隨著健康意識提升、人口結構趨向高齡化，預防保健格外受到重視，使得全球對於營養保健食品需求漸增，因此也造就了不同多元的銷售通路，其中電子商務與電話行銷通路最為成長快速。根據研究顯示，信任與忠誠度被視為重要的影響因素之一，因為這些因素也會影響著顧客是否會有購買及再購的行為，而企業經營最重要的績效就是顧客購買。
在過去的研究中，信任與忠誠度都是透過問卷來取得資料，但實際上收集問卷是很困難，因為客戶往往填寫意願不高、時間區隔長甚至會有填寫偏誤。此外，透過問卷並不能實際預測顧客未來的再購行為，因此近期有研究透過使用系統上的資料來進行分析顧客過去的行為來預測未來行為，但預測出來的結果並不能利用管理上的手段來改變顧客的行為。所以本研究利用資料驅動的方式來成功取得顧客的信任與忠誠度，隱含著資料驅動的方式能彌補問卷的缺失與提升資料收集效率。
本研究以營養保健食品產業在電話行銷通路上的通話紀錄與交易紀錄為基礎，建立操作性定義與資料轉換公式，將信任與忠誠度量化以利於衡量與分析，並利用遞迴式類神經網絡的方式，將信任與忠誠度作為輸入變數，預測顧客未來的再購行為，達70%的準確度，比傳統常用的分類方法SVM還要準確。此外，透過本研究可以探討到顧客信任以及忠誠度對再購行為的影響，未來企業可以針對這幾項指標作為KPI調整企業銷售手段或改善與顧客間的互動，同時對於未來的銷售量也能有預估及提升。

In the age of rising awareness in health, preventative medication has brought many attentions. In addition, this concept has resulted in the demand of nutrition and food supplements. The sales of these products highly depend on customer trust and loyalty. Therefore, trust and loyalty may be used to predict repurchase behavior.
In the past studies, trust and loyalty has to be analyzed with data collected with questionnaires. The common problem with this approach is low returning rate and less reliable data. This study is collect data through call records and transaction records of the nutrition and health industry through telemarketing channel. The data are used to quantify trust and loyalty. With these values, Recurrent Neural Networks(RNN) method is utilized to predict customer's future repurchase behavior. The results show that the accuracy can reach 70%, which is higher than the accuracy derived from SVM. Companies can use these indicators (trust and loyalty) as KPIs to adjust corporate sales methods and improve the interactions with customers.

［1］ Afolabi, I. T. and Oladipupo, O. O. and Worlu, Rowland E.K. and Akinyemi,(2016) A Systematic Review of Consumer Behaviour Prediction Studies
［2］ Bhattacherjee, A. (2002). Individual Trust in Online Firms: Scale Development and Initial Test. Journal of Management Information Systems.
［3］ Barbounis, T.G. and Theocharis, J.B. (2007) Locally recurrent neural networks for wind speed prediction using spatial correlation. Inf. Sci., 177, 5775–5797.
［4］ Delgado-Ballester, E. and Munuera- Aleman, J. L. (2001.) Brand trust in the context of consumer loyalty. European Journal of Marketing. 35, pp.1238- 1258
［5］ D.H. McKnight, N.L. Chervany, What trust means in e-commerce customer relationships:an interdisciplinary conceptual typology, International Journal of Electronic Commerce 6 (2) (2001) 35–59.
［6］ De Vries, B. and Principe, J.C. (1990) A theory for neural networks with time delays. Proc. 1990 Conference on Advance in Neural Information Processing Systems 3, San Francisco, CA, USA, pp. 162–168. IEEE Press, New Jersey.
［7］ Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. J. Manage. Inf. Syst., 19(4), 9-30.
［8］ David Gefen (2002).Customer Loyalty in E-Commerce, Journal of the Association for Information Systems
［9］ Erciş, A., Ünal, S., Candan, F. B., & Yıldırım, H. (2012). The Effect of Brand Satisfaction,Trust and Brand Commitment on Loyalty and Repurchase Intentions. Procedia - Social and Behavioral Sciences
［10］ Ellen Garbarino and Mark S. Johnson(1999).The Different Roles of Satisfaction, Trust, and Commitment in Customer Relationships
［11］ Gao, H., & Yao, J. (2012). A multi-dimensional trust model in e-commerce, 2012 IEEE International Conference on Computer Science and Automation Engineering.
［12］ Gefen, D., & Straub, D. (2003). Managing user trust in B2C e-services. E-Service Journal
［13］ Hui Fang,Guibing Guo,Jie Zhang(2015).Multi-faceted trust and distrust prediction for recommender systems
［14］ R.C. Mayer, J.H. Davis, F.D. Schoorman, An integrative model of organizational trust, The Academy of Management Review 20 (3) (1995) 709–734.
［15］ Hojjat Salehinejad and Shahryar Rahnamayan(2016)Customer Shopping Pattern Prediction: A Recurrent Neural Network Approach
［16］ Jane Dixon (2015) An alternative perspective on relationships, loyalty and future store choice .The International Review of Retail, Distribution and Consumer Research
［17］ Jan Roelf Bult and Tom Wansbeek (1995) Optimal Selection for Direct Mail
［18］ Lu, Y.-L., Mak, M.-W. and Siu, W.-C. (1995) Application of a fast real time recurrent learning algorithm to test-to-phone conversion. Proc. Int. Conf. Neural Netw., 5, 2853–2857.
［19］ Laura Maria Badea (2014) .Predicting Consumer Behavior with Artificial Neural Networks, Emerging Market Queries in Finance and Business EMQFB2013
［20］ McKnight, D. H., & Chervany, N. L. (2001). What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology. International Journal of Electronic Commerce
［21］ McKnight, D. H., Cummings, L. L., & Chervany, N. L. (1998). Initial trust formation in new organizational relationships. Academy of Management Review
［22］ Morgan and Hunt(1994) The Commitment -Trust Theory of Relationship Marketing
［23］ Moorman, C., Zaltman, G. and Deshpande, R. (1992).Relationships between providers and users of market research:The dynamics of trust within and between organizations.Journal of Marketing Research. 29, pp. 314-328.
［24］ Measuring Dimensions of Purchaser Trust of Industrial Salespeople
［25］ Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An Integrative Model of Organizational Trust. The Academy of Management Review
［26］ Oliveira, T., Alhinho, M., Rita, P., & Dhillon, G. (2017). Modelling and testing consumer trust dimensions in e-commerce. Computers in Human Behavior
［27］ Paul Hart & Carol Saunders (1997).Power and Trust: Critical Factors in the Adoption and Use of Electronic Data Interchange
［28］ Prokhorov, D.V., Saad, E.W. and Wunsch, D.C. (1998) Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks. IEEE Trans. Neural Netw, 9, 1456–1470.
［29］ Pan Hui Ming & Guo Yi ,2011“A Study on Network Customer Loyalty Based on e-contact Centers” 2011 International Conference on Business Computing and Global Informatization.
［30］ P. Fader(2012), Customer centricity: Focus on the right customers for strategic advantage.
［31］ Singh, J., & Sirdeshmukh, D. (2000). Agency and trust mechanisms in consumer satisfaction and loyalty judgments. Journal of the Academy of Marketing Science.
［32］ Selnes, F. (1993). An examination of the effect of product performance on brand reputation satisfaction and loyalty. European Journal of Marketing, 27(9), 19-35.
［33］ Stewart, K. J. (2003). Trust Transfer on the World Wide Web. Organization Science, 14
［34］ V. Kumar(2008), Customer lifetime value: the path to profitability. Now Publishers Inc
［35］ Wouter Poortinga1(2003) . Exploring the Dimensionality of Trust in Risk Regulation
［36］ Y. Zhang, E. T. Bradlow, and D. S. Small, “Predicting customer value using clumpiness: From rfm to rfmc,” Marketing Science, vol. 34, no. 2, pp. 195–208, 2014.
［37］ Yu-Jia Hu(2011).How Brand Equity,Marketing Mix Strategy and Service Quality Affect Customer Loyalty: The Case of Retail Chain Stores in Taiwan
［38］ Y. Zhang, E. T. Bradlow, and D. S. Small(2014).Predicting customer value using clumpiness: From rfm to rfmc,” Marketing Science, vol. 34, no. 2, pp. 195–208,
［39］ Zeng, A., Goodman, R. and Smyth, P. (1994) Discrete recurrent neural networks for grammatical inference. IEEE Trans. Neural Netw., 5, 320–330.
［40］ Zahra Idrees1, Xia Xinping1, Khuram Shafi1, Liu Hua(2015), Consumer’s brand trust and its link to brand loyalty, American Journal of Business, Economics and Management