Title: 社群商務之關鍵計算引擎與營運服務設計
Designing Core Computing Engines and Business Services for Social Commerce
Authors: 李永銘
Li Yung-Ming
Keywords: 社群網路;社群決策支援;社群擴散機制;社群行銷;社群生產;社群推薦;社群知識;Social Networks;Social Decision Support;Social Diffusion Mechanism;Social Marketing;Social Production;Social Recommendation;Social Knowledge
Issue Date: 2014
Abstract: 由傳統商業流程至社群商業的演變經過過去幾年的初期發展後,已經進入快速成長 的階段。社群商務是電子商務的一環,係以社群媒體輔助各類商品與服務的線上銷售與 購買。顧客消費經驗越來越朝向個人化發展,且顧客本身已經變成是新的訊息傳遞與擴 散的媒介。社群商務帶來最大的改變,是從單純的產品行銷發展到與顧客進行對話。由 於顧客可以從自己信任的朋友得到大量的訊息,適當的在電子商務營運活動中運用社群 媒體對於廠商與客戶都是有好處的。進行購買決策時,顧客會參考來自於身邊同儕的意 見與建議,這些緊密結合的顧客將會強化社群的影響力,並轉移品牌對於購買決策的影 響程度。 由消費端來看,如何根據不同的消費者特性,給予合宜的產品進行推薦是基礎且重 要的。由生產端來看,從線上消費者的反應了解消費者需求,並從而進行產品設計與改 良,藉以設計出更貼近客戶的產品,將可有效的提升產品形象。要使消費者認識產品, 進行廣告行銷活動是必須的。但這些廣告活動必須有良好的管道進行訊息的傳播,而這 必須從兩方面來探討。從訊息的傳播來看,訊息必須能夠被迅速有效地傳遞;從訊息的 接收來看,訊息則必須能夠被標定好的特定消費族群所接收到。由於社群商務的消費者 習慣從身邊的朋友得到訊息,因此適當的決策支援機制,也是社群商務不可或缺的基本 組成元素。 本計畫之目的在於藉由探討社群媒體在不同的消費者購買行為階段中的影響程 度,拓展社群商務的研究領域。其主要目的在於替新興的社群媒體開發一個完整的社群 商務上行銷、營運(生產與推薦)機制,並建立知識學習過程中的流程建議。具體來說, 我們將發展核心決策支援和訊息擴散的機制,以支持社群媒體上的各種應用。在社群媒 體上設計廣告/推薦系統來支援消費者的產品選擇的同時,我們也設計了消費者參與產 品設計的機制來輔助生產者進行產品改善與知識學習。
The evolution of traditional commerce to social commerce has made its baby steps in these past years, but seems to be growing rapidly. Social commerce is a subset of electronic commerce that involves using social media to assist in the online buying and selling of products. Customer experience is personalized and customers themselves are the new media outlets. The biggest change in social commerce has been the shift from pure marketing to more of a conversation with customers. The biggest change in social commerce has been the shift from pure marketing to more of a conversation with customers. Leveraging social media in e-commerce provides multiple advantages for both customers and businesses as online shoppers have access to large amounts of information provided by their trusted parties. Consumers will rely on their peers as they make online decisions. Socially connected consumers will strengthen communities and shift power away from brands. Viewing from the consumption side, how to facilitate the motivation of customer consumption and find the most appropriate group of consumers in accordance with their realistic need and characteristic of product is important. From the production site, the main purpose is to understand need of costumers and make enterprise produce fascinating product in the future. The online information is generated by the consumers who have used the product and consider it can satisfy their need. When talking about the commercial activities like marketing and advertising, the spread of information becomes a great issue. There are two dimensions of the information issue. One is the information delivering issue, and the effectiveness of diffusion mechanism will be crucial. The other issue is about the information receiving. With the personal data and behavior information the advertisers can obtain online, they can easily focus their targeted customers through characteristic matching or friends’ preference consulting. Many Internet users are getting used to make decisions based on opinions collected from their own social networks. While conventional decision support system has been extensively investigated, little specific mechanism, however, on how social networks can help users with decision-making is developed. In this project we aim to contribute to the effort of social commerce and social media research by evaluating the effects of the social media on various stages of purchase decision making and address the questions from the view of both consumer and producer. The purpose of this research is to develop a complete social media based marketing, operations (production and recommendation), and knowledge learning framework for emerging social media and business paradigm. Specifically, we will develop core decision support and information diffusion mechanisms to support various applications on social media. Meanwhile, a suite of social media based business services will also be designed to support both the demand-side participants (advertising and recommendation) and the supply-side participants (production and knowledge learning) in the social commerce
Gov't Doc #: NSC101-2410-H009-009-MY3
URI: http://hdl.handle.net/11536/100595
Appears in Collections:Research Plans