Exploratory Factor Analysis (EFA)

Principal axis factoring extraction method with Varimax rotation was conducted to assess the underlying structures that influence consumer food shopping behaviour. The variables consisted of the 59 items that were used to measure shopping motivations where each item was measured on a seven-point scale (1 = strongly = disagree, 7 = strongly agree). The variables in this study are assumed to be metric. Items were derived from Jamal et al.’s (2006) study, as well as salient items such as gender and shopping task and social acceptance which were added in the light of the qualitative research to suit the Libyan case, were used in the exploratory factor analysis EFA.

6.4.1. Confirmation of the Correlation of Data

Inter-correlation of the variables was confirmed by visual inspection of the correlation matrix, Bartlett’s test of Sphericity and the Kaiser-Meyer-Olkin test (KMO) (Hair et al., 2010). Inspection of the correlation matrix revealed the presence of some significant correlation at 0.01 levels. The Bartlett test of Sphericity was significant (2 (1711) =

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7546.841, Sig = 0.000)1. A significant result (Sig. < 0.05) indicated that the matrix was not an identity matrix; i.e., the variables do relate to one another enough to run a meaningful EFA. Furthermore, the KMO measure of sampling adequacy was around 0.7 (KMO = 0.723), exceeding the threshold value of 0.5 (Hair et al., 2010).

6.4.2. Factor Extraction

A 19- factor solution with eigenvalues greater than one was extracted by applying exploratory factor analysis using principal axis method with Varimax rotation, explaining 65.85 per cent of the total variance. Examination of the factor loadings, however, revealed that there was more than one variable which cross loaded and were thus difficult to interpret. Hair et al. (2010, p. 119) suggested that “if a variable persists in having cross loading, it becomes a candidate for deletion”. Therefore, after excluding these variables one by one and inspecting the factor solution, the item loadings and the anti-image correlation matrix, a total of 26 items were deleted. The remaining 33 items were again subjected to EFA and a 12 - factor solution was extracted.

The Bartlett test of Sphericity was significant (2 (528) = 4667.535, Sig = 0.000). The KMO measure of sampling adequacy was = 0.698 (see Table 6-11), and greater than 0.5 for each individual variable by checking the diagonal of the anti-image correlation matrix.

Table 6-11: KMO and Bartlett's Test

6.4.3. Evaluate the Goodness of Fit of the Solution

By using EFA, the 59 original variables were reduced to 12 factors. The data reduction rate was 55.93 per cent and information loss was 44.07 per cent. To determine whether a “12

1 _{Chi-square (degrees of freedom) = Chi square statistic, Significance statistic.}

Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.698

Bartlett's Test of Sphericity _{Approx. Chi-Square 4667.535}

df 528

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Factor Solution” was suitable, the communalities were examined and deemed acceptable (Communalities > 0.5). In addition, the total variance which was explained by these factors was 73.75 per cent. Furthermore, by examining the rotated factor matrix, all the factor loadings were considered practically significant. None of the items presented factor loadings of less than 0.6 even though a factor loading with 0.3 is acceptable with a sample size of more than 350 (Hair et al., 2010). Also, the factor loadings that are the most widely used approach as evidence for both convergent and discriminant validity demonstrated sufficient validity; the variables within a single factor were highly correlated (convergence) and all variables loaded significantly only on one factor (discrimination). In order to quantify the scale reliabilities of the factors identified, Cronbach’s alpha coefficients were computed. The reliability of the overall was 0.786 (see Table 6-12); none of the Cronbach’s alpha

coefficients were lower than the threshold level of 0.60 as shown in Table 6-13.

Table 6-12: Reliability Statistics

Cronbach's Alpha

N of Items

0.786 33

As detailed in Table 6-13, the 12 factors can be described as follows:

1. Hedonic shopping factor: this factor accounted for 8.14 per cent of total variance and

consisted of four of the variables “enjoy shopping”, “enjoyable activities”, “fun” and “love shopping”.

2. Confused by choice factor accounted for 7.90 per cent of total variance and was

strongly associated with “the more I learn about products, the harder it seems to choose”, “all the information I get on different products confuses me”, “there are so many brands to choose that often I feel confused” and “sometimes it’s hard to choose which stores to shop at”.

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Table 6-13: Exploratory Factor Analysis (EFA) Results

1 _{Cronbach’s alpha} 2 _h2 _{refers to communality} Items Factor loading α1 % of Variance h2

Factor 1-Hedonic shopping 0.83 8.14

I enjoy shopping more than most people do 0.82 0.73

Going shopping is one of the enjoyable activities for me 0.81 0.72

I enjoy shopping just for the fun of it 0.79 0.72

I love to go shopping when I can find time 0.70 0.62

Factor 2-Confused by choice 0.79 7.90

The more I learn about products, the harder it seems to choose the best 0.88 0.80 All the information I get on different products confuses me 0.84 0.78 There are so many brands to choose that often I feel confused 0.69 0.55

Sometimes it’s hard to choose which stores to shop at 0.65 0.56

Factor 3-Social shopping 0.86 7.24

Shopping with others is a bonding experience 0.88 0.84

I enjoy socializing with others when I shop 0.86 0.81

I like shopping with my friends or family to socialize 0.80 0.71

Factor 4-Value shopping 0.73 7.16

I enjoy looking for discounts when I shop 0.83 0.73

I enjoy hunting for bargains when I shop 0.80 0.69

For the most parts, I go shopping when there are sales 0.73 0.63

Factor 5-Brand loyal/habitual 6.17

I have favourite brands I buy over and over 0.83 0.72

Once I find a product or brand I like, I stick with it 0.78 0.65

I like to buy the same brand 0.75 0.58

Factor 6-Brand conscious 0.67 5.93

The higher the price of the product, the better is its quality 0.84 0.72

The more expensive brands are usually my choice 0.79 0.69

Nice department and specialty stores offer me the best products 0.66 0.50

Factor 7-High quality seeking 0.85 5.64

When it comes to purchasing products, I try to get the perfect choice 0.84 0.73 In general I usually try to buy the best overall quality 0.79 0.68

Getting very good quality is important to me 0.66 0.50

Factor 8- Gratification seeking 0.86 5.36

When I am in down mood, I go shopping to make me feel 0.92 0.88

To me shopping is a way to relieve stress 0.90 0.87

Factor 9- Gender roles and shopping task 0.82 5.28

Food shopping is a task for men only 0.90 0.84

A woman’s place is in the home 0.90 0.83

Factor10- Role playing 5.17

I like shopping for others because when they feel good, I feel good 0.90 0.81 0.85

I enjoy shopping for my family and friends 0.88 0.83

Factor 11-Impulsiveness 0.78 5.00

I am impulsive when purchasing 0.90 0.81

Often I make careless purchases I later wish I had not 0.88 0.81

Factor12-Social acceptance 0.69 4.76

It is acceptable for a woman to go shopping in supermarkets alone or with other woman

0.86 0.78

It is acceptable for a woman to go shopping in traditional market alone or with other woman

0.85 0.77

Total variance 73.62

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3. The third factor was correlated with “shopping with others is a bonding experience”,

“I enjoy socializing with others when I shop” and “I like shopping with my friends or family to socialize”, so can be called “social shopping” and accounted for 7.24 per cent of total variance.

4. High quality seeking factor was correlated with “When it comes to purchasing

products, I try to get the perfect choice”, “in general I usually try to buy the best overall quality” and “getting very good quality is important to me”, and accounted for 5.64 per cent of total variance.

5. Value shopping was associated with three variables: “I enjoy looking for discounts

when I shop”, “I enjoy hunting for bargains when I shop” and “for the most parts, I go shopping when there are sales”, and accounted for 7.16 per cent of total variance.

6. Brand loyalty factor was most strongly correlated with: “I have favourite brands I buy

over and over”, “once I find a product or brand I like, I stick with it” and “I like to buy the same brand”, and accounted for 6.17 per cent of total variance.

7. Brand consciousness: this factor accounted for 5.93 per cent of total variance and had

a strong association with “the higher the price of the product, the better is its quality”, “the more expensive brands are usually my choice” and “nice department and specialty stores offer me the best products”.

8. Gratification seeking factor was associated strongly with two variables: “when I am in

down mood, I go shopping to make me feel better” and “to me shopping is a way to relieve stress” and interpreted 5.36 per cent of total variance.

9. Gender roles and shopping task: it was correlated with “food shopping is a task for

men only” and “a woman’s role is in the home” and accounted for 5.28 per cent of total variance.

10. Role playing factor was associated with “I like shopping for others because when

they feel good, I feel good” and “I enjoy shopping for my family and friends” and accounted for 5.17 per cent of total variance.

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11. Impulsiveness factor: this factor was correlated with: “I am impulsive when

purchasing” and “often I make careless purchases I later wish I had not”; and accounted for 5.00 per cent of total variance.

12. Social acceptance factor: it accounted for 4.76 per cent of total variance and was

associated with: “it is acceptable for a woman to go shopping in supermarket alone or with other woman” and “it is acceptable for a woman to go shopping in a traditional market alone or with another woman”.