Main Article Content
This study sought to answer questions about the extent to which on-premise signs (OPS) along US roadways attract the attention of passing motorists, based on a sample of OPS and roadway contexts captured in photo images from along the 3,073 mile length of highway US 50. 3M's Visual Analysis Software (VAS) was used to predict the probability that the selected OPS would be viewed by passing motorists. Results show that for all signs (n=467), the average probability of being viewed was about 57%, with that rising to about 66% for a "primary signs" group (n=100). These results are consistent with early research of motorist detection of on-premise signs in real-world contexts. The findings suggest that a substantial proportion (approximately one-third) of the on-premise signs along roadways in the US are not being viewed by motorists as business intended, and both the businesses and their communities are foregoing the benefits that more effective signage would provide. This study also sought to determine whether the OPS of national and regional businesses are better able to attract the attention of passing motorists compared to the OPS of locally-based businesses. The results show the average probability of being viewed for the national and regional business OPS is significantly higher than for the local businesses, though both business types showed substantial variation in the probability of viewing. These results suggest an opportunity for the OPS of local businesses to be improved. Both findings here raise important implication for understanding how both local sign regulations and industry design and location standards factor into causing and resolving the problem. Finally, VAS was found to provide quick and inexpensive objective analysis of OPS in real-world contexts. Future research is needed to develop advanced protocols for the use of VAS in analyzing OPS in complex environmental contexts.
3M Visual Attention Software. (2017), How VAS Works. Maplewood, MN: 3M Corporation. Accessed March 29, 2017 at http://solutions.3m.com/wps/portal/3M/en_US/VAS_NA/Home/How2/.
Auffrey, C., Hildebrandt, H., & Rexhausen J. (2011), Economic Value of On-Premise Signs. Proceeding of the National Signage Research and Education Conference, Signage Foundation, Inc. Cincinnati, October.
Auffrey, C., & Hildebrandt, H. (2013), Assessment of the Impacts of Contextual Elements of On-Premise Signage. Proceeding of the National Signage Research and Education Conference, Signage Foundation, Inc. Cincinnati, October.
Auffrey, C., & Hildebrandt, H. (2014), Utilizing 3M's Visual Attention Service software to assess on-premise signage conspicuity in complex signage environments. Proceeding of the National Signage Research and Education Conference, Signage Foundation, Inc. Cincinnati, October.
Auffrey, C., Hildebrandt, H., & Mehta, V. (2015), Context and Signage Effectiveness. Proceeding of the National Sign Research and Education Conference, Signage Foundation, Inc., Norman, OK. October.
Babbie, E. (2010), The Practice of Social Research. Belmont, CA: Wadsworth Cengage.
Baines, P. & Dixon C. (2008), Signs: Lettering the Environment. London: Laurence King Publishing.
Bertucci, A. (2006), Sign Legibility Rules of Thumb. Bristol, PA: United States Sign Council.
Bertucci, A. & Crawford, R. (2016), Model Code for the Regulation of On-Premise Signs. Bristol, PA: United States Sign Council.
Calori, C. & Vanden-Eynden, D. (2015), Signage and Wayfinding Design: A Complete Guide to Creating Environmental Graphic Design Systems, 2nd Ed. Hoboken, NJ: John Wiley & Sons. https://doi.org/10.1002/9781119174615
Conroy, D. (2004), What's Your Signage? Albany: New York Small Business Development Center.
Ellis, S., Johnson, R. & Murphy, R. (1997), The Economic Value of On-Premise Signage. San Diego: California Electric Sign Association.
Garvey, P., Zineddin, A., Porter, R. and Pietrucha, M. (2002), Real World On-Premise Sign Visibility: The Impact of the Driving Task on Sign Detection and Legibility. University Park, PA: Pennsylvania Transportation Institute.
Hawkins, H.G. (2011), Sign Legibility Considerations for On-Premise Signs Technical Report, in A Legal and Technical Exploration of On-Premise Sign Regulation: An Evidence Based Model Sign Code, eds. D. Jourdan, H.G. Hawkins, R. Abrams & K. Winson-Geideman, College Station, TX: Urban Design Associates, 14-30.
Jakle, J. (2004), Signs in America's auto age: signatures of landscape and place. Iowa City, IA: University of Iowa Press.
Jourdan, D., Hurd, K., Hawkins, H.G., Abrams, R. & Winson-Geideman, K., (2013), Evidence-Based Sign Regulation: Regulating on the Basis of Empirical Wisdom (2013). Urban Lawyer, 45(2), 327-348.
Kellaris, J. & Machleit, K., 2016. Signage as Marketing Communication: A Conceptual Model and Research Proposition, Interdisciplinary Journal of Signage and Wayfinding, 1 (1).
Kuhn, B., Garvey, P. & Pietrucha, M. (1997), Model Guidelines for Visibility of On-Premise Advertisement Signs, Transportation Research Record, 1605, Paper No. 970507, 80-87.
Morris, M., Hinshaw, M., Mace, D. & Weinstein A. (2001), Context-Sensitive Signage Design, Chicago: American Planning Association.
Pegler, M. (2015), Designing the Brand Identity of Retail Spaces, New York: Fairchild Books.
Rickard, L. N., & Stedman, R. C. (2015), From ranger talks to radio stations: The role of communication in sense of place. Journal of Leisure Research, 47(1), 15-33. https://doi.org/10.1080/00222216.2015.11950349
Taylor, C.R. & Sarkees, M.E. (2016), Do bans on illuminated on-premise signs matter? Balancing environmental impact with the impact on businesses. International Journal of Advertising, 35(1): 61-73. https://doi.org/10.1080/02650487.2015.1059005
Tseng, P., Carmi, R., Cameron, I., Munoz, D. & Itti, L. (2009), Quantifying center bias of observers in free viewing of dynamic natural scenes. Journal of Vision, 9(7): 1-16. https://doi.org/10.1167/9.7.4
Wheeler, A. (2012), Designing Brand Identity: An Essential Guide for the Whole Branding Team, 4th Ed. Hoboken, NJ: John Wiley & Sons.
Zhang, L., Tong, M., Marks, T., Shan, H., & Cottrell, G. (2008), SUN: A Bayesian framework for saliency using natural statistics. Journal of Vision, 8(7): 1-20. https://doi.org/10.1167/8.7.32