Browsing by Author "Lin, Chiun-Sin"

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Combined rough set theory and flow network graph to predict customer churn in credit card accounts
(2011-01-01)
Lin, Chiun-Sin
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Tzeng, Gwo-Hshiung
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Chin, Yang-Chieh
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科技管理研究所
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Institute of Management of Technology
Customer churn has become a critical issue, especially in the competitive and mature credit card industry. From an economic and risk management perspective, it is important to understand customer characteristics in order to retain customers and differentiate high-quality credit customers from bad ones. However, studies have not yet adequately introduced rules based on customer characteristics and churn forms of original data. This study uses rough set theory, a rule-based decision-making technique, to extract rules related to customer churn; then uses a flow network graph, a path-dependent approach, to infer decision rules and variables; and finally presents the relationships between rules and different kinds of churn. An empirical case of credit card customer churn is also illustrated. In this study, we collect 21,000 customer samples, equally divided into three classes: survival, voluntary chum and involuntary churn. The data from these samples includes demographic, psychographic and transactional variables for analyzing and segmenting customer characteristics. The results show that this combined model can fully predict customer churn and provide useful information for decision-makers in devising marketing strategy. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.
Corporate Performance Forecasting Using Hybrid Rough Set Theory, Neural Networks, and DEA
(2013-05-01)
Lin, Chiun-Sin
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Lin, Tzu-Yu
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Chiu, Sheng-Hsiung
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管理科學系
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Department of Management Science
This paper proposed the hybrid model using rough set theory (RST), neural networks (NN), and data envelopment analysis (DEA) to predict the corporate performance directly. First, to evaluate corporate performance, the DEA was employed. Second, integrated RST with BPN techniques, which is one of the popular used models of NN, named RST+BPN, was used to build the corporate performance-prediction model and the corporate governance variables are used as predictive variables. This hybrid method enabled us to evaluate an individual firm and provided performance information without comparing it with other companies. The experimental result showed that the proposed model outperforms the NN model with nonextracted predictive variables and provides a promising alternative in corporate performance prediction.
Empirical mode decomposition-based least squares support vector regression for foreign exchange rate forecasting
(2012-11-01)
Lin, Chiun-Sin
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Chiu, Sheng-Hsiung
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Lin, Tzu-Yu
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管理科學系
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Department of Management Science
To address the nonlinear and non-stationary characteristics of financial time series such as foreign exchange rates, this study proposes a hybrid forecasting model using empirical mode decomposition (EMD) and least squares support vector regression (LSSVR) for foreign exchange rate forecasting. EMD is used to decompose the dynamics of foreign exchange rate into several intrinsic mode function (IMF) components and one residual component. LSSVR is constructed to forecast these IMFs and residual value individually, and then all these forecasted values are aggregated to produce the final forecasted value for foreign exchange rates. Empirical results show that the proposed EMD-LSSVR model outperforms the EMD-ARIMA (autoregressive integrated moving average) as well as the LSSVR and ARIMA models without time series decomposition. (C) 2012 Elsevier B.V. All rights reserved.
Grey forecasting model for CO(2) emissions: A Taiwan study
(2011-11-01)
Lin, Chiun-Sin
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Liou, Fen-May
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Huang, Chih-Pin
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管理科學系
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Department of Management Science
Among the various greenhouse gases associated with climate change. CO(2) is the most frequently implicated in global warming. The latest data from Carbon Monitoring for Action (CARMA) shows that the coal-fired power plant in Taichung. Taiwan emitted 39.7 million tons of CO(2) in 2007 - the highest of any power plant in the world. Based on statistics from Energy International Administration, the annual CO(2) emissions in Taiwan have increased 42% from 1997 until 2006. Taiwan has limited natural resources and relies heavily on imports to meet its energy needs, and the government must take serious measures control energy consumption to reduce CO(2) emissions. Because the latest data was from 2009, this study applied the grey forecasting model to estimate future CO(2) emissions in Taiwan from 2010 until 2012. Forecasts of CO(2) emissions in this study show that the average residual error of the GM(1,1) was below 10%. Overall, the GM(1,1) predicted further increases in CO(2) emissions over the next 3 years. Although Taiwan is not a member of the United Nations and is not bound by the Kyoto Protocol, the findings of this study provide a valuable reference with which the Taiwanese government could formulate measures to reduce CO(2) emissions by curbing the unnecessary the consumption of energy. (C) 2011 Elsevier Ltd. All rights reserved.
Grey forecasting model for CO2 emissions: A Taiwan study
(2011-11-01)
Lin, Chiun-Sin
;
Liou, Fen-May
;
Huang, Chih-Pin
;
管理科學系
;
Department of Management Science
Among the various greenhouse gases associated with climate change. CO2 is the most frequently implicated in global warming. The latest data from Carbon Monitoring for Action (CARMA) shows that the coal-fired power plant in Taichung. Taiwan emitted 39.7 million tons of CO2 in 2007 - the highest of any power plant in the world. Based on statistics from Energy International Administration, the annual CO2 emissions in Taiwan have increased 42% from 1997 until 2006. Taiwan has limited natural resources and relies heavily on imports to meet its energy needs, and the government must take serious measures control energy consumption to reduce CO2 emissions. Because the latest data was from 2009, this study applied the grey forecasting model to estimate future CO2 emissions in Taiwan from 2010 until 2012. Forecasts of CO2 emissions in this study show that the average residual error of the GM(1,1) was below 10%. Overall, the GM(1,1) predicted further increases in CO2 emissions over the next 3 years. Although Taiwan is not a member of the United Nations and is not bound by the Kyoto Protocol, the findings of this study provide a valuable reference with which the Taiwanese government could formulate measures to reduce CO2 emissions by curbing the unnecessary the consumption of energy. (C) 2011 Elsevier Ltd. All rights reserved.
Measuring competitive advantage with an asset-light valuation model
(2011-07-04)
Lin, Chiun-Sin
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Huang, Chih-Pin
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管理科學系
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Department of Management Science
Defining competitive advantage as the ability of a firm to generate returns in excess of its synthetic normal returns; the present study develops an "asset-light" valuation model to capture intangible strategic resources, that do not appear on balance sheets and could explain abnormal returns. Three propositions are derived from the model: (1) firms emphasizing light assets over tangible assets, generate superior performance; (2) at a given level of synthetic normal returns, firms possessing more "light" assets have superior performance; and (3) to achieve a given book rate of return, firms with more light assets require fewer tangible assets as inputs. An empirical study of the global semiconductor industry significantly supports all three propositions. The results show that, the excess returns observed across an industry reflect heterogeneity in the "light assets" possessed by the firms, and provide an explanation for observed differences in performance.
Optimal promotional time for maximum sales response with an initial market share in internet marketing
(2011-06-18)
Lin, Chiun-Sin
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Chiang, Chi
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Chin, Shun-Peng
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管理科學系
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Department of Management Science
Most products usually have an initial market share at the beginning in marketing. In order to increase and maximize sales response, sellers can set an optimal promotional time limit. This paper aims to explain how an existing initial market share with vital parameters affects the range and shape of sales response curve to reach optimal promotional time. We use two opposite negative exponential growth functions to build a mathematical model, apply decision calculus to determine parameters, and optimize promotional time limits for maximum sales response. We demonstrate real numerical examples of e-mail marketing by using functions with or without an initial response. Furthermore, we also conduct sensitivity analyses to compare different optimal time limits by various response rates. This paper contributes to the field by providing a sales response model with an initial market share and can be applied to the general one force or two forces cases with vital capacity parameter and exponential growth coefficient to get more elastic, adequate, and complete results.
Optimizing time limits for maximum sales response in Internet shopping promotions
(2011-01-01)
Chiang, Chi
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Lin, Chiun-Sin
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Chin, Shun-Peng
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管理科學系
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Department of Management Science
Sellers usually set a promotional time limit to ensure that products can be sold as soon as possible in Internet markets. This research attempts to build a decision support system that optimizes the time limit for maximum sales response or profit in Internet shopping promotions. We decompose the effect of time limits into two opposing forces, which are the awareness and urgency of a promotional offer that are depicted as hyperbolic S-shaped functions. Using the decision calculus approach, we can determine the optimal promotional time limit with different input parameters. We illustrate the use of the proposed system with real world examples and conduct some sensitivity analyses. We compare our numerical results from hyperbolic functions with those from simple exponential functions; we find that hyperbolic functions yield more appropriate promotional time limits on Internet. This research contributes to the field of decision support by providing a new approach to determining the optimal time limit for online sales promotions. (C) 2010 Elsevier Ltd. All rights reserved.
Recommendation sources on the intention to use e-books in academic digital libraries
(2010)
Lin, Chiun-Sin
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Tzeng, Gwo-Hshiung
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Chin, Yang-Chieh
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Chang, Chiao-Chen
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管理科學系
Purpose - Few library studies have investigated recommendation classifications for e-book (electronic book) usage, while none have directly compared what recommendation sources (word-of-mouth, advertising, and expert recommendation) might influence e-book usage intentions. To fill this gap in the literature, the main purposes of this study are to: examine how users perceive the influence of recommendations on the intention to use e-books for academic purposes; and to measure the level of the perception of trust and perceived risk when users receive e-book recommendations from peers, advertisers, and experts. Design/methodology/approach - Data for this study were collected from 382 academic digital library users between the ages of 18 and 25. A multiple regression analysis was then conducted to identify the key causal relationships. Findings - The comparison of three recommendation sources (word-of-mouth, advertising, and expert recommendations) revealed that word-of-mouth (WOM) played a more important role than other recommendations in determining the intention to use e-books in an academic digital library. In addition, enhancing the perceived trust and reducing the risk towards the use of e-books can mediate the relationship between recommendation sources and the behavioural intentions to use e-books. Research limitations/implications - This study assessed self-reported behavioural intention as part of its survey and, as a result, could have introduced unintentional inaccuracies. Practical implications - Librarians should emphasise e-book advantages (e.g. easy searching, easily accessible index) to get positive recommendation if users follow all of the recommendations of the source. They can also create online discussion forums to provide usage intention discussions, which can influence users' perceptions of trust and risk and increase the willingness of potential users to read e-books. Originality/value - Little has been written on the intentions of using e-books. Therefore, this conceptual model is novel. This model is also useful in explaining how recommendations stimulate the intentions of using e-books by enhancing the perceived trust and reducing the perceived risk; these findings may generally be applicable to librarians, current users, and potential users.
The Impact of Recommendation Sources on the Adoption Intention of Microblogging Based on Dominance-based Rough Set Approach
(2010)
Chin, Yang-Chieh
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Chang, Chaio-Chen
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Lin, Chiun-Sin
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Tzeng, Gwo-Hshiung
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管理科學系
Microblogging is a social media tool that allows users to write short text messages to public and private networks. This research focuses specifically on the microblogging on Facebook. The main purposes of this study are to investigate and compare what recommendation sources influence the intention to use microbloggings and to combine gender, daily internet hour usage and past use experience to infer the usage of microbloggings decision rules using a dominance-based rough-set approach (DRSA). Data for this study were collected from 382 users and potential users. The analysis is grounded in the taxonomy of induction-related activities using DRSA to infer the usage of microbloggings decision rules. Finally, the study of the nature of microblogging reflects essential practical and academic value.