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Effect of income diversification on the financial performance of quoted manufacturing firms in Nigeria

Corporate diversification is a center of research in strategic management and finance. Many firms are experiencing a decline in their traditional activities' dues to environmental challenges, including competition, inadequate infrastructural facilities, and economic instability. The study examines the effect of income diversification on the financial performance of quoted manufacturing firms in Nigeria. Specifically, it determines the impact of product income segment diversification and non-product income segment diversification on quoted manufacturing firms' financial performance in Nigerian. The study adopted an ex-post facto research design using secondary data of 42 firms from the 63 quoted manufacturing firms in Nigeria for 11 years (2007-2017) period. Structural equation modeling (SEM) is utilized for data analysis. The study found that both product income segment diversification and non-product income segment diversification significantly affect the financial performance (ROA and ROCE variables) of quoted manufacturing firms in Nigeria. The study concluded that quoted manufacturing firms' financial performance in Nigeria is significantly affected by product income segment diversification and non-product income diversification. The study recommended that manufacturing firms should strategically diversified to increase their income generation in both the product segment and non-product segment to improve their financial performance.


Introduction
Today's business environment is characterized by uncertainty, dynamism, volatility, and hypercompetition, forcing firms, including manufacturing firms, to stumble on new ways of furthering their growth and development drives. Additionally, the current economic situation presents a challenging business atmosphere for corporate firms operating in Nigeria. Though the nation is the largest market hub of Africa, decades in physical infrastructures, especially roads and electricity, corruption, and bureaucratic bottleneck affect firms' growth rate. To worsen the situation, the country's primary revenue drive (crude oil) is experiencing backwardness, making many critical sectors, including the manufacturing sector to be devastated and reducing revenue generation. Many firms are strategically expanding beyond their traditional operational activities to overcome this awful situation. One financial performance of the manufacturing firms' financial performance in Nigeria. The study seeks to provide answers to the following research questions: -How does product-income diversification affect the financial performance of quoted manufacturing firms in Nigeria? -To what extent does non-product-income diversification impact the financial performance of quoted manufacturing firms in Nigeria? The study will provide firms in developing nations, particularly, Nigeria access to an empirical study conducted in their peculiar business environment, and the findings therein would guide them in formulating strategies and making relevant investment decisions to optimize competitive advantage. The findings will also help managers evaluate their strength for better diversification in the highly complex market conditions and environmental instability. Furthermore, the findings would be relevant to government agencies, especially the Capital Markets, the Securities and Exchange Commission, and the Ministry of Finance in developing policies, programs, and regulations related to corporate firm performance management to maximize investment returns. Shareholders and investors would guide by the finding in improving their understanding of strategic decisions made by firms relating to investment and expansion.
The study adopted an ex-post facto research design using secondary data from annual reports and archives of forty-two (42) firms selected among the sixty-three (63) quoted manufacturing firms in Nigeria for 11 years (2007-2017 period). Structural equation modeling (SEM), a multivariate statistical analysis technique and extension of the general linear model (GLM) used in analyzing complex structural relationships, models, and regression equations simultaneously, was used for data analysis. The principal finding is that income diversification has a significant effect on quoted manufacturing firms' financial performance in Nigeria. The study's significant contribution is the utilization of path analysis of the structural equation model to investigate the constructs against regression analysis, correlation analysis, chi-square, and T-test. The study has also contributed to the existing body of literature by exposing the income and non-income dimensions of corporate diversification.
The article is structure into five (5) sections, namely, introduction, literature review, data and method, results and discussion, and conclusion. The introduction section summarizes the motivation for the study, the purpose of the study, and its significance. The literature review provides a conceptual and theoretical background for the study as well as gaps from previous studies. The data and method section entails information on the study design, population, sample, data sources, and data analysis methods. The results and discussion section describe the results and interpret them in the context of earlier studies. The last section, the conclusion, summarizes the findings, and outline implications, limitations, and potential directions for further research.

Conceptual Framework
The firm's diversification and performance are extensively discussed in corporate finance and strategic management literature, and several arguments are advances due to their complex nature (Akkermans, 2010). The majority of diversification definitions center on the notion that diversification finds its root from the word diverse, indicating diversity (Pitts & Hopkins, 1997). Riswan and Suyono (2016) define corporate diversification as an extension into many various market segments of a successful business. Ramanujam and Varadarajan (1989) see diversification as operating in several different businesses simultaneously by a corporation or an organization's entrance to new operating systems through the strategic expansion process or acquisitions. Moreover, diversification of business is a way of extending its reach, gaining an economy of scale, and producing synergistic impacts on the entire process.
According to Njuguna (2013), diversification can be a concentric, conglomerate, internal, and external. Concentric diversification occurs when a business adds similar goods or markets to create a competitive match that enables it to create cohesion and significantly more excellent performance. Conglomerates Diversification happens when a firm broadens its activities against its traditional activities to increase efficiency via corporate marketing or production collaboration. Internal diversification includes selling existing goods in emerging markets by widening the business's geographical capacity, including new consumers (either inside its homeland or in foreign markets), as well as attracting new buyers for product offerings that are new in existing markets. External diversification happens via mergers and acquisitions, where a corporation ventures beyond its existing activities and purchases access to new products or markets. The basic idea in diversification is to increase the firms' income or earnings by developing different products or services and operating in different markets or geographical locations. Accordingly, Wan et al. (2016) opine that diversification of income is the rise of revenue streams or the portion of equilibrium between the various sources, which is commonly acknowledged as a means of self-insurance but not a temporary phenomenon that is merely linked to survival. Wan et al. (2016) argued that enhancing the degree of revenue diversification allows both the amount of earning operations and each variable's volume distribution to differ. Therefore, a company with two revenue sources will be more diversified than one with only one source, and revenue diversification is also used to characterize expansion in the significance of business operations beyond the traditional activities (Daud et al . , 2018).
Income diversification relates to the degree of diversification, which concerns diversification based on a continuous measure or as a business or product count measure (Pitts & Hopkins, as cited in Datta, Rajagopalan, andRasheed, 1991 &Doaei et al., 2015). While Product-income is the revenue generated from the companies' products' sales, Non-product-income diversification is the revenue generated from other companies' business activities. Companies have started leveraging nonconventional income-generating channels to the point of institutionalizing it as a strategic business unit. Recently, half of the revenue of banks in the U.S. is derived through non -conventional operations, and this represents not only a diversification of banks into non -conventional operations but also a change in the way banks make income (DeYoung & Rice, 2004). When manufacturing firms seek to diversify their income streams, they look at activities outside their product line. Specifically, a firm dealing with different products might diversify into providing services that will generate more income. Manufacturing firms are expanding their income generation by engaging in nontraditional activities (non-products segments) from traditional activities (product segments).
On the other hand, performance often relates to efficiency and effectiveness, although firm performance's multidimensional measurement exists. There are numerous scholarships that degree firm performance through a sole indicator (uni-dimensional concept), and researchers are advised to use the dimension(s) most relevant to the study (Santos & Brito, 2012). Financial performance is often confused with organizational effectiveness, and this has to be clarified. While organizational efficiency includes other facets of the organization's functioning, such as the absence of internal tension and defects, involvement in permissible operations, the procurement of resources, and the achievement of specified objectives; financial success refers to a subset of organizational efficiency that includes operating and economic results (Cameron in Santo & Brito, 2012). One common and most acceptable way of viewing firm performance is from the viewpoint of stakeholder theory that makes it possible to differentiate among performance referents and results; suggests a framework to identify performance metrics and measurements; and suggests time as well as input feature choices (Santo & Brito, 2012). The stakeholder theory gives the company's priorities a different viewpoint and, to a degree, clashes with the economic view of maximizing profit. Under this principle, performance measurement requires identifying stakeholders and evaluating the collection of performance results that assess overall satisfaction (Connolly, Conlon, & Deutsch;Hitt;& Zammuto in Santo & Brito, 2012). Investors often used the superiority of firms' financial performance (Cho & Pucik, 2005;Venkatraman & Ramanujam, 1986), reflected by profitability, growth, and market value. Profitability reflects the previous capacity of a business to produce gains; growth reflects the firm's previous capacity to expand its size, and market value describes the external appraisal and anticipation of the potential success of businesses. Palich, Cardinal, and Miller (2000) posit that diversification literature typically used these two types of performance measures (accounting and market-based measure). Whereas accounting measures provide an evaluative referent (ex-post), market-based measures are more future-oriented measures (ex-ante) of the firms' prospects and are considered as a more long-run perspective (Dubofsky & Varadarajan, 1987). Accounting measures are appreciated because they reflect realized performance and not affected by shareholders' anticipations (Covas, 2004). The major disadvantages of the accounting-based measure of performance are that it can be manipulated to some extent by management, its inability to reflect future risk or opportunities due to its evaluative character, and it is not well suitable to compare across countries as each country has its accounting standards (Fisher & McGowan, 1983;Ramanujam & Varadarajan, 1989;Barney, 1997;& Covas, 2004). Market measures do not share any of these drawbacks; however, management primarily depends on accounting data when making strategic decisions, limiting the use of solely market-based measures. Furthermore, accounting-based measures reflect realized performance, which might measure the actual and realistic effect of diversification on performance during different situations, including crisis years. Additionally, share prices tend to follow accounting data announcements, which underline the relevance of accounting-based measures (Holzmann, Copeland & Hayya; & Fama & Miller in Akkermans, 2010).
The conceptual model in figure 1 depicts the relationship between income diversification and firms' financial performance. The input factor (income diversification) is conceptualized in two major constructs: product-income and non-product-income segment. The interaction of these diversification constructs with organization factors such as structure, culture, system, and competence, and industry factors such as a change in technology, barrier to entry, growth, concentration, and capital intensity has an impact on the performance of the organization (financial performance) measured in terms of return on assets, return on equity and return on capital employed.

Theoretical Framework
This research is focused on the modern portfolio theory introduced by Markkowitz (1952), as cited in Hsien (2012), which relies on the principle of diversification to investigate were to estimate the overall benefit of a portfolio by choosing an appropriate ratio of assets based on a specified volume of portfolio risk. Modern portfolio theory (MPT) or mean-variance analysis is a statistical method for constructing an asset portfolio, whereas a specified aspect of risk maximizes the anticipated gain. It represents and expands investment diversification in which it is less risky to own various kinds of financial assets than to own one kind only. Its central insight is that the risk and return of an asset should not be measured by itself, but by how it relates to the overall risk and return of a portfolio. Thus, by keeping a diversified portfolio of assets, investors can reduce their vulnerability to specific asset risk. When applied by Stiroh and Rumble (2006), modern portfolio theory gives interest income and non-interest income making undertakings as two distinct assets, just as this study treats product income and non-product income diversification as two diverse asset variables.

Empirical Framework
Hsien (2012) examines the influence of income diversification on Islamic banks' success in Malaysia, Saudi Arabia, Kuwait, the United Arab Emirates, Bahrain, and Qatar, wherein they function in a double banking structure besides traditional banks. From 1997 to 2009, accounting data was taken from 68 traditional and 42 Islamic banks. Using various empirical approaches and Panel data regressions, the study finds that both non-financing income segmentation and financing income segmentation have positively influenced financial performance. Although the study was carried out in the non-manufacturing sector (banks) outside Nigeria, its focus on diversification generally and generated income as a measure for diversification specifically significantly influences this study. Also, Waithira (2013) investigates the effects of revenue diversification (interest and non-interest) income on commercial banks' financial performance in Kenya. The study used descriptive design, secondary data (audited financial statements) of the six largest and most profitable commercial banks in Kenya for the period 2008 to 2012 to draw its conclusion. The study also used the regression model and chi-square to test the significance of the study variables. The finding reveals a significant impact and relationship between income diversification variables (financial and non-financial income) and financial performance (return on asset).
Similarly, Stiroh and Rumble (2006) examine whether Prospective diversification benefits justify why U.S. financial investment firms provide an increasing variety of financial services. The study explicitly investigated whether the observed change towards fee-generating, trading revenue, and other non-interest income-generating activities improved the performance of U.S. financial holding companies (FHCs) through regression analysis between 1997 and 2002. The study's main finding is that the cost of increased exposure to risky activities is more than offset by diversification gains, reflecting the dark side of the quest for diversification benefits and having consequences for administrators, managers, investors, and borrowers. Furthermore, Senyo, Olivia, and Musah (2015) conducted a study on income diversification in the Ghanaian banking sector by testing the association amongst banks' non-interest income and profits from 2002 to 2011. The research observed that the largest contributor to the banks' profits remains interest income. Revenue from non-interest sources was also found to have a growing role in periods of short drops in interest revenue. Lastly, Doaei, Anuar, and Ismail (2015) investigated the two dimensions of corporate diversification (product and international diversification) on firms' efficiency jointly. The exciting part of the study is that product diversification is measure in terms of income measured (H.H. index). The findings demonstrate a negative relationship between product diversification and efficiency, international diversification and efficiency, and corporate diversification and efficiency.

Design and Population of the Study
The study adopts an ex-post facto research design because the data required for the study was collected from annual reports and accounts of the companies under investigation. Thus, the study's phenomenon had already taken place, and the data are in existence, making it a quantitative and deductive research approach that sourced data from secondary sources. The data for the period (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017) are gathered from the annual reports and accounts of the manufacturing firms quoted on the Nigerian stock exchange. This study's population covers all the quoted manufacturing firms by the Nigerian stock exchange (NSE). According to the NSE Fact Book (2017), there are sixty-three (63) firms in five (5) sub-sectors of the manufacturing industry (Table I). Manufacturing firms are significantly involved in the production and distribution of goods used by many of the masses, making it one of the Nigerian economies' critical industries. Besides, the firms share similarities in assets and liabilities. Quoted firms are selected because they are legally expected to publish their annual reports, which provide reliable and valid data for any empirical investigation.  (2016) A judgmental sampling technique was used to select 42 firms for the study. The judgmental or purposive sampling technique allows the researcher to select sample elements or representatives of the population to provide reliable and valid information to answer the research questions and meet research objectives. In this study, not all 63 firms (study population) provide reliable and valid data required to make a reasonable conclusion because of truncated data within the study period. Thus, nine firms that are not listed within the study period and 12 firms without required data for the study are automatically excluded from the study, while the remaining 42 constituted the study's sample size.

Sources of Data
The study used secondary data from annual reports and archives of manufacturing firms listed by the Nigeria Stock exchange (NSE) for the study period. The period 2007 to 2017 is a recent period that witnesses significant economic and political developments. The world economic meltdown of 2007/2008, the oil boom period of 2011-2013, Nigeria's recession of 2014-2016 due to the collapse in crude oil prices, and different elections that produced three different democratically elected governments are few examples. Data's reliability and validity are functions of the method by which the data were collected, and the source is otherwise known as the Authority or Reputation of the source (Dochartaigh, 2002). Thus, NSE that authored the fact book from which the study's data was sourced, is an authorized body that provides valid and reliable information on listed firms in Nigeria.

Operationalization of Variables
The study uses two sets of variables: the exogenous and endogenous variables. Endogenous variables which are equivalent to dependent variables in the regression models are proxies as Return on Assets (ROA), Return on Equity (ROE), and Return on Capital Employed (ROCE). The Exogenous variables which are always independent in the SEM equations are product income segment diversification and non-product income segment diversification.
Three main measures are usually used for diversification: Standard Industrial Classification (SIC) codes, Herfindahl or H.H. index, and Entropy Index. While SIC code is a system of identifying business base on activities, the H.H. index is the total square of the sale share of each product of the firm, and the Entropy index includes three significant elements that differentiate it from others indexes; namely, the number of the industry of firm's activities, the number of total sales/assets divide across industry parts, and the power of the part of related and unrelated diversification in a firm (Doaei et al., 2015). H.H. index is commonly used to measure income diversification since it is directly related to the income generated by firms through regular sales. The H.H. measure is defined as ΣiPi2/ (ΣiPi)2, where Pi is the proportion of segment sales over the total sales of the firm. However, determining the proportion of segment sales here in Nigeria is difficult because of firms' lack of disclosure. Therefore, the firms' revenue is directly used in this study divided into product income segments and nonproduct income. While non-income diversification is determined by the total revenue generated from all business activities less total sales revenue (Total Revenue -Sales Income), income diversification is determined by the total sales revenue less revenue from other business activities (Total Revenue less non-sale income).
This study utilizes accounting-based methods of Return on Assets, Return on Equity, and Return on Capital Employed as the measurements (proxies) of financial performance as follows: Return on Assets (ROA): Return on Assets (ROA) an accounting-based performance indicator that arrests the efficiency of resource allocation via a firm operation (Waddock & Graves, 1997). ROA also soundly captures management's ability to utilize assets effectively as it is not affected by the way assets are financed, which is more relevant to diversification study as it may reveal possible diversification inefficiencies (Libby, Libby & Short, 2010). This is the most commonly used success indicator in prior diversification research (Wang & Chang, 2006;Ernest & Jooh, 2010;Adamu, Zubairu, Ibrahim, & Ibrahim, 2011). The proportion of net income (income accessible to ordinary shareholders) to the book value of total assets is ROA. It is expressed as: ROA = X 100. (1)

Return on Equity (ROE):
The proportion of net income (income available to ordinary shareholders) to shareholders' equity is the ROE indicator. From the perspective of stockholders, it is an indicator of a firm's success. Return on equity (ROE) is a metric commonly utilize to measure top management efficiency and to make judgments on executive pay (Pandya and Rao, 1998). Using the benefit for common stockholders, which is the profit after tax and after interest payments, is essential when measuring ROE. (Abdelsalam & Weetman, 2003). It is expressed as: (2)

Return on Capital Employed (ROCE):
ROCE is a measure of firm financial performance used by many diversification studies (Adamu et al., 2011). This ratio is a measure of the efficiency of management in using long-term finances to generate operating profits. ROA measure of firm performance has to be a standard and significant measure among diversification studies (Chakrabarti, Singh, & Mahmood, 2007). It is defined as the ratio of profit before interest and tax to total assets fewer current liabilities and is calculated as: (3)

Method of Data Analysis and Models
The study uses both descriptive and inferential statistics to present and analyze data through Structural Equation Model (SEM) as used by prior studies (Gammelgaard et al., 2012;Vernaik, Midgley & Devinney, 2005;Fey, Morgulis-Yakushev, Park, & Bjorkman, 2009). SEM is a multivariate statistical analysis technique and extension of the general linear model (GLM) that is used to analyze complex structural relationships and models, such as confirmatory factor analysis and time-series analyses, and test a set of regression equations simultaneously. The researcher prefers this method because it estimates the multiple and interrelated dependence in a single analysis, and it also allows the use of multiple variables, particularly dependent variables.
Descriptive analysis is used to compute the mean, standard deviation, minimum and maximum values of both the study's endogenous and exogenous variables. Correlation (Bivariate) analysis is used to explain the association between endogenous and exogenous variables. Partial Least Squares (PLS) is used to explore the exogenous variables' effect on the endogenous variables and test the hypotheses. PLS technique is used in two ways: measurement model evaluation and structural model evaluation, giving two collections of linear equations: an internal model that determines relationships between latent variables and an external model that analyzes relationships between latent variables and relevant manifest variables. This allows the simultaneous analysis of the path coefficients among latent variables and the path coefficients between these variables and their constructs (measurements) (Fey et al., 2009). This also makes it possible to determine the reliability and validity of the measurement model, as well as determine the structural model. Finally, to avoid inadequacies such as skewed distributions of manifest variables, multi-collinearity within blocks of manifest variables and between latent variables, and data omissions, the PLS approach is resourceful (Cassel, Hackl, & Westlund, 1999). The Model Specification for PLS equation is given below as capture in the structural model in figure 2: Where β = beta, ROA= Return on Assets, ROE= Return on Equity, ROCE= Return on Capital Employed, PID= Product income diversification, NID= Non-product income diversification, PNID= Product and non-product income diversification (this is included in determining the combined effect of the two independent variables on the dependent) and ɛ= Error term To assess the validity of the measurement model, this study used the criterion suggested by Ali, Liu, and Niazi (2017), and Andreev, Heart, Maoz, and Pliskin (2009). Thus, the study checked with satisfactory results reflective indicators such as item reliability, variable reliability, convergent validity, and discriminant validity. Thus, Andreev et al. (2009) suggested that formative indicators' variable reliability should be performed through a test of Variance Inflation Factor (VIF). A Variance Inflation Factor (VIF) test was conducted with a minimum mean of 1.61 (see table 4.2) to determine the presence of the collinearity problem.

Results and Discussions
This study analyses the data set through STATA 13.0 and structural equation modeling based on path analysis. Path analysis is widely used to conclude a causal relationship in the data from a longitudinal research design.   N-1.89K, N-20.88K, N-3.78K; and maximums of 0.68K, N697, and N1.13K for ROA, ROE, and ROCE, respectively. This indicates that there is substantial evidence of performance in ROE and ROCE. The implication is that Nigerian quoted manufacturing firms have experienced various levels of financial performance during the period. The standard deviation of 0.18 (ROA) and 0.38 (ROCE) show no significant variation from the average, while the value for ROC (32.44) indicates a significant variation from the average. Similarly, PID, NID, and PNID have averages for diversification of 7. 026, 5.334, and 14.267; a minimum of 4.620, 1.813, and 9.642 and maximums of 9.953, 8.978, and 19.91, respectively. This implies various levels of diversifications by the sampled firms within the study period. The standard deviations of 0.89 (ROA), 1.20 (ROE), and 1.73 (ROCE) shows that there is no significant variation from the standard average among sampled quoted manufacturing firms. This implies that diversifications among the firms are evenly spread. Source: Computation Researcher's using STATA 13.0   Table 4 shows a list of coefficients (β3), t-values, and significance values from the three models above. The left side (β1, β2, β3 ) specifies the beta and coefficients of the independent variables (PID, NID, and PNID) used for performance variables (ROA, ROE, and ROCE) respectively. The results show that a 1% increase in product income diversification (PID) leads to a positive increase of 5.8%, 29%, and 15% in ROA, ROE, and ROCE, respectively. Similarly, a percentage increase in Non-product income diversification (NID) leads to positive increases of 3%, 5.6%, and 8% in ROA, ROE, and ROCE, respectively. A one percent change in total income diversification results in 4%, 25%, and 10% increases in ROA, ROE, and ROCE, respectively. This means that both product income and non-product income diversification cause increases in ROA, ROE, and ROCE measures of quoted manufacturing firms' financial performance in Nigeria.
The table also shows that product income diversification (PID) has significant p-values of 0.041 for ROA and 0.012 for ROCE but an insignificant p-value of 0.955 for ROE at a 5% level of significance. This means that Product income diversification has a significant effect on Return on Assets and Return on Capital Employed financial performance measures but has insignificant effects on return on equity. Thus, since the two measures of financial performance (ROA and ROCE) have significant p-values, the study rejects the null hypothesis that product income segment diversification has no significant effect on quoted manufacturing firms' financial performance in Nigeria. Similarly, the p-values of 0.004 and 0.000 of Non-product income diversification (NID) for ROA and ROCE indicate a significant value at a 5% level of significance while 0.975 indicates an insignificant p-value. Therefore, the study rejected the assumption that non-product income diversification has no significant effect on quoted manufacturing firms' financial performance in Nigeria. The implication is that both product income diversification and non-product income diversification significantly affect the financial performance of quoted manufacturing firms in Nigeria.
This result is in line with Stiroh and Rumble's (2006) findings that diversification gains are more than offset by the costs of increased exposure to volatile activities. Waithira (2013) also found a significant relationship between income diversification variables (financial and non-financial income) and financial performance (return on asset) of the firms. More so, Hsien (2012) found that both nonfinancing income segmentation and financing income segmentation have positive influences on financial performance. However, the result differs from Doaei et al. (2015) study, which reveals a negative relationship between product diversification, using product income as a measurement (H.H. index) and efficiency, and Shen, et al. (2011) study that reveals that product diversification measure by-product income (H.H. index and entropy) has an inverse U-shaped relationship with firm performance.

Conclusions and Recommendation
The result reveals a significant effect of Product income diversification (PID), Non-product income diversification (NID), and product and non-product income diversification (PNID) on financial performance variables (ROA and ROCE) of quoted manufacturing firms in Nigeria. Income diversification of Quoted manufacturing firms in Nigeria is not a transient phenomenon or one just associated with survival, but a strategy associated with success in achieving competitive advantage as it has a significant effect on firms' financial performance. Thus, under the context of environmental uncertainty, quoted manufacturing firms in Nigeria must avoid an extended period of dependence on only one-or two income sources.
Base on the findings, the study recommended that quoted manufacturing firms in Nigeria should strategically diversified to increase their income generation in both product segments, the non-product segment, with the view of improving their financial performance.
The study is limited first by the generalizability of the findings to other empirical contexts from the study's empirical context (quoted manufacturing firms in Nigeria). This is due to the limited number of the sample used and the inability to use all manufacturing firms. Second, the challenge in measuring diversification using available data to meet international standards. Third, the continuous changing of measurements used for diversification due to strategic reorganization and expansion, resulting in new branches, new products, and new subsidiaries. Finally, the philosophical differences in SEM, which assumed the amount of influence rather than a cause-and-effect relationship, might limit the applicability of this study's findings.
Therefore, it is recommended that further studies should be conducted to include more companies (quoted and non-quoted), industries, and years to ensure that longer-term effects are studied. Future research should also seek the possibility of utilizing international standards measures such as Standard Code identification (SCI) and H.H index and diversification dimensions that are capable of putting strategic reorganization and expansion of the study firms into consideration. Subsequent studies should utilize new models such as the mediating effect or include more variables in the model since SEM permits multiples variables.

Author Contributions:
The two authors contributed immensely to the article. While the first author, Umar Gunu, Ph.D., help with the design, theoretical and conceptual underpinning, methodological discourse, and general supervision of the article, the second authors, Umar Suleiman Gunu, contributed to the review of related literature, methodology, data analysis and interpretation, and general execution of the write-up.
Funding: This research received no external funding.