“Integrated performance measurement system for Slovak heating industry: A balanced scorecard approach”

The prerequisite for businesses’ success, competitiveness, and non-bankruptcy is their performance. An effective performance measurement system is a suitable tool for measuring and improving business performance. The development in performance measures moved from financial measures focused on company profitability to measurement systems combining different methods, approaches, and tools. The paper aims to identify key performance indicators for Slovak heating companies based on the developed integrated performance measurement system. The analysis sampled 292 Slovak companies within SK NACE 35 (heating industry). The performance measurement system was built on balanced scorecard principles, while the least absolute shrinkage and selection operator (Lasso regression) method was used to select financial indicators. Based on the combination of the above methods, a performance measurement system framework for the analyzed sample of businesses was created. The results show that when managing performance, the analyzed businesses should focus on the following financial performance indicators: Receivables turnover ratio, Return on equity, Return on costs, Total debt to total assets, Material intensity, Labor to revenue ratio, Netto cash flow to assets, Net working capital to total assets, and Short-term liabilities to assets. When building performance measurement system based on balanced scorecard principles, financial indicators were supplemented by non-financial ones. In addition to the original balanced scorecard principles, the performance measurement system was extended by environmental constituents. Also, the paper’s deliverable combines Lasso regression and balanced scorecard principles in order to select key performance indices.


INTRODUCTION
Performance is critical in the business's life because if business is inefficient, it is not competitive and may go bankrupt. In order to effectively measure performance, companies should have a balanced system of performance measures. These measures should include the most relevant performance indicators (Oukhay & Romdhane, 2022). Several methods can be used to create performance measures, while a balanced scorecard is one of the essential approaches. However, nowadays, in creating a performance measurement system, various methods are used, including the application of mathematical and statistical ones (Valmohammadi & Servati, 2011).
The main issue is to create an effective system for measuring the business performance, which integrates key performance indicators from all functional business areas. Applying a balanced scorecard with a suitable mathematical and statistical method for selecting performance indicators is the best approach.

LITERATURE REVIEW AND HYPOTHESES
Business performance is a term widely used in the daily life of businesses. In today's dynamic and digital era, maintaining the position of companies in the market, their financial results, and performance is demanding and requires a lot of activities and subsequent measurements. Suppose companies want to achieve a significant position in the market and maintain a competitive advantage.
In that case, they need a balanced performance measurement system to ensure the controlled use of available resources to fulfill their goals and strategy. As a result, businesses became interested in developing an effective performance measurement system (Keong Choong, 2013; Vilanova et al., 2015). This topic became an important challenge for scientists and practitioners in the late 1980s, thanks to Johnson and Kaplan (1987). Neely (1999) stated that between 1994 and 1996, more than 3,600 articles were published on business performance measurement, thus giving rise to the phrase "performance measurement revolution" (Gutierrez et al., 2015). Also, Keong Choong (2014) found that recently many journals have been devoted to the issue of performance measurement.
Performance measurement can be defined as measuring performance using performance indicators. According to Neely et al. (1995), performance measures assess the effectiveness and efficiency of past actions. A quality performance measurement system is required to guide this process, namely the software, databases, and procedures necessary to ensure that performance measurement is consistent and complete. In this context, it is also possible to define management performance, according to Bititci et al. (1997), as the process by which an organization integrates its performance into its corporate and functional strategies and objectives.
Franco-Santos et al. (2007) noted two basic characteristics of the performance measurement system. A system of performance indicators is confirmed by 53% of interviewed experts; goal setting is confirmed by 35% of studies researching performance measurement system. Given the research and opinions on the issue, there is a consensus of opinions in implementing performance measurement tasks. 59% of studies consider the implemen-tation and execution of the strategy to be a vital characteristic of the performance measurement system; 41% suggest "focusing on alignment," "internal communication," and "measuring or evaluating performance," and 35% report "monitoring progress" as essential activities in this context. This process is "providing information to managers." Up to 53% of articles in the given area confirmed this system's characteristics. Bourne et al. (2000) and Nudurupati et al. (2011) noted that in creating business performance measurement systems, classical approaches were mainly applied, which were based on the use of data from accounting systems. According to , performance measurement focused primarily on financial measures. There are also new approaches to measuring financial performance and methods such as activity-based costing, free cash flow, economic value added, or shareholder value analysis.
As stated by Rosová and Balog (2012) and Horváthová and Mokrišová (2021), the system of measuring business performance began to be supplemented with non-financial business performance indicators, so the performance measurement system represented a multidimensional platform. These studies were based on Drucker's (1954) proposal to develop a balanced performance measurement system (Neely, 2005). However, this multidimensionality can cause various problems. These are, for example, conflicts between performance rates, a suitable balance of internal and external actions, and a link between measures and strategies. One way to overcome the inherent complexity of designing a performance measurement system is to use structured design methodologies (Neely et al., 1996).
Despite some shortcomings, research on performance measurement system has continued, and a large number of frameworks have emerged  A balanced scorecard is considered one of the first performance frameworks, which were complex and supplemented financial indicators with non-financial ones . It was developed by American consultants Kaplan and Norton (1992). Since then, it has gained popularity mainly due to its complexity and clarity at all levels of management (Dumitrescu & Fuciu, 2009). So far, three generations of balanced scorecards have taken turns since 1992 (Madsen & Stenheim, 2015).
A balanced scorecard represents a significant contribution in improving the company's performance. When using this method, companies must determine the mission, vision, and strategy (Kaplan & Norton, 1996;. The original performance management system introduced by Kaplan and Norton (1996) consisted of a financial perspective, customer perspective, perspective of internal processes, and learning and growth perspective, which are still used today. In addition to these traditional perspectives, new ones are emerging in line with the development of the 4th generation of a balanced scorecard (Ali, 2019). In terms of ensuring sustainable development, it is mainly an environmental, sustainability, or social responsibility perspective. Bititci et al. (2012) also mentioned the possibility of measuring performance outside the organization among business partners.
Despite the fact that the use of only financial indicators in measuring the performance of companies is often criticized, the financial perspective remains the most significant. This perspective measures the satisfaction of owners. The economic value added (EVA) is the most suitable indicator that can be used to measure satisfaction.
In addition to the EVA indicator, the indicators that will support the growth of the company's performance shall be chosen. These indicators include investment return rate, profitability, shareholder value, income growth, and unit costs. Unit costs, in particular, are among the delayed measures and indicate the organization's strategic success (Fooladvand et al., 2015). According to Sainaghi et al. (2013), the financial perspective aims to reach profitability. In this perspective, there are goals such as the value expressed by the indicators of economic value added, return on equity, return on assets, assets turnover, liquidity of the organization, or other financial goals ( Concerning the customer perspective, the company's values, goals, and measures are customer-oriented. These include values such as delivery, quality, performance, and type of communication (Fooladvand et al., 2015). According to Kaplan and Norton (1996) and Lesáková (2004), from a customer perspective, it is possible to use targets and measures focused on market share, which can be expressed as the number of customers, sales volume or number of products sold, new customers or new orders in absolute or relative terms, customer loyalty, customer satisfaction, or profitability.
The third balanced scorecard perspective is the internal business process perspective, which can include both short-term and long-term objectives (Kaplan & Norton, 1996). The critical processes that are effective in relation to the strategy are identified, and suitable indices for measuring process performance are determined (Fooladvand et al., 2015). The internal operating processes in businesses have to follow a plan of operating strategies, while businesses should do their best to achieve the expectations of their customers and shareholders (Wu et al., 2011). In line with it, the whole process starts with understanding customer requirements, innovation process, operation process, and after-sales service. Finally, it achieves customer requirements to establish evaluation indexes through all of these (Wu et al., 2011, p. 39).
According to Pandey (2005), it is the most critical perspective of the organization's success, as the internal business processes ensure the highest quality of products and services.
Concerning the perspective of growth and education, these main areas of learning and growth are defined: employee skills, information system skills, motivation, delegation of authority, and commitment. Most companies use employee goals to measure employee ability, which is taken from three groups of input measures: employee satisfaction, employee fluctuation, and employee productivity (Kaplan & Norton, 1996). From this perspective, it is possible to identify intangible and tangible backgrounds for ensuring strategic success. The strategic goals of this perspective are selected with regard to human capital, staff abilities, knowledge, technology, and organizational culture.
In recent years, in line with environmental concerns, there has been a trend of incorporating environmental and social indicators into the balanced scorecard (Krivokapić & Jovanović, 2009). According to Epstein (1996) 2015) do not focus on environmental aspects, but they prefer the sustainable balanced scorecard concept (sustainability balanced scorecard). However, it seems that there is no fundamental difference between these approaches. According to Krivokapić and Jovanović (2009), the sustainable balanced scorecard approach is predominantly oriented to formulating environmental strategies and social aspects of a business. Hsu and Liu (2010) researched balanced scorecard in more depth and formulated an environmental strategy based on a balanced scorecard. The output is an environmental strategy map.
The development of the balanced scorecard application also pointed to the fact that it is a method of implementation that helps to increase company performance ( Recently, data mining techniques have been used in various areas of business evaluation, not only when measuring the performance of businesses but also when predicting their bankruptcy. Their benefit is that they allow reducing a large number of indicators to a smaller number of key indicators for a given area of evaluation.
Therefore, the aim of the paper is to identify key performance indicators for Slovak heating companies based on the developed integrated performance measurement system. It is based on balanced scorecard principles and data mining techniques. The research question is: What financial indicators are the best measures and driving forces for increasing company performance? As a result, the study elaborates on the following hypotheses: H1: ROA is a key performance indicator for the analyzed sample of heat management companies.
H2: Total debt to total assets is a key performance indicator for the analyzed sample of heat management companies.

METHODOLOGY
The analysis sampled 292 Slovak companies within SK NACE 35 -"Supply of electricity, gas, steam, and cold air" -also known as the heating industry. In addition to certain industrial production processes, this industry is critical from a social point of view to ensure basic needs for everyday life. Therefore, it plays a key role within Slovak industries, which has been confirmed in recent years. The analyzed businesses represent local heat supply systems, which show characteristics of network industries (AOSR, 2013). They have to pay significant attention to environmental protection and renewable energy sources. The performance of analyzed businesses was assessed using liquidity and profitability ratios, debt management and assets management ratios, and operational ratios. Input data from financial statements were obtained from Slovak analytical agency CRIF -Slovak Credit Bureau (CRIF, 2022). Indicators were calculated with the use of formulas listed in Table 1. From these indicators, key performance indicators were selected.
To calculate the performance of businesses, EVA indicator was applied. The study used the following formulas to calculate EVA equity and EVA entity ( Table 2).  The most significant performance indicators selected by Lasso regression were used to create the financial perspective of performance measurement system based on balanced scorecard principles. Financial performance indicators were sup-plemented by non-financial ones arranged into customers, processes, learning and growth, and environmental perspective to create an integrated performance measurement system.

RESULTS AND DISCUSSION
The descriptive statistics of the financial indicators of heat management companies are listed in Table 3. In terms of liquidity, the average of CL achieved 1.417, which can be considered sufficient with regard to the given sector. However, the median of this indicator was significantly lower. The indicator NWCCA reached a negative value, which can be assessed negatively. Regarding assets management, the average CPP achieved a critical value of 711 days. Better was the median of this indicator, which achieved 226 days. However, to improve the performance of analyzed businesses and prevent their bankruptcy, the results of this indicator need to be improved. Another assets management indicator (which results need to be improved) is TATR. In terms of profitability, the mean of ROA is 4.5%, while its median is 4.4%. Better results were achieved in the case of ROE, with a mean of 15.4% and a median of 12.6%. In terms of debt management ratios, TDTA achieved similarly high values of average and median, confirmed by low values of average and median of ICR. In most of the analyzed companies, it is necessary to pay increased attention to the optimization of these indicators. Value of the indicator NCFD achieved on average 15%. Regarding operational ratios, the average is 1.005, while the median is slightly lower. Table 4 shows the results of the EVA indicator. Due to the large number of companies, the results were divided into intervals for better presentation. EVA equity achieved positive value in 163 businesses, which means that their perfor- The results presented in Table 4 indicate that there are more well-performing businesses than businesses with poor performance in the analyzed sample. When using the EVA entity indicator, the number of well-performing business-es was higher than some businesses with poor performance. It is given by the method of calculation and the fact that in the case of EVA entity, the result produced by the enterprise using mixed capital and the average price of mixed capital enter into the calculation. In the case of the capital structure of enterprises with a greater share of debt, it is more favorable than the equity price.
Lasso regression was used to select suitable financial performance drivers for performance measurement system (Table 5). The results of the Lasso regression confirmed the significance of the following financial indicators as performance drivers: total debt to total assets, labor to revenue ratio, netto cash flow to assets, return on costs, material intensity, short-term liabilities to assets, net working capital to total assets, return on equity and receivables turnover ratio. These results confirm H2: total debt to total assets is a key performance indicator for the analyzed sample of heat management companies.
On the other hand, the study rejects H1: ROA is not a key performance indicator for the analyzed sample of companies. Selected key financial performance indicators were used to create a financial perspective of a strategy management map ( Figure 1). Indicators for other perspectives were designed based on the secondary information of the analyzed companies. A strategy management map represents a basis for creating a performance measurement system in analyzed businesses. It contains strategic objectives which can be monitored with the use of strategic measures.
The top goal of the strategy management map is "to increase the value of the company" measured by the EVA indicator. The results of this synthetic perfor-   The choice of a balanced scorecard as a platform for the creation of performance measurement system was confirmed by Kaplan and Norton (1996)  This paper identified the following key financial performance indicators: total debt to total assets, labor to revenue ratio, netto cash flow to assets, return on costs, material intensity, short-term liabilities to assets, net working capital to total assets, return on equity, and receivables turnover ratio. Some of them were previously identified as key performance indicators. M. Hegazy and S. Hegazy (2012) proposed the following key performance indicators for the construction industry: current ratio, quick ratio, gearing, times interest, accounts receivable turnover, average collection period, inventory turnover, gross profit margin, profit margin, return on investment, and return on equity. Thus, this study concludes that some indicators are the same in the mentioned studies. However, some of them vary, which can be caused by various industries analyzed in the studies or different methods applied for indicators selection. In the future, other data mining techniques or mathematical and statistical methods can be used for indicator selection combined with balanced scorecard's principles.

CONCLUSION
The paper aimed to identify key performance indicators for Slovak heating companies using the integrated performance measurement system. Clearly, 74% of the companies from the given sample can be considered well-performing. These companies achieve a return on equity of 57% and current liquidity of 1.5. On the other hand, inefficient companies achieve a negative return on equity -30% and current liquidity of approximately 1.2.
In order to maintain and manage the performance of the analyzed sample of companies, it is necessary to build a balanced system of performance indicators. The top indicator is economic value added, a synthetic indicator whose value reflects the influence of all performance measurement system indicators. Despite criticism of the financial perspective, it plays the most crucial role in performance measurement systems.
The Lasso method was chosen for the selection of key financial indicators. The results discovered vital performance indicators of the studied sample. As it is necessary to pay attention to non-financial indicators when managing performance, the selection of financial indicators was supplemented by non-financial ones. Based on companies' business activities, four existing indices were supplemented with an environmental one according to the balanced scorecard methodology.
Therefore, future research should create a database of non-financial indicators for the industry and apply a suitable method to extract key non-financial performance indicators from the database. Also, the performance measurement system will be expanded to include the digitalization indicator focused on data collection in the business digitalization process.