Re-shuffling the Deck on Environmental Sustainability: Using a Card Sort to Uncover Perceived Behavioral Categories, Effort, and Impact in a College Environment

  • Casey G. Franklin
  • Abram Alebiosu
Part of the World Sustainability Series book series (WSUSE)


Definitions of sustainability in social settings can vary widely across contexts and age groups. The aim of this experiment is to identify actions college students classify as sustainable within their everyday context, how such actions are grouped into behavioral categories, the perceived effort and impact of actions, and ways that public spaces can limit these actions. A card-sort, co-current interview, and ranking task was conducted with ten students (ages 20–27). Student listed sustainable actions and behavioral categories were compared against a researcher-generated list of categorized actions possible within their college environment. Ranking data of perceived effort and impact was used to identify which behaviors would be easy and difficult to encourage in college buildings. Key findings are that students’ perceptions of effort and impact varied widely, students categorized actions based on many types of commonalities, students consistently placed actions appropriately in predetermined categories, and that educational environments contain social and physical norms limiting perceived ability to act. In the future, these methods could be replicated to identify perceptions influencing sustainable behaviors in multiple contexts.


Sustainable behaviors Categorization Card-sort User perceptions Behavioral effort Sustainable impact 


  1. Barlett, P. F., & Chase, G. W. (2004). Sustainability on campus: Stories and strategies for change. Cambridge: MIT Press.Google Scholar
  2. Block, L. G., & Keller, P. A. (1995). When to accentuate the negative: The effects of perceived efficacy and message framing on intentions to perform a health-related behavior. Journal of Marketing Research, XXXII, 192–203.Google Scholar
  3. Canter, D., Brown, J., & Groat, L. (1985). A multiple sorting procedure for studying conceptual systems. 27th research interview: uses and approaches. London: Academic.Google Scholar
  4. Davis, J. J. (1995). The effects of message framing on response to environmental communications. Journalism & Mass Communication Quarterly, 72(2), 285–299.CrossRefGoogle Scholar
  5. DiMaggio, P. (1997). Culture and cognition. Annual review of sociology, 23, 263–287.Google Scholar
  6. Dinas, E. (2010). The impressionable years: The formative role of family, vote and political events during early adulthood. Florence: European University Institute.Google Scholar
  7. Everitt, B. S., Landau, S., Leese, M., & Stahl, D. (2011). Hierarchical clustering. Cluster Analysis, 5th Edition, 2011, 71–110.Google Scholar
  8. Fincher, S., & Tenenberg, J. (2005). Making sense of card sorting data. Expert Systems, 22(3), 89–93.CrossRefGoogle Scholar
  9. Franklin, C. G. (2014). The impact of energy information upon small business owners. Lawrence: University of Kansas.Google Scholar
  10. Kleider, H. M., Pezdek, K., Goldinger, S. D., & Kirk, A. (2008). Schema-driven source misattribution errors: Remembering the expected from a witnessed event. Applied Cognitive Psychology, 22(1), 1–20.CrossRefGoogle Scholar
  11. Lindley, R. H. (1966). Recoding as a function of chunking and meaningfulness. Psychonomic Science, 6(8), 393–394.CrossRefGoogle Scholar
  12. Markman, A. B., & Ross, B. H. (2003). Category use and category learning. Psychological bulletin, 129(4), 592.CrossRefGoogle Scholar
  13. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological review, 63(2), 81.CrossRefGoogle Scholar
  14. Nadkarni, S., & Narayanan, V. K. (2007). Strategic schemas, strategic flexibility, and firm performance: The moderating role of industry clockspeed. Strategic management journal, 28(3), 243–270.CrossRefGoogle Scholar
  15. Paul, C. L. (2014). Analyzing card-sorting data using graphic visualization. Journal of Usability Studies, 9(3), 87–104.Google Scholar
  16. Princeton Review. (2016). Guide to Green Colleges 2016.Google Scholar
  17. Righi, C., James, J., Beasley, M., Day, D. L., Fox, J. E., Gieber, J., et al. (2013). Card sort analysis best practices. Journal of Usability Studies, 8(3), 69–89.Google Scholar
  18. Tulving, E., & Craik, F. I. (2000). The Oxford handbook of memory. Oxford: Oxford University Press.Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Design & Environmental AnalysisCornell UniversityIthacaUSA
  2. 2.Arts & Sciences, Psychology DepartmentCornell UniversityIthacaUSA

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