KEJIA HU: BUSINESS THINKER IN HUMAN-AI INTEGRATION
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Research Focus:
From Service Systems and Forecasting to Human-Algorithm Interaction

My academic odyssey commenced with the pivotal task of aligning service system designs with their overarching strategic visions. Drawing from deep empirical investigations, I decoded the nuances of human behavior within these systems, encompassing both rationally predictable patterns and those influenced by innate psychological tendencies. Simultaneously, my exploration into business analytics led to the invention of forecasting algorithms. Implementing them unveiled a compelling observation: the dynamic interplay between humans and algorithms in tangible business settings.

The insights from my foundational work in service operations and forecasting weren't merely individual achievements; they illuminated the prelude to a broader, industry-evolving narrative. In this AI era, the spotlight isn't on algorithms superseding humans, but on reshaping their collaborative relationship: Human-Algorithm Interaction. I advocate that with AI's ascendance, we don't sideline humans, but elevate them. This vision, molded by my prior research, drives my present pursuits into how businesses can cultivate a harmonious alliance between humans and algorithms, resulting in exceptional performance and a more fulfilling human experience.

Achievements and Reflections: My research have garnered attention from prominent academic journals, won numerous awards, and have been highlighted by various media outlets. This has further led to invitations as a speaker at leading academic and industrial forums.  My services on the boards of INFORMS Service Science Section and POMS College of Service Operations and editorial roles for flagship journals such as Production and Operations Management and Journal of Operations Management have provided invaluable opportunities to engage, learn, and contribute. In the realm of industry, I am grateful for the collaborations with a myriad of enterprises, from ambitious startups to Fortune 500 giants. These partnerships reaffirm the pertinence of my research in real-world settings, and I am ever eager to bridge academic insights with practical challenges.
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Figure 1. Research Focus

Research Description

In the quest to understand and optimize business operations, my academic journey has been shaped by a progressive understanding of service systems, the art and science of forecasting, and the eventual synthesis of both in the realm of human-algorithm interaction.

Service System Design: Strategy and Behavioral Insights

Delving deep into the domain of service operations, I've underscored the imperative of aligning service system design with its overarching strategic vision. Recognizing the intrinsic human element in such systems, my studies prominently feature Behavioral Service Operations. Here, I weave together human behaviour observed in service interactions, leveraging insights from economic rationally patterns to innate psychology tendencies. Moving further, my dedicated exploration in Omnichannel Service Management crystallizes the realization that a mere increase in customer engagement channels doesn't inherently translate to enhanced customer or provider benefits. Drawing from this, I've articulated strategies of channel specialization and integration, guiding entities on leveraging dedicated channels for distinct customer segments or amalgamating diverse channels for seamless service delivery.
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​Impact: This line of research stands recognized, with accolades from esteemed platforms like INFORMS and POMS, media coverage in Kellogg Insight and Vanderbilt News, and tangible impacts via collaborations with industry leaders like Marriott, Starwood, and super-platforms such as Meituan and JD.

Forecasting: Navigating Business Complexities with Predictive Precision

Armed with robust statistical training and inspired by real-world industrial challenges, I've ventured into the world of business analytics, with a specialized focus on forecasting. By harnessing both statistical and machine learning methodologies, I've crafted predictive algorithms catering to diverse challenges—from deciphering traffic data nuances in intricate networks to anticipating demand for novel products without historical sales.
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Impact: This research trajectory isn't just theoretical. Its implications resonate in accolades like being a finalist at the M&SOM Practice-based Competition, media highlights in outlets like Kellogg Insight, and practical adoptions by heavyweights like the U.S. DOE and prominent healthcare organizations.

Human-Algorithm Interaction: The Nexus of Service and Forecasting

Human-Algorithm Interaction is a compelling intersection where my extensive studies in both forecasting and human behavior within service systems converge. These twin pillars of research have provided me with a unique lens to scrutinize the nuanced dynamics between individuals and the algorithms they interface with. The renowned Jointown case, which graces the list of top 100 MBA cases, encapsulates this perfectly. While the case reveals the sophistication of modern algorithms, it equally accentuates the indispensable role of managerial foresight—from astute strategy formulation to the design of effective incentives and team reorganization—in guiding human teams to harmoniously interact with algorithmic systems. Our ongoing investigations expand on these foundations into diverse sectors: consultancy, where computational recommendations meet human acumen; healthcare diagnosis, where AI augments but doesn't supplant the clinician's discernment; manufacturing, where algorithms streamline operations overseen by human vigilance; and sales planning, where algorithmic forecasts are enriched by human insights. In my research of human-algorithm interaction, I call for three transformational imperatives: repositioning human roles, redesigning business processes, and rethinking business models. It's pivotal for businesses to adapt and evolve, creating environments where AI and human endeavors aren't just complementary but synergistic.
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​Impact: This multi-faceted delve into human-algorithm partnerships has elicited noteworthy recognition, both in academic and corporate domains. Collaborative endeavors with Fortune 500 companies have offered us unparalleled insights from real-world deployments. The acclaim of our research is further mirrored in its selection for top-tier MBA case repositories and a series of public-speaking forums, consistently captivating audiences in their hundreds. My Four-level AI framework article coauthored with PWC senior partner Jasper Xu got featured in the first edition of WAIC magazine - WAIC UP. 
By seamlessly bridging the worlds of service systems and forecasting methodologies, my research paves the way for a deeper exploration into human-algorithm interaction. At its core, it advocates for a harmonious alliance between algorithmic insights and human thinking.

Research List

Research Area:  🔵 Service System Design, 🟡 Forecasting, 🟢 Human-Algorithm Interaction.

Appeared/Forthcoming

Research Papers
🔵 1. "Supplier Selection Criteria under Heterogeneous Sourcing Needs: Evidence from an Online Marketplace for Selling Production Capacity," with Kong Lu and ZhenzhenJia
Production and Operations Management, ​Accepted. Link
🔵 2. “Delegation with Technology Migration: An Empirical Analysis of Mobile Virtual Network Operators,” with Fan Zou, Yan Dong, and Sriram Venkataraman.
Management Science, ​Accepted. Link
        🎉202021 DSI Doctoral Research Showcase Award
🔵 3. “WeStore or AppStore: Customer Behavior Differences in Mobile Apps and Social Commerce,” with Nil Karacaoglu.
Production and Operations Management, Accepted. Link
         🎉2021 INFORMS TIMES Best Working Paper Third Place
🔵 4. “Service Chains' Operational Strategies: Standardization or Customization? Evidence from the Nursing Home Industry,” with Lu Kong and Rohit Verma. 
Manufacturing & Service Operations Management, 24, no. 6 (2022): 3099-3116. Link
        📰 Media Coverage: Vanderbilt Business Live April 20, 2022
🔵 5. “Reproducibility in Management Science,” with Fišar, M., Greiner, B., Huber, C., Katok, E., Ozkes, A., and the Management Science Reproducibility Collaboration (Note: Member of the Reproducibility Collaboration)
Management Science 70, no. 3 (2024): 1343-1356. Link
🟢 6. “Analytics Applications and Strategies in the Restaurant Industry,” with Xiande Zhao and Morgan Swink.
Production and Operations Management 31, no. 10 (2022): 3710-3726. Link
        📰 Media Coverage:  “Optimizing Data Collection is on the Table for the Restaurant Industry”  Vanderbilt News 2022. Link
🔵 7. “Understanding Customers’ Retrial in Call Centers: Preferences of Service Speed and Service Quality,” with Gad Allon and Achal Bassamboo.
​Manufacturing & Service Operations Management 24, no. 2 (2021):1002-1020. Link       
        📰 Media Coverage:  “New Research Identifies Service Frameworks to Improve Customer Service without Breaking the Bank.” Vanderbilt News 2021. Link
🔵 ​8. “The Effect of Tightening Standards on Automakers’ Non-compliance,” with Sunil Chopra, and Yuche Chen.
Production and Operations Management 30.9 (2021): 3094-3115. Link
         📰 Media Coverage:  “What Volkswagen’s Emissions Scandal Can Teach Us about Why Companies Cheat.” Kellogg Insights 2017. Link
         📰 Media Coverage:  “Tightening Vehicle Emissions Standards Resulted in Higher Rates of Automaker Non-Compliance.” Vanderbilt News 2021. Link
🟡 9. “Forecasting Product Life Cycle Curves: Practical Approach and Empirical Analysis,” with Jason Acimovic, Francisco Erize, Douglas J. Thomas, and Jan A. Van Mieghem.
Manufacturing & Service Operations Management 21, no. 1 (2018): 66-85.  Link         
​         🎉 Finalist in the 2017 M&SOM Practice-based Competition.
         📰 Media Coverage:  "How to Predict Demand for Your New Product."  Kellogg Insights, 2017 Link​ 
         📰 Media Coverage:  "Launching New Tech? How Do You Make Data-driven Decisions Without Any Sales Data?" Vanderbilt News, 2018. Link
🟡 10. “Product Life Cycle Data Set: Raw and Cleaned Data of Weekly Orders for Personal Computers,” with Jason Acimovic, Francisco Erize, Douglas J. Thomas, and Jan A. Van Mieghem.
Manufacturing & Service Operations Management 21, no. 1 (2018): 171-176. Link
🔵 11. “Nox Emissions from Diesel Cars Increase with Altitude,” with Yuche Chen, Xuanke Wu, Kejia Hu, and Jens Borken-KleefeldTransportation Research Part D: Transport and Environment 115 (2023): 103573. Link
🔵 12. “Caring for an Aging Population in a Post-Pandemic World: Emerging Trends in the U.S. Older Adult Care Industry,” with Lu Kong and Matthew Walsman.
Service Science 13.4 (2021): 258-274. Link
         📰 Media Coverage:  “ Research Snapshot: COVID-19 is the disruptive moment the older adult care industry has been waiting for.” Vanderbilt News 2021. Link
🔵 13. “Fostering Older Adult Care Experiences to Maximize Well-Being Outcomes: A Conceptual Framework,” with Sertan Kabadayi, Yuna S.H. Lee, Lydia Hanks, Matthew Walsman, and David Dobrzykowski.
Journal of Service Management 31, no. 5 (2020): 953-977. Link
🔵 14. “Equilibrium Fuel Supply and Carbon Credit Pricing under Market Competition and Environmental Regulations,” with Yuche Chen.
Applied Energy 236 (2019): 815-824. Link
🟡 15. “Technological Growth of Fuel Efficiency in European Automobile Market 1975–2015,” with Yuche Chen.
Energy Policy 98 (2016): 142-148. Link
🔵 16. “A Dynamic Programming Approach for Modeling Low-carbon Fuel Technology Adoption Considering Learning-by-doing Effect,” with Yuche Chen, Yunteng Zhang, Yueyue Fan, and Jianyou Zhao.
Applied Energy 185 (2017): 825-835. Link
🔵 17. “Strategic Choice of Open and Closed Platforms: Game Theory Analysis of Downstream Vendors Behavior based on Demand and Cost Advantages.” with Guangzhen Guo, Y. Zhang. 
China Industrial Economics 3 (2017): 64-82. Link
​🟡 18. “Best Predictive Generalized Linear Mixed Model with Predictive Lasso for High-speed Network Data Analysis,” With Jaesik Choi, Alex Sim, and Jiming Jiang.
International Journal of Statistics and Probability 4, no. 2 (2015): 132. Link
🟡 19. “Estimating and Forecasting Network Traffic Performance based on Statistical Patterns Observed in SNMP Data,” with Alex Sim, Demetris Antoniades, and Constantine Dovrolis.
Proceedings of International Workshop on Machine Learning and Data Mining in Pattern Recognition, pp. 601-615. Springer, Berlin, Heidelberg, 2013. *** Link
🟡 20. “Regional Reserves Growth Shows Decline in Annual Rate of Increase,” with Gongming Yu and Yijun Wang.
​Oil & Gas Journal 114, no. 7 (2016): 40-44. Link
Case Studies & Practitioner-oriented Readings
🟢 1. Jianqiang Hu and Kejia Hu. Case Study on Jointown Pharmaceutical Group Co Ltd, China. 
 🎉 Awarded as the National Top 100 MBA Case Studies, China, 2011.
🟢 2. ​ Kejia Hu and Jasper Xu. Navigate the Four-level Framework for AI Transformation in Business.
Link
WAIC UP 1st Edition -- The official magazine of WAIC (World Artificial Intelligence Conference)

Under Revision/Review

Research Papers
Revision: 
🟢 1. “A Hybrid ODE-Neural Network Framework for Modeling and Guiding GLP-1-Mediated Glucose Dynamics,” with Zijia Wang, Sarvar Sumbal, and Christofer Toumazou.
Nature Scientific Report, Minor Revision.  
🔵 2. “Promotional Design for Small Businesses: the Operational Value of Online Deals,” with Simin Li and Martin Lariviere.
Management Science, Major Revision. Link
         🎉2019 IBM Service Science Section Best Student Paper Competition Finalist
🔵 3. “To What Extent Do Workers’ Preferences Matter?” with Zhenzhen Jia, Jianqiang Hu, and Vishal Ahuja.
Manufacturing & Service Operations Management, Major Revision. Link
         🎉2021 INFORMS Service Science Best Cluster Paper Award Finalist
         🎉2021 POMS College of Behavior OM Junior Scholar Paper — Honorable Mention
         🎉2020 INFORMS Best Working Paper Award Behavioral OM — Runner Up​
🔵 4. “How Women Promote Greater Social Responsibility on Social Media,” with Li Xiang and Huibin Du.
Manufacturing & Service Operations Management, Major Revision.    
        🎉2021 INFORMS Social Media Analytics Section Best Student Paper Award Finalist

🔵 5. “The Psychology of Virtual Queue: When Waiting Becomes Less Like Waiting,” with Xun Xu and Leo Ao.
Manufacturing & Service Operations Management, Major Revision. Link
🔵 6. Cross-Channel Marketing on E-commerce Marketplaces: Operational Value and Budget Allocation
with Qiyuan Deng and Yun Fong Lim 
Manufacturing & Service Operations Management, Major Revision.​ ​

Working Papers

Research Papers
🔵 1. “How Operational Complexity Drives Inventory Record Inaccuracy: Empirical Evidence from Cross-border E-commerce,” with Ting Wang, Stanley Lim, Yun Fong Lim, and Yugang Yu. 
🔵 2. The Cardless and Cashless Future: the Rise of Mobile Payment
with Shuai Ling, and Sriram Venkataraman 
🟢 3. More or Less: How Information Richness Affects Our Choice Consistency
with Iris Wang, and Xilin Li.
🟡 4. “Forecast & Flex: A Double Safeguard Framework for Production Planning,” with Sunil Chopra, Jan A. Van Mieghem, and Ting Wang.  
​🔵 5. “The Impact of KOL Targeting Strategy in Live eCommerce: An Empirical Study on TikTok,” with Yun Fong Lim, Kai Tian, and Ruijie Zhang. 
🔵 6.“Strike the Balance between Customization and Personalization: Individualized Standardization,” with Vikram Tiwari, Ting Wang, David Xin, and Yun Fong Lim.  
🟢 7. “Reducing Human Biases through AI: Empirical Evidence from a Consulting Platform,” with Bowen Lou and Bilal Baloch.  
🔵 8. Ambidexterity and Internationalization: Building Organizational Resilience in Emerging Market Multinational Enterprises,” with Jasper Xu and Xinyang Li.  
🔵 9. “Effectiveness of Telemedicine in Stroke Care: An Empirical Study of a Telestroke Network,” with Brandon Lee, Sriram Venkataraman, and Lawrence Fredendall
🔵 10. “Bias Through the Screen: Systematic Inequity in Online Student Evaluations of Teaching,” with Lu Kong and Lanfei Shi.  
SSRN Link: Read Kejia Hu's Latest Research

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