Julie Yu-Chih Liu

Bio: Julie Yu-Chih Liu is an academic researcher from Yuan Ze University. The author has contributed to research in topics: Project management & Information system. The author has an hindex of 15, co-authored 34 publications receiving 910 citations. Previous affiliations of Julie Yu-Chih Liu include Southern Methodist University.

An accelerated approach for solving fuzzy relation equations with a linear objective function

Abstract: In literature, the optimization model with a linear objective function subject to fuzzy relation equations has been converted into a 0-1 integer programming problem by Fang and Li (1999). They proposed a jump-tracking branch-and-bound method to solve this 0-1 integer programming problem. In this paper, we propose an upper bound for the optimal objective value. Based on this upper bound and rearranging the structure of the problem, we present a backward jump-tracking branch-and-bound scheme for solving this optimization problem. A numerical example is provided to illustrate our scheme. Furthermore, testing examples show that the performance of our scheme is superior to the procedure in the paper by Fang and Li. Several testing examples show that our initial upper bound is sharp.

The impact of financial services quality and fairness on customer satisfaction

Abstract: Purpose – Customer satisfaction in the banking industry has long been measured as a function of service quality by using a variation of the SERVQUAL instrument. The purpose of this paper is to build a broader understanding of the determinants of customer satisfaction throughout the financial services industry by incorporating the perceptions of fairness in service delivery (FAIRSERV) and outlining why and how FAIRSERV is important to customer satisfaction.Design/methodology/approach – The authors conduct a cross‐sectional questionnaire survey, including samples of 420 customers from the financial services industry in Taiwan. PLS‐Graph is used to evaluate the measures of reliability as well as validities, and to test the hypotheses.Findings – The results show that fair service not only has a significant impact on customer satisfaction, but also plays a role equivalent to service quality in determining customers’ trust and perceived value, which in turn lead to customer satisfaction.Research limitations/imp...

Privacy preserving association rule mining in vertically partitioned data

Abstract: A privacy preserving association rule mining algorithm was introducedThis algorithm preserved privacy of individual values by computing scalar productMeanwhile the algorithm of computing scalar product was given and the security was analyzed

Systems analysis and design

Abstract: Dr. Ashenhurst set the tone of the session by saying that the panel would discuss systems analysis in the industrial management sense, "With a view toward coordinating educational programs with management needs".

Restoring a Sense of Control during Implementation: How User Involvement leads to System Acceptance.

Abstract: User involvement has long been considered a critical component of effective system implementation. However, the perspective has suffered from mixed results of empirical tests and the lack of a theoretical explanation for the relationship (Ives and Olson, 1984; Baroudi, et al., 1986). Our purpose is to present a theoreticallygrounded perspective to account for effects of involving users during implementation, and to provide an initial test of this perspective. We propose that: (1) system implementation represents a threat to users’ perceptions of control over their work and a period of transition during which users must cope with differences between old and new work systems; (2) user involvement is effective because it restores or enhances perceived control. Results of a field experiment designed as a preliminary test of this perspective are discussed.

Time Series Analysis Using Composite Multiscale Entropy

Abstract: Multiscale entropy (MSE) was recently developed to evaluate the complexity of time series over different time scales. Although the MSE algorithm has been successfully applied in a number of different fields, it encounters a problem in that the statistical reliability of the sample entropy (SampEn) of a coarse-grained series is reduced as a time scale factor is increased. Therefore, in this paper, the concept of a composite multiscale entropy (CMSE) is introduced to overcome this difficulty. Simulation results on both white noise and 1/f noise show that the CMSE provides higher entropy reliablity than the MSE approach for large time scale factors. On real data analysis, both the MSE and CMSE are applied to extract features from fault bearing vibration signals. Experimental results demonstrate that the proposed CMSE-based feature extractor provides higher separability than the MSE-based feature extractor.