長久以來，人類的交易（貨品和服務的交換）基本上一直以銀貨兩訖為主的經濟交換模式。即便是物物交換的年代，也是以交易雙方互相認為合乎自己利益和價值的交換為主。但是，當前的網路經濟模式中，卻充斥著許多免費服務平台以及免費的軟體 (App) 和內容。依據傳統經濟學的觀點，若將免費平台視為公共財，大量享受資源不用付費的搭便車 (free rider) 使用者，為何未造成「公共財」的耗盡災難？而免費平台仍然有利可圖？創造 App 和內容的人也一樣前仆後繼、免費地提供其資源及努力成果？在數位網路時代，使得許多資訊產品的邊際成本幾乎為零。愈多的搭便車使用者能創造出更大的網絡效應，而衍生出多方價值交換的市場機制。因此，群眾基礎 (user base) 便成為免費平台的獲利來源。綜觀過去對於免費平台經濟模式的研究，大多僅僅歸論為由第三方付費的補償機制，即雙邊市場 (two-sided markets)，或者免費增值 (freemium) 模式。這些是否真的能完好地解釋網路時代的網路經濟現象 (cyber economies)?本研究從多方價值交換的角度，試圖經由實徵性研究，對這個現象的基本運作，提出一個合理的解釋。本研究預計採多重個案研究方式 (multi-case study)，自多個免費平台個案歸納出不同營收模式的樣態 (pattern)，進行樣態比較 (pattern matching)。同時，並與現有理論相比對，以推論出免費平台以及免費 App 和內容的營收模式的前因條件。接著運用定性比較方法 (Qualitative Comparative Analysis, QCA)，初步確認各種前因條件組態 (configuration) 與營收模式之間的因果關係，以作為確定性的論據 (conclusive evidence)，據此可更具體解釋網路世界的各種搭便車現象，並為網絡經濟的平台營收、免費軟體和內容的營收模式發展命題，以期擴張原有平台經濟的論證。 ;For Centuries, business transactions (exchange of goods and services) have long been based on mutual exchange, where the customer pays in exchange of goods and services. Even in a barter economy, buyers and sellers exchange based on balance values and utilities. However, in the current network society, the main modus operandi seems to be free services, free apps and free contents, which becomes a pillar of the cyber economy. A well-known classic economic problem with collective action is that common benefits result in the tragedy of the commons. Information goods and services represent the two related elements; with low incremental and reproduction costs, large-scale usage leads to increased gross profit while with network externality, marginal utilities increase with the growing number of users. Therefore, the “user base” becomes a source of revenue on free platforms. Most researches regarding free platforms are related to two-sided markets and freemium models. The objective of this study is to provide a theoretical framework explaining why free platforms, free apps and free contents emerge, and how they work. Based on existing revenue models of free platforms in the theoretical realm, we apply a multi-case study approach for inductive inferences on observed patterns in order to create conditions for different revenue models on the free platforms. We then conduct a qualitative comparative analysis (QCA) to confirm the conditions associated with revenue model of the free platforms to formulate conclusive evidences. Consequently, based on the result of causality assessment, we develop propositions for each revenue model to better explain the free rider phenomenon in the platforms. This approach correlates with empirical reality to expand arguments in the network economy.
