Working Capital Management (hereafter WCM) is the strategic tool that helps a company navigate through challenging economic growth, and influence its competitive performance. Thus, this study examines the impact of WCM on the competitiveness of firms operating in the non-financial sectors in Pakistan. We use the Generalized Method of Moments (GMM) technique to ensure the robustness of our results. The study findings reveal that both a large net trade cycle and surplus working capital have a substantial negative impact on firms’ competitiveness within their respective industries. These results suggest that companies should streamline their investments in working capital accounts and concentrate more resources on long-term projects that maximize value to improve their competitiveness compared to other companies. Therefore, firms that are effectively managing their short-term financial affairs are experiencing much better performance in all aspects of firm performance. The research findings highlight the urgent need for governmental initiatives designed to improve WCM practices in these industries. It is imperative for the management of  companies with excess net working capital to maximize their working capital efficiency, aligning it with industry standards to enhance competitiveness. Moreover, policymakers should prioritize easing access to financial alternatives that allow enterprises to maintain an efficient working capital structure without relying on excessive measures. Furthermore, policymakers should be cautious when determining minimum cash balance requirements in a cash-strapped economy where external financing is relatively more expensive than in other regional economies.

This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.

Regional differentiation in the Russian Federation is considered to be high in terms of gross regional product (GRP) per capita level, growth rate, and other indicators. Inefficient use of region-specific spaces entails redistribution processes in order to maximize positive agglomeration effects throughout the country. These encompass economic restructuring based on production value-added chain extension and expanding inter-regional collaborative linkages. Besides, it is vital to assess the opportunities of individual Russian territories for participation therein. The research goal is to develop a scientifically based methodology to determine promising sectoral composition of the regional economies and that of spatial interactions. Such methodology would consider the feasibility of combining “smart” industrial specializations, regional resource potential, prevailing contradictions in the economic, innovative, and technological development of the country’s internal space. The proposed methodological approach opens the way to exploit the existing regional economic potential to the full, firstly, via establishing sectoral priorities of the region regarding the regulatory factors for the territorial capital to have a major effect on the increased potential GRP level; secondly, through benchmarking performance of the available development reserves within leading regions from homogeneous groups having similar characteristics and factor potentials; thirdly, via developing inter-regional integration prospects in terms of regional potential redistribution to ensure growth in potential gross domestic product. An extensive analytical and applied investigation of the proposed methodological approach was carried out from 2014 to 2020. Diversified estimates were obtained for a wide range of indicators due to evidences from 85 Russian regions and 13 types of economic activity. Such an integrated approach allows revealing actual imbalances and barriers that impede regional development, ensures the efficient use of production factors, and enables to trace ways to implement transformation policies and design effective regulatory mechanisms. The results provide arguments in favor of strengthening inter-regional connectivity and supporting inter-regional cooperation. This insight not only contributes to the academic discourse on complex development of a territory but also holds practical implications for policymakers and regional planners aimed at ensuring comprehensiveness and robustness of the evaluation supporting the decision-making process.

Purpose: This study aimed to explore the perception types of workplace spirituality among nurses. Method: To achieve this, Q methodology was applied, selecting 34 Q samples from a total of 102 Q statements extracted. The Q samples were distributed among 40 nurses and categorized into a normal distribution. A 9-point scale was used for measurement, and the data were analyzed using the pc-QUANL program. Results: The four types identified were ‘reflective type’, ‘nursing-oriented type’, ‘relationship-oriented type’, and ‘spirituality-oriented type’. Conclusion: The four types derived in this study classify nurses’ perceptions of workplace spirituality for establishing a nurse’s workplace spirituality that provides integrated nursing care. This categorization can serve as foundational information when planning workplace spirituality programs, considering each type’s characteristics.

The proposed scientific article aims to analyze the application of Lean Six Sigma in the food industry. To this end, a detailed methodology has been designed that ranges from the selection of the works to the synthesis and presentation of the results obtained. The methodology is based on rigorous inclusion criteria to ensure the relevance and quality of the selected sources, including books, academic articles, theses, and other relevant documents. Through extensive searches of academic databases and other reliable sources, key works were identified that specifically address the implementation of Lean Six Sigma in the context of food production. Once the relevant papers were collected, a critical analysis was conducted to identify common themes, trends, and key findings. The works were classified according to their main focus, such as process improvement, waste reduction, supply chain optimization and food safety assurance. This categorization allowed the information to be organized in a coherent way and to facilitate the synthesis of the results. The results obtained were presented in a table that included details about each selected work, such as title, author, year of publication, abstract and links to the original source. This structured and rigorous approach provides a clear and comprehensive view of the topic, contributing to the advancement of knowledge in this area and offering practical guidance for practitioners and researchers interested in the application of Lean Six Sigma in the food industry. The literature on Lean Six Sigma in the food industry highlights its importance in improving efficiency, quality, and safety. Key recommendations include gradual implementation, appropriate training, focus on quality, and continuous improvement.

This article examines how financial technology determines bank performance in different EU countries. The answer to that question would allow banks to choose their development policy. The paper focuses  on the main and most popular bank services that are linked to financial technology. A SWOT analysis of FinTech is also presented to show the benefits and drawbacks of FinTech. FinTech-based services are very diverse and are provided by financial  firms and banks alike. This paper looks at the financial technology provided by banks: internet usage (internet banking), number of ATMs, credit transfers in a country, percentage of the population in a country holding a debit or credit card and whether that population has received or made a digital payment. Using the multi-criteria assessment methods of CRITIC and EDAS, the authors analysed and compared the countries of the European Union and the financial technology used in them. As a result of the application of these methods, the EU countries under consideration were ranked in terms of the use of financial technology. Subsequently, three banks from different countries with different levels of the use of financial technology were selected for the study. For these banks, financial ratios of profitability were calculated to characterise their performance. Correlation and pairwise regression analyses between the banks’ profitability ratios and financial technology were used to assess the relationship and influence between these ratios. The main conclusion of the study focuses on the extent to which financial technology influences the performance of banks in the selected countries. It is likely that further research will try to take into account the size of the country’s population when analysing all financial technologies. Researchers also needed to find out what influence financial technologies have on the such financial indicators as operational efficiency (costs), financial stability, and capital adequacy.