| Literature DB >> 31905802 |
Lingling Xu1, Xixi Yang1, Linhai Wu1.
Abstract
Against the backdrop of the continuous large-scale growth of imported milk in China, in this research 310 consumers in Shanghai were used as a sample, and a choice experiment was conducted to study consumer preference and willingness to pay for imported milk. The following product attributes were included: nutrition claim, fat content, flavor, country of origin, and price. Our results show that, excepting price, consumers consider flavor the most important attribute, followed by nutrition claim, fat content, and country of origin. Consumers can be delineated into four segments based on consumer preference for the attributes of imported milk: "nutrition claim seekers" are willing to pay the highest price for imported milk with nutrition claims, "indifferent" consumers pay little attention to imported milk attributes, "flavor-oriented" consumers have a strong preference for strawberry-flavored imported milk, and "price-sensitive" consumers weigh the price when choosing imported milk.Entities:
Keywords: choice experiment; country of origin; nutrition claim; preference
Mesh:
Year: 2019 PMID: 31905802 PMCID: PMC6982324 DOI: 10.3390/ijerph17010244
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Attributes and levels of imported milk.
| Attributes | Levels |
|---|---|
| Fat content | Whole milk |
| Skim milk | |
| Flavor | Plain |
| Strawberry flavor | |
| Banana flavor | |
| Nutrition claim | Contains vitamin A, vitamin D |
| Contains Ca, Fe, Zn, vitamin D | |
| No claim | |
| Country of origin | New Zealand |
| Germany | |
| France | |
| Price | 4.5 yuan/box |
| 5.8 yuan/box | |
| 7.1 yuan/box | |
| 8.4 yuan/box |
Figure 1Sample choice task card.
Demographic characteristics and consumption habits.
| Characteristics | Sample (n = 310) | Nutrition Claim Seekers (n = 178) | Indifferent (n = 20) | Flavor-Oriented (n = 45) | Price-Sensitive (n = 67) |
|---|---|---|---|---|---|
| Male | 43.9% | 41.6% | 80.0% | 28.9% | 49.3% |
| Female | 56.1% | 58.4% | 20.0% | 71.1% | 50.7% |
| 18–24 | 21.0% | 18.5% | 45.0% | 26.7% | 16.4% |
| 25–34 | 54.8% | 57.9% | 30.0% | 55.5% | 53.7% |
| 35–44 | 16.8% | 18.0% | 10.0% | 11.1% | 19.5% |
| ≥45 | 7.4% | 5.6% | 15.0% | 6.7% | 10.4% |
|
| |||||
| Primary school or lower | 3.2% | 2.2% | 10.0% | 4.4% | 3.0% |
| Middle school | 11.3% | 12.4% | 10.0% | 17.8% | 4.5% |
| High school | 21.9% | 18.5% | 15.0% | 31.1% | 26.9% |
| Junior college | 27.1% | 27.0% | 20.0% | 24.5% | 31.3% |
| Undergraduate | 31% | 34.3% | 30.0% | 22.2% | 28.3% |
| Master or above | 5.5% | 5.6% | 15.0% | 0% | 6.0% |
|
| |||||
| 50,000 yuan or less | 14.2% | 12.9% | 5.0% | 20.0% | 16.4% |
| 51,000–100,000 yuan | 31.6% | 34.8% | 25.0% | 22.2% | 31.3% |
| 101,000–150,000 yuan | 24.5% | 24.7% | 35.0% | 33.3% | 14.9% |
| 151,000–200,000 yuan | 14.8% | 14.0% | 10.0% | 13.4% | 19.4% |
| 201,000–300,000 yuan | 7.4% | 6.8% | 15.0% | 4.4% | 9.0% |
| 300,000 yuan or above | 7.4% | 6.8% | 10.0% | 6.7% | 9.0% |
| Never drink | 4.2% | 2.8% | 15.0% | 4.5% | 4.5% |
| 1–2 times | 30% | 28.1% | 35.0% | 33.3% | 31.3% |
| 3–4 times | 33.5% | 34.3% | 30.0% | 40.0% | 28.4% |
| 5–6 times | 19.4% | 18.0% | 15.0% | 20.0% | 23.9% |
| Drink every day | 12.9% | 16.8% | 5.0% | 2.2% | 11.9% |
| I have heard of and purchased | 27.1% | 28.1% | 20.0% | 26.7% | 26.9% |
| I have heard of but not purchased | 31.9% | 32.0% | 35.0% | 33.3% | 29.8% |
| Never heard of | 41.0% | 39.9% | 45.0% | 40.0% | 43.3% |
| 0–10% | 56.1% | 50.0% | 65.0% | 75.6% | 56.7% |
| 10–30% | 21.3% | 27.0% | 20.0% | 11.1% | 13.4% |
| 30–50% | 12.9% | 10.6% | 5.0% | 11.1% | 22.4% |
| >50% | 9.7% | 12.4% | 10.0% | 2.2% | 7.5% |
Note: One-way ANOVA and post-hoc analysis were used to test the difference between segments. *** represents that the difference between segments is significant at 5% level.
Estimation results of RPL and LCL models.
| Variables | RPL Model | LCL Model | |||
|---|---|---|---|---|---|
| Nutrition Claim Seekers | Indifferent | Flavor-Oriented | Price-Sensitive | ||
| Price | −0.1173 *** | −0.0123 | −12.2229 | −0.0659 | −0.3067 *** |
| Skim | 0.1768 *** | 0.11268 *** | 2.9184 | −0.0248 | 0.2316 * |
| Strawberry flavor | −0.3494 *** | −0.16941 *** | −4.5124 | 0.4306 *** | −1.2052 *** |
| Banana flavor | −0.5220 *** | −0.1829 *** | −9.2510 | −0.5080 *** | −1.5179 *** |
| Claim “contains vitamin A, vitamin D” | 0.1099 ** | 0.0889 * | −2.7476 | 0.3911 *** | −0.0257 |
| Claim “contains Ca, Fe, Zn, vitamin D” | 0.2235 *** | 0.1579 *** | 13.3683 | −0.1502 | 0.3771 ** |
| New Zealand | 0.0165 | −0.0307 | −4.1950 | 0.3130 ** | 0.1014 |
| Germany | 0.1660 *** | 0.1040 ** | 7.0849 | 0.0067 | 0.2900 |
| Chooseno | −1.3381 *** | −2.0426 *** | −93.7504 | 0.3928 | −1.2880 ** |
| Standard deviation estimation | |||||
| Skim | 0.2953 *** | − | − | − | − |
| Strawberry flavor | 0.7066 *** | − | − | − | − |
| Banana flavor | 0.6153 *** | − | − | − | − |
| Claim “contains vitamin A, vitamin D” | 0.3656 *** | − | − | − | − |
| Claim “contains Ca, Fe, Zn, vitamin D” | 0.3912 *** | − | − | − | − |
| New Zealand | 0.2194 * | − | − | − | − |
| Germany | 0.2569 ** | − | − | − | − |
| Class Prob. | NA | 0.5734 | 0.0655 | 0.1462 | 0.2149 |
| Number of observations | 3410 | 1958 | 220 | 495 | 737 |
| Pseudo R-squared | 0.1268 | 0.1727 | |||
| Log-likelihood | −3271.0879 | −3099.3374 | |||
| 3410 | |||||
Note: ***, **, and * denote significance at the 1%, 5%, and 10% significance levels, respectively.
Statistics to determine the optimal number of consumer segments.
| Segments | Parameters (P) | Log Likelihood (LL) | AIC | AIC3 | BIC | ρ2 |
|---|---|---|---|---|---|---|
| 2 | 19 | −3184.81366 | 6407.62732 | 6426.62732 | 3262.0911 | 0.14480 |
| 3 | 29 | −3136.65355 | 6331.30710 | 6360.30710 | 3254.6033 | 0.15498 |
| 4 | 39 | −3099.33742 | 6276.67484 | 6315.67484 | 3257.9595 | 0.15707 |
| 5 | 49 | −3100.68036 | 6299.36072 | 6348.36072 | 3299.9748 | 0.15925 |
Note: AIC = –2(LL – P); AIC3 = (–2LL + 3P); BIC = (–LL + (P/2) × ln(N)); ρ2 = (1 – AIC/2Restricted LL); Restricted Log-likelihood = –3746.26790.
Consumer WTP for each level (yuan/200 mL).
| Variables | The Sample | Nutrition Claim Seekers | Indifferent | Flavor-Oriented | Price-Sensitive |
|---|---|---|---|---|---|
|
| 3.016 | 18.292 | 0.478 | −0.753 | 1.510 |
|
| −5.959 | −27.501 | −0.738 | 13.067 | −7.859 |
|
| −8.902 | −29.685 | −1.514 | −15.414 | −9.898 |
|
| 1.874 | 14.427 | −0.450 | 11.868 | −0.168 |
|
| 3.812 | 25.638 | 2.187 | −4.557 | 2.459 |
|
| 0.281 | −4.989 | −0.686 | 9.498 | 0.661 |
|
| 2.831 | 16.888 | 1.159 | 0.203 | 1.891 |
Note: Values in the brackets are 95% confidence interval.
Knowledge, attitude, and use of nutrition and health claims.
| Sample | Nutrition Claim Seekers | Indifferent | Flavor-Oriented | Price-Sensitive | Sig. | |
|---|---|---|---|---|---|---|
| Knowledge on carbohydratesa | 77.7% | 80.2% | 76.2% | 65.2% | 80.3% | 0.000 |
| Knowledge on fibrea | 78.4% | 81.4% | 61.9% | 74.0% | 78.8% | 0.000 |
| Knowledge on cholesterola | 78.7% | 83.1% | 81.0% | 60.9% | 78.8% | 0.000 |
| Importance of claims on fatb | 3.175 | 3.237 | 2.857 | 3.064 | 3.182 | 0.000 |
| Importance of claims on sugarsb | 3.196 | 3.209 | 2.667 | 3.175 | 3.333 | 0.000 |
| Importance of claims on vitaminsb | 3.404 | 3.457 | 2.952 | 3.306 | 3.470 | 0.000 |
| Importance of health claims in generalb | 4.010 | 4.079 | 4.095 | 3.827 | 3.924 | 0.000 |
| Importance of claims on “Omega-3 fatty acids help to maintain heart health”b | 3.495 | 3.536 | 2.905 | 3.456 | 3.606 | 0.000 |
| Importance of claims on “Zinc and iron contributes to normal cognitive brain function”b | 3.778 | 3.831 | 3.238 | 3.782 | 3.803 | 0.000 |
| I often use health claims on food while food shoppingb | 3.050 | 3.203 | 2.381 | 2.868 | 2.970 | 0.000 |
| I often use nutrition claims on food while food shoppingb | 3.071 | 3.179 | 2.619 | 2.825 | 3.106 | 0.000 |
Note: a A survey of variables related to the perceptions of nutrients such as carbohydrates, level of knowledge on nutritional properties (uninformed = 0, informed = 1); b Variables on consumer attitudes, interests, and habits of nutritional information were measured using a five-point scale (e.g.,: “not important,” “less important,” “general,” “more important,” and “very important” were indicated as 1–5 points, respectively). c Significant differences in cognition, attitude, and habits among the four types of consumers were estimated in an ANOVA analysis. Sig. < 0.05 indicates significant differences among the four groups.