Purpose This study examines the dual impact of artificial intelligence (AI) on business processes by systematically identifying and prioritizing both its value-creating benefits (bright-side) and risk-inducing consequences (dark-side). The study further aims to develop an integrated theoretical framework that explains how organizations can balance these opposing effects to achieve sustainable AI-driven business transformation. Design/methodology/approach A content-driven review of recent peer-reviewed literature was conducted to identify key positive and negative impacts of AI across five business process dimensions. Expert evaluations from 42 professionals were analyzed using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution method to prioritize these impacts under uncertainty. Sensitivity analysis was performed to validate the robustness of the results, and an integrated theoretical framework was developed based on the empirical findings. Findings The results reveal that AI delivers its strongest benefits through enhanced financial risk forecasting, internal control, sustainability reporting and customer-facing automation, significantly improving operational efficiency and decision quality. However, the findings also highlight critical risks associated with inadequate governance, privacy invasion, ethical lapses and excessive reliance on automated systems. Governance-related risks emerged as the most severe challenges, indicating that the absence of robust ethical and regulatory frameworks can undermine the long-term value of AI adoption. Practical implications The study provides managers and policymakers with a structured decision-support approach to prioritize AI applications while proactively managing ethical, governance and data-related risks. Originality/value This research offers a novel integration of fuzzy multi-criteria decision analysis with theory development to present a balanced, data-driven understanding of AI's dual impact on business processes and organizational sustainability.

Nahdlatul Ulama University, which manages multiple institutions, requires an integrated information system to coordinate academic and administrative processes efficiently. However, developing such a system faces challenges related to business process complexity and the need for diverse user role distribution. This study aims to design an integrated academic information system (SIUNU) by combining BPMN business process modeling and RACI matrix analysis to produce a modular, scalable, and accountable system architecture in a multi-campus environment. The research employs a qualitative-descriptive methodology with a case study approach. Business process modeling was conducted using Business Process Model and Notation (BPMN) 2.0 to visually represent workflows. The research produced business process models for five main modules: Authentication (login, forgot password, logout), Academic Dashboard (student data, lecturer data, GPA summaries, tracer studies), Evaluation and Reporting (teaching evaluation), Letter Management (drafting, verification, disposition, archiving), and the MBKM Module (program registration, credit conversion). RACI analysis generated structured role mapping, showing the Super Admin as the primary accountable party for system configuration, PTNU Admin as the operational implementer, Lecturers as academic consultants, and Students as active users of personal data. The integration of BPMN and RACI proved effective in producing an academic information system design framework that is not only technically robust but also organizationally accountable. This research contributes to the development of academic information system literature through an integrative approach and provides a ready-to-implement design for Nahdlatul Ulama University.

Tracheostomy decannulation process model: an interprofessional, Latin-American Delphi consensus.

The evolution of consumer trends and business performance through AI-Driven marketing: A performance perspective.

Time-aware and transition-semantic graph neural networks for interpretable predictive business process monitoring

BPSmart-CARE: a framework for managing contextualized actions in IoT systems through the integration of business process modelling and complex event processing

Business Strategy Planning at PT Kurniawan Sejati Sejahtera is carried out in response to the increasingly fierce market competition in the bottled water industry. In recent years, the company has experienced fluctuations and downward trends in sales, underscoring the need for a more adaptive and competitive business strategy to sustain growth and strengthen its market position. In addition, the bottled water industry in Indonesia continues to grow rapidly, with many companies and brands competing in the same market segment, further intensifying competitive pressures. This research aims to identify the company's internal and external factors as the basis for strategy formulation, develop appropriate and effective business strategies, determine strategic priorities in the face of market competition, and map the relationship between business strategy and business processes. The methods used in this study include Value Chain Analysis to identify internal factors, Porter's Five Forces Analysis to analyze external factors, SWOT Analysis to formulate alternative strategies, and Multi-Attribute Utility Theory (MAUT) to determine strategic priorities. The results of the study show that priority strategies include maintaining the current product price while maintaining quality, increasing promotional activities through radio, social media, and endorsement services, maintaining good and mutually beneficial relationships with suppliers, choosing backup drivers, providing discounts or bonuses for regular customers, actively seeking partnership programs, continuing to develop attractive packaging design innovations, and expanding distribution channels for convenience stores. At the end of this study, a strategic map that connects business processes with goals is developed to support the implementation of effective strategies.

Digital financial services have become essential in strengthening the financial operations of Micro, Small, and Medium Enterprises (MSMEs), particularly as businesses adapt to an increasingly digital economic environment. While digital tools are widely recognized for enhancing business processes, limited research has focused on how digital financial services and digital literacy influence the financial behavior of MSMEs. This study examined the relationship between Digital Financial Services (DFS), digital literacy, and financial behavior among MSMEs in the food sector of Calapan City. A descriptive-correlational research design was used, and data were collected from 170 MSMEs using a researcher-developed questionnaire assessing DFS usage, digital literacy, and financial behavior across saving, financing, investing, and spending. The results further showed that digital literacy strengthens the effectiveness of DFS by enabling MSMEs to apply digital tools more confidently and strategically. The study highlights specific behavior areas with lower adoption, such as separating digital savings, using digital loan platforms, monitoring investments digitally, and maximizing digital payment systems. These gaps reflect the need for targeted interventions that improve MSMEs’ competencies in leveraging financial technologies. The findings emphasize the importance of DFS and digital literacy as key drivers of improved financial decision-making, stronger financial management, and greater business resilience within the MSME sector.

Metrological testing is an indispensable link supporting the high-quality development of various industries, and basic metrological inspection institutions are a key force serving the national economy and people’s livelihood, technological innovation, and industrial development. In the digital age, promoting the digital transformation of metrology is an inevitable trend for the development of metrological inspection institutions. The application value of digitalization in metrological inspection institutions is reflected in four aspects: ensuring data quality, optimizing business processes, strengthening risk prevention and control, and innovating service models. Combined with the problems in the informatization construction of metrological inspection, this paper puts forward strategies for the digital transformation and application of basic metrological inspection institutions, focusing on platform construction, system improvement, tool empowerment, facility guarantee, and team building, aiming to provide a reference for the development of metrology towards efficiency and precision.

The development of contemporary Islamic business is characterized by the increasing use of standardized sale contracts as a response to demands for efficiency, legal certainty, and the growing complexity of modern economic transactions. Contract standardization is considered an effective mechanism to streamline business processes and reduce legal risks, particularly within Islamic financial institutions and digital-based business platforms. However, the widespread application of standard contracts has raised a fundamental concern regarding the diminishing space for deliberation (musyawarah) between contracting parties, which potentially undermines ethical values and justice in Islamic commercial law. This study focuses on contemporary Islamic business contract practices by examining the position of standardized contracts and their implications for the principle of musyawarah as a core ethical and legal value in Islam. Employing a qualitative normative-empirical approach, the research analyzes Islamic jurisprudence on mu‘āmalah and Islamic business ethics, supported by document analysis of standardized contracts and selected business practices. The findings indicate that while standardized contracts enhance efficiency and legal certainty, their implementation often leads to bargaining power asymmetry and restricts meaningful participation in contract formation. This condition weakens the ethical dimension of contracts and risks distancing Islamic business practices from the principles of justice and deliberation. The study emphasizes the necessity of repositioning musyawarah within Islamic business contracts and advocates for the development of more participatory standardized contract models aligned with the normative objectives of Islamic law for both business actors and regulators.

Subject. Automation of business processes in logistics as an essential strategic asset that determines the sustainability and effectiveness of supply chains. Objectives. Systematization of modern knowledge in the field of logistics automation, comprehensive analysis of the architecture and functionality of key classes of information systems (supply chain management, enterprise resources, warehouse, transport), development of a methodological approach to assessing their economic and operational effectiveness based on a system of key indicators and financial models. Methods. The research is based on the methods of system and comparative analysis, economic modeling and forecasting. The methodological basis was the works of leading domestic and foreign scientists in the field of logistics and supply chain management. Results. An evolutionary model of logistics is presented, and the transition to process-oriented management as the basis for automation is justified. A multi-criteria classification of automation systems is proposed. A comprehensive implementation efficiency assessment methodology has been developed that integrates operational and financial key performance indicators with formalized models for calculating net present value, payback period, and total cost of ownership. The concept of the "cost of inaction" is considered as a critical argument for investment. Conclusions. The scientific novelty of the research lies in the synthesis of the process approach and the financial and economic assessment apparatus into a single methodological apparatus, which allows us to move from point optimization of functions to strategic management of the end-to-end efficiency of logistics business processes.

Subject. An organizational model capable of enhancing the efficiency of logistics management in a modern enterprise. Objectives. To develop and scientifically substantiate a model for assessing the efficiency of logistics business processes based on a balanced process-matrix structure, which ensures a comprehensive and adaptive approach to logistics management under digital transformation. Methods. Systems and process-based approaches were applied. Results. A system for calculating partial and integral indicators across four criteria – financial-economic, production, external integration, and organizational has been presented. The interpretation of the obtained values is carried out using the Harrington scale, which allows classifying the state of each process and taking timely measures. The implementation of a process-matrix structure has been proposed; a comprehensive methodology for quantitatively assessing its performance, based on an adapted concept of a balanced scorecard, has been developed; and a set of practical indicators for managerial control has been formed. A ready-to-use organizational template has been provided, enabling effective interaction between functional units. Conclusions. The developed assessment mechanism provides enterprise management with a tool for objective monitoring, identifying bottlenecks, and making informed managerial decisions. This approach ensures transparency of costs and outcomes within end-to-end business processes.

The purpose of this study is to evaluate the School Management Information System and student data governance at Medan 1 Public High School (SMAN 1 Medan) using the COBIT 2019 framework. The evaluation was conducted across three key domains: grade and NISN (National Student Identity Number) data integrity (DSS06), e-learning availability (DSS05), and student data security. A quantitative approach was employed, with data collected through questionnaires, interviews, and direct observation of operational systems. The survey participants consisted of 45 individuals, including the principal, vice principal, teachers, IT staff, and system administrators. The analysis indicated that SMAN 1 Medan's IT governance maturity was at "Level 2 (Managed)" with an average score of 2.45 out of 5. The scores by domain were 2.38 for DSS06 (Business Process Control Management), 2.52 for DSS05 (Service Request and Incident Management), and 2.45 for the Data Security domain. Key findings from the study included the identification of several areas requiring improvement: (1) insufficient documentation for grade and NISN data management procedures, (2) e-learning infrastructure limitations that caused periodic downtime, and (3) suboptimal implementation of student data security policies. The study offers strategic recommendations for raising IT governance maturity to "Level 3 (Established)" through the implementation of standard operating procedures (SOPs), infrastructure improvements, and strengthening of information security policies.

Objectives: This study aimed to examine the role of digital transformation in its three dimensions—digital technologies, digital infrastructure, and employees’ digital skills—in enhancing operational management efficiency in small and medium-sized enterprises (SMEs) within the service sector in Saudi Arabia. The study also sought to assess the impact of these dimensions on improving operational performance and increasing the efficiency of business processes in these enterprises. Methodology: A descriptive-analytical approach was adopted, appropriate to the nature of the research. The study population comprised employees working in SMEs in the service sector across Saudi Arabia. A simple random sampling method was used, resulting in a sample of 165 participants. Data were collected through a structured questionnaire. Results: The findings revealed high levels of digital transformation and operational management efficiency from the participants’ perspective. Digital transformation had a statistically significant effect on enhancing operational efficiency. Among the three dimensions, digital skills and digital technologies had the greatest impact, followed by digital infrastructure, highlighting the importance of technically qualifying employees and promoting the use of modern technologies in operational processes. Conclusion: The study concluded that investing in digital infrastructure, enhancing employees’ technical competencies, and integrating digital systems with operational processes are essential for improving operational efficiency in SMEs. It also recommended expanding future studies to cover multiple sectors and incorporating mediating variables to examine the relationship between digital transformation and operational efficiency more comprehensively.

Business process improvement is a difficult endeavour that calls for sophisticated and reliable supporting technology. Behavioural pattern identification, predictive analytics, business activity monitoring, business intelligence systems, and "type simulations" are some of the new technologies and advanced analytics techniques that can help business users continuously improve their operations. However, business users are unable to effectively obtain timely analytics data due to the large amounts of event data generated by process execution during the business lifetime. This article offers a big data-based technology solution that gives business analysts insight into distributed processes and business performance. Users may quickly monitor business performance in highly distributed situation. Keywords: Business Analytics, Big Data, Business Performance, Information Management, Data Storage Systems, Cloud Computing.

The rapid development of data-driven technologies has made business intelligence (BI) a critical tool for IT companies that aim to improve decision-making, optimize business processes, and gain competitive advantage. However, implementing BI in IT companies often faces challenges such as resistance to change, data integration issues, and lack of effective strategies. In order for BI systems to successfully integrate into an organization’s workflow and deliver maximum value, it is important to follow best practices during the implementation process. This article discusses best practices for implementing BI in IT companies, focusing on the steps and strategies that contribute to successful implementation and long-term sustainability. In addition, it highlights the main findings of various studies and provides recommendations for overcoming common barriers.

Translating unstructured user feedback into Business Process Model and Notation (BPMN) is challenging due to informal language, contextual ambiguity, and the lack of explicit structural cues. We present FB2BPMN, an end-to-end pipeline that combines natural language processing (NLP), large language models (LLMs), and fuzzy string matching to automatically generate BPMN elements from raw feedback. The pipeline comprises four stages: sentence structuring, fact extraction, role-activity mapping, and fuzzy-based semantic alignment. We evaluate FB2BPMN on 125 annotated feedback instances sampled from academic journal management systems. Using expert-authored BPMN as reference, FB2BPMN attains precision 0.97, recall 0.88, and F1 0.91 on element identification and accuracy 0.85 on process flow construction, outperforming a rule-based baseline. Results indicate strong structural and semantic correspondence, showing that FB2BPMN effectively bridges informal feedback and formal process representations.

ABSTRACT Despite the growing adoption of Business Process Management (BPM) in public administration, little is known about which factors drive BPM project success in countries like Brazil, where bureaucratic processes, heterogeneous legacy systems, and political instability create unique implementation challenges. Existing studies identify generic BPM and Information Technology (IT) success factors, yet no research has systematically examined success factors within public‐sector BPM projects, leaving a critical contextual gap. This study addresses it through an action research project conducted at a large Brazilian national public institution. Across a ten‐month Government‐to‐Government initiative, 22 semi‐structured interviews were conducted and analyzed at each project cycle, allowing success factors to be identified, followed, updated, and validated by both the project team and the client. Results confirm several factors known in the literature while revealing new factors, including analysis of information systems and legacy mappings, project manager authority and influence, client systemic understanding, and an open‐minded environment for change. A comparative analysis shows divergence in how stakeholders value these factors: the implementation team identifies more technical and managerial elements, while the client emphasizes prioritization and internal constraints. The study advances theory by contextualizing BPM success factors for the public sector. It offers practical guidance to strengthen governance, stakeholder engagement, and continuity of BPM initiatives in politically dynamic public organizations.

The development of an Electronic Health Record (EHR) system requires a well-defined data set and a robust data model to support complex clinical workflows, interoperability, and data quality. Many existing EHR implementations lack standardized and integrated data models, resulting in redundancy, semantic inconsistency, and limited support for secondary data use. This study aims to develop a comprehensive EHR data model based on a Minimum Data Set (MDS) that systematically represents medical service processes across emergency, outpatient, inpatient, and surgical care. The proposed approach involves the design of a conceptual, logical, and physical data model. Business processes were first analysed to identify relationships among clinical and administrative data classes, which were then transformed into a conceptual data model. The logical data model was developed through database normalization and schema definition, while the physical data model was constructed to represent the actual database structure for implementation. The results demonstrate a structured EHR data model comprising 21 interrelated data classes that reflect real-world medical service workflows. The conceptual data model establishes clear entity relationships, supporting data consistency and interoperability. The logical data model provides a normalized SQL-based schema that minimizes redundancy and enhances data integrity, while the physical data model enables efficient data storage and access. A prototype EHR system was implemented to evaluate the feasibility of the proposed data model, showing stable performance, usability, and alignment with functional requirements. This study concludes that a standardized EHR data model derived from an MDS can effectively support comprehensive clinical documentation, interoperability, and future scalability. The proposed model provides a strong foundation for developing national or institutional EHR systems and can serve as a reference for further EHR data standardization efforts.

ABSTRACT Peer review has long been regarded as a cornerstone of scholarly communication, ensuring high quality and credibility of published research. Although academic journals trace their origins back three centuries, the procedures for evaluating submissions, particularly peer review, have undergone continuous evolution. Peer review's formal institutionalisation in the mid‐20th century represents a significant, yet natural, phase in this ongoing transformation of scholarly communication. By the early 21st century, there emerged an opinion that the conventional model of peer review faces systematic challenges, including inefficiency, bias and institutional inertia. The study aims to synthesise the evolution, practices and outcomes of both conventional and innovative peer review models in scholarly publishing. Through a mixed‐methods approach combining interpretative literature review and process modelling (Business Process Model and Notation–BPMN), it identifies four frameworks: pre‐publication peer review, registered reports, modular publishing and the Publish‐Review‐Curate (PRC) model. While the PRC model, which integrates preprints with post‐publication review, demonstrates advantages in transparency and accessibility, no single approach emerges as universally ideal. The choice of model depends on disciplinary context, resource availability and institutional priorities. The analysis underscores the need for adaptable platforms that enable hybrid workflows, balancing rigour with inclusivity. Future research must address empirical gaps in evaluating these innovations, particularly their long‐term impact on equity and epistemic norms.