What Makes Usage of Mobile Data Service Increase or Decrease: Perspective of Two-Factor Theory

This study is to investigate factors that affect usage change in mobile data service (MDS). The central claim of this paper is that influencing forces of usage increase in MDS are different from those of usage decrease. We propose that information quality as the motivator (forces of usage increase) and system quality as the de-motivator (forces of usage decrease) of MDS. A research model is proposed and subsequent hypotheses are empirically tested with partial least square (PLS) based on 478 responses from the users of mobile data service. We have found that information quality (as a motivator) is positively associated with usage increase in mobile data service, but system quality (as a de-motivator) is not. Also, system quality is negatively associated with usage decrease, but information quality is not. Despite the recognized limitations, our study highlights the potential value of the two-factor theory in explaining user behaviors associated with mobile data services

An Empirical Study on the Importance of Psychological Contract Commitment in Information Systems Outsourcing

In IS outsourcing relationship literature, research has focused on detailed legal contracts and partnerships. We investigate the role of psychological contracts between client and vendor in the IS outsourcing context. The aim of this paper is to put the concept “psychological contract commitment” (PCC) under the spotlight, finding out its mediating effects between legal contracts/partnerships and IS outsourcing success. By analyzing 50 matched survey responses gathered from project managers, vendor firms, and end-users, we found that psychological contract commitment has both direct and mediating effects on outsourcing success. Along the same lines, the key findings suggest that psychological contract commitment explains why legal contracts and partnerships are still crucial to IS outsourcing success

맏국과 미국 매획맹들의 깨요]멀 특성여| 따른 01 가해도 ~t 이

Korean language journalThe purpose of this study was to examine for the deference of leisure activities attitude compared with Korean and America university students' characteristics of leisure activities attitude in subcategory factors of leisure activities attitude include recognitive attitude, definitive attitude, behavioral attitude. 241 M,H,Y university students in Korea and 143 North Carolina N university students are responded survey for this study from 2007, May to August. The collected data based of survey are analyzed through frequency analysis, t- test, one-way ANOV A analysis by SPSS WIN ver 12.0. The result is following : First, there were statistical difference of leisure activities attitude in behavioral attitude between Korean students and America students. Second, there were statistical difference shows difference grade sector, own major, personal expenses in recognitive attitude. Third, the statistical difference shows grade sector, personal expenses in definitive attitude. Forth, the statistical difference shows grade sector, own major and personal expenses in of behavioral attitude

Structural Optimization of a Knuckle with Consideration of Stiffness and Durability Requirements

The automobile’s knuckle is connected to the parts of the steering system and the suspension system and it is used for adjusting the direction of a rotation through its attachment to the wheel. This study changes the existing material made of GCD45 to Al6082M and recommends the lightweight design of the knuckle as the optimal design technique to be installed in small cars. Six shape design variables were selected for the optimization of the knuckle and the criteria relevant to stiffness and durability were considered as the design requirements during the optimization process. The metamodel-based optimization method that uses the kriging interpolation method as the optimization technique was applied. The result shows that all constraints for stiffness and durability are satisfied using A16082M, while reducing the weight of the knuckle by 60% compared to that of the existing GCD450

Wasserstein Geodesic Generator for Conditional Distributions

Generating samples given a specific label requires estimating conditional distributions. We derive a tractable upper bound of the Wasserstein distance between conditional distributions to lay the theoretical groundwork to learn conditional distributions. Based on this result, we propose a novel conditional generation algorithm where conditional distributions are fully characterized by a metric space defined by a statistical distance. We employ optimal transport theory to propose the \textit{Wasserstein geodesic generator}, a new conditional generator that learns the Wasserstein geodesic. The proposed method learns both conditional distributions for observed domains and optimal transport maps between them. The conditional distributions given unobserved intermediate domains are on the Wasserstein geodesic between conditional distributions given two observed domain labels. Experiments on face images with light conditions as domain labels demonstrate the efficacy of the proposed method