Skip to main content

Ling Ge

Title: Associate Professor

Department: Information Technology and Decision Sciences

College: College of Business

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, University of Texas at Austin, 2008
    Major: Management Science and Information Systems
    Specialization: Management Information Systems
  • MSc, National University of Singapore, 2001
    Major: Computer Science
  • BBA, Renmin University of China, 1997
    Major: Business

Current Scheduled Teaching

DSCI 5240.002Data Mining and Machine Learning for BusinessSpring 2025
BCIS 5110.405Programming Languages for Business AnalyticsSpring 2025
BCIS 5110.001Programming Languages for Business AnalyticsFall 2024
BCIS 5110.003Programming Languages for Business AnalyticsFall 2024
BCIS 5110.409Programming Languages for Business AnalyticsFall 2024
Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Previous Scheduled Teaching

DSCI 5240.002Data Mining and Machine Learning for BusinessSpring 2024 SPOT
BCIS 5110.005Programming Languages for Business AnalyticsSpring 2024 SPOT
BCIS 5110.001Programming Languages for Business AnalyticsFall 2023 SPOT
BCIS 5110.009Programming Languages for Business AnalyticsFall 2023 SPOT
BCIS 5110.002Programming Languages for Business AnalyticsSummer 5W1 2023 SPOT
DSCI 5240.002Data Mining and Machine Learning for BusinessSpring 2023 SPOT
BCIS 5110.005Programming Languages for Business AnalyticsSpring 2023 SPOT
BCIS 5110.001Programming Languages for Business AnalyticsFall 2022 SPOT
BCIS 5110.003Programming Languages for Business AnalyticsFall 2022 SPOT
BCIS 5110.009Programming Languages for Business AnalyticsFall 2022 SPOT
DSCI 4520.001Introduction to Data MiningSpring 2022 Syllabus SPOT
DSCI 4520.002Introduction to Data MiningSpring 2022 Syllabus SPOT
DSCI 4520.001Introduction to Data MiningFall 2021 Syllabus SPOT
BCIS 5110.001Programming Languages for Business AnalyticsFall 2021 SPOT
DSCI 4520.001Introduction to Data MiningSpring 2021 Syllabus SPOT
BCIS 5110.001Programming Languages for Business AnalyticsSpring 2021 SPOT
DSCI 4520.001Introduction to Data MiningFall 2020 Syllabus SPOT
BCIS 5110.001Programming Languages for Business AnalyticsFall 2020 SPOT
BCIS 5110.026Programming Languages for Business AnalyticsFall 2020
DSCI 3710.004Business Statistics with SpreadsheetsSpring 2020 Syllabus
DSCI 4520.001Introduction to Data MiningSpring 2020 Syllabus
DSCI 4520.001Introduction to Data MiningFall 2019 Syllabus SPOT
BCIS 4900.706Special ProblemsFall 2019
BCIS 5110.001Structure of Programming LanguagesFall 2019 SPOT
Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Published Intellectual Contributions

    Conference Proceeding

  • Prateek, P., Kim, D., Ge, L. (2021). Detection of Fraudulent Campaigns on Donation-Based Crowdfunding Platforms using a Combination of Machine Learning and Rule-Based Classifier.
  • Luo, X., Chen, L., Ge, L. (2014). Is online channel a counterstrategy to the store brand by the national brand?. Proceedings - Pacific Asia Conference on Information Systems, PACIS 2014. https://api.elsevier.com/content/abstract/scopus_id/84928594733
  • Ge, L. (2011). Hands-off the mess: Contract choice for business process outsourcing. Proceedings of the 1st International Technology Management Conference, ITMC 2011. 643-650. https://api.elsevier.com/content/abstract/scopus_id/80053002283

    • Journal Article

  • Ogbanufe, O., Ge, L. (2023). Comparative Evaluation of Behavioral Security Motives: Protection, Intrinsic, and Identity Motivations. Computers & Security.
  • Ge, L., Luo, X. Channel Structure and Fund Incentive in Prosocial Crowdfunding. Springer.
  • Luo, X., Ge, L., Wang, C. (2022). Crowdfunding for Microfinance Institutions: A New Hope. MIS Quarterly. 46 (1)
  • Dai, H., Ge, L., Li, C., Wen, Y. (2021). The interaction of discount promotion and display-related promotion on on-demand platforms. Information Systems and e-Business Management.
  • Luo, X., Ge, L., Chen, L., Li, J. (2021). Online Channels and Store Brands: Strategic Interaction. Journal of the Association for Information Systems.
  • Bai, S., Ge, L., Zhang, X. (2021). Platform or Direct Channel: Government-subsidized Recycling Strategy for WEEE. Information Systems and e-Business Management.
  • Zheng, X., Griffith, D., Ge, L., Benoliel, U. (2020). Effects of Contract Ambiguity in Interorganizational Governance. Journal of Marketing. 84 (4) 147-167.
  • Ge, L., Zhang, T., Gou, Q., Chen, L. (2018). Consumer Showrooming, the Sunk Cost Effect and Online-Offline Competition. Journal of Electronic Commerce Research. 19 (1) 55.
  • Dai, H., Ge, L., Liu, Y. (2018). Information Matters: an Empirical Study of the Efficiency of On-Demand Services. Information Systems Frontiers.
  • Ge, L., , X.L. (2016). Team rivalry and lending on crowdfunding platforms: an empirical analysis.
  • Dai, H., Ge, L., Zhou, W. (2015). A design method for supply chain traceability systems with aligned interests. International Journal of Production Economics. 170 14-24. https://api.elsevier.com/content/abstract/scopus_id/84964237891
  • Tanriverdi, H., Konana, P., Ge, L. (2007). The choice of sourcing mechanisms for business processes. Information Systems Research. 18 (3) 280-299. https://api.elsevier.com/content/abstract/scopus_id/61349127915

Contracts, Grants and Sponsored Research

    Grant - Research

  • Ge, L., "Jr. Faculty Summer Research Grant," University of North Texas, $5000 Funded. (2020).
,
Overall
Summative Rating		 Challenge and
Engagement Index		 Response Rate

out of 5
out of 7		 %
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
CLOSE