The Use of New-media Marketing in the Green Industry: Analysis of Social Media Adoption and its

impact on Sales

Becatien Yao Kansas State University

byao@ksu.edu

Aleksan Shanoyan Kansas State University

Hikaru Hanawa Peterson University of Minnesota

Selected Paper prepared for presentation at the 2017 Agricultural & Applied Economics Association

Annual Meeting, Chicago, Illinois, July 30-August 1

Copyright 2017 by Becatien Yao, Aleksan Shanoyan and Hikaru Peterson. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies.

The Use of New-media Marketing in the Green Industry: Analysis of Social Media

Adoption and its impact on Sales

Abstract

The green industry also known as environmental horticulture industry was one of the fastest

growing segment of the US agriculture in 2004. Following the recession, the decline in the

industry revenues resulted in a stream of consolidation and an increasing rivalry within the

industry, putting smaller firms at a competitive disadvantage. To remain competitive,

individually and family own nurseries and garden centers need to rely on lower cost and most

effective marketing strategies to reach their customers. During the last decade, new-media

marketing has proved to be effective in various industries but observations reveal a relatively low

use of this marketing venue among smaller green industry firms. The purpose of this study was

to understand the factors driving adoption of new media marketing and its impact on the

financial performance of the green industry firms. Using primary data from a survey covering

153 cities in six states across the US, the study examines the importance of respondent, firm and

market characteristics on the probability of new media marketing adoption leading to two

models. A binary logit model is used to analyze the factors of adoption while an OLS estimation

is conducted to determine the impact of new-media marketing on sales. The size of the network,

the personal characteristics, and beliefs and the firm’s characteristics are determinant in new-

media marketing adoption. The study also provides some evidence about the positive return of

social media use by smaller firms.

The Use of New-media Marketing in the Green Industry: Analysis of Social Media

Adoption and its impact on Sales

1. Introduction

The green industry also known as environmental horticulture industry is comprised of several

segments. The major segments of the industry include wholesale nurseries, greenhouse and sod

growers, landscape architects, contractors and maintenance firms, retail garden centers, home

centers and mass merchandisers with lawn and garden departments. The U.S. green industry

ranked among the fastest growing segments of U.S. agriculture in 2004, as a result of two

decades of steady growth (Hall et al., 2005). During the recession, the decline in home value and

home ownership has reduced the demand for ornamental plants, lawn and garden products, and

related services, which resulted in a significant negative effect on the green industry revenues

(Hodges et. al, 2015; Hall, 2010). From 2007 to 2012, the total sales of U.S. nursery and garden

center products has shrunk by 12.72% whereas the number of nurseries and garden centers has

increased by 3.87% (USDA, 2014). As a result, the industry experienced considerable

consolidation and rivalry particularly between mass merchandisers and family owned rural firms.

Garden centers are facing increased competition and using marketing channels that are less than

ideal to reach today’s modern, online consumer (Behe et al., 2013). In order to maintain long-

term competitiveness, smaller-sized nurseries need to reevaluate their marketing strategy.

New-media marketing methods provide new opportunities to firms to engage in social interaction

with their customers on the Internet. Due to the participation of the customer in generating

content, new-media marketing methods have deeply modified the configuration of the

relationship between customers and businesses since the last decade. These methods which offer

an opportunity to build and maintain stronger consumer relationship are increasingly being used

in various industries. However, Green industry firms rely more on traditional advertising

methods to reach their customers. In 2013, green industry firms and growers in particular mainly

used trade journals and trade shows to reach their customers with respectively 57% and 12% of

their advertisement budget allocated to these traditional outlets (Hodges and Khachatryan, 2015).

Although few studies have formally addressed the impact of new-media marketing on firms’

performance, their proliferation among businesses suggests a benefit from their adoption as a

marketing tool. This spread is justified not only by their effectiveness to improve business

productivity but also of their relatively low cost. The Marketing in a Digital World SMB and

Consumer Survey (2011) found that the majority of the small and medium businesses surveyed

(59%) spent less than $100 to conduct their social media marketing strategy on various channels.

The purpose of the study is to determine the factors that affect the adoption of new-media

marketing and evaluate the impact on the performance of nurseries and garden centers. The

potential factors being examined are firm characteristics, marketing practices, and market

characteristics. Although social media marketing is increasingly being adopted by small and

medium businesses, observations reveal little interest among rural nurseries and garden centers.

A few of them maintain a social media account or an interactive website. Stebner (2015) reported

that garden centers remained unsure of the impact of a social media strategy on their business

performance. Few studies that have addressed the factors and impacts of new-media marketing

adoption in the green industry indicate that agribusinesses and agricultural organizations were

not using new-media marketing tools to their full potential (Topp et al., 2014). Understanding the

potential factors of adoption and impact on sales will allow developing extension intervention

that could contribute to improving the marketing strategy of rural and smaller green industry

firms.

2. Related literature

Social media adoption has mainly been addressed from the end-user or consumer’s perspective

with scant attention paid to small and medium businesses. Zilberman and Kaplan (2014)

examined the influence of social networks on food decision-making from the consumer

standpoint by reviewing the adoption literature. They argued that the exchange of information

among members of a network was increased by social networking sites and concluded that social

media may have considerable impacts on major food-related choices by consumers. Liu and Rui

(2014) proposed an approach to estimate the impact of social media exposure on demand for

carbonated soft drinks. They combined a utility maximization and a social media exposure

function to explain how social media influenced consumer valuation of product characteristics.

They suggested that conversations about specific brands increased consumer awareness about

those brands and that conversations about sugar reduced consumer valuation of sugary drinks.

The methodology used in these studies is based on consumer’s utility maximization, not

accounting for the firm’s profit maximization problem.

From the firm’s standpoint, most of the studies conducted on social media adoption use the

technology acceptance model. For example, using the Technology Acceptance Model (TAM)

framework to study Web 2.0 adoption, Lorenzo-Romero et al. (2014) found that only the

perceived ease of use was a determinant in the adoption of Web 2.0 as a marketing tool by

Spanish retailers. Similarly, Shaw (2013) analyzed the competencies, importance, and

motivations for agricultural producers’ use of online marketing using the technology acceptance

model, along with two other IT technology adoption frameworks: the diffusion of innovation by

Rogers (2003) and the uses and gratifications theory by Katz et al. (1973).

Wamba and Carter (2014) stressed the uniqueness of new-media marketing and the need to

distinguish social media from other types of innovation. Features such as real-time sharing of

customers’ choice and active engagement of users differentiate this technology from other and

necessitate addressing social media marketing using a more adapted framework. They posited

that three sets of characteristics impact the adoption of social media by small and medium

enterprises: firm characteristics (e.g., firm innovativeness, firm size), manager characteristics

(e.g., age, gender, and education), and environmental characteristics (e.g., firm geographic

location). Their results indicated that firm innovativeness, firm size, manager’s age and industry

sector had significant impacts on the adoption of new-media marketing by firms. Nah and Saxton

(2013) modeled the adoption of social media by nonprofit organizations using key factors

identified by the nonprofit literature. They concluded that three groups of factors may impact

social media adoption: organization characteristics (organizational strategies and capacities),

management characteristics, and environmental factors (e.g., external pressures).

Few studies have addressed the factors of new-media marketing adoption in the green

industry. The recent literature focuses on the level of use of social media across agricultural

farmer’s populations. Shaw (2013) discussed the level of use of online communication tools by

beginning farmers and ranchers in Texas, Illinois, and Georgia. He found that all groups of

farmers are not using online communication tools to their full potential. Topp et al. (2014)

provided meaningful assessments of the level of use of Pinterest by agricultural producers and

businesses. They found considerable differences between agricultural segments in the degree of

use of Pinterest to reach customers, with a higher number of pinners in the livestock segment.

The specialty crops sector which includes the green industry firms accounted only for 9.1% of

Pinterest users. This study further indicated that agribusinesses and agricultural organizations

were also not using new-media marketing tools to their full potential. These results have

particular implications for our study target. First, they suggest that farmers may obtain low

outcome from their social media efforts, given their ineffective use of this marketing method.

The second conclusion that could be drawn from the results of this study is the low use of new-

media marketing tools by nurseries and garden centers which belong to the specialty crops

segment.

3. Survey instrument

Data were obtained from a web-survey of US firms operating in the green industry in 2015. The

survey instrument was designed to understand the use of social media by green industry firms

and included 40 questions in total, summarized in 4 categories: respondent characteristics,

business characteristics, marketing practices and market characteristics. Respondent

characteristics included respondent demographics and work related data. The choice of a web-

survey is justified by its low cost, flexibility in design and set-up, its adaptability, and its fast

distribution (Dillman et al., 2014). A web-based survey allows the survey flow to be tailored to

each type of respondent. For example, a non-social media user was automatically directed to

questions relevant to his profile, skipping all the questions about social media activity. Locations

included the four regions of the US: Mid-West, North-East, South, and West. The survey was

reviewed by a panel of experts including an Extension Specialist for ornamental nursery crop

production and garden centers, a Professor of food marketing and consumer economics and an

Associate Professor of agricultural communications. Prior to its distribution, the web-

questionnaire was field-tested with nursery owners in Kansas.

The survey was distributed in multiple stages. First, 42 email addresses were collected over the

telephone from an available directory of 507 live plant licensees from Missouri (406 licensees)

and North Dakota (101 licensees). The survey link was initially sent to these 42 nurseries in

March 2015. The first reminder was sent one week later, and a second reminder two weeks from

the initial email. Dillman et al. (2014) stressed the importance of reminders and stated that the

highest response rate is reached after the first reminder, one week from the initial email. Two

additional distribution networks were exploited to reach a higher number of nurseries and garden

centers: a second directory of live plant licensees and a list of 83 nursery and landscape

associations and magazines in the United States and Canada, obtained from an agricultural

Extension Specialist. A postcard containing the link to the survey was sent to the respondents as

a reminder.

4. Data

Most respondents (60.3 %) were 45 to 64 years of age. Slightly fewer female respondents

(48.5%) than male responded to the survey. More than half of the respondents had a bachelor or

associates degree (57.1%), while 88.8% of the respondents have at least attended some college.

Among respondents having attended some college, 74% were using social media for personal

purposes more than twice a month. This percentage is consistent with the 70% of social media

adopters provided by Pew Research Center (2015) for the same education level. Question 3 of

the survey was related to the products and services offered by the businesses following Hall et al.

(2005)’s description of products and services offered by the green industry. Respondents’

products and services ranged from 1 to 15 categories. The most prominent product category was

retail bedding and nursery stock (73.3%), while only 1.2% of the respondents offered wholesale

garden equipment. This statistic is supported by the value of nursery crops sales in 2012

provided the 2012 Agricultural Census.

The sample comprises nurseries of almost all sizes ranging from small (less than $2,500)

to large ($5 million or greater). Firms making less than $100,000 represent only 19.3% of the

respondents, suggesting a higher participation of bigger firms. Approximately half of the

respondents (43.5%) reported a total value of sales exceeding $1 million. Various reasons can

explain these large differences in sizes in the green industry. Businesses in the green industry

offer various products and services ranging from basic retail of florist supplies to landscape

architecture and installation. In addition, total sales include both nursery products sales and non-

nursery related products sales. In most cases, nursery and garden centers operators are involved

in other sectors such as agriculture, food, and beverage or general merchandise retail.

Regarding marketing practices, retail was the most popular marketing channel: among the

respondents, 56% made more than 80% of their sales through this channel and 41.6% made more

than 90% of their sales at retail. These proportions exceeded Behe et al. (2008)’s findings. They

also found that retail sales were the highest in the Great Plain region (67.2%). Their results

supported the high proportion of retail sales found among respondents. In the current study,

respondents were mainly located in the Great Plains. In contrast, 95.6% did not market any of

their product through the mass merchandisers’ channel, compared to Behe et al. (2008)’s 36.4%.

Marketing expenses averaged $53,050 and ranged from $0 to $1million, suggesting an important

difference among marketing strategies.

Respondents were located in 153 different cities. The Midwest had the highest percentage

of respondents (60.8%), with Kansas accounting for 29.2%. The three other regions, the

Northeast, the South and the West had similar percentages of respondents, respectively 13.7%,

13.1%, and 12.4%. According to the 2012 Agricultural Census (USDA, 2014, the leading states

in floriculture and bedding crops were California, Florida, Pennsylvania, New York and

Michigan, accounting together for 31.8% of U.S. nurseries and garden centers.

4. Model

New-media marketing adoption

Two models are specified to determine the factors impacting new media-media marketing

adoption. First, the dependent variable is specified as a binary variable with 1 for regular social

media users and 0 for non-regular users leading to a binary logit model. In a second

specification, the dependent variable is continuous and the model is estimated using ordinary

least square.

The decision of green industry firms to adopt new media marketing is considered as a

dichotomous choice with underlying latent utility maximization problem. Let y* denote the

unobserved utility from adopting the technology. The unobserved utility determined by factors

identified by previous social media literature such as the size of the firm, the geographic

location, etc. Consequently, the adoption will be observed if the underlying unobserved utility is

positive, and no adoption will be observed if the underlying utility is negative. Thus, the

adoption denoted by y can be formally defined as:

𝑦𝑦 = �1, 𝑖𝑖𝑖𝑖 𝑦𝑦 ∗ > 00, 𝑖𝑖𝑖𝑖 𝑦𝑦 ∗ < 0 (1)

Following, Greene (2012), the study uses a binomial logit model to estimate the

probability of new media marketing adoption by a green industry firm. The unconditional

probability of adopting the technology is given by:

Prob(y = 1|x) = P = exp (𝑥𝑥 ,𝛽𝛽)

1 + exp (𝑥𝑥 ,𝛽𝛽)

where x is a vector of firm and market characteristics and β a vector of parameters.

A second model is specified using a continuous dependent variable and the same set of

explanatory variables as in the previous model, and specified as follows:

𝑈𝑈𝑖𝑖 = 𝛼𝛼0 + 𝛼𝛼1𝑛𝑛𝑖𝑖 + 𝛽𝛽𝑏𝑏𝑖𝑖 + 𝛾𝛾𝑟𝑟𝑖𝑖 + 𝛿𝛿𝑚𝑚𝑖𝑖 + 𝜖𝜖𝑖𝑖 , (3)

where 𝑈𝑈𝑖𝑖 is the intensity of adoption or frequency of use of new media marketing, and 𝑛𝑛𝑖𝑖 the

number of businesses that are being followed online by the nursery, representing the size of the

nursery’s online network. b, r and m represent vectors of control variables for business,

respondent and market characteristics and 𝛽𝛽, 𝛾𝛾 𝑎𝑎𝑛𝑛𝑎𝑎 𝛿𝛿 are parameter vectors. The second model is

estimated using OLS.

Impact of new-media marketing on financial performance

Green industry firms allocate resources to promotion and advertisement to increase all

product sales at their business location rather than specific brands sales. More precisely,

advertisement and promotion efforts are typically measured in terms of marketing expenditures

(Campbell and Hall, 2010; Palma et al., 2012). However, due to their low cost, measuring new-

media marketing in terms of expenditure will not capture the investment incurred by the firm for

its media marketing efforts. Instead, the frequency of use and the time spent on social media

(2)

marketing will be considered in this study as new-media marketing efforts to evaluate their

impact on sales. The model is specified as follows:

𝑻𝑻𝑺𝑺𝑖𝑖 = 𝛼𝛼0 + 𝛼𝛼1𝑼𝑼𝑖𝑖 + 𝛽𝛽𝑏𝑏𝑖𝑖 + 𝛾𝛾𝑚𝑚𝑘𝑘 + 𝜖𝜖𝑖𝑖 (0.1), (4)

where 𝑻𝑻𝑺𝑺𝑖𝑖 is a measure of the total sales in 2014, 𝑼𝑼𝑖𝑖 is the use of new-media marketing, bi is the

vector of firm i’s characteristics and mi is the vector of firm i’s market characteristics. 𝜖𝜖𝑖𝑖 is the

individual nursery idiosyncratic term and α, β and γ are parameter vectors.

5. Results

Adoption

The selected respondent characteristics in equation (2) include age and education. The

age variable assumed the midpoint in the age range while the education variable is a binary

variable equaling one for respondent having attended some college at least. Age squared is

included to allow for a nonlinear relationship between age and adoption. The selected firm

characteristics include the number of firms being followed online by the firm, the years in

operation, the total sales in 2014, retail bedding and marketing expenditures. The size of the firm

is captured by the variable sales evaluated at the midpoint of the sales range. The binary variable

retail bedding equals one for firm retailing bedding products and zero for all other firms.

Pertaining to the perceived usefulness variable, respondents were asked to rank the importance of

social media marketing in improving sales on a 5-point Likert scale. The market characteristics

include the region and urban-rural continuum code.

The binary logit adoption model is estimated by maximum likelihood using STATA 14.2.

The results of two different model estimations are shown in Table 1. In the logit model, the

dependent variable is a discrete choice variable taking the value of 1 for frequent social media

users. The estimates are generally consistent in sign and significance level across the two model

specifications. The variable of interest, ONLINE NETWORK is positive and significant at the

5% level in the two models. The marginal effect of the ONLINE NETWORK is 0.05, meaning

that an additional firm in the nursery’s network increases the probability of social media

adoption by 0.05 percentage points. As emphasized by Bandiera and Rasoul (2006), the network

plays an important role in technology adoption. Regarding respondent characteristics, only

education and perceived usefulness are the significant estimates while the respondent’s age did

not impact social media adoption. The importance of the perceived usefulness in social media

adoption is consistent with El-Gohary (2011) and Sago (2013). Among further firm

characteristics, sales and retail bedding increased the probability of adoption of new media

marketing with parameter estimates and marginal effects significant at the 1% and 5% levels.

Higher firms tend to make more use of new-media marketing than their smaller counterpart, as

expected. This result is consistent with previous studies. Wamba and Carter (2014)’s findings

indicated that firm size and industry were important factors of new media marketing adoption.

Larger firms can afford to allocate more resources (time, human resources) to advertisement

methods including social media marketing. The positive coefficient estimate on retail bedding

plant indicates that bedding plant retailers leverage more effectively new media marketing to

reach their customer. Bedding plants include a wide variety of plants mainly used by

homeowners and businesses, which may explain the need develop a stronger customer

relationship using new-media marketing.

The only negative and significant variable among market characteristics is MARKETING

EXPENDITURES. This sign is unexpected given the positive correlation between resources

allocated to marketing in a firm and use of marketing tools. The higher cost of traditional

marketing venues could explain this result. Nurseries relying more on costly traditional

advertising outlets such as print advertisement, mass media and promotions than new media

marketing may incur higher marketing costs while using less new media platforms. In addition,

the frequency of use of social media marketing (dependent variable) may not always capture

externally managed marketing strategy in larger firms, albeit the costs of consulting service are

included in marketing expenditures. Market characteristics overall impacted positively the

probability of adopting new media marketing. Nurseries located in metro counties and in the

western region of the U.S. were more likely to adopt new media marketing than their

counterparts in rural counties and in the Midwest. The coefficient on South was also significant

at the 10% level and negative, meaning that southern firms were less likely to adopt new media

marketing by 0.2 percentage points.

Table 1. Estimation of the adoption model

Explanatory variable Logit (Standard error) Marginal effects (Standard error)

OLS (Standard error)

ONLINE NETWORK 0.7005 ** (0.2866) 0.0449 *** (0.0154) 0.1907 ** (0.0774)

YEARS IN OPERATION -0.0429 (0.0266) -0.0028 * (0.0016) -0.0053 (0.0108)

EDUCATION 3.0497 ** (1.5025) 0.1956 ** (0.0859) 0.8620 (0.7407)

AGE 0.3397 (0.3507) 0.0218 (0.0216) 0.2095 (0.1505)

AGE SQUARED -0.0036 (0.0036) -0.0002 (0.0002) -0.0023 (0.0015)

SALES 0.0021 ** (0.001) 0.0001 ** (0.0001) 0.0005 ** (0.0002) RETAIL BEDDING 3.5995 ** (1.5431) 0.2309 *** (0.0846) 1.7146 ** (0.6556) MARKETING EXPENDITURES -0.0255 ** (0.0117) -0.0016 ** (0.0007) -0.0065 * (0.0036) PERCEIVED USEFULNESS 1.4059 *** (0.4919) 0.0902 *** (0.0226) 0.6184 *** (0.2225) METRO 5.6385 ** (2.2999) 0.3616 *** (0.1213) 1.2296 ** (0.5426)

NORTHEAST 1.4226 (1.4351) 0.0739 (0.0631) -0.0387 (0.6275)

SOUTH -3.424 * (2.0833) -0.2058 ** (0.0956) -0.6962 (0.8603) WEST 5.577 ** (2.5304) 0.2087 *** (0.0378) 1.3889 * (0.7088) INTERCEPT -5.1554 (3.4770) Log likelihood -21.9077 R2= 0.4193

Note: Triple, double, and single asterisks are significance at the 1%, 5%, and 10% levels, respectively.

Impacts on sales

The impact of the use of new media marketing on nurseries’ financial performance was

examined across three firm categories: small firms (less than $100,000), medium firms

($100,000 to $500,000) and large firms (more than $500,000) leading to three different models

for each firm category. The model explained 95.35% of the variability in sales for small firms

and a lower variability in medium (66.44%) and large firms (67.02%), indicating an overall good

fit. The frequency of use of social media marketing was significant at the 5% level for small

firms. Using social media marketing an additional day in the week resulted in $8,401 additional

sales in a year for small firms. This effect was expected in the green industry given the generally

positive effect of new media marketing adoption reported for other industries. This results also

confirms the opportunity for smaller firms to leverage this low-cost marketing strategy to face

their larger competitors. These findings are supported by previous social media studies that

highlighted the financial gain of conducting a social media marketing strategy in various

industries (Paniagua and Sapena, 2014; Smits and Mogos, 2013; Onishi and Manchanda, 2012;

Lui and Rui, 2014). Pertaining to the green industry, Palma et al. (2012) found evidence that the

Internet marketing was the most effective for small firms. In contrast, MARKETING

EXPENDITURES was the most significant parameter estimate for larger and medium firms. A

$1,000 increase in marketing expenditures raised sales in average by $7,051 for medium firms

and by $10,675 in larger firms. Past studies have supported the positive impact of advertising on

short-term financial performance. Citing Lamblin (1976), Bagwell (2005) provided evidence that

firms’ current marketing expenditure were associated with higher short-term sales. In addition,

firm specific factors (quality, management) and previous spending on advertisement jointly

impacted financial performance (Bagwell, 2005). Among these specific factors, the number of

employees was positive and significant for both medium and large firms. Older nurseries

performed better financially than their younger counterparts for small firms. In larger and

medium firms, the years in operation were not significant while an additional year of operation

resulted in $3,678 additional sales for smaller firms. Market characteristics were the most

significant for medium firms. The South performed generally better than the Midwest and the

West.

Table 2. Parameter estimates of the model on impact on financial performance

Small Medium Large Frequency of use of social media 8.4013 ** 4.4108 61.2437 (2.5878) (5.7451) (50.0943) Marketing expenditures -15.5741 7.0519 ** 10.6758 *** (19.1949) (2.9245) (1.9314) Years in operation 3.678 *** 1.2613 -0.0247 (0.6551) (1.3137) (5.9919) Marketing expenditures ## Number of employees 23.2149 -0.3987 ** -0.051 * (16.2675) (0.1699) (0.027) Number of employees -12.2714 14.7225 * 18.4808 *** (17.6514) (7.4186) (3.7971) Seasonality 1.1278 4.8623 89.1043 (1.6523) (6.5526) (81.1734) Metro 6.1592 8.222 58.086 (3.6527) (6.6925) (83.9162) Northeast -60.1795 125.0804 -290.487 (68.2035) (77.1922) (362.6141) South -331.0335 138.2931 *** 963.4409 ** (179.8949) (46.9923) (437.2575) West 37.236 * 68.5703 -112.153 (13.7213) (56.2168) (431.5007) Home ownership 1.1078 -7.2959 * 36.3165 (1.0828) (3.7462) (35.1758) Intercept -149.8629 493.6222 * -2685.08 (78.2466) (238.4868) (2520.182) N 16 30 66 R2 95.35% 66.44% 67.02%

Note: Triple, double, and single asterisks are significance at the 1%, 5%, and 10% levels, respectively.

Conclusion and implications

Understanding the factors driving adoption of new media marketing strategies and their impact

on financial performance can provide insight into the use of this low-cost technology by the

firms of the green industry. A binary logistic model was specified to estimate the parameters of

the adoption model while the impact on sales was examined using an ordinary least square

estimation of a linear profit function.

This study aimed to bridge the gap in the literature on the adoption of new media marketing in

the agricultural industry in general and the green industry in particular given the underdeveloped

body of literature on both adoption and impact of new media marketing on firm performance.

The factor examined were categorized in respondent, firm and markets characteristics with

respondent characteristics comprised of age and education, the firm characteristics including

years in operation and marketing practices and the market characteristics pertaining to the

location of the firm. The determinants of adoption were the size of the online network, the

education level of the respondent, the retail sales of bedding material, the perceived usefulness of

new media marketing and the location of the firm in the metropolitan area. Adoption of new

media marketing differed by region with Western firms showing more interest in new media

marketing than the Midwest. The frequency of use of social media had a positive effect on sales

for smaller firms, confirming the potential for this category of nurseries to leverage this low-cost

technology. The results were generally consistent with the literature on new media marketing in

use in other industries.

The importance of the perceived usefulness in adoption suggests that nursery owners and

operators should be educated on the value of using a new media marketing technology to

increase the rate of adoption among firms of this category. The metropolitan area variable was

also found to impact significantly adoption. This suggests that emphasis must be put on rural

nurseries that are particularly sensitive to the competition of mass merchandisers.

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Appendix A: Repartition of respondents by age, gender and education level

Count Percentage Age 18 to 24 3 1.86% 25 to 34 23 14.29% 35 to 44 22 13.66% 45 to 54 46 28.57% 55 to 64 51 31.68% 65 to 74 15 9.32% 75 and over 1 0.62% Total 161 100.00% Gender Male 83 51.55% Female 78 48.45% Total 161 100.00% Education Less than high school graduate 2 1.24% High school graduate - diploma or GED 9 5.59% Technical, trade, or vocational school 7 4.35% Some college (no degree) 35 21.74% Bachelor or associate degree 92 57.14% Masters, doctorate, or professional degree 16 9.94% Total 161 100.00%

Appendix B Frequency of use of various marketing venues by nurseries (n = 161)

Marketing venue Daily 2 to 6

times a week

1 to 4 times a month

Once a quarter

1-3 times a

year

Less than once a year

Never

Print advertisements (newspapers, store circulars, postal mailings)

2.48%

6.83%

35.40%

8.70%

21.12%

8.07%

17.39%

Personal interactions (phone calls, emails, visits)

32.92%

14.91%

27.95%

6.83%

6.21%

1.86%

9.32%

Television/radio 5.59% 14.29% 14.91% 2.48% 9.32% 6.21% 47.20% Fairs/trade shows/garden shows 0.62% 1.24% 2.48% 9.32% 36.02% 13.66% 36.65% Online marketing (websites, blogs, social media, e-newsletters)

32.30%

30.43%

21.74%

3.73%

3.73%

1.86%

6.21%