The turfgrass industry is expanding rapidly as one of the fastest growing segments of agriculture sales in the United States due to its aesthetic benefits for residential and commercial properties (Haydu et al., 2006; Morris, 2003). The total value of turfgrass production in the five states in this study (Florida, Georgia, North Carolina, Oklahoma, and Texas) comprised $404,821,402 in sales in 2012 (USDA-NASS, 2015). Apart from providing an aesthetically pleasing surface for outdoor activities, turfgrass is also used for soil stabilization, water conservation, air and water filtration, and heat dissipation in urban areas. However, lawns occasionally create environmental externalities due to overuse of inputs like chemical fertilizer, pesticides and herbicides, high water use, and solid waste (Bormann et al., 2001).
A study by Milesi et al. (2005) found that three times more lawn is grown than any other irrigated crop in the United States, or ≈163,812 km2, making turfgrass the largest irrigated crop in the United States. According to the U.S. Geological Survey, of the 26 billion gallons of water consumed daily in the United States, ≈7.8 billion gallons (30%) are devoted to outdoor uses, mainly landscaping (Solley et al., 1998; Vickers, 2001). About 40% to 75% of household water use is used for turfgrass irrigation in arid and semiarid regions (Ferguson, 1987; Mayer et al., 1999; Morris, 2003).
In the context of weather variability, climate change, drought, and reduced water supplies, lawn maintenance has become a challenge. During drought and water shortages, municipalities often prohibit the use of potable freshwater on the turfgrass landscape, considering it a low priority (Kjelgren et al., 2000). Many cities have imposed mandatory irrigation restrictions, water audits, water bans, and increased prices for potable water to minimize water scarcity during droughts and to meet long-term water demand (Kenny et al., 2009). Thus, the shortage of freshwater or municipally treated water has compelled homeowners to use effluent or low quality water such as rainwater or reclaimed water for lawn irrigation purposes. Proper turfgrass management is also affected by several problems such as salinity, shade, winter stress, and high maintenance cost. The use of low quality water in hot and dry climates (drought conditions) may cause higher concentrations of salt in soil profile which not only adversely impacts turfgrass growth but also increases the maintenance cost. In addition, use of salt for road thawing in winter or intrusion of seawater in the coastal cities also increases the salinity problem in turfgrass (Murdoch, 1987). Furthermore, many home lawns have been adversely impacted by shade (Harivandi and Gibeault, 1996). Loss of turfgrass during winter due to freezing temperatures, termed as winterkill, is also another major problem of lawns (Frank, 2013). It is, therefore, necessary to develop more water-efficient and sustainable turfgrass cultivars that have wider geographical adaptability and are tolerant to several environmental stresses (drought, salinity, shade, and winterkill) to cope with environmental stresses and to better maintain turfgrass. This drives the demand for more innovative turf types that can tolerate stress and are economical to maintain (Yue et al., 2012). However, turfgrass breeders and producers desire more quantitative data on marketability of turfgrass traits to guide research in times of uncertain budgets (D. Martin, personal communication).
Determining consumers’ preferences for product characteristics has gained increasing attention in decision-making and public policy. Prioritizing the importance for marketed agricultural goods is necessary to understand and manage the outcomes of research in publicly funded research in variety development. Developing and releasing a product depends on the desirability of the product to consumers compared with other products with similar characteristics, in this case, turfgrass, developed over years and decades of research. This current study of how consumers’ prioritize several turf cultivars emphasizing shade, drought, winterkill, and saline tolerance in warm-season turfgrasses will help researchers focus on developing and marketing of highly desirable cultivars. Targeting research will maximize the benefit of publicly and privately funded turfgrass research and marketing efforts. Thus, the specific objective of this study is to identify the shares of preferences for stress-tolerant, low-maintenance, and low-cost turfgrass attributes from homeowners’ perspectives in five states (Florida, Georgia, North Carolina, Oklahoma, and Texas) in the southeastern and midsouthern United States.
Public preferences for different products or the attributes of a product are usually elicited by direct or indirect valuation methods. Some of the most popular and relevant methods to elicit and rank consumers’ preferences in hypothetical scenarios are the DCEs and the ranking methods such as BWM (Bleichrodt, 2002). The DCE is a stated preference method which allows us to not only analyze consumers’ preferences, but also to determine the shares of preferences of the attributes used in the experiment. The shares of preferences indicate the relative importance of the attributes used in the study ranging from 0 to 100 in percentage form. Shares of preferences for all the attributes total 100%. The shares of preferences of attributes can be determined by measuring the utility (part-worth) of attributes in various combinations of choices made (Louviere et al., 2000; Louviere and Woodworth, 1983). The BWM is a direct preference elicitation method that measures the subjective dimension, such as “degree of importance” or “degree of interest” (Auger et al., 2007). The BWM is a relatively simple method that yields coefficients for each attribute that can be used to determine the shares of preferences as the forecasted probability of the attributes.
Both the DCE (Cheraghi et al., 2008; Lancsar and Louviere, 2008; Ryan and Gerard, 2003) and the BWM (Flynn et al., 2007; Goodman et al., 2005; Lusk and Briggeman, 2009) have been widely used to determine the shares of preferences of attributes separately. Although some comparative DCE–BWM studies have been performed on the health technology sector (Potoglou et al., 2011; Whitty et al., 2014), there are few studies that focus on their relative performance in the agricultural sector goods like turfgrass, an essential component of many residential homes and always in demand. This study reports an empirical comparison of the DCE and the BWM using data collected from a survey conducted to elicit homeowners’ values for different turfgrass attributes and compares the two methods directly using shares of preference for the turfgrass attributes in five states (North Carolina, Florida, Georgia, Oklahoma, and Texas) in the southeastern and midsouthern United States.
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