Xinyi Hong | Consumer Willingness to Pay | Best Researcher Award

Xinyi Hong | Consumer Willingness to Pay | Best Researcher Award

Mr Xinyi Hong Guangzhou University of China, China

With a Ph.D. in Agricultural Economics and Food Business from the Agriculture and Food Science School at University College Dublin (UCD) in Dublin, Ireland, which she completed from 2015 to 2021 under the UCD-CSSA Full Scholarship, she brings a wealth of academic expertise to her current role. As a Postdoctoral Researcher at the School of Innovation and Entrepreneurship at Guangzhou University in China since December 2021, she focuses on researching tax cuts, fee reduction, digitalization, and enterprise innovation. Her work aims to drive forward understanding and innovation in these critical areas, contributing to advancements in entrepreneurship and economic development.

Education:

She holds a rich academic background, culminating in a Ph.D. in Agricultural Economics and Food Business from the Agriculture and Food Science School at University College Dublin (UCD) in Dublin, Ireland, which she pursued from 2015 to 2021 under the UCD-CSSA Full Scholarship. Her doctoral research, titled “Sensory Evaluation and Consumers’ Perception of Functional Pork Sausages: A Cross-Cultural Perspective,” delved into the intricate interplay between sensory perception and consumer behavior in the context of functional food products. Prior to her doctoral studies, she completed her Master of Science in Strategic Management & Planning at UCD Michael Smurfit Business School, where she earned a GPA of 3.56 and received 2.1 Upper Second Class Honors. She laid the foundation for her academic journey with a Bachelor of Science in International Business from the Economics School at Minzu University of China, Beijing, graduating with a GPA of 3.52. Through her academic pursuits, she has demonstrated a keen interest in interdisciplinary research at the intersection of economics, business, and food science, aiming to contribute meaningfully to the understanding of consumer behavior and market dynamics in the agricultural and food industry.

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Experience:

She is currently serving as a Postdoctoral Researcher at the School of Innovation and Entrepreneurship at Guangzhou University in China since December 2021. In this role, she conducts research in areas such as tax cuts, fee reduction, digitalization, and enterprise innovation. Prior to this, she worked as a Senior Industry Consultant at Hangzhou Bizhi Technology Co., Ltd., where she provided customized digitalization upgrade plans for client companies based on their data centers and AI big data intelligent service systems. She has also contributed to promoting Sino-Irish scientific research, educational, and cultural activities as an Assistant at the Irish Institute for Chinese Studies at University College Dublin in Ireland. Earlier, she served as a Teaching Assistant at University College Dublin, where she provided tutorials and assistance in modules related to economics, Chinese economy, and food marketing. Additionally, she has experience in procurement assistance and business negotiation with European food companies at Beijing Fortuneroad Trading Company in China and served as a Social Media Manager at Designer Studio “We Are Islanders” in Dublin, where she established Chinese online media platforms and managed daily website operations.

Publications:

  1. Exploring the relationship between digital transformation and green innovation: The mediating role of financing modes Published By : 2024 
  2. Exploring the Impact of China’s Internal Circulation Strategy on Its Stock Market under Deglobalization. Published By : 2024 
  3. Consumer Preferences for Processed Meat Reformulation Strategies: A Prototype for Sensory Evaluation Combined with a ChoiceBased Conjoint Experiment  Published By : 2023
  4. The Effects of Nutrition and Health Claim Information on Consumers’ Sensory Preferences and Willingness to Pay. Published By : 2022
  5. Do the government subsidies inhibit the entity overfinancialization? Fresh evidence from China. Published By : 2022
  6. Chinese consumers’ willingness-to-pay for nutrition claims on processed meat products, using functional sausages as a food medium. Published By : 2021

Adnan Amin | Customer Analytics, Machine Learning, Churn Prediction | Member

Adnan Amin | Customer Analytics, Machine Learning, Churn Prediction | Member

Dr Adnan Amin Institute of Management Sciences Peshawar, Pakistan

Adnan Amin earned his M.Sc. in Computer Science from the University of Peshawar in 2008. He received his MS-CS degree (highest 1st class honors with distinction) and a Ph.D. degree (with Scholastic Honours) in data mining and machine learning from the Institute of Management Sciences (IMSciences) Peshawar, Pakistan, in 2015 and 2023, respectively. In November 2015, he joined IMSciences as a lecturer at the Center for Excellence in Information Technology. He is the lead of IM|DigiSol and the faculty adviser for the Computing and Innovation Society (IMCIS) at IMSciences. Before, he worked as an international consultant for curriculum and academic development at the School of ICT, NIMA Kabul, which was connected to the University of Jyvaskyla in Finland. This was part of a World Bank-funded project for Maxwell Stamp PLC, London (Project Code: P102573). Dr. Adnan’s research and innovation interests are industry-driven and cross-disciplinary. He focuses on developing and commercializing digital solutions and data mining/machine learning research innovations for a variety of industries, such as education, telecommunications, and healthcare. He has completed nearly 8 research projects in collaboration with international universities. He has served as the track chair of the WorldCist’21 workshop (LCBUDAMLT), the session chair of the ICITA’22, and a member of the program committees of numerous conferences including WorldCist, SDIWC, and DATA’23. He has (co) authored 29+ publications, including 16 journal articles, 11 conferences, and 2 book chapters in Springer, and obtained nearly 1000 citations with an h-index score of 14 and an i-index score of 16.

Education:

He completed his Ph.D. in Computer Science with a specialization in Data Mining & Machine Learning from the Center for Excellence in IT at the Institute of Management Sciences, Peshawar, Pakistan, in March 2023. His research focused on developing an adaptive learning approach for customer churn prediction using naïve Bayes. Prior to his Ph.D., he earned his MS in Computer Science with the highest 1st class honors and distinction from the same institution in May 2015, where he conducted research on a similar topic. He also holds an M.Sc. in Computer Science from the University of Peshawar, which he completed with a Grade of A+ in March 2008.

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Experience:

He has been serving as a lecturer at the Institute of Management Sciences in Peshawar, Pakistan, since November 2015. In this role, he teaches both graduate and undergraduate students and leads IM DigiSol, the institute’s in-house software house. Additionally, he holds the position of Web & Database Administrator (BPS-17) at the Directorate of Information Technology, Government of KP, where he spearheads the computerization efforts of the Special Branch Police Department and Counter Terrorism Department. Prior to this, he worked as an I.T/ERP Trainer at Rehman Medical Institute & Hospital in Peshawar, Pakistan, from 2012. He also served as an international consultant for curriculum and academic development at the School of ICT, NIMA Kabul, Afghanistan, from 2009 to 2011, as part of a World Bank-funded project implemented through Maxwell Stamp PLC, London. In this capacity, he provided teaching support to undergraduate students.

Publications:

  1. Comparing oversampling techniques to handle the class imbalance problem: A customer churn prediction case study Cited By : 294, Published By : 2016
  2. Customer churn prediction in the telecommunication sector using a rough set approach Cited By : 258, Published By : 2017
  3. Customer churn prediction in telecommunication industry using data certainty Cited By : 232, Published By : 2018
  4. Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods Cited By : 88, Published By : 2019
  5. Churn prediction in telecommunication industry using rough set approach Cited By : 51, Published By : 2015
  6. Customer churn prediction in telecommunication industry: with and without counter-example Cited By : 40, Published By : 2014
  7. Just-in-time customer churn prediction in the telecommunication sector Cited By : 39, Published By : 2020
  8. Just-in-time customer churn prediction: With and without data transformation Cited By : 30, Published By : 2018
  9. A comparison of two oversampling techniques (smote vs mtdf) for handling class imbalance problem: A case study of customer churn prediction Cited By : 29, Published By : 2015
  10. Compromised user credentials detection in a digital enterprise using behavioral analytics Cited By : 27, Published By : 2019