Business Process Optimization Research Articles

Railway contactless checkout process with identification assisted by gait recognition

With business process optimization, technological advancement, equipment capability enhancement, and other means, the Railway Passenger Service Department in China is consistently working to improve the efficiency and convenience of passenger entry and exit procedures at railway stations. Concerning passengers’ checkout, not only conventional identification approaches based on manual control, identification card, and magnetic thermal paper ticket are supported, but also a recent contactless identification process based on face recognition is applied in some stations. To further improve the contactless identification ability for checkout, an advanced contactless checkout process based on gait-augmented face recognition is innovatively put forward, in which a weakly-supervised body segmentation network named Dwsegnet and an improved GaitSet model are proposed. Through comparison with various models, the effectiveness of both Dwsegnet and the improved GaitSet is validated. Specifically, the contactless identification rate of gait-augmented face recognition is improved by 2.31% when compared to single-modal face recognition, which demonstrates the superiority of the proposed process.

APPROACHES TO ANALYSIS AND OPTIMIZATION OF BUSINESS PROSSES OF AN INDUSTRIAL ENTERPRISE

The article presents an analysis of the most popular global approaches to the analysis and optimization of business processes in organizations. The article contains a description of the proposed approaches and their basic principles. The proposed approaches are Business Process Reengineering, Six Sigma method, lean Management, Business Process Management, Agile software development. The considered approaches have general principles that are advisable to apply when optimizing the business processes of an industrial organization. These include optimization of operations, standardization, automation and emerging technologies, supply chain integration, continuous improvement, employee engagement, performance measurement and analysis. Classic methods for assessing business processes can be successfully supplemented with generalized principles of modern world approaches for more effective analysis and optimization of business processes of an industrial enterprise.

CONCEPTUAL FOUNDATIONS FOR THE FORMATION OF PERSONNEL STRATEGY AT INDUSTRIAL ENTERPRISES IN THE CONTEXT OF DIGITALISATION

The relevance of research on the conceptual foundations of personnel strategy formation in industrial enterprises under the conditions of digitalisation appears to be very relevant, which is due to the following factors. The digital transformation of industrial enterprises leads to the emergence of new technologies, processes and personnel requirements. The HR strategy must adapt to these changes in order to ensure that the company has the necessary qualifications and skills. Under the conditions of digitalisation, the demand for specialists in the field of information technologies and digital data processing is increasing. Companies need to develop strategies to attract, retain and develop such personnel in order to remain competitive. Digital technologies make it possible to automate and optimise business processes, so the HR strategy must reflect these changes and take into account the new roles and requirements for personnel. As technologies and processes change, there is a need for continuous training and development of personnel. The HR strategy should include training and development programmes aimed at increasing digital skills. Studying the conceptual foundations of personnel strategy development in the conditions of digitalisation will help companies to effectively adapt to contemporary challenges and ensure their competitiveness. The purpose of the article is to disclose the conceptual foundations of forming a personnel strategy at industrial enterprises in the context of digitalisation. The methodology of the study is an interdisciplinary approach based on the idea of effective development of an industrial enterprise as a sociotechnological system, which allowed to combine systemic knowledge that will help to understand how social factors affect the implementation of technologies and the development of the enterprise as a whole. The enterprise as a complex social and technological system should be analysed within the framework of the socio-humanistic approach, which is based on the recognition of the human being as the subject and object of all processes. In the context of a socio-humanistic approach to business analysis, it is important to address aspects related to social relations, human needs and values, and the interaction between employees and management. The fundamental principles of the socio-humanistic approach, such as taking into account the individual needs of employees, supporting their development and satisfaction from professional activities, can be applied to the analysis of an enterprise's performance. This means that the efficiency and success of an organisation is assessed not only by financial indicators, but also by the level of satisfaction and development of its employees. Studying the social interactions, communication and psychological climate of the team can help to understand what factors contribute to or hinder the effective functioning of the organisation. This approach allows to see the company as a living, organic system in which human relationships and values play an essential role. The study opens up the possibility of integrating different scientific disciplines, such as sociology, technology, economics, psychology and management, in order to understand the complex relationships in today's industrial companies. The implementation of the recommendations will help companies improve the efficiency of personnel management, provide the necessary human resources and meet the requirements of the modern market. The research generates new knowledge in the field of personnel management and digitalisation, has direct practical application for companies in increasing their competitiveness and stability in the market.

Research on the Evaluation System of Digital Management Process Improvement of Automobile Transaction Business Based on CMMI

With the rapid development of information technology, enterprise digitalization, and Internet + application, the digitalization and improvement of the used car trading business and its management process improvement are facing many challenges. This paper attempts to use the CMMI process improvement model to analyze the factors affecting the digital construction, business process optimization, and digital management process improvement of the used car market through research on the digital management process and the related theories of CMMI, such as talent training, application of information technology, immature business development, irregular business process, and industry policy restriction. The FAHP analysis method is used to establish a comparison matrix to explore the construction of an evaluation system model for the improvement of the digital management process of the used car trading market based on the CMMI model.

Developing industry clusters based on 4As to support agritourism competitiveness

Abstract Competitive agritourism thrives on the pillars of the Attraction, Accessibility, Ancillary, and Amenity (4As), serving as fundamental cornerstones in tourism industry. Nonetheless, most agritourism continue to be entrenched in conventional management practices, exposing them to prevalent agricultural risks. Elevating this landscape necessitates a transformative approach. This article aims to analyze the linkages between the 4As and industry clusters in driving sustainable agritourism. The methodology used in this study is a literature review. Industry clusters in agritourism are important due to their ability to utilize shared inputs, optimize business processes through integration and collaboration, and develop outputs through network expansion. Cooperation, coordination, collaboration, and communication are essential for the successful development and competitiveness of agritourism. The arrangement of accommodation in a particular location encourages collaboration, resource sharing, and economies of scale. Increased accessibility improves supply chain management efficiency and reduces costs through collaboration. The availability of well-designed amenities further enhances the attractiveness and competitiveness of agritourism destinations. From the perspective of attractions, collaboration among agritourism contributes to innovation, product development, and sustainable practices. Understanding these linkages can inform strategic decision-making processes and guide the development of policies that leverage the strengths of the 4As to promote sustainable agritourism development.

ВИКОРИСТАННЯ МАШИННОГО НАВЧАННЯ ДЛЯ ОБРОБКИ ДАНИХ НА МІКРОКОМП’ЮТЕРАХ

Machine learning is a data analysis method that automates the construction of an analytical model. It is a branch of artificial intelligence based on the idea that machines should be able to learn and adapt through experience. It is closely related to computational statistics, which makes predictions based on statistical data collected by a computer. It is sometimes confused with data mining, but that is more focused on analyzing intelligence data, while machine learning contains complex algorithms that are used mainly for prediction, where machine learning concentrates on predicting based on already known attributes obtained through training data, then data mining focuses more on finding unknown attributes in any data. attributes in any data. Machine learning applications may be associated with spam filtering, optical character recognition, and search engines. Machine learning uses data to determine which algorithm is best for generating results based on the quantity, quality, and nature of the data. This data is then used for intelligent analysis in various ways, such as recommendation systems such as similar products on eBay, personalized content on google plus pages, video ads on sites such as YouTube, and last but not least, suggestions from friends on Facebook. Machine learning and artificial intelligence can be used to solve business problems, namely: Automating repetitive tasks such as data entry, document processing and customer service. This frees up employees' time for more complex work. Optimization of business processes. ML/AI can analyze data to identify inefficiencies and optimize business processes, increasing company productivity. Service personalization. ML/AI helps analyze customer data to provide them with personalized offers, recommendations and support. Automation of answers to questions and anticipation of customer needs. Detection of fraudulent transactions and cyber security. Risk management.

Integration of Erp in Optimizing Business Process

Integration of Erp in Optimizing Business Process

ЕКОНОМІЧНА ЕФЕКТИВНІСТЬ ІНФОРМАЦІЙНИХ СИСТЕМ УПРАВЛІННЯ НА ПІДПРИЄМСТВАХ

The scientific article analyzes the economic efficiency of information management systems at enterprises, which is a topical topic in the conditions of a dynamic market environment. The purpose of the study is to assess the impact of management information systems on key performance indicators of enterprises, such as productivity, costs and quality of customer service. It is important to note that management information systems are designed to solve the tasks of strategic and tactical planning, operational management, as well as control and accounting. With their help, you can optimize management processes and reduce the costs of secondary data processing, which is an important aspect for improving the overall efficiency of the enterprise. The use of management information systems allows not only to increase the competitiveness of enterprises, but also to reduce the complexity of management decision-making, to improve the reliability of information, which, in turn, contributes to objective financial decision-making. The active use of information technologies in business management has a positive effect on operational efficiency, providing flexibility in response to changes in the market environment. The study shows that the economic efficiency of management information systems is directly related to their ability to optimize business processes, reduce costs and increase productivity. The implementation of information management systems facilitates the automation of routine tasks, which allows employees to focus on more important aspects of the activity, improving overall performance. Thanks to this, enterprises are able to adapt faster to new economic challenges and better predict market needs. Particular attention should be paid to the influence of management information systems on the quality of customer service. Management systems allow faster processing of requests, which positively affects customer satisfaction and their loyalty. For a comprehensive analysis of the economic efficiency of information management systems, it is important to determine key indicators, such as return on investment, payback time of implementation, and labor productivity. The analysis of these indicators helps to identify optimal directions for investments and improvement of systems. The conclusions of the article confirm that management information systems are important tools for increasing efficiency, competitiveness and long-term development of enterprises in modern conditions.

Financial Stability and Innovation: Interconnection and Development Prospects

The development of the modern sphere of technologies ensures active implementation of various types of innovations in the activities of modern companies. If innovations are rationally planned, they can have a positive impact on the financial stability of business and the economy as a whole. At the same time, Ukrainian innovation activity has a huge unrealised potential, which can be realised under more favourable external conditions and high-quality planning of the specifics of innovation implementation. The purpose of the study is to summarise approaches to determining the relationship between innovation and financial stability of modern business. In order to achieve this goal, it is necessary to solve a number of urgent tasks, in particular: to determine the scale of innovation activity of modern business in the world and in Ukraine; to outline the key tasks that can be solved by innovative tools if they are implemented in business activities; to specify the directions of ensuring financial stability through the introduction of innovations. The research was based on an in-depth review of more than 50 scientific sources, including articles indexed in leading scientometric databases. The study found that the global innovation market is at the stage of active development, while Ukrainian enterprises are not currently realising their full innovation potential due to unfavourable environmental conditions. The study also identifies the tasks that can be solved by innovative tools, provided they are implemented in business activities. It is determined that the application of digital marketing tools and the use of social networks to promote products allow expanding the audience, which can have a positive impact on the development of the financial stability system. Working with data, planning, and processing data using the latest technologies can also have a positive impact on financial stability. A separate link is the optimisation of business processes (financial, production, procurement, etc.) using the latest information management tools (artificial intelligence, big data, cloud technologies), which can improve the information component of financial stability.

GAMA: A multi-graph-based anomaly detection framework for business processes via graph neural networks

Anomalies in business processes are inevitable for various reasons such as system failures and operator errors. Detecting anomalies is important for the management and optimization of business processes. However, prevailing anomaly detection approaches often fail to capture crucial structural information about the underlying process. To address this, we propose a multi-Graph based Anomaly detection fraMework for business processes via grAph neural networks, named GAMA. GAMA makes use of structural process information and attribute information in a more integrated way. In GAMA, multiple graphs are applied to model a trace in which each attribute is modeled as a separate graph. In particular, the graph constructed for the special attribute activity reflects the control flow. Then GAMA employs a multi-graph encoder and a multi-sequence decoder on multiple graphs to detect anomalies in terms of the reconstruction errors. Moreover, three teacher forcing styles are designed to enhance GAMA’s ability to reconstruct normal behaviors and thus improve detection performance. We conduct extensive experiments on both synthetic logs and real-life logs. The experiment results demonstrate that GAMA outperforms state-of-the-art methods for both trace-level and attribute-level anomaly detection.

Implementation of a Customer Relationship Management Information System in the Activities of an IT Company Using the Example of Trust LLC

The main topic of the work is the implementation of a customer relationship management information system in the activities of an IT company. The object of the study is TRUST LLC. The problem that the work solves is the need to optimize the customer relationship management process to increase the competitiveness and efficiency of the company in the IT field. The purpose of the work is to analyze the possibilities and effectiveness of implementing a customer relationship management information system using the example of the activities of TRUST LLC and offer recommendations for its use. The results of the work include an analysis of the current situation in the company, an assessment of the capabilities and advantages of using the information system, as well as the development of recommendations for using this system to optimize the customer relationship management process. As a result of the implementation of the information system, it is expected to improve the quality of customer service, improve the analysis and forecasting of their needs, as well as optimize business processes within the company.

Comparative analysis of approaches to assessing the market cost of business in domestic and foreign practice

The greatest demand in the modern world is for business valuation service. Valuation activity makes it possible to identify the important characteristics of a particular business which is necessary for making management decisions by company owners. The results of business valuation are used to determine existing perspectives: the presence of investment opportunities, ways to optimise business processes, need to expand business activities, etc. According to statistics, several decades ago, business valuation was conducted in no more than 10 % of cases. Currently, on the contrary, more than 90 % of companies are interested in regular valuation. However, the widespread demand for business valuation has made it possible to find a number of pressing problems that need to be solved in the future. One of the most serious сhallenges is the existence of problem areas in the national legal framework. The work examines the process of business valuation using basic methods and approaches, analyses the foreign experience on the research topic and also valuates a domestic enterprise in different ways. The authors concluded that it is necessary to choose the method that can be most effective in valuating a particular enterprise in particular conditions.

The Progress and Future of Artificial Intelligence in Nursing Care: A Review

Introduction The utilization of novel technologies in contemporary times not only reduces the cost associated with healthcare but also improves the efficiency of hospital resources and elevates the standard of medical assistance. One of the new technologies used in the field of health is Artificial Intelligence (AI). The purpose of this study is to investigate the application of AI in the field of nursing. Materials and Methods The present investigation was conducted in the year 2023 utilizing a review methodology and an innovative scientific inquiry. Comprehensive research was performed in reliable databases such as PubMed, Scopus, Google Scholar, Science Direct, and Springer, using the keywords AI, smart hospital, nursing, and health care to accomplish the intended objectives. From 2016 to 2023,120 articles were chosen as the initial selection. Studies that were not related to the subject matter were excluded from the analysis afterward. Results After searching and eliminating duplicate articles through objective screening, a total of 98 articles were reviewed, with 63 ultimately selected for the study. Within the realm of nursing care, research has been conducted in various areas, such as electronic health records (13 studies), health information collection and analysis (27 studies), healthcare cost analysis (16 studies), and the implementation of smart technology and hospitals (7 studies). The integration of AI technology has shown promise in enhancing nursing care by reducing diagnostic errors, improving emergency response times, improving patient care quality and psychological support, and enabling remote care for elderly patients through the use of smart technology. Conclusion AI is a significant technological advancement that can directly impact the operational effectiveness of healthcare organizations. This is achieved through the optimization of healthcare business processes and the enhancement of patient safety. However, limited research has been conducted regarding the affordability and economic aspects of AI implementation. Therefore, it is advisable for healthcare policymakers to establish the necessary infrastructure to leverage this technology, which will facilitate a more effective therapeutic and economic approach.

Prospects of business process management based on chatbots

The relevance of the study is due to the growing need to use chatbots to optimize business processes. The purpose is to form a theoretical basis and practical tools for increasing the efficiency of using chatbots in business processes. The theoretical basis involves substantiating the theoretical foundations of forming a conditional chatbot profile for an optimization system. The practical toolkit includes chatbot components that depend on the complexity of tasks, the type of services, the specifics of customers, financial conditions, and other features of business processes. The result is the formation of a system profile of the chatbot, which would allow increasing the efficiency of its use in business processes. The key system components of the chatbot are substantiated: the technologies used, types of users, optimal areas of application, application algorithms, basic tools, and limitations in application. By varying the parameters of system components, one can choose their optimal values to increase the efficiency of using chatbots in business processes. It is advisable to use the specified system in business processes when determining the demand for products and their sales. The use of chatbots allows to reduce the time to complete business processes, personnel costs, and resources related to their implementation. AcknowledgmentThe paper was prepared in the framework of the research projects “Fundamental grounds for Ukraine’s transition to a digital economy based on the implementation of Industries 3.0; 4.0; 5.0” (No. 0124U000576) and “Digital transformations to ensure civil protection and post-war economic recovery in the face of environmental and social challenges” (No. 0124U000549).

Anti-crisis design for operational management of the restaurant business in Ukrain

The object of this research is the impact of the crisis caused by military actions in Ukraine on the restaurant business. The study aims to examine the adaptation strategies that restaurants use for survival and development in the face of sudden economic changes and increasing uncertainty. The problems addressed in the study include responding to the loss of customers, rising food prices, decreasing cash flows, and a shortage of qualified workers. The main findings of the study showed that restaurants that successfully adapt implement comprehensive changes: from digitalizing ordering and delivery processes to revising menus and optimizing resource use. These steps not only reduce costs but also improve operational efficiency, which is crucial for maintaining customer loyalty and attracting new customers. Specifically, restaurants that invested in digitalization (e. g., electronic menus, online ordering, and inventory management systems) reported a 30–40 % increase in sales compared to those that did not implement such changes. Restaurants that implemented strategies for staff retention and cost optimization reduced staff turnover by 25 % and increased productivity by 20 %. The results are explained by the implementation of innovative approaches and strategic rethinking of business models, which allow quick responses to changing market conditions and consumer needs. Effective use of digital technologies and optimization of internal processes have become key success factors. The data obtained have significant theoretical and practical value, as they can be used to develop recommendations aimed at improving the resilience and adaptability of the hospitality industry in crisis conditions. These results help understand how managers can use strategic planning to optimize business processes and ensure enterprise stability. The importance of the research is also highlighted by identifying future research directions that can help the restaurant business more effectively adapt to changing market conditions and global crises.

OPERATIONAL MANAGEMENT OF SERVICE FIELD ENTERPRISES UNDER THE CONDITIONS OF DIGITALIZATION IN THE SYSTEM OF SUSTAINABLE DEVELOPMENT

The article explores the unique impact of digitalization on the operational management of service enterprises, underscoring the importance of strategies and tools for optimizing business processes. These tools empower enterprises to effectively use digital technologies, increasing productivity while reducing negative environmental impact. The study also highlights the crucial role of innovative solutions in ensuring sustainable development and how digital technologies can enhance service quality, meeting consumers’ evolving needs. The article concludes by emphasizing the necessity of involving the audience in implementing digital innovations into the management system of service enterprises, aligning with the contemporary demands of efficient and sustainable development.

Data to Decisions: Optimizing E-commerce Sales Potential with Analytics

Descriptive, diagnostic, predictive, and prescriptive analytics play crucial roles in optimizing the performance and user experience of an e-commerce site. Descriptive analytics involves examining historical data to gain insights into past performance, enabling businesses to identify trends, patterns, and anomalies. This analysis helps in understanding what has happened, such as identifying popular products or peak sales periods, and provides a foundation for further analysis. Diagnostic analytics goes beyond descriptive analytics by examining why certain events occurred, identifying factors that influenced outcomes, and uncovering strengths, weaknesses, and areas for improvement within an e-commerce platform. Predictive analytics utilizes statistical algorithms and machine learning techniques to forecast future trends and outcomes, enabling businesses to anticipate customer preferences, demand for specific products, and potential sales opportunities. By leveraging predictive insights, e-commerce sites can adjust strategies, inventory levels, and marketing campaigns proactively to stay ahead of the competition and meet evolving customer needs. Prescriptive analytics takes predictive insights to the next level by recommending specific actions or strategies to optimize business processes and achieve desired outcomes. This could involve personalized product recommendations, targeted marketing strategies, or dynamic pricing adjustments based on real-time data analysis. By harnessing these four types of analytics, e-commerce businesses can make informed, data-driven decisions, enhance customer experiences, drive sales growth, and maximize profitability.

СРАВНИТЕЛЬНЫЙ АНАЛИЗ ОТЕЧЕСТВЕННОГО ПО В СФЕРЕ ЛОГИСТИКИ

Current trends in the development of logistics emphasize the importance of using software to optimize business processes. In the context of global competition and sanctions pressure, Russian companies face the challenge of choosing between foreign and domestic software products. This article is a comparative analysis of three leading foreign and three Russian software products in the field of logistics, evaluating their functionality, flexibility of settings, integration and economic impact of use. Special attention is paid to aspects related to sanctions and the impact of the national economy.

Analysis of business processes of hotels (on the example of the mini-hotel Barin Residence Grand)

The article discusses business processes, their main elements, classification, features of the development and optimization of business processes. The issues of defining business processes for hotels are considered separately.

Perancangan Enterprise Arsitektur Menggunakan TOGAF ADM Di Bea Cukai Tanjung Pandan pada Aplikasi SIMPORA

The web-based SIMPORA Customs Tanjung Pandan application is an efficient solution for optimizing annual budgeting business processes. Customers can easily get the latest information about the services provided in real-time. So it is hoped that it can improve performance significantly. To develop it, several data collection techniques were used, namely by conducting in-depth interviews, making observations and documenting them. Meanwhile, the research methodology is TOGAF ADM 9.1. This method is known to be the best method that can develop architecture in a structured and reliable manner. Several types of diagrams that help in designing this system are Value Chain, BPMN, Context Diagram, Use Case, and Class Diagram. It is hoped that this enterprise architecture design will enable budgeting to be monitored and improved immediately by stakeholders. The result of this research is an enterprise architecture design to support business processes at Tanjung Pandan Customs and Excise. It is hoped that various budgeting errors and design inaccuracies can be reduced and eliminated with this application, so that it can support the optimization of this institution's business processes.