Reifying the Possibility Space of Iot Automation Practices: a Machine Learning Approach

We use machine learning methods to operationalize and visualize an assemblage theory interpretation of the emergence of automation practices in the IoT. We build a concrete representation of the possibility space of automation assemblages to reveal the boundaries of territorialized automation practices, using it as a basis for interpretive analysis.



Citation:

Thomas Novak and Donna L. Hoffman (2019) ,"Reifying the Possibility Space of Iot Automation Practices: a Machine Learning Approach", in NA - Advances in Consumer Research Volume 47, eds. Rajesh Bagchi, Lauren Block, and Leonard Lee, Duluth, MN : Association for Consumer Research, Pages: 347-351.

Authors

Thomas Novak, George Washington University, USA
Donna L. Hoffman, George Washington University, USA



Volume

NA - Advances in Consumer Research Volume 47 | 2019



Share Proceeding

Featured papers

See More

Featured

D3. Social Exclusion and WOM about Past versus Future Experiences

Melis Ceylan, Koc University, Turkey
Ezgi Akpinar, Koc University, Turkey
Selin Atalay, Frankfurt School of Finance and Management, Germany

Read More

Featured

Both Good from Afar…and Far from Good? Mental Representation Changes Consumer Preference for Products from a Brand with a Reputation for Innovativeness

Jeff Larson, Brigham Young University, USA
Kelly Goldsmith, Vanderbilt University, USA
BJ Allen, University of Arkansas, USA

Read More

Featured

The Slippery Slope of Green Consumption: The Nonlinear Effects of Social Class

Li YAN, Monash University, Australia
Hean Tat Keh, Monash University, Australia
Jiemiao Chen, Monash University, Australia

Read More

Engage with Us

Becoming an Association for Consumer Research member is simple. Membership in ACR is relatively inexpensive, but brings significant benefits to its members.