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This study sought to determine the strategy that allowed the Las Vegas Sands Corporation (LVS) to attain its leading status in the casino industry and to gain insight whether this status would continue given (i) the passing of the LVS founder, Sheldon Adelson, in January 2021, (ii)the sell-off of the company's Las Vegas properties early in 2022, and (iii) the firm's greater sensitivity to events in China caused by the company's increased reliance for most of its customers on the mainland China market. The study first identified the nature of the LVS competitive advantages when Adelson was directing the firm and then assessed whether these had been adversely impacted due to changes in the firm's markets, management or strategy. The study relied initially on the work of David Baron, Professor of Political Economy and Strategy at Stanford University who as early as 1981 advanced the view that corporate strategy needed to be divided in a Marketing Strategy (MS) and a Non-Market Strategy (NMS). The NMS component for LVS was critically important since government determined who could acquire a Macau casino concession and what level of visas would be provided to Mainland China gamblers to fill the Macau casinos. The key question became the nature of Adelson's Political Effectiveness as determined by the NMS he directed towards the China market. To resolve this issue, we adopted the Wellner & Lakotta proposal to extend Porter's Five Forces analytical framework by two additional dimensions, Government Interventors and Complementor Organizations. We concluded that it was highly likely that Goldman Sachs, the long-term financial backer of Sheldon Adelson, played a significant if not the major role in the success Adelson was able to achieve in the Greater China market.

The stock market's inherent volatility and complexity pose significant challenges for investors seeking to optimize their strategies. This thesis addresses the critical need for improved forecasting methods in stock price prediction by proposing a hybrid approach that combines traditional machine learning (ML) techniques, specifically Support Vector Machines (SVM) and Long Short-Term Memory (LSTM) networks, with sentiment analysis derived from financial news and social media platforms. The research establishes a theoretical framework integrating quantitative data, such as historical stock prices, with qualitative sentiment data to enhance prediction accuracy. The study involves the collection of a comprehensive dataset covering stock prices and sentiment scores from various sources, including news articles and social media posts, from January 2010 to December 2023. Rigorous data preprocessing techniques, including normalization and feature engineering, are employed to prepare the data for analysis. A comparative analysis of the SVM and LSTM models uses multiple performance metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and classification accuracy. The findings reveal that the LSTM model significantly outperforms the SVM model in predictive accuracy, demonstrating its capability to capture complex temporal dependencies inherent in financial time series data. Furthermore, integrating sentiment analysis significantly enhances the predictive performance of both models. Notably, transformer-based sentiment analysis techniques, such as BERT and DistilBERT, provide superior sentiment classifications compared to traditional methods like VADER and TextBlob. The empirical results indicate that incorporating sentiment data leads to an average accuracy improvement of 12.8% over models that rely solely on historical price data. This research contributes to the evolving field of financial forecasting by emphasizing the importance of a hybrid approach that amalgamates quantitative and qualitative data. The implications of these findings extend beyond academic research, offering valuable insights for investors and financial analysts seeking to leverage advanced predictive models to navigate market uncertainties. Ultimately, this dissertation advocates adopting sophisticated hybrid models that enhance stock investment strategies and decision-making processes in the finance sector.

Formative assessment has long been recognised as a valuable educational measurement tool; however, its application in music education in Asia, particularly in Macau, remains underexplored. This study investigated the implementation of formative assessment in Macau and the factors that influence its application. A convergent mixed-methods research approach was adopted, utilising questionnaires, interviews and observations. Initially, teacher questionnaires, interviews and classroom observations were used to comprehensively understand how teachers implement formative assessment in singing teaching within junior middle schools in Macau. This approach identified the strengths and weaknesses of the practices while drawing insights from existing literature. Additional teacher questionnaires and interviews were used to explore the factors shaping teachers’ approaches to formative assessment. To provide a holistic perspective, student questionnaires and interviews were used to examine students’ experiences and perceptions of formative assessment in singing instruction. The findings indicate that a) teachers use all five formative assessment strategies outlined by Thompson and Wiliam (2007) with varying frequencies; b) teachers prioritise skill goals and technical accuracy over expressive qualities; c) performance assessment is common in singing classes, while questioning is more typical in other settings; d) teachers prefer teacher-directed assessments over student-directed ones (self and peer assessment); e) strengths include effective teacher demonstrations, frequent descriptive feedback, self-recording, reflective questions and constructive peer feedback, while weaknesses comprise infrequent use of assessment tools, application of multiple evaluative feedback types and low specificity in some descriptive feedback and misuse of self and peer ratings; f) both personal (teacher attitude, self-efficacy and subjective norms) and contextual (school environment, student challenges and public performances) factors hinder formative assessment implementation; and g) students value strategies like teacher demonstration, descriptive feedback and self-recording but devalue others such as evaluative feedback, self-rating, peer rating and peer feedback. Expert interviews were conducted to address the identified weaknesses and formulate targeted recommendations for stakeholders, aiming to enhance the effectiveness of formative assessment in singing teaching in Macau junior middle schools.

Facial expression recognition is a key topic in computer vision, playing a crucial role in non-verbal communication. With the rapid development of artificial intelligence, significant progress has been made in improving recognition accuracy and generalization abilities. Traditional methods often suffer from low precision and poor generalization, while deep learning models have substantially advanced the field. However, deploying deep and complex models on different platforms remains challenging due to their high computational demands and frameworks. Hence, developing an efficient, real-time, and lightweight facial expression recognition system is critical. This study focuses on creating an efficient, accurate, and lightweight real-time facial expression recognition system with an emphasis on cross-platform deployment. It integrates various deep learning and optimization techniques to demonstrate flexibility across platforms. In this context, this study evaluates the performance of 10 advanced CNN models (VGG16, VGG19, ResNet50, etc.) on the facial expression dataset FER2013. YOLOv8 combined with ResNet50 achieved 70.56% accuracy on FER2013, outperforming YOLOv8 alone by 2.1%. Multi-module fusion models (MobileFaceNet, IR50, HyViT, SE) achieved an accuracy of 92.58% and 74.8% on the RAF-DB and FER2013 datasets, respectively, showing superior performance in ablation experiments. Given the significant impact of data quality on model performance, this study performed data cleaning on the FER2013 dataset, resulting in a 3.25% accuracy improvement for the YOLOv8 + ResNet50 model, which reached 73.81%. The high-resolution RAF-DB dataset, with fewer errors, led to improved performance, achieving 92.56% accuracy with the fusion model. A multi-purpose facial expression recognition system, VISTA, was developed using Python and PyQt5. The system supports multiple data formats and provides real-time emotional feedback, thus enhancing its usability for both research and practical applications. Furthermore, the fusion model was quantized using the OpenVINO toolkit, reducing its parameters by 75% while maintaining an accuracy of 91.17%. Inference speed was improved, and XGrad-CAM was employed to enhance model interpretability, revealing that the YOLOv8 + ResNet50 combination more effectively captured facial features. Finally, the high-performance model was successfully deployed on Intel CPUs, NVIDIA GPUs, and embedded devices Raspberry Pi 4B, demonstrating the portability and flexibility of the VISTA system across various platforms. This research provides promising solutions for applications in human-computer interaction, affective computing, and real-time emotional analysis, with significant advancements made in improving system real-time performance, accuracy, and cross-platform deployment capabilities. It contributes to the development of facial expression recognition technology and lays the foundation for its widespread future applications in fields such as smart healthcare, business analytics, education, and mental health.

Artificial intelligence (AI) is changing the way we operate as a society. Generative AI models are especially known for being used to generate synthetic artifacts, such as texts, music, and images. This doctoral thesis explores generative AI's ability to create accurate images from prompt text. Our work aims to prove how generative AI tools are creating images that are remarkably similar in appearance as those created by humans. In addition to the theoretical contributions, this thesis explores broader secondary open questions about generative AI: what implications arise for the perception of what is virtual and non-virtual in our contemporary visual landscape? How does the new nature of interaction with generative AI change human-machine communication? Generative AI tools saw a series of breakthroughs these last years, which led to models that generate texts and images that are increasingly more difficult to distinguish from human- made creative content. As of 2022, Open AI developed and released ChatGPT, a chatbot enabling human users to converse, ask questions, explain concepts, and create new text-based content. However, the capabilities of generative AI went far beyond text generation. For example, gen AI models, Midjourney and DALL-E 3, are specifically designed to create images based on text prompts. These images are artificially created, meaning every screen pixel was produced using AI. Throughout this research, we explore new concepts of creative content generation, perception of virtual and non-virtual, memory, and trustworthiness in our contemporary imagery. Using an interdisciplinary methodological framework, this thesis engages with the creation of synthetic imagery as an opportunity for an infinite source of creativity or a detrimental disruption of contemporary visual culture.

This study investigates the regulatory-operational dynamics of the premium market in Macau casinos using a constructivist grounded theory approach. Qualitative in-depth interviews were conducted with 25 participants from three stakeholder groups. The grounded theory analysis identifies seven core categories illustrating the impact of the new regulatory system on the premium direct and premium mass segments in casinos. These categories include regulatory changes and operational challenges, decline of gaming promoters, premiumization of the gaming market, new player retention strategies, cross-border player acquisition risks, presence of unauthorized agents in casinos, and non-gaming development amid international competition. These insights highlight four major regulatory impacts on the industry themes and operational trends, i.e., industry regularization, market premiumization, product diversification, and criminal fragmentation. This study also identifies specific regulatory mechanisms and operational management in premium gaming, such as premium player identification, enhanced operational procedures, multi-tiered market segmentation, and the provision of personalized services. Additionally, stakeholder perceptions of the new gaming regulatory system are explored, with casino and expert groups considering it necessary and junket participants finding it restrictive. From these findings, a conceptual model structured around regulatory functions, compliance, and improvement is developed to provide a theoretical regulatory framework that aligns with the characteristics of the gaming industry in Macau and possibly other gaming jurisdictions.

As an important part of the global economy, family business have made a lot of contributions to the world economy. With the deepening of China's reform and opening up, the scale and volume of family business have increased dramatically in the national economy. In recent years, more and more family-owned enterprises have entered the list of “Top 500 Chinese Enterprises” and become an important part of the national economy. As a special enterprise organization, family business has certain characteristics. Most of the Chinese family business were founded in the early stage of China's reform and opening up, and now more and more family business are facing the problem that the founders need to leave the family business due to their advanced age. How to ensure the smooth succession of family business and avoid conflicts and contradictions in the process of succession is an important challenge faced by many family business. How to ensure that family business can continue to develop and maintain a high performance status is of great significance to the founders and their successors, as well as to the Chinese economy. Therefore, this research examines how the characteristics of successors affect enterprise performance based on the context of intergenerational succession in family business. This research is based on a multi-case study in which in-depth interviews were conducted with the founders and successors of five cases, which led to the conclusion that five successor characteristics have an impact on enterprise performance. They are inclusiveness, forward thinking, sociable and good communication, sense of social responsibility and sense of family mission. This finding has significant implications for the training of successors and the management of the succession process in Chinese family business. This study is conducive to the discovery of the mechanism of successor characteristics on enterprise performance as well as to make a realistic contribution to the research on the outcomes of family business in China.

Artificial Intelligence (AI) is being applied in different areas of Administration and Management including finance, e-commerce, etc. Project Management (PM) is one area that may benefit from the use of AI to support project managers in making more accurate predictions, more quickly, such as deadline adjustments and cost updates, while at the same time helping with some of repetitive tasks of PM by relieving managers from these processes. Nevertheless, multiple aspects are still in consideration to allow AI to be widely adopted in PM, including lack of validated systems, including aspects of quality and prevalence, trust from users, market and specialists, and how the government will play a role to support the wider adoption of AI tools. This research explores the integration of Artificial Intelligence (AI) in Project Management and its potential to enhance four aspects: service quality, trust, prevalence, and government support. The proposed methodology employs a systematic literature review (SLR) combining with a quantitative survey to assess the current state of AI in project management. The SLR covers scholarly articles from 2016 to 2021, focusing on AI's impact on project management across various industries. The survey, conducted among 200 professionals, gathers insights into AI's perceived benefits and challenges in project management. The research findings indicate a positive inclination towards AI in project management, with respondents recognizing its potential to improve efficiency, support data-driven decisions, and enhance risk management. However, the study also reveals concerns regarding data quality, privacy, and the need for ethical considerations in AI applications. Most respondents agree on the necessity of government support to foster AI adoption and the importance of establishing trust in AI systems through transparency and security measures. The thesis concludes with recommendations for practitioners and policymakers to effectively leverage AI in project management. It proposes a framework including the development of training programs, the establishment of quality standards for AI services, and the promotion of public-private partnerships to drive innovation. The study emphasizes the importance of a multi-faceted approach to AI integration, considering technological, organizational, and ethical dimensions.

Since early times, the effects of a booming sector in other sectors of a small economy have been of interest to scholars. There is a general perception that the booming Gaming sector has contributed to the overall growth in Macau through the trickle-down effect, passing on the benefits of growth to other sectors. After the liberalization of the gaming industry in 2002, this booming sector experienced several years of exponential growth, becoming the driving industry for Macao’s economy. Several scholars and researchers have dedicated their studies to the effects of the casino gaming industry as a booming sector in such a small economy. However, there is a gap in what concerns measuring the influence of the Gaming sector as a driving industry for several other sectors or following industries of Macau’s economy. The purpose of this research study is to investigate in what measure the Gaming sector in Macao leveraged the other economic sectors and how related or correlated are the different industries of Macao’s Economy. A protocol-driven understanding of the state of the art on the interrelations between economic sectors and different techniques used to study those inter-relations was conducted through a systematic literature review. Given the limited available data on the Gross Value Added (GVA), or Gross Domestic Product (GDP) on the supply side, as a central measure of economic activity in the different sectors, several possible interpolation models using auxiliary high-frequency data (indicators) were compared, to achieve the optimal model for interpolation of each variable. Several forecasts for the future performance of Macau's four major economic sectors were presented based on different regression techniques. Autoregressive Integrated Moving Average (ARIMA) models were developed to assess the dependence of the future performance of a sector’s GVA on its past performance. Optimal Vector Autoregressive (VAR) models were created to identify the explanatory power of some sectors of Macau’s economy in others. Based on available auxiliary data in high-frequency (quarterly) it was possible to interpolate the quarterly GVA per economic sector, available only in low-frequency (annually), for the major sectors of Macao’s economy. Some sectors have a considerable explanatory power on the performance of other sectors, however, the proposed regression models did not identify a clear relation between the performance of the Gaming sector and the performance of other major sectors from Macao’s economy

Source-based summary writing is an important aspect of academic writing at the undergraduate level; it includes summarizing and paraphrasing when producing texts in essay, report, or thesis formats. For university students whose second language or foreign language is English, source-based writing can be a challenging task as it involves and requires complex cognitive processes as well as reading-and-writing demands. Organized into three phases, this mixed method, small-scale exploratory feasibility case study investigated: (i) challenges and difficulties in online and offline English source-based summary writing of English as a Foreign Language (EFL) university students in Macao, identifying the cognitive and writing processes they experienced in a timed reading-writing task; and (ii) how to design and conduct interventions that could be used to diagnose, assess, and address essay challenges in source-based summary essay writing in everyday classroom sessions. Quantitative and qualitative data were collected through a summary online writing essay using Inputlog, a keystroke logging software, and retrospective think-aloud protocol in Phase One, a source-based summary essay writing task in a quasi-experiment in Phase Two, and a survey questionnaire and error analysis of pre-test and post-test essays of the control and experimental groups in Phase Three. The processes of reading and writing in English were found to be challenging and complex for EFL university students to perform in a limited time. As an initial exploratory feasibility, efficacy trial, deliberately small scale to address issues of risk, this study found that the diagnostic assessment tools and interventions had the potential to improve the summary writing processes and proficiency of EFL students, focusing on their cognitive writing skills in everyday class sessions. The thesis recommends scaling up the research in future studies, in terms of sampling and the duration of interventions designed to improve source-based summary essay writing and the cognitive writing processes that are part of this

The thesis identifies concerns preserving, maintaining, and developing the Catholic identity of Catholic schools in Macao, the largest providers of schooling whilst being a minority religion, and with its teachers, parents, and students coming from Catholic and non-Catholic backgrounds, cultures, and values. To understand the present situation of Catholic identity in Macao’s Catholic schools, manifesting itself in part through the Catholic ethos of schools, and to identify key features, mission, vision, values, and areas for the development of Catholic identity, together with its presence and practices, this thesis reports a study of the perceptions of, and attitudes to, Catholic identity held by three key stakeholder parties in a carefully chosen representative selection of Catholic schools: teachers, parents, and students. The thesis reports their views on what the Catholic schools are currently doing in the areas of Catholic identity, and what they consider that they should be doing in these areas. The areas of focus draw on scholarship and teachings on Catholic identity, with particular emphasis placed on documents on Catholic identity and ethos from the Vatican, Archbishop Miller, and Monsignor Stock. A large-scale empirical survey here found that there was considerable support for Catholic schools in Macao, their identity, ethos, and values from the three parties. Two emergent patterns of findings are reported concerning the steps that Catholic schools were taking to promote their identity: (a) what Catholic schools should be doing concerning Catholic identity received consistently higher scores than what they were currently doing; and (b) consistently higher support for Catholic identity came from the teachers, slightly less so from the parents, and slightly less than that from the students. The study conducted a follow-up, small-scale study to investigate why these might be the case, and it suggested that the combination of Catholic values and Chinese cultural features might explain the findings on Catholic identity in the schools. The study identifies areas for possible development of, and improvements to, the identity of Catholic schools, that take account of the local cultural contexts and the teachings of the Catholic church on identity, and how these might be addressed in practice

Drama-in-Education (DiE) has been recognised as a valuable teaching pedagogy in the western world for decades, and yet it has not been fully or systematically adopted in the secondary English classes in Asian contexts, including Macau, despite the numerous reported advantages for English language teaching (ELT) in the past studies. This study explores Macau’s secondary school English teachers’ perceptions of utilising DiE in their classes. A mixed-methods research (MMR) approach was adopted in this study, consisting of three phases. First, pre-survey interviews were conducted to understand the potential major concerns about the choices of teaching approaches and the application of DiE of Macau’s secondary school English teachers. Subsequently, a questionnaire survey targeting local secondary school English teachers was administered, the results of which were cross-examined by, and integrated with, the results of two post-survey group interviews. While the results affirm the local secondary school English teachers’ positive view on DiE as an ELT pedagogy and identify their perceived advantages of DiE, the study indicates the over-determination of multi-faceted challenges to its implementation in Macau’s secondary education context. The study identifies and recommends necessary substantial changes to further the application of DiE in Macau’s secondary education milieu

This thesis aims to demonstrate how Pope Benedict XVI's Eucharistic theology can be used to fill the gap it identifies in the content within the Religious Education curriculum of Macao Catholic secondary schools and also extend support to the evangelization mission carried out in these schools. The thesis is divided into three parts. The first part focuses on the ideal religious formation of teachers and students in a Catholic school should be according to the teaching and discipline of the Catholic Church and how this is presently performed in three local Catholic secondary schools. This identifies a gap between theory and practice. The gap lies in the absence of formation in the sacramental and, therefore, Eucharistic teaching of the Church. The second part elaborates on the Catholic understanding of the human person and the basic needs for the development of adolescents. It does this to ensure that when the thesis proposes a solution to fill the gap in the curriculum, that solution is appropriate to the needs of the subjects of religious education, that is the adolescents in Macao Catholic secondary schools. In the third part, the Eucharistic theology of Pope Benedict XVI is explored, along with its relevance to the curriculum of the schools under investigation. It examines how it could enhance the experience of the educational mission of these schools and responds to the needs for adolescent development. Finally, suggestions are provided as how to incorporate the Eucharistic theme in the curriculum and create a Eucharistic education program for an enhanced evangelization outcome. This research has significant implications for all those who are involved in Catholic education, particularly in secondary schools

Virtual reality (VR), a computer-generated 3D environment, allows one to navigate and possibly interact, resulting in real-time simulation of one or more of the user’s five senses (M. Gutierrez et al., 2008; Vince, 2004). Despite its history through past decades, this technology has quickly developed recently. Virtual tours and spaces have been widely used in the education, arts, and rehabilitation industries. According to research, it has significant effects on mindfulness (improving mood), cognitive development (better learning ability), and embodiment (relieving pain and medical conditions). This thesis aims to identify the conditions for Macao's single-user experience to achieve mindfulness in virtual reality through immersion and interactivity. With their various definitions, this research uses the two spectrums on the levels of immersion and interactivity, conducts four experiment settings with Macao residents, and collects qualitative questionnaires and quantitative survey data. The four settings differ as they tackle different aspects: spiritual memory, historical memory, aesthetic appreciation, and meditation through concept. The analysed results were then evaluated to seek better conditions for the local community to achieve mindfulness by immersing themselves in virtual reality

This doctoral research delves into the transformative potential of Hyperledger Fabric Blockchain and the Internet of Things (IoT) within business management, specifically in the development and implementation of a Computerised Maintenance Management System (CMMS). It suggests that merging these advanced technologies could revolutionise maintenance management and overall system performance. The study assesses the impact on fundamental business processes within the IoT paradigm, highlighting the role of the Hyperledger Fabric blockchain network in ensuring data integrity and enhancing transparency. The integration of Blockchain protocol with IoT offers efficient data transactions, thereby improving business data management and decision-making. The research further validates the robustness of Fabric release V2.4 for CMMS development. The study concludes by emphasising the need for additional research to understand long-term implications and challenges in different business environments

The Job Demands-Resources (JD-R) model is one of the most influential models for studying burnout and work engagement. However, the relationship between job demands and work engagement yields inconsistent results in empirical research. This study adopted the JD-R model as the theoretical base, together with the differentiated job demands approach, to examine the inconsistent relationship between job demands (i.e., emotional labor) and work engagement. Additionally, the newly proposed job resource (i.e., transformational leadership) and its relationship between burnout and work engagement were examined. Moreover, the moderating role of personal resources (i.e., emotional intelligence) was tested. Data were collected from employees working in the hospitality industry. The results revealed that (1) surface acting correlated positively with emotional exhaustion and cynicism; (2) deep acting was positively correlated with professional efficacy, cognitive, emotional, and physical work engagement; (3) the transformational leadership style negatively predicted emotional exhaustion and cynicism, while positively predicting professional efficacy, cognitive, emotional, and physical work engagement; (4) emotional intelligence moderated the relationship between deep acting, professional efficacy, and emotional work engagement; and (5) the mediation role of burnout was found in the current study

This study examined the acquisition of higher-order thinking skills in an English as a Second Language (ESL) classroom at a secondary school in Macau. It included an investigation of the way teaching might affect the development of higher-order thinking skills and language proficiency. This study also included an examination of the degree to which existing societal practices or values might have influenced the acquisition of higher-order thinking skills. Research instruments such as a questionnaire, a twelve-week experiment, pre-and post-tests and interview sessions were used for the data collection. The findings suggested that after twelve weeks the experimental groups developed higher synthetical and evaluative skills than the control groups which instead demonstrated better language skills. The results also identified incongruences between the curriculum and the expectations of the parents and employers

The demand for plastic has led to enormous plastic waste in the environment, which persist and negatively impact the ecosystems. Polyethylene terephthalate (PET) is one of the most common thermoplastic polymers available on the market. The concerns about plastic waste generated an interest in strategies to enhance its biodegradation and finding alternative polymers. In this work was investigated the possibility of using bacteria to degrade PET and to produce bioplastics (Polyhydroxyalkanoates, PHAs). Finally, the integration of the two processes was tested. Overall, the work aimed to investigate the potential to recycle PET into bioplastic using bacteria. The potential of bacterial consortia from various environmental samples to degrade PET granules in liquid matrix was investigated. . The results revealed maximum PET granules degradation of 1.1 % by one of the tested consortia. PET degradation intermediate terephthalic acid (TPA) was not detected at the end of 55 days. Fourier-transform infrared spectroscopy (FTIR) results showed major spectral peak shifts and bends on PET chemical structure compared to non-inoculated control. The biodegradation of PET films buried in the soil (A), with mangrove plants (B), and bioaugmented with a bacterial consortium (C) was also investigated. The experiments were conducted for 270 days at ambient conditions. The results revealed no difference between treatments in the degradation, with a maximum weight loss of 0.118 % in the bioaugmented treatment. Nevertheless, Scanning Electron Microscope (SEM) and FTIR results indicated significant surface changes, spectral peak shifts, and stretches in PET chemical structures. Bacterial consortia isolated from the soil of the experimental treatments were assessed for degradation of PET monomers, TPA and monoethylene glycol (MEG), and intermediate Bis(2-hydroxyethyl) terephthalate (BHET). The consortia were inoculated in flasks containing minimal media with 1000 mg/L TPA or BHET or1113 mg/L MEG as the sole carbon source. Results showed complete degradation of TPA and significant degradation of BHET (96.09%), and MEG (83.65%) by the consortia. In the second part of the study, bacteria were isolated from various environmental samples and screened for PHA production using Sudan Black B staining on colonies and smeared glass slides. Transmission Electron Microscope images were captured to confirm the intracellular PHA inclusions. A total of 35 isolates were screened for PHA, and 22 showed positive staining. The isolate showing higher levels of PHA synthesis (EC2-30-3) was identified based on 16S rRNA gene sequence as Bacillus sp. and selected for PET monomers degradation and fermentation cultures for PHA production. It was cultured in minimal (Moreira et al., 2013) media with 1000 mg/L TPA and 1113 mg/L MEG as the carbon source for eight days. The isolate grew better in media containing MEG, which was selected as a substrate model for PHA fermentation. To integrate PET monomers biodegradation and production of PHA, the isolate was cultured in 0.2 % MEG. A control with 0.2 % of glucose was prepared, and the cultures were incubated for 96 hours. Bacillus sp. EC2-30-3 showed higher PHA accumulation in media supplied with MEG (40.31%) than glucose (25.53%). This is the first report showing that Bacillus sp. uses PET monomer as carbon source to produce a biopolymer. FTIR results of the extracted PHA identified its functional units as C–H, CH3, C=O, and C–O groups. The absorption bands obtained are closely related to the structure of PHB. The study thus confirmed the ability of the isolated bacteria to degrade PET monomers and produce biopolymers. The results of this work open the possibility for upscaling the use of bacteria to mitigate the impact of PET on the environment while producing environmentally friendly bioplastics