*2.4. Conjoint Analysis Experiment Procedure*

The Conjoint Analysis (CA) experiment was designed using ornamental landscape plants (i.e., bedding plants, flowering annuals, and perennials) as the product, since they generated the most plant sales in Florida in 2013 [40]. Additionally, plants were selected as a product because they typically are sold with very little in-store signage and limited brand promotions [41]. Consequently, participants' preconceptions about the products are more limited than highly branded or promoted products. Several species of plants (petunias, pentas, and hibiscus) were included in the analysis to account for differences in individual preferences (Table 2). To simulate a common retail garden center display, five plants were presented on a bench, with additional attributes (i.e., price, production method, origin, and pollinator friendly attributes) being presented as above-plant signs (Figure 1). Previous studies have successfully used this bench/attribute sign design to elicit consumers' purchasing preferences for ornamental plants [2,42,43].


<sup>a</sup> Plant types and price points were selected based on products and prices at several retail outlets (i.e., big box stores, independent garden centers, etc.) in the study area. <sup>b</sup> Indicates base variables.

In this study, three price points (\$10.98, \$12.98, \$14.98) were used based on prices of similar plants in higher end specialty garden centers, as well as lower price points from mass retailers and box stores in the study area (Table 2). Production methods included certified organic, organic production (but not certified), and conventional levels. Origin attributes included in-state, domestic, and imported levels. The pollinator friendly attribute was either labeled or not labeled. Sign order was

randomized to eliminate order effect. Production method, origin, and pollinator friendly attributes were included to cover credence attributes that potentially add value to the products [44]. Additional attributes (such as size, care requirements, etc.) were controlled by informing participants that they were consistent across the products. A fractional factorial design was used to generate 16 product images for the Conjoint Analysis (CA) experiment to reduce participant fatigue. Participants rated their purchase likelihood for each product on a 7 point Likert scale (1 = not at all likely; 7 = very likely). While evaluating each product scenario, participants' eye movements were recorded. Participants also completed a survey with price-conscious and socio-demographic questions.

**Figure 1.** Example of the conjoint analysis product images.
