Controlling in the Process of Development of the Energy and Heating Sector Based on Research of Enterprises Operating in Poland

Abstract

Enterprises operating in the energy and heating (E&H) sector play a particularly important role in the economy of each country. At the same time, the conditions in which they currently operate mean that the managers of these organizations have many decision-making problems that they have to deal with. They can be supported by the introduction of well-functioning controlling. This forces scientists to conduct extended research aimed at determining the current and future directions of development of controlling in E&H sector enterprises. At the moment, this is not a frequent field of research exploration. The area of research concerns issues related to the use of controlling in E&H sector enterprises. The objective of this paper is to present the results of the research obtaining knowledge on to what extent companies in the energy and heating sector use controlling tools helping them to increase efficiency of enterprises and effectiveness of the decisions made by managers. The scientific problem is looking for a way in which controlling can increase the efficiency of enterprises in the E&H sector and how it can improve the effectiveness of decisions made by managers. The general conclusion of the research is that it seems necessary to strengthen the role of controlling aimed at its transformation from reporting controlling to management controlling. In view of the challenges of the global economy related to the energy crisis, controlling should be used to a greater extent in the E&H industry to increase the efficiency of basic processes and to effectively implement modern management tools.

1. Introduction

Increasingly, economists are of the opinion that maximizing shareholder returns should not be the main goal of companies, given the complex environment in which they operate and the interactions that exist with various stakeholders. Maximizing the positive impact of enterprises on stakeholders is a new approach that contributes to the metamorphosis of business strategies of enterprises in various fields, especially those that generate negative social and environmental expansions, such as enterprises in the energy and heating sector (E&H) [1,2].

The increase in energy demand, the level of its consumption, climate change caused by economic and social development, limited resources, and the political situation in the world brought the recognition of the strategic importance of the companies from the E&H sector. This is also reflected in specific legal regulations and instruments regulating the activities of enterprises in this sector in the EU. The economic development of countries depends on access to energy. Looking at it through the prism of numbers, it should be stated that over the period 2010–2020, the global demand for electricity increased from 64.4 thousand PJ (petajoule) up to 82.0 thousand PJ, or 27.3% over eleven years. In Poland, the trend was also upward. Electricity consumption in Poland in 2010 amounted to 427 PJ, and in 2020 it was 494 PJ, which is 15.7% more. As for heat energy, global consumption increased from 11.5 thousand PJ in 2010 to 12.9 thousand PJ in 2020, so by 12.2%. During this period, Poland saw a decrease in demand from 274 PJ in 2010 to 235 PJ in 2020 (a change of −14.2%).

The energy sector is not uniform. It consists of companies that constitute the elements of value chain of energy supplied to the end user. In addition, the characteristics of the energy market determine its dissimilarity in comparison with traditional commodity markets, as well as with the financial market [3,4]. From the institutional side, the electricity market in 2020 in Poland was dominated by the three largest entities (PGE Polska Grupa Energetyczna S.A., ENEA S.A., TAURON Polska Energia S.A.), which accounted for approximately 62% of electricity production [5]. In the case of thermal energy production, the market is more diversified. In Poland, at the end of 2020, there were 387 companies operating on the regulated heat market that held concessions for the production, transmission and distribution as well as heat trading [6].

Energy companies, while conducting business activity, are also obliged to ensure the continuity of energy supplies, while being supervised by governments. They are also subject to other systemic regulations at national and international levels. Energy sector companies are important for the economy because, on the one hand, they are obliged to ensure energy security, and on the other hand, they can lead to energy poverty, because the increase in energy prices directly affects consumers’ access to energy [7,8].

On the one hand, companies operating in the E&H sector play a particularly important role in the economy of each country; on the other hand, the conditions in which these entities currently operate mean that the managers of these organizations have many decision-making problems they have to deal with. The solution is to introduce well-functioning controlling to these enterprises, which supports managers in making the right decisions. This forces scientists to conduct extended research aimed at determining the current and future directions of development of controlling in enterprises of the energy sector [9,10]. At the moment the vast majority of authors focus only on selected aspects of controlling, its instruments, or the process of implementation in enterprises of the E&H sector. Therefore, the area of research presented in this paper concerns issues related to the use of controlling in E&H sector enterprises.

The objective of this paper is to present the results of the research obtaining knowledge to what extent companies in the Energy and Heating sector use controlling tools helping them to increase efficiency of enterprises and effectiveness of the decisions made by managers.

The scientific problem is looking for a way in which controlling can increase the efficiency of enterprises in the E&H sector and how it can improve the effectiveness of decisions made by managers.

The research presented in this paper has been discussed in six parts. After the Section 1, Section 2.1 presents a literature review on the concept of controlling and its role in an enterprise management. Section 2.2 elaborates on the current scientific achievements in the area of research on the use of controlling in E&H sector enterprises. Section 3 discusses the applied research procedure and data sources. The results of the research are presented in Section 4. Finally, in Section 5, a discussion and conclusions from the conducted research are formulated.

2. Theoretical Framework

2.1. Review of the Research in the Field of Controlling

The concept of controlling does not have a uniform definition in the world literature. Different schools of thought around the world have different views, and numerous authorities in the field of management indicate helplessness in trying to organize this concept. Preissler rightly states that “everyone has their own ideas about what controlling means or should mean, only that everyone thinks something different” [11]. The multiplicity of definitions is also caused by the use of controlling in many different enterprises with different organizational or financial situations. The fact that controlling may concern many functional areas also affects the multitude of concepts. One of the reasons for many different theories may be the ambiguity of the English word “to control”.

The Americans and Germans had the greatest influence on shaping the term controlling. The American approach to controlling assigns it the task of monitoring current results and constantly comparing them to planned assumptions, as well as forecasting and providing managers with various information that can serve the implementation of the company’s goals. For this reason, the American controller is more identified with the finance and accounting department, and his duties are similar to those of the European chief accountant. Controlling plays an advisory role in the management process. For German scientists, controlling is a more comprehensive process that includes a wide range of instruments for managing and controlling the company’s finances, while the controller’s attention is focused on all departments of the company. Controlling not only supports the functions of the management process, but even creates them; hence, it can be said that it is a management system. The differences between these two fundamental approaches to controlling are presented in

Table 1. Controlling functions according to the German and American schools.

Functions	Germany				USA
	Controlling				Management Control (Controllership)
Controlling Functions	Horvath	Kupper	Vollmuth	Weber	Anthony	Belkaoui	Horngren	Kaplan
Information flow	T	T	T	W/T	P	P	P/T	P
Planning	T	T	T	W/T	P	P	P	W
Control	T	T	T	W/T	P	P	P	W
Leading a team	-	T	T	W/T	W	W	P	W
Organization	-	T	T	W/T	W	W	T	W
Coordination	G	G	G	G	G	G	G	G

W—Function support, P—Taking over some functions, T—Creating a function, G—Depth of a function; Source: own elaboration based on: [12,13,14,15,16,17,18,19].

.

In the literature on the subject, controlling is understood ambiguously as: a philosophy [20,21,22], system [23,24,25], management method [26,27], or management tool [28,29,30,31]. It is associated with management systems and perceived as “managerial control” [32,33,34], or as “management control and accounting” [35,36,37]. Many scientists believe that the idea of controlling is now also expressed in management accounting [38] and [23] (p. 19). More and more frequently among researchers of the subject, the concept of controlling is sometimes called performance management [39,40,41,42,43]. The multitude of definitions, terms and interpretations indicate various areas and functions of controlling, presenting different ways of understanding it both by management theoreticians and practitioners. Research [44,45,46,47] presents detailed characteristics of controlling, its tasks, possible competencies and importance for the management system.

Understanding controlling as a tool to support managers determines its positive features, among which are: lowering costs, increasing profits, increasing work efficiency, and developing effective strategies and structures that facilitate the decision-making process by improving the information system or profitability analysis in various functional areas of the company [48].

The concept of controlling in its contemporary meaning was created in German countries and it is perceived as a subsystem supporting organization management [23]. Similarly, it is characterized as support for planning and coordination subsystems [49], or as coordination of the management system in terms of solving various types of decision-making tasks [50].

In his research, Mocanu states that controlling is an important method supporting management, it is one of the most frequently used management methods, and it is associated with a relatively large polemic related to its different perceptions [51]. The issue of controlling, due to its high applicability, is often taken up in scientific research. The works carried out by foreign and Polish scientists concern enterprises with various types of activity and from various sectors of the economy. Research conducted by Abdel-Kader and Luther [52] seeks to find out why companies adopt different practices in the field of management accounting and what the process of change in this area looks like [53]. There are also studies on the impact of variously understood managerial control strategies on the financial results of the surveyed organizations [54,55,56,57,58,59,60,61]. Schäffer and Binder present extensive considerations pointing to the development and use of management accounting and management control research in German-speaking countries [62].

Research on the use of controlling in the economy is conducted by many scientists from various foreign universities. The leaders are mainly scientists from research centres in Germany and the USA, conducting multidimensional research on enterprises using controlling [63,64,65,66,67,68,69,70,71]. The ICV (Controller-Verein e.V.—Wörthsee, Germany), founded in 1975, is of great importance for expanding knowledge on controlling solutions in the economy, which prepares numerous reports containing guidelines for controlling [72]. Extensive information on the development of controlling tools in the practice of German enterprises can be obtained on numerous Internet portals [73,74,75,76]. In Poland, the issue of controlling is a field of exploration pursued by many scientists. These studies are conducted mainly at the Cracow University of Economics, the Wrocław University of Economics, and the Wrocław University of Technology, with the support of scientists from other academic centres in Poland [77,78,79,80,81,82,83,84,85,86,87,88].

2.2. Controlling in Companies from the Energy and Heating Sector

Scientific considerations over the last few decades also concern the use of controlling in management within the energy sector enterprises. However, their number is relatively small, compared to the research on typically productive sectors of the economy. In manufacturing enterprises, a distinction is usually made between the primary activity related to the production of specific products and services and the auxiliary activity, the primary task of which is to support the core activity. However, the organization of manufacturing processes in energy sector enterprises is more complicated and, therefore, model controlling solutions are significantly diversified, from the method supporting management [89,90] to the implementation of its selected tools [91].

Scientific considerations regarding the energy sector indicate that Polish enterprises are often characterized by a management approach based on management accounting and budgeting. They use traditional tools in the form of budgets and financial evaluation indicators more often than more advanced controlling instruments [92,93,94,95]. A common controlling tool, implemented in practice, are models of systematic cost accounting, the implementation of which is to help in providing relevant and useful information about the costs of the company’s activity [96]. In Polish research, we will also find references to the possibility of using problem-based cost accounting in energy sector enterprises, such as ecology cost accounting [97] or quality cost accounting [98]. An analogy can also be found in scientific research conducted on the example of Slovak enterprises, also from the energy sector [99].

The increase in the demand for information on the costs of energy production and transmission reported by the management staff, and on the other hand, the growing complexity of the processes of supplying individual types of energy, the significant diversity of energy consumers and products, and the increase in the share of indirect costs, became the basis for the development of management accounting instruments used in enterprises of the energy sector, especially in relation to activity-based costing [100,101,102,103,104].

As indicated by the researchers of the subject, companies from the energy sector are also looking for more advanced controlling tools that respond to the new approach to management—management by value. This idea considers the process of creating company value in terms of activities. According to this concept, energy company is as a whole composed of processes and activities aimed at creating value. Few studies in this area in the energy sector indicate that the integration of activity-based costing and the EVA method increases the effectiveness of enterprise management. The combination of these methods makes it possible to identify activities that reduce a company value, which should be modified or eliminated [103,105,106].

In the literature on the subject, there are also studies indicating that limited energy resources and energy security concerns in relation to alternative energy sources prompt the use of product life cycle analysis (LCA) to analyse sensitivity and compare the level of costs for different energy sources. The research points out that the concept of a product life cycle management (LCM) aims to minimize the environmental and socio-economic burdens associated with the product throughout its life cycle. It is emphasized that one of the directions of development of controlling in the energy sector should be the use of this tool by investors and decision makers in the process of making decisions regarding sustainable development [107,108,109].

Additionally, of interest are the studies indicating the potential of personnel controlling and the system of human capital valuation indicators in energy enterprises [45]. Some studies emphasize the importance of financial controlling and its impact on the results and efficiency of operations [110], or the possibility of using the balanced scorecard (BSC) as an instrument of strategic controlling, which can effectively support the management processes of a company operating in the E&H industry [111].

Few studies in the energy sector include: verification of the levels of use and use of BSC, the impact of individual characteristics, the most commonly used metrics and the characteristics of its effective implementation. Despite the widespread use of this instrument in many sectors of the economy, as scientific considerations show, it is not a popular controlling instrument in energy enterprises. The authors point to the need to implement BSC in these entities, for example through benchmarking on other industries where BSC was used, which should lead to faster and better results in the energy sector [112,113].

In the processes supporting project management in energy enterprises, real and adequate use should be made of project controlling [82]. The subject of consideration of researchers is also the use of controlling from the conceptual and organizational side in the process of restructuring enterprises from the energy sector [89,114,115,116].

Due to the nature of the E&H sector, scientists pay attention to another research area, which is the scope and effectiveness of implementing operational tools and strategic controlling in energy companies towards sustainable development and corporate social responsibility [117].

In recent years, the field of exploration has been the practice of management accounting in the field of obtaining environmental information for managers, the so-called environmental management accounting [118,119]. Many researchers [120,121] draw attention to the use of environmental reporting, with particular emphasis on the energy sector, asking how accounting and management systems introduced in enterprises can reduce their negative impact on sustainable development [122].

The literature on the subject also indicates the need to develop controlling tools for managing carbon dioxide emissions, not only in energy sector companies (so-called carbon accounting) [123,124].

In recent decades, we have been dealing with regulations’ changes in many areas, including the energy sector, not only in Poland, but also in other countries. When talking about regulation, we mean widely existing (and sometimes emerging) law, other legal requirements, standards and generally recognized guidelines. Currently, scientific considerations indicate the need to conduct theoretical and empirical research in the field of controlling, management accounting in the area of regulation to which the energy system is subject. Many of these regulatory changes come with disclosure and transparency requirements. So, there is a need to test them causally, not just to document it [125].

Research conducted by Kowalewski and Lelusz [126] showed that, in the opinion of managers, often the main reason for implementing controlling in an enterprise from the energy sector is the need to systematize planning and analyses. However, the main barrier to its implementation is the insufficient knowledge of employees on this subject. According to the managers, the most important positive effects of the implementation of controlling in the E&H sector are: the organization of the division of tasks and goals to be achieved in individual organizational units as well as the increase in the professionalism of employees. The research also looks for factors determining the success of the implementation of controlling in companies from the energy sector [127].

Due to the strategic nature of this sector for the economy, E&H is subject to many legal regulations, indicated in the Energy Law [128]. The obligations of companies in this sector include the preparation of a number of industry reports indicated by the Energy Regulatory Office. Reporting obligations are also imposed by the Accounting Act [129], tax laws or requirements of other public and local government institutions. This applies to reporting not only financial data, but also qualitative and non-financial data. This multidimensional reporting system requires ordering and synchronization, which is ensured by well-implemented and updated reporting controlling. Hence, in the further part of the work, the results of the original research presenting the current state of the use of controlling in enterprises of the energy and heating sector in Poland are presented.

3. Data and Descriptive Statistics

Research Procedure and Data

The research procedure was adapted to the research objectives of this paper.

In the years 2013–2022, the research was conducted with the aim to determine the state of maturity of the use of controlling in enterprises operating in Poland. In the empirical research, a non-probability method of sampling (purposive sampling) was used to enable obtaining the results that were as representative as possible for the E&H registered companies. E&H firms from the companies register databases were approached. The respondents were the management representatives, including both the top management level, as well as directors or operational managers and controllers of E&H companies. The respondents were mainly employees who understood the problems posed in the research survey.

The surveys were carried out using a business intelligence IT system called Business Navigator [130] by Archman sp. z o.o. from Krakow and the Google survey system [131]. The Business Navigator system has a survey module that supports large-scale research and enables the presentation of results in any layout. Its key functionalities include: fully independent user-defined surveys and directing them to selected respondents; defining serial surveys, created and sent automatically by the system after previously defining the sending parameters; and managing access to the results for selected people. The survey was initially prepared in a spreadsheet and then transposed to the Business Navigator IT system and the Google survey system. The next step was to register the respondent’s e-mail address, after obtaining his consent to participate in the study. From the IT system, the questionnaire was directly and automatically sent by e-mail to the respondent with a request to complete it. The time of starting work on the survey was recorded in the system, thanks to which it was possible to obtain information about the number of survey participants on an ongoing basis. The respondent was able to stop filling in the survey at any time, save the results, and return to it at a convenient time. After completing the questionnaire, the respondent received an automatic e-mail informing him that sending the questionnaire was successful. As a token of gratitude for their time, the respondents received an electronic version of the monograph entitled “Controlling. Assessment System of Performance Responsibility Centres.” [132].

First, the questionnaire was sent to a selected group of 30 respondents (pilot studies), people who worked in controlling positions. They were asked to complete the questionnaire and indicate their comments, both substantive and technical, regarding the transparency and understanding of the questionnaire. The purpose of such action was the need to verify the research tool in such a way that it was detailed on the one hand, but on the other hand did not lead to its negative reception by the respondents. The collected comments were used to develop the second version of the questionnaire, slightly reduced in size, which was sent to 884 respondents who declared their willingness to participate in the research. The database of potential respondents was developed on the basis of initial interviews with employees of the managerial level and those employed in the financial and controlling departments of organizations operating in Poland. A fully completed questionnaire was submitted by 289 respondents (32.7% of the total research frame). A total of 595 (67.3%) surveys were not returned, with 195 (22.0%) respondents starting surveys but not completing them. Some of the respondents who did not complete the questionnaire indicated that after reading the detailed questions, they were not able to answer the questions in a professional and reliable way. They argued that they have a lack of knowledge on the subject of the conducted research.

The survey consisted of six thematic areas of various volumes. In addition, in order to obtain knowledge about the respondent, a detailed specification about them and the company they represent was included. In the survey, it was also decided to use the formula of open questions, allowing the respondents to comment more extensively on specific problems. The commentaries supplemented the answers with valuable—from the research point of view—opinions of people completing the survey.

This publication presents the results of research conducted in the areas of: organization of controlling functions, accounting recording solutions, cost accounting and cost management tools, management reporting and budgeting. The survey consisted of 103 questions, the vast majority of which were closed questions, and the respondents could add comments to their answers each time. The presented results include selected questions considered important in the course of the conducted analyses.

In the first step, the collected empirical material was analysed. The aim of the research was to analyse the controlling solutions used in companies in the energy and heating industry against the background of solutions used in enterprises of other industries. The analysis began with the presentation of the research sample. The collected empirical material covering 289 companies operating in Poland was presented, including 51 entities included in the energy and heating (E&H) industry. It should be noted that only the binding answers provided by the respondents were analysed. Missing answers and or “I do not know” answers were omitted. The energy and heating sector companies were characterized against the background of other companies (Others). Then, selected areas of controlling were analysed, looking for features characteristic of solutions used in energy and heating.

The empirical material was analysed and statistically inferred. The analyses were conducted primarily with the use of contingency tables as well as multiple-response and dichotomy tables; the descriptive statistics of defined variables were inspected and tests concerning the analysis of variance were performed. The analysis of the relationship between the variables was tested with Pearson’s chi2 and maximum likelihood chi2 statistics, taking into account Yates’ corrections for lower expected numbers. In addition, the assessment of the strength of the relationship between the variables was identified by Pearson’s convergence coefficient and Spearman’s rank correlation coefficient.

4. Empirical Framework

4.1. Characteristics of Companies in the Energy and Heating Industry

The analysed sample included companies with various characteristics. The identified size classes of entities were similar in terms of numbers: large companies—40%, medium-sized companies—29%, and small companies—31%. The sample was dominated by entities with over 15 years of experience on the market, as mature companies constituted 65% of all respondents. Companies with dominant production activity (42%) were represented similarly to companies with dominant service activity (46%), while companies with dominant commercial activity represented 12% of the total. Most of the analysed entities operated in conditions of high competition (45%) and offered specialist products (57%), acting for the mass client (75%).

E&H companies accounted for 18% of the analysed sample.

Table 2. Features of the research sample.

Panel A: Analysis Results in Two-Way Tables
Industry/Feature		Company Size				Period of Operation				Competition
		Big	Medium	Small	Total	Mature	Medium	Young	Total	Big	Medium	Small	Total
E&H	Count A	25.0	15.0	11.0	51	36.0	13.0	2.0	51	9.0	22.0	20.0	51
	Expected count B	20.6	14.6	15.7	51	33.4	13.9	3.7	51	22.9	18.5	9.5	51
	A-B	4.4	0.4	−4.7	0	2.6	−0.9	−1.7	0	−13.9	3.5	10.5	0
Others	Count A	92.0	68.0	78.0	238	153.0	66.0	19.0	238	121.0	83.0	34.0	238
	Expected count B	96.4	68.4	73.3	238	155.6	65.1	17.3	238	107.1	86.5	44.5	238
	A-B	−4.4	−0.4	4.7	0	−2.6	0.9	1.7	0	13.9	−3.5	−10.5	0
Total	Count A	117	83	89	289	189	79	21	289	130	105	54	289
Panel B: Statistics
Pearson’s chi-squared test (χ2)		2.836	p = 0.242			1.285	p = 0.525			25.046	p = 0.000
Maximum-likelihood chi-squared		2.941	p = 0.229			1.436	p = 0.487			24.933	p = 0.000
Phi coefficient (φ)		0.099				0.067				0.294
Pearson’s contingency coefficient (C)		0.098				0.066				0.282
Spearman rank correlation coefficient (ρ)		−0.0484	p = 0.411			−0.057	p = 0.332			0.0658	p = 0.267
Panel A: analysis results in two-way tables
Industry/Feature		Product–market relationship					Dominant capital			Dominant type of activity
		mass product, many customers	specialized product, many customers	specialized product, few customers	mass product, few customers	Total	Public	Private	Total	Production	Trade	Services	Total
E&H	Count A	22.0	16.0	8.0	5.0	51	21.0	30.0	51	22.0	10.0	19.0	51
	Expected count B	19.8	18.4	10.9	1.9	51	14.5	36.5	51	21.2	6.2	23.6	51
	A-B	2.2	−2.4	−2.9	3.1	0	6.5	−6.5	0	0.8	3.8	−4.6	0
Others	Count A	90.0	88.0	54.0	6.0	238	61.0	177.0	238	98.0	25.0	115.0	238
	Expected count B	92.2	85.6	51.1	9.1	238	67.5	170.5	238	98.8	28.8	110.4	238
	A-B	−2.2	2.4	2,9	−3.1	0	−6.5	6.5	0	−0.8	−3.8	4.6	0
Total	Count A	112	104	62	11	289	82	207	289	120	35	134	289
Panel B: Statistics
Pearson’s chi-squared test (χ2)		7.486	p = 0.057				4.994	p = 0.025		4.021	p = 0.133
Maximum-likelihood chi-squared		6.234	p = 0.100				4.725	p = 0.029		3.732	p = 0.154
Phi coefficient (φ)		0.160					−0.131			0.117
Pearson’s contingency coefficient (C)		0.158					0.130			0.117
Spearman rank correlation coefficient (ρ)		−0.0138	p = 0.814				−0.131	p = 0.025		−0.054	p = 0.354

presents the characteristics of the sample broken down by the E&H sector and other entities. Companies from the E&H industry did not differ from others in terms of size and time of operation on the market, as well as in terms of the subject of activity. The homogeneity of these features in the two surveyed groups is important from the point of view of the analysis of controlling solutions observed in the E&H sector against the background of the entire sample. E&H companies in the analysed sample operated in conditions of low and medium competition much more often than in the Others group. This relationship was clear and observed at any low level of confidence. Similarly clear differences were observed for the dominant capital feature. E&H companies in the analysed sample definitely more often represented entities with dominant public capital. There were also surpluses of the observed frequencies over the expected ones for offering a mass product for both narrow and mass customers, with the statistics confirming the significance of this relationship for 0.05 < p < 0.1.

4.2. Organization of the Controlling Function in the Energy and Heating Industry

The results of the analyses concerning the organization of the controlling function are presented in

Table 3. Organization of the controlling function in the surveyed entities.

Panel A: Analysis Results in Two-Way Tables
Industry/Feature		Controlling Cell			Type of the Cell			Place in the Structure			Dependence
		No	Yes	Total	Single- Position	Multi-Position	Total	Line	Staff	Total	Management	Director of Finance	Chief Accountant	Total
E&H	Count A	8.0	43.0	51	4.0	40.0	44	38.0	13.0	51	23.0	21.0	7.0	51
	Expected count B	19.1	31.9	51	7.8	36.2	44	30.7	20.3	51	21.3	27.1	2.7	51
	A-B	−11.1	11.1	0	−3.8	3.8	0	7.3	−7.3	0	1.8	−6.1	4.3	0
Others	Count A	96.0	130.0	226	29.0	112.0	141	83.0	67.0	150	61.0	77.0	3.0	141
	Expected count B	84.9	141.1	226	25.2	115.8	141	90.3	59.7	150	58.8	74.9	7.3	141
	A-B	11.1	−11.1	0	3.8	−3.8	0	−7.3	7.3	0	2.3	2.1	−4.3	0
Total	Count A	104	173	277	33	152	185	121	80	201	80	102	10	192
Panel B: Statistics
Pearson’s chi-squared test (χ2)		12,737	p = 0.000		3.013	p = 0.082		5.841	p = 0.015		10.217	p = 0.006
Maximum-likelihood chi-squared		14,153	p = 0.000		3.391	p = 0.065		6.087	p = 0.013		8.750	p = 0.012
Phi coefficient (φ)		0.214			0.127			−0.17			0.230
Pearson’s contingency coefficient (C)		0.209			0.126			0.168			0.224
Spearman rank correlation coefficient (ρ)		0.214	p = 0.000		0.127	p = 0.083		−0.170	p = 0.015		0.108	p = 0.135

Source: own study.

. The vast majority of the analysed E&H companies distinguished the controlling function in the organizational structure. 84% of the analysed entities declared institutional separation of this function. This share is definitely higher than in the case of other companies (58%) and the entire sample (62%). It was observed that E&H companies form controlling structures. The need to use controlling tasks seems to be present in the E&H industry, regardless of the size and time of operation of the entity on the market. Among the eight companies in which the controlling unit was not separated, there were mainly entities of medium size and average experience in the market; in three of them; the performance of controlling tasks was declared in a non-institutional form, by assigning tasks to other organizational units; and in three companies, the performance of the function was declared by an outsourced service. It is noteworthy that the implementation of controlling tasks in the E&H industry generally requires the creation of complex multi-station structures. The functioning of such structures was declared by as many as 51% of the surveyed companies and 40% of multi-position structures; only in 9% of the cases was it declared that the controlling task was handled by a single position separated in the organizational structure.

The results regarding the location of controlling tasks in the organizational structure seem surprising. Three out of four analysed companies in the E&H industry distinguish the controlling unit on the line position as one of the company’s functions. The results of the conducted analyses clearly indicate that this feature distinguishes the analysed E&H companies from the other analysed entities. The differences are significant and their statistical significance has been clearly confirmed. The results are surprising, because modern controlling tasks seem to be staff orientation in the organizational structure, which was recorded only in 25% of E&H companies, compared to 55% in other companies, taking into account that a significant part of them does not distinguish controlling structures at all.

Statistical analysis shows that the direct subordination of controlling structures to the organizational structure is also a feature that distinguishes E&H companies from others. E&H companies more often than other surveyed entities subordinate their controlling unit to chief accountants and directly to the management board. Significantly less often, however, it is subordinated to the financial director. The significance of these differences in this area between the studied E&H entities and Others was confirmed statistically at a low level of confidence. This relationship seems to be worth mentioning, as it indicates that the controlling unit very often supports the reported tasks assigned to accounting departments. An interesting analysis would also be supplementing the applications with verification of how often the position of CFO is separated in E&H companies.

4.3. Accounting Records of Economic Events

Table 4. Responsibility centres in the audited entities.

Panel A: Analysis Results in Two-Way Tables
Industry/Feature		Responsibility Centres			Investment Centres
		NO	YES	TOTAL	NO	YES	TOTAL
E&H	Count A	12.0	33.0	45	29.0	22.0	51
	Expected count B	17.5	27.5	45	39.5	11.5	51
	A-B	−5.5	5.5	45	−10.5	10.5	0
Others	Count A	88.0	124.0	212	195.0	43.0	238
	Expected count B	82.5	129.5	212	184.5	53.5	238
	A-B	5.5	−5.5	0	10.5	−10.5	0
Total	Count A	100	157	257	224	65	289
Panel B: Statistics
Pearson’s chi-squared test (χ2)		3.440	p = 0.063		15.142	p = 0.000
Maximum-likelihood chi-squared		3.586	p = 0.058		13.501	p = 0.000
Phi coefficient (φ)		0.115			0.228
Pearson’s contingency coefficient (C)		0.114			0.223
Spearman rank correlation coefficient (ρ)		0.115	p = 0.064		0.228	p = 0.000

Source: own study.

presents the results regarding the scope of separating the centres of responsibility. 75% of the surveyed companies from the E&H sector indicated that they create responsibility centres. This result is higher than in Others entities, where it is about 58%. It has been observed that E&H companies create use more responsibility centres.

The analysis of solutions in the field of recording economic events was carried out primarily in terms of the method of separating the centres of responsibility. In the survey, respondents were asked what type of responsibility centres are created, indicating the following options: department, employee, process, type of cost, type of activity, device, task/project, investment sentence and order. The question also contained an open answer, other, where the respondent could indicate any number of other centres of responsibility used.

On the basis of the answers obtained, a synthetic variable counting how many different types of responsibility centres were identified was defined. The results obtained in this regard, broken down by E&H and Others, are presented in

Table 5. Number of different types of responsibility centres in the surveyed entities.

Panel A: Descriptive Statistics
Industry	N Valid	Mean	Trimmed Mean	Winsor Mean	Median	Minimum	Maximum	Q3	Q1	Standard Deviation
E&H	37	2.730	2.636	2.676	2.000	1.000	6.000	2.000	4.000	1.427
Others	138	2.080	1.984	2.036	2.000	1.000	5.000	1.000	3.000	1.153
Panel A: Variance tests
t	−2.890		p = 0.004
quotient F	1.532		p = 0.085

Source: own study.

. The results indicate that the surveyed E&H companies distinguish definitely more types of responsibility centres than other entities. The significance of these differences was confirmed by the conducted statistical analyses. Further analysis was carried out at the level of selected types of responsibility centres. Significant differences were identified primarily in relation to investment tasks. The results in this regard are presented in Table 5. Companies from the E&H sector definitely more often than other analysed entities identify centres dedicated to the implemented investments in the records system. The differences in this respect between E&H and Others are clear and reported as statistically significant at any low level of confidence. This seems to be directly related to the specificity of E&H activities, which usually require significant investments in production or network infrastructure related to energy supply.

It should be assumed that separating a given type of responsibility centre requires the organization of dedicated recording tools, most often an account segment in the records of economic events. The analysis of the tools for recording economic events presented in

Table 6. Accounting record tools used in the surveyed entities.

Panel A: Analysis Results in Two-Way Tables
Industry/Function		Document Workflow Tools				System of Cost Record Accounting
		Absence	ERP	Dedicated	TOTAL	Dedicated	Accounting System	TOTAL
E&H	Count A	32.0	10.0	2.0	44	5.0	35.0	40
	Expected count B	32.4	5.5	6.1	44	8.6	31.4	40
	A-B	−0.4	4.5	−4.1	0	−3.6	3.6	0
Others	Count A	144.0	20.0	31.0	195	47.0	154.0	201
	Expected count B	143.6	24.5	26.9	195	43.4	157.6	201
	A-B	0.4	−4.5	4.1	0	3.6	−3.6	0
Total	Count A	176	30	33	239	52	189	241
Panel B: Statistics
Pearson’s chi-squared test (χ2)		5.841	p = 0.015			2.335	p = 0.126
Maximum-likelihood chi-squared		6.088	p = 0.013			2.587	p = 0.107
Phi coefficient (φ)		−0.17				0.098
Pearson’s contingency coefficient (C)		0.168				0.097
Spearman rank correlation coefficient (ρ)		−0.17	p = 0.015			0.098	p = 0.127

Source: own study.

shows that, in most cases, E&H companies keep records of costs directly in the financial and accounting system, without separating data relevant for management reporting outside these systems. This feature does not distinguish E&H companies from practices recorded in other entities.

The way of document circulation also distinguishes the E&H industry from the rest. Nearly 73% of the companies declared the lack of any tools supporting the circulation of documents and indicated the paper circulation of documents. This ratio is comparable to that recorded in the Others group, where it is 74%. It should be added, however, that these data were collected 5 years ago; hence, it should be assumed that the current state of use of systems supporting the circulation of documents is greater in both groups. Irrespectively, what draws attention in the obtained results is the fact that E&H companies use ERP systems directly for the circulation of documents. Both reported dependencies—more frequent use of ERP systems to handle more extensive cost accounting than observed in the Others segment and more frequent use of ERP for document circulation may be important when formulating requirements for these systems for the E&H industry.

4.4. Cost Accounting and Cost Management Tools

Further analyses of controlling solutions focused on the applied cost accounting. The results of selected analyses are presented in

Table 7. Cost accounting and cost management in the surveyed enterprises.

Panel A: Analysis Results in Two-Way Tables
Industry/Feature		Variable Costing			Full-Absorption Costing			Activity-Based Costing			Cost Accounting Records System				Time Accounting			Margin Model
		No	Yes	Total	No	Yes	Total	No	Yes	Total	Excel	Dedicated	Accounting System	Total	No	Yes	Total	No	Yes	Total
E&H	Count A	37.0	14.0	51	29.0	22.0	51	47.0	4.0	51	2.0	6.0	41.0	98	17.0	34.0	51	16.0	9.0	25
	Expected count B	26.6	24.4	51	25.2	25.8	51	45.7	5.3	51	4.1	12.0	32.9	49	33.0	18.0	51	13.7	11.3	25
	A-B	10.4	−10.4	0	3.8	−3.8	0	1.3	−1.3	0	−2.1	−6.0	8.1	49	−16.0	16.0	0	2.3	−2.3	0
Others	Count A	114.0	124.0	238	114.0	124.0	238	212.0	26.0	238	18.0	53.0	120.0	191	170.0	68.0	238	106.0	92.0	198
	Expected count B	124.4	113.6	238	117.8	120.2	238	213.3	24.7	238	15.9	47.0	128.1	191	154.0	84.0	238	108.3	89.7	198
	A-B	−10.4	10.4	0	−3.8	3.8	0	−1.3	1.3	0	2.1	6.0	−8.1	0	16.0	−16.0	0	−2.3	2.3	0
Total	Count A	151	138	289	143	146	289	259	30	289	20	59	161	289	187	102	289	122	101	223
Panel B: Statistics
Pearson’s chi-squared test		10,228	p = 0.001		1.349	p = 0.245		0.429	p = 0.512		7.675	p = 0.021			26.689	p = 0.000		0.981	p = 0.321
Maximum-likelihood chi-squared		10,591	p = 0.001		1.352	p = 0.244		0.457	p = 0.499		8.438	p = 0.014			25.564	p = 0.000		0.996	p = 0.318
Phi coefficient (φ)		−0.18			−0.06			−0.03			0.178				0.303			−0.066
Pearson’s contingency coefficient (C)		0.184			0.068			0.038			0.176				0.290			0.066
Spearman rank correlation coefficient (ρ)		−0.18	p = 0.001		−0.060	p = 0.246		−0.03	p = 0.514		0.176	p = 0.006			0.303	p = 0.000		−0.066	p = 0.324

Source: own study.

. Based on the observations made, it is difficult to identify cost accounting solutions dedicated or preferred in the E&H industry. The observations made indicate that respondents from E&H pointed to the use of variable costing much less often than other market segments. The results confirm the statistical significance of these differences at any low level of significance. There was an excess of the observed numbers over the expected ones in the case of full cost accounting in E&H companies, but the analyses did not confirm that this segment differed from the others in a statistically significant way. The use of problem costing, including activity-based costing in the observed E&H group, was low and amounts to about 8%. The observed use of these cost accounts in the Others group was also low and amounts to approximately 15%. Statistical analysis, however, does not allow accepting the hypothesis that the use of these cost management tools differs significantly in both analysed groups.

Differences between the groups were noted in terms of cost accounting techniques and tools used. E&H companies more often apply tasks related to cost settlements directly to ERP systems; similar dependencies have already been identified in other areas. The use of dedicated tools (controlling systems) or even a spreadsheet for tasks related to cost settlement is observed less often in the E&H industry than in other analysed entities.

In the conducted research, the types of cost settlements were analysed. Respondents were asked both what cost settlements are performed and what are the basis for these settlements. Selected results are summarized in Table 7 and

Table 8. Number of types of billing keys used.

Panel A: Descriptive Statistics
Industry	N Valid	Mean	Trimmed Mean	Winsor Mean	Median	Minimum	Maximum	Q3	Q1	Standard Deviation
E&H	50	1.580	1.477	1.540	1.000	1.000	4.000	2.000	0.859	1.427
Others	216	1.667	1.567	1.662	1.000	1.000	5.000	2.000	0.950	1.153
Panel A: Variance tests
t	0.591	p = 0.555
quotient F	1.222	p = 0.408

Source: own study.

. The conducted analysis showed that respondents most often indicated the use of one type of cost carrier, average 1.5, with a choice of: natural units (pcs., kg, etc.), direct costs, internally defined price lists, transfer pricing rates, agreed percentages, normative costs, person-hours according to registered working time and others with the option of indicating any other settlement bases.

There were no significant differences in the number of cost carrier types used between the companies classified in the E&H and Others groups. However, differences in the frequency of use of particular types of carriers were identified. Companies in the E&H industry use time-based cost settlements more often than observed in other entities. The excess of observed observations over expected observations is significant and confirms the statistical significance of the conclusion.

There were also no differences as to the introduction of controlling reporting models for the profit and loss account in the form of a multi-block margin account. Only 36% of respondents from the E&H industry indicated that the companies they represent create this type of model, in the group of other companies, the corresponding indicator is 46%. The small number of observations recorded in this respect for E&H does not allow us to confirm the statistical significance of the observed differences.

4.5. Role and Tasks of Controlling

The scope of activities undertaken by the controlling structures created in the surveyed enterprises was also analysed. The survey indicated typical activities carried out by the controlling department, asking the respondents to indicate whether the given activities are undertaken and what percentage of time the controllers spend on their performance. The analysed tasks included: supporting strategic planning, budgeting and cost control, providing information from the environment, providing management tools, coordination of planning and control, monitoring goals, operational tasks of employees, budgets and implementation of strategic tasks, internal and external reporting, creating analyses and reports on the company’s environment and internal financial statements, implementation of new and optimization of existing IT tools, support for planning and financial control, and other tasks. Selected obtained results are presented in

Table 9. The tasks and role of controlling indicated by the respondents.

Panel A: Analysis Results in Two-Way Tables
Industry/Feature			Reporting Tools					Budgeting				Operational Support					Decision Making
			Excel by Hand	Domain System	Warehouse	Excel Automat	Total	>50%	<25%	25–50%	Total	0%	<25%	25–50%	>50%	Total	No	Yes	Total
E&H	Count A		17.0	14.0	9.0	8.0	48	21.0	8.0	21.0	50.0	14.0	12.0	14.0	0.0	40.0	41.0	6.0	47
	Expected count B		14.5	22.5	6.2	4.8	48	19.5	14.0	16.5	50.0	11.3	8.0	19.3	1.5	40.0	36.6	10.4	47
	A-B		2.5	−8.5	2.8	3.2	0	1.5	−6.0	4.5	0.0	2.8	4.0	−5.3	−1.5	0.0	4.4	−4.4	0
Others	Count A		55.0	98.0	22.0	16.0	191	57.0	48.0	45.0	150.0	31.0	20.0	63.0	6.0	120.0	90.0	31.0	121
	Expected count B		57.5	89.5	24.8	19.2	191	58.5	42.0	49.5	150.0	33.8	24.0	57.8	4.5	120.0	94.4	26.6	121
	A-B		−2.5	8.5	−2.8	−3.2	0	−1.5	6.0	−4.5	0.0	−2.8	−4.0	5.3	1.5	0.0	−4.4	4.4	0
Total	Count A		72	112	31	24	239	78	56	66	200	45	32	77	6	160	131	37	168
Panel B: Statistics
Pearson’s chi-squared test (χ2)			12.737	p = 0.000				5.218	p = 0.073			7.472	p = 0.058				3.256	p = 0.071
Maximum-likelihood chi-squared			14.153	p = 0.000				5.567	p = 0.061			8.790	p = 0.032				3.534	p = 0.060
Phi coefficient (φ)			0.214					0.161				0.216					−0.138
Pearson’s contingency coefficient (C)			0.209					0.159				0.211					0.137
Spearman rank correlation coefficient (ρ)			0.214	p = 0.000				0.037	p = 0.602			−0.02	p = 0.799				−0.13	p = 0.071
Panel A: analysis results in two-way tables
Industry/Feature						Budget management				Process management						External reporting
						No	Yes	Total		No		Yes		Total		No		Yes	Total
E&H		Count A				20.0	31.0	51		10.0		41.0		51.0		23.0		28.0	51.0
		Expected count B				28.4	22.6	51		12.4		38.6		51.0		31.8		19.2	51.0
		A-B				−8.4	8.4	0		−2.4		2.4		0.0		−8.8		8.8	0.0
Others		Count A				141.0	97.0	238		60.0		178.0		238.0		157.0		81.0	238.0
		Expected count B				132.6	105.4	238		57.6		180.4		238.0		148.2		89.8	238.0
		A-B				8.4	−8.4	0		2.4		−2.4		0.0		8.8		−8.8	0.0
Total		Count A				161	128	289		70		219		289		180		109	289
Panel B: Statistics
Pearson’s chi-squared test (χ2)						6.828	p = 0.008			0.7181		p = 0.396				7.786		p = 0.005
Maximum-likelihood chi-squared						6.796	p = 0.009			0.7457		p = 0.387				7.567		p = 0.005
Phi coefficient (φ)						0.153				0.049						0.164
Pearson’s contingency coefficient (C)						0.151				0.049						0.161
Spearman rank correlation coefficient (ρ)						0.153	p = 0.008			0.049		p = 0.398				0.164		p = 0.005

Source: own study.

. The obtained results allowed us to identify the relationships presented below.

The tasks of controlling in E&H companies more often than in other analysed entities concern budgeting. Budget management as a task of controllers was indicated more often in a statistically significant way in E&H companies compared to Others companies. At the same time, it was noted that respondents in E&H companies indicated that a greater percentage of controllers’ working time was devoted to this task. For E&H companies, there were surpluses of the observed numbers over the expected ones in the category above 50% of working time and 25–50% of working time is devoted to budgeting and supervision over the implementation of the budget. Companies from the Others group more often spend up to 25% of their working time on this type of activity. The significance of these dependencies was confirmed at the level of p = <10%, but it is not without significance here that the respondents to the questions asking for an estimate of the time spent on particular activities often did not answer or chose the answer “I do not know”, as a result of which the collected material was often insufficient to carry out full inference.

An observation regarding external reporting is also noteworthy. Compared to the Others segment, E&H companies more often indicated that such actions were taken by the controlling services. Differences are confirmed statistically. Their reasons should probably be sought in the obligations imposed on E&H companies related to reporting to market regulators.

In E&H companies, activities related to the direct involvement of controllers in decision-making processes or preparation of decisions were less frequently recorded. Although there were no differences in the frequency of activities related to process efficiency management, which are rarely undertaken both in the E&H and Others industries, 20% and 25% of respondents, respectively, indicated that controllers undertook this type of activity; the differences in supporting the building of operational efficiency were more visible. Controllers of E&H companies are less likely to engage in activities related to supporting the building of operational efficiency compared to the observations recorded for Others companies.

There were observed surpluses of the observed frequencies over the expected ones for the following categories: (1) analyses are not conducted and (2) up to 25% of working time is devoted to analyses, with the significance level of p = <10%. Similarly, it has been noted that E&H companies are less likely to involve controllers in decision-making processes.

Tools supporting the work of controllers were also analysed. The E&H industry is dominated by reporting based on obtaining data from ERP systems and using various tools (spreadsheets, automatically fed spreadsheets, and data warehouses) and their further processing into controlling reports. It has been observed that systems dedicated to management reporting are used less frequently in E&H companies compared to the Others segment.

4.6. Budgeting

Over 90% of the analysed E&H companies declared that they implement procedures related to budgeting. In this respect, the E&H companies performed slightly better compared to the Others group, where this ratio was 85%. However, one cannot talk about the statistical significance of these differences. Additionally, the results, related to the assessment of the business usefulness of the implemented budget processes, were somewhat surprising, indicated in the synthetic assessment made by the respondents as part of the question whether budget processes fulfil their tasks. For companies from the E&H sector, respondents more often indicated “no” and “rather no” answers compared to the choice of these answers indicated in the Others group. The results obtained in this regard are presented in

Table 10. Implementation of budgeting processes and assessment of their usefulness.

Panel A: Analysis Results in Two-Way Tables
Industry/Feature		Budget is Prepared?			Is the Budget Fulfilling the Tasks?
		Yes	No	Total	Yes or Rather Yes	No or Rather No	Total
E&H	Count A	38.0	4.0	42	25.0	19.0	44.0
	Expected count B	36.2	5.8	42	35.3	8.7	44.0
	A-B	1.8	−1.8	0	−10.3	10.3	0.0
Others	Count A	197.0	34.0	231	153.0	25.0	178.0
	Expected count B	198.8	32.2	231	142.7	35.3	178.0
	A-B	−1.8	1.8	0	10.3	−10.3	0.0
Total	Count A	235	38	273	178	44	222
Panel B: Statistics
Pearson’s chi-squared test (χ2)		0.800	p = 0.670		18.846	p = 0.000
Maximum-likelihood chi-squared		0.870	p = 0.647		16.431	p = 0.000
Phi coefficient (φ)		0.054			0.291
Pearson’s contingency coefficient (C)		0.054			0.279
Spearman rank correlation coefficient (ρ)		−0.05	p = 0.372		0.291	p = 0.000

Source: own study.

.

In order to assess the reasons for this state of affairs, the occurrence of errors and deficiencies of budgetary processes most often indicated in the literature was analysed. In the questions presented to the respondents, it was verified whether they indicated the following issues:

• There is a budget, but there are no strategic goals and tasks, so we do not know where we are going; there is no connection with the strategy (involving managers in explaining, commenting on deviations from budgets).
• The budget is detached from strategic goals and tasks.
• Budgets are out of date (outdated).
• Budgets are rigid and therefore do not adjust to the current market situation (mismatched to the market situation).
• Budgets are too general (too general).
• Budgets are too detailed (too detailed).
• There is a belief that if there is a budget, it is necessary to complete all purchases, even those unjustified (priority of implementation).
• Preparation of budgets is very time-consuming (time-consuming).
• Budgets are imposed on managers in advance (imposed).
• Managers have to explain business-insignificant deviations.
• Managers prepare budgets and then fail to implement them anyway (non-compliance).

The results obtained for selected parameters are presented in

Table 11. Budgeting problems indicated by respondents.

Panel A: Analysis Results in Two-Way Tables
Industry/Feature		No Link with the Strategy		Outdated		Non-Compliance		Too General		Too Detailed		Priority of Implementation		Mismatched to the Market		Time-Consuming		Enforced
		No	Yes	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes	No	Yes	Total
E&H	Count A	46.0	5.0	38.0	13.0	45.0	6.0	48.0	3.0	39.0	12.0	38.0	13.0	38.0	13.0	36.0	15.0	42.0	9.0	51
	Expected count B	44.3	6.7	45.5	5.5	43.9	7.1	45.5	5.5	44.1	6.9	44.5	6.5	44.5	6.5	40.8	10.2	39.4	11.6	51
	A-B	1.7	−1.7	−7.5	7.5	1.1	−1.1	2.5	−2.5	−5.1	5.1	−6.5	6.5	−6.5	6.5	−4.8	4.8	2.6	−2.6	0
Others	Count A	205.0	33.0	220.0	18.0	204.0	34.0	210.0	28.0	211.0	27.0	214.0	24.0	214.0	24.0	195.0	43.0	181.0	57.0	238
	Expected count B	206.7	31.3	212.5	25.5	205.1	32.9	212.5	25.5	205.9	32.1	207.5	30.5	207.5	30.5	190.2	47.8	183.6	54.4	238
	A-B	−1.7	1.7	7.5	−7.5	−1.1	1.1	−2.5	2.5	5.1	−5.1	6.5	−6.5	6.5	−6.5	4.8	−4.8	−2.6	2.6	0
Total	Count A	251	38	258	31	249	40	258	31	250	39	252	37	252	37	231	58	223	66	289
Panel B: Statistics
Pearson’s chi-squared test (χ2)		0.606	p = 0.436	14.095	p = 0.000	0.223	p = 0.636	1.517	p = 0.217	5.347	p = 0.020	8.929	p = 0.002	8.929	p = 0.002	3.369	p = 0.066	0.946	p = 0.330
Maximum-likelihood chi-squared		0.646	p = 0.421	11.507	p = 0.000	0.231	p = 0.630	1.728	p = 0.188	4.714	p = 0.029	7.636	p = 0.005	7.636	p = 0.005	3.127	p = 0.077	0.992	p = 0.319
Phi coefficient (φ)		−0.041		0.220		−0.021		−0.07		0.135		0.175		0.175		0.107		−0.05
Pearson’s contingency coefficient (C)		0.045		0.215		0.027		0.072		0.134		0.173		0.173		0.107		0.057
Spearman rank correlation coefficient (ρ)		−0.041	p = 0.437	0.220	p = 0.000	−0.02	p = 0.637	−0.07	p = 0.219	0.135	p = 0.020	0.175	p = 0.002	0.175	p = 0.002	0.107	p = 0.066	−0.05	p = 0.332

.

The budget processes implemented in E&H companies do not seem to generate problems related to the mismatch with the company’s strategy. However, the situation related to the adequacy of budgets to the changing market situation looks different. E&H respondents in 25% of cases indicated that budgets are mismatched to the current market situation. In the Other group, 10% of respondents indicated a similar mismatch. The conducted analyses confirmed that the mismatch between budgets and the market situation is higher than in companies from the Others sector. Similar results were obtained in the case of the point concerning the lack of flexibility of budgets, which means that they do not adjust to the current market situation. E&H respondents more often pointed to this problem in relation to the Others sector, which confirms the statistical significance of these differences.

The obtained results indicate that the applied budgetary procedures are assessed by the respondents as too detailed and excessively laborious, with an excessive regime of compliance with budget assumptions that does not take into account the current situation. Respondents indicated the occurrence of these problems more often in E&H companies, compared to the responses recorded for the Others group. The differences were confirmed as statistically significant.

Due to the identified challenges of budgeting processes, the scope of created budgets was analysed. Respondents were asked what elements the budget contains, and to indicate those that are present in the company. The question distinguishes: pro-forma balance sheet, depreciation budget, investment budget, direct costs budget, overhead budget, sales budget, salary budget, pro-forma cash flow statement, consolidated budget of costs and revenues in the management layout, consolidated budget in the accounting layout profit and loss account (the so-called pro-forma profit and loss account), budgets of individual organizational units, budgets of individual accounting accounts, quantity budgets (kg, items, m), budgets for individual products, and budgets for individual contractors. Then, how many of the indicated budget elements were used in a given entity was counted. The results obtained for the synthetic variable defined in this way (budget complexity) are presented in

Table 12. Budget complexity.

Panel A: Descriptive Statistics
Industry	N Valid	Mean	Trimmed Mean	Winsor Mean	Median	Minimum	Maximum	Q3	Q1	Standard Deviation
E&H	51	7.098	7.133	7.118	8.000	1.000	15.000	4.000	10.000	3.700
Others	192	5.984	6.017	5.964	6.000	1.000	15.000	4.000	8.000	2.961
Panel A: Variance tests
t	−2.259	p	0.025
quotient F	1.561	p	0.035

Source: own study.

. E&H companies showed a higher content of budgets. The presence of 8 items was most often indicated (average 7.1), while in the Others group, a median of 6 and an average of 6.0 were noted.

Selected other characteristics of budgeting processes are presented in

Table 13. Characteristics of budgeting processes in the surveyed enterprises.

Panel A: Analysis Results in Two-Way Tables
Industry/Feature		Is the Budget Updated?				Who is Budgeting?			Manager’s Influence			IT System			Deviation Analysis
		Quarterly. Semi-Annually	Quarterly Rolling	Annual not Updated	Total	Department	Centrally	Total	Yes	No	Total	Yes	No	Total	Yes	No	Total
E&H	Count A	0.0	22.0	4.0	26	26.0	20.0	46.0	28.0	17.0	45	23.0	26.0	49	14.0	30.0	44
	Expected count B	2.1	21.7	2.2	26	25.3	20.7	46.0	30.6	14.4	45	17.2	31.8	49	25.6	18.4	44
	A-B	−2.1	0.3	1.8	0	0.7	−0.7	0.0	−2.6	2.6	0	5.8	−5.8	0	−11.6	11.6	0
Others	Count A	18.0	164.0	15.0	197	91.0	76.0	167.0	116.0	51.0	167	59.0	126.0	185	118.0	65.0	183
	Expected count B	15.9	164.3	16.8	197	91.7	75.3	167.0	113.4	53.6	167	64.8	120.2	185	106.4	76.6	183
	A-B	2.1	−0.3	−1.8	0	−0.7	0.7	0.0	2.6	−2.6	0	−5.8	5.8	0	11.6	−11.6	0
Total	Count A	18	186	19	223	117	96	213	144	68	212	82	152	234	132	95	227
Panel B: Statistics
Pearson’s chi-squared test (χ2)		4.008	p = 0.134			0.0600	p = 0.806		0.852	p = 0.355		3.853	p = 0.049		15.550	p = 0.000
Maximum-likelihood chi-squared		5.823	p = 0.054			0.0601	p = 0.806		0.835	p = 0.360		3.744	p = 0.052		15.467	p = 0.000
Phi coefficient (φ)		0.134				−0.01			0.063			−0.12			−0.26
Pearson’s contingency coefficient (C)		0.132				0.016			0.063			0.127			0.253
Spearman rank correlation coefficient (ρ)		0.133	p = 0.046			−0.01	p = 0.807		0.063	p = 0.358		−0.12	p = 0.049		−0.26	p = 0.000

Source: own study.

E&H companies used fixed, non-updated annual budgets more often than the Others group, and they used rolling budgets less often, but the significance of these differences was not confirmed with a sufficient level of confidence. There were no differences in the central mode of budgeting or the influence of the manager on budgets when comparing the results for the E&H and Others groups. In turn, clear differences were observed in the processes of budget implementation. No differences were identified in the frequency of reporting deviations, while E&H companies indicate that they are less likely to involve managers in explaining them. E&H companies report the use of IT tools in budgeting more often than Others group.

5. Discussion and Conclusions

The Polish energy sector is largely detached from the proven laws of economics and does not follow global development trends. This is important for the economy as it generates very high costs and strives to increase the scale of domestic funding, without introducing changes aimed at adapting to the real economy and global trends. Poland occupies the penultimate place in Europe (per capita) when it comes to obtaining funds for research and development in the field of energy. In addition, the monopolization of the energy sector supports those business models that are based on protecting the state and limiting innovation.

Gradual changes are visible in the economic area, especially in the area of implementing controlling and adjusting it to the specific needs of energy companies. A properly designed controlling system provides the management of an energy company with access to information indicating which product or service is profitable, which creates added value, and which brings losses. The database of information on the costs incurred in connection with the conducted activity enables the optimization of the use of possessed resources and the achievement of the planned goals of this sector of the economy.

Proper management of the effects of operating activities becomes a necessity, and the measurement of the effectiveness of decisions taken is an element of management focused on creating conditions for a stable improvement in economic results. Controlling contributes to supervising the stability of economic results by ensuring that their improvement is linked to the rationalization of the financing costs related to the functioning of the enterprise.

The main purpose of the conducted research was to obtain knowledge on to what extent companies in the energy and heating sector use controlling tools.

The conclusions from original empirical research are:

• The conducted research shows that controlling is an important issue for the E&H industry. Companies in the sector declare the use of controlling in business activity much more often than others, and this relationship is observed regardless of the size or period of operation of the company on the market.
• The results of the study indicate that the tasks of controlling in the E&H industry are different to those observed in other industries. A large share of reporting tasks focusing on budget management and investments is noteworthy. Research shows that controlling very often supports reporting tasks related to the processing of accounting data, which strongly supports accounting departments. This role is strongly influenced by the need to fulfil numerous reporting obligations, including those for energy market regulators. An important task of controlling in the E&H industry is reporting on investments, which is related to the specificity of the industry requiring numerous investments. The tasks of controlling in E&H companies, more often than in other analysed entities, concern budgeting. Budget management is indicated as the main task involving controlling services, and E&H companies devote much more time to this purpose than in other industries.
• Controlling tasks translate into the way the controlling is organized in E&H enterprises. Furthermore, the tasks performed are so diverse that it is necessary to expand the enterprises’ organizational structures. E&H companies more often create multi-position organizational units. Examples of overly developed controlling divisions consisting of many people and positions have been observed many times. The need to use controlling tasks seems to be present in the E&H industry, regardless of the size and time of operation of the entity on the market. What is worth emphasizing is that the controlling department is most often located in the organizational structure in a linear position, which clearly distinguishes E&H from other companies. The specific and dominant solutions also include assigning the responsibility of supervision over controlling directly to the chief accountant.
• E&H’s extensive reporting needs to translate into complex cost accounting systems. E&H creates more complex record systems and separates more account segments than are used outside of this industry. There were solutions in which more than 10 account segments were used. Most often, this record, as well as cost settlements, are made directly in the accounting system. E&H companies use multiple costing, typically time-based. All this causes the information on costs to become highly complex and, as the conclusions of the conducted research show, it is not easy to report.
• The conducted research indicates that the controlling solutions are of the nature of reporting controlling, not management controlling. Research indicates that controlling tasks rarely focus on support in formulating and implementing decisions. Controllers of E&H companies are less likely to engage in activities related to supporting the building of operational efficiency compared to observations recorded for companies outside this industry. Consuming significantly more time than in other industries, the budgeting process appears to be ineffective in the light of the conducted research. Over 43% of respondents state that budgeting in E&H does not fulfil its tasks and this ratio is definitely higher in the E&H industry than in other groups of enterprises. Detailed budgeting and budgeting procedures are more extensive compared to the other groups. Preparation of one, rigid annual budget, which is not modified during the year, is very common. In most cases, the budget is prepared mainly to fulfil the indicated reporting obligations towards regulators and does not fulfil its management controlling function. This is evidenced by the rare involvement of managers in explaining deviations from budgets, which was revealed in the research.

To improve the efficiency and effectiveness of enterprises operating in the E&H sector, the authors recommend primarily:

• Strengthening the role of controlling aimed at its transformation from reporting controlling to management controlling; in view of the challenges of the global economy related to the energy crisis, controlling should be used to a greater extent in the E&H industry to increase the efficiency of basic processes and effectively implement management tools.
• Strengthening the role of the controlling department in the enterprise as a department co-creating decisions, changing its place in the organizational structure from a line position to a staff position; this raises the authority of the controlling department and it is conducive to achieving the assumed goals.
• Assigning typical reporting activities, specific to the E&H industry, regarding mandatory reporting for regulators or development funds to dedicated units; controlling departments should be relieved of these reporting tasks.
• The separation of accounting records from controlling records, because controlling for effectiveness measurement requires completely different, sometimes even variant, settlements of cost assignments; these analyses cannot and should not be carried out in accounting systems and should not affect companies’ trading books. The observed solutions cause, on one hand, an increase in labour intensity on the part of accounting departments, and on the other hand, they limit access to information useful for airworthy cost and efficiency management.
• The use of cost drivers other than working time and the introduction of tools supporting the use of working time for cost settlements; additionally, reporting of the costs of unused production capacity should be introduced, which is particularly important in E&H companies.
• Simplifying and making budget processes more flexible, which can be achieved by implementing more frequently verified and rolling budgets, developed on the basis of key parameters and involving fewer employees; this will enable better use of forecasting tools, including scenario budgeting.
• Linking information from controlling systems with the process of motivating employees and making part of their remuneration dependent on the effectiveness of the tasks performed; the presented answers of respondents to questions in this area indicate great difficulties in implementing this solution, which is the result of low involvement of the managerial staff of E&H sector enterprises and it limits benefits resulting from the analysis of controlling data.
• Increasing the emphasis on the use of modern IT tools, business intelligence, and performance management classes supporting the use of management controlling, as well as increasing interest in artificial intelligence algorithms.