3,213 research outputs found
HOW CUSTOMER PARTICIPATION CAN DRIVE REPURCHASE INTENT
The purpose of this paper is to examine the impact of customer participation in the service delivery process by designing and testing an empirical model with the customers’ point of view in mind. Data are collected in the context of professional financial insurance services. The proposed model is analyzed with partial least squares (PLS) path modeling in SmartPLS 2.0 software. The results of the study show that customer participation produces positive effects on customer satisfaction and affective commitment through the customer relational value. Affective commitment is a strong predictor of repurchase intent, but no relationship between customer satisfaction and repurchase intent was found. This study suggests that customer participation can be a win-win situation for customers and the service firm. Customers who create relational value with their service providers effectively enjoy their services more and are more likely to build and maintain long-term relationships with their service firm. Our findings highlight the roles of the customer and indicate the heuristic value of viewing customer satisfaction and affective commitment as consequences of customer participation. This can enhance the understanding of how encounters should be designed in order to support employees and improve the co-creation of value
The Development of a Computer Auditing System Sufficient for Sarbanes-Oxley Section 404 - A Study on the Purchasing and Expenditure Cycle of the ERP System
After Section 404 of the Sarbanes-Oxley Act was released, developing an effective computer auditing system became critical for management and auditors. In this study, the researchers used Gowin\u27s Vee, raised as a research strategy by Novak and Gorwin (1984). On the theoretical side, the researchers arranged documents and employed an expert questionnaire to identify 8 operational procedure elements and 34 critical factors for the purchasing and expenditure cycle. The application side was built upon the model. The researchers then developed the computer auditing system based on the developments of this study. To test the suitability of the system, the researchers conducted a case study whose results showed that this system can provide the company owners and their accountants with a simple, continuous, timely, and analytical method which may help them detect promptly any irregular internal control issues, thus identifying measures to improve the condition
A generalized Gaussian process model for computer experiments with binary time series
Non-Gaussian observations such as binary responses are common in some
computer experiments. Motivated by the analysis of a class of cell adhesion
experiments, we introduce a generalized Gaussian process model for binary
responses, which shares some common features with standard GP models. In
addition, the proposed model incorporates a flexible mean function that can
capture different types of time series structures. Asymptotic properties of the
estimators are derived, and an optimal predictor as well as its predictive
distribution are constructed. Their performance is examined via two simulation
studies. The methodology is applied to study computer simulations for cell
adhesion experiments. The fitted model reveals important biological information
in repeated cell bindings, which is not directly observable in lab experiments.Comment: 49 pages, 4 figure
An interactively recurrent functional neural fuzzy network with fuzzy differential evolution and its applications
In this paper, an interactively recurrent functional neural fuzzy network (IRFNFN) with fuzzy differential evolution (FDE) learning method was proposed for solving the control and the prediction problems. The traditional differential evolution (DE) method easily gets trapped in a local optimum during the learning process, but the proposed fuzzy differential evolution algorithm can overcome this shortcoming. Through the information sharing of nodes in the interactive layer, the proposed IRFNFN can effectively reduce the number of required rule nodes and improve the overall performance of the network. Finally, the IRFNFN model and associated FDE learning algorithm were applied to the control system of the water bath temperature and the forecast of the sunspot number. The experimental results demonstrate the effectiveness of the proposed method
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