Browsing by Author "Lai, Cheng-Yang"

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A Diffusing Path Planning Mechanism for Marketing Information Propagation over Social Media
(2013-01-01)
Li, Yung-Ming
;
Lai, Cheng-Yang
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Social media are gaining importance as a component of marketing strategies. Many of them, such as social networking site, blogosphere, and microblogosphere, have been seeking business opportunities and establishing brand expression in recent years. Online marketing information diffusion becomes the critical business model for online social networks. Marketers attempt to diffuse advertisements for reaching potential customers through the Internet. However, current marketing research discovered possible influencers but not appropriate support them to diffuse advertisements. In this research, a diffusing path planning mechanism for advertisement was developed for supporting influencers to propagate marketing information and supporting marketers to evaluate possible reward under different marketing strategies.
A diffusion planning mechanism for social marketing
(2017-07-01)
Li, Yung-Ming
;
Lai, Cheng-Yang
;
Lin, Lien-Fa
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Social media is gaining importance as a component of marketing strategies. Many types of social media, such as social networking sites, blogospheres and micro-blogospheres, have been seeking business opportunities and establishing brand expression in the recent years. Online marketing information diffusion has become the critical business model of online social networks. However, most of the current marketing studies on discovering potential influences do not appropriately support them to diffuse advertisements. Therefore, marketing information may be lost during the diffusion process and cannot be sent to potential customers successfully. In this research, a diffusion path planning mechanism for advertisements is developed to help influencers to propagate marketing information and help marketers to evaluate possible rewards under different marketing strategies. Our experimental results show that the proposed mechanism can significantly improve the diffusion process of advertising messages and decrease marketing uncertainty. (C) 2016 Elsevier B.V. All rights reserved.
A social appraisal mechanism for online purchase decision support in the micro-blogosphere
(2014-03-01)
Li, Yung-Ming
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Lai, Cheng-Yang
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Owing to the plentiful participation of knowledgeable users, an online social network could be seen as a large group of experts that support the decisions of online users. Collective opinions solicited from friends are largely beneficial for online purchase support and can create significant opportunities for sales. In this paper, a social appraisal mechanism composed using the methodologies of social companionship analysis, collective opinion analysis, and consensus decision analysis is proposed for the online users of the micro-blogosphere. The proposed mechanism can successfully summarize collective opinions and expedite the decision-making process that characterizes users' purchasing behaviors. (C) 2013 Elsevier B.V. All rights reserved.
A social recommender mechanism for e-commerce: Combining similarity, trust, and relationship
(2013-06-01)
Li, Yung-Ming
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Wu, Chun-Te
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Lai, Cheng-Yang
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Online business transactions and the success of e-commerce depend greatly on the effective design of a product recommender mechanism. This study proposes a social recommender system that can generate personalized product recommendations based on preference similarity, recommendation trust, and social relations. Compared with traditional collaborative filtering approaches, the advantage of the proposed mechanism is its comprehensive consideration of recommendation sources. Accordingly, our experimental results show that the proposed model outperforms other benchmark methodologies in terms of recommendation accuracy. The proposed framework can also be effectively applied to e-commerce retailers to promote their products and services. (C) 2013 Elsevier B.V. All rights reserved.
A social referral appraising mechanism for the e-marketplace
(2017-04-01)
Lai, Cheng-Yang
;
Li, Yung-Ming
;
Lin, Lien-Fa
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
With the popularity of social media, in order to achieve word-of-mouth marketing, many marketers and individual sellers are actively engaged in achieving positive ratings in the e-marketplace. Although many seller review mechanisms have been developed, e-commerce market operators and consumers still face trust fraud issues. Trust is one of the major issues that confuse online purchase activities. In this paper, we develop a social referral mechanism to verify sellers based on the experiences of friends within a buyer's social network. The proposed framework estimates the trust values of sellers from the perspective of the social network in order to stop buyers from making transactions with fraudulent sellers in the online marketplace. (C) 2016 Elsevier B.V. All rights reserved.
A Social Referral Mechanism on e-Marketplace
(2013-01-01)
Lai, Cheng-Yang
;
Li, Yung-Ming
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
With the popularity of social media, in order to achieve the word-of-mouth marketing, many marketers and individual sellers are actively engaged in getting positive ratings on e-marketplace. Although there are many seller review mechanisms developed, the electronic commerce market operators and the consumers are still facing the trust fraud challenge. Trust is one of major issues that baffle online purchase activities. In this paper, we develop a seller referral mechanism to verify sellers based on the experience of friends within a buyer\'s social network. The proposed framework estimates trust values of sellers from the perspective of social network for helping buyers prevent making transactions with the fraudulent sellers in the online marketplace.
Building a qualitative recruitment system via SVM with MCDM approach
(2011-08-01)
Li, Yung-Ming
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Lai, Cheng-Yang
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Kao, Chien-Pang
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Advances in information technology have led to behavioral changes in people and submission of curriculum vitae (CV) via the Internet has become an often-seen phenomenon. Without any technological support for the filtering process, recruitment can be difficult. In this research, a method combining five-factor personality inventory, support vector machine (SVM), and multi-criteria decision-making (MCDM) method was proposed to improve the quality of recruiting appropriate candidates. The online questionnaire personality testing developed by the International Personality Item Pool (IPIP) was utilized to identify the personal traits of candidates and both SVM and MCDM were employed to predict and support the decision of personnel choice. SVM was utilized to predict the fitness of candidates, while MCDM was employed to estimate the performance for a job placement. The results show the proposed system provides a qualified matching according to the results collected from enterprise managers.
Discovering influencers for marketing in the blogosphere
(2011-12-01)
Li, Yung-Ming
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Lai, Cheng-Yang
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Chen, Ching-Wen
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Discovering influential bloggers will not only allow us to understand better the social activities taking place in the blogosphere, but will also provide unique opportunities for sales and advertising. In this paper, we develop an MIV (marketing influential value) model to evaluate the influential strength and identify the influential bloggers in the blogosphere. We analyze three dimensions of blog characteristics (network-based, content-based, and activeness-based factors) and utilize an artificial neural network (ANN) to discover potential bloggers. Based on peer and official evaluations, the experimental results show that the proposed framework outperforms two social-network-based methods (out-degree and betweenness centrality algorithms) and two content-based mechanisms (review rating and popular author approaches). The proposed framework can be effectively applied to support marketers or advertisers in promoting their products or services. (C) 2011 Elsevier Inc. All rights reserved.
Identifying influential reviewers for word-of-mouth marketing
(2010-07-01)
Li, Yung-Ming
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Lin, Chia-Hao
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Lai, Cheng-Yang
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資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
The key to word-of-mouth marketing is to discover the potential influential nodes for efficiently spreading product impressions. In this paper, a framework combined with mining techniques, a modified PMI measure, and an adaptive RFM model is proposed to evaluate the influential power of online reviewers. An artificial neural network is adopted to identify the target reviewers and a well-developed trust mechanism is utilized for effectiveness evaluation. This proposed framework is verified by the data collected from Epinions.com, one of the most popular online product review websites. The experimental results show that the proposed model could accurately identify which reviewers to select to become the influential nodes. This proposed approach can be exploited in effectively carrying out online word-of-mouth marketing, which can save a lot of resources in finding customers. (C) 2010 Elsevier B.V. All rights reserved.