Computational technologies and well-being!

Individuals often adopt based on their perception of rewards. In fact, neuro scientific evidence indicates that human neural networks act (e.g. invest in stocks) to seek rewards (Peterson 2005; McClure et al. 2004). In general, intentions to adopt technologies are influenced by perceptions of its usefulness (Davis 1989; Davis, Bagozzi, and Warshaw 1989). For more details on these aspects, participants may read Chapters 1, and 2 in Setia (2018) (available for free to the computational society premium members for the first 6 months).                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      

The book discusses a model for human choice in the era of computational technologies.
Chapter 1 discusses the notion of individual well -being and how technology influences it. Noting that individual capabilities have been limited, the chapter outlines technology as offering enhanced capabilities that may influence well-;being. Outlining the growth in computational intensity due to modern day computational technologies, the chapter uses a fitness perspective to conceptualize a fitness landscape. Along with computational intensity, individual aspirations are proposed to influence well-being. The chapter models the influence of aspirations and computational intensity on fitness (well-being).
Chapter 2 discusses the foundation concepts of choice, explaining what is choice and the information processing basis for choice. The book identifies two questions: why and how technologies influence choices and argues for the presence of a choice making process that accounts for errors in human choice-making.

Case Study #3 Topic Choices
Topic 1: Identify how analytics or other computational technologies used in healthcare (say hospitals) or education (say schools) are influencing patient health or student outcomes, respectively. What are the effects of these technologies on the performance of healthcare organizations or educational institutions?
Topic 2: How are computational technologies (say, price comparison software) changing the ways human shop or consume? How are modern technologies influencing these activities and well-being?
Topic 3: class="ex1" Has the advent of technologies changed the way individuals play and entertain? Identify technologies being used in the arena of sports and recreation? How are these influencing individual activities and well-being?
Topic 4: Identify the negative influence of computational technologies on individual well-being?
Topic 5: Identify how computational technologies are influencing the emotional and physical well-being of individuals, such as by helping them network (e.g., through social networking website), communicate (e.g., through Skype), or learn (e.g., through online lectures).
Other topics: Participants are encouraged to find another topic (not listed here) in the domain of retail automation and analytics, for their case study. Please write to us at, to check if the topic may be appropriate for the competition.

  1. Books and Research Links:

    • Brynjolfsson, E., & McAfee, A. (2014a). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. New York, NY: WW Norton & Company.
    • Edelman, S. (2008). Computing the mind: How the mind really works. Oxford, NY: Oxford University Press.
    • Krugman, H. E. (1971). Brain wave measures of media involvement. Journal of Advertising Research, 11(1), 3—9.
    • O’Shea, M. (2005a). The brain: A very short introduction. Oxford, NY: OUP Oxford.

  2. Other References and Publications

  3. Databases: