# Experimental Study on the Risk Preference Characteristics of Members in Supply Chain Emergencies
## 3 Results
### Data Analysis of Experiment 2  
Through the statistics of the turning points of all subjects, all (\(\alpha\), \(\sigma\)) combinations were obtained, and the means of \(\alpha\) and \(\sigma\) were calculated. The mean was the coefficient that measured the risk preference degrees of the subjects. Specifically, in the supplies emergency scenario, the turning point values of 26 groups' (\(\alpha\), \(\sigma\)) combinations with no time pressure and 38 groups' (\(\alpha\), \(\sigma\)) combinations with time pressure were obtained. The mean of (\(\alpha\), \(\sigma\)) with no time pressure was (0.909, 0.917), and the mean of (\(\alpha\), \(\sigma\)) with time pressure was (0.702, 0.798). This shows that supply chain members tended to avoid risks with no time pressure in emergencies, and the degree of risk aversion was weakened with time pressure. Figure 1 shows the turning point distribution of the subjects. The numbers on the coordinate axes represent the turning points of series 1 and 2, and the height of each cone represents the number of subjects at the turning points. The black areas indicate the turning point of \(\alpha=1\), which describes the situation of risk aversion. As can be seen from the figure above, the turning points with no time pressure were more densely distributed near the black areas; the turning points with time pressure were more dispersed and were far from the black areas. It is shown that the risk preference of subjects tended to be in the state of risk aversion with no time pressure, and the degree of risk aversion was strong. However, the subjects gradually weakened their risk aversion with time pressure. It should be noted that the risk appetite coefficient in this experiment with no time pressure was quite different from the values estimated by [PERSON] (1996), who took residents of South Asian countries, and [PERSON] (2008) (2018) (2018) (2018). who took Chinese farmers as subjects. As shown in Table 6, the risk preferences of decision makers were also different when there were differences in, e.g., the decision-making scenario, market environment, personal knowledge structure, and economic income. Influenced by the market economy for many years, Chinese supply chain members have become more risk-averse, and their economic behavior and maturity are gradually improving. The coefficients of risk preference with \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Risk** & **Risk** & **Risk** & **Risk-** & **Risk** & **Risk** & **Risk** & **Risk-** \\
**Areas** & **Neutrality** & **Aversion** & **Seeking** & **Areas** & **Neutrality** & **Aversion** & **Seeking** \\ \hline Morality & 231 & 41 & 60 & Demand & 232 & 48 & 52 \\ Law & 228 & 60 & 44 & Cooperation & 212 & 60 & 60 \\ Information & 209 & 67 & 56 & Economy & 235 & 53 & 44 \\ Supply & 228 & 64 & 40 & Politics & 220 & 52 & 60 \\ Logistics & 212 & 60 & 60 & Emergency & 215 & 57 & 60 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The distribution of risk preferences in the supply chain risk field. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **Total Risk** & **Risk Aversion** & **Total Risk** & **Risk Seeking** & **Total** & **All** \\
**Aversion** & **or Neutrality** & **Neutrality** & **or Neutrality** & **Risk** & **Three** \\  & & & & & **Seeking** & **Have** \\ \hline Total & 0 & 92 & 44 & 104 & 0 & 92 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Risk preference distribution of individuals in the supply chain risk fields. time pressure in this experiment were smaller than those obtained by [PERSON] [24] (2015), who took Chinese students as subjects in an emergency environment, as shown in Table 7. It should be noted that unlike the student participants, the subjects were employees of a supply chain. As a result, it shows that the decision-making behavior of Chinese supply chain economies did not reflect a high degree of risk aversion, regardless of time pressure or the lack thereof.