| Literature DB >> 35250766 |
Jiaji An1, He Di1, Guoliang Liu1.
Abstract
Inappropriate social interactions of entrepreneurs can generate negative effects in the peer-to-peer lending market. To address this problem and assist peer-to-peer entrepreneurs in customizing their online interaction strategies, we used the cutting-edge cognitive-experiential self-system conceptual model and studied the relationship between peer-to-peer entrepreneurs' interactions and financing levels. Online interactive information was categorized as emotional or cognitive, adding the moderator of entrepreneur popularity, and the effect of these interactions on individual investors was analyzed. We found that the entrepreneurs' online interactive information affected psychological perception of entrepreneurs and their corresponding brand image. The interaction between popularity and interactive information types was significant. The findings imply that less popular entrepreneurs should engage in emotional interactions, while more popular entrepreneurs should choose cognitive interactions. Online interaction created comparative advantages in the financing activities of peer-to-peer companies. These results expand understanding of the psychological facets of the consumer-brand relationship in the digital world, and extend the current literature. This study also highlights key areas of learning and application for both practitioners and scholars of organizational psychology.Entities:
Keywords: entrepreneurship; individual investors; interaction behavior; online popularity; peer-to-peer lending; psychological perception
Year: 2022 PMID: 35250766 PMCID: PMC8895197 DOI: 10.3389/fpsyg.2022.825478
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
FIGURE 1Theoretical logic framework.
P2P lending platform sample statistics.
| Number | Enterprises | Entrepreneurs | Registered capital (million RMB) | Average loan duration (days) | Average interest rate |
| 1 | Renrendai | YANG | 2,000 | 244 | 10.20% |
| 2 | Niwodai | YAN | 550 | 360 | 10.80% |
| 3 | Eloancn | ZHANG | 1,000 | 360 | 10.24% |
| 4 | 5aitou | LIU | 535 | 360 | 9.60% |
| 5 | PPmoney | CHEN | 500 | 381 | 9.24% |
| 6 | Guangxindai | ZHANG | 500 | 360 | 11% |
| 7 | Yooli | ZHANG | 1,000 | 578 | 11.58% |
| 8 | Xiaoniu | PENG | 103 | 360 | 8% |
| 9 | XSjinfu | Yuan | 100 | 352 | 11% |
| 10 | HYJF | LIU | 500 | 182 | 7.11% |
| 11 | Lending51 | ZHANG | 500 | 180 | 11% |
| 12 | Gxyclub | LIN | 200 | 304 | 9.50% |
| 13 | 91wangcai | XU | 60 | 30 | 6% |
| 14 | Iqianjin | DONG | 1,000 | 304 | 12.83% |
| 15 | Hurbao | MENG | 60 | 100 | 10.33% |
| 16 | Juzilicai | XIAO | 510 | 477 | 11% |
| 17 | Xywj | TANG | 500 | 288 | 6.59% |
| 18 | Huilc | GUO | 50 | 210 | 11.30% |
| 19 | Jrjc | ZHANG | 66 | 180 | 9% |
| 20 | XSPH | ZHENG | 111 | 90 | 8% |
| 21 | CGN | LUO | 50 | 180 | 7.50% |
| 22 | Souyidai | ZHOU | 300 | 395 | 8.55% |
| 23 | BJDP2P | WEN | 142 | 103 | 7.28% |
| 24 | FYJF | LI | 50.4 | 65 | 5.56% |
| 25 | 51rzy | ZHONG | 100 | 90 | 9% |
| 26 | NNb | LIN | 100 | 730 | 12% |
| 27 | PHLC | LI | 50 | 177 | 9.17% |
| 28 | YYfax | WU | 70.4 | 720 | 8.20% |
| 29 | Qianlindai | HU | 100 | 90 | 9% |
| 30 | HYR | SONG | 500 | 785 | 11.83% |
| 31 | Niuyan | LUO | 118 | 91 | 8.52% |
| 32 | Myerong | LIN | 100 | 1,080 | 11% |
| 33 | TGJR | LI | 50 | 180 | 9% |
| 34 | CCD | LIU | 50 | 164 | 6.82% |
| 35 | WSD | Zhang | 50 | 90 | 10% |
| 36 | GLJR | YANG | 50 | 180 | 12% |
| 37 | XWJR | CHEN | 50 | 95 | 5.60% |
| 38 | BGNC | ZHENG | 120 | 462 | 7.44% |
| 39 | HJB | PAN | 50 | 53 | 12% |
| 40 | I2p | CHEN | 100 | 30 | 8% |
| 41 | JPB | GE | 100 | 90 | 9% |
| 42 | CTZR | ZHONG | 66.15 | 60 | 12% |
| 43 | ZYXR | LUO | 52.63 | 180 | 10% |
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Descriptive analysis.
| Title | Min. | Max. | Mean |
| LPC (thousand RMB) | 0.19 | 78.8 | 8.5 |
| TOI | 1 | 9 | 4.07 |
| POP (thousand people) | 24.3 | 3757.1 | 614.4 |
| NUM | 2 | 299 | 21.3 |
| TIM | 14 | 49 | 31.4 |
Regression analysis.
| Model 1 | Model 2 | |||
| Variables | Coefficient | Coefficient | ||
| Constant | 0.126 | 10.573 | 0.128 | 10.321 |
| TOI | –0.154 | –4.561 | –0.186 | –3.958 |
| POP | –0.017 | –5.903 | –0.016 | –6.362 |
| TOI*POP | 0.033 | 4.909 | 0.034 | 5.069 |
| TIM | 0.027 | 1.042 | ||
| NUM | 0.036 | 3.051 | ||
| Adjusted | 0.662 | 0.679 | ||
| Prob (F-statistic) | 0.000 | 0.000 | ||
**Represents significance at the 5% level.