Financial performance prediction model based on firms’ internal capability determinants: evidence from listed firms in Thailand during the transition period of going public

Figures & data

Table 1. A literature summary and research gap

Study	Determinants							Firm Performance				Timing Effect			Analysis Techniques
	Liquidity	Leverage	Cost of goods sold	Company size	Asset Utilization	Tangibility	Others^1	ROA	ROE	ROS	Others^2	Not Include	Calendar Year	Relative Transition Year
Majumdar (1997)	✓	✓		✓		✓	✓				✓		✓		Multiple Regression
Opler et al. (1999)					✓		✓					✓			T-Test and Multiple Regression
Harvey et al. (2001)		✓		✓		✓	✓				✓	✓			Regression
Lam (2004)	✓				✓		✓		✓				✓		Neural Networks
Pasiouras and Kosmidou (2007)	✓			✓			✓	✓				✓			Multiple Regression
Ghosh (2008)		✓		✓		✓		✓				✓			Multiple Regression
Ravi et al. (2008)	✓	✓					✓				✓		✓		Neural Network, Support Vector Machine
Liargovas and Skandalis (2010)	✓	✓		✓		✓	✓	✓	✓	✓		✓			Multiple Regression
Fazlzadeh et al. (2011)	✓	✓		✓			✓	✓			✓	✓			F-Test, T-Test, and Multiple Regression
Seema and Surendra (2011)	✓	✓					✓	✓	✓		✓		✓		Paired T-test and Independent T-Test
Almajali et al. (2012)	✓	✓		✓			✓	✓				✓			T-test and Multiple Regression
Muritala (2012)		✓		✓	✓	✓	✓	✓	✓			✓			Multiple Regression
Olson et al. (2012)			✓	✓	✓		✓				✓	✓			Logistic Regression, Decision Tree, Neural Network and Support Vector Machines
Wan Yusoff and Alhaji (2012)							✓		✓		✓		✓		Spearman’s Correlation Matrix
Babalola (2013)	✓	✓		✓			✓	✓				✓			Multiple Regression
Ghafoorifard et al. (2014)				✓							✓	✓			Linear Regression
Abor (2005)		✓		✓					✓			✓			Multiple Regression
Banafa et al. (2015)		✓						✓			✓	✓			T-Test
Bongoye et al. (2016)	✓			✓		✓	✓	✓				✓			T-Test
Park and Guahk (2017)		✓			✓		✓	✓	✓	✓	✓	✓			Multiple Regression
Altaf and Shah (2018)	✓	✓		✓			✓	✓			✓	✓			Multiple Regression
Ahmed and Afza (2019)	✓	✓		✓		✓	✓	✓	✓		✓	✓			Multiple Regression
Le Thi Kim et al. (2021)	✓	✓		✓	✓		✓		✓	✓		✓			Linear Regression and Blinder–Oaxaca decomposition analysis
Nasrallah and El Khoury (2022)				✓			✓	✓			✓	✓			Multiple Regression
This Study	✓	✓	✓	✓	✓	✓		✓	✓	✓				✓	Logistic Regression and Multiple Regression

Remarks: (1) Other determinants include Competitive intensity, Risk, Growth opportunity, Company age, Investment and management efficiency, etc.

(2) Other financial performances include Sales, Net profit, Tobin’s Q, Return on Investment, Earnings before Interest and Taxes and etc.

Figure 1. Timeline Overview.

Table 2. Number of firms as classified by industry groups

Industry group	No. of firms
Agro & Food Industry	12
Consumer Products	5
Industrials	16
Property & Construction	43
Resources	14
Technology	21
Total	111

Table 3. Number of new listed firms in each year

Year	No. of firms
2014	12
2013	6
2012	3
2011	2
2010	3
2009	4
2008	7
2007	5
2006	8
2005	24
2004	23
2003	14
Total	111

Table 4. Definition of dependent variable

Dependent Variable		Definition
Firm financial performance	Combination of ROA, ROE, ROS	ROA + ROE + ROS
	ROA	Net income/Total assets
	ROE	Net income/Total shareholders’ equity
	ROS	Net income/Total sales

Table 5. Definitions of independent variables

Independent Variable		Definition
Firm financial strengths	Liquidity	Total current assets/Total current liability	X1
	Leverage	Total liabilities/Total assets	X2
	COGS	Cost of goods sold/Total sales	X3
Firm characteristics	Asset utilization	Total sales/Total assets	X4
	Tangibility	Total fixed assets/Total assets	X5
	Company size	ln(Total assets)	X6

Figure 2. Conceptual framework.

Table 6. Pearson’s correlation coefficient of the case with one year before becoming public firms

Condition	Liquidity	Leverage	Cost of goods sold ratio	Asset utilization	Tangibility	Company size
Liquidity	1
Leverage	−0.201	1
Cost of goods sold	−0.040	0.207	1
Asset utilization	−0.201	−0.075	0.357	1
Tangibility	−0.232	−0.141	−0.245	−0.101	1
Company size	−0.048	−0.095	0.046	−0.043	0.352	1

Figure 3. Error assumptions of the multiple regression model for one year before becoming public firms.

Table 7. MAPE of each multiple regression model

Relative Year	MAPE
One year before	42.28%
One year after	48.96%
Two years after	45.16%
Three years after	49.04%
Four years after	48.47%

Table 8. Accuracy rates of logistic models

Relative Year	2-group	3-group	4-group
One year before	78.95%	61.05%	58.95%
One year after	80.00%	63.00%	52.00%
Two years after	74.03%	59.74%	44.16%
Three years after	89.25%	65.59%	52.69%
Four years after	78.57%	69.05%	64.29%
Average	80.16%	63.69%	54.42%

Figure 4. The impact of liquidity on predicted performance.

Figure 5. The impact of leverage on predicted performance.

Figure 6. The impact of COGS on predicted performance.

Figure 7. The impact of asset utilization on predicted performance.

Figure 8. The impact of tangibility on predicted performance.

Figure 9. The impact of company size on predicted performance.

Table 9. Status of the firm in each scenario

Factors	Firms
	A	B	C
Liquidity	1.7	1.2	0.7
Leverage	0.9	0.7	0.5
COGS	0.7	0.8	0.9
Asset Utilization	0.9	0.7	0.5
Tangibility	0.9	0.7	0.5
Company Size	23	22	21

Table 10. Range variation of each factor

Variation Range
Liquidity	0–3
Leverage	0–1
COGS	0–1
Asset Utilization	0–1
Tangibility	0–1
Company Size	20–25

Table 11. Financial data of firm Z

Source	Financial Data	Value (million baht)
Selected data from the balance sheet	Current Assets	700
	Non-current Assets	1,000
	Total Assets	1,700
	Current Liabilities	600
	Non-current Liabilities	300
	Total Liabilities	900
Selected data from the income statement	Sales	1,000
	Cost of Goods Sold	800

Table 12. Status of firm Z

Factors	Values
Liquidity	1.167
Leverage	0.529
COGS	0.8
Asset Utilization	0.588
Tangibility	0.588
Company Size	21.254

Table 13. Financial data of firm Z after the investment

Source	Financial Data	Value (million baht)
Selected data from the balance sheet	Current Assets	660
	Non-current Assets	1,400
	Total Assets	2,060
	Current Liabilities	600
	Non-current Liabilities	700
	Total Liabilities	1,300
Selected data from the income statement	Sales	1,000
	Cost of Goods Sold	800

Table 14. Status of firm Z after the investment

Factors	Values
Liquidity	1.1
Leverage	0.631
COGS	0.8
Asset Utilization	0.485
Tangibility	0.679
Company Size	21.445

Table 15. Financial data of firm Z after the investment and the increase in sales

Source	Financial Data	Value (million Baht)
Selected data from the balance sheet	Current Assets	660
	Non-current Assets	1,400
	Total Assets	2,060
	Current Liabilities	600
	Non-current Liabilities	700
	Total Liabilities	1,300
Selected data from the income statement	Sales	1,300
	Cost of Goods Sold	1,040

Table 16. Status of firm Z after the investment and the increase in sales

Factors	Values
Liquidity	1.1
Leverage	0.631
COGS	0.8
Asset Utilization	0.631
Tangibility	0.679
Company Size	21.445

Figure 10. The financial performance prediction tool (input part).

Figure 11. The financial performance prediction tool (output part).

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