“The effect of a firm’s internal factors on its profitability: Evidence from Jordan”

The aim of this study is to investigate the effect of a firm’s size, asset growth, asset tan- gibility, and financial leverage on profitability for all listed corporate firms in Jordan using unbalanced panel data (time series and cross-sectional) regression analysis for a sample of 1,663 observations over the period from 2011 to 2018. The overall results show a significant positive effect of a firm’s size and asset growth on profitability. However, asset tangibility presents a significant negative effect on profitability, while financial leverage has an insignificant positive effect on profitability. An analysis of each of the main sectors also point to a consistently positive effect of a firm’s size on profitability, while the results for growth in assets and financial leverage are nearly consistent with overall findings, but not those for asset tangibility. Furthermore, the sub-sample industry analysis reveals mixed results due to the different industry shapes and structures. This study is expected to be of value to firm managers, investors, researchers, and regulators.


INTRODUCTION
Profitability is a firm's ability to use its investment to generate earnings exceeding the cost of these investments' use (Nishanthini & Nimalathasan, 2013). Firms consider profitability as a vital measure of success, efficiency, performance, and effectiveness, as it turns firms' available assets into profits (Devi & Devi, 2014). Profitability also indicates the company's ability to produce profits at an asset level, sales, and capital (Margaretha & Supartika, 2016). The determinants of firms' profitability and their improvement are critical. It can teach lessons to both corporate managers and policy makers. This issue has sparked debate in the literature and is still vital in the business arena. Profitable businesses generate value, employ employees, and strive to be more creative and appealing to potential and current investors (Odusanya et al., 2018;Ananzeh et al., 2021). The importance of this study stems from identifying the internal determinants affecting a firm's profitability and how to develop it. This will lead to continued growth, stability, survival, and the possibility to predict a firm's performance. All these attract more investors, raise the stock price and increase a company's value (Khan et al., 2018). This study is expected to be important to firms' managers and investors, as well as to researchers and regulatory bodies.
According to the literature, profitability is affected by both external and firm-specific factors. External factors mainly include the economic growth rate, inflation rate, trade interdependence, interest rate, innovation, technological change, and employment. Internal factors are financial indicators that contribute to evaluating the effi-

LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT
There are two theories with rival models of firm profitability in the modern literature: the structure-conduct-performance (SCP) model and the firm effect model. In each of these, a range of models has now been established. According to the SCP theory, market structure affects firm behavior and profitability. In the firm effect theory, the distribution of firms and profits determines the market structure. According to the general SCP model, which is based on neoclassical theory, firms in concentrated industries are more efficient than firms in perfectly competitive markets. Firm effect models are based on the premise that firms in a sector are heterogeneous. Such models indicate that variations in firm-level characteristics such as performance, organizational structure, and management quality occur, persist, and trigger profitability differences (Stierwald, 2009). Demsetz (1973) suggested the superior firm theory, which implies that firms are differentiated based on their efficiency levels. More profitable firms have a competitive advantage over their less productive competitors, which is reflected in profitability. Lower manufacturing costs, economies of scale, or improved product quality may all lead to increased cost-efficiency (Stierwald, 2009 Moving the focus to Jordan, Alalaya and Ahmad (2020) investigated the effect of some internal and external determinants of profitability for all banks in Jordan from 2008 to 2018 using panel data and time series statistical techniques. The results showed a positive effect for the tested internal determinants of profitability, while the external determinants of profitability had a negative effect. In another Jordanian study, Al-Nawaiseh (2020) tested the effect of a firm's growth, size, and age on its profitability for a sample of 22 Jordanian insurance firms listed on the Amman Stock Exchange during the period 2008 to 2017 using simple regression analysis. The results indicated an insignificant effect of the insurance firm's growth, size, and age on its profitability.
However, some researchers investigated the role of one or more of these internal factors on firms' profitability and found opposite effects on profitability to those found elsewhere in the literature for similar contexts. For example, Glancy (1998)  A positive relationship between size and profitability has been theoretically supported by economies of scale and economies of scope. Size qualifies large companies to benefit from superior capabilities in management, product development, marketing, and diversification, together with more capital cost-saving, and a shorter cash conversion cycle (Dahmash, 2015 Ravenscraft & Scherer, 1987). Large firms have lower information asymmetry and more ability to obtain external financing, which make these firms more flexible in their policies concerning receivables and inventory (Brennan & Hughes, 1991). Despite the advantages of size, some researchers indicated a possible negative relationship between size and profitability because a larger firm can have higher bargaining power with its customers and suppliers, so it keeps a low level of cash based on its ease of accessibility to capital (Chiou et al., 2006;Moussawi et al., 2006). Hence, a positive relationship is expected between size and ROA.
Firms use growth to measure their performance, based on their belief that it is a sign of progress, success, and an introduction to a sustainable competitive advantage and profitability (Markman & Gartner, 2002). Small firms consider growth as the best measure for their progress and success, and accordingly, these firms expect a positive relationship between their growth and profitability if they rely on their internally generated funds for any expansion process (Glancey, 1998). Any increase in firms' assets or any new assets in firms generate new growth opportunities, which will lead to a higher profitability level, and these new growth opportunities can take the shape of new product lines, new development projects, the replacement of existing assets and the acquisition of other firms (Myers, 1977 Glancy, 1998). In line with these studies, a positive relationship is expected between growth and ROA.
A large portion of tangible assets generally increases the firms' profitability because tangible assets are more likely to have an increased market value in the future, while intangible assets will lose value over time. Therefore, the more their tangible assets, the lower the risk of lending to such firms. However, in prior studies a positive relationship was indicated between leverage and tangibility, and a negative or insignificant positive relationship between leverage and profitability ( Glancy, 1998). In this study, all types of industries are covered using recent data from Jordan. The aim is to explore this context more deeply and to establish whether these results agree with or differ from the findings of previous studies, especially those on emerging markets.
This study's aim is to examine the effect of a firm's size, asset growth, asset tangibility, and financial leverage for all firms listed on the Amman Stock Exchange over the period from 2011 to 2018. So, the following hypotheses will be formulated to achieve the goal of this study:

METHODOLOGY
This study covered all firms listed on the Amman Stock Exchange from 2011 to 2018. Since firms can enter and exit the listing during this period, the number of firms varied from year to year. The initial sampling started with 1,869 observations and ended with 1,663, selected according to the following process (Table 1). This study investigates the effect of size, growth, tangibility, and leverage on ROA. These factors and their measurements are presented in Table 2.  Table 3 presents the summary statistics of the main pooled sample variables of this study.  The multicollinearity analysis between independent variables is performed using the variance inflation factor (VIF) method (see Table 4). According to Myers (1990), there is no concern if the VIF value is less than 10. Table 4 reveals that all values conform to this principle, indicating no multicollinearity problem between the independent variables.

Summary statistics
Hausman's test was used to select the more appropriate estimation method between the fixed effect estimator model and the random effect estimator model to test the model presented in equation (1) (Hausman, 1978). Table 5 summarizes the results of this test. These results show a probability value of 0. As this is less than the cutoff of 0.05, the fixed effect estimator model is the appropriate estimation method. Table 6 presents the regression analysis results of the estimated model from equation (1) for the pooled sample and the other three major industry sector samples. To overcome any heteroscedasticity problem, an unbalanced panel regression analysis was used (White, 1980).  Table 7 shows the regression analysis results for the financial sector sub-samples.  Table 8 gives the regression analysis results for the industrial sector sub-samples.  Table 9 provides the regression analysis results for the services sector sub-samples.  Table 6 indicates that ROA is positively affected by a firm's size and asset growth. This is consistent with previous studies arguing that large firms benefit from economies of scale and economies of scope, capital accessibility, superior management, diversification capabilities, and the low level of information asymmetry ( , 1999). However, this inverse statistical effect indicates that firms that invest more in tangible assets own costly and less productive fixed assets, and it has been reported that they prefer to focus more on enhancing their human capital and benefiting from long-term investments (Diaz & Hindro, 2017;Nunes et al., 2009). Based on this result, the third null hypothesis (H3) is rejected as there is a significant statistical effect of tangibility on ROA of Jordanian firms.

DISCUSSION
It is clear from the estimates that there is an insignificant positive effect of leverage on ROA, thus null hypothesis (H4) is also rejected. This insignificant positive effect of leverage on ROA is similar to prior studies that showed that firms with greater debt are expected to have higher leverage by using more external funds, which is more costly and risky and less internally generated. Accordingly, the firm's profitability will be decreased (e.g.,  Another robustness analysis is made for financial, industrial, and services sectors, as shown in Table  6. The results imply a positive effect of size for the three main sectors, which is consistent with the main pooled sample and in line with previous studies (e.g., Gaio & Henriques, 2018;Dahmash, 2015;Dogan, 2013;Bayyurt, 2007;Jónsson, 2007).  Table 7 indicates a positive significant statistical effect of size for real estate companies and banks only, consistent with the main pooled sample and the financial sector sample of which they form part. Growth has a significant positive effect on ROA for firms in the financial sector sample, except for banks, and these effects are consistent with the main pooled sample. The tangibility of assets has a positive significant statistical effect on ROA for real estate firms only, and this effect is inconsistent with the main pooled sample and the financial sector sample. Leverage has a significant negative effect on ROA for real estate and insurance subfirms, which inconsistent with the main pooled sample and the financial sector sample. Table 8 shows a positive significant statistical effect of size on ROA for extraction and construction companies and pharmaceutical and chemical companies only, which is consistent with the main pooled sample and the industrial sector sample. There is a significant positive effect of growth on ROA for all firms in these industry sub-samples, which is consistent with the main pooled and industrial sector samples. Tangibility indicates a significant inverse effect for industrial sub-samples firms, except for beverages and food sub-sample firms, and these effects are consistent with the main pooled and industrial sector samples. Leverage implies a negative significant statistical effect for paper and textile sub-sample firms only, and these effects are inconsistent with the main pooled sample and the industrial sector sample. Table 9 demonstrates a significant positive effect of size on ROA for all services sub-samples, which is consistent with the pooled and services sector samples. Growth has a significant positive effect on ROA for both the health care and transportation sub-sample firms and technology and utilities sub-sample firms. These effects are consistent with the main pooled sample, contrast with the services sector sample. The tangibility of assets has a significant positive effect on ROA for educational and commercial sub-sample firms only, and this is inconsistent with the pooled sample and services sub-sample. Leverage has a negative significant statistical effect on ROA for health care and transportation firms only. These two effects were consistent with the services sector sample but not with the main pooled sample.
Based on the previous results of the main industry sector samples and the other sub-sector samples, it can be concluded that different industry shapes and structures can play a vital role in changing the effect of the explanatory variables of size, growth, tangibility, and leverage on ROA.
The accounting variables could present some problems as financial statements are not submitted to market assessments before their publication. Therefore, another robustness check was done with market variables (see Table 10). Tobin Q was used as a proxy for profitability, the logarithm of market capitalization as a proxy for size, and market to book value as a proxy for growth opportunities. The final number of observations for the new sample was 1,448 after excluding missing and unavailable data. First, an analysis was executed for these three market variables, and then another analysis was done for the same three variables after adding the tangibility and leverage variables. Tangibility and leverage variables are the same variables that are tested in the main model as there is no specific market measure to replace tangibility and there is a shortage of data concerning the market value of debt, since there are few companies in Jordan issued corporate bonds, and most of corporate debt are generated from banks loans. Table 10 indicates that the estimated regression model of the pooled sample seems to have a high explanatory power (with adjusted R-square of 67.1%). Tobin Q is positively affected by tangibility and the market to book value, which is similar to previous results (see Table 6). The logarithm of market capitalization does not affect Tobin Q, which is not the case for the size variable. Leverage has a similar result as in the previous analysis.

CONCLUSION
The aim of this study was to investigate the effect of a firm's size, asset growth, asset tangibility, and financial leverage on ROA using a static model applied on unbalanced panel data for an integrated sample of firms listed on the Amman Stock Exchange from 2011 to 2018. An extended analysis was undertaken for the main sector samples and the sub-samples of these main sectors to investigate if the effect of the explanatory variables on the firm's ROA changes at these levels.
The pooled sample showed a positive effect of the firm's size and asset growth on ROA. However, ROA was inversely affected by asset tangibility, and insignificantly by leverage. The main sector samples had the same results regarding size and asset growth, excluding the services sector. The effect of asset tangibility for the pooled sample was consistent with the main industrial sector sample. The leverage effect was consistent for the main financial and industrial sector samples.
When exploring the data at a more detailed level of industry sub-sectors, mix of results arose concerning the effect of the explanatory variables on ROA. The results of this study indicate that a firm's size and asset growth have the most positively significant effect on ROA, and are almost the most consistent variables at the main pool level. However, the results clearly point to the important role of industry shape and structure. These change the effect of the explanatory variables of firm's size, asset growth, asset tangibility, and leverage on ROA, and this varies from one industry to another. In addition, the results of this study support the argument that firms' profitability is not always affected most significantly by any particular internal factors.
Based on the results of this study, several recommendations emerge. Corporate management should consider the most positive effects of size and growth on ROA, minimize the less productive fixed assets, depend less on external risky and costly finance sources, and rely much more on internally generated funds. Further research may include investigating the effect of additional internal factors on ROA in the same context or other contexts. The effect of macro economic factors on ROA can also be explored.