| Literature DB >> 30621243 |
Lijia Wang1,2, Jianhua Wang3, Xuexi Huo4.
Abstract
The aim of the paper was to assess how consumers evaluate organic labeled fruits and to what extent they are willing to pay a premium for fresh fruits with organic labels. A double-hurdle model is applied to data obtained by interviewing 407 fresh fruit consumers in nine Chinese cities. Willingness-to-pay a premium was modeled as a function of a series of demographic, socio-economic variables, plus fruit attributes, perceptions of fruit safety, and risk attitudes. Results indicate that the most important factors influencing willingness to pay a premium involved positive attitudes toward organic label, attention to fruit safety, the perception of importance of fruit attributes. Moreover, the more income consumers earn, the more likely they would be willing to pay a premium for organic fresh fruits. The recorded consumer interest in safety and quality of fresh fruits reveals that a promising market for organic fruits could be developed by an adequate knowledge on organic label and an effective market monitoring system.Entities:
Keywords: China; double-hurdle model; organic fruits; premium; willingness to pay
Mesh:
Year: 2019 PMID: 30621243 PMCID: PMC6339216 DOI: 10.3390/ijerph16010126
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1China Organic Product Certification Mark. Source: https://www.organic-bio.com/en/labels.
Figure 2Per Capita Consumption of Major Food of Urban Households, 1990–2012. Note: The data are compiled on the basis of the integrated household income and expenditure survey of the National Bureau of Statistics of the People’s Republic of China, including urban and rural households.
Figure 3Location of the sample cities in China.
Summary statistics for empirical variables.
| Variable | Description | Variable Scale | Mean | Std. Dev. |
|---|---|---|---|---|
| WTP | Willingness to pay a premium | 1 = Willing to pay; | 0.61 | 0.49 |
| MONE | The premium pay for organic fresh fruit | yuan/kg | 0.69 | 0.85 |
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| SEX | Gender | 1 = male; | 0.46 | 0.50 |
| AGE | Age | Years | 38.96 | 14.66 |
| EDU | Education a | Years of schooling | 16.04 | 2.97 |
| SIZE | Household size | Number of individuals | 3.07 | 0.93 |
| INCM | Monthly income | 1–5 b | 2.37 | 1.52 |
| OCCP | Occupation | 1 = Well educated; | 0.78 | 0.41 |
| DEVE | Location of residence | 1 = developed city; | 0.49 | 0.50 |
| PPRI | Purchase price | yuan/kg | 7.58 | 3.93 |
| CFRE | Consumption frequency | 1–5 c | 3.57 | 0.97 |
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| PRIC | Sales price | 1–5 d | 3.51 | 0.89 |
| WRAP | Wrapping | 2.30 | 0.87 | |
| APPE | Appearance | 4.00 | 0.76 | |
| NUTR | Nutritional value | 3.10 | 1.08 | |
| EABU | Purchase convenience | 3.41 | 0.84 | |
| PREG | Province of origin | 2.46 | 1.23 | |
| ORLB | Organic label | 2.41 | 1.01 | |
| VATY | Variety | 3.60 | 0.93 | |
| TAST | Taste | 4.35 | 0.83 | |
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| WSAF | Worried fruit safety | 1–5 c | 1.81 | 0.65 |
| QUTI | Notice of organic label | 2.30 | 1.01 | |
| ATTE | Concerns about fruit safety | 3.23 | 0.80 | |
| CRED | Credence in organic label | 4.39 | 0.94 | |
| FREQ | Frequency of buying unsafely fruit which causing diarrhea or other diseases | 2.83 | 0.94 | |
| POSB | Possibility of buying fruits produced by companies occurred safety incident | 1.70 | 1.23 | |
Note: a 6 = primary school, 9 = middle school, 12 = high school, 16 = bachelor degree, 19 = master degree, 22 = PhD; b 1 = less than 3000 yuan, 2 = (3000, 4000) yuan, 3 = (4000, 5000) yuan, 4 = (5000, 6000) yuan, 5 = equal and more than 6000 yuan; c 1 = very low, 2 = low, 3 = moderate, 4 = high, 5 = very high; d 1 = not importance at all, 2 = not important, 3 = moderate, 4 = important, 5 = very important.
Figure 4Comparison of attitudes toward fruit safety between WTP and UWTP consumers. Note: For the purpose of presentation, the five digit-scale categories were combined into three: “high” in the figure combines the frequencies of “very high” and “high” responses; “low” combines the frequencies of “very low” and “low” responses.
Perception of Importance on fruit attributes. (Percent of respondents in each category) a.
| Item | Willing to Pay (N = 250) | Unwilling to Pay (N = 157) | ||||
|---|---|---|---|---|---|---|
| Unimportant | Moderate | Important | Unimportant | Moderate | Important | |
| Taste | 3.2 | 11.6 | 85.2 | 4.5 | 7.0 | 88.5 |
| Appearance | 3.6 | 12.8 | 83.6 | 3.2 | 17.2 | 79.6 |
| Purchase convenience | 8.8 | 30.8 | 60.4 | 18.5 | 45.9 | 35.7 |
| Variety | 10.4 | 29.2 | 60.4 | 15.3 | 25.5 | 59.2 |
| Nutritional Value | 19.6 | 32.8 | 47.6 | 39.5 | 42.0 | 18.5 |
| Sales price | 16.8 | 40.0 | 43.2 | 13.4 | 14.6 | 72.0 |
| Province of origin | 49.2 | 22.0 | 28.8 | 62.4 | 28.7 | 8.9 |
| Organic label | 42.0 | 34.0 | 24.0 | 75.8 | 23.6 | 0.6 |
| Wrapping | 49.2 | 44.4 | 6.4 | 63.7 | 33.1 | 3.2 |
Note: a For the purpose of presentation, the five digit-scale categories were combined into three: “important” in this table combines the frequencies of “very important” and “important” responses; “unimportant” combines the frequencies of “not important at all” and “not important” responses.
Estimation results of the double-hurdle model.
| Independent Variables | First Hurdle | Second Hurdle | ||
|---|---|---|---|---|
| Coef. (Std. Err.) | Marginal Effect | Coef. (Std. Err.) | Elasticity a | |
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| SEX | −0.1355 (0.2026) | −0.0492 | 0.0939 (0.1964) | 0.0838 |
| AGE | −0.0034 (0.0097) | −0.0012 | −0.0769 (0.0498) | −0.0687 |
| EDU | 0.1018 (0.0510) ** | 0.0369 | 0.0339 (0.0107) *** | 0.0271 |
| SIZE | −0.1286 (0.1049) | −0.0467 | −0.0521 (0.1086) | −0.0465 |
| INCM | 0.3769 (0.1249) *** | 0.1368 | 0.1990 (0.0680) *** | 0.1777 |
| OCCP | 0.6892 (0.2409) *** | 0.2622 | 0.2168 (0.3441) | −0.1136 |
| DEVE | 0.6381 (0.2070) *** | 0.2292 | 0.6895 (0.2129) *** | 0.6156 |
| PPRI | 0.1633 (0.0265) *** | 0.0593 | 0.1258 (0.0270) *** | 0.1123 |
| CFRE | 0.2471 (0.0843) *** | 0.0897 | 0.0887 (0.0896) | 0.0792 |
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| PRIC | 0.0323 (0.1242) | 0.0117 | 0.0899 (0.2868) | 0.0803 |
| WRAP | −0.0979 (0.0711) | −0.0355 | 0.0930 (0.1166) | 0.0830 |
| APPE | 0.3205 (0.1130) *** | 0.1163 | 0.3702 (0.1245) *** | 0.3305 |
| NUTR | 0.3255 (0.1020) *** | 0.1181 | 0.0100 (0.1086) | 0.0089 |
| EABU | 0.0398 (0.1004) | 0.0144 | 0.3458 (0.1241) | 0.3088 |
| PREG | −0.0255 (0.0771) | −0.0093 | 0.0917 (0.1064) | 0.0819 |
| ORLE | 0.5193 (0.1272) *** | 0.1884 | 0.2698 (0.0801) *** | 0.2409 |
| VATY | 0.0544 (0.0978) | 0.0198 | 0.0959 (0.1011) | 0.0856 |
| TAST | 0.2071 (0.1146) * | 0.0752 | 0.1635 (0.1287) | 0.1460 |
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| WSAF | 0.0442 (0.1429) | 0.0160 | −0.0189 (0.1422) | −0.0169 |
| QUTI | 0.0457 (0.0994) | 0.0166 | −0.0289 (0.0967) | −0.0258 |
| ATTE | 0.1536 (0.1208) *** | 0.0557 | 0.3014 (0.0999) *** | 0.2691 |
| CRED | 0.3678 (0.0951) | 0.1334 | 0.3946 (0.1238) | 0.3523 |
| FREQ | 0.2429 (0.1249) * | 0.0881 | 0.0845 (0.1824) | 0.0754 |
| POSB | −0.0470 (0.0746) | −0.0170 | −0.1596 (0.3433) | −0.1425 |
| Observations (n) | 407 | 250 | ||
| Wald | 162.12 | 72.82 | ||
| Log pseudo-likelihood | −168.18 | −214.01 | ||
| Sigma b | 0.8954 | |||
Note: Standard errors which are robust are reported in parentheses. Marginal effects of changing the explanatory variables are evaluated at the mean of the explanatory variables; a The elasticity is calculated at the sample mean; b Sigma is the error variance; * significant at the 10% level; ** significant at the 5% level; *** significant at the1 percent level.