Community pharmacies are highly accessed for vaccination and other injection services. The COVID-19 pandemic accelerated changes in work practices and in healthcare delivery, influencing patient preferences for timely and convenient care. This research examines patient-level and organizational factors associated with the administration of injections at Canadian community pharmacies during hours where other primary care providers may not be available. A cross-sectional retrospective analysis of appointments for injection services (vaccines and injectable medications) at community pharmacies through software from MedEssist or MedMe Health from January to December 2023 was performed. Appointments outside the hours of 9am to 5pm on weekdays, on weekends, or on federal or statutory holidays were considered to fall during 'off-clinic' hours when other health care settings where injections are provided may not be available. A multivariable logistic regression was performed to identify patient, pharmacy, community, or product factors associated with scheduling appointments during 'off-clinic' hours. Of 1,226,903 appointments scheduled, 27.0% were during off-clinic hours, ranging from 9.1% among banner or independent pharmacies to 34.0% among chain pharmacies. Scheduling of appointments during 'off-clinic' hours was positively associated with younger age (OR 1.74, 95%CI 1.69, 1.79 for age < 18 years vs. 18-49) and male gender (OR 1.05, 95%CI 1.03, 1.07 vs. female) and negatively associated with rural pharmacy location (OR 0.77, 95%CI 0.75, 0.80). Community pharmacies often provide care over extended hours, offering convenience and accessibility that can support vaccine uptake and injectable medication adherence. Younger patient age, male gender, and urban pharmacy location are associated with greater use of appointments outside of typical business hours.

How can competitiveness be maintained in deep-sea environments? Typical business model innovation and competitive strategies of marine aquaculture enterprises in China

This research presents the development of a universal genetic optimizer (UGO) aimed at solving optimization problems across a wide range of test functions, focusing on achieving reliable global extrema for both theoretical and practical applications. The study utilizes a genetic algorithm (GA) enhanced with neural network-based approaches, implementing key genetic operators such as crossover, mutation, and elitism. The algorithm was tested on benchmark functions including Rosenbrock, De Jong, and Griewank, among others, with statistical analysis identifying optimal parameter settings. The results demonstrate superior performance compared to traditional tools like Excel Solver and GAMS, particularly when elitism is included. The proposed framework highlights the adaptability of evolutionary computation when combined with machine learning techniques. Moreover, it opens perspectives for applying UGO in real-world optimization challenges such as logistics, energy systems, and engineering design.

The research background is the promotion of interest rate liberalization, deepening market opening, and urgent need for transformation. The research significance is to improve the theoretical system, provide strategies for practice, and provide references for policies. The research topic is to follow the logical mainline from necessity analysis to strategy construction, and comprehensively demonstrate the development of investment banking business. Combining macro environmental changes with micro banking practices, comprehensively considering multiple factors. Systematically demonstrate the strategic value and implementation path of investment banking business, with clear organization. The research method is literature review, which sorts out the theoretical framework related to the investment banking business of commercial banks. Comparative analysis method, comparing the differences in banking practices between domestic and foreign banks. Case analysis method, in-depth analysis of typical bank business practices. The research conclusion is that developing investment banking business is an inevitable choice for commercial banks to cope with the impact of interest rate marketization and an important path for transformation. It is necessary to break through the bottleneck of developing investment banking business through strategic focus, organizational restructuring, and talent construction measures.

ABSTRACT Severe turbulence, as evidenced during major crises over the past 15 years, challenges the effectiveness of taken-for-granted strategic stances such as entrepreneurial or digital postures, which are likely to be developed during typical business cycles. Our longitudinal study investigates how firms can protect, or fail to protect, sales growth under the atypical conditions of severe turbulence, depending on their adoption of entrepreneurial and digital postures and their trajectories from pre-turbulence growth. Our findings reveal a paradox: firms with high levels of pre-turbulence growth experience weaker post-turbulence growth when pursuing either a digital posture or an entrepreneurial posture or some combination of both. Instead, firms are most successful in increasing growth when they paradoxically minimise their postures, adopting a “no-posture” stance. Conversely, a no-posture stance proves particularly disadvantageous for firms with low pre-turbulence sales growth leaving these firms in the least favourable position once turbulence subsides. We unpack key mechanisms that explain the paradox.

Background: A farm, like any other business, needs to be resilient in order to cope with the challenges of everyday life. However, farms often face additional and distinct challenges beyond those of a typical business. As part of the farm team and often in the role of trusted adviser, veterinary surgeons may be involved in delivering bad news or handling challenging outcomes. Vets are also well placed to provide advice and to support the farm team with changes to mitigate issues recurring in future. Aim of the article: This article provides an overview of contingency planning for farms and looks at examples of how vets may assist in this area. The aim is to guide vets who find themselves in similar challenges or who need to apply their knowledge and skills to navigate unfamiliar scenarios.

In the new journey of comprehensively building a modern socialist country, high-quality development has become the primary task, and new quality productive forces are the core engine promoting industrial structure optimization and economic level upgrading. As a new growth point of the national economy and the head of the "five happiness industries," the sports industry is facing a historical transformation from traditional factor-driven to innovation-driven development. This transformation process urgently needs to break away from traditional path dependence and turn to a new quality productive force development model led by technological innovation, driven by digital transformation, and based on green development. As the blood of the modern economy and the core mechanism of resource allocation, finance plays an irreplaceable and decisive role in cultivating new quality productive forces in the sports industry. Based on the productivity theory of Marxist political economy and combining modern financial function theory, this paper constructs a three-dimensional coupling logic framework of "Technology-Capital-Industry" to deeply analyze the internal mechanism of financial support for sports industry upgrading. Selecting Guangzhou as the object of empirical investigation, and combining regional industrial planning and typical business characteristics, this paper systematically sorts out the realistic foundation of Guangzhou's sports industry. It reveals the structural mismatch, institutional obstruction, and ecological deficiency existing in the current financial supply when matching the characteristics of "high technology, light assets, long cycle, and high risk" of new quality productive forces in sports. Based on this, this paper proposes practical paths such as building a full life cycle financial support chain, deepening the "Sports + Finance + Technology" integration ecology, improving the multi-level capital market system, and strengthening policy financial guidance. The aim is to provide solid theoretical support and decision-making reference for Guangzhou to build a world-famous sports city and achieve the modernization of the sports industry.

In the fierce market competition, enterprises take improving economic benefits as their core goal. There is a close correlation between business management methods and economic benefits, and scientifically appropriate management methods are crucial to the development of enterprises at different stages. This paper aims to study the practical application of business management methods in enterprises, explore the feasibility of these methods, and analyze the gaps in daily research. By integrating literature and theories related to business management methods and conducting comparative case analysis, this paper systematically sorts out the implementation paths of typical business management methods, proposes the research theme of the correlation between business management methods and enterprise economic benefits, and empirically analyzes the specific impact of business management methods on enterprises. The experimental results show that scientifically appropriate business management methods can increase enterprise economic benefits by an average of 15% to 20%. The research conclusions reveal the positive driving mechanism of business management methods on enterprise economic benefits, providing a theoretical basis and practical reference for enterprises to enhance their core competitiveness by optimizing management models.

ABSTRACT Under the background of accelerating digital transformation, enterprises demand higher response speed and accuracy of business decisions. Based on big data analysis technology, this paper constructs a comprehensive research framework covering data collection, model construction, system deployment and scenario application, and realises decision optimisation of core business links such as procurement, sales and inventory. On the data level, heterogeneous data resources within the enterprise are integrated to complete data cleaning and feature construction. In the modelling stage, the prediction effects of decision tree, random forest, XGBoost and neural network are compared, and those with excellent performance are selected to be embedded in the actual business process. The optimisation objective function is constructed to realise the linkage decision of forecasting and scheduling. The system deployment adopts containerised architecture to meet the requirements of real-time and scalability. The empirical part of the model is applied to the typical business scenarios of enterprises, and the procurement cost is reduced, the inventory efficiency is improved, and the customer response cycle is shortened, which shows that the big data-driven mechanism has practical value for improving the resource allocation capacity of enterprises.

The article discusses the procedure for identifying, documenting, and accounting for the re-sorting of stocks. The conditions for mutual offsetting of surpluses and shortages, established by FSBI 28/2023 «Inventory», are analyzed in detail. Special attention is paid to the methodology of accounting for the cost difference arising during the recalculation, with the implementation of typical business situations and related accounting transactions. The material is supported by practical examples for a clear understanding of the procedure.

U.S. higher education faces mounting existential pressures—enrollment declines, cost escalation, political skepticism, and administrative managerialism that prioritizes short-term institutional survival over long-term scholarly mission. Despite widespread critique, business management faculty have largely failed to mount effective resistance to managerialist interventions, even as these practices erode academic autonomy and institutional purpose. This paradox deepens when considering that many senior administrators implementing managerial reforms lack formal training in management and strategy, sometimes producing poorly conceived interventions that damage institutions while expanding administrative ranks. This essay examines why business faculty—who possess expertise to recognize problematic management practices—often remain complicit in or complacent toward managerialism. Drawing on identity theory and organizational scholarship, we argue that typical business faculty identities neither frame managerialism as a personal threat nor create obligation to apply professional expertise to institutional challenges. Before mounting effective response, business management faculty may need to cultivate alternative identities as stewards of organizational practice, not merely teachers of management abstracted from institutional context.

The 2020 pandemic has impacted businesses more than in the past. Businesses need to look beyond short-term performance and fundamental organizational health to the future in a world where the future is unclear and changing quickly. Organizations need to grow stronger in addition to having the capacity to resist unforeseen challenges or changes. Put simply, they need to develop resilience. Organizations that possess resilience are able to endure unforeseen changes or dangers and grow stronger as a result. This article studies the resilience of a typical business from each of the eight sectors by analyzing its share price and financial data, as well as how it behaved during an outbreak. Firms that possess resilience are able to perceive and adjust to the swiftly shifting market dynamics caused by the pandemic while maintaining a focused business plan. Remarkably resilient companies typically leverage their resilience to overcome possible catastrophes and emerge stronger than before. Businesses that possess this quality frequently have an easier time achieving goals for sustainable growth, which has a big impact on investment choices. Thus, learning about this subject can aid investors in making decisions.

This study focuses on the core proposition of "financial technology empowering the financing of micro and small enterprises," systematically exploring its business model innovation and risk governance framework construction. The paper first analyzes the theoretical logic and practical motivations for financial technology to solve the financing difficulties of micro and small enterprises, pointing out that it effectively alleviates the two core obstacles of information asymmetry and excessively high transaction costs by reconstructing risk pricing models and service processes. The study further deconstructs the value creation mechanisms and operational characteristics of typical business models such as digital lending, supply chain finance, and big data risk control, finding that while these models improve the accessibility and efficiency of financial services, they also generate complex challenges such as technological risks, new business risks, compliance risks, and systemic risks. Based on an in-depth analysis of risk characteristics, this paper innovatively proposes a multi-layered, dynamic risk governance framework. This framework emphasizes the organic unity of internal governance, external supervision, and ecosystem collaboration: at the micro level, it requires fintech companies to establish a full-process risk control system and compliant technology applications; at the meso level, it advocates adaptive regulatory models such as regulatory sandboxes and penetrating supervision; and at the macro level, it requires improving infrastructure such as credit information sharing and multi-party co-governance mechanisms. The case study of MYbank validated the practical value of this governance framework. The study ultimately concluded that the sustainable development of fintech must be built upon the simultaneous improvement of business model innovation and risk governance capabilities, requiring the construction of a dynamic governance ecosystem that balances innovation incentives and risk control.

Artificial intelligence (AI) has taken a leading position in various fields, especially in the development of information solutions. This article presents a case study of mobile application user interface redesign to highlight the benefits and improvements of integrating artificial intelligence. The study analyzes a typical mobile application, including technical and business details. The integration of artificial intelligence tools such as open source SolidGPT helps improve the development process in every aspect compared to the original version. The results show a lot of time saved and a lot of time reduced for similar activities. Additionally, the quality of the final product has improved, as evidenced by the reduction in crashes and issues found in similar time frames. The improvements achieved are very promising. The case study can be useful for technicians implementing AI tools and for decision-makers justifying investments in such integration.

Introduction. In the current geopolitical situation caused by martial law in Ukraine, domestic small businesses operate under pervasive risks, limited financial resources and increasing tax burdens, which challenge their security, resilience and survival. The choice of an optimal legal form of business and tax regime directly affects the profitability of entrepreneurial activity. Sole proprietors under Group 2 of the simplified taxation system are approaching the upper income thresholds, which raises the question of choosing between transitioning to Group 3 of the single tax or registering a limited liability company (LLC). Tax planning becomes increasingly complex due to the lack of comprehensive studies that account for the specifics of different types of activities, cost structures and administrative burdens. Purpose. The aim of the study is to conduct a comparative analysis of the efficiency of operating as a Group 2 sole proprietor, Group 3 sole proprietor and an LLC, taking into account the full scope of tax liabilities, mandatory payments and administrative costs; to identify critical transition points between legal forms for two typical business models – service provision and retail trade; and to develop practical recommendations for optimising tax burdens under the legislation effective in 2025. Methodology. The research is based on comparative analysis of tax regimes using financial modelling under various activity-level scenarios. A calculation and analytical method is applied to determine income thresholds at which a change in legal form becomes economically justified. A structural cost analysis is used to define the total tax burden, including the single tax, military levy, unified social contribution, value-added tax and administrative expenses. Results. A detailed assessment of tax liabilities for a Group 2 sole proprietor, Group 3 sole proprietor (with and without VAT) and an LLC under the general taxation system was performed for two business models. For service activities with a low share of material costs, it was established that a Group 3 sole proprietor without VAT remains the optimal option up to an annual income of UAH 6.5 million, providing savings of up to UAH 150,000 compared to an LLC. For retail trade with a high share of goods procurement, a critical transition point to a Group 3 sole proprietor with VAT occurs at an annual turnover starting from UAH 5 million, where VAT credit recovery reduces the effective tax burden to 8.2–9.1%. A decision matrix was developed to support the selection of an optimal business form depending on income volume, cost structure and the need to work with VAT payers. A methodology for calculating the economic feasibility of transitions between business forms, considering transitional costs and tax audit risks, is proposed.

We analyze a monetary quasi–experiment in Sweden from 2010–2011, when the Riksbank raised the interest rate substantially. We argue that this increase was beyond what labor market conditions warranted, driven instead by new concerns about financial stability. Using a battery of specifications that rule out domestic or international confounders, we show that this monetary tightening led to a substantial economic contraction, raising unemployment by 1–2 percentage points. Using administrative microdata, we find that sectors with nominal wage rigidity drove much of the response and that the monetary contraction was more regressive than the typical business cycle. (JEL E24, E32, E43, E52, E58)

In today's competitive company climate, understanding how personnel variables influence organizational income creation is crucial for long-term success. The aim of the research is to use machine learning (ML) to create reliable models for analyzing employee characteristics like engagement and happiness and how they affect the organization's ability to generate income. Businesses can have a deeper understanding of workforce dynamics and implement data-driven talent management strategies by utilizing advanced predictive analytics. This strategy promotes long-term financial development and stability by optimizing organizational performance in addition to increasing staff productivity. A novel model, the Scalable Snow Ablation-Optimized Adaptive Random Forest Tree (SSA-ARFT) algorithm, is introduced to predict organizational outcomes with high precision. The data used is derived to examine various factors influencing employee performance and happiness in a typical business setting. Z-score normalization is used as a preprocessing step to standardize variables and mitigate the impact of outliers, ensuring uniformity across the dataset. Principal Component Analysis (PCA) is used to extract features to reduce dimensionality while maintaining important information for accurate predictions. This method improves computational efficiency and guarantees that the model focuses on the most important factors affecting employee performance and organizational success. The experimental findings show that SSA-ARFT performs noticeably better than conventional forecasting techniques. The performance of the model has been assessed by accuracy (94.66%), precision (90%), recall (78.2%), F1-score (88.1%), RMSE (3.031), MAPE (4.5610) and MAE (3.032). Compared to traditional models, the hybrid approach predicts the influence of employee factors on organizational revenue with greater accuracy and durability. The SSA-ARFT method helps analysts and investors improve the forecast accuracy of employee revenue by removing the drawbacks of conventional methods.

Jason Julier’s piece is on Glen Mhor distillery and his website www.glenmhorwhisky.com where he has worked to collect and collate materials relating to the distillery into an online repository. Jason started this archive as a passion project in 2021 relying on being able to source materials from a variety of different places, meaning it is not a typical business archive created by professional archivists. Nevertheless, Jason’s piece provides us with another aspect on the relationship between businesses and archives which resides in the informal space where collectors and amateur archivists come together (facilitated in no small part by modern technology such as blogging platforms) to create something accessible which would otherwise be lost to time. Collecting and collating materials from disparate sources, Jason has worked for several years to develop the website into a repository of digitised archival materials including photographs, records, letters, and short biographies relating to the inverness-based distillery that operated from 1892 until it closed in 1983. In his article he provides a reflection on how the archive came into being, the processes by which he was able to develop it, and some of his reasoning for undertaking the work. What is interesting about Jason’s story and approach is his refusal to turn the work into a book, but instead to have it as a living and evolving archive which can be added to, repositioned, and reconfigured in different ways as and when new materials become available. The whisky industry has numerous different projects and books written by amateur archivists and historians, driven by their interest in the industry and particular distilleries and brands. Their invaluable work in creating archives through cataloguing materials that are otherwise often either lost or locked away allows for wider and deeper interrogation of one of Scotland’s most iconic and important industries which has been historically difficult to access. Technology plays a critical role in this with the internet offering both a place for hosting and accessing materials through formal and informal networks. Jason Julier’s article details how his work on Glen Mhor has benefitted both technology and the goodwill of people in supporting the creation of this fascinating and easily accessed archive.

This study aims to analyze the implementation of spiritual leadership in an effort to improve employee performance in RM. Pangestu Special Lalapan mention of the Jember. The background of this research is based on the increasingly fierce competitin in the culinary business in Jember Regency, especially in the typical food business sector. RM. Pangestu Special Lalapan, which has been established since 2001, applies spiritual values as part of its human resource management strategy to create a harmonious and productive work environment. This study uses a qualitative approach with a case study method. Data was collected through in-depth interviews, observations, documentation of owners, HR managers, employees, and costumers. The main theory used is Spiritual Leadership Theory by Fry et al. which includes three main dimensions, namely: vision, altruistic love, and faith/hope.

Investment in innovation significantly diverges from typical business expenditures due to the inherent characteristics of Research and Development (R&amp;D), which include high upfront costs, specialized human resources, and considerable uncertainty about the economic returns. Unlike physical assets, the intangible outcomes of R&amp;D have limited collateral value, restricting their suitability for conventional debt financing. This complexity is further exacerbated by informational asymmetry and the risks associated with moral hazard, which inflate external funding costs relative to internal funding options.