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不少很重要的資訊，例如對於本研究用來測量垂直整合程度很重要的員工費用 總計，在許多上市公司的報表或附注中就沒有提供；
(5) 報表資料的可靠性問題，有時，企業管理者為了使報表顯示出企業良好的財務 狀況及經營成果，會在會計處理方法上採用一些手段來粉飾財務報表，這時基 於財務報表分析的研究就容易進入誤區。
因此，本文依據次級資料所作的分析必將受到財務報表本身不可避免的局限性影響，
使研究結論在一定程度上存在局限性。
最後，樣本資料沒有選擇2009年之前的資料，本文只著重分析風險偏好對公司行爲 的影響，限於篇幅，對突發性歷史事件的影響未作深入分析，2007-2008年全球金融危機 的突發事件對於全球製造業的影響極大，假如引入更多非常時期的資料，與其他年份的 資料一起做計量回歸，預計回歸結果會受到更大的影響。
第四節 建議進一步研究的研究方向
本文在模型（B）中用「審慎程度DOP」作爲企業的風險偏好的結果來代理風險偏 好，證明瞭績效展望和風險偏好的關係完全符合模型（B）的假設，但是本文的重點是 研究模型（A）中垂直整合VI與績效展望的關係，而且「垂直整合VI」與「損失展望LP」
的關係得也到了充分的論證，但是「垂直整合VI」與「利得展望GP」的相關係數在10%
顯著性水準上未能通過統計檢驗，說明當公司的績效預期高於績效目標，績效展望爲正 時，決策者的風險偏好爲風險趨避，但是利得展望與垂直整合VI的關係不顯著，本研究 嘗試用實物期權的觀念，以及「不作為偏誤」的維持現狀作用來解釋。然而在相同的資
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產特用性下，風險趨避的決策者要著手降低交易成本/治理成本時，從相關理論的演繹 結果理應是更多地選擇層級治理，現在本研究的實證檢驗未能支持理論的演繹假説H4.0，
不排除是因爲受資料可得性的限制，即我們用來代理利得展望的自變數，以及垂直整合 的測量等資料來源等存在偏誤所致。在利得展望的情形下，決策者究竟是會更多地選擇 層級治理還是選擇市場治理的途徑，這仍然是一個值得進一步研究的問題。
其次，我們在本文中發展的模型中，發展的績效展望與垂直整合的函數關係是綫性 的，一個可以考慮的後續研究方法是使用非綫性函數，例如冪函數等，也許能夠得到更 高的模型契合度以及對應變數的解釋量R
2
。最後，後續研究還可以考慮區別細分行業因素的影響，尤其是高科技產業與傳統製 造業在垂直整合策略上的差異。美國上市公司中有許多高科技企業，Barney（1999）認 爲，快速發展的高科技産業往往更傾向於通過非層級治理形式獲得能力，儘管這種決定 可能帶來機會主義的威脅，但是自己去重新開發或者購買另一家擁有這些能力公司的成 本高昂，所以使用市場或中間形式的治理成爲一種更具吸引力的選擇。不過，如何區別 細分出高科技產業可能需要新的方法，在本研究採用的Compustat資料庫中，用SIC CODE方法較難甄別出高科技産業別，例如我們認爲Apple公司應屬高科技產業，但在 Compustat資料庫中Apple的明細SIC CODE是3663，即Radio and Television Broadcasting and Communications Equipment（廣播電視播放設備），還個產業也許可歸為高科技產業，
但是緊鄰的3661對應的產業別是電話及電報設備，3652是留聲唱片及磁帶等，這些產業 公司使用的科技很多出現在兩個世紀前，所以要準確地甄別産業仍需尋找其他資料庫；
或者還可引入更多的變數，例如Williamson在TCE模型中提出的不確定性或者交易頻率 等，這些新變數如何和展望理論的進一步交互作用，都是值得深入研究的問題。
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