Valerie Good serves as an Assistant Professor in the Department of Marketing and Transportation at the Walton College of Business, University of Arkansas, where she contributes to academic research and teaching in marketing disciplines. Her research spans critical domains including: Sales Management : Investigating salesperson well-being, motivation, and digital transformation impacts Retail Marketing : Analyzing online retail formats and product sales dynamics B2B Marketing : Exploring brand leverage and end-user engagement strategies Corporate Social Responsibility : Examining CSR's role during economic recessions Analysis of her 15 recent publications (2021-2025) reveals three dominant trajectories: (1) Human elements in sales processes, including resilience, loneliness, and purpose-driven motivation; (2) Digital transformation effects on retail formats, lead quality, and sales arrangements; (3) Strategic applications of corporate social responsibility during economic volatility. Her work consistently bridges theoretical rigor with practical sales and marketing applications, demonstrating increasing focus on psychological factors within commercial contexts.
Julien Chanal is a researcher at the Faculty of Psychology and Educational Sciences, University of Geneva, specializing in Methodology and Data Analysis (MAD group). His work bridges educational psychology, motivation theory, and neuropsychology through empirical studies on self-determination, physical activity, and cognitive function. Primary affiliation: University of Geneva Research focus: Motivation and executive function assessment Key areas: Physical education, materialism effects, neuropsychological testing His research spans two decades, producing 38 publications with over 19,000 views. Recent projects examine motivation multidimensionality (2025), aerobic fitness-cognition links (2024), and neural correlates of materialism (2018). Despite extensive publication history, specific student names remain unspecified. Methodological innovations include epoch-length analysis in physical education (2015), self-concept modeling (2009), and neuropsychological norm establishment in Cameroon (2009). His work remains actively cited across disciplines, though no scientific awards are explicitly documented in available sources.
Ravi Pappu is an Associate Professor of Marketing at the School of Business, University of Queensland, Australia. He holds a PhD in marketing from the University of New England and an MBA with Distinction from the University of Waikato, New Zealand. PhD, University of New England, Australia MBA (Distinction), University of Waikato, New Zealand Postgraduate Diploma in Marketing (Distinction), University of Waikato Bachelor (First Class) in Mechanical Engineering, JNTU Anantapur His research bridges marketing communications and brand management, focusing on: Consumer decision-making across brand types Brand equity measurement frameworks Celebrity endorsement effectiveness Corporate sponsorship strategies Country-of-origin effects on brand perception Retailer brand value assessment His work has been downloaded over 370,000 times, with multiple papers in top journals like: Journal of the Academy of Marketing Science European Journal of Marketing Journal of International Business Studies Journal of Business Research Scientific awards highlight his contributions: 2018 JPBM Most Impactful Article Award 2016 Emerald Outstanding Reviewer Award 2015 UQ Teaching Excellence Award 2006 UQ Research Excellence Award He supervises projects in: Celebrity endorsement Corporate sponsorship Country branding Brand innovativeness
Jason Hartline is a Professor of Computer Science at the McCormick School of Engineering, Northwestern University, with a courtesy appointment in Managerial Economics & Decision Sciences. His research bridges computer science and economics, focusing on mechanism design, auction theory, and approximation algorithms. Ph.D. in Computer Science from the University of Washington (2003) Postdoctoral Fellow at Carnegie Mellon University (2003-2004) Researcher at Microsoft Research (2004-2007) His work develops methodologies to analyze and design economic systems using computational theory, particularly in auction mechanisms and non-truthful settings. Key contributions include the textbook Mechanism Design and Approximation and frameworks for Bayesian and prior-independent mechanism design. Recent publications (2018-2023) span topics like non-truthful mechanism learning, multi-dimensional agent modeling, and computational law. Collaborations include researchers from Harvard, Microsoft, and institutions across economics and theoretical computer science. Grants include multiple NSF awards (CCF, ECCS, HDR TRIPODS) for projects in data economics, machine learning integration, and peer grading systems. Former advisees hold academic positions at Stanford, Yale, and Penn State.
Aric Rindfleisch is the John M. Jones Professor of Marketing and Executive Director of the Illinois MakerLab at the University of Illinois Urbana-Champaign’s Gies College of Business. He serves as area chair of marketing and Vernon Zimmerman Faculty Fellow. His research focuses on 3D printing, new product development, consumer values, and AI applications in marketing. Rindfleisch has held editorial roles across 10 journals and received teaching accolades, including recognition by Princeton Review as one of America’s top professors. Education: Bachelor of Science from Connecticut State University (1987) Master of Business Administration from Cornell University (1990) Doctor of Philosophy from University of Wisconsin-Madison (1998) Rindfleisch’s research interests span innovation ecosystems, digital manufacturing, consumer behavior in the sharing economy, and materialism’s societal impact. His work bridges academic rigor with practical applications, particularly in leveraging technology like 3D printing for sustainable innovation. His recent publications highlight themes such as AI’s role in qualitative research, consumer responses to crises like the pandemic, and disruptive innovations in retail and transportation. Rindfleisch actively contributes to academic discourse through editorial roles and serves as a thought leader in marketing strategy and innovation management. Awards: Princeton Review’s “The Best 300 Professors” (2020) His leadership at Illinois MakerLab drives hands-on innovation, emphasizing collaboration between academia and industry. Rindfleisch’s work integrates marketing, technology, and consumer psychology to address modern challenges in product development and societal consumption patterns.
Stefan Hoderlein is a Professor in the Department of Economics at Emory University. His expertise lies in econometrics, with a focus on nonparametric methods, panel data analysis, and structural models. He holds a PhD from Bonn University and the London School of Economics (2002), and a Diplom Volkswirt from Bonn University (1997). His research interests include advanced econometric techniques such as instrumental variable estimation, demand analysis, and random coefficient models. He has contributed to methodologies addressing unobserved heterogeneity, endogeneity, and identification challenges in economic data. His work often explores applications in consumer behavior, market structure, and policy evaluation. Recent research trends in his publications emphasize nonparametric identification strategies, panel data methodologies, and the integration of big data into econometric frameworks. His technical contributions include Stata modules for statistical testing and frameworks for analyzing aggregate demand and welfare effects. While no specific awards are listed, his extensive publication record reflects sustained scholarly impact in econometric theory and applied economics. Advising details and grant information are not explicitly provided in the sources, though his work often involves collaborative research teams. His office is located in the R. Rollins Building (R428), and he maintains an active academic website.
Erik Hjalmarsson is a Professor of Banking and Financial Economics at the Department of Economics, University of Gothenburg. He holds the Felix Neubergh Chair and previously served as Director of the Centre for Finance. His research focuses on empirical asset pricing, financial econometrics, and long-run stock returns. Hjalmarsson earned his PhD from Yale University and has held roles at the Federal Reserve Board and Winton Capital Management. Education: PhD (Yale University, 2005), M.Sc. in Econometrics (London School of Economics, 2000), B.Sc. in Mathematical Statistics (University of Gothenburg, 1999). Research interests include stock return predictability, high-frequency trading, and econometric methods. His work has been published in top journals like the Journal of Finance and Journal of Financial Economics . Key grants include funding from the Swedish Research Council and Marianne and Marcus Wallenberg Foundation. Awards include the Carl Anderson Prize (2004) and multiple stipends for doctoral education. He supervises PhD students and advises on central bank policies. His recent studies explore long-horizon returns, inflation expectations, and portfolio strategies. Teaching includes PhD courses in econometrics and financial economics. He serves on editorial boards and as a referee for leading journals.
J. Isaac Miller is a Professor and Department Chair in the Department of Economics at the University of Missouri. His research focuses on econometrics, time series analysis, energy economics, and climate change impact assessment. He has developed structural econometric models for climate and energy demand, with applications to policy evaluation and forecasting. Key research areas: Climate econometrics, mixed-frequency time series, energy demand modeling, and economic impacts of climate change. Recent publications highlight statistical frameworks for climate sensitivity analysis, energy consumption forecasting, and mitigation strategy optimization. Teaching includes graduate courses in econometric theory and advanced time series methods.
Amanda N. Laubmeier is an Assistant Professor in the Department of Mathematics & Statistics at Texas Tech University. Her research integrates mathematical modeling with ecological systems, focusing on predator-prey dynamics, pest suppression, and biodiversity mechanisms. She holds a Ph.D. in Applied Mathematics from North Carolina State University (advised by H. T. Banks) and a B.S. in Mathematics from the University of Arizona. Her postdoctoral work at the University of Nebraska-Lincoln (under Richard Rebarber and Brigitte Tenhumberg) further developed her expertise in ecological modeling. Her research interests emphasize theoretical exploration and data-driven validation of ecological processes, particularly in agricultural and climate-sensitive contexts. Key areas include predator community dynamics, temperature effects on ecosystems, and the compatibility of biological control with pesticides. She actively engages in scientific outreach to promote inclusivity in academia and supports underserved communities in STEM. Her recent publications explore topics such as trap crop efficacy, predator-prey models under climate change, and parameter estimation in ecological systems. These studies highlight interdisciplinary approaches combining mathematical theory with empirical validation. She also contributes to educational initiatives like the Science Meets Popular Culture Speaker Series, bridging academic research with public engagement. Laubmeier advises students through her research group, which focuses on ecological modeling projects. While no named advisees are listed, her group’s work is detailed on her website. Her grants and funding history are not explicitly mentioned, but her CV (dated Jan. 2025) likely provides further details. She advocates for inclusive academic practices and integrates outreach into her professional activities.
Kannan Srinivasan is the H.J. Heinz II Professor of Management, Marketing and Business Technology at Carnegie Mellon University's Tepper School of Business, a position he has held since 1999. Prior to joining CMU, he taught at the business schools of the University of Chicago and Stanford University. His academic career spans over three decades with significant contributions to marketing science and data analytics. His educational background includes: Ph.D. in Management from University of California Los Angeles (1986) MBA in Marketing/Finance from Xavier School of Management, Jamshedpur, India (1980) BA in Engineering from University of Madras, Chennai, India (1978) Srinivasan's research focuses on advanced data analytics models applied to marketing problems, with particular expertise in internet-generated large-scale data analysis. His work bridges the gap between theoretical marketing models and practical business applications, especially in the areas of algorithmic pricing, consumer behavior analysis, and AI-driven marketing strategies. He has pioneered research in dynamic pricing systems, location-aware marketing technologies, and the economic implications of AI in consumer markets. Analysis of his recent publications reveals a strong trend toward examining the intersection of artificial intelligence, consumer welfare, and market dynamics. His work increasingly focuses on ethical implications of AI in marketing, algorithmic bias, and the socioeconomic impacts of digital platforms across various sectors including real estate, social media, and e-commerce. His scientific achievements include: Elected Fellow of the Informs Society of Marketing Science (2013) for lifetime contribution to the field Served as President of the Informs Society of Marketing Science Holds multiple patents related to time and location aware dynamic push content, dynamic pricing, and online advertising Srinivasan has advised numerous doctoral students whose careers have led them to faculty positions at top institutions including Duke, Harvard, Columbia, Yale, University of Chicago, Wharton, University of Michigan, and Indian Institute of Management Bangalore. He has extensive consulting experience with large firms and startups, translating academic research into practical business applications. His professional service includes editorial roles at prestigious journals including Management Science, Marketing Science, and Quantitative Marketing and Economics, as well as significant committee service within CMU including the Elliott D. Smith Award Committee and various Dean's Advisory committees. His research is organized around several key initiatives focused on applying advanced analytics to solve complex marketing problems, with particular emphasis on developing interpretable AI models that balance business objectives with consumer welfare considerations.
Adam Dubé is an Associate Professor in the Department of Educational and Counselling Psychology at McGill University's Faculty of Education. He directs the Technology, Learning, & Cognition (TLC) Lab and holds a McGill Faculty of Education Distinguished Teacher award. His research focuses on how educational technologies like tablet computers and digital games enhance learning, particularly in mathematics and cognitive development. He has published extensively on educational app design, digital assistant impacts on children’s cognitive theories, and teacher adoption of educational technologies. Education: Postdoctoral Research Fellow, University of Toronto PhD in Psychology, University of Regina MA in Psychology, University of Regina Research Interests: Educational Technology & Teaching Innovation Cognitive Development Child-Tablet Interaction Mathematical Cognition Educational App Evaluation Awards: McGill Distinguished Teacher Award (2021) Fellow, American Educational Research Association Fellow, Society for Research in Child Development Grants & Funding: SSHRC Insight Development Grants (2021-2022, 2020-2021) MITACS Accelerate Grant (2020-2021) Labs/Teams: Lead researcher at the TLC Lab, collaborating with Ubisoft Montreal on educational game curriculum guides.
Ben Faber is an Associate Professor in the Department of Economics at the University of California, Berkeley. His research focuses on the intersection of international trade and development economics, with particular emphasis on migration patterns, market integration, and policy interventions in rural and urban contexts. He joined UC Berkeley in 2013 and currently teaches courses on international economics and supervises doctoral students. His research explores topics such as the economic impacts of senior migration on local development, rural-urban migration dynamics, and the welfare implications of incomplete price data. He has also studied agricultural policy scalability, responsible sourcing practices in global supply chains, and the role of e-commerce in connecting rural regions. His work frequently integrates empirical evidence from case studies in Mexico, China, and the Democratic Republic of Congo. Faber’s recent publications analyze the effects of retail globalization on household welfare, the relationship between tourism and coastal economic development, and the challenges of artisanal mining in cobalt supply chains. His research methodologies often involve innovative use of scanner data, spatial analysis, and econometric modeling to address complex development questions.
Greg Taylor is an Associate Professor and Senior Research Fellow at the Oxford Internet Institute (OII), University of Oxford. His research focuses on digital economy dynamics, competition policy, and regulation, with expertise in platform markets, data-driven mergers, and antitrust frameworks. He advises UK and global regulators and has held roles such as Director of Graduate Studies (2018-2022) and MSc Programme Director. Taylor’s work bridges theoretical economics with policy impact, addressing issues like digital bundling, consumer search behavior, and data’s role in market competition. Education: PhD in Economics from the University of Southampton. Research Interests: Digital markets, competition policy, platform economics, network economics, and the economics of data. His recent projects include modeling data-driven mergers and analyzing anticompetitive bundling strategies. Teaching: Teaches Internet Economics , covering competition, information asymmetry, and network economics. Supervises doctoral students with backgrounds in economics and game theory applications. Grants & Funding: Supported by the Carnegie Corporation, John Fell Fund, and Dieter Schwarz Stiftung. Advises HM Government and the Competition and Markets Authority (CMA) on digital policy. Labs/Teams: Leads the Data-driven Mergers project and contributes to the Research Programme on AI, Government, and Policy.
Giuseppe Moscarini is the Philip Golden Bartlett Professor of Economics at Yale University and a Research Associate at the National Bureau of Economic Research (NBER). He co-chairs the Micro and Macroeconomic Perspectives on the Aggregate Labor Market working group at NBER and serves as Co-Director of the Research Program in Macroeconomics at the Cowles Foundation. Previously, he held the Henry Kohn Associate Professorship at Yale and was a Sloan Foundation Research Fellow. His research focuses on labor markets, unemployment, wage inequality, and business cycles, with recent work analyzing labor market flows and employer-to-employer transitions. He has developed methodologies to measure and predict wage inflation dynamics, including a novel Phillips curve framework. Education: Ph.D. in Economics from MIT (1996), Laurea in Economia e Commercio from Università di Roma La Sapienza (1991). Research emphasizes theoretical and empirical labor market dynamics, including pricing, monetary policy, and information economics. His work bridges macroeconomic and microeconomic perspectives, with contributions to understanding firm size impacts on job creation and cyclical job ladder dynamics. Articles highlight employer mobility, wage dispersion, and post-recession labor market challenges. Awards: None explicitly listed. Editorial roles include co-Editor of Theoretical Economics and Associate Editor of the Journal of Economic Theory. Grants and lab affiliations include the Cowles Foundation and Federal Reserve Bank collaborations. Advising includes PhD student Francesco Beraldi.
Meng Liang is a Teaching Professor in the Centre for Interdisciplinary Methodologies (CIM) at the University of Warwick. Her research focuses on digital media economies, algorithmic media systems, and the attention economy, particularly in East Asian contexts. She holds a Ph.D. in Media and Film Studies from University College London (UCL), supported by the Overseas Research Scholarship (ORS-UCL). Her doctoral work examined participatory media and attention economy models in China since 1995. Key research interests include the cultural and social impacts of algorithmic media platforms like TikTok, emotional dependency in user demographics, and the interplay between media technology and cultural norms. She has conducted research at MIT’s Global Media Technology and Cultural (GMTaC) Lab (2019-2020). Her recent work explores data attraction models reshaping social media dynamics, Chinese compressed modernity in short video platforms, and transmedia storytelling in East Asia. She has presented at international conferences including MIT Worlding 2023 and the Critical Digital and Social Media Research Conference (2019). Notable awards include the ORS-UCL scholarship. She teaches the module IM901: Cultures of the Digital Economy at Warwick.
