Browsing by Author "Hung, Hui-Chih"

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A membership pricing policy to facilitate service scale-expansion
(2017-01-01)
Hung, Hui-Chih
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Chung, Chung-Yu
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Wu, Muh-Cherng
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Shen, Wan-Ling
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工業工程與管理學系
This paper proposes a multi-year membership pricing policy for a service business like a gym chain. In the pricing policy, the equivalent membership price per year is relatively low to attract customers, and the multi-year membership fees must be prepaid in full. The prepaid cash provides resources for scale-expansion by opening new stores. We develop a nonlinear mixed integer programming model to formulate the pricing decisions. Numerical experiments reveal that the multi-year membership pricing policy, from a long-term perspective, is substantially better than the business-as-usual pricing policy (1-year membership) in cash balance, profit, and market share. Yet, the performances of the two pricing policies do not differ much from a short-term perspective. These findings indicate that the multi-year pricing policy may be a good strategy, because it initially attracts less attention of competitors; suddenly it emerges and substantially outperforms its competitors in cash balance, profit, and market share.
A modified Lotka-Volterra model for competition forecasting in Taiwan\'s retail industry
(2014-11-01)
Hung, Hui-Chih
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Tsai, Yun-San
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Wu, Muh-Cherng
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工業工程與管理學系
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Department of Industrial Engineering and Management
The retail industry is an important component of the supply chain of the goods and services that are consumed daily and competition has been increasing among retailers worldwide. Thus, forecasting the degree of retail competition has become an important issue. However, seasonal patterns and cycles in the level of retail activity dramatically reduce forecasting accuracy. This paper attempts to develop an improved forecasting methodology for retail industry competition subject to seasonal patterns and cycles. Using market share data and the moving average method, a modified Lotka-Volterra model with an additional constraint on the summation of market share is proposed. Furthermore, the mean absolute error is used to measure the forecasting accuracy of the market share. Real Taiwanese retail data from 1999 is used to validate the forecasting accuracy of our modified Lotka-Volterra model. Our methodology successfully mitigates errors from seasonal patterns and cycles and outperforms other benchmark models. These benchmarks include the Bass and Lotka-Volterra models for revenue or market share data, with or without using the moving average method. Our methodology assists the retail industry in the development of management strategies and the determination of investment timing. We also demonstrate how the Lotka-Volterra model can be used to forecast the degree of industry competition. (C) 2014 Elsevier Ltd. All rights reserved.
A Modified Lotka-Volterra Model for Diffusion and Substitution of Multigeneration DRAM Processing Technologies
(2017-01-01)
Hung, Hui-Chih
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Chiu, Yu-Chih
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Wu, Muh-Cherng
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工業工程與管理學系
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Department of Industrial Engineering and Management
We attempt to develop an effective forecasting model for the diffusion and substitution of multigeneration Dynamic Random Access Memory (DRAM) processing technologies. We consider market share data and propose a modified Lotka-Volterramodel, in which an additional constraint on the summation of market share is introduced. The mean absolute error is used to measure the accuracy of our market share predictions. Market share data in DRAM industries from quarter one (Q1) of 2005 to 2013 Q4 is collected to validate the prediction accuracy. Our model significantly outperforms other benchmark forecasting models of both revenue and market share data, including the Bass and Lotka-Volterra models. Compared to prior studies on forecasting the diffusion and substitution of multigeneration technologies, our model has two new perspectives: (1) allowing undetermined number of multigeneration technologies and inconsecutive adoption of new technologies and (2) requiring less data for forecasting newborn technologies.
An enhanced application of Lotka-Volterra model to forecast the sales of two competing retail formats
(2017-07-01)
Hung, Hui-Chih
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Chiu, Yu-Chih
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Huang, Huang-Chen
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Wu, Muh-Cherng
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工業工程與管理學系
This research develops a sales forecasting model that can analyze the interaction effects of two retail competing formats (convenience-oriented vs. budget-oriented formats). A traditional approach to making such a forecast is based on the Lotka-Volterra equations (also called the LV-model). The LV-model assumes that the population of each species is affected by its self-growth, internal interaction within the species, and external interaction with other species. Most prior studies in business applications directly use sales data as input to the LV-model. The prior approach may result in misleading conclusions when sales data are embedded with seasonal variation, because this variation is not addressed in the original development of the LV-model. Therefore, this study proposes a forecasting framework (an enhanced application of the LV-model). The sales data of each retail format is considered as a compound data, which is decomposed into three individual components: (1) aggregate, (2) competition, and (3) seasonal components. The LV-model is used to forecast the competition component; the other two components are forecasted by typical time series methods; and the data of three components are finally combined into one. Empirical study indicates that the proposed method substantially outperforms the prior approach in terms of forecasting errors (4.4% vs. 16.7% for convenience-oriented and 5.8% vs. 16.2% for budget oriented). In addition, the proposed method reveals a more convincing predator-prey relationship between the two retail formats, which concludes that the convenience-oriented is the predator. To the opposite, the prior approach, concluding that the budget-oriented is the predator, is quite doubtful because the convenience-oriented shall be preferred while the GDP grows over time. This research makes a contribution in how to appropriately apply the LV-model in forecasting revenue and analyzing the interaction effects of two competing business species. (C) 2017 Elsevier Ltd. All rights reserved.
Analysis of Competition Between IDM and Fabless-Foundry Business Models in the Semiconductor Industry
(2017-08-01)
Hung, Hui-Chih
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Chiu, Yu-Chih
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Wu, Muh-Cherng
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工業工程與管理學系
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Department of Industrial Engineering and Management
Three major business models are found in the semiconductor industry, namely, the integrated device manufacturer (IDM), fabless, and foundry models. IDMs design and manufacture integrated circuits (ICs), fabless companies focus only on IC design, and foundry companies are concerned only with IC manufacturing. The business model resulting when fabless and foundry companies form a strategic alliance is called the fabless-foundry model. Recently, the revenue growth rate of the fabless-foundry model has been considerably higher than that of IDM. This raises the question of whether the fabless- foundry model will ultimately dominate the semiconductor industry or grow only to a certain extent. To investigate this, we adopted the Hodrick-Prescott filter to remove the cyclic signal from original revenue data and then applied the Lotka-Volterra model to analyze the competition and cooperation relationships between pairs of these business models. The results reveal that the fabless and foundry models have a mutualistic relationship, whereas IDM competes with both the fabless and foundry models. IDM and the fabless- foundry model compete, but their revenues should ultimately arrive at an equilibrium point. In the long term, IDM and the fabless- foundry model should coexist; the ultimate market share of IDM is predicted to be approximately 55% and that of the fabless- foundry model approximately 45%.
Dynamic inventory rationing for systems with multiple demand classes and general demand processes
(2012-09-01)
Hung, Hui-Chih
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Chew, Ek Peng
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Lee, Loo Hay
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Liu, Shudong
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工業工程與管理學系
"We consider the dynamic rationing problem for inventory systems with multiple demand classes and general demand processes. We assume that backorders are allowed. Our aim is to find the threshold values for this dynamic rationing policy. For single period systems, dynamic critical level policy is developed and the detailed cost approximation subject to this policy is derived. For multiperiod systems, a dynamic rationing policy with periodic review is proposed. The numerical study shows that our dynamic critical level policies are close to being optimal for various parameter settings. (C) 2012 Elsevier B.V. All rights reserved."
Minimal Antizyme Peptide Fully Functioning in the Binding and Inhibition of Ornithine Decarboxylase and Antizyme Inhibitor
(2011-09-09)
Hsieh, Ju-Yi
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Yang, Jung-Yen
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Lin, Chih-Li
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Liu, Guang-Yaw
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Hung, Hui-Chih
Antizyme (AZ) is a protein with 228 amino acid residues that regulates ornithine decarboxylase (ODC) by binding to ODC and dissociating its homodimer, thus inhibiting its enzyme activity. Antizyme inhibitor (AZI) is homologous to ODC, but has a higher affinity than ODC for AZ. In this study, we quantified the biomolecular interactions between AZ and ODC as well as AZ and AZI to identify functional AZ peptides that could bind to ODC and AZI and inhibit their function as efficiently as the full-length AZ protein. For these AZ peptides, the inhibitory ability of AZ_95-228 was similar to that of AZ_WT. Furthermore, AZ_95-176 displayed an inhibition (IC(50): 0.20 mu M) similar to that of AZ-95-228 (IC(50): 0.16 mM), even though a large segment spanning residues 177-228 was deleted. However, further deletion of AZ_95-176 from either the N-terminus or the C-terminus decreased its ability to inhibit ODC. The AZ_100-176 and AZ_95-169 peptides displayed a noteworthy decrease in ability to inhibit ODC, with IC(50) values of 0.43 and 0.37 mM, respectively. The AZ_95-228, AZ_100-228 and AZ_95-176 peptides had IC(50) values comparable to that of AZ_WT and formed AZ-ODC complexes with K(d,AZ-ODC) values of 1.5, 5.3 and 5.6 mu M, respectively. Importantly, our data also indicate that AZI can rescue AZ peptide-inhibited ODC enzyme activity and that it can bind to AZ peptides with a higher affinity than ODC. Together, these data suggest that these truncated AZ proteins retain their AZI-binding ability. Thus, we suggest that AZ_ 95-176 is the minimal AZ peptide that is fully functioning in the binding of ODC and AZI and inhibition of their function.
Preemptive parallel-machine scheduling problem of maximizing the number of on-time jobs
(2019-08-01)
Hung, Hui-Chih
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Lin, Bertrand M. T.
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Posner, Marc E.
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Wei, Jun-Min
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工業工程與管理學系
This paper investigates the classical preemptive parallel-machine scheduling problem of maximizing number of on-time jobs. While the problem is known to be NP-hard, no theoretical analysis of approximation algorithms exists in the literature. As part of the analysis, a new non-standard mixed integer formulation is developed. We propose heuristics based on different design strategies. These heuristics have asymptotically tight relative errors of 1/2. Experimental tests evaluate the computational performance of the procedures.