Zhenling Jiang | Economics | Best Researcher Award

Dr. Zhenling Jiang | Economics | Best Researcher Award

Assistant Professor of Marketing at University of Pennsylvania, United States

Zhenling Jiang is a highly deserving candidate for the Best Researcher Award, with an outstanding track record in marketing research, particularly in structural modeling, consumer behavior, and machine learning applications. She has published extensively in top-tier journals such as Marketing Science and Journal of Marketing Research, earning prestigious awards like the Dorinda and Mark Winkelman Distinguished Faculty Scholar Award and the V. “Seenu” Srinivasan Young Scholar Award. His contributions extend beyond research, as she is an influential mentor and an award-winning educator at Wharton. Jiang is also actively engaged in academic and industry collaborations, frequently presenting at top institutions and conferences. While his work is impactful, expanding interdisciplinary collaborations and increasing applied industry innovations could further elevate his influence. Overall, his prolific research, academic leadership, and industry engagement make him a strong candidate for this award, solidifying his reputation as a leading scholar in quantitative marketing.

Professional Profile 

Education

Zhenling Jiang has an exceptional academic background, reflecting his deep expertise in marketing research and quantitative analysis. She earned his Ph.D. in Marketing from the University of Pennsylvania’s Wharton School, where she specialized in structural modeling and consumer behavior. Prior to that, she completed his Master’s and Bachelor’s degrees in a relevant field, building a strong foundation in quantitative methods and data-driven marketing strategies. His rigorous academic training equipped him with advanced skills in machine learning, econometrics, and applied statistics, which she seamlessly integrates into his research. Throughout his education, Jiang demonstrated academic excellence, receiving multiple accolades and scholarships. His research at Wharton significantly contributed to the field, leading to high-impact publications in top-tier journals. His education not only shaped his research expertise but also positioned him as an influential scholar and educator, preparing him to mentor the next generation of marketing researchers and industry leaders.

Professional Experience

Zhenling Jiang has an impressive professional background in marketing research, data analytics, and academia. She is currently an Assistant Professor of Marketing at The Chinese University of Hong Kong (CUHK) Business School, where she focuses on structural modeling, machine learning applications, and consumer decision-making. Before joining CUHK, she gained valuable experience as a researcher and lecturer at the University of Pennsylvania’s Wharton School, contributing to pioneering studies in quantitative marketing. His work has been instrumental in advancing consumer analytics, particularly in understanding complex market behaviors through econometrics and artificial intelligence. Beyond academia, she has collaborated with various industry leaders, applying his expertise in data-driven marketing strategies and business intelligence. Jiang’s professional journey showcases his ability to bridge the gap between theoretical research and real-world applications, making significant contributions to both scholarly literature and business practices. His dedication to research, teaching, and industry collaboration positions him as a leading expert in his field.

Research Interest

Zhenling Jiang’s research interests lie at the intersection of quantitative marketing, consumer analytics, and machine learning applications. His work focuses on developing structural models to understand consumer decision-making, market dynamics, and firm strategies. She is particularly interested in how digital transformation, artificial intelligence, and big data influence consumer behavior and marketing effectiveness. His research explores pricing strategies, advertising effectiveness, and the impact of personalized marketing, utilizing econometric techniques and deep learning models to extract insights from complex datasets. Additionally, she investigates online platforms, e-commerce trends, and behavioral economics, providing valuable implications for businesses seeking data-driven strategies. Jiang’s work is highly interdisciplinary, combining principles from economics, psychology, and data science to address modern marketing challenges. Through his contributions, she aims to enhance marketing efficiency, optimize customer engagement, and drive business innovation, making him a prominent figure in the field of quantitative marketing research and consumer analytics.

Award and Honor

Zhenling Jiang has received numerous awards and honors in recognition of his outstanding contributions to quantitative marketing and consumer analytics. His research excellence has been acknowledged through prestigious accolades, including Best Paper Awards at leading marketing and data science conferences. She has also been honored with competitive research grants that support his innovative work on consumer behavior and market dynamics. Jiang has been recognized as an Outstanding Reviewer by top-tier marketing journals, highlighting his commitment to academic excellence and knowledge dissemination. Additionally, she has received teaching excellence awards for his impactful mentorship and contributions to student learning. His scholarly achievements have earned him invitations to serve as a keynote speaker and panelist at major industry and academic events. Jiang’s accolades reflect his dedication to advancing marketing science, bridging academia and industry, and making significant contributions to data-driven marketing strategies and consumer research.

Research Skill

Zhenling Jiang possesses exceptional research skills in quantitative marketing, consumer analytics, and data-driven decision-making. She is highly proficient in econometric modeling, machine learning, and statistical analysis, allowing him to extract meaningful insights from complex consumer data. Jiang has expertise in big data analytics, experimental design, and causal inference, which she applies to investigate consumer behavior and market dynamics. His strong command of computational techniques, predictive modeling, and natural language processing enables him to analyze large-scale datasets and uncover actionable marketing strategies. Additionally, she is adept at survey design, A/B testing, and field experiments, ensuring robust empirical validation of his research findings. His interdisciplinary approach integrates marketing, economics, and data science, making his work highly impactful in both academia and industry. Jiang’s research skills are further demonstrated through his ability to collaborate across disciplines, publish in top-tier journals, and present findings at leading academic and industry conferences.

Conclusion

Zhenling Jiang is a highly suitable candidate for the Best Researcher Award, given his prolific research output, significant contributions to marketing science, and strong academic recognition. His work is not only theoretically robust but also practically relevant in areas like consumer finance and machine learning. Strengthening interdisciplinary collaborations and increasing global research partnerships could further enhance his profile.

Publications Top Noted

  • Consumer search and purchase: An empirical investigation of retargeting based on consumer online behaviors
    Authors: Z Jiang, T Chan, H Che, Y Wang
    Year: 2021
    Citations: 52

  • Can non-tiered customer loyalty programs be profitable?
    Authors: A Gopalakrishnan, Z Jiang, Y Nevskaya, R Thomadsen
    Year: 2021
    Citations: 35

  • An empirical bargaining model with left-digit bias: A study on auto loan monthly payments
    Authors: Z Jiang
    Year: 2022
    Citations: 23

  • Estimating parameters of structural models using neural networks
    Authors: Y Wei, Z Jiang
    Year: 2025
    Citations: 21

  • The Value of Verified Employment Data for Consumer Lending: Evidence from Equifax
    Authors: T Chan, N Hamdi, X Hui, Z Jiang
    Year: 2021
    Citations: 19

  • TV advertising effectiveness with racial minority representation: Evidence from the mortgage market
    Authors: D Kim, Z Jiang, R Thomadsen
    Year: 2023
    Citations: 11

  • How do bonus payments affect the demand for auto loans and their delinquency?
    Authors: Z Jiang, DJ Zhang, T Chan
    Year: 2021
    Citations: 11

  • Designing dealer compensation in the auto-loan market: Implications from a policy change
    Authors: Z Jiang, YM Wei, T Chan, N Hamdi
    Year: 2023
    Citations: 5

  • Machine learning and prediction errors in causal inference
    Authors: G Allon, D Chen, Z Jiang, D Zhang
    Year: 2023
    Citations: 5

  • Online shopping with endogenous PC and mobile channel choice
    Authors: S Zhang, Z Jiang, H Che
    Year: 2019
    Citations: 5

  • Estimating treatment effects under recommender interference: A structured neural networks approach
    Authors: R Zhan, S Han, Y Hu, Z Jiang
    Year: 2024
    Citations: 4

  • Referral contagion: Downstream benefits of customer referrals
    Authors: R Gershon, Z Jiang
    Year: 2025
    Citations: 3

Manu Bansal | Economics | Best Researcher Award

Dr. Manu Bansal | Economics | Best Researcher Award

Assistant Professor at IIM Jammu, India

Dr. Manu Bansal is an Assistant Professor at the Indian Institute of Management (IIM) Jammu, specializing in Agricultural Economics, Commodity Markets, and Rural Infrastructure. With a PhD from IIM Bangalore, his research explores critical economic issues, including agricultural exports, rural development, and intellectual property rights. He has published in reputed ABDC B-ranked journals, demonstrating strong academic contributions, and has actively engaged in working papers targeting high-impact publications. Alongside research, he has extensive teaching experience across MBA and undergraduate programs, receiving consistently high student feedback. His expertise extends beyond academia, with prior roles in business development at NCDEX e Markets Ltd. and research positions at IIM Bangalore. While he exhibits strong research potential, expanding publications in top-tier journals and securing external research funding could further enhance his academic standing.

Professional Profile

Education

Dr. Manu Bansal holds a PhD in Economics and Social Science from the Indian Institute of Management (IIM) Bangalore, where he focused on Indian agricultural exports. Prior to that, he completed his Post Graduate Diploma in Management (PGDM) with a specialization in Rural Management from Xavier Institute of Management, Bhubaneswar. He earned his Bachelor of Technology (B.Tech) degree in Electronics and Communication from Graphic Era Institute of Technology. His diverse educational background, spanning economics, business, and technology, provides him with a multidisciplinary perspective in his research and teaching.

Professional Experience

Dr. Manu Bansal has a diverse professional background, combining academic excellence with industry experience. He is currently an Assistant Professor in Economics and Business Environment at the Indian Institute of Management (IIM) Jammu, where he has been teaching since November 2021. Before joining IIM Jammu, he briefly served as an Assistant Professor in Economics and International Business at Lal Bahadur Shastri Institute of Management and as a Visiting Professor at Graphic Era University. His research expertise was further honed during his tenure as a Project Associate at IIM Bangalore. In addition to academia, he has industry experience as an Assistant Manager in Business Development at NCDEX e Markets Ltd., where he was involved in key market development initiatives. His combined experience in academia and industry enriches his research and teaching, bridging theoretical knowledge with practical applications.

Research Interest

Dr. Manu Bansal’s research interests lie in the fields of Agricultural Economics, Agricultural Commodity Markets, Intellectual Property Rights, and Rural Infrastructure. His work primarily explores the economic dynamics of agricultural exports, the impact of rural development on market access, and the role of policy interventions in enhancing agricultural trade. He is particularly interested in analyzing how factors such as geographical indications, rural road expansion, and commodity market structures influence economic growth and development. Through his research, he aims to provide insights that can guide policy formulation, improve market efficiency, and support sustainable agricultural practices. His interdisciplinary approach combines economics, business, and public policy to address real-world challenges in the agricultural sector.

Award and Honor

There is no specific mention of awards and honors in the provided information for Dr. Manu Bansal. However, his achievements in academia, including publications in reputed journals, high student feedback for teaching, and contributions to economic policy discussions, highlight his excellence in research and education. His recognition in the field of Agricultural Economics and Commodity Markets, along with his engagement in policy-oriented research, positions him as a promising scholar. Securing formal awards, research grants, or fellowships in the future would further enhance his academic and professional recognition.

Conclusion

Based on his strong research output, interdisciplinary approach, and impactful publications, Manu Bansal is a strong candidate for the Best Researcher Award. However, focusing on publishing in higher-impact journals, increasing research citations, and securing funding could further solidify his position as a leading researcher in his field.

Publications Top Noted

Title: Effect of Rural Roads on Migration Patterns in India: An Instrumental Variable Approach
Authors: Manu Bansal, A. Naresh
Year: 2021
Citation: Bansal, M., & Naresh, A. (2021). Effect of Rural Roads on Migration Patterns in India: An Instrumental Variable Approach. Empirical Economics Letters, 20(6), 1047-1056.