Modern models for predicting bankruptcy to detect early signals of business failure: Evidence from Montenegro.

This paper explores predicting early signals of business failure using modern models for bankruptcy prediction. It reviews how continuous operations enhance market value, strengthening competitiveness and reputation among stakeholders. The study involves medium and large companies in the Montenegrin market from 2015 to 2020, comprising 30 bankrupt and 70 financially stable firms. Logistic regression is also employed to create a logit model for early detection of bankruptcy signals in companies. This research establishes the empirical validity of modern models in predicting business failure in the Montenegrin market, particularly through logistic regression. Significant indicators, such as the Degree of Indebtedness (DI) and turnover ratio of business assets (TR), exhibit strong predictive power with a p-value less than 0.001 according to Likelihood ratio tests. The paper underscores the potential benefits of bankruptcy prediction for both internal and external stakeholders, especially investors, in enhancing the competitiveness of Montenegro's large and medium-sized companies. Notably, the research contributes by bridging the gap between theory and practice in Montenegro, as bankruptcy prediction models have not been extensively applied in the market. The authors suggest the possible applicability of the created logit model to neighboring countries with similar economic development levels. In that sense, the concept of predicting bankruptcy is positioned as integral to corporate strategy, impacting the overall reduction of bankruptcies. The paper concludes by highlighting its role as a foundation for future research, addressing the literature gap in the application of bankruptcy prediction models in Montenegro. The created logit model, tailored to the specific needs of Montenegrin companies, is presented as an original contribution, emphasizing its potential to strengthen the competitiveness of companies in the market.

Research on the Effect of Load and Rotation Speed on Resistance to Combined Wear of Stainless Steels Using ANOVA Analysis.

This research was carried out with the aim of obtaining appropriate principles for describing the influence of working parameters and the aggressive action of an acidic medium on the wear and corrosion resistance of martensitic stainless steels. Tribological tests were performed on induction-hardened surfaces of stainless steels X20Cr13 and X17CrNi16-2 under combined wear conditions at a load of 100 to 300 N and a rotation speed of 382 to 754 min-1. The wear test was carried out on a tribometer with the use of an aggressive medium in the chamber. After each wear cycle on the tribometer, the samples were exposed to corrosion action in a corrosion test bath. Analysis of variance revealed a significant influence of rotation speed and load due to wear on the tribometer. Testing the difference in the mass loss values of the samples due to corrosion using the Mann-Whitney U test did not show a significant effect of corrosion. Steel X20Cr13 showed greater resistance to combined wear, which had a 27% lower wear intensity compared to steel X17CrNi16-2. The increase in wear resistance of X20Cr13 steel can be attributed to the higher surface hardness achieved and the effective depth of hardening. The mentioned resistance is the result of the creation of a martensitic surface layer with dispersed carbides, which increases the resistance to abrasion, dynamic durability, and fatigue of the surface of the protective layer.

Influence of cultivar and fertilization treatment on the yield and leaf nutrients content of apple (Malus domestica Borkh.).

Fertilisation strategy can have a big impact on apple (Malus domestica Borkh) yield, with considerable environmental and economic implications. This research paper presents the yield and leaf nutrients content of three apple cultivars fertilised with three treatment regimes over 2 years (2020-202) in Bosnia and Herzegovina. The specific apple cultivars investigated were: Jonagold Decosta, Red Idared and Gala Schnitzer®Schniga, each fertilised with three treatments: T1 (control‒without fertilization); T2 (300 kg ha-1 NPK (6:18:36) + 150 kg/ha N (calcium ammonium nitrate‒CAN)) and T3 (foliar nutrition‒mixture organic-mineral fertilizer commercially named "FitoFert Kristal" (0.6%) (10:40:10) + "FitoFert Kristal" (0.6%) (20:20:20) + "FoliFetril Ca" (0.5%) (N:Ca)) in Bosnia and Herzegovina in the period of two years (2020-2021). Significant differences of different yield categories (yield per tree, yield per hectare and yield efficiency) were found among cultivar/treatment combinations, cultivars, treatments and years. Yield per tree, yield per hectare and yield efficiency were lowest in cultivar Jonagold DeCosta. Fertilization treatment T1 significantly influenced the lowest yield per tree and yield per hectare with the magnitudes 7.55 kg tree-1 and 27.96 t ha-1, respectively. The highest yield efficiency was found in trees fertilised with treatment T3 with 9.21 55 kg tree-1, 34.11 96 t ha-1 and yield efficiency of 0.25 kg cm-2. Six mineral elements in the apple leaf, such as boron (B), calcium (Ca), manganese (Mn), iron (Fe), potassium (K), and zinc (Zn), were presented in known magnitudes. The cultivar Jonagold DeCosta's leaves had the highest K, B, and Zn contents with 8500.8 mg kg-1 FW (i.e. fresh weight of leaves), 33.8 mg kg-1 FW, and 12.2 mg kg-1 FW, respectively, while cultivar Red Idared's leaves had the highest Ca, Fe, and Mg contents. The fertilisation treatment T3 influenced significantly the highest content of Ca (301.37 mg kg-1 FW), Fe (116.5 mg kg-1 FW), B (41.6 mg kg-1 FW), Mn (22.4 mg kg-1 FW), and Zn (14.9 mg kg-1 FW) in leaves, while the highest content of K was found in leaves from trees fertilised with treatment T2 (8130.5 mg kg-1 FW). The experimental outcomes have proven that the cultivar/treatment combinations, cultivars, treatments, and time duration (in years) are the key factors affecting the potassium, calcium, iron, boron, and manganese contents. It was concluded that the foliar application enables easier mobility of elements, which results in a greater number of fruits and larger fruits, which leads to a higher yield. This study is the first of its kind in Bosnia and Herzegovina, and the findings of this research will pave the way for future research activities involving increasing the number of cultivars and different fertilisation treatments on apple yield and leaf mineral composition.

Feasibility study for estimating optimal substrate parameters for sustainable green roof in Sri Lanka.

In twenty-first century buildings, green roof systems are envisioned as great solution for improving Environmental sustainability in urban ecosystems and it helps to mitigate various health hazards for humans due to climatic pollution. This study determines the feasibility of using five domestic organic wastes, including sawdust, wood bark, biochar, coir, and compost, as sustainable substrates for green roofs as compared to classical Sri Lankan base medium (fertiliser + potting mix) in terms of physicochemical and biological parameters associated with growing mediums. Comprehensive methodologies were devised to determine the thermal conductivity and electric conductivity of growing mediums. According to preliminary experimental results, the most suitable composition for green roof substrates comprised 60% organic waste and 40% base medium. Sawdust growing medium exhibited the highest moisture content and minimum density magnitudes. Biochar substrate was the best performing medium with the highest drought resistance and vegetation growth. The wood bark substrate had the highest thermal resistance. Growing mediums based on compost, sawdust, and coir produced the best results in terms of nitrate, phosphate, pH, and electric conductivity (EC) existence. This study provided a standard set of comprehensive comparison methodologies utilising physicochemical and biological properties required for substrate characterization. The findings of this research work have strong potential in the future to be used in selecting the most suitable lightweight growing medium for a green roof based on stakeholder requirements.

Measurement of Air Pollution Parameters in Montenegro Using the Ecomar System.

Particulate matter air pollution is one of the most dangerous pollutants nowadays and an indirect cause of numerous diseases. A number of these consequences could possibly be avoided if the right information about air pollution were available at a large number of locations, especially in urban areas. Unfortunately, this is not the case today. In the whole of Europe, there are just approximately 3000 automated measuring stations for PM10, and only about 1400 stations equipped for PM2.5 measurement. In order to improve this issue and provide availability of real-time data about air pollution, different low-cost sensor-based solutions are being considered both on-field and in laboratory research. In this paper, we will present the results of PM particle monitoring using a self-developed Ecomar system. Measurements are performed in two cities in Montenegro, at seven different locations during several periods. In total, three Ecomar systems were used during 1107 days of on-field measurements. Measurements performed at two locations near official automated measuring stations during 610 days justified that the Ecomar system performance is satisfying in terms of reliability and measurement precision (NRMSE 0.33 for PM10 and 0.44 for PM2.5) and very high in terms of data validity and operating stability (Ecomar 94.13%-AMS 95.63%). Additionally, five distant urban/rural locations with different traffic, green areas, and nearby industrial objects were utilized to highlight the need for more dense spatial distributions of measuring locations. To our knowledge, this is the most extensive study of low-cost sensor-based air quality measurement systems in terms of the duration of the on-field tests in the Balkan region.

Attracting Green Consumers as a Basis for Creating Sustainable Marketing Strategy on the Organic Market-Relevance for Sustainable Agriculture Business Development.

The aim of this paper was to analyze the main factors that affect green consumers' choice regarding the purchase of organic agriculture products. The data collected through a survey of 559 green consumers were analyzed using explanatory factor analysis, the Relative Importance Index, and logistic regression. The results point out eleven main factors related to the offerings on the organic agriculture market that predominantly drive green consumers' purchasing decisions. The Relative Importance Index identified health benefits that stem from a specific way of production as the main purchasing motive. This was also confirmed by the results of logistic regression, which showed that a respondent who buys organic agricultural products on a daily basis is approximately 71.5% less likely to disagree with the claim that organic products are healthier than non-organic, compared to a consumer who purchases organic products several times a week or month. However, as these benefits cannot be empirically confirmed, green consumers look for official labels on the product packaging. In order to assure the product quality, more than half of them find out very important information about producers: whether they have a product quality certificate (69.5%), how many years they are engaged in production (56.2%), and whether they have specific product packaging (54.9%). The Relative Importance Index also revealed that the main purchasing barriers that consumers face are scarce offerings and an insufficient development of the distribution channel, which were ranked in first and second place. The price as a barrier is of less importance. About 30.8% of the respondents are willing to pay up to 20% higher prices for organic food compared to conventional food, while 39.4% of them would pay even up to 40% higher prices. Based on the given results, there are clear suggestions for creating a sustainable marketing strategy for organic agriculture products as the main prerequisite for an increase of healthy food choices and fostering the future development of organic agriculture businesses at the local and global levels.

The Impact of Online Media on Parents' Attitudes toward Vaccination of Children-Social Marketing and Public Health.

The aim of this paper was to investigate the level of influence of online media on the parents' attitudes toward vaccination of children in three countries of the Western Balkans-Montenegro, Serbia, and Bosnia and Herzegovina, in order to use the potentials of this form of communication effectively and efficiently. Online media are a critical factor of influence on the formation of attitudes in many areas of modern society, which is why their proper use plays an important role in strengthening vaccine confidence and which may further contribute to improvement of public health. On the other side, having in mind the fact that communication is an integral part of marketing, it is clear that social marketing has an extremely important role regarding the analyzed topic, especially because of the fact that social marketing activities tend to change or maintain people's behavior for the benefit of individuals and society as a whole. For the purpose of this research, a conceptual model was developed. Quantitative research was conducted online in the first quarter of 2020 using the survey method. Statistical analysis was applied to data collected from 1593 parents in the analyzed countries. The relevance of the hypotheses was tested using standard statistical tests, ANOVA test, eta coefficient, and logistic regression. The research showed that all analyzed variables from the model have a significant impact on the parents' attitudes toward the vaccination of children and that they correlate with the degree of trust in vaccines. The results also approved that online media have a significant influence on the formation of parents' attitudes toward the vaccination of children (obtained values of eta coefficient η2 = 0.216, η2 = 0.18, η2 = 0.167, η2 = 0.090, reliability Cronbach's Alpha 0.892), which confirms the importance of the use of social marketing in order to direct communication properly and to strengthen the level of trust in vaccines. Additionally, the results of logistic regression showed that the following groups of parents are particularly vulnerable to the influence of online media on attitudes toward vaccines: women, parents of younger age ("millennials"), and parents who are in common law marriage, as well as parents who have more children. In addition, the results showed that there is no statistically significant difference in the attitudes of parents in the observed countries (η2 = 0.000, F = 0.85). Based on the results of the research, the authors suggest that decision makers should pay more attention to modern forms of online communication and social marketing in order to use their potential for improvement of public health, as well as avoid the harmful impact that certain forms of communication may have on the formation of attitudes and loss of confidence in vaccines. The findings provide an important contribution for public health policy makers to identify and understand properly the impact of online media and social marketing and thus to better adapt their initiatives to changes in modern society.

The Analysis of Marketing Factors Influencing Consumers' Preferences and Acceptance of Organic Food Products-Recommendations for the Optimization of the Offer in a Developing Market.

Considering the benefits of the organic production system, it is recognized as one of the main drivers of future economic development. However, the imbalance between demand and supply at the local market level represents one of the serious obstacles that prevents its future growth. Therefore, this article examines the key factors related to the main elements of the offer that have the strongest impact on consumer preferences and acceptance of organic food products. In that sense, organic product, price, distribution channel, and promotion are considered the main elements of the offer and are analyzed in this paper from the consumer preferences perspective. Further, this article provides insight into some of the sensory properties of the offer that are important to consumers. Finally, it gives recommendations for optimization of the offer on the organic food market based on the analysis of the influence of each of those elements (product, price, distribution, and promotion) on consumer acceptance of organic products and making purchasing decisions. The data were collected using a questionnaire, and analyzed using the structural equation model (SEM). The results revealed that price and promotion have the strongest impact on consumer acceptance and buying decisions. Further analysis revealed that attitudes towards organic food products, price/quality ratio, distribution barriers, and modern media as a promotion instrument are the factors that have the most significant impact on consumer perception and attitudes towards the available market offer. These findings can help producers and other decision makers to better understand what creates added value of the organic food products in consumers' mind and therefore make an offer that is in line with their expectations and preferences, which is recognized as one of the main prerequisites for the acceptance and purchase of organic food products.

Comparative Characteristics of Ductile Iron and Austempered Ductile Iron Modeled by Neural Network.

Experimental research of cutting force components during dry face milling operations are presented in the paper. The study was provided when milling of ductile cast iron alloyed with copper and its austempered ductile iron after the proper austempering process. In the study, virtual instrumentation designed for cutting forces components monitoring was used. During the research, orthogonal cutting forces components versus time were monitored and relationship of cutting forces components versus speed, feed and depth of cut were determined by artificial neural network and response surface methodology. An analysis was made regarding the consistency of the measured cutting forces and the values obtained from the model supported by an artificial neural network for the investigated interval of the cutting regime. Based on the results, an analysis of the feasibility of the application of austempered ductile iron in the industrial sector with the aspect of machinability as well as the application of the models based on artificial intelligence, was given. At the end of the presentation, the influence of the aforementioned cutting regimes on cutting force components is presented as well.