Arboriculture & Urban Forestry 35(1): January 2009 Table 2. Patronage variables—scenario comparisons. Scenarios Patronage variable Time willing to travel to reach place? Pearson χ 2 V = 0.271 Less than 10 min 10 to 20 min More than 20 min Total Distance willing to travel? Pearson χ 2 V = 0.183 Up to 2 mi 2 to 5 mi More than 5 mi Total Time would spend during visit? Pearson χ 2 V = 0.272 Up to 10 min 10 to 30 min More than 30 min Total Frequency or how often return? Pearson χ 2 V = 0.354 Less than once a month Once a week to once a month Once a week or more Total Response frequencies expressed as percentages. malls are not linear; responses to vegetated conditions exhibit a slight decline at the variables’ highest response levels but generally remain at higher frequencies than for the more barren streetscape. Why is the relationship of landscape and patronage behavior important? Multiple parameters affect the revenue potential of a site. For instance, visit frequency and duration, and customer travel range, have implications. Respondents claimed greater travel times for a mall that is landscaped, suggesting an expanded trade area radius that potentially includes thousands of people within dense urban population centers. Many businesses in strip malls are small, independent, startup enterprises. Increasing the amount of time spent by returning customers and having more people who have traveled greater distances to a mall site may translate to greater sales revenue (Underhill 1999) and perhaps a higher success rate for new entrepreneurs. Product Pricing The urban forest is a public good, rarely generating products that can be directly exchanged on markets. A pricing assessment was done using contingent valuation method (Mitchell and Carson 1989) to assess the impact of site landscape on local economics. Respondents were presented with a list of goods and services that 54 33 13 100% n = 76 20 51 29 100% n = 65 = 17.664, P < 0.000, Cramer’s DISCUSSION This and prior studies indicate that public response to retail land- scapes extends from what is visually pleasing to implications for shopper actions. A four-concept framework—visual quality, place perceptions, shopper patronage, and product pricing—guided a comprehensive measures approach that demonstrates the value of a green consumer environment. The product pricing results are often of greatest interest to merchant audiences, but other mea- sures yield insights as to why shoppers may be willing to pay more for products in malls having better landscape quality. Study images displayed a range of streetscape revisions. Public judgments of visual quality were most enhanced by the presence of trees and associated vegetation. Landscape influences obvious place qualities and provides cues of retail experiences for which there is no direct information. Although preference ratings were higher for landscaped settings, ratings of this study fell short of the highs in studies of central business districts (Wolf 2005), sug- gesting concerns about strip malls and reduced visual quality. Positive judgments about maintenance and image were also associated with the presence of landscape, despite the scenario base images having the same levels of building care and site tidiness. Respondents also attributed social traits and charac- teristics of the in-store experience based on vegetation condi- tions. Judgments of products and merchants were more positive in heavily landscaped places as were inferences about product value, product quality, and merchant responsiveness. Urban greening advocates are often challenged to demon- strate fiscal benefits from trees and other vegetation in urban set- tings. Responses on patronage variables relate directly to revenue potential, because they indicate a potentially expanded customer ©2009 International Society of Arboriculture = 11.327, P < 0.003, Cramer’s 29 54 17 100% n = 81 12 49 39 100% n = 72 = 5.185, P < 0.075, Cramer’s 40 32 28 100% n = 82 24 36 40 100% n = 72 55 41 4 100% n = 82 32 53 15 100% n = 72 = 11.310, P < 0.004, Cramer’s No Vegetation Mature Vegetation Index Convenience goods Shopping goods Specialty goods Table 3. Products pricing—scenario comparisons. Scenarios No Vegetation Mature Vegetation [Mean (SD)] [Mean (SD)] 7.74 (3.23) 10.34 (4.10) Independent samples t-test t = –3.840, P < 0.000, df = 116 37.88 (16.60) 52.96 (17.68) t = –4.650, P < 0.000, df = 110 54.64 (26.25) 67.24 (24.58) t = –2.220, P < 0.03, df = 79 would be available in a strip mall, representing product classes generally used by marketers: convenience, shopping, and spe- cialty goods. Respondents were asked to state the price they would be will- ing to pay for each of 15 items. Three index variables were con- structed. Significant differences were found when comparing means ( Table 3 ). Respondents reported lower values for goods in the No Vegetation mall. Price differences between scenarios are considerable: approximately 34% for convenience, 40% for shopping, and 23% for specialty goods. Analysis using weighted standardized scores across all products generated a more con- servative 8.8% difference, a finding consistent with the 9% to 12% range found for central business districts (Wolf 2005). An “amenity margin” in pricing represents potential revenues that can offset landscape investment and management costs. 37
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