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Frontiers of Business Research in China

Table 9 Changes in “nontraditional” financing products before and after the pandemic

From: How different types of financial service providers support small- and medium- enterprises under the impact of COVID-19 pandemic: from the perspective of expectancy theory

 

Goods/inventory pledged

Trade agency

Factoring

Financing based on taxation data analysis

Financing with insurance

Financing based on operational data mining

Financing with LC

Before the pandemic

3.86

1.63

4.22

0.86

0.96

2.36

1.13

During and after the pandemic

4.19

1.74

4.25

1.13

1.625

2.81

1.14

Changes

8.48%

7.01%

0.61%

31.76%

68.70%

18.97%

1.30%

p-value

0.168

0.787

0.638

0.017*

0.000***

0.004***

0.933

  1. The p values in the last line refer to the differences in FSPs’ financing attitude to each industry before and after the pandemic. The values in this table refer to the weighted score of the corresponding items in the Appendix of each type, reflecting the importance of each industry. The higher the value, the higher is the degree of importance. The weighted score of each item = ∑(frequency times weight)/the number of observations; the weight is determined by where the items are arranged. For example, if there are three items involved in sorting, then the item in the first position gets a weight of 3, the one in the second position gets a weight of 2, and the one in the third position weights 1
  2. Notes. *** p < 0.001, ** p < 0.01, * p < 0.1
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