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  4. Electronic Theses and Dissertations Collection (ETD) @FBL
  5. Doctor of Business Administration
  6. Project Risk Management Strategies in the Construction of Mega Integrated Casino Resorts based on Statistical and Machine Learning Approaches
 
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Project Risk Management Strategies in the Construction of Mega Integrated Casino Resorts based on Statistical and Machine Learning Approaches

Date Issued
2025-06
Author(s)
Sin, Tou Meng
Abstract
Macau Special Administrative Region (SAR) is the only jurisdiction within the People’s Republic of China where casino gambling is legally permitted. Under Portuguese colonial rule, the gaming industry operated under a government-sanctioned monopoly, and in 1982, the Sociedade de Turismo e Diversões de Macau (STDM), a syndicate of Hong Kong and Macau entrepreneurs, was awarded a forty-year exclusive concession for all gaming operations. Following Macau’s handover to China in 1999, the Macau SAR government initiated significant policy reforms to liberalize the gaming sector, aiming to diversify the economy and attract foreign investment. In 2002, the government opened bidding for casino concessions, leading to the entry of major international operators, including Wynn Resorts, Galaxy Casino, Venetian Macau, MGM Grand Paradise, and Melco Crown (Macau), while Sociedade de Jogos de Macau (SJM), a subsidiary of STDM, retained its presence. This liberalization transformed Macau’s gaming industry, with foreign capital fuelling the development of large-scale, Las Vegas-style integrated resorts, replacing outdated facilities and expanding the city’s tourism and entertainment offerings. Between 2003 and 2018, the casino construction industry grew rapidly, yet faced unique challenges, including resource constraints, political sensitivities, and skilled labour shortages. This thesis analyses the evolution of Macau’s casino construction industry during this transformative period, with a particular focus on project risk management practices. Using a quantitative research approach based on a survey collected with 100 respondents, the study identifies critical barriers to effective risk management, such as regulatory uncertainty, contractor capacity limitations, and supply chain vulnerabilities. Statistical and Machine learning techniques are adopted to identify clusters and extract insights from the data. The findings reveal that while foreign investment and expertise significantly enhanced construction quality and project scale, risk management practices often lagged behind industry expansion. This research contributes to the limited academic literature on project risk management within emerging gaming economies and offers practical insights for policymakers, developers, and investors aiming to foster more resilient and sustainable infrastructure development in Macau’s next phase of growth.
Subjects

Project Risk Manageme...

Construction Industry...

Statistical Analysis

Machine Learning

Framework

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Sin Tou Meng 201700065 (Signed) - Tou Meng Sin.pdf

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12.93 MB

Format

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(MD5):9937a90f3f07888fb59470b94f6ea9a6


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