Case Study #2: Artificial intelligence (AI) and Analytics to Unravel Individual Choice

Individual choices determine their well-being. Identification of these choices is required for the growth of organizations. Not surprisingly, various models have been proposed to discern how individuals (e.g., consumers) make choices (Ross 1979; Thaler 1985; Bettman, Luce, and Payne 1998). However, the use of artificial intelligence (AI) and analytics is unraveling patterns of consumer choice not known before. For example, it is now becoming apparent that significant life events–such as marriage, buying a new house, or divorce–lead to changes in the purchase of coffee, cereal, or beer, respectively (Duhigg 2012). Further, organizations are influencing customer choice, by leveraging the power of analytics for advertising, as organizations are integrating their advertising across mediums, tracking consumer choices and optimizing ad strategies and spends (Nichols 2013). Similarly, technologies are enabling advanced loyalty and reward programs (Starvish 2011; Corstjens and Lal 2014). Firms are using location-based mobile advertising, making offers to customers based on their geographic location (Fang, Luo, and Keith 2015). The case study may present a detailed account of any of these or other uses of technologies, focusing on any one of the topics below.

Case Study #2 Topic Choices

Topic 1: What are the types of choices customer make while shopping, working, playing, relationship, or learning? How are firms using analytics to influence these choices? The case study may focus on any one or multiple domains or companies.

Topic 2: How are organization/s using digital advertising to market their offerings? The case may examine how organizations are using analytics to advertise their offerings to the new age consumers, by changing the content of the message, the timing of the message, or the channels and strategies used to send the message.

Topic 3: What is the role of analytics in influencing organizational mechanisms to incentivize customers to delay rewards. The study may focus on the influence on analytics on schemes for loyalty and participation in rewards programs, which encourage customers to stay with the company by delaying incentives.

Topic 4: How are firms using the power of analytics to identify what customers want and serve like-minded customer segments? How is analytics helping organizations customize offerings, to serve customers with similar aspirations?

Topic 5: Case study may highlight the challenges and opportunities in the organizational use of analytics. For example, does analytics use has any ill-effects on affordability (say jobs or income) of individuals. How are firms or individuals harnessing the power of analytics while overcoming these challenges?

Other topics: Participants are encouraged to find another topic (not listed here) in the domain of Analytics to unravel choice process, for their case study. Please write to us at, to check if the topic may be appropriate for the competition.


Participants are advised to start by reading the book:

How Computational Technologies Influence Choice: A Neuroscientific Perspective Part 1. By Dr. Pankaj Setia

Accessible at ,, and at other retailers. Participants may write to for a free copy!

Other Rules

  • The project submissions must entirely be the work of the individual or the project team. While faculty and other individuals can help review the submission, they should not contribute to the content of the report or the solution.
  • Incomplete submissions will not be considered, so make sure you have all of your submission deliverables in the submission package.
  • The contest materials must be submitted by the due dates. Late submissions will not be accepted and no extensions will be given.
  • For participating in the second stage of competition, teams and individuals must be members of an AIS Student Chapter.
  • Submission Instructions

    What you should submit

    • A case study file will be submitted as a Word document: The case study is expected to have various figures and graphics (See the resources for creating infographics and case study). Refer to the Resources section for access to resources for creating info graphics and case studies.
    • Participants are encouraged to use data to present tables, to present their arguments. (See the resources for data and visualization).Refer to the Resources section for access to resources for data and visualization.
    • The Word file should be between 5-15 pages long (not including references or appendix).
    • The file should specify the names of the participants as well as the topic chosen. See the details of the topics and more resources about the topic at computational society resource pages
    • A cover letter in the format found at

    How you should submit

    • Inform about the intent to participate in the competition as soon as possible by writing to
    • Register after you are provided access to the website (you will receive this as a reply to your intent to participate request) at The membership will be upgraded to a premium membership after registration for no additional fee.
    • Email your entry to by 11:59 p.m. U.S. Eastern Time, March 1, 2019.

    What happens after you submit

    • You will receive a confirmation email acknowledging your entry.
    • Finalists will be notified by email after March 1, 2019.
    • Finalists will present their work in front of the judging panel at the AIS SCLC April 11-13, 2019. See the page on The Computational Society website for details of prizes and awards. Visit or contact for details.
  • Timeline

    All preliminary submissions must be received no later than March 1, 2020
    Finalists will be announced after March 1, 2020
    The winner will be revealed at the Student Chapters Leadership Conference between April 11 – 13, 2020

  • Prizes

    Entrants to the 2019 Computational Society Case Challenge will be competing with AIS and non-AIS student chapter teams and individuals across the globe, in Stage 1. Non-AIS members will be awarded based on their Stage 1 performance. The top AIS-affiliated teams and individuals from Stage 1 of the competition will move forward to compete at the 2019 AIS Student Chapter Leadership Conference in Philadelphia April 11-13. Stage 2 is exclusively for AIS student chapter teams and individuals* selected as finalist in Stage 1. AIS Stage 1 finalist will then compete for top prizes in Philadelphia. Submissions to all case studies are judged collectively and prizes are awarded to the top 3 cases regardless of the selected case scenario: (1) Retail Analytics and Automation of Choice, or (2) Analytics to Unravel Individual Choice, or (3) Artificial Intelligence (AI), Computational technologies, and well-being!

    Monetary Prizes, based on Stage 1 performance

    First place – $250
    Second place – $150
    Third place – $100

    Monetary Prizes, based on Stage 2 performance

    First place – $2,000
    Second place – $1,000
    Third place – $500

    Other Prizes

    • Certificates: All finalists are given certificates indicating their rank.

    *To compete as an AIS team or individual, you must be an officially recognized chapter or a member of an officially recognized chapter. Forming an AIS Student Chapter at your institution is easy, but can take as much 6-8 weeks to complete the process depending on your university policy and procedures so get started today. For more information on how you can start a chapter, contact Dr. Rhonda Syler, AIS Vice President for Student Chapters, at

  • Questions


References (also see more under the case 2 on the[1]):

Bettman, James R, Mary Frances Luce, and John W Payne. 1998. “Constructive Consumer Choice Processes.” Journal of Consumer Research 25 (3):187–217.

Corstjens, Marcel, and Rajiv Lal. 2014. “Busting Six Myths About Customer Loyalty Programs.” Harvard Business School. 2014.

Duhigg, Charles. 2012. “How Companies Learn Your Secrets.” The New York Times Magazine. 2012.

Fang, Zheng, Xueming Luo, and Megan E. Keith. 2015. “How Effective Is Location-Targeted Mobile Advertising?” 2015.

Nichols, Wes. 2013. “Advertising Analytics 2.0.” Harvard Business Review. 2013.

Ross, Ivan. 1979. “An Information Processing Theory of Consumer Choice.” Journal of Marketing (Pre-1986) 43 (000003):124.

Starvish, Maggie. 2011. “Customer Loyalty Programs That Work.” Harvard Business School. 2011.

Thaler, Richard. 1985. “Mental Accounting and Consumer Choice.” Marketing Science 4 (3):199–214.

[1] For access, write to

Additional Resources

  • Please visit the competition page on The Computational Society ( for more details about the challenges.

How to Get and Process Data

Creating Maps

Visualization and Infographic tools resources

You may access some tutorials from to do the case study


How entries will be evaluated

All entries will be evaluated by the judges on two major criteria: content and presentation. Judges will evaluate the case studies based on the following:

  • Clarity (how well the case study explains the topic)
  • Novelty/creativity (originality of thought)
  • Insight (how well the case study uses graphic aids to explain the data)
  • Utility (what is the value of case study to firms or society)
  • Completeness (degree to which the case study answers the chosen topic)
  • Depth (sophistication of the logic or analysis)
  • Consistency (conclusions consistent with the logic or analysis)

The points will be awarded based on the following: 

  1. Context (explaining what phenomenon does the case study examine) (20%)
  2. Problem statement (identifying the problem) (10%)
  3. Computational technology (explaining the features and capabilities of the technology) (10%)
  4. Case dynamics (describing how the computational technology influences the context) (25%)
  5. Tables and figures (giving an in–depth view into the above topics and may include data and analysis) (20%)
  6. Conclusions (discussing the implications for society, organizations, or individuals (15%)

Your entry will be disqualified if…

  • It is submitted after the deadline.
  • The attachments won’t open or are in the wrong file format.
  • You don’t specify the chosen case study topic.
  • Team member names and college name are not on the case study.
  •  The cover letter is missing.