Groff, Andrew J.

Kreider, Craig Robert

Toensmeyer, Ulrich C.

English

Research Papers in Economics

Analysis of the Delaware Market
For Organically Grown Produce*
by
Andrew J, Groff
Undergraduate Research Assistant
Delaware Agricultural Experiment Station
Department of Food and Resource Economics
University of Delaware
Newark, DE
Craig R. Kreider
Former Undergraduate Research Assistant
Delaware Agricultural Experiment Station
Department of Food and Resource Economics
University of Delaware
Newark, DE
Ulrich C. Toensmeyer
Professor
Delaware Agricultural Experiment Station
Department of Food and Resource Economics
University of Delaware
Newark, DE
Introduction
Recent growth of organic produce sales in
California and New Jersey indicate a trend toward
increased consumer desire for organically grown
produce. In 1987, the California market for
organics ranged between $54 -68 million in
wholesale prices, and was projected to exceed
$300 million by mid-1992 (l+anco, 1989). While
much smaller, the New Jersey market for organics
ranged between $1-3 million wholesale in 1988,
and “the organic produce market offers a growth
area for New Jersey growers” (Morgan and
Barbour, 1991).
The fresh produce industry is a small but
important aspect of Delaware agriculture.
Delaware producers are continuously searching for
new opportunities in produce production and
marketing, and this recent trend in the growth of
organic produce sales may provide an area of
growth for Delaware producers. Of importance,
* The researchwas funded in partthrougha grantfrom the Delaware StateDepartmentof Agricultureand Regional
Research Project S-222.
February 931page 118 Journal of Food Distribution Researchhowever, is knowledge of consumer attitudes
toward and opinions about organic produce. One
topic to be explored is consumer rating of organic
versus conventional produce.
Certain information about consumer atti-
tudes and purchasing determinants is available
from the study entitled ‘An Analysis of Con-
sumer Preference between Organically and Con-
ventionally Grown Produce in Delaware” (Groff,
unpublished thesis, May, 1993). It was found that
the factors of freshness, healthfulness, flavor,
safety, nutrition, appearance, and price were
largely unanimously important factors in organic
purchasing decisions, This importance was not as
clear for the factors of brand name and where the
produce was grown. Perhaps certain demographic
groups feel these factors are important, while
others may not. Knowing this information would
help in determining the target consumers for
organics.
Objectives
The objectives of this study were to
1) determine the overall probabilities and marginal
demographic effects for consumer rating of organ-
ics versus conventional produce, and 2) determine
the importance of various factors in consumer
organic produce purchasing decisions.
Data
Data was collected from a consumer mail
survey on organic and conventional produce con-
ducted in Delaware during 1990 (Byrne, 1991).
A random mailing sample of listed and unlisted
telephone subscribers was obtained from Donnelly
Marketing (Nevada, Iowa). This random mailing
was sent to a total of 6155 households across the
state, with 4070 in New Castle county, 1010 in
Kent county and 1075 in Sussex county. The
response rates were 13.5, 9.8, and 9.8 percent for
New Castle, Kent, and Sussex counties, respec-
tively, with a statewide response rate of 12.2
percent.
Procedures
Ordered logit models were utilized to deter-
mine the three objectives of this study. The fol-
lowing material on ordered logit analysis is quite
standard, and the procedures used are patterned
after those set forth in Byrne’s unpublished theais
(Byrne, 1991). Ordered logit analysis was used
for questions representing dependent variables
with contingent valuation measures based on the
1-7 scale. The dependent variables were aggre-
gated into three categories for estimation pur-
poses.
Responses to consumer rating of organics
versus conventional produce (RTORG) were
aggregated into the following three categories:
O = organics worse than conventional produce
1 = organics same as conventional produce
2 = organics better than conventional produce
The observed frequency responses were .1009,
.2710, and .6280, respectively. Responses to
consumer rating of the importance of where the
produce was grown (WHER) and brand name
(BRAN) in their produce purchasing decisions
were aggregated as follows:
O = unimportant
1 = neutral
2 = important
The observed frequency respoases were .3774,
.1824, and .4403, respectively for WHER, and
.4611, .2305, and .3084, respectively for BRAN.
The regression model used for all ordered
logit models in this study is as follows:
Y = & + 131AGE+ /3,MALE + /3,1NCOME
+ /3ASOMECOLLEGE
+ j3~BACHELORDEGREE
+ /3bGRADUATE WORK or DEGREE
+ /37KID+ /9gMARRIED
where:
RTORG, BRAN, and WHER are substituted
Y depending on the model being run
AGE = respondent age in years
MALE = 1 if male; Ootherwise
for
Journalof Food Distribution Research February 931page 119INCOME = total household income
KID = 1 if Kids present; Ootherwise
SOME COLLEGE = 1 if only attended some
college; Ootherwise
BACHELOR DEGREE = 1 if completed
bachelor degree; Ootherwise
GRADUATE WORK or DEGREE = 1 if com-
pleted some graduate work; Ootherwise
MARRIED = 1 if married; Ootherwise
The base group consisted of single females with a
high school diploma or less.
Outcome prediction for individuals is not
the reason that these ordered logit models were
utilized. The intent of analyzing the demographic
effects on the relevant dependent variable may be
lost if too much emphasis is placed on improving
the predictive ability of these models (Greene),
Instead, characterization of the population requires
good parameter estimates of the true independent
variables. Logit modelling uses maximum likeli-
hood estimators to maximize the combined density
of the observed dependent variable, as opposed to
the classical regression which chooses estimates to
maximize the fitting of the dependent variable
prediction and thus maximizing R2. Additionally,
a good fitting of the observed dependent variable
and achieving valid coefficient estimates are not
necessarily compatible (Greene). Hence, eliminat-
ing pseudo-independent variables, such as safety
rating, avoids artificial inflation of prediction and
reduction of true independent variable effects.
Chi-square values verify each model’s
significance for these structural analysis models,
resulting as a difference of the restricted and
unrestricted log likelihood functions. The
restricted regression for these models consists of
the intercept as the only right-hand-side variable
(Maddala). Comparing the observed frequencies
and the estimated overall probabilities provides
further evidence of significance. The Score Test
for the Proportional Odds Assumption confirmed
parallelism for the ordered logit models (SAS
Institute, Inc.).
Demographic Overview
Demographically, Sussex county residents
are older, as 47.6 percent of respondents are 50
years of age or older, whereas 40.1 and 36.1
percent of respondents in New Castle and Kent
counties, respectively, are 50 or older ~able 1).
New Castle residents are more educated, as 48,7
percent of respondents have at least a bachelors
degree, compared to 41.9 and 35.6 percent,
respectively, in Kent and Sussex. Income distri-
bution varies by county, as New Castle respon-
dents have higher annual incomes. The percent-
age of respondents earning over $50,000 annually
in New Castle, Sussex and Kent, respectively, are
48.9, 32,7 and 27.3. Sixty and 52.0 percent of
Kent and Sussex respondents earn between
$30,000 and $50,000 annually, whereas 44.6
percent in New Castle earn between $30,000 and
$50,000.
Consumer Rating of Organic
Versus Conventional Produce
This model shows that the overall proba-
bilities for rating organics as much worse, the
same, or much better than conventional produce
were .0882, ,2721, and .6397, respectively (Table
2). These probabilities were similar to observed
frequencies, and the model has a significant chi-
square value.
For every 10 year increase in age above the
mean age of approximately 47, a respondent was
5.4 percent less likely to rate organics as much
better than conventional produce. Similarly,
males were 14.11 percent less likely to rate organ-
ics as much better, and 4.97 percent more likely
to rate organics as much worse. Education also
decreases the likelihood of a much better rating,
but only significant for graduate degree holders,
who were 16.97 percent less likely than their high
school educated counterparts to rate organics as
much better than conventional produce. This
indicates that a strategy which targets younger
female respondents without high education would
be aimed at a group that is more likely to feel that
organics are much better than conventional pro-
duce.
February 93/page 120 Journalof Food Distribution ResearchTable 1
Demographic Characteristics of Consumers, by County, Delaware, 1990
Survey area
Chara r“ “ @glstlc New Castle Kent ~ex State
AGE
18-34 years of age 24.7
35-49 35.2
50-64 23.6
65 or older M
TOTAL 100.0
$@X
Male 50.2
Female M
TOTAL 100.0
EDUCATION
Less than high school 4.1
High school graduate 27.1
Some college 20.1
Bachelor degree 24.6
Some graduate work or degree ~
TOTAL 100.0
ANNUAL HOUSEHOLD INCOME
<$10,000 1.6
$10,OOO-19,999 4.9
$20,000-29,999 10.7
$30,000-39,999 13.2
$40,000-49,999 20.7
$50,000-59,999 14.6
$60,000-69,999
$70,000 or higher 4
TOTAL 100.0
SOURCE: Consumer survey and calculations
----- - -percent -------
21.6
42.3
20.6
m
100.0
47.4
m
100.0
7.1
32.6
18.4
27.6
N
100.0
1.1
11.6
22,1
12.6
25.3
6.3
G
100.0
19.4
33.0
27.2
20.4
100.0
45.6
%
100.0
9.6
29.8
25.0
23.1
12,5
100.0
2.0
13.3
17.3
21,4
13.3
9.2
G
100.0
23.6
35.8
23.7
m
100.0
49.2
100.O
5.3
28.2
20,6
24.8
21.1
100,0
1.6
7.0
13.1
14.3
20.3
12.7
z
100.0
Journalof Food Distribution Research February 93/page 121Table 2
Ordered Logit Overall Probabilities and Demographic Effects
For Consumer Rating of Organic Produce Versus Conventional Produce, Delaware, 1990
P: P: P:
MUCH WORSE SAME MUCH BETTER
OVERALL 0.0882 0.2721 0.6397
(chi-squared = 45.0160’)
MARGINAL EFFIW’T~
Age” 0.00194 0.0035 4.0054
(mean = 46.793)
Malt? 0.0497s 0.0914 -0.1411
Income 0.00044 0.0006 -0.0010
(mean = 50.8210)
Kid 0.00075 0.0014 -0.0021
Married -0.00075 -0.0013 0.0020
Some college 0.0204s 0.0431 -0.0635
Bachelor degree 0.025@ 0.0516 -0.0766
Graduate degrtx? 0.0622s 0.1075 -0.1697
N = 535
‘Significant at the .01 level
bSignificant at the ,05 level
‘Significant at the .10 level
*Computed as PO ‘
~ +lx
(Greene)
1 + = ‘P’x
2Computed as PI =
#-fYx
- P. (Greene)
1 + #-P’x
3Computed as P2 = 1- (PO+ PI) (Greene)
‘Marginal effect (ME) of continuous variables (var) calculated:
P.: -[p, * (l-f’,)] * Pvar
~: [P2 * (l-pz)] * Pv.. P
P“ 1“ o- (PO+P2)
‘ME of dummy variables calculated: ME = Pi[x= 1] - [X sO]
SOURCE: Delmarva consumer survey and calculations
February 93/page 122 Journalof Food Distribution ResearchTable 3
Consumer Rating of Factor Importance in
Organic Produce Purchasing Decisions by County, Delaware, 1990
Survey area
FACTORS NEW CASTLE KENT Suss EX STATE
Freshness
Health
Flavor
Nutrition
Safety
Appearance
Price
Envir. effect
Certification
Where grown
Brand name
mearf
1.46
1,67
1,70
1.71
1.72
2,13
2.44
2.44
2.52
3.83
4.36
s.d.
0,03
0.05
0!04
0.05
0.05
0.06
0.07
0.07
0.08
0.09
0.08
mean’
1.30
1.49
1.59
1.54
1.73
2.06
1.98
2.46
2.67
3.79
4.29
s.d.
0.06
0.10
0.09
0.11
0.13
0.12
0.13
0.17
0.21
0.22
0.19
mean’
1.38
1,49
1.57
1.57
1.55
2,11
2.15
2.29
2.57
3.74
4.65
S.d.
0.06
0.08
0.08
0.09
0,10
0.13
0.15
0.17
0.19
0.22
0.19
mean’
1.43
1.62
1.67
1.67
1.70
2.12
2.34
2.42
2.55
3.81
4.39
s.d.
0.03
0.04
0.04
0.04
0.04
0.05
0.06
0.06
0.07
0.08
0.07
al = very important and 7 = very unimportant
SOURCE: Consumer mail survey and calculations
Importance of Various ries. The importance of brand name @RAN) and
Purchasing Determinants
The most important factors affecting con-
sumer organic produce purchasing decisions are
freshness, healthfulness, flavor, nutrition, and
safety (Table 3). overall, where the produce was
grown and its brand name are of the least concern
in consumer purchasing decisions.
Chi-square testing for significance showed
that freshness, flavor, nutrition, health, safety,
appearance, price, and environmental effects are
highly important factors in consumer produce
purchasing decisions for all demographic catego-
where grown (WHER) were not so strongly
agreed upon, however. The purpose of the fol-
lowing two models is to determine whether certain
demographic groups are more likely to rate
WHER and BRAN as important in their purchas-
ing decisions.
Overall probabilities for respondents rating
of WHER as important, neutral, or important
were .3707, .1911, and .4382, respectively (Table
4). These were similar to the observed frequen-
cies, and the model had a significant chi-square
value.
Journal of Food Distribution Research February931page 123Table 4
Ordered Logit Overall Probabilities and Demographic Effects
On the Importance of Where Produce is Grown (WHER)
As a Purchasing Determinant, Delaware, 1990
P: P: P:
Unimr)ortant Neutral Important
Overall (chi-squared = 35.48%) 0.3707 0.1911 0.4382
Margh.alE#ects
Age (mean = 46.313) -0.00154 -0.0001 0.0016
Malec 0.06375 0!0035 -0.0672
Incom& (mean = 50,767) 0.00244 0.0001 -0.0025
Kid -0.04375 -0.0039 0.0476
Married o.o16@ 0.0010 -0.0170
Some college 0.02835 0.0036 -0.0319
Bachelor degree 0.07075 0.0064 -0.0771
Graduate degree” 0.14915 0.0037 -0.1528
N = 636
‘Significant at the .01 level
bSignificant at the .05 level
“Significant at the .10 level
e +x
lComputed as PO = (Greene)
1 + e-fl’x
2Computed as PI =
eh’@x
- PO (Greene)
1 + #0-P’x
3Computed as Pz = 1- (PO+ PI) (Greene)
‘Marginal effect (ME) of continuous variables (var) calculated:
P.: -[PO * (l-p,)] * P“..
,: [P, * (l-l’z)] * Pvar P
~: 0-( PO+P2) P
‘ME of dummy variables calculated: ME = Pi[x= 1] - [X= O]
SOURCE: Delmarva consumer survey and calculations
February 93/page 124 Journalof Food Distribution ResearchMales were 6.72 percent leas likely than
females, and graduate degree holders were 15.28
percent less likely than respondents with at most
a high school education to rate WHER as impor-
tant to their organic produce purchasing decisions.
Respondents with some college or a bachelor
degree also are lws likely to feel WHER is impor-
tant than do their high school educated counter-
parts, but not significantly.
Similarly, most of the significant effects in
the importance of brand name (BRAN) are cases
of groups being less likely, no more, to rate it as
important. All education beyond high school
tended to make BRAN less important, as respon-
dents with some college, a bachelor degree, or a
graduate degree, are 9.14, 7.94, and 13.27 per-
cent, respectively, less likely to rate BRAN as
important (Table 5). However, for every ten
years older than the mean age a rapondent is,
s/he was 2.0 percent more likely to rate BRAN as
important, indicating some benefit to marketing a
branded organic item to older individuals.
This model had overall probabilities to rate
BRAN as unimportant, neutral, or important of
.4572, .2374, and .3054, respectively, and had a
significant chi-square value.
Conclusions
(1) This study concludes that younger respon-
dents, female respondents, and those with lower
education levels were more likely to feel organics
are a better produce than is conventionally grown
produce.
(2) Education and being male had negative
effects on the likelihood to feel that where the
produce was grown is important in organic pro-
duce purchasing decisions.
(3) Increasing age raised the likelihood for
respondents to feel brand name is important, while
higher education lessened the likelihood.
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Journalof Food Distribution Research Febnuuy 93/page 12STable 5
Ordered Logit Overall Probabilities and Demographic Effects
On the Importance of Brand Name (BRAN)
As a Purchasing Determinant, Delaware, 1990
P; P? P;
Unimportant Neutral Im~ortant
Overall (chi-squared = 23.00Y) 0.4572 0.2374 0.3054
MarginalE#ects
Age” (mean = 46.294) -0.00234 -0.0003 0.0020
Male 0.0232s -0.0034 -0.0198
Income (mean = 50.732) 0.0010’ -0.0001 -0.0009
Kld -0.038(Y 0.0045 0.0335
Married 0.0623S -0.0074 -0.0549
Some collegeb 0.10145 -0.0102 -0.0914
Bachelor degree” 0.087& -0.0076 -0.0794
Graduate degretf O.1548S -0.0221 -0.1327
N = 636
‘Significant at the .01 level
bSignificant at the .05 level
‘Significant at the .10 level
‘Computed as P. =
~ +x
(Greene)
1 + ~ “Vx
Womputed as PI =
~kql-pix
- P. (Greene)
1 + @-l@x
3Computed as Pz = 1- (PO+ Pi) (Greene)
‘Marginal effect (ME) of continuous variables (var) calculated:
P.: -[PO * (l-Po)] * Pvar
~: [P2 * (l-l=’,)] * Pvaz P
P’1’ 0- (PO+P2)
5ME of dummy variables calculated: ME = Pi[x= 1] - [X= O]
SOURCE: Delmarva consumer survey and calculations
February 93/page 126 Journalof Food Distribution Research

An Analysis of Cbnsumer Preference Betwen Conventionally and OrganicallyGrownProduce in

An Analysis of the California Market for Organically Grown Produce,”

An unpublished senior thesis in the Department of Food and Resource Economics,

Analysisof Chsumer Attitudes Clmcerning FoodSafetyandFreshProduce in the iUarkzt Place, An unpublished Master’s th~is in the Department of Food and Resource Economics,

Distribution Research Febnuuy 93/page 12STable 5 Ordered Logit Overall Probabilities and Demographic Effects On the Importance of Brand Name (BRAN) As a Purchasing Determinant, Delaware,

Inc., SAS/STAT User’s Guide, Version 6,

Limited-Dependentand Qualitative VariablesinEconomem”cs.New York:

Marketing Organic Produce in New Jersey: Obstacles and Opportunities,

ANALYSIS OF THE DELAWARE MARKET FOR ORGANICALLY GROWN PRODUCE

ANALYSIS OF THE DELAWARE MARKET FOR ORGANICALLY GROWN PRODUCE

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