由於能源危機與環保意識的抬頭，無污染且取之不盡的再生能源受到重視而蓬勃發展。在各種再生能源之中，太陽能由於具有最高發電量的潛力，以及其安裝地點彈性的特性，成為各國積極投入發展的目標。然而，由於進入障礙相對較低所以競爭者眾多，以及高度依賴政府補助政策來刺激需求的特性，使得太陽能產業的供需變動極大。在2005年，由於石油價格屢創新高所帶來的大量需求導致上游多晶矽供不應求及報價高漲，讓太陽能廠商尋求長期合約或轉投資上游原料廠以確保原料來源及成本控制；然而，隨著2008年金融風暴及景氣低迷，政府減少甚至取消補助造成的供過於求及削價競爭，又讓矽原料跌至將近成本價，當初的合約及投資反而成為負擔。在這樣高度變化的經營環境下，如何決定上下游自製外包的比例以確保競爭力，成為太陽能廠商的重要課題。然而回顧過去的文獻中，較少有包含完整因子的自製外包決策架構，且較少考慮同時自製且外包這種在太陽能產業常見的經營模式。
本研究應用分析網路程序法（Analytic Network Process, ANP）發展一自製外包決策模型，協助決策者決定上下游自製外包的相對比例。首先由文獻回顧整理垂直整合的關鍵因子，考慮因子間的相互影響關係來建立網路架構，並透過問卷進行成對比較蒐集各項因子及供應鏈上下游間的相對權重，以求得適切的上下游相對比例。本研究以三家台灣太陽能製造商為實證進行案例分析，並進行敏感度分析以驗證研究效度。

To survive in the highly competitive and volatile solar business environment, the ability to decide what layers along the supply chain to invest in and develop internally and which to leave others to develop is a critical problem for players in solar industry. For example, the supply shortage of polysilicon in 2005 severely tested the manufacturers in the industry. Long-term contract and vertical integration was the strategy to acquire raw material. However, when the financial crisis in 2008 made governments cut off the subsidies, the demand dropped dramatically. The price of raw material fell down rapidly and the contract and integration become a huge burden. We can observe that both make and buy is a strategy for solar manufacturers to maintain the competitiveness. However, only few researches propose comprehensive make or buy methodology, and concurrently make and buy was not an option.
This research aims to build relative weightings of upstream-downstream layers decision framework for solar industry based on analytical network process (ANP), to help decision maker to decide an appropriate management structure in a supply chain. The tasks involved in this research includes: (1) Reviewing and sorting out critical factors for integration in economics theories and empirical studies. (2) Taking dependences and feedback in criterion and alternatives into the decision framework. (3) Derived the relative weightings between layers through ANP pairwise comparison, taking into account decision maker’s preferences and judgments. (4) Empirical study included face to face surveys with three solar companies in Taiwan, and the results were analyzed and discussed, including a sensitivity analysis.

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