smotheness of kernel functions – which is no longer valid for big wave numbers.

Gives means of solving problems of big dimensions in terms of number of unknowns – without the need to tailor the approach for the specific kernel function. The original integration functions used to fill the full matrix can be used here.

The paper represents one of the first attempts to use the above‐mentioned techniques for the high frequency domain.

Despite much attention being devoted to shared leadership, the negotiation of such arrangements remains underexplored. In parallel, the revival of interest in matrix structures reveals their challenges but neglects the dynamics of shared leadership. In this case study, the author analyzes the tensions experienced by senior managers of a healthcare organization transitioning from a hierarchical to matrix structure as they negotiate their leadership roles in this new arrangement.

The author interviewed 16 senior managers, observed their meetings and analyzed documents. These data were combined with secondary data including previous interviews and observations of this top leadership team. The author then conducted an inductive data analysis.

The author's analysis reveals that the tensions experienced by senior managers as they negotiate their roles reflect the co-existence of leadership surpluses (too much leadership) and deficits (too little leadership) in matrix organizations. The author argues that surpluses and deficits are not mutually exclusive but are interrelated and shows how leadership surpluses can create leadership deficits.

The author’s findings suggest that in contexts of leader abundance, actors should explore leadership voids. Particular attention should be paid to incidents of intrusion and exclusion, moments of transition and intense role negotiation, as those contexts are particularly conducive to leadership deficits.

While previous work on matrix structures focuses on leadership surpluses, the author discusses leadership deficits. The author explores how more leaders do not necessarily mean more leadership, but instead how more leaders may result in leadership voids.

The purpose of this paper is to present the embedding of linear and nonlinear order reduction methods in a theoretical framework for handling hierarchically interconnected dynamical systems.

Based on the component connection modeling (CCM), a modified framework called mCCM for describing interconnected dynamic systems especially with hierarchical structures is introduced and used for order reduction purposes. The balanced truncation method for linear systems and the trajectory piecewise linear reduction scheme are used for the order reduction of systems described within the mCCM framework.

It is shown that order reduction methods can be embedded into the context of interconnected dynamical systems with the benefit of having a further degree of freedom in form of the hierarchical level, on which the order reduction is performed.

The aspect of hierarchy within system descriptions is exploited for order reduction purposes. This distinguishes the presented approach from common methods, which already start with single large-scale systems without explicitly considering hierarchical structures.

The purpose of this paper is to introduce a novel approach to solving linear systems arising from applying a Boundary Element Method (BEM) to elasticity problems.

The key idea is based on using wavelet transforms as a tool to change dense and fully populated matrices of BEM systems into sparse matrices. Wavelets are then used again to produce an algorithm to solve the resultant sparse linear systems. The wavelet transformation part of the method can be added as a black box to existing BEM codes.

Numerical results focusing on the sensitivity of the solution for various physical variables to the thresholding parameters, and savings in computer time and memory are presented. The results show that the proposed method is efficient for large problems.

Application of the proposed method is restricted to problems with number of DOF equal to an integer power of 2.

The novel algorithm to solve transformed algebraic linear equations uses NS‐form of the modified matrix, taking the advantage of the hierarchical nature of Multi‐Resolution Analysis (MRA) to decompose a parent system into descendant systems with reduced size. These smaller systems are then solved iteratively using generalized minimal residual method.

This study elicits the critical attributes, consequences and values associated with the purchasing process in the context of cross-border e-commerce (CBEC). The purpose is to provide a better understanding of the fundamental factors that determine consumer values in CBEC.

The study applies the means-end-chain theory and soft-laddering techniques to interview 60 CBEC consumers to construct an implication matrix and a hierarchical value map (HVM) of the consumer purchasing process, consisting of attribute-consequence-value (A-C-V) paths.

By analyzing the significant linkages, elements, ladders and chains in the HVM, four dominant A-C-V paths were identified: economic-driven, efficiency-driven, progress-driven and quality-driven paths.

This study included only Chinese CBEC buyers. This limitation might affect the generalizability of the conclusions as culture, purchase habits and economic development differ between China and other countries.

The results of this study provide CBEC practitioners an understanding of the consumer purchasing process and how consumer values are associated with platform characteristics. Thus, the results aid practitioners in allocating resources and developing CBEC platforms in an appropriate manner and direction.

This study sheds lights on the emerging phenomenon of CBEC. By applying the means-end-chain approach, the study provides a comprehensive HVM for interpreting the consumer online purchasing process in this novel context. By illustrating the dominant paths, this research provides deeper theoretical insights into the specific focuses of CBEC consumer purchasing.