Abstract
Online sales of plants are relatively new compared with other products. An online survey was used to measure online and in-store plant/flower spending from 1290 participants. Participants were satisfied with their online plant/flower purchases and spent $31.86 more on plants/flowers through online retailers than in stores. Participants’ social media use increased their in-store plant/flower spending but not online spending. Using Amazon, Google, and farm-direct online retailers increased both in-store and online plant/flower spending. Demographic characteristics did not influence online or in-store spending, except income which had a positive effect.
Before 2017, horticulture had limited (∼5%) online sales capacity (Cohen and Baldwin 2018). In 2017, an estimated 19% of horticulture firms sold online with less than 1% using Amazon (Baker et al. 2018). More recently, online plant sales were 17.5% in 2021 but dropped to 11% in 2023 after the pandemic (Whitinger and Cohen 2021, 2023). During the pandemic, plant purchasers indicated evolving preferences toward online and in-store plant purchasing (Campbell et al. 2021). This study investigates the extent to which satisfaction, product reviews, and time spent online influences consumer plant/flower spending online vs. in store.
Studies show a direct relationship between satisfaction and online spending (Akhter 2012; Nisar and Prabhakar 2017) and time spent online (Hannah and Lybecker 2009). One study found that online reviews did not affect movie purchase decisions, but the volume of reviews increased sales (Duan et al. 2008). Although research has investigated consumer satisfaction and reviews’ impact for online shopping, that is not the case for in-store purchasing. One study found a positive relationship between customer satisfaction and future spending but did not look at specific retail channels (Fornell et al. 2010). In the horticulture industry, Baker et al. (2020) determined that millennials respond well to high-quality visuals, but not 360-degree videos, when making online purchases. We did not identify any studies that investigated whether online (vs. in-store) spending on plants/flowers was influenced by satisfaction, product reviews, and time spent online.
Materials and methods
An online survey was launched through Qualtrics LLC (Provo, UT, USA) in Sep 2022. Qualtrics is an online survey and panel provider with 200 million panelists (Qualtrics.com). Before participation, panelists must pass a series of screening questions. In the current work, to participate, participants needed to be 18 years old or older and have purchased a flower/plant within the past 6 months. Only participants who had purchased a flower/plant online were analyzed. A total of 2144 people completed the survey, and 1290 (60% of the sample) purchased plants/flowers online. All procedures were approved by an institutional review board (MSU7913).
Stated preference metrics were used, which occur when people indicate their preferences, in contrast to revealed preferences, which are from actual purchases. Stated preferences data assess values and choice behavior but are subject to hypothetical bias given that no purchase occurs (Johnston et al. 2017). The survey included questions on online and in-store plant/flower purchases, online spending, online retailers used to buy plants/flowers, time spent online, online review perceptions, satisfaction, and demographics (Table 1). Three spending metrics (online and in-store plant/flower spending, and general online spending) were measured using a $0 to $500+ scale. Eight online retailers were listed, and participants selected where they bought plants/flowers (1 = selected; 0 = otherwise).
Questions and answer options from the survey instrument used to determine online and in-store plant spending (n = 1290).
Participants’ satisfaction level with their online plant/flower purchases was measured using five statements (1 = very unsatisfied; 7 = very satisfied; Fig. 1). An index was generated in which the statements were recoded into three categories [unsatisfied (<4), neutral (4), and satisfied (>4)] and averaged (Cronbach’s alpha = 0.859). Participants responded to four review perception statements (1 = strongly disagree; 5 = strongly agree) that were averaged for a single “review” index with a Cronbach’s alpha of 0.816 (Fig. 2).
Satisfaction statement ratings distribution.
Citation: HortTechnology 34, 4; 10.21273/HORTTECH05427-24
Review index statement means (n = 1290).
Citation: HortTechnology 34, 4; 10.21273/HORTTECH05427-24
Plant/flower spending was the dependent variable with a lower ($0) and upper limit ($500+), because of these parameters, Tobit models were used. Two models addressed differences by retailer type with Model 1 analyzing online plant/flower spending, while Model 2 focused on in-store spending.
Results
Average age was 43 years old (SD = 12.7), 53.2% (SD = 0.50) were female, 35.2% (SD = 0.48) had a college degree, 38.0% (SD = 0.49) had a graduate degree, and the 2021 household income was $107,380 (SD = 68.15). The majority were White/Caucasian (M = 0.86, SD = 0.346), 9.5% (SD = 0.29) were Black, and 5.3% (SD = 0.23) were other races/ethnicities. Participants spent $222.05 (SD = 166.93) on plants/flowers online and $150.53 (SD = 139.26) on plants/flowers in-store in the prior 6 months. Generally, participants were satisfied with their online purchases (87% were satisfied). Amazon was used by 64% of the sample to buy plants/flowers, followed by farm-direct sites (56%), social media (35%), Google (29%), Etsy (24%), neighborhood sites (20%), other sites (10%), and Craigslist (9%). People spent 20.5 h/week online for work (SD = 16.6), 22.7 h/week for leisure (SD = 16.0), and $297.80 (SD = 169.72) on online purchases. The four review index statements are presented in Fig. 1. The review index’s mean of 4.10 (SD = 0.70) indicated agreement that reviews positively impact online purchasing behavior.
The Tobit models assessed how factors impact plant/flower spending (Table 2). People who were satisfied with their online purchase spent $31.86 more on plants/flowers through online retailers (model 1), which aligns with the retailing literature (Akhter 2012; Nisar and Prabhakar 2017). People who bought plants/flowers through Amazon, Google, Etsy, farm-direct, and neighborhood sites spent more on plants/flowers online. More work and leisure time spent online increased online plant/flower spending and is supported by retail research (Hannah and Lybecker 2009). Online spending increased the amount spent on plants/flowers online by $0.51. Income positively influenced online plant/flower spending.
Factors impacting plant spending at online and in-store retailers from online plant buyers from an online survey of US consumers in 2022 (n = 1290).
For in-store plant/flower spending (model 2), satisfaction with online plant/flower purchases had a negative impact on in-store spending (−$21.63; Table 2). Interestingly, purchasing plants/flowers via social media, Amazon, Google, and farm-direct websites increased in-store spending. Time spent online for work and leisure, online spending, and income increased in-store spending. Customers may use online information to explore options before purchase. For instance, Cao et al. (2012) demonstrated positive relationships between online searches and in-store visits and shopping.
Discussion
Satisfaction increased online plant/flower spending, which may reflect greater customer satisfaction with online purchases due to greater efficiency, availability and searchability rather than traveling from store to store, seeking a specific item. The literature shows that heightened satisfaction is linked to spending more online (Akhter 2012; Nisar and Prabhakar 2017). Social media use increased in-store plant/flower spending but not online spending; perhaps social media is being used for inspiration. Use of Amazon, Etsy, and farm-direct may serve similar roles, whereas Google is used to find retailer locations and product availability. Relatedly, time and online spending both positively influenced plant/flower spending. This finding underscores the importance of having timely information readily available when customers are online to stimulate ideas and purchases. Supporting evidence shows online searches positively impact in-store purchasing (Cao et al. 2012). Higher income also increased spending, so targeting higher-income households with marketing strategies is beneficial. Conversely, product reviews did not influence spending. Study limits include hypothetical methods and limited number of study parameters. Future studies could incorporate retail scanner data and additional parameters to address these limits and generate marketing insights.
References cited
Akhter SH. 2012. Who spends more online? The influence of time, usage variety, and privacy concern on online spending. J Retail Cons Serv. 19(1):109–115. https://doi.org/10.1016/j.jretconser.2011.10.002.
Baker LM, Boyer CR, Peterson HH, King AE. 2018. Online opportunities: A quantitative content analysis benchmark study of online retail plant sales. HortTechnology. 28(4):516–523. https://doi.org/10.21273/HORTTECH03901-17.
Baker LM, Tull KM, Sumners DR, Jones EF, León-Reyes AE, Boyer C, Peterson HH. 2020. Is it for generation me? A qualitative study exploring marketing and selling plants online to millennial-aged consumers. J Appl Commun. 104(2):2.
Campbell BL, Rihn AL, Campbell JH. 2021. Impact of the Coronavirus pandemic on plant purchasing in Southeastern United States. Agribusiness. 37(1):160–170. https://doi.org/10.1002/agr.21685.
Cao XJ, Xu Z, Douma F. 2012. The interactions between e-shopping and traditional in-store shopping: An application of structural equations model. Transportation. 39(5):957–974. https://doi.org/10.1007/s11116-011-9376-3.
Cohen P, Baldwin I. 2016. National Gardening Survey. National Gardening Association, Williston, VT, USA.
Duan W, Gu B, Whinston AB. 2008. Do online reviews matter?—An empirical investigation of panel data. Decis Support Systems. 45(4):1007–1016. https://doi.org/10.1016/j.dss.2008.04.001.
Fornell C, Rust RT, Dekimpe MG. 2010. The effect of customer satisfaction on consumer spending growth. J Market Res. 47(1):28–35. https://doi.org/10.1509/jmkr.47.1.28.
Hannah B and Lybecker KM. 2009. Determinants of recent online purchasing and the percentage of income spent online. Colorado College Working Paper No. 2009-02. https://ciaotest.cc.columbia.edu/wps/doeabcc/0017429/f_0017429_14911.pdf. [accessed 5 May 2022].
Johnston RJ, Boyle KJ, Adamowicz W, Benneett J, Brouwer R, Cameron TA, Hanemann WM, Hanley N, Ryan M, Scarpa R, Tourangeau R, Vossler CA. 2017. Contemporary guidance for stated preference studies. J Assoc Environ Resource Econ. 4(2):319–405.
Nisar TM, Prabhakar G. 2017. What factors determine e-satisfaction and consumer spending in e-commerce retailing? J Retail Cons Serv. 39:135–144. https://doi.org/10.1016/j.jretconser.2017.07.010.
Stata. 2024. Tobit regression | Stata Annotated Output. https://stats.oarc.ucla.edu/stata/output/tobit-regression/#:~:text=Tobit%20regression%20coefficients%20are%20interpreted,increase%20in%20the%20corresponding%20predictor. [accessed 28 Jun 2024].
Whitinger D, Cohen P. 2021. National Gardening Survey: 2021 Edition. Conducted by Dynata for National Gardening Association, https://gardenresearch.com/view/national-gardening-survey-2021-edition/. [accessed 5 May 2022].
Whitinger D, Cohen P. 2023. National Gardening Survey: 2023 Edition. Conducted by Dynata for National Gardening Association, https://gardenresearch.com/view/national-gardening-survey-2023-edition/. [accessed 12 Jan 2024].