Hasil untuk "Business records management"

T. Murdoch, A. Detsky

Габріелла Лоскоріх, Вероніка Ганусич, Оксана Перчі

The sustainability of the revenue base of local budgets during wartime largely depends on the stability of tax revenues and the ability of communities to adapt their tax base to changes in economic activity. The purpose of this study is to conduct a structural-dynamic analysis of tax revenues of the Berehove Territorial Community budget in 2021–2025 and to substantiate directions for strengthening and diversifying the tax base. The Berehove Territorial Community, located in Ukraine’s western border region, is characterized by a specific sectoral structure of entrepreneurship, a significant role of small and medium-sized enterprises, and active cross-border economic linkages. The study employs an empirical analysis  of the community’s budget execution indicators, with a focus on changes in the structure of tax revenues and the role of different categories of taxpayers.  The analysis proceeds from the hypothesis that the growth of tax revenues during the wartime period is uneven across tax groups and is accompanied by a transformation in the relative fiscal contributions of individuals and legal entities. The methodological framework includes structural-dynamic analysis and factor decomposition of the contribution of major tax groups to changes in total tax revenues. The results reveal the dominance of taxes on income, profits, and capital gains, alongside an increasing contribution of local taxes and fees as well as internal taxes on goods and services. It is demonstrated that the main increase in tax revenues in 2021–2024 was generated primarily by income-related taxes and local taxes and fees, while other components had a limited impact. Changes in the structure of taxpayers are also identified: in 2023–2024, the share of individuals in the total amount of taxes paid increased, whereas in 2024–2025 the growth of revenues was predominantly ensured by legal entities. The theoretical significance of the study lies in the advancement of approaches to assessing the sustainability of a community’s tax base through the combined application of structural-dynamic and factor analysis. The practical significance is reflected in the possibility of using the results to refine local tax policy priorities and to support the diversification of the revenue base. A limitation of the study is the use of 2025 data covering only nine months; further research should refine the conclusions based on full-year data for 2025 and provide a more detailed breakdown by specific taxes and types of economic activity.

Cosmin PROȘCANU, Miruna PROȘCANU

There have been numerous reports of news articles that exhibit predominantly negative quality and tone. These types of incidents happen rather often. However, there are certain situations where the news might be highly detrimental, even though it remains essential and continues to hold importance in our lives. Our approach entails leveraging programming skills to gather news stories, which are subsequently assessed using a toxicity meter and analyzed. This operation is undertaken with the purpose of enriching the data that is fed into the programming solution. Improving the current solutions for detecting toxic news can only help to better understand the patterns and the purpose of this news. Moreover, improving this level of understanding can be achieved by further processing the resulting data with new technologies. For the time being the proposed solution helps with the classification of the most toxic news.

І. В. Артімонова, А. В. Семисал, Д. А. Качан

У статті досліджено теоретичні та практичні аспекти застосування традиційних та сучасних маркетингових інструментів у процесі формування попиту та пропозиції на ринку насіння в Україні з урахуванням сучасних глобальних викликів. Визначено роль насіннєвого матеріалу як стратегічного ресурсу забезпечення продовольчої безпеки, підвищення конкурентоспроможності аграрного виробництва та адаптації аграрного виробництва до кліматичних змін та соціально-економічної нестабільності. Метою дослідження є визначити тенденції розвитку сучасного маркетингового інструментарію на ринку насіннєвого матеріалу, оцінити його вплив на формування платоспроможного попиту та товарної пропозиції і обґрунтувати напрями вдосконалення маркетингових стратегій як необхідної умови підвищення ефективності та адаптивності агробізнесу. Основною гіпотезою дослідження виступає припущення про те, що комплексне використання класичних та сучасних інструментів маркетингу в кризових умовах ведення агробізнесу забезпечить підвищення ефективності формування попиту та стабілізацію пропозиції на ринку насіннєвого матеріалу через адаптацію маркетингових стратегій до мінливого ринкового середовища, оптимізацію логістичних ланцюгів та посилення клієнтоорієнтованого підходу, що дозволить компаніям-виробникам насіння зберегти конкурентні позиції та забезпечити сталий розвиток бізнесу. Дослідження ґрунтується на системному методичному підході із застосуванням методів системного аналізу, структурно-функціонального підходу та порівняльного аналізу, що дозволив отримати комплексну оцінку ефективності використання різних маркетингових інструментів при формуванні попиту та пропозиції на ринку насіннєвого матеріалу та розробити обґрунтовані рекомендації щодо їх оптимізації з урахуванням глобальних тенденцій та умов трансформаційної економіки. Теоретичне значення дослідження полягає в розширенні наукового розуміння особливості використання сучасних маркетингових інструментів в агропромисловому секторі. Практична цінність дослідження полягає у тому, що отримані наукові результати можуть бути використані в процесі розробки маркетингових стратегій формування попиту та пропозиції на сучасному ринку насіннєвого матеріалу України, оскільки без них неможливо реально вплинути на ефективне співвідношення попиту і пропозиції в ринковому середовищі. Перспективи подальших досліджень полягають у поглибленому аналіз впливу цифрових маркетингових технологій та штучного інтелекту на персоналізацію маркетингових стратегій в насіннєвому секторі, а також дослідження ефективності омніканального підходу в умовах зростаючої цифровізації агросектору.

Kun Tan, Linya Huang, Yuxian Nie et al.

This paper, based on data from inpatient medical records with uterine fibroids (ICD-10: D25) from the medical record homepages of secondary and higher-level hospitals in Sichuan Province between 2016 and 2024, investigated differences in medical resource consumption and costs between high-intensity focused ultrasound (HIFU) and traditional surgical treatments under the diagnosis-related group (DRG) system. Cases were classified using the MS-DRG grouper into groups with and without complications or comorbidities (CC/MCC). An XGBoost model was employed to reclassify data for HIFU patients, addressing missing coding. Group validity was assessed using the coefficient of variation (CV) and reduction in variance (RIV). Factors influencing costs were identified via multifactorial regression analysis. Results showed that in the group without CC/MCC, HIFU treatment significantly reduced the length of hospital stay, decreased the proportion of consumables costs and medication costs, but increased the proportion of treatment costs. Median hospitalization costs were significantly higher in the CC/MCC group than in the non-CC/MCC group. Multifactorial regression analysis identified length of stay (LOS), HIFU treatment, and CC/MCC grouping as key cost drivers. Additionally, costs for patients covered by Urban Employee Basic Medical Insurance and Commercial Health Insurance were significantly higher than those with other payment types. This paper confirms the effectiveness of DRG grouping in reflecting resource consumption disparities and reveals the potential of HIFU technology for optimizing medical resource allocation. Recommendations include promoting HIFU adoption, optimizing medical insurance payment policies, and strengthening hospital management to achieve dual goals of cost control and healthcare quality improvement. The findings provide empirical evidence for DRG payment reform and the selection of uterine fibroid treatment modalities.

Ruiming Min

This study examines whether the tariff policies delivered on promises to revitalize American manufacturing and create jobs. Using county-level business application data from 2018-2025, we analyze the relationship between tariff implementation and new business formation through linear regression analysis. Our findings reveal a statistically significant positive association between US tariffs on China and American business applications. However, when Chinese retaliatory tariffs are included in the analysis, their negative coefficient substantially exceeds the positive US tariff effect, suggesting that retaliatory measures largely offset the benefits of protectionist policies. Control variables including inflation rate, federal funds rate, and government spending show significant positive effects on business formation. These results indicate that while protectionist trade policies may stimulate domestic business formation, their effectiveness is significantly diminished by retaliatory responses from trading partners. The study provides evidence that unilateral tariff measures without diplomatic coordination produce limited net benefits, confirming that trade wars create scenarios where potential gains are neutralized by counteractions.

Arni Utamaningsih, Nilawati Fiernaningsih, Siti Nurbaya et al.

This research aims to explore whether the proceeds, age, revenue, and underwriter rating of IPO companies affect disclosure; whether disclosure mediates the relationship between the four exogenous variables and underpricing; and whether underpricing mediates the relationship between disclosure and returns. This research uses Partial Least Squares Structural Equation Modelling (PLS-SEM) as the data processing method. Since this research examines interactions between variables, PLS-SEM is an effective data processing method. This research identifies four key exogenous variables: funds raised from the IPO, the age of the IPO company, the income of the companies prior to the IPO, and the ranking of underwriting companies. The research finds that the R-squared of the disclosure variable is 0.0037, or 3.7%, while the Q-squared of the disclosure variable is 0.0039. Meanwhile, the R-squared of the underpricing variable is 0.435, and the Q-squared of the underpricing variable is 0.456. The research also finds that higher proceeds, age, revenue, and underwriter ranking of IPO companies will reduce disclosure. Conversely, higher proceeds and age of the IPO companies will reduce underpricing, while higher revenue and underwriter ranking of the IPO company will increase underpricing. Finally, the research finds that higher disclosure will increase underpricing. Статтю розміщено в рамках грантової програми ГО «НАУКОВО-ОСВІТНІЙ ІННОВА- ЦІЙНИЙ ЦЕНТР СУСПІЛЬНИХ ТРАНСФОРМАЦІЙ» за підсумками Конкурсу індивідуальних грантів «Ініціатива підтримки науковців»

Fernando Acebes, José Manuel González-Varona, Adolfo López-Paredes et al.

The project managers who deal with risk management are often faced with the difficult task of determining the relative importance of the various sources of risk that affect the project. This prioritisation is crucial to direct management efforts to ensure higher project profitability. Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to their likelihood of occurrence and impact on project objectives. However, the existing literature highlights several limitations to use the risk matrix. In response to the weaknesses of its use, this paper proposes a novel approach for prioritising project risks. Monte Carlo Simulation (MCS) is used to perform a quantitative prioritisation of risks with the simulation software MCSimulRisk. Together with the definition of project activities, the simulation includes the identified risks by modelling their probability and impact on cost and duration. With this novel methodology, a quantitative assessment of the impact of each risk is provided, as measured by the effect that it would have on project duration and its total cost. This allows the differentiation of critical risks according to their impact on project duration, which may differ if cost is taken as a priority objective. This proposal is interesting for project managers because they will, on the one hand, know the absolute impact of each risk on their project duration and cost objectives and, on the other hand, be able to discriminate the impacts of each risk independently on the duration objective and the cost objective.

Yannick Becker, Pascal Halffmann, Anita Schöbel

In portfolio optimization, decision makers face difficulties from uncertainties inherent in real-world scenarios. These uncertainties significantly influence portfolio outcomes in both classical and multi-objective Markowitz models. To address these challenges, our research explores the power of robust multi-objective optimization. Since portfolio managers frequently measure their solutions against benchmarks, we enhance the multi-objective min-regret robustness concept by incorporating these benchmark comparisons. This approach bridges the gap between theoretical models and real-world investment scenarios, offering portfolio managers more reliable and adaptable strategies for navigating market uncertainties. Our framework provides a more nuanced and practical approach to portfolio optimization under real-world conditions.

N. Badri, Leila Nasraoui, L. Saïdane

The integration of the Internet of Things (IoT) with blockchain technology has enabled a significant digital transformation in the areas of E‐health, supply chain, financial services, smart grid, and automated contracts. Many E‐health organizations take advantage of the game‐changing power of blockchain and IoT to improve patient outcomes and optimize internal operational activities. In particular, it proposes a decentralized and evolutive way to model and acknowledge trust and data validity in a peer‐to‐peer network. Blockchain promises transparent and secure systems to provide new business solutions, especially when combined with smart contracts. In this paper, we provide a comprehensive survey of the literature involving blockchain technology applied to E‐health. First, we present a brief background on blockchain and its fundamentals. Second, we review the opportunities and challenges of blockchain in the context of E‐health. We then discuss popular consensus algorithms and smart contracts in blockchain in conjunction with E‐health. Finally, blockchain platforms are evaluated for their suitability in the realm of IoT‐based E‐health, including electronic health records, electronic management records, and personal health records, from the perspective of remote patient monitoring.

A. Sunyaev, Niclas Kannengießer, R. Beck et al.

Transfers of ownership of assets (e.g., fiat money, company shares, or usage rights) between agents (here, individuals or organizations) is often mediated by trusted third parties (TTPs) such as banks or notaries to increase reliability of the transfer process. The involvement of TTPs often introduces drawbacks, like increased costs, longer processing time, and the presence of a single point of failures. These drawbacks motivate the automation and decentralization of several services offered by TTPs. Technological advances have enabled the digital representation and management of asset ownerships using tokens on decentralized digital platforms without the need for TTPs. A token is a sequence of characters that serves as an identifier for a specific asset (e.g., a personalized usage rights) or asset type (e.g., a cryptocurrency). The abilities to represent assets in form of digital tokens on a decentralized digital platform and to assign ownership of these assets to agents in a fraud-resistant way can help to reduce drawbacks related to TTPs (e.g., the presence of single points of failures) and enable a new type of economy: the token economy. In tackling drawbacks related to TTPs, the token economy holds a large transformative value (Benlian et al. 2018) that can strongly affect businesses (e.g., by enabling novel business models and increasing transparency of business processes) and our daily life (e.g., by being able to monetize our own personal data instead of just giving it away). This chapter discusses the key concept of decentralization, which the token economy is built on, from two fundamental perspectives (i.e., technical and political decentralization) and provides propositions to discuss decentralization. Moreover, this chapter explicates the need for interdisciplinary research (e.g., information systems research, computer science, management science, and social science) to embrace both perspectives. In the token economy, technical protocols take over several tasks that traditional TTPs previously handled. For example, technical protocols running decentralized digital platforms can check individual agents’ legitimate ownership of assets and create a tamper-resistant record of the A. Sunyaev (&) N. Kannengießer Karlsruhe Institute of Technology, Karlsruhe, Germany e-mail: sunyaev@kit.edu

J. Newton, R. Nettle, J. Pryce

Abstract Digitalization and the use of Smart Farming Technologies are considered a major opportunity for the future of agriculture. However, realisation of full benefits is constrained by: (1) farmers' interest in and use of big data to improve farm decision making; (2) issues of data sovereignty and trust between providers and users of data and technology; (3) institutional arrangements associated with the governance of data platforms. This paper examines the case of Australia's dairy herd milk recording system, arguably one of agriculture's first cases of ‘big data’ use, which collects, analyses and uses farm-level data (milk production, lactation and breeding records) to provide individual cow and herd performance information, used by individual farmers for farm management decisions. The aim of this study was to 1) examine the use of big data to add value to farm decision making; and 2) explore factors and processes, including institutional arrangements, which influence farmer engagement with and use of big data. This paper traces the Australian history of the organisation of dairy herd recording (established in 1912 and digitalized in late 1970s) and then uses findings from a longitudinal study of 7 case study dairy farms, which were incentivised to become involved in herd recording in 2015. Applying a conceptual framework linking path dependency in farm decision making and collaborative governance capacity, we find three new important dimensions of the farm user context influencing farmer demand for big data applications: 1) the transition to a new business stage; 2) the additionality farmers seek from data generated in one component of the farm system to other subsystems, and 3) the use of data in long term or strategic decision making. Further, we identified critical attributes of support services in addressing digital literacy, capacity and capability issues at farm level, including diversity in data presentation formats and facilitation of the on-farm transition process through intermediary herd test organisations. The role of farmers as governance actors, or citizens in the decisions of the trajectory of big data applications, adds to understanding of the nature of collaborative governance arrangements that support farm engagement.

B. Chillakuri, V. P. Attili

Purpose This study aims to broaden the understanding of the blockchain for human resource (HR) managers through use cases. The study presents a plausible solution for HR professionals to effectively manage some of the core processes to focus on more strategic work and be a true HR business partner for the organization. Design/methodology/approach The study adopted a case research strategy. The case research strategy is well-suited to capture the practitioner’s knowledge, mainly when focusing on contemporary events (such as COVID-19). Data collected from 12 tech organizations through telephonic conversations and the interviews were recorded and transcribed using NoNotes call recording. Findings This study identifies five use cases to streamline the critical processes, helping HR professionals such as certificates verification, skill mapping, payroll processing, data protection and performance management. These early use cases offer a plausibly superior alternative in managing critical HR functions and associated business processes with blockchain technology. Research limitations/implications Despite the growing number of blockchain applications, its usage in HR activities is limited. By extensive qualitative case study and data triangulation, the study integrates a resource-based view and unified theory of acceptance by explaining how blockchain adoption helps organizations use their internal resources and capabilities to gain a competitive advantage. The study presents five use cases and propositions that can act as building blocks for the HR department in adopting blockchain applications. Lack of empirical validation (quantitative rigor) of the propositions is the limitation and can be a future research scope. Practical implications Adopting new technologies is not new for HR managers. However, most of the technologies are disjointed applications, and therefore, the need for an all-pervasive solution assumes significance. Several of the blockchain concepts are still in the nascent stage. Thus, the study highlights the need for HR leaders to work alongside technical architects to create blockchain applications. Unlike other HR applications, blockchain can integrate all the employees, clients, vendors and businesses seamlessly. This study proposes research propositions that provide research directions for future research. Originality/value Academic literature on connecting blockchain technology with HR functions and applications is notably absent. This research can be considered one of the first academic articles connecting blockchain and HR processes.

Nijat Mehdiyev, Peter Fettke

The contemporary process-aware information systems possess the capabilities to record the activities generated during the process execution. To leverage these process specific fine-granular data, process mining has recently emerged as a promising research discipline. As an important branch of process mining, predictive business process management, pursues the objective to generate forward-looking, predictive insights to shape business processes. In this study, we propose a conceptual framework sought to establish and promote understanding of decision-making environment, underlying business processes and nature of the user characteristics for developing explainable business process prediction solutions. Consequently, with regard to the theoretical and practical implications of the framework, this study proposes a novel local post-hoc explanation approach for a deep learning classifier that is expected to facilitate the domain experts in justifying the model decisions. In contrary to alternative popular perturbation-based local explanation approaches, this study defines the local regions from the validation dataset by using the intermediate latent space representations learned by the deep neural networks. To validate the applicability of the proposed explanation method, the real-life process log data delivered by the Volvo IT Belgium's incident management system are used.The adopted deep learning classifier achieves a good performance with the Area Under the ROC Curve of 0.94. The generated local explanations are also visualized and presented with relevant evaluation measures that are expected to increase the users' trust in the black-box-model.

Agnieszka Knap-Stefaniuk, Artur Jacek Kożuch, Monika Wakuła

The aim of this paper is to evaluate the behavior of small and medium-sized enterprises against a backdrop of the risk of extraordinary events and to present the key actions to allow business continuity in the present environment. To meet the study objective, a mixed research methodology was applied. The case study was conducted on the basis of case files of the District Court in a damages action for a loss of profit brought by a small enterprise owner. The financial analysis comprised records filed in the claim for damages and was aimed to illustrate the consequences following from owner’s exclusion from business activities and to examine the compliance of the contents of the above documents with the concepts of management and quality sciences. The court proceedings, along a literature review, were used in the process of conclusion-making with the application of techniques of deduction to produce a general model of reference for proceedings regarding extraordinary events in the operation of small and medium enterprises. One of the more significant findings to emerge from this study is that the provision of business continuity conditioned, among other things, by revenues, requires solutions regarding procedures of extraordinary occurrence risk management.

David Chapela-Campa, Marlon Dumas

Business Process Simulation (BPS) is a common technique to estimate the impact of business process changes, e.g. what would be the cycle time of a process if the number of traces increases? The starting point of BPS is a business process model annotated with simulation parameters (a BPS model). Several studies have proposed methods to automatically discover BPS models from event logs -- extracted from enterprise information systems -- via process mining techniques. These approaches model the processing time of each activity based on the start and end timestamps recorded in the event log. In practice, however, it is common that the recorded start times do not precisely reflect the actual start of the activities. For example, a resource starts working on an activity, but its start time is not recorded until she/he interacts with the system. If not corrected, these situations induce waiting times in which the resource is considered to be free, while she/he is actually working. To address this limitation, this article proposes a technique to identify the waiting time previous to each activity instance in which the resource is actually working on them, and repair their start time so that they reflect the actual processing time. The idea of the proposed technique is that, as far as simulation is concerned, an activity instance may start once it is enabled and the corresponding resource is available. Accordingly, for each activity instance, the proposed technique estimates the activity enablement and the resource availability time based on the information available in the event log, and repairs the start time to include the non-recorded processing time. An empirical evaluation involving eight real-life event logs shows that the proposed approach leads to BPS models that closely reflect the temporal dynamics of the process.

Hanan Shteingart, Gerben Oostra, Ohad Levinkron et al.

Data science has the potential to improve business in a variety of verticals. While the lion's share of data science projects uses a predictive approach, to drive improvements these predictions should become decisions. However, such a two-step approach is not only sub-optimal but might even degrade performance and fail the project. The alternative is to follow a prescriptive framing, where actions are "first citizens" so that the model produces a policy that prescribes an action to take, rather than predicting an outcome. In this paper, we explain why the prescriptive approach is important and provide a step-by-step methodology: the Prescriptive Canvas. The latter aims to improve framing and communication across the project stakeholders including project and data science managers towards a successful business impact.

Ioanna Boulouta, C. Pitelis

Wil M.P. van der Aalst, H. Reijers, Minseok Song

Maria-Cristina MITRICĂ (PĂDURE)

In the last decades, our society and economy have undergone shocking changes, leading to the emergence of new economic models. They were originally born in more developed countries. Subsequently, the information revolution swept the world and contributed to the development of the new model. The cooperative economy is one of them. Through technology and the internet and tools that can instantly access any information from anywhere in the world, the collaborative economy is expanding and developing. This makes communication between different categories of people easier and easier. The purpose of this article is to highlight the challenges, opportunities and benefits of cooperative economies in national and international environments and to find out the current level of understanding and acceptance by different stakeholders. This article contains an analysis of the challenges of collaborative economy, which is an important economic transformation in recent years and contributed to the birth of a new perspective on business environment.