Arboriculture & Urban Forestry 37(3): May 2011 ing diverse and adaptable long term fund-raising strategies and funding mechanisms is, thus, very important. Current informa- tion about the financial sources for community tree programs is lacking, partly due to the diverse sources (a mix of public funding; cost avoidance, reduction, and recovery; trust/private funds) and changing organizations involved (Zhang et al. 2009). In order to facilitate the development of urban and community forestry programs from a financial perspective, and to formulate a workable strategy, the industry needs to explore, assemble, and share information regarding public attitudes toward urban trees and the public’s willingness to support urban forestry programs financially. Public attitudes have a significant influence on many aspects, such as budgeting, public involvement and participa- tion, integration of tree programs into social infrastructure, and community identity (see Sommer et al. 1994; Barro et al. 1997; Austin 2002). Therefore, it is important to consult the public and better understand their attitudes in developing a diverse and adaptable strategy. Obtaining information regarding public pref- erences to support urban tree programs is, as a result, important. While many studies on urban forestry have analyzed public at- titudes on the benefits of urban trees (e.g., Dwyer and Miller 1999; McPherson et al. 1999; Thompson et al. 1999; Tyrvainen 2001; Gorman 2004; Lohr et al. 2004), a more critical issue is in de- veloping a sustainable and adequate community forestry support program (e.g., Lorenzo et al. 2000). The purpose of this paper is twofold. First, to examine public attitudes to urban trees including both amenities and negative impacts from trees, from the demand side. Secondly, to explore the public’s willingness and preferences to financially support urban forestry programs from a supply side. DATA COLLECTION AND METHODOLOGY To know public attitudes toward urban trees and to formulate a financial strategy for urban forest programs acceptable to the public, a household survey was conducted with a mail-in ques- tionnaire. Questions related to the following aspects were asked: • Perceived importance of urban trees on personal and com- munity property • Perceived benefits and negative features of urban trees and forests • Attitudes toward public funding of urban forests and the variety of sources of funding • Participation in urban forestry activities • Willingness to donate money or volunteer time to urban tree activities • Socio-demographic information such as age, education, employment status, income, race, gender and number of children The survey was conducted from late 2004 to early 2005. Survey Sampling International (One Post Road, Fairfield, CT, 06824 U.S.) was asked to obtain 3,500 random home ad- dresses (including phone number, addresses, and names) from major cities in the state of Alabama (Greenville, Cull- man, Mobile, Fairhope, Dothan, Montgomery, Demopo- lis, Auburn, Hoover, Birmingham, Huntsville, Florence). The questionnaires were mailed to the 3,500 participants. Ap- proximately 280 completed responses were received, with rough- ly 350 returned mailings (due to relocating homes or the database 119 used by Survey Sampling International having been too old). After three to four weeks the questionnaires were mailed again to those who did not respond. Approximately 220 completed re- sponses were received, with 50 additional bad addresses. After one month, the study authors randomly selected 250 addresses who never responded. These addresses were targeted with the en- closed incentive of 3.7 U.S. dollars (the value of postage). This method did work to some degree, since 80 of these 250 addresses were also received. In total, 582 responses were received, of which there were 102 incomplete responses. Overall there was a 20% response rate from 3,100 valid addresses. The response rate was a little lower than expected considering the nature of the survey. In the data analysis, simple statistical methods are used to describe the attitudes and preferences to urban trees and financ- ing strategies. OLS (ordinary linear regression) regression and ordered logistic model are further applied to investigate what fac- tors might influence the preferences. For example, the amount of monetary value that the respondents consider “should” be do- nated (e.g., using tax to impose the changes to all households) and “would” be donated (voluntary contribution) as a function of family background, personal characteristics, and their atti- tude indicators was of particular interest. The difference between public choice (should donate) and individual choice (willing- ness to donate or would donate) has been investigated for sev- eral decades (e.g., Arrow 1951). People have one set of prefer- ences that govern their private choices, and another set that governs social actions and choices (Kelman 1981; Sagoff 1988; Sen 1995). For example, individual choice of grazing under open access institutional arrangement would cause the tragedy of the commons due to free rider problem. However, open ac- cess would not be chosen if public choice arrangement is made. The central question here—“should donate” versus “would donate”—is to see the individual behaviors under current insti- tution of voluntary contribution versus public choice of forced payment on public support to urban tree program. For example, many people would say they would not donate, but they might support to collect additional property tax to support the urban forest program. For this purpose, a question in the question- naires was intended to ask the amounts of an average family support urban tree program annually through state sales tax, lo- cal property tax, estate tax alcohol, tobacco tax, state income tax, corporate income tax, and private donations to know how much the respondents think is appropriate (or should) to sup- port urban tree programs. The second question asked regard- ed the amount the respondent would like to donate of their money to support urban tree activities in their area annually. Following research by others (e.g., Yen et al. 1997; Saz- Salazar and Garcia-Menendez 2001), it is hypothesized that an individual’s response to support urban tree programs depends on his/her income, education, race, gender, experience, and residential location. The OLS regression models are as follows: [1] [2] Would donate = β0 Should donate = β0 + βi + βi χi χi + ε + ε where should donate is the response to the answer of Question 1 and would donate is the response to the answer of Question 2. The de- pendent variable equals the mean value of each choice. For exam- ple, choice C is corresponding to $115. The independent variables ©2011 International Society of Arboriculture
May 2011
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