| Literature DB >> 30621184 |
Takashi Suzuki1, Taro Oishi2, Hisashi Kurokura3, Nobuyuki Yagi4.
Abstract
This research examined post-disaster consumer perception of food value and their effects on purchase intent by focusing on Japanese seafood industry after the Great East Japan earthquake. Online surveys on consumers living in Tokyo and Osaka Prefectures were conducted to investigate consumer value perceptions of Miyagi salmon in 2012 and 2015. Multiple-group structural equation modeling (SEM) on the 2012 survey results showed that desire to contribute to restoration (social value) had the greatest positive influence on purchase intent in both regions. Concern about radiation threats (safety value) had a negative influence on purchase intent, with a stronger impact in Osaka than Tokyo. In comparison, the 2015 results revealed a reduction in the effects of these two potent factors (i.e., safety value and social value) on purchase intent only in Osaka. The beneficial value of seafood had a general positive influence on purchase intent, but its magnitude of effect differed by regional and chronological context. Among these three values, sales promotion with emphasis on social value is more effective than with other values. In cases of future disasters in a similar context, marketers are recommended to adopt different value transfer strategies according to geographical and temporal diversity.Entities:
Keywords: Fukushima nuclear accident; Miyagi; consumer purchase intent; factor analysis; food value; marketing strategy; salmon; structural equation modeling; the Great East Japan earthquake
Year: 2019 PMID: 30621184 PMCID: PMC6352202 DOI: 10.3390/foods8010014
Source DB: PubMed Journal: Foods ISSN: 2304-8158
Figure 1Conceptual model of the relationship between values of seafood and purchase intent. Note: Observable variables of consumer food value perceptions are represented by boxes, and latent variables which exert indirect effects on purchase intent by ellipses.
Figure 2Photo of a Miyagi salmon product.
Questionnaire on consumer perception and purchase intent of the value of Miyagi salmon.
| Construct | Items | Measurement |
|---|---|---|
| Taste | Miyagi salmon tastes good | Five-point Likert scale |
| Price | Miyagi salmon is priced higher than other salted salmon products | |
| Nutrition | Miyagi salmon is rich in nutrition | |
| Seasonality | Miyagi salmon is valued as a seasonal product | |
| Appearance | Miyagi salmon looks good and fresh | |
| Naturalness * | Farming of Miyagi salmon has a large environmental load because salmon farming seems to need antibiotics | |
| Convenience * | Miyagi salmon is easy to cook because it is prepared without bones | |
| Safety 1 | I have concerns about the institutions responsible for inspecting Miyagi salmon | |
| Safety 2 | I have concerns about the method of inspection (complete or sampled) on radioactivity of Miyagi salmon | |
| Social 1 | By purchasing Miyagi salmon, we contribute to the reconstruction of disaster-affected areas | |
| Social 2 | By purchasing Miyagi salmon, considerable employment can be created in disaster-affected areas | |
| Social 3 | By purchasing Miyagi salmon, we can protect rural fishery culture (fishery industry, cooking methods) in disaster-affected areas | |
| Origin * | If there is no difference in the price of salmon between Miyagi and overseas products, I want to buy Miyagi salmon | |
| Environment * | Harvesting of Miyagi salmon has a large environmental load for nature because it needs huge amounts of feed | |
| Purchase intent | I want to purchase Miyagi salmon for home consumption |
Note: * indicates questions which were excluded from the 2015 questionnaire.
Figure 3A radius map around the Fukushima nuclear plant. Note: Solid lines indicate borders between prefectures. Black circles indicate radius distances of 200 km, 400 km, and 600 km from Fukushima where the nuclear plant is located.
Results of factor analysis and correlations among constructs in the 2012 survey for the two groups (NTokyo = 340; NOsaka = 319).
| Tokyo | Osaka | ||||||
|---|---|---|---|---|---|---|---|
| Beneficial | Social | Safety | Beneficial | Social | Safety | ||
| Taste | 0.585 | 0.186 | 0.019 | 0.685 | −0.008 | −0.003 | |
| Nutrition | 0.733 | −0.036 | 0.076 | 0.778 | 0.010 | 0.062 | |
| Seasonality | 0.811 | −0.042 | −0.046 | 0.840 | 0.006 | −0.029 | |
| Appearance | 0.758 | −0.008 | −0.050 | 0.669 | 0.132 | 0.004 | |
| Price | 0.554 | −0.027 | 0.015 | 0.652 | −0.106 | −0.037 | |
| Safety 1 | 0.010 | −0.004 | 0.909 | −0.014 | 0.011 | 0.982 | |
| Safety 2 | −0.007 | 0.002 | 0.969 | 0.005 | −0.020 | 0.909 | |
| Social 1 | −0.007 | 0.882 | 0.024 | −0.008 | 0.908 | −0.056 | |
| Social 2 | 0.033 | 0.918 | 0.004 | −0.025 | 0.969 | 0.021 | |
| Social 3 | −0.036 | 0.908 | −0.031 | 0.012 | 0.923 | 0.027 | |
| KMO measure of sampling adequacy | 0.781 | 0.785 | |||||
| Bartlett’s test of sphericity | Approximate chi-squared | 1977.771 | 2225.943 | ||||
|
| 45 | 45 | |||||
| Significant | 0.000 | 0.000 | |||||
| Cronbach’s alpha | 0.817 | 0.928 | 0.937 | 0.847 | 0.943 | 0.950 | |
| eigenvalue | 3.003 | 3.007 | 1.841 | 3.319 | 3.284 | 1.847 | |
| Correlations | Beneficial | 1 | 1 | ||||
| Social | 0.458 | 1 | 0.488 | 1 | |||
| Safety | 0.158 | −0.010 | 1 | 0.133 | 0.020 | 1 | |
Note: df = degree of freedom; items with factor loadings above 0.4 are presented in boxes. KMO = Kaiser–Meyer–Olkin.
Results of factor analysis and correlations among constructs in the 2015 survey for the two groups NTokyo = 722; NOsaka = 472).
| Tokyo | Osaka | ||||||
|---|---|---|---|---|---|---|---|
| Beneficial | Social | Safety | Beneficial | Social | Safety | ||
| Taste | 0.627 | 0.081 | −0.029 | 0.753 | 0.046 | −0.053 | |
| Nutrition | 0.730 | −0.019 | 0.085 | 0.782 | −0.007 | 0.042 | |
| Seasonality | 0.828 | −0.023 | −0.091 | 0.776 | 0.014 | −0.023 | |
| Appearance | 0.707 | 0.087 | 0.031 | 0.739 | 0.046 | 0.035 | |
| Price | 0.649 | −0.079 | 0.018 | 0.697 | −0.084 | −0.007 | |
| Safety 1 | 0.019 | 0.001 | 0.912 | 0.034 | −0.009 | 0.993 | |
| Safety 2 | −0.010 | 0.000 | 0.981 | −0.037 | 0.010 | 0.893 | |
| Social 1 | 0.021 | 0.877 | −0.011 | −0.019 | 0.871 | −0.005 | |
| Social 2 | −0.022 | 0.912 | 0.022 | −0.002 | 0.947 | −0.006 | |
| Social 3 | 0.003 | 0.903 | −0.011 | 0.016 | 0.924 | 0.013 | |
| KMO measure of sampling adequacy | 0.794 | 0.788 | |||||
| Bartlett’s test of sphericity | Approximate chi-squared | 4396 | 3180 | ||||
|
| 45 | 45 | |||||
| Significant | 0.000 | 0.000 | |||||
| Cronbach’s alpha | 0.864 | 0.937 | 0.940 | 0.834 | 0.925 | 0.945 | |
| Eigenvalue | 3.422 | 3.172 | 1.824 | 3.242 | 3.156 | 1.835 | |
| Correlations | Beneficial | 1 | 1 | ||||
| Social | 0.521 | 1 | 0.477 | 1 | |||
| Safety | 0.088 | 0.006 | 1 | −0.109 | −0.005 | 1 | |
Note: df = degree of freedom; items with factor loadings above 0.4 are presented in boxes. KMO = Kaiser–Meyer–Olkin.
Figure 4Revised conceptual model of the relationship between values of seafood and purchase intent. Note: β figures correspond to path coefficients of Tokyo 2012 (β12T), Osaka 2012 (β12O), Tokyo 2015 (β15T) and Osaka 2015 (β15O). Note: GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; RMSEA = root mean square error approximation; SEM = structural equation modeling.
Goodness of fit indices in SEM for the four groups.
| 2012 | 2015 | ||||
|---|---|---|---|---|---|
| Tokyo | Osaka | Tokyo | Osaka | ||
| Goodness of fit indices | GFI | 0.964 | 0.954 | 0.973 | 0.963 |
| AGFI | 0.942 | 0.926 | 0.956 | 0.941 | |
| RMSEA | 0.047 | 0.059 | 0.051 | 0.056 | |
Note: GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; RMSEA = root mean square error approximation; SEM = structural equation modeling.
Results of multiple-group SEM and goodness of fit indices.
| 2012 | 2015 | ||||||
|---|---|---|---|---|---|---|---|
| Tokyo | Osaka | z | Tokyo | Osaka | z | ||
| Standardized path coefficient (β) | Beneficial value →Purchase intent | 0.220 | 0.314 | 1.228 | 0.328 | 0.403 | 0.234 |
| Social value →Purchase intent | 0.486 | 0.405 | −0.934 | 0.453 | 0.293 | −2.524 *** | |
| Safety value →Purchase intent | −0.201 | −0.324 | −2.472 *** | −0.246 | −0.209 | 0.903 | |
| Beneficial value ⇔Social value | 0.474 | 0.500 | −0.702 | 0.538 | 0.491 | −0.195 | |
| Goodness of fit indices | GFI | 0.965 | |||||
| AGFI | 0.944 | ||||||
| RMSEA | 0.026 | ||||||
Note: *** significant at p < 0.001; GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; RMSEA = root mean square error approximation.