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ICoRD'13 pp 1287–1299Cite as

Classifying Shop Signs: Open Card Sorting of Bengaluru Shop Signs (India)

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Part of the Lecture Notes in Mechanical Engineering book series (LNME)


Any Classification into categories aids in retrieving information. It develops a system for an object or phenomena. Hence, a classification of shop signs would provide an informed view about the system of elements that form the identity of a shop sign. The Philosophy of Classification as explained by Ereshefsky [1] brings to light three kinds of paradigms: Essentialism Sorts, Cluster Analysis and Historical classification. This study investigates the relevance of creating categories through cluster analysis. The analysis helps collate the pragmatic approach applied by the viewers of the shop signs. How people classify shop signboards mentally? What clues they use to attach qualities or concepts with a shop sign? Applying the method of Open Card Sorting [2] increased the analytical scope about the new values attached with the identities represented on these shop signs through text, images and materials. There is a paucity of published research in favour of the above statement. Therefore, this paper is a sincere attempt to substantiate the benefits of arriving at new categories via Open Card Sorting. This method provided the participants to design their own labels and classification structure for the given shop signs. A group of 30 participants (15 designers and rest 15 from other professions) underwent Open Card Sorting exercise. With formal instructions about card sort method, every participant was asked to ‘think aloud’ in order to resolve the 90 cards puzzle. Additionally, two standard questions regarding good and bad signs in the picture cards were asked. Around 20 new categories could be accumulated in the SPSS software. The viewers did not categorise total 10 cards of the 90 into any label(s). Cluster Analysis of this data gave rise to new classes/genres of these shop signs. It also clustered those cards that were considered good and bad shop signs. It is a unique study to know how people view, read and form opinions about shop signs. Results of this study can be used to inform the designers about the new features/qualities of the content and form observed by viewers along with their opinions on good and bad signs. Therefore, these insights would be the essential parameters in terms of elements of design and related qualities that sign designers should apply in the design of shop signs.


  • Open Card Sorting
  • Generative Research Methodology
  • Classification
  • Structures
  • Taxonomy
  • Shop Signs
  • Identification
  • Signs
  • India

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I express my utmost gratitude to my guide, Prof. Ravi Poovaiah for motivating discussions regarding the research aims and the methods used for the current study. My deepest gratitude goes to Prof. Uday A. Athavankar to share his insights as one of the participants and further aid in bringing more respondents for the study. This experimental study wouldn’t have been possible without the support of Prof. B. K. Chakravarthy. He provided us with good space of IDC studio to conduct the experiment.

A Big Thank You to all the respondents from IDC and other departments of IIT Bombay for their keen interest to sort cards and solve the puzzle.

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Correspondence to Nanki Nath .

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© 2013 Springer India

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Nath, N., Poovaiah, R. (2013). Classifying Shop Signs: Open Card Sorting of Bengaluru Shop Signs (India). In: Chakrabarti, A., Prakash, R. (eds) ICoRD'13. Lecture Notes in Mechanical Engineering. Springer, India.

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  • Publisher Name: Springer, India

  • Print ISBN: 978-81-322-1049-8

  • Online ISBN: 978-81-322-1050-4

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