Chen T.-H.,National Pingtung Institute of Commerce
Computers and Industrial Engineering | Year: 2011
This study deals with the news-vendor problem to the case of a two-level supply chain consisting of one manufacturer and one retailer, and investigates the combined effects of the cooperative advertising mechanism, the return policy and the channel coordination. The manufacturer and the retailer could maintain the potential market size by making some marketing expenditures on some national brand names and invest in local advertising, but with diminishing returns. The decision problem facing the profit-oriented entities in the supply chain is to determine the optimal advertising and inventory policies for maximizing their own profit. Both the non-cooperative policy and the cooperative policy are formulated to offer structural and quantitative insights into the interplay between upstream and downstream entities of the supply chain. In addition, the implications of a profit-sharing mechanism based on achieving a win-win relationship of the channel members was also proposed. © 2011 Elsevier Ltd. All rights reserved.
Horng M.-H.,National Pingtung Institute of Commerce
Expert Systems with Applications | Year: 2011
Multilevel thresholding is an important technique for image processing and pattern recognition. The maximum entropy thresholding (MET) has been widely applied in the literature. In this paper, a new multilevel MET algorithm based on the technology of the artificial bee colony (ABC) algorithm is proposed: the maximum entropy based artificial bee colony thresholding (MEABCT) method. Four different methods are compared to this proposed method: the particle swarm optimization (PSO), the hybrid cooperative-comprehensive learning based PSO algorithm (HCOCLPSO), the Fast Otsu's method and the honey bee mating optimization (HBMO). The experimental results demonstrate that the proposed MEABCT algorithm can search for multiple thresholds which are very close to the optimal ones examined by the exhaustive search method. Compared to the other four thresholding methods, the segmentation results of using the MEABCT algorithm is the most, however, the computation time by using the MEABCT algorithm is shorter than that of the other four methods. © 2011 Elsevier Ltd. All rights reserved.
Tai Y.-M.,National Pingtung Institute of Commerce
Industrial Management and Data Systems | Year: 2011
Purpose - This paper seeks to investigate the value enterprise customers perceive in information sharing services and the consequences of that perceived value for relationship intention. Design/methodology/approach - An impact model was developed to assess the associations between the functional and relational value perceived by enterprise customers in regards to information sharing services and their relationship commitment and loyalty intention. The model was tested on 81 firms which had participated in e-business projects subsidized by the Taiwan Government. Partial least squares was conducted to assess hypothesized information sharing marketing effects. Findings - The findings suggest that functional and relational value enterprise customers perceive in information sharing services will positively influence their relationship intention. Research limitations/implications - The proposed model provides an expanded view of the marketing effects of an information sharing service. Researchers believe this work to be a starting point for the research of the marketing effects of an information sharing service. Originality/value - The research results of this study reveal that information sharing not only can be used to support supply chain activities (i.e. facilitating supply chain management), but also can be used to support marketing activities (i.e. enhancing customer relationships). © Emerald Group Publishing Limited.
Chang C.L.-H.,National Pingtung Institute of Commerce
Computers in Human Behavior | Year: 2011
The development of information technology has a significant influence on social structure and norms, and also impacts upon human behavior. In order to achieve stability and social harmony, people need to respect various norms, and have their rights protected. Students' information ethics values are of critical and radical importance in achieving this goal. Using qualitative approach, the present study utilizes Kohlberg's CMD model to measure improvement in students' "information ethics values" through "technology mediated learning (TML)" models, and to assess the extent to which it is influenced by gender and Chinese guanxi culture. We find that while e-learning improves female students' "respect rules," "privacy," " accessibility" and "intellectual property" values more than male students, the percentages relating to "intellectual property" for females in the higher stages remain lower than for males. Moreover, these results are interpreted from a Chinese guanxi culture perspective. In light of these results, educators should take account of such improvements when designing effective teaching methods and incentives. © 2011 Elsevier Ltd. All rights reserved.
Lee M.-C.,National Pingtung Institute of Commerce
Computers and Education | Year: 2010
Although e-learning has been prompted to various education levels, the intention to continue using such systems is still very low, and the acceptance-discontinuance anomaly phenomenon (i.e., users discontinue using e-learning after initially accepting it) is a common occurrence. This paper synthesizes the expectation-confirmation model (ECM), the technology acceptance model (TAM), the theory of planned behavior (TPB), and the flow theory to hypothesize a theoretical model to explain and predict the users' intentions to continue using e-learning. The hypothesized model is validated empirically using a sample collected from 363 learners of a Web-based learning program designed for continuing education. The results demonstrate that satisfaction has the most significant effect on users' continuance intention, followed by perceived usefulness, attitude, concentration, subjective norm, and perceived behavior control as significant but weaker predictors. The implications of these findings for e-learning practitioners are discussed at the end of this work. © 2009 Elsevier Ltd. All rights reserved.