Papers by Dr Ethan E Yeoh
Contemporary Mathematics, 2023
The cryptocurrency market, specifically the non-fungible token (NFT) market, has been gaining pop... more The cryptocurrency market, specifically the non-fungible token (NFT) market, has been gaining popularity with the rise of social finance, game finance, metaverse, and web 3.0 technologies. With the increasing interest in cryptocurrency, it is essential to develop a comprehensive understanding of the market dynamics to aid investment decisions. This paper aims to analyze the impact of news sentiment on the prices of two cryptocurrencies, Green Satoshi Token (GST) and Green Metaverse Token (GMT). The sentiment analysis model used in this study is Finance Bidirectional Encoder Representations from Transformers (FinBERT), a pre-trained deep neural network model designed for financial sentiment analysis. Additionally, we introduce the use of the Extreme Gradient Boosting (XGBoost) algorithm to evaluate the sentiment result on the model’s performance. The study period covered from March 2022 to April 2022, and the sentiment score of the result generated by FinBERT on crypto, stock market, and finance news was found to be correlated with the prices of GST and GMT. The findings suggest that the sentiment score of GST reflects changes in the price earlier than GMT. These findings have significant implications for decision-making strategies and can aid investors in making more informed decisions. The research highlights the importance of sentiment analysis in understanding the market dynamics and its potential impact on the prices of cryptocurrencies. The use of FinBERT and XGBoost algorithms provides valuable insights into market trends and can aid investors in making informed decisions.
IGI Global eBooks, Jan 6, 2023
IGI Global eBooks, Jan 6, 2023
At the end of 2019, individuals' outdoor activities were restricted due to the emergence ... more At the end of 2019, individuals' outdoor activities were restricted due to the emergence of COVID-19. As a result of this phenomenon, interest in online activities and interaction in the metaverse environment has increased. Online games have exploded in popularity with the young generation in Metaverse where they can earn money through the platforms. Thus, it is desirable to investigate emerging technology and analyse how to invest using techniques, such as sentiment analysis and machine learning (ML), to predict crypto trends. This study analysed time series data for crypto price and text, where information like news, articles, and feedback from social media can use the input to generate the sentiment score to understand the crypto trends. FinBERT is a sentiment model that was used for this study to generate the result. The AI investing framework is built to incorporate both sentiment analysis technique and …
Direct real estate investment is required large fund before able to invest. Most of the investor ... more Direct real estate investment is required large fund before able to invest. Most of the investor in Malaysia has been face the challenge to invest direct real estate nowadays. It is not easy to get expected return like previously that can be more than 6% per annual. Most of the expected return per annual in Malaysia market are below 4%, this create difficulty for them to pay their monthly mortgage loan payment that could 100% cover. An alternative investment related to real estate that have better option which could get expected return more than 5%. That is indirect real estate. For instance, real estate investment trust (REIT), and other similar type of investment in equity structure. When come to decision making for real estate investment in indirect form, there are too many information across. This will create ambiguous for investor to make better decision as they don't know which is the reliable source. Most of the investors in Malaysia were blindly invest with the information that might not valid which they collected in the market. This paper is to create a better way for investor to know how to make better decision with the secondary data and use data science to test the time series for forecasting by (ARIMA) model and predict stock price performance based on dependent variables. Eventually, this could make better decision to reduce risk and improve or optimize investment performance. Data science can cater for big data and easier to reproducible, with the data science technique it will help to continue research from the past research.
An artificial intelligence (AI) is a computer system that learn and mimic the human intelligence.... more An artificial intelligence (AI) is a computer system that learn and mimic the human intelligence. It is getting more and more advance in the coming next decades. AI capable to assist human especially when deal with big data and it could improve efficiency of the marketing and sales that more reliable and better prediction result for them to make decision. AI consist of features like Natural Language Processing, Computer Vision, Optical Character Recognition, Voice Recognition and Cognitive science that help to create advanced analytics (Albert Technologies, 2018). This intelligence machine that this research paper we evaluate is a Digital Assistance or Chatbot that consists of those features. It may also able to provide functions like calculation, remainder, and prediction that help to improve operation or productivity for marketing and sales that help them to reduce time response, improve customer service and customer satisfaction.
Many big corporations spent billions of dollars just to study on consumer behavior, they look for... more Many big corporations spent billions of dollars just to study on consumer behavior, they look for innovative way to understand how consumer make buying decision and what influence their decisions. Hence, they applied data-driven to improve business opportunity and lead more sales. Data-driven could help business to stay competitive than others. The entire of customer lifecycle will be different compare to few decades ago, the new way of data-driven are getting advanced and able to be optimized how marketing and sales team use advanced analytics to predict consumer behavior that maximize return(Lang & Rettenmeier, n.d.). They are many models from the past turn into more advanced computerize which involved using machine learning and deep learning to improve from previous researchers. Basically, consumer behavior will be going through the process of customer acquisition, customer engagement and customer retention which analytic could target for measured the key metrics within the processes. By using this data science modeling, it will provide a clear objective where marketing team can target the right audience from the result predicted, provide action to apply the right channel and advertise the right message with the right time for all the perfect timing that is much more intelligence nowadays. This report will provide a comprehensive review from the literature and identify what the model that been applied data science into the marketing & sales. We identified two model where analyzed the traditional model and modern model that involved machine learning or deep learning. This included analysis in detail from the variables for each model in various literature and provide the critical analysis on the strengths and weaknesses of each model.
Yeoh Eik Den, 2018
This paper provided the gap analysis that focus on real estate retail space and propose by using ... more This paper provided the gap analysis that focus on real estate retail space and propose by using data analytics to improve the supply and demand process that enable real estate management to make better decision to resolve the critical gaps. This included a set of key performance indicators (KPI) to monitor and control the supply chain process and optimize business value. Factors that influence the demand and supply of real estate management in Malaysia can be from government policy, economic, demographic and etc. However, there are not many of the real estate management know how to apply data to identify the potential value to this area for improve their business and how to stay more competitive advantage. The main focus on this paper is how operation excellences with identify the key factors and how data can help real estate management to stay competitive and planning that improve the sustainable environment especially in the retail space that include commercial purpose.
Many organizations today have more information ever before. In many cases, the information is not being utilized which organizations missing on the potential competitive opportunity. This may due to number of challenges that faced by management such as still comfortable with the existing method or doesn’t know how to move forward to setup the rights skills of data science team. Even they willing to hire, but there is a big gap to hire the right one in the market. This is new trend and still very less resources in the market, this need government to play an important role to build and encourage education institutes to provide such skillset to fill the gap. Data sciences and business analytics will be important and critical skills for many businesses to find the potential opportunity to improve their supply chain process nowadays. It is about the quantitative analysis and predictive modeling towards data-driven competitive strategies that could align with the sustainable strategies and improvement to the organizations supply chains process.
The world is in industrial revolution 4.0 (IR4), digital and technology advances were associated ... more The world is in industrial revolution 4.0 (IR4), digital and technology advances were associated with efficiency. When driven by new technologies and getting more towards globalization, the world of work will remove human intervention from work and replacing by the automation are changing the way how it perform from the past (Xu et al., 2018). With this revolution, the collaboration of how future work are breaking traditional boundaries, this include the social media that can change the way how employee communicate and collaboration not only between internal but also facing external resources who working to collaborate and achieve their goal together. This is call digital workplace that interconnected with internal and external resources to work together (Tencati & Zsolnai, 2009). We claims this to be more connected, flexible, lean and cost efficient on how resource communicate. This is not news as many organization already implemented this from the past decades. I believed that the digital workplace will be changes in the next future especially the current trend are talking about Artificial Intelligence (AI). AI mainly addresses on automation and intelligences that outperform beyond human capacity. With AI applied into Digital Workplace, there are more way that AI can facilitates the automate large part of business areas that were further change the way how people collaborate with using digital workplace from the past (vom Brocke et al., 2018). How technology is changing work and organization is an interesting area that what scholars would like to find out either from psychology or organization behavior (Tencati & Zsolnai, 2009). Many organizations are realize the important of workplace transformation where will reflects the modern of work styles, employee preferences and the technologies applied will change the way how the future work (Jee, 2017). For understand the effects of the technology on work and organization, we applied research based answers to implicate both research and practice about the organizational reality that might be produced in Malaysia. Thus, our objective here is to evaluate the progress, direction and the purposes how
Yeoh Eik Den, 2018
Managing supply chains, is very difficult and complex and it can be span over numbers of stages o... more Managing supply chains, is very difficult and complex and it can be span over numbers of stages or multiple geographical involved. Because of the lack of transparency with the traditional method, many companies are look into blockchain in big data technology where they can improve and transform the supply chains management process(Ghosh & Tan, 2018). Blockchain is a chain that able to track ledger and validate in real time with each transaction occurred. It keeps the record such as any point of time, who created it and etc. This paper mainly reviews and analysis of the main features in each risk management model that use by Nestle under the Milo supply chain. With understand the model, the paper includes to propose and introduce the strategy on how to sustain the process and as well as using technology such as blockchain in big data, internet of things (IoT) and data science analytics to enhance and control the supply chain process. This is to drive transparency that use new technologies for provide data that what supply chains process needs and become an essential part to establish trust from consumers and securing reputation toward the company’s brand.
Drafts by Dr Ethan E Yeoh
Real Estate Investment Trust Research Paper
Real Estate Portfolio Management Research Paper
Uploads
Papers by Dr Ethan E Yeoh
Many organizations today have more information ever before. In many cases, the information is not being utilized which organizations missing on the potential competitive opportunity. This may due to number of challenges that faced by management such as still comfortable with the existing method or doesn’t know how to move forward to setup the rights skills of data science team. Even they willing to hire, but there is a big gap to hire the right one in the market. This is new trend and still very less resources in the market, this need government to play an important role to build and encourage education institutes to provide such skillset to fill the gap. Data sciences and business analytics will be important and critical skills for many businesses to find the potential opportunity to improve their supply chain process nowadays. It is about the quantitative analysis and predictive modeling towards data-driven competitive strategies that could align with the sustainable strategies and improvement to the organizations supply chains process.
Drafts by Dr Ethan E Yeoh
Many organizations today have more information ever before. In many cases, the information is not being utilized which organizations missing on the potential competitive opportunity. This may due to number of challenges that faced by management such as still comfortable with the existing method or doesn’t know how to move forward to setup the rights skills of data science team. Even they willing to hire, but there is a big gap to hire the right one in the market. This is new trend and still very less resources in the market, this need government to play an important role to build and encourage education institutes to provide such skillset to fill the gap. Data sciences and business analytics will be important and critical skills for many businesses to find the potential opportunity to improve their supply chain process nowadays. It is about the quantitative analysis and predictive modeling towards data-driven competitive strategies that could align with the sustainable strategies and improvement to the organizations supply chains process.