Could Surplus Food in Blind Box Form Increase Consumers’ Purchase Intention?
Abstract
:1. Introduction
1.1. Research Background
1.2. Research Motivation and Purpose
2. Relevant Studies
2.1. Perceived Value
2.2. Perceived Risk
2.3. Subjective Norm
2.4. Perceived Food Quality
2.5. Brand Image
2.6. Perceived Playfulness
2.7. Perceived Variety
2.8. Convenience
2.9. Purchase Intention
3. Research Method and Hypothesis
3.1. Research Hypothesis and Model Construction
3.2. Design of Questionnaires
3.3. Design of Questionnaires
4. Research Analysis and Results
4.1. Reliability Analysis
4.2. Exploratory Factor Analysis
4.3. Confirmatory Factor Analysis
4.3.1. First-Order Confirmatory Factor Analysis
4.3.2. Second-Order Confirmatory Factor Analysis
4.3.3. Results of the Structural Equation Model
4.4. Discussions
5. Conclusions and Suggestions
5.1. Theoretical Implications
5.2. Practical Implications
- Increasing the reputation of surplus food blind boxes (SN). For instance, promoting the amount of carbon dioxide that is reduced per serving and offering reduced prices can attract more customers with a variety of different attributes while making them possible repeat customers.
- Making blind boxes more interesting (PP), for example, by developing different styles of blind boxes (while preserving the mysterious characteristics of the blind box). The box may look similar, however, there are likely to be additional surprises within. It is also possible to add a QR code to the blind box, so the consumers can scan it and view the condition of the surplus food materials or the cooking process, which is not only entertaining, but also makes them feel more at ease. Maintain a consistent experience (CON) along the entire purchase path, focusing particularly on communication details and smoothness that stimulate consumers’ feelings, such as improving menu logic, simplifying purchase steps, etc.
- Pay attention to the combination of ingredients (PVAR). Although there are relatively few combinations of surplus food, we can develop a number of combinations of surplus food that will best suit the tastes of consumers.
5.3. Limitations and Future Research
- This paper does not demonstrate the existence of a direct relationship between PR, PV, and PI, but there may be some unknown complete mediation, which is worth investigating.
- PVAL can be divided in order to study the different dimensions of surplus food blind boxes.
- Separate the population into distinct subpopulations and conduct differential research and analysis.
- The present study is a quantitative study using structural equation modeling as the research and analysis method. In the future, qualitative research can be added to elaborate the deeper meaning that quantitative data cannot convey.
- In this study, Chinese samples were used as research subjects. Research in the future may also establish a comparison of Chinese and foreign data, which will broaden the research horizon and expand the research findings.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Measurements | Description |
---|---|
Food waste in China annually | Approximately 17 to 18 metric tons of food are wasted annually [5], which produces 54 metric tons of carbon dioxide equivalent emissions, consumes 24 metric tons of water, and occupies 23 million hectares of land [6]. |
Food waste in Chinese households annually | About 5.5 metric tons of food are wasted annually, equivalent to 22% of total food production. For vegetables and fruits, this percentage is even higher [7]. |
Amount of food wasted per Chinese per day | It is about 93 g per meal, about 279 g three times a day [8]. |
Attributes | Variables | Operating Definition | Request References |
---|---|---|---|
first-order | Subjective norm (SN) | Social pressures that encourage or discourage individuals to make an action with the surplus food blind box | [49] |
Perceived food quality (PQ) | Consumers’ judgment of quality of the surplus food blind box based on cues | [29] | |
Brand image (BI) | Brand image is related to the consumers’ use of the brand to reflect their symbolic meaning of consumption and identity in self-expression | [50] | |
Perceived playfulness (PP) | perceived playfulness as the degree to which the consumer believes that enjoyment could be derived when shopping for the surplus food blind box | [51] | |
Perceived variety (PVAR) | The pursuit and experience of diverse types of food in consumer’s shopping for the surplus food blind box | [52] | |
Convenience (CON) | Consumers’ perceptions of their time and effort with regards to purchasing the surplus food blind box | [43] | |
Perceived risk (PR) | Perceived risk is defined as a potential consumer’ perception about the possible uncertain negative outcomes from shopping for the surplus food blind box | [53] | |
Perceived value (PVAL) | Consumer’s overall assessment of the utility of the surplus food blind box | [29] | |
Purchase intention (PI) | Consumer’s intention to purchase the surplus food blind box | [54] | |
Second-order | Access convenience (AC) | Access convenience refers to the degree of ease and comfort for the consumer to arrive at the trading venue | [43] |
Decision convenience (DC) | Decision convenience relates to the time and effort utilized by consumers in making purchase decisions and deciding between products, brands, or service providers | [43] | |
Transaction convenience (TC) | Transaction convenience refers to the time and effort the consumers spend to finalize a purchase | [43] |
Sample | Category | Number | Percentage (%) |
---|---|---|---|
Gender | male | 410 | 55.8% |
Female | 325 | 44.2% | |
Age | 19–29 | 342 | 46.5% |
30–39 | 297 | 40.4% | |
40–49 | 75 | 10.2% | |
above 50 | 21 | 2.9% | |
Marriage Status | Married | 553 | 75.2% |
unmarried | 182 | 24.8% | |
Monthly Income | Below 4000 | 74 | 10.1% |
4001–8000 | 148 | 20.1% | |
8001–16,000 | 335 | 45.6% | |
16,001–30,000 | 134 | 18.2% | |
30,001 or more | 44 | 6.0% | |
Education | Junior high school or below | 3 | 0.4% |
high school or secondary school | 27 | 3.7% | |
Undergraduate or college | 641 | 87.2% | |
Institute including above | 64 | 8.7% | |
Occupation | civil servant | 69 | 9.4% |
clerk | 353 | 48.0% | |
Worker | 108 | 14.7% | |
public service agency | 79 | 10.7% | |
student | 50 | 6.8% | |
self-employed | 76 | 10.3% | |
Area | East area | 412 | 56.1% |
Central Region | 131 | 17.8% | |
Western Region | 153 | 20.8% | |
North-west region | 39 | 5.3% |
Construct | Item | Mean | Std. Deviation | CITC | Cronbach’s α If Item Deleted | Cronbach’s α |
---|---|---|---|---|---|---|
SN | SN1 | 3.478 | 1.053 | 0.706 | 0.762 | 0.835 |
SN2 | 3.579 | 1.118 | 0.695 | 0.774 | ||
SN3 | 3.513 | 1.046 | 0.689 | 0.778 | ||
PP | PP1 | 3.565 | 1.151 | 0.715 | 0.692 | 0.814 |
PP2 | 3.379 | 1.156 | 0.654 | 0.755 | ||
PP3 | 3.744 | 1.123 | 0.627 | 0.783 | ||
PQ | PQ1 | 3.576 | 1.091 | 0.470 | 0.702 | 0.714 |
PQ2 | 3.433 | 1.059 | 0.547 | 0.607 | ||
PQ3 | 3.493 | 1.062 | 0.585 | 0.560 | ||
BI | BI1 | 3.161 | 1.151 | 0.554 | - | 0.713 |
BI2 | 3.460 | 1.108 | 0.554 | - | ||
PVAR | PVAR1 | 3.893 | 1.004 | 0.615 | 0.737 | 0.793 |
PVAR2 | 3.891 | 1.003 | 0.568 | 0.761 | ||
PVAR3 | 3.995 | 0.912 | 0.565 | 0.761 | ||
PVAR4 | 3.985 | 0.918 | 0.672 | 0.709 | ||
DC | DC1 | 3.561 | 0.939 | 0.448 | 0.591 | 0.657 |
DC2 | 3.542 | 1.172 | 0.463 | 0.580 | ||
DC3 | 3.571 | 1.010 | 0.507 | 0.511 | ||
AC | AC1 | 3.556 | 1.020 | 0.539 | 0.674 | 0.736 |
AC2 | 3.502 | 1.068 | 0.546 | 0.666 | ||
AC3 | 3.472 | 1.109 | 0.597 | 0.605 | ||
TC | TC1 | 3.976 | 0.965 | 0.521 | 0.575 | 0.689 |
TC2 | 3.954 | 0.904 | 0.495 | 0.608 | ||
TC3 | 4.108 | 0.871 | 0.499 | 0.605 | ||
PR | PR1 | 3.084 | 1.194 | 0.687 | 0.751 | 0.824 |
PR2 | 3.352 | 1.218 | 0.684 | 0.754 | ||
PR3 | 3.334 | 1.163 | 0.670 | 0.768 | ||
PVAL | PVAL1 | 3.565 | 0.925 | 0.546 | 0.677 | 0.740 |
PVAL2 | 3.452 | 1.058 | 0.566 | 0.656 | ||
PVAL3 | 3.652 | 0.998 | 0.587 | 0.627 | ||
PI | PI1 | 3.725 | 1.039 | 0.730 | 0.787 | 0.852 |
PI2 | 3.845 | 1.052 | 0.735 | 0.781 | ||
PI3 | 3.774 | 1.031 | 0.703 | 0.812 |
Construct | KMO | Bartlett Sphere Test | Item | Component Matrix | Communalities | Eigenvalue | Total Variation Explaine% |
---|---|---|---|---|---|---|---|
SN | 0.726 | 0 | SN1 | 0.873 | 0.762 | 2.258 | 75.255 |
SN2 | 0.886 | 0.751 | |||||
SN3 | 0.863 | 0.745 | |||||
PP | 0.703 | 0 | PP1 | 0.883 | 0.780 | 2.187 | 72.910 |
PP2 | 0.848 | 0.719 | |||||
PP3 | 0.829 | 0.688 | |||||
PQ | 0.660 | 0 | PQ1 | 0.745 | 0.555 | 1.913 | 63.771 |
PQ2 | 0.812 | 0.659 | |||||
PQ3 | 0.836 | 0.699 | |||||
BI | 0.500 | 0 | BI1 | 0.882 | 0.777 | 1.554 | 77.707 |
BI2 | 0.882 | 0.777 | |||||
PVAR | 0.789 | 0 | PVAR1 | 0.796 | 0.634 | 2.479 | 61.987 |
PVAR2 | 0.758 | 0.575 | |||||
PVAR3 | 0.756 | 0.572 | |||||
PVAR4 | 0.836 | 0.698 | |||||
DC | 0.655 | 0 | DC1 | 0.754 | 0.568 | 1.791 | 59.697 |
DC2 | 0.764 | 0.583 | |||||
DC3 | 0.800 | 0.640 | |||||
AC | 0.680 | 0 | AC1 | 0.794 | 0.630 | 1.964 | 65.460 |
AC2 | 0.798 | 0.637 | |||||
AC3 | 0.835 | 0.697 | |||||
TC | 0.669 | 0 | TC1 | 0.799 | 0.638 | 1.852 | 61.733 |
TC2 | 0.777 | 0.604 | |||||
TC3 | 0.781 | 0.609 | |||||
PR | 0.721 | 0 | PR1 | 0.864 | 0.747 | 2.221 | 74.027 |
PR2 | 0.863 | 0.744 | |||||
PR3 | 0.854 | 0.729 | |||||
PVAL | 0.686 | 0 | PVAL1 | 0.797 | 0.636 | 1.976 | 65.862 |
PVAL2 | 0.811 | 0.658 | |||||
PVAL3 | 0.826 | 0.682 | |||||
PI | 0.731 | 0 | PI1 | 0.883 | 0.780 | 2.316 | 77.195 |
PI2 | 0.886 | 0.785 | |||||
PI3 | 0.867 | 0.751 |
Common Indices | χ2 | df | χ2/df | GFI | AGFI | CFI | NFI | RMSEA | SRMR |
---|---|---|---|---|---|---|---|---|---|
Judgement criteria | <3 | >0.9 | >0.9 | >0.9 | >0.9 | <0.08 | <0.08 | ||
Value | 755.646 | 440 | 1.717 | 0.941 | 0.924 | 0.972 | 0.935 | 0.031 | 0.032 |
Item | Factor Loading | SMC | t | S.E. | Sig. | CR | AVE |
---|---|---|---|---|---|---|---|
SN1 | 0.818 | 0.668 | 25.363 | 0.020 | 0.001 | 0.836 | 0.629 |
SN2 | 0.784 | 0.615 | 23.909 | 0.018 | 0.001 | ||
SN3 | 0.777 | 0.603 | 23.603 | 0.021 | 0.001 | ||
PP1 | 0.848 | 0.719 | 27.276 | 0.015 | 0.001 | 0.816 | 0.598 |
PP2 | 0.730 | 0.533 | 22.048 | 0.020 | 0.001 | ||
PP3 | 0.737 | 0.543 | 22.340 | 0.023 | 0.001 | ||
PQ1 | 0.627 | 0.393 | 17.849 | 0.027 | 0.001 | 0.721 | 0.464 |
PQ2 | 0.686 | 0.470 | 19.939 | 0.022 | 0.002 | ||
PQ3 | 0.726 | 0.527 | 21.411 | 0.023 | 0.001 | ||
BI1 | 0.705 | 0.497 | 19.445 | 0.024 | 0.001 | 0.715 | 0.558 |
BI2 | 0.786 | 0.617 | 21.754 | 0.026 | 0.001 | ||
PVAR1 | 0.691 | 0.477 | 19.998 | 0.026 | 0.002 | 0.797 | 0.497 |
PVAR2 | 0.676 | 0.457 | 19.457 | 0.027 | 0.002 | ||
PVAR3 | 0.667 | 0.445 | 19.120 | 0.030 | 0.001 | ||
PVAR4 | 0.780 | 0.609 | 23.585 | 0.022 | 0.002 | ||
DC1 | 0.597 | 0.368 | 15.538 | 0.035 | 0.001 | 0.662 | 0.395 |
DC2 | 0.661 | 0.437 | 17.431 | 0.032 | 0.001 | ||
DC3 | 0.626 | 0.392 | 16.400 | 0.033 | 0.001 | ||
AC1 | 0.679 | 0.462 | 18.687 | 0.026 | 0.001 | 0.737 | 0.484 |
AC2 | 0.673 | 0.454 | 18.488 | 0.026 | 0.001 | ||
AC3 | 0.733 | 0.537 | 20.500 | 0.026 | 0.001 | ||
TC1 | 0.684 | 0.468 | 18.434 | 0.031 | 0.001 | 0.690 | 0.427 |
TC2 | 0.627 | 0.393 | 16.641 | 0.033 | 0.001 | ||
TC3 | 0.647 | 0.419 | 17.264 | 0.031 | 0.001 | ||
PR1 | 0.772 | 0.595 | 22.839 | 0.021 | 0.001 | 0.824 | 0.610 |
PR2 | 0.808 | 0.652 | 24.241 | 0.019 | 0.001 | ||
PR3 | 0.763 | 0.582 | 22.509 | 0.021 | 0.001 | ||
PVAL1 | 0.669 | 0.448 | 19.074 | 0.029 | 0.001 | 0.741 | 0.489 |
PVAL2 | 0.704 | 0.496 | 20.362 | 0.028 | 0.001 | ||
PVAL3 | 0.723 | 0.523 | 21.069 | 0.023 | 0.001 | ||
PI1 | 0.818 | 0.670 | 26.160 | 0.018 | 0.002 | 0.853 | 0.658 |
PI2 | 0.824 | 0.680 | 26.454 | 0.016 | 0.001 | ||
PI3 | 0.792 | 0.627 | 24.923 | 0.020 | 0.001 |
SN | PP | PQ | BI | PVAR | DC | AC | TC | PR | PVAL | PI | |
---|---|---|---|---|---|---|---|---|---|---|---|
SN | 0.793 | ||||||||||
PP | 0.625 | 0.773 | |||||||||
PQ | 0.571 | 0.664 | 0.681 | ||||||||
BI | 0.467 | 0.535 | 0.559 | 0.747 | |||||||
PVAR | 0.481 | 0.601 | 0.594 | 0.439 | 0.705 | ||||||
DC | 0.393 | 0.396 | 0.519 | 0.450 | 0.444 | 0.628 | |||||
AC | 0.429 | 0.453 | 0.515 | 0.493 | 0.437 | 0.461 | 0.696 | ||||
TC | 0.360 | 0.432 | 0.447 | 0.375 | 0.572 | 0.410 | 0.459 | 0.653 | |||
PR | −0.398 | −0.447 | −0.495 | −0.363 | −0.322 | −0.310 | −0.392 | −0.305 | 0.781 | ||
PVAL | 0.538 | 0.570 | 0.635 | 0.513 | 0.535 | 0.536 | 0.495 | 0.445 | −0.437 | 0.699 | |
PI | 0.630 | 0.734 | 0.640 | 0.508 | 0.608 | 0.482 | 0.479 | 0.501 | −0.503 | 0.662 | 0.811 |
Common Indices | χ2 | df | χ2/df | GFI | AGFI | CFI | NFI | RMSEA | SRMR |
---|---|---|---|---|---|---|---|---|---|
Judgement criteria | <3 | >0.9 | >0.9 | >0.9 | >0.9 | <0.08 | <0.08 | ||
Value | 69.560 | 24 | 2.898 | 0.979 | 0.960 | 0.971 | 0.957 | 0.035 | 0.051 |
Common Indices | χ2 | df | χ2/df | GFI | AGFI | CFI | NFI | RMSEA | SRMR |
---|---|---|---|---|---|---|---|---|---|
Judgement criteria | <3 | >0.9 | >0.9 | >0.9 | >0.9 | <0.08 | <0.08 | ||
Value | 938.453 | 462 | 2.031 | 0.924 | 0.908 | 0.957 | 0.919 | 0.038 | 0.037 |
DV | IV | Direct Effect | Indirect Effect | Total Effect | |||
---|---|---|---|---|---|---|---|
β | B-C Sig. | β | B-C Sig. | β | B-C Sig. | ||
BI | PR | 0.167 | 0.246 | - | - | 0.167 | 0.246 |
CON | −0.327 | 0.263 | - | - | −0.327 | 0.263 | |
PVAR | 0.406 | 0.038 | - | - | 0.406 | 0.038 | |
PQ | −0.636 | 0.103 | - | - | −0.636 | 0.103 | |
PP | −0.193 | 0.316 | - | - | −0.193 | 0.316 | |
SN | 0.001 | 0.892 | - | - | 0.001 | 0.892 | |
BI | PVAL | −0.119 | 0.329 | −0.003 | 0.584 | −0.122 | 0.285 |
CON | 0.571 | 0.010 | 0.005 | 0.530 | 0.576 | 0.011 | |
PVAR | −0.090 | 0.547 | −0.006 | 0.725 | −0.096 | 0.477 | |
PQ | 0.109 | 0.616 | 0.010 | 0.771 | 0.119 | 0.644 | |
PP | 0.416 | 0.016 | 0.003 | 0.492 | 0.419 | 0.014 | |
SN | 0.121 | 0.087 | 0.000 | 0.876 | 0.121 | 0.087 | |
PR | −0.016 | 0.773 | - | - | −0.016 | 0.773 | |
BI | PI | - | - | −0.119 | 0.228 | −0.119 | 0.228 |
CON | - | - | 0.534 | 0.008 | 0.534 | 0.008 | |
PVAR | - | - | −0.111 | 0.331 | −0.111 | 0.331 | |
PQ | - | - | 0.146 | 0.487 | 0.146 | 0.487 | |
PP | - | - | 0.386 | 0.016 | 0.386 | 0.016 | |
SN | - | - | 0.108 | 0.088 | 0.108 | 0.088 | |
PR | −0.063 | −0.308 | −0.014 | 0.771 | −0.077 | 0.199 | |
PVAL | 0.891 | 0.001 | - | - | 0.891 | 0.001 |
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Yang, C.; Chen, X.; Sun, J.; Wei, W.; Miao, W.; Gu, C. Could Surplus Food in Blind Box Form Increase Consumers’ Purchase Intention? Agriculture 2022, 12, 864. https://doi.org/10.3390/agriculture12060864
Yang C, Chen X, Sun J, Wei W, Miao W, Gu C. Could Surplus Food in Blind Box Form Increase Consumers’ Purchase Intention? Agriculture. 2022; 12(6):864. https://doi.org/10.3390/agriculture12060864
Chicago/Turabian StyleYang, Chun, Xuqi Chen, Jie Sun, Wei Wei, Wei Miao, and Chao Gu. 2022. "Could Surplus Food in Blind Box Form Increase Consumers’ Purchase Intention?" Agriculture 12, no. 6: 864. https://doi.org/10.3390/agriculture12060864
APA StyleYang, C., Chen, X., Sun, J., Wei, W., Miao, W., & Gu, C. (2022). Could Surplus Food in Blind Box Form Increase Consumers’ Purchase Intention? Agriculture, 12(6), 864. https://doi.org/10.3390/agriculture12060864