| Literature DB >> 31597262 |
Lan Li1, Gang Li2, Xiaoling Feng3, Zhigao Liu4, Fu-Sheng Tsai5,6,7.
Abstract
Repurchasing intention of agricultural materials is a key to a sustainable food business system. The novel contribution of this study is that we go beyond technical aspect and look into human capital dynamics in a general context, by examining how different dimensions of 'guanxi' (i.e., personal relations and instrumentality) between farmers and agricultural retailers affect trust between the two and, in turn, repeated purchase intention of agricultural materials by farmers in China. To further generate implications for food system as a whole, we also examined how dynamic environment moderates the effects mentioned above. Adopting survey method and multivariate analyses, this study tests the hypotheses with a collected data set of 578 farmers from representative rural areas of China. The results show that guanxi between farmers and agricultural retailers has a positive effect on trust between them and on repeated purchase intentions of farmers. While instrumentality has a negative effect on trust between them and on repeated purchase intentions of farmers. The trust between farmers and agricultural retailers promotes farmers' repeated purchase intentions. The intensity of competition negatively moderates the positive relation between trust and repeated purchases. Demand uncertainty does not moderate the positive effect of trust on repeated purchases. The results and discussion shed light on agricultural food system sustainability from a dynamic environment embedded business relationship perspective.Entities:
Keywords: agricultural food system; dynamic environment; guanxi; repeated purchase intention; trust
Mesh:
Year: 2019 PMID: 31597262 PMCID: PMC6801770 DOI: 10.3390/ijerph16193773
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Conceptual model.
Sample profile (%)
| Variables | Profile |
|---|---|
|
| |
| Male | 66.78 |
| Female | 33.22 |
|
| |
| ≤10 years | 23.9 |
| 11–30 years | 38 |
| ≥31 years | 38.1 |
|
| |
| Less literacy | 10.38 |
| Elementary school | 31.66 |
| Junior high school | 45.67 |
| High school/technical school | 11.07 |
| Diploma and above | 1.21 |
|
| |
| ≤25% | 50.9 |
| 26–50% | 27.8 |
| ≥51% | 21.3 |
|
| |
| ≤36 | 10.38 |
| 37–46 | 26.12 |
| 47–54 | 27.85 |
| 55–65 | 23.70 |
|
| |
| ≤10,000 | 25.78 |
| 10,000–30,000 | 47.58 |
| 30,000–60,000 | 19.55 |
| 60,000–90,000 | 3.80 |
| >90,000 | 3.29 |
Reliability and validity
| Scale | Factor Loadings |
|---|---|
|
| |
| When local farmers interact with sales staff in agricultural retail stores, they think each other is a friend of their own. | 0.725 |
| Local farmers are willing to help each other on non-work issues when they interact with sales staff at agricultural retail stores. | 0.712 |
| Local farmers often talk about some personal issues when they interact with salespeople in agricultural retail stores. | 0.627 |
| When local farmers interact with the sales staff of the agricultural retail store, even if the current buying and selling relationship is over, they will keep in constant contact with each other. | 0.736 |
| Local farmers think of each other as a circle when they interact with sales staff at agricultural retail stores. | 0.688 |
|
| |
| If local farmers are not buying agricultural materials (pesticide, fertilizer, seeds), they are not willing to contact agricultural retail stores. | 0.922 |
| I believe that if there is not a demand for agricultural materials, local farmers will not be willing to contact agricultural retail stores. | 0.922 |
|
| |
| Agricultural retail stores are committed to us. | 0.657 |
| We believe that the information provided by agricultural retail stores. | 0.775 |
| Agricultural retail stores really care about our agricultural harvest. | 0.753 |
| When making important decisions, the agricultural retail store will consider giving both-sides benefits. | 0.764 |
| We believe that agricultural retail stores are always concerned about our interests. | 0.696 |
| Agricultural retail stores are worthy of trust. | 0.764 |
|
| |
| The demand of local farmers in the agricultural retail industry is difficult to predict. | 0.754 |
| Local farmers in the agricultural retail industry always seek new differences. | 0.864 |
| The preferences of local farmers in the agricultural retail industry are always changing. | 0.877 |
|
| |
| There are many agricultural retail stores in the agricultural retail market that provide similar agricultural materials (pesticide, fertilizer, seeds). | 0.704 |
| Agricultural materials (pesticide, fertilizer, seeds) in the agricultural retail industry are changing rapidly. | 0.677 |
| The market competition of agricultural materials retail industry is very fierce. | 0.752 |
|
| |
| Local farmers will have more business dealings with agricultural retail stores in the future. | 0.763 |
| Local farmers will purchase new agricultural materials (pesticide, fertilizer, seeds) or new services provided by frequent agricultural retail stores. | 0.881 |
| Local farmers will buy more agricultural materials (pesticide, fertilizer, seeds) or services from frequent agricultural retail stores. | 0.873 |
Note. CR = construct reliability; AVE = Average Variance Extracted.
KMO and Bartlett sphericity test.
| KMO and Bartlett Sphericity Test | Personal Relations | Instrumentality | Trust | Demand Uncertainty | Competition Intensity | Repeated Purchase Intention | |
|---|---|---|---|---|---|---|---|
| Kaiser–Meyer–Olkin | 0.756 | 0.500 | 0.830 | 0.664 | 0.637 | 0.669 | |
| Bartlett sphericity test | Approximate chi-square distribution | 663.836 | 390.141 | 1189.210 | 530.125 | 183.003 | 571.656 |
| Freedom | 10 | 1 | 15 | 3 | 3 | 3 | |
| Significant probability | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | |
Correlation coefficient between statistical description and each research variable.
| Variables | Means | Standard Deviation | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|---|---|
| 1. Repeat purchase intention | 5.641 | 0.996 | (0.841) | |||||
| 2. Personal relations | 5.012 | 1.088 | 0.392 ** | (0.712) | ||||
| 3. Instrumentality | 4.001 | 1.665 | −0.137 ** | 0.095 | (0.922) | |||
| 4. Trust | 5.352 | 0.960 | 0.539 ** | 0.431 ** | −0.022 | (0.736) | ||
| 5. Demand uncertainty | 4.737 | 1.372 | 0.105 * | 0.236 ** | 0.160 ** | 0.144 ** | (0.834) | |
| 6. Competition intensity | 5.555 | 0.986 | 0.211 ** | 0.197 ** | 0.017 | 0.199 ** | 0.228 ** | (0.748) |
Note: The number of samples is N = 578; the value in parentheses on the diagonal is the square root of the mean variation extraction (AVE). The non-diagonal is the correlation coefficient of each variable, ** p < 0.01 means significant at 99% confidence, and * p < 0.05 means significant at 95% confidence.
Results of hierarchical regression.
| Variables | Trust (TR) | Repeat Purchase Intention (RI) | ||||
|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | |
| Personal relation (PR) | 0.437 *** | 0.215 *** | 0.203 *** | 0.203 *** | 0.205 *** | 0.204 *** |
| Instrumentality (IV) | −0.063 * | −0.148 *** | −0.148 *** | −0.149 *** | −0.153 *** | −0.153 *** |
| Trust (TR) | 0.443 *** | 0.431 *** | 0.430 *** | 0.810 *** | 0.820 *** | |
| Uncertainty in demand (DU) | −0.001 | 0.002 | 0.003 | 0.002 | ||
| Competition intensity (CI) | 0.088 ** | 0.088 ** | 0.475 *** | 0.486 *** | ||
| Uncertainty in demand × Trust | −0.017 | 0.008 | ||||
| Competition intensity × Trust | −0.601 ** | −0.616 ** | ||||
| R | 0.436 | 0.586 | 0.592 | 0.592 | 0.598 | 0.598 |
| R2 | 0.190 | 0.343 | 0.350 | 0.351 | 0.358 | 0.358 |
| ΔR2 | 0.187 | 0.340 | 0.345 | 0.344 | 0.351 | 0.350 |
| F | 67.465 | 99.950 | 61.734 | 51.418 | 52.960 | 45.325 |
Note: ***, p < 0.01; **, p < 0.05; *, p < 0.1.
Figure 2Moderation effect of demand uncertainty on the relationship between trust and repeated purchase intention.
Figure 3Moderation effect of competition intensity on the relationship between trust and repeated purchase intentions.
Results of hierarchical regression analysis (after selecting 300 samples)
| Variables | Trust (TR) | Repeated Purchase Intention (RI) | ||||
|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | |
| Personal relations (PR) | 0.441 *** | 0.239 *** | 0.236 *** | 0.235 *** | 0.245 *** | 0.244 *** |
| Instrumentality (IV) | −0.126 ** | −0.210 *** | −0.207 *** | −0.205 *** | −0.213 *** | −0.210 *** |
| Trust (TR) | 0.452 *** | 0.447 *** | 0.449 *** | −0.021 *** | 0.433 *** | |
| Uncertainty in demand (DU) | −0.026 | −0.033 | 0.068 | −0.031 | ||
| Competition intensity (CI) | 0.057 | 0.055 | 0.433 | 0.066 | ||
| Uncertainty in demand × Trust | 0.038 | 0.059 | ||||
| Competition intensity × Trust | −0.084 * | −0.096 ** | ||||
| R | 0.444 | 0.632 | 0.634 | 0.635 | 0.639 | 0.642 |
| R2 | 0.197 | 0.399 | 0.402 | 0.403 | 0.409 | 0.412 |
| ΔR2 | 0.192 | 0.393 | 0.392 | 0.391 | 0.397 | 0.398 |
| F | 36.530 | 65.474 | 39.529 | 33.022 | 33.756 | 29.210 |
Note: ***, p < 0.01; **, p < 0.05; *, p < 0.1.