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Business Valuation and Internationalization of Listed Companies in Nigeria
- Folajimi F. Adegbie
- Nelson Okutu
- 315-
- Mar 5, 2023
- Business Administration
Business Valuation and Internationalization of Listed Companies in Nigeria
Folajimi F. Adegbie & Nelson Okutu*
Department of Accounting, School of Management Sciences, Babcock University, Ilishan-Remo, Ogun State, Nigeria.
*Corresponding Author
Abstract
Insiders and outsiders frequently have competing interests in international corporations. The complexity of information and monitoring foreign operations raises the costs associated with multinational corporations’ bonding activities. One of the significant events is that equity holders now take value away from minority shareholders. The objective of the study is to study the effect of business valuation on the internationalization of listed companies in Nigeria. The second objective is to assess the effect of moderating effect of firm size on the effect of business valuation and internationalization of listed companies in Nigeria. The study adopted a secondary dataset through the use of purposive sampling technique to select the eleven (11) companies listed on the Nigeria Group exchange from 2011 to 2020. The research, however, used a panel regression analysis which consists of Pooled ordinary least square (OLS) with Cluster Std. Error. The study found that the asset approach insignificantly positively affected internationalization. Income approach and firm age insignificantly and negatively affected internationalization. Also, the market approach significantly and negatively affected the internationalization of listed companies in Nigeria. The study concluded that business valuation significantly affected the internationalization of listed companies in Nigeria (Adj. R square = 0.219; F(3,126) = 13.09, and p-value = 0.000). The result implied that there is a competitive structure to which the companies belongs in that new market. Therefore, the study recommended that management should pursue internationalization strategies to generate economies of scale and achieve resource efficiency.
Keywords: Asset Approach, Business Valuation, Income Approach, Internationalization, Market Approach
Introduction
Many organizations look for ways to develop their businesses and operate in the international market because it is one of the ways businesses secure more profit in the long run (Reim et al., 2022). Businesses operating in a global market used to differ significantly from conventional business practices, and in some cases, necessitates a change in the company’s business model (Child, Narooz, Hsieh, Elbanna, Karmowska, Marinova, Puthussery, Tsai, & Zhang, 2022).
Insiders and outsiders frequently have competing interests in international corporations. Because of the complexity of information and the monitoring of foreign operations raises the costs associated with multinational corporations’ bonding activities (Tsao & Chen, 2010). Equity holders now take value away from minority shareholders. Multinational corporations play an important role in business evaluation to improve industrial production and country development (Glonti, Manvelidze & Surmanidze, 2021; Reim, Yli-Viitala, Arrasvuori, & Parida, 2022).
Internationalization adds more versatility to the market system, galvanizes the industry’s financial means by reducing monopoly trends, promoting scientific-technological progress, and is a crucial component in evaluating the business. The transformation and evaluation of the business to a market approach are becoming more intense and vital for company growth (Chitanava, 2018). The value of a company’s assets, liabilities, and equity are determined by its valuation, which is solely based on how likely it is to make a profit. The size, location, and sector of the economy in which a company operates can all impact its value.
Meanwhile, extensive studies have been conducted on business valuation and internationalization. The studies proved that most studies conducted in this line of research used internationalization as an independent variable (Attia, 2016; Benito et al., 2016; Chen, 2021; Shchelokova & Shuan, 2022; Shuan, 2020; Wei et al., 2019; Zhang et al., 2022). Most researchers have not considered internationalization a dependent variable measured with foreign shares to total shares. Researchers considered business valuation from the aspect of the asset approach and some from the aspect of the income approach. Few researchers have combined all the proxies this research considered (asset approach (Agarwal, 2021; Kim & Kwon, 2022; Yildiz, 2021; Zhang et al., 2013), income approach, and market approach) to explain or investigate the effect of internationalization. Several questions are upstretched in this article by answering how business valuation affects the internationalization of companies whose headquarters or branches are in Nigeria.
The global market is, however, a dynamic market, and internationalization of a firm through any entry model represents a change in the way business are operating. According to Schneider and Spieth (2013) and Lee, Shin and Park (2012), the effects of increasing globalization in the business valuation are a driver of a firm’s need to innovate its business model. The business valuation that effectively supports a company’s competitive advantage in one market may face competition in another. As a result, business valuation must be innovated or adapted tobetter fit specific international market contexts (Landau, Karna, & Sailer 2016).
The primary corporate goal of all international companies in developing countries such as Nigeria is to create shareholder value. Top executives are well aware of the company’s shareholders’ power. Stakeholder positioning has always been influenced by the spread of shareholder value and the formation of various company partners (Bancel, 2010). Though investors want to increase their portfolio diversification and return as a result of the advice they receive on international assets, they are always confronted with the issue of higher transaction costs, current volatility, and liquidity risks, which is why potential investors are often afraid of investing in international businesses (Mansa, 2022). Internationalization of business and global marketing issues have an impact on the marketing environment and the company’s marketing activities. Thus, the research investigated the effect of business valuation on the internationalization of listed companies in Nigeria using variables such as asset approach, income approach, and market approach to determine business valuation and foreign sales to total sales to measure internationalization. To solve the research objectives, another aspect of the article is structured into four sections. Section 2 reviews past studies relating to business valuation and internationalization. Section 3 shows the details of the materials and methods used. The result and discussion of findings explained in Section 4, followed by the conclusion and recommendation in Section 5.
Literature Review and Theoretical Framework
Conceptual Review
Internationalization
Internationalization is a global determinant of business valuation. It is used to describe the complex entity, theories, and frameworks that have been developed to characterize the process of company expansion into the international market. In other words, it refers to a company that takes steps to increase its footprint or capture greater market share outside of its country of domicile by branching out into international markets.
It is defined as a company expanding into foreign markets in order to gain a larger market share. Ribau et al. (2018) defined internationalization as the process and terms under which firms engage in activities to gain access to foreign markets. It is also known as the process of increasing one’s involvement in international operations (Welch & Luostarinen, 1988).
Business Valuation
Business valuation is defined in the field of business as the process of determining the economic value of a company. The value of a business is determined by a variety of factors, including sales value, establishing partner ownership, and proceedings. The theory is applied when a company wishes to sell all or a portion of its operations, merge with, or acquire another company. It could include an examination of the company’s management, capital structure, and asset market value. Evaluators, businesses, and industries all use different tools for valuation. A review of financial statements, discounting cash flow models, and similar company comparisons are common approaches to business valuation.
Theoretical Review
Internationalization Theory
Buckley and Casson developed the internationalization theory in 1976, and Johansson and Mattson established it in 1988 when they researched and thoroughly discussed internationalization theory. The theory assumes that firms learn by gaining market experience, which becomes a source of increased confidence and market commitment over time. Except when failure to perform in that market indicates a need to retreat, it is a model of increasing commitment. Different authors have employed the use of internationalization theory using different topics relating to this research paper. The study of Rugman and Verbeke (2003) adopted the theory to explain internalization and strategic management perspectives. The study was used to establish the extending theory of multinational enterprises. Oviatt and McDougall (1997) also use the theory to explain the case of international new ventures. Their study focused on the challenges of adopting this theory. However, the theory is relevant to this research due to its support for internationalization firms. It is obvious that successful international companies articulate their desire for growth and demonstrate the efficiency of their operations by testing and venturing into foreign operations. Many of these businesses prevent the idea of local top teams by venturing offshore and across borders, making internationalization appropriate for this study.
Valuation Theory
Valuation theory started in 1912 by the Hungarian mathematician, Josef Kurschak who formulated the valuation axioms and was propounded by William Stanley Jevons, Lean Walras, and Carls Menger in the late 19th century. The motive behind the theory is to provide the solid foundation for the theory of p-adic fields as explained by Kurt Hensel. The theory observed a quick development of valuation theory, triggered mainly by the discovery that much of algebraic number theory could be better understood by using valuation theoretic notions and methods. The theory is based on shareholder value and dividend discount which explained the future stream of cash flow in multinational enterprises. The limitation of the theory is to relate the cash dividends to earnings, an accrual accounting flow, and the capital structure of the funding effects. The theory has been used by Berger, Eechambadi, George, Lehmann, Rizley, and Venkatesan (2006) to explain the customer lifetime value to shareholder value using a theoretical and empirical approach. Hence, the research is relevant to this paper because it knows an accurate value for businesses and will impact the current financial well-being of companies.
Theoretical Framework and Research Hypotheses
In the research of Kim (2018), internationalization is the geographic location expansion of a country’s economic activities beyond its national borders. Internationalization can e explained from the economic approach and how international activities are related to large multinational companies. Theoretically, the international can be described using three main theories, which include monopolistic advantage theory, eclectic theory, and internalization theory, as identified by Ruzzier, Hisrich and Antoncic (2006). Among the three theories, the internationalization theory of a multinational corporation is the most appropriate theory and the underpinning theory. The theory is used because it focuses primarily on large multinational corporations and their investment, which resulted in a large body of theoretical and empirical information. Also, most of the companies are selected because they have a company in Nigeria and foreigners from different countries could invest in them. Hence, two different hypotheses are formulated as thus:
H01: Business valuation has no significant effect on the internationalization of
listed companies in Nigeria.
H02: Firm age moderately affects the effect of business valuation and internationalization
of listed companies in Nigeria.
Empirical Review
Empirical Review
Few researchers have studied the effect of business valuation and internationalization of listed companies in Nigeria; an instance is the study of Zhang, Yang, and Wang (2022), who explained the concept of enterprise internationalization from Western China using evidence of listed companies. The study was based on enterprise value, trademark internationalization, and enterprise Internationalization. In their study, the researchers used a dataset from 2010 to 2019 to show how the extent of internationalization affects the level of trademark value using descriptive statistics, correlation analysis and multiple regression analysis. The study discovered that trademark internationalization level positively impacted enterprise value while the extent of internationalization negatively impacted value. Research carried out by Wei, Lin, and Gan (2019) on the degree of internationalization and performance of industry-specific companies found a similar result to the research of Zhang et al. (2022), where Wei et al. (2019) discovered that internationalization negatively impacted the company performance.
In China, Zhou (2017) demonstrated the effect of internationalization on performance using the dataset from Chinese-listed manufacturing firms between 2001 to 2014. The paper found that internationalization negatively affects performance even though it was related. Similarly, Zhou (2018) collected a dataset from China stock market using 535 manufacturing firms. The study found a similar result where he concluded that internationalization and performance are related and shaped in overall samples. Chen and Tan (2012) used 887 firms for nine years and found that internationalization significantly varies within the greater China region, Asia, and outside Asia.
The article of Tsao and Chen (2010) found mixed results in this research by discovering the ownership concentration and showing an insight into corporate governance’s role in internationalization. Attia (2016) used evidence from Jianhuai Automobile in the Anhui province of China to explain how internationalization policies on Chinese state-owned performance. Mixed dataset were adopted and thereby concluded that state-owned companies (STOEs) in China enabled the government to improve its performances and gave better policies and future prospective on reforms. Benito, Rygh, and Lunnan (2016) used panel data to explain the dataset of Norwegian firms collected from 2000 to 2010, thereby showing that STOEs have no evidence of reducing the benefits of internationalization. Cuervo-Cazurra and Li (2020) found mixed results by concluding how STOEs related to balancing stakeholder demand, how STOEs and government affected the political systems, and how home and host countries’ governments impacted the dynamics of state-owned multinationals.
Other studies related include Su, Song, and Guo (2022), who explored foreign ownership, tax preference and firm performance. Using multiple regression analysis, the article explored datasets from A-share listed firms in China between 2011 and 2017. The study discovered that tax preference positively relates to foreign-funded firm investment, and foreign-funded firm investment and shareholding positively impacted firm performance. Chen, (2021) investigated the Internationalization of Chinese STOEs under multiple institutional complexities. Shuan (2020) and Shchelokova and Shuan, (2022) used the Kazakhstan market to explain the internationalization strategy of Chinese STOEs oil companies.
In addition, researchers worked on foreign shareholders and some other variables. The study of Setiawan, Christiana, and Singh (2020) investigated foreign institutional shareholders and corporate pay-out policy. In Japan, Lida (2019) examined foreign shareholders and corporate governance. Park, Chae, and Cho (2016) controlled the shareholders’ ownership structure using foreign investors’ monitoring and investment efficiency and thereby found that investment efficiency reduced as the control ownership wedge significantly improved. Cui, Ding, Han, and Suardi (2022) illustrated the description of foreign shareholders, relative foreign policy uncertainty and corporate cash holdings. The paper found that a negative and significant relationship is caused by firms’ precautionary and transactional motives, as foreign investors perceive lower corporate risk and better investment opportunities in host country firms.
Guvenen, Mataloni, Rassier, and Ruhl (2022) used United States multinational enterprises between 1982 to 2016. The study discovered that adjusting for profit shifting reduces the trade deficit by lowering the return on US foreign direct investment (FDI) abroad, which increases productivity growth rates in the late 1990s and early 200s and lowers labour share of income. Augustine Umezurike, Gervase Iwu, and Asuelime (2016) demonstrated the socio-economic implications of South Africa’s FDI in Southern African development. The study used the documentary analysis method, which enabled the authors to source and uses documents from private and public domains based on their relevance to the research.
Diouf and Hai explain the impact of FDI and trade on Africa’s Economic Growth (2017). Ahiakpor, Brafu-Insaidoo, Obeng, and Wiafe (2017) used a Bayesian model selection approach to describe Ghana’s FDI and export performance. The paper discovered that domestic savings, trade liberalization, and infrastructure development have a more significant impact on export performance than FDI inflows. Scholars who worked on FDI and asset approach include Agarwal (2021), Zhang, Chau, and Xie (2012), Zhang, Zhang, and Zhang (2013), Kim and Kwon (2022) and many others.
In an emerging market, Yildiz (2021) looked ta foreign institutional investors, information asymmetries and asset valuation. The scholar clarified that the paper is essential for comprehending the investment behaviour of foreign institutional investors in an emerging market with high information asymmetries between investor groups. Furthermore, the findings shed light on how IFRS adoption and boardroom internationalization play a role in reducing information asymmetries within the firm. Diyarbakirlioglu (2011b) explained foreign equity flows, the size Bias, and the evidence from an emerging stock market. Diyarbakirlioglu (2011a) investigated the domestic and foreign country bias in international equity portfolios.
Kim, Wu, Schuler, and Hoskisson (2019) worked on Chinese multinationals; fast internationalization using financial performance advantages and disadvantages. The paper used a dataset from 767 publicly listed companies for thirteen (13) years to find the fast-mover Chinese multinational enterprises. The study concluded by suggesting a framework that integrates internationalization speed and home regionalization literature. Serrano, Fernández-Olmos, and Pinilla (2018) used an approach of agricultural foods firms to explain the concept of internationalization and performance. Alon, Anderson, Munim, and Ho (2018) reviewed studies on the Internationalization of Chinese and thereby discovered four research streams, including testing traditional FDI theory, entry mode, location, and internationalization motivations and drivers. Hence, this research would consider using panel regression analysis to investigate the effect of business valuation on internationalization.
Methodology
The panel research design was adopted to explain the effect of business valuation and internationalization. A time frame of ten (10) years, the 2011 to 2020 dataset, was used through the use of secondary source of data, indicating that the use of already proceed data from the annual report of the Nigeria Group Exchange (NGX). Using the purposive sampling technique, a sample size of eleven (11) companies listed on the Nigeria Group Exchange (NGX) was selected. The multinational companies were selected based on the fact that companies have either branches or headquarters in Nigeria, and they include PZ Cusson, Nestle Nigeria, Flour Mill, Cadbury Nigeria, Guaranty Trust Bank (GTB), First City Momentum Bank (FCMB), United Bank for Africa (UBA), Zenith Bank, Lafarge PLC, Dangote PLC, First Bank of Nigeria PLC, Unilever PLC, and Guinness Nigeria. Meanwhile, the validity of the dataset was confirmed by proper checking of the obtained dataset.
Figure 1: Conceptual Framework
Source: Author’s Conceptual Model
Data Analysis Techniques
Descriptive and inferential techniques of the analysis dataset were adopted, and the inferential method was used to test the formulated research hypotheses. The inferential statistics used include bivariate analysis and multivariate analysis. The bivariate analysis (Pearson product-moment coefficient) was used to test whether the proxies of business valuation are highly correlated, while multivariate analysis (panel regression analysis) was conducted to determine the predictive nature of business valuation and internationalization. Regarding the diagnostic test, the Hausman test, in conjunction with Testparm, was used to choose the most appropriate technique among the fixed effect model, random effect model and Pooled ordinary least square regression analysis. The model was also tested using heteroskedasticity and serial correlation analysis.
The regression model adopted for this study is given as:
In the model above, represents constant, is the coefficient of the independent variables, represents the coefficient of the control variable (firm age), ASTA = asset approach, INMA = income approach, MKTA = market approach, FA = firm age, INT = internationalization, = residual term, i = the number of international companies and t = period. Meanwhile, ASTA is measured using return on the asset; INMA is measured using return on capital employed; MKTA is measured using market share; INT is measured using foreign sales to total shares, and FA is measured using the year of establishment.
Results, Analysis and Discussion of Findings
This paper analyzed the series in the distribution for descriptive statistics and multicollinearity problem, and the regression analysis tested the hypotheses. The result of the summary statistics, interpretation, and discussions are demonstrated in Tables 1, 2 and 3 accordingly. Eleven (11) companies were used to analyze the panel regression analysis with ten (10) years of the dataset. Using descriptive statistics, the minimum age of a company is two years, which happened to be Dangote in 2011 and the oldest company is Guinness, 56 years. The company’s average age is 31 years, indicating that most companies’ age is greater than 16.
The average benchmark of multinational companies located in Nigeria is 17.9 million, with a negative minimum value of -18.661 million and a maximum income of 108.184. Also, multinational companies have an average value of 5.643 million, a minimum value of -43.34 million and a maximum value of 26.34 million. The market approach showed an average value of 8.165 million, a minimum value of 7.444 and the maximum value of 9.015 million. The range of foreign sales to total sales revealed an average value of 32.082 million, with minimum sales of 0.057 million and maximum sales of 83.81 million.
Table 1: Summary Statistics
Variables | Minimum | Maximum | Std. dev | Mean |
Business Valuation | ||||
ASTA | -43.34 | 26.49 | 8.422 | 5.643 |
INMA | -18.661 | 108.184 | 20.842 | 17.907 |
MKTA | 7.444 | 9.015 | 0.371 | 8.165 |
Control Variable | ||||
FA | 2 | 56 | 16.353 | 31.269 |
Internationalization | ||||
Foreign Sales to Total Sales | 0.057 | 83.81 | 29.884 | 32.082 |
*** Number of Observations = 110.
Source: Author’s Computation, 2022.
The bivariate analysis explains the presence of multicollinearity among the proxies of business valuation, the values of the correlation matrix are less than the benchmark of 0.8, as suggested by Baltagi (2021), the most negligible correlation value is -0.003, and the highest correlation value is 0.673. The bivariate analysis results are confirmed by the variance inflation factor (VIF), showing the mean value of 1.49, which is the lower benchmark of 5. Thus, the paper concluded that the issue of multicollinearity does not occur in the proxies of business valuation, as displayed in Table 2.
Table 2: Analysis of the Multicollinearity Test
ASTA | INMA | MKTA | FA | VIF | 1/VIF | |
ASTA | 1.000 | 1.97 | 0.507 | |||
INMA | 0.673 | 1.000 | 1.88 | 0.532 | ||
MKTA | 0.163 | 0.054 | 1.000 | 1.05 | 0.955 | |
-0.172 | -0.003 | -0.148 | 1.000 | 1.07 | 0.935 | |
Mean VIF | 1.49 |
VIF indicated Variance inflation factor
Source: Author’s Computation, 2022
Regression Analysis
Table 3 presents the panel regression analysis using the Hausman test as a diagnostic test. It showed a significant result of the p-value of 0.019 < 0.05 (5% significance level), negating the null hypothesis of the Hausman test, indicating that the fixed effect model is consistent and appropriate for the analysis. Choosing between a fixed effect model and pooled regression analysis, testparm was adopted. The result failed to reject the null hypothesis, indicating fixed effect is not required in this analysis. Hence, Pooled OLS is a consistent and appropriate statistical tool for model one.
In the same way, the Hausman test of model two was significant (p-value = 0.046), revealing that a fixed effect is appropriate. The result of the testparm indicated that the null hypothesis was not rejected. Pooled OLS is also appropriate and consistent for model two. Furthermore, the two models are heteroscedastic, indicating that no residuals vary over time, and the models have serial correlation problems.
Models, one and two are estimated using Pooled ordinary least square with cluster standard errors given the models as thus:
The probability value of model one showed that the asset approach insignificantly affected internationalization, the income approach insignificantly affect internationalization, and the market approach significantly affect internationalization. Firm age was used as a control variable to make hypothesis 2 (model 2). The result of the probability value of model 2 was similar to that of model 1 and it was shown that firm age insignificantly affected internationalization .
Model one, coefficient value of the proxies of business valuation ASTA; INMA, and MKTA, revealed that the asset approach positively affects internationalization while income approach and market approach negatively affect internationalization. The magnitude of the effect of ASTA revealed that per cent increase in internationalization, while the magnitude of the effect of INMA per cent) and MKTA per cent) decreased internationalization. Additionally, the joint variability of the proxies of business valuation yielded a 21.9% variation in internationalization, while the remaining 78.1% changes in internationalization are caused by factors not considered in model one. Hence, at the level of significance 0.05 and the degree of freedom 3, the F statistics is 13.09, while the p-value of the F statistics is 0.000 which is lower than 0.05 (5% significance level) adopted level of statistics, therefore the study reject the null hypothesis which means business valuation significantly affected the internationalization of listed companies in Nigeria.
As presented in Table 3, firm age is used as a control variable, representing model two of the research studies. The coefficient value of ASTA; INMA; MKTA , and FA. The analysis showed that the asset approach positively affected internationalization, while the income approach, market approach and firm age negatively affected internationalization. The joint variability of the explanatory variable (business valuation) yielded a 21.3% variation in the internationalization of listed companies in Nigeria. The remaining part, 78.7% of changes in internationalization, is caused by factors not considered in the model. At a level of significance 0.05 and the degree of freedom 4, the F statistics is 9.74, while the p-value of the F statistics is 0.000 which is lower than 0.05 (5% significance level) adopted level of statistics, therefore, the study reject the null hypothesis which means that firm size moderately affects business valuation and internationalization of listed companies in Nigeria.
Table 3: Regression results for the test of business valuation and internationalization
Model One | Model Two | |||||||
Pooled OLS with Cluster Std. Error | Pooled OLS with Cluster Std. Error | |||||||
Coeff | Std. Error | T-stat | P-value | Coeff | Std. Error | T-stat | P-value | |
Constant | 347.769 | 51.912 | 6.70 | 0.000 | 348.484 | 53.195 | 6.55 | 0.000 |
ASTA | 0.663 | 0.379 | 1.75 | 0.082 | 0.658 | 0.389 | 1.69 | 0.093 |
INMA | -0.026 | 0.151 | -0.17 | 0.864 | -0.024 | 0.154 | -0.16 | 0.874 |
MKTA | -39.067 | 6.366 | -6.14 | 0.000 | -39.116 | 6.434 | -6.08 | 0.000 |
FA | -0.010 | 0.148 | -0.07 | 0.947 | ||||
Adj. R square | 0.219
F(3, 126) = 13.09 0.000 Chi2(3) = 9.95 (0.0190) F (9, 105) = 0.58 (0.808) Chi2(1) = 1.85 (0.174) F(1, 12) = 16.355 (0.002) |
0.213 | ||||||
F stat | F(4, 126) = 9.74
0.000 Chi2(4) = 9.68 (0.046) F (9, 105) = 0.58 (0.808) Chi2(1) = 1.76 (0.185) F (1, 12) = 15.443 (0.002) |
|||||||
Prob (F Stat) | ||||||||
Hausman Test | ||||||||
Testparm Test/LM Test | ||||||||
Heteroskedasticity Test | ||||||||
Serial Correlation Test |
Source: Author’s Computation, 2022.
Discussion of Findings
The models showed that the null hypothesis is rejected at p-value (0.000) < 0.05 (5% significance level), indicating that business valuation significantly affects the internationalization of listed companies in Nigeria. Also, the second model revealed that firm age moderately affected the effect of business valuation and internationalization of listed companies in Nigeria. Model one and model two showed no difference among the proxies of business valuation despite introducing a control variable, firm age, to the proxies of business valuation.
The result of the two models, as displayed in Table 3, showed that model one is better than model two, despite introducing a controlling variable. The controlling variable shows little effect between business valuation and internationalization of listed companies in Nigeria. The study findings supported the research of Zhang et al. (2022), indicating that trademark internationalization impacted enterprise value. The research of Wei et al. (2019) also impacted the company’s performance. Other research related to these findings that found a significant effect includes the paper of Zhou (2017), which found that internationalization affected performance. Chen and Tan (2012) also found that internationalization varied within the China region within Asia and outside Asia.
Comparing the result of the multinational companies with the oil and gas companies showed a consistent result, indicating that Shchelokova and Shuan, (2022) found that internationalization affected Chinese STOEs. The research of Kim et al. (2019) discovered that internationalization speeds home regionalization literature. Contrarily to this research finding, the report of Benito et. al., (2016) showed that there is no evidence of reducing the benefits of internationalization.
Conclusion and Recommendations.
The study has shown that business valuation significantly affected the internationalization of listed companies in Nigeria. The three approaches of business valuation considered showed mixed results. ASTA revealed a positive effect on INT, while INMA and MKTA showed a negative effect on INT. The result of model one and model two of the research paper is similar even though firm age was added to model one. Based on the findings, the paper revealed that business valuation significantly affected the internationalization of listed companies in Nigeria. Thus, the paper suggested that Internationalized companies should be strategic to understand how well a company generate profit from its capital as it is put to use. Investors tend to favour companies with stable and rising returns on capital employed, which will increase investors’ income and aid the company’s performance.
Contribution to Future Research
The paper will assist the policymakers, the management, and the investors to contribute significantly towards the decision-making of their companies in order to improve the business valuation of the companies. The study would also contribute to the existing literature by evaluating the measurement of business valuation through the use of the income approach, market approach, and asset approach.
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Appendix
Companies | YEAR | ROCE | ROA | MS | FSTS | FA |
PZ Cusson | 2011 | 17.297 | 8.270 | 7.819 | 69.773 | 38 |
PZ Cusson | 2012 | 10.555 | 3.940 | 7.858 | 68.765 | 39 |
PZ Cusson | 2013 | 15.458 | 7.360 | 7.853 | 69.773 | 40 |
PZ Cusson | 2014 | 14.306 | 7.160 | 7.863 | 69.773 | 41 |
PZ Cusson | 2015 | 14.640 | 6.780 | 7.864 | 70.949 | 42 |
PZ Cusson | 2016 | 7.914 | 2.860 | 7.842 | 70.949 | 43 |
PZ Cusson | 2017 | 10.691 | 4.090 | 7.901 | 73.275 | 44 |
PZ Cusson | 2018 | 6.225 | 2.170 | 7.906 | 73.275 | 45 |
PZ Cusson | 2019 | -1.017 | 1.450 | 7.871 | 73.275 | 46 |
PZ Cusson | 2020 | -18.661 | -9.230 | 7.826 | 73.275 | 47 |
Nestle Nigeria | 2011 | 41.346 | 21.220 | 7.991 | 63.300 | 33 |
Nestle Nigeria | 2012 | 42.172 | 23.760 | 8.067 | 63.480 | 34 |
Nestle Nigeria | 2013 | 37.605 | 20.570 | 8.124 | 63.480 | 35 |
Nestle Nigeria | 2014 | 48.019 | 20.960 | 8.156 | 63.480 | 36 |
Nestle Nigeria | 2015 | 57.480 | 19.910 | 8.180 | 63.480 | 37 |
Nestle Nigeria | 2016 | 87.354 | 4.670 | 8.260 | 66.177 | 38 |
Nestle Nigeria | 2017 | 88.327 | 22.970 | 8.388 | 66.177 | 39 |
Nestle Nigeria | 2018 | 88.807 | 26.490 | 8.425 | 66.177 | 40 |
Nestle Nigeria | 2019 | 108.184 | 23.620 | 8.453 | 66.177 | 41 |
Nestle Nigeria | 2020 | 81.175 | 15.930 | 8.458 | 66.496 | 42 |
Flour Mill | 2011 | 25.549 | 8.550 | 7.532 | 41.521 | 3 |
Flour Mill | 2012 | 16.677 | 6.010 | 7.581 | 53.293 | 4 |
Flour Mill | 2013 | 15.547 | 5.130 | 7.660 | 47.414 | 5 |
Flour Mill | 2014 | 17.121 | 5.250 | 7.741 | 47.414 | 6 |
Flour Mill | 2015 | 7.389 | 1.650 | 7.691 | 52.176 | 7 |
Flour Mill | 2016 | -5.126 | -3.980 | 7.707 | 52.176 | 8 |
Flour Mill | 2017 | 10.592 | 3.800 | 7.726 | 33.393 | 9 |
Flour Mill | 2018 | 9.808 | 3.550 | 7.854 | 54.695 | 10 |
Flour Mill | 2019 | 4.114 | 0.050 | 7.872 | 55.030 | 11 |
Flour Mill | 2020 | 6.195 | 0.460 | 7.906 | 62.952 | 12 |
Cadbury Nigeria | 2011 | 25.810 | 10.910 | 7.533 | 74.999 | 36 |
Cadbury Nigeria | 2012 | 24.320 | 8.600 | 7.526 | 74.999 | 37 |
Cadbury Nigeria | 2013 | 26.023 | 13.950 | 7.553 | 74.971 | 38 |
Cadbury Nigeria | 2014 | 9.929 | 5.250 | 7.485 | 74.972 | 39 |
Cadbury Nigeria | 2015 | 9.290 | 4.060 | 7.444 | 74.972 | 40 |
Cadbury Nigeria | 2016 | -3.500 | -1.040 | 7.477 | 74.972 | 41 |
Cadbury Nigeria | 2017 | 5.652 | 1.060 | 7.520 | 74.972 | 42 |
Cadbury Nigeria | 2018 | 10.406 | 2.990 | 7.556 | 74.972 | 43 |
Cadbury Nigeria | 2019 | 8.139 | 3.720 | 7.595 | 74.972 | 44 |
Cadbury Nigeria | 2020 | 2.184 | 2.810 | 7.549 | 74.972 | 45 |
GTB | 2011 | 11.198 | 3.090 | 8.102 | 12.726 | 16 |
GTB | 2012 | 17.561 | 5.000 | 8.231 | 19.991 | 17 |
GTB | 2013 | 15.857 | 4.280 | 8.268 | 22.327 | 18 |
GTB | 2014 | 15.778 | 4.190 | 8.302 | 10.743 | 19 |
GTB | 2015 | 13.202 | 3.940 | 8.360 | 25.896 | 20 |
GTB | 2016 | 14.612 | 4.240 | 8.419 | 28.194 | 21 |
GTB | 2017 | 15.534 | 5.090 | 8.515 | 42.111 | 22 |
GTB | 2018 | 21.273 | 5.620 | 8.487 | 34.907 | 23 |
GTB | 2019 | 18.894 | 5.240 | 8.465 | 34.907 | 24 |
GTB | 2020 | 16.588 | 4.070 | 8.460 | 21.964 | 25 |
FCMB | 2011 | 24.041 | -1.540 | 7.940 | 14.973 | 8 |
FCMB | 2012 | 8.404 | 1.660 | 7.940 | 14.762 | 9 |
FCMB | 2013 | 6.205 | 1.590 | 8.007 | 62.741 | 10 |
FCMB | 2014 | 5.497 | 1.890 | 8.072 | 41.539 | 11 |
FCMB | 2015 | 1.691 | 0.410 | 8.092 | 38.717 | 12 |
FCMB | 2016 | 3.169 | 1.220 | 8.097 | 31.498 | 13 |
FCMB | 2017 | 2.310 | 0.790 | 8.230 | 28.900 | 14 |
FCMB | 2018 | 3.026 | 1.050 | 8.120 | 25.619 | 15 |
FCMB | 2019 | 2.775 | 1.040 | 8.138 | 25.887 | 16 |
FCMB | 2020 | 2.735 | 0.950 | 8.179 | 13.488 | 17 |
UBA | 2011 | -8.218 | -0.490 | 8.055 | 10.079 | 42 |
UBA | 2012 | 14.429 | 2.470 | 8.176 | 9.882 | 43 |
UBA | 2013 | 11.652 | 1.760 | 8.269 | 9.882 | 44 |
UBA | 2014 | 9.479 | 1.730 | 8.294 | 9.882 | 45 |
UBA | 2015 | 10.203 | 2.170 | 8.369 | 12.600 | 46 |
UBA | 2016 | 3.755 | 2.060 | 8.422 | 11.275 | 47 |
UBA | 2017 | 7.878 | 1.930 | 8.513 | 10.888 | 48 |
UBA | 2018 | 7.021 | 1.610 | 8.560 | 11.232 | 49 |
UBA | 2019 | 6.283 | 1.590 | 8.607 | 11.232 | 50 |
UBA | 2020 | 6.521 | 1.480 | 8.631 | 6.252 | 51 |
Zenith | 2011 | 24.349 | 2.520 | 8.213 | 6.909 | 8 |
Zenith | 2012 | 48.091 | 4.700 | 8.345 | 13.859 | 9 |
Zenith | 2013 | 30.969 | 3.620 | 8.415 | 16.737 | 10 |
Zenith | 2014 | 9.836 | 2.650 | 8.496 | 16.277 | 11 |
Zenith | 2015 | 8.669 | 2.640 | 8.542 | 20.372 | 12 |
Zenith | 2016 | 8.925 | 2.740 | 8.585 | 23.125 | 13 |
Zenith | 2017 | 9.431 | 3.180 | 8.676 | 23.859 | 14 |
Zenith | 2018 | 10.228 | 3.250 | 8.644 | 18.062 | 15 |
Zenith | 2019 | 11.671 | 3.290 | 8.619 | 19.739 | 16 |
Zenith | 2020 | 0.823 | 2.720 | 8.624 | 20.239 | 17 |
Larfarge | 2011 | 11.125 | 5.660 | 7.796 | 58.000 | 33 |
Larfarge | 2012 | 22.196 | 9.680 | 7.944 | 58.000 | 34 |
Larfarge | 2013 | 26.108 | 17.550 | 7.995 | 58.000 | 35 |
Larfarge | 2014 | 18.159 | 11.330 | 8.314 | 72.738 | 36 |
Larfarge | 2015 | 10.994 | 5.960 | 8.427 | 76.313 | 37 |
Larfarge | 2016 | -2.240 | 3.360 | 8.342 | 72.589 | 38 |
Larfarge | 2017 | 3.753 | -5.990 | 8.476 | 71.352 | 39 |
Larfarge | 2018 | 8.066 | -1.630 | 8.489 | 76.320 | 40 |
Larfarge | 2019 | 9.059 | 3.120 | 8.328 | 83.810 | 41 |
Larfarge | 2020 | 12.454 | 6.080 | 8.363 | 83.810 | 42 |
Dangote | 2011 | 29.032 | 23.060 | 8.383 | 0.064 | 2 |
Dangote | 2012 | 27.697 | 22.550 | 8.475 | 0.064 | 3 |
Dangote | 2013 | 28.427 | 23.860 | 8.587 | 0.064 | 4 |
Dangote | 2014 | 28.954 | 16.200 | 8.593 | 0.064 | 5 |
Dangote | 2015 | 26.657 | 16.320 | 8.692 | 0.064 | 6 |
Dangote | 2016 | 22.282 | 12.210 | 8.789 | 0.064 | 7 |
Dangote | 2017 | 29.885 | 12.260 | 8.906 | 0.064 | 8 |
Dangote | 2018 | -10.752 | 23.040 | 8.955 | 0.064 | 9 |
Dangote | 2019 | 27.748 | 11.520 | 8.950 | 0.064 | 10 |
Dangote | 2020 | 34.990 | 13.650 | 9.015 | 0.057 | 11 |
FBN | 2011 | 3.946 | 0.650 | 8.328 | 0.162 | 43 |
FBN | 2012 | 11.805 | 2.370 | 8.458 | 0.162 | 44 |
FBN | 2013 | 9.697 | 1.820 | 8.510 | 0.217 | 45 |
FBN | 2014 | 7.190 | 1.910 | 8.559 | 0.217 | 46 |
FBN | 2015 | 1.800 | 0.360 | 8.598 | 0.084 | 47 |
FBN | 2016 | 1.406 | 0.360 | 8.608 | 0.084 | 48 |
FBN | 2017 | 2.715 | 0.910 | 8.672 | 0.147 | 49 |
FBN | 2018 | 3.136 | 1.070 | 8.638 | 0.147 | 50 |
FBN | 2019 | 3.846 | 1.190 | 8.646 | 0.077 | 51 |
FBN | 2020 | 2.996 | 0.980 | 8.585 | 0.077 | 52 |
Unilever | 2011 | 63.229 | 17.100 | 7.738 | 0.601 | 39 |
Unilever | 2012 | 64.398 | 15.340 | 7.745 | 0.601 | 40 |
Unilever | 2013 | 51.580 | 10.990 | 7.778 | 0.601 | 41 |
Unilever | 2014 | 34.463 | 5.270 | 7.746 | 0.601 | 42 |
Unilever | 2015 | 31.933 | 2.380 | 7.773 | 0.601 | 43 |
Unilever | 2016 | 36.003 | 4.240 | 7.844 | 0.601 | 44 |
Unilever | 2017 | 17.322 | 6.150 | 7.958 | 0.760 | 45 |
Unilever | 2018 | 14.914 | 6.930 | 7.968 | 0.760 | 46 |
Unilever | 2019 | -14.427 | -7.160 | 7.782 | 0.760 | 47 |
Unilever | 2020 | -6.894 | -43.340 | 7.792 | 0.760 | 48 |
Guiness Nigeria | 2011 | 48.017 | 19.440 | 8.092 | 0.540 | 47 |
Guiness Nigeria | 2012 | 36.962 | 13.410 | 8.066 | 0.540 | 48 |
Guiness Nigeria | 2013 | 30.285 | 9.800 | 8.088 | 0.540 | 49 |
Guiness Nigeria | 2014 | 18.668 | 7.230 | 8.038 | 0.540 | 50 |
Guiness Nigeria | 2015 | 20.993 | 6.380 | 8.074 | 0.540 | 51 |
Guiness Nigeria | 2016 | 8.015 | -1.470 | 8.009 | 0.540 | 52 |
Guiness Nigeria | 2017 | 15.112 | 1.320 | 8.100 | 0.540 | 53 |
Guiness Nigeria | 2018 | 14.118 | 4.380 | 8.155 | 0.540 | 54 |
Guiness Nigeria | 2019 | 8.681 | 3.410 | 8.119 | 0.540 | 55 |
Guiness Nigeria | 2020 | -14.999 | -8.730 | 8.019 | 0.540 | 56 |