Introduction

In general, company activities start with a single business venture and serve a specific market. However, along with the development of similar companies and changes in population it becomes an opportunity as well as a challenge. This phenomenon encourages companies to design development strategies so that they can remain competitive and thrive in their respective industry. Business diversification is one such development strategy. Diversification is considered as one of the best long run growth strategies for the companies. It is a form of corporate strategy aimed at increasing profitability through increasing the volume of sales in the form of new products and/or goods and services, or new markets. Diversification strategies include expanding or adding different business units from previous businesses with the aim of increasing the company's market strength (Ramadhan, 2017).

A company diversifies for various reasons. Many companies apply diversification to enhance their overall strategic competitiveness, support value creation, gain market share, neutralise competitor strength, or expand the company's portfolio. In addition, the motives of business managers in implementing diversification are driven by the benefits that can increase the company’s position in the market (Hitt et al., 1997; Said, Alam, Mohamed & Rafidi, 2017). So, the company diversifies due to a range of internal and external factors. Internal factors are conditions within the company itself that motivate the need to diversify. For example, a company management assesses if the company's expertise does not match the developments that the initial market wants; the company wants to exploit its resource base. External factors, namely the encouragement of outside opportunities that encourage companies to start a new market; can represent certain threats that cause companies to look for other opportunities.

Diversification can be categorised into related diversification and unrelated diversification. Related diversification is implemented to gain market power. A company can be said to have adopted a related diversification strategy when each business unit of the company is linked in some way. The purpose of such related diversification is to control costs and quality of production in order to control sale prices and increase revenue (Wirama, Wiksuana, Mohd-Sanusi & Kazemian, 2017). Conversely, in an unrelated diversification scenario, businesses launch a new or unrelated line of products and penetrate new markets. Unrelated diversification can improve company performance through internal capital efficiency because it is used for businesses that are related to its main or core business. As well, unrelated diversification can create value through two types of economic and financial approaches, namely internal capital market allocation and structuring (Hitt et al., 1997).

Most companies that implement diversification require substantial capital support. Average companies face difficulties in obtaining additional capital to diversify and expand business. Diversification becomes an attractive option for companies when facing a situation of intense competition and industry conditions are not fixed. The diversification policy arises from companies’ desire to expand their business through the addition of new business units, and where both businesses are directly or indirectly related to the previous line of business. On the other hand, diversification can cause problems. In an economic situation that is not yet strong, companies will face uncertainty that might lead to success or failure. Thus, the application of diversification provides two urgencies. First, it can increase the profitability of the company and second, it can trigger complexity situations which can hinder what the company is trying to achieve (Said, Hui, Othman & Taylor, 2011; Satoto, 2009).

The application of diversification is expected to have a positive impact on the companies, especially in improving their performance. With the addition of business units and business expansion the company can increase its operational activities. Then potential investors and creditors can assess the company's performance through financial statements and use them as a basis to invest in it and offer financial assistance if all parties are on the same page. Therefore, companies must perform well in order to be trusted by investors and creditors because it will determine companies’ operational processes and how the company manages its capital and estimates its Return on Capital (ROC) (Kazemian et al., 2021; Ramadhan, 2017).

The possibility of failure when applying diversification can be caused by a resistant bureaucracy or excessive ‘red tape’, weak coordination between segments, there is a conflict of interest between the managers and owners over policy decisions. However, this is not absolute because diversification can still be applied by considering the factor of the company’s age, size, and leverage. These variables will reflect the position of companies in a competitive environment. In this study, it is proven that diversifying companies are able to rival competitors because they are motivated to obtain long-term and sustainable growth. Puasani (2013) states that an older company can provide wider financial information compared to companies that are relatively new. Large companies have the ability to leave the industry to expand their portfolio of business activities (Aji, 2015). Leverage will help companies make the most of their opportunities to make investments (Ramadhan, 2017). Research by Sindhu, et al., (2014) supports the use of leverage to implement diversification strategies. Diversified companies have higher leverage than those companies that do not diversify.

Several researchers such as Ramadan (2017); Sari, et al., (2014) stated that corporate diversification can undermine company performance. Satoto (2009) in his research mentioned that diversification helps to increase profitability but at the same time can trigger the complexity of a company due to uncertain economic situations, thus compromising the company’s goals. Unrelated diversification has a significant positive effect on the company's financial performance as measured by ROI. Unrelated diversification is more effective in improving a company's financial performance than related diversification if measured by ROI. Business priorities will relate to the company's goal to create value for itself, so that the company seeks to obtain sustainable growth and aim to reduce any risks. The time the company spends while in a particular industry allows it to obtain low growth. Large companies tend to have the will to leave the industry where they have operated before in the hope of expanding their portfolio of business activities (Aji, 2015; Kazemian et al., 2020). Unrelated diversification becomes the best alternative than related diversification because it can improve company performance.

Reflections on better performance from unrelated diversification are supported by MBV theory. The theory asserts that companies maintain a competitive advantage by preventing the entry of new competitors in the same industry. By implementing diversification, the company's position can still be superior because it has several revenue streams from different business segments, can reduce risk, and can increase the value of the company. In terms of taxation, companies can reduce taxes when the loss segment is balanced with high profit segments (Ramadhan, 2017; Chirani & Effatdoost, 2013; Setapa, Mamat, Bakar, Yusuf & Kazemian, 2020; Said, Ghani, Zawawi & Yusof, 2012). Diversification unrelated in the life cycle stage of large companies is an important strategy for future development. In this research, senior/executive managers are advised to employ diversification in several stages. It should be noted that determining the time period and not deciding too quickly on the best policies and strategy is crucial. MBV theory is the fundamental basis for formulating competitive strategies, so that the industrial structure’s strengths and weaknesses can be explained. This process makes it possible to evaluate the opportunities and threats in the business environment, and highlight potential business development pathways.

Therefore, given the complexities of running a company, managers need to efficiently reach the target market through business diversification. Top managers are responsible for effectively planning and implementing strategies to achieve long-term corporate goals without compromising the quality of products or services. The purpose of establishing a long-term strategy is to achieve the best production processes, maximise the value of the company and minimise costs. In that case, it is important to know how business diversification affects the financial performance of a company as well as which type of diversification leads to better financial outcomes such as profits.

Research Methods

Data

This research was conducted in 2018-2019 with data covering the period 2013 to 2017. Samples were obtained through the purposive sampling method, so that out of the manufacturing companies listed on the Jakarta stock exchange, 13 manufacturing companies that produced consumer goods met the criteria for this study. The data consists of observations made over a 5-year period from 2013 to 2017. The data was obtained from BEI, and the official websites and annual reports of each company.

Measurement of Variables

Diversification

Diversification is a strategy that includes expanding or adding business units that are different from previous businesses with the aim of increasing the company's market position (Ramadhan, 2017). Diversification is measured using the Herfindahl index. The index is calculated using the ratio of the sum of the squares of sales of each segment and the square of the company's total sales. Segment sales are known from the records of each company's financial statements (Ramadhan, 2017). The Herfindahl index calculation is as follows:

The more the Herfindahl index approaches the number one, the more will the company's sales be concentrated in certain business segments (tending to be a single segment). Conversely, the more the Herfindahl index nears zero, the more will the company's sales be diversified in several business segments. To see variations in groups of company segments, researchers provide codes for each segment based on SIC (Standard Industrial Classification). In accordance with Jiang, Zhihui & Chan's (2005) research, the SIC code serves to identify variations in company business segments that are grouped into 21 categories. In this study, code 1 is given for related diversification while code 0 for diversification is not related.

Company Performance

Performance refers to the level of successfully implementing a company's policies in realizing the goals, objectives, etc., that are documented in the strategic plan (Iskandar et al., 2017). The company’s performance is measured using Tobin's Q and return on investment (ROI) method calculated using the following formula:

Where, Q is Tobin's Q ratio; MVS is market value of equity (obtained by multiplying the number of shares outstanding by the closing price of the stock); D is total debt; TA is total assets. Tobin's Q method is used as a measure of performance appraisal in the company’s financial data. This method provides information about the company's market value and this can be reflected in the company's stock market price. The company's stock price shows the overall investors’ valuation of each equity owned by the company. The company's performance is also measured by utilising the Return On Investment (ROI) formula, which is the ratio between the company's net profit and the total assets:

Econometric Model

To draw inferences this study relies on the panel ordinary least squares (PLOS) model. This study also runs the fixed effect and random effect models and decided the appropriate method was the Hausman test and LM test. The working models are written below:

ROI_ij = α_ij + β1 DIV_ij + β2 DIV*DT_ij + β3 LEV_ij + β4 AGE_ij + β4 SIZE_ij +μ_ij (1)

TQ_ij = α_ij + β1 DIV_ij + β2 DIV*DT_ij + β3 LEV_ij + β4 AGE_ij + β4 SIZE_ij +μ_ij (2)

Where, ROI is return on investment, TQ is Tobin’s Q, DIV is diversification, DIV*DT indicates diversification types – unrelated or related diversification, LEV is financial leverage, AGE is age of the company, and SIZE is total assets of the company.

Results and Analysis

Descriptive Analysis

The descriptive statistics are reported in Table 1, showing that diversification has a minimum value of 0.26 and a maximum value of 0.99. The lowest value company reflects the highest diversification such as becoming a multi-business company while the maximum value company reflects the lowest diversification. It means the company has only a single business because the numbers are close to one. The average diversification is 0.5497, meaning that during the study period almost all of the sample companies implemented diversification. The standard deviation shows the value of 0.21666, suggesting that in the research period the deviation of data from the diversification variable is 0.21666 from an average of 0.5497. It indicates that the average value can be used as a representation of the whole data.

Table 1 Descriptive Statistics
Variables	N	Minimum	Maximum	Mean	Sdt. Deviation
DIV	65	.26	.99	.549	.216
DIV*DT	65	.00	.99	.290	.354
TOBINSQ	65	.39	23.29	3.193	4.832
LEV	65	.14	.73	.419	.161
AGE	65	6	35	19.690	8.342
SIZE	65	26.93	32.11	29.322	1.505
ROI	65	-9.71	41.72	9.441	10.087

Diversification Type (DIV * DT) has a minimum value of 0.00 and a maximum value of 0.99. This value is obtained by multiplying the value of diversification with the type of diversification (number 1 for related diversification and number 0 for unrelated diversification). The average value of 0.2905 reflects that in this study the majority of the sample belonged to the unrelated diversification type category (because the number did not reach one). The standard deviation of the diversification type variable from 65 observations is 0.35418.

Tobin's Q variable produces a minimum value of 0.39 and a maximum value of 23.29. The average value of Tobin's Q is 3.1935, so that research confirms good market performance. Good market performance can be known if the value of Tobin's Q> 1. Standard deviation of 4.83226 shows the size of the spread of Tobin's Q variable derived from 65 observations.

Descriptive statistical results of leverage show a minimum value of 0.14, a maximum value of 0.73 and the average leverage is 0.4193, meaning that in this study period the ratio of total debt and total assets of the company is 41.93%. The standard deviation of 0.16133 shows the size of the spread of leverage from 65 observations. Standard deviations that are smaller than the average value can explain the representation of the whole data because the data distribution is small.

Descriptive statistics of the age of the company produced a minimum value of 6 and a maximum value of 35. According to (Puasanti, 2013), the older the company means that it can provide more financial information compared to younger companies. Therefore, older companies will tend to disclose more complete information because the disclosure of detailed information can provide added value for them in attracting the interest of the wider community. High company age will indicate that the company can survive and be able to compete with other businesses. The mean value for the age variable is 19.69 and the standard deviation is 8.342. Standard deviations smaller than the average value can explain the representation of the whole data because the data distribution is small.

The company size variable produces a minimum value of 26.93 (which is equivalent to total assets of IDR 497.354bn) while a maximum value of 32.11 (which is equivalent to total assets of IDR 31,620bn). Companies with a high total asset value indicate that a company is relatively more stable and able to generate profits compared to companies with small total assets. In the end, it was concluded that if the company was large, management would be more flexible in using assets that could be optimised for the company's operational interests. The average value of the variable size is 29.3223 and the standard deviation is 1.50519. From these figures, the average value can reflect the entire data because the value is greater than the standard deviation.

In the case of ROI, the maximum value is 41.72 and its minimum value of -9.71. The higher the value of ROI, the greater the funds that can be obtained from the company's total assets that become profits. So the greater the company's net profit, then the better the performance. The average value of profitability measured by ROI is 9.44%, while the standard deviation of 10.08663.

Regression Analysis

Based on the findings from regression (Table 2), corporate diversification has no significant effect on the company's financial performance both calculated by ROI and TQ. However, the type of related diversification wields positive significant impacts on both ROI and TQ. Moreover, the financial leverage, age, and size all demonstrate a significant positive relationship with ROI and TQ.

Table 2 Regression Output
Dependent Variable	Independent Variables	Coefficient	SDT Error	T-value	P-value
	(Constant)	-88.75*	23.37	-3.8	0
	DIV	-5.2	7.9	-0.66	0.513
ROI	DIV*DT	12.38**	5.44	2.28	0.027
	LEV	21.25***	7.93	2.68	0.01
	AGE	0.81*	0.14	5.67	0
	SIZE	2.48*	0.77	3.21	0.002
	(Constant)	-38.15*	10.88	-3.51	0.001
	DIV	-2.19	3.68	-0.6	0.554
TQ	DIV*DT	6.79***	2.53	2.68	0.01
	LEV	13.71*	3.69	3.71	0
	AGE	0.42*	0.07	6.27	0
	SIZE	0.91**	0.36	2.53	0.014

Model Diagnostic Test

Normality Test

Normality test is used to determine whether the data is normally distributed. Normal data will produce an unbiased analysis result. Based on the Kolmogorov-Smirnov test results for each of the dependent variables in Table 3 show that the p-value value. (2-tailed)> 0.05 is equal to 0.20, which means that the residual data is normally distributed.

Table 3 Normality Test Results
		Unstandardised residual Tobins Q	Unstandardised Residual ROI
N		65	65
Normal Parametersa,b	Mean	.0000000	.0000000
	SDT. Deviation	3.22410396	6.92129568
Most Extreme	Absolute	.074	.066
Differences	Positive	.074	.065
	Negative	-.054	-.066
Test Statistic		.074	.066
Asymp. Sig. (2-tailed)		.200c,d	.200c,d
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
d. This is a lower bound of the true significance.

Multicollinearity Test

Table 4 shows that all independent variables did not indicate multicollinearity in the regression equation. This is evident from the test results revealing a tolerance value of more than 0.10 and a VIF of less than 10.

Table 4 Multicollinearity Test Results
Variables	Collinearity Statistics
	Tolerance	VIF
DIV	0.277	3.609
DIV*DT	0.219	4.57
LEV	0.496	2.015
AGE	0.574	1.741
SIZE	0.602	1.662

Autocorrelation Test

Based on the results of the Durbin-Watson test in Table 5, the DW value generated is between dU <d <4 - dU. Therefore, it can say that autocorrelation did not occur both for the regression Models 1 and 2.

Table 5 Autocorrelation Test Results
Regression Model	Durbin-Watson
1	2.050
2	1.830

Heteroscedasticity Test

Based on the Scatterplot graph, Tobin's Q and ROI show no symptoms of heteroscedasticity. This can be seen from the pattern that spreads above and below the number 0 on the Y axis in Figure 1.

F-test

Based on the F test results in Table 6 below, the significance value produced by Model 1 and Model 2 is 0,000, so the value is smaller than the significance level of 0.05. Thus, the two regression models consisting of diversified independent variables – types of diversification, leverage, age, size - are said to have a joint (simultaneous) effect on company performance as measured by ROI and Tobin's Q.

Table 6 Result of F-Test
Equation	Model	Sum of Squares	DF	Mean Square	F	SIG.
Panel 1	Regression	3445.991	5	689.198	13.263	.000
	Residual	3065.877	59	51.964
	Total	6511.868	64
	Regression	829.176	5	165.835	14.707	.000
	Residual	665.270	59	11.276
	Total	1494.446	64

Discussion

Effect of Diversification on Company Performance

The findings show that diversification has no effect on the company's financial performance. It is therefore evident that diversification of companies does not always result in benefits. Possible failures in the application of diversification can be caused by difficult or resistant bureaucratic processes, weak coordination between segments, and conflict of interests between managers and owners over policy and procedural issues. However, this is not absolute because diversification can still be applied by considering the age factor of the company, and its size and leverage. These variables will determine the company's ability to compete with other businesses. In this research, it is proven that diversifying companies are classified able to do well in a given industry because they want to achieve long-term and sustainable growth.

Puasani (2013) states that if a company is older, it can provide more financial information compared to companies that are relatively young (relatively new). Large companies have the will to expand their portfolio of business activities in other industries (Aji, 2015). Leverage will help a company optimise its opportunities for investment (Harto, cited in (Ramadan, 2017). Research by Sindhu, et al., (2014) supports the consideration of leverage in the implementation of diversification strategies. Diversified companies have higher leverage than those companies that do not diversify. This research is consistent with research conducted by Ramadan, (2017); Sari, et al., (2014) which state that corporate diversification has a negative effect on company performance. Satoto, (2009) contended that the application of diversification can increase company profitability but at the same time can trigger unforeseen difficulties due to uncertain economic situations in the industry or the overall economy.

Effect of Diversification Type on Company Performance

The regression results show that related diversification has a significantly positive effect on the company's financial performance. Related diversification is more effective in enhancing a company's financial performance than unrelated diversification. Business priorities will relate to the company's goal of creating value for it, so that the company can obtain sustainable growth and expect risks to be less of a problem. The time the company spends while in a particular sector allow it to experience high growth and better efficiency, which is a good omen for sustainable growth (Nor et al., 2017; Shuhidan, Said, Mokri & Kazemian, 2016). This is how related diversification is superior to unrelated diversification in improving a company’s performance.

Reflections on better performance from related diversification are supported by Resource-Based View (RBV) theory. This theory is the fundamental basis for the formulation of competitive strategies to produce an analysis of industrial structure that can explain certain strengths and weaknesses, make use of opportunities and threats to the environment, and highlight potential pathways for business development (Aji, 2015). The theory discusses how companies maintain their competitive advantage over others in the same industry. This research is consistent with studies conducted by Barney (2001); Lubatkin & Chatterjee, (1994); Aziz, Said & Alam, (2015).

Effect of Control Variables on Company Performance

Based on the regression output this study found that profitability of companies will have a significant positive relationship with leverage, which is consistent with the findings of (Gill et al., 2011; Alam et al., 2019). It also found that company size exerts a significant positive relationship with profitability which implies that larger firms are more profitable than smaller ones. This finding is consistent with work done by Yazdanfar & Öhman (2015), (Chadha & Sharma, 2015; Simerly & Li, 2000). Similarly, it found a positive relationship between age and profitability which is consistent with the findings reported in Yazdanfar & Öhman (2015); Chadha & Sharma (2015); Nunes et al., (2009). Moreover, this study detected a significant positive relationship between the firm’s value measured using Tobin’s Q and leverage, size and age of the firm. This result is consistent with the findings of (Farooq & Masood, 2016; Bestariningrum, 2015).

Conclusion

This study investigates the effects of business diversification and types of diversification on the financial performance of Indonesian public listed companies. The study found that overall diversification as well as unrelated diversification has no effect on company performance, but related diversification is better than unrelated diversification. The failure to implement diversification in improving performance can be caused by issues involving bureaucracy, weak coordination between business segments, and conflicting interests between managers and owners over policy and procedural issues. However, diversification can still be applied by considering the company’s age, size, and leverage. These three variables can help companies in dealing with their competition. Diversifying companies are classified as those able to compete with other companies because they are motivated to achieve long-term and sustainable growth. Future studies should use this analysis as the basis to explore other industrial sectors. They can also use variations of other measurement tools to measure and explain the effects of diversifications on company performance. This study will benefit business managers and investors to understand and improve how well their businesses are performing.

Acknowledgement

We are very thankful to Universitas Islam Indonesia, Universitas Amikom Yogyakarta and Universiti Teknologi Mara for supporting this research. Corresponding authors’ emails: agus_h@uii.ac.id , rezawp@amikom.ac.id.

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