本篇論文使用財務/非財務指標來研究動態的經營績效。效率評等應該被視為達成較好經營績效暨較佳市場位置的一種關鍵要素。本論文藉由資料包絡分析法(DEA)整合財務/非財務指標的績效模型來衡量賭場之效率評等。也進一步運用動態差額變數資料包絡分析。這項研究的結果能為賭場產業的管理者提供對資源配置的瞭解和探究競爭優勢所在，並且幫助經營者在金融危機下或競爭激烈的環境擬定適當的經營策略。
首先就跨期研究(cross-period study) 而言本研究運用動態資料包絡分析法，以會計跨期結轉觀點探討動態營運績效，使用兩階段的方式來分析博弈產業跨期(2004-2013) 的管理績效。第一階段將動態差額變數為基礎的測度(dynamic slack-based measure) 模式，用來衡量博弈產業的效率。第二階段藉由無母數檢定來找出影響博弈產業經營績效的作業特徵。數個實證結果說明如下：（1）賭場公司績效在金融危機前期比之後期好;（2）後金融危機時期從馬太效應觀察看出規模大的公司績效比較好;（3）集團結構完整的公司後危機比其他非集團型的賭場公司更好。
最後，本研究的發現可以視為處理博奕產業相關議題的指引。我們也希望在本研究所使用的數量模型暨方法論可廣泛應用到不同產業，探究不同的議題。

This dissertation reconciles diverse financial/non-financial measures to characterize the business performances of Casino Companies (CCs). Efficiency ratings should be considered as a key element for achieving greater business performance and better market position. The technology of data envelopment analysis (DEA) is employed to determine a multi-factor business performance model which inherently recognizes tradeoffs among various financial/non-financial measures. This study also presents an extension to the DEA, by dynamic slack-based measure (DSBM) DEA for assessing the performance of CCs. The results of this study can provide CCs’ operations with insights into resource allocation and competitive advantage and help with strategic decision-making, especially regarding operational styles under an intense competitive environment through high CCs density.
This paper explores whether company size confers a Matthew effect that is able to reduce losses during severe economic downturns, e.g., global financial crises. Casinonomics provides good jobs, pays for vital public services and boosts local communities. This research methodology integrates the radial and non-radial measures of efficiency into the dynamic production process framework with carry-over and, utilizes a dynamic slack measure model to evaluate gambling industry performance. Identifying the characteristics of the gambling industry including those of size and operating patterns will provide insight into the causes of imperfectly competitive conditions. This paper examines the performance of CCs before and after a financial crisis in North America. The methodology employs dynamic data envelopment analysis to evaluate casino industry performance. Our empirical results show that (1) CCs are generally more efficient prior to a financial crisis than afterward; post-financial crisis CCs suffer from the Matthew effect; (2) generally, large-size CCs are more efficient than small-size CCs; and (3) CCs with conglomerate structures perform better post-crisis than others.
Finally, our findings can serve as a guideline in the casino industry for coping with issues relating to CCs. It is also hoped that the models and methods implemented in this study can bring about other related research to a variety of industry.

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