Faculty Profile

Ling Ge

Title
Associate Professor
Department
Information Technology and Decision Sciences
College
College of Business
Associate Professor
Information Technology and Decision Sciences
College of Business

    

    

      


                          

            
Curriculum Vitae

            

              Click Here to View Faculty CV
            

          

        
                          

            
Education

            



  

  


  
PhD, University of Texas at Austin, 2008. 
Major: Management Science and Information Systems
Degree 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 5240.002, Data Mining and Machine Learning for Business, Spring 2024 Syllabus
BCIS 5110.005, Programming Languages for Business Analytics, Spring 2024 Syllabus


          
*
  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*


            
                    

                    BCIS 5110.001, Programming Languages for Business Analytics, Fall 2023 Syllabus SPOT
                    

                    BCIS 5110.009, Programming Languages for Business Analytics, Fall 2023 Syllabus SPOT
                    

                    BCIS 5110.002, Programming Languages for Business Analytics, Summer 5W1 2023 Syllabus SPOT
                    

                    DSCI 5240.002, Data Mining and Machine Learning for Business, Spring 2023 Syllabus SPOT
                    

                    BCIS 5110.005, Programming Languages for Business Analytics, Spring 2023 Syllabus SPOT
                    

                    BCIS 5110.001, Programming Languages for Business Analytics, Fall 2022 Syllabus SPOT
                    

                    BCIS 5110.003, Programming Languages for Business Analytics, Fall 2022 Syllabus SPOT
                    

                    BCIS 5110.009, Programming Languages for Business Analytics, Fall 2022 Syllabus SPOT
                    

                    DSCI 4520.001, Introduction to Data Mining, Spring 2022 Syllabus SPOT
                    

                    DSCI 4520.002, Introduction to Data Mining, Spring 2022 Syllabus SPOT
                    

                    DSCI 4520.001, Introduction to Data Mining, Fall 2021 Syllabus SPOT
                    

                    BCIS 5110.001, Programming Languages for Business Analytics, Fall 2021 Syllabus SPOT
                    

                    DSCI 4520.001, Introduction to Data Mining, Spring 2021 Syllabus SPOT
                    

                    BCIS 5110.001, Programming Languages for Business Analytics, Spring 2021 Syllabus SPOT
                    

                    DSCI 4520.001, Introduction to Data Mining, Fall 2020 Syllabus SPOT
                    

                    BCIS 5110.001, Programming Languages for Business Analytics, Fall 2020 Syllabus SPOT
                    

                    BCIS 5110.026, Programming Languages for Business Analytics, Fall 2020 
                    

                    DSCI 3710.004, Business Statistics with Spreadsheets, Spring 2020 Syllabus
                    

                    DSCI 4520.001, Introduction to Data Mining, Spring 2020 Syllabus
                    

                    DSCI 4520.001, Introduction to Data Mining, Fall 2019 Syllabus SPOT
                    

                    BCIS 4900.706, Special Problems, Fall 2019 
                    

                    BCIS 5110.001, Structure of Programming Languages, Fall 2019 Syllabus 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 Publications



  

  
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



	
		
		
	  

	

	

  
    
	

	

	  

		

		   
Awarded Grants



  
  
  	  
          
Contracts, Grants and Sponsored Research  

 	 
	 	 
  
Grant - Research   
Ge, L., "Jr. Faculty Summer Research Grant," University of North Texas, $5000 Funded. (2020 – Present).



	
		
		
	  

	

	

	
	

  
  
  

  	

		

		,  
			
				

					
					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
      • 
				
    
			
    • 
		

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