At the individual level, research in the past has extensively looked into decisions of adopting a technology. However, for me what is more fascinating, is to explore how after voluntary adoption of technology (specifically Internet of Things such as wearables, smart assistants), people decide to either continue using their devices or stop using them. This is specifically because these types of devices are still only “good to have” devices and have not yet become “must have” devices like mobile phones.
Radhika Garg
Therefore, along with Ph.D. and master’s students at the , I conducted a survey to identify factors and reasons that influence such a decision. One of the factors that is motivating people to keep using the device was the competitive edge among peers that these devices provided. Survey respondents mentioned that they use these devices to give an impression of being rich by flaunting the devices in their social circle. This study also suggested that use and non-use of technology (which occurs after adopting a technology) might not be two dichotomous analytic categories. Rather they might be categories or users’ states of intersecting with technology on a continuum from use to non-use. The paper we published recently can be found .
I started doing research as a master’s student, but I became involved in this specific research around technology and decision making in early 2013 when I started my Ph.D. studies. In my dissertation work, I focused on Cloud technologies as a case example for organizational decision making. I developed a “Trade-offs based decision methodology for adopting Cloud-based services in an Organization.” To this end I conducted a mixed-method study. First, interviews were conducted with organizations to identify the factors that influence such a decision. Second, using multi-criteria decision algorithms, trade-offs based automated methodology was developed to help organizations make such decisions. During the course of this work I realized technology adoption is not merely a function of its technical efficiency but is also influenced by multiple other factors such as economic and organization factors. This work made me curious and interested in exploring such decisions at the individual level. Therefore, after joining the iSchool I extended my work to study individual decisions relating to technology use or non-use.
All new technologies promise to be technically more effective than their predecessors, economically more viable and profitable, and to have a potential to transform and create new opportunities/capabilities for users, organizations, societies and cultures. Even though I am a trained computer scientist, my research draws and expands from various disciplines, such as science and technology studies, psychology and decision sciences. Furthermore, I am currently collaborating with faculty from the iSchool and the to analyze the manner in which high- and low-skilled workers transition from one employment status to another and how they decide among alternative jobs. My own interest in interdisciplinary work and the possibility to collaborate with faculty and students from various streams attracted me to the iSchool and to ϲ.
It’s interesting that you ask this. I am currently designing a study that will explore this aspect of technology use. Past research on users’ privacy concerns has shown that people from the U.S. had more specific concerns than their Chinese or Indian counterparts. Therefore, my current hypothesis is that there exist differences (both subtle and noticeable) in the way people use technology, specifically between users from developing countries and developed countries.
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