Business Requirements Research Articles

The Impact of Corporate Sustainability Reporting Regulation on Business and Financial Performances of Companies in Bosnia and Herzegovina

Given the global trends and initiatives for environmental preservation and transition to sustainable development, the corporate sector has been facing a turning point in corporate reporting. The sustainable business requirements also initiate a series of new challenges in the financial and accounting sector related to the development of accounting solutions for integrating sustainability issues into financial statements. In addressing the green transition problems, the EU has adopted the Corporate Sustainability Reporting Directive (CSRD), which modernizes and strengthens the rules concerning the social and environmental information companies must report in their financial statements. The research was carried out by conducting a survey among the population interested in corporate finances, especially accountants. The main goal of the research is to analyse the impact of sustainable reporting regulation on the corporate sector’s financial performance and companies’ operations in Bosnia and Herzegovina. The results show that EU CSRD will significantly impact doing business and performances of companies and that the companies that adapt to new sustainability reporting regulations will have higher chances of obtaining positive financial performances and adequately addressing the increasing demand of stakeholders for more comprehensive business reporting.

Popularity Bias in Correlation Graph-based API Recommendation for Mashup Creation

The explosive growth of the Application Programming Interfaces (APIs) economy in recent years has led to a dramatic increase in available APIs. Mashup development, a dominant approach for creating data-centric applications based on APIs, has experienced a surge in popularity. However, the vast array of choices poses a challenge for mashup developers when selecting appropriate API compositions to meet specific business requirements. Correlation graph-based recommendation approaches have been designed to assist developers in discovering related and compatible API compositions for mashup creation. Unfortunately, these approaches often suffer from popularity bias issues, leading to an inequality in API usage and potential disruptions to the entire API ecosystem. To address these challenges, our research begins with a theoretical analysis of the popularity bias introduced by correlation graph-based API recommendation approaches. Subsequently, we empirically validate the presence of popularity bias in API recommendations through a data-driven study. Finally, we introduce the p opularity b ias aware w eb A PI r ecommendation ( PB-WAR ) approach to mitigate popularity bias in correlation graph-based API recommendations. Experimental results over a real-world dataset demonstrate that PB-WAR offers the optimal tradeoff between accuracy and debiasing performance compared to other competitive methods.

Emerging Dilemmas in the Age of Resistance: The Case of Sexually Transmitted Infections.

The stage is set for a new era of precariousness in modern medicine, driven by the increasing failure of a key pharmaceutical pillar-antimicrobials. In the context of sexually transmitted infections (STIs), the rise of antimicrobial resistance is introducing urgent questions around what might constitute "best practice" in a rapidly evolving scene, including the value of asymptomatic screening (test and treat), and the consequent downstream collateral damage emerging from over-use of our diminishingly effective antimicrobial resources. Drawing on interviews with clinicians, experts, and industry representatives, we examine resistance as a site of emerging and co-constitutive moral, temporal, and economic dilemmas. Such dilemmas, as illustrated in participants' accounts, involve complexities regarding prioritization between competing health demands; doing good work while meeting business requirements; considering trade-offs between visibility and amplifying the problem; difficulties balancing presents and futures; reconciling divergent clinical opinions and expertise; and managing patient subjectivities, while considering the implications of clinical practices for resistance. Importantly, centering dilemmas in context of antibiotic-resistant STIs open greater theoretical scope to consider the challenging spaces that key actors such as clinicians and decision-makers occupy, as they attempt to curb resistance while caring for individuals and the community.

Socio-Economic Characteristics of Women Entrepreneurs in Botswana

The present study offers a comprehensive examination of the socio-economic attributes of female entrepreneurs in Botswana, specifically emphasizing the convergence of demographic profiles, educational backgrounds, and entrepreneurial performance. Employing a mixed-methods approach that combines quantitative and qualitative research, the study rigorously analyses the elements influencing entrepreneurial outcomes for women in the region. The findings emphasize a robust positive association between increased levels of education and the achievement of business success. Specifically, women with higher education qualifications exhibit better business results in revenue growth, market expansion, and operational profitability. Nevertheless, the research also reveals enduring obstacles female entrepreneurs encounter, namely in obtaining financial access, managing socio-cultural limitations, and harmonizing family responsibilities with business requirements. The results emphasize the necessity of implementing focused policy measures, educational changes, and support structures that specifically tackle the distinct obstacles that women encounter in entrepreneurship.

The Influence Of Career Development, Work Environment And Workload On Job Satisfaction And Its Impact On Employee Performance

Objectives – Company performance is highly dependent on public administration personnel, including individual resources to work in all organizations. Management performance can be improved by ensuring that each level of the organization has adequate business requirements and clear plans to support management objectives. This research uses a quantitative approach with a type of causal research. This research focuses on PT. SSP contact center employees. as a population of 100 individuals. The saturated sampling method was used to select the research sample, which means the entire population was included. The questionnaire uses a Likert scale which is one of the questionnaire measuring tools. SmartPLS version 3. is software used to analyze data related to various variables. Innovation/Value - Learning organizations and employee empowerment drive continuous improvement, innovation and adaptability, enabling employees to make informed decisions and contribute to organizational goals. This helps organizations align and maintain competitive advantage by improving careers, environments and jobs.

A Methodological Approach to Prioritize Digital Twin Development in Manufacturing

ABSTRACTThe digital age has brought about a need for organizations to utilize Digital Twins to improve operational efficiency and decision‐making. However, it is difficult for companies to identify and prioritize Digital Twin initiatives that meet the needs of their stakeholders and align with the capabilities of the company and its strategic plans. This paper proposes a methodology for the systematic identification and prioritization of Digital Twin applications in complex industrial settings. The methodology begins by documenting business requirements, current processes, and challenges, and subsequently identifying areas with potential benefits from Digital Twins through the use of an opportunity scoring system. To refine the portfolio of Digital Twin applications to include only those that are impactful and viable, the feasibility of Digital Twin is quantified by evaluating technological (technical capacity and digital skills), organizational, and project risk factors. To validate the proposed methodology, a case study was conducted in collaboration with an industrial partner specializing in injection molding. This real‐world application demonstrates the effectiveness of our approach in identifying and prioritizing Digital Twin applications in a complex industrial context. This research contributes to the growing body of knowledge surrounding Digital Twins, providing organizations with a structured approach to leverage the potential of this transformative technology.

Characteristics and Analysis of Factors Affecting the Performance of Service Providers (Contractors) in Denpasar City in 2023

Contractors are individuals or business entities that have expertise in carrying out construction work in accordance with planning, where the appointment of contractors is mostly carried out through a tender/auction system (Sholeh, 2020). Nowadays, contractors are a business that is in great demand by the public, but the development of the quantity of construction service companies has not been followed by an increase in qualifications and performance. One of the reasons is that the business and expertise requirements (SKK) are still not met, which will later affect business reliability and competitiveness. (Priana, 2018). Seeing this situation, it is very important to research the characteristics and factors that affect the performance of service providers (contractors) in the city of Denpasar in 2023. The method used in this study is descriptive statistics as well as factor analysis is used to explain the factors that affect contractor performance. From the research that has been carried out, 1). Contractors in the city of Denpasar have good human resources, experience, finance, and equipment and are in accordance with Law No. 11 of 2020 concerning Job Creation and LPJK No. 3 of 2017 concerning Certification and Registration of Construction Implementation Services Business. 2). The most influential factor on contractor performance is in group I with a total diversity value of 32.756%.

Performance Analysis and Prediction of 5G Round-Trip Time Based on the VMD-LSTM Method

With the increasing level of industrial informatization, massive industrial data require real-time and high-fidelity wireless transmission. Although some industrial wireless network protocols have been designed over the last few decades, most of them have limited coverage and narrow bandwidth. They cannot always ensure the certainty of information transmission, making it especially difficult to meet the requirements of low latency in industrial manufacturing fields. The 5G technology is characterized by a high transmission rate and low latency; therefore, it has good prospects in industrial applications. To apply 5G technology to factory environments with low latency requirements for data transmission, in this study, we analyze the statistical performance of the round-trip time (RTT) in a 5G-R15 communication system. The results indicate that the average value of 5G RTT is about 11 ms, which is less than the 25 ms of WIA-FA. We then consider 5G RTT data as a group of time series, utilizing the augmented Dickey–Fuller (ADF) test method to analyze the stability of the RTT data. We conclude that the RTT data are non-stationary. Therefore, firstly, the original 5G RTT series are subjected to first-order differencing to obtain differential sequences with stronger stationarity. Then, a time series analysis-based variational mode decomposition–long short-term memory (VMD-LSTM) method is proposed to separately predict each differential sequence. Finally, the predicted results are subjected to inverse difference to obtain the predicted value of 5G RTT, and a predictive error of 4.481% indicates that the method performs better than LSTM and other methods. The prediction results could be used to evaluate network performance based on business requirements, reduce the impact of instruction packet loss, and improve the robustness of control algorithms. The proposed early warning accuracy metrics for control issues can also be used to indicate when to retrain the model and to indicate the setting of the control cycle. The field of industrial control, especially in the manufacturing industry, which requires low latency, will benefit from this analysis. It should be noted that the above analysis and prediction methods are also applicable to the R16 and R17 versions.

Reform of control (supervisory) activities: orientation towards a balance of interests of the parties

This article analyzes the key legislative acts adopted following the completion of the next large-scale stage of reform of control (supervisory) activities, from the perspective of considering in them the problem of the relationship between private and public interests, as well as finding a balance in their provision during the socio-economic crisis. The author focuses on issues related to updating the system of mandatory requirements for business as part of the implementation of the “regulatory guillotine” mechanism, taking into account the introduction of digital technologies into the established sphere. The result of the work is the conclusion that, taking into account the complex nature of business legislation and the need to maintain economic growth rates in conditions of a socio-economic crisis, the main task of the state is to create a favorable business, investment and entrepreneurial climate, including through compliance with reasonable legislation balance of public and private interests.

Mapping the Embarkation Haji dormitory model equivalent to a star rating hotel to empower local communities and improve the national economy

The aim of this research is to map a model for utilizing Hajj dormitories in terms of products, services, management and relevant policies, towards utilizing Hajj dormitories equivalent to star hotels through Hajj dormitory accommodation services to empower local communities and improve the national economy. Specific objective: To realize the management of Hajj dormitories equivalent to star hotels in Indonesia. Research stages: in 2024 research will be carried out on the Medan Hajj embarkation dormitory. Method: This research was carried out descriptively, qualitatively, quantitatively, with a star hotel study approach, as well as community base tourism, as a model for using Hajj dormitories on a par with star hotels. The data was analyzed using the theory of hotel and tourism quality standards, and relevant theories according to the data found at the research site. The research results show a significant value, and equivalently the star hotel rating according to the Ministry of Tourism and Creative Economy no. 53/2013 shows the results, namely: 1). Product with a score of 429, out of 118 elements assessed, 2). Service with a score of 83 out of 31 elements assessed. , 3). Management with a score of 79 out of 20 elements assessed. Fulfillment just needs to improve 9 elements of the standard target score of 600 according to the business requirements for star hotel ratings. The suggestions are: fulfillment of the annual budget needs to be increased to improve product standards, services, training, competency tests, and direct employee involvement, as well as local community empowerment needs to be maximized.

Supply chain risk identification: Signaling companies’ social sustainability reputation

Over the past decades, supply chains have become global, longer, and consequently more complex to manage and control. This evolving context has shaped the current business landscape, which increasingly demands socio-environmental accountability from firms. This paper addresses these emerging business requirements, making an original contribution to its field by drawing on stakeholder and signaling theories to identify whether the adoption of supply chain risk identification practices exerts a positive effect upon firms’ social performance. Additionally, it assesses the role of digital technology in strengthening this relationship. A survey of manufacturing firms was conducted to gather data, which was analyzed via covariance-based structural equation modeling and AMOS 28.0 software. The research found that practices intended to identify supply chain risks make a considerable contribution towards signaling a positive social sustainability reputation and highlighting the application of digital technology to help attain better social performance. Stakeholder saliency is an aspect that still requires further research.

An Ensemble Method for the Fraud Detection in Transactions

In today's world, bank fraud has become one of the significant threats to the financial stability and security of clients of financial institutions. The development of technologies, in particular in the field of machine learning, opens up wide opportunities for building effective systems for detecting and preventing fraud in the banking sector [1, 2]. Detecting fraudulent transactions is an important task that requires thoughtful and technological solutions. One of these methods is the use of machine learning approaches and methods. This paper proposes the use of an ensemble method that combines several machine learning models at once. This approach will reduce the probability of false positives and increase classification accuracy. In addition, for the optimal operation of the model, preprocessing of the data will be carried out, in particular, their normalization, balancing of classes, as well as the selection of features. During the research, it is important not only to achieve high accuracy, but also to reduce as much as possible the number of fraudulent transactions that will be mistakenly classified as normal [3]. This is related to the business requirements of the banking sector, as each such transaction causes losses to the system's reputation, as well as direct financial losses. Within the framework of the study, it is substantiated that the use of this approach gives better classification results than single models due to the compensation of the shortcomings of each of them. The choice of this approach is also due to high practicality, compatibility with financial systems, as well as ease of integration. This paper analyzes the proposed model, its advantages and disadvantages in comparison with analogues. The ensemble method helps to combine the advantages of simple models and reduce the impact of their shortcomings on the final result. In general, the choice of software should depend on the technical requirements of the project and to obtain better results, different models and approaches should be analyzed.

Navigating the Digital Marketplace: Legal Requirements for Online Contracts with Consumers in the European Union

The internet has revolutionized shopping, offering unparalleled convenience for consumers in the EU and worldwide. However, this digital ease is underpinned by a robust legal framework that ensures fair play for businesses and consumers. Understanding the key legal requirements for online contracts in the EU is crucial for businesses to operate smoothly and ethically within this dynamic market. This article delves into these requirements, equipping businesses with the knowledge to navigate the online contracting landscape confidently. This article explores the key legal requirements for businesses operating in the EU when forming online contracts with consumers. This article further discusses the challenges in the present legal framework and suggests potential solutions. Furthermore, the author has attempted to present a comparative framework with legal requirements of online contracts with consumers in the United States (US) and the United Kingdom (UK). Thus, this article will provide insight to businesses and consumers and aid in navigating the e-commerce and digital marketplace by ensuring the rights of the consumers in the EU are protected.

API integration in FinTech: Challenges and best practices

API integration is a cornerstone of innovation in the FinTech sector, enabling seamless connectivity between disparate financial systems, enhancing service delivery, and fostering the development of new financial products. This review explores the challenges and best practices associated with API integration in FinTech, emphasizing the importance of effective strategies for overcoming integration obstacles and achieving successful outcomes. APIs (Application Programming Interfaces) facilitate the exchange of data and functionality between financial applications, such as payment systems, banking platforms, and financial data aggregators. However, integrating these APIs presents several challenges, including compatibility issues, security concerns, and regulatory compliance. Ensuring that APIs are compatible with various systems and standards is essential for smooth integration. Security is another critical concern, as financial data is highly sensitive and requires robust protection against breaches and unauthorized access. Compliance with financial regulations, such as GDPR and PSD2, adds an additional layer of complexity to API integration. To address these challenges, best practices in API integration include adopting standardized protocols and frameworks to enhance compatibility and interoperability. Implementing comprehensive security measures, such as encryption, authentication, and authorization, is crucial to safeguarding data and maintaining trust. Additionally, establishing clear documentation and version control practices helps ensure that APIs are easy to use and integrate while accommodating future updates and changes. Effective API management also involves continuous monitoring and testing to identify and resolve issues promptly. Leveraging API management platforms can streamline the integration process by providing tools for monitoring performance, managing security, and facilitating communication between systems. Collaboration between development teams, IT departments, and business stakeholders is essential for aligning technical and business requirements and ensuring that integration goals are met. In conclusion, while API integration in FinTech presents various challenges, adhering to best practices and leveraging appropriate tools can facilitate successful integration. By addressing compatibility, security, and compliance issues, FinTech organizations can enhance their service offerings, drive innovation, and improve operational efficiency. Keywords: API Integration, Fintech, Compatibility, Security, Regulatory Compliance, Standardized Protocols, Encryption, Authentication, API Management, Performance Monitoring.

Building Scalable Data Warehouses: Best Practices and Case Studies

In today's data-driven world, the ability to manage, store, and analyze large volumes of data is crucial for business success. The demand for scalable data warehouses has risen dramatically as organizations seek to handle the explosion of data generated by modern applications and digital transactions. "Building Scalable Data Warehouses: Best Practices and Case Studies" explores the key strategies, methodologies, and technologies involved in designing and implementing scalable data warehouses that meet the demands of today and the future. The paper highlights the importance of architecture choices, data modeling techniques, and performance optimization in creating data warehouses that can grow with an organization’s needs. Additionally, it provides case studies that demonstrate the real-world application of these principles in various industries, showing how scalable data warehouses have enabled companies to maintain high performance, reduce costs, and enhance decision-making capabilities. The paper begins by defining what constitutes a scalable data warehouse, emphasizing the importance of a flexible and adaptive architecture that can accommodate growing data volumes and changing business requirements. It explores different architectural approaches, including the benefits and challenges of traditional on-premises data warehouses versus cloud-based solutions. The paper also discusses the role of data modeling, including dimensional and normalized approaches, in ensuring that the data warehouse can handle increasing complexity without compromising performance.

Perencanaan Enterprise Architecture Sistem Informasi pada Akademik: Studi Literatur

The progress of time and rapid technological advancements have driven higher education institutions and other educational organizations to adopt Enterprise Architecture (EA) as a strategic approach to planning and managing their information systems. EA planning begins with an in-depth analysis of the academic literature study environment, including a deep understanding of the needs and challenges faced. Subsequently, business requirement mapping is conducted to identify the strategic goals and objectives that the information system must achieve. Structured approaches like TOGAF (The Open Group Architecture Framework) are often used as a guide in EA planning to ensure consistency and sustainability of the information system. Additionally, it is important to note that EA planning does not solely focus on technical aspects but also involves organizational, human, and process aspects. This includes mapping roles and responsibilities in information system management, developing the skills and capabilities of human resources, and designing effective business processes. By adopting Enterprise Architecture planning for academic literature studies, educational institutions can optimize the use of information technology to enhance efficiency, productivity, and quality in the learning and research processes. EA also enables better integration between existing information systems and future systems, allowing institutions to be better prepared for future challenges.

Optimized task scheduling approach with fault tolerant load balancing using multi-objective cat swarm optimization for multi-cloud environment

Multi-cloud environment enables an organization to access services from more than one cloud service providers the use of multiple cloud computing and it can be treated as single heterogeneous environment. It enables autonomy to run the tasks on private or public cloud based on business or technical requirements. In a multi-cloud platform, load balancing is an essential task to serve the requests from multiple users with different resources effectively. It helps to improve utilization of the cloud resources, throughput, reduce makespan and avoid overload at resources. Load balancing also facilitates the redirection of traffic to resources running in another cloud when a failure occurs in a cloud. Hence, it is more vital to have optimized load balancing methods in multi-cloud infrastructure in order to improve the system performance. This paper presents an optimized fault tolerant load balancing method using multi-objective cat swarm optimization algorithm called MCSOFLB and the results are then compared against other powerful optimization algorithms. The experimental results evidently show that the proposed algorithm ranks first on the whole. The MCSOFLB method produces an average improvement of 31 % makespan, 6 % resource utilization, 12 % cost, 6 % success rate and 32 % average throughput over other benchmark algorithms.

A Dynamic Behavior Verification Method for Composite Smart Contracts Based on Model Checking

A composite smart contract can execute smart contracts that may belong to other owners or companies through external calls, bringing more security challenges to blockchain applications. Traditional static verification methods are inadequate for analyzing the dynamic execution of these contracts, resulting in misjudgment and omission issues. Therefore, this paper proposes a model checking approach based on dynamic behavior that verifies the security and business logic of composite smart contracts. Utilizing automata, the method models contracts, users, attackers, and extracts properties, focusing on six types of common security vulnerabilities. A thorough case study and experimental evaluation demonstrate the method’s efficiency in identifying vulnerabilities and ensuring alignment with business requirements. The UPPAAL tool is employed for comprehensive verification, proving its effectiveness in enhancing smart contract security.

ĐÀO TẠO NGUỒN NHÂN LỰC XANH TRONG GIÁO DỤC NGHỀ NGHIỆP

This article investigates the necessary solutions to improve the quality of vocational training associated with social needs, especially green innovation in the goal of sustainable development. Methods of collecting documents, analyzing and synthesizing are applied throughout the article to deduce and find out solutions suitable to the conditions of vocational education in Vietnam. The results show that green training of human resources contributes to raising awareness of environmental protection, improving training quality, reducing labor waste and creating jobs for young people in appropriately trained occupations with business requirements. However, the participation of experts throughout the curriculum and practical support devices in business connection is needed to find practical value for the output. Keywords: Vocational education; output quality; interactivity; green innovation; capacity development.

Information security and data protection at an industrial enterprise in modern conditions

It is impossible to imagine a modern enterprise without automation and digitalization of production processes. At the same time, new ways of doing business in the digital era are accompanied by such information threats as: data leaks, encryption viruses and attacks on critical information infrastructure. All data and assets need protection. This is not only a business requirement, but also the requirements of laws on CII and the processing of personal data. This is where information security comes to the aid of companies and enterprises.