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Understanding Apple Attribute Preferences of US Consumers
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This entry is adapted from the peer-reviewed paper 10.3390/foods11020166

Fresh apples are a commonly consumed and widely available product in food markets around the world.

US consumers apple attitude

1. Introduction

Apples as a horticultural consumer good are comprised of various product attributes, some of which may have varying levels of importance for consumers. Relevant consumer attributes possessed by fresh apples include the colour of the skin, shape, aroma, apple variety, texture and the length of their shelf life [1][2][3][4]. This latter attribute is particularly important, as even though apples have good storing qualities, they are ultimately perishable [5][6][7]. Colour and appearance are crucial in retail situations as they attract the consumer’s attention. Colour often serves as a cue for fruit quality; consumers commonly attempt to estimate the texture of apples as this gives them an indication of the taste [8]. Extant literature in this area classifies consumers into two main categories: those who prefer firmness, juiciness, and bit of acidity in apples, and those that who like sweeter, but less firm apples [9]. In addition to these product attributes which are inherent to the apple (intrinsic attributes), consumers are also interested in commercial attributes, such as price, packaging, branding, country of origin, and sustainability [10][11][12]. These are linked to the production, distribution, and presentation of apples (extrinsic attributes) [13][14][15][16][17]. Although early studies on horticultural and agricultural products have emphasised the importance of intrinsic attributes for consumers, more recent studies show that for agricultural and horticultural products external attributes are equally important for consumers [18][19][20][21][22]. Consumer choices regarding apple attributes, as well as the willingness to pay for fresh or processed apple products has been intensively studied in the US [23][24][25]; Consumer choice relies on a trade off between bundles of intrinsic and extrinsic product attribute; these include aspects of consumers personal backgrounds, including their sensory preferences and attitudes [26]. However, key-factors which lead to the determination of apple preferences are not as widely studied. In the following sub sections these factors are explained in more detail as they underpin the conceptual framework for this study. US consumers’ objective and subjective knowledge, as well as their sociodemographic backgrounds, their discernment as a buyer and their attitudes towards apple growers are likely to be key factors in determining the importance that US consumers place on physical and commercial apple attributes.

2. Apple Buyer Discernment

For the US food retail industry, as well as for the horticultural industry, it is important to know consumer preferences for new and existing varieties, as well as their ability to distinguish varieties [27]. This allows businesses to offer products that consumers need and want, and enables marketers to differentiate their products from existing ones. Very few studies have focused on the perception of apple varieties and the ability of consumers to distinguish them [27]. Studies which have shown that consumers are necessarily able to distinguish apple varieties have found that mostly neophobia or neophilia determines preference or aversion towards new apple varieties [23][27]. In the US, new varieties are often termed as club varieties [23]. Club varieties are subject to patent-protection. Growers who are part of the club have exclusive rights to produce and market the club variety as stipulated by a licensing contract. This includes both fruit quality and quantity [28]. Common examples of club varieties on the US market are ‘Jazz™’, ‘SnowSweet®’, ‘Sweet Sixteen’, ‘SweeTango®’, ‘Zestar!™’, and ‘Pink Lady®’ [23]. Examples of more traditional varieties are ‘Red’ and ‘Golden Delicious’, ‘Granny Smith’, ‘Fuji’, ‘Honeycrisp’, ‘McIntosh’, ‘Cripps Pink’ [29]. Given that the majority of consumers do not possess a good varietal knowledge, marketing promotions, such as tasting experiences which offer free samples coupled with promotional materials regarding varietals are crucial to improve the ability of consumers to distinguish amongst different varieties [28].

3. Current Insight on Apple Attribute Preferences of US Consumers

The descriptive statistics of the sample are displayed in Table 1. The median respondent was aged between 25 and 34 years, had obtained a bachelor degree, and earned an annual pre-tax income ranging between USD 25,000 to USD 50,000 per year. Additionally, the other scale measured in the model was the objective apple knowledge score, which had a mean of 1.02, a range of between −4 to +5, and a standard deviation of 1.834.
Table 1. Sample description.
Table
  Freq % Median StDev
Age        
Under 21 2 0.5    
21–24 16 4.2    
25–34 215 56.1 ✓ 0.940
35–44 104 27.2    
45–54 27 7.0    
55–64 14 3.7    
65+ 5 1.3    
Total 383 100    
Education        
Did not finish high school 6 1.6    
Finished high school 46 12.0    
Attended University 40 10.4    
Bachelors Degree 223 58.2 ✓ 0.927
Postgraduate Degree 68 17.8    
Total 383 100    
Household Annual Income        
USD 0 to 24,999 80 20.9    
USD 25,000 to 49,999 117 30.5 ✓ 1.141
USD 50,000 to 74,999 119 31.1    
USD 75,000 to 99,999 40 10.4    
USD 100,000 or higher 27 7.0    
Total 383 100    
Gender        
Male 196 51.2 ✓ 0.501
Female 187 48.8    
Total 383 100    
US Geographical Distribution      
North-East 83 21.7    
Mid-West 133 34.8    
South 90 23.5    
West 77 20.1    
Total 383 100  
The measurement model assessment included the use of reliability to test the model constructs, as well as the use convergent and discriminant validity to conduct further checks. All items achieved a factor loading of well above the minimum of 0.4, indicating their suitable contribution to the scale (see Table 2). Reliability was confirmed by both the Cronbach Alpha and composite reliability scores being above 0.6. Convergent validity was also indicated by AVE scores being higher than 0.5 for all the scales. Given that all indicators were within acceptable ranges, the requirements of construct reliability and validity were considered satisfactory [30].
Table 2. Scale loadings, reliabilities, and convergent validity.
Table
Scales and Items Factor Loadings Cronbach’s Alpha Composite Reliability Average Variance Extracted
Discerning Apple Buyer   0.836 0.877 0.504
How similar are Pink Lady and Cosmic Crisp 0.741      
How similar are Granny Smith and Royal Gala 0.731      
How similar are Pink Lady and Cripps Pink 0.706      
How similar are McIntosh and Braeburn 0.749      
How similar are Zestar! and Sweet Tango 0.718      
How similar are Fuji and Red Delicious 0.639      
How similar are Red Delicious and Golden Delicious 0.680      
Importance of Apple Commercial Attributes   0.701 0.817 0.527
Importance of—Price 0.702      
Importance of—Labelled as sustainable 0.719      
Importance of—Labelled as traditional varieties such as Royal Gala, Braeburn, Granny Smith 0.735      
Importance of—Labelled as club apples such as Pink lady or Cosmic Crisp 0.747      
Importance of Apple Physical Attributes   0.723 0.825 0.543
Importance of—Colour of the skin is true to variety 0.773      
Importance of—Smell is appealing 0.700      
Importance of—Texture is soft 0.793      
Importance of—Skin is free of visual blemishes 0.673      
My Attitudes towards US Apple Growers   0.836 0.880 0.552
I think that US growers have a longstanding tradition and lots of experience in growing sustainable apples. 0.728      
I think that US apple growers contribute to the care and maintenance of the landscape 0.678      
I think that US apple growers make active contributions to preserve biodiversity 0.841      
I think that US apple growers treat land resources responsible 0.707      
I think that social pressure on apple growers should be increased as they are main agents of climate change. 0.665      
I think that US apple growers are environmental conscious 0.821      
Subjective Apple Knowledge   0.860 0.905 0.704
I understand a lot about apples 0.821      
I am confident in my knowledge of apples 0.810      
Among my friends I am the apple expert 0.882      
I know more about apples than others do 0.841    
Both the Fornell–Larker criterion and Heterotrait–Monotrait (HTMT) ratios were utilized to test discriminant validity, with the requirements for discriminant validity being met for all of the variable constructs (see Table 3). The square root of each constructs’ AVE was found to be higher than its correlation with other constructs. HTMT ratios are all less than 0.90, with the exception of the HTMT ratio between the importance placed on physical apple attributes and the importance placed on commercial apple attributes (1), which is a higher ratio than that which is recommended. However, this does not represent a problem because the two constructs both measure the apple attribute importance, with one construct being intrinsic and the other extrinsic to the product. Additionally, the largest VIF was 1.338 and the average VIF was 1.158, indicating that there were no problems with multicollinearity [31].
Table 3. Scale discriminant validity.
Table
Fornell–Larcker Criterion Discerning Apple Buyer Importance of Apple Commercial Attributes Importance of Apple Physical Attributes Attitudes towards US Apple Growers Subjective Apple Knowledge
Discerning Apple Buyer 0.710        
Importance of Apple Commercial Attributes 0.638 0.726      
Importance of Apple Physical Attributes 0.571 0.719 0.737    
Attitudes towards US Apple Growers 0.503 0.476 0.501 0.743  
Subjective Apple Knowledge 0.484 0.426 0.360 0.548 0.839
Heterotrait–Monotrait Ratio          
Discerning Apple Buyer          
Importance of Apple Commercial Attributes 0.831        
Importance of Apple Physical Attributes 0.713 1      
Attitudes towards US Apple Growers 0.588 0.614 0.618    
Subjective Apple Knowledge 0.566 0.546 0.417 0.635  
The conceptual framework and its overall structure was tested, resulting in a Goodness of Fit of 0.43 and a Normed Fit Index of 0.676. A Standardised Root Mean Square Residual of 0.074 was also achieved, and this indicated that adequacy of the overall model fit. The explanatory and predictive power of the conceptual model was also tested, and this resulted in average R2/Q2 values of 0.349/0.293, which indicates that the model has overall weak/moderate explanatory power and moderate predictive relevance. However, some parts of the model were found to be stronger than other parts. The R2/Q2 scores of 0.248/0.336 for discerning apple buyers would be considered weak in their explanatory power and moderate in their predictive relevance, but the score of 0.440/0.216 for importance placed on commercial apple attributes, and 0.388/0.247 for importance placed on physical apple attributes indicate weak/moderate levels of explanatory power and small predictive relevance. The score of 0.321/0.372 for attitudes towards US growers would be considered to have moderate explanatory power and medium predictive relevance. The structure of the model was confirmed to be fit for hypothesis testing due to the adequate model fit, the weak to moderate explanatory power, and the weak to medium predictive accuracy. Table 4 and Figure 1 show the results of the hypothesis testing.
Foods 11 00166 g002 550
Figure 1. Results of the conceptual model.
Table 4. Path coefficients and hypothesis testing results.
Table
Hypothesised Relationship Coefficient T Stat p Value
H1a: Objective Apple Knowledge -> Discerning Apple Buyer −0.008 0.191 0.848
H1b: Subjective Apple Knowledge -> Discerning Apple Buyer 0.456 11.929 0.000
H2a: Gender -> Discerning Apple Buyer −0.027 0.627 0.530
H2b: Age -> Discerning Apple Buyer −0.077 1.773 0.076
H2c: Education -> Discerning Apple Buyer 0.068 1.511 0.131
H2d: Income -> Discerning Apple Buyer −0.054 1.206 0.228
H3a: Objective Apple Knowledge -> My Attitudes towards US Apple Growers −0.086 2.133 0.033
H3b: Subjective Apple Knowledge -> My Attitudes towards US Apple Growers 0.536 10.553 0.000
H4a: Gender -> My Attitudes towards US Apple Growers −0.006 0.129 0.898
H4b: Age -> My Attitudes towards US Apple Growers 0.031 0.729 0.466
H4c: Education -> My Attitudes towards US Apple Growers 0.126 2.134 0.033
H4d: Income -> My Attitudes towards US Apple Growers 0.005 0.140 0.889
H5: Discerning Apple Buyer -> Importance of Apple Physical Attributes 0.428 7.142 0.000
H6: My Attitudes towards US Apple Growers -> Importance of Apple Physical Attributes 0.286 4.776 0.000
H7: Discerning Apple Buyer -> Importance of Apple Commercial Attributes 0.534 9.267 0.000
H8: My Attitudes towards US Apple Growers -> Importance of Apple Commercial Attributes 0.208 3.586 0.000
Bold = p < 0.05.
The subjective knowledge was the most important factor determining the discernment of buyers and attitudes towards US growers. Objective knowledge was not found to have any impact, while only education as a sociodemographic factor had impact. The discernment as a buyer and the ability to distinguish apple varieties had the greatest impact on the importance that US consumers placed on apple attributes. Additionally, attitudes towards growers impacted the importance consumers placed on intrinsic and extrinsic apple attributes.

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Subjects: Behavioral Sciences
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