Are we ready for climate risk? Assessing the bottom-up climate maturity

Figures & data

Figure 1. The upward trend of Climate Change Risk Research in scopus.

Table 1. The descriptive statistics of organizational context

Sector	Frequency	Percent
Service	34	17
Industrial	30	15.0
Financial Institution	21	10.5
Real Estate	20	10.0
Agro & Food	19	9.5
Resources & Energy	16	8.0
Consumer Product	15	7.5
Technology & Innovation	6	3.0
Others	39	19.5
Total	200	100.0
Size given staff #	Frequency	Percent
0–500	105	52.5
501–1,000	33	16.5
1,001–1,500	13	6.5
1,501–2,000	10	5
>2,000	39	19.5
Total	200	100.0
Respondent Positions	Frequency	Percent
Manager	98	49
Staff Level	96	48
Management & Board	6	3
Total	200	100.0

Table 2. ANOVA of 3 cluster to show the significant climate adaptation and mitigation across maturity level

Zscore	F statistics	Significant
Zscore (Adaptation)	349.1	0.0
Zscore (Mitigation)	743.75	0.0

Table 3. The result of overall maturity level from clustering

Maturity Level	Definition	Number of Firm
High	Both adaptation and mitigation of Climate risk are well implemented.	33
Medium	Firms have just started to realize is climate risk.	53
Low	Firms have not started yet to realize in climate risk	114
Total		200

Table 4. Maturity Level Across Company Size

Maturity Level	Company Size (Staff Number)
	0–500	501–1,000	1,001–1,500	1,501–2,000	>2,000	Total
High	11	4	2	2	14	33
Medium	18	6	6	7	16	53
Low	76	23	5	1	9	114
Total	105	33	13	10	39

Table 5. Maturity level across sectors

Sectors	High Maturity	Medium Maturity	Low Maturity
Agro & Food	3	10	6
Consumer Product	2	6	7
Industry	6	10	14
Financial Institution	2	3	16
Real Estate	2	5	13
Service	1	7	26
Resources & Energy	11	3	2
Technology & Innovation	1	3	2
Others*	5	6	28
Total	33	53	114

As shown in Table 4, a large company has higher climate maturity than does a small company. Conversely, most of the small-sized companies (76/105), where the number of staff is less than 500, perceive a low climate maturity. In addition, the energy sector, which directly relates to most GHG emissions, has the highest maturity. Conversely, nearly all the service sectors are low in maturity.

Figure 2. Linearity testing.

Table 6. Testing normality and multicollinearity

Variables	VIF	Skewness and Kurtosis
Climate Governance	4.4	(0.62, −0.87)
Climate Strategy	7.2	(0.61,-0.73)
Climate Risk Management	8.1	(0.73, −0.65)
Climate Metric	4.8	(0.81, −0.69)
Maturity of Climate Risk	Not Test for Dependent Variable	(0.63,-1.4)

Table 7. ANOVA of determinants and maturity of climate risk

Variables	Sectors (Sig)	Company Size (Sig)
Climate Governance	0.001	0.026
Climate Strategy	0.001	0.043
Climate Risk Management	0.005	0.005
Climate Metric	0.000	0.002
Maturity of Climate Risk	0.000	0.000

Table 8. Overall model fit

MDA Function	Wilks’ Lambda (Sig)	Canonical Correlation
1	0.000	0.839
2	0.561	0.102

Table 9. Determinants size effect

Factor	Tests of Equality of Group Means (Sig)	Standardized Canonical Discriminant Function Coefficients
Climate Governance	0.000	0.070
Climate Strategy	0.000	0.205
Climate Risk Management	0.000	0.191
Climate Metric	0.000	0.663

Table 10. Classification results

	Predicted Group Members
	Maturity	Low	Medium	High	Total
Case	Low	35	5	13	53
	Medium	9	24	0	33
	High	10	1	103	114
Percent	Low	66.0	9.4	24.5	100
	Medium	27.3	72.7	0	100
	High	8.8	0.9	90.3	100

Figure 3. Proposed conceptual framework.

Table 11. Refined model with MDA Stepwise

Variable in the Analysis	Variable not in the Analysis
Climate Metric	Climate Governance
Climate Strategy	Climate Risk Management

Case Studies.

Figure 4. Proposed policy recommendation Model.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon request.