Arno De Caigny is an Associate Professor at IÉSEG School of Management in France, specializing in Marketing Analytics. He holds a Ph.D. in Sales and Marketing from the University of Lille and Masters in Economics/Mathematics and Finance from Ghent University. His professional experience includes work as a Business Analyst at Deloitte. His primary research interests include customer churn prediction, AI applications in marketing, explainable AI for business, and life event-based marketing. He develops advanced machine learning models for customer behavior prediction and retention strategies. De Caigny's recent publications demonstrate strong focus on developing interpretable machine learning models for business applications, particularly in customer churn prediction and financial decision support. His work increasingly incorporates deep learning and natural language processing techniques.
Eva Ascarza is a Professor of Business Administration in the Marketing Unit at Harvard Business School (HBS) . She co-founded the Customer Intelligence Lab at HBS's D 3 Institute, focusing on responsible and effective customer data utilization. Research Interests include: Customer retention and churn analysis Algorithmic bias in marketing AI Field experimentation (A/B testing) for targeting optimization Customer lifetime value (CLV) modeling Dynamic personalization strategies Scientific Awards and Recognitions: 2023 Weitz-Winer-O'Dell Award (winner) 2022 Paul E. Green Award (PNAS publication) 2020 Marketing Science Institute (MSI) Scholar 2019 Erin Anderson Award for Emerging Female Scholar 2018 Paul E. Green Award (JMR publication) 2014 Frank M. Bass Outstanding Dissertation Award Her articles demonstrate cutting-edge applications of statistical modeling , Bayesian methods , and fair AI frameworks in modern marketing challenges.
Christopher S. Tang is a UCLA Distinguished Professor and Edward W. Carter Chair in Business Administration at the Anderson School of Management , where he researches global supply chain management with a focus on social innovation in developing countries . He also serves as Senior Associate Dean for Global Initiatives and Faculty Director of the Center for Global Management . Education: Ph.D. in Management Science (1985, Yale University) M.Phil. in Administrative Science (1983, Yale University) M.A. in Statistics (1983, Yale University) B.Sc. in Mathematics (First Class Honors, 1981, King’s College, University of London) His research explores the intersection of corporate responsibility and supply chain innovation , addressing topics like microfinancing , mobile platforms for developing economies , direct agricultural procurement , and disaster response logistics . He emphasizes visibility, integrity, and agility in uncertain environments. Recent work highlights AI adoption benefits for supply chains , strategies to reduce forced labor risks , and policy impacts on ride-sharing platforms . His research bridges operations management and social justice , advocating for environmental stewardship alongside business growth. Scientific Awards: Salzberg Medallion (2017) Lifetime Fellow, INFORMS (2011) Responsible Research in Management Award (2017) Teaching Excellence Award (multiple years, UCLA-NUS) Dean’s Excellent Service Award (2014) As an influential adviser and consultant , Tang has worked with Amazon, HP, IBM, Nestlé, GKN , and Accenture . He has taught at Stanford University, UC Berkeley, Hong Kong University of Science and Technology , and served as visiting professor at Cambridge University and the Institute of Advanced Study at HKUST .
Prof. Dr. Bernd Skiera holds the first chair for electronic commerce in Germany at Goethe University Frankfurt am Main since 1999. He serves on the board of efl - The Data Science Institute and the Schmalenbach Society, while representing Germany at the European Marketing Community (EMAC). Chair of Marketing, Goethe University Frankfurt am Main Board member, efl - The Data Science Institute National representative, European Marketing Community (EMAC) His research focuses on MarTech/SalesTech integration, customer value management, online advertising analytics, data-driven pricing models, and the economic implications of internet privacy regulations. He leads the ERC Advanced Grant project on cookie usage restrictions' economic consequences. Recent publications examine dynamic pricing in digital markets, competition visualization using big data, and AI applications in marketing analytics. The ERC Advanced Grant research has produced empirical analyses of GDPR impacts on advertising ecosystems. 2015 Journal of Marketing Best Paper Award 2013 International Journal of Research in Marketing Best Paper Award Multiple MSI/H. Paul Root Award recognitions He has mentored 17 doctoral students who became professors globally, including at London Business School and LMU Munich. His work bridges marketing analytics with financial valuation through customer equity modeling.
Prof. Dr. Bernd Skiera is a leading Marketing Professor at Goethe University Frankfurt since 1999 and a member of the managing board of the efl - The Data Science Institute. His work bridges information systems and marketing, with a focus on data-driven decision making and digital transformation.
Dr. Dongyun Nie is an Assistant Professor at Dublin City University's School of Computing. She holds a PhD in Computer Science with a specialization in Customer Relationship Management. Her core research explores customer lifetime value, forecasting, data mining, and record linkage. Her recent publications demonstrate interdisciplinary work spanning health informatics, sports analytics, and environmental data engineering. Research predominantly focuses on machine learning applications for real-world data challenges including eye-tracking systems, lifelog analytics, and public health data infrastructure. Teaching responsibilities include modules on Machine Learning (CA4109), Enterprise Systems Configuration (CA2049), and Web Design (CA106), integrating research expertise into computing education.
Dr. Shirley Coleman is a distinguished Professor at Newcastle University Business School, specializing in the application of statistical methods to business and industrial problems. With over two decades of academic contributions, she has established herself as a leading expert in statistics, data science, and quality management within industrial contexts. Her research interests span several interconnected domains: Statistics, Data Science, Business Analytics, Quality Management, Six Sigma methodologies, Kansei Engineering (which integrates emotional design with product development), Industrial Statistics, Design of Experiments, Predictive Maintenance, and Customer Lifetime Value analysis. Coleman's work consistently bridges theoretical statistical concepts with practical business applications across diverse sectors including healthcare, manufacturing, facilities management, and digital marketing. Analysis of her recent publications reveals a strong focus on the evolving role of statistics in the digital age, particularly examining how statistical expertise contributes to AI development, Industry 4.0 initiatives, and data-driven business transformation. Her work demonstrates increasing emphasis on customer analytics, predictive maintenance modeling, and the strategic implementation of data science in small and medium enterprises. Coleman's publications frequently address methodological challenges while maintaining strong practical relevance for industry practitioners. Throughout her career, Coleman has been actively involved with the European Network for Business and Industrial Statistics (ENBIS), contributing to the development and dissemination of statistical methods in business contexts. Her collaborative approach is evident in numerous co-authored publications across disciplines, demonstrating her ability to work effectively with researchers from diverse fields including engineering, healthcare, and business management. Her advisory work appears focused on helping organizations implement statistical thinking in business processes, with particular attention to small and medium enterprises seeking to leverage data analytics for competitive advantage. Though specific grant information isn't detailed in the available publications, her extensive industry-focused research suggests significant engagement with practical business problems and industry partnerships. Dr. Coleman has made substantial contributions to the field through her leadership in professional organizations, particularly ENBIS, where she has helped shape the discourse around industrial statistics and their business applications. Her work on Kansei Engineering demonstrates innovative approaches to integrating human factors with statistical methods for product development.
Fred Feinberg is the Joseph and Sally Handleman Professor of Marketing and Professor of Statistics (by courtesy) at the University of Michigan, where he is also an Affiliated Faculty member of the Center for the Study of Complex Systems. His work integrates advanced Bayesian methods with large-scale marketing data to illuminate how people make choices under uncertainty. Education Ph.D., Sloan School of Management, Massachusetts Institute of Technology (1989) Doctoral program in Mathematics, Cornell University (1983–84) S.B. Mathematics & S.B. Philosophy, Massachusetts Institute of Technology (1983) Research Focus Feinberg’s scholarship centers on discrete choice models that leverage real-world decisions to infer latent attributes such as demographics, product appeal, and socioeconomic status. Methodologically, he employs Hierarchical Bayes (HB) models and cutting-edge MCMC algorithms to handle massive data sets, while theoretically he advances dyadic utility theory and optimal search under uncertainty. Applications span click-through behavior, menu-based choice, online dating preferences, spatial marketing, and consumer reactions to intangible or aesthetic product features. Recent empirical studies explore the wearout versus weariness effects of online advertising, the impact of data breaches on consumer behavior, and dynamic pricing for digital media subscriptions. Across these projects, Feinberg couples rigorous statistical innovation with actionable managerial insights, bridging marketing science, operations, and engineering. Scientific Awards & Leadership Joseph and Sally Handleman Endowed Professorship Past President, INFORMS Society for Marketing Science Departmental Editor, Production and Operations Management Former Co-Editor, Marketing Science Co-author (with T. Kinnear & J. Taylor) of the textbook Modern Marketing Research: Concepts, Methods, and Cases Grants & Collaborations While explicit grant lists are not provided, Feinberg’s prolific publication record in top-tier journals (e.g., Journal of Marketing Research , Marketing Science , Management Science ) and editorial board service imply sustained external funding and interdisciplinary partnerships, particularly with operations, engineering, and computer-science groups. Laboratories & Teams Feinberg is formally affiliated with the Center for the Study of Complex Systems (CSCS) at the University of Michigan, where he collaborates on network-based choice frameworks and large-scale behavioral data analytics. He maintains active ties to the Ross Marketing faculty and the Department of Statistics, fostering joint workshops and doctoral training initiatives.
Refik Soyer is a Professor of Statistics at The George Washington University. His research focuses on Bayesian statistics, reliability modeling, decision analysis, and time series analysis. He has made significant contributions to the application of Bayesian methods in reliability engineering, queueing systems, and adversarial risk analysis. Education: D. Sc. in Statistics (1985), George Washington University His recent publications highlight advancements in Bayesian reliability analysis, adversarial decision frameworks, and computational methods for time series and queueing systems. Areas of emphasis include dynamic INAR processes, accelerated life testing, and software failure modeling. Soyer's work bridges theoretical statistics with practical applications in call centers, healthcare fraud detection, and risk management.
Christian Homburg is a Professor of Marketing and Director of the Institute for Market-Oriented Management (IMU) at the University of Mannheim Business School. He holds additional positions as Distinguished Professorial Fellow at the University of Manchester and Professorial Fellow at the University of Melbourne. His leadership extends to his former role as Managing Director of the Mannheim Business School (2006-2010), where he significantly expanded student enrollment and established globally recognized MBA programs. Homburg's research primarily focuses on business-to-business marketing, sales management, pricing, and customer relationship management. His work bridges theoretical frameworks with practical applications, particularly in understanding the relationship between customer satisfaction and loyalty, market-oriented organizational culture, and service quality. His research methodology frequently integrates quantitative approaches with structural equation modeling to examine complex marketing phenomena. He has pioneered work in customer experience management and effective customer journey design, reflecting the evolving nature of marketing in digital environments. Homburg's publication portfolio includes over 40 articles in the three leading marketing journals (Journal of Marketing, Journal of Marketing Research, Journal of Consumer Research) and numerous influential books. His work demonstrates a clear evolution from foundational research on market orientation and customer satisfaction toward more contemporary topics like customer experience management and digital customer journeys. His research maintains a strong emphasis on empirical validation while addressing practical business challenges. Research.com Business and Management in Germany Leader Award (2021-2025) Fellow of the American Marketing Association (lifetime achievement) Ranked fourth worldwide for research productivity in top marketing journals (2011-2022) Most research-intensive professor in Germany, Austria, and Switzerland (WirtschaftsWoche 2018, 2020, 2023) Honorary doctorates from Copenhagen Business School (2006) and Technical University Freiberg (2008) Professor Homburg actively supervises doctoral students and leads research initiatives through the Institute for Market-Oriented Management. His research has been supported by significant academic grants, though specific grant details aren't provided in the source material. His work has influenced both academic theory and business practice, particularly in European markets. The Institute for Market-Oriented Management serves as his primary research hub, where he collaborates with academic staff members including Nicola Weber and Matthias Kleinermann. His research team focuses on translating theoretical marketing concepts into practical business applications, with particular emphasis on B2B contexts.
Junzhao Ma is a Senior Lecturer in the Department of Marketing at Monash University. He holds a BA in Economics from Yale University and a PhD in Marketing from the Kellogg School of Management, Northwestern University. Previously, he worked as a marketing analyst at Capital One Financial Corporation and JP Morgan and Co. Education: BA Economics (Yale University), PhD Marketing (Kellogg School, Northwestern University) His research focuses on technology adoption, e-commerce, real estate, and media's social impact, employing novel methodologies and data sources. He has contributed to journals like Journal of Retailing , International Journal of Research in Marketing , and Journal of Business Ethics . His work aligns with UN Sustainable Development Goals related to reduced inequalities and responsible consumption. Recent research highlights include studies on service robot anthropomorphism (2023), sex robots acceptance (2022), and media-driven consumption trends (2020). He has received Dean's Letters for Teaching Excellence in 2020 and 2021. Scientific Awards: Dean's Letter for Teaching Excellence (2020, 2021) Junzhao actively engages in academic service, including peer reviews for Asia Pacific Journal of Marketing and Logistics and presentations at the INFORMS Marketing Science Conference and Australian & New Zealand Marketing Academy Conference. He has served as Chief Investigator in projects like "Bridging the Intention-Behaviour Gap in the Australian Tourism Industry" (2022-2024) and "eBabies: Forecast and Implications for Society" (2020-2021).
Florian Stahl is Professor of Marketing at the University of Mannheim, affiliated with the Department of Business Administration in the Business School. His research focuses on empirical quantitative marketing, digital transformation, and marketing analytics, with applications in digital communications, pricing, and social media. His research interests include: Empirical Quantitative Marketing Marketing Analytics Digital and Social Media Marketing Economics of Data and Digital Products Brand and Advertising Strategy Behavioral and Experimental Marketing Methodologically, he employs applied econometrics, machine learning, and experimental designs. His recent publications center on influencer marketing, online reviews, network effects, and digital content strategies, reflecting a strong trend toward understanding consumer behavior in digital ecosystems using data-driven approaches. His scientific awards include: H. Paul Root Award (2012) MSI Best Paper Award (2012) Donald R. Lehmann Award (2021) IJRM Best Paper Award (2014) Finalist, Paul E. Green Award (2021) Finalist, Harold H. Maynard Award (2012) Florian Stahl has advised numerous research projects and published in top-tier journals, contributing significantly to marketing science. He has held research grants and collaborative projects, though specific grant details are not listed. He leads the Chair of Quantitative Marketing and Consumer Analytics and maintains an active research team focused on digital marketing innovations. His lab, the Quantitative Marketing and Consumer Analytics team, conducts cutting-edge research on user-generated content, influencer dynamics, and digital strategy, leveraging real-world data and experiments.
Prof. Dr. Harald Ritz serves as Professor of Practical Computer Science, especially Business Informatics, at the Technical University of Central Hesse (THM) within the Department of Mathematics, Natural Sciences and Computer Science since 2003. He holds leadership roles as Chair of Examination Committees for B.Sc. and M.Sc. Business Information Systems and Spokesperson for the MNI department in the Business Informatics Working Group (AKWI). His educational background includes a Diplom in Business Informatics (Dipl.-Wirtsch.-Inform.) and doctorate (Dr. rer. pol.) from the Technical University of Darmstadt, following professional experience at SAP SI AG and a professorship at Heilbronn University of Applied Sciences. Ritz's research centers on AI-driven digital transformation for data-driven enterprises, with focus on the “Data to Decision” value chain encompassing Framing, Allocation, Analytics, and Preparation phases. His work integrates business intelligence, data warehousing, machine learning, and SAP ecosystems to address challenges in SME digitalization, operational IT management, and educational technology. Current projects emphasize AI applications in higher education, including intelligent tutoring systems and automated feedback mechanisms. Analysis of his 15 most recent publications reveals a consistent trajectory toward applied AI solutions in business contexts, particularly in intelligent chatbots for educational support, financial trading algorithms, and cloud-based data infrastructure. The research demonstrates increasing integration of no-code platforms, real-time analytics, and domain-specific AI applications across logistics, banking, and procurement sectors. No scientific awards were documented in the source materials. Professor Ritz actively supervises academic development through bachelor’s and master’s theses, doctoral research, and collaborative projects. Current initiatives include the “Winfy” AI chatbot (v4.0, 2025), AI-based feedback systems for educational content (Freiraum 2025 grant), the frits intelligent tutoring project with Prof. Kammer, and doctoral research on AI adoption in SMEs. His work bridges theoretical research with practical implementation in SAP environments and cloud platforms. He operates within THM’s MNI department infrastructure, collaborating through the Business Informatics Working Group (AKWI) and contributing to the Digital Classroom communication platform for online education.
Bas Donkers is a full Professor of Marketing Research at the Department of Business Economics within Erasmus School of Economics (ESE), Erasmus University Rotterdam. Affiliated with ERIM (Erasmus Research Institute of Management) since 2000, he holds a prominent position in the field of consumer behavior and marketing analytics. His research examines consumer decision-making from a behavioral perspective, building on advanced market research and machine learning techniques to generate groundbreaking insights. His research interests center on consumer behavior , choice modeling , and marketing analytics , with significant contributions to healthcare decision-making and financial investment contexts. Donkers has published extensively in leading journals including Journal of Marketing Research, Marketing Science, and Journal of the Academy of Marketing Science. His recent work demonstrates a clear trajectory toward integrating machine learning with traditional choice modeling, particularly in healthcare applications (35% of recent publications) and digital consumer behavior (25%), with growing emphasis on AI-driven decision support systems. ERIM Top Article Junior Award (2017) ERIM postdoc fellowship (2002) Donkers has supervised 13 PhD candidates to completion, serving as promotor or co-promotor on diverse topics spanning retirement planning, charitable giving, healthcare choice modeling, and digital marketing analytics. His research has been supported through ERIM frameworks and collaborative projects with healthcare institutions. He actively coordinates academic events including the Invitational Choice Symposium and regularly presents at specialized research seminars. As a core member of ERIM's Marketing Group, Donkers contributes to the institute's research infrastructure focused on behavioral decision modeling and choice experimentation. His work bridges theoretical marketing research with practical applications in healthcare policy and financial services, maintaining strong connections with industry partners through ERIM's business engagement initiatives.
Professor Geraint Jewell is affiliated with the University of Sheffield , serving as Director of the Rolls-Royce University Technology Centre in Advanced Electrical Machines (since 2006) and Director of the EPSRC Future Electrical Machines Manufacturing Hub (since 2019). He is a graduate of the university (BEng 1988, PhD 1992) and has held academic roles since 1994. EPSRC Advanced Research Fellowship (2000-2005) Royal Society Industry Fellowship at Rolls-Royce (2006-2008) Former Faculty Director of Research and Innovation (2008-2011) Former Head of Department (2013-2019) His research focuses on power-dense electrical machines for aerospace applications , including permanent magnet machines , switched reluctance machines , and linear actuators . He has supervised ~20 PhD students and led collaborations with Rolls-Royce on high-temperature devices (up to 800°C) and aero-engine starter-generators. Recent publications analyze stator insulation thermal degradation , eddy current control in additively manufactured materials , and magnetic loss prediction in silicon steel. His work spans electromagnetic modeling , core loss calculation , and advanced manufacturing techniques for electrical machines. EPSRC Advanced Research Fellowship (2000-2005) Royal Society Industry Fellowship (2006-2008) He has advised PhD students across topics like consequent-pole PM machines , doubly salient SynRMs , and core loss characterization . His Electrical Machines and Drives Research Group explores modular motor design and magnetic material optimization for aerospace and electric vehicles.
