Aplikasi Structural Equation Modelling Dalam Perencanaan Strategi Pemasaran Berbasis Kepemimpinan Dan Budaya Organisasi (Studi Kasus UKM Batik Tradisional)

Persaingan USAha pada kelompok UKM Batik tradisional semakin lama semakin ketat. Hal ini menuntut Perusahaan untuk merancang strategi bersaing yang sesuai dengan kemampuan internal Perusahaan dan tuntutan eksternal lingkungan persaingan. Salah satu aktivitas penting dalam menjabarkan strategi bersaing kedalam strategi fungsional pemasaran adalah dengan mengembangkan budaya unggul pada semua entitas organisasi USAha tersebut. Budaya dan gaya kepemimpinan pemilik Perusahaan akan mempengaruhi pilihan UKM Batik tersebut dalam strategi bersaingnya, khususnya strategi pemasaran produk mereka. Penelitian ini menggunakan metode Structural Equation Modelling (SEM) yang akan digunakan untuk memeriksa validitas dari faktor-faktor konfirmatori yang berupa variabel-variabel pembentuk gaya kepemimpinan seperti kharisma, inspirasi, stimulus intelektual, dan perhatian individual serta faktor-faktor budaya organisasi seperti simbol material, perilaku, linguistik, dan individu. SEM juga digunakan untuk menguji model berkaitan dengan hubungan antar variabel laten yang sesuai analisis path, serta mendapat model terstruktur yang bermanfaat untuk memperkirakan strategi pemasaran yang sesuai. Dari variabel-variabel pembentuk gaya kepemimpinan, maka faktor stimulus intelektual (=0,37) memiliki pengaruh yang sangat dominan terhadap strategi pemasaran. Dari sisi faktor-faktor budaya organisasi, maka faktor simbol perilaku (=0,69) memiliki peran dominan. Berdasarkan hasil analisis SWOT dengan IFAS = 1,4 dan EFAS = 0,75, maka grand strategi agresif dirasa tepat diaplikasikan. Beberapa strategi yang direkomendasikan adalah penetrasi pasar, pengembangan pasar, pengembangan produk, integrasi dan diversifikasi produk

Some nonlinear second order equation modelling rocket motion

In this paper, we consider a nonlinear second order equation modelling rocket motion in the gravitational field obstructed by the drag force. The proofs of the main results are based on topological fixed point approach.Comment: 8 page

General tooth boundary conditions for equation free modelling

We are developing a framework for multiscale computation which enables models at a ``microscopic'' level of description, for example Lattice Boltzmann, Monte Carlo or Molecular Dynamics simulators, to perform modelling tasks at ``macroscopic'' length scales of interest. The plan is to use the microscopic rules restricted to small "patches" of the domain, the "teeth'', using interpolation to bridge the "gaps". Here we explore general boundary conditions coupling the widely separated ``teeth'' of the microscopic simulation that achieve high order accuracy over the macroscale. We present the simplest case when the microscopic simulator is the quintessential example of a partial differential equation. We argue that classic high-order interpolation of the macroscopic field provides the correct forcing in whatever boundary condition is required by the microsimulator. Such interpolation leads to Tooth Boundary Conditions which achieve arbitrarily high-order consistency. The high-order consistency is demonstrated on a class of linear partial differential equations in two ways: firstly through the eigenvalues of the scheme for selected numerical problems; and secondly using the dynamical systems approach of holistic discretisation on a general class of linear \textsc{pde}s. Analytic modelling shows that, for a wide class of microscopic systems, the subgrid fields and the effective macroscopic model are largely independent of the tooth size and the particular tooth boundary conditions. When applied to patches of microscopic simulations these tooth boundary conditions promise efficient macroscale simulation. We expect the same approach will also accurately couple patch simulations in higher spatial dimensions.Comment: 22 page

Interacting single-file system: Fractional Langevin formulation versus diffusion-noise approach

We review the latest advances in the analytical modelling of single file diffusion. We focus first on the derivation of the fractional Langevin equation that describes the motion of a tagged file particle. We then propose an alternative derivation of the very same stochastic equation by starting from the diffusion-noise formalism for the time evolution of the file density

qˉq{\bar {q}}q condensate for light quarks beyond the chiral limit

We determine the ${\bar{q}}q$ condensate for quark masses from zero up to that of the strange quark within a phenomenologically successful modelling of continuum QCD by solving the quark Schwinger-Dyson equation. The existence of multiple solutions to this equation is the key to an accurate and reliable extraction of this condensate using the operator product expansion. We explain why alternative definitions fail to give the physical condensate.Comment: 13 pages, 8 figure

A framework for power analysis using a structural equation modelling procedure

BACKGROUND: This paper demonstrates how structural equation modelling (SEM) can be used as a tool to aid in carrying out power analyses. For many complex multivariate designs that are increasingly being employed, power analyses can be difficult to carry out, because the software available lacks sufficient flexibility. Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used. METHODS: The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis. CONCLUSIONS: The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres