s2fieldsofstudy: Economics Business

text:
MANAGEMENT OF SOCIO-ECONOMIC DEVELOPMENT OF TOURISM ENTERPRISES

To date, the tourism business is developing rapidly and the mountainous territories are not inferior in competition to other tourist territories. For the development of the tourism business, it is necessary to conduct effective management of socio-economic development. The main purpose of the study is to identify and assess the main threats to the socio-economic development of the tourism business in the mountainous territories of Eastern Europe. We have applied the methods of synthesis, analysis, deduction, induction, mathematical methods, methods of expert research. The importance of research on the management of socio-economic development of the mountains in the conditions of increasing the efficiency of the tourism business is proved. Peculiarities of managing the socio-economic development of the mountains in the conditions of increasing the efficiency of the tourism business are considered. As a result of the study, threats were identified that most negatively affect the management system of the socio-economic development of the tourism business in the mountains. The novelty of the study is the formation of coordinate systems in the trust or distrust of the management and executive staff of travel companies in making management decisions.

Introduction
Tourism is one of the few sectors of the economy that are able to restore quickly their volumes of activity while creating favorable conditions. The development of tourism enables many countries of the world to receive significant funds in the state budget, to increase the income of related sectors of the economy due to the multiplier effect, to improve the state of the infrastructure of tourist destinations.
Tourism has a special place in the system of sectors of the national economy. As a type of outdoor activity, it is one of the main needs of the population and their expenses. Enterprises serving tourism represent a whole sector of the economy, covering both the tourism industry and the industries that are associated with it indirectly.
These include: transport, communications, trade, construction, agriculture, oil refining, public services, food, light, local industry, etc. (about 60 different industries and sub-sectors of the economy that provide characteristic, territories. Mechanisms for the implementation of mountain policy include the development of a strategy and relevant local programs for the socio-economic development of mountain areas, the regulation of economic activity in various areas of their socio-economic complex by executive authorities and local governments for the development of tourism business.
The main purpose of the study is to identify and assess the main threats to the socio-economic development of the tourism business in the mountainous territories of Eastern Europe.
The main subjects of the study are travel companies in Eastern Europe, operating in the mountainous area.

Literature review
Scientific knowledge about the management issues in the field of socio-economic development of mountainous territories is characterized by a variety of subjectmethodological approaches to the analysis of economic, environmental, legal support of these territories. This is primarily due to the versatility and complexity of the investigated phenomenon itself, as well as to those specific tasks that individual researchers pose. Despite the fact that the problem of managing the socio-economic development of mountainous areas is interdisciplinary in nature, it requires an analysis of some literary sources related to it.
Modern scientific thought gradually demonstrates elements of awareness of the essence of the mountain policy of the state and the study of the features of its implementation, which is crucial in the process of regulating the socio-economic development of mountain territories. There is considerable interest in this regard are the works of Avakyan (2019), Badenkov (2017), Belaya (2019), Golubets (2007), Demchenko (2018), Samoletova (2005), Stadnitsky (2004), Surazakova (2003) and other authors who substantiate conceptual approaches to determining the socio-economic and legal aspects of the implementation of mountain policy.
The problem of state management of the socio-economic development of depressed territories, which include mountains, in the conceptual and institutional dimension was the subject of research by Danylyshyn (2006), Korotich (2010), Nikolaev (2011), Pitukhina (2004, Polishchuk (2009) and other authors. The monograph by Mamonova (2006), which allows to see the complex and contradictory process of state regulation of the socio-economic development of territories, deserves special attention.
Szromek (2019) explored new business models for tourism enterprises. Butler (2019), having also dedicated his research to the selection of business models for enterprises in the tourism industry. Kozak, Derkach, and Huz (2019) investigated possible options for forming a development strategy for tourism enterprises in the modern conditions of their functioning.
Tourism companies are currently experiencing difficult times because of the epidemic and coronavirus in such moments, a study of their socio-economic development is very relevant. In such a period, it still remains relevant and necessary to determine the main threats to the tourism sector, which even before the epidemic started significantly hindered its socio-economic development.
Methodological approaches to the formation of a common EU regional policy for the development of problematic (depressed areas) are analyzed in the works of Matviishin (2009). Researchers have identified the forms and methods for implementing the joint regional policy of the EU, which takes into account the differentiation of levels of socio-economic development of regions, in particular mountainous, and aims at their gradual convergence.

Methodology and data
In determining the scientific foundations of the study, the authors proceeded from the complexity and interdisciplinarity of the subject of the study. The theoretical and methodological basis of the work was constituted by the fundamental principles of the theory of public administration, scientific works of domestic and foreign scientists on the management of the socio-economic development of regions and their depressed territories. General scientific and special research methods were used.
Using the analytical method, the selection and analysis of scientific literature on the topic of research was carried out. Historical and logical methods were used to elucidate the theoretical foundations of the development and implementation of mountain policies for the socio-economic development of mountain territories. Comparative and logical-semantic methods were used in the study of mountain development. The comparative method made it possible to generalize European approaches to the management of problem areas, which include mountainous territories, and to consider existing managerial models for their development. Using this method, changes in the development of strategies and programs for the socio-economic development of mountain areas were studied, which then allowed the formation of a mechanism for managing the socio-economic development of mountain areas in the context of increasing the efficiency of the tourism business. For a theoretical generalization and formation of conclusions, an abstract logical method was used.
The expert method for determining threats was already used in their study by Franchuk et al. (2020).
Separately, it is worth highlighting the expert method, with the help of which a survey of leading experts in the field of tourism business in the mountainous territories of Eastern Europe was conducted. The composition and structure of experts includes 20 respondents, 12 of whom have been working in the tourism business for more than 10 years. A survey of experts made it possible to obtain data on the main threats that negatively affect the socio-economic development of mountainous areas and the tourism business as a whole (Table 1). We have chosen 20 experts, since it is precisely so many leading experts in the field of tourism that have responded to our request to participate in the study. Our study envisaged the choice of threats to the socio-economic development of the tourism business in the mountainous areas, requiring the choice of only those threats, the most common in the answers of experts.
Separately, for a more detailed analysis of the main threats to the socio-economic development of the tourism business in the mountainous territories, an expert study of two leading enterprises in this field of activity was carried out.

Results and discussions
In a significant number of countries in Eastern Europe, the volume of tourist spending is growing, only confirms the relevance of improving the management of socio-economic development of the tourism business ( Figure 1).
In the context of the strategy of socio-economic development of mountainous areas, tourism plays an exceptional role. Today in many countries of the world it has turned into a large industry, is developing rapidly. As stated in the materials of the Hague Declaration of the Inter-Parliamentary Conference on Tourism: "Tourism can be an effective means of promoting socio-economic growth for all countries if the necessary measures are taken to fulfill the most urgent national tasks and achieve the national economy an acceptable level of self-sufficiency, at which a country should not spend more than what it hopes to receive from tourism.
Changes in the political and economic conditions that took place in Eastern Europe in the 80s of the last century allowed structural reforms in the direction of the prevalence of tourist services over other sectors of the economy, and a focus on the efficient use of tourism potential. Tourism development is manifested in its diversified nature and close factor interdependence with almost all spheres of life, which allows it to be used as an effective tool to stimulate social and economic growth at the national and local levels.
The socio-economic development of the tourism business in the mountainous territories, first of all, is based on three main factors: -the natural resource potential of mountainous territories and the possibility of its optimal use; -financial support of economic entities in terms of the possibility of influence from the regional and local administrations; -organizational and legal support for the effective operation of all sectors of the socio-economic complex of mountainous territories. To effectively solve the problems of developing the socio-economic complex of mountainous territories (as well as other territories), it is necessary to quickly assess the situation in the economy, make optimal use of existing resources, identify the strengths and weaknesses of the territory and ultimately make informed management decisions. However, this can only be successfully implemented with an appropriate management system [30], which can provide both information-analytical (combining key diagnostic elements for preparing decisions) and organizational-infrastructure (clear distribution of responsibilities, communication efficiency, coordination of actions of the parties involved) components management activities of authorities. Successful implementation of the mountain policy directly depends on the effective management of the economic, environmental and social development of the mountain territories, in accordance with a pre-developed strategy. Priority areas of implementation are: -development of infrastructure, primarily transport, road, communication; -the development of high-tech, energy-saving, hightech and ecophilic industries; -coordination of activities in the social sphere with the main directions of economic policy on the basis of state and regional programs of socio-economic development; -ensuring effective employment, preventing unemployment, creating new jobs. Successful implementation of mountain policy presupposes, first of all, effective state regulation of economic and social processes in mountain territories, provides for a clear distribution of functions and mechanisms for its implementation. It should be noted that the functions of state management of the socio-economic development of mountainous areas determine the specific type of management activity that is objectively necessary to achieve a specific goal. They are relatively isolated in the process of division of labor in the areas of public administration and differ in content, specific forms and methods of developing and exercising influence on managed objects. The main functions of state administration of the socioeconomic development of mountainous areas include the following: -determination of the goals and objectives of the socio-economic development of mountain areas; -the formation of strategies, current and long-term programs for the socio-economic development of these territories; -implementation of an effective financial, credit, budgetary and fiscal policy; -ensuring environmental and social safety of the population of mountain areas; -coordination of the interests of all subjects of state administration of the socio-economic development of mountain regions; -monitoring and analysis of the results of mining policy in the regions; -control, which includes an assessment of the implementation of targeted programs, normative legal or regulatory acts with the aim of further adjusting the actions and activities of state authorities to stimulate the socio-economic development of mountain territories. It should be noted that in general, state instruments for implementing mountain policy in the EU countries are divided into the following main groups: -organizational and institutional mechanism that ensures the implementation of mountain policy; -administrative and management mechanism (conclusion of regional agreements and contracts); -the mechanism of spatial planning and the "growth point"; -a mechanism for financial support for the development of mountainous areas (subsidies for certain amounts of investments, loans, financial benefits, subsidies in connection with job creation, etc.); -economic mechanism (the so-called "soft" means of stimulating the creation of a favorable business environment, the use of regional development agencies, support for consulting activities, the development of cluster development plans, etc.); -a mechanism for statistical support of programs for the socio-economic development of territories; -monitoring the effectiveness of planned and implemented measures for the sustainable development of mountain territories. The effectiveness of the implementation of these tools depends primarily on the organizational and institutional mechanism, which is designed to develop, implement and properly control them. This mechanism for implementing mountain policy in the EU country provides for: an understandable and adequate definition of mountain territories; the availability of opportunities for the mountain population to control the use of natural resources, to solve the problems of free access to land use in mountain territories; possible participation of mountain population in decision-making regarding the socio-economic development of their settlements; their free access to credit; providing effective and efficient incentives to support the development of mountain, green tourism, creating the proper balance between environmental protection and the proper standard of living of mountain people.
Foreign experience in managing the recreational development of mountainous areas, as the leading industry in their socio-economic complex, indicates that the priority areas for the development of this industry are determined taking into account data from sociological studies conducted to identify preferences of different contingents of recreants. So, in Poland, an impulse to the development of the recreational sphere was given by a well-thought-out state policy, which was oriented towards external demand. The state provided tremendous support to small and medium-sized businesses, introducing them to the development of material and specialized transport infrastructure of this industry.
The experience of the EU countries shows that solving the problems of tourism business in mountainous areas requires the use of tools such as stimulating "growth points". It should be noted that the concept of "growth point" is quite common, while there is no clear definition of it. As a rule, we are talking about the availability of the necessary conditions and sufficient (necessary) resources, with which the effect of socio-economic growth is achieved.
To disclose the "growth points" of mountain areas at the local level, regional strategies include the use of the following tools: 1. The creation on the basis of clusters of promising "growth points", "areas of economic development", can positively affect the socio-economic development of these territories.
2. "Regional and local availability. " The goal is to provide better communications with mountain areas remote from the center through road and transport construction; step up the development of their social infrastructure.
We were interviewed leading experts in the field of socio-economic development of the tourism business in the mountainous territories of Eastern Europe in order to establish, today, the threats have the greatest impact. According to the results of the survey, we streamlined them and determined which of them have the most negative impact on the management of the socio-economic development of the tourism business in the mountainous territories of Eastern Europe (Figure 2).
Take, for example, the problem of the lack of dialogue between top managers and executives on which it is impossible to effectively manage the socio-economic development of the tourism business in the mountainous territories of Eastern Europe. For the study of assessing the level of trust between the management staff and the executive staff, we selected two leading travel companies that are active in the mountainous territories of Eastern Europe and asked them the question "Do you have confidence in the decisions that your leaders make?" and "Do you believe in the effective implementation of your managerial decisions by executive staff?" (Figure 3).
The companies that were selected as part of the study were asked to remain anonymous; however, it should be noted that they operate in the Central-Eastern part of Europe.  The survey at the enterprises of the tourism industry took place in the context of a rating on a point scale, from 10 to -10 points, respectively, as far as they trust the management and its management.
The results showed that the level of trust is below average, which means that such a threat exists and can have a negative impact on the governance system of the socioeconomic development of the tourism business.
In case of negative influence of threats, it is necessary to choose which type of control should be used. Together with experts, we agreed and identified two main types of management of the socio-economic development of the tourism business in the mountains (Figure 4).
Adaptive management of the socio-economic development of the tourism business in the mountainous territories provides for an analysis of the functioning environment and adaptation to new functioning conditions.
With sufficient resources, it is possible to take and implement measures to directly counter the negative impact of threats.
Despite the category tourism enterprises in the mountain territories fall into, the following areas and tasks in the field of mountain tourism should be: -study of existing and identifying potential opportunities for the development of mountain tourism; -development of a mountain tourism development strategy; -promoting the development of tourism services in the mountains; -attraction of financial and economic resources of district state administrations, village and village councils, specialized funds for the implementation of pilot projects for the development of mountain tourism; -standardization and certification of services of tourism entities; -initiating the development of agro-mountain tourism associations, stimulating the implementation of relevant training programs in the field of "green" tourism, etc. -creation of an information and consulting center for the development of mountain tourism; -staffing of various types of tourism in the mountainous territories; -lobbying for the interests of mountain tourism subjects in government at all levels; -marketing and advertising in the field of mountain tourism and others. The priority areas and tasks of management activities in the field of mountain tourism should be: research into existing and identify potential opportunities for the development of mountain tourism; attraction of financial and economic resources of district state administrations, village and village councils, specialized funds for the implementation of pilot projects for the development of tourism in mountainous areas; standardization and certification of services of rural tourism entities; Creation of information and consulting centers for the development of mountain tourism; staffing for mountain tourism; lobbying for the interests of mountain tourism subjects in government bodies; marketing and advertising in the tourism sector and more. More attention should be paid to cooperation with business structures in the tourism industry, which should include the participation not only of tourism entities, but also business entities of related industries, due to the monofunctional direction of tourism.

Conclusions
The need to reform and effective development of the socioeconomic complex of mountainous areas should be recognized at all levels of government, as this is the only promising way to solve the socio-economic problems of these territories. But this in no way means that by forcing economic processes in this direction, the desired results will be immediately achieved. Well-balanced decisions and thoughtful practical actions are needed here. Therefore, the further development of the mountainous territories of the studied region should be considered in the context of the structural restructuring of the entire socio-economic complex, in a promising model of which the recreational, health and tourism industries should become one of the main ones.
We, as a result of an expert study, identified threats that have the greatest negative impact on the management system of the socio-economic development of the tourism business in the mountainous territories. As a result, the presence of a partial mistrust of the management and executive staff of travel companies in making management decisions was proved.
As a result of the study of the main threats to the socio-economic development of tourism companies, an inter-level streamlining of the main threats to managing the socio-economic development of the tourism business in the mountains was formed.
In the future, it is necessary to consider in more detail the main aspects of the work of travel companies and develop an effective mechanism for ensuring stable socioeconomic development.
The study is not without limitations. Our study is not without limitations. Unfortunately, our analysis was only part of the tourism industry of individual countries in Eastern Europe.


Sorry, we’re open: Golden open-access and inequality in non-human biological sciences

Golden Open-access (GOA) journals make research more accessible and therefore more citable; however, the publication fees associated with GOA journals can be costly and therefore not a viable option for many researchers seeking high-impact publication outlets. In this study, metadata was collected from 174 open-access, non-human biological science journals and analyzed to determine relationships between Article Processing Charges (APC), Impact Factor (IF), Eigen Factor (EF), citability, h-index, journal rank, and potential contributing factors to publishing preference, such as years of available open access, publication frequency, and average review process time. Further, the aforementioned bibliometrics were examined in relation to country of publisher, as well as their national income threshold. The results of this study provide evidence that bibliometric values such as IF, EF, citability, h-index, and journal rank all increase as APC increases, and each of these metrics are higher in publishers from high-income countries in comparison to upper-middle and lower-middle income countries. Implications of these trends are discussed in regards to non-human biological sciences, and potential consequences of inequality within the global scientific community overall.

Introduction
With the prominence of entities such as Sci-Hub (Black Open-access) and ResearchGate (Green Open-access), the availability of journal articles has increased and may all but nullify the previous paywall system from creating capital for journals (Björk 2017;Fuchs and Sandoval 2013). While this increase in accessibility of scientific literature has removed constraints of researchers and the general public on a global scale, it has also caused many high-impact 1 3 journals to transition to mandatory open-access, also known as Golden Open-access (GOA) in order to continue their profitability through scientific publication (Piwowar et al. 2018;Lewis 2012;Harnad et al. 2008). Although the concept of open-access science may seem genuine on its face, the cost associated with publishing in open-access journals (i.e. Article Processing Charges), as well as a journal's perceived reliability and importance, is what makes this system potentially problematic.
Although many journals enable funding assistance for certain countries and institutions, and Article Processing Charges (APC) can sometimes be factor into project funding, this isn't the case for all researchers and projects, especially when it comes to more expensive, prestigious journals. A study by Ellers et al. (2017) provided evidence that researchers from institutions in developing countries are still paying the full price of developed western nations to publish in high-impact "Mega-Journals" in order to gain exposure and credibility for their research. Unfortunately, the alternative, especially when it comes to GOA, is to publish in journals with a lower Impact Factor (IF), hybrid journals which allow subscription based options, or otherwise publish in potential predatory journals which have low-quality peer review and publish other questionable articles which then impact the credibility of a manuscript by affiliation (Beall 2013). Although publishing in predatory journals is typically frowned upon in the scientific community, researchers may publish in them unknowingly (Drake 2019), to inflate their curricula vitarum (CV) due to rapid publication rate (Pond et al. 2019), and to increase their likelihood of payout for academic research-output bonuses (Hedding 2019).
In this study, I build on the concepts of: (1) Demeter (2019) who, in an editorial, outlines the potential for inequality in publishing through Golden Open Access journals; (2) Björk (2017) who predicts that the most viable business model in lieu of increasing literature piracy outlets such as Sci-hub is a complete transition to GOA with APC for submissions; (3) van Vlokhoven (2019) who provides evidence that research quality and reliability is likely to be reduced with open-access publishing models, and (4) Björk and Solomon (2015), who provided evidence that researchers are more likely to submit to journals based on higher article publishing cost and perceived quality. By analyzing the metadata of open-access journals, I sought to answer the question of whether there are any correlations between journal impact factor, eigen factor, citability, h-index, rank, years of available open access, publication frequency, average review process time, and article publication costs, as well as the aforementioned bibliometrics' relationship to publisher country and associated country income level for comparable journals pertaining to fields of non-human biological sciences, which focus on plants, animals, fungi, bacteria and viruses. The objective of this study was to test various bibliometric statistics against APC to see how they correlate under the hypothesis that researchers seek the best journals, but aren't always financially equipped to pay the high costs of publication. Furthermore, since research is international, there should theoretically be an equal system in place for researchers to gain exposure through their local (national) journals at a cost that represents their nations. Therefore, the additional analysis of publisher's country was to reveal potential for upward mobility of journals from various nations and corresponding income levels.

Methods
Bibliographic measurements and metadata, also known as bibliometrics used in this study include impact factor, Eigen factor, citability, h-index, journal rank, article processing charge, total years of available as open-access, open-access publication frequency, and average review process time (Table 1).

3
The complete dataset from the Directory of Open-access Journals (DOJ) (Morrison, 2008) was used to acquire journal name, APC, country of publisher, average review time, first record of open-access publication, most recent open access publication, number of open-access publication records, and APC currency/cost data (n = 14,275). R statistical software was used for all data analyses; functions and packages used in the analyses included: (1) the get_impactfactor function of the scholar package (Keirstead 2016), which accesses Google Scholar to generate impact factor, Eigen factor and citation metrics for vectors of journal name strings from the most recent year (2019); (2) the getFX function of the quantmod package (Ryan et al. 2019) to convert all currencies to USD for standardization, conversions were made using conversion rates of January 1st, 2020; (3) the dplyr package (Wickham et al. 2015) and reshape2 package (Wickham 2012) to clean and select specific data, and (4) ggplot2 package (Wickham et al. 2016) for data visualizations. In order to obtain journal rank and h-index values, the srjdata package (Kashnitsky 2020) was used to query all data from SCImago Journal & Country Rank Data (SJR) and merge with the journal data in the final analysis. Country income data was acquired using the wbstats R package (Piburn 2016), which queries all currently updated World Bank data.
A subset of journals (n = 1047) which had topics relative to animals, plants, fungi, microorganisms, and viruses was queried by creating a subset from the keyword metadata column of the original DOJ dataset. Since there were large disparities between human (i.e. human medical, chemical, and physiological journals) and journals which are not exclusively pertinent to humans (hereafter "non-human biological sciences") in relation to impact factor, journals with an IF > 40 were excluded from the analysis. The excluded An evaluation of a journals overall impact and quality within its respective field, calculated by the number of citations for a journal and the relative prestige of the journals where the citations come from journals were checked via keywords to ensure none were related to non-human biological sciences; excluded journals were related to topics in oncology, medicine, and engineering. Finally, the remaining journals were manually checked via their relative websites to verify they were not human-centric. The final analyses were performed on a deeply vetted dataset of open-access, biological science journals (n = 174). However, h-index and journal rank metrics queried from SJR were only available for 156 journals out of the dataset, with a range of values for multiple years. To compensate for this, the SJR data was merged with the final dataset using only values for years of available open access of each journal, then h-index and journal rank values were aggregated to generate a mean for the available years combined.
In order to explore potential trends in the data, APC was examined in relation to overall citability (annual citations based on the currently available year), IF (general impact of the journal), and Eigen Factor (relative importance of the journal). However, since years of available open-access, publishing frequency, and avg, review time may indicate publishing preference and influence APC these statistical relationships were also considered. The country of each journal publisher was also examined against cost, citability, IF, Eigen Factor (EF hereafter), years of available open-access, publication frequency, and avg. review time to locate any potential similarities or disparities between them. Using functions from the ggpubr package (Kassambara 2020), Pearson's correlation coefficient was used to analyze significance in correlation between the aforementioned bibliometrics, and country of publishers were highlighted to examine trends in top ranking nations above mean values. Finally, h-index and journal rank were tested against APC, and countries above the mean were highlighted using the available 156 journal data records. Both metrics were thereafter tested for correlations, with journal rank being tested as a negative value as lower journal rank is a positive indicator of journal success.

Results
A linear trend was evident between IF, EF, and citability in relation to APC. Additionally, it was found that journal publishers from developed countries were more likely to have higher APC, IF, EF, and citability ( Fig. 1). Mean APC of open-access journals analyzed (n = 174) was $1354.77 USD, mean IF was 2.72, mean EF was 0.017, and mean total citation count or citability was 5034.32. APC was found to be significantly positively correlated with IF (Pearson correlation: r(174) = 0.47, p < .001). There was also a significant positive correlation between APC and EF (Pearson correlation: r(174) = 0.293, p < .001). Finally, there was a significant positive correlation between APC and citability (Pearson correlation: r(174) = 0.284, p < .001).
Journals published in the United States, United Kingdom, Ukraine, Switzerland, Saudi Arabia, Poland, Netherlands, South Korea, Germany, Canada, Bulgaria, Brazil, and Australia were more likely to have an IF above the overall mean than other countries. Journals published in the United States, United Kingdom, Switzerland, and Germany were more likely to have an EF above the overall mean. Journals publish in the United States, United Kingdom, Switzerland, Germany and Canada were more likely to have more total citations than the mean of other nations. Publishing cost was highest journals from the United States, United Kingdom, Switzerland, Netherlands, and Germany.
Furthermore, trends varied between a journal's years available as open-access, publication frequency, review times, and APC (Fig. 2). Mean years available as an open-access journal was 11.64; mean annual publication frequency was 147.09, and mean avg. review time was 18.39 weeks. Years of available open-access was found to be significantly negatively correlated with APC (Pearson correlation: r(174) = -0.178, p = .017) Publication frequency was found to have a significant positive correlation with APC (Pearson correlation: r(174) = 0.227, p = .003). Lastly, no significant correlation was found between avg. review time and APC (Pearson correlation: r(174) = -0.1, p = 0.186).
Years of available open access was highest in publishers from the United States, United Kingdom, Switzerland, South Africa, Poland, Netherlands, Mexico, Italy, Iran, Germany, Finland, Canada, Bulgaria, and Brazil. Publications frequency was higher for journal publishers from the United States, United Kingdom, Switzerland, Poland, Lithuania, Italy, India, Germany, Canada, Bulgaria, and Brazil. Avg. review times showed no particular trend, though was higher from publishers based in the United States, United Kingdom, Switzerland, Saudi Arabia, Poland, Mexico, India, Germany, Finland, China, Chile, Canada, Brazil and Argentina.
Also, trends in h-index and journal rank showed similar trends in regards to APC and country of publisher comparable to IF, EF, and citability (Fig. 3). The mean h-index for journals in the revised SJR dataset (n = 156) was 42.82, and the mean journal rank was 8154.53. A significant positive correlation was found between both h-index and journal rank in relation to APC (Pearson correlation: r(156) = 0.411, p < .001); Pearson correlation: r(156) = 0.503, p < .001).
In relation to country of publisher, nations with journals above the mean h-index included the United States, United Kingdom, Ukraine, Switzerland, Russia, Poland, South Overall, trends among bibliometric values for countries of publishers and their associated income levels varied between measurements, though showed an overall bias toward high-income countries where journal values fell consistently over the overall mean (Table 2). Among the open-access, non-human biology journals in this study, journal publishers were most represented by high-income countries (n = 144), followed by upper-middle income countries (n = 29) and lower-middle income countries (n = 4). Journal publishers from exclusively high-income countries (n = 7) had the highest mean APC. Journals from eight high-income countries and one lower-middle income country had the highest mean IF. Journals from only three high-income countries had mean EF above the overall mean. Only two high-income countries had mean citation values above the overall mean. Five high-income and four upper-middle income countries had mean years of available open access above the overall mean. Four high-income and one Lower-middle income country had a mean publication frequency above the overall mean. Review times were ambiguous among country income level, with mean values above the overall mean occurring in journals based out of high-income countries (n = 5), upper-middle income countries (n = 3), and lower-middle income countries (n = 1). The majority of h-index values which fell above the overall mean were from journal publishers based out of high-income countries; however, there was also a single instance of publishers from upper-middle income (Russia), and lower-middle (Ukraine) income countries above the overall mean as well. Mean journal rank was highest in high-income countries (n = 8), with a similar trend from a single instance of an upper-middle income (Russia), and lower-middle (Ukraine) income country.

Discussion
The results of this study provide evidence that with increasing publishing costs, IF, EF, citations, h-index, and journal rank in open-access, non-human biological science journals also increase. Furthermore, the results show that the majority of journal publishers with Fig. 3 Trends h-index, journal rank, and APC: a APC and h-index, b APC and journal rank; for each of the two upper graphs, mean APC is represented as a dashed vertical line, a General Linear Model (GLM) trendline is fitted to the data with standard error shadow, and notable outliers are labeled with the journal name; c h-indices by country of publisher; d journal ranks by country of publishers. For the two lower graphs, all publishing countries which exceed the mean h-index, and journal rank (dashed vertical line) are represented in bold; logarithmic scale was applied to the y axis (Fig. 3a) and x axis (Fig. 3c) for increased visibility of overall datapoints Table 2 Countries of publishers and associated income levels with overall mean bibliometric measurements of their journals; values which fall above the overall mean (top row) for each measurement (below the mean for rank) are bold Country the highest APC, IF, EF, citability, h-index, and journal rank are from high-income countries, which indicates that research published in journals from countries which aren't highincome are less likely to gain exposure, publisher are less likely to generate profit, and more importantly both lower income researchers and publishers are more likely to receive less credibility for their publications. These results confirm similar trends to the SNIP analysis conducted by Björk and Solomon (2015) in regards to correlation with APC. Interestingly enough, after testing for other potential open-access journal statistics such as years of available open access, it was found that journals which have become openaccess more recently were more likely to have higher APC, whereas journals which have provided open-access options for many more years had lower APC. In fact, two Polish journals, Acta Societalis Botanicorum Polinae (available open-access for 97 years; APC = $24) and Acta Palaeontologica Polonica (available open-access for 63 years; APC = $483) were open access for the longest, the former of which has the lowest overall APC next to Revista De La Facultad De Ciencias Agrarias ($20 APC). This indicates that with open-access journals in non-human biological fields of science, age is not necessarily an indicator of prestige or value.
In regards to publication frequency, there was a significant positive correlation with APC, indicating that publishers with higher publication frequency were likely to have higher APC; however, average review times were ambiguously distributed among publishers and not correlated with APC. This means that average time of a manuscript being handled isn't necessarily what drives researchers to publish in journal from these fields, and the correlated indicators such as IF, EF, citability, h-index, and journal rank are.
To summarize, these trends indicate that: 1) journals which have recently provided open-access options have more expensive APC than journals which have been open-access for longer; 2) publication frequency, citation scores, and associated indices/ranks increase as APC increases, and 3) publishers from high-income countries are better represented and are more likely to have higher APC, and therefore higher citation metrics and ranks. Therefore, APC appears to be the overall determining factor in perceived credibility and prestige of open-access journals based in high-income countries in these fields of biology rather than a journal's history of open-access options, or review times. With that in mind, should all journals eventually transition over to Golden OA as theorized by Björk (2017), these issues will not only persist, but will likely become even more exaggerated, as concluded by van Vlokhoven (2019); thus leading to an increase in wide-ranging scientific inequality, biased toward developed nations and prestigious institutions, caused by the GOA movement, as projected by Demeter (2019). Not to mention, trends such as these may cause a rise in pay-to-publish (payment for publication rather than scientific reliability) and publish-to-pay (researcher bonuses for publication output) instances, which cause an increase in predatory journals, further muddying the waters of reliability in peer-reviewed scientific literature (Bartholomew 2014;Hedding, 2019).
To build on these points, it is worth noting that expensive APC in prestigious journals are not linked to reliability of the research published in them (van Vlokhoven 2019; Brembs 2018). Additionally, the impact factor of prestigious journals also creates a false perception of reliability in research they have published (Brembs et al. 2013). The paradox of GOA journals is that the system itself is inherently flawed, where the more manuscripts a journal publishes, the more capital it stands to generate, which gives rise to predatory journals and editorial complacency (Beall 2013). Therefore, GOA journals may create an environment where publisher profit is prioritized over scientific integrity of published research, while still maintaining prestige as an outlet of highly-credible research over other journals.
Unfortunately, the irregular distribution of resources throughout the world, and correspondingly in academia, creates a bubble where higher ranking institutions have more access to expensive, higher impact journals, while lower ranking institutions are forced to publish in less expensive or closed access journals (Siler et al. 2018). The alternative is that authors from developing countries must pay the prices of developed countries in order to gain access to higher impact journals (Ellers et al. 2017). As results of this study show, upward mobility of open-access journals of lower income countries is less likely, thus confirming and reinforcing this concept. On the other hand, options become even more narrow for individual researchers and groups who have no academic institutional affiliation, whether it be through personal career choice, transitionary period, or numerous other situations that prevent the benefits of institutional finance allowances (Burchardt 2014). This is increasingly more problematic for scientific output, as independent researchers with no institutional affiliation have been on the rise over the past decade (ElSabry 2017). However, evidence suggests that the researchers being put on the backburner are no less reliable than the privileged few institutions which have the advantages to publish in high-impact, high APC journals (Brembs 2018;Brembs et al. 2013;ElSabry 2017;Siler et al. 2018).
Although there are many financial support options for GOA journals, there are also many caveats to their eligibility criteria. For example, once an international collaborator from a developed country is named as an author on a manuscript of authors which would otherwise be eligible for publication funding assistance such as Research4Life (Research-4Life 2015), the eligibility for financial assistance becomes void. I know this from personal experience after being rejected from funding assistance multiple times while attempting to publishing important studies on the critically endangered Sumatran elephant in GOA journals. While my co-authors were from eligible developing countries, I am from the United States, but have no current institutional affiliation and therefore none of the accompanying financial benefits, and none of us had access to the > 1000 USD for publication fees. Does this mean the research we were reporting is not important, or reliable? Not at all. However, our options were narrowed significantly down to low-impact journals, which consequently are cited much less, and generally seen as less credible sources of scientific information. Cases like this may force an author to be removed from a manuscript in order to gain access to publication funds, which is not an environment that the process of publishing scientific research should ever be responsible for creating; nor should potentially important research on conservation of critically endangered species fly under the academic radar due to APC funding constraints preventing research exposure.
Since the journals analyzed in this study are related to non-human biological sciences, these results also have implications for the research regarding ecology and conservation of species. Most biodiversity hotspots are located in the tropics; therefore, the vast majority of conservation research is conducted in tropical regions (Myers et al. 2000). While many nations in tropical regions fall within the criteria for APC assistance from Research-4Life, as they are considered developing or under-developed countries (Research4Life 2020), Many published articles coming from these undeveloped tropical regions historically include authors from developed countries (Stocks et al. 2008). With the current criteria systems in place for APC funding assistance in GOA journals for biological sciences through Research4life, foreign authors from developed countries would nullify the eligibility for assistance with publication costs, forcing authors to seek closed-access or hybrid journals, low-impact open-access journals, or potentially even predatory journals to publish their research.

Conclusion
To conclude, the current transition to GOA publishing by prestigious, high-impact journals, namely in non-human biological sciences, shows trends in inequality in global research output. Inequality amongst institutions, publishers, journals, and researchers is likely to prevent adequate exposure of potentially important research, while promoting the false ideology that prestige and costliness of journal publications are the equivalent of reliable science (Brembs 2018;Brembs et al. 2013;ElSabry 2017;Siler et al. 2018). In the current age of technology, most journals have flipped the publication model from print to digital and online (Beall 2013;Fitzpatrick 2011), and even with a decrease in hardcopy production, publication fees are still increasing (Morrison 2018). Journal publications, research impact, and citations are the academic currency of career scientists and scholars (Hirsch 2005) and the scientific community is international. We must address these issues to create a more inclusive environment for important research to be recognized and researchers to prosper on a global scale, regardless of country, income, or institutional affiliation.


Optimization of Selection of the Machinery Park in Sustainable Agriculture

: A correct selection of the machinery park is vital for correct functioning of a farm. It is significant in sustainable farming where, except for economic factors, application of a suitable technique and technology in order to lead an effective production is crucial. The paper presents a method of designing a set of machines for a farm. The method was implemented in the computer application. A suitably selected, optimised machinery park enables a sustainable agricultural production and achievement of the desired economic, production and environmental effects. The application was practically verified and is used in teaching and farming practice. insurances, or subsidies it is possible to calculate a production balance in a farm. In case the result is unsatisfactory, returns to previous versions of the project and new calculation after corrections are possible. Feedbacks marked on the diagram show places to which one can return in order to correct data. A vast range of data causes that bases must be properly built. Presently, the following data bases are used in the model: database of machines and farm tractors, database of mineral and organic fertilizers, database of crop protection substances, database of products and production means. The use of information available in databases enables automation of calculation and a relevant capacity of the base enables the increase of the number of the analysed simulation results.

inter alia, because of the limitations concerning data [21,22]. Attempts to use Big Data for the support of agricultural production management have been taken for several years [23].
Decision processes in management of agricultural machines, except for decisions concerning current exploitation of machines include a decision on selection and collection of sets of machines of farms [24]. In these cases, a key aspect is a need to undertake best decisions to increase production, raising its quality and maintaining suitable environmental conditions. A high participation of mechanization costs causes that a correct choice of the machines set and its relevant use that guarantee the lowest mechanisation costs and thus the highest incomes from the rendered activity is significant [25].
When designing a machinery park of farms, many methods of designing are used, including indicator and coefficient methods, technological methods (including a peak method of uniform works) or the linear programming method [26]. Research concerning the search for a rational selection method of machines for a single farm show clearly the problem scale with which an owner will have to face when taking decisions concerning investing in the agricultural technology [27]. Informatics and artificial intelligence are more often used for control of complex technical and technological solutions, which support production processes in an agricultural farm.
Presently, even big farms often buy new machines not having in mind rational principles of their selection but under the impulse of an immediate need of purchase or present opportunities to make a purchase e.g., in the form of the possibilities of funding the purchase from outside funds [28]. On the other hand, small farms have a set of machines that are merely used, and its size depends on many various factors which, as a rule, have not much in common with farmer's real needs [29]. The studies show that principles of the sustainable agriculture including a conservation tillage are applied mainly by big farms. Owners of farms merely comply to these principles [30].
Technological methods of selection of a machinery park in farms, although they have good results, are rarely used in practice. Producers and sellers of farm machines who want to sell their products, convince farmers to make a purchase often using simplified calculation methods. Such calculations of profitability are not always thorough, as a rule, they are based on simplified rates and cannot prove objective results. Precise calculations of profitability require laborious calculations that include production technologies used by farmers and resources engaged in the production process. Additionally, the process of designing is impeded by mutual relations which occur in a farm including various production branches, technical equipment and other elements of the agricultural enterprise.
Agricultural producers are interested mainly in a current control of the production process and reporting related thereto. Thus, computer programs that a farmer is offered include supporting of the current production management, reporting and problems solving, which may occur in the close future [31,32]. The problems of exploitation of the machinery park in a farm may be included as an element of the decision support system for the entire farm or be a subject of the separate application [33][34][35]. Although there are many IT tools that support decision-making in agriculture, the use of those applications by farmers is quite low [36]. On the other hand, the analyses that were carried out prove that farmers are very engaged users of farm management supporting systems [37][38][39]. The studies proved that in general, they look for specific advices from advisers and specialists.
Although there are many programs that support designing of various technical systems, there are few applications that enable the best design of a machinery park in an agricultural farm. This function is performed by OTR-7 program that acts based on the modified technological method and enables designing a production technology in a farm and on its basis enables calculation of an indispensable number of machines, their annual use and exploitation costs. In practice, operational sheets are only pieces of a project since for making all calculations the entire production that is carried out by a farmer must be designed. As a result, a model is formed that enables analysis of various options of the equipment of a farm and its production systems. Therefore, OTR-7 program, except for its basic destination (designing a machinery park) enables a complex analysis of the entire farm and production profitability. Although, the method applied in the program is mainly designated for designing the multi-area farms, it may be used successfully also for designing small objects and for reorganization of the existing farms.
A possibility of planning mechanization services and a detailed calculation of the costs of exploitation of machines are additional functions of the program. The correct design of mechanization in a farm is a significant element of the sustainable agriculture.
The objective of the study is to present calculation methods developed for OTR-7 program and used in this application. The described computer program is a tool, where its algorithms and calculation procedures were tested practically in real farms. During classes, students with the use of OTR-7 learn the principles of correct designing of a machinery park and analyse the impact of changes in the set of machines as a result of the activity of a farm or a group of farms.

Materials and Methods
Modified technological methods of peaks of uniform works were used for designing a machinery park of a farm. This method is based on production technologies, designed in the form of operational sheets. Operational sheets of plants include a set of agri-technical activities carried out for a specific plant along with determination of the date and the surface on which the activity is performed. These sheets after transformation enable making a list of works in the quantitative and time view which enables determination of the periods of the highest intensity of works. These periods of accumulation of works along with the assumed time, serve for calculation of the minimum number of sets of machines indispensable for performing works in the assumed time.
In a classical approach, this method has some flaws. In the presented solution it was thus properly modified to better correspond to the requirements of calculations with the use of a computer technology. For the purposes of creation of software, operational sheets were modified adding a possibility of including technologies applied in animal production and additional activity carried out in a farm. Each of these departments required preparation of a special type of an operational sheet specific for a particular activity. For designing plant production it was assumed that agrotechnical activities are planned with a precision to one decade (i.e., 10 days). Such a precision is sufficient and is often used when planning field works. It enables assumption of the available time which includes a possibility of occurrence of unpredicted random events (60 available hours in a decade were assumed by default). The animal production has got a completely different specificity, thus technological sheets used here concern mainly activities that are carried out regularly (everyday) which include, inter alia: duration of activity or available time, multiplication (on how many days is the activity performed) and the period to which the sheet refers to (number of days, time limit). Another, the third type of the technological sheet enables determination in a simplified form, the time of work in particular decades of the year and is mainly used for general farming works (additional activity). Although, particular types of sheets are dedicated for specific production departments, during the verification of the method it was found out that there is a need to use various types of sheets in various production departments interchangeably. As a result, the method and the software provide for such an opportunity.
It is assumed that the developed application has not only to enable calculation of the minimal required number of machines but also enable calculation of costs of their exploitation, expenditures of human work and calculation of a thermal balance of the entire farm and a detailed analysis of the results of calculations. The designed production technologies (operational sheets) enable estimation of the annual use of machines and this combined with the parameters of machines (such as e.g., price of a machine, unit fuel consumption, exploitation period of a machine etc.,) enables calculation of particular elements of their costs. Collection of information on the performed production in the data base of OTR-7 program in combination with the calculated costs of mechanization enable calculation of the thermal balance of a farm according to the following Equation (1): where PG means production obtained for particular plants (R), production of animal groups (Z) and additional production (D); NM stands for expenditures incurred on each crop (R), animal group (Z) and additional activity (D); KM stands for mechanization costs including costs of exploitation of particular tractors and agricultural machines and mechanization services; KB stands for costs of buildings and KI for additional costs that cannot be ordered to any production branch.
Modelling consists of simplification of complex facilities and phenomena that take place in a real world to obtain a clear model which may be used for desired purposes (e.g., optimisation) [40,41]. An agricultural farm is a specific facility that may carry out varied production. The fact that modelling is related to biological facilities in combination with the random character of phenomena that take place in the environment causes that the farm model may be more complex than the model of the production enterprise. Additional impediment results from relations between the production departments, division of production resources and a great variability of farms (various cultivated plants, animal groups, production technologies, etc.,). As a result, although the general formula is quite simple, calculation of each of elements may be a complex process.
The main purpose of functioning of an enterprise or a farm (and of designing) is obtaining a high income, namely maximisation of a function f(x) with maintaining border conditions. In the analysed cases it was assumed that production (PG) and material expenditures (NM) do not change (const) and only a technique and technology of production change through modification of the machinery park equipment. A suitable quality of the manufactured production and principles of sustainable agriculture are maintained. As a result, the function of the purpose is minimisation of the mechanization costs i.e., such change of tractors and machines owned by a farmer that enables obtaining minimal mechanization costs with maintenance of the assumed level of production and maintaining principles of the sustainable production. Such approach enables precise modelling of production in a farm including all departments of production that occur therein and elements of infrastructure and tractors and farm machines participating in it.
In order to perform calculations, it is necessary to collect in the software data indispensable to calculate particular output indices. To design a farm, information on, inter alia, machines, treatments in a farm, products, buildings, plant production, animal production, additional activity, production technology and employees, is needed. Data on the cultivated plants, inventory animals group or additional activity are stored in a uniform format where the data type depends on the type of production (plant, animal or additional production). The range of the stored data must include the network of relations between particular elements of the designed object (a farm).
The developed method was implemented in the software and was modified to enable modelling of events occurring in various types of farms. Modelling must be dedicated for a specific, single object or carried out universally. In the described case, it was assumed that the method should be universal and may be used in each type of a farm that has already existed or is being designed. It enables a wide application of the software, but some elements must be designed in a simplified manner. Although, modelling assumes some simplifications, however, one should aim to copy the reality in the most credible manner.

Results
One of the principles of sustainable agriculture is a rational use of the production means owned by a farmer to obtain a relevant income by a farmer. Relevant equipment with machines and farm tractors has a significant impact not only on the economic indicators but also on the impact on the natural environment, consumption of energy carriers, ergonomics of work and many others. The developed method and the computer program based on it are applied in the existing or formed new farms. Designing of new facilities and modernisation of the existing ones is possible to obtain better production results with keeping the set limitations.

Calculation Method
A simplified block scheme of a farm and the calculation method of the selected indicators used in the described method are presented in Figure 1.
Sustainability 2020, 11, x FOR PEER REVIEW 5 of 16 farms. Designing of new facilities and modernisation of the existing ones is possible to obtain better production results with keeping the set limitations.

Calculation Method
A simplified block scheme of a farm and the calculation method of the selected indicators used in the described method are presented in Figure 1.  The schematic representation is universal, covers entire farms and enables introduction of data of practically each existing or newly formed facility. The process of designing starts from introduction Sustainability 2020, 12, 1380 6 of 15 of general data (first assumptions) that characterize a designed facility. Another stage of designing the production. The program stipulates three production departments: plant, animal and additional activity (which may be a profitable activity but also general farming and cleaning activities etc.,). Mechanization services that by increasing the use of machines and tractors significantly affect the mechanization costs were distinguished.
In case of production planning, it is necessary to determine plant crops (main and side) and material expenditures (sowing material, seedlings, fertilizers, crop protection substances, fodder, etc.,). Another stage is planning the production technology in the form of operational sheets. In case of plants, the most often dates are agreed with a precision to one decade (10 days), in case of daily works in animal production, the daily time for a particular activity. There is also a possibility to determine the number of hours in particular period in the form of a mark-up-such solution is good in planning general farming works and outside transport. Another step is determination of the method of performance of agrotechnical activities. Three methods of performance of works are expected: with own machine, through a service and manually (without machines). Respect for resources of the natural environment is an absolute condition that must be included in the process of designing Figure 2 presents the types of data that are provided to the model to obtain results of calculations. Data that are used in calculations may be introduced manually by the system user (left side of the diagram) or collected from relevant data bases (right side of the diagram).
Sustainability 2020, 11, x FOR PEER REVIEW 6 of 16 The schematic representation is universal, covers entire farms and enables introduction of data of practically each existing or newly formed facility. The process of designing starts from introduction of general data (first assumptions) that characterize a designed facility. Another stage of designing the production. The program stipulates three production departments: plant, animal and additional activity (which may be a profitable activity but also general farming and cleaning activities etc.,). Mechanization services that by increasing the use of machines and tractors significantly affect the mechanization costs were distinguished.
In case of production planning, it is necessary to determine plant crops (main and side) and material expenditures (sowing material, seedlings, fertilizers, crop protection substances, fodder, etc.,). Another stage is planning the production technology in the form of operational sheets. In case of plants, the most often dates are agreed with a precision to one decade (10 days), in case of daily works in animal production, the daily time for a particular activity. There is also a possibility to determine the number of hours in particular period in the form of a mark-up-such solution is good in planning general farming works and outside transport. Another step is determination of the method of performance of agrotechnical activities. Three methods of performance of works are expected: with own machine, through a service and manually (without machines). Respect for resources of the natural environment is an absolute condition that must be included in the process of designing Figure 2 presents the types of data that are provided to the model to obtain results of calculations. Data that are used in calculations may be introduced manually by the system user (left side of the diagram) or collected from relevant data bases (right side of the diagram).  Further stages of calculations do not require any user's interference (on the diagram these are rectangles with a white background). Number of hours in given decades is calculated. On this basis, a minimum necessary number of machines and the number of people which must be employed in a farm is determined. After additional elements have been included, such as buildings and taxes, insurances, or subsidies it is possible to calculate a production balance in a farm. In case the result is unsatisfactory, returns to previous versions of the project and new calculation after corrections are possible. Feedbacks marked on the diagram show places to which one can return in order to correct data.
A vast range of data causes that bases must be properly built. Presently, the following data bases are used in the model: database of machines and farm tractors, database of mineral and organic fertilizers, database of crop protection substances, database of products and production means. The use of information available in databases enables automation of calculation and a relevant capacity of the base enables the increase of the number of the analysed simulation results. Figure 3 presents a scheme of obtaining the selected results calculated by OTR-7. Possibility of access to further levels, even more detailed data enables a manner of model analysis. It enables an easy search and correction of elements that unfavourably influence the obtained output indices. a minimum necessary number of machines and the number of people which must be employed in a farm is determined. After additional elements have been included, such as buildings and taxes, insurances, or subsidies it is possible to calculate a production balance in a farm. In case the result is unsatisfactory, returns to previous versions of the project and new calculation after corrections are possible. Feedbacks marked on the diagram show places to which one can return in order to correct data.
A vast range of data causes that bases must be properly built. Presently, the following data bases are used in the model: database of machines and farm tractors, database of mineral and organic fertilizers, database of crop protection substances, database of products and production means. The use of information available in databases enables automation of calculation and a relevant capacity of the base enables the increase of the number of the analysed simulation results. Figure 3 presents a scheme of obtaining the selected results calculated by OTR-7. Possibility of access to further levels, even more detailed data enables a manner of model analysis. It enables an easy search and correction of elements that unfavourably influence the obtained output indices.
Indices calculated by the program may be analysed on many levels, and the results may be presented in the form of tables and graphs.  Indices calculated by the program may be analysed on many levels, and the results may be presented in the form of tables and graphs.

Description of OTR-7 Program
OTR-7 program (see supplementary) was written in Delphi language (in Embarcadero RAD Studio environment). The program data are recorded in files with a suitable format including data on the designed object. During the work of the program, specially developed algorithms of calculations are performed. For protection against introduction of incorrect information, the program is equipped with mechanisms that serve for initial verification of the introduced data. When the data are incorrect, the program signalizes this with a suitable message. Despite these limitations, the user has a considerable freedom to enter data which shows that the program is universal. If there are no data or data are incorrect, the program ceases calculations and informs the user where the error occurred suggesting at the same time how to remove it. Introduction of edit boxes in the program marked with red, which means incorrect values and with yellow-not recommended values (probably incorrect) caused that the number of errors caused by users who make designs decreased considerably.
To make a project/model of a farm, it is necessary to introduce the data that describe the production. In case of the plant production, these are: areas of particular crops, yields, material expenditures and additional data, such as: a level of subsidies for production. Technological sheets suitable for each production type are a significant part of the model. As the above-mentioned data are introduced to the software, information on products in a farm and production activities occur. Another set of information concerns farm machines used in a farm and buildings. A relevant design of the above-mentioned elements enables calculation of the output indices of the model.
In case a full set of initial data is introduced, the program automatically calculates the indicators that characterise a farm. Such calculation is performed automatically after each change introduced by a designer. A module that enables showing the interface in various languages was used, which gives an opportunity to use OTR-7 program in various countries. The application may be started with the interface in Polish or English. Introduction of further language versions requires translation of messages included in the text file and selection of the translation file in the options of the program. The application is designed to work on Windows platform. It also operates correctly in Linux environment. The software was compiled and then the installation program was created. Configuration data are stored in the user's profile. Additional applications are installed and configured in a similar manner. OTR-7 program is available on the author's website, it is free, and its use does not require introduction of any charges.
The use of OTR-7 is intuitive but for correct operation, knowledge of the designing method is required. Knowledge of the principles of agrotechnology, agricultural technique, economics of agriculture, principles of sustainable agriculture and any other which enable to correctly make and analyse the equipment and production project in a farm is indispensable. The program has a user's manual and on the webpage of the program there are animations showing step by step how to work with the program. Animations were made in flash technology and additional commentaries enable understanding of the principles of work with the program.
The window of the program is divided into two parts ( Figure 4). The upper part serves for introduction of data, the lower, on the other hand, includes results of calculations. Particular parts of the project are grouped in relevant sheets and selected elements open their dialogue windows. The results are presented in tables or graphs with a possibility to analyse the values of selected indices.
Since, in modern programming methods, the program operates by events handling (e.g., clicking of any button), making the calculations algorithm does not require filling of subsequent dialogue fields (solution along with the following filling of fields is often used in non-complex programs and internet applications). As a result, the order of data introduction is free. However, it is recommended to fill the fields and bookmarks with the order resulting from the applied design method. The person that designs the farm may return to the previous data and correct them any time. An exemplary screenshot ( Figure 4) presents a data card of the selected machine (a big tractor)-an upper part of the program  Since, in modern programming methods, the program operates by events handling (e.g., clicking of any button), making the calculations algorithm does not require filling of subsequent dialogue fields (solution along with the following filling of fields is often used in non-complex programs and internet applications). As a result, the order of data introduction is free. However, it is recommended to fill the fields and bookmarks with the order resulting from the applied design method. The person that designs the farm may return to the previous data and correct them any time. An exemplary screenshot ( Figure 4) presents a data card of the selected machine (a big tractor)-an upper part of the program window and below the calculated use of machines along with the graph of the machine use within one year (a tractor) as well as the window with a list of treatments performed during a selected period (2nd decade of September).
In order to maintain a universality of the program, it was assumed that there is no built-in data bases in the program, that include information which may become outdated with time. Such data may be imported from other applications that are developed regardless OTR-7 program and are updated systematically. As a result, OTR-7 program may import the following external data: -Data on machines from the catalogue of farm machines (program Maszyny-2, Maszyny-3, Maszyny-4); -Mineral fertilization plan (program Nawozy-2, Nawoy-5); -Chemical plant protection plan (program Herbicyd-2); -Calculation of the work cycle of a machine (program Agregat-2); -Machine power demand (program Bilenero); -Selected data from other projects made in OTR-7 (e.g., machine data).
The whole forms a system including several applications that enable designing of any farm. Data are transferred between particular programs with the use of a clipboard of Windows system. In order to maintain a universality of the program, it was assumed that there is no built-in data bases in the program, that include information which may become outdated with time. Such data may be imported from other applications that are developed regardless OTR-7 program and are updated systematically. As a result, OTR-7 program may import the following external data: -Data on machines from the catalogue of farm machines (program Maszyny-2, Maszyny-3, Maszyny-4); -Mineral fertilization plan (program Nawozy-2, Nawoy-5); -Chemical plant protection plan (program Herbicyd-2); -Calculation of the work cycle of a machine (program Agregat-2); -Machine power demand (program Bilenero); -Selected data from other projects made in OTR-7 (e.g., machine data).
The whole forms a system including several applications that enable designing of any farm. Data are transferred between particular programs with the use of a clipboard of Windows system.
When the program was created, attempts were made to always calculate the same index in the same manner with the same procedure. Additionally, majority of functions and calculation procedures was designed in such a way to perform the calculations for the selected input parameters. For example, to determine the costs of machines a procedure is used that calculates the machine use. Whereas, for calculation of the farm balance, a procedure that calculates the costs of a machine is used. On the other hand, calculation of the global production of a farm, depending on the set of input parameters of the procedure, provides a production of the entire farm, plant or animal production or production obtained with a selected plant. Such approach requires a good design of the application structure and a very well thought out creation of functions and procedures. However, as a result, it enables avoiding many programming mistakes and provides for an opportunity to calculate and show in the program which element factors influence the value of the calculated indices.
The program enables a multi-level analysis of the obtained results. Except for calculation of many indicators that characterize farms and its machinery park, it is possible to show additional information such as diagrams and sets as well as values, which comprise the calculated indicator. Such approach enables simpler search for elements which may be corrected and such that are the most or the least effective. The program also has elements that facilitate its use in teaching.

Verification of the Method
The described method of designing and the computer program that uses it was verified and tested in practice. The program was used for optimization of the existing farms and for designing non-existing objects. In case of real objects, results of simulation calculations made in the program were confirmed often through the effects of changes introduced by farmers in the analysed farms. Additionally, with the use of the program, students made several hundred designs. By this, they learn how to design farms and in particular a machinery park and agricultural production technologies.
To show effects obtained with the method and the computer program that uses it, the further part of the section presents the selected results of model calculations. Table 1 shows the selected parameters of particular models. Indices were provided for the basic version of the model (A). Exemplary results of simulation made on nine objects are presented in Figures 5-7. Simulations were made for agricultural farms with a varied surface area. Farms were characterised with a varied structure of sowing. As a result, equipment with farm tractors and machines also differed. The surface area of the analysed objects was respectively 150 ha in model 1; 120 ha in model 2; 90 ha in model 3; 60 ha in model 4 and 30 ha in models 5-9. The presented results of analyses concern three versions of the farm project. Each subsequent version of the project is better than the previous one. The diagram also shows a percentage decrease of the mechanization costs in further versions (a change from version A to B and from version A to C) and the income of a farm (in thousand PLN). The base project (version A) not always was profitable. In some cases, a positive balance could not have been achieved with the use of only own machines (version B). Introduction of possibilities of rendering mechanization services included in version C. In case of students' machine sets were designed in such a manner. One may notice, a considerable divergence of the calculated indexes in farms with the same surface area (30 ha-models from 5 to 9), which is confirmed by the fact that amount of the income is determined only by the farm area. The manner of managing the farm mainly influences the effects of farming. criterion cannot be the only one which is taken into consideration. Non-economic factors are of great meaning, especially those which influence the crop quality, ergonomics of the performance of work and the impact of the production on the natural environment. Including these factors in the optimization process may be carried out through application of suitable conditions which must be absolutely met. A sustainable production should result from designing relevant production technologies and equipping a farmer with a suitable set of farming machines.  Figure 6 shows a size of the selected indices that characterize a machinery park of farms in particular models. The annual use of all owned tractors by farmers was described in hours and the annual fuel cost in K PLN. In model farms, fuel (diesel oil) was used by tractors and self-propelled machines including harvesters and field chuff-cutters. These indices reduced in most cases as a result of the optimization that was carried out.    Figure 6 shows a size of the selected indices that characterize a machinery park of farms in particular models. The annual use of all owned tractors by farmers was described in hours and the annual fuel cost in K PLN. In model farms, fuel (diesel oil) was used by tractors and self-propelled machines including harvesters and field chuff-cutters. These indices reduced in most cases as a result of the optimization that was carried out.  There was one exception. Namely, a situation when mechanization services, which could increase both the use of tractors and fuel consumption, were provided. However, the increase of these costs is compensated with incomes obtained for provided services which as a result positively influenced the economic effect.
Although, in general labour inputs in the analysed model reduced in subsequent versions, also in this case, the increase of the number of work hours in some C models is caused by provision of mechanization services. The increase of fuel consumption designed for works outside a farm, although it burdens a farm, globally gives positive environmental results since it enables elimination of unnecessary machines in the client's farm. It should be noticed that the size of the calculated indices does not only depend on the farm area. In the 120 ha object, the highest inputs were incurred than in the 150 ha farm and the inputs in the third farm (60 ha) are lower than in some 30 ha objects. Educational application of an application is of great importance. Therefore, except for software for teaching purposes, it was necessary to develop relevant schedules and the scope and instructions for designs. Designs made by students aim not only at obtaining relevant economic results but also at performing in simulations effects which are important from the point of view of sustainable agriculture. These effects may be obligatory or obtained as a final result-in this case the assessment of the design will depend on the degree of realisation of these requirements. To obtain relevant effects of learning, it is important to discuss the obtained results of calculations, thus analysis and justification. Therefore, such effects were obtained. Such detailed analysis may be carried out with the use of the described computer program. The use of a program as a part of classes enabled to Simulations made showed that there is a possibility of the considerable growth of the production profitability of a farm with relevant design of the production technique and technology. The presented results show how one may increase the production effectiveness with the use of relevant designing methods. It should be emphasised that during designing of the machine set, the economic criterion cannot be the only one which is taken into consideration. Non-economic factors are of great meaning, especially those which influence the crop quality, ergonomics of the performance of work and the impact of the production on the natural environment. Including these factors in the optimization process may be carried out through application of suitable conditions which must be absolutely met. A sustainable production should result from designing relevant production technologies and equipping a farmer with a suitable set of farming machines. Figure 6 shows a size of the selected indices that characterize a machinery park of farms in particular models. The annual use of all owned tractors by farmers was described in hours and the annual fuel cost in K PLN. In model farms, fuel (diesel oil) was used by tractors and self-propelled machines including harvesters and field chuff-cutters. These indices reduced in most cases as a result of the optimization that was carried out.
There was one exception. Namely, a situation when mechanization services, which could increase both the use of tractors and fuel consumption, were provided. However, the increase of these costs is compensated with incomes obtained for provided services which as a result positively influenced the economic effect.
Although, in general labour inputs in the analysed model reduced in subsequent versions, also in this case, the increase of the number of work hours in some C models is caused by provision of mechanization services. The increase of fuel consumption designed for works outside a farm, although it burdens a farm, globally gives positive environmental results since it enables elimination of unnecessary machines in the client's farm. It should be noticed that the size of the calculated indices does not only depend on the farm area. In the 120 ha object, the highest inputs were incurred than in the 150 ha farm and the inputs in the third farm (60 ha) are lower than in some 30 ha objects.
Educational application of an application is of great importance. Therefore, except for software for teaching purposes, it was necessary to develop relevant schedules and the scope and instructions for designs. Designs made by students aim not only at obtaining relevant economic results but also at performing in simulations effects which are important from the point of view of sustainable agriculture. These effects may be obligatory or obtained as a final result-in this case the assessment of the design will depend on the degree of realisation of these requirements. To obtain relevant effects of learning, it is important to discuss the obtained results of calculations, thus analysis and justification. Therefore, such effects were obtained. Such detailed analysis may be carried out with the use of the described computer program. The use of a program as a part of classes enabled to remove errors in the program and introduce a modification and new functionalities suggested by students. Such a fast and precise feedback on the program performance would not be possible in case of other groups of users, such as e.g., farmers or farm advisers.

Discussion
Research on the IT application in the agricultural activity in a broad sense and in teaching, that have been carried so far, enable to conclude that propagation of the use of IT solutions in farm management, including those that support decisions of the rational selection of the machinery park, are right [42]. Fast effects of facilitation of management with particular processes of production carried out directly or indirectly by the use of a relevant technical base are visible. The obtained effects enable to significantly limit the risk of improperly taken decisions concerning the purchase of the technical equipment. This risk takes place when the result which may be obtained in the future is unknown. OTR-7 program, which is the subject of discussions enables determination of diverse options of procedure that eliminate the risk of improper choice of the machinery park by agricultural producers. The program is a universal tool and may be used in any place around the world where there is a need of rational planning of the equipment of the machinery park in agriculture. Models made using the described software well reflect farms that were proved by the verification carried out in real objects. This task in facilitated by the structure of the application equipped with language modules which can be easily translated into various languages.
Incorrect decisions taken with regard to the purchase of agricultural machines, except for economic effects, may cause unfavourable environmental effects [43]. This may cause increased pollution of the environment, great consumption of energy carriers, soil degradation, soil compacting by unnecessary crossings, elevated level of emission of fumes or the increased consumption of fertilizers and crop protection substances [44].
To train next generation of students, many institutions and universities created educational program in agroecology. These programs differ in particular countries, however, many of them are based on the case studies or designs concerning specific cases [45]. Teaching with the software that optimises the selection of the machinery park becomes a part of this trend [46]. To raise the level of knowledge of students, it is necessary to introduce modern teaching tools and techniques [47]. The supporting software for designing and optimisation of production processes considerably raises knowledge and skills of people who make designs [48,49]. Projects made with the use of OTR-7 teach how the correctly selected machinery park and used technologies influence the sustainable agricultural production.

Conclusions
The presented software uses a modified technological method of designing a machinery park in a farm. Calculation algorithms developed for the program enable calculations of basic indexes that characterize a machinery park and the production system of a farm. The developed software was verified and tested. It is used in the agricultural practice and for teaching methods of designing the machinery park and analysis of the impact of particular technologies on the production profitability.
A method of designing and the computer program that uses it are suitable for designing farms that carry out a sustainable agricultural production. Models of the farm equipment with corresponding production technologies enable selection of the solution, which not only enables achieving an appropriate farmer's income but also enables meeting the conditions of a production according to the principles of ecology and sustainable agriculture.