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Drivers of Demand for Specialty Crops: The Example of Arizona-Grown Medjool Dates
Carola Grebitus
Assistant Professor
Morrison School of Agribusiness
W.P. Carey School of Business
Arizona State University
7231 E. Sonoran Arroyo Mall
Mesa, AZ 85212
[email protected]
(Corresponding Author)
Anne O. Peschel
Assistant Professor
MAPP - Department of Management
Aarhus University
[email protected]
Renée Shaw Hughner
Associate Professor
Morrison School of Agribusiness
W.P. Carey School of Business
Arizona State University
[email protected]
Selected Paper prepared for presentation at the Agricultural & Applied Economics
Association’s 2016 AAEA Annual Meeting, Boston, MA, July 30-August 2, 2016.
Copyright 2016 by Carola Grebitus, Anne O. Peschel, Renée Shaw Hughner. 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.
Drivers of Demand for Specialty Crops: The Example of Arizona-Grown Medjool Dates
Abstract. Recently, gross production of Medjool dates has approximately doubled in Arizona,
with the growing region increasing to over 3,000 harvested acres in 2014. As the supply of Medjool
dates increases, consumer demand needs to increase accordingly. This research aims to investigate
consumer preferences for specialty crops such as Medjool dates. This paper analyzes the impact
of Arizona Grown and California Grown labeling on consumer preferences for Medjool dates
applying choice experiments. Furthermore, the influence of pesticide-free labeling and GMO-free
labeling on willingness to pay is tested both individually and as interaction effect. Results show
that consumers prefer dates grown in California and Arizona over dates not labeled for region of
origin. Between California and Arizona, those dates originating in California are preferred. Also,
pesticide free and GM-free dates are preferred with pesticide free having a larger impact on
choices. Overall, results can be used by stakeholders to create target oriented marketing activities.
Key Words. Choice experiments, Medjool dates, Preferences, Arizona grown, Pesticide free,
GMO free
JEL Code. M31, Q13
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1. Introduction
Creating demand for fruits and vegetables has become important in recent years. From Michelle
Obama’s “Let’s Move” campaign to the Produce for Better Health Foundation’s “More Matters”,
Americans are being encouraged to eat more fruits and vegetables. State agricultural departments
have hoped to capitalize on the increased focus of produce consumption, as well as consumer
preferences for locally grown produce (Patterson, Olofsson, Richards and Sass 1999). Towards
this endeavor, federal specialty crop block grants have provided funding to help states enhance the
competitiveness of their specialty crops. This research stems from one such grant. As growers
are currently navigating the maze of packaging and labeling options available to them, questions
remain as to the value consumers attribute to various labeling designations. The fresh date industry
is an industry in which an understanding of consumer preferences and consumers’ willingness to
pay for various product attributes is needed. This research uses the Medjool date industry as a
context to examine date attributes, such as growing region, “GMO-free” and “organic”, and their
effect on consumers’ willingness to pay. The date industry provides a compelling field of study;
the industry has experienced considerable growth, with worldwide sales of dates increasing 14%
over the last decade. In the United States, sales of dates increased 7.2% from 2014-2015, in a
category where overall fruit consumption declined or remained stagnant (Mintel Reports 2015). In
the United States, the vast majority of date production occurs in Coachella Valley, California, with
more than 90 percent of U.S. dates grown here. In recent decades, though, date production has
expanded to the Southwestern Arizona desert, along the California-Arizona border, with the wide
planting of Medjool date palm trees. In a depressed economic region, the Medjool date industry
has contributed significantly to the region’s economy. It is estimated that 7,500 acres of Medjool
dates are planted in Southwestern Arizona, producing 14 million pounds of dates, totaling $8
2
million in market value (Riggs 2015). Additionally, a packing coop located in the area, packs about
20 million pounds of Medjool dates annually. Medjool date farming adds an estimated $30 million
to the Arizona economy. While the Medjool date industry is vitally important to this region, experts
have noted that “the biggest challenge in the Medjool date industry is increasing interest in
consumers eating dates” (Riggs 2015). Thus, this research examines the drivers of Medjool date
demand by looking at consumers’ preferences for various date attributes (e.g., growing region,
pesticide usage, and presence of genetic modification). The remainder of the paper is organized as
follows: section 2 presents a discussion of the literature on consumers’ willingness to pay for
various produce attributes (region of origin, pesticide free production and GMO free production);
section 3 provides the methodological background; section 4 presents the empirical results; and
section 5 concludes with a discussion of implications.
2. Literature review
Several studies have suggested that consumers are willing to pay price premiums for produce with
specific production practices, such as organic produce (Batte et al. 2007; Goldman and Clancy
1991; Jolly et al. 1991; Yiridoe, Bonti-Ankomah and Martin 2005). Though, the association of
consumer demographics, such as education, income and age, have yielded mixed results. For
example, research has found that respondents with higher income levels are more willing to pay
higher premiums for organic and GMO-free products (Loureiro and Hine 2002; Bernard and
Bernard 2010); however, other studies have found the converse to be true (Jolly and Dhesi 1989;
Jolly 1991). Lifestyle and attitudinal factors seem to be better suited in explaining willingness to
pay (WTP). For example, Huang et al. (1999) found that more health-conscious consumers were
willing to pay more for organic and GMO-free food. Loureiro and Hine (2002) found that
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importance of freshness and nutrition had a positive effect on the premiums that consumers are
willing to pay, stating that GMO-free products would be beneficial to target the segment of
consumers who are more food safety-conscious. Moon and Balasubramanian (2003) found that
US consumers who perceived health and/or environmental risks related to biotechnology in food
production, were willing to pay a premium to avoid cereals made with biotech ingredients.
However, consumers who attributed benefits to biotechnological food (i.e., reduction in pesticide
usage, greater supply of food, improved nutrition), were less likely to pay a premium. In 2005,
Lusk, Mutsafa, Kurlander and Taulman conducted a meta-analysis of 25 studies and developed a
model which estimated consumer demand for GMO-free food. They found that consumers across
the world appeared to be somewhat averse to genetically modified (GM) foods and value non-GM
foods over GM foods. However, GM products that provided tangible benefits, such as increased
nutrition to consumers, significantly decreased premiums for non-GM food. They called for more
research in the area of GM food. As Bonti-Ankomah and Yiridoe (2006) note, WTP premiums
differ widely among countries, consumer segments, product types, and consumer behavior.
Adams and Salois (2010) also provided a review of consumer preferences and willingness to pay
for local and organic food, and noted the shift towards “local” in light of “corporatization” of the
organic food sector.
In fact, recent years have seen a dramatic increase in marketing and consumption of locally
grown produce (Agricultural Marketing Service 2009). Consumer preference for locally grown
foods is well-documented (Patterson et al., 1999; Jekanowski, Williams and Schiek, 2000; Onken
and Bernard 2010), and when compared to organic food, several relatively recent studies have
noted consumers place a greater value on local produce over organic produce (e.g., Thilmany,
Bond, and Bond 2008; Hu, Woods, and Bastin 2009; Loureiro and Hine 2002). The U.S.
4
Department of Agriculture (USDA) suggested that consumers are choosing local food products
because of perceptions of its freshness and health benefits, familiarity with its sources,
environmental sustainability, and as a way of supporting small farms and local economies
(Martinez et al. 2010). Several studies have indicated that consumers not only prefer local
products, but are willing to pay substantial premiums for locally grown produce; though, the
premiums consumers are willing to pay, vary by state and by product (Giraud, Bond, and Bond
2005). For example, preferences for Arizona grown products by residents, as well as by the state’s
tourists were found (Patterson et al. 2003; Patterson et al. 1999). Jekanowski, Williams, and
Schiek (2000) found that perceptions of quality played an important role in consumer preference
for local products. In a study on the New England states, consumers in Vermont, New Hampshire,
and Maine were willing to pay a small premium for local specialty food products (e.g., maple
syrup, salsa, cookies; Giraud, Bond, & Bond 2005). Using choice experiments, James, Rickard
and Rossman (2009) found that across segments of consumers, applesauce designated “locally
grown” had the highest WTP estimates. Carpio and Isengildina-Massa (2009) found that South
Carolina consumers were willing to pay an average premium of 27% for local produce, and that
WTP for local produce was positively influenced by increases in consumer age and income, as
well as by “perceived product quality, a desire to support the local economy, patronage of farmers
markets, and consumer ties to agriculture”. Finally, Onken, Bernard, and Pesek (2011) conducted
a choice experiment of Mid-Atlantic consumers and found that consumers in Maryland,
Pennsylvania and Virginia had a much greater WTP for locally grown strawberry preserves; while,
respondents in New Jersey were more likely to prefer state promoted produce. While more research
into locally grown and state-branded foods exist; to our knowledge, no research has yet considered
Medjool dates or the proximity of California to Arizona as a substitute for locally grown.
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This research is unique from the above literature in the type of food product (Medjool
dates), the growing origin, as well as the production processes (i.e., pesticide-free and Non-GMO).
While organic produce in the U.S. does not contain genetically modified food, and is commonly
thought to be pesticide-free, the labels of interest in the current study are specifically “GMO -free”
and “pesticide-free”. For the most part, Medjool dates grown in Arizona are not treated with
pesticides, as the dry, hot climate does not allow pests to survive; however, many of the growers
have not gone through the cumbersome process of getting USDA Organic certified. Thus,
pesticide-free designation is a particularly meaningful one. Secondly, because it is not
economically feasible to sell dates strictly within the confines of the state, they cannot be labelled
as locally grown. The question then becomes whether including the state of origin is of value to
consumers and whether it acts as a proxy for locally grown. California is the largest growing region
of dates in the United States; however, the Medjool dates of interest are grown in Arizona. The
two states have vastly different public images, from the landscape and terrain to political ideology.
Whether these state differences may impact the value attributed to dates, is not known. Taken as
a whole, even though a plethora of research surrounding state branding programs, locally grown
and organic research exists, there is still much to learn about consumers’ willingness to pay for
various food attributes.
3. Methodological background
3.1 Choice experiments
The main objective of this research project is to measure the premiums consumers are willing to
pay for Medjool dates labeled for region of origin, pesticide-free production and GMO-free
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production. In addition, we test whether those consumers that prefer pesticide-free dates are more
likely to prefer GMO-free dates, and vice versa.
Choice experiments are a commonly used tool set used to isolate individual product
characteristics, such as region of origin labeling, and their specific influence on price. This
provides an insight into consumers’ preferences and related willingness to pay. In choice
experiments, participants make repeated choices between different bundles that are characterized
by different attributes and the respective levels of these attributes. The individual’s utility depends
on attribute levels of the choices made from the choice sets. This procedure enables the researcher
to determine the attributes which influence the choice significantly and the marginal WTP for an
increase/ decrease in the significant attributes (Goldberg and Roosen, 2007).
Following Alfnes et al. (2006) we run a hypothetical online choice experiment to collect
data that provide stated preferences of consumers for 8 oz of Medjool dates. Medjool dates are
premium dates. In general, dates are fresh fruit that are characterized by high shares of potassium
and fiber. The experimental design is as follows. Shelf simulation of 8 oz of Medjool date packages
is prepared by taking premium photographs of dates and generating pictures of the alternatives that
include the respective attributes. Each participant makes 12 choices. The experimental design is a
hybrid design. It consists of 6 choice sets which were generated using a fractional factorial design.
Each participant received 3 out of these 6 choice sets. In addition, an efficient design was created
consisting of 36 choice sets. The efficient design was a block design consisting of 4 blocks, which
means that each participant received 9 choice sets to choose from the efficient design. Both designs
were created using Ngene. To create the efficient design we conducted a pre-test using an optimal
orthogonal in the differences (OOD) design. The pre-test data was used to estimate mixed logit
models to generate priors for the efficient design.
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The experiment is conducted with 750 participants. Participants are recruited via Qualtrics.
The online survey is programmed in Qualtrics.
Participants made repeated choices between scenarios of four different Medjool date
packages. The experimental design included price with six levels, region of origin with three levels
and pesticide-free and GMO-free labeling with two levels each. The attributes differed from
scenario to scenario according to either a fractional factorial design or efficient design.
The four alternatives of dates were referred to as option A, option B, option C and option
D. In addition, the participants were able to choose “none-of-these” alternatives. The dates were
characterized by different combinations of the attributes (see Table 1). For example a date package
might be GMO-free, Pesticide-free, California grown and cost $3.49 per 8 oz (see Figure 1, option
B).
Table 1: Attributes of the dates
Attribute
Price / 8oz
Region of origin
Pesticide free
GMO free
Level
$2.49
California grown
Label
Label
$3.49
Arizona grown
No label
No label
$4.49
No label
$5.49
$6.49
$7.49
8
Figure 1 presents an example of a choice set.
Figure 1. Choice set example
Option
A
B
C
D
$2.49
$3.49
$3.49
$6.49
Arizona grown
California grown
Arizona grown
Pesticide free
Pesticide free
Pesticide free
GMO free
GMO free
None
8 oz of
of
Medjool
Pesticide free
these
dates
I choose:
3.2 Mixed logit model
To analyze the data a multinomial mixed logit model with individual specific, random and
independent parameters to capture taste variations is used. Compared to the multinomial logit
model the mixed logit model has the relevant advantage of allowing for taste heterogeneity
unconditional on socio-economic covariates (Menapace et al., 2008). Moreover, the mixed logit
obviates three limitations of the standard logit model by allowing for random taste variation,
unrestricted substitution patterns, and correlation in unobserved factors over time (Train, 2003).
This is particularly relevant because several studies have shown that taste variation is only partially
linked to and poorly explained by socio-economic variables such as age and education (e.g. Baker
and Burnham, 2001).
The mixed logit can be defined as any model whose choice probabilities are integrals of
standard logit probabilities over the density of parameters to be estimated. It can be specified via
random parameters in the utility function and the goal is to estimate the moments of the
distributions of individual-specific taste parameters.
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The following example explains this point. One of the explanatory variables used in the
model is the region of origin ‘California grown’. It is reasonable to assume that consumers differ
in their level of appreciation for a specific region of origin of dates. Some consumers may prefer
California grown while others may prefer Arizona grown. In this model, the random behavior of
taste for the variable ‘California grown; is described by a normal distribution with a certain mean
and variance. The mixed logit task is to estimate mean and variance, which completely describe
the normal distribution.
An important implication of the mixed logit is that probability statements can be attached
to the values of these parameters. The mixed logit produces efficient parameter estimation when
the same individual makes repeated choices since it considers the correlation over sequential
choices induced by the variability in the individual-specific parameters.
Model specification and estimation
Each decision maker i (i  1,...,20) faces T=12 choice situations (t  1,..., T ). In each choice
situation, the decision maker is presented with a set of alternatives. Each set contains 5 elements:
4 date alternatives and the ‘no purchase’ alternative. In total, there are J=49 alternatives in each
block, indexed by j, j  {1,..., J }, including 48 date packages and the ‘no purchase’ ( j37 ). J t
represents the set of alternatives at time t , for t  1,..., T , J t  { j2t 1 , j2t , j37 }.
The choice probabilities of a mixed logit for panel data and with linear random utility function can
be specified as shown in the following. The utility of individual i from alternative j, in choice
scenario t , is denoted by
U ijt  i xijt   ijt ,
(1)
10
where  ijt is distributed iid extreme values over individuals, alternatives and time, and xijt is a
vector of observed variables relating to alternative j , which is described in detail below.  is a
vector of unobserved coefficients that vary over individuals but not over alternatives (representing
the individuals’ tastes). It varies over individuals with density g (   ) , where  represents the
parameters of this distribution. For example, if  is normally distributed in the population 
represents the mean and covariance (Revelt and Train, 1999).
Within a choice set, an individual chooses the option that maximizes utility within the given
set. Let y it denote the individual’s chosen alternative in situation t , and let yi  yi1 ,..., yiT denote
the person i’s sequence of chosen alternatives. Since the  ijt ' s are distributed extreme value, the
probability conditional on  i that the individual chooses alternative j in situation t is standard
logit (Revelt and Train, 1999):
Li ( j , t  ) 
e
 i X jt
e
 i X jt
(2)
j
and since the  ijt ' s are independent over choice situations, the probability of the individual’s
sequence of choices, conditional on  i , is the product of logits. We do not observe  i , and so
these conditional probabilities are integrated over all possible values of  i , using the population
density of  i . The integral in the mixed logit probability generally does not have a closed form,
and so it is approximated numerically through simulation. The parameter estimation is obtained
by maximizing the simulated log-likelihood function. The estimated coefficients in the (linear)
utility function vary over people but are constant over choice situations for each individual.
Properties of the maximum simulated likelihood estimator are given by Hajivassiliou and Ruud
(1994).
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The parameter distributions are assumed to be independent normal distributions. Across
individuals the price coefficient is fixed. The advantage of having a fixed coefficient for price is
that the WTP for each non-price attribute has the same distribution as the attribute’s coefficient.
As suggested by Train (2003) the mixed logit estimates presented in this paper are obtained via
simulated maximum likelihood using 250 Halton draws. In the models seven explanatory variables
are included. Table 2 gives a summary of the included variables.
Table 2: Summary of variables used in the analysis
Variable
Variable Definition
Price
Continuous variable indicating price of $2.49, $3.49, $4.49, $5.49, $6.49,
$7.49
California grown
Dummy variable equal to 1 if date alternative was labeled “California
grown”
Arizona grown
Pesticide-free
Dummy variable equal to 1 if date alternative was labeled “Arizona grown.”
No-label option was excluded because of multicollinearity.
Dummy variable equal to 1 if date alternative is carrying label “pesticidefree”
GMO-free
Dummy variable equal to 1 if date alternative is carrying label “GMO-free”
Pest-GMO
Interaction effect between Pesticide-free and GMO-free
NOT
Dummy variable equal to 1 if the none-of-these option was chosen for a
choice set.
To estimate the model we use the mixed logit code in NLogit/Limdep. The code is designed for
panel data and accounts explicitly for the correlation over time in unobserved utility that arises
when there are repeated choices by a given individual. We use the panel version of the mixed logit
code because each participant gives rise to a panel of 12 choices. In the model six random
coefficients and one fixed coefficient (price) are used.
12
4. Results
At the time of paper submission we were still collecting data. Therefore, we present the results
from the pre-test. The pre-test was conducted with N=20 individuals. Each individual completed
36 choices, generated with the OOD design, resulting in a total of 720 observations. The results of
the mixed logit estimates of our model are presented in Table 3. The estimated models show the
following results and effects on consumers’ preferences for dates:
Table 3: Parameter estimates
Coeff.
SE
z-value p-value
California grown (M)
1.388
***
0.438
3.170
0.002
Arizona grown (M)
0.747
**
0.373
2.000
0.045
Pesticide-free (M)
2.363
***
0.512
4.620
0.000
GMO-free (M)
0.855
**
0.430
1.990
0.047
Pest-GMO (M)
2.448
***
0.679
3.610
0.000
NOT (M)
-13.875 ***
1.475
-9.410
0.000
Price (M)
-2.740
***
0.205
-13.380 0.000
California grown (SD)
4.233
***
0.543
7.790
0.000
Arizona grown (SD)
0.578
*
0.307
1.890
0.059
Pesticide-free (SD)
2.089
***
0.613
3.410
0.001
GMO-free (SD)
2.636
***
0.458
5.760
0.000
Pest-GMO (SD)
2.578
***
0.496
5.190
0.000
NOT (SD)
4.515
***
1.552
2.910
0.004
Note: *** p<0.01; ** p<0.05; * p<0.1
Results show that the price coefficient is significant and negative, as expected. That means the
higher the price the less preferred the presented option of Medjool dates. California grown and
Arizona grown dates are both preferred over non-labeled options, with California grown dates
being more likely to be chosen than Arizona grown dates.
13
Furthermore, participants preferred dates that were labeled as Pesticide-free and GMOfree. Also, the interaction effect between these two labeling options is significant and positive,
indicating that those individuals that are more likely to choose Pesticide-free labeled dates are
more likely to choose GMO-free dates. The NOT variable is significant and negative suggesting
that participants rather chose “something” over “nothing.”
The standard deviation parameters are significant for all variables. This finding leads to the
conclusion that there is heterogeneity in the preferences of consumers when it comes to region of
origin and production methods of dates. This means that, indeed some consumers may prefer, for
example, California grown dates, but this does not have to hold for all consumers.
Looking at willingness to pay in Figure 2, results show that consumers are willing to pay
$0.51 more for 8 oz of dates from California, while they are willing to pay $0.27 more for 8oz of
dates from Arizona. Dates labeled as pesticide-free increase $0.86 in value per 8oz, while dates
labeled as GMO-free increase $0.31 in value per 8oz. However, results have to be treated with
caution, since these are preliminary results based on a pre-test.
WTP in $/8oz
1.00
0.86
0.80
0.60
0.51
0.40
0.27
0.31
0.20
0.00
California
grown
Arizona grown Pesticide-free
GMO-free
Figure 2. Willingness to pay
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5. Conclusion
Our research project aims to investigate consumer preferences for specialty crops such as Medjool
dates. Determining consumer preferences and related willingness to pay, enables stakeholders to
better understand consumers and to create target-oriented marketing strategies to more effectively
communicate benefits of Medjool dates. Considering the high unemployment rate in date growing
regions, such as, Yuma, AZ, it is of high socio-economic relevance to strengthen producers’ ability
to market their product more efficiently, in order to increase demand for Arizona grown Medjool
dates and secure employment for the local population.
By employing choice experiments with relevant consumer attributes, such as price, region
of origin and pesticide-free as well as GMO-free labelling, we could estimate consumer
preferences and WTP for these attributes. Using multinomial mixed logit choice modelling, we
account for consumer heterogeneity in our analysis. Our pre-test results show that on average,
consumers are willing to pay a larger premium for California grown Medjool dates than Arizona
grown Medjool dates. Considering that Arizona is the largest producer of Medjool dates, it is
surprising that even the local population prefers dates from another state. This strengthens our
argument to provide local producers with better strategies to successfully market their products.
Providing consumers with information about the benefits of buying Arizona grown Medjool dates
would be the first step in this regard.
Moreover, consumers were willing to pay almost a $1 premium for pesticide-free
production labelling of Medjool dates. Considering that this label is not in use currently, it will be
a viable tool to communicate the production method in the market place. In addition, consumers
who preferred the pesticide-free production method were more likely to choose products that also
15
carried the GMO-free label, indicating that providing products with both labels, would not
cannibalize but rather augment the effect of the other.
Overall, our results show that consumers respond to region of origin and production
method labelling and that producers should consider strategies to improve the brand image of
Arizona grown products and that they could benefit from incorporating and communicating
pesticide-free production of Medjool dates. Future research will generalize these results to a larger
sample in order to identify consumer segments of Medjool date preferences.
Acknowledgements. Funding received from the Arizona Department of Agriculture Specialty
Crop Block Grant Program (SCBGP), Grant Award Agreement #SCBGP-FB15-24, is gratefully
acknowledged.
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