Oli Rui | Quantitative Hypotheses | Best Researcher Award

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Oli Rui | Quantitative Hypotheses | Best Researcher Award

Prof Dr Oli Rui, China Europe International Business School, China

Prof. Dr. Oliver Rui is a distinguished scholar with a strong background in finance and accounting. His impressive academic and professional achievements make him a suitable candidate for the Best Researcher Award.

Publication profile

google scholar

Academic and Professional Background

Dr. Rui holds advanced degrees in Economics and Finance from prestigious institutions, including Oklahoma State University and the University of Houston. He has held significant academic positions, including a tenured professorship at the Chinese University of Hong Kong and currently serves as a Professor of Finance and Accounting at CEIBS. Additionally, he holds professional designations as a Certified Financial Analyst (CFA) and Financial Risk Manager (FRM).

Teaching and Leadership

He has taught a variety of courses at top universities such as Tsinghua University, Hong Kong Polytechnic University, and Shanghai National Institute of Accounting. Dr. Rui has also been recognized for his teaching excellence, receiving awards for his contributions to education, including the Faculty Teaching Award at CUHK and the Teaching Excellence Award at CEIBS.

Research Excellence

Dr. Rui has an extensive publication record with over 70 papers in reputable Economics, Finance, Accounting, and Management journals. His research covers a wide range of topics, including corporate governance, stock market dynamics, and behavioral finance. His work has had significant impact, with high citation counts and publications in top-tier journals like the Journal of Financial Economics and the Academy of Management Journal. He has also authored several textbooks, further contributing to his field.

Awards and Recognition

Dr. Rui’s contributions to research have been recognized with multiple awards, including the Research Excellence Award at CEIBS and the prestigious CEIBS Medal for Research Excellence. His consistent output and high-quality research have earned him a reputation as a leading scholar in his field.

Professional and Public Engagement

Beyond academia, Dr. Rui is actively involved in various professional organizations and has served in leadership roles, including as Vice President of Shanghai Fintech Union. He is a sought-after expert in finance, with frequent contributions to international media.

Research focus

OM Rui’s research primarily focuses on corporate governance, stock market dynamics, and investor behavior, particularly within the context of emerging markets like China. His work explores ownership structures, CEO compensation, and gender diversity’s impact on corporate performance and fraud. Additionally, he investigates behavioral biases such as overconfidence and the disposition effect in trading, as well as the dynamic relationships between stock returns, trading volume, and volatility. His studies often provide empirical evidence from China, contributing to a deeper understanding of financial markets and governance mechanisms in emerging economies. 📊📈🌍

Conclusion

Given Dr. Rui’s extensive academic credentials, impactful research, teaching excellence, and professional leadership, he is a highly deserving candidate for the Best Researcher Award. His contributions to finance and accounting are both significant and influential, making him a standout in his field.

Publication top notes

Ownership structure, corporate governance, and fraud: Evidence from China

Corporate performance and CEO compensation in China

Trading performance, disposition effect, overconfidence, representativeness bias, and experience of emerging market investors

Gender diversity and securities fraud

Ownership, two-tier board structure, and the informativeness of earnings–Evidence from China

Stock market linkages: evidence from Latin America

The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence

The dynamic relation between stock returns, trading volume, and volatility

Public governance and corporate finance: Evidence from corruption cases

How ownership and corporate governance influence chief executive pay in China’s listed firms

Faroque Ahmed | Quantitative Hypotheses | Best Researcher Award

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Faroque Ahmed | Quantitative Hypotheses | Best Researcher Award

Mr Faroque Ahmed, Ural Federal University, Russia, Russia

Faroque Ahmed is a PhD researcher at Ural Federal University, Russia 🇷🇺, specializing in development studies and financial economics 📊. He holds an M.Sc. and B.Sc. in Statistics from Islamic University, Kushtia-Jhinaidah, where he achieved top positions in his class 🥇. With research interests in quantile-based methods, VARs, data mining, and machine learning 🤖, he has served as a Senior Research Associate at the Bangladesh Institute of Governance and Management (BIGM) and as a Research Assistant at the Islamic University, working on credit card fraud detection. Faroque also boasts excellent academic achievements and IELTS proficiency 🏅📚.

Publication profile

Scopus

Education

📚 With a strong academic background, I hold a Master’s in Statistics from Islamic University, Kushtia-Jhinaidah, completed in 2015 with an ‘A’ grade and a CGPA of 3.91, securing first-class first position 🥇. My Bachelor’s in Statistics from the same university, completed in 2014, earned me an ‘A’ grade and a CGPA of 3.84, ranking second in first class 🥈. Prior to this, I excelled in Science, achieving a perfect GPA of 5.00 in both my Higher Secondary (2009) and Secondary (2006) School Certificates at New Govt. Degree College and Masjid Mission Academy, respectively 🌟.

Experience

Since 2022, the user has been a PhD Researcher at the Laboratory of International & Regional Economics (LIRE) at the Graduate School of Economics and Management (GSEM), Ural Federal University, Yekaterinburg, Russia 📚🌍. Concurrently, they have served as a Senior Research Associate at the Bangladesh Institute of Governance and Management (BIGM), affiliated with the University of Dhaka, since 2019 🏢🇧🇩. Previously, from 2016 to 2019, they worked as a Research Assistant at the Quantitative Financial Economic Development (QFED) Lab in the Dept. of Statistics at Islamic University, Kushtia, Bangladesh, focusing on credit card fraud detection using machine-learning algorithms under the supervision of Md. Altaf Hossain 💳🤖.

Research Interest

I am passionate about the fields of development studies and financial economics, focusing on advanced methodologies and data analysis. My expertise includes quantile-based methods, various types of VARs, and data mining techniques. I am proficient in leveraging machine learning and big data analysis for robust econometric modeling. Through these skills, I aim to contribute to the understanding and development of economic policies and practices. 📊💡🔍📉💻🔎

Awards

In 2017-18, I was awarded the UGC research grant for my master’s project on the socio-economic effects of remittance on Bangladeshi migrant households. Under the supervision of Md. Altaf Hossain, an Associate Professor at Islamic University, Kushtia, Bangladesh, I conducted extensive research in this area. Additionally, in 2017, I completed Big Data Analytics Training through the LICT project of the ICT Ministry, People’s Republic of Bangladesh. 📚🔍💼 The grant and training significantly enhanced my research capabilities and data analysis skills, contributing to my academic and professional growth. 📈🌏

Research focus

Faheem Ahmed’s research primarily focuses on the intersection of economics, environmental studies, and technological applications. His work includes examining the impact of geopolitical risks on global finance, analyzing the economic growth-environment nexus, and exploring the implications of AI technology on industrial outputs and energy consumption. Additionally, Ahmed delves into health outcomes influenced by governance and education, social distancing behaviors during Covid-19, and predictive modeling for air quality and credit card fraud detection. His interdisciplinary approach combines machine learning with economic and environmental analysis, reflecting a broad interest in sustainable development and risk management. 🌍📊💡🌱📉🔍.

Publication top notes

Robot race in geopolitically risky environment: Exploring the Nexus between AI-powered tech industrial outputs and energy consumption in Singapore

Semi-Supervised Machine Learning Method for Predicting Observed Individual Risk Preference Using Gallup Data

Assessing the impact of Russian–Ukrainian geopolitical risks on global green finance: a quantile dependency analysis

An inquiry into the achievements in health outcomes of Bangladesh: role of health expenditure, income, governance and female education

Integration of theory of planned behavior into actual social distancing behavior amid Covid-19

Economic growth and environmental pollution nexus in Ba

An analysis of energy, environment and economic growth (EEE) nexus: a 2SLS approach

Creative social media use for Covid-19 prevention in Bangladesh: a structural equation modeling approach

A comparative study of credit card fraud detection using the combinati

Predicting air quality of Dhaka and Sylhet divisions in Bangladesh: a time series modeling approach

 

Raksmey Sann | Quantitative Hypotheses | Best Researcher Award

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Raksmey Sann | Quantitative Hypotheses | Best Researcher Award

Prof Raksmey Sann, Khon Kaen university, Thailand

Dr. Raksmey Sann is an accomplished academic specializing in International Tourism, Hospitality, and Events Management. He earned his Ph.D. from the National Pingtung University of Science and Technology, Taiwan, with First-Rank Honor and a dissertation on cross-cultural online complaining behavior in the hospitality industry 📚. Dr. Sann is currently a faculty member at Khon Kaen University, Thailand, where he teaches research methodology, tourism management, and sustainable event management 🌏. His research focuses on service marketing, data mining, and consumer behavior, with numerous publications in top-tier journals. He has received multiple scholarships and research grants for his outstanding work in the field 🎓.

Publication profile

google scholar

Education

I hold a distinguished academic background in International Tourism, Hospitality, and Events Management, having earned a degree with First-Rank Honor from the National Pingtung University of Science and Technology, Taiwan, in September 2020 🎓. His dissertation, “Investigating Cross-Cultural Online Complaining Behavior in the Hospitality Industry,” was guided by a notable committee, including Professor Li, Yi-Ming (chair). I was awarded the Excellent Foreign Student Scholarship 🏆. His MSc, also from the same university, focused on “Cross-Cultural Tourist Online Hotel Booking Behaviour” and received Second-Rank Honor. I previously graduated with a BA from Mahasarakham University, Thailand, with First-Class Honor, supported by the Princess Maha Chakri Sirindhorn Scholarship 👑. My academic journey began with a BS Ed in TEFL from the Royal University of Phnom Penh, Cambodia 📚.

Honors and Awards

During my academic journey, I was honored to receive multiple prestigious scholarships. From 2018 to 2020, I was awarded the Excellent Foreign Student Scholarship, a full government scholarship by the Ministry of Education, Taiwan 🇹🇼. Similarly, from 2016 to 2018, I received the same distinguished scholarship 🇹🇼. Earlier, I was privileged to earn the Her Royal Highness Princess Maha Chakri Sirindhorn Scholarship from 2011 to 2015, a full government scholarship by the Ministry of Education, Thailand 🇹🇭. My academic excellence was also recognized in Cambodia 🇰🇭, where I received the National Excellent Student Scholarship from 2009 to 2011.

 

Research Experience

In 2020, at the National Pingtung University of Science and Technology, Taiwan, I completed my dissertation titled “Investigating Cross-Cultural Online Complaining Behavior in the Hospitality Industry: An Application of Content Analysis and Data Mining Approach,” under the guidance of Professor Pei-Chun Lai. This research delved into service marketing, service quality, and online consumer behavior, employing natural language processing, data mining, and big data analytics to uncover insights 📊. Previously, in 2018, I conducted exploratory research on cross-cultural tourist online hotel booking behavior, focusing on the impact of electronic word-of-mouth (eWOM). This thesis, also advised by Professor Lai, encompassed e-commerce, cross-cultural studies, and eWOM, using multivariate analysis, qualitative methods, and content analysis to draw its conclusions 🌐.

 

Teaching Experience

Since December 2021, I have been a faculty member at Khon Kaen University’s Faculty of Business Administration and Accountancy in the Department of Tourism Innovation Management. I teach courses such as Research Methodology, Research Project, English for Tourism Business, and Sustainable Event Management, engaging with 120 undergraduate students each semester. For graduate students (MSc. & PhD), I cover Qualitative Research Methodology, Multivariate Analysis, and other advanced topics with over 20 students per semester. Previously, I taught various hospitality and tourism management courses at Khon Kaen University International College (Dec 2020 – Nov 2021). My teaching career began as a teaching assistant at National Pingtung University of Science and Technology (2016-2020) and teaching English to orphaned children in Phnom Penh (2009-2011). 📚🌍🎓

Recognition 🏅

His accolades include the Best Outstanding PhD Research Performance (2021) from NPUST, Taiwan, and the Distinguished Master Thesis Award (2018) from the TSC Thesis Symposium, Taiwan. He has also won several presentation and competition awards throughout his academic career. 🥇

Research focus

R. Sann’s research primarily focuses on the hospitality industry, particularly on online customer behavior and sentiment analysis using advanced data analytics techniques. Key areas of interest include understanding online complaining behavior, the impact of cultural backgrounds on service perceptions, and the application of big data analytics to online reviews. Sann’s work also explores the effects of service quality, guest experiences, and health-related concerns on consumer behavior, integrating theories like the theory of planned behavior. This multidisciplinary approach leverages tools like NLP and machine learning to derive insights from large datasets, aiming to enhance service quality and customer satisfaction in hospitality. 🏨📊🧠💬

Publication top notes

Understanding homophily of service failure within the hotel guest cycle: Applying NLP-aspect-based sentiment analysis to the hospitality industry

Predicting Online Complaining Behavior in the Hospitality Industry: Application of Big Data Analytics to Online Reviews

Online complaining behavior: Does cultural background and hotel class matter?

Modelling theory of planned behavior on health concern and health knowledge towards purchase intention on organic products

Review papers on eWOM: prospects for hospitality industry

Analysis of online customer complaint behavior in Vietnam’s hotel industry

Crisis Adaptation in a Thai Community-Based Tourism Setting during the COVID-19 Pandemic: A Qualitative Phenomenological Approach

An extension of the theory of planned behaviour in Thailand cycling tourism: The mediating role of attractiveness of sustainable alternatives

Multidimensional scale development and validation: university service quality (UNIQUAL)

Topic modeling of the quality of guest’s experience using latent Dirichlet allocation: Western versus eastern perspectives

 

 

 

Quantitative Hypothesis Award

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Quantitative Hypothesis Award

Introduction:

Welcome to the Quantitative Hypothesis Award, honoring individuals who excel in proposing and testing hypotheses using quantitative methods. This prestigious award celebrates the rigor, innovation, and impact of quantitative research in advancing knowledge across various domains.

Award Overview:

The Quantitative Hypothesis Award recognizes individuals who demonstrate excellence in formulating, testing, and validating hypotheses using quantitative techniques, contributing to the advancement of scientific inquiry and evidence-based decision-making.

Eligibility:

  • Open to researchers, scientists, and scholars utilizing quantitative methods in their work
  • No age limits apply
  • Qualification: Demonstrated proficiency in quantitative analysis and hypothesis testing
  • Publications: Evidence of quantitative research findings published in peer-reviewed journals or presented at academic conferences
  • Recurrements: Continued engagement in quantitative research and hypothesis-driven inquiry

Evaluation Criteria:

Candidates will be evaluated based on the following criteria:

  1. Clarity and precision in formulating quantitative hypotheses
  2. Soundness and robustness of quantitative methodology used for hypothesis testing
  3. Rigor and validity of data analysis and interpretation
  4. Impact and significance of research findings on advancing knowledge or informing decision-making

Submission Guidelines:

  • Submit a detailed biography highlighting quantitative research expertise and achievements
  • Include an abstract summarizing the quantitative hypothesis, methodology, and key findings
  • Provide supporting files such as research papers, data sets, statistical analyses, and visualizations

Recognition:

Recipients of the Quantitative Hypothesis Award will receive:

  • A prestigious award certificate
  • Recognition at a prominent scientific conference or symposium
  • Opportunities for collaboration and networking with quantitative researchers and practitioners

Community Impact:

Winners of the award are expected to inspire and promote excellence in quantitative research, fostering a culture of data-driven inquiry and evidence-based decision-making within their respective communities and beyond.

Biography:

A comprehensive biography outlining the candidate's quantitative research background, expertise, and contributions to the field is required.

Abstract and Supporting Files:

Candidates must submit an abstract summarizing their quantitative hypothesis, methodology, and key findings, along with supporting files such as research papers, data sets, statistical analyses, and visualizations to demonstrate the rigor and impact of their work.