Prof. dr. T. (Ting) Li

Rotterdam School of Management (RSM)
Erasmus University Rotterdam
Former ERIM PhD Candidate
Field: Logistics & Information Systems
Former Associate Member ERIM
Field: Logistics & Information Systems
Member ERIM
Field: Logistics & Information Systems
Affiliated since 2004

Ting Li is the Professor of Digital Business at Rotterdam School of Management (RSM), Erasmus University. She is the founding member and the Academic Director of Digital Business Practice of the Erasmus Centre for Data Science and Business Analytics. Ting Li is an expert in Digital Strategy, Ecommerce, Social Media Analytics, Mobile Marketing, Business Analytics, Online Advertising, and Pricing and Revenue Management. She has been a Visiting Professor at the Wharton School of Business, Temple University, Arizona State University, City University of Hong Kong, and Tsinghua University. In 2017, she was named by Poets & Quants as one of the Top 40 Professors Under 40 Worldwide.

Ting Li's research interest focuses on the understanding of the strategic use of information and its economic impacts on consumer behavior and firm strategy. Theoretically, she proposes new theoretical perspectives to understand why and how firms develop digital capabilities to improve their business capability, and how new information (technologies) impact consumer behavior and decision making. Methodologically, she applies inter-disciplinary approaches combining large-scale randomized field experiments, lab experiment, survey, eye-tracking, agent-based simulation, and machine learning techniques such as text mining and sentiment analysis to investigate the impact of IT on individuals, organizations, markets, and networks. Her work has been published in leading scientific journals, including Management Science, Information Systems Research, Journal of Information Technology, Decision Support Systems, European Journal of Information Systems, International Journal of Electronic Commerce, and many others. Her research has been recognized with best paper awards and nominations (European Research Paper of the Year 2015), and best dissertation awards (Prof. Aart Bosman Dissertation Award, Accenture-PIM Marketing Science Dissertation Award). Her interdisciplinary research has been sponsored by multiple grants from the Dutch National Science Foundation (NWO) and multinational companies.

Ting Li develops close collaborations with industry partners. Her academic work introduces methods, models, and principles to guide organizations to manage informational challenges, build capabilities and compete in digital environments. She has consulted and worked in various capacities with Shell, Coolblue, Wehkamp, VIVAT, HelloPrint, KPMG, PwC, Accenture, Tweakers, Shop2Market, Dutch Railways, RET, amongst others. Ting’s teaching expertise is in the areas of digital strategy, digital transformation, digital commerce, social and mobile analytics, and social networks. She teaches in various RSM Bachelor, Master, and MBA/EMBA degree programs and is active in executive education programs. Prior to joining academic, Ting worked for General Electric and IBM in the area of e-business in supply chains, web services, and grid computing. She obtained her Ph.D. in Management Science at the Erasmus University and MSc in Computational Science at the University of Amsterdam. Her faculty page can be found at: http://www.rsm.nl/people/ting-li/. Follow her on Twitter at @tinglinl.

PhD Track Informedness and Customer-Centric Revenue Management

The recent pervasive adoption of modern IT in the marketplace has profoundly changed information availability to customers and firms. This improved information endowment results in changes in consumer behavior and corporate strategy. This dissertation proposes new theoretical perspectives – firm informedness, customer informedness, and informedness through learning – to re-conceptualize the decision making process of customer-centric revenue management. It consists of three studies. First, using multiple cases in which firms adopt smart cards and mobile technologies in America, Europe, and Asia, we examine the value creation process of the firm using the explanation of firm informedness and investigate how it advances revenue management. Second, we test the theory of consumer informedness and examine heterogeneity in consumer preferences using stated choice experiments. We find the evidence for trading down and trading out behavior and show that the use of mobile ticketing technologies can help firms to build a hyper-differentiated transport market. Finally, using a computational simulation, we explore the opportunity for devising service offerings to capture profitable consumer responses, considering demand-driven revenue and capacity-management. Overall, this research introduces methods, models, and guidelines for organizations to strategize the informational challenge, make informed decisions, and create transformational values to win in today’s competitive network environment.

Keywords
adaptive learning, capacity management, consumer choice, consumer informedness, firm informedness, hyperdifferentiation, information availability, IT, mobile technology, pricing, public transport, rational expectations, resonance marketing, revenue management, smart cards, simulation, stated choice experiment
Time frame
2004 - 2009

Publications

  • Academic (1)
    • Li, T., Lovric, M., & Vervest, P. (2013). Understanding Complexity in Public Transportation. Haveka.

  • Professional (1)
    • Kroon, LG., Li, T., & Zuidwijk, R. (2010). Liber Amicorum in Memory of Jo van Nunen. Dinalog.

  • Academic (2)
    • Li, T., van Heck, E., & Vervest, P. (2006). Customer-Centric Business Networks: Case of the Evolutionary Network of Octopus. In P. Vervest, E. van Heck, & K. Preiss (Eds.), Smart Business Network: A New Business Paradigm Springer-Verlag.

    • Li, T., van Heck, E., & Vervest, P. (2006). Dynamic Pricing Strategies for Yield Improvement with Smart Card Adoption in Dutch Travel Industry. In M. Hitz, M. Sigala, & J. Murphy (Eds.), Information and Communication Technologies in Tourism Springer-Verlag.

  • Academic (2)
    • Bouman, P., Kroon, L., Li, T., & Vervest, P. (2013). Detecting activity patterns from smart card data. Belgian/Netherlands Artificial Intelligence Conference, 9-16.

    • Bouman, P., Lovric, M., Li, T., Kroon, L., & Vervest, P. (2012). Recognizing demand patterns from smart card data for agent-based micro-simulation of public transport. Belgian/Netherlands Artificial Intelligence Conference.

  • Academic (5)
    • Mehrdar, A., & Li, T. (2020). An Optimal Pricing Strategy with Cannibalization. Statistical Challenges in Electronic Commerce Research, Madrid, Spain.

    • Frick, T., Li, T., & Pavlou, P. (2016). Investigating The Impact Of Social Influence On The Personalization-Privacy Paradox: An Eye Tracking Study. INFORMS 2016, Nashville.

    • Frick, T., & Li, T. (2015). Social Retargeting – A Randomized Field Experiment. 37th ISMS Marketing Science Conference.

    • Frick, T., & Li, T. (2015). Understanding Information Privacy Concerns in Social Advertising: An Eye Tracking Study. 37th ISMS Marketing Science Conference.

    • Kauffman, R. J., Li, T., Van Heck, E., & Vervest, P. (2008). Integrating service attribute bundle designs and capacity management using a customer-centric approach. 212-217. 2008 Workshop on Information Technologies and Systems, WITS 2008, Paris, France.

  • Academic (32)
    • Mehrdar, A., & Li, T. (2020). An Optimal Pricing Strategy with Cannibalization. In Annual Meeting of the Academy of Management

    • Yang, Z., & Li, T. (2020). Life-Event Targeting and Customer Uncertainty – Evidence from Field and Online Experiments. In Proceedings of the 19th Workshop on e-Business (WEB-2020)

    • Balocco, F., & Li, T. (2019). LemonAds: Impression quality in programmatic advertising. In 40th International Conference on Information Systems, ICIS 2019 Article 2905 Association for Information Systems. https://aisel.aisnet.org/icis2019/general_topics/general_topics/19/?utm_source=aisel.aisnet.org%2Ficis2019%2Fgeneral_topics%2Fgeneral_topics%2F19&utm_medium=PDF&utm_campaign=PDFCoverPages

    • Yang, Z., Cheng, Z., & Li, T. (2019). Still targeting younger customers? A field experiment on digital communication channel migration. In 40th International Conference on Information Systems, ICIS 2019 Article 2822 Association for Information Systems. https://aisel.aisnet.org/icis2019/business_models/business_models/13/

    • Li, T., Tsekouras, D., & Cheng, Z. (2019). Free Shipping Promotions: Leveraging Scarcity and Popularity Information. In Annual Meeting of the Academy of Management

    • Li, T., Tsekouras, D., & Cheng, Z. (2018). Free Shipping Promotions: Leveraging Scarcity and Popularity Information. In Proceedings of the International Conference on Information Systems

    • Andrews, M., Li, T., & Balocco, F. (2018). The Effect of Mobile Search Ads across Devices: A Geo Experiment. In Proceedings of the International Conference on Information Systems

    • Cheng, Z., Li, T., & Pavlou, P. (2016). Acquisition Channels and Customer Churn: Evidence from the Auto Insurance Industry. In -

    • Frick, T., & Li, T. (2016). Social Retargeting: A Field Experiment. In Proceedings of the Statistical Challenge in eCommerce Research Symposium

    • Frick, T., & Li, T. (2016). Social Retargeting: A Field Experiment. In The Economics of Information and Communication Technologies, ZEW Conference Centre for European Economics Research.

    • Frick, T., & Li, T. (2016). Personalization in Social Retargeting – A Field Experiment. In - Association for Information Systems (AIS).

    • Tsekouras, D., Frick, T., & Li, T. (2016). Don’t Take It Personally: The Effect of Explicit Targeting in Advertising Personalization. In - (pp. 10). Association for Information Systems (AIS). http://hdl.handle.net/1765/100010

    • Li, T., & Tsekouras, D. (2015). Effort Reciprocity on Perceived Recommendation Agent Quality: An Experimental Study. In Proceedings of the International Conference on Information Systems

    • Tsekouras, D., & Li, T. (2015). Effort Reciprocity on Perceived Recommendation Agent Quality: An Experimental Study. In Proceedings of the European Conference on Information Systems

    • Li, T., & Tsekouras, D. (2015). Free Shipping 3.0: Leveraging Scarcity and Popularity Information – A Randomized Field Experiment. In Conference on Information Systems and Technology

    • Frick, T., Tsekouras, D., & Li, T. (2014). The Times They Are A-Changin:Examining the Impact of Social Media on Music Album Performance. In -

    • Bouman, P., Lovric, M., Li, T., Hurk, E., Kroon, LG., & Vervest, P. (2012). Recognizing Demand Patterns from Smart Card Data for Agent-Based Micro-simulation of Public Transport. In M. Vasirani, E. Camponogara, H. Hiromitsu, & F. Klügl (Eds.), Proceedings of the 7th Workshop on Agents in Traffic and Transportation

    • Li, T., & Soonius, G. (2012). Is Your Social Media Strategy Effective? An Empirical Study of the Factors Influencing the Success of Facebook Campaigns. In Proceedings of the Workshop on Electronic Business

    • Li, T., & Tsekouras, D. (2012). More Effort to Personalize? Examining Perceived Effort as a Signal for Quality. In Proceedings of the International Conference on Electronic Commerce

    • Li, T., Berens, G., & de Maertelaere, M. (2012). Social Influence: The Effect of Twitter Information on Corporate Image. In Proceedings of the International Conference on Electronic Commerce

    • Li, T., Lovric, M., & Vervest, P. (2011). Agent-Based Modeling Approach to Revenue Management in Public Transportation. In Organizations and Society in Information Systems OASIS.

    • Kauffman, R., Li, T., & van Heck, E. (2010). A Theory of Informedness and Business Network Co-Production. In R. Sprague (Ed.), Proceedings of the 43th Hawaii International Conference on Systems Science IEEE Computer Society.

    • Kauffman, R., Li, T., van Heck, E., & Vervest, P. (2009). Consumer Informedness and Resonance Marketing: An Empirical Test of The Hyperdifferentiation Hypothesis. In R. Sprague (Ed.), Proceedings of the 42th Hawaii International Conference on Systems Science IEEE Computer Society.

    • Kauffman, R. J., Li, T., Van Heck, E., & Vervest, P. (2009). Consumer informedness and hyperdifferentiation: An empirical test of the 'trading down' and 'trading out' hypotheses. In Proceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS Article 4755684 https://doi.org/10.1109/HICSS.2009.130

    • Kauffman, R., Li, T., van Heck, E., & Vervest, P. (2008). Consumer Informedness and Information Technology: An Empirical Study of Heterogeneous Consumer Choice. In Twentieth Workshop on Information Systems and Economics

    • Kauffman, R., Li, T., van Heck, E., & Vervest, P. (2008). A Multi-Method Approach to Integrate and Joint Optimize Service Attribute Bundles and Capacity Management. In Proceedings of the Eighteenth Annual Workshop on Information Technologies and Systems

    • Li, T., van Heck, E., & Vervest, P. (2008). Use and Impact of Mobile Ticketing Technologies for Revenue Management. In Academy of Management Meeting

    • Li, T., van Heck, E., & Fleischmann, M. (2007). Understanding Dynamic Pricing in Public Transport: The Role of Smart Card Technology Adoption. In Academy of Management Meeting

    • Li, T., van Heck, E., & Vervest, P. (2007). Study of Network Structural Properties of Complex Dutch Railway Transportation Network. In Transportation Research Board 86th Annual Meeting

    • Li, T., van Heck, E., Vervest, P., Voskuilen, J., Hofker, F., & Jansma, F. (2006). Passenger Travel Behavior Model in Railway Network Simulation. In Proceedings of the 38th Conference on Winter Simulation IEEE.

    • Li, T., Hofker, F., van Heck, E., & Vervest, P. (2006). Do Customers Respond to Differentiated Pricing in Public Transport? -- An Analysis of Behavioral Response Using Stated Preference Experiment. In Proceeding of the TRAIL Research Congress 2006

    • Li, T., Vervest, P., van Heck, E., & Rooijmans, P. (2006). Improve Yield in Public Transport – A Focus on ICT Capability. In Proceeding of the IEEE International Conference on Service Operations and Logistics, and Informatics

  • Internal (1)
    • Li, T. (2009). Informedness and Customer-Centric Revenue Management. [Doctoral Thesis, Erasmus University Rotterdam]. Erasmus University Rotterdam (EUR).

  • Popular (1)
    • Li, T. (2018). Digital Traces: Personalization and Privacy. Erasmus Research Institute of Management (ERIM). ERIM Inaugural Address Series Research in Management http://hdl.handle.net/1765/108848

  • Academic (1)
    • Tsekouras, D., Li, T., & Frick, T. (2023). Don’t Take it Personally: An Empirical Investigation of Consumer Responses to Explicit Targeting. Journal of the Association for Information Systems.

  • Academic (11)
    • Bar, D., Feuerriegel, S., Li, T., & Weinmann, M. (2023). Behavioral interventions increase the adoption of green technologies (under review).

    • Kanellopoulos, I., Gutt, D., Tunc, M., & Li, T. (2023). How Do Platform Subsidies Affect Creation, Engagement, and Pricing? Evidence from Non-Fungible Tokens. https://doi.org/10.2139/ssrn.4335127

    • Zhu, R., Yi, C., & Li, T. (2023). Harnessing the Metaverse: An Empirical Investigation of the Effects of Multimodal AR Interaction on Information Search and Learning in Aircraft Maintenance Training (under review).

    • Yi, C., Zhu, R., & Li, T. (2023). Where to Display What? Investigating the Effects of Augmented Reality and Information Type on Work Performance (under review).

    • Kanellopoulos, I., Gutt, D., & Li, T. (2022). Do Non-Fungible Tokens (NFTs) Affect Prices of Physical Products? Evidence from Trading Card Collectibles (under review). https://doi.org/10.2139/ssrn.3918256

    • Mehrdar, A., & Li, T. (2022). Should Price Cannibalization be Avoided or Embraced? An Empirical Investigation of an Optimal Pricing Strategy with Price Overlap (under review). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3908037

    • Cheng, A., Li, T., & Pavlou, P. (2022). Information Transparency and Customer Churn: Evidence from the Insurance Industry (under review).

    • Tsekouras, D., Li, T., & Gong, J. (2022). Are You Still Interested in This Item? Field Evidence on the Effectiveness of Onsite Retargeting (under review). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3907869

    • Balocco, F., Yixin, L., Li, T., & Gupta, A. (2022). LemonAds: Impression Quality in Programmatic Advertising (under review).

    • Yang, Z., Cheng, A. Z., & Li, T. (2022). Firm’s Consent Elicitation and Consumer Segmentation under Privacy Regulations: Strategies for Digital Laggards (under review). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3966138

    • Li, T., Tsekouras, D., & Cheng, Z. (2021). Free Shipping Promotions: Leveraging Scarcity and Popularity Information (under review).

  • MIS Quarterly: Management Information Systems (Journal)

    Editorial work (Academic)

  • Information Systems Research (Journal)

    Editorial work (Academic)

  • Journal of Management Information Systems (Journal)

    Editorial work (Academic)

  • Role: Promotor
  • PhD Candidate: Thomas Frick
  • Time frame: 2013 - 2018
  • Role: Promotor, Daily Supervisor
  • PhD Candidate: Atabak Mehrdar
  • Time frame: 2018 -
  • Role: Promotor
  • PhD Candidate: Agapi-Thaleia Fytraki
  • Time frame: 2010 - 2018
  • Role: Promotor
  • PhD Candidate: Agnieszka Kloc
  • Time frame: 2019 -
  • Role: Promotor
  • PhD Candidate: Charles Wan
  • Time frame: 2019 -
  • Role: Promotor
  • PhD Candidate: Tamara Thuis
  • Time frame: 2020 -
  • Role: Member Doctoral Committee
  • PhD Candidate: Zeynep Aydin
  • Time frame: 2009 - 2021
  • Role: Member Doctoral Committee
  • PhD Candidate: Huong May Truong
  • Time frame: 2016 - 2021
  • Role: Promotor
  • PhD Candidate: Clarisse Lucienne Sophie Dupont
  • Time frame: 2021 -
  • Role: Member Doctoral Committee
  • PhD Candidate: Ainara Novales
  • Time frame: 2016 - 2022
  • Role: Promotor
  • PhD Candidate: Linda Punt
  • Time frame: 2022 -
  • Role: Member Doctoral Committee
  • PhD Candidate: Silviu Horia Tierean
  • Time frame: 2012 - 2022
  • Role: Promotor
  • PhD Candidate: Magnus van Haaren
  • Time frame: 2022 -
  • Role: Promotor
  • PhD Candidate: Wei Wang
  • Time frame: 2022 -
  • Role: Member Doctoral Committee
  • PhD Candidate: Joshua Paundra
  • Time frame: 2015 - 2023
Parttime PhD programme
  • Role: Promotor
  • PhD Candidate: Tristan Hahn
  • Time frame: 2023 -
  • Role: Member Doctoral Committee
  • PhD Candidate: Alexandros-Myron Pasparakis
  • Time frame: 2016 - 2023
  • Role: Member Doctoral Committee
  • PhD Candidate: Curtis Meloy Goldsby
  • Time frame: 2019 -
  • Role: Promotor
  • PhD Candidate: Xinmiao Lan
  • Time frame: 2024 -

Immersive technologies, such as virtual reality (VR), augmented reality (AR), and mixed reality (MR), can transform how we perceive, interact, and communicate with the world and each other. The future internet will be immersive, and according to Forbes, it is currently among the top 5 technology trends. The related market is expected to rapidly yet sustainably grow over the next decades, as confirmed by major consulting firms such as Accenture, McKinsey, and Gartner. The tremendous impact of these new technologies is already visible in many sectors today, including education, entertainment, health, and socialization.

There are many concrete examples that illustrate the benefits of immersive technology. In industrial work environments, AR can be used for equipment inspection and maintenance, providing real-time data overlays and interactive guides to ensure accuracy and efficiency. In health, for hearing and vision-impaired individuals, AR glasses can offer significant enhancements to daily life and social interactions. Additionally, virtual training can reduce learning time and costs (e.g., Accenture, Police). The possibility for remote interaction and supervision also reduces CO2 emissions, as many real-world displacements can be replaced. The ability to capture, analyze, and review user actions with machine precision is relevant for many domains, such as sports (e.g., athlete performance analysis) or the medical sector (e.g., Alzheimer/Parkinson behavior analysis). Having control over the virtual environment is a key aspect to investigate specific scenarios in such contexts. Virtual content itself is beneficial in various ways; for example, realistic depictions can serve for virtual exhibitions or previsualization of architectural elements. Furthermore, immersive data visualization is a field that holds tremendous promise but has received little attention.

We’re launching the Immersive AI Lab, a joint research collaboration between researchers from Erasmus University and the Technology University of Delft, sponsored by Convergence of AI, Data & Digitalization. Our aim is to unlock the potential of immersive and AI technologies by exploring fundamental questions and innovative application contexts. Our goal is to gain insights that are generally applicable while simultaneously opting for concrete outcomes that can make a difference in specific domains today. In this way, we believe it is possible to build a basis for the long-term effectiveness and sustainability of the lab. The initial themes have been carefully chosen with the duality of impact and fundamental research in mind, focusing on: multimodal augmentation for user-centric solutions, social interactions and collaboration, virtual environments, and immersive data visualization.

We are seeking highly motivated PhD students with demonstrated academic ability who are passionate about immersive technology and AI, and who want to contribute to the research in our Immersive AI Lab. Ideal candidates will possess a commitment to interdisciplinary research on significant information technology and management issues and a desire to pursue an academic research career in this field. You will be part of the Business Information Management (BIM) section within the Department of Technology & Operations Management at the Rotterdam School of Management, Erasmus University.

Applicants must have strong quantitative training, with preference given to candidates who have earned an MSc, MPhil, or Research Master in economics, computer science, econometrics, statistics, or a related field. Successful candidates should have proficiency with R, SQL, Python, or other programming languages.

As a Ph.D. student, you will gain the training and experience necessary to conduct independent research through coursework in information systems, economics, econometrics, machine learning, and large-scale data analytics. You will work closely with the advisors to define, develop, and execute your own research. The Ph.D. dissertation will be defined by you with inputs from the advisors, requiring creativity, self-direction, and a passion for scientific inquiry.

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2020
March
12
2020
March
03
2019
September
17
2019
February
11
2019
January
24
2018
June
20
Inaugural Address
As: Speaker
2018
February
06
2018
February
05
2017
March
15
Research Seminar
As: Contact, Coordinator
2017
February
23
2017
February
21
Research Seminar
As: Contact, Coordinator
2017
January
10
Research Seminar
As: Coordinator, Contact
2016
December
20
Research Seminar
As: Coordinator, Contact
2016
September
06
2016
June
14
Research Seminar
As: Coordinator, Contact
2016
June
07
Research Seminar
As: Contact, Coordinator
2016
May
31
Research Seminar
As: Contact, Coordinator
2016
April
19
2014
May
15
Research Seminar
As: Contact, Coordinator
2014
April
15
2013
December
12
Research Seminar
As: Coordinator, Contact
2013
October
11
Research Seminar
As: Contact, Coordinator
2013
August
30
2013
July
12
2013
June
18
Research Seminar
As: Contact, Coordinator
2013
June
03
Research Seminar
As: Coordinator
2013
March
15
2013
January
18
2009
January
16

Address

Visiting address

Office: Mandeville Building T09-16
Burgemeester Oudlaan 50
3062 PA Rotterdam

Postal address

Postbus 1738
3000 DR Rotterdam
Netherlands