An Exploration of Sustainable Customer Value and the Procedure of the Intelligent Digital Content Analysis Platform for Big Data Using Dynamic Decision Making

The dynamic Parasuraman, Zeithaml and Berry (PZB) service quality model is applied in the analysis of different customer clusters of sustainable customer value, while considering enterprise sustainability, customer relationship management (CRM), and customer equity of customer satisfaction and customer value. Based on intelligent digital content analysis and the recommendation platform of the different customer clusters of sustainable customer value, the dynamic six-sigma method is applied to the leisure agriculture of sustainable key resources and procedures solutions, as well as the impact of environmental and social costs and benefits. Based on the leisure agriculture of sustainable key resources and procedures solutions, the sustainable contradictions of leisure ecotourism agriculture are considered using dynamic multi-criteria decision making (dynamic gray multi-attribute decision making and dynamic multi-objective planning) to analyze the optimal plan for balancing the leisure agriculture of ecotourism and sustainable contradictions. First, sustainable and local identification plans are developed by the dynamic grey multi-attribute decision making method. Next, dynamic multi-objective planning is developed, as based on the priority factors sorted by gray multi-attribute decision making, in order to carry out the decision-making analysis of different objectives under different situations; thereby, helping the development of featured sustainable customer value of local leisure agriculture

Analysis of Life Context of On-Line Group-Buying Population by Dynamic Decision

While it is difficult to avoid uncertainties when shopping on the Internet, trust can reduce customers’ perceived uncertainties, and enhance their willingness and frequency to buy products and services. The difference in time and space information transparency between customers and on-line sellers, as well as the complex unpredictability of network structure, result in frequent uncertainty for on-line transactions. Therefore, through text mining and integrating the Genetic Algorithm (GA) with the Support Vector Machine (SVM), this project classifies the data of on-line group buying community complaints according to the posts left on Facebook and the three major group-buying websites of Taiwan. The terms are selected based on term frequency, document frequency, uniformity, and conformity, while document classification effectiveness is calculated using precision, recall rate, and F-measure. Community complaints are classified into the uncertain performance indicators that influence on-line group buying for integrated statistics, in order that specific performance indicators of community group-buying websites can be generated. Afterwards, based on the on-line group buying community performance indicator sequence, as integrated according to the dynamic Multicriteria Optimization and Compromise Solution (VIKOR) method and prosperity countermeasure signals, grey correlation sorting is applied to analyze the dynamic performance indicator sequence of different communities, in order to determine the life context of different populations for the reference of on-line group buying providers

Analysis of Life Context of On-Line Group-Buying Population by Dynamic Decision

While it is difficult to avoid uncertainties when shopping on the Internet, trust can reduce customers’ perceived uncertainties, and enhance their willingness and frequency to buy products and services. The difference in time and space information transparency between customers and on-line sellers, as well as the complex unpredictability of network structure, result in frequent uncertainty for on-line transactions. Therefore, through text mining and integrating the Genetic Algorithm (GA) with the Support Vector Machine (SVM), this project classifies the data of on-line group buying community complaints according to the posts left on Facebook and the three major group-buying websites of Taiwan. The terms are selected based on term frequency, document frequency, uniformity, and conformity, while document classification effectiveness is calculated using precision, recall rate, and F-measure. Community complaints are classified into the uncertain performance indicators that influence on-line group buying for integrated statistics, in order that specific performance indicators of community group-buying websites can be generated. Afterwards, based on the on-line group buying community performance indicator sequence, as integrated according to the dynamic Multicriteria Optimization and Compromise Solution (VIKOR) method and prosperity countermeasure signals, grey correlation sorting is applied to analyze the dynamic performance indicator sequence of different communities, in order to determine the life context of different populations for the reference of on-line group buying providers

Characterization of the Psychological, Physiological and EEG Profile of Acute Betel Quid Intoxication in Naïve Subjects

Betel quid use and abuse is wide spread in Asia but the physiological basis of intoxication and addiction are unknown. In subjects naïve to the habit of betel quid intoxication, the psychological and physiological profile of intoxication has never been reported. We compared the effect of chewing gum or chewing betel quid, and subsequent betel quid intoxication, on psychological assessment, prospective time interval estimation, numerical and character digit span, computerized 2 choice tests and mental tasks such as reading and mathematics with concurrent monitoring of ECG, EEG and face temperature in healthy, non-sleep deprived, male subjects naïve to the habit of chewing betel quid. Betel quid intoxication, dose dependently induced tachycardia (max 30 bpm) and elevated face temperature (0.7°C) (P<0.001) above the effects observed in response to chewing gum (max 12 bpm and 0.3°C) in 12 subjects. Gross behavioral indices of working memory such as numerical or character digit span in 8 subjects, or simple visual-motor performance such as reaction speed or accuracy in a two choice scenario in 8 subjects were not affected by betel quid intoxication. Betel quid intoxication strongly influenced the psychological aspects of perception such as slowing of the prospective perception of passage of a 1 minute time interval in 8 subjects (P<0.05) and perceived increased arousal (P<0.01) and perceived decreased ability to think (P<0.05) in 31 subjects. The EEG spectral profile recorded from mental states associated with open and closed eyes, and mental tasks such as reading and eyes closed mental arithmetic were significantly modified (P<0.05) relative to chewing gum by betel quid intoxication in 10 subjects. The prevalence of betel quid consumption across a range of social and work settings warrants greater investigation of this widespread but largely under researched drug

Mobile app stores from the user's perspectives

YesThe use of smartphones has become more prevalent in light of the boom in Internet services and Web 2.0 applications. Mobile stores (e.g., Apple’s App Store and Google Play) have been increasingly used by mobile users worldwide to download or purchase different kinds of applications. This has prompted mobile app practitioners to reconsider their mobile app stores in terms of design, features and functions in order to maintain their customers’ loyalty. Due to the lack of research on this context, this study aims to identify factors that may affect users’ satisfaction and continued intention toward using mobile stores. The proposed model includes various factors derived from information systems literature (i.e., usefulness, ease of use, perceived cost, privacy and security concerns) in addition to the dimensions of mobile interactivity (i.e. active control, mobility, and responsiveness). The study sets out 13 hypotheses that include mediating relationships (e.g., perceived usefulness mediates the influence of ease of use, active control, responsiveness and mobility; perceived ease of use mediates the influence of active control). As well as outlining the proposed research method, the research contributions, limitations and future research recommendations are also addressed

Using the Taguchi-Genetic Algorithm to Improve Lithographic Photoresist Operating Conditions of Touch Panels to Upgrade After-Develop Inspection

In order to use touch control products more conveniently, a general objective is to develop lighter and smaller touch panels. A touch panel using the one glass solution (OGS) is an important development. The black matrix (BM) in an OGS touch panel is used as a black frame. The photoresist is divided into a positive photoresist and a negative photoresist. The BM photoresist is negative. After coating, exposure, and development in the BM process, after-develop inspection is implemented to check if the appearance is abnormal. It is quite difficult to rework the negative photoresist process. There is still room for improving the BM photoresist process capability Cpk. Thus, in order to reduce the customer complaint rate and enhance stability, the photolithography process is improved to enhance Cpk. Among the BM black negative photoresist forming process conditions of OGS products, the pre-baking time is the most important process control factor. The method set up herein improves the original Cpk = 0.90. This study employs the fast messy genetic algorithm (fmGA) to select the optimum orthogonal array of the Taguchi method, so as to implement the decision process of optimum parameter design. The Cpk of the optimum parameter is 2.12

Mobile Phone Recommender System Using Information Retrieval Technology by Integrating Fuzzy OWA and Gray Relational Analysis

With the advancement and diversification of information retrieval technology, such technology has been widely applied in recent years in personalized information recommender systems (RSs) and e-commerce RSs in addition to data-mining applications, especially with respect to mobile phone purchases. By integrating the weights of fuzzy ordered weighted averaging (OWA) and gray relational analysis, this research calculated the recommended F1 indices of three weight calculation methods to be 20.5%, 14.36%, and 16.43% after an examination by 30 experimenters. According to the operational results attained by the 30 experimenters, the recommended products obtained by the fuzzy OWA and gray relational analysis calculation method covered the products recommended by the other two weight calculation methods with a higher recommendation effect

Research Article An Analysis of the Optimal Multiobjective Inventory Clustering Decision with Small Quantity and Great Variety Inventory by Applying a DPSO

License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. When an enterprise has thousands of varieties in its inventory, the use of a single management method could not be a feasible approach. A better way to manage this problem would be to categorise inventory items into several clusters according to inventory decisions and to use different management methods for managing different clusters. The present study applies DPSO (dynamic particle swarm optimisation) to a problem of clustering of inventory items.Without the requirement of prior inventory knowledge, inventory items are automatically clustered into near optimal clustering number. The obtained clustering results should satisfy the inventory objective equation, which consists of different objectives such as total cost, backorder rate, demand relevance, and inventory turnover rate. This study integrates the above four objectives into a multiobjective equation, and inputs the actual inventory items of the enterprise into DPSO. In comparison with other clustering methods, the proposed method can consider different objectives and obtain an overall better solution to obtain better convergence results and inventory decisions. 1

c 2013 NSP Natural Sciences Publishing Cor. Analysis of Optimized Logistics Service of 3C Agents in Taiwan Based on ABC-KMDSS

Abstract: 3C (computer, communication, and consumer electronics) distributors in Taiwan provide world-class logistics service quality, as enterprises can provide logistics services for customized products (products with segmented standardization and customized standardization) in the value chain that meet individual customer needs. If enterprises can achieve the objective of providing customers with services in accordance with their individual needs, they are more likely to obtain high customer satisfaction. This study selected multinational 3C distributors in Taiwan as the subjects and their internal MIS (management information system) databases as data sources. Data mining was employed to screen important and relevant information from the MIS databases. The key factors affecting the service quality of customized logistics, as obtained from the benchmarking platform of cost information, were used as the contents of a hierarchical structure. After the information was input into the linear planning model, better solutions were obtained. Moreover, the results were saved in the ABC (activity based costing)-KMDSS (knowledge management decision support system) database. The rules for enterprise operation in the knowledge database, together with data from the ABC-KMDSS database, were used for the CBR (casebased reasoning) method of knowledge reasoning to determine the proper decision-making for logistics services of relevant customized products