2. Literature Review
4.1 Pearson correlation
In this section, the dataset will be reviewed through a Pearson correlations analysis. This is done to view if the variables have a relationship with the dependent variable, purchase intention (Pearson’s Correlation Coefficient, 2020). When it is concluded that is the case, a regression analysis is performed to reveal if the data has predictive power, and what that entails.
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39 4.1.1 Quality Pearson correlation
The data set was first analysed using the Pearson correlation analysis. By analysing the variable questions against their core anchor quality question, the following interesting findings were found.
Correlations
Q26 Q10 Q21 Q22 Q23 Q24 Q25
Q26 Pearson Correlation 1 .013 .247 -.100 .480** .528** .503**
Sig. (2-tailed) .921 .055 .442 .000 .000 .000
Sum of Squares and Cross-products
129.639 1.328 28.869 -10.902 61.984 71.885 57.344
Covariance 2.161 .022 .481 -.182 1.033 1.198 .956
N 61 61 61 61 61 61 61
**. Correlation is significant at the 0.01 level (2-tailed).
Table 1 Correlation matrix Quality 1
The participants showed that nutrient information is important to millennials buying PL coffee. The data also reflected how higher quality means they are also willing to pay more for PL coffee; however, it was contradicting other results. To be more specific, participants were asked if they would purchase low price PL coffee if the quality was low, which the participants also scored high meaning that price was hard to determine with quality. The quality standard of the QMS certificate is deemed especially important for quality standards and it was also interesting to see how quality over time is valued remarkably high.
Another factor that Chinese millennials view as an important sign of quality is when a PL coffee brands itself as being like known brands – meaning it would increase the level of purchase intention of the PL Coffee brand or product. Finally, when a product or brand owns good reviews online, participants would overlook the fact that the brand or product is seen as lesser or owning a lower qualitative coffee brand or product.
4.1.2 Price Pearson correlation
The findings for pricewere also interesting. The Chinese millennials found that when a PL coffee brand or product has good reviews online, like quality, the consciousness for price
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went down. Should the PL coffee product or brand also have a large price difference, regardless of the risk or price, the participants were eager to try it out. The large price difference also affected the extend to familiarity, that when a brand was not known but offered a significant cost saving the participants were motivated to try it out.
Correlations
Q20 Q16 Q17 Q18 Q19
Q20 Pearson Correlation 1 .483** .066 .379** .434**
Sig. (2-tailed) .000 .615 .003 .000
Sum of Squares and Cross-products
74.787 53.311 5.672 27.754 42.082
Covariance 1.246 .889 .095 .463 .701
N 61 61 61 61 61
Table 2 Correlation matrix Price 1
Correlations
Q26 Q32 Q34 Q37 Q38 Q40
Q2 Pearson Correlation 1 -.235 .115 -.004 -.298* -.109
Sig. (2-tailed) .068 .378 .974 .020 .403
Sum of Squares and Cross-products
129.639 -27.426 15.787 -.508 -30.885 -11.574
Covariance 2.161 -.457 .263 -.008 -.515 -.193
N 61 61 61 61 61 61
Table 3: Correlation Matrix Price 2
4.1.3 Risk Pearson correlation
Correlations
Q35 Q11 Q15 Q16 Q17 Q19 Q21
Q35 Pearson Correlation 1 .486** .071 .135 .351** .337** -.076
Sig. (2-tailed) .000 .587 .298 .006 .008 .560
Sum of Squares and Cross-products
70.361 40.902 5.984 14.492 29.377 31.656 -6.557
Covariance 1.173 .682 .100 .242 .490 .528 -.109
N 61 61 61 61 61 61 61
**. Correlation is significant at the 0.01 level (2-tailed).
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*. Correlation is significant at the 0.05 level (2-tailed).
Table 4: Correlation Matrix Risk 1
The Pearson correlation tests, showed a significant correlation for PL products that are deemed of lesser quality than known brands. A QMS-certificate showed to be particularly important to reduce the consciousness of risk. There was no significant correlation between a price discount and a lower sense of risk. Chinese millennials did not feel a sense of risk should coffee lose quality over time and a high sense of risk correlates when a PL product or brand is not known, also confirmed by Baltas (1997). When the PL coffee brand or product clearly expressed their benefits, it lowered the assumed risk of price; meaning a lower sense of price means a lower sense of risk.
Correlations
Q35 Q32 Q33 Q34 Q41
Q35 Pearson Correlation 1 .508** .334** .319* .193
Sig. (2-tailed) .000 .009 .012 .136
Sum of Squares and Cross-products
70.361 43.689 27.262 32.344 14.246
Covariance 1.173 .728 .454 .539 .237
N 61 61 61 61 61
Table 5 Correlation Matrix Risk 2
An interesting finding as well, is that consumers experience more psychological risk when purchasing a product online as shown in question 31.
Correlations
Q35 Q29 Q30 Q31 Q32
Q35 Pearson Correlation 1 .310* .536** .265* .508**
Sig. (2-tailed) .015 .000 .039 .000
Sum of Squares and Cross-products
70.361 30.525 36.443 25.279 43.689
Covariance 1.173 .509 .607 .421 .728
N 61 61 61 61 61
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
Table 6: Correlation Matrix Risk 3
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It may be important for PL exporters to ensure that the products are also physically advertised and promoted in samples to raise a form of trust or familiarity, thus lowering the sense of risk.
An important preliminary conclusion for retailers to avoid risk is to offer Chinese millennials multiple PL coffee products under one brand and lower the conscious risk of price.
This offers interesting questions for future research regarding Chinese millennials and PL coffee, whether this consumer group is risk averse, or very mindful of risk and what this would mean in terms of PL coffee branding.
4.1.4 Familiarity Pearson correlation
The Pearson correlation test gave interesting results for the variable Familiarity. The brand awareness became less relevant when the product seemed to own a higher sense of quality.
Correlations
Q43 Q7 Q8
Q43 Pearson Correlation 1 .280* .152
Sig. (2-tailed) .029 .241
Sum of Squares and Cross-products
67.443 8.443 4.852
Covariance 1.124 .141 .081
N 61 61 61
*. Correlation is significant at the 0.05 level (2-tailed).
Table 7: Correlation Matrix Familiarity 1
Similarly, the participants revealed how higher familiarity led to a lower sense of risk, including reading positive reviews. This criterion revealed to be important, with a correlation value of 0.328. Finally, participants showed that they knew what PL products were, however, did not buy it often.
Correlations
Q43 Q36 Q37 Q38 Q39 Q40
Q43 Pearson Correlation 1 .475** .068 .328** .099 .214
Sig. (2-tailed) .000 .603 .010 .446 .098
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Sum of Squares and Cross-products
67.443 31.738 5.820 24.525 9.656 16.377
Covariance 1.124 .529 .097 .409 .161 .273
N 61 61 61 61 61 61
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
Table 8: Correlation Matrix Familiarity 2
Correlations
Q43 Q41 Q42
Q43 Pearson Correlation 1 .547** .562**
Sig. (2-tailed) .000 .000
Sum of Squares and Cross-products 67.443 39.508 41.525
Table 9: Correlation Matrix Familiarity 3