Tainan University of Technology

About: Tainan University of Technology is a education organization based out in Tainan City, Taiwan. It is known for research contribution in the topics: Password & Authentication. The organization has 311 authors who have published 641 publications receiving 10826 citations.

Spillover Effects of Tourism Policy Changes on Hospitality Industries

Abstract: This study aimed at using the industry-related spillover model to examine the spillover effects of the change in tourism policy and employed the induced employment model and the gross-induced added value model to measure the employment income, gross added value, and employment creation. Our results showed evidence that the consumption of Chinese tourists visiting Taiwan has brought a substantial impact on the hospitality and restaurant industries. In addition, the economy of scale created in the restaurant industry was smaller than that in the hospitality industry, since Chinese tourists allocated less expenditure for food. However, the spillover effects in the restaurant industry were larger than that in the hospitality industry.

A web-based dss architecture and its forecasting core in supply chain management

Abstract: In a competitive market environment, supply chain management (SCM) has been critical for companies to survive. Demand planning plays an important role in SCM, for it provides accurate demand forecasts which may achieve customer satisfaction by offering benefits such as low inventory level, short lead time, efficient resource allocation, and quick response. To obtain more accurate forecasts, this study presents a web-based Decision Support System (DSS) architecture and its forecasting core. The forecasting core, named Panel Function, contains three modules: Segmentation Module, Forecasting Module, and Coordination Module. The Segmentation Module categorizes customers into three segments: Loyal Customer Segment, Potential Customer Segment, and Switcher Segment. Based on the three segments, the Forecasting Module employs different forecasting and analysis technologies to make an integrated forecast estimate: time-series forecasting to capture the loyal customer demand trend, Bayesian inference to estimate the predicted value of switcher purchase quantity, and questionnaire analysis and brand choice models to unearth potential customers. The results from these three processes are then synthesized to obtain the integrated forecast, which is then used in the Coordination Module as the base of distribution planning, and provides a minimal system-wide total cost solution for all parties in the supply chain. As a whole, this DSS architecture has been shown to provide an efficient mechanism for collaborative demand planning and help create the maximum profit for the supply chain.

Correction to: Basic Conditions of Early Mathematics Education—a Comparison between Germany, Taiwan and Switzerland

Abstract: The original version of this article unfortunately contains incorrect formatting of section 2 sub-headings and Tables 2 to 5 with typing errors in Tables 4 and 5.

Goodness-of-fit tests of generalized linear mixed models for repeated ordinal responses

Abstract: Categorical longitudinal data are frequently applied in a variety of fields, and are commonly fitted by generalized linear mixed models (GLMMs) and generalized estimating equations models. The cumulative logit is one of the useful link functions to deal with the problem involving repeated ordinal responses. To check the adequacy of the GLMMs with cumulative logit link function, two goodness-of-fit tests constructed by the unweighted sum of squared model residuals using numerical integration and bootstrap resampling technique are proposed. The empirical type I error rates and powers of the proposed tests are examined by simulation studies. The ordinal longitudinal studies are utilized to illustrate the application of the two proposed tests.

Using fictitious time integration method to study wave propagation over arbitrary bathymetry

Abstract: In this study, the fictitious time integration method (FTIM) is applied to investigate wave propagation over an arbitrary bathymetry with measured uncertainty. The FTIM is used to convert the higher-order elliptic mild-slope equation (EMSE) into a FTIM like EMSE (FTIMEMSE). It has the advantage to describe wave transformation from deep water to shallow water region in a large coastal area with numerical efficiency. The validity of the noise resistance for the measured uncertainty of the bathymetry is also studied. In addition, typical examples for waves propagating over an elliptic shoal rest on a horizontal and sloping bottom is presented. It is concluded that the FTIM is robust in the numerical stability and capable of against the noise of the measurement.