有關企業對企業（B2B）和企業對消費者（B2C）的商展中，參展廠商一向對觀展者在展場的參觀、購物及下單等購買行為非常有興趣，過去有關企業商展為主題的研究多聚焦於商展性質的選擇、參展動機、參展執行表現和參展利益等論述；然而，並無太多實證研究運用人臉辨識系統，來檢視參展廠商在商展中的執行及效益，並以具體數據及分析報表即時展現。本研究採用人臉辨識系統結合軟體、伺服器及連結物聯網、大數據、雲端運算等概念，在亞洲的台灣、中國及日本三地進行6場商展中，使用實驗法及觀察法的研究方法，以人臉辨識系統結合視訊及掃描系統，設置於商展場出入口進行智慧人流統計與資訊收集實證作業；有三場實證個案是企業對企業模式(B2B)，另三場是企業對消費者模式(B2C)。研究結果顯示人臉辨識系統，可精確即時掌握包括人數、年齡、性別及駐足時間的訪客分佈資訊，參展廠商依據人流統計數據之離尖峰時段或展場冷熱區，即時、動態調整人力布局、展示品調整及相關行銷活動。有關人臉辨識及智慧人流統計系統在智慧商業的應用研究，在2016年12月14~16日參加於日本所舉行的「東京的IoT應用展」，在展位及展會中佈建6套人臉辨識及智慧人流統計系統，模擬智慧商業的應用，以實驗設計方法探討應用人臉影像辨識技術，自動偵測、辨識消費者的人數、性別與年齡；後臺雲端系統連結廣告機顯示器及整合人臉辨識系統功能及廣告機顯示器的智慧型智自動販賣機，透過人臉辨識系統功能得知消費者的性別、年齡後，雲端伺服器主動派播適當廣告文字、圖像或動畫等內容，給予顧客商品建議並吸引目光，引導消費者即時進行網路購物的數位化銷售，實現精準行銷活動並達到廣告效外溢效果，電子支付功能及即時物流指令傳遞，提供消費者更便利的購物活動，從而創造出另一種全新的智慧商業模式。

Exhibitors are highly interested in visitation, ordering, and buying behaviors of visitors in business-to-business (B2B) and business-to-consumer (B2C) trade shows. Previous studies on business trade shows have focused on various aspects, such as trade show selection, motivation, performance, and benefits. However, only a few empirical studies have examined the experiences of exhibitors in their participation in face recognition systems in trade shows. In this study, face recognition software combined with a server that links the Internet of things (IoT), big data and cloud computingconcept were adopted. People flow tally and data collection were conducted in six empirical cases of Asian trade shows. These cases include three B2B and three B2C cases in three Asian countries, namely, Taiwan, China, and Japan, through experimentation and observation methods coupled with a video and scanning system that was set up at site exits and entrances. Results show that the face recognition system can provide data distribution precisely and timely on the number of people at an exhibition site, including their age, gender, and time of stay. The exhibitors can use data tally and information on the peak and off-peak hours of people flow or the cold and warm areas of the exhibition site to adjust marketing activities timely and dynamically. In addition, an application research of the face recognition system for business intelligence this study participated in the “IoT application exhibition in Tokyo” held on December 14–16, 2016, in Japan, particularly in the booth and exhibition hall. This application research was aimed at establishing six systems of intelligent applications, simulating the results of the face recognition system and its application for business intelligence, experimentally designing methods to explore the application of face recognition technology, and automatically detecting the gender and age of consumers. Moreover, this application research immediately actively played advertisement texts, images, or animations to advice customers on a certain commodity to attract them to stop and satisfy their purchase desire, thus creating a new smart business model. Finally, theoretical and practical implications of this study are also discussed.

中文參考文獻
1. 日本自動販賣機工業會，民102。全球自動販賣機裝置統計。日本: 自動販賣機工業會。
2. 杜育麟，民96。參加商展之成本效益分析－以個案公司為例。國立中山大學財務管理學系碩士在職專班，未出版碩士論文。
3. 李世珍，民105。商業興觀點／服務創新 無人概念崛起。台北: 商發院經營模式創新研究所。
4. 高肇宏，李宗展，黃鐘賢，民100。結合二維與深度影響資訊之人臉辨識技術概述。電腦與通訊期刊，第139期，81-87頁。
5. 溫月球，民94。如何參加國外展覽。台北：外貿協會。
6. 陳建州，民93。利用獨立成分分析法在區域特徵上的人臉辨識。國立成功大學資訊工程學系，未出版碩士論文。
7. 黃俊章，吳彥奇，陳永晴，林敬喬，民94。人臉檢測與定位。私立逢甲大學自動控制工程學系專題論文，臺中。
8. 趙昌孟，民101。國際花卉博覽會場館規劃與營運專案管理—2010臺北花博爭艷館個案研究。國立高雄師範大學成人教育研究所，未出版碩士論文。
9. 資策會，民106。新興通路變革大未來-流通服務業智慧商店實驗推動計畫彙整。台北:資訊工業策進會創新應用服務研究所。
10. 資策會，民99。互動式數位看板產品功能簡介。台北:資訊工業策進會創新應用服務研究所。
11. 經濟部投資事業處，民97。會展產業分析及投資機會。台北：經濟部。
12. 經濟部投資事業處，民105。臺灣會展效益研究–海外參展篇。台北：經濟部。

英文參考文獻
1. Aaker, D. A.（1996）. Measuring brand equity across products and markets, California Management Review, Vol. 38, No. 3, pp. 102-120.
2. Assadi, A. & Behrad, A. (2010). A new method for human face recognition using texture and depth information, in Proc. of 10th Symposium on Neural Network Applications in Electrical Engineering, Belgrade, Serbia, November, pp. 201-205.
3. Bateson, J. E. G. (1985). Self-service consumer: An exploratory study, Journal of Retailing, Vol. 61, No. 3, pp.49-76
4. Blythe, J. (2002). Using trade fairs in key account management. Industrial Marketing Management, Vol. 31, No. 7, pp. 627-635.
5. Camarero, C., Garrido, M. J. & Vicente, E. (2010). Components of art exhibition brand equity for internal and external visitors. Tourism Management, Vol. 31, pp. 495-504.
6. Chiang, D. (2017). Real-time data delivering based on prediction scheme over internet of things. Journal of Internet Technology, Vol. 18, No. 2, pp. 395-405.
7. Stuart, T. (2013). Cisco at mobile world congress: How service providers can monetize wi-fi. Cisco Internet Business Solutions Group.
8. Curran, J. M. & Meuter, M. L. (2005). Self-service technology adoption: Comparing three technologies. Journal of Services Marketing, Vol. 19, No. 2, pp. 103-113.
9. Dabholkar, P. A. (1992). Role of affect and need for interaction in on-site service encounters. Advances in Consumer Research, Vol. 19, No. 1, pp.563-589
10. Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality. International Journal of Research in Marketing, Vol. 13, PP. 29-51.
11. Ebert, R. J. & Griffin, R. W. (2017). Business Essentials, 11/e, U.S.A.: Pearson Education Limited.
12. Gartner, Inc. (2016). Analysts to discuss shift to modern business intelligence and analytics at Gartner business intelligence. Analytics & Information Summits in Sydney, Australia.
13. Globerson, S. & Maggard, M. J. (1991). A conceptual model of self-service. International Journal of Operation Production Management, Vol. 11, No. 4, pp. 33-44.
14. Gopalakrishna, S. & Lilien, G. (2012). Trade shows in the business marketing communications mix, In: Lilien, G.L. and Grewal, R. (Eds.), Handbook of Business to Business Marketing, Part III, pp. 226-245, Edward Elgar Publishing, Cheltenham.
15. Gottlieb, U. & Bianchi, C. (2017). Virtual trade shows: Exhibitors’ perspectives on virtual marketing capability requirements. Electronic Commerce Research and Applications, Vol. 21, pp. 17-26.
16. Hansen, K. (2004). Measuring performance at trade shows: Scale development and validation. Journal of Business Research, Vol. 57, No. 11, pp. 1-13.
17. Hsu, T. H., Chou, Y. Y., Tang, J. W., Huang, B. W. & Cheng, W. M. (2011). The analysis of key success factors for exhibition marketing. Marketing Review, Vol. 8, No. 3, pp. 367-384.
18. Jung, M. (2005). Determinants of service exhibition quality as perceived by attendees. Journal of Convention and Event Tourism, Vol. 7, No. 3, pp. 85-98.
19. Kerin, R. A. & Cron, W. L. (1987). Assessing trade show functions and performance: An exploratory study. Journal of Marketing, Vol. 51, No. 3, pp. 87-94.
20. Kellezi, J. (2014). Trade shows: A strategic marketing tool for global competition. Procedia Economics and Finance, Vol. 9, pp. 466-471.
21. Kim, H. Kim, D. & Bang, S. (2002). Face retrieval using 1st- and 2nd-order PCA mixture model. International Conference on Image Processing, Rochester, New York, Sept. pp. 391-400.
22. Kirchgeorg, M., Springer, C. & Kästner, E. (2009). Objectives for successfully participating in trade shows. Journal of Business and Industrial Marketing, Vol. 25, No. 1, pp. 63-72.
23. Meuter, M.L., Ostrom, A.L., Roundtree, R.I. & Bitner, M. J. (2000). Self-service technologies: understanding customer satisfaction with technology-based service encounters. Journal of Marketing, Vol. 64, No. 3, pp. 50-64.
24. Meuter, M. L., Ostrom, A. L., Bitner, M. J. & Roundtree, R. I. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies, Journal of Business Research, Vol. 56, No. 11, pp. 899-906.
25. Meuter, M. L., Bitner, M. J., Ostrom, A. L. & Brown, S. W. (2005). Choosing among alternative service delivery modes: An investigation of customer trial of self-service technologies. Journal of Marketing, Vol. 69, No. 2, pp. 61-83.
26. Moore, S. (2016). Analysts to discuss shift to modern business intelligence and analytics. Gartner Business Intelligence, Gartner Research Report.
27. Plume, C. J., Dwivedi, Y. K. & Slade, E.L. (2016). Social media in the marketing context: A state of the art analysis and future directions. U.S.: John Wiley & Sons.
28. Rittichainuwat, B. & Mair, J. (2102). Visitor attendance motivations at consumer travel exhibitions. Tourism Management, Vol. 33, No. 5, pp. 1236-1244.
29. Sarmento, M., Simões, C. & Farhangmehr, M. (2015). Applying a relationship marketing perspective to B2B trade fairs: The role of socialization episodes. Industrial Marketing Management, Vol. 44, pp. 131-141.
30. Sashi, C. M. & Perretty J. (1992). Do trade shows provide value? Industrial Marketing Management, Vol. 21, No. 3, pp. 249-255.
31. Sato, Y. D. & Kuriya, Y. (2011). Visual constructed representations for object recognition and detection. In: Lu, B.-L., Zhang, L. & Kwok, J. (eds.) ICONIP 2011, Part III. LNCS, vol. 7064, 611-620, Springer, Heidelberg.
32. Sato, Y. D., & Kuriya, Y. (2012). Effective and efficient Gabor feature representation for face detection. World Academy of Science, Engineering and Technology, Vol. 63, pp. 149-152.
33. Tanner, J. F. (2002). Leveling the playing field: Factors influencing trade show success for small companies. Industrial Marketing Management, Vol. 31, No. 3, pp. 229-239.
34. TechNavio Global Information (2017). Global intelligent vending machine market 2017-2021. U.S. TechNavio Infiniti Research Ltd.
35. Turk, M. & Pentland, A. (1991). Eigenfaces for recognition. Journal of Cognitive Neuroscience, Vol. 3, No. 1, pp. 71-86.
36. Vodafone Group. (2014). Empowering everybody to be confidently connected. Vodafone Group Annual Report.
37. Wertime, K. & Fenwick, I. (2017). DigiMarketing: The essential guide to new media & digital marketing. U.S.: John Wiley & Sons.
38. Whitfield, J. & Webber, D. (2011). Which exhibition attributes create repeat visitation? International Journal of Hospitality Management, Vol. 30, No. 2, pp. 439- 447.
39. Wolfrum, P., Wolff, C., Lucke, J. & von der Malsburg, C. (2008). A recurrent dynamic model for correspondence-based face recognition. Journal of Vision, 8, pp. 1-18.
40. Zhou, Q. Xiao, D. Tang, Y. & Rong, C. (2014) Trusted big data capture and transport architecture for wireless sensor network. Journal of Internet Technology, Vol. 15, No. 6, pp. 1033-1041.